Abdilla, A & Fitch, R 2017, 'FCJ-209 Indigenous Knowledge Systems and Pattern Thinking: An Expanded Analysis of the First Indigenous Robotics Prototype Workshop', Fibreculture Journal: internet theory criticism research, no. 28, pp. 1-14.
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In November 2014, the lead researcher’s interest in the conceptual development of digitaltechnology and her cultural connection to Indigenous Knowledge Systems created an opportunity toexplore a culturally relevant use of technology with urban Indigenous youth: the Indigenous RoboticsPrototype Workshop. The workshop achieved a sense of cultural pride and confidence in Indigenoustraditional knowledge while inspiring the youth to continue with their engagement in coding andprogramming through building robots. Yet, the outcomes from the prototype workshop further revealed aneed to investigate how Indigenous Knowledge Systems, and particularly Pattern Thinking, might hinttoward a possible paradigm shift for the ethical and advanced design of new technologies. This articleexamines the implications of such a hypothetical shift in autonomous systems in robotics and artificialintelligence (AI), using the Indigenous Robotics Prototype Workshop as a case study and springboard.
Abdolali, A, Ngo, HH, Guo, W, Zhou, JL, Zhang, J, Liang, S, Chang, SW, Nguyen, DD & Liu, Y 2017, 'Application of a breakthrough biosorbent for removing heavy metals from synthetic and real wastewaters in a lab-scale continuous fixed-bed column', Bioresource Technology, vol. 229, pp. 78-87.
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© 2017 Elsevier Ltd A continuous fixed-bed study was carried out utilising a breakthrough biosorbent, specifically multi-metal binding biosorbent (MMBB) for removing cadmium, copper, lead and zinc. The effect of operating conditions, i.e. influent flow rate, metal concentration and bed depth was investigated at pH 5.5 ± 0.1 for a synthetic wastewater sample. Results confirmed that the total amount of metal adsorption declined with increasing influent flow rate and also rose when each metal concentration also increased. The maximum biosorption capacities of 38.25, 63.37, 108.12 and 35.23 mg/g for Cd, Cu, Pb and Zn, respectively, were achieved at 31 cm bed height, 10 mL/min flow rate and 20 mg/L initial concentration. The Thomas model better described the whole dynamic behaviour of the column rather than the Dose Response and Yoon–Nelson models. Finally, desorption studies indicated that metal-loaded biosorbent could be used after three consecutive sorption, desorption and regeneration cycles by applying a semi-simulated real wastewater.
Abdul Hanan, AH, Yazid Idris, M, Kaiwartya, O, Prasad, M & Ratn Shah, R 2017, 'Real traffic-data based evaluation of vehicular traffic environment and state-of-the-art with future issues in location-centric data dissemination for VANETs', Digital Communications and Networks, vol. 3, no. 3, pp. 195-210.
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© 2017 Chongqing University of Posts and Telecommuniocations Extensive investigation has been performed in location-centric or geocast routing protocols for reliable and efficient dissemination of information in Vehicular Adhoc Networks (VANETs). Various location-centric routing protocols have been suggested in literature for road safety ITS applications considering urban and highway traffic environment. This paper characterizes vehicular environments based on real traffic data and investigates the evolution of location-centric data dissemination. The current study is carried out with three main objectives: (i) to analyze the impact of dynamic traffic environment on the design of data dissemination techniques, (ii) to characterize location-centric data dissemination in terms of functional and qualitative behavior of protocols, properties, and strengths and weaknesses, and (iii) to find some future research directions in information dissemination based on location. Vehicular traffic environments have been classified into three categories based on physical characteristics such as speed, inter-vehicular distance, neighborhood stability, traffic volume, etc. Real traffic data is considered to analyze on-road traffic environments based on the measurement of physical parameters and weather conditions. Design issues are identified in incorporating physical parameters and weather conditions into data dissemination. Functional and qualitative characteristics of location-centric techniques are explored considering urban and highway environments. Comparative analysis of location-centric techniques is carried out for both urban and highway environments individually based on some unique and common characteristics of the environments. Finally, some future research directions are identified in the area based on the detailed investigation of traffic environments and location-centric data dissemination techniques.
Abdulwahid, WM & Pradhan, B 2017, 'Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)', Landslides, vol. 14, no. 3, pp. 1057-1076.
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Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the de...
Abualigah, LM, Khader, AT, Hanandeh, ES & Gandomi, AH 2017, 'A novel hybridization strategy for krill herd algorithm applied to clustering techniques', Applied Soft Computing, vol. 60, pp. 423-435.
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Krill herd (KH) is a stochastic nature-inspired optimization algorithm that has been successfully used to solve numerous complex optimization problems. This paper proposed a novel hybrid of KH algorithm with harmony search (HS) algorithm, namely, H-KHA, to improve the global (diversification) search ability. The enhancement includes adding global search operator (improvise a new solution) of the HS algorithm to the KH algorithm for improving the exploration search ability by a new probability factor, namely, Distance factor, thereby moving krill individuals toward the best global solution. The effectiveness of the proposed H-KHA is tested on seven standard datasets from the UCI Machine Learning Repository that are commonly used in the domain of data clustering, also six common text datasets that are used in the domain of text document clustering. The experiments reveal that the proposed hybrid KHA with HS algorithm (H-KHA) enhanced the results in terms of accurate clusters and high convergence rate. Mostly, the performance of H-KHA is superior or at least highly competitive with the original KH algorithm, well-known clustering techniques and other comparative optimization algorithms.
Acuna, P, Aguilera, RP, Ghias, AMYM, Rivera, M, Baier, CR & Agelidis, VG 2017, 'Cascade-Free Model Predictive Control for Single-Phase Grid-Connected Power Converters', IEEE Transactions on Industrial Electronics, vol. 64, no. 1, pp. 285-294.
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In a conventional finite control set model predictive control (FCS-MPC) formulation, active and reactive power control loops rely on the predictive controller, whereas the dc-bus voltage is usually governed by a PI-based control loop. This originates from fact that the dynamic equations for describing the predictions of these variables are heavily coupled. In this paper, a cascade-free FCS-MPC for single-phase grid-connected power converters is presented. The proposed control algorithm is formulated in terms of established dynamic references design, which was originally proposed to directly govern active and reactive power, and dc-voltage in three-phase power converters. In this paper, the dynamic reference design concept is extended to control single-phase grid-connected power converters. The proposed control algorithm does not use instantaneous ac-power calculations; instead, it directly formulates the optimal control problem on the grid-current in the original stationary reference frame. The experimental results obtained with a single-phase grid-connected neutral point clamped (NPC) converter confirm a successful design, where system constraints, e.g., maximum power and weighted switching frequency, are easily taken into account
Adak, C, Chaudhuri, BB & Blumenstein, M 2017, 'An Empirical Study on Writer Identification & Verification from Intra-variable Individual Handwriting', IEEE Access, vol. 7, pp. 24738-24758.
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The handwriting of an individual may vary substantially with factors such asmood, time, space, writing speed, writing medium and tool, writing topic, etc.It becomes challenging to perform automated writer verification/identificationon a particular set of handwritten patterns (e.g., speedy handwriting) of aperson, especially when the system is trained using a different set of writingpatterns (e.g., normal speed) of that same person. However, it would beinteresting to experimentally analyze if there exists any implicitcharacteristic of individuality which is insensitive to high intra-variablehandwriting. In this paper, we study some handcrafted features and auto-derivedfeatures extracted from intra-variable writing. Here, we work on writeridentification/verification from offline Bengali handwriting of highintra-variability. To this end, we use various models mainly based onhandcrafted features with SVM (Support Vector Machine) and featuresauto-derived by the convolutional network. For experimentation, we havegenerated two handwritten databases from two different sets of 100 writers andenlarged the dataset by a data-augmentation technique. We have obtained someinteresting results.
Aditya, L, Mahlia, TMI, Rismanchi, B, Ng, HM, Hasan, MH, Metselaar, HSC, Muraza, O & Aditiya, HB 2017, 'A review on insulation materials for energy conservation in buildings', Renewable and Sustainable Energy Reviews, vol. 73, pp. 1352-1365.
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© 2017 Elsevier Ltd In residential sector, air conditioning system takes the biggest portion of overall energy consumption to fulfil the thermal comfort need. In addressing the issue, thermal insulation is one efficient technology to utilize the energy in providing the desired thermal comfort by its environmentally friendly characteristics. The principle of thermal insulation is by the proper installation of insulation using energy-efficient materials that would reduce the heat loss or heat gain, which leads to reduction of energy cost as the result. This paper is aimed to gather most recent developments on the building thermal insulations and also to discuss about the life-cycle analysis and potential emissions reduction by using proper insulation materials.
Afzal, MU & Esselle, KP 2017, 'Steering the Beam of Medium-to-High Gain Antennas Using Near-Field Phase Transformation', IEEE Transactions on Antennas and Propagation, vol. 65, no. 4, pp. 1680-1690.
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A method to steer the beam of aperture-type antennas is presented in this paper. Beam steering is achieved by transforming phase of the antenna near field using a pair of totally passive metasurfaces, which are located just above and parallel to the antenna. They are rotated independently or synchronously around the antenna axis. A prototype, with a peak gain of 19.4 dBi, demonstrated experimentally that the beam of a resonant cavity antenna can be steered to any direction within a large conical region (with an apex angle of 102°), with less than 3-dB gain variation, by simply turning the two metasurfaces without moving the antenna at all. Measured gain variation within a 92° cone is only 1.9 dBi. Contrary to conventional mechanical steering methods, such as moving reflector antennas with multiaxis rotary joints, the 3-D volume occupied by this antenna system does not change during beam steering. This advantage, together with its low profile, makes it a strong contender for space-limited applications where beam steering with active devices is not desirable due to cost, nonlinear distortion, limited power handling, sensitivity to temperature variations, radio frequency losses, or associated heating. This beam steering method using near-field phase transformation can also be applied to other aperture-type antennas and arrays with medium-to-high gains.
Aghdam, IN, Pradhan, B & Panahi, M 2017, 'Landslide susceptibility assessment using a novel hybrid model of statistical bivariate methods (FR and WOE) and adaptive neuro-fuzzy inference system (ANFIS) at southern Zagros Mountains in Iran', Environmental Earth Sciences, vol. 76, no. 6, pp. 1-22.
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The aim of landslide susceptibility mapping (LSM) is to produce the most important and basic information required for overall landslide disaster planning and mitigation. Different statistical bivariate methods such as frequency ratio (FR) and weights-of-evidence (WOE) have been widely used for LSM. Although results of these aforementioned statistical methods are generally acceptable, however, they can be improved further by fine tuning the conditioning factor’s classes. The purpose of this paper is to overcome some drawbacks of the bivariate models by developing a novel hybrid method using adaptive neuro-fuzzy inference system (ANFIS) and statistical bivariate methods (FR and WOE) in geographical information system. The provinces of southern Zagros Mountains (Iran) are chosen as a case study to implement the proposed method. First, landslide inventory map was produced using various data source such as historical landslides locations, remote sensing images and land surveying techniques. Second, the inventory data were divided into a ratio 70:30 for training and testing the models. Third, twelve landslide conditioning and triggering factors (such as altitude, slope, aspect, plan and profile curvatures, distance to roads, distance to streams, distance to faults, rainfall, seismicity, land use and lithology) were selected and categorized in two groups consisting of numerical and nominal values. Then, each conditioning factor was classified and the weight of each class was determined by using FR and WOE models. The outputs of individual statistical and hybrid methods were applied to determine nominal and continuous numerical data, respectively. In the hybrid approach, the calculated weights of each class were allocated to the center of each class, and the rest of the weights were determined by ANFIS. Landslide locations which were not used in training the models were used for validation. The produced susceptibility maps were validated and compared using area under the...
Aguilera, RP, Acuna, P, Lezana, P, Konstantinou, G, Wu, B, Bernet, S & Agelidis, VG 2017, 'Selective Harmonic Elimination Model Predictive Control for Multilevel Power Converters', IEEE Transactions on Power Electronics, vol. 32, no. 3, pp. 2416-2426.
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© 2016 IEEE.In this study, a model predictive control (MPC) strategy that combines finite-control-set MPC with selective harmonic elimination (SHE) modulation pattern in its formulation is proposed to govern multilevel power converters. Based on a desired operating point for the system state (converter current reference), an associated predefined SHE voltage pattern is obtained as a required steady-state control input reference. Then, the cost function is formulated with the inclusion of both system state and control input references. According with the proposed reference and cost function formulation, the predictive controller prefers to track the converter output current reference in transients, while preserving the SHE voltage pattern in steady state. Hence, as evidenced by experimental results, a fast dynamic response is obtained throughout transients while a predefined voltage and current spectrum with low switching frequency is achieved in steady state.
Aguilera, RP, Acuna, P, Yu, Y, Konstantinou, G, Townsend, CD, Wu, B & Agelidis, VG 2017, 'Predictive Control of Cascaded H-Bridge Converters Under Unbalanced Power Generation', IEEE Transactions on Industrial Electronics, vol. 64, no. 1, pp. 4-13.
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© 1982-2012 IEEE.This work presents a predictive control strategy for grid-connected Cascaded H-Bridge (CHB) converters under unbalanced power generation among each converter phase. The proposed controller belongs to the Finite-Control-Set Model Predictive Control (FCS-MPC) family and is designed to extract unbalanced power from each CHB converter phase while providing balanced power to the grid. The key novelty of this strategy lies in the way the unbalanced power generation among the phases is explicitly considered into the optimal control problem. Power balance is achieved by enforcing the CHB converter to work with a suitable zero-sequence voltage component. The proposed predictive controller is directly formulated in the original abc-framework to account for the commonmode voltage. Simulation and experimental results are provided to verify the effectiveness of the proposed FCS-MPC strategy.
Aguilera, RP, Urrutia, G, Delgado, RA, Dolz, D & Aguero, JC 2017, 'Quadratic Model Predictive Control Including Input Cardinality Constraints', IEEE Transactions on Automatic Control, vol. 62, no. 6, pp. 3068-3075.
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© 2017 IEEE. This note addresses the problem of feedback control with a constrained number of active inputs. This problem is known as sparse control. Specifically, we describe a novel quadratic model predictive control strategy that guarantees sparsity by bounding directly the l0-norm of the control input vector at each control horizon instant. Besides this sparsity constraint, bounded constraints are also imposed on both control input and system state. Under this scenario, we provide sufficient conditions for guaranteeing practical stability of the closed-loop. We transform the combinatorial optimization problem into an equivalent optimization problem that does not consider relaxation in the cardinality constraints. The equivalent optimization problem can be solved utilizing standard nonlinear programming toolboxes that provides the input control sequence corresponding to the global optimum.
Ahadi, A, Hellas, A & Lister, R 2017, 'A Contingency Table Derived Method for Analyzing Course Data', ACM Transactions on Computing Education, vol. 17, no. 3, pp. 1-19.
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We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online exercises done during semester with subsequent performance on questions in a paper-based exam at the end of semester. We found that it is useful to include data about the number of attempts a student makes on an online exercise.
Ahadi, A, Sablok, G & Hutvagner, G 2017, 'miRTar2GO: a novel rule-based model learning method for cell line specific microRNA target prediction that integrates Ago2 CLIP-Seq and validated microRNA–target interaction data', Nucleic Acids Research, vol. 45, no. 6, pp. e42-e42.
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© 2016 The Author(s). MicroRNAs (miRNAs) are ∼19-22 nucleotides (nt) long regulatory RNAs that regulate gene expression by recognizing and binding to complementary sequences on mRNAs. The key step in revealing the function of a miRNA, is the identification of miRNA target genes. Recent biochemical advances including PAR-CLIP and HITS-CLIP allow for improved miRNA target predictions and are widely used to validate miRNA targets. Here, we present miRTar2GO, which is a model, trained on the common rules of miRNA-target interactions, Argonaute (Ago) CLIP-Seq data and experimentally validated miRNA target interactions. miRTar2GO is designed to predict miRNA target sites using more relaxed miRNA-target binding characteristics. More importantly, miRTar2GO allows for the prediction of celltype specific miRNA targets. We have evaluated miRTar2GO against other widely used miRNA target prediction algorithms and demonstrated that miRTar2GO produced significantly higher F1 and G scores. Target predictions, binding specifications, results of the pathway analysis and gene ontology enrichment of miRNA targets are freely available at http://www.mirtar2go.org.
Ahmadi, M, Naderpour, H, Kheyroddin, A & Gandomi, AH 2017, 'Seismic Failure Probability and Vulnerability Assessment of Steel-Concrete Composite Structures', Periodica Polytechnica Civil Engineering, vol. 61, no. 4, pp. 939-950.
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Building collapse in earthquakes caused huge losses, both in human and economic terms. To assess the risk posed by using the composite members, this paper investigates seismic failure probability and vulnerability assessment of steel-concrete composite structures constituted by rectangular concrete filled steel tube (RCFT) columns and steel beams. To enable numerical simulation of RCFT-structure, the details of components modeling are developed using OpenSEES finite element analysis package and the validation of proposed procedure is investigated through comparisons with available experimental results. The seismic fragility and vulnerability curves of RCFT-structures are created through nonlinear dynamic analysis using an appropriate suite of ground motions for seismic loss assessment. These curves developed for three-, six- and nine-story prototypes of RCFT-structure. Fragility curves are an appropriate tool for representing the seismic failure probabilities and vulnerability curves demonstrate a probability of exceeding loss to a measure of ground motion intensity.
Ahmed, M, Wang, B, Gupta, B, Boeckl, JJ, Motta, N & Iacopi, F 2017, 'On-Silicon Supercapacitors with Enhanced Storage Performance', Journal of The Electrochemical Society, vol. 164, no. 4, pp. A638-A644.
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© 2017 The Electrochemical Society. All rights reserved. The expanding development of portable electronic devices and ubiquitous sensing systems has created a strong demand for efficient miniaturized energy storage units, with planar geometries and capable of being integrated on a silicon platform. Generally, the performance of thin-film storage devices, including using graphene, is dramatically limited by their low surface area for ionexchange. We had recently shown that a higher number of graphene layers does not translate into higher storage performance. Here we show a way to overcome this limitation and achieve a maximum accessible area for ion exchange. A repeated graphitization strategy using a nickel catalyst on epitaxial silicon carbide films on silicon yields few-layers graphenic nanocarbon electrodes with prominent edge defects, facilitating the intercalation between multiple graphenic sheets while maintaining overall a high electrode conductivity.
Ahmed, MB, Johir, MAH, Zhou, JL, Ngo, HH, Guo, W & Sornalingam, K 2017, 'Photolytic and photocatalytic degradation of organic UV filters in contaminated water', Current Opinion in Green and Sustainable Chemistry, vol. 6, pp. 85-92.
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© 2017 Elsevier B.V. UV filters as emerging contaminants are of great concern and their wide detection in aquatic environments indicates their chemical stability and persistence. This review summarized the photolytic and photocatalytic degradation of UV filters in contaminated water. The findings indicated that limited research has been conducted on the photolysis and photocatalysis of UV filters. Photolysis of UV filters through UV irradiation in natural water was a slow process, which was accelerated by the presence of photosensitisers e.g. triplet state of chromaphoric dissolved organic matter (3CDOM*) and nutrients but reduced by salinity, dissolved organic matter (DOM) and divalent cations. UV Photocatalysis of 4-methylbenzylidene camphor and 2-phenylbenzimidazole-5-sulfonic acid was very effective with 100% removal within 30 min and 90 min using medicated TiO2/H2O2 and TiO2, respectively. The radiation source, type of catalyst and oxygen content were key factors. Future research should focus on improved understanding of photodegradation pathways and by-products of UV filters.
Ahmed, MB, Zhou, JL, Ngo, HH, Guo, W, Johir, MAH & Belhaj, D 2017, 'Competitive sorption affinity of sulfonamides and chloramphenicol antibiotics toward functionalized biochar for water and wastewater treatment', Bioresource Technology, vol. 238, pp. 306-312.
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© 2017 Elsevier Ltd Competitive sorption of sulfamethazine (SMT), sulfamethoxazole (SMX), sulfathiazole (STZ) and chloramphenicol (CP) toward functionalized biochar (fBC) was highly pH dependent with maximum sorption at pH ∼4.0–4.25. Equilibrium data were well represented by the Langmuir and Freundlich models in the order STZ > SMX > CP > SMT. Kinetics data were slightly better fitted by the pseudo second-order model than pseudo first-order and intra-particle-diffusion models. Maximum sorptive interactions occurred at pH 4.0–4.25 through H-bonds formations for neutral sulfonamides species and through negative charge assisted H-bond (CAHB) formation for CP, in addition to π-π electron-donor-acceptor (EDA) interactions. EDA was the main mechanism for the sorption of positive sulfonamides species and CP at pH < 2.0. Sorption of negative sulfonamides species and CP at pH > 7.0 was regulated by H-bond formation and proton exchange with water by forming CAHB, respectively. The results suggested fBC to be highly efficient in removing antibiotics mixture.
Ahmed, MB, Zhou, JL, Ngo, HH, Guo, W, Johir, MAH & Sornalingam, K 2017, 'Single and competitive sorption properties and mechanism of functionalized biochar for removing sulfonamide antibiotics from water', Chemical Engineering Journal, vol. 311, pp. 348-358.
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© 2016 Elsevier B.V. Single and competitive sorption of ionisable sulphonamides sulfamethazine, sulfamethoxazole and sulfathiazole on functionalized biochar was highly pH dependent. The equilibrium data were well represented by both Langmuir and Freundlich models for single solutes, and by the Langmuir model for competitive solutes. Sorption capacity and distribution coefficient values decreased as sulfathiazole > sulfamethoxazole > sulfamethazine. The sorption capacity of each antibiotic in competitive mode is about three times lower than in single solute sorption. The kinetics data were best described by the pseudo second-order (PSO) model for single solutes, and by PSO and intra-particle diffusion models for competitive solutes. Adsorption mechanism was governed by pore filling through diffusion process. The findings from pH shift, FTIR spectra and Raman band shift showed that sorption of neutral sulfonamide species occurred mainly due to strong H-bonds followed by π+-π electron-donor-acceptor (EDA), and by Lewis acid-base interaction. Moreover, EDA was the main mechanism for the sorption of positive sulfonamides species. The sorption of negative species was mainly regulated by proton exchange with water forming negative charge assisted H-bond (CAHB), followed by the neutralization of –OH groups by H+released from functionalized biochar surface; in addition π-π electron-acceptor-acceptor (EAA) interaction played an important role.
Ahmed, MB, Zhou, JL, Ngo, HH, Guo, W, Johir, MAH, Sornalingam, K, Belhaj, D & Kallel, M 2017, 'Nano-Fe 0 immobilized onto functionalized biochar gaining excellent stability during sorption and reduction of chloramphenicol via transforming to reusable magnetic composite', Chemical Engineering Journal, vol. 322, pp. 571-581.
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© 2017 Elsevier B.V. The widely used nanosized zero-valent iron (nZVI or nFe0) particles and their composite material lose reductive nature during application, and the stability of transformed composite material for repeatable application is not addressed to date. To shed light on this, nZVI was synthesized from scrap material and immobilized on functionalized biochar (fBC) to prepare nZVI-fBC composite. Comparative study between nZVI and nZVI-fBC composite on the removal of chlorinated antibiotic chloramphenicol from different water types was conducted. The results suggested that nZVI was solely responsible for reduction of chloramphenicol. Whereas nZVI-fBC could be applied once, within a few hours, for the reduction of chloramphenico (29–32.5%) and subsequently sorption (67.5–70.5%) by transforming to a fully magnetic composite (nFe3O4-fBC) gaining stability with synergistic sorption performance. In both cases, two reduction by-products were identified namely 2-chloro-N-[1,3-dihydroxy-1-(4-aminophenyl)propan-2-yl]acetamide (m/z 257) and dechlorinated N-[1,3-dihydroxy-1-(4-aminophenyl)propan-2-yl]acetamide (m/z 223). The complete removal of 3.1 µM L−1 of chloramphenicol in different water was faster by nZVI-fBC (∼12–15 h) than by stable nFe3O4-fBC composite (∼18 h). Both nZVI-fBC and nFe3O4-fBC composites removed chloramphenicol in the order: deionized water > lake water > synthetic wastewater. nFe3O4-fBC showed excellent reusability after regeneration, with the regenerated nFe3O4-fBC composite (after 6 cycles of application) showing significant performance for methylene blue removal (∼287 mg g−1). Therefore, the transformed nFe3O4-fBC composite is a promising and reusable sorbent for the efficient removal of organic contaminants.
Ahmed, MB, Zhou, JL, Ngo, HH, Guo, W, Thomaidis, NS & Xu, J 2017, 'Progress in the biological and chemical treatment technologies for emerging contaminant removal from wastewater: A critical review', Journal of Hazardous Materials, vol. 323, pp. 274-298.
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© 2016 Elsevier B.V. This review focuses on the removal of emerging contaminants (ECs) by biological, chemical and hybrid technologies in effluents from wastewater treatment plants (WWTPs). Results showed that endocrine disruption chemicals (EDCs) were better removed by membrane bioreactor (MBR), activated sludge and aeration processes among different biological processes. Surfactants, EDCs and personal care products (PCPs) can be well removed by activated sludge process. Pesticides and pharmaceuticals showed good removal efficiencies by biological activated carbon. Microalgae treatment processes can remove almost all types of ECs to some extent. Other biological processes were found less effective in ECs removal from wastewater. Chemical oxidation processes such as ozonation/H2O2, UV photolysis/H2O2 and photo-Fenton processes can successfully remove up to 100% of pesticides, beta blockers and pharmaceuticals, while EDCs can be better removed by ozonation and UV photocatalysis. Fenton process was found less effective in the removal of any types of ECs. A hybrid system based on ozonation followed by biological activated carbon was found highly efficient in the removal of pesticides, beta blockers and pharmaceuticals. A hybrid ozonation-ultrasound system can remove up to 100% of many pharmaceuticals. Future research directions to enhance the removal of ECs have been elaborated.
Ai, XL, Yu, JQ, Chen, YB, Chen, FZ & Shen, YC 2017, 'Optimal formation control with limited communication for multi-unmanned aerial vehicle in an obstacle-laden environment', Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 231, no. 6, pp. 979-997.
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This paper investigates the formation control problem of multiple unmanned aerial vehicles (UAVs) with limited communication in a known and realistic obstacle-laden environment. In order to deal with the limited communication constraints, the leader–follower strategy and the virtual leader strategy are integrated into an optimal control framework to formulate this formation control problem. This combination formation framework can be achieved by integrating a redefined directed graph and a proposed information vector. In more practical applications, an obstacle/collision avoidance strategy is achieved by constructing a non-quadratic cost function innovatively using a virtual flow field approach. The proposed optimal control laws, which derive from the local information rather than the global information, are proved to guarantee the stability of the close-loop system by an inverse optimal control approach. The simulation results demonstrate the effectiveness of the formation flight of multiple UAVs with limited communication in an obstacle-laden environment.
Ajaj, QM, Pradhan, B, Noori, AM & Jebur, MN 2017, 'Spatial Monitoring of Desertification Extent in Western Iraq using Landsat Images and GIS', Land Degradation & Development, vol. 28, no. 8, pp. 2418-2431.
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AbstractDesertification refers to land degradation in arid, semi‐arid, and dry sub‐humid areas caused by various factors, including climatic variations and human activities. In recent decades, sandstorms have increased significantly in Western Iraq, which primarily increased desert lands. Proper management is required to control and to monitor the phenomena, as well as to calculate the desertified areas caused by desertification. The study area covered 50,861.854 km2 in Western Iraq. Landsat‐5 TM, Landsat‐7 ETM+, and Landsat‐8 OLI data for 1990, 2002, and 2014 were used. Maximum likelihood algorithm was used to classify the images. Change detection results were discussed in two terms: short‐term (1990–2002) and (2002–2014) and long‐term (1990–2014) analysis. Change detection analysis from 1990 to 2014 showed that desert area increased to 2286.7308 km2, becoming a new source of dust storms. Hazard occurrence probability was studied on September and October 2014. The desertification amount decreased from 1990 to 2002 and increased significantly from 2002 to 2014. Sandstorms have recently been considered a hazardous phenomenon affecting the human population, the vegetation, and the ecosystem in Iraq. Copyright © 2017 John Wiley & Sons, Ltd.
Al Kim, HAHH, Subramanian, R, Afroz, F & Sandrasegaran, K 2017, 'Comparison of Performance of Packet Scheduling Algorithms in LTE-A HetNets', Wireless Personal Communications, vol. 97, no. 2, pp. 1947-1965.
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Al Muderis, M, Lu, W & Li, JJ 2017, 'Osseointegrated Prosthetic Limb for the treatment of lower limb amputations', Der Unfallchirurg, vol. 120, no. 4, pp. 306-311.
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BACKGROUND: Osseointegration has emerged over the past two decades as a dramatically different approach for the treatment of lower limb amputations, which involves direct attachment of the prosthesis to the skeletal residuum. This approach can address many of the socket-interface issues associated with socket prostheses which represent the current standard of care for amputees. The Osseointegrated Prosthetic Limb (OPL) is an osseointegration implant with a new design and improved features compared to other available implant systems. OBJECTIVES: To report on the experience and outcomes of using the OPL for osseointegrated reconstruction of lower limb amputations. MATERIALS AND METHODS: This is a retrospective study of 22 patients who received the OPL implant between December 2013 and November 2014. Clinical outcomes were obtained pre- and post-operatively, with results reported at the 1‑year follow-up. Outcome measures included the Questionnaire for persons with a Trans-Femoral Amputation (Q-TFA), Short Form Health Survey 36 (SF-36), Six-Minute Walk Test (6MWT), and Timed Up and Go (TUG). Adverse events were also recorded. RESULTS: Compared to the mean pre-operative values obtained while patients were using socket prostheses or were wheelchair-bound, the mean post-operative values for all four validated outcome measures were significantly improved. There were 15 episodes of minor infections in 12 patients, all of which responded to antibiotics. Soft tissue refashioning was performed electively on 6 patients. No other adverse events were recorded. CONCLUSIONS: The results demonstrate that osseointegration surgery using the OPL is a relatively safe and effective procedure for the reconstruction and rehabilitation of lower limb amputees.
Al Muderis, M, Lu, W, Tetsworth, K, Bosley, B & Li, JJ 2017, 'Single-stage osseointegrated reconstruction and rehabilitation of lower limb amputees: the Osseointegration Group of Australia Accelerated Protocol-2 (OGAAP-2) for a prospective cohort study', BMJ Open, vol. 7, no. 3, pp. e013508-e013508.
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IntroductionLower limb amputations have detrimental influences on the quality of life, function and body image of the affected patients. Following amputation, prolonged rehabilitation is required for patients to be fitted with traditional socket prostheses, and many patients experience symptomatic socket–residuum interface problems which lead to reduced prosthetic use and quality of life. Osseointegration has recently emerged as a novel approach for the reconstruction of amputated limbs, which overcomes many of the socket-related problems by directly attaching the prosthesis to the skeletal residuum. To date, the vast majority of osseointegration procedures worldwide have been performed in 2 stages, which require at least 4 months and up to 18 months for the completion of reconstruction and rehabilitation from the time of the initial surgery. The current prospective cohort study evaluates the safety and efficacy of a single-stage osseointegration procedure performed under the Osseointegration Group of Australia Accelerated Protocol-2 (OGAAP-2), which dramatically reduces the time of recovery to ∼3–6 weeks.Methods and analysisThe inclusion criteria for osseointegrated reconstruction under the OGAAP-2 procedure are age over 18 years, unilateral transfemoral amputation and experiencing problems or difficulties in using socket prostheses. All patients receive osseointegrated implants which are press-fitted into the residual bone. Functional and quality-of-life outcome measures are recorded preoperatively and at defined postoperative follow-up intervals up to 2 years. Postoperative adverse events are also recorded. The preoperative and postoperative values are compared for each outcome measure, and the benefits and harms of the single-stage OGAAP-2 procedure will be compared with the results obtained using a previously employed 2-stage procedure.
Alanezi, AA & Altaee, A 2017, 'Enhanced Performance Dual Stage Pressure Retarded Osmosis', Energy Procedia, vol. 142, pp. 4182-4197.
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© 2017 The Authors. Published by Elsevier Ltd. A dual stage PRO process has been proposed for power generation from a salinity gradient across a semi-permeable membrane. Both closed-loop and open-loop dual stage PRO system were evaluated using 2 M NaCl and Dead Sea as draw solutions, whereas the feed solution was either fresh water or seawater. The impact of feed salinity gradient resource and feed pressure on the net power generation and water flux were evaluated. DSPRO can be combined with desalination plant using seawater brine as the draw solution either in closed-loop or open-loop. This hybridization has multiple applications such as reducing the impact of discharging concentrated brine to sea, energy storage, and increase the recovery rate of the desalination. Power generation by DSPRO will reduce the energy consumption by the desalination processes. Waste heat from power plants can be used for the regeneration of the draw solution in the closed-loop DSPRO. Process modelling has been performed and shown promising results for DSPRO application for power generation.
Alavi, AH & Gandomi, AH 2017, 'Big data in civil engineering', Automation in Construction, vol. 79, pp. 1-2.
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Albahrani, SA, Parker, A, Heimlich, M & Schwitter, B 2017, 'Iso-Trapping Measurement Technique for Characterization of Self-Heating in a GaN HEMT', IEEE Transactions on Electron Devices, vol. 64, no. 1, pp. 102-108.
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Albanese, B, Gibson, T, Whyte, T, Meredith, L, Savino, G, de Rome, L, Baldock, M, Fitzharris, M & Brown, J 2017, 'Energy attenuation performance of impact protection worn by motorcyclists in real-world crashes', Traffic Injury Prevention, vol. 18, no. sup1, pp. S116-S121.
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Laboratory studies have demonstrated that impact protectors (IP) used in motorcycle clothing can reduce fracture severities. While crash studies have reported IP are associated with reduced likelihood of soft tissue injury, there is little evidence of their effectiveness in reducing fracture likelihood. This discrepancy might be related to IP quality. There are mandatory requirements for IP supplied with protective clothing in Europe, but not elsewhere. This study examines the energy attenuation performance of IP used by Australian riders.IP were harvested from clothing worn by crashed riders admitted to hospital. The IP were examined and energy attenuation properties were determined using EN 1621-1 test procedures. Impact injury was identified from medical records and defined as fractures, dislocations, and avulsions that occurred following impact to the rider's shoulders, elbows, hips, and/or knees. Fisher's exact test was used to examine the relationship between meeting the EN 1621-1 energy attenuation requirements and impact injury. The association between the average and maximum transmitted force, and impact injury was examined using generalized estimating equations. Motorcycle riders were recruited as part of an in-depth crash study through three hospitals in New South Wales, Australia, between 2012 and 2014. Riders were interviewed, and engineers conducted site, vehicle, and clothing inspections. Clothing was collected, or identical garments were purchased.Clothing was inspected for 62 riders. Of these, 19 wore clothing incorporating 76 IP. Twenty-six of these were impacted in the crash event. Almost all impacted IP (96%) were CE marked, and most (83%) met Level 1 energy attenuation requirements of EN 1621-1 when tested. Of the 26 impacted IP, four were associated with impact injuries, including midshaft and distal clavicle fractures and a scapula and olecranon fracture. No associations between meeting EN 1621-1 requirements and impact injury were found (p...
Alharbi, SK, Kang, J, Nghiem, LD, van de Merwe, JP, Leusch, FDL & Price, WE 2017, 'Photolysis and UV/H 2 O 2 of diclofenac, sulfamethoxazole, carbamazepine, and trimethoprim: Identification of their major degradation products by ESI–LC–MS and assessment of the toxicity of reaction mixtures', Process Safety and Environmental Protection, vol. 112, no. Part B, pp. 222-234.
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© 2017 Institution of Chemical Engineers The photolysis of diclofenac (DCF), sulfamethoxazole (SMX), carbamazepine (CBZ), and trimethoprim (TMP) was investigated using a low-pressure (LP) mercury ultraviolet (UV) lamp (254 nm) and a combination of UV with hydrogen peroxide (H 2 O 2 ). For each experiment, 5 mg/L of each pharmaceutical was prepared in pure water and individually degraded by either UV alone or UV/H 2 O 2 . DCF and SMX were highly susceptible to UV treatment and completely degraded to below their LC–MS detection limit (1 μg/L) after only 8 min of UV irradiation. TMP and CBZ were more resistant to UV treatment, with only 58.2 and 25.2% degradation (after 1 h UV exposure). The combination of H 2 O 2 addition (up to 0.2 g/L) with UV significantly improved the removal rate of TMP and CBZ up to 91.2 and 99.7% of the initial concentration, respectively. A number of novel transformation compounds were identified as UV or UV/H 2 O 2 degradation products using LC–MS. The range and amount of these transformation compounds strongly depended on the applied treatment conditions. The toxicity of each pharmaceutical solution before and after treatment was also evaluated and all parent compounds were non-toxic at the tested concentration (i.e. 5 mg/L). DCF, in particular, but also CBZ and SMX, showed an increase in solution toxicity after treatment with UV only, indicating the presence of photolytic degradation products that are more toxic than the parent compounds. Treatment with UV/H 2 O 2 reduced the toxicity of all solutions to below the detection limit of the assay.
Ali, A & Lee, JE-Y 2017, 'Single device on-chip feedthrough cancellation for enhanced electrical characterization of piezoelectric-on-silicon resonators in liquid', Sensors and Actuators A: Physical, vol. 260, pp. 131-138.
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Alizadeh, A, Warkiani, ME & Wang, M 2017, 'Manipulating electrokinetic conductance of nanofluidic channel by varying inlet pH of solution', Microfluidics and Nanofluidics, vol. 21, no. 3, pp. 1-15.
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© 2017, Springer-Verlag Berlin Heidelberg. The electrokinetic conductivity of micro-/nanofluidic systems, which strongly depends on the local solution properties (e.g., pH and ionic strength), has wide applications in nanosystems to control the system performance and ion rectification. Accurate and active manipulation of this parameter is proven to be very challenging since, in nanoscale, the ion transport is particularly dominated by the acquired surface charge on the solid–liquid interfaces. In this study, we propose an approach to manipulate the nanochannel electrokinetic conductivity by changing the pH value of the solution at the inlet in order to impose asymmetrical conditions inside nanochannel. The variable surface charge of walls is determined by considering the chemical adsorption on the solid–liquid interface and the electrical double layer interaction. The presented numerical model, which couples Poisson–Nernst–Planck and Navier–Stokes equations, can fully consider the electro-chemo-mechanical transport phenomena and predict the electrokinetic conductivity of nanofluidic channels with good accuracy. Modeling results show that the electrokinetic conductivity of the nanofluidic systems can be regulated by varying the solution pH at the inlet. It is revealed that the stronger electric double layers interaction can enhance the sensitivity of the nanochannel electrokinetic conductance to the inlet pH. This unique behavior of the nanochannel electrokinetic conductivity could broaden potential applications in biomedical, energy, and environmental systems using nanofluidic devices.
Al-Jubainawi, A, Ma, Z, Guo, Y, Nghiem, LD, Cooper, P & Li, W 2017, 'Factors governing mass transfer during membrane electrodialysis regeneration of LiCl solution for liquid desiccant dehumidification systems', Sustainable Cities and Society, vol. 28, pp. 30-41.
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© 2016 Elsevier Ltd This study investigates the mass transfer mechanisms and the performance of membrane electrodialysis (ED) for regenerating lithium chloride (LiCl) solution commonly used in liquid desiccant dehumidification systems. Experiments were conducted using an ED experimental system while numerical simulation was performed using COMSOL Multiphysics. The results showed that the water flux transfer due to osmosis and electro-osmosis during ED regeneration of LiCl liquid desiccant was significant and could not be ignored. The water flux due to osmosis and electro-osmosis is directly associated with the osmotic gradient and the applied current between the cathode and anode, respectively. The average flux of water from the spent solution to the regenerated solution decreased from 0.292 to 0.161 g/s m 2 when the initial concentration of the solutions in the spent and regenerated tanks increased from 18 to 30% (wt/wt) with the same applied current of 12 A and the same solution flow rate of 100 L/h. On the other hand, the salt flux due to osmosis was insignificant. The average salt flux transfer was 0.0053 g/s m 2 when the initial concentration difference between the regenerated and the spent channels was 25% (wt/wt). Simulations were conducted to elucidate the relationship between the concentration profile of LiCl solution along the membrane surface and the concentration polarization in the ED channel with respect to the circulation flow rate and applied current. Overall, the results suggest that the concentration difference between the regenerated and spent LiCl solutions should be minimized for an optimum ED performance.
Alshahrani, AA, Al-Zoubi, H, Nghiem, LD & in het Panhuis, M 2017, 'Synthesis and characterisation of MWNT/chitosan and MWNT/chitosan-crosslinked buckypaper membranes for desalination', Desalination, vol. 418, pp. 60-70.
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© 2017 Elsevier B.V. Novel buckypaper (BP) membranes for nanofiltration application were fabricated from multi-walled carbon nanotubes (MWNT) and biopolymer containing quaternary amine groups (chitosan and chitosan-crosslinked by in-situ amine crosslinking). Characteristics of the BP membranes were systematically characterized in terms of mechanical (tensile strengths varied between 49 ± 4 and 59 ± 3 MPa) and electrical properties (60 ± 1 to 70 ± 1 S/cm), contact angle (76 ± 3° to 102 ± 3°), surface morphology, membrane swelling, pore size, surface charge, solubility, water permeability (ranging from 019 ± 0.01 to 0.87 ± 0.03 L m− 2 h− 1 bar− 1), and salts rejection (80–95% for MgCl2, 21–63% for NaCl, 18–37% for MgSO4 and 6–14% for Na2SO4). These BP membranes were able to sustain up to 18 bar of pressure. Their properties were significantly affected by the type of biopolymer modifiers. The highest water permeability was obtained with the MWNT/chitosan BP membrane, while the MWNT/chitosan-crosslinked membranes showed the best salt rejection performance. In addition, separation performance by these membranes appeared to be governed by the unhydrated radii of these inorganic salts.
Altaee, A, Millar, GJ, Zaragoza, G & Sharif, A 2017, 'Energy efficiency of RO and FO–RO system for high-salinity seawater treatment', Clean Technologies and Environmental Policy, vol. 19, no. 1, pp. 77-91.
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© 2016, Springer-Verlag Berlin Heidelberg. Forward osmosis (FO) has been proposed as an alternative method for seawater desalination, wherein reverse osmosis (RO) membrane technology is used for regeneration of the draw solution. Previous studies have indicated that a standalone RO unit is more energy efficient than an FO–RO system, and as such it was recommended that an FO–RO system is best employed only for the desalination of high-salinity seawaters. This study examined FO–RO applicability in more detail by examining the impact of seawater salinity, impact of an energy recovery device (ERD), and the effect of membrane fouling. For comparison purposes, the performance of the FO process was improved to minimize the impact of concentration polarization and optimize the concentration of draw solution. Model calculations revealed that FO–RO is more energy efficient than RO when no ERD was employed. However, results showed that there was no significant difference in the power consumption between the FO–RO system and the RO unit at high seawater salinities particularly when a high-efficiency ERD was installed. Moreover, the FO–RO system required more membrane area than a conventional RO unit which may further compromise the FO–RO desalination cost.
Altaee, A, Palenzuela, P, Zaragoza, G & AlAnezi, AA 2017, 'Single and dual stage closed-loop pressure retarded osmosis for power generation: Feasibility and performance', Applied Energy, vol. 191, pp. 328-345.
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© 2017 Elsevier Ltd This work proposes an analysis of conventional (single stage) and dual stage Closed-Loop Pressure Retarded Osmosis (CLPRO) for power generation from a salinity gradient resource. Model calculations were performed taking into account the influence of operating parameters such as the draw solution concentration, membrane area, and draw solution pressure on the performance of the CLPRO process. Modeling results showed that the dual stage CLPRO process outperformed the conventional CLPRO process and power generation increased 18% by adding a second stage of PRO membrane. Multi-Effect Distillation (MED) was selected for the regeneration of the draw solution taking advantage of an available source of waste heat energy. The performance of MED process has been assessed by investigating two key parameters: the specific thermal consumption and the specific heat transfer area. The model calculations showed that the power generation by the single and dual stage CLPRO was higher than the electrical power consumption by the MED plant. In the case of the power generation obtained by the dual stage CLPRO, it was 95% higher than the electrical power consumption by the MED plant, proving the possibility of using low-grade heat for producing electricity from a salinity gradient resource.
Altaee, A, Zaragoza, G, Drioli, E & Zhou, J 2017, 'Evaluation the potential and energy efficiency of dual stage pressure retarded osmosis process', Applied Energy, vol. 199, pp. 359-369.
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© 2017 Power generation by means of Pressure Retarded Osmosis (PRO) has been proposed for harvesting the energy of a salinity gradient. Energy recovery by the PRO process decreases along the membrane module due to depleting of the chemical potential across the membrane and concentration polarization effects. A dual stage PRO (DSPRO) design can be used to rejuvenate the chemical potential difference and reduce the concentration polarization on feed solution. Several design configurations were suggested for the membrane module arrangements in the first and second stage of the PRO process. PRO performance was evaluated for a number of salinity gradients proposed by coupling Dead Sea water or Reverse Osmosis (RO) brine with seawater or wastewater effluent. Maximum specific energy of inlet and outlet feeds was calculated using a developed computer model to identify the amount of recovered and remaining energy. Initially, specific power generation by the PRO process increased by increasing the number of modules of the first stage. Maximum specific energy is calculated along the PRO module to understand the degradation of the maximum specific energy in each module before introducing a second stage PRO process. Adding a second stage PRO process resulted in a sharp increase of the chemical potential difference and the specific energy yield of the process. Between 10% and 13% increase of the specific power generation was achieved by the DSPRO process for the Dead Sea-seawater salinity gradient depending on the dual stage design configuration. For Dead Sea-RO brine, 12–16% increase of the specific power generation was achieved by the dual stage PRO process. For Dead Sea-wastewater and RO brine-wastewater, a neutral and sometimes negative impact occurred when a second stage PRO process was introduced. We concluded that, for a given draw solution concentration, dual stage performs better than the conventional PRO process at high feed salinities, yet requires lower h...
Altaee, A, Zhou, J, Alhathal Alanezi, A & Zaragoza, G 2017, 'Pressure retarded osmosis process for power generation: Feasibility, energy balance and controlling parameters', Applied Energy, vol. 206, pp. 303-311.
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© 2017 The feasibility of pressure-retarded osmosis (PRO) for power generation was evaluated with consideration of the energy inputs and losses in the process. The effects of the concentration polarization, reverse salt diffusion, and external resistance at the membrane porous layer were quantified, for the first time, along the membrane module to determine their contributions to the energy loss in the PRO process. Concentration polarization was responsible for up to 40% of the energy loss during the PRO process. However, increasing the PRO membrane modules from 1 to 4 resulted in a variable increase of the energy output depending on the salinity gradient. The energy requirements for draw and feed solution pretreatment were estimated to be over 38% of the total energy inputs. Results showed that coupling seawater (SW) with river water (RW) was unable to generate sufficient energy to compensate for the energy inputs and losses during the PRO process. With 0.39 kwh/m3 maximum specific energy in the PRO process, the energy yield of reverse osmosis brine (ROB)-wastewater (WW) salinity gradient was slightly greater than the total energy inputs, although using Dead Sea-SW/ROB salinity gradient was more promising. Overall, the primary current limitation is the lack of suitable PRO membranes that can withstand a high hydraulic pressure.
Althuwaynee, OF & Pradhan, B 2017, 'Semi-quantitative landslide risk assessment using GIS-based exposure analysis in Kuala Lumpur City', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 706-732.
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Alturki, R & Gay, V 2017, 'Usability Testing of Fitness Mobile Application : Case Study Aded Surat App', International Journal of Computer Science and Information Technology, vol. 9, no. 5, pp. 105-125.
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Amin, M, Putra, N, Kosasih, EA, Prawiro, E, Luanto, RA & Mahlia, TMI 2017, 'Thermal properties of beeswax/graphene phase change material as energy storage for building applications', Applied Thermal Engineering, vol. 112, pp. 273-280.
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© 2016 Elsevier Ltd Increased energy consumption in buildings is a worldwide issue. This research is concerned with the implementation of a phase change material for thermal storage. This concept has gained great attention as a solution to reduce energy consumption in buildings. Beeswax, which is a phase change material with a high thermal capacity, is investigated in this research. This paper is intended to measure and analyze the thermal properties of beeswax/graphene as a phase change material. The melting temperature, thermal capacity and latent heat were determined using differential scanning calorimetry (DSC), and the thermal conductivity was investigated using a thermal conductivity measurement apparatus. To discover the change in the physical properties due to the effect of nanoparticles, the viscosity of the material was investigated as well. Based on the result from the DSC, the latent heat of 0.3 wt% beeswax/graphene increased by 22.5%. The thermal conductivity of 0.3 wt% beeswax/graphene was 2.8 W/m K. The existence of graphene nanoplatelets enhanced both the latent heat and thermal conductivity of the beeswax. Therefore, based on this result, beeswax/graphene is concluded to have the potential to reduce energy consumption in buildings.
Amin, U, Hossain, MJ, Lu, J & Fernandez, E 2017, 'Performance analysis of an experimental smart building: Expectations and outcomes', Energy, vol. 135, pp. 740-753.
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Amini, Z, Ilham, Z, Ong, HC, Mazaheri, H & Chen, W-H 2017, 'State of the art and prospective of lipase-catalyzed transesterification reaction for biodiesel production', Energy Conversion and Management, vol. 141, pp. 339-353.
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Amini, Z, Ong, HC, Harrison, MD, Kusumo, F, Mazaheri, H & Ilham, Z 2017, 'Biodiesel production by lipase-catalyzed transesterification of Ocimum basilicum L. (sweet basil) seed oil', Energy Conversion and Management, vol. 132, pp. 82-90.
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Amiri, M, Tofigh, F, Ghafoorzadeh Yazdi, A & Abolhasan, M 2017, 'Exponential Antipodal Vivaldi Antenna With Exponential Dielectric Lens', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 1-1.
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Amjadipour, M, MacLeod, J, Lipton-Duffin, J, Iacopi, F & Motta, N 2017, 'Epitaxial graphene growth on FIB patterned 3C-SiC nanostructures on Si (111): reducing milling damage', Nanotechnology, vol. 28, no. 34, pp. 345602-345602.
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Epitaxial growth of graphene on SiC is a scalable procedure that does not require any further transfer step, making this an ideal platform for graphene nanostructure fabrication. Focused ion beam (FIB) is a very promising tool for exploring the reduction of the lateral dimension of graphene on SiC to the nanometre scale. However, exposure of graphene to the Ga+ beam causes significant surface damage through amorphisation and contamination, preventing epitaxial graphene growth. In this paper we demonstrate that combining a protective silicon layer with FIB patterning implemented prior to graphene growth can significantly reduce the damage associated with FIB milling. Using this approach, we successfully achieved graphene growth over 3C-SiC/Si FIB patterned nanostructures.
Andaluz-Ojeda, D, Nguyen, HB, Meunier-Beillard, N, Cicuéndez, R, Quenot, J-P, Calvo, D, Dargent, A, Zarca, E, Andrés, C, Nogales, L, Eiros, JM, Tamayo, E, Gandía, F, Bermejo-Martín, JF & Charles, PE 2017, 'Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity', Annals of Intensive Care, vol. 7, no. 1.
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� 2017, The Author(s). Background: The use of novel sepsis biomarkers has increased in recent years. However, their prognostic value with respect to illness severity has not been explored. In this work, we examined the ability of mid-regional proadrenomedullin (MR-proADM) in predicting mortality in sepsis patients with different degrees of organ failure, compared to that of procalcitonin, C-reactive protein and lactate. Methods: This was a two-centre prospective observational cohort, enrolling severe sepsis or septic shock patients admitted to the ICU. Plasma biomarkers were measured during the first 12�h of admission. The association between biomarkers and 28-day mortality was assessed by Cox regression analysis and Kaplan–Meier curves. Patients were divided into three groups as evaluated by the Sequential Organ Failure Assessment (SOFA) score. The accuracy of the biomarkers for mortality was determined by area under the receiver operating characteristic curve (AUROC) analysis. Results: A total of 326 patients with severe sepsis (21.7%) or septic shock (79.3%) were enrolled with a 28-day mortality rate of 31.0%. Only MR-proADM and lactate were associated with mortality in the multivariate analysis: hazard ratio 8.5 versus 3.4 (p� < �0.001). MR-proADM showed the best AUROC for mortality prediction at 28�days in the analysis over the entire cohort (AUROC [95% CI] 0.79 [0.74–0.84] ) (p� < �0.001). When patients were stratified by the degree of organ failure, MR-proADM was the only biomarker to predict mortality in all severity groups (SOFA�≤�6, SOFA�=�7–12, and SOFA�≥�13), AUROC [95% CI] of 0.75 [0.61–0.88] , 0.74 [0.66–0.83] and 0.73 [0.59–0.86] , respectively (p� < �0.05). All patients with MR-proADM concentrations ≤0.88�nmol/L survived up to 28�days. In patients with SOFA�≤�6, the addition of MR-proADM to the SOFA score increased the ability of SOFA to identify non-survivors, AUROC [95% CI] 0.70 [0.58–0.82] and 0.77 [0.66–0...
Ansari, AJ, Hai, FI, Price, WE, Drewes, JE & Nghiem, LD 2017, 'Forward osmosis as a platform for resource recovery from municipal wastewater - A critical assessment of the literature', Journal of Membrane Science, vol. 529, pp. 195-206.
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© 2017 Forward osmosis (FO) is an emerging membrane separation technology that has the potential to serve as a game changer in wastewater treatment. FO-based processes can simultaneously produce high quality effluent and pre-concentrated wastewater for anaerobic treatment to facilitate the recovery of energy and nutrients. Complex wastewaters can be directly pre-treated by FO and fresh water can be produced when coupled with a draw solute recovery process (i.e. reverse osmosis or membrane distillation). By enriching organic carbon and nutrients for subsequent biogas production, FO extends the resource recovery potential of current wastewater treatment processes. Here, we critically review recent applications of FO for simultaneous treatment and resource recovery from municipal wastewater. Research conducted to date highlights the importance of successfully integrating FO with anaerobic treatment. Emphasis is also placed on the development of novel FO-based hybrid systems utilising alternative energy sources for draw solute recovery. There remain several technical challenges to the practical realisation of FO for resource recovery from wastewater including salinity build-up, membrane fouling, and system scale-up. Strategies to overcome these challenges are critically assessed to establish a research roadmap for further development of FO as a platform for resource recovery from wastewater.
Antunes, N, Pipiras, V, Abry, P & Veitch, D 2017, 'Small and large scale behavior of moments of Poisson cluster processes', ESAIM: Probability and Statistics, vol. 21, pp. 369-393.
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Poisson cluster processes are special point processes that find use in modeling Internet traffic, neural spike trains, computer failure times and other real-life phenomena. The focus of this work is on the various moments and cumulants of Poisson cluster processes, and specifically on their behavior at small and large scales. Under suitable assumptions motivated by the multiscale behavior of Internet traffic, it is shown that all these various quantities satisfy scale free (scaling) relations at both small and large scales. Only some of these relations turn out to carry information about salient model parameters of interest, and consequently can be used in the inference of the scaling behavior of Poisson cluster processes. At large scales, the derived results complement those available in the literature on the distributional convergence of normalized Poisson cluster processes, and also bring forward a more practical interpretation of the so-called slow and fast growth regimes. Finally, the results are applied to a real data trace from Internet traffic.
Archibald, C, Schwalm, L & Ball, JE 2017, 'A SURVEY OF SECURITY IN ROBOTIC SYSTEMS: VULNERABILITIES, ATTACKS, AND SOLUTIONS', International Journal of Robotics and Automation, vol. 32, no. 2.
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Argha, A, Li, L & W. Su, S 2017, 'Sliding mode stabilisation of networked systems with consecutive data packet dropouts using only accessible information', International Journal of Systems Science, vol. 48, no. 6, pp. 1291-1300.
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© 2016 Informa UK Limited, trading as Taylor & Francis Group. This paper develops a novel stabilising sliding mode for systems involving uncertainties as well as measurement data packet dropouts. In contrast to the existing literature that designs the switching function by using unavailable system states, a novel linear sliding function is constructed by employing only the available communicated system states for the systems involving measurement packet losses. This also equips us with the possibility to build a novel switching component for discrete-time sliding mode control (DSMC) by using only available system states. Finally, using a numerical example, we evaluate the performance of the designed DSMC for networked systems.
Argha, A, Su, SW & Celler, BG 2017, 'Heart rate regulation during cycle-ergometer exercise via event-driven biofeedback', Medical & Biological Engineering & Computing, vol. 55, no. 3, pp. 483-492.
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© 2016, International Federation for Medical and Biological Engineering. This paper is devoted to the problem of regulating the heart rate response along a predetermined reference profile, for cycle-ergometer exercises designed for training or cardio-respiratory rehabilitation. The controller designed in this study is a non-conventional, non-model-based, proportional, integral and derivative (PID) controller. The PID controller commands can be transmitted as biofeedback auditory commands, which can be heard and interpreted by the exercising subject to increase or reduce exercise intensity. However, in such a case, for the purposes of effectively communicating to the exercising subject a change in the required exercise intensity, the timing of this feedback signal relative to the position of the pedals becomes critical. A feedback signal delivered when the pedals are not in a suitable position to efficiently exert force may be ineffective and this may, in turn, lead to the cognitive disengagement of the user from the feedback controller. This note examines a novel form of control system which has been expressly designed for this project. The system is called an “actuator-based event-driven control system”. The proposed control system was experimentally verified using 24 healthy male subjects who were randomly divided into two separate groups, along with cross-validation scheme. A statistical analysis was employed to test the generalisation of the PID tunes, derived based on the average transfer functions of the two groups, and it revealed that there were no significant differences between the mean values of root mean square of the tracking error of two groups (3.9 vs. 3.7 bpm, p= 0.65). Furthermore, the results of a second statistical hypothesis test showed that the proposed PID controller with novel synchronised biofeedback mechanism has better performance compared to a conventional PID controller with a fixed-rate biofeedback mechanism (Group 1: 3.9 vs...
Armaghani, DJ, Mohamad, ET, Narayanasamy, MS, Narita, N & Yagiz, S 2017, 'Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition', Tunnelling and Underground Space Technology, vol. 63, pp. 29-43.
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Arodudu, O, Helming, K, Wiggering, H & Voinov, A 2017, 'Bioenergy from Low-Intensity Agricultural Systems: An Energy Efficiency Analysis', Energies, vol. 10, no. 1, pp. 29-29.
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In light of possible future restrictions on the use of fossil fuel, due to climate change obligations and continuous depletion of global fossil fuel reserves, the search for alternative renewable energy sources is expected to be an issue of great concern for policy stakeholders. This study assessed the feasibility of bioenergy production under relatively low-intensity conservative, eco-agricultural settings (as opposed to those produced under high-intensity, fossil fuel based industrialized agriculture). Estimates of the net energy gain (NEG) and the energy return on energy invested (EROEI) obtained from a life cycle inventory of the energy inputs and outputs involved reveal that the energy efficiency of bioenergy produced in low-intensity eco-agricultural systems could be as much as much as 448.5–488.3 GJ·ha−1 of NEG and an EROEI of 5.4–5.9 for maize ethanol production systems, and as much as 155.0–283.9 GJ·ha−1 of NEG and an EROEI of 14.7–22.4 for maize biogas production systems. This is substantially higher than for industrialized agriculture with a NEG of 2.8–52.5 GJ·ha−1 and an EROEI of 1.2–1.7 for maize ethanol production systems, as well as a NEG of 59.3–188.7 GJ·ha−1 and an EROEI of 2.2–10.2 for maize biogas production systems. Bioenergy produced in low-intensity eco-agricultural systems could therefore be an important source of energy with immense net benefits for local and regional end-users, provided a more efficient use of the co-products is ensured.
Arodudu, O, Helming, K, Wiggering, H & Voinov, A 2017, 'Towards a more holistic sustainability assessment framework for agro-bioenergy systems — A review', Environmental Impact Assessment Review, vol. 62, pp. 61-75.
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Arodudu, OT, Helming, K, Voinov, A & Wiggering, H 2017, 'Integrating agronomic factors into energy efficiency assessment of agro-bioenergy production – A case study of ethanol and biogas production from maize feedstock', Applied Energy, vol. 198, pp. 426-439.
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© 2017 Elsevier Ltd Previous life cycle assessments for agro-bioenergy production rarely considered some agronomic factors with local and regional impacts. While many studies have found the environmental and socio-economic impacts of producing bioenergy on arable land not good enough to be considered sustainable, others consider it still as one of the most effective direct emission reduction and fossil fuel replacement measures. This study improved LCA methods in order to examine the individual and combined effects of often overlooked agronomic factors (e.g. alternative farm power, seed sowing, fertilizer, tillage and irrigation options) on life-cycle energy indicators (net energy gain-NEG, energy return on energy invested-EROEI), across the three major agro-climatic zones namely tropic, sub-tropic and the temperate landscapes. From this study, we found that individual as well as combined effects of agronomic factors may improve the energy productivity of arable bioenergy sources considerably in terms of the NEG (from between 6.8 and 32.9 GJ/ha to between 99.5 and 246.7 GJ/ha for maize ethanol; from between 39.0 and 118.4 GJ/ha to between 127.9 and 257.9 GJ/ha for maize biogas) and EROEI (from between 1.2 and 1.8 to between 2.1 and 3.0 for maize ethanol, from between 4.3 and 12.1 to between 15.0 and 33.9 for maize biogas). The agronomic factors considered by this study accounted for an extra 7.5–14.6 times more of NEG from maize ethanol, an extra 2.2–3.3 times more of NEG from maize biogas, an extra 1.7 to 1.8 times more of EROEI from maize ethanol, and an extra 2.8–3.5 times more of EROEI from maize biogas respectively. This therefore underscores the need to factor in local and regional agronomic factors into energy efficiency and sustainability assessments, as well as decision making processes regarding the application of energy from products of agro-bioenergy production.
Arora, A, Furlong, PM, Fitch, R, Sukkarieh, S & Fong, T 2017, 'Multi-Modal Active Perception for Information Gathering in Science Missions', Autonomous Robots, vol. 43, no. 7, pp. 1827-1853.
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Robotic science missions in remote environments, such as deep ocean and outerspace, can involve studying phenomena that cannot directly be observed usingon-board sensors but must be deduced by combining measurements of correlatedvariables with domain knowledge. Traditionally, in such missions, robotspassively gather data along prescribed paths, while inference, path planning,and other high level decision making is largely performed by a supervisoryscience team. However, communication constraints hinder these processes, andhence the rate of scientific progress. This paper presents an active perceptionapproach that aims to reduce robots' reliance on human supervision and improvescience productivity by encoding scientists' domain knowledge and decisionmaking process on-board. We use Bayesian networks to compactly model criticalaspects of scientific knowledge while remaining robust to observation andmodeling uncertainty. We then formulate path planning and sensor scheduling asan information gain maximization problem, and propose a sampling-based solutionbased on Monte Carlo tree search to plan informative sensing actions whichexploit the knowledge encoded in the network. The computational complexity ofour framework does not grow with the number of observations taken and allowslong horizon planning in an anytime manner, making it highly applicable tofield robotics. Simulation results show statistically significant performanceimprovements over baseline methods, and we validate the practicality of ourapproach through both hardware experiments and simulated experiments with fielddata gathered during the NASA Mojave Volatiles Prospector science expedition.
Arslan, A, Masjuki, HH, Kalam, MA, Varman, M, Mosarof, MH, Mufti, RA, Quazi, MM, Khuong, LS, Liaqat, M, Jamshaid, M, Alabdulkarem, A & Khurram, M 2017, 'Investigation of laser texture density and diameter on the tribological behavior of hydrogenated DLC coating with line contact configuration', Surface and Coatings Technology, vol. 322, pp. 31-37.
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Aryal, R, Beecham, S, Sarkar, B, Chong, MN, Kinsela, A, Kandasamy, J & Vigneswaran, S 2017, 'Readily Wash-Off Road Dust and Associated Heavy Metals on Motorways', Water, Air, & Soil Pollution, vol. 228, no. 1, pp. 1-12.
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© 2016, Springer International Publishing Switzerland. Road dust contains a wide range of potentially health-hazardous pollutant sources. In this study, road dust samples were collected from nine locations along the Sydney orbital motorway during wet weather events and analysed for their mineralogy and heavy metal contents. The aim of this study was to examine for the specific particle size fractions in road dust samples that can be associated with anthropogenic pollutant sources, mainly on the prevalence of heavy metals. Surface morphological and elemental composition of the road dust particles was analysed using scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX). The heavy metal contents and degree of contamination were also investigated including in the two specific particle size fractions of < 75 and 75–150 μm. It was found that the particle size fraction of < 75 μm made up between 6 and 16% of the entire particle size distributions and contributed to more than 90% of the heavy metal contents. In addition, a moderate to high degree of heavy metal contamination was measured in the collected road dust samples, and this was correlated well with the local traffic volumes. The good correlation between heavy metals and traffic volumes in the finer road dust particle size fraction of < 75 μm indicated that the finer road dust particles were not only important in terms of heavy metal attachment, accumulation and mobilisation during wet weather events but they could also provide evidence of potential anthropogenic pollution sources. These findings will facilitate our scientific understanding on the specific role and importance of particle size fractions on the mobilisation of pollutant sources, particularly heavy metals during wet weather events. It is anticipated that this study will assist in the development of best management practices for pollution prevention and control strategies on the frequency of road sweeping and rete...
Asadnia, M, Khorasani, AM & Warkiani, ME 2017, 'An Accurate PSO-GA Based Neural Network to Model Growth of Carbon Nanotubes', Journal of Nanomaterials, vol. 2017, pp. 1-6.
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By combining particle swarm optimization (PSO) and genetic algorithms (GA) this paper offers an innovative algorithm to train artificial neural networks (ANNs) for the purpose of calculating the experimental growth parameters of CNTs. The paper explores experimentally obtaining data to train ANNs, as a method to reduce simulation time while ensuring the precision of formal physics models. The results are compared with conventional particle swarm optimization based neural network (CPSONN) and Levenberg–Marquardt (LM) techniques. The results show that PSOGANN can be successfully utilized for modeling the experimental parameters that are critical for the growth of CNTs.
Asadnia, M, Mousavi Ehteshami, SM, Chan, SH & Warkiani, ME 2017, 'Development of a fiber-based membraneless hydrogen peroxide fuel cell', RSC Advances, vol. 7, no. 65, pp. 40755-40760.
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Polyvinylidene fluoride (PVDF) electrospun nano-fiber is suggested as the substrate material for developing biocompatible membraneless hydrogen peroxide fuel cells.
Ashamalla, A, Beydoun, G & Low, G 2017, 'Model driven approach for real-time requirement analysis of multi-agent systems.', Comput. Lang. Syst. Struct., vol. 50, pp. 127-139.
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Software systems can fail when requirement constraints are overlooked or violated. With the increased complexity of software systems, software development has become more reliant on model driven development. The paper advocates a model driven approach to ensure real-time requirement constraints are taken into account prior to the design of a multi-agent system (MAS). The paper presents the synthesis of a real-time metamodel to support requirements analysis of a MAS. The metamodel describes a collection of modelling units and constraints that can be used to identify the real-time requirements of a multi-agent system during the analysis phase. The paper takes the view that the earlier you model real-time requirements in the software development life cycle, the more reliable and robust the resultant system will be. Furthermore, the more likely it is an appropriate balance between competing time requirements will be achieved. The paper also presents a validation of the metamodel in a Call Management MAS application. This provides a preliminary evidence of the coverage and validity of the metamodel presented.
Asif, M, Hai, F, Kang, J, Van de Merwe, J, Leusch, F, Yamamoto, K, Price, W & Nghiem, L 2017, 'Degradation of Trace Organic Contaminants by a Membrane Distillation—Enzymatic Bioreactor', Applied Sciences, vol. 7, no. 9, pp. 879-879.
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A high retention enzymatic bioreactor was developed by coupling membrane distillation with an enzymatic bioreactor (MD-EMBR) to investigate the degradation of 13 phenolic and 17 non-phenolic trace organic contaminants (TrOCs). TrOCs were effectively retained (90–99%) by the MD membrane. Furthermore, significant laccase-catalyzed degradation (80–99%) was achieved for 10 phenolic and 3 non-phenolic TrOCs that contain strong electron donating functional groups. For the remaining TrOCs, enzymatic degradation ranged from 40 to 65%. This is still higher than those reported for enzymatic bioreactors equipped with ultrafiltration membranes, which retained laccase but not the TrOCs. Addition of three redox-mediators, namely syringaldehyde (SA), violuric acid (VA) and 1-hydroxybenzotriazole (HBT), in the MD-EMBR significantly broadened the spectrum of efficiently degraded TrOCs. Among the tested redox-mediators, VA (0.5 mM) was the most efficient and versatile mediator for enhanced TrOC degradation. The final effluent (i.e., membrane permeate) toxicity was below the detection limit, although there was a mediator-specific increase in toxicity of the bioreactor media.
Asif, MB, Hai, FI, Hou, J, Price, WE & Nghiem, LD 2017, 'Impact of wastewater derived dissolved interfering compounds on growth, enzymatic activity and trace organic contaminant removal of white rot fungi – A critical review', Journal of Environmental Management, vol. 201, pp. 89-109.
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© 2017 Elsevier Ltd White-rot fungi (WRF) and their ligninolytic enzymes have been investigated for the removal of a broad spectrum of trace organic contaminants (TrOCs) mostly from synthetic wastewater in lab-scale experiments. Only a few studies have reported the efficiency of such systems for the removal of TrOCs from real wastewater. Wastewater derived organic and inorganic compounds can inhibit: (i) WRF growth and their enzyme production capacity; (ii) enzymatic activity of ligninolytic enzymes; and (iii) catalytic efficiency of both WRF and enzymes. It is observed that essential metals such as Cu, Mn and Co at trace concertation (up to 1 mM) can improve the growth of WRF species, whereas non-essential metal such as Pb, Cd and Hg at 1 mM concentration can inhibit WRF growth and their enzyme production. In the case of purified enzymes, most of the tested metals at 1–5 mM concentration do not significantly inhibit the activity of laccases. Organic interfering compounds such as oxalic acid and ethylenediaminetetraacetic acid (EDTA) at 1 mM concentration are potent inhibitors of WRF and their extracellular enzymes. However, inhibitory effects induced by interfering compounds are strongly influenced by the type of WRF species as well as experimental conditions (e.g., incubation time and TrOC type). In this review, mechanisms and factors governing the interactions of interfering compounds with WRF and their ligninolytic enzymes are reviewed and elucidated. In addition, the performance of WRF and their ligninolytic enzymes for the removal of TrOCs from synthetic and real wastewater is critically summarized.
Asif, MB, Hai, FI, Singh, L, Price, WE & Nghiem, LD 2017, 'Degradation of Pharmaceuticals and Personal Care Products by White-Rot Fungi—a Critical Review', Current Pollution Reports, vol. 3, no. 2, pp. 88-103.
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White-rot fungi (WRF) mediated treatment can offer an environmentally friendly platform for the removal of pharmaceuticals and personal care products (PPCPs) from wastewater. These PPCPs may have adverse impacts on aquatic organisms and even human and thus their removal during wastewater treatment is of significant interest to the water industry. Whole-cell WRF or their extracellular lignin modifying enzymes (LMEs) have been reported to efficiently degrade PPCPs that are persistent to conventional activated sludge process. WRF mediated treatment of PPCPs depends on a number of factors including physicochemical properties of PPCPs (e.g., hydrophobicity and chemical structure) and wastewater matrix (e.g., pH, temperature, and dissolved constituents), type of WRF species and their specific extracellular enzymes. This review critically analyzes the performance of whole-cell WRF and their LMEs for the removal of PPCPs; particularly, it offers insights into PPCP removal mechanisms (e.g., biosorption vs. biodegradation) and degradation pathways as well as the formation of intermediate byproducts.
Asif, MB, Nguyen, LN, Hai, FI, Price, WE & Nghiem, LD 2017, 'Integration of an enzymatic bioreactor with membrane distillation for enhanced biodegradation of trace organic contaminants', International Biodeterioration & Biodegradation, vol. 124, pp. 73-81.
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© 2017 Elsevier Ltd A novel membrane distillation – enzymatic membrane bioreactor (MD-EMBR) system was developed for efficient degradation of trace organic contaminants (TrOCs). Degradation of five TrOCs, namely carbamazepine, oxybenzone, diclofenac, atrazine and sulfamethoxazole was examined using two commercially available laccases (from Trametes versicolor and Aspergillus oryzae). The MD system ensured complete retention ( > 99%) of both enzyme and TrOCs. Of particular interest was that the complete retention of the TrOCs resulted in high TrOC degradation by both laccases. Oxybenzone and diclofenac degradation in the MD-EMBR ranged between 80 and 99%. Compared to previously developed EMBRs, as much as 40% improvement in the removal of resistant non-phenolic TrOCs (e.g., carbamazepine) was observed. Laccase from A. oryzae demonstrated better TrOC degradation and enzymatic stability. With the addition of redox mediators, namely 1-hydroxybenzotriazole (HBT) or violuric acid (VA), TrOC degradation was improved by 10–20%. This is the first demonstration of a laccase-based high retention membrane bioreactor for enhanced biodegradation of TrOCs.
Asikin-Mijan, N, Lee, HV, Taufiq-Yap, YH, Abdulkrem-Alsultan, G, Mastuli, MS & Ong, HC 2017, 'Optimization study of SiO 2 -Al 2 O 3 supported bifunctional acid–base NiO-CaO for renewable fuel production using response surface methodology', Energy Conversion and Management, vol. 141, pp. 325-338.
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Askari, M, Li, J & Samali, B 2017, 'Cost-effective multi-objective optimal positioning of magnetorheological dampers and active actuators in large nonlinear structures', Journal of Intelligent Material Systems and Structures, vol. 28, no. 2, pp. 230-253.
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The optimal number and location of control devices not only play a major role in an effective structural control system but also lead to a cost-effective design. This article presents a multi-objective optimization method based on a new genetic algorithm for simultaneous finding of the optimal number and placement of actuators and magnetorheological dampers, in active and semi-active vibration control of structures. The proposed strategy considers three objective functions to be minimized through optimization, including peak inter-storey drift ratio, peak acceleration and peak base shear force to make sure both human comfort and safety of the structure are guaranteed. Also, by choosing a pre-defined level of performance on dynamic responses of a structure, the designer can decide on decreasing or increasing the number of control devices in a systematic way and minimize the control cost. The approach is then validated through a nonlinear 20-storey benchmark problem. The results from active control system show how a problem that was initially solved with 25 actuators can be solved with less than a quarter of those actuators, having similar results in terms of aforementioned indices. The optimal distribution of different numbers of magnetorheological dampers in the same benchmark building is also studied in this article and compared to those obtained from actuators. Due to highly nonlinear behaviour of these devices, and also the complexity of the under-study benchmark structure, few reported researches have been conducted in this area. Also, the comparison between optimal places of active and semi-active control devices in the same structure has hitherto not been reported in the open literature.
Atallah, R, Li, JJ, Lu, W, Leijendekkers, R, Frölke, JP & Al Muderis, M 2017, 'Osseointegrated Transtibial Implants in Patients with Peripheral Vascular Disease', Journal of Bone and Joint Surgery, vol. 99, no. 18, pp. 1516-1523.
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Background: Osseointegration is an alternative treatment for amputees who are unable to wear or have difficulty wearing a socket prosthesis. Although the majority of limb amputations are due to vascular disease, such amputations have been perceived as a contraindication to osseointegration surgery. We report the outcomes of osseointegrated reconstruction in a series of 5 patients with limb amputation due to peripheral vascular disease. Methods: Five patients with transtibial amputation and a history of peripheral vascular disease who received an osseointegration implant from 2014 to 2015 were followed for 12 months. Clinical and functional outcomes were assessed, including pain, the amount of time the patient wore the prosthesis, mobility, walking ability, and quality of life. Adverse events, including infection, fracture, implant failure, revision surgery, additional amputation, and death, were monitored and recorded. Results: Five transtibial amputees (56 to 84 years of age) followed for 1 year after osseointegration surgery were included in this case series. The mobility of all patients was improved at the time of follow-up. Three patients were wheelchair-bound prior to the surgery but all 5 were able to walk and perform daily activities at the time of follow-up. Four of the 5 patients were pain-free at 12 months postoperatively, and all 5 were using the osseointegrated prosthesis. Two patients had a single episode of superficial soft-tissue infection. Conclusions: An osseointegrated implant may be considered a feasible alternative to the conventional socket pros...
Avilés-Ochoa, E, Perez-Arellano, LA, León-Castro, E & Merigó, JM 2017, 'PRIORITIZED INDUCED PROBABILISTIC DISTANCES IN TRANSPARENCY AND ACCESS TO INFORMATION LAWS', FUZZY ECONOMIC REVIEW, vol. 22, no. 01, pp. 45-55.
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© 2016 Int. Association for Fuzzy-Set Management and Economy. All rights reserved. In this paper, a new extension of the ordered weighted average (OWA) operator is developed using four different methods: prioritized operators, induced operators, probabilistic operators and distance techniques. This new operator is called the prioritized induced probabilistic ordered weighted average distance (PIPOWAD) operator. The primary advantage is that we include in one formulation different characteristics and information provided by a group of decision makers to compare actual and ideal situations. Finally, an example of transparency and access to information law in Mexico is presented to forecast the score based on the expectations of decision makers.
Awadallah, M, Tawadros, P, Walker, P & Zhang, N 2017, 'Dynamic modelling and simulation of a manual transmission based mild hybrid vehicle', Mechanism and Machine Theory, vol. 112, pp. 218-239.
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© 2017 Elsevier Ltd This paper investigates the development of a mild hybrid powertrain system through the integration of a conventional manual transmission equipped powertrain and a secondary power source in the form of an electric motor driving the transmission output shaft. The primary goal of this paper is to study the performance of partial power-on gear shifts through the implementation of torque hole filling by the electric motor during gear changes. To achieve this goal, mathematical models of both conventional and mild hybrid powertrain are developed and used to compare the system dynamic performance of the two systems. This mathematical modelling is used to run different simulations for gear-shift control algorithm design during system development, allowing us to evaluate the achievable performance and its dependency on system properties. The impact of motor power on the degree of torque hole compensation is also investigated, keeping in mind the practical limits to motor specification. This investigation uses both the output torque, vehicle speed as well as vibration dose value to evaluate the quality of gearshifts at different motor sizes. Results demonstrate that the torque hole may be eliminated using a motor power of 50 kW. However, the minimum vibration dose value during gear change is achieved using a peak power of 16–20 kW.
Awadallah, M, Tawadros, P, Walker, P & Zhang, N 2017, 'Impact of Low and High Congestion Traffic Patterns on a Mild-HEV Performance', SAE Technical Paper Series, vol. 2017-October.
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Copyright © 2017 SAE International. Driven by stricter mandatory regulations on fuel economy improvement and emissions reduction, market penetration of electrified vehicles will increase in the next ten years. Within this growth, mild hybrid vehicles will become a leading sector. The high cost of hybrid electric vehicles (HEV) has somewhat limited their widespread adoption, especially in developing countries. Conversely, it is these countries that would benefit most from the environmental benefits of HEV technology. Compared to a full hybrid, plug-in hybrid, or electric vehicle, a mild hybrid system stands out due to its maximum benefit/cost ratio. As part of our ongoing project to develop a mild hybrid system for developing markets, we have previously investigated improvements in drive performance and efficiency using optimal gearshift strategies, as well as the incorporation of high power density supercapacitors. In this paper, the fuel and emissions of a baseline conventional vehicle and mild hybrid electric vehicle (MHEV) are compared. The objective of this analysis is to compare the fuel economy and Greenhouse Gas (GHG) emissions of the baseline and MHEV models, using low and high-density traffic patterns chosen for their similarity to traffic density profiles of our target markets. Results demonstrate the benefits of a lower ongoing cost for the HEV architecture. These advantages include torque-hole filling between gear changes, increased fuel efficiency and performance.
Awwad, S & Piccardi, M 2017, 'Prototype-based budget maintenance for tracking in depth videos', Multimedia Tools and Applications, vol. 76, no. 20, pp. 21117-21132.
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© 2016 Springer Science+Business Media New YorkThe use of conventional video tracking based on color or gray-level videos often raises concerns about the privacy of the tracked targets. To alleviate this issue, this paper presents a novel tracker that operates solely from depth data. The proposed tracker is designed as an extension of the popular Struck algorithm which leverages the effective framework of structural SVM. The main contributions of our paper are: i) a dedicated depth feature based on local depth patterns, ii) a heuristic for handling view occlusions in depth frames, and iii) a technique for keeping the number of the support vectors within a given “budget” so as to limit computational costs. Experimental results over the challenging Princeton Tracking Benchmark (PTB) dataset report a remarkable accuracy compared to the original Struck tracker and other state-of-the-art trackers using depth and RGB data.
Aya-Bonilla, CA, Marsavela, G, Freeman, JB, Lomma, C, Frank, MH, Khattak, MA, Meniawy, TM, Millward, M, Warkiani, ME, Gray, ES & Ziman, M 2017, 'Isolation and detection of circulating tumour cells from metastatic melanoma patients using a slanted spiral microfluidic device', Oncotarget, vol. 8, no. 40, pp. 67355-67368.
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Circulating Tumour Cells (CTCs) are promising cancer biomarkers. Several methods have been developed to isolate CTCs from blood samples. However, the isolation of melanoma CTCs is very challenging as a result of their extraordinary heterogeneity, which has hindered their biological and clinical study. Thus, methods that isolate CTCs based on their physical properties, rather than surface marker expression, such as microfluidic devices, are greatly needed in melanoma. Here, we assessed the ability of the slanted spiral microfluidic device to isolate melanoma CTCs via label-free enrichment. We demonstrated that this device yields recovery rates of spiked melanoma cells of over 80% and 55%, after one or two rounds of enrichment, respectively. Concurrently, a two to three log reduction of white blood cells was achieved with one or two rounds of enrichment, respectively. We characterised the isolated CTCs using multimarker flow cytometry, immunocytochemistry and gene expression. The results demonstrated that CTCs from metastatic melanoma patients were highly heterogeneous and commonly expressed stem-like markers such as PAX3 and ABCB5. The implementation of the slanted microfluidic device for melanoma CTC isolation enables further understanding of the biology of melanoma metastasis for biomarker development and to inform future treatment approaches.
Ayanian, N, Fitch, R, Franchi, A & Sabattini, L 2017, 'Multirobot Systems [TC Spotlight]', IEEE Robotics & Automation Magazine, vol. 24, no. 2, pp. 12-16.
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The Technical Committee (TC) on Multirobot Systems (MRS) was founded in 2014 to create a focal point for the wide and diverse community of researchers interested in MRS. Researchers interested in MRS represent an inherently diverse community because several competences are needed in this field, including control systems, mechanical design, coordination, cooperation, estimation, perception, and interaction. MRS research comprises three broad research areas. These areas of interest are modeling and control of MRS, planning and decision making for MRS, and applications of MRS and technological and methodological issues. The MRS TC sponsors many activities that bring our members together, both in person and online. Our flagship achievement to date is the founding of a new conference dedicated to multirobot and multiagent systems, the International Symposium on Multirobot and Multiagent Systems.
Azadeh, A, Foroozan, H, Ashjari, B, Motevali Haghighi, S, Yazdanparast, R, Saberi, M & Torki Nejad, M 2017, 'Performance assessment and optimisation of a large information system by combined customer relationship management and resilience engineering: a mathematical programming approach', Enterprise Information Systems, vol. 11, no. 9, pp. 1-15.
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Azadeh, A, Jebreili, S, Chang, E, Saberi, M & Hussain, OK 2017, 'An integrated fuzzy algorithm approach to factory floor design incorporating environmental quality and health impact', International Journal of System Assurance Engineering and Management, vol. 8, no. S4, pp. 2071-2082.
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This paper presents an integrated algorithm based on fuzzy simulation, fuzzy linear programming (FLP), and fuzzy data envelopment analysis (FDEA) to cope with a special case of workshop facility layout design problem with ambiguous environmental and health indicators. First a software package is used for generating feasible layout alternatives and then quantitative performance indicators are calculated. Weights are estimated by LP for pairwise comparisons (by linguistic terms) in evaluating certain qualitative performance indicators. Fuzzy simulation is then employed for modeling different layout alternatives with uncertain parameters. Next, the impacts of environment and health indicators are retrieved from a standard questionnaire. Finally, FDEA is used for ranking the alternatives and consequently finding the optimal layout design alternatives. A possibilistic programming approach is used to modify the fuzzy DEA model to an equivalent crisp one. Moreover, fuzzy principal component analysis method is used to validate the results of FDEA model at various α-cut levels by Spearman correlation experiment. This is the first study that presents an integrated algorithm for optimization of facility layout with environmental and health indicators.
Azadeh, A, Sadri, S, Saberi, M, Yoon, JH, Chang, E, Khadeer Hussain, O & Pourmohammad Zia, N 2017, 'An Integrated Fuzzy Trust Prediction Approach in Product Design and Engineering', International Journal of Fuzzy Systems, vol. 19, no. 4, pp. 1190-1199.
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Baba, AA, Hashmi, RM & Esselle, KP 2017, 'Achieving a Large Gain-Bandwidth Product From a Compact Antenna', IEEE Transactions on Antennas and Propagation, vol. 65, no. 7, pp. 3437-3446.
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Babanajad, SK, Gandomi, AH & Alavi, AH 2017, 'New prediction models for concrete ultimate strength under true-triaxial stress states: An evolutionary approach', Advances in Engineering Software, vol. 110, pp. 55-68.
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The complexity associated with the in-homogeneous nature of concrete suggests the necessity of conducting more in-depth behavioral analysis of this material in terms of different loading configurations. Distinctive feature of Gene Expression Programming (GEP) has been employed to derive computer-aided prediction models for the multiaxial strength of concrete under true-triaxial loading. The proposed models correlate the concrete true-triaxial strength (σ1) to mix design parameters and principal stresses (σ2,σ3), needless of conducting any time-consuming laboratory experiments. A comprehensive true-triaxial database is obtained from the literature to build the proposed models, subsequently implemented for the verification purposes. External validations as well as sensitivity analysis are further carried out using several statistical criteria recommended by researchers. More, they demonstrate superior performance to the other existing empirical and analytical models. The proposed design equations can readily be used for pre-design purposes or may be used as a fast check on deterministic solutions.
Bakirov, R, Gabrys, B & Fay, D 2017, 'Multiple adaptive mechanisms for data-driven soft sensors', Computers & Chemical Engineering, vol. 96, pp. 42-54.
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Recent data-driven soft sensors often use multiple adaptive mechanisms to cope with non-stationary environments. These mechanisms are usually deployed in a prescribed order which does not change. In this work we use real world data from the process industry to compare deploying adaptive mechanisms in a fixed manner to deploying them in a flexible way, which results in varying adaptation sequences. We demonstrate that flexible deployment of available adaptive methods coupled with techniques such as cross-validatory selection and retrospective model correction can benefit the predictive accuracy over time. As a vehicle for this study, we use a soft-sensor for batch processes based on an adaptive ensemble method which employs several adaptive mechanisms to react to the changes in data.
Ball, J 2017, 'Review Comments', Hydrology Earth Systems Science Dicsions, pp. C!-C3.
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Ball, JE, Anderson, DT & Chan, CS 2017, 'Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community', Journal of Applied Remote Sensing, vol. 11, no. 04, pp. 1-1.
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Banihashemi, S, Ding, G & Wang, J 2017, 'Developing a Hybrid Model of Prediction and Classification Algorithms for Building Energy Consumption', Energy Procedia, vol. 110, pp. 371-376.
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© 2017 The Authors. Artificial intelligence algorithms have been applied separately or integrally for prediction, classification or optimization of buildings energy consumption. However, there is a salient gap in the literature on the investigation of hybrid objective function development for energy optimization problems including qualitative and quantitative datasets in their constructs. To tackle with this challenge, this paper presents a hybrid objective function of machine learning algorithms in optimizing energy consumption of residential buildings through considering both continuous and discrete parameters of energy simultaneously. To do this, a comprehensive dataset including significant parameters of building envelop, building design layout and HVAC was established, Artificial Neural Network as a prediction and Decision Tree as a classification algorithm were employed via cross-training ensemble equation to create the hybrid function and the model was finally validated via the weighted average of the error decomposed for the performance. The developed model could effectively enhance the accuracy of the objective functions used in the building energy prediction and optimization problems. Furthermore, the results of this novel approach resolved the inclusion issue of both continuous and discrete parameters of energy in a unified objective function without threatening the integrity and consistency of the building energy datasets.
Bannister, KW, Shannon, RM, Macquart, J-P, Flynn, C, Edwards, PG, O’Neill, M, Osłowski, S, Bailes, M, Zackay, B, Clarke, N, D’Addario, LR, Dodson, R, Hall, PJ, Jameson, A, Jones, D, Navarro, R, Trinh, JT, Allison, J, Anderson, CS, Bell, M, Chippendale, AP, Collier, JD, Heald, G, Heywood, I, Hotan, AW, Lee-Waddell, K, Madrid, JP, Marvil, J, McConnell, D, Popping, A, Voronkov, MA, Whiting, MT, Allen, GR, Bock, DC-J, Brodrick, DP, Cooray, F, DeBoer, DR, Diamond, PJ, Ekers, R, Gough, RG, Hampson, GA, Harvey-Smith, L, Hay, SG, Hayman, DB, Jackson, CA, Johnston, S, Koribalski, BS, McClure-Griffiths, NM, Mirtschin, P, Ng, A, Norris, RP, Pearce, SE, Phillips, CJ, Roxby, DN, Troup, ER & Westmeier, T 2017, 'The Detection of an Extremely Bright Fast Radio Burst in a Phased Array Feed Survey', The Astrophysical Journal Letters, vol. 841, no. 1, pp. L12-L12.
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Abstract We report the detection of an ultra-bright fast radio burst (FRB) from a modest, 3.4-day pilot survey with the Australian Square Kilometre Array Pathfinder. The survey was conducted in a wide-field fly’s-eye configuration using the phased-array-feed technology deployed on the array to instantaneously observe an effective area of 160 deg2, and achieve an exposure totaling 13200 deg2 hr . We constrain the position of FRB 170107 to a region in size (90% containment) and its fluence to be 58 ± 6 Jy ms. The spectrum of the burst shows a sharp cutoff above 1400 MHz, which could be due to either scintillation or an intrinsic feature of the burst. This confirms the existence of an ultra-bright ( Jy ms) population of FRBs.
Bano, M, Zowghi, D & Rimini, FD 2017, 'User satisfaction and system success: an empirical exploration of user involvement in software development.', Empir. Softw. Eng., vol. 22, no. 5, pp. 2339-2372.
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© 2016, Springer Science+Business Media New York. For over four decades user involvement has been considered intuitively to lead to user satisfaction, which plays a pivotal role in successful outcome of a software project. The objective of this paper is to explore the notion of user satisfaction within the context of the user involvement and system success relationship. We have conducted a longitudinal case study of a software development project and collected qualitative data by means of interviews, observations and document analysis over a period of 3 years. The analysis of our case study data revealed that user satisfaction significantly contributes to the system success even when schedule and budget goals are not met. The case study data analysis also presented additional factors that contribute to the evolution of user satisfaction throughout the project. Users’ satisfaction with their involvement and the resulting system are mutually constituted while the level of user satisfaction evolves throughout the stages of software development process. Effective management strategies and user representation are essential elements of maintaining an acceptable level of user satisfaction throughout software development process.
Barnet, MB, O’Toole, S, Horvath, LG, Selinger, C, Yu, B, Ng, CC, Boyer, M, Cooper, WA & Kao, S 2017, 'EGFR–Co-Mutated Advanced NSCLC and Response to EGFR Tyrosine Kinase Inhibitors', Journal of Thoracic Oncology, vol. 12, no. 3, pp. 585-590.
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Barns, S, Balanant, MA, Sauret, E, Flower, R, Saha, S & Gu, Y 2017, 'Investigation of red blood cell mechanical properties using AFM indentation and coarse-grained particle method', BioMedical Engineering OnLine, vol. 16, no. 1.
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© 2017 The Author(s). Background: Red blood cells (RBCs) deform significantly and repeatedly when passing through narrow capillaries and delivering dioxygen throughout the body. Deformability of RBCs is a key characteristic, largely governed by the mechanical properties of the cell membrane. This study investigated RBC mechanical properties using atomic force microscopy (AFM) with the aim to develop a coarse-grained particle method model to study for the first time RBC indentation in both 2D and 3D. This new model has the potential to be applied to further investigate the local deformability of RBCs, with accurate control over adhesion, probe geometry and position of applied force. Results: The model considers the linear stretch capacity of the cytoskeleton, bending resistance and areal incompressibility of the bilayer, and volumetric incompressibility of the internal fluid. The model's performance was validated against force-deformation experiments performed on RBCs under spherical AFM indentation. The model was then used to investigate the mechanisms which absorbed energy through the indentation stroke, and the impact of varying stiffness coefficients on the measured deformability. This study found the membrane's bending stiffness was most influential in controlling RBC physical behaviour for indentations of up to 200 nm. Conclusions: As the bilayer provides bending resistance, this infers that structural changes within the bilayer are responsible for the deformability changes experienced by deteriorating RBCs. The numerical model presented here established a foundation for future investigations into changes within the membrane that cause differences in stiffness between healthy and deteriorating RBCs, which have already been measured experimentally with AFM.
Barua, P, Rahman, SH & Molla, MH 2017, 'Sustainable adaptation for resolving climate displacement issues of south eastern islands in Bangladesh', International Journal of Climate Change Strategies and Management, vol. 9, no. 6, pp. 790-810.
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PurposeClimate change is affecting people displacement in Bangladesh by both sudden environmental events and gradual environmental change. This paper aims to assess the sustainable adaptation measures for resolving the displacement problem induced by climate change considering the socioeconomic differences between the past and the present location of living places for island dwellers of the south-eastern coast of Bangladesh.Design/methodology/approachBoth qualitative and quantitative approaches were adopted for conducting the study. The main tool of the household survey was a questionnaire survey. In addition to the estimate of displacement, the authors have used hazard impact analysis, weightage analysis and sustainable adaptation analysis with various ranking. Meaningful data were analyzed through SPSS software and presented through statistical techniques.FindingsClimate change-induced different natural disasters, such as cyclone, tidal surge, tidal flood and coastal erosion, were frequent in the study areas and responsible for mass displacement. After displacement, people lost not only their identity but also social and cultural harmony and faced different economic and environmental crises. However, nearly 20 types of adaptation options were identified for protection from the displacement of coastal people.Practical implicationsThe study prescribed 11 specific criteria and 4 principles of sustainable adaptation options for resolving the climate displacement problem. Moreover, seven adaptation practices showed high sustainability, ten showed medium sustainability and five ...
Basack, S & Nimbalkar, S 2017, 'Free strain analysis of the performance of vertical drains for soft soil improvement', Geomechanics and Engineering, vol. 13, no. 6, pp. 963-975.
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Improvement of soft clay deposit by preloading with vertical drains is one of the most popular techniques followed worldwide. These drains accelerate the rate of consolidation by shortening the drainage path. Although the analytical and numerical solutions available are mostly based on equal strain hypothesis, the adoption of free strain analysis is more realistic because of the flexible nature of the imposed surcharge loading, especially for the embankment loading used for transport infrastructure. In this paper, a numerical model has been developed based on free strain hypothesis for understanding the behaviour of soft ground improvement by vertical drain with preloading. The unit cell analogy is used and the effect of smear has been incorporated. The model has been validated by comparing with available field test results and thereafter, a hypothetical case study is done using the available field data for soft clay deposit existing in the eastern part of Australia and important conclusions are drawn therefrom.
Basack, S & Nimbalkar, S 2017, 'Numerical Solution of Single Pile Subjected to Torsional Cyclic Load', International Journal of Geomechanics, vol. 17, no. 8, pp. 04017016-04017016.
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© 2017 American Society of Civil Engineers. Large structures, such as offshore platforms, wind turbine foundations, wide buildings, bridges, and railway granular embankments, are often supported by pile foundations. These structures are usually subjected to large cyclic loads (in axial, lateral, and torsional modes) arising from actions of waves, ship impacts, or moving trains. Significant torsional cyclic forces can be transferred to the foundation piles due to the eccentricity of the lateral loads. In the past, several theoretical and experimental investigations were carried out on piles under axial and lateral cyclic loads; however, study of the influence of torsional cyclic loads on pile foundations is rather limited. This paper presents a novel numerical model based on the boundary element approach to analyze the response of a single, vertical, floating pile subjected to torsional cyclic load. The nonlinear stress-strain response of soil is incorporated, and the pile material was idealized as elastic-perfectly plastic. The effect of progressive degradation of soil strength and stiffness under cyclic stress reversal is incorporated in the numerical method. Apart from predicting the degradation of torsional pile-soil interactive performance, the profiles for shear stress and angle of twist are also captured by the proposed solution. Validation of the model indicates the suitability and accuracy of the proposed solutions. The frequency, amplitude, and number of cycles play significant roles in torsional cyclic response of piles. The proposed model is also applied successfully to selected case studies on single piles under torsional cyclic loading, and important conclusions are drawn from there.
Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2017, 'Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017016-04017016.
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Bathrellos, GD, Skilodimou, HD, Chousianitis, K, Youssef, AM & Pradhan, B 2017, 'Suitability estimation for urban development using multi-hazard assessment map', Science of The Total Environment, vol. 575, pp. 119-134.
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© 2016 Preparation of natural hazards maps are vital and essential for urban development. The main scope of this study is to synthesize natural hazard maps in a single multi-hazard map and thus to identify suitable areas for the urban development. The study area is the drainage basin of Xerias stream (Northeastern Peloponnesus, Greece) that has frequently suffered damages from landslides, floods and earthquakes. Landslide, flood and seismic hazard assessment maps were separately generated and further combined by applying the Analytical Hierarchy Process (AHP) and utilizing a Geographical Information System (GIS) to produce a multi-hazard map. This map represents the potential suitability map for urban development in the study area and was evaluated by means of uncertainty analysis. The outcome revealed that the most suitable areas are distributed in the southern part of the study area, where the landslide, flood and seismic hazards are at low and very low level. The uncertainty analysis shows small differences on the spatial distribution of the suitability zones. The produced suitability map for urban development proves a satisfactory agreement between the suitability zones and the landslide and flood phenomena that have affected the study area. Finally, 40% of the existing urban pattern boundaries and 60% of the current road network are located within the limits of low and very low suitability zones.
Bayat, E, Rodríguez, JF, Saco, PM, de Almeida, GAM, Vahidi, E & García, MH 2017, 'A tale of two riffles: Using multidimensional, multifractional, time‐varying sediment transport to assess self‐maintenance in pool‐riffle sequences', Water Resources Research, vol. 53, no. 3, pp. 2095-2113.
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AbstractPool‐riffle sequences play a central role in providing habitat diversity conditions both in terms of flow and substrate in gravel bed streams. Understanding their capacity to self‐maintain has been the focus of research for many years, starting with the velocity reversal hypothesis. This hypothesis relied only on cross sectional averaged flow information, but its limited success prompted extensions of the hypothesis and alternative explanations for self‐maintenance. Significant advances beyond the velocity reversal hypothesis have been achieved by incorporating more information either on flow or sediment transport characteristics. However, this has been done in a compartmentalized way, with studies either focusing on one or the other aspect. This work bridges the gap between these two aspects by using an approximate methodology that combines observed characteristic stage‐dependent 3‐D flow patterns with time‐varying cross sectional information on bed shear stresses, sediment distribution, and sediment bed changes during a 1 year record of continuous discharges from a real stream. This methodology allows us to track the behavior of different sediment size fractions along flow streamlines over time and identify self‐maintenance conditions due to the combined effect of both flow multidimensionality and sediment transport. We apply this approximate methodology to two contiguous pools and riffles and demonstrate that, unexpectedly, they may rely on different mechanisms for self‐maintenance due to differences in geometry and sediment size distribution. We also demonstrate that our methodology is potentially overarching and integrative of previous partial approaches based on flow multidimensionality or sediment transport, which tend to underestimate the occurrence of self‐maintenance.
Belete, GF, Voinov, A & Laniak, GF 2017, 'An overview of the model integration process: From pre-integration assessment to testing', Environmental Modelling & Software, vol. 87, pp. 49-63.
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© 2016 Elsevier Ltd Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems.
Belete, GF, Voinov, A & Morales, J 2017, 'Designing the Distributed Model Integration Framework – DMIF', Environmental Modelling & Software, vol. 94, pp. 112-126.
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� 2017 Elsevier Ltd We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of interoperability. Reusable web service wrappers were developed for technical interoperability models created in NetLogo and GAMS modeling languages. We investigated automated semantic mapping of text-based input-output data and attribute names of components using word overlap semantic matching algorithms and using an openly available lexical database. We also incorporated automated unit conversion in semantic mediation by using openly available ontologies. DMIF helps to avoid significant amount of reinvention by framework developers, and opens up the modeling process for many stakeholders who are not prepared to deal with the technical difficulties associated with installing, configuring, and running various models. As a proof of concept, we implemented our design to integrate several climate-energy-economy models.
Belhaj, D, Athmouni, K, Frikha, D, Kallel, M, El Feki, A, Maalej, S, Zhou, JL & Ayadi, H 2017, 'Biochemical and physiological responses of halophilic nanophytoplankton (Dunaliella salina) from exposure to xeno-estrogen 17α-ethinylestradiol', Environmental Science and Pollution Research, vol. 24, no. 8, pp. 7392-7402.
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© 2017, Springer-Verlag Berlin Heidelberg. The environmental impacts of various pollutants on the entire levels of organisms are under investigation. Among these pollutants, endocrine-disrupting compounds (EDCs) present a serious hazard, even though the environmental significance of these compounds remains basically unknown. To drop some light on this field, we assessed the effects of a 11-day exposure of 17α-ethinylestradiol (EE2) on the growth, metabolic content, antioxidant response, oxidative stress, and genetic damage of Dunaliella salina, isolated from Tunisian biotopes. The results showed that at 10 ng L−1, EE2 could stimulate the growth of D. salina and increase its cellular content of photosynthetic pigments and metabolites; however, it did not significantly increase the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) or the level of malondialdehyde (MDA) and hydrogen peroxide (H2O2). In contrast, exposure to high levels of EE2 concentrations significantly inhibited the growth of D. salina (P < 0.05), decreased the cellular content of photosynthetic pigments, increased the cellular content of all of the metabolites and the SOD activity, and inhibited CAT and GPx activities. Nevertheless, the balance between oxidant and antioxidant enzymes was disrupted because H2O2 content along with MDA content simultaneously increased. Contrary to expected results, DNA damage (strand breaks) decreased after the exposure of algae to EE2. The results of this study suggest that EE2 toxicity could result in environmental impacts with consequences on the whole aquatic community. [Figure not available: see fulltext.]
Belhaj, D, Frikha, D, Athmouni, K, Jerbi, B, Ahmed, MB, Bouallagui, Z, Kallel, M, Maalej, S, Zhou, J & Ayadi, H 2017, 'Box-Behnken design for extraction optimization of crude polysaccharides from Tunisian Phormidium versicolor cyanobacteria (NCC 466): Partial characterization, in vitro antioxidant and antimicrobial activities', International Journal of Biological Macromolecules, vol. 105, pp. 1501-1510.
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© 2017 In this study, response surface methodology (RSM) based on Box-Behnken design (BBD) was employed to optimize the aqueous extraction of crude polysaccharides from Tunisian cyanobacteria Phormidium versicolor (NCC 466). The optimal extraction conditions with an extraction yield of 21.56 ± 0.92% were as follows: extraction temperature at 81.05 °C, extraction time of 3.99 h, and water to raw material ratio of 21.52 mL g−1. Crude Phormidium versicolor polysaccharides (CPv-PS) are found to be a hetero-sulfated-anionic polysaccharides that contained carbohydrate (79.37 ± 1.58%), protein (0.45 ± 0.11%), uronic acids (4.37 ± 0.19%) and sulfate (6.83 ± 0.28%). The carbohydrate fraction was composed of arabinose, xylose, ribose, rhamnose, N-acetyl glucosamine, galactose, glucose, mannose, glucuronic acid and saccharose with corresponding mole percentages of 2.41, 14.58, 2.18, 6.23, 7.04, 28.21, 26.04, 3.02, 0.86 and 5.07, respectively. Evaluation of the antioxidant activity in vitro suggested that CPv-PS strongly scavenged radicals, prevented bleaching of β-carotene and reduced activity. Furthermore, the CPv-PS exhibited effective antimicrobial properties.
Belotti, Y, Huang, T, McKenna, S, Nabi, G & McGloin, D 2017, 'High-throughput, imaging based mechanical phenotyping of prostate cancer cells', Optics InfoBase Conference Papers, vol. Part F81-EQEC 2017.
Benamú, M, Lacava, M, García, LF, Santana, M, Fang, J, Wang, X & Blamires, SJ 2017, 'Nanostructural and mechanical property changes to spider silk as a consequence of insecticide exposure', Chemosphere, vol. 181, pp. 241-249.
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Bennett, NS 2017, 'Thermoelectric performance in n‐type bulk silicon: The influence of dopant concentration and dopant species', physica status solidi (a), vol. 214, no. 7, pp. 1-5.
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Silicon (Si) has received recent interest for thermoelectric (TE) applications. For all TE materials, accurately tuning the doping concentration remains the easiest way to maximise the thermoelectric figure‐of‐merit (ZT). This study investigates the thermoelectric properties at 300 K of n‐type Si as a function of both dopant concentration (N ∼1019–1020 cm−3) and dopant species (P, As and Sb), including measurements of electrical resistivity, thermal conductivity, Seebeck coefficient and Hall mobility. All properties were found to vary as a function of both doping concentration and species, leading to impacts on the ZT. The electrical resistivity was lowest for P‐doped Si and highest in Sb‐doped Si. For the Seebeck coefficient, the situation was reversed. The thermal conductivity was lowest for Sb‐doping and highest in P‐doped Si. In all cases As‐doping was the intermediate dopant. An optimum doping concentration was realized at a value of ∼6–7 × 1019cm−3, and is similar for both As‐ and P‐doped Si. For Sb‐doping, the optimum value is likely to be similar, but the highest doping in commercially available wafers was ∼4 × 1019cm−3. At 300 K, ZT ∼0.010 is achieved for P‐doped bulk Si, however the best overall value was for As‐doped Si, at ∼0.013. For Sb doping the best value is ∼0.012, though a higher value is likely to be possible, but only if doping levels approximately double the concentrations available for this current study can be achieved in starting substrates. These results provide a useful insight for researchers who are selecting a starting substrate for top‐down nano‐structuring approaches to Si thermoelectrics, where a wafer with optimised ZT is required.
Best, G, Martens, W & Fitch, R 2017, 'Path Planning With Spatiotemporal Optimal Stopping for Stochastic Mission Monitoring', IEEE Transactions on Robotics, vol. 33, no. 3, pp. 629-646.
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© 2017 IEEE. We consider an optimal stopping formulation of the mission monitoring problem, in which a monitor vehicle must remain in close proximity to an autonomous robot that stochastically follows a predicted trajectory. This problem arises in a diverse range of scenarios, such as autonomous underwater vehicles supervised by surface vessels, pedestrians monitored by aerial vehicles, and animals monitored by agricultural robots. The key problem characteristics we consider are that the monitor must remain stationary while observing the robot, robot motion is modeled in general as a stochastic process, and observations are modeled as a spatial probability distribution. We propose a resolution-complete algorithm that runs in a polynomial time. The algorithm is based on a sweep-plane approach and generates a motion plan that maximizes the expected observation time and value. A variety of stochastic models may be used to represent the robot trajectory. We present results with data drawn from real AUV missions, a real pedestrian trajectory dataset and Monte Carlo simulations. Our results demonstrate the performance and behavior of our algorithm, and relevance to a variety of applications.
Beydoun, G, Hoffmann, A & Gill, A 2017, 'Constructing enhanced default theories incrementally', Complex & Intelligent Systems, vol. 3, no. 2, pp. 83-92.
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The main difference between various formalisms of non-monotonic reasoning is the representation of non-monotonic rules. In default logic, they are represented by special expressions called defaults. In default logic, commonsense knowledge about the world is represented as a set of named defaults. The use of defaults is popular because they reduce the complexity of the representation, and they are sufficient for knowledge representation in many naturally occurring contexts. This paper offers an incremental process to acquire defaults from human experts directly and at the same time it provides added semantics to defaults by adding priorities to defaults and creating additional relations between them. The paper uses an existing incremental framework, NRDR, to generate these defaults. This framework is chosen as it not only enables incremental context driven formulation of defaults, but also allows experts to introduce their own domain terms. In choosing this framework, the paper broadens its utility.
Bharathy, G & Raji, P 2017, 'Room temperature ferromagnetic behavior of Mn doped NiO nanoparticles: a suitable electrode material for supercapacitors', Journal of Materials Science: Materials in Electronics, vol. 28, no. 23, pp. 17889-17895.
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Bishop, D, Situ, R, Brown, R & Surawski, N 2017, 'Numerical Modelling of Biodiesel Blends in a Diesel Engine', Energy Procedia, vol. 110, pp. 402-407.
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© 2017 The Authors. Biodiesel is a biofuel which has similar properties to diesel and can readily be used in a diesel engine with minimal modifications. Promising results have been determined using mixtures of biodiesel and diesel with the reduction of soot and emissions of a diesel engine. Experimental analysis of diesel engines can be expensive and therefore Computation Fluid Dynamics programs are used to analyses the combustion process. The AVL Fire ESED program is currently being employed to investigate the effects of biodiesel on the diesel engines soot, emissions and power generation from a Cummins ISBE220 engine. Investigation is performed on pre and post injection-rate shapes on the combustion process establishing the results correlate accurately with researched data. A pre injection was determined to increase maximum power, reduce combustion generated noise, increase early in cylinder temperature and reduce fuel consumption due to the increase in power. A post injection was verified to reduce soot emissions while increasing NOx emissions marginally. The investigation of the injection-rate shape established the soot-NOx trade-off which was also found in the research. The models developed were agreeable with biodiesel data with percentage error in indicated power ranging from 1.62-8.85%. The models suggested that biodiesel assists in reducing NOx and soot emissions. The soot-NOx trade-off was further investigated determining the theory that then by reducing the combustion temperature in the combustion chamber the NOx emissions can be reduced while increasing soot emissions. By increasing the temperature in the combustion chamber the opposite effect was found to occur.
Blamires, SJ, Hasemore, M, Martens, PJ & Kasumovic, MM 2017, 'Diet-induced covariation between architectural and physicochemical plasticity in an extended phenotype', Journal of Experimental Biology, vol. 220, no. Pt 5, pp. 876-884.
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The adaptive benefits of extended phenotypic plasticity are imprecisely defined due to a paucity of experiments examining traits that are manipulable and measurable across environments. Spider webs are often used as models to explore the adaptive benefits of variations in extended phenotypes across environments. Nonetheless, our understanding of the adaptive nature of the plastic responses of spider webs is impeded when web architectures and silk physicochemical properties appear to co-vary. An opportunity to examine this co-variation is presented by modifying prey items while measuring web architectures and silk physiochemical properties. Here we performed two experiments to assess the nature of the association between web architectures and gluey silk properties when the orb web spider Argiope keyserlingi was fed a diet that varied in either mass and energy or prey size and feeding frequency. We found web architectures and gluey silk physicochemical properties to co-vary across treatments in both experiments. Specifically, web capture area co-varied with gluey droplet morphometrics, thread stickiness and salt concentrations when prey mass and energy were manipulated, and spiral spacing co-varied with gluey silk salt concentrations when prey size and feeding frequency were manipulated. We explained our results as A. keyserlingi plastically shifting its foraging strategy as multiple prey parameters simultaneously varied. We confirmed and extended previous work by showing that spiders use a variety of prey cues to concurrently adjust web and silk traits across different feeding regimes.
Blanco-Mesa, F & Merigó, JM 2017, 'BONFERRONI DISTANCES WITH HYBRID WEIGHTED DISTANCE AND IMMEDIATE WEIGHTED DISTANCE', FUZZY ECONOMIC REVIEW, vol. 22, no. 02, pp. 2274-2274.
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© 2017 Int. Association for Fuzzy-Set Management and Economy. All rights reserved. The aim of the paper is to develop new aggregation operators using Bonferroni means, ordered weighted averaging (OWA) operators and some measures of distance. We introduce the Bonferroni Hybrid-weighted distance (BON-HWD), and Bonferroni distances with OWA operators and weighted averages (BON-IWOWAD). The main advantages of using these operators are that they allow the consideration of different aggregations contexts to be considered and multiple-comparison between each argument and distance measures in the same formulation. We develop a mathematical application to show the versatility of new models. Finally, this new group of family distances can be used in a wide range of management and economic fields.
Blanco-Mesa, F, Merigó, JM & Gil-Lafuente, AM 2017, 'Fuzzy decision making: A bibliometric-based review', Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2033-2050.
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Fuzzy decision-making consists in making decisions under complex and uncertain environments where the information can be assessed with fuzzy sets and systems. The aim of this study is to review the main contributions in this field by using a bibliometric approach. For doing so, the article uses a wide range of bibliometric indicators including the citations and the h -index. Moreover, it also uses the VOS viewer software in order to map the main trends in this area. The work considers the leading journals, articles, authors and institutions. The results indicate that the USA was the traditional leader in this field with the most significant researcher. However, during the last years, this field is receiving more attention by Asian authors that are starting to lead the field. This discipline has a strong potential and the expectations for the future is that it will continue to grow.
Bluff, A & Johnston, A 2017, 'Creature:Interactions: A Social Mixed-Reality Playspace', Leonardo, vol. 50, no. 4, pp. 360-367.
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This paper discusses Creature:Interactions (2015), a large-scale mixed-reality artwork created by the authors that incorporates immersive 360° stereoscopic visuals, interactive technology, and live actor facilitation. The work uses physical simulations to promote an expressive full-bodied interaction as children explore the landscapes and creatures of Ethel C. Pedley’s ecologically focused children’s novel, Dot and the Kangaroo. The immersive visuals provide a social playspace for up to 90 people and have produced “phantom” sensations of temperature and touch in certain participants.
Booth, N, Davidson, G, Imperia, P, Lee, S, Stuart, B, Thomas, P, Komatsu, K, Yamane, R, Prescott, SW, Maynard-Casely, HE, Nelson, A & Rule, KC 2017, 'Three impossible things before lunch – the task of a sample environment specialist', Journal of Neutron Research, vol. 19, no. 1-2, pp. 49-56.
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© 2017 - IOS Press and the authors. All rights reserved. In the course of their day, sample environment professionals can be confronted by numerous technical challenges applicable to a range of scientific questions. This paper presents three successful outcomes from user-posed sample environment challenges for in situ neutron scattering experiments undertaken at the Australian Centre for Neutron Scattering (formerly the Bragg Institute). The sample environments presented here have nothing in common other than their novelty. They may not be the best solution but have been constrained by time, resources and ability. The questions the users posed were: Can we mount a cylinder in cylinder (CIC) rheometer, more regularly used on a small angle scattering instrument, on a diffraction instrument and obtain usable data? Can we supply high-voltage (up to 10 kV) across a sample within the Paris-Edinburgh press while mounted on a powder diffraction instrument? And finally can a Lakeshore 340 and an in-house built liquid conductivity cell do the job of a commercial liquid conductivity meter? This paper presents the engineering and equipment solutions that were used to answer these questions, and in each case the scientific users left with useful, intriguing and, hopefully, publishable data.
Bower, M, Wood, L, Lai, J, Howe, C, Lister, R, Mason, R, Highfield, K & Veal, J 2017, 'Improving the Computational Thinking Pedagogical Capabilities of School Teachers', Australian Journal of Teacher Education, vol. 42, no. 3, pp. 53-72.
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The idea of computational thinking as skills and universal competence which every child should possess emerged last decade and has been gaining traction ever since. This raises a number of questions, including how to integrate computational thinking into the curriculum, whether teachers have computational thinking pedagogical capabilities to teach children, and the important professional development and training areas for teachers. The aim of this paper is to address the strategic issues by illustrating a series of computational thinking workshops for Foundation to Year 8 teachers held at an Australian university. Data indicated that teachers' computational thinking understanding, pedagogical capabilities, technological know-how and confidence can be improved in a relatively short period of time through targeted professional learning.
Bożejko, W, Chaczko, Z, Uchroński, M & Wodecki, M 2017, 'Parallel patterns determination in solving cyclic flow shop problem with setups', Archives of Control Sciences, vol. 27, no. 2, pp. 183-195.
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AbstractThe subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP). We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.
Braun, G, Jain, R, Lee, T & Pokutta, S 2017, 'Information-theoretic approximations of the nonnegative rank', computational complexity, vol. 26, no. 1, pp. 147-197.
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Broekhuijsen, M, van den Hoven, E & Markopoulos, P 2017, 'From PhotoWork to PhotoUse: exploring personal digital photo activities', Behaviour & Information Technology, vol. 36, no. 7, pp. 754-767.
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Broom, M, Gardner, A, Kecskes, Z & Kildea, S 2017, 'Transition from an open‐plan to a two‐cot neonatal intensive care unit: a participatory action research approach', Journal of Clinical Nursing, vol. 26, no. 13-14, pp. 1939-1948.
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Aims and objectivesTo facilitate staff transition from an open‐plan to a two‐cot neonatal intensive care unit design.BackgroundIn 2012, an Australian regional neonatal intensive care unit transitioned from an open‐plan to a two‐cot neonatal intensive care unit design. Research has reported single‐ and small‐room neonatal intensive care unit design may negatively impact on the distances nurses walk, reducing the time they spend providing direct neonatal care. Studies have also reported nurses feel isolated and need additional support and education in such neonatal intensive care units. Staff highlighted their concerns regarding the impact of the new design on workflow and clinical practice.DesignA participatory action research approach.MethodsA participatory action group titled the Change and Networking Group collaborated with staff over a four‐year period (2009–2013) to facilitate the transition. The Change and Networking Group used a collaborative, cyclical process of planning, gathering data, taking action and reviewing the results to plan the next action. Data sources included meeting and workshop minutes, newsletters, feedback boards, subgroup reports and a staff satisfaction survey.ResultsThe study findings include a description of (1) how the participatory action research cycles were used by the Change and Networking Group: providing examples of projects and strategies undertaken; and (2) evaluations of participatory action research methodology and Group by neonatal intensive care unit staff and Change and Networking members.ConclusionThis study has described the benefits of using participatory a...
Burton, GJ, Pineda, JA, Sheng, D, Airey, DW, Zhang, F, Rawat, A, Al-Badran, YM & Schanz, T 2017, 'Exploring one-dimensional compression of compacted clay under constant degree of saturation paths', Géotechnique, vol. 67, no. 1, pp. 86-90.
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Cagno, E, Trianni, A, Spallina, G & Marchesani, F 2017, 'Drivers for energy efficiency and their effect on barriers: empirical evidence from Italian manufacturing enterprises', Energy Efficiency, vol. 10, no. 4, pp. 855-869.
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© 2017, Springer Science+Business Media Dordrecht. Industrial activities are responsible for a significant share of both global delivered energy demand and CO2 emissions. Hence, a widespread adoption of energy-efficient technologies and practices represents a crucial means for sustainable production. Adopting a novel framework of drivers for energy efficiency describing the effect of drivers on barriers in the decision-making process steps and able to account for the nature of drivers and the stakeholders responsible for their promotion, we have performed an exploratory investigation into 61 manufacturing small- and medium-sized enterprises in Northern Italy. Our findings have highlighted the importance of information and economic drivers, showing the need for enterprises to be supported not only by public institutions but also by external stakeholders involved in the supply of energy-efficient technologies and practices such as industrial associations and groupings, as well as service and technology suppliers. Moreover, our study has highlighted an almost equal relevance of both internal and external drivers. According to our findings, the increase of awareness—generating the interest to energy issues and stimulated both by external and internal stakeholders—as well as financial issues have emerged as the most critical in the decision-making process to adopt an energy-efficient measure. A preliminary comprehension of the mechanisms relating drivers to barriers in the decision-making process brought additional value to the study, highlighting the most effective and specific means to overcome the existing barriers. We have also explored the effect of several firm characteristics, such as firm size and energy intensity offering suggestions for industrial decision-makers as well as policy-makers.
Cai, Q, Turner, BD, Sheng, D & Sloan, S 2017, 'Impact of Barium and Cadmium on Defluoridation by Calcite: Batch Reactor and Column Tests', Environmental Engineering Science, vol. 34, no. 11, pp. 792-804.
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Cai, Y, Chen, Q, Zhou, Y, Nimbalkar, S & Yu, J 2017, 'Estimation of Passive Earth Pressure against Rigid Retaining Wall Considering Arching Effect in Cohesive-Frictional Backfill under Translation Mode', International Journal of Geomechanics, vol. 17, no. 4, pp. 04016093-04016093.
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n this study, a novel analytical approach is proposed to calculate the passive earth pressure against a rigid retaining wall subjected to the translation mode. Effects of arching in cohesive backfill soils as well as friction mobilized along the wall–soil interface are considered. Analytical expressions of the earth pressure, passive resistance, and its height of application on the backface of the retaining wall were derived based on static equilibrium of forces under passive conditions acting on the failure wedge. A parametric study was undertaken to assess effects of internal friction angle of backfill, wall–soil interface friction angle, surcharge pressure, cohesion, unit weight, and inclination angle of the slip surface on the active earth pressure as well as on the slip-surface angle. The results of the proposed method were then verified against the existing test data as well as the predictions by Coulomb theory and Rankine theory. The results show that the proposed method yields satisfactory results
Cai, Y, Zhang, Y, Ding, C & Qian, Z 2017, 'A Wideband Multilayer Substrate Integrated Waveguide Cavity-Backed Slot Antenna Array', IEEE Transactions on Antennas and Propagation, vol. 65, no. 7, pp. 3465-3473.
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© 2017 IEEE. In this paper, a wideband 2 × 2 multilayer substrate integrated waveguide (SIW)-based cavity-backed slot array is proposed. The array element is constructed by stacking five layers of SIW cavity-backed slots and has a wide impedance bandwidth from 18 to 30 GHz. Two different feed networks based on probe coupling and slot coupling are introduced to maintain the wideband characteristic of the proposed element when employed in an array. Two 2 × 2 arrays fed by the proposed feed networks are designed, fabricated, and tested. The measured results show that both the arrays employing probe coupling and slot coupling feed networks have a wide impedance bandwidth over 30%. Within the obtained operation bands, good radiation performance is achieved. Moreover, advantages and disadvantages of the proposed two feed networks are discussed.
Callingham, JR, Ekers, RD, Gaensler, BM, Line, JLB, Hurley-Walker, N, Sadler, EM, Tingay, SJ, Hancock, PJ, Bell, ME, Dwarakanath, KS, For, B-Q, Franzen, TMO, Hindson, L, Johnston-Hollitt, M, Kapińska, AD, Lenc, E, McKinley, B, Morgan, J, Offringa, AR, Procopio, P, Staveley-Smith, L, Wayth, RB, Wu, C & Zheng, Q 2017, 'Extragalactic Peaked-spectrum Radio Sources at Low Frequencies', The Astrophysical Journal, vol. 836, no. 2, pp. 174-174.
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Abstract We present a sample of 1483 sources that display spectral peaks between 72 MHz and 1.4 GHz, selected from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. The GLEAM survey is the widest fractional bandwidth all-sky survey to date, ideal for identifying peaked-spectrum sources at low radio frequencies. Our peaked-spectrum sources are the low-frequency analogs of gigahertz-peaked spectrum (GPS) and compact-steep spectrum (CSS) sources, which have been hypothesized to be the precursors to massive radio galaxies. Our sample more than doubles the number of known peaked-spectrum candidates, and 95% of our sample have a newly characterized spectral peak. We highlight that some GPS sources peaking above 5 GHz have had multiple epochs of nuclear activity, and we demonstrate the possibility of identifying high-redshift (z > 2) galaxies via steep optically thin spectral indices and low observed peak frequencies. The distribution of the optically thick spectral indices of our sample is consistent with past GPS/CSS samples but with a large dispersion, suggesting that the spectral peak is a product of an inhomogeneous environment that is individualistic. We find no dependence of observed peak frequency with redshift, consistent with the peaked-spectrum sample comprising both local CSS sources and high-redshift GPS sources. The 5 GHz luminosity distribution lacks the brightest GPS and CSS sources of previous samples, implying that a convolution of source evolution and redshift influences the type of peaked-spectrum sources identified below 1 GHz. Finally, we discuss sources with optically thick spectral indices that exceed the synchrotron self-absorption limit.
CALVO, RA, MILNE, DN, HUSSAIN, MS & CHRISTENSEN, H 2017, 'Natural language processing in mental health applications using non-clinical texts', Natural Language Engineering, vol. 23, no. 5, pp. 649-685.
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AbstractNatural language processing (NLP) techniques can be used to make inferences about peoples’ mental states from what they write on Facebook, Twitter and other social media. These inferences can then be used to create online pathways to direct people to health information and assistance and also to generate personalized interventions. Regrettably, the computational methods used to collect, process and utilize online writing data, as well as the evaluations of these techniques, are still dispersed in the literature. This paper provides a taxonomy of data sources and techniques that have been used for mental health support and intervention. Specifically, we review how social media and other data sources have been used to detect emotions and identify people who may be in need of psychological assistance; the computational techniques used in labeling and diagnosis; and finally, we discuss ways to generate and personalize mental health interventions. The overarching aim of this scoping review is to highlight areas of research where NLP has been applied in the mental health literature and to help develop a common language that draws together the fields of mental health, human-computer interaction and NLP.
Cancino, C, Merigo, JM, Coronado, F, Dessouky, Y & Dessouky, M 2017, 'Forty years of computers and industrial engineering: A bibliometric analysis', Proceedings of International Conference on Computers and Industrial Engineering, CIE, vol. 0, pp. 614-629.
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Computers & Industrial Engineering is a leading international journal in the field of industrial engineering that published its first issue in 1976. In 2016, the journal has celebrated the 40th anniversary. Motivated by this event, the aim of this study is to develop a bibliometric overview of the publications of the journal between 1976 and 2015. The objective is to identify the leading trends that are occurring in the journal in terms of productivity and influence of topics, authors, universities and countries. For doing so, the work uses the Web of Science Core Collection database to analyse the bibliometric data. The results show the strong position of the USA in the journal although China and other Asian countries are becoming very significant.
Cancino, C, Merigó, JM, Coronado, F, Dessouky, Y & Dessouky, M 2017, 'Forty years of Computers & Industrial Engineering: A bibliometric analysis', Computers & Industrial Engineering, vol. 113, pp. 614-629.
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Computers & Industrial Engineering is a leading international journal in the field of industrial engineering that published its first issue in 1976. In 2016, the journal has celebrated the 40th anniversary. Motivated by this event, the aim of this study is to develop a bibliometric overview of the publications of the journal between 1976 and 2015. The objective is to identify the leading trends that are occurring in the journal in terms of productivity and influence of topics, authors, universities and countries. For doing so, the work uses the Web of Science Core Collection database to analyse the bibliometric data. The results show the strong position of the USA in the journal although China and other Asian countries are becoming very significant.
Cancino, CA, Merigo, JM & Coronado, FC 2017, 'Big Names in Innovation Research:A Bibliometric Overview', Current Science, vol. 113, no. 08, pp. 1507-1507.
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Over the last few years an increasing number of scientific studies related to innovation research has been carried out. The present study analyses innovation research developed between 1989 and 2013. It uses the Web of Science database and provides several author-level bibliometric indicators including the total number of publications and citations, and the h-index. The results indicate that the most influential professors over the last 25 years, according to their highest h-index, are David Audretsch, Michael Hitt, Shaker Zahra, Rajshree Agarwal, Eric Von Hippel, David Teece, Will Mitchell and Robert Cooper. Among these authors, it is possible to demonstrate that they are not necessarily the most productive authors, with the highest number of publications; however, they are the most influential, with the highest number of citations. The incorporation of a larger number of journals to the Web of Science has granted different authors access to publish their work on innovation research.
Cancino, CA, Merigó, JM & Coronado, FC 2017, 'A bibliometric analysis of leading universities in innovation research', Journal of Innovation & Knowledge, vol. 2, no. 3, pp. 106-124.
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© 2017 Journal of Innovation & Knowledge The number of innovation studies with a management perspective has grown considerably over the last 25 years. This study identified the universities that are most productive and influential in innovation research. The leading innovation research journals were also studied individually to identify the most productive universities for each journal. Data from the Web of Science were analyzed. Studies that were published between 1989 and 2013 were filtered first by the keyword “innovation” and second by 18 management-related research areas. The results indicate that US universities are the most productive and influential because they account for the most publications with a high number of citations and high h-index. Following advances in the productivity of numerous European journals, however, universities from the UK and the Netherlands are the most involved in publishing in journals that specialize in innovation research.
Cao, Y, Wen, S & Huang, T 2017, 'New Criteria on Exponential Lag Synchronization of Switched Neural Networks with Time-Varying Delays', Neural Processing Letters, vol. 46, no. 2, pp. 451-466.
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This paper addresses the problem of global exponential lag synchronization of switched neural networks with time-varying delays and general activation functions. Based on the Lyapunov–Krasovskii functional method and free weighting matrix technique, delay-dependent criteria for the global exponential lag synchronization of switched neural networks are derived in form of linear matrix inequalities. A numerical example is utilized to illustrate the characteristics of the results.
Cao, Z, Liu, X, Xu, J, Zhang, J, Yang, Y, Zhou, J, Xu, X & Lowry, GV 2017, 'Removal of Antibiotic Florfenicol by Sulfide-Modified Nanoscale Zero-Valent Iron', Environmental Science & Technology, vol. 51, no. 19, pp. 11269-11277.
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Florfenicol (FF, C12H14Cl2FNO4S), an emerging halogenated organic contaminant of concern was effectively degraded in water by sulfidized nanoscale zerovalent iron (S-nZVI). Sulfidized nZVI (62.5 m2 g-1) that was prepared using a one-step method resulted in small Fe0/Fe-sulfide particles that were more stable against aggregation than unsulfidized nZVI (10.2 m2 g-1). No obvious removal of FF was observed by unsulfidized nZVI. S-nZVI degraded FF, having a surface area normalized reaction rate constant of 3.1 × 10-4 L m-2 min-1. The effects of the S/Fe molar ratio, initial FF concentration, initial pH, temperature, and water composition on the removal of FF by S-nZVI, and on the formation of reaction products, were systematically investigated. Both dechlorination and defluorination were observed, resulting in four degradation products (C12H15ClFNO4S, C12H16FNO4S, C12H17NO4S, and C12H17NO5S). High removal efficiencies of FF by S-nZVI were achieved in groundwater, river water, seawater, and wastewater. The reactivity of S-nZVI was relatively unaffected by the presence of both dissolved ions and organic matter in the waters tested.
Carmichael, MG, Liu, D & Waldron, KJ 2017, 'A framework for singularity-robust manipulator control during physical human-robot interaction', The International Journal of Robotics Research, vol. 36, no. 5-7, pp. 861-876.
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Collaborative robot manipulators are being used to assist human workers performing physically intensive tasks. The finite reach of the manipulator often results in the robot being operated in proximity to kinematic singularity, negatively affecting the stability and performance of operation. Methods of controlling manipulators in the proximity of singularities and mitigating their effects on performance have been widely researched. However, little attention has been given to developing suitable methods for handling singularities specifically for applications where the manipulator physically interacts with a human operator. In these applications additional factors such as human comfort and interaction experience need to be considered. This work presents a framework for handling robotic singularities developed with the human operator in mind. Singularity robustness is achieved using a novel approach to dampen motion of the manipulator along singular directions. An exponential scaling shapes the damping to create a smooth behavior beneficial for physical human–robot interaction. The damping is applied asymmetrically depending on if the robot is heading towards or away from singular configurations, improving the interaction experience for the human operator. Additionally, bounded virtual forces are used to subtly guide the operator away from singular configurations. The proposed framework is validated in simulation and tested on an industrial manipulator.
Cetindamar, D & Ozkazanc‐Pan, B 2017, 'Assessing mission drift at venture capital impact investors', Business Ethics: A European Review, vol. 26, no. 3, pp. 257-270.
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AbstractIn this article, we consider a recent trend whereby private equity available from venture capital (VC) firms is being deployed toward mission‐driven initiatives in the form of impact investing. Acting as hybrid organizations, these impact investors aim to achieve financial results while also targeting companies and funds to achieve social impact. However, potential mission drift in these VCs, which we define as a decoupling between the investments made (means) and intended aims (ends), might become detrimental to the simultaneous financial and social goals of such firms. Based on a content analysis of mission statements, we assess mission drift and the hybridization level of VC impact investors by examining their missions (ends/goals) and their investment practices (means) through the criteria of social and financial logic. After examining eight impact‐oriented VC investors and their investments in 164 companies, we find mission drift manifest as a disparity between the means and ends in half of the VC impact investors in our sample. We discuss these findings and make suggestions for further studies.
Cetindamar, D & Rickne, A 2017, 'Using the functional analysis to understand the emergence of biomaterials within an existing biotechnology system: observations from a case study in Turkey.', Technol. Anal. Strateg. Manag., vol. 29, no. 3, pp. 313-324.
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The paper applies a functional approach to the analysis of an emerging technology within an innovation system (IS) in a developing country. By doing so, the paper identifies the advantages and drawbacks of the approach through a dynamic analysis and highlights the life cycle of an IS within which a new technology is emerging. This is done empirically by analysing the emergence of biosimilars within the infant Turkish biotechnology system mainly from the perspective of firms. Our analysis of the Turkish case illustrates how the tool of functional approach could be valuable in understanding the dynamics of a technology in a developing country context. Policy suggestions and implications of the study are presented as concluding remarks.
Chai, R, Ling, SH, San, PP, Naik, GR, Nguyen, TN, Tran, Y, Craig, A & Nguyen, HT 2017, 'Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks', Frontiers in Neuroscience, vol. 11, no. 103, pp. 1-14.
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This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN) and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6% and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3% and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8%, 9.5% and 2.5% over ANN, BNN and DBN classifiers respectively.
Chai, R, Naik, GR, Ling, SH & Nguyen, HT 2017, 'Hybrid brain–computer interface for biomedical cyber-physical system application using wireless embedded EEG systems', BioMedical Engineering OnLine, vol. 16, no. 1, pp. 1-23.
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© 2017 The Author(s). Background: One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. Methods: This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Results: Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.
Chai, R, Naik, GR, Nguyen, TN, Ling, SH, Tran, Y, Craig, A & Nguyen, HT 2017, 'Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System', IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 3, pp. 715-724.
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This paper presents a two-class electroencephalography (EEG)-based classification for classifying of driver fatigue (fatigue state vs. alert state) from 43 healthy participants. The system uses independent component by entropy rate bound minimization analysis (ERBM-ICA) for the source separation, autoregressive (AR) modeling for the features extraction and Bayesian neural network for the classification algorithm. The classification results demonstrate a sensitivity of 89.7%, a specificity of 86.8% and an accuracy of 88.2%. The combination of ERBM-ICA (source separator), AR (feature extractor) and Bayesian neural network (classifier) provides the best outcome with a p-value < 0.05 with the highest value of area under the receiver operating curve (AUC-ROC=0.93) against other methods such as power spectral density (PSD) as feature extractor (AUC-ROC=0.81). The results of this study suggest the method could be utilized effectively for a countermeasure device for driver fatigue identification and other adverse event applications.
Chandrakanthan, V, Kang, YC, Knezevic, K, Qiao, Q, Oliver, RA, Unnikrishnan, A, Beck, D, Lee, B, Brownlee, C, Power, C & Pimanda, JE 2017, 'Genetic Fate Mapping of Mesenchymal Stem-Like Cells in the Aorta-Gonad Mesonephros (AGM) and Their Contribution to Definitive Hematopoiesis', Mechanisms of Development, vol. 145, pp. S55-S56.
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Chang, L, Li, W, Qin, L, Zhang, W & Yang, S 2017, 'pSCAN: Fast and Exact Structural Graph Clustering.', IEEE Trans. Knowl. Data Eng., vol. 29, no. 2, pp. 387-401.
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© 2016 IEEE. We study the problem of structural graph clustering, a fundamental problem in managing and analyzing graph data. Given an undirected unweighted graph, structural graph clustering is to assign vertices to clusters, and to identify the sets of hub vertices and outlier vertices as well, such that vertices in the same cluster are densely connected to each other while vertices in different clusters are loosely connected. In this paper, we develop a new two-step paradigm for scalable structural graph clustering based on our three observations. Then, we present a pSCAN approach, within the paradigm, aiming to reduce the number of structural similarity computations, and propose optimization techniques to speed up checking whether two vertices are structure-similar. pSCAN outputs exactly the same clusters as the existing approaches SCAN and SCAN++, and we prove that pSCAN is worst-case optimal. Moreover, we propose efficient techniques for updating the clusters when the input graph dynamically changes, and we also extend our techniques to other similarity measures, e.g., Jaccard similarity. Performance studies on large real and synthetic graphs demonstrate the efficiency of our new approach and our dynamic cluster maintenance techniques. Noticeably, for the twitter graph with 1 billion edges, our approach takes 25 minutes while the state-of-the-art approach cannot finish even after 24 hours.
Chang, X, Ma, Z, Yang, Y, Zeng, Z & Hauptmann, AG 2017, 'Bi-Level Semantic Representation Analysis for Multimedia Event Detection', IEEE Transactions on Cybernetics, vol. 47, no. 5, pp. 1180-1197.
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© 2013 IEEE. Multimedia event detection has been one of the major endeavors in video event analysis. A variety of approaches have been proposed recently to tackle this problem. Among others, using semantic representation has been accredited for its promising performance and desirable ability for human-understandable reasoning. To generate semantic representation, we usually utilize several external image/video archives and apply the concept detectors trained on them to the event videos. Due to the intrinsic difference of these archives, the resulted representation is presumable to have different predicting capabilities for a certain event. Notwithstanding, not much work is available for assessing the efficacy of semantic representation from the source-level. On the other hand, it is plausible to perceive that some concepts are noisy for detecting a specific event. Motivated by these two shortcomings, we propose a bi-level semantic representation analyzing method. Regarding source-level, our method learns weights of semantic representation attained from different multimedia archives. Meanwhile, it restrains the negative influence of noisy or irrelevant concepts in the overall concept-level. In addition, we particularly focus on efficient multimedia event detection with few positive examples, which is highly appreciated in the real-world scenario. We perform extensive experiments on the challenging TRECVID MED 2013 and 2014 datasets with encouraging results that validate the efficacy of our proposed approach.
Chang, X, Yu, Y-L, Yang, Y & Xing, EP 2017, 'Semantic Pooling for Complex Event Analysis in Untrimmed Videos', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 8, pp. 1617-1632.
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© 1979-2012 IEEE. Pooling plays an important role in generating a discriminative video representation. In this paper, we propose a new semantic pooling approach for challenging event analysis tasks (e.g., event detection, recognition, and recounting) in long untrimmed Internet videos, especially when only a few shots/segments are relevant to the event of interest while many other shots are irrelevant or even misleading. The commonly adopted pooling strategies aggregate the shots indifferently in one way or another, resulting in a great loss of information. Instead, in this work we first define a novel notion of semantic saliency that assesses the relevance of each shot with the event of interest. We then prioritize the shots according to their saliency scores since shots that are semantically more salient are expected to contribute more to the final event analysis. Next, we propose a new isotonic regularizer that is able to exploit the constructed semantic ordering information. The resulting nearly-isotonic support vector machine classifier exhibits higher discriminative power in event analysis tasks. Computationally, we develop an efficient implementation using the proximal gradient algorithm, and we prove new and closed-form proximal steps. We conduct extensive experiments on three real-world video datasets and achieve promising improvements.
Chang, Y-S, Nie, F, Li, Z, Chang, X & Huang, H 2017, 'Refined Spectral Clustering via Embedded Label Propagation', Neural Computation, vol. 29, no. 12, pp. 3381-3396.
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Spectral clustering is a key research topic in the field of machine learning and data mining. Most of the existing spectral clustering algorithms are built on gaussian Laplacian matrices, which is sensitive to parameters. We propose a novel parameter-free distance-consistent locally linear embedding. The proposed distance-consistent LLE can promise that edges between closer data points are heavier. We also propose a novel improved spectral clustering via embedded label propagation. Our algorithm is built on two advancements of the state of the art. First is label propagation, which propagates a node's labels to neighboring nodes according to their proximity. We perform standard spectral clustering on original data and assign each cluster with [Formula: see text]-nearest data points and then we propagate labels through dense unlabeled data regions. Second is manifold learning, which has been widely used for its capacity to leverage the manifold structure of data points. Extensive experiments on various data sets validate the superiority of the proposed algorithm compared to state-of-the-art spectral algorithms.
Chapman, RJ, Karim, A, Huang, Z, Flammia, ST, Tomamichel, M & Peruzzo, A 2017, 'Beating the Classical Limits of Information Transmission using a Quantum Decoder', Phys. Rev. A, vol. 97, no. 1, p. 012315.
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Encoding schemes and error-correcting codes are widely used in informationtechnology to improve the reliability of data transmission over real-worldcommunication channels. Quantum information protocols can further enhance theperformance in data transmission by encoding a message in quantum states,however, most proposals to date have focused on the regime of a large number ofuses of the noisy channel, which is unfeasible with current quantum technology.We experimentally demonstrate quantum enhanced communication over an amplitudedamping noisy channel with only two uses of the channel per bit and a singleentangling gate at the decoder. By simulating the channel using a photonicinterferometric setup, we experimentally increase the reliability oftransmitting a data bit by greater than 20% for a certain damping range overclassically sending the message twice. We show how our methodology can beextended to larger systems by simulating the transmission of a single bit withup to eight uses of the channel and a two-bit message with three uses of thechannel, predicting a quantum enhancement in all cases.
Chaudhuri, BB & Adak, C 2017, 'An approach for detecting and cleaning of struck-out handwritten text', Pattern Recognition, vol. 61, pp. 282-294.
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This paper deals with the identification and processing of struck-out texts in unconstrained offline handwritten document images. If run on the OCR engine, such texts will produce nonsense character-string outputs. Here we present a combined (a) pattern classification and (b) graph-based method for identifying such texts. In case of (a), a feature-based two-class (normal vs. struck-out text) SVM classifier is used to detect moderate-sized struck-out components. In case of (b), skeleton of the text component is considered as a graph and the strike-out stroke is identified using a constrained shortest path algorithm. To identify zigzag or wavy struck-outs, all paths are found and some properties of zigzag and wavy line are utilized. Some other types of strike-out stroke are also detected by modifying the above method. The large sized multi-word and multi-line struck-outs are segmented into smaller components and treated as above. The detected struck-out texts can then be blocked from entering the OCR engine. In another kind of application involving historical documents, page images along with their annotated ground-truth are to be generated. In this case the strike-out strokes can be deleted from the words and then fed to the OCR engine. For this purpose an inpainting-based cleaning approach is employed. We worked on 500 pages of documents and obtained an overall F-Measure of 91.56% (91.06%) in English (Bengali) script for struck-out text detection. Also, for strike-out stroke identification and deletion, the F-Measures obtained were 89.65% (89.31%) and 91.16% (89.29%), respectively.
Chekli, L, Corjon, E, Tabatabai, SAA, Naidu, G, Tamburic, B, Park, SH & Shon, HK 2017, 'Performance of titanium salts compared to conventional FeCl3 for the removal of algal organic matter (AOM) in synthetic seawater: Coagulation performance, organic fraction removal and floc characteristics', Journal of Environmental Management, vol. 201, pp. 28-36.
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© 2017 Elsevier Ltd During algal bloom periods, operation of seawater reverse osmosis (SWRO) pretreatment processes (e.g. ultrafiltration (UF)) has been hindered due to the high concentration of algal cells and algal organic matter (AOM). The present study evaluated for the first time the performance of titanium salts (i.e. titanium tetrachloride (TiCl4) and polytitanium tetrachloride (PTC)) for the removal of AOM in seawater and results were compared with the conventional FeCl3 coagulant. Previous studies already demonstrated that titanium salts not only provide a cost-effective alternative to conventional coagulants by producing a valuable by-product but also minimise the environmental impact of sludge production. Results from this study showed that both TiCl4 and PTC achieved better performance than FeCl3 in terms of turbidity, UV254 and dissolved organic carbon (DOC) removal at similar coagulant dose. Liquid chromatography – organic carbon detection (LC-OCD) was used to determine the removal of AOM compounds based on their molecular weight (MW). This investigation revealed that both humic substances and low MW organics were preferentially removed (i.e. up to 93% removal) while all three coagulants showed poorer performance for the removal of high MW biopolymers (i.e. less than 50% removal). The detailed characterization of flocs indicated that both titanium coagulants can grow faster, reach larger size and present a more compact structure, which is highly advantageous for the design of smaller and more compact mixing and sedimentation tanks. Both titanium coagulants also presented a higher ability to withstand shear force, which was related to the higher amount of DOC adsorbed with the aggregated flocs. Finally, TiCl4 had a better recovery after breakage suggesting that charge neutralization may be the dominant mechanism for this coagulant, while the lower recovery of both PTC and FeCl3 indicated that sweep flocculation is also a contributing mechan...
Chekli, L, Kim, JE, El Saliby, I, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Kyong Shon, H 2017, 'Fertilizer drawn forward osmosis process for sustainable water reuse to grow hydroponic lettuce using commercial nutrient solution', Separation and Purification Technology, vol. 181, pp. 18-28.
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© 2017 Elsevier B.V. This study investigated the sustainable reuse of wastewater using fertilizer drawn forward osmosis (FDFO) process through osmotic dilution of commercial nutrient solution for hydroponics, a widely used technique for growing plants without soil. Results from the bench-scale experiments showed that the commercial hydroponic nutrient solution (i.e. solution containing water and essential nutrients) exhibited similar performance (i.e., water flux and reverse salt flux) to other inorganic draw solutions when treating synthetic wastewater. The use of hydroponic solution is highly advantageous since it provides all the required macro- (i.e., N, P and K) and micronutrients (i.e., Ca, Mg, S, Mn, B, Zn and Mo) in a single balanced solution and can therefore be used directly after dilution without the need to add any elements. After long-term operation (i.e. up to 75% water recovery), different physical cleaning methods were tested and results showed that hydraulic flushing can effectively restore up to 75% of the initial water flux while osmotic backwashing was able to restore the initial water flux by more than 95%; illustrating the low-fouling potential of the FDFO process. Pilot-scale studies demonstrated that the FDFO process is able to produce the required nutrient concentration and final water quality (i.e., pH and conductivity) suitable for hydroponic applications. Coupling FDFO with pressure assisted osmosis (PAO) in the later stages could help in saving operational costs (i.e., energy and membrane replacement costs). Finally, the test application of nutrient solution produced by the pilot FDFO process to hydroponic lettuce showed similar growth pattern as the control without any signs of nutrient deficiency.
Chekli, L, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Shon, HK 2017, 'Evaluation of fertilizer-drawn forward osmosis for sustainable agriculture and water reuse in arid regions', Journal of Environmental Management, vol. 187, pp. 137-145.
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© 2016 Elsevier Ltd The present study focused on the performance of the FDFO process to achieve simultaneous water reuse from wastewater and production of nutrient solution for hydroponic application. Bio-methane potential (BMP) measurements were firstly carried out to determine the effect of osmotic concentration of wastewater achieved in the FDFO process on the anaerobic activity. Results showed that 95% water recovery from the FDFO process is the optimum value for further AnMBR treatment. Nine different fertilizers were then tested based on their FO performance (i.e. water flux, water recovery and reverse salt flux) and final nutrient concentration. From this initial screening, ammonium phosphate monobasic (MAP), ammonium sulfate (SOA) and mono-potassium phosphate were selected for long term experiments to investigate the maximum water recovery achievable. After the experiments, hydraulic membrane cleaning was performed to assess the water flux recovery. SOA showed the highest water recovery rate, up to 76% while KH2PO4 showed the highest water flux recovery, up to 75% and finally MAP showed the lowest final nutrient concentration. However, substantial dilution was still necessary to comply with the standards for fertigation even if the recovery rate was increased.
Chen, C, Guo, W, Ngo, HH, Chang, SW, Duc Nguyen, D, Dan Nguyen, P, Bui, XT & Wu, Y 2017, 'Impact of reactor configurations on the performance of a granular anaerobic membrane bioreactor for municipal wastewater treatment', International Biodeterioration & Biodegradation, vol. 121, pp. 131-138.
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© 2017 Elsevier Ltd This study compared overall performance of an external granular anaerobic membrane bioreactor and a submerged granular anaerobic membrane bioreactor (EG-AnMBR and SG-AnMBR, respectively), to determine which type of G-AnMBRs is more preferred for municipal wastewater treatment. Both systems presented similar COD removal efficiencies (over 91%) and methane yield of 160 mL CH4 (STP) (g COD removed)−1 although volatile fatty acids (VFA) accumulation was found in the SG-AnMBR. Membrane direct incorporation into the SG-AnMBR significantly affected the concentration and properties of microbial products (e.g. soluble microbial products (SMP) and extracellular polymeric substances (EPS)) in the cake layer, mixed liquor and granular sludge, as well as granular sludge size and settleability. The EG-AnMBR demonstrated less SMP and EPS in the mixed liquor and cake layer, which might reduce the cake layer resistance and lower the fouling rate. Liquid chromatography-organic carbon detection (LC-OCD) analysis of foulant revealed that biopolymers along with low molecular weight neutrals and acids and building blocks were responsible for higher fouling propensity in the SG-AnMBR. It is evident that compared to the SG-AnMBR, the EG-AnMBR serves as a better G-AnMBR configuration for municipal wastewater treatment due to less fouling propensity and superior granule quality.
Chen, C, Guo, WS, Ngo, HH, Liu, Y, Du, B, Wei, Q, Wei, D, Nguyen, DD & Chang, SW 2017, 'Evaluation of a sponge assisted-granular anaerobic membrane bioreactor (SG-AnMBR) for municipal wastewater treatment', Renewable Energy, vol. 111, pp. 620-627.
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© 2017 Elsevier Ltd This study compared a conventional granular anaerobic membrane bioreactor (CG-AnMBR) with a sponge assisted-granular anaerobic membrane bioreactor (SG-AnMBR) in terms of treatment performance, granular sludge properties, membrane fouling behaviour and biogas production. The SG-AnMBR showed better organics and nutrient removal, and enhanced methane yield at 156.3 ± 5.8 mL CH4(STP)/g CODremoved. Granular sludge from the SG-AnMBR had superior quality with better settleability, larger particle size, higher EPS content and more granule abundance. The SG-AnMBR also exhibited slower fouling development with 50.7% lower total filtration resistance than those of the CG-AnMBR. Sponge addition effectively affected the concentration and properties of microbial products (e.g. soluble microbial products (SMP) and extracellular polymeric substances (EPS)) in granular sludge, cake layer as well as settling zone mixed liquor, thus alleviating the fouling propensity. The liquid chromatography-organic carbon detection (LC-OCD) analysis suggested that sponge addition reduced the concentrations of biopolymers, low molecular weight neutrals and acids, and building blocks of the foulants. Compared with the SG-AnMBR, GC-MS analysis confirmed the accumulation of volatile fatty acids, particularly acetic acid in the CG-AnMBR. It is evident that the SG-AnMBR could be a promising solution for improving overall G-AnMBR performance and substantially mitigating membrane fouling.
Chen, G, Liu, R, Shon, HK, Wang, Y, Song, J, Li, X-M & He, T 2017, 'Open porous hydrophilic supported thin-film composite forward osmosis membrane via co-casting for treatment of high-salinity wastewater', Desalination, vol. 405, pp. 76-84.
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© 2016 High-performance thin film composite (TFC) forward osmosis (FO) membranes with a low degree of internal concentration polarization (ICP) are critical for concentrating high-salinity wastewaters. This report focuses on the preparation of TFC FO membranes via a sacrificial approach. In order to improve the FO flux, hydrophilicity and morphology of the support membrane were mainly investigated. The hydrophilicity of the polysulfone (PSF) substrate was tuned by blending with sulfonated poly (ether ether ketone) (SPEEK), and the resulting SPEEK blended PSF membrane was denoted as SPSF substrate. The pore structure of the SPSF membrane was tailored by the application of a co-casting technique, which yielded a TFC membrane with a structure parameter (S) of 191 μm. In contrast, the TFC membranes based on the PSF and SPSF substrates through single layer casting showed S values of 527 μm and 361 μm, respectively. These results indicate that the combined hydrophilicity and open pore structure are responsible for the lowered S value. Further application of the hydrophilic substrate based TFC membranes in the treatment of high salinity wastewaters (10 wt%) demonstrated the higher initial water flux (28.3 L/m2·h) with a water recovery rate of 53.2% in comparison to the TFC membrane based on the pristine PSF through the single layer casting. This new method paves a way to generate high-performing FO membranes.
Chen, H, Yue, Y, Jin, W, Zhou, X, Wang, Q, Gao, S-H, Xie, G-J, Du, S, Tu, R, Han, S & Guo, K 2017, 'Enrichment and characteristics of ammonia-oxidizing archaea in wastewater treatment process', Chemical Engineering Journal, vol. 323, pp. 465-472.
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High purity ammonia-oxidizing archaea (AOA) culture containing a single AOA strain was enriched from the filtering materials of biological aerated filter. The concentration of AOA reached 3.27 × 107 copies/mL, while its proportion was 91.40%. The AOA amoA gene sequence belonged to Nitrososphaera cluster. Ammonia concentration significantly influenced the growth of AOA in culture, while total organic carbon (TOC) concentration had no obvious effect. The optimum ammonia concentration, temperature, pH and DO concentration for growth of AOA were 1 mM, 30 °C, 7.5 and 2.65 mg/L, respectively. Under the optimum growth conditions, the AOA abundance and ammonia oxidation rate were 3.53 × 107 copies/mL and 2.54 × 10−10 mg/(copies·d).
Chen, H, Zhang, G, Zhu, D & Lu, J 2017, 'Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014', Technological Forecasting and Social Change, vol. 119, no. June 2017, pp. 39-52.
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© 2017 Elsevier Inc. The study of technological forecasting is an important part of patent analysis. Although fitting models can provide a rough tendency of a technical area, the trend of the detailed content within the area remains hidden. It is also difficult to reveal the trend of specific topics using keyword-based text mining techniques, since it is very hard to track the temporal patterns of a single keyword that generally represents a technological concept. To overcome these limitations, this research proposes a topic-based technological forecasting approach, to uncover the trends of specific topics underlying massive patent claims using topic modelling. A topic annual weight matrix and a sequence of topic-based trend coefficients are generated to quantitatively estimate the developing trends of the discovered topics, and evaluate to what degree various topics have contributed to the patenting activities of the whole area. To demonstrate the effectiveness of the approach, we present a case study using 13,910 utility patents that were published during the years 2000 to 2014, owned by Australian assignees, in the United States Patent and Trademark Office (USPTO). The results indicate that the proposed approach is effective for estimating the temporal patterns and forecast the future trends of the latent topics underlying massive claims. The topic-based knowledge and the corresponding trend analysis provided by the approach can be used to facilitate further technological decisions or opportunity discovery.
Chen, J, Li, C, Ristovski, Z, Milic, A, Gu, Y, Islam, MS, Wang, S, Hao, J, Zhang, H, He, C, Guo, H, Fu, H, Miljevic, B, Morawska, L, Thai, P, LAM, YF, Pereira, G, Ding, A, Huang, X & Dumka, UC 2017, 'A review of biomass burning: Emissions and impacts on air quality, health and climate in China', Science of The Total Environment, vol. 579, pp. 1000-1034.
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Biomass burning (BB) is a significant air pollution source, with global, regional and local impacts on air quality, public health and climate. Worldwide an extensive range of studies has been conducted on almost all the aspects of BB, including its specific types, on quantification of emissions and on assessing its various impacts. China is one of the countries where the significance of BB has been recognized, and a lot of research efforts devoted to investigate it, however, so far no systematic reviews were conducted to synthesize the information which has been emerging. Therefore the aim of this work was to comprehensively review most of the studies published on this topic in China, including literature concerning field measurements, laboratory studies and the impacts of BB indoors and outdoors in China. In addition, this review provides insights into the role of wildfire and anthropogenic BB on air quality and health globally. Further, we attempted to provide a basis for formulation of policies and regulations by policy makers in China.
Chen, J, Li, K, Tang, Z, Bilal, K, Yu, S, Weng, C & Li, K 2017, 'A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment', IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 4, pp. 919-933.
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With the emergence of the big data age, the issue of how to obtain valuable knowledge from a dataset efficiently and accurately has attracted increasingly attention from both academia and industry. This paper presents a Parallel Random Forest (PRF) algorithm for big data on the Apache Spark platform. The PRF algorithm is optimized based on a hybrid approach combining dataparallel and task-parallel optimization. From the perspective of data-parallel optimization, a vertical data-partitioning method is performed to reduce the data communication cost effectively, and a data-multiplexing method is performed is performed to allow the training dataset to be reused and diminish the volume of data. From the perspective of task-parallel optimization, a dual parallel approach is carried out in the training process of RF, and a task Directed Acyclic Graph (DAG) is created according to the parallel training process of PRF and the dependence of the Resilient Distributed Datasets (RDD) objects. Then, different task schedulers are invoked for the tasks in the DAG. Moreover, to improve the algorithm's accuracy for large, high-dimensional, and noisy data, we perform a dimension-reduction approach in the training process and a weighted voting approach in the prediction process prior to parallelization. Extensive experimental results indicate the superiority and notable advantages of the PRF algorithm over the relevant algorithms implemented by Spark MLlib and other studies in terms of the classification accuracy, performance, and scalability. With the expansion of the scale of the random forest model and the Spark cluster, the advantage of the PRF algorithm is more obvious.
Chen, J, Liu, B, Zhou, H, Yu, Q, Gui, L & Shen, X 2017, 'QoS-Driven Efficient Client Association in High-Density Software-Defined WLAN', IEEE Transactions on Vehicular Technology, vol. 66, no. 8, pp. 7372-7383.
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Chen, Q, Lan, C, Chen, B, Wang, L, Li, J & Zhang, C 2017, 'Exploring Consensus RNA Substructural Patterns Using Subgraph Mining', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 14, no. 5, pp. 1134-1146.
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Chen, Q, Wang, Y, Chen, B, Zhang, C, Wang, L & Li, J 2017, 'Using propensity scores to predict the kinases of unannotated phosphopeptides', Knowledge-Based Systems, vol. 135, pp. 60-76.
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© 2017 Protein phosphorylation is the process of binding a protein kinase to a specific site in a protein substrate for post-translational modification. Thousands of distinct phosphorylation sites have been identified, but most of them are not annotated with any kinase information. This work proposes a novel kinase-subgrouping propensity method (kiSP) to predict the binding kinases for phosphopeptides. Existing methods do not distinguish the residue conservation properties of the kinase family subgroups for annotation. Our method exploits maximum entropy variance to prune non-conserved sites from the subset of phosphopeptides that bind to the same kinase family. We also use maximal mutual information to estimate an appropriate upstream-downstream window size for this subset. A propensity score for every kinase family is calculated from its positive and negative data, which indicates its effectiveness as a site for each test phosphopeptide. Experimental results demonstrate that our method outperforms current algorithms in specificity and sensitivity under cross-validation. kiSP is also demonstrated to correctly predict kinase families for phosphopeptides with unknown kinase information.
Chen, S, Han, E, Xu, H, Zhu, L, Liu, B, Zhang, G & Lu, M 2017, 'P2-type Na0.67Ni0.33−x Cu x Mn0.67O2 as new high-voltage cathode materials for sodium-ion batteries', Ionics, vol. 23, no. 11, pp. 3057-3066.
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Chen, SJ, Li, WG, Ruan, CK, Sagoe-Crentsil, K & Duan, WH 2017, 'Pore shape analysis using centrifuge driven metal intrusion: Indication on porosimetry equations, hydration and packing', Construction and Building Materials, vol. 154, pp. 95-104.
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© 2017 Porosity is an intrinsic property of many cementitious materials. This study uses a new centrifugation-based low-melting-point metal intrusion technique to characterize and analyze the shape of pores in cementitious materials. Low energy electrons with ultra-long beam dwell time are used to obtain nano meter level resolution of the pore shape. Three descriptors, namely circularity, solidity, and aspect ratio, are proposed to represent the area-perimeter relationship, hydration and packing and 3D shape of the pores, respectively. Circularity is found to hold a consistent power correlation with pore size. Based on this correlation, the Washburn's equation is modified to correct the biased prediction of pore size using mercury intrusion porosimetry (MIP). Solidity, is found to decrease with increased pore size, denser packing of cement particles and more hydration products. Aspect ratio of the observed pores is found to average at about 2 representing an oblate ellipsoid shape of pore in 3D space.
Chen, S-L, Qin, P-Y, Ding, C & Guo, YJ 2017, 'Cavity-Backed Proximity-Coupled Reconfigurable Microstrip Antenna With Agile Polarizations and Steerable Beams', IEEE Transactions on Antennas and Propagation, vol. 65, no. 10, pp. 5553-5558.
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© 1963-2012 IEEE. A major challenge for a combined reconfigurable antenna is to realize both polarization switching and beam steering independently in a compact antenna structure. A cavity-backed proximity-coupled reconfigurable microstrip antenna proposed in this communication provides an efficient solution. Beam lead p-i-n diodes DSM8100-000 are employed as switching elements to achieve reconfiguration. Three different linear polarizations (0°, 45°, and 90°) are realized by switching the diodes on a proximity-coupled feed network. For each polarization state, the main beam can be steered to three directions by using a reconfigurable parasitic-element network. The parasitic-element network is printed on the same plane of the radiating patch, thereby making the antenna compact. This antenna has nine different working modes, and for all the working modes, the reflection coefficients are below -10 dB with the measured realized gains ranging from 7.2 to 8.1 dBi.
Chen, S-L, Qin, P-Y, Guo, YJ, Liu, Y & You, P 2017, 'Generalized 2-D Numerical Pattern Synthesis Algorithm for Low Cross Polarization and Low Sidelobe Synthesis', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 2578-2581.
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© 2017 IEEE. Numerical pattern synthesis (NPS) algorithm based on adaptive array theory is an effective spatial power pattern synthesis method for antenna arrays. In this letter, instead of using the artificial interferences weighted on the total power pattern in the conventional NPS algorithm, a generalized two-dimensional (2-D) NPS algorithm is proposed in which two weighting functions are assigned to control the copolarization and cross-polarization patterns, respectively. The weighting functions are iteratively updated until both the sidelobe and cross-polarization levels reach their prescribed ones. Two numerical examples for synthesizing the patterns of a linearly polarized planar array and a circularly polarized cylindrical array are provided to validate effectiveness and advantages of the proposed generalized 2-D NPS algorithm.
Chen, S-L, Wei, F, Qin, P-Y, Guo, YJ & Chen, X 2017, 'A Multi-linear Polarization Reconfigurable Unidirectional Patch Antenna', IEEE Transactions on Antennas and Propagation, vol. 65, no. 8, pp. 4299-4304.
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© 1963-2012 IEEE. A novel multi-linear polarization (multi-LP) reconfigurable unidirectional circular patch antenna is proposed, which can switch among four LPs at every 45° rotation. The patch antenna is fed in the center and shorting posts are used to excite TM11 mode with LP. By controlling the connections between the four shorting posts and the ground plane using p-i-n diodes, four reconfigurable polarization states at φ =0°, φ =45 , φ =90 , or φ =135 can be realized. The size of this antenna is about 0.57λ × 0.57λ × 0.07λ at 2.45 GHz. It can be easily fabricated and has a simple biasing network. The measured overlapping impedance bandwidth for different polarizations under the condition S 11≤ -10 dB is from 2.33 to 2.50 GHz, which agrees well with the simulated one. Moreover, the antenna maintains stable radiation patterns and the measured realized gains range from 5.3 to 5.9 dBi.
Chen, W, Deng, W & Goldys, EM 2017, 'Light-Triggerable Liposomes for Enhanced Endolysosomal Escape and Gene Silencing in PC12 Cells', Molecular Therapy - Nucleic Acids, vol. 7, pp. 366-377.
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Liposomes are an effective gene and/or drug delivery system, widely used in biomedical applications including gene therapy and chemotherapy. Here, we designed a photo-responsive liposome (lipVP) loaded with a photosensitizer verteporfin (VP). This photosensitizer is clinically approved for photodynamic therapy (PDT). LipVP was employed as a DNA carrier for pituitary adenylyl cyclase-activating polypeptide (PACAP) receptor 1 (PAC1R) gene knockdown in PC12 cells. This has been done by incorporating PAC1R antisense oligonucleotides inside the lipVP cavity. Cells that have taken up the lipVP were exposed to light from a UV light source. As a result of this exposure, reactive oxygen species (ROS) were generated from VP, destabilizing the endolysosomal membranes and enhancing the liposomal release of antisense DNA into the cytoplasm. Endolysosomal escape of DNA was documented at different time points based on quantitative analysis of colocalization between fluorescently labeled DNA and endosomes and lysosomes. The released antisense oligonucleotides were found to silence PAC1R mRNA. The efficiency of this photo-induced gene silencing was demonstrated by a 74% ± 5% decrease in PAC1R fluorescence intensity. Following the light-induced DNA transfer into cells, cell differentiation with exposure to two kinds of PACAP peptides was observed to determine the cell phenotypic change after PAC1R gene knockdown.
Chen, W, Xie, X, Wang, J, Pradhan, B, Hong, H, Bui, DT, Duan, Z & Ma, J 2017, 'A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility', CATENA, vol. 151, pp. 147-160.
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© 2016 Elsevier B.V. The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and classification and regression tree (CART) models, to map landslide susceptibility. Long County was selected as the study area. First, a landslide inventory map was constructed using history reports, interpretation of aerial photographs, and extensive field surveys. A total of 171 landslide locations were identified in the study area. Twelve landslide-related parameters were considered for landslide susceptibility mapping, including slope angle, slope aspect, plan curvature, profile curvature, altitude, NDVI, land use, distance to faults, distance to roads, distance to rivers, lithology, and rainfall. The 171 landslides were randomly separated into two groups with a 70/30 ratio for training and validation purposes, and different ratios of non-landslides to landslides grid cells were used to obtain the highest classification accuracy. The linear support vector machine algorithm (LSVM) was used to evaluate the predictive capability of the 12 landslide conditioning factors. Second, LMT, RF, and CART models were constructed using training data. Finally, the applied models were validated and compared using receiver operating characteristics (ROC), and predictive accuracy (ACC) methods. Overall, all three models exhibit reasonably good performances; the RF model exhibits the highest predictive capability compared with the LMT and CART models. The RF model, with a success rate of 0.837 and a prediction rate of 0.781, is a promising technique for landslide susceptibility mapping. Therefore, these three models are useful tools for spatial prediction of landslide susceptibility.
Chen, W-H, Hsu, H-J, Kumar, G, Budzianowski, WM & Ong, HC 2017, 'Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis', Bioresource Technology, vol. 246, pp. 12-19.
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Chen, X, Liu, Y, Peng, L & Ni, B-J 2017, 'Perchlorate, nitrate, and sulfate reduction in hydrogen-based membrane biofilm reactor: Model-based evaluation', Chemical Engineering Journal, vol. 316, pp. 82-90.
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© 2017 Elsevier B.V. A biofilm model was developed to evaluate the key mechanisms including microbially-mediated ClO4−, NO3−, and SO42−reduction in the H2-based membrane biofilm reactor (MBfR). Sensitivity analysis indicated that the maximum growth rate of H2-based denitrification (μ1) and maximum growth rate of H2-based SO42−reduction (μ3) could be reliably estimated by fitting the model predictions to the experimental measurements. The model was first calibrated using the experimental data of a single-stage H2-based MBfR fed with different combinations of ClO4−, NO3−, and/or SO42−together with a constant dissolved oxygen (DO) concentration at three operating stages. μ1and μ3were determined at 0.133 h−1and 0.0062 h−1, respectively, with a good level of identifiability. The model and the parameter values were further validated based on the experimental data of a two-stage H2-based MBfR system fed with ClO4−, NO3−, SO42−, and DO simultaneously but at different feeding rates during two running phases. The validated model was then applied to evaluate the quantitative and systematic effects of key operating conditions on the reduction of ClO4−, NO3−, and SO42−as well as the steady-state microbial structure in the biofilm of a single-stage H2-based MBfR. The results showed that i) a higher influent ClO4−concentration led to a higher ClO4−removal efficiency, compensated by a slightly decreasing SO42−removal; ii) the H2loading should be properly managed at certain critical level to maximize the ClO4−and NO3−removal while limiting the growth of sulfate reducing bacteria which would occur in the case of excessive H2supply; and iii) a moderate hydraulic retention time and a relatively thin biofilm were required to maintain high-level removal of ClO4−and NO3−but restrict the SO42−reduction.
Chen, X, Ni, W, Chen, T, Collings, IB, Wang, X & Giannakis, GB 2017, 'Real-Time Energy Trading and Future Planning for Fifth Generation Wireless Communications', IEEE Wireless Communications, vol. 24, no. 4, pp. 24-30.
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© 2017 IEEE. Future 5G cellular networks, equipped with energy harvesting devices, are uniquely positioned to interoperate with smart grid, due to their resemblance in scale and ubiquity. New interoperable functionalities, such as real-time energy trading and future planning, are of particular interest to improve productivity, but extremely challenging due to the physical characteristics of wireless channels and renewable energy sources, as well as time-varying energy prices. Particularly, a priori knowledge on future wireless channels, energy harvesting, and pricing is unavailable in practice. In this scenario, simple but efficient Lyapunov control theory can be applied to stochastically optimize energy trading and planning. Simulations demonstrate that Lyapunov control can approach the offline optimum which is obtained under the ideal assumption of full a priori knowledge, leading to 65 percent reduction of the operational expenditure of 5G on energy over existing alternatives.
Chen, X, Qin, P-Y, Guo, YJ & Fu, G 2017, 'Low-Profile and Wide-Beamwidth Dual-Polarized Distributed Microstrip Antenna', IEEE Access, vol. 5, pp. 2272-2280.
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© 2013 IEEE. A low-profile and wide-beamwidth dual-polarized distributed microstrip antenna is presented in this paper. Four isolated micro patches are proposed as the radiation components and are excited by a compact differential-fed network. The micro patches in two diagonals determine the operating frequency bands of the two polarizations, respectively. By increasing the distances between the micro patches, the beamwidth in E plane can be broadened. Shorting poles between the patches and the ground plane are used to achieve good impedance matching. Compact dual-polarized differential-fed networks are also studied and compared with achieve the best antenna performance. To validate the proposed method, a wide-beamwith dual-polarized distributed microstrip antenna, whose dual polarizations operate at 2 and 2.2 GHz, respectively, is manufactured and measured. The external dimensions of the antenna is 70mm × 10 mm (0.49λ × 0.07λ ). The experimental results agree well with the simulated ones. The 3dB beamwidths in E planes reach 116° and 115°, and the gains are 5.15 and 5.5 dB for two polarizations, respectively. Meanwhile, the cross polarizations are less than -26.2 and -27.8 dB. In addition, the impedance bandwidths of 9.2% and 9.9% for VSWR leq 2 are achieved, and the port isolation is greater than 25.4 dB in the bands.
Chen, Y, Jia, Z, Ai, X, Yang, D & Yu, J 2017, 'A modified two-part wolf pack search algorithm for the multiple traveling salesmen problem', Applied Soft Computing, vol. 61, pp. 714-725.
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This paper proposes a modified two-part wolf pack search (MTWPS) algorithm updated by the two-part individual encoding approach as well as the transposition and extension (TE) operation for the multiple travelling salesmen problem (MTSP). Firstly, the two-part individual encoding approach is introduced into the original WPS algorithm for MTSP, which is named the two-part wolf pack search (TWPS) algorithm, to minimize the size of the problem search space. Secondly, the analysis of the convergence rate performance is presented to illustrate the reasonability of the maximum terminal generation of the novel TWPS algorithm deeply. Then, based on the definition of the global reachability, the TWPS algorithm is modified by the TE operation further, which can greatly enhance the search ability of the TWPS algorithm. Finally, focusing on the objective of minimizing the total travel distance and the longest tour, comparisons of the robustness and the optimality between different algorithms are presented, and experimental results show that the MTWPS algorithm can obtain higher solution quality than the other the ones of the other two methods
Chen, Y, Yue, X, Xu, RYD & Fujita, H 2017, 'Region scalable active contour model with global constraint', Knowledge-Based Systems, vol. 120, pp. 57-73.
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© 2016Existing Active Contour methods suffer from the deficiencies of initialization sensitivity, slow convergence, and being insufficient in the presence of image noise and inhomogeneity. To address these problems, this paper proposes a region scalable active contour model with global constraint (RSGC). The energy function is formulated by incorporating local and global constraints. The local constraint is a region scalable fitting term that draws upon local region information under controllable scales. The global constraint is constructed through estimating the global intensity distribution of image content. Specifically, the global intensity distribution is approximated with a Gaussian Mixture Model (GMM) and estimated by Expectation Maximization (EM) algorithm as a prior. The segmentation process is implemented through optimizing the improved energy function. Comparing with two other representative models, i.e. region-scalable fitting model (RSF) and active contour model without edges (CV), the proposed RSGC model achieves more efficient, stable and precise results on most testing images under the joint actions of local and global constraints.
Chen, Z, You, X, Zhong, B, Li, J & Tao, D 2017, 'Dynamically Modulated Mask Sparse Tracking', IEEE Transactions on Cybernetics, vol. 47, no. 11, pp. 3706-3718.
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© 2013 IEEE. Visual tracking is a critical task in many computer vision applications such as surveillance and robotics. However, although the robustness to local corruptions has been improved, prevailing trackers are still sensitive to large scale corruptions, such as occlusions and illumination variations. In this paper, we propose a novel robust object tracking technique depends on subspace learning-based appearance model. Our contributions are twofold. First, mask templates produced by frame difference are introduced into our template dictionary. Since the mask templates contain abundant structure information of corruptions, the model could encode information about the corruptions on the object more efficiently. Meanwhile, the robustness of the tracker is further enhanced by adopting system dynamic, which considers the moving tendency of the object. Second, we provide the theoretic guarantee that by adapting the modulated template dictionary system, our new sparse model can be solved by the accelerated proximal gradient algorithm as efficient as in traditional sparse tracking methods. Extensive experimental evaluations demonstrate that our method significantly outperforms 21 other cutting-edge algorithms in both speed and tracking accuracy, especially when there are challenges such as pose variation, occlusion, and illumination changes.
Cheng, H, Zhang, J, Wu, Q, An, P & Liu, Z 2017, 'Stereoscopic visual saliency prediction based on stereo contrast and stereo focus', EURASIP Journal on Image and Video Processing, vol. 2017, no. 1.
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© 2017, The Author(s). In this paper, we exploit two characteristics of stereoscopic vision: the pop-out effect and the comfort zone. We propose a visual saliency prediction model for stereoscopic images based on stereo contrast and stereo focus models. The stereo contrast model measures stereo saliency based on the color/depth contrast and the pop-out effect. The stereo focus model describes the degree of focus based on monocular focus and the comfort zone. After obtaining the values of the stereo contrast and stereo focus models in parallel, an enhancement based on clustering is performed on both values. We then apply a multi-scale fusion to form the respective maps of the two models. Last, we use a Bayesian integration scheme to integrate the two maps (the stereo contrast and stereo focus maps) into the stereo saliency map. Experimental results on two eye-tracking databases show that our proposed method outperforms the state-of-the-art saliency models.
Cheng, H-C, Hsieh, M-H & Tomamichel, M 2017, 'Quantum Sphere-Packing Bounds with Polynomial Prefactors', IEEE Transactions on Information Theory, 65(5):2872-2898, May 2019, vol. 65, no. 5, pp. 2872-2898.
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We study lower bounds on the optimal error probability in classical codingover classical-quantum channels at rates below the capacity, commonly termedquantum sphere-packing bounds. Winter and Dalai have derived such bounds forclassical-quantum channels; however, the exponents in their bounds onlycoincide when the channel is classical. In this paper, we show that these twoexponents admit a variational representation and are related by theGolden-Thompson inequality, reaffirming that Dalai's expression is stronger ingeneral classical-quantum channels. Second, we establish a sphere-packing boundfor classical-quantum channels, which significantly improves Dalai's prefactorfrom the order of subexponential to polynomial. Furthermore, the gap betweenthe obtained error exponent for constant composition codes and the best knownclassical random coding exponent vanishes in the order of $o(\log n / n)$,indicating our sphere-packing bound is almost exact in the high rate regime.Finally, for a special class of symmetric classical-quantum channels, we cancompletely characterize its optimal error probability without the constantcomposition code assumption. The main technical contributions are two converseHoeffding bounds for quantum hypothesis testing and the saddle-point propertiesof error exponent functions.
Cheng, L, Chen, Y, Zheng, YY, Zhan, Y, Zhao, H & Zhou, JL 2017, 'Bioaccumulation of sulfadiazine and subsequent enzymatic activities in Chinese mitten crab (Eriocheir sinensis)', Marine Pollution Bulletin, vol. 121, no. 1-2, pp. 176-182.
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The bioaccumulation of sulfadiazine and subsequent enzymatic activities in Chinese mitten crab (Eriocheir sinensis) were studied in microcosms, by exposing to 50, 100, 500 and 1000ng/L of sulfadiazine for 44days. An effective method for extracting sulfadiazine in crab tissues was established by modifying the cleanup method after ultrasound extraction, with improved recoveries of 61.8%, 93.7% and 100.5% in gill, muscle and liver samples. The results showed that sulfadiazine residues were all <3ng/g dry weight in different tissues, and that sulfadiazine bioaccumulation in crab was not dose-dependent. A significantly negative correlation was observed between acetylcholinesterase activity and the residue concentration of sulfadiazine during exposure to 50ng/L and 1000ng/L, and between alkaline phosphatase and sulfadiazine residues in the 100ng/L exposure group in the gill, suggesting that the two enzymes played an important role in the metabolism of sulfadiazine in crab.
Cheng, S, Yu, L, Zhang, D & Ji, J 2017, 'Consensus of multiple Euler-Lagrange systems using one Euler-Lagrange System’s velocity measurements', International Journal of Control, Automation and Systems, vol. 15, no. 1, pp. 450-456.
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© 2016, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg. This brief paper studies the stationary consensus of multiple Euler-Lagrange systems with nonlinear protocols. Two consensus protocols are given to guarantee that positions and velocities of multiple Euler-Lagrange systems reach consensus. Proposed protocols need only the relative position measurements and the velocity measurements of one Euler-Lagrange system. Finally, numerical simulations are given to illustrate the theoretical results.
Cheng, T & Lu, DDC 2017, 'Three-port converters with a flexible power flow for integrating pv and energy storage into a DC bus', Journal of Power Electronics, vol. 17, no. 6, pp. 1433-1444.
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A family of non-isolated DC-DC three-port converters (TPCs) that allows for a more flexible power flow among a renewable energy source, an energy storage device and a current-reversible DC bus is introduced. Most of the reported non-isolated topologies in this area consider only a power consuming load. However, for applications such as hybrid-electric vehicle braking systems and DC microgrids, the load power generating capability should also be considered. The proposed three-port family consists of one unidirectional port and two bi-directional ports. Hence, they are well-suited for photovoltaic (PV)-battery-DC bus systems from the power flow viewpoint. Three-port converters are derived by combining different commonly known power converters in an integrated manner while considering the voltage polarity, voltage levels among the ports and the overall voltage conversion ratio. The derived converter topologies are able to allow for seven different modes of operation among the sources and load. A three-port converter which integrates a boost converter with a buck converter is used as a design example. Extensions of these topologies by combining the soft-switching technique with the proposed design example are also presented. Experiment results are given to verify the proposed three-port converter family and its analysis.
Cheng, X, Jiang, Z, Wei, D, Hao, L, Wu, H, Xia, W, Zhang, X, Luo, S & Jiang, L 2017, 'Effects of surface preparation on tribological behaviour of a ferritic stainless steel in hot rolling', Wear, vol. 376-377, no. PART B, pp. 1804-1813.
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© 2017 Elsevier B.V. Some defects on the surface of carbon steel do not need to be removed before hot rolling because the surface will be vigorously oxidised in a reheating environment. Thus the defects can be minimised by oxidising and then removed by the de-scaling process. The defects on the surface of ferritic stainless steels, however, are not easily removed by oxidation when a high chromium concentration is used. In this paper, a ferritic stainless steel grade 445 was selected as a research material. The effects of different surface features on oxidation and tribological behaviour in the hot rolling process were investigated. Three surface states were prepared, namely, smooth surface, surface with 45° grinding marks and surface with oscillation marks. The samples were put into an electric furnace at 1100 °C for reheating. Hot rolling tests were carried out on a 2-high Hille 100 experimental rolling mill. Rolling forces were measured, and the coefficient of friction was calculated and compared under various rolling parameters. It was found that the original surfac e profiles with grinding marks were still maintained during oxidation. The original oxide scale on the surface with oscillation marks caused the formation of irregular oxide nodules and the spallation of the oxide scale. Surface morphology and the reduction in thickness had a significant impact on the oxide scale integrity and coefficient of friction in the hot rolling process.
Cheng, X, Wei, D, Jiang, Z & Jiang, L 2017, 'Analysis of oxide scale deformation and surface roughness characterisation in hot rolling of stainless steels', International Journal of Surface Science and Engineering, vol. 11, no. 3, pp. 241-241.
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© 2017 Inderscience Enterprises Ltd. Stainless steels are iron-based alloys that contain a minimum of about 12% Cr. They have been classified by microstructure at room temperature. Two stainless steel grades 304 and 410L were studied in this paper. Hot rolling was performed on a Hille 100 experimental rolling mill under various reductions with consideration of the oxide scale thickness controlled by oxidation time. The experimental results show that the deformation behaviour of the oxide scale on the stainless steel 304 is sensitive to its thickness and exhibits higher resistance to be deformed. However, the reduction in thickness plays an important role in the uniformity of the oxide scale deformation for the stainless steel 410L. Friction coefficients were calculated and compared. Simulations results show that the reduction in thickness and initial surface roughness play roles on final surface roughness. Steel substrate surface is rougher than that of the oxide scale at different reductions.
Choi, I, Milne, DN, Glozier, N, Peters, D, Harvey, SB & Calvo, RA 2017, 'Using different Facebook advertisements to recruit men for an online mental health study: Engagement and selection bias', Internet Interventions, vol. 8, pp. 27-34.
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© 2017 A growing number of researchers are using Facebook to recruit for a range of online health, medical, and psychosocial studies. There is limited research on the representativeness of participants recruited from Facebook, and the content is rarely mentioned in the methods, despite some suggestion that the advertisement content affects recruitment success. This study explores the impact of different Facebook advertisement content for the same study on recruitment rate, engagement, and participant characteristics. Five Facebook advertisement sets (“resilience”, “happiness”, “strength”, “mental fitness”, and “mental health”) were used to recruit male participants to an online mental health study which allowed them to find out about their mental health and wellbeing through completing six measures. The Facebook advertisements recruited 372 men to the study over a one month period. The cost per participant from the advertisement sets ranged from $0.55 to $3.85 Australian dollars. The “strength” advertisements resulted in the highest recruitment rate, but participants from this group were least engaged in the study website. The “strength” and “happiness” advertisements recruited more younger men. Participants recruited from the “mental health” advertisements had worse outcomes on the clinical measures of distress, wellbeing, strength, and stress. This study confirmed that different Facebook advertisement content leads to different recruitment rates and engagement with a study. Different advertisement also leads to selection bias in terms of demographic and mental health characteristics. Researchers should carefully consider the content of social media advertisements to be in accordance with their target population and consider reporting this to enable better assessment of generalisability.
Choi, Y, Naidu, G, Jeong, S, Vigneswaran, S, Lee, S, Wang, R & Fane, AG 2017, 'Experimental comparison of submerged membrane distillation configurations for concentrated brine treatment', Desalination, vol. 420, pp. 54-62.
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© 2017 Elsevier B.V. Membrane distillation (MD) is an attractive technology for seawater reverse osmosis (SWRO) brine treatment. Submerged MD (S-MD) offers an additional advantage of a compact system compared to cross-flow MD. This study evaluated the performances of three different S-MD configurations; submerged direct contact membrane distillation (S-DCMD), submerged vacuum direct contact membrane distillation (S-VDCMD) and submerged vacuum membrane distillation (S-VMD) for SWRO brine treatment. A 13–77% higher water flux was obtained by S-MDs with vacuum incorporation (S-VMD and S-VDCMD) compared to S-DCMD, attributed to higher driving force. Evaluation on the influence of feed concentration and permeate temperature revealed that S-MD with high vacuum was significantly affected by feed concentration. Meanwhile S-DCMD was more severely affected by feed temperature losses, based on the tendency of membrane pore crystallization formation. The crystallization tendency on the membrane surface was influenced by the presence of vacuum pressure. A repeated cycle of S-DCMD with membrane air-backwashing was effective for flux recovery and to reduce membrane crystallization, enabling to concentrate SWRO brine by 2.8 times of volume concentration factor.
Chua, L, Head, K, Thomas, P & Stuart, B 2017, 'FTIR and Raman microscopy of organic binders and extraneous organic materials on painted ceremonial objects from the Highlands of Papua New Guinea', Microchemical Journal, vol. 134, pp. 246-256.
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© 2017 Elsevier B.V. This paper presents a challenging case where organic materials in micro-sized paint samples extracted from mid-20th century ceremonial objects of the Papua New Guinea (PNG) Highlands are characterized using FTIR microscopy, with the aid of solvent extraction and pre-treatment with hydrofluoric acid (HF) targeted for micro-sized samples, as well as Raman microscopy and SEM-EDS. An eclectic range of binder classes including plant-based organic matter, animal fat, wax, natural and synthetic resin, were identified on several ceremonial objects based on spectral signatures. The tree resins detected (tigaso oil and kilt tree resin) are specific to the natural flora from the PNG Highlands. Tannin-rich charred wood forming the base substrate of different ceremonial objects was also identified. In addition, degradation products from metal soaps from both synthetic and biological sources were identified.
Chubb, CT, Tan, VYF & Tomamichel, M 2017, 'Moderate deviation analysis for classical communication over quantum channels', Communications in Mathematical Physics, vol. 355, no. 3, pp. 1283-1315.
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We analyse families of codes for classical data transmission over quantumchannels that have both a vanishing probability of error and a code rateapproaching capacity as the code length increases. To characterise thefundamental tradeoff between decoding error, code rate and code length for suchcodes we introduce a quantum generalisation of the moderate deviation analysisproposed by Altug and Wagner as well as Polyanskiy and Verdu. We derive such atradeoff for classical-quantum (as well as image-additive) channels in terms ofthe channel capacity and the channel dispersion, giving further evidence thatthe latter quantity characterises the necessary backoff from capacity whentransmitting finite blocks of classical data. To derive these results we alsostudy asymmetric binary quantum hypothesis testing in the moderate deviationsregime. Due to the central importance of the latter task, we expect that ourtechniques will find further applications in the analysis of other quantuminformation processing tasks.
Chul Woo, Y, Chen, Y, Tijing, LD, Phuntsho, S, He, T, Choi, J-S, Kim, S-H & Kyong Shon, H 2017, 'CF4 plasma-modified omniphobic electrospun nanofiber membrane for produced water brine treatment by membrane distillation', Journal of Membrane Science, vol. 529, pp. 234-242.
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© 2017 Elsevier B.V. This study describes the development and performance of an omniphobic poly(vinylidene fluoride) (PVDF) membrane by electrospinning and CF4plasma surface modification for air gap membrane distillation (AGMD). The effect of different duration of plasma treatment on the nanofiber membrane characteristics was investigated. The AGMD performance of the membranes was evaluated using real reverse osmosis (RO) brine produced from coal seam gas (CSG) water that was added with low surface tension liquid (surfactant) as feed solution. Results indicated the formation of new CF2-CF2and CF3bonds after plasma treatment, which lowered the surface energy of the membrane, providing omniphobic property, as indicated by its wetting resistance to different low surface tension liquids such as methanol, mineral oil and ethylene glycol. Though no appreciative changes in morphology of the membrane were observed after plasma treatment, optimal treatment condition of 15 min (i.e., P/CF-15 membrane) exhibited lotus effect membrane surface with increased liquid entry pressure of 187 kPa compared to 142 kPa for neat membrane. AGMD performance showed stable normalized flux (initial flux of 15.3 L/m2h) and rejection ratio (100%) for P/CF-15 even with the addition of up to 0.7 mM sodium dodecyl sulfate surfactant to the RO brine from CSG produced water feed, while commercial PVDF membrane suffered membrane wetting after 0.3 mM of surfactant addition. Based on the results, the present omniphobic membrane has good potential for producing clean water from challenging waters containing high salinity and organic contaminants.
Chung, W-J, Torrejos, REC, Park, MJ, Vivas, EL, Limjuco, LA, Lawagon, CP, Parohinog, KJ, Lee, S-P, Shon, HK, Kim, H & Nisola, GM 2017, 'Continuous lithium mining from aqueous resources by an adsorbent filter with a 3D polymeric nanofiber network infused with ion sieves', Chemical Engineering Journal, vol. 309, pp. 49-62.
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© 2016 Elsevier B.V. Electrospun composite nanofiber (NF) was fabricated and employed as an adsorbent membrane filter in a continuous Li + mining process from seawater. The filter was composed of a hydrophilic polyacrylonitrile (PAN) matrix infused with lithium ion sieves (LIS) H 1.6 Mn 1.6 O 4 . Characterization of the LIS/PAN NF confirmed its favorable structural and surface properties for effective Li + adsorption. The LIS/PAN NF was mechanically suitable as a microfiltration membrane with high water flux and low pressure requirement. Breakthrough experiments at varied feed concentrations (C f ), seawater flowrates (F), and NF thicknesses (Z) revealed the dynamic adsorption behavior of the filter. The seawater residence time was most critical and must be kept ⩾0.12 min at any given C f and Z to maximize the Li + capacity of the filter. This can be conveniently achieved by adjusting the F of the process. Analogous to a packed bed system, the predictive power of nine breakthrough models were determined through non-linear regression analyses. Results reveal that bed-depth-space-time, Bohart-Adams (BA) and Thomas models adequately predicted the performance of the filter albeit BA exhibited the best agreement. Meanwhile, Wolborska failed to converge with any of the experimental results while Yoon-Nelson, Wang, Clark, dose-response, and modified dose-response were too simple to provide any meaningful information. Cycled Li + adsorption-desorption runs successfully collected and concentrated Li + in a mild acid stripping solution. After ten cycles, Li + was separated 155–1552 times more efficiently than Na + , K + , Mg 2+ and Ca 2+ . Overall results demonstrate the potential of LIS/PAN NF as an adsorbent membrane filter for continuous Li + mining from aqueous resources.
Clement, S, Sobhan, M, Deng, W, Camilleri, E & Goldys, EM 2017, 'Nanoparticle-mediated singlet oxygen generation from photosensitizers', Journal of Photochemistry and Photobiology A: Chemistry, vol. 332, pp. 66-71.
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Cooper, CS, Franklin, DR, Ros, M, Safaei, F & Abolhasan, M 2017, 'A Comparative Survey of VANET Clustering Techniques.', IEEE Commun. Surv. Tutorials, vol. 19, no. 1, pp. 657-681.
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A vehicular ad hoc network (VANET) is a mobile ad hoc network (MANET) in which network nodes are vehicles – most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organised nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, inforomation dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming – the lack of realistic vehicular channel modelling – is identified. The importance of a rigorous and standardised performance evaluation regime utilising realistic vehicular channel models is demonstrated.
Corio, E, Laccone, F, Pietroni, N, Cignoni, P & Froli, M 2017, 'Conception and parametric design workflow for a timber large-spanned reversible grid shell to shelter the archaeological site of the roman shipwrecks in pisa', International Journal of Computational Methods and Experimental Measurements, vol. 5, no. 4, pp. 551-561.
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Corsetti, S, Rabl, T, McGloin, D & Kiefer, J 2017, 'Intermediate phases during solid to liquid transitions in long-chain n-alkanes', Physical Chemistry Chemical Physics, vol. 19, no. 21, pp. 13941-13950.
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Temperature-dependent Raman spectra of tetradecane, pentadecane and hexadecane are collected and analysed to unveil the difference in the speed of their phase transitions while gaining information about their structural changes.
Coughlan, CP, Ainsworth, RE, Eislöffel, J, Hoeft, M, Drabent, A, Scaife, AMM, Ray, TP, Bell, ME, Broderick, JW, Corbel, S, Grießmeier, J-M, van der Horst, AJ, van Leeuwen, J, Markoff, S, Pietka, M, Stewart, AJ, Wijers, RAMJ & Zarka, P 2017, 'A LOFAR DETECTION OF THE LOW-MASS YOUNG STAR T TAU AT 149 MHz', The Astrophysical Journal, vol. 834, no. 2, pp. 206-206.
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ABSTRACT Radio observations of young stellar objects (YSOs) enable the study of ionized plasma outflows from young protostars via their free–free radiation. Previous studies of the low-mass young system T Tau have used radio observations to model the spectrum and estimate important physical properties of the associated ionized plasma (local electron density, ionized gas content, and emission measure). However, without an indication of the low-frequency turnover in the free–free spectrum, these properties remain difficult to constrain. This paper presents the detection of T Tau at 149 MHz with the Low Frequency Array (LOFAR)—the first time a YSO has been observed at such low frequencies. The recovered total flux indicates that the free–free spectrum may be turning over near 149 MHz. The spectral energy distribution is fitted and yields improved constraints on local electron density ( cm−3), ionized gas mass ( ), and emission measure ( pc cm−6).
Coyer, F, Gardner, A & Doubrovsky, A 2017, 'An interventional skin care protocol (InSPiRE) to reduce incontinence-associated dermatitis in critically ill patients in the intensive care unit: A before and after study', Intensive and Critical Care Nursing, vol. 40, pp. 1-10.
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Crisostomo, F, Hjerrild, N, Mesgari, S, Li, Q & Taylor, RA 2017, 'A hybrid PV/T collector using spectrally selective absorbing nanofluids', Applied Energy, vol. 193, pp. 1-14.
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Nanotechnology is a rapidly developing field with a wide range of potential applications. One such application is using nanoparticles to selectively absorb and transmit light. By controlling the material, size and shape of nanoparticles it is possible to achieve spectrally selective optical properties. This phenomena can be exploited in solar energy applications where selective absorption of the solar spectrum enables high efficient hybrid photovoltaic/thermal (PV/T) collectors. In this study, we suspend core-shell Ag-SiO nanoparticles in water to filter out the ideal spectrum for creating electricity from Si PV cells. A detailed optical and heat transfer model for this approach was developed and validated using the electric and thermal outputs from a prototype system operating in real outdoor conditions. The results of this experimental work indicates that 12% more value (weighted energy output) can be achieved from this PV/T prototype compared with a stand-alone PV system under the same illumination. Since the proposed system inherently decouples the thermal receiver from the PV cells, it is possible to extend this technology to industrial combined heat and power applications. 2
Cu, P & Ball, JE 2017, 'Parameter estimation for a large catchment', Australasian Journal of Water Resources, vol. 21, no. 1, pp. 20-33.
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© 2017 Engineers Australia. Estimation of parameter values is an essential step in the application of catchment modelling systems. This step is time-consuming and requires considerable effort. While a variety of approaches have been developed to accelerate the process, this paper proposes a method to reduce significantly the number of parameters for a large catchment when a semi-distributed catchment modelling system is applied. Past studies have reported on the use of a scaling parameter to adjust parameter values from their initial values, introduced herein is the use of a scaling parameter together with a variation coefficient. This enables the spatial variation of changes in parameter values across the catchment to be considered. A case study was conducted for a 14,000 km2 catchment to assess the validity of this approach where the focus of the catchment modelling was the prediction of a design flood statistic. This catchment was divided into 155 subcatchments with 5 sensitive parameters per subcatchment. Hence, a total of 775 parameters needed to be considered. Using the proposed approach, the number of parameters considered during the calibration was reduced to 8 coefficients which was reasonable for a calibration and validation process that also enabled an estimate of the parameter variability.
Cu, PT & Ball, JE 2017, 'The influence of the calibration metric on design flood estimation using continuous simulation', International Journal of River Basin Management, vol. 15, no. 1, pp. 9-20.
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© 2016 International Association for Hydro-Environment Engineering and Research. Estimation of design flood flow has been and remains a concern for both hydrologic research and hydrologic practice. Knowledge of design flood flows provides a basis for sustainable flood management, which has the aim of reducing flood risk, thereby protecting people’s lives and property. Design floods for a given location can be estimated by a number of approaches including analysis of past flood statistics and the use of catchment modelling. When catchment modelling approaches are applied estimation of design flood flows, there is a need to calibrate the model parameters. As part of this calibration process, a calibration metric, or fitness measure, is needed to enable assessment of alternative sets of parameter values. Presented herein is an investigation into design flood quantiles derived from predictions obtained from a continuous catchment modelling system when alternative calibration metrics are used to assess the suitability of parameter values. Two alternative calibration metrics are considered with one calibration metric aimed at ensuring replication of recorded hydrographs and the second calibration metric aimed at ensuring replication of the statistical characteristics of the annual maxima series. It was found that use of the later calibration metric resulted in better reproduction of the flood probability model estimated from the historical data while reproduction of the recorded hydrographs (i.e. the first calibration metric) did not ensure reproduction of the flood probability model.
Cui, H, Xu, F & Saha, SC 2017, 'Transition to unsteady natural convection flow in a prismatic enclosure of triangular section', International Journal of Thermal Sciences, vol. 111, pp. 330-339.
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© 2016 Elsevier Masson SAS Natural convection in a prismatic enclosure of triangular section with the top cooling and the bottom heating is investigated using three dimensional (3D) numerical simulations for a wide range of Rayleigh numbers from 10 0 to 1.25 × 10 6 . The numerical result has been compared with the experiment. The development of natural convection flows in the cavity following sudden heating and cooling involves three stages: an initial stage, a transitional stage and a fully developed stage. Transition to unsteady natural convection flow in the fully developed stage, dependent on the Rayleigh number, is described. The flow structure including transversal and longitudinal rolls is characterized and the corresponding mechanism is discussed. The critical Rayleigh number for the transition to unsteady natural convection flow is obtained. The dependence of heat transfer on the Rayleigh number is quantified.
Cui, Q, Gu, Y, Ni, W & Liu, RP 2017, 'Effective Capacity of Licensed-Assisted Access in Unlicensed Spectrum for 5G: From Theory to Application', IEEE Journal on Selected Areas in Communications, vol. 35, no. 8, pp. 1754-1767.
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© 1983-2012 IEEE. License-assisted access (LAA) is a promising technology to offload dramatically increasing cellular traffic to unlicensed bands. Challenges arise from the provision of quality-of-service (QoS) and the quantification of capacity, due to the distributed and heterogeneous nature of LAA and legacy systems (such as Wi-Fi) coexisting in the bands. In this paper, we develop new theories of the effective capacity to measure LAA under statistical QoS requirements. A new four-state semi-Markovian model is developed to capture transmission collisions, random backoffs, and lossy wireless channels of LAA in distributed heterogeneous network environments. A closed-form expression for the effective capacity is derived to comprehensively analyze LAA. The four-state model is further abstracted to an insightful two-state equivalent which reveals the concavity of the effective capacity in terms of transmit rate. Validated by simulations, the concavity is exploited to maximize the effective capacity and effective energy efficiency of LAA, and provide significant improvements of 62.7% and 171.4%, respectively, over existing approaches. Our results are of practical value to holistic designs and deployments of LAA systems.
Cui, Q, Yuan, T & Ni, W 2017, 'Energy-Efficient Two-Way Relaying Under Non-ideal Power Amplifiers', IEEE Transactions on Vehicular Technology, vol. 66, no. 2, pp. 1257-1270.
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© 2016 IEEE. Energy efficiency (EE) is crucial to many batterypowered relay applications. Maximizing EE is challenging due to non-convex structures resulting from non-ideal power amplifiers (PAs) and non-negligible circuit power. We formulate such non-convex problems to maximize the EE of two-way relay systems, where the transmit power and duration of all participating nodes are jointly optimized. The intrinsic connection between the optimal transmit power and duration is established through our derived necessary conditions of the optimality. It enables us to reformulate the non-convex problems to problems with rigorously proved convexity in the vicinities of the optimal transmit duration and to solve the problems using simple convex search. Simulation results show that the EE gain of our approach is substantial, compared with the state of the art, when the traffic demand is low or unbalanced in the two link directions. The gain enlarges as the imbalance of traffic demand grows.
Cui, Q, Zhang, Y, Ni, W, Valkama, M & Jantti, R 2017, 'Energy Efficiency Maximization of Full-Duplex Two-Way Relay With Non-Ideal Power Amplifiers and Non-Negligible Circuit Power', IEEE Transactions on Wireless Communications, vol. 16, no. 9, pp. 6264-6278.
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© 2002-2012 IEEE. In this paper, we maximize the energy efficiency (EE) of full-duplex (FD) two-way relay (TWR) systems under non-ideal power amplifiers (PAs) and non-negligible transmission-dependent circuit power. We start with the case where only the relay operates full duplex and two timeslots are required for TWR. Then, we extend to the advanced case, where the relay and the two nodes all operate full duplex, and accomplish TWR in a single timeslot. In both cases, we establish the intrinsic connections between the optimal transmit powers and durations, based on which the original non-convex EE maximization can be convexified and optimally solved. Simulations show the superiority of FD-TWR in terms of EE, especially when traffic demand is high. The simulations also reveal that the maximum EE of FD-TWR is more sensitive to the PA efficiency, than it is to self-cancellation. The full FD design of FD-TWR is susceptible to traffic imbalance, while the design with only the relay operating in the FD mode exhibits strong tolerance.
da Rocha, CG & Sattler, MA 2017, 'Improving Acceptance of More Sustainable Technologies: Exploratory Study in Brazil', Journal of Urban Planning and Development, vol. 143, no. 2, pp. 05016015-05016015.
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Dackermann, U, Yu, Y, Niederleithinger, E, Li, J & Wiggenhauser, H 2017, 'Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines', Sensors, vol. 17, no. 12, pp. 2938-2938.
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This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.
Dadzie, J, Ding, G & Runeson, G 2017, 'Relationship between Sustainable Technology and Building Age: Evidence from Australia', Procedia Engineering, vol. 180, pp. 1131-1138.
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© 2017 The Authors. Published by Elsevier Ltd. The overall energy performance of existing buildings is an important consideration in decisions to demolish or refurbish. To refurbish means to use sustainable technologies (STs) to improve energy efficiency, health of occupants, energy cost and environmental sustainability. This paper examines the use of STs to streamline energy efficiency in existing buildings. It analyses various buildings of different ages retrofitted over the last 5 years and the various STs used to enhance energy efficiency through an in-built case study in a survey. The results show that buildings less than 15 years old have been improved with fewer façade technologies compared to those between 16-30 years old. Overall, buildings aged between 16-30 years are the most improved with STs followed by buildings less than 15 years old and those between 31-45 years, in that order. Buildings over 45 years are the least improved with STs for energy efficiency. They had received less than 10% of ST technology injection. The lighting systems, sensors, energy efficient equipment and passive strategies have been applied improve energy efficiency across all ages. However, solar technologies, HVAC systems, façade technologies and building management systems are the least adopted across all ages.
Daly, L, Bland, PA, Dyl, KA, Forman, LV, Evans, KA, Trimby, PW, Moody, S, Yang, L, Liu, H, Ringer, SP, Ryan, CG & Saunders, M 2017, 'In situ analysis of Refractory Metal Nuggets in carbonaceous chondrites', Geochimica et Cosmochimica Acta, vol. 216, pp. 61-81.
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Daly, L, Bland, PA, Dyl, KA, Forman, LV, Saxey, DW, Reddy, SM, Fougerouse, D, Rickard, WDA, Trimby, PW, Moody, S, Yang, L, Liu, H, Ringer, SP, Saunders, M & Piazolo, S 2017, 'Crystallography of refractory metal nuggets in carbonaceous chondrites: A transmission Kikuchi diffraction approach', Geochimica et Cosmochimica Acta, vol. 216, pp. 42-60.
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Damanik, N, Ong, HC, Chong, WT & Silitonga, AS 2017, 'Biodiesel production from Calophyllum inophyllum−palm mixed oil', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 39, no. 12, pp. 1283-1289.
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The objective of this study is to investigate the biodiesel production from Calophyllum inophyllum −palm mixed oil. The C. inophyllum–palm biodiesel (C. inophyllum palm oil methyl ester, CPME) is first produced by mixing the crude oils at an equal ratio of 50:50 vol%, followed by degumming, acid-catalyzed esterification, purification, and, last, alkaline-catalyzed transesterification. With this systematic procedure, the acid value of the CPME is 0.4 mg KOH/g, resulting in a significant enhancement of oxidation stability (114.21 h). The results indicate that the fatty acid methyl ester composition of the CPME may be the reason for its larger higher heating value (39.4 MJ/kg) and lower kinematic viscosity (4.15 mm2/s). In short, CPME satisfied the ASTM D6751 and EN 14214 standards as a promising alternative fuel in the future.
Daniel, S, Mazzolini, A & Mann, L 2017, 'Contextual Categorisation of Academics’ Conceptions of Teaching', Scientia in educatione, vol. 8.
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Background: Despite large-class research-based instructional strategies being firmly established in the literature, traditional teacher-centred lecturing remains the norm. This is particularly the case in physics, where Physics Education Research (PER) has blossomed as a discipline in its own right over the last few decades, but research-based strategies are not widely implemented. This variation in practice is underpinned by variations in beliefs and understandings about teaching. Studies investigating the spectrum of conceptions of teaching held by teachers and, in particular, academics have almost uniformly identified a single dimension from teacher-centred to student-centred. These studies have used a phenomenographic approach to capture the variety of conceptions of teaching, but have excluded contextual issues like class size. Research Question: How does class size affect academics’ conceptions of teaching? Method: This study used an online survey to compare and contrast respondents’ experiences of small and large classes, and in particular lectures. The survey was promoted to Australian university academics from a range of disciplines, predominantly science, technology, engineering, and mathematics (STEM). Responses to the sets of small-class questions were analysed independently from the sets of equivalent large-class questions. For each respondent their small-class responses were categorised, where possible, as either being student-centred or teacher-centred, and likewise, independently, for their large-class responses. Results: In total, 107 survey responses were received. Of these, 51 had the sets of both their large- and small-class responses unambiguously categorised. Five of these were student-centred regardless of class size, and 17 of these were teacher-centred regardless of class size. All of the remaining 29 responses were teacher-centred in large classes, but student-centred in small classes. Conversely, none of the responses cor...
Dantas Neto, SA, Indraratna, B, Oliveira, DAF & de Assis, AP 2017, 'Modelling the Shear Behaviour of Clean Rock Discontinuities Using Artificial Neural Networks', Rock Mechanics and Rock Engineering, vol. 50, no. 7, pp. 1817-1831.
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Darestani, M, Haigh, V, Couperthwaite, SJ, Millar, GJ & Nghiem, LD 2017, 'Hollow fibre membrane contactors for ammonia recovery: Current status and future developments', Journal of Environmental Chemical Engineering, vol. 5, no. 2, pp. 1349-1359.
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© 2017 Elsevier Ltd. Hydrophobic membrane contactors represent a credible solution to the problem of recycling ammoniacal nitrogen from waste, water or wastewater resources. This study critically evaluated existing literature in terms of process principles, membrane types and functionality, membrane contactor application, technology status, and future research required. The key operational parameter was the presence of ammonia gas and thus pH should be above 9. Hollow fibre membranes are usually employed, composed of primarily polypropylene, polyvinylidene fluoride, or polytetrafluoroethylene. The stripping solution is normally sulphuric acid which reacts with ammonia to create ammonium sulphate. The acid is best circulated inside the lumen with any suitable velocity, and kept in excess concentration. In terms of operational parameters: feed fluid velocity is important in open loop configurations due to the effect upon ammonia residence time at the membrane surface; and, ammonia concentration did not notably impact the mass transfer coefficient which was ca. 1 × 10-5 m/s until in excess of 2000 mg/L wherein the transport process diminished. The greatest quantity of ammonia was recovered in the initial membrane stages where the driving force is greatest. Bench and pilot plant studies concerned wastewater treatment plants, anaerobic digesters, manure management, industrial manufacturing, and animal rearing operations. It is recommended to focus upon challenges such as development of new membrane types customised for ammonia removal, a greater understanding of the process engineering and economics involved, consideration of the impact of osmotic distillation, integration of membrane contactors with other water treatment technologies and development of cleaning in place procedures.
Davis, JJJ, Lin, C-T, Gillett, G & Kozma, R 2017, 'An Integrative Approach to Analyze Eeg Signals and Human Brain Dynamics in Different Cognitive States', Journal of Artificial Intelligence and Soft Computing Research, vol. 7, no. 4, pp. 287-299.
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AbstractElectroencephalograph (EEG) data provide insight into the interconnections and relationships between various cognitive states and their corresponding brain dynamics, by demonstrating dynamic connections between brain regions at different frequency bands. While sensory input tends to stimulate neural activity in different frequency bands, peaceful states of being and self-induced meditation tend to produce activity in the mid-range (Alpha). These studies were conducted with the aim of: (a) testing different equipment in order to assess two (2) different EEG technologies together with their benefits and limitations and (b) having an initial impression of different brain states associated with different experimental modalities and tasks, by analyzing the spatial and temporal power spectrum and applying our movie making methodology to engage in qualitative exploration via the art of encephalography. This study complements our previous study of measuring multichannel EEG brain dynamics using MINDO48 equipment associated with three experimental modalities measured both in the laboratory and the natural environment. Together with Hilbert analysis, we conjecture, the results will provide us with the tools to engage in more complex brain dynamics and mental states, such as Meditation, Mathematical Audio Lectures, Music Induced Meditation, and Mental Arithmetic Exercises. This paper focuses on open eye and closed eye conditions, as well as meditation states in laboratory conditions. We assess similarities and differences between experimental modalities and their associated brain states as well as differences between the different tools for analysis and equipment.
Dear, RF, McGeechan, K, Barnet, MB, Barratt, AL & Tattersall, MHN 2017, '“Standard Care” in Cancer Clinical Trials: An Analysis of Care Provided to Women in the Control Arms of Breast Cancer Clinical Trials', Journal of the National Comprehensive Cancer Network, vol. 15, no. 9, pp. 1131-1139.
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Dehbari, N, Tavakoli, J, Singh Khatrao, S & Tang, Y 2017, 'In situ polymerized hyperbranched polymer reinforced poly(acrylic acid) hydrogels', Materials Chemistry Frontiers, vol. 1, no. 10, pp. 1995-2004.
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A novel hyperbranched polymer reinforced poly(acrylic acid) hydrogel with high water swelling abilities was synthesized by one-step in situ polymerization.
Dehbari, N, Tavakoli, J, Zhao, J & Tang, Y 2017, 'In situ formed internal water channels improving water swelling and mechanical properties of water swellable rubber composites', Journal of Applied Polymer Science, vol. 134, no. 9, pp. 1-6.
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ABSTRACTIn this study, electrospun nanofibers of poly (vinyl alcohol) (PVA) and styrene–butadiene–styrene triblock copolymer (SBS) were employed in conventional water‐swellable rubber (WSR) to design WSR composites with improved water swelling and mechanical properties. With the introduction of PVA nanofibers, considerable improvement in elasticity, strength, and water‐swelling behavior was observed. After immersion, PVA nanofibers dissolved within the composite to in situ form water channels to connect isolated super‐absorbent polymers (SAPs). Those water channels led to an increase in water uptake by the WSR composite. Furthermore, the secondary water‐swelling behaviors of the WSR composite showed a remarkable increase in swelling rate as well as in mechanical properties. The addition of SBS nanofibers had a marked impact on the mechanical properties of the WSR composite. Their roles became more pronounced after water immersion. The proposed enhancement mechanism is also discussed. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44548.
Deng, S, Huang, L, Xu, G, Wu, X & Wu, Z 2017, 'On Deep Learning for Trust-Aware Recommendations in Social Networks', IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 5, pp. 1164-1177.
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© 2016 IEEE. With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user's trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users' interests and their trusted friends' interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.
Deng, Y, Kan, ME, Indraratna, B & Zhong, R 2017, 'Finite Element Analysis of Vacuum Consolidation With Modified Compressibility and Permeability Parameters', International Journal of Geosynthetics and Ground Engineering, vol. 3, no. 2.
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© 2017, Springer International Publishing Switzerland. Laboratory tests and case history studies indicate that soil subjected to vacuum preloading may not behave the same as ground treated by traditional surcharge preloading. In detail, soil compression under vacuum pressure is smaller than or equal to that induced by positive pressure with the same magnitude; soil rebound after stopping the vacuum is not as high as after removing the surcharge; and the consolidation rate is usually faster under vacuum pressure than with surcharge preloading. Analysis of vacuum consolidation with existing methods cannot gain all these differences. Thus, in this study, three factors for adjusting compressibility and permeability are proposed based on past laboratory and field results which are used in a finite element analysis of soft soil foundation under vacuum-assisted preloading. This proposed method can be incorporated in existing computer programs associated with classical soil models (e.g., the modified Cam-Clay model and the Soft-Soil model); it is then examined via three distinct simulation scenarios including a laboratory model test and two prototype field cases. The improved accuracy in relation to consolidation by the proposed method is demonstrated and practical ranges for the adjustment factors are discussed.
Deng, Y-B, Liu, G-B, Indraratna, B, Rujikiatkamjorn, C & Xie, K-H 2017, 'Model Test and Theoretical Analysis for Soft Soil Foundations Improved by Prefabricated Vertical Drains', International Journal of Geomechanics, vol. 17, no. 1, pp. 04016045-04016045.
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Dennehy, C, Lawlor, PG, Jiang, Y, Gardiner, GE, Xie, S, Nghiem, LD & Zhan, X 2017, 'Greenhouse gas emissions from different pig manure management techniques: a critical analysis', Frontiers of Environmental Science & Engineering, vol. 11, no. 3, pp. 1-16.
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© 2017, Higher Education Press and Springer-Verlag Berlin Heidelberg. Manure management is the primary source of greenhouse gas (GHG) emissions from pig farming, which in turn accounts for 18% of the total global GHG emissions from the livestock industry. In this review, GHG emissions (N2O and CH4 emissions in particular) from individual pig manure (PGM) management practices (European practises in particular) are systematically analyzed and discussed. These manure management practices include manure storage, land application, solid/liquid separation, anaerobic digestion, composting and aerobic wastewater treatment. The potential reduction in net GHG emissions by changing and optimising these techniques is assessed. This review also identifies key research gaps in the literature including the effect of straw covering of liquid PGM storages, the effect of solid/liquid separation, and the effect of dry anaerobic digestion on net GHG emissions from PGM management. In addition to identifying these research gaps, several recommendations including the need to standardize units used to report GHG emissions, to account for indirect N2O emissions, and to include a broader research scope by conducting detailed life cycle assessment are also discussed. Overall, anaerobic digestion and compositing to liquid and solid fractions are best PGM management practices with respect to their high GHG mitigation potential. [Figure not available: see fulltext.].
Dharma, S, Hassan, MH, Ong, HC, Sebayang, AH, Silitonga, AS & Kusumo, F 2017, 'Optimization of biodiesel production from mixed jatropha curcas-ceiba pentandra using artificial neural network- genetic algorithm: Evaluation of reaction kinetic models', Chemical Engineering Transactions, vol. 56, pp. 547-552.
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Biodiesel production from non-edible vegetable oil is one effective way to anticipate the problems associated with fuel crisis and environmental issues. In this study, artificial neural network and genetic algorithm based Box Behnken experimental design used to optimize the parameters of the biodiesel production for mixed of Jatropha curcas?Ceiba pentandra oil such as methanol to oil ratio, agitation speed and catalyst concentration. Based on the results, the optimum operating parameters for the transesterification of the oil mixture J50C50 are as follows: methanol-To-oil ratio: 40 %v/v, agitation speed: 1,794 rpm and the catalyst concentration: 0.68 % wt. This process is carried out at constant temperature and time of 60 °C and 2 h. The theoretical yield predicted under this the highest yield for the J50C50 biodiesel with a value of 93.70 %. The model developed was validated by applying the optimum values to three independent experimental replicates with a 93.56 %. Comparison between the predicted values to the actual value with a small error percentage indicates that the regression model was reliable in predicting the conversion at any given conditions within the ranges studied. Moreover, the activation energy of 24.421 kJmol-1 and frequency factor of 1.88 x 102 min-1 was required for the transesterification process. The fuel properties of the biodiesel were measured according to ASTM D 6751 and EN14214 standards and found to be within the specifications.
Dharma, S, Hassan, MH, Ong, HC, Sebayang, AH, Silitonga, AS, Kusumo, F & Milano, J 2017, 'Experimental study and prediction of the performance and exhaust emissions of mixed Jatropha curcas-Ceiba pentandra biodiesel blends in diesel engine using artificial neural networks', Journal of Cleaner Production, vol. 164, pp. 618-633.
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Ding, C, Jones, B, Guo, YJ & Qin, P-Y 2017, 'Wideband Matching of Full-Wavelength Dipole With Reflector for Base Station', IEEE Transactions on Antennas and Propagation, vol. 65, no. 10, pp. 5571-5576.
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© 1963-2012 IEEE. This communication introduces a wideband hybrid feeding method for full-wavelength dipole antennas with a reflector. A full-wavelength dipole is designed to cover the band from 698 to 960 MHz for cellular base station applications. Its matching circuit consists of a triple-tuned circuit and a quasi-quarter-wavelength impedance transformer. The proposed matching circuit can provide balanced feeding as a balun and has a compact size. The working mechanism and a complete design scheme of the proposed matching circuit are elaborated. The matching circuit is designed and optimized using a circuit theory model and then physically realized using microstrip lines based on full-wave simulation. The measured reflection coefficient |S-{11}| is lesser than -14 dB across the entire band from 698 to 960 MHz, exhibiting a bandwidth of 32%. This is the first time that a wideband center-fed full-wavelength dipole is proposed.
Ding, C, Sun, H, Ziolkowski, RW & Guo, YJ 2017, 'Simplified Tightly-Coupled Cross-Dipole Arrangement for Base Station Applications', IEEE Access, vol. 5, pp. 27491-27503.
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© 2013 IEEE. The electromagnetic fundamentals that govern the performance characteristics of dual-polarized tightly coupled cross-dipoles that are widely used in cellular base station applications are investigated. The mutual coupling effects and their impact on standard performance indices are stressed. A model is developed that considers this type of cross-dipole as an array. Links between the physical dimensions of the components of these model and key radiation characteristics, including directivity, half-power-beam width, and cross polarization discrimination levels, are established. The model guides the introduction and optimization of a simplified cross-dipole structure that exhibits excellent performance. A prototype was fabricated, assembled, and tested. The measured results are in good agreement with their simulated values, validating the model, and its governing principles.
Ding, L, Zhu, X, Wang, Y, Shi, B, Ling, X, Chen, H, Nan, W, Barrett, A, Guo, Z, Tao, W, Wu, J & Shi, X 2017, 'Intracellular Fate of Nanoparticles with Polydopamine Surface Engineering and a Novel Strategy for Exocytosis-Inhibiting, Lysosome Impairment-Based Cancer Therapy', Nano Letters, vol. 17, no. 11, pp. 6790-6801.
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Dorrell, DG, Salah, A & Guo, Y 2017, 'The Detection and Suppression of Unbalanced Magnetic Pull in Wound Rotor Induction Motors Using Pole-Specific Search Coils and Auxiliary Windings', IEEE Transactions on Industry Applications, vol. 53, no. 3, pp. 2066-2076.
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© 2017 IEEE. This paper puts forward a concept for measuring rotor eccentricity in a wound rotor induction machine. The analysis is fully developed in the theory section, then an experimental rig is described and measurements are taken. These are compared with the calculated values. Pole-specific search windings are necessary in a wound rotor machine, because standard sideband current measurement techniques are only valid for cage induction machines. The search coils can also be used to suppress unbalanced magnetic pull.
Dovey, K, Burdon, S & Simpson, R 2017, 'Creative leadership as a collective achievement: An Australian case', Management Learning, vol. 48, no. 1, pp. 23-38.
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In this article, we examine the construct of ‘leadership’ through an analysis of the social practices that underpinned the Australian Broadcasting Corporation television production entitled The Code. Positioning the production within the neo-bureaucratic organisational form currently adopted by the global television industry, we explore new conceptualisations of the leadership phenomenon emerging within this industry in response to the increasingly complex, uncertain and interdependent nature of creative work within it. We show how the polyarchic governance regime characteristic of the neo-bureaucratic organisational form ensures broadcaster control and coordination through ‘hard power’ mechanisms embedded in the commissioning process and through ‘soft power’ relational practices that allow creative licence to those employed in the production. Furthermore, we show how both sets of practices (commissioning and creative practices) leverage and regenerate the relational resources – such as trust, commitment and resilience – gained from rich stakeholder experience of working together in the creative industries over a significant period of time. Referencing the leadership-as-practice perspective, we highlight the contingent and improvisational nature of these practices and metaphorically describe the leadership manifesting in this production as a form of ‘interstitial glue’ that binds and shapes stakeholder interests and collective agency.
Du, B, Wang, Z, Zhang, L, Zhang, L, Liu, W, Shen, J & Tao, D 2017, 'Exploring Representativeness and Informativeness for Active Learning', IEEE Transactions on Cybernetics, vol. 47, no. 1, pp. 14-26.
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© 2013 IEEE. How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network modeling, etc. Although combining representativeness and informativeness of samples has been proven promising for active sampling, state-of-the-art methods perform well under certain data structures. Then can we find a way to fuse the two active sampling criteria without any assumption on data? This paper proposes a general active learning framework that effectively fuses the two criteria. Inspired by a two-sample discrepancy problem, triple measures are elaborately designed to guarantee that the query samples not only possess the representativeness of the unlabeled data but also reveal the diversity of the labeled data. Any appropriate similarity measure can be employed to construct the triple measures. Meanwhile, an uncertain measure is leveraged to generate the informativeness criterion, which can be carried out in different ways. Rooted in this framework, a practical active learning algorithm is proposed, which exploits a radial basis function together with the estimated probabilities to construct the triple measures and a modified best-versus-second-best strategy to construct the uncertain measure, respectively. Experimental results on benchmark datasets demonstrate that our algorithm consistently achieves superior performance over the state-of-the-art active learning algorithms.
Du, G, Huang, X, Li, Y, Ouyang, Q & Wang, J 2017, 'Performance of a semi-active/passive integrated isolator based on a magnetorheological elastomer and spring', Smart Materials and Structures, vol. 26, no. 9, pp. 095024-095024.
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© 2017 IOP Publishing Ltd. This paper reports an investigation on a semi-active/passive integrated vibration isolator utilizing a magnetorheological elastomer (MRE) and spring. To overcome the main shortcoming of passive isolation systems, i.e. lack of adaptability, the semi-active/passive integrated isolator (SAPII) based on an MRE and spring is designed and prototyped. The magnetic circuit is optimized by finite element analysis to fully unlock the unique features of the MRE. The dynamic response characteristic of the SAPII is experimentally investigated under a sweep frequency test. A dynamic model of the SAPII vibration isolation system is established on the basis of the Kelvin model. The model parameters, such as equivalent stiffness and equivalent damping, are identified from experimental data. An ON-OFF control law based on the minimal displacement transmissibility is designed for isolation control of the sinusoid excitation. Two control laws, i.e. ON-OFF control and fuzzy logic control, are designed for vibration isolation of random excitation. Finally, the effectiveness of these control laws is verified by numerical simulation and experiment.
Du, J, Pegrum, CM, Gao, X, Weily, AR, Zhang, T, Guo, YJ & Foley, CP 2017, 'Harmonic Mixing Using a HTS Step-Edge Josephson Junction at 0.6 THz Frequency', IEEE Transactions on Applied Superconductivity, vol. 27, no. 4, pp. 1-5.
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© 2002-2011 IEEE. A high-temperature superconducting (HTS) terahertz (THz) heterodyne mixer based on a thin-film antenna-coupled YBa 2 Cu 3 O 7- x step-edge Josephson junction is presented. The frequency down-conversion from 0.6 THz to an intermediate frequency (IF) of 2 GHz was achieved using high-order harmonic mixing of a local oscillator (LO), thus removing the need to use a second THz source as the LO pumping source. The DC and RF characteristics of the harmonic mixer as well as the relationship of the IF output power versus the harmonic number were experimentally studied and compared with simulated results. Most of our measurements were made at 40 K, but we also observed stable harmonic mixing at 77 K which we believe has not been reported previously in HTS junction mixers.
Du, J, Sugumaran, V & Gao, B 2017, 'RFID and Multi-Agent Based Architecture for Information Sharing in Prefabricated Component Supply Chain', IEEE Access, vol. 5, pp. 4132-4139.
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Du, J, Weily, AR, Gao, X, Zhang, T, Foley, CP & Guo, YJ 2017, 'HTS step-edge Josephson junction terahertz harmonic mixer', Superconductor Science and Technology, vol. 30, no. 2, pp. 024002-024002.
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© 2016 Federal Australian Crown copyright. A high-temperature superconducting (HTS) terahertz (THz) frequency down-converter or mixer based on a thin-film ring-slot antenna coupled YBa 2 Cu 3 O 7-x (YBCO)/MgO step-edge Josephson junction is reported. The frequency down-conversion was achieved using higher order harmonics of an applied lower frequency (19-40 GHz) local oscillator signal in the Josephson junction mixing with a THz signal of over 600 GHz, producing a 1-3 GHz intermediate frequency signal. Up to 31st order of harmonic mixing was obtained and the mixer operated stably at temperatures up to 77 K. The design details of the antenna, HTS Josephson junction mixer, the matching and isolation circuits, and the DC and RF performance evaluation are described in this paper.
Du, Y, Li, H, Luo, Z & Tian, Q 2017, 'Topological design optimization of lattice structures to maximize shear stiffness', Advances in Engineering Software, vol. 112, pp. 211-221.
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© 2017 Elsevier Ltd To improve the poor shear performance of periodic lattice structure consisting of hexagonal unit cells, this study develops a new computational design method to apply topology optimization to search the best topological layout for lattice structures with enhanced shear stiffness. The design optimization problem of micro-cellular material is formulated based on the properties of macrostructure to maximize the shear modulus under a prescribed volume constraint using the energy-based homogenization method. The aim is to determine the optimal distribution of material phase within the periodic unit cell of lattice structure. The proposed energy-based homogenization procedure utilizes the sensitivity filter technique, especially, a modified optimal algorithm is proposed to evolve the microstructure of lattice materials with distinct topological boundaries. A high shear stiffness structure is obtained by solving the optimization model. Then, the mechanical equivalent properties are obtained and compared with those of the hexagonal honeycomb sandwich structure using a theoretical approach and the finite element method (FEM) according to the optimized structure. It demonstrates the effectiveness of the proposed method in this paper. Finally, the structure is manufactured, and then the properties are tested. Results show that the shear stiffness and bearing properties of the optimized lattice structure is better than that of the traditional honeycomb sandwich structure. In general, the proposed method can be effectively applied to the design of periodic lattice structures with high shear resistance and super bearing property.
Duan, H, Ye, L, Erler, D, Ni, B-J & Yuan, Z 2017, 'Quantifying nitrous oxide production pathways in wastewater treatment systems using isotope technology – A critical review', Water Research, vol. 122, pp. 96-113.
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© 2017 Elsevier Ltd Nitrous oxide (N2O) is an important greenhouse gas and an ozone-depleting substance which can be emitted from wastewater treatment systems (WWTS) causing significant environmental impacts. Understanding the N2O production pathways and their contribution to total emissions is the key to effective mitigation. Isotope technology is a promising method that has been applied to WWTS for quantifying the N2O production pathways. Within the scope of WWTS, this article reviews the current status of different isotope approaches, including both natural abundance and labelled isotope approaches, to N2O production pathways quantification. It identifies the limitations and potential problems with these approaches, as well as improvement opportunities. We conclude that, while the capabilities of isotope technology have been largely recognized, the quantification of N2O production pathways with isotope technology in WWTS require further improvement, particularly in relation to its accuracy and reliability.
Dumée, LF, Maina, JW, Merenda, A, Reis, R, He, L & Kong, L 2017, 'Hybrid thin film nano-composite membrane reactors for simultaneous separation and degradation of pesticides', Journal of Membrane Science, vol. 528, pp. 217-224.
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Membrane reactors typically combine chemically reactive pathways with separation opportunities to increase conversion and chemical processes efficiency in liquid effluents treatment. The treatment of industrial bio-products, waste mixed solvents and agro-chemicals with such reactors are however challenging due to the natural affinity of such reactive materials for organic and biological matter leading to surface adsorption and fouling tendencies. Here, hybrid thin film composite catalytic membranes offering superior flow permeation characteristics, extremely high retention of low molecular weight organics and partial salt rejection capabilities were for the first time synthesized. Catalytic silver-metal nano-materials were for the first time homogeneously templated and encapsulated across metal organic frameworks nano-particles and incorporated across the top surface of poly(amide) thin films during interfacial polymerization. These novel materials offer high catalytic/anti-microbial behaviours due to the nano-structure of the metal nano-particles reduced within the metal organic framework template, forming unique hierarchical sub-100 nm hybrid nano-structures. These ultra-thin but yet dense membranes were able to simultaneously degrade chemicals and filter contaminants, opening new pathways for the design of the next generation thin film nano-composite membranes. Catalytic properties and homogeneity were evaluated for the Fenton-like heterogeneous catalytic degradation of 2,4-Dichlorophenoxyacetic acid, a waste pesticide contained in agricultural wastewater.
Dumée, LF, Yi, Z, Tardy, B, Merenda, A, des Ligneris, E, Dagastine, RR & Kong, L 2017, 'Silver metal nano-matrixes as high efficiency and versatile catalytic reactors for environmental remediation', Scientific Reports, vol. 7, no. 1, p. 45112.
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AbstractNano-porous metallic matrixes (NMMs) offer superior surface to volume ratios as well as enhanced optical, photonic, and electronic properties to bulk metallic materials. Such behaviours are correlated to the nano-scale inter-grain metal domains that favour the presence of electronic vacancies. In this work, continuous 3D NMMs were synthesized for the first time through a simple diffusion-reduction process whereby the aerogel matrix was functionalized with (3-Mercaptopropyl)trimethoxysilane. The surface energy of the silica monolith templates was tuned to improve the homogeneity of the reduction process while thiol functionalization facilitated the formation of a high density of seeding points for metal ions to reduce. The diameter of NMMs was between 2 and 1000 nm, corresponding to a silver loading between 1.23 and 41.16 at.%. A rates of catalytic degradation kinetics of these NMMS which is three orders of magnitude higher than those of the non-functionalized silver-silica structures. Furthermore, the enhancement in mechanical stability at nanoscale which was evaluated by Atomic Force Microscopy force measurements, electronic density and chemical inertness was assessed and critically correlated to their catalytic potential. This strategy opens up new avenues for design of complex architectures of either single or multi-metal alloy NMMs with enhanced surface properties for various applications.
Duong, HC, Hai, FI, Al-Jubainawi, A, Ma, Z, He, T & Nghiem, LD 2017, 'Liquid desiccant lithium chloride regeneration by membrane distillation for air conditioning', Separation and Purification Technology, vol. 177, pp. 121-128.
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Duong, HC, Xia, L, Ma, Z, Cooper, P, Ela, W & Nghiem, LD 2017, 'Assessing the performance of solar thermal driven membrane distillation for seawater desalination by computer simulation', Journal of Membrane Science, vol. 542, pp. 133-142.
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Durinck, K, Dewyn, J, Beckers, A, Loontiens, S, Vanhauwaert, S, Carter, D, Chueng, B, Marshall, G, Depreter, K, Westermann, F & Speleman, F 2017, 'Abstract 1527: BRD3 as a specific vulnerable therapeutic target in neuroblastoma', Cancer Research, vol. 77, no. 13_Supplement, pp. 1527-1527.
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Abstract Introduction: BET inhibitors have raised high expectations for cancer treatment given their anti-proliferative effect by inhibiting BRD4 controlled enhancer activity of highly transcribed genes such as MYC(N). However, current inhibitors also target BRD2 and BRD3 which are functionally nonredundant with BRD4. In neuroblastoma only MYCN amplified tumors respond well to these drugs. Methods: We performed an integrated bioinformatics approach to scrutinize BET family genes as well as further candidate epigenetic regulators as targets for novel therapies in neuroblastoma. Results: First we performed a time-resolved expression data analysis of week 1 and 2 hyperplastic lesions and tumors derived from the TH-MYCN transgenic mouse model and confirmed dynamic regulation during tumor development for established neuroblastoma oncogenes and tumor suppressor genes. Next, we filtered within the highest upregulated genes for Cancer Gene Census (CGC) genes and identified 21 upregulated CGC genes mainly involved in chromatin remodeling and DNA repair. Finally, after further selection based on expression in CCLE and survival in neuroblastoma patients, BRD3 was identified as the top-ranked candidate. BRD3 exhibits drastic upregulation during tumor formation. Elevated BRD3 expression is the highest expressed gene in neuroblastoma cell lines upon analysis of the CCLE panel and associated with very poor prognosis. To explore the nonredundant functions of BRD3 in relation to BRD4, we performed RNA-sequencing after stable knockdown of BRD3 in neuroblastoma cell lines and compared the downstream effects on the transcriptome as well as the impact on cell viability to knockdown of BRD4 and pharmacological treatment with BET-inhibitors (JQ1, OTX015). In addition, we dissected the BRD3 protein complex by means of label-free mass spectrometry analysis to gain fur...
Edwards, D, Cheng, M, Wong, IA, Zhang, J & Wu, Q 2017, 'Ambassadors of knowledge sharing', International Journal of Contemporary Hospitality Management, vol. 29, no. 2, pp. 690-708.
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PurposeThe aim of this study is to understand the knowledge-sharing structure and co-production of trip-related knowledge through online travel forums.Design/methodology/approachThe travel forum threads were collected from TripAdvisor’s Sydney travel forum for the period from 2010 to 2014, which contains 115,847 threads from 8,346 conversations. The data analytical technique was based on a novel methodological approach – visual analytics, including semantic pattern generation and network analysis.FindingsFindings indicate that the knowledge structure is created by community residents who camouflage as local experts and serve as ambassadors of a destination. The knowledge structure presents collective intelligence co-produced by community residents and tourists. Further findings reveal how these community residents associate with each other and form a knowledge repertoire with information covering various travel domain areas.Practical implicationsThe study offers valuable insights to help destination-management organizations and tour operators identify existing and emerging tourism issues to achieve a competitive destination advantage.Originality/valueThis study highlights the process of social media mediated travel knowledge co-production. It also discovers how community residents engage in reaching out to tourists by camouflaging as ordinary users.
Erfani, SS, Abedin, B & Blount, Y 2017, 'The effect of social network site use on the psychological well‐being of cancer patients', Journal of the Association for Information Science and Technology, vol. 68, no. 5, pp. 1308-1322.
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Social network sites (SNSs) are growing in popularity and social significance. Although researchers have attempted to explain the effect of SNS use on users' psychological well‐being, previous studies have produced inconsistent results. In addition, most previous studies relied on healthy students as participants; other cohorts of SNSs users, in particular people living with serious health conditions, have been neglected. In this study, we carried out semistructured interviews with users of the Ovarian Cancer Australia (OCA) Facebook to assess how and in what ways SNS use impacts their psychological well‐being. A theoretical model was proposed to develop a better understanding of the relationships between SNS use and the psychological well‐being of cancer patients. Analysis of data collected through a subsequent quantitative survey confirmed the theoretical model and empirically revealed the extent to which SNS use impacts the psychological well‐being of cancer patients. Findings showed the use of OCA Facebook enhances social support, enriches the experience of social connectedness, develops social presence and learning and ultimately improves the psychological well‐being of cancer patients.
Erkmen, RE & Saleh, A 2017, 'ITERATIVE GLOBAL-LOCAL APPROACH TO CONSIDER THE EFFECTS OF LOCAL ELASTO-PLASTIC DEFORMATIONS IN THE ANALYSIS OF THIN-WALLED MEMBERS', International Journal for Multiscale Computational Engineering, vol. 15, no. 2, pp. 143-173.
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© 2017 by Begell House, Inc. The aim of this study is to develop an iterative global-local analysis method to efficiently model the local deformation effects for the nonlinear elasto-plastic analysis of thin-walled beams. Thin-walled members are usually modeled by using beam-type one-dimensional finite elements, which are based on rigid cross-section assumption. Therefore, only deformations associated with the beam axis behavior such as flexural-, torsional-, or lateral buckling can be considered in these formulations, whereas local deformations, namely flange or web local buckling, can be captured by shell-type models. The proposed method allows the local use of shell elements in critical areas to incorporate the local deformation effects on the overall behavior of the thin-walled beam without necessitating a shell model for the whole structure. In this study, the local shell formulation is able to capture the elasto-plastic metal behavior based on the von Mises yield criterion and the associated flow rule for plane stress, which may cause unstable post-buckling response. In order to trace an unstable post-buckling curve, the iterative global-local analysis method is incorporated into the arc-length solution procedure. In order to improve the convergence characteristics, the procedure introduces strong discontinuities in the beam element formulation in the region of the local shell elements. These discontinuities are in the form of an internal enrichment considering additional local degrees of freedom associated with some penalty terms which adjust the tangent stiffness matrix of the beam for the prediction in the next step according to the effects of the local shell model in the previous step. Comparisons with full shell-type analysis are provided in order to illustrate the accuracy and efficiency of the method developed herein.
Erkmen, RE, Gowripalan, N & Sirivivatnanon, V 2017, 'Elasto-plastic damage modelling of beams and columns with mechanical degradation', Computers and Concrete, vol. 19, no. 3, pp. 315-323.
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© 2017 Techno-Press, Ltd. Within the context of continuum mechanics, inelastic behaviours of constitutive responses are usually modelled by using phenomenological approaches. Elasto-plastic damage modelling is extensively used for concrete material in the case of progressive strength and stiffness deterioration. In this paper, a review of the main features of elasto-plastic damage modelling is presented for uniaxial stress-strain relationship. It has been reported in literature that the influence of Alkali-Silica Reaction (ASR) can lead to severe degradations in the modulus of elasticity and compression strength of the concrete material. In order to incorporate the effects of ASR related degradation, in this paper the constitutive model of concrete is based on the coupled damage-plasticity approach where degradation in concrete properties can be captured by adjusting the yield and damage criteria as well as the hardening moduli related parameters within the model. These parameters are adjusted according to results of concrete behaviour from the literature. The effect of ASR on the dynamic behaviour of a beam and a column are illustrated under moving load and cyclic load cases.
Faizi, K, Rashid, ASA, Armaghani, DJ, Nazir, R & Momeni, E 2017, 'The Influence of Bituminous Coating on Uplift Resistance of Short Pile Foundations in Sand', Soil Mechanics and Foundation Engineering, vol. 54, no. 3, pp. 177-182.
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Falque, R, Vidal-Calleja, T & Miro, J 2017, 'Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data', Sensors, vol. 17, no. 10, pp. 2276-2276.
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Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects.
Fan, X, Xu, RYD, Cao, L & Song, Y 2017, 'Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network', IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 589-599.
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© 2013 IEEE. Relational model learning is useful for numerous practical applications. Many algorithms have been proposed in recent years to tackle this important yet challenging problem. Existing algorithms utilize only binary directional link data to recover hidden network structures. However, there exists far richer and more meaningful information in other parts of a network which one can (and should) exploit. The attributes associated with each node, for instance, contain crucial information to help practitioners understand the underlying relationships in a network. For this reason, in this paper, we propose two models and their solutions, namely the node-information involved mixed-membership model and the node-information involved latent-feature model, in an effort to systematically incorporate additional node information. To effectively achieve this aim, node information is used to generate individual sticks of a stick-breaking process. In this way, not only can we avoid the need to prespecify the number of communities beforehand, the algorithm also encourages that nodes exhibiting similar information have a higher chance of assigning the same community membership. Substantial efforts have been made toward achieving the appropriateness and efficiency of these models, including the use of conjugate priors. We evaluate our framework and its inference algorithms using real-world data sets, which show the generality and effectiveness of our models in capturing implicit network structures.
Fang, F, Qiao, L-L, Ni, B-J, Cao, J-S & Yu, H-Q 2017, 'Quantitative evaluation on the characteristics of activated sludge granules and flocs using a fuzzy entropy-based approach', Scientific Reports, vol. 7, no. 1, pp. 1-9.
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AbstractActivated sludge granules and flocs have their inherent advantages and disadvantages for wastewater treatment due to their different characteristics. So far quantitative information on their evaluation is still lacking. This work provides a quantitative and comparative evaluation on the characteristics and pollutant removal capacity of granules and flocs by using a new methodology through integrating fuzzy analytic hierarchy process, accelerating genetic algorithm and entropy weight method. Evaluation results show a higher overall score of granules, indicating that granules had more favorable characteristics than flocs. Although large sized granules might suffer from more mass transfer limitation and is prone to operating instability, they also enable a higher level of biomass retention, greater settling velocity and lower sludge volume index compared to flocs. Thus, optimized control of granule size is essential for achieving good pollutant removal performance and simultaneously sustaining long-term stable operation of granule-based reactors. This new integrated approach is effective to quantify and differentiate the characteristics of activated sludge granules and flocs. The evaluation results also provide useful information for the application of activated sludge granules in full-scale wastewater treatment plants.
Fang, J, Qiu, N, An, X, Xiong, F, Sun, G & Li, Q 2017, 'Crashworthiness design of a steel–aluminum hybrid rail using multi-response objective-oriented sequential optimization', Advances in Engineering Software, vol. 112, pp. 192-199.
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Fang, J, Sun, G, Qiu, N, Kim, NH & Li, Q 2017, 'On design optimization for structural crashworthiness and its state of the art', Structural and Multidisciplinary Optimization, vol. 55, no. 3, pp. 1091-1119.
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© 2016, Springer-Verlag Berlin Heidelberg. Optimization for structural crashworthiness and energy absorption has become an important topic of research attributable to its proven benefits to public safety and social economy. This paper provides a comprehensive review of the important studies on design optimization for structural crashworthiness and energy absorption. First, the design criteria used in crashworthiness and energy absorption are reviewed and the surrogate modeling to evaluate these criteria is discussed. Second, multiobjective optimization, optimization under uncertainties and topology optimization are reviewed from concepts, algorithms to applications in relation to crashworthiness. Third, the crashworthy structures are summarized, from generically novel structural configurations to industrial applications. Finally, some conclusions and recommendations are provided to enable academia and industry to become more aware of the available capabilities and recent developments in design optimization for structural crashworthiness and energy absorption.
Fang, J, Sun, G, Qiu, N, Steven, GP & Li, Q 2017, 'Topology Optimization of Multicell Tubes Under Out-of-Plane Crushing Using a Modified Artificial Bee Colony Algorithm', Journal of Mechanical Design, vol. 139, no. 7.
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Multicell tubal structures have generated increasing interest in engineering design for their excellent energy-absorbing characteristics when crushed through severe plastic deformation. To make more efficient use of the material, topology optimization was introduced to design multicell tubes under normal crushing. The design problem was formulated to maximize the energy absorption while constraining the structural mass. In this research, the presence or absence of inner walls were taken as design variables. To deal with such a highly nonlinear problem, a heuristic design methodology was proposed based on a modified artificial bee colony (ABC) algorithm, in which a constraint-driven mechanism was introduced to determine adjacent food sources for scout bees and neighborhood sources for employed and onlooker bees. The fitness function was customized according to the violation or the satisfaction of the constraints. This modified ABC algorithm was first verified by a square tube with seven design variables and then applied to four other examples with more design variables. The results demonstrated that the proposed heuristic algorithm is capable of handling the topology optimization of multicell tubes under out-of-plane crushing. They also confirmed that the optimized topological designs tend to allocate the material at the corners and around the outer walls. Moreover, the modified ABC algorithm was found to perform better than a genetic algorithm (GA) and traditional ABC in terms of best, worst, and average designs and the probability of obtaining the true optimal topological configuration.
Fang, K, Wang, X, Tomamichel, M & Duan, R 2017, 'Non-asymptotic entanglement distillation', IEEE Transactions on Information Theory, vol. 65, no. 10, pp. 6454-6465.
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Entanglement distillation, an essential quantum information processing task,refers to the conversion from multiple copies of noisy entangled states to asmaller number of highly entangled states. In this work, we study thenon-asymptotic fundamental limits for entanglement distillation. We investigatethe optimal tradeoff between the distillation rate, the number of preparedstates, and the error tolerance. First, we derive the one-shot distillableentanglement under completely positive partial transpose preserving operationsas a semidefinite program and demonstrate an exact characterization via thequantum hypothesis testing relative entropy. Second, we establish efficientlycomputable second-order estimations of the distillation rate for generalquantum states. In particular, we provide explicit as well as approximateevaluations for various quantum states of practical interest, including purestates, mixture of Bell states, maximally correlated states and isotropicstates.
Fang, XS, Sheng, QZ, Wang, X, Ngu, AHH & Zhang, Y 2017, 'GrandBase: generating actionable knowledge from Big Data', PSU Research Review, vol. 1, no. 2, pp. 105-126.
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PurposeThis paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.Design/methodology/approachIn particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.FindingsEmpirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.Originality/valueTo revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has ...
Fang, Z, Ni, W, Liang, F, Shao, P & Wu, Y 2017, 'Massive MIMO for Full-Duplex Cellular Two-Way Relay Network: A Spectral Efficiency Study', IEEE Access, vol. 5, pp. 23288-23298.
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© 2017 IEEE. This paper presents the new analysis of the applications of massive multiple-input-multiple-output (MIMO) in full-duplex (FD) cellular two-way relay networks, and sheds valuable insights on the interactions between massive MIMO, and relay and duplex modes. Practical scenarios are considered, where massive MIMO is deployed at the base station and the relay station. Based on generic relay modes, namely, antenna-selection-based decode-and-forward (DF) relay and signal-space alignment based amplify-and-forward (AF) relay, closed-form expressions for the asymptotic signal-to-interference-plus-noise ratios (SINRs) are derived. The difference between AF and DF in the FD mode is quantified, and so is that between FD and half-duplex (HD) under the two relay modes. With massive MIMO, the superiority of DF in the FD mode is confirmed in terms of spectral efficiency. The sufficient conditions for the FD mode to outperform the HD mode are identified. The effectiveness of massive MIMO in terms of self-loop interference cancellation and inter-user interference suppression is proved. All these insightful findings are corroborated by simulations.
Far, H & Flint, D 2017, 'Significance of using isolated footing technique for residential construction on expansive soils', Frontiers of Structural and Civil Engineering, vol. 11, no. 1, pp. 123-129.
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Expansive soils cause problems with the founding of lightly loaded structures in many parts of the world. Foundation design for expansive soils is one of the most discussed and problematic issues in Australia as expansive soils were responsible for billions of dollars’ worth of damage to man-made structures such as buildings and roads. Several studies and reports indicate that one of the most common and least recognized problems causing severe structural damage to houses lies in expansive soils. In this study, a critical review has been carried out on the current Australian standards for building on expansive soils and they are compared with some techniques that are not included in the current Australian standards for residential slabs and footings. Based on the results of this review, the most effective and economical method has been proposed for construction of footings on all site classifications without restriction to 75mm of characteristic movement. In addition, it has become apparent that as design procedures for footings resting on sites with extreme characteristic movements are not included in the current Australian standards, there is a strong need for well-developed and simplified standard design procedures for characteristic soil movement of greater than 75mm to be included into the Australian Standards.
Far, H, Saleh, A & Firouzianhaji, A 2017, 'A simplified method to determine shear stiffness of thin walled cold formed steel storage rack frames', Journal of Constructional Steel Research, vol. 138, pp. 799-805.
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© 2017 Elsevier Ltd The shear stiffness of braced frames of thin-walled cold-formed steel storage racks was experimentally and numerically investigated in order to establish the effect of connection flexibility on the accuracy of different analysis methods. The analyses which included a detailed 3D Finite Element model, a 2D frame analysis with beam elements and a simple hand calculation indicated significant variation of results compared with experimental values. A simplified modelling approach for 2D elastic analysis of braced frames was proposed. The approach is aimed at practical applications to account for the flexibility in bolted connections and leads to better approximation of the shear stiffness.
Faria, AF, Liu, C, Xie, M, Perreault, F, Nghiem, LD, Ma, J & Elimelech, M 2017, 'Thin-film composite forward osmosis membranes functionalized with graphene oxide–silver nanocomposites for biofouling control', Journal of Membrane Science, vol. 525, pp. 146-156.
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© 2016 Elsevier B.V. Innovative approaches to prevent bacterial attachment and biofilm growth on membranes are critically needed to avoid decreasing membrane performance due to biofouling. In this study, we propose the fabrication of anti-biofouling thin-film composite membranes functionalized with graphene oxide–silver nanocomposites. In our membrane modification strategy, carboxyl groups on the graphene oxide–silver nanosheets are covalently bonded to carboxyl groups on the surface of thin-film composite membranes via a crosslinking reaction. Further characterization, such as scanning electron microscopy and Raman spectroscopy, revealed the immobilization of graphene oxide–silver nanocomposites on the membrane surface. Graphene oxide–silver modified membranes exhibited an 80% inactivation rate against attached Pseudomonas aeruginosa cells. In addition to a static antimicrobial assay, our study also provided insights on the anti-biofouling property of forward osmosis membranes during dynamic operation in a cross-flow test cell. Functionalization with graphene oxide–silver nanocomposites resulted in a promising anti-biofouling property without sacrificing the membrane intrinsic transport properties. Our results demonstrated that the use of graphene oxide–silver nanocomposites is a feasible and attractive approach for the development of anti-biofouling thin-film composite membranes.
Farrok, O, Islam, MR, Sheikh, MRI, Guo, YG & Zhu, JG 2017, 'Design and Analysis of a Novel Lightweight Translator Permanent Magnet Linear Generator for Oceanic Wave Energy Conversion', IEEE Transactions on Magnetics, vol. 53, no. 11, pp. 1-4.
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© 1965-2012 IEEE. At present, most of the linear generators contain a heavy translator for converting wave power from the ocean into electrical power. As the translator is connected to the buoy, the buoy dynamic performance is reduced by the large mass and, as a result, low velocity of the translator would degrade the electricity generation of the linear generator. This problem has been minimized by the new design in this paper, where the translator is clipped off at first and split into two separate portions to minimize its weight. The secondary stator is magnetically coupled with a special m-shaped main stator which is used to flow the necessary magnetic flux. The weight of the proposed translator is 21.82% lower than that of conventional one and 49.1% by using a recently available permanent magnet with higher specifications. The finite-element method is applied in ANSYS simulation environment for the analysis and comparison between the proposed and conventional designs. Different parameters of the conventional and the proposed linear generator have been discussed in this paper. The simulation results show that the proposed design can generate the same amount of electricity as the existing one with almost half of the translator size. According to the mathematical model, it is understood that the dynamics of the translator would be higher for its lower mass and vice versa. Therefore, minimizing the translator size would result in decrease of mass, which increases the dynamics of the buoy connected to the translator.
Fasugba, O, Koerner, J, Mitchell, BG & Gardner, A 2017, 'Meatal cleaning with antiseptics for the prevention of catheter-associated urinary tract infections: A discussion paper', Infection, Disease & Health, vol. 22, no. 3, pp. 136-143.
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Fasugba, O, Koerner, J, Mitchell, BG & Gardner, A 2017, 'Systematic review and meta-analysis of the effectiveness of antiseptic agents for meatal cleaning in the prevention of catheter-associated urinary tract infections', Journal of Hospital Infection, vol. 95, no. 3, pp. 233-242.
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Feng, B, Zhang, H, Zhou, H & Yu, S 2017, 'Locator/Identifier Split Networking: A Promising Future Internet Architecture', IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2927-2948.
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The Internet has achieved unprecedented success in human history. However, its original design has encountered many challenges in the past decades due to the significant changes of context and requirements. As a result, the design of future networks has received great attention from both academia and industry, and numerous novel architectures have sprung up in recent years. Among them, the locator/identifier (Loc/ID) split networking is widely discussed for its decoupling of the overloaded IP address semantics, which satisfies several urgent needs of the current Internet such as mobility, multi-homing, routing scalability, security, and heterogeneous network convergence. Hence, in this paper, we focus on Loc/ID split network architectures, and provide a related comprehensive survey on their principles, mechanisms, and characteristics. First, we illustrate the major serious problems of the Internet caused by the overloading of IP address semantics. Second, we classify the existing Loc/ID split network architectures based on their properties, abstract the general principle and framework for each classification, and demonstrate related representative architectures in detail. Finally, we summarize the fundamental features of the Loc/ID split networking, compare corresponding investigated architectures, and discuss several open issues and opportunities.
Feng, J, Wu, D, Gao, W & Li, G 2017, 'Uncertainty analysis for structures with hybrid random and interval parameters using mathematical programming approach', Applied Mathematical Modelling, vol. 48, pp. 208-232.
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© 2017 Elsevier Inc. A novel computational method, namely the unified perturbation mathematical programming (UPMP) approach, for hybrid uncertainty analysis of engineering structures is proposed in this paper. The presented study considers a mixture of random and interval system parameters which are frequently encountered in engineering applications. Within the UPMP approach, matrix perturbation theory is adopted in combination with the mathematical programming approach. The proposed computational method provides a non-simulative hybrid uncertainty analysis framework, which is competent to offer the extreme bounds of the statistical characteristics (i.e., mean and variance) of any concerned structural responses in computationally tractable fashion. In order to thoroughly explore various intricate aspects of the engineering system involving hybrid uncertainties, systematic numerical experiments have also been conducted. Diverse statistical analyses are implemented to identify the bounded probability profile of the uncertain structural responses. Both academic and practical engineering structures are investigated to justify the applicability, accuracy and efficiency of the proposed UPMP approach.
Figtree, GA, Bubb, KJ, Tang, O, Kizana, E & Gentile, C 2017, 'Vascularized Cardiac Spheroids as Novel 3D in vitro Models to Study Cardiac Fibrosis', Cells Tissues Organs, vol. 204, no. 3-4, pp. 191-198.
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Spheroid cultures are among the most explored cellular biomaterials used in cardiovascular research, due to their improved integration of biochemical and physiological features of the heart in a defined architectural three-dimensional microenvironment when compared to monolayer cultures. To further explore the potential use of spheroid cultures for research, we engineered a novel in vitro model of the heart with vascularized cardiac spheroids (VCSs), by coculturing cardiac myocytes, endothelial cells, and fibroblasts isolated from dissociated rat neonatal hearts (aged 1-3 days) in hanging drop cultures. To evaluate the validity of VCSs in recapitulating pathophysiological processes typical of the in vivo heart, such as cardiac fibrosis, we then treated VCSs with transforming growth factor beta 1 (TGFβ1), a known profibrotic agent. Our mRNA analysis demonstrated that TGFβ1-treated VCSs present elevated levels of expression of connective tissue growth factor, fibronectin, and TGFβ1 when compared to control cultures. We demonstrated a dramatic increase in collagen deposition following TGFβ1 treatment in VCSs in the PicroSirius Red-stained sections. Doxorubicin, a renowned cardiotoxic and profibrotic agent, triggered apoptosis and disrupted vascular networks in VCSs. Taken together, our findings demonstrate that VCSs are a valid model for the study of the mechanisms involved in cardiac fibrosis, with the potential to be used to investigate novel mechanisms and therapeutics for treating and preventing cardiac fibrosis in vitro.
Fitz-Walter, Z, Johnson, D, Wyeth, P, Tjondronegoro, D & Scott-Parker, B 2017, 'Driven to drive? Investigating the effect of gamification on learner driver behavior, perceived motivation and user experience', Computers in Human Behavior, vol. 71, pp. 586-595.
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Fontugne, R, Abry, P, Fukuda, K, Veitch, D, Cho, K, Borgnat, P & Wendt, H 2017, 'Scaling in Internet Traffic: A 14 Year and 3 Day Longitudinal Study, With Multiscale Analyses and Random Projections', IEEE/ACM Transactions on Networking, vol. 25, no. 4, pp. 2152-2165.
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© 2017 IEEE. In the mid 1990s, it was shown that the statistics of aggregated time series from Internet traffic departed from those of traditional short range-dependent models, and were instead characterized by asymptotic self-similarity. Following this seminal contribution, over the years, many studies have investigated the existence and form of scaling in Internet traffic. This contribution first aims at presenting a methodology, combining multiscale analysis (wavelet and wavelet leaders) and random projections (or sketches), permitting a precise, efficient and robust characterization of scaling, which is capable of seeing through non-stationary anomalies. Second, we apply the methodology to a data set spanning an unusually long period: 14 years, from the MAWI traffic archive, thereby allowing an in-depth longitudinal analysis of the form, nature, and evolutions of scaling in Internet traffic, as well as network mechanisms producing them. We also study a separate three-day long trace to obtain complementary insight into intra-day behavior. We find that a biscaling (two ranges of independent scaling phenomena) regime is systematically observed: long-range dependence over the large scales, and multifractallike scaling over the fine scales. We quantify the actual scaling ranges precisely, verify to high accuracy the expected relationship between the long range dependent parameter and the heavy tail parameter of the flow size distribution, and relate fine scale multifractal scaling to typical IP packet inter-arrival and to round-trip time distributions.
Forouzesh, M, Siwakoti, YP, Gorji, SA, Blaabjerg, F & Lehman, B 2017, 'Step-Up DC–DC Converters: A Comprehensive Review of Voltage-Boosting Techniques, Topologies, and Applications', IEEE Transactions on Power Electronics, vol. 32, no. 12, pp. 9143-9178.
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© 1986-2012 IEEE. DC-DC converters with voltage boost capability are widely used in a large number of power conversion applications, from fraction-of-volt to tens of thousands of volts at power levels from milliwatts to megawatts. The literature has reported on various voltage-boosting techniques, in which fundamental energy storing elements (inductors and capacitors) and/or transformers in conjunction with switch(es) and diode(s) are utilized in the circuit. These techniques include switched capacitor (charge pump), voltage multiplier, switched inductor/voltage lift, magnetic coupling, and multistage/-level, and each has its own merits and demerits depending on application, in terms of cost, complexity, power density, reliability, and efficiency. To meet the growing demand for such applications, new power converter topologies that use the above voltage-boosting techniques, as well as some active and passive components, are continuously being proposed. The permutations and combinations of the various voltage-boosting techniques with additional components in a circuit allow for numerous new topologies and configurations, which are often confusing and difficult to follow. Therefore, to present a clear picture on the general law and framework of the development of next-generation step-up dc-dc converters, this paper aims to comprehensively review and classify various step-up dc-dc converters based on their characteristics and voltage-boosting techniques. In addition, the advantages and disadvantages of these voltage-boosting techniques and associated converters are discussed in detail. Finally, broad applications of dc-dc converters are presented and summarized with comparative study of different voltage-boosting techniques.
From, CS, Sauret, E, Armfield, SW, Saha, SC & Gu, YT 2017, 'Turbulent dense gas flow characteristics in swirling conical diffuser', Computers & Fluids, vol. 149, pp. 100-118.
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© 2017 Elsevier Ltd Diffusers placed at the exit of turbines are essential to recover pressure and increase turbine efficiency. This increase of efficiency is critical for the overall cycle efficiency of renewable power cycles based on low temperature renewable resources. Optimising the performance of a conical diffuser in renewable power cycles using high-density fluids can be established by examining the turbulence characteristics of both air considered as an ideal gas (IG) and R143a, a refrigerant with high-density in a non-ideal state, considered as a real gas (RG). Turbulence was firstly modelled and validated against experimental results from the ERCOFTAC swirling conical diffuser database and previous numerical results. The real gas thermodynamic and transport properties of refrigerant R143a were then obtained from the NIST REFPROP database. Investigating both RG and IG revealed that general trends remain, where the stronger wall components in RG help improve the diffuser performance. Furthermore, investigations regarding turbulence intensities indicated a clear effect on the flow behaviour for IG while being ineffective on the RG. The final application analysed the diffuser performance using the inlet conditions extracted directly from a potential radial-inflow turbine working with R143a. The change of conditions highlighted that radial components can be reduced, and thus the swirling number too. By implementing the first numerical study on real gas swirling conical diffuser, it was established that real gas flow regimes differ from the ones previously established for ideal gas, and thus preliminary flow regimes for R143a, specifically, are proposed.
Fu, L, Morsch, M, Shi, B, Wang, G, Lee, A, Radford, R, Lu, Y, Jin, D & Chung, R 2017, 'A versatile upconversion surface evaluation platform for bio–nano surface selection for the nervous system', Nanoscale, vol. 9, no. 36, pp. 13683-13692.
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There is considerable interest in developing diagnostic nanotools for early detection and delivery of various therapeutic agents for treatment of neurodegenerative diseases.
Fu, Q, Ruan, Q, McKenzie, TG, Reyhani, A, Tang, J & Qiao, GG 2017, 'Development of a Robust PET-RAFT Polymerization Using Graphitic Carbon Nitride (g-C3N4)', Macromolecules, vol. 50, no. 19, pp. 7509-7516.
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The metal-free semiconductor, graphitic carbon nitride (g-C3N4), was introduced into RAFT polymerization for the first time. The production of linear polyacrylate and polyacrylamide has been achieved via PET-RAFT polymerization using g-C3N4 as a photoactive organocatalyst without prior deoxygenation. The resulting polymers display controlled molecular weights, narrow polymer dispersities, and high end-group fidelity as exemplified by 1H NMR analysis, MALDI-TOF-MS measurement, and chain extension experiment. Temporal control is illustrated by intermittent light and dark cycles, with polymer growth arrested in the absence of irradiation. The effects of changing RAFT agents (i.e., trithiocarbonates), solvents, catalyst concentrations, and degrees of polymerization in this system have been investigated. The successful polymerization of nonpurified monomer (i.e., still containing radical inhibitors) demonstrates the robust nature of the presented PET-RAFT system.
Fu, Q, Xie, K, McKenzie, TG & Qiao, GG 2017, 'Trithiocarbonates as intrinsic photoredox catalysts and RAFT agents for oxygen tolerant controlled radical polymerization', Polymer Chemistry, vol. 8, no. 9, pp. 1519-1526.
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In this study, we reported on the discovery that trithiocarbonates (RAFT agents) can act as intrinsic photocatalyst to significantly reduce the oxygen level in a controlled radical polymerization under visible light irridation.
Fu, W, Zhang, C, Sun, L, Askari, M, Samali, B, Chung, K & Sharafi, P 2017, 'Experimental Investigation of a Base Isolation System Incorporating MR Dampers with the High-Order Single Step Control Algorithm', Applied Sciences, vol. 7, no. 4, pp. 344-344.
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The conventional isolation structure with rubber bearings exhibits large deformation characteristics when subjected to infrequent earthquakes, which may lead to failure of the isolation layer. Although passive dampers can be used to reduce the layer displacement, the layer deformation and superstructure acceleration responses will increase in cases of fortification earthquakes or frequently occurring earthquakes. In addition to secondary damages and loss of life, such excessive displacement results in damages to the facilities in the structure. In order to overcome these shortcomings, this paper presents a structural vibration control system where the base isolation system is composed of rubber bearings with magnetorheological (MR) damper and are regulated using the innovative control strategy. The high-order single-step algorithm with continuity and switch control strategies are applied to the control system. Shaking table test results under various earthquake conditions indicate that the proposed isolation method, compared with passive isolation technique, can effectively suppress earthquake responses for acceleration of superstructure and deformation within the isolation layer. As a result, this structural control method exhibits excellent performance, such as fast computation, generic real-time control, acceleration reduction and high seismic energy dissipation etc. The relative merits of the continuity and switch control strategies are also compared and discussed.
Fujioka, T, Kodamatani, H, Aizawa, H, Gray, S, Ishida, KP & Nghiem, LD 2017, 'Role of membrane fouling substances on the rejection of N-nitrosamines by reverse osmosis', Water Research, vol. 118, pp. 187-195.
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The impact of fouling substances on the rejection of four N-nitrosamines by a reverse osmosis (RO) membrane was evaluated by characterizing individual organic fractions in a secondary wastewater effluent and deploying a novel high-performance liquid chromatography-photochemical reaction-chemiluminescence (HPLC-PR-CL) analytical technique. The HPLC-PR-CL analytical technique allowed for a systematic examination of the correlation between the fouling level and the permeation of N-nitrosamines in the secondary wastewater effluent and synthetic wastewaters through an RO membrane. Membrane fouling caused by the secondary wastewater effluent led to a notable decrease in the permeation of N-nitrosodimethylamine (NDMA) while a smaller but nevertheless discernible decrease in the permeation of N-nitrosomethylethylamine (NMEA), N-nitrosopyrrolidine (NPYR) and N-nitrosomorpholine (NMOR) was also observed. Fluorescence spectrometry analysis revealed that major foulants in the secondary wastewater effluent were humic and fulvic acid-like substances. Analysis using the size exclusion chromatography technique also identified polysaccharides and proteins as additional fouling substances. Thus, further examination was conducted using solutions containing model foulants (i.e., sodium alginate, bovine serum albumin, humic acid and two fulvic acids). Similar to the secondary wastewater effluent, membrane fouling with fulvic acid solutions resulted in a decrease in N-nitrosamine permeation. In contrast, membrane fouling with the other model foulants resulted in a negligible impact on N-nitrosamine permeation. Overall, these results suggest that the impact of fouling on the permeation of N-nitrosamines by RO is governed by specific small organic fractions (e.g. fulvic acid-like organics) in the secondary wastewater effluent.
Gadalla, BS, Schaltz, E, Siwakoti, Y & Blaabjerg, F 2017, 'Analysis of loss distribution of Conventional Boost, Z-source and Y-source Converters for wide power and voltage range', Transactions on Environment and Electrical Engineering, vol. 2, no. 1, pp. 1-1.
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Boost converters are needed in many applications which require the output voltage to be higher than the input voltage. Recently, boost type converters have been applied for industrial applications, and hence it has become an interesting topic of research. Many researchers proposed different impedance source converters with their unique advantages as having a high voltage gain in a small range of duty cycle ratio. However, the thermal behaviour of the semiconductor devices and passive elements in the impedance source converter is an important issue from a reliability point of view and it has not been investigated yet. Therefore, this paper presents a comparison between the conventional boost, the Z-source, and the Y-source converters based on a thermal evaluation of the semiconductors. In addition, the three topologies are also compared with respect to their efficiency. In this study the results show that the boost converter has higher efficiency than the Zsource and Y-source converter for these specific voltage gain of 2 and 4. The operational principle, mathematical derivations, simulation results and final comparisons are presented in this paper.
Gandomi, AH, Alavi, AH, Gandomi, M & Kazemi, S 2017, 'Formulation of shear strength of slender RC beams using gene expression programming, part II: With shear reinforcement', Measurement, vol. 95, pp. 367-376.
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In this study, a new variant of genetic programming, namely gene expression programming (GEP) is utilized to predict the shear strength of reinforced concrete (RC) beams with stirrups. The derived model relates the shear strength to mechanical and geometrical properties. The model is developed using a database containing 466 experimental test results gathered from the literature. Sensitivity and parametric analyses are performed for further verification of the model. The comparative study proves the superior performance of the GEP model compared to the expressions developed in several codes of practice.
Gandomi, AH, Kashani, AR & Zeighami, F 2017, 'Retaining wall optimization using interior search algorithm with different bound constraint handling', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 41, no. 11, pp. 1304-1331.
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Along with the applicability of optimization algorithms, there are lots of features that can affect the functioning of the optimization techniques. The main purpose of this paper is investigating the significance of boundary constraint handling (BCH) schemes on the performance of optimization algorithms. To this end, numbers of deterministic and probabilistic BCH approaches are applied to one of the most recent proposed optimization techniques, named interior search algorithm (ISA). Apart from the implementing different BCH methods, a sensitivity analysis is conducted to find an appropriate setting for the only parameter of ISA. Concrete cantilever retaining wall design as one of the most important geotechnical problems is tackled to declare proficiency of the ISA algorithm, on the one hand, and benchmark the effect of BCH schemes on the final results, on the contrary. As results demonstrate, various BCH approaches have a perceptible impact on the algorithm performance. In like manner, the essential parameter of ISA can also play a pivotal role in this algorithm's efficiency. Copyright © 2017 John Wiley & Sons, Ltd.
Gandomi, AH, Kashani, AR, Mousavi, M & Jalalvandi, M 2017, 'Slope stability analysis using evolutionary optimization techniques', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 41, no. 2, pp. 251-264.
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SummarySlope stability optimization, in the presence of a band of a weak layer between two strong layers, is accounted for in complicated geotechnical problems. Classical optimization algorithms are not suitable for solving such problems as they need a proper preliminary solution to converge to a valid result. Therefore, it is necessary to find a proper algorithm which is capable of finding the best global solution. Recently a lot of metaheuristic algorithms have been proposed which are able to evade local minima effectively. In this study four evolutionary algorithms, including well‐known and recent ones, such as genetic algorithm, differential evolution, evolutionary strategy and biogeography‐based optimization (BBO), are applied in slope stability analysis and their efficiencies are explored by three benchmark case studies. Result show BBO is the most efficient among these evolutionary algorithms and other proposed algorithms applied to this problem. Copyright © 2016 John Wiley & Sons, Ltd.
Gandomi, AH, Kashani, AR, Roke, DA & Mousavi, M 2017, 'Optimization of retaining wall design using evolutionary algorithms', Structural and Multidisciplinary Optimization, vol. 55, no. 3, pp. 809-825.
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This paper explores the performance of three evolutionary optimization methods, differential evolution (DE), evolutionary strategy (ES) and biogeography based optimization algorithm (BBO), for nonlinear constrained optimum design of a cantilever retaining wall. These algorithms are based on biological contests for survival and reproduction. The retaining wall optimization problem consists of two criteria, geotechnical stability and structural strength, while the final design minimizes an objective function. The objective function is defined in terms of both cost and weight. Constraints are applied using the penalty function method. The efficiency of the proposed method is examined by means of two numerical retaining wall design examples, one with a base shear key and one without a base shear key. The final designs are compared to the ones determined by genetic algorithms as classical metaheuristic optimization methods. The design results and convergence rate of the BBO algorithm show a significantly better performance than the other algorithms in both design cases.
Gao, H, Wu, B, Xu, D, Aguilera, RP & Acuna, P 2017, 'Model Predictive Switching Pattern Control for Current-Source Converters With Space-Vector-Based Selective Harmonic Elimination', IEEE Transactions on Power Electronics, vol. 32, no. 8, pp. 6558-6569.
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© 2017 IEEE. This paper presents a model predictive switching pattern control (MPSPC) for a current-source converter (CSC), which achieves superb low-order harmonics elimination performance in steady state and improved transient responses. Based on a proposed space-vector-based selective harmonic elimination (SHE) method and prediction of load current at the next sampling instant, MPSPC prefers to following a precalculated SHE-pulse width modulation (PWM) pattern in steady state, and governing the CSC through a model predictive control (MPC) approach during transients. In comparison with existing schemes, the advantages of MPSPC are threefold: First, quantization error, introduced by a constant sampling frequency in MPC and degrading steady-state low-order harmonic elimination, is mitigated in the proposed scheme. Second, there is no weighting factor in the cost function, as used in existing schemes. Finally, MPSPC is totally realized based on one-step prediction, which simplifies the structure of the scheme. Both simulation and experimental results verify the steady state and dynamic performance of MPSPC with different SHE-PWM patterns.
Gao, H, Wu, B, Xu, D, Pande, M & Aguilera, RP 2017, 'Common-Mode-Voltage-Reduced Model-Predictive Control Scheme for Current-Source-Converter-Fed Induction Motor Drives', IEEE Transactions on Power Electronics, vol. 32, no. 6, pp. 4891-4904.
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© 2016 IEEE. Common-mode voltages (CMVs) in a motor drive system could damage the motor insulation and induce destructive bearing current, especially at medium-voltage (MV) level. Various reduced CMV space vector modulation (RCMV SVM) methods have been proposed for current-source converter (CSC)-fed motor drives. However, no matter what kind of RCMV SVM methods, the CMV peak value can only be reduced to no larger than summation of half peak values of capacitor phase voltages at both rectifier and inverter sides, since only zero-state vectors with higher CMV values are eliminated. In this paper, a CMV reduced model-predictive control (RCMV-MPC) is proposed to further mitigate the CMV peak value through selecting optimal space vectors for both current-source rectifier and current-source inverter simultaneously. A novel unified cost function is developed to realize both rectifier- and inverter-side reference tracks and CMV peak value further reduction at the same time. With RCMV-MPC, the CMV peak value in a CSC-fed induction motor drive can be further reduced inside a calculated CMV peak value limitation. In fact, the CMV peak value of RCMV-MPC can be reduced to nearly 60% of that in existing zero-state vector selection-based RCMV SVM methods. Besides, satisfactory performance on reference tracks, especially during transients, is also guaranteed based on the unified cost function. Simulation results in a high-power MV CSC-fed IM drive (1 MW, 4160 V), and experiments in a low-power prototype (5 kW, 208 V) verify the effectiveness of RCMV-MPC.
Gao, H, Wu, B, Xu, DD, Pande, M & Aguilera, RP 2017, 'Model predictive control scheme with active damping function for current source rectifiers', IET Power Electronics, vol. 10, no. 7, pp. 717-725.
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This study presents a model predictive control (MPC) with active damping function for current‐source rectifiers (CSRs). Since optimal modulating vector selection process of MPC leads to spread harmonic distribution in pulse‐width‐modulated (PWM) waveform, inductor‐capacitor (LC) resonance can be easily excited. Conventional MPC was designed without the consideration of active damping, since it is for low‐power CSRs with large line resistors physically connected inside the circuit, whereas the proposed scheme achieves active damping function through a specially developed cost function, which realizes active damping function even for high‐power CSRs with lightly damped LC circuit. In comparison with conventional MPC, the advantages of the proposed scheme are three‐fold: first, the proposed scheme is totally based on MPC concept, without conventional linear controller used. Second, with the active damping term added in the developed cost function, active damping effect can be involved into MPC, which extends MPC to high‐power CSRs with lightly damped LC circuit. Last but not least, the proposed scheme is realized in the dq‐axis synchronous frame, which allows the use of simple low‐pass filters instead of complex band‐stop filters to obtain the damping current.
Gao, K, Gao, W, Wu, D & Song, C 2017, 'Nonlinear dynamic characteristics and stability of composite orthotropic plate on elastic foundation under thermal environment', Composite Structures, vol. 168, pp. 619-632.
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An analytical computational scheme for nonlinear dynamic characteristics and stability of an eccentrically composite orthotropic plate on Winkler-Pasternak elastic foundation subjected to different axial velocities is proposed with the incorporation of mercurial damping effects under thermal environment. Incorporating the classical plate theory and Von-Kármán strain-displacement relation, the nonlinear compatibility equation is derived. The Galerkin method and Airy's stress function are implemented to establish the nonlinear dynamic buckling equation accommodating the thermal and damping effects. Then the developed nonlinear differential equations are solved numerically by the fourth-order Runge-Kutta method. The characteristics of natural frequency, linear and nonlinear vibration, frequency-amplitude curve and nonlinear dynamic responses are investigated by the developed approach with validations by other literatures. The nonlinear dynamic buckling loads are determined by using Budiansky-Roth criterion. Additionally, various effects of velocity, damping ratio, temperature change, buckling mode, initial imperfection and foundation parameter on nonlinear dynamic buckling of the orthotropic plate are discussed.
Gao, K, Gao, W, Wu, D & Song, C 2017, 'Nonlinear dynamic stability analysis of Euler–Bernoulli beam–columns with damping effects under thermal environment', Nonlinear Dynamics, vol. 90, no. 4, pp. 2423-2444.
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© 2017, Springer Science+Business Media B.V. In this study, a unified nonlinear dynamic buckling analysis for Euler–Bernoulli beam–columns subjected to constant loading rates is proposed with the incorporation of mercurial damping effects under thermal environment. Two generalized methods are developed which are competent to incorporate various beam geometries, material properties, boundary conditions, compression rates, and especially, the damping and thermal effects. The Galerkin–Force method is developed by implementing Galerkin method into force equilibrium equations. Then for solving differential equations, different buckled shape functions were introduced into force equilibrium equations in nonlinear dynamic buckling analysis. On the other hand, regarding the developed energy method, the governing partial differential equation for dynamic buckling of beams is also derived by meticulously implementing Hamilton’s principles into Lagrange’s equations. Consequently, the dynamic buckling analysis with damping effects under thermal environment can be adequately formulated as ordinary differential equations. The validity and accuracy of the results obtained by the two proposed methods are rigorously verified by the finite element method. Furthermore, comprehensive investigations on the structural dynamic buckling behavior in the presence of damping effects under thermal environment are conducted.
Gao, L, Luan, TH, Yu, S, Zhou, W & Liu, B 2017, 'FogRoute: DTN-based Data Dissemination Model in Fog Computing', IEEE Internet of Things Journal, vol. 4, no. 1, pp. 1-1.
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Fog computing, known as 'cloud closed to ground,' deploys light-weight compute facility, called Fog servers, at the proximity of mobile users. By precatching contents in the Fog servers, an important application of Fog computing is to provide high-quality low-cost data distributions to proximity mobile users, e.g., video/live streaming and ads dissemination, using the single-hop low-latency wireless links. A Fog computing system is of a three tier Mobile-Fog-Cloud structure; mobile user gets service from Fog servers using local wireless connections, and Fog servers update their contents from Cloud using the cellular or wired networks. This, however, may incur high content update cost when the bandwidth between the Fog and Cloud servers is expensive, e.g., using the cellular network, and is therefore inefficient for nonurgent, high volume contents. How to economically utilize the Fog-Cloud bandwidth with guaranteed download performance of users thus represents a fundamental issue in Fog computing. In this paper, we address the issue by proposing a hybrid data dissemination framework which applies software-defined network and delay-tolerable network (DTN) approaches in Fog computing. Specifically, we decompose the Fog computing network with two planes, where the cloud is a control plane to process content update queries and organize data flows, and the geometrically distributed Fog servers form a data plane to disseminate data among Fog servers with a DTN technique. Using extensive simulations, we show that the proposed framework is efficient in terms of data-dissemination success ratio and content convergence time among Fog servers.
Gao, X, Du, J, Zhang, T & Guo, YJ 2017, 'Noise and conversion performance of a high-Tc superconducting Josephson junction mixer at 0.6 THz', Applied Physics Letters, vol. 111, no. 19, pp. 192603-192603.
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This letter presents both theoretical and experimental investigations on the noise and conversion performance of a high-Tc superconducting (HTS) step-edge Josephson-junction mixer at the frequency of 0.6 THz and operating temperatures of 20–40 K. Based on the Y-factor and U-factor methods, a double-sideband noise temperature of around 1000 K and a conversion gain of −3.5 dB were experimentally obtained at 20 K. At the temperature of 40 K, the measured mixer noise and conversion efficiency are around 2100 K and −10 dB, respectively. The experimental data are in good agreement with the numerical analysis results using the three-port model. A detailed performance comparison with other reported HTS terahertz mixers has confirmed the superior performance of our presented mixer device.
Gao, X, Du, J, Zhang, T, Jay Guo, Y & Foley, CP 2017, 'Experimental Investigation of a Broadband High-Temperature Superconducting Terahertz Mixer Operating at Temperatures Between 40 and 77 K', Journal of Infrared, Millimeter, and Terahertz Waves, vol. 38, no. 11, pp. 1357-1367.
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© 2017, Springer Science+Business Media, LLC. This paper presents a systematic investigation of a broadband thin-film antenna-coupled high-temperature superconducting (HTS) terahertz (THz) harmonic mixer at relatively high operating temperature from 40 to 77 K. The mixer device chip was fabricated using the CSIRO established step-edge YBa 2 Cu 3 O 7-x (YBCO) Josephson junction technology, packaged in a well-designed module and cooled in a temperature adjustable cryocooler. Detailed experimental characterizations were carried out for the broadband HTS mixer at both the 200 and 600 GHz bands in harmonic mixing mode. The DC current-voltage characteristics (IVCs), bias current condition, local oscillator (LO) power requirement, frequency response, as well as conversion efficiency under different bath temperatures were thoroughly investigated for demonstrating the frequency down-conversion performance.
Gao, X, Zhang, T, Du, J, Weily, AR, Guo, YJ & Foley, CP 2017, 'A wideband terahertz high-Tcsuperconducting Josephson-junction mixer: electromagnetic design, analysis and characterization', Superconductor Science and Technology, vol. 30, no. 9, pp. 095011-095011.
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© 2017 IOP Publishing Ltd. This paper presents a wideband terahertz (THz) mixer based on a thin-film antenna-coupled high-temperature superconducting (HTS) YBa 2 Cu 3 O 7-x (YBCO) step-edge Josephson junction. The HTS mixer enables the flexible harmonic mixing operation at multiple THz bands with the same microwave local oscillator (LO) source, and features very wide intermediate-frequency or instantaneous bandwidth. In order to optimize the frequency down-conversion performance of the mixer, systematic electromagnetic design and analysis have been carried out to improve the power coupling of THz radiation as well as wideband transmission of microwave signals. Experimental characterization of a fabricated device prototype has demonstrated that the mixer exhibits good performance at both the 200 GHz and 600 GHz bands. Detailed measurement results including the DC characteristics, LO pumping requirement, frequency response, mixing linearity and conversion gain are presented in this paper.
Ge, XJ, Livesey, P, Wang, J, Huang, S, He, X & Zhang, C 2017, 'Deconstruction waste management through 3d reconstruction and bim: a case study', Visualization in Engineering, vol. 5, no. 1.
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AbstractThe construction industry is responsible for 50% of the solid waste generated worldwide. Governments around the world formulate legislation and regulations concerning recycling and re-using building materials, aiming to reduce waste and environmental impact. Researchers have also been developing strategies and models of waste management for construction and demolition of buildings. The application of Building Information Modeling (BIM) is an example of this. BIM is emergent technology commonly used to maximize the efficiency of design, construction and maintenance throughout the entire lifecycle. The uses of BIM on deconstruction or demolition are not common; especially the fixtures and fittings of buildings are not considered in BIM models. The development of BIM is based on two-dimensional drawings or sketches, which may not be accurately converted to 3D BIM models. In addition, previous researches mainly focused on construction waste management. There are few studies about the deconstruction waste management focusing on demolition. To fill this gap, this paper aims to develop a framework using a reconstructed 3D model with BIM, for the purpose of improving BIM accuracy and thus developing a deconstruction waste management system to improve demolition efficiency, effective recycling and cost savings. In particular, the developed as-built BIM will be used to identify and measure recyclable materials, as well as to develop a plan for the recycling process.
Gerami, A, Armstrong, RT, Johnston, B, Warkiani, ME, Mosavat, N & Mostaghimi, P 2017, 'Coal-on-a-Chip: Visualizing Flow in Coal Fractures', Energy & Fuels, vol. 31, no. 10, pp. 10393-10403.
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© 2017 American Chemical Society. Geomaterial microfluidics are the next generation of tools necessary for studying fluid flows related to subsurface engineering technologies. Traditional microfluidic devices do not capture surface wettability and roughness parameters that can have a significant influence on porous media flows. This is particularly important for coal seam gas reservoirs in which methane gas is transported through a well-developed system of natural fractures that display unique wettability and roughness characteristics. A coal geomaterial microfluidic device can be generated by etching a fracture pattern on a coal surface by using three-dimensional laser micromachining; however, it is unclear if the resulting surface properties are representative of real coal. In an effort to generate a realistic coal microfluidic device, we characterize coal surface roughness properties from real coal cleats. We then compare these results to the roughness of the patterns, generated from laser etching. Roughness measurements in real coal fractures show that cleats and microfractures are mostly oriented parallel to the coal beddings rather than perpendicular to the bedding, which is important when selecting coal for fabrication of a microfluidic device since we find that the natural microfractures influence the resulting roughness of etched fractures. We also compare resulting coal/brine/gas contact angles under static and dynamics conditions. The contact angle for coal is highly heterogeneous. Surface roughness and pore pressure may influence the contact angle. With the aid of the coal geomaterial device, the effect of these parameters on coal wettability can be explored and a range of possible coal contact angles can be visualized and represented. The geomaterial fabrication, as outlined herein, provides a tool to capture more realistic coal surface properties in microfluidics experiments.
Ghaffari Jadidi, M, Miro, JV & Dissanayake, G 2017, 'Warped Gaussian Processes Occupancy Mapping With Uncertain Inputs', IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 680-687.
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© 2017 IEEE. In this paper, we study extensions to the Gaussian processes (GPs) continuous occupancy mapping problem. There are two classes of occupancy mapping problems that we particularly investigate. The first problem is related to mapping under pose uncertainty and how to propagate pose estimation uncertainty into the map inference. We develop expected kernel and expected submap notions to deal with uncertain inputs. In the second problem, we account for the complication of the robot's perception noise using warped Gaussian processes (WGPs). This approach allows for non-Gaussian noise in the observation space and captures the possible nonlinearity in that space better than standard GPs. The developed techniques can be applied separately or concurrently to a standard GP occupancy mapping problem. According to our experimental results, although taking into account pose uncertainty leads, as expected, to more uncertain maps, by modeling the nonlinearities present in the observation space WGPs improve the map quality.
Gharib, M, Khezri, M, Foster, SJ & Castel, A 2017, 'Application of the meshless generalised RKPM to the transient advection-diffusion-reaction equation', Computers & Structures, vol. 193, pp. 172-186.
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Gheisari, S, Charlton, A, Catchpoole, DR & Kennedy, PJ 2017, 'Computers can classify neuroblastic tumours from histopathological images using machine learning', Pathology, vol. 49, pp. S72-S73.
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Gholami, MF, Daneshgar, F, Beydoun, G & Rabhi, FA 2017, 'Challenges in migrating legacy software systems to the cloud - an empirical study.', Inf. Syst., vol. 67, pp. 100-113.
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© 2017 Moving existing legacy systems to cloud platforms is a difficult and high cost process that may involve technical and non-technical resources and challenges. There is evidence that the lack of understanding and preparedness of cloud computing migration underpin many migration failures in achieving organisations’ goals. The main goal of this article is to identify the most important challenging activities for moving legacy systems to cloud platforms from a perspective of reengineering process. Through a combination of a bottom-up and a top-down analysis, a set of common activities is derived from the extant cloud computing literature. These are expressed as a model and are validated using a population of 104 shortlisted and randomly selected domain experts from different industry sectors. We used a Web-based survey questionnaire to collect data and analysed them using SPSS Sample T-Test. The results of this study highlight the most important and critical challenges that should be addressed by various roles within a legacy to cloud migration endeavour. The study provides an overall understanding of this process including common occurring activities, concerns and recommendations. In addition, the findings of this study constitute a practical guide to conduct this transition. This guide is platform agnostic and independent from any specific migration scenario, cloud platform, or an application domain.
Gholampour, A, Gandomi, AH & Ozbakkaloglu, T 2017, 'New formulations for mechanical properties of recycled aggregate concrete using gene expression programming', Construction and Building Materials, vol. 130, pp. 122-145.
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This paper presents new empirical models for prediction of the mechanical properties of recycled aggregate concrete (RAC) using gene expression programming (GEP) technique. A large and reliable test database containing the results of 650 compressive strength, 421 elastic modulus, 346 splitting tensile strength, and 152 flexural strength, tests of RACs containing no pozzolanic admixtures is collated through an extensive review of the literature. The performance of existing mechanical property models of RACs is then assessed using the database, and the results of this assessment are presented using selected statistical indicators. New expressions for the predictions of 28-day compressive strength, elastic modulus, flexural strength, and splitting tensile strength of RACs are developed based on the database. The assessment results indicate that the predictions of the proposed models are in close agreement with the test results, and the new models provide improved estimates of the mechanical properties of RACs compared to the existing models.
Ghosh, B, Fatahi, B & Khabbaz, H 2017, 'Analytical Solution to Analyze LTP on Column-Improved Soft Soil Considering Soil Nonlinearity', International Journal of Geomechanics, vol. 17, no. 3, pp. 04016082-04016082.
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© 2016 American Society of Civil Engineers. In this paper, a mechanical model to idealize the load-settlement response of the load transfer platform (LTP) on column-improved soft soil is proposed. This model simultaneously considers the nonlinear and time-dependent stress-strain behavior of soft soil and the negligible tensile strength of the granular material in LTP. The reinforced Timoshenko beam is adopted to model LTP to consider the shear and flexural deformations. Soft soil is idealized by a spring-dashpot system that includes nonlinear and time-dependent behaviors. The columns and geosynthetics are modeled with linear Winkler springs in the applied range of stresses and rough elastic membrane, respectively. The response function of LTP has been derived for distributed pressure loading in the plane strain condition. The principle of superposition is used to solve the fourth-order differential equations. Parametric studies indicate that the spacing of columns, thickness of LTP, degree of consolidation of the soft soil, and tensile stiffness of the geosynthetics significantly affect the behavior of LTP. This study also evaluates the accuracy of using reinforced Timoshenko theory by comparing the results with Pasternak and Euler-Bernoulli theories.
Ghosh, B, Fatahi, B, Khabbaz, H & Yin, J-H 2017, 'Analytical study for double-layer geosynthetic reinforced load transfer platform on column improved soft soil', Geotextiles and Geomembranes, vol. 45, no. 5, pp. 508-536.
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© 2017 The objective of this study is to propose a reasonably accurate mechanical model for double-layer geosynthetic reinforced load transfer platform (LTP) on column reinforced soft soil which can be used by practicing engineers. The developed model is very useful to study the behaviour of LTP resting on soft soil improved with conventional columns such as concrete columns, piles, and deep soil mixing columns. The negligible tensile strength of granular material in LTP, bending and shear deformations of LTP, compressibility and shearing of soft soil have been incorporated in the model. Furthermore, the results from the proposed model simulating the soft soil as Kerr foundation model are compared to the corresponding solutions when the soft soil is idealised by Winkler and Pasternak foundation models. It is observed from the comparison that the presented model can be used as a tool for a better prediction of the LTP behaviour with multi layers of geosynthetics, in comparison with the situation that soft soil is modelled by Winkler and Pasternak foundations. Furthermore, parametric studies show that as the column spacing increases, the maximum deflection of LTP and normalised tension in the geosynthetics also increase. Whereas, the maximum deflection of LTP and normalised tension in the geosynthetics decrease with increasing LTP thickness, stiffness of subsoil, and stiffness of geosynthetic reinforcement. In addition, it is observed that the use of one stronger geosynthetic layer (e.g. 1 × 2000 kN/m) with the equivalent stiffness of two geosynthetic layers (e.g. 2 × 1000 kN/m) does not result in the same settlement of LTP and the tension of the geosynthetic reinforcement when compared to two weaker geosynthetic layers.
Ghosh, S & Lee, JE-Y 2017, 'A Lorentz force magnetometer based on a piezoelectric-on-silicon square-extensional mode micromechanical resonator', Applied Physics Letters, vol. 110, no. 25.
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In this letter, we present a Lorentz force magnetic field sensor based on a thin-film piezoelectric-on-silicon (TPoS) CMOS-compatible resonator for the detection of an out-of-plane (perpendicular to the plane of fabrication) magnetic field. We here exploit the fundamental breathing mode of vibration in a suspended square plate, which is commonly referred to as the square-extensional (SE) mode. The symmetric stress profile of the SE mode avails stresses in the two orthogonal in-plane axes to be effectively coupled into a charge output through the piezoelectric transducers. This in turn enhances the output motional current from the device, which effectively determines the responsivity of the device. In this context, the responsivity has been defined as a ratio of output motional current to the external magnetic field, which has been further normalized against the input reference current of the device. The reported device has recorded a responsivity of 6950 ppm/T (μA/A.T) at a resonant frequency of 5.28 MHz and a reasonable mechanical quality (Q) factor of 1056 in air.
Ghosh, S & Lee, JE-Y 2017, 'A piezoelectric-on-silicon width-extensional mode Lorentz force resonant MEMS magnetometer', Sensors and Actuators A: Physical, vol. 260, pp. 169-177.
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Ghosh, S, Li, J, Cao, L & Ramamohanarao, K 2017, 'Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns', Journal of Biomedical Informatics, vol. 66, pp. 19-31.
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© 2016 Background and objective Critical care patient events like sepsis or septic shock in intensive care units (ICUs) are dangerous complications which can cause multiple organ failures and eventual death. Preventive prediction of such events will allow clinicians to stage effective interventions for averting these critical complications. Methods It is widely understood that physiological conditions of patients on variables such as blood pressure and heart rate are suggestive to gradual changes over a certain period of time, prior to the occurrence of a septic shock. This work investigates the performance of a novel machine learning approach for the early prediction of septic shock. The approach combines highly informative sequential patterns extracted from multiple physiological variables and captures the interactions among these patterns via coupled hidden Markov models (CHMM). In particular, the patterns are extracted from three non-invasive waveform measurements: the mean arterial pressure levels, the heart rates and respiratory rates of septic shock patients from a large clinical ICU dataset called MIMIC-II. Evaluation and results For baseline estimations, SVM and HMM models on the continuous time series data for the given patients, using MAP (mean arterial pressure), HR (heart rate), and RR (respiratory rate) are employed. Single channel patterns based HMM (SCP-HMM) and multi-channel patterns based coupled HMM (MCP-HMM) are compared against baseline models using 5-fold cross validation accuracies over multiple rounds. Particularly, the results of MCP-HMM are statistically significant having a p-value of 0.0014, in comparison to baseline models. Our experiments demonstrate a strong competitive accuracy in the prediction of septic shock, especially when the interactions between the multiple variables are coupled by the learning model. Conclusions It can be concluded that the novelty of the approach, stems from the integration of sequence-based phy...
Gibril, MBA, Bakar, SA, Yao, K, Idrees, MO & Pradhan, B 2017, 'Fusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area', Geocarto International, vol. 32, no. 7, pp. 735-748.
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In this study, we investigated the performance of different fusion and classification techniques for land cover mapping in Hilir Perak, Peninsula Malaysia using RADAR and Landsat-8 images in a predominantly agricultural area. The fusion methods used are Brovey Transform, Wavelet Transform, Ehlers and Layer Stacking and their results classified into seven different land cover classes which include (1) pixel-based classifiers (spectral angle mapper (SAM), maximum likelihood (ML), support vector machine (SVM)) and (2) Object-based (rule-based and standard nearest neighbour (NN)) classifiers. The result shows that pixel-based classification achieved maximum accuracy of the optical data classification using SVM in Landsat-8 with 74.96% accuracy compared to SAM and ML. For multisource data classification, the highest overall accuracy recorded for layer stacking (SVM) was 79.78%, Ehlers fusion (SVM) with 45.57%, Brovey fusion (SVM) with 63.70% and Wavelet fusion (SVM) 61.16%. And for object-based classifiers, the overall classification accuracy is 95.35% for rule-based and 76.33% for NN classifier, respectively. Based on the analysis of their performances, object-based and the rule-based classifiers produced the best classification accuracy from the fused images.
Gill, AQ, Braytee, A & Hussain, FK 2017, 'Adaptive service e-contract information management reference architecture', VINE Journal of Information and Knowledge Management Systems, vol. 47, no. 3, pp. 395-410.
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PurposeThe aim of this paper is to report on the adaptive e-contract information management reference architecture using the systematic literature review (SLR) method. Enterprises need to effectively design and implement complex adaptive e-contract information management architecture to support dynamic service interactions or transactions.Design/methodology/approachThe SLR method is three-fold and was adopted as follows. First, a customized literature search with relevant selection criteria was developed, which was then applied to initially identify a set of 1,573 papers. Second, 55 of 1,573 papers were selected for review based on the initial review of each identified paper title and abstract. Finally, based on the second review, 24 papers relevant to this research were selected and reviewed in detail.FindingsThis detailed review resulted in the adaptive e-contract information management reference architecture elements including structure, life cycle and supporting technology.Research limitations/implicationsThe reference architecture elements could serve as a taxonomy for researchers and practitioners to develop context-specific service e-contract information management architecture to support dynamic service interactions for value co-creation. The results are limited to the number of selected databases and papers reviewed in this study.Originality/valueThis paper offers a review of the body of knowledge and novel e-contract information management reference architecture, ...
Glynn, PD, Voinov, AA, Shapiro, CD & White, PA 2017, 'From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments', Earth's Future, vol. 5, no. 4, pp. 356-378.
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Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer‐term and the larger‐scale. Taking BBHV into account, we explain and provide a cyclic science‐infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an “Open Traceable Accountable Policy” initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.Plain Language SummaryOur review paper suggests that society can improve the management of natural resources and environments by (1) recognizing the sources of human decisions and thinking and understanding their role in the scientific progression to knowledge; (2) considering innate human needs and biases, beliefs, heuristics, and values that may need to be countered or embraced; and (3) creating science and policy governance that is inclusive, integrated, considerate of diversity, explicit, and accountab...
Golsorkhi, MS, Lu, DD-C & Guerrero, JM 2017, 'A GPS-Based Decentralized Control Method for Islanded Microgrids', IEEE Transactions on Power Electronics, vol. 32, no. 2, pp. 1615-1625.
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Golsorkhi, MS, Savaghebi, M, Lu, DD-C, Guerrero, JM & Vasquez, JC 2017, 'A GPS-Based Control Framework for Accurate Current Sharing and Power Quality Improvement in Microgrids', IEEE Transactions on Power Electronics, vol. 32, no. 7, pp. 5675-5687.
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© 1986-2012 IEEE.This paper proposes a novel hierarchical control strategy for improvement of load sharing and power quality in ac microgrids. This control framework is composed of a droop based controller at the primary level, and a combination of distributed power sharing and voltage conditioning schemes at the secondary level. The controllers in the primary level use GPS timing technology to synchronize the local reference angles. The voltage reference of each Distributed Generation (DG) is adjusted according to a voltage-current (V-I) droop characteristic to enable proper current and power sharing with a fast dynamic response. The droop coefficient, which acts as a virtual resistance is adaptively changed as a function of the peak current. This strategy not only simplifies the control design but also improves the current sharing accuracy at high loading conditions. The distributed power sharing scheme uses consensus protocol to ensure proportional sharing of average power. The voltage conditioning scheme produces compensation signals at fundamental and dominant harmonics to improve the voltage quality at a sensitive load bus. Experimental results are presented to validate the efficacy of the proposed method.
Golsorkhi, MS, Shafiee, Q, Lu, DD-C & Guerrero, JM 2017, 'A Distributed Control Framework for Integrated Photovoltaic-Battery-Based Islanded Microgrids', IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 2837-2848.
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This paper proposes a new cooperative control framework for coordination of energy storage units (ESUs), photovoltaic (PV) panels, and controllable load units in single-phase low voltage microgrids (MGs). The control objectives are defined and acted upon using a two level structure; primary and secondary control. Unlike conventional methods, a V-I droop mechanism is utilized in the primary control level. A distributed strategy is introduced for the secondary control level to regulate the MG voltage and manage state of charge (SoC) and power among the ESUs. The distributed secondary controllers are coordinated based on a leader-follower framework, where the leader restores the MG voltage to the rated value and the followers manage the sharing of power between the ESUs so as to balance the SoCs. Once the ESUs reach the minimum charge level, the information state increases above a positive critical value, at which point load control units perform load shedding. Similarly, fair PV curtailment is conducted in case the ESUs reach the maximum charge level. Experimental results are presented to demonstrate the efficacy of the proposed method.
Gong, W, Luo, L, Li, W, Luo, X, Liang, H, Ngo, H & Guo, W 2017, 'Using Chemically Enhanced Primary Treatment (CEPT) as a Pretreatment Option for Anaerobic Digestate from Cattle Manure Digestion System', Water, vol. 9, no. 7, pp. 487-487.
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Anaerobic digestate from cattle manure fermentation may pose a threat to the environment. How to stabilize the digestate’s characteristics so that they do not disturb the bio-system is a critical issue for digestate management. Chemically enhanced primary treatment (CEPT) was investigated as a pretreatment option for digestate treatment. The performance of CEPT for digestate management was carried out under rapid mixing (200 r/min) and slow stirring (40 r/min), respectively. The optimal dosage of ferric chloride (FeCl3) was 40 mg/L. The combination of FeCl3 and anionic polyacrylamide (APAM) had no obvious influence on TP removal, while COD removal efficiency was improved by 15.4%. The digestate pH and temperature remained stable for CEPT application and required no adjustment. The results indicate that CEPT was effective and feasible in enhancing the removal of COD and TP for digestate pretreatment by using FeCl3 and APAM.
Gong, Y, Gai, L, Tang, J, Fu, J, Wang, Q & Zeng, EY 2017, 'Reduction of Cr(VI) in simulated groundwater by FeS-coated iron magnetic nanoparticles', Science of The Total Environment, vol. 595, pp. 743-751.
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FeS-coated iron (Fe/FeS) magnetic nanoparticles were easily prepared, characterized, and applied for Cr(VI) removal in simulated groundwater. TEM, XRD, and BET characterization tests showed that FeS coating on the surface of Fe0 inhibited the aggregation of Fe0 and that Fe/FeS at a S/Fe molar ratio of 0.207 possessed a large surface area of 62.1m2/g. Increasing the S/Fe molar ratio from 0 to 0.138 decreased Cr(VI) removal by 42.8%, and a further increase to 0.207 enhanced Cr(VI) removal by 63% within 72h. Moreover, Fe/FeS inhibited the leaching of Fe, reducing the toxicity of the particles. Mechanistic analysis indicated that Fe0, Fe2+, and S2- were synergistically involved in the reduction of Cr(VI) to nontoxic Cr(III), which further precipitated as (CrxFe1-x)(OH)3 and Cr(III)-Fe-S. The process of Cr(VI) sorption by Fe/FeS (S/Fe=0.207) was fitted well with a pseudo-second-order kinetic model, and the isotherm data were simulated by Langmuir isotherm model with a maximum sorption capacity of 69.7mg/g compared to 48.9mg/g for Fe0. Low pH and initial Cr(VI) concentration favored Cr(VI) removal. Continuous fixed bed column studies showed that simulated permeable reactive barriers (PRB) with Fe/FeS was considerably effective for in situ removal of Cr(VI) from groundwater. This study demonstrated the high potential of Fe/FeS for Cr(VI) immobilization in water, groundwater, and soil.
Gopinadhan, M, Choo, Y, Kawabata, K, Kaufman, G, Feng, X, Di, X, Rokhlenko, Y, Mahajan, LH, Ndaya, D, Kasi, RM & Osuji, CO 2017, 'Controlling orientational order in block copolymers using low-intensity magnetic fields', Proceedings of the National Academy of Sciences, vol. 114, no. 45, pp. E9437-E9444.
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Significance Magnetic field interactions with condensed matter can produce orientationally ordered states that are important for fundamental research and technological applications. Block copolymer (BCP) mesophases typically exhibit weak field coupling, requiring high-intensity fields generated by superconducting magnets to produce such states. This work advances a strategy for circumventing such field intensity limitations and creates highly aligned mesophases using fields an order of magnitude smaller than typically required and that can be produced by simple permanent magnets. We elucidate the roles of molecular mobility, grain size, and ordering kinetics on the mesophase field response. Low-intensity field-directed BCP ordering has potentially profound implications for processing functional materials and developing complex textures by field shaping.
Gordic, S, Ayache, JB, Kennedy, P, Besa, C, Wagner, M, Bane, O, Ehman, RL, Kim, E & Taouli, B 2017, 'Value of tumor stiffness measured with MR elastography for assessment of response of hepatocellular carcinoma to locoregional therapy', Abdominal Radiology, vol. 42, no. 6, pp. 1685-1694.
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Gourlay, ML, Ritter, VS, Fine, JP, Overman, RA, Schousboe, JT, Cawthon, PM, Orwoll, ES, Nguyen, TV, Lane, NE, Cummings, SR, Kado, DM, Lapidus, JA, Diem, SJ & Ensrud, KE 2017, 'Comparison of fracture risk assessment tools in older men without prior hip or spine fracture: the MrOS study', Archives of Osteoporosis, vol. 12, no. 1, pp. 1-11.
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© 2017, International Osteoporosis Foundation and National Osteoporosis Foundation. Abstract: Summary: Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated. Introduction: We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality. Methods: A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline. Results: Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools. Conclusion: In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as ac...
Gourlay, ML, Ritter, VS, Fine, JP, Overman, RA, Schousboe, JT, Cawthon, PM, Orwoll, ES, Nguyen, TV, Lane, NE, Cummings, SR, Kado, DM, Lapidus, JA, Diem, SJ & Ensrud, KE 2017, 'Correction to: Comparison of fracture risk assessment tools in older men without prior hip or spine fracture: the MrOS study', Archives of Osteoporosis, vol. 12, no. 1, pp. 99-99.
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Owing to an oversight by the authors, the acknowledgments were incomplete.
Granade, C, Ferrie, C & Flammia, ST 2017, 'Practical adaptive quantum tomography', New Journal of Physics, vol. 19, no. 11, pp. 113017-113017.
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© 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. We introduce a fast and accurate heuristic for adaptive tomography that addresses many of the limitations of prior methods. Previous approaches were either too computationally intensive or tailored to handle special cases such as single qubits or pure states. By contrast, our approach combines the efficiency of online optimization with generally applicable and well-motivated data-processing techniques. We numerically demonstrate these advantages in several scenarios includ ing mixed states, higher-dimensional systems, and restricted measurements.
Grant, MJ & Stewart, MG 2017, 'Benefit of Distributed Security Queuing for Reducing Risks Associated With Improvised Explosive Device Attacks in Airport Terminals', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, vol. 3, no. 2.
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Abstract Brussels Airport ceased operations for 12 days after a coordinated improvised explosive device (IED) attack by suicide bombers in March 2016, demonstrating that critical transport hubs can be disrupted for significant durations by terrorists. Designers of critical infrastructure need to consider countermeasures to such attacks, reducing a target's attractiveness and improving opportunities for business continuity. This can be achieved by considering the cost–benefit of potential countermeasures during the design phase for infrastructure. This paper uses a probabilistic risk assessment (PRA) model for IED attack to assess the costs and benefits of using distributed security queuing at airport terminals. Our results demonstrate that the use of distributed security queuing will offer casualty reductions when used in preference to centralized security queuing. However, when considering the cost–benefit of introducing distributed security queuing, on the basis of a single small to medium IED attack, it is likely that implementing this countermeasure would not be deemed cost-effective from a purely financial perspective, particularly when the threat likelihood is very low.
Grant, MJ & Stewart, MG 2017, 'Modelling improvised explosive device attacks in the West – Assessing the hazard', Reliability Engineering & System Safety, vol. 165, pp. 345-354.
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Improvised Explosive Devices (IEDs) continue to be a terrorist weapon of choice. With increasing pressures on the economies of Western nations, spending on counter-terrorism is subject to greater scrutiny. Homeland security agencies are no longer exempt from government fiscal due diligence, needing to justify how their spending achieves best value-for-money. Probabilistic Risk Assessment (PRA) is a valuable tool that can assist in this endeavour. This paper introduces a PRA model that characterises IED attacks in Western nations, and can be used to assess the risk reduction associated with IED attack countermeasures. When using the model with the START open-source terrorism database we identified that current IED attack countermeasures provide a risk reduction of at approximately 22%, and that terrorists using IEDs in Western nations cannot generally be considered adaptive, with the operational effectiveness of terrorists being approximately 7%.
Grochow, JA & Qiao, Y 2017, 'Algorithms for Group Isomorphism via Group Extensions and Cohomology', SIAM Journal on Computing, vol. 46, no. 4, pp. 1153-1216.
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© 2017 SIAM. The isomorphism problem for finite groups of order n (GpI) has long been known to be solvable in nlog n+O(1) time, but only recently were polynomial-time algorithms designed for several interesting group classes. Inspired by recent progress, we revisit the strategy for GpI via the extension theory of groups. The extension theory describes how a normal subgroup N is related to G/N via G, and this naturally leads to a divide-and-conquer strategy that 'splits' GpI into two subproblems: one regarding group actions on other groups, and one regarding group cohomology. When the normal subgroup N is abelian, this strategy is well known. Our first contribution is to extend this strategy to handle the case when N is not necessarily abelian. This allows us to provide a unified explanation of all recent polynomial-time algorithms for special group classes. Guided by this strategy, to make further progress on GpI, we consider central-radical groups, proposed in Babai et al. [Code equivalence and group isomorphism, in Proceedings of the 22nd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'11), SIAM, Philadelphia, 2011, ACM, New York, pp. 1395-1408]: the class of groups such that G modulo its center has no abelian normal subgroups. This class is a natural extension of the group class considered by Babai et al. [Polynomial-time isomorphism test for groups with no abelian normal subgroups (extended abstract), in International Colloquium on Automata, Languages, and Programming (ICALP), 2012, pp. 51-62], namely those groups with no abelian normal subgroups. Following the above strategy, we solve GpI in nO(log log n) time for central-radical groups, and in polynomial time for several prominent subclasses of centralradical groups. We also solve GpI in nO(log log n) time for groups whose solvable normal subgroups are elementary abelian but not necessarily central. As far as we are aware, this is the first time there have been worst-case guarantees on an n...
Gu, X, Yu, Y, Li, J & Li, Y 2017, 'Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model', Journal of Sound and Vibration, vol. 406, pp. 346-362.
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© 2017 Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.
Guadie, A, Tizazu, S, Melese, M, Guo, W, Ngo, HH & Xia, S 2017, 'Biodecolorization of textile azo dye using Bacillus sp. strain CH12 isolated from alkaline lake', Biotechnology Reports, vol. 15, pp. 92-100.
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© 2017 The Authors Textile azo dye decolorizing bacteria were isolated from alkaline Lakes Abaya and Chamo using Reactive Red 239 (RR239) dye. Through subsequent screening process, strain CH12 was selected to investigate the effects of nutrient supplement, DO, pH, temperature, dye concentration and types on decolorization. Based on 16S rRNA gene sequence analysis, strain CH12 was identified as Bacillus sp. Decolorization efficiencies were significantly enhanced with carbon (≥98%) and organic nitrogen (∼100%) supplements. Complete decolorization was also observed under anoxic and anaerobic conditions, and at the temperature of 30 °C and the pH of 10. However, the azo dye decolorization efficiency of strain CH12 was significantly reduced when NaNO 3 (1–8%) was supplemented or under aerobic culturing condition (≤6%), indicating that RR239 was less preferred electron acceptor. Overall, strain CH12 can be a promising candidate for decolorization applications due to its potential to effectively decolorize higher RR239 concentrations (50−250 mg/L) and six additional dyes.
Guan, J, Feng, Y & Ying, M 2017, 'Super-activating Quantum Memory with Entanglement', Quantum Information and Computation, vol. 18, no. 13-14, pp. 1115-1124.
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Noiseless subsystems were proved to be an efficient and faithful approach topreserve fragile information against decoherence in quantum informationprocessing and quantum computation. They were employed to design a general(hybrid) quantum memory cell model that can store both quantum and classicalinformation. In this paper, we find an interesting new phenomenon that thepurely classical memory cell can be super-activated to preserve quantum states,whereas the null memory cell can only be super-activated to encode classicalinformation. Furthermore, necessary and sufficient conditions for thisphenomenon are discovered so that the super-activation can be easily checked byexamining certain eigenvalues of the quantum memory cell without computing thenoiseless subsystems explicitly. In particular, it is found that entangled andseparable stationary states are responsible for the super-activation of storingquantum and classical information, respectively.
Guan, Q, Cheng, J, Li, X, Ni, W & Wang, B 2017, 'Porous CoF2 Spheres Synthesized by a One‐Pot Solvothermal Method as High Capacity Cathode Materials for Lithium‐Ion Batteries', Chinese Journal of Chemistry, vol. 35, no. 1, pp. 48-54.
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AbstractUp to now, there are rare reports of CoF2 spheres used as high capacity cathode materials. Herein, porous CoF2 spheres were synthesized and studied as cathode materials for LIBs. The porous CoF2 spheres were synthesized by a facile one‐pot solvothermal method using a safe and inexpensive ammonium fluoride as the fluorine sources. The nature of the synthesis can avoid using corrosive fluorine sources and additional high‐temperature thermal treatment. The structure, morphologies and electrochemical performance of the samples obtained at different reaction times and solvothermal temperatures were investigated. The results show that the CoF2 spheres obtained at 200 °C for 20 h show better electrochemical performances, including a high initial discharge capacity, good capacity retention and high Coulombic efficiency. It can deliver a high initial discharge capacity of 537.8 mA•h•g−1 and keep 127.4 mA•h•g−1 after 30 cycles used as cathode materials for lithium‐ion batteries. The good electrochemical performances may be attributed to good crystallinity, porous structure and relatively intermediate sphere size.
Guan, R, Zhang, L, Su, QP, Mickolajczyk, KJ, Chen, G-Y, Hancock, WO, Sun, Y, Zhao, Y & Chen, Z 2017, 'Crystal structure of Zen4 in the apo state reveals a missing conformation of kinesin', Nature Communications, vol. 8, no. 1.
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AbstractKinesins hydrolyse ATP to transport intracellular cargoes along microtubules. Kinesin neck linker (NL) functions as the central mechano-chemical coupling element by changing its conformation through the ATPase cycle. Here we report the crystal structure of kinesin-6 Zen4 in a nucleotide-free, apo state, with the NL initial segment (NIS) adopting a backward-docked conformation and the preceding α6 helix partially melted. Single-molecule fluorescence resonance energy transfer (smFRET) analyses indicate the NIS of kinesin-1 undergoes similar conformational changes under tension in the two-head bound (2HB) state, whereas it is largely disordered without tension. The backward-docked structure of NIS is essential for motility of the motor. Our findings reveal a key missing conformation of kinesins, which provides the structural basis of the stable 2HB state and offers a tension-based rationale for an optimal NL length to ensure processivity of the motor.
Gulzar, M, Masjuki, HH, Alabdulkarem, A, Kalam, MA, Varman, M, Zulkifli, NWM, Zahid, R & Yunus, R 2017, 'Chemically active oil filter to develop detergent free bio-based lubrication for diesel engine', Energy, vol. 124, pp. 413-422.
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Gulzar, M, Masjuki, HH, Kalam, MA, Varman, M, Zulkifli, NWM, Mufti, RA, Zahid, R & Yunus, R 2017, 'Dispersion Stability and Tribological Characteristics of TiO2/SiO2 Nanocomposite-Enriched Biobased Lubricant', Tribology Transactions, vol. 60, no. 4, pp. 670-680.
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The stable dispersion of nano-additives is highly desirable for the effective lubrication performance of nanolubricants. The compatibility of base oil with selected nano-additives is required for uniform and stable dispersion. This research evaluated the dispersion stability and tribological characteristics of nano-TiO2/SiO2 (average particle size 50 nm) as an additive in a biobased lubricant. The wear protection and friction reducing characteristics of the formulations were evaluated by four-ball extreme pressure tests and piston ring–cylinder liner sliding tests. Surface analysis tools, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, and atomic force microscopy, were used to characterize the worn surfaces. Results showed that the nanolubricants demonstrated appreciable dispersion capability in the absence of a surfactant and an improvement in load-carrying capacity, antiwear behavior, and friction reduction capability.
Guo, D, Xu, J, Zhang, J, Xu, M, Cui, Y & He, X 2017, 'User relationship strength modeling for friend recommendation on Instagram', Neurocomputing, vol. 239, pp. 9-18.
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© 2017 Elsevier B.V. Social strength modeling in the social media community has attracted increasing research interest. Different from Flickr, which has been explored by many researchers, Instagram is more popular for mobile users and is conducive to likes and comments but seldom investigated. On Instagram, a user can post photos/videos, follow other users, comment and like other users’ posts. These actions generate diverse forms of data that result in multiple user relationship views. In this paper, we propose a new framework to discover the underlying social relationship strength. User relationship learning under multiple views and the relationship strength modeling are coupled into one process framework. In addition, given the learned relationship strength, a coarse-to-fine method is proposed for friend recommendation. Experiments on friend recommendations for Instagram are presented to show the effectiveness and efficiency of the proposed framework. As exhibited by our experimental results, it can obtain better performance over other related methods. Although our method has been proposed for Instagram, it can be easily extended to any other social media communities.
Guo, J, Ni, B-J, Han, X, Chen, X, Bond, P, Peng, Y & Yuan, Z 2017, 'Data on metagenomic profiles of activated sludge from a full-scale wastewater treatment plant', Data in Brief, vol. 15, pp. 833-839.
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© 2017 The Authors The data in this article mainly present the sequences of activated sludge from a full-scale municipal wastewater treatment plant (WWTP) carrying out simultaneous nitrogen and phosphorous removal in Beijing, China. Data include the operational conditions and performance, dominant microbes and taxonomic analysis in this WWTP, and function annotation results based on SEED, Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Sequencing data were generated by using Illumina HiSeq. 2000 platform according to the recommendations of the manufacturer. The sequencing data have been deposited in MG-RAST server (project ID: mgm4735473.3). For more information, see “Unraveling microbial structure and diversity of activated sludge in a full-scale simultaneous nitrogen and phosphorus removal plant using metagenomic sequencing” by Guo et al. (2017) [1].
Guo, J, Ni, B-J, Han, X, Chen, X, Bond, P, Peng, Y & Yuan, Z 2017, 'Unraveling microbial structure and diversity of activated sludge in a full-scale simultaneous nitrogen and phosphorus removal plant using metagenomic sequencing', Enzyme and Microbial Technology, vol. 102, pp. 16-25.
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© 2017 Activated sludge contains highly complex microbial communities, which play crucial roles in pollutant removal performance in wastewater treatment plants (WWTPs). Metagenomic sequencing was applied to characterize microbial community and functional profiles within activated sludge from a full-scale municipal WWTP carrying out simultaneous nitrogen and phosphorous removal (SNPR). We applied the assembled contigs (N90 of 591 bp) and predicted genes to conduct taxonomic and function annotations, respectively. Results revealed the extraordinary microbial diversity of activated sludge, which included detection of minority populations that are difficult to be explored by traditional molecular methods. Taxonomic analysis indicated that the dominant bacterial phyla were Proteobacteria, Nitrospirae, Bacteroidetes, Actinobacteria and Firmicutes. The abundance of the key organisms involved in nitrogen and phosphorous removal were qualified. Aerobic ammonia-oxidizing bacteria distinctly dominate over ammonia-oxidizing archaea and anaerobic ammonium oxidation bacteria. Various key enzymes involved in the global nitrogen cycle were annotated in the activated sludge. High abundance of the known polyphosphate accumulating organisms was detected (approximately 4.89% of the overall population reads), supporting good phosphorous removal performance. This study provides a comprehensive insight into the community structure and diversity of the SNPR system, and will provide foundation for optimal operation of nutrient removal systems.
Guo, T, Wu, J, Zhu, X & Zhang, C 2017, 'Combining Structured Node Content and Topology Information for Networked Graph Clustering', ACM Transactions on Knowledge Discovery from Data, vol. 11, no. 3, pp. 1-29.
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Graphs are popularly used to represent objects with shared dependency relationships. To date, all existing graph clustering algorithms consider each node as a single attribute or a set of independent attributes, without realizing that content inside each node may also have complex structures. In this article, we formulate a new networked graph clustering task where a network contains a set of inter-connected (or networked) super-nodes, each of which is a single-attribute graph. The new super-node representation is applicable to many real-world applications, such as a citation network where each node denotes a paper whose content can be described as a graph, and citation relationships between papers form a networked graph (i.e., a super-graph). Networked graph clustering aims to find similar node groups, each of which contains nodes with similar content and structure information. The main challenge is to properly calculate the similarity between super-nodes for clustering. To solve the problem, we propose to characterize node similarity by integrating structure and content information of each super-node. To measure node content similarity, we use cosine distance by considering overlapped attributes between two super-nodes. To measure structure similarity, we propose an Attributed Random Walk Kernel (ARWK) to calculate the similarity between super-nodes. Detailed node content analysis is also included to build relationships between super-nodes with shared internal structure information, so the structure similarity can be calculated in a precise way. By integrating the structure similarity and content similarity as one matrix, the spectral clustering is used to achieve networked graph clustering. Our method enjoys sound theoretical properties, including bounded similarities and better structure similarity assessment than traditional gr...
Guo, Z-C, Wong, S-W, Lin, J-Y, Zhu, L, Chu, Q-X, Zhang, Q & Yang, Y 2017, 'Triple-Mode Cavity Bandpass Filter on Doublet With Controllable Transmission Zeros', IEEE Access, vol. 5, pp. 6969-6977.
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© 2013 IEEE. On the basis of doublet and its properties, a class of multiple-mode narrow band bandpasss filter is designed and fabricated by simultaneously exploiting the three resonant modes in a single rectangular cavity: TE101, TE011, and TM110 modes. The input/output ports of the proposed filter are fed by coupling a microstrip line to a slot on the side wall of a rectangular cavity. Different modes are excited by changing the position and shape of the two slots at input and output of the rectangular cavity without any intra-cavity coupling. Besides three poles within the passband, a pair of transmission zeros (TZs) is achieved, which can be controlled independently by setting the positions of the two TZs at the lower and/or upper stopband. High stopband attenuation and high filtering selectivity are achieved by considerably allocating three transmission poles and two zeros. In order to verify the proposed theory, two filter prototypes are fabricated and measured.
Ha, DT, Dang, TQ, Tran, NV, Pham, TNT, Nguyen, ND & Nguyen, TV 2017, 'Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)', Scientific Reports, vol. 7, no. 1.
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AbstractThe primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844–0.898) in the development cohort and 0.783 (95% CI, 0.743–0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests.
Habibkhah, S, Ghiyasi, M, Arasi, J & Li, L 2017, 'Parameters Identification of Industrial Induction Motor Using Manufacturer Data Sheet and Power Quality Analyzer', International Review of Automatic Control (IREACO), vol. 10, no. 4, pp. 341-341.
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© 2017 Praise Worthy Prize S.r.l. - All rights reserved. This paper intends to identify circuit parameters of an installed induction motor in an innovative way which is different from standard tests. In this paper, easily available motor manufacturer data is used by which rated output power, rated terminal voltage, full load efficiency, full load power factor, nominal speed, number of poles, and locked rotor current are provided. In order to estimate the parameters, nonlinear mathematical equations of motor are derived and iterative Gauss-Seidel method is used to solve them in MATLAB. Identified parameters are then transferred to MATLAB/Simulink model of the motor to simulate its performance during Star-Delta start. Validation of parameters is evaluated by comparing the result of Simulink with real-time measurement of an industrial Power Quality Analyzer.
Habibullah, M, Lu, DD, Xiao, D, Fletcher, JE & Rahman, MF 2017, 'Low complexity predictive torque control strategies for a three‐level inverter driven induction motor', IET Electric Power Applications, vol. 11, no. 5, pp. 776-783.
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Iterative and complex prediction loop is a challenge for the implementation of finite‐state predictive torque control (FS‐PTC) of motor drive. The complexity is due to the complex torque calculations, number of available voltage vectors (which are called as prediction vectors), and weighting factor tuning for torque and flux errors in the cost function. One way to reduce the complexity is an equivalent reference stator flux vector calculation (RSFVC) from torque and flux references, which also solves the problem of weighting factor tuning. Along with a new stator flux based RSFVC technique, a reduced number of prediction vectors are proposed in this study to reduce the number of iteration of the prediction loop. The position of the stator flux and sign of the stator flux‐error are considered to lessen the number of prediction vectors. Hence, the implementation challenges of FS‐PTC algorithm are overcome. The performance of the proposed technique is investigated for two types of RSFVCs: one is based on the stator flux, and another one is based on the rotor flux. Experimental results verify that the proposed low complexity FS‐PTC strategies retain the advantages of a conventional FS‐PTC.
Habibullah, M, Lu, DD-C, Xiao, D & Rahman, MF 2017, 'Finite-State Predictive Torque Control of Induction Motor Supplied From a Three-Level NPC Voltage Source Inverter', IEEE Transactions on Power Electronics, vol. 32, no. 1, pp. 479-489.
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© 2016 IEEE. Finite-state predictive torque control (FS-PTC) of an induction motor (IM) drive has been widely investigated for two-level voltage source inverter recently. This control method suffers from high and variable switching frequencies in a wide range, due to the limited number of available voltage vectors of the power converter. In order to take advantage of multilevel inverter drives which offer the benefits of low harmonic distortion of the stator currents, torque ripple, and low switching frequency, this paper proposes the integration of the FS-PTC with a three-level neutral-point clamped (3L-NPC) inverter driven IM drive. The drawback inherited from the topology of 3L-NPC voltage source inverter (VSI), such as neutral-point voltage, is easily handled by treating it as a variable to the cost function. Similarly, apart from the inverter topology itself, the average switching frequency is reduced further, and is maintained almost constant over a wide speed range. The effectiveness of the proposed FS-PTC in terms of torque and flux responses, capacitor voltage balancing, and low average switching frequency is validated through experimental results.
Habibullah, M, Lu, DD-C, Xiao, D, Fletcher, JE & Rahman, MF 2017, 'Predictive Torque Control of Induction Motor Sensorless Drive Fed by a 3L-NPC Inverter', IEEE Transactions on Industrial Informatics, vol. 13, no. 1, pp. 60-70.
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© 2016 IEEE.A finite-state predictive torque control system for a speed-sensorless induction motor drive supplied from a threelevel neutral-point clamped inverter is proposed. For sensorless operation, the controller requires estimated speed and rotor/stator flux. In this study, the rotor speed and the rotor flux are estimated accurately by using an extended Kalman filter. Due to the large number of available voltage vectors, the control algorithm for a multi-level inverter-fed drive is computationally expensive. As a consequence, the controller requires longer execution time that yields worse torque, flux, and speed responses, especially at low-speed. In order to reduce the computational burden, a reduced number of voltage vectors for prediction and optimization in the control algorithm is proposed in this paper. The sign of the stator flux deviation and the position of the stator flux are predicted to lessen the number of voltage vectors tested. Experimental results illustrate that the proposed encoderless strategy can estimate the speed accurately over a wide speed range including field-weakening region while maintaining robustness and excellent torque and flux responses.
Habibullah, M, Lu, DD-C, Xiao, D, Osman, I & Rahman, MF 2017, 'Selected Prediction Vectors Based FS-PTC for 3L-NPC Inverter Fed Motor Drives', IEEE Transactions on Industry Applications, vol. 53, no. 4, pp. 3588-3597.
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© 1972-2012 IEEE. Computational burden is a major hurdle for practical implementation of finite-state predictive torque control (FS-PTC) of motor drive fed by a multilevel inverter. One of the reasons of computational complexity is that all voltage vectors are evaluated for prediction and actuation. This paper proposes a reduced number of voltage vectors for the prediction and actuation, which are called prediction vectors in FS-PTC. The performance is investigated for a three-level neutral-point clamped inverter fed motor drive in terms of torque and flux response, stator current total harmonic distortion, robustness, average switching frequency, and neutral-point voltage variation. The number of prediction vectors is reduced based on the position of stator flux and the deviation in stator flux from its reference. Experimental results confirm that the computational burden could be reduced by 38%, while the dynamic performance is comparable with the conventional all voltage vectors based FS-PTC.
Hadgraft, RG 2017, 'New curricula for engineering education: Experiences, engagement, e-resources', Global Journal of Engineering Education, vol. 19, no. 2, pp. 112-117.
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In an increasingly complex world, engineering students need to learn innovation and complex problem-solving in socio-technical contexts, combining fundamental knowledge of many disciplines, not just mathematics and physics. Our job as educators is to create engaging learning experiences to take students on a learning journey from high school student to proto-engineer. These learning experiences increasingly draw upon industry-relevant project work. There are now several Australian examples of curricula that combine student immersion in projects, supported by on-line learning. Fortunately, the fundamentals of engineering are being made available (and assessed) on-line, e.g. Khan Academy and numerous MOOCs. Engineering curricula are being flipped from first teach the fundamentals to first engage with the engineering problems and use these problems as motivators for students to learn the fundamentals. This is also assisted by the availability of extraordinary design software to solve the governing equations for most routine engineering tasks. E-learning has morphed from electronic learning in the last 20 years to experiential and engaged learning. This is the future of engineering curricula.
Halkon, BJ & Rothberg, SJ 2017, 'Reprint of: Taking laser Doppler vibrometry off the tripod: correction of measurements affected by instrument vibration', Optics and Lasers in Engineering, vol. 99, pp. 3-10.
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© 2017. Laser Doppler vibrometers (LDVs) are now well-established as an effective non-contact alternative to traditional contacting transducers. Despite 30 years of successful applications, however, very little attention has been given to sensitivity to vibration of the instrument itself. In this paper, the sensitivity to instrument vibration is confirmed before development theoretically and experimentally of a practical scheme to enable correction of measurements for arbitrary instrument vibration. The scheme requires a pair of correction sensors with appropriate orientation and relative location, while using frequency domain processing to accommodate inter-channel time delay and signal integrations. Error reductions in excess of 30. dB are delivered in laboratory tests with simultaneous instrument and target vibration over a broad frequency range. Ultimately, application to measurement on a vehicle simulator experiencing high levels of vibration demonstrates the practical nature of the correction technique and its robustness in a challenging measurement environment.
Halkon, BJ & Rothberg, SJ 2017, 'Restoring high accuracy to laser Doppler vibrometry measurements affected by vibration of beam steering optics', Journal of Sound and Vibration, vol. 405, pp. 144-157.
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© 2017 Elsevier Ltd Laser Doppler vibrometers are now well-established as an effective non-contact alternative to traditional contacting transducers. Wide-ranging applications include those where beam steering optics are required to reach locations that are difficult to access but no attention has yet been given to measurement sensitivity to the vibration of those optics. In this paper, a thorough mathematical treatment of this sensitivity to steering optic vibration and its correction is set out. A very practical scheme requiring a single correction measurement, from the back-surface of the mirror at the incidence point and aligned with the mirror normal, delivers an error reduction typically in excess of 30 dB. After validation in the laboratory, the scheme is then applied to a genuinely challenging measurement scenario on a single cylinder racing motorcycle. Correction is theoretically perfect for translational mirror vibrations but angular mirror vibrations require an adapted scheme using a triplet of accelerometers arranged around a circular path on the mirror back-surface and this is set out theoretically.
Halkon, BJ & Rothberg, SJ 2017, 'Taking laser Doppler vibrometry off the tripod: correction of measurements affected by instrument vibration', Optics and Lasers in Engineering, vol. 91, pp. 16-23.
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© 2016 Elsevier Ltd Laser Doppler vibrometers (LDVs) are now well-established as an effective non-contact alternative to traditional contacting transducers. Despite 30 years of successful applications, however, very little attention has been given to sensitivity to vibration of the instrument itself. In this paper, the sensitivity to instrument vibration is confirmed before development theoretically and experimentally of a practical scheme to enable correction of measurements for arbitrary instrument vibration. The scheme requires a pair of correction sensors with appropriate orientation and relative location, while using frequency domain processing to accommodate inter-channel time delay and signal integrations. Error reductions in excess of 30 dB are delivered in laboratory tests with simultaneous instrument and target vibration over a broad frequency range. Ultimately, application to measurement on a vehicle simulator experiencing high levels of vibration demonstrates the practical nature of the correction technique and its robustness in a challenging measurement environment.
Halton, K, Hall, L, Gardner, A, MacBeth, D & Mitchell, BG 2017, 'Exploring the context for effective clinical governance in infection control', American Journal of Infection Control, vol. 45, no. 3, pp. 278-283.
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Hamzehei, A, Jiang, S, Koutra, D, Wong, R & Chen, F 2017, 'Topic-based Social Influence Measurement for Social Networks', Australasian Journal of Information Systems, vol. 21, no. 0, pp. 1-14.
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Social science studies have acknowledged that the social influence of individuals is not identical. Social networks structure and shared text can reveal immense information about users, their interests, and topic-based influence. Although some studies have considered measuring user influence, less has been on measuring and estimating topic-based user influence. In this paper, we propose an approach that incorporates network structure, user-generated content for topic-based influence measurement, and user’s interactions in the network. We perform experimental analysis on Twitter data and show that our proposed approach can effectively measure topic-based user influence.
Han, J, Lu, J & Zhang, G 2017, 'Tri-level decision-making for decentralized vendor-managed inventory', Information Sciences, vol. 421, pp. 85-103.
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© 2017 Elsevier Inc. Vendor-managed inventory (VMI) is a common inventory management policy which allows the vendor to manage the buyer's inventory based on the information shared in the course of supply chain management. One challenge in VMI is that both the vendor and buyer are manufacturers who try to achieve an inventory as small as possible or even a zero inventory; it is therefore difficult to manage inventory coordination between them. This paper considers a decentralized VMI problem in a three-echelon supply chain network in which multiple distributors (third-party logistics companies) are selected to balance the inventory between a vendor (manufacturer) and multiple buyers (manufacturers). To handle this issue, this paper first proposes a tri-level decision model to describe the decentralized VMI problem, which allows us to examine how decision members coordinate with each other in respect of decentralized VMI decision-making in a predetermined sequence. We then turn our attention to the geometry of the solution space and present a vertex enumeration algorithm to solve the resulting tri-level decision model. Lastly, a computational study is developed to illustrate how the proposed tri-level decision model and solution approach can handle the decentralized VMI problem. The results indicate that the proposed tri-level decision-making techniques provide a practical way to design a novel manufacturer-manufacturer (vendor-buyer) VMI system where third-party logistics are involved.
Han, L, Ou, X, Du, J, Han, X & Guo, Y 2017, 'Study of Direct Coupling in Stator Dual Windings of a Brushless Doubly Fed Machine', IEEE Transactions on Energy Conversion, vol. 32, no. 3, pp. 974-982.
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© 1986-2012 IEEE. A brushless doubly fed machine (BDFM) usually contains two sets of independent three-phase symmetrical stator windings. Judgment of the direct electromagnetic coupling phenomenon between the two sets of stator windings is one of the most important prerequisites when safeguarding the excellent operation and control performances of the BDFM. However, because of the diversity among the stator winding structures, the generation mechanism and the existing criterion of direct coupling between the two sets of stator windings have not been fully revealed yet. This paper analyzes the mutually induced electromotive force (EMF) in the coils per pole per phase of a single stator winding that is induced by the rotating magnetic field of the other stator winding. Detailed studies of the effects of the winding structures on the mutually induced EMF and the circulating current are performed and the results are verified by finite element analysis and experimental studies of an existing BDFM prototype. The results show that the direct coupling between the two sets of stator windings is related to the combination of poles number, the number of parallel branches, the winding type, and the winding connection.
Hanif, M, Mahlia, TMI, Aditiya, HB & Abu Bakar, MS 2017, 'Energy and environmental assessments of bioethanol production from Sri Kanji 1 cassava in Malaysia', Biofuel Research Journal, vol. 4, no. 1, pp. 537-544.
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© 2017 BRTeam. According to the Malaysia's biofuel policy, renewable fuels are crucial for energy sustainability in the transportation sector in the future. This study was aimed to evaluate the potential of bioethanol production from Sri Kanji 1 cassava in Malaysia in terms of energy efficiency and renewability, as well to estimate the potential greenhouse gas (GHG) emissions reduction in CO2 equivalent. Bioethanol production process from cassava includes cassava farming, ethanol production, and transportation in which the primary energy consumption was considered. The Net Energy Balance (NEB) and Net Energy Ratio (NER) of 25.68 MJ/L and 3.98, respectively, indicated that bioethanol production from Sri Kanji 1 cassava in Malaysia was energy efficient. From the environmental perspective, the GHG balance results revealed that the production and distribution of 1 L of Cassava Fuel Ethanol (CFE) could reduce GHG emissions by 73.2%. Although found promising in the present study, Sri Kanji 1 cassava as bioethanol feedstock should be further investigated by constructing an actual ethanol plant to obtain real life data.
Hao, L, Wu, H, Wei, D, Cheng, X, Zhao, J, Luo, S, Jiang, L & Jiang, Z 2017, 'Wear and friction behaviour of high-speed steel and indefinite chill material for rolling ferritic stainless steels', Wear, vol. 376-377, pp. 1580-1585.
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© 2017 Elsevier B.V. In this paper, wear and friction behaviour of high-speed steel (HSS) and indefinite chill (IC) material for rolling a ferritic stainless steel were investigated on a tribometer. A disk specimen of the ferritic stainless steel-B445J1M was pre-oxidised at 1100 °C for 30 min, and then rotated against a pin at 500 °C for 30 min. The pin was made of HSS or IC material. It was found that the friction coefficient of the IC was lower than that of the HSS, but the mass loss of the HSS pin was less than that of the IC pin. The oxide scale of the disk was more easily worn out and attached on the HSS pin than that of the IC pin.
Harper, R, Chapman, RJ, Ferrie, C, Granade, C, Kueng, R, Naoumenko, D, Flammia, ST & Peruzzo, A 2017, 'Explaining quantum correlations through evolution of causal models', Physical Review A, vol. 95, no. 4, pp. 1-16.
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© 2017 American Physical Society. We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.
Hasan, MAM, Li, J, Ahmad, S & Molla, MKI 2017, 'predCar-site: Carbonylation sites prediction in proteins using support vector machine with resolving data imbalanced issue', Analytical Biochemistry, vol. 525, pp. 107-113.
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The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Alzheimer's disease, diabetes, and Parkinson's disease. However, since the experimental technologies are costly and time-consuming to detect the carbonylation sites in proteins, an accurate computational method for predicting carbonylation sites is an urgent issue which can be useful for drug development. In this study, a novel computational tool termed predCar-Site has been developed to predict protein carbonylation sites by (1) incorporating the sequence-coupled information into the general pseudo amino acid composition, (2) balancing the effect of skewed training dataset by Different Error Costs method, and (3) constructing a predictor using support vector machine as classifier. This predCar-Site predictor achieves an average AUC (area under curve) score of 0.9959, 0.9999, 1, and 0.9997 in predicting the carbonylation sites of K, P, R, and T, respectively. All of the experimental results along with AUC are found from the average of 5 complete runs of the 10-fold cross-validation and those results indicate significantly better performance than existing predictors. A user-friendly web server of predCar-Site is available at http://research.ru.ac.bd/predCar-Site/.
Hasanipanah, M, Faradonbeh, RS, Amnieh, HB, Armaghani, DJ & Monjezi, M 2017, 'Forecasting blast-induced ground vibration developing a CART model', Engineering with Computers, vol. 33, no. 2, pp. 307-316.
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Hasanipanah, M, Faradonbeh, RS, Armaghani, DJ, Amnieh, HB & Khandelwal, M 2017, 'Development of a precise model for prediction of blast-induced flyrock using regression tree technique', Environmental Earth Sciences, vol. 76, no. 1.
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Hasanipanah, M, Jahed Armaghani, D, Bakhshandeh Amnieh, H, Majid, MZA & Tahir, MMD 2017, 'Application of PSO to develop a powerful equation for prediction of flyrock due to blasting', Neural Computing and Applications, vol. 28, no. S1, pp. 1043-1050.
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Hasanipanah, M, Shahnazar, A, Bakhshandeh Amnieh, H & Jahed Armaghani, D 2017, 'Prediction of air-overpressure caused by mine blasting using a new hybrid PSO–SVR model', Engineering with Computers, vol. 33, no. 1, pp. 23-31.
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Hassan, M & Liu, D 2017, 'Simultaneous area partitioning and allocation for complete coverage by multiple autonomous industrial robots', Autonomous Robots, vol. 41, no. 8, pp. 1609-1628.
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© 2017, Springer Science+Business Media New York. For tasks that require complete coverage of surfaces by multiple autonomous industrial robots, it is important that the robots collaborate to appropriately partition and allocate the surface areas amongst themselves such that the robot team’s objectives are optimized. An approach to this problem is presented, which takes into account unstructured and complex 3D environments, and robots with different capabilities. The proposed area partitioning and allocation approach utilizes Voronoi partitioning to partition objects’ surfaces, and multi-objective optimization to allocate the partitioned areas to the robots whilst optimizing robot team’s objectives. In addition to minimizing the overall completion time and achieving complete coverage, which are objectives particularly useful for applications such as surface cleaning, manipulability measure and joint’s torque are also optimized so as to help autonomous industrial robots to operate better in applications such as spray painting and grit-blasting. The approach is validated using six case studies that consist of comparative studies, complex simulated scenarios as well as real scenarios using data obtained from real objects and applications.
Hatoum, D, Yagoub, D, Ahadi, A, Nassif, NT & McGowan, EM 2017, 'Annexin/S100A Protein Family Regulation through p14ARF-p53 Activation: A Role in Cell Survival and Predicting Treatment Outcomes in Breast Cancer', PLOS ONE, vol. 12, no. 1, pp. e0169925-e0169925.
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© 2017 Hatoum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The annexin family and S100A associated proteins are important regulators of diverse calcium- dependent cellular processes including cell division, growth regulation and apoptosis. Dysfunction of individual annexin and S100A proteins is associated with cancer progression, metastasis and cancer drug resistance. This manuscript describes the novel finding of differential regulation of the annexin and S100A family of proteins by activation of p53 in breast cancer cells. Additionally, the observed differential regulation is found to be beneficial to the survival of breast cancer cells and to influence treatment efficacy. We have used unbiased, quantitative proteomics to determine the proteomic changes occurring post p14ARF-p53 activation in estrogen receptor (ER) breast cancer cells. In this report we identified differential regulation of the annexin/S100A family, through unique peptide recognition at the N-terminal regions, demonstrating p14ARF-p53 is a central orchestrator of the annexin/S100A family of calcium regulators in favor of pro-survival functions in the breast cancer cell. This regulation was found to be cell-type specific. Retrospective human breast cancer studies have demonstrated that tumors with functional wild type p53 (p53wt) respond poorly to some chemotherapy agents compared to tumors with a non-functional p53. Given that modulation of calcium signaling has been demonstrated to change sensitivity of chemotherapeutic agents to apoptotic signals, in principle, we explored the paradigm of how p53 modulation of calcium regulators in ER+ breast cancer patients impacts and influences therapeutic outcomes.
Hayati, H, Hosseini, SA & Rahmani, O 2017, 'Coupled twist–bending static and dynamic behavior of a curved single-walled carbon nanotube based on nonlocal theory', Microsystem Technologies, vol. 23, no. 7, pp. 2393-2401.
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© 2016 Springer-Verlag Berlin Heidelberg The static and dynamic behavior of a curved single-walled carbon nanotube which is under twist–bending couple based on nonlocal theory is analyzed. The nonlocal theory is used to model the mechanical behavior of structure in small scale. The obtained differential equations are solved using a simply supported boundary condition and Navier analytical method. Moreover the twisted vibration and bending of curved nanotube is analyzed and also the armchair model is assumed in this study. The following parameters were studied in this paper: the effect of nonlocal parameter, the curved nanotube’s opening angel, the Young’s modulus and the mode number is studied. The results were verified with the previous literature which showed an excellent agreement. The results of this paper can be used as a benchmark for future investigations.
He, Q, Xie, X, Wang, Y, Ye, D, Chen, F, Jin, H & Yang, Y 2017, 'Localizing Runtime Anomalies in Service-Oriented Systems', IEEE Transactions on Services Computing, vol. 10, no. 1, pp. 94-106.
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He, Q, Zhou, R, Zhang, X, Wang, Y, Ye, D, Chen, F, Grundy, JC & Yang, Y 2017, 'Keyword Search for Building Service-Based Systems', IEEE Transactions on Software Engineering, vol. 43, no. 7, pp. 658-674.
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He, X, Cai, G, Zhao, C & Sheng, D 2017, 'On the stress-force-fabric equation in triaxial compressions: Some insights into the triaxial strength', Computers and Geotechnics, vol. 85, pp. 71-83.
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The strength of granular materials during triaxial compression is investigated via a grain scale analysis in this paper. A 3D Discrete Element Method (DEM) program provides the triaxial strength data and helps to validate the micromechanical analysis. Some standard methods in statistics are employed first to quantitatively examine the assumptions made when deriving the stress-force-fabric (SFF) equation. After careful validation, a more concise format for the SFF equation is proposed for triaxial compressions. With this SFF equation, the strength is found to be jointly contributed by the magnitudes of the contact force anisotropy and fabric anisotropy. The influence of the initial void ratio, confining pressure and loading direction on the development of contact force anisotropy and fabric anisotropy is examined and presented. With similar techniques, the “force” term in the SFF equation is further decoupled, and an equation is obtained such that it explicitly links the contact force term with the friction coefficient between grains, a tensor defined as a statistic of the normal contact forces and a tensor defined as a statistic of the mobilisation status of contacts. Based on this equation, another equation regarding the stress ratio of granular assembly is obtained, and it clearly indicates two sources that contribute to the phenomenological friction nature of granular assembly. These two sources are caused by the contact force at the grain scale. The first is the anisotropy of the average normal contact forces, and the second is the mobilisation of contacts.
He, X, Wu, Y, Yu, D & Merigó, JM 2017, 'Exploring the Ordered Weighted Averaging Operator Knowledge Domain: A Bibliometric Analysis', International Journal of Intelligent Systems, vol. 32, no. 11, pp. 1151-1166.
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© 2017 Wiley Periodicals, Inc. Ordered weighted averaging (OWA) operator has been received increasingly widespread interest since its appearance in 1988. Recently, a topic search with the keywords “ordered weighted averaging operator” or “OWA operator” on Web of Science (WOS) found 1231 documents. As the publications about OWA operator increase rapidly, thus a scientometric analysis of this research field and discovery of its knowledge domain becomes very important and necessary. This paper studies the publications about OWA operator between 1988 and 2015, and it is based on 1213 bibliographic records obtained by using topic search from WOS. The disciplinary distribution, most cited papers, influential journals, as well as influential authors are analyzed through citation and cocitation analysis. The emerging trends in OWA operator research are explored by keywords and references burst detection analysis. The research methods and results in this paper are meaningful for researchers associated with OWA operator field to understand the knowledge domain and establish their own future research direction.
He, Z, Teng, J, Zhang, S & Sheng, D 2017, 'Moisture transfer and phase change in unsaturated soils: an experimental study of two types of canopy effect', SCIENCES IN COLD AND ARID REGIONS, vol. 9, no. 3, pp. 243-249.
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Henderson, IEJ, Zhu, XQ, Uy, B & Mirza, O 2017, 'Dynamic behaviour of steel-concrete composite beams retrofitted with various bolted shear connectors', Engineering Structures, vol. 131, pp. 115-135.
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© 2016 Elsevier Ltd In structural engineering, composite construction has become increasingly widespread due to the improvement of mechanical properties it provides. Retrospective application of the composite construction principle to old structures may be beneficial. Many end of life structures are decommissioned and replaced. If the structural integrity of old structures could be improved their service life may be extended. Recently research on the development of post-installed or retrofitted shear connectors has been conducted. Most of the research in this area is concerned with modified versions of welded shear studs or various threaded rod and nut configurations, and refer to only one type of shear connector. Therefore, the suitability of the proposed models across differing shear connection types is unknown. An experimental study has been undertaken to ascertain the differences in dynamic behaviour of cast-in and retrofitted shear connectors using a series of identical steel-concrete composite beams with various shear connection systems. Two blind bolt connector types were used as shear connection systems in steel-concrete composite beams alongside a welded shear stud specimen in both cast-in and retrofitted configurations. A finite element model was then developed. The nature of changes in dynamic behaviour due to damage were investigated using the finite element model. It was found that at increased loading the behaviour of the cast-in and retrofitted connectors was fundamentally different due to the retrofitting procedure.
Heng, J, Wang, J, Xiao, L & Lu, H 2017, 'Research and application of a combined model based on frequent pattern growth algorithm and multi-objective optimization for solar radiation forecasting', Applied Energy, vol. 208, pp. 845-866.
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© 2017 Elsevier Ltd Solar radiation forecasting plays a significant role in precisely designing solar energy systems and in the efficient management of solar energy plants. Most research only focuses on accuracy improvements; however, for an effective forecasting model, considering only accuracy or stability is inadequate. To solve this problem, a combined model based on nondominated sorting-based multiobjective bat algorithm (NSMOBA) is developed for the optimization of weight coefficients of each model to achieve high accuracy and stability results simultaneously. In addition, a statistical method and data mining-based approach are used to determine the input variables for constructing the combined model. Monthly average solar radiation and meteorological variables from six datasets in the U.S. collected for case studies were used to assess the comprehensive performance (both in accuracy and stability) of the proposed combined model. The simulation in four experiments demonstrated the following: (a) the proposed combined model is suitable for providing accurate and stable solar radiation forecasting; (b) the combined model exhibits a more competitive forecasting performance than the individual models by using the advantage of each model; (c) the NSMOBA is an efficient algorithm for providing accurate forecasting results and improving the stability where the single bat algorithm is insufficient.
Henke, T, Weisner, K, Schulte, L & Deuse, J 2017, 'Einzel- und Kleinserienfertigung von Großgeräten', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 112, no. 12, pp. 873-876.
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Kurzfassung Die Nachfrage nach individuellen Produkten erfordert auch in der Großgerätemontage das Angebot eines breiten Produktspektrums. Ein hohes Optimierungspotenzial weist dabei die Materialbereitstellung auf, deren Planung und Steuerung sehr aufwändig und wenig standardisiert ist. In dem Forschungsvorhaben „SySMaG“ des IPS (Dortmund) wird daher eine Planungssystematik entwickelt, mit der das Optimierungspotenzial bei der Materialbereitstellung in der Großgerätemontage nutzbar gemacht werden soll.**)
Henke, T, Weisner, K, Schulte, L & Deuse, J 2017, 'Planning framework to standardize the material supply for individual and small series of large scale products with many variants', ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, vol. 112, no. 12, pp. 873-876.
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Since the demand of individual products rises, large scale product manufacturer need to offer a wide product range. Especially the material supply, whose planning and control is very complex and unstandardized, offers a high potential for optimization. Therefore within the research project “SySMaG” of the IPS (Dortmund) a planning framework will be developed, with which the existing potential for optimization in material supply can be harnessed in large scale product assembly in the near future.
Herr, D, Nori, F & Devitt, SJ 2017, 'Lattice surgery translation for quantum computation', New Journal of Physics, vol. 19, no. 1, pp. 013034-013034.
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© 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. In this paper we outline a method for a compiler to translate any non fault tolerant quantum circuit to the geometric representation of the lattice surgery error-correcting code using inherent merge and split operations. Since the efficiency of state distillation procedures has not yet been investigated in the lattice surgery model, their translation is given as an example using the proposed method. The resource requirements seem comparable or better to the defect-based state distillation process, but modularity and eventual implementability allow the lattice surgery model to be an interesting alternative to braiding.
Herr, D, Nori, F & Devitt, SJ 2017, 'Optimization of Lattice Surgery is NP-Hard', npj Quantum Information 3, Article number: 35 (2017), vol. 3, no. 1, pp. 1-5.
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The traditional method for computation in either the surface code or in theRaussendorf model is the creation of holes or 'defects' within the encodedlattice of qubits that are manipulated via topological braiding to enact logicgates. However, this is not the only way to achieve universal, fault-tolerantcomputation. In this work, we focus on the Lattice Surgery representation,which realizes transversal logic operations without destroying the intrinsic 2Dnearest-neighbor properties of the braid-based surface code and achievesuniversality without defects and braid based logic. For both techniques thereare open questions regarding the compilation and resource optimization ofquantum circuits. Optimization in braid-based logic is proving to be difficultand the classical complexity associated with this problem has yet to bedetermined. In the context of lattice-surgery-based logic, we can introduce anoptimality condition, which corresponds to a circuit with the lowest resourcerequirements in terms of physical qubits and computational time, and prove thatthe complexity of optimizing a quantum circuit in the lattice surgery model isNP-hard.
Hesamian, MH, Mashohor, S, Saripan, MI & Adnan, WAW 2017, 'Designing the Network Topology of Feedforward Neural Network for Scene Illumination Classification', Advanced Science Letters, vol. 23, no. 6, pp. 5269-5272.
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Determining the topology of network as one of the objectives of ANN systems, is not following any certain rules or algorithms but still there are several hints which help us to restrict the neural network architecture set. Hence, the process of testing structures will be the solution of finding most effective one among a limited set. This study aims to apply testing method on scene illumination classification system to find out the appropriate ANN structure. The results of this study apply on similar classification systems to avoid redoing the testing process.
Himanshu, Bhaskar, R, Sharma, N, Mehta, M, Singh, A, Yashwant, Yadav, NS, Khatik, GL & Verma, S 2017, 'Development and evaluation of buccoadhesive film of ropinirole hydrochloride for the treatment of Parkinson’s disease', International Journal of Drug Delivery Technology, vol. 7, no. 2, pp. 106-112.
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The present research article represents the formulation and evaluation of buccoadhessive film of ropinirole hydrochloride. This drug is an oral non-ergoline dopamine agonist with the greater affinity at D3 receptor. This drug having low molecular weight (296.84 g/mol), and short biological half-life (4-6 hrs) which necessitates for multiple dosing for maintaining therapeutic effect throughout the day. Moreover, drug is metabolized in liver forming several inactive metabolites which decrease it oral bioavailability upto 50% making it a suitable candidate for administration of drug through buccal mucosa. Buccal films of ropinirole hydrochloride were prepared using various polymers (HPMC, EC, PVA and Carbopol) by solvent casting method using propylene glycol as plasticizer. These films were evaluated for various parameter such as appearance, surface texture, weight uniformity, thickness, folding endurance, surface pH, drug content and swelling index. All the formulations were subjected to in vitro drug release study which were carried out using egg membrane as semi permeable membrane.
Ho, L & Fatahi, B 2017, 'Axisymmetric Consolidation in Unsaturated Soil Deposit Subjected to Time-Dependent Loadings', International Journal of Geomechanics, vol. 17, no. 2, pp. 04016046-04016046.
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© 2016 American Society of Civil Engineers. This paper presents an analytical solution to predict the axisymmetric consolidation in unsaturated soil deposits subjected to different time-dependent loadings. The mathematical procedure uses the separation of variables and Laplace transformation methods to obtain the final solution. A set of polar governing equations of flow are obtained and presented under the partial differential equations (PDEs), and then the variable separation technique is used to alter the PDEs to ordinary differential equations (ODEs) consisting of distinctive variables. Fourier Bessel and sine series are used to present functions of radial and vertical flows, respectively, and the Laplace transformation is used to obtain a function of time. Four primary time-dependent loading functions, including ramping, asymptotic, sinusoid, and damped sine wave, are mathematically simulated and incorporated into the proposed solutions. This study investigates changes in excess pore-air and pore-water pressures as well as consolidation settlement against the air-to-water permeability ratio and various loading parameters. Moreover, changes in suction and net stress induced by ramped and asymptotic loadings are also presented in the worked examples.
Ho, Y-J, Lin, Y-M, Huang, Y-C, Shi, B, Yeh, K-T, Gong, Z & Lu, J-W 2017, 'Prognostic significance of high YY1AP1 and PCNA expression in colon adenocarcinoma', Biochemical and Biophysical Research Communications, vol. 494, no. 1-2, pp. 173-180.
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Hoang, DT, Niyato, D, Wang, P, Kim, DI & Han, Z 2017, 'Ambient Backscatter: A New Approach to Improve Network Performance for RF-Powered Cognitive Radio Networks', IEEE Transactions on Communications, vol. 65, no. 9, pp. 3659-3674.
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© 1972-2012 IEEE. This paper introduces a new solution to improve the performance for secondary systems in radio frequency (RF) powered cognitive radio networks (CRNs). In a conventional RF-powered CRN, the secondary system works based on the harvest-then-transmit protocol. That is, the secondary transmitter (ST) harvests energy from primary signals and then uses the harvested energy to transmit data to its secondary receiver (SR). However, with this protocol, the performance of the secondary system is much dependent on the amount of harvested energy as well as the primary channel activity, e.g., idle and busy periods. Recently, ambient backscatter communication has been introduced, which enables the ST to transmit data to the SR by backscattering ambient signals. Therefore, it is potential to be adopted in the RF-powered CRN. We investigate the performance of RF-powered CRNs with ambient backscatter communication over two scenarios, i.e., overlay and underlay CRNs. For each scenario, we formulate and solve the optimization problem to maximize the overall transmission rate of the secondary system. Numerical results show that by incorporating such two techniques, the performance of the secondary system can be improved significantly compared with the case when the ST performs either harvest-then-transmit or ambient backscatter technique.
Hoang, DT, Wang, P, Niyato, D & Hossain, E 2017, 'Charging and Discharging of Plug-In Electric Vehicles (PEVs) in Vehicle-to-Grid (V2G) Systems: A Cyber Insurance-Based Model', IEEE Access 2017, vol. 5, pp. 732-754.
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In addition to being environment-friendly, vehicle-to-grid (V2G) systems canhelp the plug-in electric vehicle (PEV) users in reducing their energy costsand can also help stabilizing energy demand in the power grid. In V2G systems,since the PEV users need to obtain system information (e.g., locations ofcharging/discharging stations, current load and supply of the power grid) toachieve the best charging and discharging performance, data communication playsa crucial role. However, since the PEV users are highly mobile, informationfrom V2G systems is not always available for many reasons, e.g., wireless linkfailures and cyber attacks. Therefore, in this paper, we introduce a novelconcept using cyber insurance to 'transfer' cyber risks, e.g., unavailableinformation, of a PEV user to a third party, e.g., a cyber insurance company.Under the insurance coverage, even without information about V2G systems, a PEVuser is always guaranteed the best price for charging/discharging. Inparticular, we formulate the optimal energy cost problem for the PEV user byadopting a Markov decision process framework. We then propose a learningalgorithm to help the PEV user make optimal decisions, e.g., to charge ordischarge and to buy or not to buy insurance, in an online fashion. Throughsimulations, we show that cyber insurance is an efficient solution not only indealing with cyber risks, but also in maximizing revenue of the PEV user.
Hoang, TM, Duong, TQ, Tuan, HD & Poor, HV 2017, 'Secure Massive MIMO Relaying Systems in a Poisson Field of Eavesdroppers', IEEE Transactions on Communications, vol. 65, no. 11, pp. 4857-4870.
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© 1972-2012 IEEE. A cooperative relay network operating in the presence of eavesdroppers, whose locations are distributed according to a homogeneous Poisson point process, is considered. The relay is equipped with a very large antenna array and can exploit maximal ratio combing in the uplink and maximal ratio transmission in the downlink. A realistic model in which the channel state information of every eavesdropper is not known is considered, as eavesdroppers tend to hide themselves in practice. The destination is thus in a much weaker position than all the eavesdroppers because it only receives the retransmitted signal from the relay. Under this setting, the security performance is investigated for two relaying protocols: amplify-and-forward and decode-and-forward. The secrecy outage probability, the connection outage probability, and the tradeoff between them, which is controlled by the source power allocation, are examined. Finally, suitable solutions for the source power (such that once the transmission occurs with high reliability, the secure risk is below a given threshold) are proposed for a tradeoff between security and reliability.
Hoermann, S, McCabe, KL, Milne, DN & Calvo, RA 2017, 'Application of Synchronous Text-Based Dialogue Systems in Mental Health Interventions: Systematic Review', Journal of Medical Internet Research, vol. 19, no. 8, pp. e267-e267.
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© Simon Hoermann, Kathryn L McCabe, David N Milne, Rafael A Calvo. Background: Synchronous written conversations (or 'chats') are becoming increasingly popular as Web-based mental health interventions. Therefore, it is of utmost importance to evaluate and summarize the quality of these interventions. Objective: The aim of this study was to review the current evidence for the feasibility and effectiveness of online one-on-one mental health interventions that use text-based synchronous chat. Methods: A systematic search was conducted of the databases relevant to this area of research (Medical Literature Analysis and Retrieval System Online [MEDLINE], PsycINFO, Central, Scopus, EMBASE, Web of Science, IEEE, and ACM). There were no specific selection criteria relating to the participant group. Studies were included if they reported interventions with individual text-based synchronous conversations (ie, chat or text messaging) and a psychological outcome measure. Results: A total of 24 articles were included in this review. Interventions included a wide range of mental health targets (eg, anxiety, distress, depression, eating disorders, and addiction) and intervention design. Overall, compared with the waitlist (WL) condition, studies showed significant and sustained improvements in mental health outcomes following synchronous text-based intervention, and post treatment improvement equivalent but not superior to treatment as usual (TAU) (eg, face-to-face and telephone counseling). Conclusions: Feasibility studies indicate substantial innovation in this area of mental health intervention with studies utilizing trained volunteers and chatbot technologies to deliver interventions. While studies of efficacy show positive post-intervention gains, further research is needed to determine whether time requirements for this mode of intervention are feasible in clinical practice.
Ho-Le, TP, Center, JR, Eisman, JA, Nguyen, HT & Nguyen, TV 2017, 'Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling', Journal of Bone and Mineral Research, vol. 32, no. 2, pp. 285-293.
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ABSTRACT Although the susceptibility to fracture is partly determined by genetic factors, the contribution of newly discovered genetic variants to fracture prediction is still unclear. This study sought to define the predictive value of a genetic profiling for fracture prediction. Sixty-two bone mineral density (BMD)-associated single-nucleotide polymorphisms (SNPs) were genotyped in 557 men and 902 women who had participated in the Dubbo Osteoporosis Epidemiology Study. The incidence of fragility fracture was ascertained from X-ray reports between 1990 and 2015. Femoral neck BMD was measured by dual-energy X-ray absorptiometry. A weighted polygenic risk score (genetic risk score [GRS]) was created as a function of the number of risk alleles and their BMD-associated regression coefficients for each SNP. The association between GRS and fracture risk was assessed by the Cox proportional hazards model. Individuals with greater GRS had lower femoral neck BMD (p < 0.01), but the variation in GRS accounted for less than 2% of total variance in BMD. Each unit increase in GRS was associated with a hazard ratio of 1.20 (95% CI, 1.04 to 1.38) for fracture, and this association was independent of age, prior fracture, fall, and in a subset of 33 SNPs, independent of femoral neck BMD. The significant association between GRS and fracture was observed for the vertebral and wrist fractures, but not for hip fracture. The area under the receiver-operating characteristic (ROC) curve (AUC) for the model with GRS and clinical risk factors was 0.71 (95% CI, 0.68 to 0.74). With GRS, the correct reclassification of fracture versus nonfracture ranged from 12% for hip fracture to 23% for wrist fracture. A genetic profiling of BMD- associated genetic variants could improve the accuracy of fracture prediction over and above that of clinical risk factors ...
Hollis, L, Barnhill, E, Perrins, M, Kennedy, P, Conlisk, N, Brown, C, Hoskins, PR, Pankaj, P & Roberts, N 2017, 'Finite element analysis to investigate variability of MR elastography in the human thigh', Magnetic Resonance Imaging, vol. 43, pp. 27-36.
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Hong, H, Chen, W, Xu, C, Youssef, AM, Pradhan, B & Tien Bui, D 2017, 'Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy', Geocarto International, vol. 32, no. 2, pp. 1-16.
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© 2016 Taylor & Francis. The main objective of the study was to evaluate and compare the overall performance of three methods, frequency ratio (FR), certainty factor (CF) and index of entropy (IOE), for rainfall-induced landslide susceptibility mapping at the Chongren area (China) using geographic information system and remote sensing. First, a landslide inventory map for the study area was constructed from field surveys and interpretations of aerial photographs. Second, 15 landslide-related factors such as elevation, slope, aspect, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to faults, distance to rivers, distance to roads, landuse, NDVI, lithology and rainfall were prepared for the landslide susceptibility modelling. Using these data, three landslide susceptibility models were constructed using FR, CF and IOE. Finally, these models were validated and compared using known landslide locations and the receiver operating characteristics curve. The result shows that all the models perform well on both the training and validation data. The area under the curve showed that the goodness-of-fit with the training data is 79.12, 80.34 and 80.42% for FR, CF and IOE whereas the prediction power is 80.14, 81.58 and 81.73%, for FR, CF and IOE, respectively. The result of this study may be useful for local government management and land use planning.
Hong, H, Liu, J, Zhu, A-X, Shahabi, H, Pham, BT, Chen, W, Pradhan, B & Bui, DT 2017, 'A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)', Environmental Earth Sciences, vol. 76, no. 19, pp. 1-19.
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This study proposed a hybrid modeling approach using two methods, support vector machines and random subspace, to create a novel model named random subspace-based support vector machines (RSSVM) for assessing landslide susceptibility. The newly developed model was then tested in the Wuning area, China, to produce a landslide susceptibility map. With the purpose of achieving the objective of the study, a spatial dataset was initially constructed that includes a landslide inventory map consisting of 445 landslide regions. Then, various landslide-influencing factors were defined, including slope angle, aspect, altitude, topographic wetness index, stream power index, sediment transport index, soil, lithology, normalized difference vegetation index, land use, rainfall, distance to roads, distance to rivers, and distance to faults. Next, the result of the RSSVM model was validated using statistical index-based evaluations and the receiver operating characteristic curve approach. Then, to evaluate the performance of the suggested RSSVM model, a comparison analysis was performed to other existing approaches such as artificial neural network, Naïve Bayes (NB) and support vector machine (SVM). In general, the performance of the RSSVM model was better than the other models for spatial prediction of landslide susceptibility. The AUC results of the applied models are as follows: RSSVM (AUC = 0.857), followed by MLP (AUC = 0.823), SVM (AUC = 0.814) and NB (AUC = 0.783). The present study indicates that RSSVM can be used for landslide susceptibility evaluation, and the results are very useful for local governments and people living in the Wuning area.
Hong, H, Pradhan, B, Bui, DT, Xu, C, Youssef, AM & Chen, W 2017, 'Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 544-569.
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Suichuan is a mountainous area at the Jiangxi province in Central China, where rainfall-induced landslides occur frequently. The purpose of this study is to assess landslide susceptibility of this region using support vector machine (SVM) with four kernel functions: polynomial (PL), radial basis function (RBF), sigmoid (SIG), and linear (LN). A total of 178 landslides were used to accomplish this approach, of which, 125 (70%) landslides were randomly selected for training the landslide susceptibility models, whereas the remaining 53 (30%) were used for the model validation. Fifteen landslide conditioning factors were considered including slope-angle, altitude, slope-aspect, topographic wetness index (TWI), sediment transport index (STI), stream power index (SPI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, precipitation, landuse, normalized difference vegetation index (NDVI), and lithology. Using the training dataset, nine landslide susceptibility models for the Suichuan area were constructed with the four kernel functions. To evaluate the performance of these models, the receiver-operating characteristic curve (ROC) and area under the curve (AUC) were used. Using the training dataset, AUC values for the SVM-PL models with six degrees PL function (1–6) are 0.715, 0.801, 0.856, 0.891, 0.919, 0.953, respectively, and for the SVM-RBF model, the SVM-SIG model, and the SVM-LN model are 0.716, 0.741, and 0.740, respectively. Using the validation dataset, AUC values for the SVM-PL models with six degrees PL function (1–6) are 0.738, 0.730, 0.683, 0.648, 0.608, and 0.598, respectively, and for the SVM-RBF model, the SVM-SIG model, and the SVM-LN model are 0.716, 0.741, and 0.740, respectively. Our results suggested that the SVM-RBF model is the most suitable for landslide susceptibility assessment for the study area.
Hong, H, Pradhan, B, Sameen, MI, Chen, W & Xu, C 2017, 'Spatial prediction of rotational landslide using geographically weighted regression, logistic regression, and support vector machine models in Xing Guo area (China)', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1997-2022.
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Ho-Pham, LT & Nguyen, TV 2017, 'The Vietnam Osteoporosis Study: Rationale and design', Osteoporosis and Sarcopenia, vol. 3, no. 2, pp. 90-97.
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Objectives:Osteoporosis and fracture impose a significant health care burden on the contemporary populations in developing countries. The Vietnam Osteoporosis Study (VOS) sought to assess the burden of osteoporosis and its comorbidities in men and women. Methods:The study was designed as a population-based family investigation in which families were randomly recruited from Ho Chi Minh City, Vietnam. Individuals were assessed for bone health, including bone mineral density (BMD) and body composition and trabecular and cortical bone properties by pQCT (peripheral quantitative computed tomography). Fasting blood samples were obtained for the analysis of plasma glucose, glycosylated hemoglobin, and bone turnover markers. Genomic DNA extraction from whole blood samples for further genetic and genomic analyses. Results:We have recruited more than 4157 individuals from 817 families. The average age of participants was 51, with approximately 45% of the individuals aged 50 years and older. Approximately 3% of participants were obese (body mass index ≥ 30 kg/m2), and 21% were overweight. Notably, 11% of participants aged 40 years and older were diabetic. Among those aged 50 years and older, approximately 14% of women and 5% of men had osteoporosis (i.e., femoral neck BMD T-scores ≤ -2.5). There were modest correlations between volumetric BMD and areal BMD. Conclusions:VOS is a major bone research project in Vietnam aimed at comprehensively documenting the burden osteoporosis, its co-occurrence of chronic diseases, and their underlying etiologies. The Study will make important contributions to the literature of bone health worldwide.
Ho-Pham, LT, Lai, TQ, Nguyen, UDT, Bui, QV & Nguyen, TV 2017, 'Delineating the Relationship Between Leptin, Fat Mass, and Bone Mineral Density: A Mediation Analysis', Calcified Tissue International, vol. 100, no. 1, pp. 13-19.
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© 2016, Springer Science+Business Media New York. To test the hypothesis that the relationship between fat mass (FM) and bone mineral density (BMD) is mediated by leptin. The study involved 611 individuals aged 20–89 years who were randomly sampled from Ho Chi Minh City (Vietnam). BMD at the femoral neck (FN), lumbar spine (LS), and whole body (WB) was measured by DXA. Lean mass and FM were derived from the WB DXA scan. Leptin was measured by ELISA (DRG Diagnostics, Germany). The regression method was used to partition the variance of leptin and FM on BMD. The mediated effect of leptin was analyzed by the mediation analysis model. In the multiple linear regression, leptin, FM, and age collectively accounted for ~34 % variation in FNBMD in men and women. However, only 0.5 % of this explained variance was due to leptin. Of the total effect of FM on FNBMD, the mediated effect of leptin accounted for 6.1 % (P = 0.38) in men and 7.1 % (P = 0.99) in women. The same trend was observed for LS and WBBMD. These data suggest that greater FM is associated with greater BMD, but the association is not mediated by leptin, and that leptin has a non-significant influence on bone mass.
Ho-Pham, LT, Nguyen, UDT, Tran, TX & Nguyen, TV 2017, 'Discordance in the diagnosis of diabetes: Comparison between HbA1c and fasting plasma glucose', PLOS ONE, vol. 12, no. 8, pp. e0182192-e0182192.
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© 2017 Ho-Pham et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective HbA1c has been introduced as a complementary diagnostic test for diabetes, but its impact on disease prevalence is unknown. This study evaluated the concordance between HbA1c and fasting plasma glucose (FPG) in the diagnosis of diabetes in the general population. Materials and methods The study was designed as a population based investigation, with participants being sampled from the Ho Chi Minh City, Vietnam. Blood samples were collected after overnight fasting and analyzed within 4 hours after collection. HbA1c was measured with high pressure liquid chromatography (Arkray Adams, Japan). FPG was measured by the hexokinase method (Advia Autoanalyzer; Bayer Diagnostics, Germany). Diabetes was defined as HbA1c 6.5% or FPG 7.0 mmol/L. Prediabetes was classified as HbA1c between 5.7% and 6.4%. Results The study included 3523 individuals (2356 women) aged 30 years and above. Based on the HbA1c test, the prevalence of diabetes and prediabetes was 9.7% (95%CI, 8.7–10.7%; n = 342) and 34.6% (33.0–36.2; n = 1219), respectively. Based on the FPG test, the prevalence of diabetes and prediabetes was 6.3% (95%CI, 5.5–7.2%; n = 223) and 12.1% (11.1–13.2; n = 427). Among the 427 individuals identified by FPG as 'pre-diabetes', 28.6% were classified as diabetes by HbA1c test. The weighted kappa statistic of concordance between HbA1c and FPG was 0.55, with most of the discordance being in the prediabetes group. Conclusion These data indicate that there is a significant discordance in the diagnosis of diabetes between FPG and HbA1c measurements, and the discordance could have significant impact on clinical practice. FPG appears to underestimate the burden of undiagnosed diabetes.
Hoque, MA-A, Phinn, S & Roelfsema, C 2017, 'A systematic review of tropical cyclone disaster management research using remote sensing and spatial analysis', Ocean & Coastal Management, vol. 146, pp. 109-120.
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Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2017, 'Tropical cyclone disaster management using remote sensing and spatial analysis: A review', International Journal of Disaster Risk Reduction, vol. 22, pp. 345-354.
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Hosoe, S, Tuan, HD & Nguyen, TN 2017, '2D Bilinear programming for robust PID/DD controller design', International Journal of Robust and Nonlinear Control, vol. 27, no. 3, pp. 461-482.
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© 2016 John Wiley & Sons, Ltd.A new design method of PID structured controllers to achieve robust performance is developed. Both robust stabilization and performance conditions are losslessly expressed by bilinear constraints in the proportional-double derivative variable (kP,kDD) and the integral-derivative variable (kI,kD). Therefore, the considered control design can be efficiently solved by alternating optimization between (kP,kDD) and (kI,kD), which is a 2D computationally tractable program. The proposed method works equally efficiently whenever even higher order differential or integral terms are included in PID control to improve its robustness and performance. Numerical examples are provided to show the viability of the proposed development.
Hossain, M, Pota, H, Issa, W & Hossain, M 2017, 'Overview of AC Microgrid Controls with Inverter-Interfaced Generations', Energies, vol. 10, no. 9, pp. 1300-1300.
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Distributed generation (DG) is one of the key components of the emerging microgrid concept that enables renewable energy integration in a distribution network. In DG unit operation, inverters play a vital role in interfacing energy sources with the grid utility. An effective interfacing can successfully be accomplished by operating inverters with effective control techniques. This paper reviews and categorises different control methods (voltage and primary) for improving microgrid power quality, stability and power sharing approaches. In addition, the specific characteristics of microgrids are summarised to distinguish from distribution network control. Moreover, various control approaches including inner-loop controls and primary controls are compared according to their relative advantages and disadvantages. Finally, future research trends for microgrid control are discussed pointing out the research opportunities. This review paper will be a good basis for researchers working in microgrids and for industry to implement the ongoing research improvement in real systems.
Hossain, MA, Pota, HR, Haruni, AMO & Hossain, MJ 2017, 'DC-link voltage regulation of inverters to enhance microgrid stability during network contingencies', Electric Power Systems Research, vol. 147, pp. 233-244.
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Hossain, N, Haji Zaini, J & Mahlia, TMI 2017, 'A Review of Bioethanol Production from Plant-based Waste Biomass by Yeast Fermentation', International Journal of Technology, vol. 8, no. 1, pp. 5-5.
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© IJTech 2017. Commercialization of bioethanol has recently intensified due to its market stability, low cost, sustainability, alternative fuel energy composition, greener output and colossal fossil fuel depletion. Recently, because of greenhouse intensity worldwide, many researches are ongoing to reprocess the waste as well as turning down the environmental pollution. With this scenario, the invention of bioethanol was hailed as a great accomplishment to transform waste biomass to fuel energy and in turn reduce the massive usages of fossil fuels. In this study, our review enlightens various sources of plant-based waste feed stocks as the raw materials for bioethanol production because they do not adversely impact the human food chain. However, the cheapest and conventional fermentation method, yeast fermentation is also emphasized here notably for waste biomass-to-bioethanol conversion. Since the key fermenting agent, yeast is readily available in local and international markets, it is more cost-effective in comparison with other fermentation agents. Furthermore, yeast has genuine natural fermentation capability biologically and it produces zero chemical waste. This review also concerns a detailed overview of the biological conversion processes of lignocellulosic waste biomass-to-bioethanol, the diverse performance of different types of yeasts and yeast strains, plusbioreactor design, growth kinetics of yeast fermentation, environmental issues, integrated usages on modern engines and motor vehicles, as well as future process development planning with some novel co-products.
Hossain, N, Jalil, R, Mahlia, TMI & Zaini, J 2017, 'Calorific Value Analysis of Azadirachta Excelsa and Endospermum Malaccense as Potential Solid Fuels Feedstock', International Journal of Technology, vol. 8, no. 4, pp. 634-634.
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© IJTech 2017. Thermal conversion of woody biomass to fuel has been intensified in recent decades due to the depletion of fossil fuels, greenhouse effect and high energy demand worldwide. Screening the potential feedstock is being considered as one of the alternatives to identifying the most suitable biomass resources prior to being converted into renewable energy in the form of solid fuels, such as charcoal and briquettes. Generally, high calorific value (CV) indicates high potential of feedstock for briquettes, torrefied wood and coal generation. In this study, CV was characterized using a bomb calorimeter that was based on 3 different ranges of moisture content (MC) that are > 25%, 20%-25% and < 20% for two tropical tree species, namely Azadirachta excelsa (Sentang) and Endospermum malaccense (Sesenduk), respectively. This standard method for the characterization process was considered to determine the CV. Average CV for both samples ranged between 16-17 MJ/kg. The highest CV was 17.3490 MJ/kg and 17.1273 MJ/kg for Sesenduk and Sentang, respectively and calorific values were obtained at MC less than 20%. The experimental study demonstrated that the decreasing value of MC has increased the CV because of the high value of oxygen-to-carbon (O/C) ratio in the wood; additionally, the energy density of the wood sample was also improved when CV increased. Both of these species were proved to contain the potential of being feedstock as wood fuel resources, since they carry standard CVs, obtain fast growth with suitable conditions in Malaysia and are grown at very low cost of production for plantations, fertilizer, pesticides, labor, transportation and handling.
Hou, P, Cai, Y, Cheng, X, Zhang, X, Zhou, Z, Ye, Z, Zhang, L, Li, W & Shah, SP 2017, 'Effects of the hydration reactivity of ultrafine magnesium oxide on cement-based materials', Magazine of Concrete Research, vol. 69, no. 22, pp. 1135-1145.
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The size of magnesium oxide may greatly affect its behaviour in cement-based materials (CBMs), and this has not been fully investigated. The reactivity of ultrafine magnesium oxide (UFM) of size 40 nm to 20 μm was assessed, and its effects on the compressive strength and volume stability of cement mortar were investigated. The results showed that the hydration of UFM followed the first-order reaction mode in the first 3 d and then slowed down due to the alteration of the reaction to the diffusion-controlled mode. UFM contributed to an increase in compressive strength and a decrease in shrinkage of CBMs at the very early age, but hindered the hydration of cement at later ages, coarsened the microstructure, and decreased the later-age shrinkage to a much smaller extent than normal light-burnt magnesium oxide. The relatively high hydration reactivity of UFM may contribute to the formation of a more compact gel structure around cement particles at the very early age, which may hinder the reaction of cement at later ages, thus leading to the slowed property gain of CBMs at later ages. The findings from this study may help in the selection of magnesium oxide types for achieving a desired CBM with certain properties.
Hou, S, Chen, L, Tao, D, Zhou, S, Liu, W & Zheng, Y 2017, 'Multi-layer multi-view topic model for classifying advertising video', Pattern Recognition, vol. 68, pp. 66-81.
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© 2017 Elsevier Ltd The recent proliferation of advertising (ad) videos has driven the research in multiple applications, ranging from video analysis to video indexing and retrieval. Among them, classifying ad video is a key task because it allows automatic organization of videos according to categories or genres, and this further enables ad video indexing and retrieval. However, classifying ad video is challenging compared to other types of video classification because of its unconstrained content. While many studies focus on embedding ads relevant to videos, to our knowledge, few focus on ad video classification. In order to classify ad video, this paper proposes a novel ad video representation that aims to sufficiently capture the latent semantics of video content from multiple views in an unsupervised manner. In particular, we represent ad videos from four views, including bag-of-feature (BOF), vector of locally aggregated descriptors (VLAD), fisher vector (FV) and object bank (OB). We then devise a multi-layer multi-view topic model, mlmv_LDA, which models the topics of videos from different views. A topical representation for video, supporting category-related task, is finally achieved by the proposed method. Our empirical classification results on 10,111 real-world ad videos demonstrate that the proposed approach effectively differentiate ad videos.
Hu, C, Liu, X & Lu, J 2017, 'A bi-objective two-stage robust location model for waste-to-energy facilities under uncertainty', Decision Support Systems, vol. 99, pp. 37-50.
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© 2017 Elsevier B.V. Waste-to-energy (WTE) facilities have begun to play an increasingly important role in the management of municipal solid waste (MSW) worldwide. However, due to the environmental and economic impacts they impose on urban sustainability, the location of WTE facilities is always a sensitive issue. With the frequent involvement of private investors in WTE projects in recent years, the uncertainties associated with MSW generation often impose a huge financial risk on both the private investors involved and the government. Therefore, decision support for the location planning of WTE facilities is necessary and critical. A bi-objective two-stage robust model has been developed to help governments identify cost-effective and environmental-friendly WTE facility location strategies under uncertainty, in which one objective is to minimize worst-case annual government spending, while the other minimizes environmental disutility. To efficiently solve the model, a novel solution method has been developed based on a combination of the ϵ-constraint method and the column-and-constraint generation algorithm. The proposed model is demonstrated via a case study in the city of Shanghai where the government plans to locate incinerators to release pressure on sanitary landfills. The computational results show that the proposed model and solution method can effectively support decision-makers. A further sensitivity analysis reveals several useful MSW management insights.
Hu, L, Cao, L, Cao, J, Gu, Z, Xu, G & Wang, J 2017, 'Improving the Quality of Recommendations for Users and Items in the Tail of Distribution', ACM Transactions on Information Systems, vol. 35, no. 3, pp. 1-37.
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Short-head and long-tail distributed data are widely observed in the real world. The same is true of recommender systems (RSs), where a small number of popular items dominate the choices and feedback data while the rest only account for a small amount of feedback. As a result, most RS methods tend to learn user preferences from popular items since they account for most data. However, recent research in e-commerce and marketing has shown that future businesses will obtain greater profit from long-tail selling. Yet, although the number of long-tail items and users is much larger than that of short-head items and users, in reality, the amount of data associated with long-tail items and users is much less. As a result, user preferences tend to be popularity-biased. Furthermore, insufficient data makes long-tail items and users more vulnerable to shilling attack. To improve the quality of recommendations for items and users in the tail of distribution, we propose a coupled regularization approach that consists of two latent factor models: C-HMF, for enhancing credibility, and S-HMF, for emphasizing specialty on user choices. Specifically, the estimates learned from C-HMF and S-HMF recurrently serve as the empirical priors to regularize one another. Such coupled regularization leads to the comprehensive effects of final estimates, which produce more qualitative predictions for both tail users and tail items. To assess the effectiveness of our model, we conduct empirical evaluations on large real-world datasets with various metrics. The results prove that our approach significantly outperforms the compared methods.
Hu, L, Cao, L, Cao, J, Gu, Z, Xu, G & Yang, D 2017, 'Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains', ACM Transactions on Information Systems, vol. 35, no. 2, pp. 1-37.
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In the real-world environment, users have sufficient experience in their focused domains but lack experience in other domains. Recommender systems are very helpful for recommending potentially desirable items to users in unfamiliar domains, and cross-domain collaborative filtering is therefore an important emerging research topic. However, it is inevitable that the cold-start issue will be encountered in unfamiliar domains due to the lack of feedback data. The Bayesian approach shows that priors play an important role when there are insufficient data, which implies that recommendation performance can be significantly improved in cold-start domains if informative priors can be provided. Based on this idea, we propose a Weighted Irregular Tensor Factorization (WITF) model to leverage multi-domain feedback data across all users to learn the cross-domain priors w.r.t. both users and items. The features learned from WITF serve as the informative priors on the latent factors of users and items in terms of weighted matrix factorization models. Moreover, WITF is a unified framework for dealing with both explicit feedback and implicit feedback. To prove the effectiveness of our approach, we studied three typical real-world cases in which a collection of empirical evaluations were conducted on real-world datasets to compare the performance of our model and other state-of-the-art approaches. The results show the superiority of our model over comparison models.
Hu, R, Wen, S, Zeng, Z & Huang, T 2017, 'A short-term power load forecasting model based on the generalized regression neural network with decreasing step fruit fly optimization algorithm', Neurocomputing, vol. 221, pp. 24-31.
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Short term power load forecasting plays an important role in the security of power system. In the past few years, application of artificial neural network (ANN) for short-term load forecasting (STLF) has become a research hotspots. Generalized regression neural network (GRNN) has been proved to be suitable for solving the non-linear problems. And according to the historical load curve, it can be known that STLF is a non-linear problem. Thus, the GRNN was used for STLF in this paper. However, the value of spread parameter σ determines the performance of the GRNN. The fruit fly optimization algorithm with decreasing step size (SFOA) is introduced to select an appropriate spread parameter σ. Combined with the weather factors and the periodicity of short-term load, an effective STLF model based on the GRNN with decreasing step FOA was proposed. Performance of the proposed SFOA-GRNN model is compared with other ANN on the basis of prediction error.
Hu, S-S, Chen, P, Wang, B & Li, J 2017, 'Protein binding hot spots prediction from sequence only by a new ensemble learning method', Amino Acids, vol. 49, no. 10, pp. 1773-1785.
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Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods have been widely used for hot spot prediction through sequence or structure characterization. As the structural information of proteins is not always solved, and thus hot spot identification from amino acid sequences only is more useful for real-life applications. This work proposes a new sequence-based model that combines physicochemical features with the relative accessible surface area of amino acid sequences for hot spot prediction. The model consists of 83 classifiers involving the IBk (Instance-based k means) algorithm, where instances are encoded by important properties extracted from a total of 544 properties in the AAindex1 (Amino Acid Index) database. Then top-performance classifiers are selected to form an ensemble by a majority voting technique. The ensemble classifier outperforms the state-of-the-art computational methods, yielding an F1 score of 0.80 on the benchmark binding interface database (BID) test set.http://www2.ahu.edu.cn/pchen/web/HotspotEC.htm .
Hu, Y, Wang, XC, Sun, Q, Ngo, HH, Yu, Z, Tang, J & Zhang, Q 2017, 'Characterization of a hybrid powdered activated carbon-dynamic membrane bioreactor (PAC-DMBR) process with high flux by gravity flow: Operational performance and sludge properties', Bioresource Technology, vol. 223, pp. 65-73.
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Three PAC-DMBRs were developed for wastewater treatment under different PAC dosages with biomass concentrations averaged at 2.5, 3.5 and 5.0g/L. The DMBRs could be continuously operated at 40-100L/m(2)h, while higher fluxes were obtained within the PAC-DMBRs with hydraulic retention times varying in 4-10h. A dose of 1g/L PAC brought about obvious improvement in the sludge particle size distribution, settling, flocculating and dewatering properties due to the formation of biological PAC, and the sludge properties were further improved at a higher PAC dose (3g/L). The addition of PAC notably shortened the DM formation time after air backwashing and enhanced pollutant removal. Moreover, under a long solid retention time (approximately 150d), the concentrations of both soluble and bound extracellular polymeric substances (EPS) decreased substantially because of the adsorption and biodegradation effects of the biological PAC. No obvious impact on biomass activity was observed with PAC addition.
Hu, Y, Yang, Y, Wang, XC, Hao Ngo, H, Sun, Q, Li, S, Tang, J & Yu, Z 2017, 'Effects of powdered activated carbon addition on filtration performance and dynamic membrane layer properties in a hybrid DMBR process', Chemical Engineering Journal, vol. 327, pp. 39-50.
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© 2017 Elsevier B.V. A powdered activated carbon-dynamic membrane bioreactor (PAC-DMBR) was developed and used to treat domestic wastewater by dosing with 3 g/L PAC. The experimental results were compared with those of a control DMBR to investigate the filtration performance and various properties of the dynamic membrane (DM) layer. One flat-sheet DM module made of nylon mesh (pore size 75 μm) was used for effluent production at a high stable flux (50–100 L/m 2 h) under a 10 cm water head by gravity flow, resulting in continuous operation cycles of 60–120 h. During the operation period, the PAC-DMBR showed enhanced removal efficiency of pollutants, higher stable membrane flux (10 L/m 2 h more), lower filtration resistance (6.0–8.0 × 10 10 m −1 ), quicker formation of the DM layer (within 5 min), and better DM layer regeneration after air backwashing. The DM layer in the PAC-DMBR showed a more porous and incompressible structure, because less extracellular polymeric substance and a portion of the biological PAC were incorporated into the DM layer formed as verified by the analytical results. Using high-throughput pyrosequencing technology, it was revealed that at the genus level the diversity of bacterial communities increased from 18 to 23 genera, while several genera that were favored in the PAC-assisted environment or were responsible for degrading complex organics were enriched. Moreover, the abundance of phylum Proteobacteria, which served as pioneer surface colonizers, was reduced in the PAC-DMBR. It was concluded that PAC addition could modify various aspects of the activated sludge and the DM layer properties, which affected the filtration behavior of the DM layer in the PAC-DMBR.
Hu, Y, Zheng, K, Wang, X & Yang, Y 2017, 'WORM-HUNTER: A Worm Guard System using Software-defined Networking', KSII Transactions on Internet and Information Systems, vol. 11, no. 1, pp. 484-510.
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Huang, J, Lin, W, Qiu, F, Jiang, C, Lei, D & Guo, YJ 2017, 'A Low Profile, Ultra-Lightweight, High Efficient Circularly-Polarized Antenna Array for Ku Band Satellite Applications', IEEE Access, vol. 5, pp. 18356-18365.
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© 2013 IEEE. A novel low-profile, ultra-lightweight, high-efficient circularly polarized (CP) planar patch antenna array is reported for Ku-band satellite TV reception applications. The basic radiating element of the antenna array is realized by a $2 \times 2$ corner-removed patch subarray. This $2 \times 2$ patch subarray is center-fed by a rectangular coupling aperture etched on the top surface of a substrate-integrated-waveguide cavity. A novel compact sequential rotation feeding technique is adopted to broaden the operating bandwidth without occupying additional area. The $2 \times 2$ CP subarray can be easily scaled up for large size antenna arrays due to its single layer feeding network and compact radiating elements. In addition, the patch radiators are printed on a thin layer of Polyimide film backed by a piece of supporting foam to minimize the entire weight. To verify the design concept, a 96-element ( $16 \times 6$ ) CP patch array was fabricated and tested. Measured results show that the operating bandwidth is 700 MHz from 11.55 to 12.25 GHz. The gain is stable across the operating bandwidth with a realized peak gain of 26.4 dBic. The height of the antenna is $0.05~\lambda {0}$ and the total weight is only 66.5 g. It serves as an excellent candidate for Ku-band satellite applications.
Huang, J, Qiu, F, Lin, W, Tang, Z, Lei, D, Yao, M, Chu, Q-X & Guo, YJ 2017, 'A New Compact and High Gain Circularly-Polarized Slot Antenna Array for Ku-Band Mobile Satellite TV Reception', IEEE Access, vol. 5, pp. 6707-6714.
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Huang, M, Ouyang, L, Chen, Z, Peng, C, Zhu, X & Zhu, M 2017, 'Hydrogen production via hydrolysis of Mg-oxide composites', International Journal of Hydrogen Energy, vol. 42, no. 35, pp. 22305-22311.
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Huang, M, Ouyang, L, Liu, J, Wang, H, Shao, H & Zhu, M 2017, 'Enhanced hydrogen generation by hydrolysis of Mg doped with flower-like MoS 2 for fuel cell applications', Journal of Power Sources, vol. 365, pp. 273-281.
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Huang, S & Dissanayake, G 2017, 'Special Issue on Localization and Mapping in Challenging Environments', Robotics and Autonomous Systems, vol. 97, pp. 16-17.
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Huang, S, Wei, Z, Yuan, X, Feng, Z & Zhang, P 2017, 'Performance Characterization of Machine-to-Machine Networks With Energy Harvesting and Social-Aware Relays', IEEE Access, vol. 5, pp. 13297-13307.
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Huang, S, Zhang, J, Schonfeld, D, Wang, L & Hua, X-S 2017, 'Two-Stage Friend Recommendation Based on Network Alignment and Series Expansion of Probabilistic Topic Model', IEEE Transactions on Multimedia, vol. 19, no. 6, pp. 1314-1326.
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© 2017 IEEE. Precise friend recommendation is an important problem in social media. Although most social websites provide some kinds of auto friend searching functions, their accuracies are not satisfactory. In this paper, we propose a more precise auto friend recommendation method with two stages. In the first stage, by utilizing the information of the relationship between texts and users, as well as the friendship information between users, we align different social networks and choose some 'possible friends.' In the second stage, with the relationship between image features and users, we build a topic model to further refine the recommendation results. Because some traditional methods, such as variational inference and Gibbs sampling, have their limitations in dealing with our problem, we develop a novel method to find out the solution of the topic model based on series expansion. We conduct experiments on the Flickr dataset to show that the proposed algorithm recommends friends more precisely and faster than traditional methods.
Huang, X & Guo, YJ 2017, 'Radio Frequency Self-Interference Cancellation With Analog Least Mean-Square Loop', IEEE Transactions on Microwave Theory and Techniques, vol. 65, no. 9, pp. 3336-3350.
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© 1963-2012 IEEE. A multitap adaptive filter with analog least mean-square (ALMS) loop is proposed in this paper for effective and low complexity self-interference cancellation implemented as part of the radio frequency frontend in a full duplex transceiver. Comprehensive analyses of the ALMS loop's behaviors at both micro and macroscales are presented for a wireless communication system with single carrier signaling. It is revealed that there is always an irreducible residual interference due to the cyclostationary property of the transmitted signal. The interference suppression ratio (ISR) lower bound is derived accordingly, which can be used as a design rule for determining the ALMS loop parameter. Stationary analysis shows that the convergence speed and achievable ISR of the ALMS loop are determined by the loop gain and the autocorrelation function of the transmitted signal. The interference channel modeling error with the adaptive filter also accounts for part of the residual interference power. These theoretical findings are verified by simulation and experimental results.
Huang, Y, Zhu, D, Qian, Y, Zhang, Y, Porter, AL, Liu, Y & Guo, Y 2017, 'A hybrid method to trace technology evolution pathways: a case study of 3D printing', Scientometrics, vol. 111, no. 1, pp. 185-204.
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Hurley-Walker, N, Callingham, JR, Hancock, PJ, Franzen, TMO, Hindson, L, Kapińska, AD, Morgan, J, Offringa, AR, Wayth, RB, Wu, C, Zheng, Q, Murphy, T, Bell, ME, Dwarakanath, KS, For, B, Gaensler, BM, Johnston-Hollitt, M, Lenc, E, Procopio, P, Staveley-Smith, L, Ekers, R, Bowman, JD, Briggs, F, Cappallo, RJ, Deshpande, AA, Greenhill, L, Hazelton, BJ, Kaplan, DL, Lonsdale, CJ, McWhirter, SR, Mitchell, DA, Morales, MF, Morgan, E, Oberoi, D, Ord, SM, Prabu, T, Shankar, NU, Srivani, KS, Subrahmanyan, R, Tingay, SJ, Webster, RL, Williams, A & Williams, CL 2017, 'GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey – I. A low-frequency extragalactic catalogue', Monthly Notices of the Royal Astronomical Society, vol. 464, no. 1, pp. 1146-1167.
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Abstract Using the Murchison Widefield Array (MWA), the low-frequency Square Kilometre Array precursor located in Western Australia, we have completed the GaLactic and Extragalactic All-sky MWA (GLEAM) survey, and present the resulting extragalactic catalogue, utilizing the first year of observations. The catalogue covers 24 831 square degrees, over declinations south of +30° and Galactic latitudes outside 10° of the Galactic plane, excluding some areas such as the Magellanic Clouds. It contains 307 455 radio sources with 20 separate flux density measurements across 72–231 MHz, selected from a time- and frequency-integrated image centred at 200 MHz, with a resolution of ≈2 arcmin. Over the catalogued region, we estimate that the catalogue is 90 per cent complete at 170 mJy, and 50 per cent complete at 55 mJy, and large areas are complete at even lower flux density levels. Its reliability is 99.97 per cent above the detection threshold of 5σ, which itself is typically 50 mJy. These observations constitute the widest fractional bandwidth and largest sky area survey at radio frequencies to date, and calibrate the low-frequency flux density scale of the southern sky to better than 10 per cent. This paper presents details of the flagging, imaging, mosaicking and source extraction/characterization, as well as estimates of the completeness and reliability. All source measurements and images are available online.1 This is the first in a series of publications describing the GLEAM survey results.
Hussain, W, Hussain, FK, Hussain, OK, Damiani, E & Chang, E 2017, 'Formulating and managing viable SLAs in cloud computing from a small to medium service provider's viewpoint: A state-of-the-art review', Information Systems, vol. 71, pp. 240-259.
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In today's competitive world, service providers need to be customer-focused and proactive in their marketing strategies to create consumer awareness of their services. Cloud computing provides an open and ubiquitous computing feature in which a large random number of consumers can interact with providers and request services. In such an environment, there is a need for intelligent and efficient methods that increase confidence in the successful achievement of business requirements. One such method is the Service Level Agreement (SLA), which is comprised of service objectives, business terms, service relations, obligations and the possible action to be taken in the case of SLA violation. Most of the emphasis in the literature has, until now, been on the formation of meaningful SLAs by service consumers, through which their requirements will be met. However, in an increasingly competitive market based on the cloud environment, service providers too need a framework that will form a viable SLA, predict possible SLA violations before they occur, and generate early warning alarms that flag a potential lack of resources. This is because when a provider and a consumer commit to an SLA, the service provider is bound to reserve the agreed amount of resources for the entire period of that agreement – whether the consumer uses them or not. It is therefore very important for cloud providers to accurately predict the likely resource usage for a particular consumer and to formulate an appropriate SLA before finalizing an agreement. This problem is more important for a small to medium cloud service provider which has limited resources that must be utilized in the best possible way to generate maximum revenue. A viable SLA in cloud computing is one that intelligently helps the service provider to determine the amount of resources to offer to a requesting consumer, and there are number of studies on SLA management in the literature. The aim of this paper is two-fold. First, it pr...
Hussain, W, Hussain, OK, Hussain, FK & Khan, MQ 2017, 'Usability Evaluation of English, Local and Plain Languages to Enhance On-Screen Text Readability: A Use Case of Pakistan', Global Journal of Flexible Systems Management, vol. 18, no. 1, pp. 33-49.
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© 2016, Global Institute of Flexible Systems Management. In today’s digital world, information can very easily be accessed and digitally processed anywhere. Devices which are capable of processing digital data range from desktop computers to laptops, mobile phones, tablets, and personal digital assistants. For effective communication, text on a Web site should catch a reader’s attention and should be easy to both read and understand. Different constraints are associated with on-screen text readability and legibility, such as font size, color, and style, as well as foreground and background color contrast, line spacing, text congestion, vocabulary and grammar, but text recognition and comprehension are two of the major problems. In this study, we address the issue of how to enhance text readability for non-native English speakers who have a basic understanding of English language and speak local languages which are not formally taught in academia. We select a use case in Pakistan, a country in which English and Urdu are the official languages, and a number of local languages are spoken in different parts of the country. Due to the wide variety of local languages, no Web site can support the many local language scripts or alphabets and display them on digital devices. When users with only a basic knowledge of English—particularly low-literate users from a local language background—try to read an English text, it is highly challenging for them to understand the meaning of words. In this study, we propose a plain language scheme in which a text is converted into a roman text. A roman text is formed by using the English alphabet and combining letters in such a way that when it is read, it sounds like a local language. To evaluate the applicability of our approach, we conducted a survey of users from different educational backgrounds, using a text written in English, local and plain language from users who speak particular local language. For each survey, we ...
Hussein, F & Piccardi, M 2017, 'V-JAUNE', ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 13, no. 2, pp. 1-19.
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Video summarization and action recognition are two important areas of multimedia video analysis. While these two areas have been tackled separately to date, in this article, we present a latent structural SVM framework to recognize the action and derive the summary of a video in a joint, simultaneous fashion. Efficient inference is provided by a submodular score function that accounts for the action and summary jointly. In this article, we also define a novel measure to evaluate the quality of a predicted video summary against the annotations of multiple annotators. Quantitative and qualitative results over two challenging action datasets—the ACE and MSR DailyActivity3D datasets—show that the proposed joint approach leads to higher action recognition accuracy and equivalent or better summary quality than comparable approaches that perform these tasks separately.
Huynh, NV, Hoang, DT, Lu, X, Niyato, D, Wang, P & Kim, DI 2017, 'Ambient Backscatter Communications: A Contemporary Survey', IEEE Communications Surveys and Tutorials, vol. 20, no. 4, pp. 2889-2922.
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Recently, ambient backscatter communications has been introduced as acutting-edge technology which enables smart devices to communicate by utilizingambient radio frequency (RF) signals without requiring active RF transmission.This technology is especially effective in addressing communication and energyefficiency problems for low-power communications systems such as sensornetworks. It is expected to realize numerous Internet-of-Things (IoT)applications. Therefore, this paper aims to provide a contemporary andcomprehensive literature review on fundamentals, applications, challenges, andresearch efforts/progress of ambient backscatter communications. In particular,we first present fundamentals of backscatter communications and briefly reviewbistatic backscatter communications systems. Then, the general architecture,advantages, and solutions to address existing issues and limitations of ambientbackscatter communications systems are discussed. Additionally, emergingapplications of ambient backscatter communications are highlighted. Finally, weoutline some open issues and future research directions.
Imdadul, HK, Masjuki, HH, Kalam, MA, Zulkifli, NWM, Kamruzzaman, M, Shahin, MM & Rashed, MM 2017, 'Evaluation of oxygenated n-butanol-biodiesel blends along with ethyl hexyl nitrate as cetane improver on diesel engine attributes', Journal of Cleaner Production, vol. 141, pp. 928-939.
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Imdadul, HK, Rashed, MM, Shahin, MM, Masjuki, HH, Kalam, MA, Kamruzzaman, M & Rashedul, HK 2017, 'Quality improvement of biodiesel blends using different promising fuel additives to reduce fuel consumption and NO emission from CI engine', Energy Conversion and Management, vol. 138, pp. 327-337.
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Imdadul, HK, Zulkifli, NWM, Masjuki, HH, Kalam, MA, Kamruzzaman, M, Rashed, MM, Rashedul, HK & Alwi, A 2017, 'Experimental assessment of non-edible candlenut biodiesel and its blend characteristics as diesel engine fuel', Environmental Science and Pollution Research, vol. 24, no. 3, pp. 2350-2363.
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Imran Azim, M, Hossain, J & Pota, H 2017, 'Design of Droop-based Control for Power Management in Islanded RL-type Microgrids', International Journal of Emerging Electric Power Systems, vol. 18, no. 2.
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AbstractThis paper proposes a new type of generalized droop-based proportional power sharing scheme during load change for parallel inverter-interfaced islanded microgrids, which is an automatic strategy and is independent of any particular nature of transmission lines, i.e., resistive or inductive. Real and reactive powers are shared in proportion to the droop gains by implementing the voltage control law proposed in this paper; in which the inverter-interfaced voltage-sources are kept at equal reference values. The control gains are chosen based on eigenvalue analysis in a way that the system stability is ascertained. The performance of the designed controller is simulated under different microgrid structures such as load variation and various types of transmission lines; in which the results show superior dynamic performance in comparison to the conventional droop-based control strategy.
Inan, DI & Beydoun, G 2017, 'Disaster Knowledge Management Analysis Framework Utilizing Agent-Based Models: Design Science Research Approach', Procedia Computer Science, vol. 124, pp. 116-124.
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Indraratna, B & Sun, Y 2017, 'Closure to “Laboratory Assessment of the Role of Particle Size Distribution on the Deformation and Degradation of Ballast under Cyclic Loading” by Buddhima Indraratna, Yifei Sun, and Sanjay Nimbalkar', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 9, pp. 07017023-07017023.
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Indraratna, B, Baral, P, Ameratunga, J & Kendaragama, B 2017, 'Potential biological and chemical clogging of piezometer filters in acid sulphate soil', Australian Geomechanics Journal, vol. 52, no. 2, pp. 79-85.
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Instrumentation for performance monitoring of an embankment built on soft soils is vital for assessing the progress of consolidation and confirming (or refuting) soil parameters used in design when there are significant design uncertainties and the monitoring data can be used to calibrate the design soil parameters. A suite of instruments including settlement plates, extensometers, piezometers, inclinometers is often employed for this purpose. In the first Author's experience, erroneous readings interpretations of pore water pressure (PWP) readings have been reported in various case studies involving transport infrastructure development and reclamations works both in Australia and South East Asia, especially in low-lying acid sulphate soil floodplains. It has been observed that in spite of the presence of vertical drains (PVDs), excess pore water pressure readings from vibrating wire piezometers (VWPs) do not always dissipate as fast as expected especially after a certain period of time, typically a year. The article discusses the potential factors affecting the reliability of VWPs including filter tip clogging, extreme smearing of soil adjoining the filter, gas generation or cavitation, chemical alteration or corrosion of the filter, electro-osmotic effects and cavitation due to bacterial activity. Based on this, the response of VWPs may be divided into a distinct trilinear trend, observed for much of the Australian northern and eastern coastal belt that is predominantly affected by Acid sulphate soil (ASS) conditions where oxidisable pyrite layers are present within relatively shallow depths of the upper Holocene clay.
Indraratna, B, Ngo, NT & Rujikiatkamjorn, C 2017, 'Improved Performance of Ballasted Rail Tracks Using Plastics and Rubber Inclusions', Procedia Engineering, vol. 189, pp. 207-214.
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Current railroads require significant upgrading to meet the challenges of heavier loads at higher speeds. Due to excessive track degradation, the Australian rail industry spends large amounts on frequent track repair and maintenance, as well as ground improvement prior to track construction where soft and saturated subgrade soils pose considerable difficulties in design and construction. Moreover, the degradation of ballast particles under impact loading seriously hampers the safety and efficiency of rail tracks, which leads to speed restrictions and more frequent track upgrading. Hence, there is a need for innovative design solutions that can extend the service life of tracks to cater for faster and heavier train traffic. The use of planar geosynthetics and recycled rubber mats placed at the interface of ballast and subballast layer has proven an effective approach to mitigate ballast degradation and improve track longevity. This paper presents the current state-of-the-art knowledge of rail track geomechanics conducted at the University of Wollongong (UOW) including topics relating to laboratory testing and computational modeling approaches. The load-deformation responses of rubber mat/geogrid-stabilised ballast are studied in the laboratory using a large-scale drop weight impact testing facility, and Track Process Simulation Apparatus (TPSA). Numerical modelling using discrete element methods (DEM) are used to model geogrid-reinforced ballasted tracks, capturing both the discrete nature of ballast subject to various types of loading and boundary conditions. These results provide promising approaches to incorporate into the existing track design routines catering for future high speed and heavy haul trains.
Indraratna, B, Pathirage, PU & Banasiak, LJ 2017, 'Remediation of acidic groundwater by way of permeable reactive barrier', Environmental Geotechnics, vol. 4, no. 4, pp. 284-298.
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A permeable reactive barrier (PRB) was installed in the Shoalhaven Floodplain about 100 km south of Sydney (Australia), where acidic groundwater generation from pyritic soil poses a severe environmental and socioeconomic problem. Recycled concrete aggregates were a promising source of alkalinity-generating material and adopted as the reactive media for this PRB. The current study simulates the performance of the PRB through coupling geochemical reactions involved with recycled concrete and acidic groundwater with geohydraulics (transient groundwater flows). This is the first such attempt made for time-dependent modelling and performance verification of a PRB located in acid sulfate soil (ASS) terrain. The developed model describes the chemical clogging due to mineral precipitates and the associated reductions in porosity and hydraulic conductivity of the reactive medium. The governing equations of the model were incorporated into commercial software, MODFLOW and RT3D. The field results are in favourable agreement with the model predictions, confirming that the reduction in hydraulic conductivity due to mineral precipitation occurs predominantly at the entrance zone of the PRB and insignificantly in the middle and exit zones after 7 years of operation. Mineralogical analysis undertaken on sample specimens from the PRB also confirms that clogging is minimal at the entrance zone.
Indraratna, B, Sun, Q & Grant, J 2017, 'Behaviour of subballast reinforced with used tyre and potential application in rail tracks', Transportation Geotechnics, vol. 12, pp. 26-36.
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Rubber tyres have a three dimensional cylindrical structure, and as such could be used to stabilise foundations by increasing the bearing capacity and reducing settlement for transport infrastructure. It is therefore expected that in railroad engineering, a capping layer reinforced with rubber tyres could help to reduce the thickness of the granular layer (i.e. ballast), improve the track bearing capacity, and reduce the frequency of maintenance. However, there is a notable gap between the conceptual theories and real-life applications pertaining to the mechanisms of rubber tyre-reinforced foundations. In pavement engineering, the bearing capacity is closely linked to plate load tests. In this study, plate load tests were carried out on a single tyre filled with subballast material and subjected to a vertical load. This testing process was then modelled using the Finite Element software ABAQUS to study and quantify the interaction between the tyre and the granular medium. The experimental and numerical results reveal that the rubber tyre can significantly increase the modulus and ultimate bearing capacity of the granular layer. The numerical process was further extended to a finite element track model to demonstrate the expected response of a ballasted railway track with and without tyre reinforcement.
Indraratna, B, Sun, Q, Ngo, NT & Rujikiatkamjorn, C 2017, 'Current research into ballasted rail tracks: model tests and their practical implications', Australian Journal of Structural Engineering, vol. 18, no. 3, pp. 204-220.
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Ballasted rail tracks are the most important mode of transportation in terms of traffic tonnage serving the needs of bulk freight and passenger movement, but under train loads, the particles degrade due to breakage and the progressive accumulation of external fines or mud-pumping under the subgrade, all of which reduce its shear strength and increase track instability. These actions adversely affect the safety, passenger comfort and efficiency of tracks, as well as enforcing speed restrictions and more frequent track maintenance. In spite of advances in rail track geotechnology, the optimum choice of ballast for track design is still considered critical because ballast degradation is influenced by the amplitude and number of load cycles, particle gradation, track confining pressure and the angularity and fracture strength of individual grains. One of the most effective methods of enhancing track stability and reducing the stresses transmitted to a soft subgrade layer is to increase the stiffness of the overlying granular media. This paper presents our current knowledge of rail track geomechanics, including important concepts/topics related to laboratory testing and computational modelling approaches used to study the load–deformation behaviour of ballast improved with waste tyres, synthetic geogrids and geocells.
Indraratna, B, Zhong, R, Fox, PJ & Rujikiatkamjorn, C 2017, 'Large-Strain Vacuum-Assisted Consolidation with Non-Darcian Radial Flow Incorporating Varying Permeability and Compressibility', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 1, pp. 04016088-04016088.
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Iranmanesh, S, Ong, HC, Ang, BC, Sadeghinezhad, E, Esmaeilzadeh, A & Mehrali, M 2017, 'Thermal performance enhancement of an evacuated tube solar collector using graphene nanoplatelets nanofluid', Journal of Cleaner Production, vol. 162, pp. 121-129.
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Irga, PJ, Abdo, P, Zavattaro, M & Torpy, FR 2017, 'An assessment of the potential fungal bioaerosol production from an active living wall', Building and Environment, vol. 111, pp. 140-146.
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© 2016 Active living walls, or indoor air biofilters, have been proposed as a sustainable and aesthetic means of improving indoor air quality. However these systems have yet to be adequately assessed for their potential contribution to airborne fungal proliferation in indoor spaces. The current work represents a simulation study to determine, under realistic office conditions, whether a typical active living wall makes a quantifiable contribution to the airborne aeromycota. We found that the living wall studied made no significant contribution to the density or diversity of airborne culturable fungi in a test room. Few organisms of concern to public health were identified. We conclude that active biofilters are unlikely to make hazardous contributions to indoor fungi; however, further work that documents the bioaerosol generation rate with variations in temperature, airflow, plant varieties, planting densities, maintenance schedule, age of plants, plant growth substrates and substrate moisture content need further elucidation.
Irga, PJ, Braun, JT, Douglas, ANJ, Pettit, T, Fujiwara, S, Burchett, MD & Torpy, FR 2017, 'The distribution of green walls and green roofs throughout Australia: Do policy instruments influence the frequency of projects?', Urban Forestry & Urban Greening, vol. 24, pp. 164-174.
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© 2017 Elsevier GmbH Green roofs and green walls are gaining popularity as a means of mitigating a range of environmental impacts associated with urbanisation. Although this technology has been widely implemented in some parts of the world, uptake within Australia has been slow. This might be attributed to a range of factors, including a lack of awareness; a scarcity of urban green infrastructure policies; a lack of examples to give urban designers confidence in the technology; and perhaps also a limited number of professionals capable of installing green infrastructure systems. This paper researches the distribution of green wall and green roof projects in urban Australia, and the possible influence of local government policies and guidelines that have been designed to promote the increase of green infrastructure in Australia's cities. Differences were observed among project distributions and frequency, both within and between cities. In addition, councils that offered policy instruments and guidance tended to have more green wall and green roof projects than those which have no such policies in place. Compared to successful examples seen internationally, further policy implementation in Australia could increase the frequency of green infrastructure projects, indicating that governmental influence may play a substantial role in encouraging green infrastructure installation.
Irga, PJ, Paull, NJ, Abdo, P & Torpy, FR 2017, 'An assessment of the atmospheric particle removal efficiency of an in-room botanical biofilter system', Building and Environment, vol. 115, pp. 281-290.
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© 2017 Elsevier Ltd In addition to the growing requirement to reduce building energy needs, demand has arisen to find sustainable methods of improving indoor air quality. Recent advances in green wall technology have led to the development of activated systems, termed botanical biofilters, that move air through the plant growth substrate to increase the rate at which the interior atmospheric environment is exposed to the components of the plant-substrate system that are active in air pollutant removal. Development of this technology is moving towards green wall integration within building air conditioning and ventilation systems. The work presented here describes an evaluation of several parameters essential for determining the functionality of a modular botanical biofilter, as well as experiments to systematically determine the filtration performance of the device, specifically the single-pass particulate rem filtration efficiency was evaluated and defined. The maximum filtration efficiency for total suspended particulate matter peaked at an air flow rate of 11.25 L s−1 through the 0.25 m2 filter, with any increases in air flow rate met with a reduction in efficiency. The system recorded removal efficiencies were 53.35 ± 9.73% for total suspend particles, 53.51 ± 15.99% for PM10, and 48.21 ± 14.71% for PM2.5. Comparisons were made against the single pass efficiency of the system without the botanical component, as well as a common in-duct pleated panel air filter, indicating that further development is required to enhance the filtration capacity of the system if it is match current air filtration standards.
Islam, MR, Das, NG, Barua, P, Hossain, MB, Venkatramanan, S & Chung, SY 2017, 'Environmental assessment of water and soil contamination in Rajakhali Canal of Karnaphuli River (Bangladesh) impacted by anthropogenic influences: a preliminary case study', Applied Water Science, vol. 7, no. 2, pp. 997-1010.
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Islam, MR, Mahfuz-Ur-Rahman, AM, Islam, MM, Guo, YG & Zhu, JG 2017, 'Modular Medium-Voltage Grid-Connected Converter With Improved Switching Techniques for Solar Photovoltaic Systems', IEEE Transactions on Industrial Electronics, vol. 64, no. 11, pp. 8887-8896.
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© 1982-2012 IEEE. The high-frequency common magnetic-link made of amorphous material, as a replacement for common dc-link, has been gaining considerable interest for the development of solar photovoltaic medium-voltage converters. Even though the common magnetic-link can almost maintain identical voltages at the secondary terminals, the power conversion system loses its modularity. Moreover, the development of high-capacity high-frequency inverter and power limit of the common magnetic-link due to leakage inductance are the main challenging issues. In this regard, a new concept of identical modular magnetic-links is proposed for high-power transmission and isolation between the low and the high voltage sides. Third harmonic injected sixty degree bus clamping pulse width modulation and third harmonic injected thirty degree bus clamping pulse width modulation techniques are proposed which show better frequency spectra as well as reduced switching loss. In this paper, precise loss estimation method is used to calculate switching and conduction losses of a modular multilevel cascaded converter. To ensure the feasibility of the new concepts, a reduced size of 5 kVA rating, three-phase, five-level, 1.2 kV converter is designed with two 2.5 kVA identical high-frequency magnetic-links using Metglas magnetic alloy-based cores.
Islam, MS, Saha, SC, Sauret, E, Gemci, T & Gu, YT 2017, 'Pulmonary aerosol transport and deposition analysis in upper 17 generations of the human respiratory tract', Journal of Aerosol Science, vol. 108, pp. 29-43.
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© 2017 Elsevier Ltd The major problem in understanding the therapeutically targeted drug delivery system in the deeper airways of the human lung is the lack of adequate data of particle transport and deposition (TD) in the transitional and respiratory zones (deeper airways) of the human lung. An understanding of the morphometry of the pulmonary airways and the lungs forms the primary step in a study of pulmonary aerosol deposition. The present study is the first-ever approach to explore the pulmonary aerosol TD in a digital 17-generation human pulmonary airway model. The present numerical study achieved the lack of the particle TD data in the deeper airways of the human lung. This paper presents a 3-D (3-dimensional) CFD (Computational Fluid Dynamics) study of an anatomically realistic 17-generation lung bronchial tree model based on the high-resolution computer tomography (HRCT) data by Schmidt et al. (2004). Physical morphometry is necessary for sufficiently calculating air and particle dynamics in human pulmonary airways with available data on a large number of generations. A Lagrangian-based Discrete Phase Model (DPM) is used to study the particle TD in the 17-generation of the lung airways. The numerical results demonstrate that inertial impaction is dominant in the upper airways and a large percentage of particles is deposited in the upper airways. The numerical results also illustrate that a large percentage of smaller diameter particles leaves through the airway outlet boundary at the 17th generation irrespective of breathing patterns. The escaped particles are considered to continue to follow the airway flow field further downstream after the 17th generation till the 23rd generation and some of them will reach the alveolar sacs region. This computational model could potentially aid in overcoming the nanobiotechnology toxicity problem for drug delivery in the deeper airways.
Islam, MS, Saha, SC, Sauret, E, Gemci, T, Yang, IA & Gu, YT 2017, 'Ultrafine particle transport and deposition in a large scale 17-generation lung model', Journal of Biomechanics, vol. 64, pp. 16-25.
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© 2017 Elsevier Ltd To understand how to assess optimally the risks of inhaled particles on respiratory health, it is necessary to comprehend the uptake of ultrafine particulate matter by inhalation during the complex transport process through a non-dichotomously bifurcating network of conduit airways. It is evident that the highly toxic ultrafine particles damage the respiratory epithelium in the terminal bronchioles. The wide range of in silico available and the limited realistic model for the extrathoracic region of the lung have improved understanding of the ultrafine particle transport and deposition (TD) in the upper airways. However, comprehensive ultrafine particle TD data for the real and entire lung model are still unavailable in the literature. Therefore, this study is aimed to provide an understanding of the ultrafine particle TD in the terminal bronchioles for the development of future therapeutics. The Euler-Lagrange (E-L) approach and ANSYS fluent (17.2) solver were used to investigate ultrafine particle TD. The physical conditions of sleeping, resting, and light activity were considered in this modelling study. A comprehensive pressure-drop along five selected path lines in different lobes was calculated. The non-linear behaviour of pressure-drops is observed, which could aid the health risk assessment system for patients with respiratory diseases. Numerical results also showed that ultrafine particle-deposition efficiency (DE) in different lobes is different for various physical activities. Moreover, the numerical results showed hot spots in various locations among the different lobes for different flow rates, which could be helpful for targeted therapeutical aerosol transport to terminal bronchioles and the alveolar region.
Israr, J & Indraratna, B 2017, 'Internal Stability of Granular Filters under Static and Cyclic Loading', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017012-04017012.
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Ivanyos, G, Qiao, Y & Subrahmanyam, KV 2017, 'Non-commutative Edmonds’ problem and matrix semi-invariants', computational complexity, vol. 26, no. 3, pp. 717-763.
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© 2016, Springer International Publishing. In 1967, J. Edmonds introduced the problem of computing the rank over the rational function field of an n× n matrix T with integral homogeneous linear polynomials. In this paper, we consider the non-commutative version of Edmonds’ problem: compute the rank of T over the free skew field. This problem has been proposed, sometimes in disguise, from several different perspectives in the study of, for example, the free skew field itself (Cohn in J Symbol Log 38(2):309–314, 1973), matrix spaces of low rank (Fortin-Reutenauer in Sémin Lothar Comb 52:B52f 2004), Edmonds’ original problem (Gurvits in J Comput Syst Sci 69(3):448–484, 2004), and more recently, non-commutative arithmetic circuits with divisions (Hrubeš and Wigderson in Theory Comput 11:357-393, 2015. doi:10.4086/toc.2015.v011a014). It is known that this problem relates to the following invariant ring, which we call the F-algebra of matrix semi-invariants, denoted as R(n, m). For a field F, it is the ring of invariant polynomials for the action of SL (n, F) × SL (n, F) on tuples of matrices—(A, C) ∈ SL (n, F) × SL (n, F) sends (B1, … , Bm) ∈ M(n, F) ⊕m to (AB1CT, … , ABmCT). Then those T with non-commutative rank < n correspond to those points in the nullcone of R(n, m). In particular, if the nullcone of R(n, m) is defined by elements of degree ≤ σ, then there follows a poly (n, σ) -time randomized algorithm to decide whether the non-commutative rank of T is full. To our knowledge, previously the best bound for σ was O(n2·4n2) over algebraically closed fields of characteristic 0 (Derksen in Proc Am Math Soc 129(4):955–964, 2001). We now state the main contributions of this paper:We observe that by using an algorithm of Gurvits, and assuming the above bound σ for R(n, m) over Q, deciding whether or not T has non-commutative rank < n over Q can be done deterministically in time polynomial in the input size and σ.When F is large enough, we devise an algorithm ...
Jaber, HS, Mansor, S, Pradhan, B & Ahmad, N 2017, 'Rainfall–runoff modelling and water balance analysis for Al-Hindiyah barrage, Iraq using remote sensing and GIS', Geocarto International, vol. 32, no. 12, pp. 1407-1420.
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Jafari, M, Malekjamshidi, Z, Lei, G, Wang, T, Platt, G & Zhu, J 2017, 'Design and Implementation of an Amorphous High-Frequency Transformer Coupling Multiple Converters in a Smart Microgrid', IEEE Transactions on Industrial Electronics, vol. 64, no. 2, pp. 1028-1037.
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© 1982-2012 IEEE. Recent improvements in magnetic material characteristics and switching devices have generated a possibility to replace the electrical buses with high-frequency magnetic links in microgrids. Multiwinding transformers (MWTs) as magnetic links can effectively reduce the number of conversion stages of renewable energy system by adjusting turn ratio of windings according to the source voltage level. Other advantages are galvanic isolation, bidirectional power flow capability, and simultaneous power transfer between multiple ports. Despite the benefits, design, and characterization of MWTs are relatively complex due to their structural complexity and cross-coupling effects. This paper presents all stages of numerical design, prototyping, and characterization of an MWT for microgrid application. To design the transformer for certain value of parameters, the reluctance network method is employed. Due to the iterative nature of transformer design, it presented less computation time and reasonable accuracy. A prototype of designed transformer is implemented using amorphous magnetic materials. A set of experimental tests are conducted to measure the magnetic characteristics of the core and series coupling and open-circuit tests are applied to measure the transformer parameters. A comparison between the simulation and experimental test results under different loads within the medium-frequency range validated both design and modeling procedures.
Jahed Armaghani, D, Shoib, RSNSBR, Faizi, K & Rashid, ASA 2017, 'Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles', Neural Computing and Applications, vol. 28, no. 2, pp. 391-405.
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Jamshidi Chenari, R, Fatahi, B, Akhavan Maroufi, MA & Alaie, R 2017, 'An Experimental and Numerical Investigation into the Compressibility and Settlement of Sand Mixed with TDA', Geotechnical and Geological Engineering, vol. 35, no. 5, pp. 2401-2420.
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A series of large scale oedometer experiments were carried out to investigate the settlement of sand reinforced with tire derived aggregates (TDA). The parameters studied were five different amounts of TDAs, three aspect ratios and relative skeletal densities, and seven overburden pressures. The volume compressibility coefficient was calculated against different input parameters, and the constraint condition used enabled Poisson’s ratio to be calculated from an “at-rest” coefficient of earth pressure. The triaxial modulus was calculated indirectly and then adopted in subsequent numerical analyses. Finite element analysis and Monte Carlo simulations were used to investigate the settlement of this mixture and to study how the different parameters affected the settlement mixtures of sand and TDAs. The experimental and numerical results reveal that the amount of TDAs is the major parameter which affects settlement, although the overburden pressure and relative skeletal density are also important. The aspect ratio of the shred has almost no effect on volume compressibility parameters as long as constraint compression condition governs. Two index parameters were defined to discuss the type of shred distribution and how it affects settlement of the mixture.
Jan, M, Nanda, P, Usman, M & He, X 2017, 'PAWN: a payload‐based mutual authentication scheme for wireless sensor networks', Concurrency and Computation: Practice and Experience, vol. 29, no. 17, pp. e3986-e3986.
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SummaryWireless sensor networks (WSNs) consist of resource‐starving miniature sensor nodes deployed in a remote and hostile environment. These networks operate on small batteries for days, months, and even years depending on the requirements of monitored applications. The battery‐powered operation and inaccessible human terrains make it practically infeasible to recharge the nodes unless some energy‐scavenging techniques are used. These networks experience threats at various layers and, as such, are vulnerable to a wide range of attacks. The resource‐constrained nature of sensor nodes, inaccessible human terrains, and error‐prone communication links make it obligatory to design lightweight but robust and secured schemes for these networks. In view of these limitations, we aim to design an extremely lightweight payload‐based mutual authentication scheme for a cluster‐based hierarchical WSN. The proposed scheme, also known as payload‐based mutual authentication for WSNs, operates in 2 steps. First, an optimal percentage of cluster heads is elected, authenticated, and allowed to communicate with neighboring nodes. Second, each cluster head, in a role of server, authenticates the nearby nodes for cluster formation. We validate our proposed scheme using various simulation metrics that outperform the existing schemes.
Jauregi, I, Solar, H, Beriain, A, Zalbide, I, Jimenez, A, Galarraga, I & Berenguer, R 2017, 'UHF RFID Temperature Sensor Assisted With Body-Heat Dissipation Energy Harvesting', IEEE Sensors Journal, vol. 17, no. 5, pp. 1471-1478.
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Jayawardhana, M, Zhu, X, Liyanapathirana, R & Gunawardana, U 2017, 'Compressive sensing for efficient health monitoring and effective damage detection of structures', Mechanical Systems and Signal Processing, vol. 84, pp. 414-430.
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© 2016 Elsevier Ltd Real world Structural Health Monitoring (SHM) systems consist of sensors in the scale of hundreds, each sensor generating extremely large amounts of data, often arousing the issue of the cost associated with data transfer and storage. Sensor energy is a major component included in this cost factor, especially in Wireless Sensor Networks (WSN). Data compression is one of the techniques that is being explored to mitigate the effects of these issues. In contrast to traditional data compression techniques, Compressive Sensing (CS) – a very recent development – introduces the means of accurately reproducing a signal by acquiring much less number of samples than that defined by Nyquist's theorem. CS achieves this task by exploiting the sparsity of the signal. By the reduced amount of data samples, CS may help reduce the energy consumption and storage costs associated with SHM systems. This paper investigates CS based data acquisition in SHM, in particular, the implications of CS on damage detection and localization. CS is implemented in a simulation environment to compress structural response data from a Reinforced Concrete (RC) structure. Promising results were obtained from the compressed data reconstruction process as well as the subsequent damage identification process using the reconstructed data. A reconstruction accuracy of 99% could be achieved at a Compression Ratio (CR) of 2.48 using the experimental data. Further analysis using the reconstructed signals provided accurate damage detection and localization results using two damage detection algorithms, showing that CS has not compromised the crucial information on structural damages during the compression process.
Ji, J 2017, 'Stability of the coupled vibrations of work roll and strip in cold rolling process', Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 231, no. 7, pp. 1169-1181.
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Undesirable vibrations that occurred in cold rolling mills, widely known as chatter, are studied in this article by considering the interaction of three types of vibrations, namely, the longitudinal vibration of the rolled strip and the torsional and vertical vibrations of the upper work roll. The dynamic component of rolling force is determined using the quasi-static model under the assumption that the changes in roll gap and strip tension produce the variation of rolling force. The coupled vibrations of the work roll and rolled strip are mathematically governed by a set of 3-degree-of-freedom non-linear equations. Under chatter conditions, a new variable is introduced to represent the motion of the quasi-neutral point. A stability criterion for the motion of the quasi-neutral point is developed by studying the eigenvalues of the corresponding characteristic equation of the linearized parts of the non-linear equations. The chatter stability can then be examined by evaluating the determinants of five matrices. Numerical examples are given to show the stable and unstable vibrations in the cold rolling process. The unstable vibration would lead to skidding phenomenon and even break the rolled strip. The results presented in this article provide new insights into the dynamic interaction of the coupled vibrations and the dynamics of the rolling process.
Ji, JC & Brown, T 2017, 'Periodic and Chaotic Motion of a Time-Delayed Nonlinear System Under Two Coexisting Families of Additive Resonances', International Journal of Bifurcation and Chaos, vol. 27, no. 05, pp. 1750066-1750066.
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A time-delayed quadratic nonlinear mechanical system can exhibit two coexisting stable bifurcating solutions (SBSs) after two-to-one resonant Hopf bifurcations occur in the corresponding autonomous time-delayed system. One SBS is of small-amplitude and has the Hopf bifurcation frequencies (HBFs), while the other is of large-amplitude and contains the shifted Hopf bifurcation frequencies (the shifted HBFs). When the forcing frequency is tuned to be the sum of two HBFs or the sum of two shifted HBFs, two families of additive resonances can be induced in the forced response. The forced response under the additive resonance related to the HBFs can demonstrate periodic, quasi-periodic and chaotic motion. On the contrary, the forced response under the additive resonance associated with the shifted HBFs may exhibit period-three periodic motion and quasi-periodic motion. Bifurcation diagrams, time trajectories, frequency spectra, phase portraits and Poincaré sections are presented to show periodic, quasi-periodic, and chaotic motion of the time-delayed nonlinear system under the two families of additive resonances.
Ji, JC & Zhou, J 2017, 'Coexistence of two families of sub-harmonic resonances in a time-delayed nonlinear system at different forcing frequencies', Mechanical Systems and Signal Processing, vol. 93, pp. 151-163.
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© 2017 Elsevier Ltd Two coexisting families of sub-harmonic resonances can be induced at different forcing frequencies in a time-delayed nonlinear system having quadratic nonlinearities. They occur in the region where two stable bifurcating periodic solutions coexist in the corresponding autonomous system following two-to-one resonant Hopf bifurcations of the trivial equilibrium. The forced response is found to demonstrate small- and large-amplitude quasi-periodic motion under the family of sub-harmonic resonances related to Hopf bifurcation frequencies, and large-amplitude periodic and quasi-periodic motion under the family of sub-harmonic resonances associated with the shifted Hopf bifurcation frequencies. The family of sub-harmonic resonances related to Hopf bifurcation frequencies may cease to exist with the loss of the initially established frequency relationship of sub-harmonic resonances when the magnitude of periodic excitation is beyond a certain value. This will lead to a jump phenomenon from small- to large-amplitude quasi-periodic motion. Bifurcation diagrams, time trajectories and frequency spectra are numerically obtained to characterize the sub-harmonic resonances of the time-delayed nonlinear system around the critical point of the resonant Hopf bifurcations.
Jia, H, Yang, G, Ngo, H-H, Guo, W, Zhang, H, Gao, F & Wang, J 2017, 'Enhancing simultaneous response and amplification of biosensor in microbial fuel cell-based upflow anaerobic sludge bed reactor supplemented with zero-valent iron', Chemical Engineering Journal, vol. 327, pp. 1117-1127.
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© 2017 Elsevier B.V. The development of a convenient and sensitive sensor such as a microbial fuel cell (MFC) to monitor the operation of upflow anaerobic sludge blanket (UASB) is indispensable. However, the biosensor's properties were affected due to excessive acidification and suffocation of the electron transport. In this study, zero-valent iron (ZVI) was applied to restrain excessive acidification and improve the sensing performance. According to the results, the response rate of electrical signal accumulated with the addition of ZVI compared to the control reactor. As well as the electrical signal amplified and the subsidence rate maximum reached 0.059 V/h with 30 mg/L ZVI added that 883% higher than the control one during the stage (COD concentration 500 mg/L–1000 mg/L). With the electrochemical analysis, the internal resistance of ZVI-UASB-MFC decreased and redox activity promoted effectively with ZVI added. During the overloading phase, the fractional content of butyric acid changed from 53% to 31%, while that of acetic acid rose from 18% to 39% after 30 mg/L ZVI addition. These results indicated that adding ZVI to the digestion could retard excessive acidification by promoting butyric acid conversion and accumulating direct interspecies electron transfer simultaneous for enhancing the biosensor's performance. According to the Fe 2+ and Fe 3+ of effluent were 2.25 mg/L and 0.39 mg/L with 50 mg/L ZVI addition, moderate amount of ZVI was effective for system and safety to the environment. It might helpfully provide a promising way to enhance biosensing.
Jia, Y, Liu, Y, Guo, YJ, Li, K & Gong, S 2017, 'A Dual-Patch Polarization Rotation Reflective Surface and Its Application to Ultra-Wideband RCS Reduction', IEEE Transactions on Antennas and Propagation, vol. 65, no. 6, pp. 3291-3295.
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© 2017 IEEE. An ultra-wideband polarization rotation reflective surface (PRRS) with a high polarization conversion ratio (PCR) is proposed, which can reflect a linearly polarized incident wave with 90° polarization rotation. The unit cell of the proposed PRRS consists of a square and L-shaped patches printed on a substrate, which is covered by a superstrate and backed by a metallic ground. The two patches are connected to the ground using two metallic vias, respectively. Compared with the previously reported PRRS, the polarization rotation bandwidth of the proposed PRRS is enhanced from 49% to 97% with a high PCR of 96%. The frequency responses within the operation frequency band are consistent under oblique incident waves. Furthermore, the designed PRRS is applied to the ultra-wideband radar cross-section (RCS) reduction by forming a checkerboard surface. A 10-dB RCS reduction is achieved over an ultrawideband of 98%. To validate the simulation results, a prototype of the checkerboard surface is fabricated and measured. A good agreement between the experimental and simulation results is obtained.
Jia, Z, Yu, J, Mei, Y, Chen, Y, Shen, Y & Ai, X 2017, 'Integral backstepping sliding mode control for quadrotor helicopter under external uncertain disturbances', Aerospace Science and Technology, vol. 68, pp. 299-307.
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In this paper, a novel nonlinear control strategy along with its simulation for a quadrotor helicopter is proposed. The normal 6-DOF dynamic model of the quadrotor based on the Newton–Euler formula as well as the model with external uncertain disturbances are established. Considering the underactuated and strongly coupled characteristics of quadrotor helicopter, we design a nonlinear control method by using integral backstepping combined with the sliding mode control (integral BS-SMC) to stabilize the quadrotor attitude and to accomplish the task of trajectory tracking. The designed controllers based on the hierarchical control scheme can be divided into rotational controller and translational controller and their stability are validated by the Lyapunov stability theorem. By means of the proposed controllers, the chattering phenomenon and discontinuousness of control inputs faced by traditional sliding mode control (SMC) can be avoided. The feasibility of the control approach presented in this paper is verified by the simulations under different scenarios. The results show that the nonlinear control method not only has a better tracking performance than others but also has a higher robustness when unknown disturbances occur.
Jiang, D, Luo, X, Xuan, J & Xu, Z 2017, 'Sentiment Computing for the News Event Based on the Social Media Big Data', IEEE Access, vol. 5, pp. 2373-2382.
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© 2013 IEEE. The explosive increasing of the social media data on the Web has created and promoted the development of the social media big data mining area welcomed by researchers from both academia and industry. The sentiment computing of news event is a significant component of the social media big data. It has also attracted a lot of researches, which could support many real-world applications, such as public opinion monitoring for governments and news recommendation for Websites. However, existing sentiment computing methods are mainly based on the standard emotion thesaurus or supervised methods, which are not scalable to the social media big data. Therefore, we propose an innovative method to do the sentiment computing for news events. More specially, based on the social media data (i.e., words and emoticons) of a news event, a word emotion association network (WEAN) is built to jointly express its semantic and emotion, which lays the foundation for the news event sentiment computation. Based on WEAN, a word emotion computation algorithm is proposed to obtain the initial words emotion, which are further refined through the standard emotion thesaurus. With the words emotion in hand, we can compute every sentence's sentiment. Experimental results on real-world data sets demonstrate the excellent performance of the proposed method on the emotion computing for news events.
Jiang, J, Wen, S, Yu, S, Xiang, Y & Zhou, W 2017, 'Identifying Propagation Sources in Networks: State-of-the-Art and Comparative Studies', IEEE Communications Surveys & Tutorials, vol. 19, no. 1, pp. 465-481.
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It has long been a significant but difficult problem to identify propagation sources based on limited knowledge of network structures and the varying states of network nodes. In practice, real cases can be locating the sources of rumors in online social networks and finding origins of a rolling blackout in smart grids. This paper reviews the state-of-the-art in source identification techniques and discusses the pros and cons of current methods in this field. Furthermore, in order to gain a quantitative understanding of current methods, we provide a series of experiments and comparisons based on various environment settings. Especially, our observation reveals considerable differences in performance by employing different network topologies, various propagation schemes, and diverse propagation probabilities. We therefore reach the following points for future work. First, current methods remain far from practice as their accuracy in terms of error distance (δ) is normally larger than three in most scenarios. Second, the majority of current methods are too time consuming to quickly locate the origins of propagation. In addition, we list five open issues of current methods exposed by the analysis, from the perspectives of topology, number of sources, number of networks, temporal dynamics, and complexity and scalability. Solutions to these open issues are of great academic and practical significance.
Jiang, L, Gentile, C, Lauto, A, Cui, C, Song, Y, Romeo, T, Silva, SM, Tang, O, Sharma, P, Figtree, G, Gooding, JJ & Mawad, D 2017, 'Versatile Fabrication Approach of Conductive Hydrogels via Copolymerization with Vinyl Monomers', ACS Applied Materials & Interfaces, vol. 9, no. 50, pp. 44124-44133.
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Functionalized poly(ethylene dioxythiophene) (f-PEDOT) was copolymerized with two vinyl monomers of different hydrophilicity, acrylic acid and hydroxyethyl methacrylate, to produce electroconductive hydrogels with a range of physical and electronic properties. These hydrogels not only possessed tailored physical properties, such as swelling ratios and mechanical properties, but also displayed electroactivity dependent on the chemical composition of the network. Raman spectroscopy indicated that the functional PEDOT in the hydrogels is in an oxidized form, most likely accounting for the good electrochemical response of the hydrogels observed in physiological buffer. In vitro cell studies showed that cardiac cells respond differently when seeded on hydrogel substrates with different compositions. This study presents a facile approach for the fabrication of electroconductive hydrogels with a range of properties, paving the way for scaffolds that can meet the requirements of different electroresponsive tissues.
Jiang, P, Liu, F & Song, Y 2017, 'A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting', Energy, vol. 119, pp. 694-709.
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The ultimate issue in electricity loads modelling is to improve forecasting accuracy as well as guarantee a robust prediction result, which will save considerable manual labor material resources and economic consumption. For addressing this challenge, many researchers are committed to investigating highly accurate forecasting models, and feature selection (FS) technologies are considered as a powerful tool to improve performance of models in many literature. However, common FS technologies applied for Short-term load forecasting (STLF) ignore to select date information of the observed series as feature candidates and pay less attention to reduction rates of feature candidates, which will result in loss of date information and redundancy of features. Both drawbacks provide a significant roadblock for improving forecasting accuracy. Aiming to overcome both drawbacks and develop an effective model for STLF, this paper successfully investigates the date-framework strategy (DFS) to construct the pool of features and develops an FS technology, genetic algorithm binary improved cuckoo search (GABICS), to search a solution with the lowest reduction rate. Assigning the extreme learning machine (ELM) to be the forecast, GABICS-DFS-ELM not only obtains a minimum and effective subset of features but also has a satisfactory forecasting result with high accuracy and robustness.
Jiang, Y, Tsai, P, Yeh, W-C & Cao, L 2017, 'A honey-bee-mating based algorithm for multilevel image segmentation using Bayesian theorem', Applied Soft Computing, vol. 52, pp. 1181-1190.
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© 2016 Elsevier B.V. The image thresholding techniques are considered as a must for objects segmentation, compression and target recognition, and they have been widely studied for the last few decades; for example, the multi-level thresholding methods, and as such (they) render more great challenges for image segmentation techniques that remain computationally more expensive, when their choices of threshold numbers were increased. Therefore, our aim was to propose an algorithm based on Bayesian theorem and the so-called honey-bee-mating algorithm (HBMA), called a Bayesian honey bee mating algorithm BHBMA. It can not only reduce the computational time and curse of dimensionality, but also can run more reliably and more stably. This enhanced capability was technically accomplished by embedding a new population initialization strategy based on the characteristics of multi-level thresholding technique in pixel-based intensity images arranged from lower grey levels to higher ones. Extensive experiments have shown that our proposed method outperformed other state-of-the-art algorithms empirically in terms of their effectiveness and efficiency, when applying to complex image processing scenario such as automatic target recognition.
Jiang, YB, He, N, Xu, BH, Zhou, YZ & Zhang, ZL 2017, 'Model tests on negative pressure distribution in vacuum preloading', Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering, vol. 39, no. 10, pp. 1874-1883.
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The rule of negative pressure distribution is an important subject in the studies on vacuum preloading mechanism. By discussing the spatial distribution characteristics of vacuum preloading and the associated concepts, the negative pressure is defined in a broad sense, and the methods and influencing factors for the negative pressure measurement are analyzed. The tests are carried out, with a well-designed large scale indoor model 15 m in vertical height, to study the negative pressure distribution in vacuum preloading. The test results show that there is hysteresis effect in vacuum measurement in saturated clay soil, and the limit depth where vacuum exists is 8.9 m. The pore water pressure and vacuum degree in drain board exhibit a symmetrical linear distribution above zero pressure plane at the vacuum stable stage, and the slope is similar to hydrostatic pressure gradient. The negative pressure distribution along the depth is of piecewise linear type, due to the energy consumption in water lifting, attenuation is found in the unsaturated soil above the underground water level, and the average attenuation value is 21.4 kPa in the stable period. The negative pressure is uniform with no attenuation under the average water level, and the corresponding average negative pressure is -67.0 kPa within the depth scope of drainage board in the stable period. Based on the experimental results and the flow pattern distribution of gas-liquid two-phase flow in the equivalent drainage tube, the piecewise linear negative pressure boundary of the vertical drainage board in the stable period of vacuum preloading is put forward.
Jiang, Z, Zhao, J, Lu, H, Wei, D, Manabe, K-I, Zhao, X, Zhang, X & Wu, D 2017, 'Influences of temperature and grain size on the material deformability in microforming process', International Journal of Material Forming, vol. 10, no. 5, pp. 753-764.
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© 2016, Springer-Verlag France. This paper investigated the influences of temperature and grain size on the deformability of pure copper in micro compression process. Based on the dislocation theory, a constitutive model was proposed taking into account the influences of forming temperature, Hall-Petch relationship and surface layer model. Vacuum heat treatment was employed to obtain various grain sizes of cylindrical workpieces, and then laser heating method was applied to heat workpieces during microforming process. Finite element (FE) simulation was also performed, with simulated values agreed well with the experimental results in terms of metal flow stress. Both the FE simulated and experimental results indicate that forming temperature and grain size have a significant influence on the accuracy of the produced product shape and metal flow behaviour in microforming due to the inhomogeneity within the deformed material. The mechanical behaviour of the material is found to be more sensitive to forming temperature when the workpieces are constituted of fine grains.
Jin, T, Song, J, Zhu, J, Nghiem, LD, Zhao, B, Li, X-M & He, T 2017, 'The role of the surfactant sodium dodecyl sulfate to dynamically reduce mass transfer resistance of SPEEK coated membrane for oil-in-water emulsion treatment', Journal of Membrane Science, vol. 541, pp. 9-18.
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© 2017 Elsevier B.V. Membrane fouling during the treatment of produced water containing oil emulsions remains a major technical challenge for the oil and gas industry. Here, we demonstrate the preparation and performance of a fouling resistant hollow fiber membrane using a synthetic saline oil-in-water emulsion. The membrane was prepared by coating commercial polyethersulfone (PES) hollow fibers with a layer of sulfonated polyether ether ketone (SPEEK). The SPEEK coated membrane was significantly more oleophobic than the support PES membrane, possibly due to a non-porous surface, higher hydrophilicity, and more negatively charged SPEEK surface. The SPEEK coated membrane could achieve complete oil rejection without any observable membrane fouling and considerably higher salt, turbidity, and sodium dodecyl sulfate (SDS) rejection than the support PES membrane. An initial increase in water flux was observed with the SPEEK coated membrane. The flux increase observed here could be attributed to the incorporation of SDS molecules into SPEEK polymeric network and subsequent electrostatic interaction amongst charged functional groups leading to conformational changes of the SPEEK layer. Dynamic adsorption and desorption experiments illustrated the interaction between SDS and SPEEK. A strong correlation between the amount of SDS entrapped in the SPEEK polymeric network and water flux was observed. Results from this study illustrated the potential of SPEEK coated membrane as a major breakthrough for oil recovery and wastewater reuse in the oil and gas industry.
Jozi, B, Braun, R, Samali, B, Li, J & Dackermann, U 2017, 'Limitation of the Lateral Angled Broadband Low Frequency Impact Excitation on the Non-Destructive Condition Assessment of the Timber Utility Poles', International Journal of Advancements in Technology, vol. 08, no. 04, pp. 1-8.
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Timber utility poles play a significant role in the infrastructure of Australia as well as many other countries for power distribution and communication networks. Due to the advanced age of Australia’s timber pole infrastructure, substantial efforts are undertaken on maintenance and asset management to avoid any failures of the utility lines. Nevertheless, the lack of reliable tools for assessing the condition of in-service poles seriously jeopardizes the maintenance and asset management. For instance, each year approximately 300,000 poles are replaced in the Eastern States of Australia with up to 80% of them still being in a very good condition, resulting in major waste of natural resources and money. Non-destructive testing (NDT) methods based on stress wave propagation can potentially offer simple and cost-effective tools for identifying the in-service condition of timber poles. Nonetheless, most of the currently available methods are not appropriate for condition assessment of timber poles in-service due to presence of uncertainties such as complicated material properties, environmental conditions, interaction of soil and structure, and an impact excitation type. In order to address these complexities, advanced digital signal processing methodologies are needed to be employed. Deterministic signal separation, blind signal separation, and frequency-wavenumber velocity filtering are the three groups of methodologies, which could most probably provide solutions. In this paper applicability and effectiveness of the blind signal separation methods is investigated through a numerical data obtained from of a timber pole modelled with both isotropic and orthotropic material properties. Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and K-means clustering algorithms are the blind signal separation methodologies that are employed in this research work.
Kaiwartya, O, Prasad, M, Prakash, S, Samadhiya, D, Abdullah, AH & Rahman, SOA 2017, 'An investigation on biometric internet security', International Journal of Network Security, vol. 19, no. 2, pp. 167-176.
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Due to the Internet revolution in the last decade, each and every work area of society are directly or indirectly depending on computers, highly integrated computer networks and communication systems, electronic data storage and high transfer based devices, e-commerce, e-security, e-governance, and e-business. The Internet revolution is also emerged as significant challenge due to the threats of hacking systems and individual accounts, malware, fraud and vulnerabilities of system and networks, etc. In this context, this paper explores E-Security in terms of challenges and measurements. Biometric recognition is also investigated as a key e-security solution. E-Security is precisely described to understand the concept and requirements. The major challenges of e-security; namely, threats, attacks, vulnerabilities are presented in detail. Some measurement are identified and discussed for the challenges. Biometric recognition is discussed in detail wit pros and cons of the approach as a key e-security solution. This investigation helps in clear understating of e-security challenges and possible implementation of the identified measurements for the challenges in wide area of network communications.
Kalam, MA, Masjuki, HH, Cho, HM, Mosarof, MH, Mahmud, MI, Chowdhury, MA & Zulkifli, NWM 2017, 'Influences of thermal stability, and lubrication performance of biodegradable oil as an engine oil for improving the efficiency of heavy duty diesel engine', Fuel, vol. 196, pp. 36-46.
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Nowadays, the development of biodegradable products is important in improving energy efficiency and green environment, particularly in energy conservation and rotation of machinery systems. In the case of sliding components, lubrication system and lubricant quality plays an important role for energy efficiency as it is directly involved with frictional force and components wear characteristics. The conventional mineral oil-based lubricant is used for machinery lubrications; however, it is nonbiodegradable and is an environmental pollutant. This investigation attempts to develop biolubricant acquired from various vegetable oils to replace mineral oil-based lubricants. This study evaluates the physicochemical properties, thermal stability, and lubricating and tribological characteristics of olive oil and its comparative analysis with commercial lube oil. A four-ball tribotester was used to measure the friction and wear properties of the sample according to the ASTM 4172 method. Olive oil has an excellent oxidation stability due to the presence of high percentages of oleic acid in fatty acid composition. Olive oil showed higher viscosity index and kinematic viscosity than other vegetable oils; hence, it is better for boundary lubrication. Thermogravimetric analysis showed that olive oil persists thermally steady up to 390 °C. Olive oil showed a lower coefficient of friction, wear scar diameter, and worn scar surface area than commercial lube oil. Therefore, due to the better lubricating performance, olive oil has high potential for use as an engine lubricating oil for improving efficiency of heavy-duty engines in the automotive applications.
Kalantar, B, Mansor, S, Khuzaimah, Z, Ibrahim Sameen, M & Pradhan, B 2017, 'MODELLING MEAN ALBEDO OF INDIVIDUAL ROOFS IN COMPLEX URBAN AREASUSING SATELLITE IMAGES AND AIRBORNE LASER SCANNING POINT CLOUDS', The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W7, no. 2W7, pp. 237-240.
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Abstract. Knowledge of surface albedo at individual roof scale is important for mitigating urban heat islands and understanding urban climate change. This study presents a method for quantifying surface albedo of individual roofs in a complex urban area using the integration of Landsat 8 and airborne LiDAR data. First, individual roofs were extracted from airborne LiDAR data and orthophotos using optimized segmentation and supervised object based image analysis (OBIA). Support vector machine (SVM) was used as a classifier in OBIA process for extracting individual roofs. The user-defined parameters required in SVM classifier were selected using v-fold cross validation method. After that, surface albedo was calculated for each individual roof from Landsat images. Finally, thematic maps of mean surface albedo of individual roofs were generated in GIS and the results were discussed. Results showed that the study area is covered by 35% of buildings varying in roofing material types and conditions. The calculated surface albedo of buildings ranged from 0.16 to 0.65 in the study area. More importantly, the results indicated that the types and conditions of roofing materials significantly effect on the mean value of surface albedo. Mean albedo of new concrete, old concrete, new steel, and old steel were found to be equal to 0.38, 0.26, 0.51, and 0.44 respectively. Replacing old roofing materials with new ones should highly prioritized.
Kalantar, B, Mansor, SB, Sameen, MI, Pradhan, B & Shafri, HZM 2017, 'Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis', International Journal of Remote Sensing, vol. 38, no. 8-10, pp. 2535-2556.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. Land-cover maps provide essential data for a wide range of practical and small-scale applications. A number of data sources appropriate for land-cover extraction are available. Among these, images captured using unmanned aerial vehicles (UAVs) are low cost, have very high resolution, and can be acquired at any time with few restrictions. Over the past two decades, various classification techniques have been developed to extract land-cover features from UAV images, and object-based image analysis (OBIA) is the preferred technique based on the recent literature. This study presents a novel method that integrates the fuzzy unordered rule induction algorithm (FURIA) into OBIA to achieve accurate land-cover extraction from UAV images. The images were segmented using a multiresolution segmentation algorithm with an optimized scale parameter. The scale parameter was optimized using a novel approach that integrated feature space optimization into the plateau objective function. During the classification stage, significant features were selected via random forest, and rule sets were developed using FURIA. For comparison, result of the proposed approach was compared with those of decision tree (DT) rules and the Support Vector Machine (SVM) classification method. The results of this study indicate that the proposed method outperforms DT and SVM with an overall accuracy of 91.23%. A transferability evaluation showed that FURIA achieved accurate classification results on different UAV image subsets captured at different times. The findings suggest that fuzzy rules are more appropriate than conventional crisp rules for land-cover extraction from UAV images.
Kalaruban, M, Loganathan, P, Kandasamy, J, Naidu, R & Vigneswaran, S 2017, 'Enhanced removal of nitrate in an integrated electrochemical-adsorption system', Separation and Purification Technology, vol. 189, pp. 260-266.
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© 2017 Elsevier B.V. The electrochemical (EC) method of removing pollutants in water is a widely used process in water and wastewater treatment. An EC-adsorption integrated system was investigated to test whether the simultaneous removal of nitrate by the two processes would be better than removal utilising the individual EC and adsorption methods. In the integrated system, an adsorbent (ion exchange resin - Dowex 21k XLT) was placed inside a stainless steel box that served as an anode with a Cu plate as cathode. In an experiment using 2 L nitrate solution containing 20 mg N/L and 2 g adsorbent the rate of nitrate removal in the integrated system was initially fast with 35% removed in 30 min, though slowing down later. The rate of removal increased with increasing current, voltage and pH up to 7 but decreased as the distance between the electrodes also increased. The optimum nitrate removal of 67% was obtained at pH 7, 1 A, and 31 V for a distance of 1 cm between the electrodes after 180 min. The amount of nitrate removed fell when sulphate was present in the integrated system due to sulphate competing with nitrate for adsorption. Concentration of ammonium produced by nitrate reduction in the EC system was reduced in the presence of adsorbent. Nitrate removal in the integrated system is approximately equal to the sum of the removals in the two individual processes.
Kalhori, H, Makki Alamdari, M, Zhu, X, Samali, B & Mustapha, S 2017, 'Non-intrusive schemes for speed and axle identification in bridge-weigh-in-motion systems', Measurement Science and Technology, vol. 28, no. 2, pp. 025102-025102.
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© 2017 IOP Publishing Ltd. Bridge weigh-in-motion (BWIM) is an approach through which the axle and gross weight of trucks travelling at normal highway speed are identified using the response of an instrumented bridge. The vehicle speed, the number of axles, and the axle spacing are crucial parameters, and are required to be determined in the majority of BWIM algorithms. Nothing-on-the-road (NOR) strategy suggests using the strain signals measured at some particular positions underneath the deck or girders of a bridge to obtain this information. The objective of this research is to present a concise overview of the challenges of the current non-intrusive schemes for speed and axle determination through bending-strain and shear-strain based approaches. The problem associated with the global bending-strain responses measured at quarter points of span is discussed and a new sensor arrangement is proposed as an alternative. As for measurement of local responses rather than the global responses, the advantage of shear strains over bending strains is presented. However, it is illustrated that shear strains at quarter points of span can only provide accurate speed estimation but fail to detect the correct number of axles. As a remedy, it is demonstrated that, even for closely-spaced axles, the shear strain at the beginning of the bridge is capable of reliably identifying the number of axles. In order to provide a fully automated speed and axle identification system, appropriate signal processing including low-pass filtering and wavelet transforms are applied to the raw time signals. As case studies, the results of experimental testing in laboratory and on a real bridge are presented.
Kalhori, H, Ye, L & Mustapha, S 2017, 'Inverse estimation of impact force on a composite panel using a single piezoelectric sensor', Journal of Intelligent Material Systems and Structures, vol. 28, no. 6, pp. 799-810.
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Identification of location and magnitude of impact forces on a rectangular carbon fibre–epoxy honeycomb composite panel has been experimentally investigated through an inverse approach. The dynamic signals captured by a single piezoelectric (PZT) sensor installed on the panel remotely from the impact locations are utilized to identify the impact forces generated by an instrumented hammer. A number of potential impact locations on the panel are assumed to be known a priori. An actual impact is then occurred at one or two of these locations. The objective is to simultaneously identify the location and magnitude of the impact forces using the PZT sensor. The problem is solved through minimization of an extended matrix form of the convolution integral incorporating linear superposition of the responses due to impact at different locations. The under-determined problem is ill-posed and is regularized by Tikhonov and generalized cross validation methods. It is revealed that impact forces occurred at any location among four possible locations can be well identified.
Kamal, MS & Nimmy, SF 2017, 'StrucBreak: A Computational Framework for Structural Break Detection in DNA Sequences', Interdisciplinary Sciences: Computational Life Sciences, vol. 9, no. 4, pp. 512-527.
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Kamal, MS, Chowdhury, L, Khan, MI, Ashour, AS, Tavares, JMRS & Dey, N 2017, 'Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images', Computational Biology and Chemistry, vol. 68, pp. 231-244.
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Kamal, MS, Parvin, S, Ashour, AS, Shi, F & Dey, N 2017, 'De-Bruijn graph with MapReduce framework towards metagenomic data classification', International Journal of Information Technology, vol. 9, no. 1, pp. 59-75.
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Kapińska, AD, Staveley-Smith, L, Crocker, R, Meurer, GR, Bhandari, S, Hurley-Walker, N, Offringa, AR, Hanish, DJ, Seymour, N, Ekers, RD, Bell, ME, Callingham, JR, Dwarakanath, KS, For, B-Q, Gaensler, BM, Hancock, PJ, Hindson, L, Johnston-Hollitt, M, Lenc, E, McKinley, B, Morgan, J, Procopio, P, Wayth, RB, Wu, C, Zheng, Q, Barry, N, Beardsley, AP, Bowman, JD, Briggs, F, Carroll, P, Dillon, JS, Ewall-Wice, A, Feng, L, Greenhill, LJ, Hazelton, BJ, Hewitt, JN, Jacobs, DJ, Kim, H-S, Kittiwisit, P, Line, J, Loeb, A, Mitchell, DA, Morales, MF, Neben, AR, Paul, S, Pindor, B, Pober, JC, Riding, J, Sethi, SK, Shankar, NU, Subrahmanyan, R, Sullivan, IS, Tegmark, M, Thyagarajan, N, Tingay, SJ, Trott, CM, Webster, RL, Wyithe, SB, Cappallo, RJ, Deshpande, AA, Kaplan, DL, Lonsdale, CJ, McWhirter, SR, Morgan, E, Oberoi, D, Ord, SM, Prabu, T, Srivani, KS, Williams, A & Williams, CL 2017, 'Spectral Energy Distribution and Radio Halo of NGC 253 at Low Radio Frequencies', The Astrophysical Journal, vol. 838, no. 1, pp. 68-68.
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Abstract We present new radio continuum observations of NGC 253 from the Murchison Widefield Array at frequencies between 76 and 227 MHz. We model the broadband radio spectral energy distribution for the total flux density of NGC 253 between 76 MHz and 11 GHz. The spectrum is best described as a sum of a central starburst and extended emission. The central component, corresponding to the inner 500 pc of the starburst region of the galaxy, is best modeled as an internally free–free absorbed synchrotron plasma, with a turnover frequency around 230 MHz. The extended emission component of the spectrum of NGC 253 is best described as a synchrotron emission flattening at low radio frequencies. We find that 34% of the extended emission (outside the central starburst region) at 1 GHz becomes partially absorbed at low radio frequencies. Most of this flattening occurs in the western region of the southeast halo, and may be indicative of synchrotron self-absorption of shock-reaccelerated electrons or an intrinsic low-energy cutoff of the electron distribution. Furthermore, we detect the large-scale synchrotron radio halo of NGC 253 in our radio images. At 154–231 MHz the halo displays the well known X-shaped/horn-like structure, and extends out to ∼8 kpc in the z-direction (from the major axis).
Karimi, M, Croaker, P & Kessissoglou, N 2017, 'Acoustic scattering for 3D multi-directional periodic structures using the boundary element method', The Journal of the Acoustical Society of America, vol. 141, no. 1, pp. 313-323.
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An efficient boundary element formulation is proposed to solve three-dimensional exterior acoustic scattering problems with multi-directional periodicity. The multi-directional periodic acoustic problem is represented as a multilevel block Toeplitz matrix. By exploiting the Toeplitz structure, the computational time and storage requirements to construct and to solve the linear system of equations arising from the boundary element formulation are significantly reduced. The generalized minimal residual method is implemented to solve the linear system of equations. To efficiently calculate the matrix-vector product in the iterative algorithm, the original matrix is embedded into a multilevel block circulant matrix. A multi-dimensional discrete Fourier transform is then employed to accelerate the matrix-vector product. The proposed approach is applicable to a periodic acoustic problem for any arbitrary shape of the structure in both full space and half space. Two case studies involving sonic crystal barriers are presented. In the first case study, a sonic crystal barrier comprising rigid cylindrical scatterers is modeled. To demonstrate the effectiveness of the proposed technique, periodicity in one, two, or three directions is examined. In the second case study, the acoustic performance of a sonic crystal barrier with locally resonant C-shaped scatterers is studied.
Karimi, M, Croaker, P, Kinns, R & Kessissoglou, N 2017, 'Effect of a serrated trailing edge on sound radiation from nearby quadrupoles', The Journal of the Acoustical Society of America, vol. 141, no. 5, pp. 2997-3010.
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A periodic boundary element technique is implemented to study the noise reduction capability of a plate with a serrated trailing edge under quadrupole excitation. It is assumed for this purpose that the quadrupole source tensor is independent of the trailing edge configuration and that the effect of the trailing edge shape is to modify sound radiation from prescribed boundary layer sources. The flat plate is modelled as a continuous structure with a finite repetition of small spanwise segments. The matrix equation formulated by the periodic boundary element method for this 3D acoustic scattering problem is represented as a block Toeplitz matrix. The discrete Fourier transform is employed in an iterative algorithm to solve the block Toeplitz system. The noise reduction mechanism for a serrated trailing edge in the near field is investigated by comparing contour plots obtained from each component of the quadrupole for unserrated and serrated trailing edge plate models. The noise reduction due to the serrated trailing edge is also examined as a function of the source location.
Karimi, M, Croaker, P, Peake, N & Kessissoglou, N 2017, 'Acoustic Scattering for Rotational and Translational Symmetric Structures in Nonuniform Potential Flow', AIAA Journal, vol. 55, no. 10, pp. 3318-3327.
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Karmokar, DK, Guo, YJ, Qin, P-Y, Esselle, KP & Bird, TS 2017, 'Forward and Backward Beam-Scanning Tri-Band Leaky-Wave Antenna', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 1891-1894.
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© 2002-2011 IEEE. The main limitations of uniform half-width microstrip leaky-wave antennas (HW-MLWAs), namely a single operating band and only forward beam scanning, are overcome here with an HW-MLWA loaded with periodic L-shaped slots. The antenna exhibits tri-band operation, and the main beam can be steered in the forward direction in one band, and in the backward direction in the other two bands. Its size is halved with a shorting wall. The antenna was fabricated and tested to validate the concept, and the measured and simulated results agree very well. The measured matched (10-dB return loss) bandwidths of the prototype are 22.34% (5.05-6.32 GHz), 15.85% (8.77-10.28 GHz), and 11.21% (12.63-14.13 GHz) in the first, second, and third bands, respectively. The beam-scanning ranges of the prototyped antenna are 30° to 64°, -75° to -18°, and -19° to -4° when the frequency sweeps from 5 to 6 GHz, 8.85 to 10.5 GHz, and 13 to 14.25 GHz, respectively. The measured peak gains (within the scanning range) are 12.4, 14.3, and 14.7 dBi in the first, second, and third bands with variations of 2.5, 3.4, and 3.1 dB, respectively.
Kaufman, G, Liu, W, Williams, DM, Choo, Y, Gopinadhan, M, Samudrala, N, Sarfati, R, Yan, ECY, Regan, L & Osuji, CO 2017, 'Flat Drops, Elastic Sheets, and Microcapsules by Interfacial Assembly of a Bacterial Biofilm Protein, BslA', Langmuir, vol. 33, no. 47, pp. 13590-13597.
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Kaur, P, Goyal, M & Lu, J 2017, 'A Comparison of Bidding Strategies for Online Auctions Using Fuzzy Reasoning and Negotiation Decision Functions', IEEE Transactions on Fuzzy Systems, vol. 25, no. 2, pp. 425-438.
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Kautzka, Z, Clement, S, Goldys, EM & Deng, W 2017, 'Light-triggered liposomal cargo delivery platform incorporating photosensitizers and gold nanoparticles for enhanced singlet oxygen generation and increased cytotoxicity', International Journal of Nanomedicine, vol. Volume 12, pp. 969-977.
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Keam, SP, Sobala, A, ten Have, S & Hutvagner, G 2017, 'tRNA-Derived RNA Fragments Associate with Human Multisynthetase Complex (MSC) and Modulate Ribosomal Protein Translation', Journal of Proteome Research, vol. 16, no. 2, pp. 413-420.
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© 2016 American Chemical Society. The functionality of small RNAs from abundant species of 'housekeeping' noncoding RNAs (e.g., rRNA, tRNA, snRNA, snoRNA, etc.) remains a highly studied topic. The current state of research on short RNAs derived from transfer RNA (tRNA), called tRNA-derived fragments (tRFs), has been restricted largely to expression studies and limited functional studies. 5′ tRFs are known translational inhibitors in mammalian cells, yet little is known about their functionality. Here we report on the first experimental evidence of the tRF protein interactome, identifying the mammalian multisynthetase complex as the primary interactor of the 5′ tRF Gln19. We also present proteome-wide SILAC evidence that 5′ tRFs increase ribosomal and poly(A)-binding protein translation.
Kennedy, P, Macgregor, LJ, Barnhill, E, Johnson, CL, Perrins, M, Hunter, A, Brown, C, van Beek, EJR & Roberts, N 2017, 'MR elastography measurement of the effect of passive warmup prior to eccentric exercise on thigh muscle mechanical properties', Journal of Magnetic Resonance Imaging, vol. 46, no. 4, pp. 1115-1127.
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PurposeTo investigate the effect of warmup by application of the thermal agent Deep Heat (DH) on muscle mechanical properties using magnetic resonance elastography (MRE) at 3T before and after exercise‐induced muscle damage (EIMD).Materials and MethodsTwenty male participants performed an individualized protocol designed to induce EIMD in the quadriceps. DH was applied to the thigh in 50% of the participants before exercise. MRE, T2‐weighted MRI, maximal voluntary contraction (MVC), creatine kinase (CK) concentration, and muscle soreness were measured before and after the protocol to assess EIMD effects. Five participants were excluded: four having not experienced EIMD and one due to incidental findings.ResultsTotal workload performed during the EIMD protocol was greater in the DH group than the control group (P < 0.03), despite no significant differences in baseline MVC (P = 0.23). Shear stiffness |G*| increased in the rectus femoris (RF) muscle in both groups (P < 0.03); however, DH was not a significant between‐group factor (P = 0.15). MVC values returned to baseline faster in the DH group (5 days) than the control group (7 days). Participants who displayed hyperintensity on T2‐weighted images had a greater stiffness increase following damage than those without: RF; 0.61 kPa vs. 0.15 kPa, P < 0.006, vastus intermedius; 0.34 kPa vs. 0.03 kPa, P = 0.06.ConclusionEIMD produces increa...
Kermany, AR, Bennett, JS, Valenzuela, VM, Bowen, WP & Iacopi, F 2017, 'Potential of epitaxial silicon carbide microbeam resonators for chemical sensing', physica status solidi (a), vol. 214, no. 4, pp. 1600437-1600437.
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© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.Epitaxial silicon carbide is promising for chemical resonant sensing applications due to its excellent mechanical, thermal, and biochemical properties. This paper reviews six important aspects of (i) silicon carbide heteroepitaxial growth and residual stress; (ii) silicon carbide beam resonators, resonator types, and fabrication processes; (iii) sensing principles, dynamic sensing mechanical performance, and transduction techniques; (iv) damping parameters; (v) mean stress influence on mass sensitivity of SiC flexural microbridge resonators; and (vi) gradient stress impact on SiC cantilever static behavior. The primary goal is to suggest the means to improve the mass sensitivity parameter and application range of epitaxial silicon carbide microbeam resonators and benchmark it with other relevant materials.
Keshavarz, R, Mohammadi, A & Abdipour, A 2017, 'A linearity improved quad-band amplifier based on E-CRLH transmission line', International Journal of Microwave and Wireless Technologies, vol. 9, no. 8, pp. 1603-1610.
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This paper outlines a new class of quad-band amplifier (QBA) realized using extended composite right- and left-handed coupled lines. The design procedure to reach the QB CLs with predefined frequency operations and characteristic impedance of their ports is clearly presented. Designed and fabricated QBA operation frequencies are$f_{b_{1}} = 2.9\,GHz$and${\rm \;} f_{b_2} = 4.3\,GHz$(output port B)${\bi \;} \; f_{f_1} = 3.8\,GHz\; $and$\; \; f_{f_2} = 5\,GHz\; $(output port C) and the proposed structure exhibits a matching (−10 dB) bandwidth of over 300 MHz in each operation frequency bands. In addition, the insertion loss is smaller than 1 dB. The length and the width of the proposed QBA are approximately 7.7 and 2.4 cm, respectively. To further demonstrate the idea, a QBA is successfully designed and fabricated. The simulated and measured results of the proposed QBA are presented to verify the proposed idea.
Keshavarzi, A & Ball, J 2017, 'Enhancing PIV image and fractal descriptor for velocity and shear stresses propagation around a circular pier', Geoscience Frontiers, vol. 8, no. 4, pp. 869-883.
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© 2016 China University of Geosciences (Beijing) and Peking University In this study, the fractal dimensions of velocity fluctuations and the Reynolds shear stresses propagation for flow around a circular bridge pier are presented. In the study reported herein, the fractal dimension of velocity fluctuations (u′, v′, w′) and the Reynolds shear stresses (u′v′ and u′w′) of flow around a bridge pier were computed using a Fractal Interpolation Function (FIF) algorithm. The velocity fluctuations of flow along a horizontal plane above the bed were measured using Acoustic Doppler Velocity meter (ADV) and Particle Image Velocimetry (PIV). The PIV is a powerful technique which enables us to attain high resolution spatial and temporal information of turbulent flow using instantaneous time snapshots. In this study, PIV was used for detection of high resolution fractal scaling around a bridge pier. The results showed that the fractal dimension of flow fluctuated significantly in the longitudinal and transverse directions in the vicinity of the pier. It was also found that the fractal dimension of velocity fluctuations and shear stresses increased rapidly at vicinity of pier at downstream whereas it remained approximately unchanged far downstream of the pier. The higher value of fractal dimension was found at a distance equal to one times of the pier diameter in the back of the pier. Furthermore, the average fractal dimension for the streamwise and transverse velocity fluctuations decreased from the centreline to the side wall of the flume. Finally, the results from ADV measurement were consistent with the result from PIV, therefore, the ADV enables to detect turbulent characteristics of flow around a circular bridge pier.
Khakzad, N, Naderpour, M & Reniers, G 2017, 'A Markov chain approach to domino effects in chemical plants', Journal of safety, health & environmental research, vol. 13, no. 2, pp. 360-369.
Khalilpour, KR, Vassallo, AM & Chapman, AC 2017, 'Does battery storage lead to lower GHG emissions?', The Electricity Journal, vol. 30, no. 10, pp. 1-7.
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© 2017 Elsevier Inc. A study of the Australian National Electricity Market shows that using battery storage in the Australian national electricity grid reduces CO2 emissions by providing further flexibility for the operation of conventional generators and also by decreasing the amount of unused renewable energy. Interestingly, energy storage is more efficient at reducing carbon emissions in the context of higher carbon and/or fuel prices. In addition to reducing emissions, battery storage can decrease the cost of delivered energy.
Khalilpour, R, Milani, D, Qadir, A, Chiesa, M & Abbas, A 2017, 'A novel process for direct solvent regeneration via solar thermal energy for carbon capture', RENEWABLE ENERGY, vol. 104, no. C, pp. 60-75.
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The energy for the solvent regeneration of post-combustion carbon capture (PCC) process is typically provided by steam bleeding from the power plant (PP) steam cycle. The energy penalty for steam bleeding results in serious reduction in the PP capacity estimated to be in the range of 10–40%. Power plant repowering or hybridization using solar-assisted PCC (SPCC) is a promising approach to satisfy carbon capture targets as well as PP load, concurrently. The drawback of this methodology is that notable amounts of solar energy are wasted during heat transfer from solar radiation to rich solvent.
Khan, I, Castel, A & Gilbert, RI 2017, 'Effects of Fly Ash on Early-Age Properties and Cracking of Concrete', ACI Materials Journal, vol. 114, no. 4, pp. 673-681.
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Khan, I, Castel, A & Gilbert, RI 2017, 'Tensile creep and early-age concrete cracking due to restrained shrinkage', Construction and Building Materials, vol. 149, pp. 705-715.
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Concrete structures are prone to cracking due to restraint provided to early age autogenous and drying shrinkage. In addition, the risk of early-age thermal cracking is increased by increasing the degree of restraint to early-age thermal contraction. At this early-age, tensile creep plays a key role in relaxing shrinkage induced tensile stresses and delaying the time to cracking. However, limited data are available concerning tensile creep of concrete and the magnitude and rate of development of the early-age shrinkage of concrete. As a consequence, restraint to shrinkage is often poorly modelled in structural design. In order to accurately quantify the early-age shrinkage and tensile creep of concrete, a comprehensive experimental program is being conducted at the UNSW Centre for Infrastructure Engineering and Safety. Tensile creep is measured on dog-bone shaped specimens subjected to constant sustained tensile stress, while shrinkage is measured on identical unloaded specimens. Restrained ring tests were also performed to validate the tensile creep coefficients calculated from dog-bone specimens. A simple analytical procedure to accurately predict the degree of restraint and the tensile stresses in concrete induced by shrinkage is described for the restrained ring specimens.
Khan, MH, Jamali, SS, Lyalin, A, Molino, PJ, Jiang, L, Liu, HK, Taketsugu, T & Huang, Z 2017, 'Atomically Thin Hexagonal Boron Nitride Nanofilm for Cu Protection: The Importance of Film Perfection', Advanced Materials, vol. 29, no. 4, pp. 1-7.
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Outstanding protection of Cu by high-quality boron nitride nanofilm (BNNF) 1-2 atomic layers thick in salt water is observed, while defective BNNF accelerates the reaction of Cu toward water. The chemical stability, insulating nature, and impermeability of ions through the BN hexagons render BNNF a great choice for atomic-scale protection.
Khan, MH, Liu, HK, Sun, X, Yamauchi, Y, Bando, Y, Golberg, D & Huang, Z 2017, 'Few-atomic-layered hexagonal boron nitride: CVD growth, characterization, and applications', Materials Today, vol. 20, no. 10, pp. 611-628.
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© 2017 Two-dimensional (2D) materials have shown outstanding properties that make them the materials of choice for future semiconductor and flexible nanoelectronics. Hexagonal boron nitride nanosheet (BNNS) is one of the most studied 2D materials due to its extraordinary properties and potential applications. The synthesis of large, homogeneous, and few-layered BNNS, however, remains challenging. Among the various synthetic routes, chemical vapour deposition (CVD) is preferred on the grounds of its potential to yield large BNNS with controllable atomic layers and minimal contamination. We thus devote this review to the CVD growth of BNNS, and its characterization and applications. The recent progresses in the CVD growth of BNNS is firstly summarized from the aspects of precursors, substrates, growth mechanisms, and transfer techniques. This review then moves on to the characterization of few-atomic-layered h-BN sheets, covering a variety of microscopic and spectroscopic techniques that have proved useful for assessing the quality of BNNS. The applications of the BNNS are also summarized. This review is expected to instigate new methods and improvements in relation to the CVD growth of BNNS, which has enabled exceptional performance as a key component of nanoscale electronics.
Khan, MSH, Castel, A & Noushini, A 2017, 'Carbonation of a low-calcium fly ash geopolymer concrete', Magazine of Concrete Research, vol. 69, no. 1, pp. 24-34.
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The carbonation resistance of a blended slag and low-calcium fly ash (FA) geopolymer concrete was investigated. The geopolymer binder studied was composed of 90% low-calcium FA and 10% ground granulated blast-furnace slag. The alkalinity of the pore solution plays a pivotal role in carbonation progression and subsequent corrosion initiation. pH profiles were measured to assess the pore solution alkalinity. Phenolphthalein indicator was used to measure the carbonation depth. X-ray diffraction (XRD) and quantification were carried out to identify and quantify the carbonation products. The obtained pH profiles illustrated a wider semi-carbonation zone in the geopolymer specimens, although the pH drop was insignificant in most cases. XRD analysis revealed that nahcolite mainly formed at 3% carbon dioxide concentration and led to a significant drop in pH values. The results further demonstrated that 1% accelerated carbonation replicated the natural carbonation process well, with only natron identified as a carbonation product. This work contributes to the assessment of the risk of carbonation-induced reinforcement corrosion in low-calcium FA geopolymer concrete.
Khan, ZH, Kermany, AR, Öchsner, A & Iacopi, F 2017, 'Mechanical and electromechanical properties of graphene and their potential application in MEMS', Journal of Physics D: Applied Physics, vol. 50, no. 5, pp. 053003-053003.
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� 2017 IOP Publishing Ltd. Graphene-based micro-electromechanical systems (MEMS) are very promising candidates for next generation miniaturized, lightweight, and ultra-sensitive devices. In this review, we review the progress to date of the assessment of the mechanical, electromechanical, and thermomechanical properties of graphene for application in graphene-based MEMS. Graphene possesses a plethora of outstanding properties - such as a 1 TPa Young's modulus, exceptionally high 2D failure strength that stems from its sp 2 hybridization, and strong sigma bonding between carbon atoms. Such exceptional mechanical properties can enable, for example, graphene-based sound sources capable of generating sound beyond the audible range. The recently engineered piezoelectric properties of atomic force microscope tip-pressed graphene membranes or supported graphene on SiO 2 substrates, have paved the way in fabricating graphene-based nano-generators and actuators. On the other hand, graphene's piezoresistive properties have enabled miniaturized pressure and strain sensors. 2D graphene nano-mechanical resonators can potentially measure ultralow forces, charges and potentially detect single atomic masses. The exceptional tribology of graphene can play a significant role in achieving superlubricity. In addition, the highest reported thermal conductivity of graphene is amenable for use in chips and providing better performing MEMS, as heat is efficiently dissipated. On top of that, graphene membranes could be nano-perforated to realize specialized applications like DNA translocation and desalination. Finally, to ensure stability and reliability of the graphene-based MEMS, adhesion is an important mechanical property that should be considered. In general, graphene could be used as a structural material in resonators, sensors, actuators and nano-generators with better performance and sensitivity than conventional MEMS.
Khandelwal, M, Armaghani, DJ, Faradonbeh, RS, Yellishetty, M, Majid, MZA & Monjezi, M 2017, 'Classification and regression tree technique in estimating peak particle velocity caused by blasting', Engineering with Computers, vol. 33, no. 1, pp. 45-53.
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Khandelwal, M, Mahdiyar, A, Armaghani, DJ, Singh, TN, Fahimifar, A & Faradonbeh, RS 2017, 'An expert system based on hybrid ICA-ANN technique to estimate macerals contents of Indian coals', Environmental Earth Sciences, vol. 76, no. 11.
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Khandelwal, M, Shirani Faradonbeh, R, Monjezi, M, Armaghani, DJ, Majid, MZBA & Yagiz, S 2017, 'Function development for appraising brittleness of intact rocks using genetic programming and non-linear multiple regression models', Engineering with Computers, vol. 33, no. 1, pp. 13-21.
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Khuat, TT & Le, MH 2017, 'A genetic algorithm with multi-parent crossover using quaternion representation for numerical function optimization', Applied Intelligence, vol. 46, no. 4, pp. 810-826.
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Khuat, TT & Le, MH 2017, 'Applying teaching-learning to artificial bee colony for parameter optimization of software effort estimation model', Journal of Engineering Science and Technology, vol. 12, no. 5, pp. 1178-1190.
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Artificial Bee Colony inspired by the foraging behaviour of honey bees is a novel meta-heuristic optimization algorithm in the community of swarm intelligence algorithms. Nevertheless, it is still insufficient in the speed of convergence and the quality of solutions. This paper proposes an approach in order to tackle these downsides by combining the positive aspects of Teaching-Learning based optimization and Artificial Bee Colony. The performance of the proposed method is assessed on the software effort estimation problem, which is the complex and important issue in the project management. Software developers often carry out the software estimation in the early stages of the software development life cycle to derive the required cost and schedule for a project. There are a large number of methods for effort estimation in which COCOMO II is one of the most widely used models. However, this model has some restricts because its parameters have not been optimized yet. In this work, therefore, we will present the approach to overcome this limitation of COCOMO II model. The experiments have been conducted on NASA software project dataset and the obtained results indicated that the improvement of parameters provided better estimation capabilities compared to the original COCOMO II model.
Kiani, B, Sajedi, S, Gandomi, AH, Huang, Q & Liang, RY 2017, 'Optimal adjustment of ACI formula for shrinkage of concrete containing pozzolans', Construction and Building Materials, vol. 131, pp. 485-495.
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Very few models have been developed to estimate shrinkage of concrete containing pozzolans, and most existing models (particularly the ACI model) are not calibrated with pozzolanic concrete. This paper presents an improvement of the ACI model for shrinkage of concrete containing three types of pozzolans including silica fume (SF), fly ash (FA), and slag (SL). A comprehensive database is collected from the literature to cover a wide range of mixture components and mix proportions. In particular, to capture the effect of the dosage and type of each pozzolan, the time function in the ACI model is modified and a new correction factor associated with compressive strength is added. The model parameters in the modified time function and the new correction factor are assessed using a computational intelligence method called particle swarm optimization. The results of several statistical indicators show better prediction performance for the modified ACI model (M-ACI) than the original ACI formula.
Kianinia, M, Bradac, C, Wang, F, Sontheimer, B, Tran, TT, Nguyen, M, Kim, S, Xu, Z-Q, Jin, D, Schell, AW, Lobo, CJ, Aharonovich, I & Toth, M 2017, 'Super-resolution imaging of quantum emitters in layered materials', Nature Communications, vol. 9, no. 1, pp. 874-874.
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Layered van der Waals materials are emerging as compelling two-dimensional(2D) platforms for studies of nanophotonics, polaritonics, valleytronics andspintronics, and have the potential to transform applications in sensing,imaging and quantum information processing. Amongst these, hexagonal boronnitride (hBN) is unique in that it hosts ultra-bright, room temperature singlephoton emitters (SPEs). However, an outstanding challenge is to locate SPEs inhBN with high precision, a task which requires breaking the optical diffractionlimit. Here, we report the imaging of SPEs in layered hBN with a spatialresolution of 63 nm using ground state depletion (GSD) nanoscopy. Furthermore,we show that SPEs in hBN possess nonlinear photophysical properties which canbe used to realize a new variant of GSD that employs a coincident pair ofdoughnut-shaped lasers to reduce the laser power that is needed to achieve agiven resolution target. Our findings expand the current understanding of thephotophysics of quantum emitters in layered hBN and demonstrate the potentialfor advanced nanophotonic and bio-imaging applications which requirelocalization of individual emitters with super-resolution accuracy.
Kieferová, M & Wiebe, N 2017, 'Tomography and generative training with quantum Boltzmann machines', Physical Review A, vol. 96, no. 6.
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Kim, E, Wright, MJP, Sioson, L, Novos, T, Gill, AJ, Benn, DE, White, C, Dwight, T & Clifton-Bligh, RJ 2017, 'Utility of the succinate:fumarate ratio for assessing SDH dysfunction in different tumor types', Molecular Genetics and Metabolism Reports, vol. 10, pp. 45-49.
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Kim, J, Blandin, G, Phuntsho, S, Verliefde, A, Le-Clech, P & Shon, H 2017, 'Practical considerations for operability of an 8″ spiral wound forward osmosis module: Hydrodynamics, fouling behaviour and cleaning strategy', Desalination, vol. 404, pp. 249-258.
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© 2016 Elsevier B.V. A better understanding of large spiral wound forward osmosis (SW FO) module operation is needed to provide practical insight for a full-scale FO practical implementation desalination plant. Therefore, this study investigated two different 8″ SW FO modules (i.e. cellulose tri acetate, CTA and thin film composite, TFC) in terms of hydrodynamics, operating pressure, water and solute fluxes, fouling behaviour and cleaning strategy. For both modules, a significantly lower flow rate was required in the draw channel than in the feed channel due to important pressure-drop in the draw channel and was a particularly critical operating challenge in the CTA module when permeate spacers are used. Under FO and pressure assisted osmosis (PAO, up to 2.5 bar) operations, the TFC module featured higher water flux and lower reverse salt flux than the CTA module. For both modules, fouling tests demonstrated that feed inlet pressure was more sensitive to foulant deposition than the flux, thus confirming that FO fouling deposition occurs in the feed channel rather than on the membrane surface. Osmotic backwash combined with physical cleaning used in this study confirmed to be effective and adapted to large-scale FO module operation.
Kim, J, Cheng, J, Guivant, J & Nieto, J 2017, 'Compressed fusion of GNSS and inertial navigation with simultaneous localization and mapping', IEEE Aerospace and Electronic Systems Magazine, vol. 32, no. 8, pp. 22-36.
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Unmanned aerial vehicles (UAVs) have attracted significant attention from both civilian and defense industries over the last few decades. With the advances in low-cost inertial sensor technology and the global navigation satellite system (GNSS), the six degreesof-freedom (6DOF) vehicle state can be estimated accurately by fusing this information, which has been a crucial step toward realtime guidance and flight control [1], [2].
Kim, JE, Phuntsho, S, Chekli, L, Hong, S, Ghaffour, N, Leiknes, T, Choi, JY & Shon, HK 2017, 'Environmental and economic impacts of fertilizer drawn forward osmosis and nanofiltration hybrid system', Desalination, vol. 416, pp. 76-85.
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© 2017 Environmental and economic impacts of the fertilizer drawn forward osmosis (FDFO) and nanofiltration (NF) hybrid system were conducted and compared with conventional reverse osmosis (RO) hybrid scenarios using microfiltration (MF) or ultrafiltration (UF) as a pre-treatment process. The results showed that the FDFO-NF hybrid system using thin film composite forward osmosis (TFC) FO membrane has less environmental impact than conventional RO hybrid systems due to lower consumption of energy and cleaning chemicals. The energy requirement for the treatment of mine impaired water by the FDFO-NF hybrid system was 1.08 kWh/m3, which is 13.6% less energy than an MF-RO and 21% less than UF-RO under similar initial feed solution. In a closed-loop system, the FDFO-NF hybrid system using a TFC FO membrane with an optimum NF recovery rate of 84% had the lowest unit operating expenditure of AUD $0.41/m3. Besides, given the current relatively high price and low flux performance of the cellulose triacetate and TFC FO membranes, the FDFO-NF hybrid system still holds opportunities to reduce operating expenditure further. Optimizing NF recovery rates and improving the water flux of the membrane would decrease the unit OPEX costs, although the TFC FO membrane would be less sensitive to this effect.
Kim, Y, Li, S, Chekli, L, Phuntsho, S, Ghaffour, N, Leiknes, T & Shon, HK 2017, 'Influence of fertilizer draw solution properties on the process performance and microbial community structure in a side-stream anaerobic fertilizer-drawn forward osmosis – ultrafiltration bioreactor', Bioresource Technology, vol. 240, pp. 149-156.
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© 2017 Elsevier Ltd In this study, a side-stream anaerobic fertilizer-drawn forward osmosis (FDFO) and ultrafiltration (UF) membrane bioreactor (MBR) hybrid system was proposed and operated for 55 days. The FDFO performance was first investigated in terms of flux decline with various fertilizers draw solution. Flux decline was very severe with all fertilizers due to the absence of aeration and the sticky property of sludge. Flux recovery by physical cleaning varied significantly amongst tested fertilizers which seriously affected biofouling in FDFO via reverse salt flux (RSF). Besides, RSF had a significant impact on nutrient accumulation in the bioreactor. These results indicated that nutrient accumulation negatively influenced the anaerobic activity. To elucidate these phenomena, bacterial and archaeal community structures were analyzed by pyrosequencing. Results showed that bacterial community structure was affected by fertilizer properties with less impact on archaeal community structure, which resulted in a reduction in biogas production and an increase in nitrogen content.
Kim, Y, Li, S, Chekli, L, Woo, YC, Wei, C-H, Phuntsho, S, Ghaffour, N, Leiknes, T & Shon, HK 2017, 'Assessing the removal of organic micro-pollutants from anaerobic membrane bioreactor effluent by fertilizer-drawn forward osmosis', Journal of Membrane Science, vol. 533, pp. 84-95.
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© 2017 Elsevier B.V. In this study, the behavior of organic micro-pollutants (OMPs) transport including membrane fouling was assessed in fertilizer-drawn forward osmosis (FDFO) during treatment of the anaerobic membrane bioreactor (AnMBR) effluent. The flux decline was negligible when the FO membrane was oriented with active layer facing feed solution (AL-FS) while severe flux decline was observed with active layer facing draw solution (AL-DS) with di-ammonium phosphate (DAP) fertilizer as DS due to struvite scaling inside the membrane support layer. DAP DS however exhibited the lowest OMPs forward flux or higher OMPs rejection rate compared to other two fertilizers (i.e., mono-ammonium phosphate (MAP) and KCl). MAP and KCl fertilizer DS had higher water fluxes that induced higher external concentration polarization (ECP) and enhanced OMPs flux through the FO membrane. Under the AL-DS mode of membrane orientation, OMPs transport was further increased with MAP and KCl as DS due to enhanced concentrative internal concentration polarization while with DAP the internal scaling enhanced mass transfer resistance thereby lowering OMPs flux. Physical or hydraulic cleaning could successfully recover water flux for FO membranes operated under the AL-FS mode but only partial flux recovery was observed for membranes operated under AL-DS mode because of internal scaling and fouling in the support layer. Osmotic backwashing could however significantly improve the cleaning efficiency.
Kim, Y, Woo, YC, Phuntsho, S, Nghiem, LD, Shon, HK & Hong, S 2017, 'Evaluation of fertilizer-drawn forward osmosis for coal seam gas reverse osmosis brine treatment and sustainable agricultural reuse', Journal of Membrane Science, vol. 537, pp. 22-31.
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© 2017 Elsevier B.V. The fertilizer-drawn forward osmosis (FDFO) was investigated for treating coal seam gas (CSG) produced water to generate nutrient rich solution for irrigation. Its performance was evaluated and compared with reverse osmosis (RO) in terms of specific energy consumption (SEC) and nutrient concentrations in the final product water. The RO-FDFO hybrid process was developed to further improve FDFO. The results showed that FDFO has the lowest SEC followed by the RO-FDFO and RO processes. The final nutrient concentration simulation demonstrated that the RO-FDFO hybrid process has lower final concentration, higher maximum recovery and lower nutrient loss than the stand alone FDFO process. Therefore, it was suggested that the RO-FDFO is the most effective treatment option for CSG produced water as well as favourable nutrient supply. Lastly, membrane fouling mechanism was examined in CSG RO brine treatment by FDFO, and the strategies for controlling fouling were critically evaluated. KNO3 exhibited the highest flux decline corresponding to the highest reverse salt flux, while the most severe membrane scaling was observed with calcium nitrate, primarily due to the reverse transport of calcium ions. To control membrane fouling in FDFO process, both physical flushing and chemical cleaning were examined. Membrane cleaning with citric acid of 5% resulted in a complete flux recovery.
Klaseboer, E, Sepehrirahnama, S & Chan, DYC 2017, 'Space-time domain solutions of the wave equation by a non-singular boundary integral method and Fourier transform', The Journal of the Acoustical Society of America, vol. 142, no. 2, pp. 697-707.
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The general space-time evolution of the scattering of an incident acoustic plane wave pulse by an arbitrary configuration of targets is treated by employing a recently developed non-singular boundary integral method to solve the Helmholtz equation in the frequency domain from which the space-time solution of the wave equation is obtained using the fast Fourier transform. The non-singular boundary integral solution can enforce the radiation boundary condition at infinity exactly and can account for multiple scattering effects at all spacings between scatterers without adverse effects on the numerical precision. More generally, the absence of singular kernels in the non-singular integral equation confers high numerical stability and precision for smaller numbers of degrees of freedom. The use of fast Fourier transform to obtain the time dependence is not constrained to discrete time steps and is particularly efficient for studying the response to different incident pulses by the same configuration of scatterers. The precision that can be attained using a smaller number of Fourier components is also quantified.
Ko, L-W, Komarov, O, Hairston, WD, Jung, T-P & Lin, C-T 2017, 'Sustained Attention in Real Classroom Settings: An EEG Study', Frontiers in Human Neuroscience, vol. 11, pp. 1-10.
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© 2017 Ko, Komarov, Hairston, Jung and Lin. Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra.
Kolamunna, H, Chauhan, J, Hu, Y, Thilakarathna, K, Perino, D, Makaroff, D & Seneviratne, A 2017, 'Are Wearables Ready for Secure and Direct Internet Communication?', GetMobile: Mobile Computing and Communications, vol. 21, no. 3, pp. 5-10.
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Recent advances in wearable technology tend towards standalone wearables. Most of today's wearable devices and applications still rely on a paired smartphone for secure Internet communication, even though many current generation wearables are equipped with Wi-Fi and 3G/4G network interfaces that provide direct Internet access. Yet it is not clear if such communication can be efficiently and securely supported through existing protocols. Our findings show that it is possible to use secure and efficient direct communication between wearables and the Internet
Kong, F, Sun, X, Guo, YJ & Zhu, H 2017, 'Queue-Aware Optimal Bandwidth Allocation in Heterogeneous Networks', IEEE Wireless Communications Letters, vol. 6, no. 6, pp. 730-733.
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© 2017 IEEE. This letter considers how to allocate the bandwidth to multiple radio access technologies (RATs) in heterogeneous networks. In contrast to previous studies where base stations (BSs) are assumed to be transmitting all the time, it is assumed that the incoming packets from users form a queue in each BS. A minimization problem of the network average power consumption and a maximization problem of the network signalto- interference ratio coverage are formulated, which are shown to be convex and concave with respect to the bandwidth allocation to each RAT, respectively. By using an approximation of the average traffic intensity, closed-form solutions are obtained for both problems.
Kong, FH & Manchester, IR 2017, 'Contraction Analysis of Nonlinear Iterative Learning Control', IFAC-PapersOnLine, vol. 50, no. 1, pp. 10876-10881.
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Iterative learning control (ILC) is widely used as a simple method for precise tracking of systems under repetitive conditions. ILC operates by “learning” from the previous iteration's errors, correcting them over a number of iterations. However, the question of whether or not a nonlinear ILC system converges is still in general an open one. Assuming a state-space formulation, we use contraction analysis to formulate a convergence condition for ILC system as a linear matrix inequality (LMI). Finally, we compute a convergence certificate for a simple example involving “anticogging” a permanent-magnet synchronous motor driving a pendulum in simulation.
Kong, S, Li, S & Sioutis, M 2017, 'Exploring Directional Path-Consistency for Solving Constraint Networks', The Computer Journal, vol. 61, no. 9.
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Among the local consistency techniques used for solving constraint networks,path-consistency (PC) has received a great deal of attention. However,enforcing PC is computationally expensive and sometimes even unnecessary.Directional path-consistency (DPC) is a weaker notion of PC that considers agiven variable ordering and can thus be enforced more efficiently than PC. Thispaper shows that DPC (the DPC enforcing algorithm of Dechter and Pearl) decidesthe constraint satisfaction problem (CSP) of a constraint language if it iscomplete and has the variable elimination property (VEP). However, we also showthat no complete VEP constraint language can have a domain with more than 2values. We then present a simple variant of the DPC algorithm, called DPC*, andshow that the CSP of a constraint language can be decided by DPC* if it isclosed under a majority operation. In fact, DPC* is sufficient for guaranteeingbacktrack-free search for such constraint networks. Examples of majority-closedconstraint classes include the classes of connected row-convex (CRC)constraints and tree-preserving constraints, which have found applications invarious domains, such as scene labeling, temporal reasoning, geometricreasoning, and logical filtering. Our experimental evaluations show that DPC*significantly outperforms the state-of-the-art algorithms for solvingmajority-closed constraints.
Kong, S, Li, S, Li, Y & Long, Z 2017, 'On tree-preserving constraints', Annals of Mathematics and Artificial Intelligence, vol. 81, no. 3-4, pp. 241-271.
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© 2017, Springer International Publishing Switzerland. The study of tractable subclasses of constraint satisfaction problems is a central topic in constraint solving. Tree convex constraints are extensions of the well-known row convex constraints. Just like the latter, every path-consistent tree convex constraint network is globally consistent. However, it is NP-complete to decide whether a tree convex constraint network has solutions. This paper studies and compares three subclasses of tree convex constraints, which are called chain-, path-, and tree-preserving constraints respectively. The class of tree-preserving constraints strictly contains the subclasses of path-preserving and arc-consistent chain-preserving constraints. We prove that, when enforcing strong path-consistency on a tree-preserving constraint network, in each step, the network remains tree-preserving. This ensures the global consistency of consistent tree-preserving networks after enforcing strong path-consistency, and also guarantees the applicability of the partial path-consistency algorithms to tree-preserving constraint networks, which is usually much more efficient than the path-consistency algorithms for large sparse constraint networks. As an application, we show that the class of tree-preserving constraints is useful in solving the scene labelling problem.
Kook, S, Kim, J, Kim, S-J, Lee, J, Han, D, Phuntsho, S, Shim, W-G, Hwang, M, Shon, HK & Kim, IS 2017, 'Effect of initial feed and draw flowrates on performance of an 8040 spiral-wound forward osmosis membrane element', Desalination and Water Treatment, vol. 72, pp. 1-12.
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© 2017, Desalination Publications. All rights reserved. This study investigated the effects of initial feed (20–50 L/min) and draw flowrates (2–5 L/min) on 8040 spiral-wound FO element performances in serial configuration for a forward osmosis and reverse osmosis (FO-RO) hybrid system employing single element-based tests. Average Jw,ave values for varying feed and draw flowrates were found to be 20.93, 19.38 and 18.71 LMH at E1, E2 and E3 (first, second and third elements in a serial configuration), respectively, with averaged diluted draw concentrations of 12.55, 7.88 and 5.77 g/L (initial conc. = 35 g/L). The draw stream dilution was not governed by Jw,ave but by the initial draw flowrates at the inlet that governs the retention time of the draw water body in the element. To sum up the performance results, it was concluded that initial draw flowrate is found to govern the performances of FO elements in series in terms of both production of diluted draw stream, determined by the averaged water flux of the FO element, Jw,ave, and the degree of draw stream dilution. Specific energy consumptions (SECs) of RO were estimated with varying RO feed concentrations (i.e. diluted draw concentration); it was observed the efficiency of SEC reduction by the dilution significantly decays after a critical RO recovery rate. This study successfully provides a valuable insight for feasible application of the FO-RO hybrid system.
Krzoska, S, Eickelmann, M, Schmitt, J & Deuse, J 2017, 'Data Mining-based forecasting of rework duration-Predictive rework control and work process optimization in the automotive assembly', WT Werkstattstechnik, vol. 107, no. 10, pp. 773-778.
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The article shows at the example of rework control and operating process optimization in the car assembly how recorded product- and process-related quality data can be analyzed and used efficiently by using Data Mining-methods. With data from MES-systems regression trees were built for a vehicle-specific rework duration forecast. The basic concept and validation results will be presented below.
Krzoska, S, Eickelmann, M, Schmitt, J & Deuse, JP 2017, 'Data Mining zur Nacharbeitsdauerprognose*/Data Mining-based forecasting of rework duration - Predictive rework control and work process optimization in the automotive assembly', wt Werkstattstechnik online, vol. 107, no. 10, pp. 773-778.
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Der Fachbeitrag zeigt am Beispiel der Nacharbeitssteuerung und Arbeitsprozessoptimierung in der Automobilmontage, wie produkt- und prozessbezogene Qualitätsdaten durch den Einsatz von Data Mining-Methoden analysiert sowie effizient genutzt werden können. Dazu wurden Daten aus Manufacturing-Execution-Systemen (MES) mithilfe von Regressionsbäumen zur Entwicklung einer fahrzeugspezifischen Nacharbeitsdauerprognose ausgewertet. Das grundlegende Data Mining-Konzept sowie die Pilotierungsergebnisse werden nachfolgend dargestellt.
The article shows at the example of rework control and operating process optimization in the car assembly how recorded product- and process-related quality data can be analyzed and used efficiently by using Data Mining-methods. With data from MES-systems regression trees were built for a vehicle-specific rework duration forecast. The basic concept and validation results will be presented below.
Kuang, S, Dong, D & Petersen, IR 2017, 'Rapid Lyapunov control of finite-dimensional quantum systems', Automatica, vol. 81, pp. 164-175.
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Kulasinghe, A, Perry, C, Kenny, L, Warkiani, ME, Nelson, C & Punyadeera, C 2017, 'PD-L1 expressing circulating tumour cells in head and neck cancers', BMC Cancer, vol. 17, no. 1, pp. 1-6.
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© 2017 The Author(s). Background: Blockade of the PD-1/PD-L1 immune checkpoint pathway is emerging as a promising immunotherapeutic approach for the management and treatment of head and neck cancer patients who do not respond to 1st/2nd line therapy. However, as checkpoint inhibitors are cost intensive, identifying patients who would most likely benefit from anti PD-L1 therapy is required. Developing a non-invasive technique would be of major benefit to the patient and to the health care system. Case presentation: We report the case of a 56 year old man affected by a supraglottic squamous cell carcinoma (SCC). A CT scan showed a 20 mm right jugulodigastric node and suspicious lung lesions. The lung lesion was biopsied and confirmed to be consistent with SCC. The patient was offered palliative chemotherapy. At the time of presentation, a blood sample was taken for circulating tumour cell (CTC) analysis. The dissemination of cancer was confirmed by the detection of CTCs in the peripheral blood of the patient, measured by the CellSearch System (Janssen Diagnostics). Using marker-independent, low-shear spiral microfluidic technology combined with immunocytochemistry, CTC clusters were found in this patient at the same time point, expressing PD-L1. Conclusion: This report highlights the potential use of CTCs to identify patients which might respond to anti PD-L1 therapy.
Kulasinghe, A, Tran, THP, Blick, T, O’Byrne, K, Thompson, EW, Warkiani, ME, Nelson, C, Kenny, L & Punyadeera, C 2017, 'Enrichment of circulating head and neck tumour cells using spiral microfluidic technology', Scientific Reports, vol. 7, no. 1, pp. 1-10.
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AbstractWhilst locoregional control of head and neck cancers (HNCs) has improved over the last four decades, long-term survival has remained largely unchanged. A possible reason for this is that the rate of distant metastasis has not changed. Such disseminated disease is reflected in measurable levels of cancer cells in the blood of HNC patients, referred to as circulating tumour cells (CTCs). Numerous marker-independent techniques have been developed for CTC isolation and detection. Recently, microfluidics-based platforms have come to the fore to avoid molecular bias. In this pilot, proof of concept study, we evaluated the use of the spiral microfluidic chip for CTC enrichment and subsequent detection in HNC patients. CTCs were detected in 13/24 (54%) HNC patients, representing both early to late stages of disease. Importantly, in 7/13 CTC-positive patients, CTC clusters were observed. This is the first study to use spiral microfluidics technology for CTC enrichment in HNC.
Kumara, C & Indraratna, B 2017, 'Normal Deformation and Formation of Contacts in Rough Rock Fractures and Their Influence on Fluid Flow', International Journal of Geomechanics, vol. 17, no. 1, pp. 04016022-04016022.
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Kurian, JC & John, BM 2017, 'User-generated content on the Facebook page of an emergency management agency', Online Information Review, vol. 41, no. 4, pp. 558-579.
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PurposeThe purpose of this paper is to explore themes eventuating from the user-generated content posted by users on the Facebook page of an emergency management agency.Design/methodology/approachAn information classification framework was used to classify user-generated content posted by users including all of the content posted during a six month period (January to June 2015). The posts were read and analysed thematically to determine the overarching themes evident across the entire collection of user posts.FindingsThe results of the analysis demonstrate that the key themes that eventuate from the user-generated content posted are “Self-preparedness”, “Emergency signalling solutions”, “Unsurpassable companion”, “Aftermath of an emergency”, and “Gratitude towards emergency management staff”. Major user-generated content identified among these themes are status-update, criticism, recommendation, and request.Research limitations/implicationsThis study contributes to theory on the development of key themes from user-generated content posted by users on a public social networking site. An analysis of user-generated content identified in this study implies that, Facebook is primarily used for information dissemination, coordination and collaboration, and information seeking in the context of emergency management. Users may gain the benefits of identity construction and social provisions, whereas social conflict is a potential detrimental implication. Other user costs include lack of social support by stakeholders, investment in social infrastructure and additional work force req...
Kuruneru, STW, Sauret, E, Saha, SC & Gu, YT 2017, 'A coupled finite volume & discrete element method to examine particulate foulant transport in metal foam heat exchangers', International Journal of Heat and Mass Transfer, vol. 115, pp. 43-61.
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© 2017 Elsevier Ltd The exorbitant costs associated with particulate fouling necessitates the need to formulate advanced methods to comprehend mass transport and fouling in heat exchangers. A coupled finite volume and discrete element method is developed to investigate the mechanisms that govern particle-laden gas flows and particulate fouling in idealized porous metal foam heat exchangers. This meticulous examination will take great precedence in addressing the negative impact particulate fouling has in the industry. The numerical method will permit engineers to better optimize porous metal foams for applications such as air-cooled heat aluminium heat exchangers. The robustness of this numerical method is validated against the original and modified Darcy-Forchheimer analytical equations through a novel modified porosity theory. Good agreement is obtained between the numerical and analytical results. It is shown that both 2D and 3D heat exchanger configurations of identical porosities with different geometric profiles have shown similar deposition fraction and pressure drop magnitudes albeit having a slightly different fouling layer distribution. This is attributable to the particle properties and the variation between the 2D and 3D inlet injection plane surface area. It is found that the commencement of sandstone and sawdust deposition in a 6-pore configuration differs by 0.57 s, whereas a three pore configuration completely nullifies particulate fouling irrespective of foulant type. A staggered row configuration has shown significant reduction in pressure drop as compared to the 6-pore heat exchanger configuration. For the case of sandstone particles, the optimum heat exchanger geometry exhibits 78% less pressure drop and 100% less deposition fraction compared with the original 6-pore configuration.
Kuruneru, STW, Sauret, E, Saha, SC & Gu, YT 2017, 'Two- and four-way coupling of cohesive poly-disperse particulate foulants on a metal foam fibre immersed in quiescent fluid', International Communications in Heat and Mass Transfer, vol. 89, pp. 176-184.
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© 2017 Elsevier Ltd The ubiquity and complexity of the unsteadiness of fouling and multiphase flows in various engineering systems signify the need to develop advanced numerical methods to study the underlying phenomena of two-phase particle-laden fluid flows in heat exchanger systems such as, compact electronics cooling (i.e. heat sinks) and HVAC & R systems. Fouling is omnipresent in many industries such as power generation, chemical, petroleum, among others. The mechanisms governing fouling coupled with multiphase foulant-laden fluid flow in porous heat exchangers, such as metal foams, are very complex and poorly understood. This investigation forms the basis for addressing the implications of fouling for a myriad of industrial processes. This study will discuss the development of a coupled finite volume method and discrete element method (FVM-DEM) numerical framework to investigate the mechanisms governing particulate fouling in an idealized metal foam heat exchanger. This study resolves four-way and two-way coupled interactions based on poly-disperse cohesive foulants in fluid-saturated foam. The significance stems from the inclusion of cohesiveness between particle-particle and particle-wall contacts which play a decisive role in the foulant aggregation process prevalent in particles with a diameter smaller than 50 μm. The present results show that the cohesive foulants exhibit strong tendency to aggregate with time and form chain-like projections. A rigid aggregate stack is formed which alters the fluid velocity of the fluid-filled foam. Quantitative analysis of the foulant count and time-averaged aggregate count is discussed. The presented results and the numerical framework could potentially be used to optimize heat exchanger designs by considering operating conditions and foam morphology (i.e. pore diameter, ligament thickness, porosity) that is most susceptible to particulate fouling.
Kuruneru, STW, Sauret, E, Vafai, K, Saha, SC & Gu, Y 2017, 'Analysis of particle-laden fluid flows, tortuosity and particle-fluid behaviour in metal foam heat exchangers', Chemical Engineering Science, vol. 172, pp. 677-687.
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© 2017 Elsevier Ltd Tortuosity and porosity are critical parameters for characterizing fluid flow in porous media. These parameters are of paramount importance in the design of porous compact heat exchangers, packed bed reactors, and catalysis supports; however, in the context of heat exchangers, these parameters are generally formulated for single-phase fluid flow under steady-state conditions. However, most industrial flows in a porous medium such as metal foams comprise of transient particle-laden fluid flow. A coupled finite volume and discrete element method (FVM-DEM) is developed to examine transient particle-laden Stokesian flow, particulate fouling (deposition), and fluid flow patterns in an idealized porous metal foam. This work presents a comparative analysis of the analytical and numerical pressure drop profiles. The solid-gas suspension in a porous media is discussed. Secondly, a new time-dependent pore-level fluid tortuosity relation is established which is linked with a modified porosity-based Darcy-Forchheimer equation. Fluid disturbance attributable to the inception of particle deposition is quantified by the tortuosity and instantaneous shift in streamline angle ratio. It is shown that the streamline angle ratio and the meandering of fluid flow paths vary with changing porosity and tortuosity. Moreover, the Reynolds number and particle density play a critical role in the alteration of the resistance to fluid flow and permeability which is related to the tortuosity and variation in fluid flow behaviour. The results and numerical method serves as a steppingstone to better optimize various heat exchangers while taking into account complex multiphase flow behaviour and the tortuous flow paths of porous structures.
Kusumo, F, Silitonga, AS, Masjuki, HH, Ong, HC, Siswantoro, J & Mahlia, TMI 2017, 'Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and artificial neural networks', Energy, vol. 134, pp. 24-34.
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© 2017 Elsevier Ltd In this study, kernel-based extreme learning machine (K-ELM) and artificial neural network (ANN) models were developed in order to predict the conditions of an alkaline-catalysed transesterification process. The reliability of these models was assessed and compared based on the coefficient of determination (R2), root mean squared error (RSME), mean average percent error (MAPE) and relative percent deviation (RPD). The K-ELM model had higher R2 (0.991) and lower RSME, MAPE and RPD (0.688, 0.388 and 0.380) compared to the ANN model (0.984, 0.913, 0.640 and 0.634). Based on these results, the K-ELM model is a more reliable prediction model and it was integrated with ant colony optimization (ACO) in order to achieve the highest Ceiba pentandra methyl ester yield. The optimum molar ratio of methanol to oil, KOH catalyst weight, reaction temperature, reaction time and agitation speed predicted by the K-ELM model integrated with ACO was 10:1, 1 %wt, 60 °C, 108 min and 1100 rpm, respectively. The Ceiba pentandra methyl ester yield attained under these optimum conditions was 99.80%. This novel integrated model provides insight on the effect of parameters investigated on the methyl ester yield, which may be useful for industries involved in biodiesel production.
Kusumo, F, Silitonga, AS, Ong, HC, Masjuki, HH & Mahlia, TMI 2017, 'A comparative study of ultrasound and infrared transesterification of Sterculia foetida oil for biodiesel production', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 39, no. 13, pp. 1339-1346.
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© 2017 Taylor & Francis. In this study, biodiesel production using ultrasound and infrared techniques is introduced. The ultrasound and infrared techniques are more efficient for biodiesel production since they improve the mass transfer between the immiscible reactants, increase chemical reactions, and decrease the reaction time and energy consumption. The effect of the reaction time on the acid value of the esterified Sterculia feotida oil is also investigated and it is found that the acid value is 0.76 and 0.85 mg KOH/g for the ultrasound and infrared technique, respectively, at a reaction time of 60 min. In addition, it is found that the biodiesel yield obtained from the ultrasound technique is higher (99.41%) compared to the infrared technique (98.55%) at a reaction time of 60 min. The KOH catalyst is analyzed for both of these techniques and it is found that the ultrasound technique gives faster absorbed reaction compared to the infrared technique. Hence, it can be concluded that the ultrasound and infrared transesterification techniques are promising techniques for biodiesel production.
Kwon, T, Prentice, H, Oliveira, JD, Madziva, N, Warkiani, ME, Hamel, J-FP & Han, J 2017, 'Microfluidic Cell Retention Device for Perfusion of Mammalian Suspension Culture', Scientific Reports, vol. 7, no. 1, pp. 1-11.
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AbstractContinuous production of biologics, a growing trend in the biopharmaceutical industry, requires a reliable and efficient cell retention device that also maintains cell viability. Current filtration methods, such as tangential flow filtration using hollow-fiber membranes, suffer from membrane fouling, leading to significant reliability and productivity issues such as low cell viability, product retention, and an increased contamination risk associated with filter replacement. We introduce a novel cell retention device based on inertial sorting for perfusion culture of suspended mammalian cells. The device was characterized in terms of cell retention capacity, biocompatibility, scalability, and long-term reliability. This technology was demonstrated using a high concentration (>20 million cells/mL) perfusion culture of an IgG1-producing Chinese hamster ovary (CHO) cell line for 18–25 days. The device demonstrated reliable and clog-free cell retention, high IgG1recovery (>99%) and cell viability (>97%). Lab-scale perfusion cultures (350 mL) were used to demonstrate the technology, which can be scaled-out with parallel devices to enable larger scale operation. The new cell retention device is thus ideal for rapid perfusion process development in a biomanufacturing workflow.
Laengle, S, Loyola, G & Merigo, JM 2017, 'Mean-Variance Portfolio Selection With the Ordered Weighted Average', IEEE Transactions on Fuzzy Systems, vol. 25, no. 2, pp. 350-362.
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© 1993-2012 IEEE. Portfolio selection is the theory that studies the process of selecting the optimal proportion of different assets. The first approach was introduced by Harry Markowitz and was based on a mean-variance framework. This paper introduces the ordered weighted average (OWA) in the mean-variance model. The main idea is to replace the classical mean and variance by the OWA operator. By doing so, the new model is able to study different degrees of optimism and pessimism in the analysis being able to develop an approach that considers the decision makers attitude in the selection process. This paper also suggests a new framework for dealing with the attitudinal character of the decision maker based on the numerical values of the available arguments. The main advantage of this method is the ability to adapt to many situations offering a more complete representation of the available data from the most pessimistic situation to the most optimistic one. An illustrative with fictitious data and a real example are studied.
Laengle, S, Merigó, JM, Miranda, J, Słowiński, R, Bomze, I, Borgonovo, E, Dyson, RG, Oliveira, JF & Teunter, R 2017, 'Forty years of the European Journal of Operational Research: A bibliometric overview', European Journal of Operational Research, vol. 262, no. 3, pp. 803-816.
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© 2017 Elsevier B.V. The European Journal of Operational Research (EJOR) published its first issue in 1977. This paper presents a general overview of the journal over its lifetime by using bibliometric indicators. We discuss its performance compared to other journals in the field and identify key contributing countries/institutions/authors as well as trends in research topics based on the Web of Science Core Collection database. The results indicate that EJOR is one of the leading journals in the area of operational research (OR) and management science (MS), with a wide range of authors from institutions and countries from all over the world publishing in it. Graphical visualization of similarities (VOS) provides further insights into how EJOR links to other journals and how it links researchers across the globe.
Lai, L, Qin, L, Lin, X & Chang, L 2017, 'Scalable subgraph enumeration in MapReduce: a cost-oriented approach.', VLDB J., vol. 26, no. 3, pp. 421-446.
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© 2017, Springer-Verlag Berlin Heidelberg. Subgraph enumeration, which aims to find all the subgraphs of a large data graph that are isomorphic to a given pattern graph, is a fundamental graph problem with a wide range of applications. However, existing sequential algorithms for subgraph enumeration fall short in handling large graphs due to the involvement of computationally intensive subgraph isomorphism operations. Thus, some recent researches focus on solving the problem using MapReduce. Nevertheless, exiting MapReduce approaches are not scalable to handle very large graphs since they either produce a huge number of partial results or consume a large amount of memory. Motivated by this, in this paper, we propose a new algorithm TwinTwigJoin based on a left-deep-join framework in MapReduce, in which the basic join unit is a TwinTwig (an edge or two incident edges of a node). We show that in the Erdös–Rényi random graph model, TwinTwigJoin is instance optimal in the left-deep-join framework under reasonable assumptions, and we devise an algorithm to compute the optimal join plan. We further discuss how our approach can be adapted to handle the power-law random graph model. Three optimization strategies are explored to improve our algorithm. Ultimately, by aggregating equivalent nodes into a compressed node, we construct the compressed graph, upon which the subgraph enumeration is further improved. We conduct extensive performance studies in several real graphs, one of which contains billions of edges. Our approach significantly outperforms existing solutions in all tests.
Lai, P-W, Ko, L-W, Wang, Y & Lin, C-T 2017, 'EEG-based assessment of pilot spatial navigation on an aviation simulator', Journal of Science and Medicine in Sport, vol. 20, pp. S37-S38.
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Lal, S, Hall, RM & Tipper, JL 2017, 'Concentration and size distribution data of silicon nitride nanoparticles measured using nanoparticle tracking analysis', Data in Brief, vol. 15, pp. 821-823.
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© 2017 This article refers to the paper “A novel method for isolation and recovery of ceramic nanoparticles and metal wear debris from serum lubricants at ultra-low wear rates” (Lal et al., 2016) [1] and describes the concentration and size distribution data of silicon nitride nanoparticles measured using nanoparticle tracking analysis (NTA). A NanoSight LM10 instrument was used to capture the video data of silicon nitride nanoparticles moving under Brownian motion in the water. The video data was then analyzed using the NanoSight NTA software. This article also describes a methodology for calculating the percentage recovery of a nanoparticle isolation process.
Lalbakhsh, A, Afzal, MU & Esselle, KP 2017, 'Multiobjective Particle Swarm Optimization to Design a Time-Delay Equalizer Metasurface for an Electromagnetic Band-Gap Resonator Antenna', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 912-915.
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This letter presents an efficient particle swarm optimization (PSO) algorithm developed to design a near-field time-delay equalizer metasurface (TDEM) for the purpose of improving directivity and radiation patterns of classical electromagnetic band-gap resonator antennas. Triple layers of conductive printed patterns in the metasurface were optimized by the PSO algorithm to systematically design the TDEM. Predicted and measured results show a significant improvement in antenna performance including 9.6 dB enhancement in antenna directivity, lower sidelobes, and higher gain. The measured directivity of the prototype is 21 dBi, and 3-dB bandwidth is 11.8%.
Lam, MK, Yusoff, MI, Uemura, Y, Lim, JW, Khoo, CG, Lee, KT & Ong, HC 2017, 'Cultivation of Chlorella vulgaris using nutrients source from domestic wastewater for biodiesel production: Growth condition and kinetic studies', Renewable Energy, vol. 103, pp. 197-207.
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Lang, L, Pocquet, M, Ni, B-J, Yuan, Z & Spérandio, M 2017, 'Comparison of different two-pathway models for describing the combined effect of DO and nitrite on the nitrous oxide production by ammonia-oxidizing bacteria', Water Science and Technology, vol. 75, no. 3, pp. 491-500.
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The aim of this work is to compare the capability of two recently proposed two-pathway models for predicting nitrous oxide (N2O) production by ammonia-oxidizing bacteria (AOB) for varying ranges of dissolved oxygen (DO) and nitrite. The first model includes the electron carriers whereas the second model is based on direct coupling of electron donors and acceptors. Simulations are confronted to extensive sets of experiments (43 batches) from different studies with three different microbial systems. Despite their different mathematical structures, both models could well and similarly describe the combined effect of DO and nitrite on N2O production rate and emission factor. The model-predicted contributions for nitrifier denitrification pathway and hydroxylamine pathway also matched well with the available isotopic measurements. Based on sensitivity analysis, calibration procedures are described and discussed for facilitating the future use of those models.
Law, AMK, Lim, E, Ormandy, CJ & Gallego-Ortega, D 2017, 'The innate and adaptive infiltrating immune systems as targets for breast cancer immunotherapy', Endocrine-Related Cancer, vol. 24, no. 7, pp. X1-X1.
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Law, AMK, Lim, E, Ormandy, CJ & Gallego-Ortega, D 2017, 'The innate and adaptive infiltrating immune systems as targets for breast cancer immunotherapy', Endocrine-Related Cancer, vol. 24, no. 4, pp. R123-R144.
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A cancer cell-centric view has long dominated the field of cancer biology. Research efforts have focussed on aberrant cancer cell signalling pathways and on changes to cancer cell DNA. Mounting evidence demonstrates that many cancer-associated cell types within the tumour stroma co-evolve and support tumour growth and development, greatly modifying cancer cell behaviour, facilitating invasion and metastasis and controlling dormancy and sensitivity to drug therapy. Thus, these stromal cells represent potential targets for cancer therapy. Among these cell types, immune cells have emerged as a promising target for therapy. The adaptive and the innate immune system play an important role in normal mammary development and breast cancer. The number of infiltrating adaptive immune system cells with tumour-rejecting capacity, primarily, T lymphocytes, is lower in breast cancer compared with other cancer types, but infiltration occurs in a large proportion of cases. There is strong evidence demonstrating the importance of the immunosuppressive role of the innate immune system during breast cancer progression. A consideration of components of both the innate and the adaptive immune system is essential for the design and development of immunotherapies in breast cancer. In this review, we focus on the importance of immunosuppressive myeloid-derived suppressor cells (MDSCs) as potential targets for breast cancer therapy.
Law, AMK, Yin, JXM, Castillo, L, Young, AIJ, Piggin, C, Rogers, S, Caldon, CE, Burgess, A, Millar, EKA, O’Toole, SA, Gallego-Ortega, D, Ormandy, CJ & Oakes, SR 2017, 'Andy’s Algorithms: new automated digital image analysis pipelines for FIJI', Scientific Reports, vol. 7, no. 1.
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AbstractQuantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy’s Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3′-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy’s Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy’s algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy’s Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm.
Le, M, Gabrys, B & Nauck, D 2017, 'A hybrid model for business process event and outcome prediction', Expert Systems, vol. 34, no. 5, pp. 1-11.
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AbstractLarge service companies run complex customer service processes to provide communication services to their customers. The flawless execution of these processes is essential because customer service is an important differentiator. They must also be able to predict if processes will complete successfully or run into exceptions in order to intervene at the right time, preempt problems and maintain customer service. Business process data are sequential in nature and can be very diverse. Thus, there is a need for an efficient sequential forecasting methodology that can cope with this diversity. This paper proposes two approaches, a sequential k nearest neighbour and an extension of Markov models both with an added component based on sequence alignment. The proposed approaches exploit temporal categorical features of the data to predict the process next steps using higher order Markov models and the process outcomes using sequence alignment technique. The diversity aspect of the data is also added by considering subsets of similar process sequences based on k nearest neighbours. We have shown, via a set of experiments, that our sequential k nearest neighbour offers better results when compared with the original ones; our extension Markov model outperforms random guess, Markov models and hidden Markov models.
Le, NT & Hoang, DB 2017, 'Capability Maturity Model and Metrics Framework for Cyber Cloud Security', Scalable Computing: Practice and Experience, vol. 18, no. 4, pp. 277-290.
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Le, TM, Fatahi, B, Khabbaz, H & Sun, W 2017, 'Numerical optimization applying trust-region reflective least squares algorithm with constraints to optimize the non-linear creep parameters of soft soil', Applied Mathematical Modelling, vol. 41, pp. 236-256.
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© 2016 Determination of the creep model parameters is a challenging task particularly when a non-linear elastic visco-plastic (EVP) model is adopted, mainly due to the limited test duration as well as the assumption of the reference time. Therefore, this paper presents an innovative numerical solution to find the EVP model parameters applying the trust-region reflective least square optimization algorithm. The developed approach involves several available laboratory consolidation test results in the optimization procedure with the adopted commencing time to creep as a unit of time. In this paper, the laboratory results of Ottawa clay were employed to demonstrate the limitation of the recent method to obtain model parameters. Furthermore, the developed method is verified against Skå-Edeby clay in the laboratory conditions. The EVP model parameters are obtained by applying the developed method to the available laboratory consolidation results of clay samples. The analysis results of vertical strains and excess pore water pressures demonstrate that the developed method can be a feasible tool to estimate the settlement properties of clays.
Lee, A, Rayner, SL, De Luca, A, Gwee, SSL, Morsch, M, Sundaramoorthy, V, Shahheydari, H, Ragagnin, A, Shi, B, Yang, S, Williams, KL, Don, EK, Walker, AK, Zhang, KY, Yerbury, JJ, Cole, NJ, Atkin, JD, Blair, IP, Molloy, MP & Chung, RS 2017, 'Casein kinase II phosphorylation of cyclin F at serine 621 regulates the Lys48-ubiquitylation E3 ligase activity of the SCF (cyclin F) complex', Open Biology, vol. 7, no. 10, pp. 170058-170058.
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Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder that is characterized by progressive weakness, paralysis and muscle loss often resulting in patient death within 3–5 years of diagnosis. Recently, we identified disease-linked mutations in the CCNF gene, which encodes the cyclin F protein, in cohorts of patients with familial and sporadic ALS and frontotemporal dementia (FTD) (Williams KL et al . 2016 Nat. Commun. 7 , 11253. ( doi:10.1038/ncomms11253 )). Cyclin F is a part of a Skp1-Cul-F-box (SCF) E3 ubiquitin-protein ligase complex and is responsible for ubiquitylating proteins for degradation by the proteasome. In this study, we investigated the phosphorylation status of cyclin F and the effect of the serine to glycine substitution at site 621 (S621G) on E3 ligase activity. This specific mutation (S621G) was found in a multi-generational Australian family with ALS/FTD. We identified seven phosphorylation sites on cyclin F, of which five are newly reported including Ser621. These phosphorylation sites were mostly identified within the PEST (proline, glutamic acid, serine and threonine) sequence located at the C-terminus of cyclin F. Additionally, we determined that casein kinase II (CK2) can phosphorylate Ser621 and thereby regulate the E3 ligase activity of the SCF (cyclin F) complex. Furthermore, the S621G mutation in cyclin F prevents phosphorylation by CK2 and confers elevated Lys48-ubiquitylation activity, a hallmark of ALS/FTD pathology. These findings highlight the importance of phosphorylation in regulatin...
Lee, D, van Dorp Schuitman, J, Cabrera, D, Qiu, X & Burnett, I 2017, 'Comparison of psychoacoustic-based reverberance parameters', The Journal of the Acoustical Society of America, vol. 142, no. 4, pp. 1832-1840.
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This study compared psychoacoustic reverberance parameters to each other, as well as to reverberation time (RT) and early decay time (EDT) under various acoustic conditions. The psychoacoustic parameters were loudness-based RT (TN), loudness-based EDT [EDTN; Lee, Cabrera, and Martens, J. Acoust. Soc. Am. 131, 1194–1205 (2012a)], and parameter for reverberance [PREV; van Dorp Schuitman, de Vries, and Lindau., J. Acoust. Soc. Am. 133, 1572–1585 (2013)]. For the comparisons, a wide range of sound pressure levels (SPLs) from 20 dB to 100 dB and RTs from 0.5 s to 5.0 s were evaluated, and two sets of subjective data from the previous studies were used for the cross-validation and comparison. Results of the comparisons show that the psychoacoustic reverberance parameters provided better matches to reverberance than RT and EDT; however, the performance of these psychoacoustic reverberance parameters varied with the SPL range, the type of audio sample, and the reverberation conditions. This study reveals that PREV is the most relevant for estimating a relative change in reverberance between samples when the SPL range is small, while EDTN is useful in estimating the absolute reverberance. This study also suggests the use of PREV and EDTN for speech and music samples, respectively.
Lee, E-J, An, AK, Hadi, P, Lee, S, Woo, YC & Shon, HK 2017, 'Advanced multi-nozzle electrospun functionalized titanium dioxide/polyvinylidene fluoride-co-hexafluoropropylene (TiO2/PVDF-HFP) composite membranes for direct contact membrane distillation', Journal of Membrane Science, vol. 524, pp. 712-720.
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The unique capabilities of electrospinning technology are being increasingly utilized in the fabrication of hydrophobic membranes to improve the membrane distillation (MD) process in recent years. In this study, hydrophobic titanium dioxide (TiO2) nanoparticles functionalized by fluorosilane were incorporated into electrospun membranes using single, coaxial, and dual nozzles to develop novel membrane architectures for improved physico-chemical properties for MD. By incorporating fluorosilane coated TiO2 into the PVDF-HFP solution during the membrane synthesis and using an advanced multi-nozzle to form various hierarchical membrane structures tuned the size and structure of the nanofibers and made them vastly superior for the application in MD. The single and coaxial nozzle membranes showed contact angles close to 150° and the dual-nozzle membrane assembled bead-on-string fibers achieved superhydrophobicity (i.e., contact angle of 153.4°). To test the functionalized titanium dioxide/polyvinylidene fluoride-co-hexafluoropropylene (TiO2/PVDF-HFP) composite membranes for MD performance, the membranes were subjected to long-term direct contact MD for about two days to monitor their water vapor flux and selectivity. Compared to commercial PVDF membranes, all electrospun F-TiO2/ PVDF-HFP membrane achieved higher water vapor flux of 40 L m−2 h−1 (60 °C feed and 20 °C permeate) with a brine (7.0 wt% NaCl) as the feed solution and also exhibited anti-wetting property while maintaining high water flux compared to the membrane without TiO2 incorporation.
Lee, E-J, Deka, BJ, Guo, J, Woo, YC, Shon, HK & An, AK 2017, 'Engineering the Re-Entrant Hierarchy and Surface Energy of PDMS-PVDF Membrane for Membrane Distillation Using a Facile and Benign Microsphere Coating', Environmental Science & Technology, vol. 51, no. 17, pp. 10117-10126.
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© 2017 American Chemical Society. To consolidate the position of membrane distillation (MD) as an emerging membrane technology that meets global water challenges, it is crucial to develop membranes with ideal material properties. This study reports a facile approach for a polyvinylidene fluoride (PVDF) membrane surface modification that is achieved through the coating of the surface with poly(dimethylsiloxane) (PDMS) polymeric microspheres to lower the membrane surface energy. The hierarchical surface of the microspheres was built without any assistance of a nano/microcomposite by combining the rapid evaporation of tetrahydrofuran (THF) and the phase separation from condensed water vapor. The fabricated membrane exhibited superhydrophobicity - a high contact angle of 156.9° and a low contact-angle hysteresis of 11.3° - and a high wetting resistance to seawater containing sodium dodecyl sulfate (SDS). Compared with the control PVDF-hexafluoropropylene (HFP) single-layer nanofiber membrane, the proposed fabricated membrane with the polymeric microsphere layer showed a smaller pore size and higher liquid entry pressure (LEP). When it was tested for the direct-contact MD (DCMD) in terms of the desalination of seawater (3.5% of NaCl) containing SDS of a progressively increased concentration, the fabricated membrane showed stable desalination and partial wetting for the 0.1 and 0.2 mM SDS, respectively.
Lee, J, Vigneswaran, S, Zhang, Y, Raj Reddy, RSP & Liu, Z 2017, 'Effective natural organic matter removal in pond water by carbon nanotube membrane with flocculation/adsorption', Water Supply, vol. 17, no. 4, pp. 1080-1087.
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A carbon nanotube (CNT) ultrafiltration (UF) membrane was applied to natural organic matter (NOM) removal in pond water treatment. The source water was pretreated by flocculation and/or adsorption prior to the UF process to alleviate permeate flux decline and improve NOM removal efficiency. The performance of a commercial polyethersulfone (PES) UF membrane was compared to evaluate that of the CNT membrane. The CNT membrane outperformed the PES-UF membrane. The permeate flux, total organic carbon and humic acid (HA) removal rate of the CNT membrane was observed to be 230 LMH/bar, 60%, and 80% when 30 mg/L poly aluminium chloride (PACI) flocculation was applied. This highlights that the permeate flux was three times higher with slightly higher rejection efficiency than the PES-UF membrane. In particular, severe permeate flux decline was completely overcome by the CNT membrane with 30 mg/L PACI coagulation. For powder activated carbon (PAC) adsorption, even though there was a severe permeate flux decline in the CNT membrane, almost complete HA removal (98%) was achieved when 0.5 g/L PAC adsorption was coupled. Based on the superior performance of the CNT membrane with pretreatment, the CNT membrane is suggested to be a robust system for a high concentration of organic matter pond water treatment without membrane flux decline.
Lee, T, Wei, Z & de Wolf, R 2017, 'Some upper and lower bounds on PSD-rank', Mathematical Programming, vol. 162, no. 1-2, pp. 495-521.
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Leijia, W 2017, 'A Contribution to the Study on Sanguo Yanyi', Monumenta Serica, vol. 65, no. 1, pp. 43-60.
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This is a study of the Sanguo yanyi (hereafter Yanyi), one of the four great literary
classics of China, in terms of its political standpoint, character evaluation, and character
development. It questions the traditional views related to Yanyi’s stance of
revering Liu Bei 劉備and belittling Cao Cao 曹操. The argument here is that the
novel’s political standpoint is mainly based on zhongyi 忠義(loyalty and righteousness),
rather than lineage, benevolence, and other factors. Although Yanyi has a
clear political position, it is relatively objective and neutral in evaluating historical
figures from different camps. The character development of Yanyi is very successful.
The character images are round and rich, rather than flat and stereotypical. Both
positive and negative characters have their merits and weaknesses.
Lekitsch, B, Weidt, S, Fowler, AG, Mølmer, K, Devitt, SJ, Wunderlich, C & Hensinger, WK 2017, 'Blueprint for a microwave trapped ion quantum computer', Science Advances, vol. 3, no. 2, pp. 1-11.
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Design to build a trapped ion quantum computer with modules connected by ion transport and voltage-driven quantum gate technology.
Lemmerz, K, Glogowski, P, Arenbeck, H, Barthelmey, A, Strothotte, L, Hypki, A, Kuhlenkötter, B & Deuse, J 2017, 'Collaborative assembly system', Productivity Management, vol. 22, no. 4, pp. 13-15.
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The design of assembly systems with human-robot collaboration (HRC) is a complex task due to the variety of goal criteria that have to be considered. A digital tool for designing and securing HRC-applications as well as adequate training and qualification concepts for companies are yet missing and are still major obstacles to the use of HRC. This paper proposes a new methodology for the task-based digital design of collaborative assembly systems. In the future, this will ensure that companies are getting empowered for a straightforward development and commissioning of HRC-systems.
Leong, KY, Ku Ahmad, KZ, Ong, HC, Ghazali, MJ & Baharum, A 2017, 'Synthesis and thermal conductivity characteristic of hybrid nanofluids – A review', Renewable and Sustainable Energy Reviews, vol. 75, pp. 868-878.
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Leong, KY, Najwa, ZA, Ku Ahmad, KZ & Ong, HC 2017, 'Investigation on Stability and Optical Properties of Titanium Dioxide and Aluminum Oxide Water-Based Nanofluids', International Journal of Thermophysics, vol. 38, no. 5.
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Leurent, M, Jasserand, F, Locatelli, G, Palm, J, Rämä, M & Trianni, A 2017, 'Driving forces and obstacles to nuclear cogeneration in Europe: Lessons learnt from Finland', Energy Policy, vol. 107, pp. 138-150.
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© 2017 Elsevier Ltd Nuclear power plants generate electricity and a large amount of waste heat which is valuable for cogeneration. District heating (DH) is a suitable technology to decarbonize the European heat sector. By contrast with most of nuclear non-electric applications, nuclear district heating (NDH) has already been implemented in Europe, thus providing us with some valuable empirical insights. This paper investigates the forces and obstacles to nuclear cogeneration by looking at the Loviisa 3 NDH project in Finland. The key forces are energy efficiency, decarbonization of the heat sector, operational competitiveness of future nuclear technologies, and synergies with renewable energies. The key obstacles are split incentives, electricity prices volatility, inexpediency of business models and regulatory frameworks, electioneering of local authorities and pessimist expectations with regards to project financing. Policy makers should recognize nuclear plants alongside other utilities generating large amounts of wasted heat. International cooperation programs involving both nuclear and heat stakeholders should be encouraged. EU28 Member States wanting to promote nuclear cogeneration may consider providing support for the electricity generated by high-efficiency plants.
Leveaux, R 2017, 'An Elite Sporting Organization’s Perceptions to the Uptake of Information Technology', IBIMA Business Review, vol. 2017, pp. 1-14.
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In recent years, technology has enabled sporting organizations to become innovators in the global sports arena. Elite sporting teams and bodies are becoming increasingly dependent on technology for daily operations and subsequently these organizations are more and more reliant on technological developments in sport. Player training and management
technologies and team performance tools have given sporting organizations the avenues to become more competitive. Organizations invest in information technology for many reasons, for example cutting costs, increase in production and services without increasing costs, improving the quality of services or products and sporting organizations and bodies are no different in looking to technology to gain competitive edges as well as improvement of athlete preparation. However, in spite of these innovations and the potential to gain competitive edges, some seem to struggle with technology resulting in ambiguous and
sometimes negative perceptions of IT services. Through a qualitative case study and using interviews with a short survey, the building of credibility in sporting organizations through education and the development of positive perceptions of information technology was
examined. The findings provide a basis for further studies and possible trials of differing education formats in technology to further develop both the positive acceptance of sports related technologies and assist in improving the sporting organization’s environment.
Leveaux, R 2017, 'An Examination of Information Technologies Changing the Shape of Sport', Communications of the IBIMA, vol. 2016, pp. 1-9.
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Today’s sport is changing due to various factors external to the sport which impact on the shape of a sport. The focus of this study was to examine changes due to the uses of information technologies. A series of interviews (n=36) was conducted across three areas: (1) Professional players and coaches of professional players (2) amateur players and coaches at amateur levels and (3) spectators to gain an understanding of the applications of information technologies in sport. The findings indicated that players at the professional level are using various technologies such as GPS vests to manage workload and reduce risk of injury. With amateur level sport, technologies are not as prevalent and the possible introduction of technology was surprisingly not considered as imperative. Spectators, in general, considered that the introduction of technologies changed the dimensions of their involvement both positively and negatively. The findings provide a basis for further studies and possible trials with additional technologies to further assist the athlete and coaches and innovatively further enhance the spectator’s experience.
Leyendekkers, JV, Shannon, AG & Hillman, RA 2017, 'The Brocard-Ramanujan diophantine equation', Advanced Studies in Contemporary Mathematics (Kyungshang), vol. 27, no. 4, pp. 571-575.
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Using integer structure analysis in the modular ring Z4 it is shown that the only integer solutions of the Brocard-Ramanujan equation, n! + l = m2, occur for (n, ra) ϵ {(4, 5), (5, 11), (7, 71)}. When 3 | m the rows in the ring can never be equal, but when 3 ł m the rows of n! always satisfy an exponential function while the rows of m2 satisfy two quadratic forms. The intersections of the exponential with the quadratic occur only for (n, m) above.
Li, B, Chen, S, Sutton, GJ, Shi, Y & Liu, RP 2017, 'MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture', IEEE Access, vol. 5, pp. 10649-10661.
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© 2013 IEEE. In practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a vehicular network performance-prediction model for a Rayleigh capture channel in Drive-thru Internet scenario. The model incorporates the capture effect into a 2-D Markov chain modeling the high-node mobility and distributed coordination function broadcast scheme. The performance-prediction model unveils the impacts of mobility velocity and number of vehicles on the throughput in a Rayleigh capture channel. We use a vehicular traffic flow model to predict vehicular movement on road by aggregating all vehicles into a flow. Simulation results confirm that our performance-prediction model accurately predicts the performance of traveling vehicles with Rayleigh capture channel in the Drive-thru Internet scenario. We demonstrate that using our performance-prediction model, we can obtain optimal contention window value, by which the best system throughput can be reached without wasting contention time. This is also proved by Anastasi et al.
Li, B, Sutton, GJ, Hu, B, Liu, RP & Chen, S 2017, 'Modeling and QoS analysis of the IEEE 802.11p broadcast scheme in vehicular ad hoc networks', Journal of Communications and Networks, vol. 19, no. 2, pp. 169-179.
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© 2011 KICS. Quality of service (QoS) and queue management are critical issues for the broadcast scheme of IEEE 802.11p systems in vehicular ad hoc networks (VANETs). However, existing 1-dimensional (1-D) Markov chain models of 802.11p systems are unable to capture the complete QoS performance and queuing behavior due to the lack of an adequate finite buffer model. We present a 2-dimensional (2-D) Markov chain that integrates the broadcast scheme of the 802.11p system and the queuing process into one model. The extra dimension, which models the queue length, allows us to accurately capture the important QoS measures, delay and loss, plus throughput and queue length, for realistic 802.11p systems with finite buffer under finite load. We derive a simplified method to solve the steady state probabilities of the 2-D Markov chain. Our 2-D Markov chain model is the first finite buffer model defined and solved for the broadcast scheme of 802.11p systems. The 2-D model solutions are validated by extensive simulations. Our analyses reveal that the lack of binary exponential backoff and retransmission in the 802.11p system results in poor QoS performance during heavy traffic load, particularly for large VANETs. We demonstrate that our model provides traffic control guidelines to maintain good QoS performance for VANETs.
Li, B, Zhao, J, Liu, X, Guo, Y, Hu, H & Li, J 2017, 'Detent Force Reduction of an Arc-Linear Permanent-Magnet Synchronous Motor by Using Compensation Windings', IEEE Transactions on Industrial Electronics, vol. 64, no. 4, pp. 3001-3011.
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© 2016 IEEE. An arc-linear permanent-magnet synchronous machine (AL-PMSM) is a kind of servo machine used for a scanning system to meet the requirements of high positioning accuracy, high response performance, and wide scanning range. To reduce the detent force and increase the travel range of the AL-PMSM, a novel hybrid excited AL-PMSM with a normal armature winding and compensation windings is proposed and investigated. The compensation windings are installed on the end teeth of the primary side. The influence of a compensation direct current is analyzed by a finite element method (FEM). Based on the result of the analysis, a proper compensation current is proposed to reduce the detent force. The result after the compensation is simulated by the FEM. In addition, a combination of primary length optimization and current compensation is proposed, the proper formula for the compensation current is deduced, and the result calculated by the FEM is provided. To reduce the detent force of the travel end, a proper current is supplied into the compensation winding, the detent force during the both end of the travel range is much reduced, so the smooth travel range is increased. Finally, prototypes of AL-PMSM are manufactured and experiments are conducted to validate the proposed compensation method.
Li, H & Huang, X 2017, 'Multicast Systems With Fair Scheduling in Non-identically Distributed Fading Channels', IEEE Transactions on Vehicular Technology, vol. 66, no. 10, pp. 8835-8844.
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© 1967-2012 IEEE. Multicasting is emerging as an efficient method to deliver the same data to a group of users, thereby saving network resources. The fairness between different multicast groups is an important quality-of-service (QoS) indication, but it has not been given significant attention. In this paper, we propose a normalized signal-To-noise ratio (SNR)-based fair scheduling for multiple multicast groups in multicast systems. The system fairness and capacity are then analyzed and compared for both fair scheduling and greedy scheduling over independent but non-identically distributed (i.n.d.) fading channels. Closed-form expressions in terms of the system spectral efficiency, outage probability, system fairness, and average bit error rate (BER) are derived in an uncoded/coded M-Ary quadrature amplitude modulation based adaptive transmission multicast system over i.n.d. Rayleigh fading channels. Numerical results show that compared with greedy scheduling, fair scheduling achieves considerably high fairness at the cost of slight system capacity loss, regardless of the number of multicast groups. Our focus is on the physical layer without rate loss, but we also briefly discuss applications of the proposed scheduling in a cross-layer design subject to the loss rate QoS constraint.
Li, H, Zhou, B, Tian, Z, Guo, J, Ngo, HH, Lu, C, Han, Y & Song, Y 2017, 'Improving anoxic/aerobic nutrients removal by the enhanced biological phosphorus removal-sulfur autotrophic denitrification (EBPR-SAD) system when treating low C/N ratio municipal wastewater', Desalination and Water Treatment, vol. 95, pp. 247-261.
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© 2017 Desalination Publications. All rights reserved. A novel nutrients removal system integrating enhanced biological phosphorus removal (EBPR) and sulfur autotrophic denitrification (SAD) was developed to upgrade the Shenyang Degremont Anoxic Oxic process (SDAO). In this system, the EBPR process was mainly employed to utilize organic carbon for denitrification and phosphorus removal; the SAD process was used to remove nitrate, which was not removed in the EBPR process because of a low C/N ratio. The results showed that the EBPR-SAD effluent COD, TN, NH4+–N and TP were 24.6, 1.21, 1.09 and 0.24 mg/L, respectively. Compared with those of the original system, the removal efficiencies of TN and TP increased to 95.8% and 86.9%. It was demonstrated that the EBPR-SAD system could achieve nearly complete nutrients removal from low C/N ratio municipal wastewater. Cluster analysis and principal coordinate analysis showed that bacterial community structures were significantly different between SDAO, EBPR and SAD processes, indicating that bacterial community structures were affected by the type of wastewater biotreatment system. Taxonomic analysis showed that the nine most abundant phyla in the SDAO and EBPR-SAD system accounted for 87.0%–90.7% of the total effective sequences. Redundancy analysis was used to reveal the relationship between the abundance of bacterial phyla and environmental parameters in the SDAO and EBPR-SAD system.
Li, J, Deng, C, Da Xu, RY, Tao, D & Zhao, B 2017, 'Robust Object Tracking With Discrete Graph-Based Multiple Experts', IEEE Transactions on Image Processing, vol. 26, no. 6, pp. 2736-2750.
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© 1992-2012 IEEE. Variations of target appearances due to illumination changes, heavy occlusions, and target deformations are the major factors for tracking drift. In this paper, we show that the tracking drift can be effectively corrected by exploiting the relationship between the current tracker and its historical tracker snapshots. Here, a multi-expert framework is established by the current tracker and its historical trained tracker snapshots. The proposed scheme is formulated into a unified discrete graph optimization framework, whose nodes are modeled by the hypotheses of the multiple experts. Furthermore, an exact solution of the discrete graph exists giving the object state estimation at each time step. With the unary and binary compatibility graph scores defined properly, the proposed framework corrects the tracker drift via selecting the best expert hypothesis, which implicitly analyzes the recent performance of the multi-expert by only evaluating graph scores at the current frame. Three base trackers are integrated into the proposed framework to validate its effectiveness. We first integrate the online SVM on a budget algorithm into the framework with significant improvement. Then, the regression correlation filters with hand-crafted features and deep convolutional neural network features are introduced, respectively, to further boost the tracking performance. The proposed three trackers are extensively evaluated on three data sets: TB-50, TB-100, and VOT2015. The experimental results demonstrate the excellent performance of the proposed approaches against the state-of-the-art methods.
Li, J, Hao, H & Wu, C 2017, 'Numerical study of precast segmental column under blast loads', Engineering Structures, vol. 134, pp. 125-137.
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© 2016 Elsevier Ltd Constructions with precast technology have seen a fast development over the past several decades. Despite advantages including short construction period, better quality control, less environmental and traffic impact, a lack of study on their behaviour under dynamic loads have prevented the widespread use of precast constructions in high seismic zones and where terrorist attack could be a concern. Among all precast structural components, precast segmental columns have been found one of the construction techniques with great potentials. Intensive research efforts have been spent on investigating the segmental columns under seismic loadings in recent years. During its service life, besides seismic action, structure may subject to other dynamic loads like impact and blast. It is therefore important to perform multi-hazard analyse to better understand structural performance. This study investigates the blast loading resistance capacities of segmental reinforced concrete (RC) columns. RC segmental columns with or without shear keys and energy dissipation bars are considered. Influence of the number of segments and different levels of post tensioning forces on column dynamic performance is also investigated. Commercial code LS-DYNA is used to perform numerical simulations of the segmental columns under different blast loadings. Accuracy of the numerical model is verified against available testing data on RC columns. Numerical results of the segmental columns under different blast loadings are calculated and compared with those of the monolithic RC columns. Discussions on the capabilities of segmental RC columns in resisting blasting loads are made with respect to those of the monolithic RC columns.
Li, J, Jiang, B, Liu, Y, Qiu, C, Hu, J, Qian, G, Guo, W & Ngo, HH 2017, 'Preparation and adsorption properties of magnetic chitosan composite adsorbent for Cu 2+ removal', Journal of Cleaner Production, vol. 158, pp. 51-58.
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Li, J, Masia, MJ & Stewart, MG 2017, 'Stochastic spatial modelling of material properties and structural strength of unreinforced masonry in two-way bending', Structure and Infrastructure Engineering, vol. 13, no. 6, pp. 683-695.
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The paper describes the development of a computational method to predict the strength for unreinforced masonry walls subject to two-way out-of-plane bending considering unit-to-unit spatial variability of the material properties of mortar joints and bricks. The study involves conducting a numerical simulation of full-sized walls subject to two-way bending using stochastic analysis in the form of Monte Carlo simulations and comparing the results with experimental work. A 3-D non-linear Finite Element Analysis is used to study how the spatial variability of material properties affect non-load bearing wall failure progression. The numerical results are compared to the experimental results in terms of the wall failure progression and wall capacity. It is shown that the model which considers the spatial variability of brickwork can best capture the failure patterns and predict the cracking and ultimate loads for walls subjected to two-way bending.
Li, J, Mei, X, Prokhorov, D & Tao, D 2017, 'Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene', IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 3, pp. 690-703.
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© 2016 IEEE. Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.
Li, J, Wu, C, Hao, H & Liu, Z 2017, 'Post-blast capacity of ultra-high performance concrete columns', Engineering Structures, vol. 134, pp. 289-302.
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© 2016 Elsevier Ltd Over the past several decades, iconic and public buildings have become targets of terrorist bomb attacks, but most of these buildings were built without consideration of blast loading scenarios. Key load-carrying elements such as concrete columns are probably the most critical structural components for structural protection against bomb threats. Failures of columns may trigger catastrophic progressive collapse if there is insufficient structural redundancy. In a recent study, novel ultra-high performance concrete (UHPC) material formulated based on reactive powder concrete (RPC) was developed. Field blast tests on columns made of this material were performed. Test results showed that UHPC columns had excellent blast resistant capability, only small mid-height deflection and minor concrete damage was observed after the blasting tests. In the present study, to quantify blast-induced damage and assess residual loading capacity of UHPC columns, static axial loading tests on post-blast UHPC columns were carried out. Undamaged control samples were tested to provide benchmarks. Damage index and residual loading capacity of UHPC columns after various blast loadings were obtained. It was found that column cast with micro steel fibre reinforced UHPC preserved more than 70% of its loading capacity after 35 kg TNT detonation at 1.5 m standoff distance, while high strength concrete column only maintained 40% loading capacity after 8 kg TNT detonation at 1.5 m standoff distance.
Li, J, Wu, C, Hao, H & Su, Y 2017, 'Experimental and numerical study on steel wire mesh reinforced concrete slab under contact explosion', Materials & Design, vol. 116, pp. 77-91.
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© 2016 Elsevier Ltd With the rising of terrorism and rapid urbanization around the world, increasingly more structures are exposed to the threats from accidental and hostile explosion loads. To provide adequate structural protection against blast load, novel materials and strengthening techniques are under fast development. In the present study, a composite slab design aiming at high level blast resistance is studied. In the matrix of high strength self-compacting concrete, besides conventional rebars serving as primary reinforcement, steel wire meshes are embedded and served as secondary reinforcements. Moreover, on the concrete cover layer where the tensile cracks locate, steel fibres are added to provide micro crack-bridging effect. Preliminary numerical simulations adopting coupled Finite Element (FE) and Smoothed Particle Hydrodynamics (SPH) are carried out in hydro-code and the results are used as guide for field blast test. Composite slab with optimal design is field tested under 1 kg TNT contact detonation, and the results are compared with slabs made of conventional and ultra-high performance concrete without steel wire meshes. The results demonstrate that slab with steel wire mesh reinforcement develops localized membrane effect when subjected to blast loads and shows better blast resistant capability as compared to the slabs without steel wire meshes.
Li, J, Wu, C, Hao, H, Su, Y & Li, Z-X 2017, 'A study of concrete slabs with steel wire mesh reinforcement under close-in explosive loads', International Journal of Impact Engineering, vol. 110, pp. 242-254.
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© 2017 Elsevier Ltd Structural responses and damages under blast loading environments are critical to structural and personnel safety. The blast scenarios involving close-in detonations are attracting increasingly more attentions over the last few decades due to the rising of terrorism. Under close-in detonations, structural elements tend to fail in a brittle mode including shear, concrete crater and spall. In such loading scenarios, the structural designated loading capacity which is usually based on flexural deformation assumption is not fully developed. To provide high-level structural protection, high performance concretes with varying fibre additions are now widely investigated and used in blast resistance designs. In the present study, field blast tests results on reinforced concrete slabs under close-in detonations are presented. Performances of slabs made of normal strength concrete and steel fibre reinforced concrete are compared and discussed. Besides conventional steel rebar reinforcement, new reinforcement scheme i.e. hybrid steel wire mesh-micro steel fibre reinforcement is investigated through the laboratory static tests and field blast tests. Furthermore, a numerical study based on Multi-Material ALE and Lagrangian algorithm is carried out to further investigate the field tests’ phenomenon.
Li, JJ, Roohani-Esfahani, S-I, Kim, K, Kaplan, DL & Zreiqat, H 2017, 'Silk coating on a bioactive ceramic scaffold for bone regeneration: effective enhancement of mechanical and in vitro osteogenic properties towards load-bearing applications', Journal of Tissue Engineering and Regenerative Medicine, vol. 11, no. 6, pp. 1741-1753.
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Bioactive ceramic scaffolds represent competitive choices for clinical bone reconstruction, but their widespread use is restricted by inherent brittleness and weak mechanical performance under load. This study reports the development of strong and tough bioactive scaffolds suitable for use in load-bearing bone reconstruction. A strong and bioactive ceramic scaffold (strontium-hardystonite-gahnite) is combined with single and multiple coating layers of silk fibroin to enhance its toughness, producing composite scaffolds which match the mechanical properties of cancellous bone and show enhanced capacity to promote in vitro osteogenesis. Also reported for the first time is a comparison of the coating effects obtained when a polymeric material is coated on ceramic scaffolds with differing microstructures, namely the strontium-hardystonite-gahnite scaffold with high-density struts as opposed to a conventional ceramic scaffold, such as biphasic calcium phosphate, with low-density struts. The results show that silk coating on a unique ceramic scaffold can lead to simple and effective enhancement of its mechanical and biological properties to suit a wider range of applications in clinical bone reconstruction, and also establish the influence of ceramic microstructure on the effectiveness of silk coating as a method of reinforcement when applied to different types of ceramic bone graft substitutes. Copyright © 2015 John Wiley & Sons, Ltd.
Li, K, Liu, Y, Jia, Y & Guo, YJ 2017, 'A Circularly Polarized High-Gain Antenna With Low RCS Over a Wideband Using Chessboard Polarization Conversion Metasurfaces', IEEE Transactions on Antennas and Propagation, vol. 65, no. 8, pp. 4288-4292.
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© 1963-2012 IEEE. A new approach for the gain enhancement and wideband radar cross section (RCS) reduction of an antenna based on the chessboard polarization conversion metasurfaces (CPCMs) is proposed. Compared with the previous low-RCS antennas, high gain and wideband low RCS of a circularly polarized (CP) antenna are achieved simultaneously. The proposed CPCM is the chessboard configuration of the polarization conversion metasurfaces (PCMs), which is made up of adjoining two-layer substrates with three metallic patterns. Low RCS is realized by 180° (±30°) reflection phase variations between two neighboring PCMs. Gain enhancement is achieved by employing a Fabry-Perot cavity, which is constructed by the PCM and the ground of the antenna. The antenna with CPCM operating at the X -band, excited by a sequentially rotated feeding network, is fabricated and measured. Simulated and measured results show that the left-hand CP gain of the antenna with CPCM is at least 3 dB higher than that of the reference antenna from 8.5 to 9.5 GHz and the monostatic RCS is effectively reduced from 6 to 14 GHz.
Li, L, Yu, X, Zhang, S, Zhao, X & Zhang, L 2017, '3D cost aggregation with multiple minimum spanning trees for stereo matching', Applied Optics, vol. 56, no. 12, pp. 3411-3411.
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Li, M, Wu, H, Zhang, J, Ngo, HH, Guo, W & Kong, Q 2017, 'Nitrogen removal and nitrous oxide emission in surface flow constructed wetlands for treating sewage treatment plant effluent: Effect of C/N ratios', Bioresource Technology, vol. 240, pp. 157-164.
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In order to design treatment wetlands with maximal nitrogen removal and minimal nitrous oxide (N2O) emission, the effect of influent C/N ratios on nitrogen removal and N2O emission in surface flow constructed wetlands (SF CWs) for sewage treatment plant effluent treatment was investigated in this study. The results showed that nitrogen removal and N2O emission in CWs were significantly affected by C/N ratio of influent. Much higher removal efficiency of NH4(+)-N (98%) and TN (90%) was obtained simultaneously in SF CWs at C/N ratios of 12:1, and low N2O emission (8.2mg/m(2)/d) and the percentage of N2O-N emission in TN removal (1.44%) were also observed. These results obtained in this study would be utilized to determine how N2O fluxes respond to variations in C/N ratios and to improve the sustainability of CWs for wastewater treatment.
Li, Q, Ni, W, Deng, Z, Liu, M, She, L & Xie, Q 2017, 'Targeting nasopharyngeal carcinoma by artesunate through inhibiting Akt/mTOR and inducing oxidative stress', Fundamental & Clinical Pharmacology, vol. 31, no. 3, pp. 301-310.
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AbstractDrug repurposing has become an alternative therapeutic strategy for cancer treatment given the known pharmacokinetics and toxicity. The inhibitory effects of artesunate have been reported in various cancers. In this work, we investigated the effects of artesunate in nasopharyngeal carcinoma (NPC). We demonstrate that artesunate significantly inhibits proliferation via arresting NPC cells at G2/M phase. It also induces apoptosis through caspase‐dependent and mitochondria‐independent pathways in multiple NPC cell lines. The combination of artesunate and cisplatin is synergistic in targeting NPC cells in in vitro cellular culture system and in vivo xenograft tumor models. Artesunate inhibits phosphorylation of essential molecules involved in Akt/mTOR pathway in NPC cells, such as Akt, mTOR, and 4EBP1, and its inhibitory effects are partially abolished by overexpression of constitutively active Akt. In addition, artesunate also induces mitochondrial dysfunction and oxidative stress via inhibiting mitochondrial respiration, increasing levels of mitochondrial superoxide and cellular reactive oxygen species (ROS), leading to decreased ATP levels. Two ROS scavengers partially abolish the inhibitory ...
Li, Q, Xiong, R & Vidal-Calleja, T 2017, 'A GMM based uncertainty model for point clouds registration', Robotics and Autonomous Systems, vol. 91, pp. 349-362.
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© 2016 Elsevier B.V. The existing methods for the registration of point clouds acquired by laser scanners have some limitations. Firstly, as some samples of surface, a point cloud acquired by the laser scanner, which normally works in a spherical fashion, has very limited density when the surface is far away from the laser scanner and the density varies a lot at different ranges. Current registration methods cannot accurately model the surface uncertainty for such kind of point clouds of limited and large varying density. Secondly, when the point cloud is acquired while the platform is simultaneously moving, the estimation error of the platform motion makes the acquired point cloud distorted. To deal with these problems, in this paper, we propose an uncertainty model based on the Gaussian Mixture Model (GMM) to represent the point cloud. Specifically, we construct the GMM piece-wisely on the underlying surface of point cloud, which will accurately model the surface uncertainty. Also a hierarchical structure is employed to increase the robustness of the registration. Furthermore, by assigning each Gaussian component with a pose, a probabilistic graph can be constructed to tackle the problem of registration when the platform is moving while scanning. In this way the distorted point cloud, caused by the estimation error of the platform's motion, can be corrected by performing graph optimization. Simulation and real world experimental results show that our method leads to better convergence than the state-of-the-art methods due to the accurate modeling of the surface uncertainty and the hierarchical structure, and it also enables us to correct the distorted point clouds.
Li, R-H, Qin, L, Yu, JX & Mao, R 2017, 'Finding influential communities in massive networks.', VLDB J., vol. 26, no. 6, pp. 751-776.
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© 2017, Springer-Verlag Berlin Heidelberg. Community search is a problem of finding densely connected subgraphs that satisfy the query conditions in a network, which has attracted much attention in recent years. However, all the previous studies on community search do not consider the influence of a community. In this paper, we introduce a novel community model called k-influential community based on the concept of k-core to capture the influence of a community. Based on this community model, we propose a linear time online search algorithm to find the top-rk-influential communities in a network. To further speed up the influential community search algorithm, we devise a linear space data structure which supports efficient search of the top-rk-influential communities in optimal time. We also propose an efficient algorithm to maintain the data structure when the network is frequently updated. Additionally, we propose a novel I/O-efficient algorithm to find the top-rk-influential communities in a disk-resident graph under the assumption of U= O(n) , where U and n denote the size of the main memory and the number of nodes, respectively. Finally, we conduct extensive experiments on six real-world massive networks, and the results demonstrate the efficiency and effectiveness of the proposed methods.
Li, S, Kim, Y, Chekli, L, Phuntsho, S, Shon, HK, Leiknes, T & Ghaffour, N 2017, 'Impact of reverse nutrient diffusion on membrane biofouling in fertilizer-drawn forward osmosis', Journal of Membrane Science, vol. 539, pp. 108-115.
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© 2017 Elsevier B.V. Biofouling in fertilizer-drawn forward osmosis (FDFO) for water reuse was investigated by spiking pure bacteria species Pseudomonas aeruginosa PAO1+GFP and using three different fertilizers KNO3, KCl and KH2PO4 as draw solutions. The performance of FO process for treating synthetic wastewater was assessed and their influence on the membrane fouling and in particular biofouling was evaluated relative to the type of different fertilizers used and their rates of reverse diffusion. FO performances using KNO3 as draw solute exhibited severer flux decline (63%) than when using KCl (45%) and KH2PO4 (30%). Membrane autopsy indicated that the mass of organic foulants and biomass on fouled membrane surface using KNO3 as draw solute (947.5 mg/m2 biopolymers, 72 µm biofilm thickness and 53.3 mg/m2 adenosine triphosphate) were significantly higher than that using KCl (450 mg/m2 biopolymers, 33 µm biofilm thickness and 28.2 mg/m2 ATP) and KH2PO4 (440 mg/m2 biopolymers, 35 µm biofilm thickness and 33.5 mg/m2 ATP). This higher flux decline is likely related to the higher reverse diffusion of KNO3 (19.8 g/m2/h) than KCl (5.1 g/m2/h) and KH2PO4 (3.7 g/m2/h). The reverse diffused potassium could promote the organics and bacterial adhesion on FO membrane via charge screening effect and compression of electrical double layer. Moreover, reverse diffused nitrate provided increased N:P nutrient ratio was favorable for the bacteria to grow on the feed side of the FO membrane.
Li, S, Kim, Y, Phuntsho, S, Chekli, L, Shon, HK, Leiknes, T & Ghaffour, N 2017, 'Methane production in an anaerobic osmotic membrane bioreactor using forward osmosis: Effect of reverse salt flux', Bioresource Technology, vol. 239, pp. 285-293.
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© 2017 Elsevier Ltd This study investigated the impact of reverse salt flux (RSF) on microbe community and bio-methane production in a simulated fertilizer driven FO-AnMBR system using KCl, KNO3 and KH2PO4 as draw solutes. Results showed that KH2PO4 exhibited the lowest RSF in terms of molar concentration 19.1 mM/(m2.h), while for KCl and KNO3 it was 32.2 and 120.8 mM/(m2.h), respectively. Interestingly, bio-methane production displayed an opposite order with KH2PO4, followed by KCl and KNO3. Pyrosequencing results revealed the presence of different bacterial communities among the tested fertilizers. Bacterial community of sludge exposed to KH2PO4 was very similar to that of DI-water and KCl. However, results with KNO3 were different since the denitrifying bacteria were found to have a higher percentage than the sludge with other fertilizers. This study demonstrated that RSF has a negative effect on bio-methane production, probably by influencing the sludge bacterial community via environment modification.
Li, W, Huang, Z, Hu, G, Hui Duan, W & Shah, SP 2017, 'Early-age shrinkage development of ultra-high-performance concrete under heat curing treatment', Construction and Building Materials, vol. 131, pp. 767-774.
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© 2016 Elsevier Ltd The effects of a novel heat curing regime and longitudinal reinforcement ratio on early-age shrinkage of ultra-high performance concrete (UHPC) were experimentally investigated in this study. The microstructure, porosity and calcium hydroxide (CH) content of UHPC after different heat curing durations were characterized with scanning electron microscopy, mercury intrusion porosimetry and thermal analysis. The results indicate that slight shrinkage was observed when the heat curing duration was less than 60 min and curing temperature reached 48 °C. However, when the heat curing duration approached 70 min and curing temperature was around 55 °C, the early-age shrinkage increased dramatically. It was found that the early-age shrinkage is approximately 450 με after 48 h of heat curing. The results also show that the early-age shrinkage of UHPC significantly decreased by percentage of 33–60% with the increase of longitudinal steel reinforcement ratio from 2.0 to 4.52%. Meantime, after 10 h of heat curing, the cement hydration and secondary hydration in UHPC tend to finish, which consequently leads to dense microstructure and low CH content in UHPC.
Li, W, Li, X, Chen, SJ, Liu, YM, Duan, WH & Shah, SP 2017, 'Effects of graphene oxide on early-age hydration and electrical resistivity of Portland cement paste', Construction and Building Materials, vol. 136, pp. 506-514.
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© 2017 Elsevier Ltd The effects of graphene oxide (GO) on the early-age hydration process and mechanical properties of Portland cement paste were experimentally investigated in this study. Based on an isothermal calorimeter measurement, the hydration rate of cement was observed to increase with the increase of GO content by nucleation effect. On the other hand, the electrical resistivity development of GO-cement paste was monitored using a non-contact electrical resistivity device. The result showed that electrical the resistivity of GO-cement paste was evidently higher than that of plain cement paste. However, cement paste with excessive amounts of GO exhibited a decreased electrical resistivity due to the massive ion diffusion caused by GO. Compared to plain cement paste, the GO-cement paste exhibited obviously higher compressive and flexural strengths, but the enhancements in compressive strength began to decline when the GO amount was greater than 0.04%. The microstructure characterization indicated that GO can apparently densify the cement pastes with less porosity and hydrates networking, which is consistent with the results of hydration acceleration and strength enhancement.
Li, W, Li, X, Chen, SJ, Long, G, Liu, YM & Duan, WH 2017, 'Effects of Nanoalumina and Graphene Oxide on Early-Age Hydration and Mechanical Properties of Cement Paste', Journal of Materials in Civil Engineering, vol. 29, no. 9, pp. 04017087-04017087.
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© 2017 American Society of Civil Engineers. The effects of nanoalumina (NA) and graphene oxide (GO) on the early-age hydration and mechanical properties of portland cement pastes were investigated in this study. The hydration heat release rate and cumulative heat of cement pastes incorporating different dosages of NA and GO were evaluated using an isothermal calorimeter measurement method. Early-age electrical resistivity development was investigated by a noncontact electrical resistivity technique. The results show that both NA and GO could efficiently accelerate cement hydration. As a physical filler, NA significantly accelerates the hydration of tricalcium aluminate (C3A) in cement. On the other hand, GO is able to obviously reduce the dormant period of cement hydration and shift the heat flow peaks to the left by accelerating the hydration of tricalcium silicate (C3S) in cement. Compared to plain cement pastes, both the compressive and flexural strengths of cement pastes incorporating NA or GO are significantly increased. However, when NA and GO contents exceed the optimal amounts, improvements in flexural strength tend to decline, which is probably due to particle agglomeration. NA-cement paste exhibited slightly higher electrical resistivity than plain cement paste during hydration acceleration and deceleration stages. But GO-cement paste clearly showed lower electrical resistivity, which might be attributed to iron diffusion caused by GO with large surface areas.
Li, W, Long, C, Tam, VWY, Poon, C-S & Hui Duan, W 2017, 'Effects of nano-particles on failure process and microstructural properties of recycled aggregate concrete', Construction and Building Materials, vol. 142, pp. 42-50.
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© 2017 Elsevier Ltd The effects of nano-particles including nano-silica (NS) and nano-limestone (NL) on the crack propagation and microstructure properties of recycled aggregate concrete (RAC) were experimentally investigated in this study. The crack initiation and propagation of nano-particles modified RAC with different nano-particle modification were evaluated using digital image correlation technique (DIC). The microstructures and porosity of interfacial transition zones (ITZ) in nano-modified RAC were also examined using scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP). It was found that the micro-cracks were typically derived from relatively weak ITZs in RAC, and then progressively propagated along the compressive loading direction. The meso-crack developments eventually led to final splitting failure. The results indicated that compared to NL, NS was more effective in improving the microstructure properties and enhance the mechanical strength of RAC. The porosity and water absorption of RAC were obviously reduced by the NS incorporation. However, due to particles agglomeration, NL could not effectively improve the microstructure of RAC for further enhancing the RAC mechanical properties. Furthermore, in terms of severe particles agglomeration, NL was even detrimental to the mechanical strength of RAC especially at the late-age.
Li, W, Luo, Z, Tao, Z, Duan, WH & Shah, SP 2017, 'Mechanical behavior of recycled aggregate concrete-filled steel tube stub columns after exposure to elevated temperatures', Construction and Building Materials, vol. 146, pp. 571-581.
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© 2017 Elsevier Ltd The compressive mechanical behaviors of recycled aggregate concrete-filled steel tube (RACFST) stub columns after exposure to elevated temperatures were experimentally investigated in this study. The RACFST stub columns incorporating different recycled coarse aggregate (RCA) replacement ratios of 0, 50% and 100% were heated under elevated temperatures of 200 °C, 500 °C, and 700 °C. The results show that the compressive strength and elastic modulus of RACFST columns were relatively inferior to those of the corresponding natural aggregate concrete-filled steel tube (NACFST) columns after exposure to the same elevated temperatures, and the degradations became more pronounced with increasing RCA replacement ratio and higher temperature. This phenomenon might be attributed to the lower resistance of recycled aggregate concrete (RAC) than natural aggregate concrete (NAC) when was exposed to elevated temperatures. However, after elevated temperature exposure, the peak strain of RACFST stub column was relatively higher than that of the NACFST counterpart. Degradation regression formulas of mechanical properties and deformation behaviors of RACFST stub columns after exposure to elevated temperatures were proposed and agreed well with the experimental results.
Li, W, Luo, Z, Wu, C, Tam, VWY, Duan, WH & Shah, SP 2017, 'Experimental and numerical studies on impact behaviors of recycled aggregate concrete-filled steel tube after exposure to elevated temperature', Materials & Design, vol. 136, pp. 103-118.
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© 2017 Elsevier Ltd This study investigated the impact behaviors of recycled aggregate concrete-filled steel tube (RACFST) after exposed to elevated temperatures by experimental and numerical studies. The impact test on RACFST was conducted by a split Hopkinson pressure bar (SHPB) with 100 mm-diameter. After the validation of finite element method simulation by the experimental results, parametric analysis were applied to analyze the effects of RAC strength, steel strength and steel ratio on the impact behaviors and deformation properties of the RACFSTs exposed to elevated temperatures ranging from 20 °C, 200 °C to 500 °C and to 700 °C. The results show that both the increases in RAC strength, steel strength and steel ratio significantly enhance the impact resistance of RACFST. However, when RAC strength deteriorates quickly after exposure to high temperature, the increase in RAC strength just slightly improves the impact properties of RACFST, especially after exposure to elevated temperatures higher than 500 °C. In conclusion, increasing steel ratio is an effective way for improving the impact behaviors of RACFST, but resulting in higher cost for practical application. For the impact design of RACFST, steel strength and steel ratio are two essential factors in terms of impact behavior enhancement and cost efficiency.
Li, W, Sun, Z, Luo, Z & Shah, SP 2017, 'Retraction: Influence of Relative Mechanical Strengths between New and Old Cement Mortars on the Crack Propagation of Recycled Aggregate Concrete', Journal of Advanced Concrete Technology, vol. 15, no. 3, pp. 110-125.
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Li, W, Xu, KD, Tang, X, Yang, Y, Liu, Y & Liu, QH 2017, 'Substrate Integrated Waveguide Cavity-Backed Slot Array Antenna Using High-Order Radiation Modes for Dual-Band Applications in $K$ -Band', IEEE Transactions on Antennas and Propagation, vol. 65, no. 9, pp. 4556-4565.
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© 2017 IEEE. A novel compact dual-band cavity-backed substrate integrated waveguide (SIW) array antenna using high-order radiation modes has been proposed in this paper. The first high-order hybrid mode (superposition of TM310 and TM130) and the second high-order mode (TM320) of K-band in the SIW cavity are excited by an inductive window for dual-band application. The operation mechanism of high-order modes is analyzed and then verified through simulations by inserting metallic vias in different positions of the resonant SIW cavity. The designed subarray antenna has the advantages of high gain, high front-to-back ratio, and low cross-polarization level. To further validate the design idea, a dual-frequency band $2 \times 2$ array antenna has been fabricated and measured including reflection coefficients, realized gains, and radiation patterns. The measured results show that the 10-dB impedance bandwidths at resonant frequencies of 21 and 26 GHz are 800 MHz (3.7%) and 700 MHz (2.6%), and the realized gains at boresight direction are around 16 and 17.4 dBi, respectively. Moreover, the proposed array antenna also possesses both advantages of metallic cavity-backed antennas and planar patch antennas, such as low cost, easy fabrication with the printed circuit board technology, and integration with other planar circuits.
Li, X, Liu, YM, Li, WG, Li, CY, Sanjayan, JG, Duan, WH & Li, Z 2017, 'Effects of graphene oxide agglomerates on workability, hydration, microstructure and compressive strength of cement paste', Construction and Building Materials, vol. 145, pp. 402-410.
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© 2017 Elsevier Ltd In this study, the effects of graphene oxide (GO) agglomerates on the workability, hydration, microstructure, and compressive strength of cement paste were addressed. The workability of cement paste was reduced because of the presence of GO agglomerates, which entrap a large amount of water. The mini-slump diameter was reduced by 21% with the incorporation of 0.03% by weight GO in cement paste. Hydration of the cement paste was accelerated due to nucleation sites provided by GO agglomerates serving as seeding material in the cement paste. The incorporation of GO refined the pore structure of the cement paste. The incorporation of GO was found to have much greater impact on macropores than on large and small mesopores. At 28 days, the incorporation of 0.04% by weight GO produced a 14% improvement in the compressive strength of cement paste. Below 0.03%, the incorporation of GO had no positive effects on compressive strength.
Li, X, Lu, Z, Chuah, S, Li, W, Liu, Y, Duan, WH & Li, Z 2017, 'Effects of graphene oxide aggregates on hydration degree, sorptivity, and tensile splitting strength of cement paste', Composites Part A: Applied Science and Manufacturing, vol. 100, pp. 1-8.
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© 2017 Elsevier Ltd It has recently been found the graphene oxide (GO) aggregates form in cement paste due to the chemical cross-linking of calcium cations. Therefore, the effects of GO addition on the properties of cement based materials should be dependent on the properties of GO aggregates rather than GO nanosheets. In this study, GO aggregates were first characterized by particle size measurement. Then, the effects of GO aggregates on the degree of hydration, sorptivity, and tensile strength of cement paste were investigated. The aspect ratio of GO aggregates is much larger than that of the original GO nanosheets. Compared to plain cement paste, the increase of non-evaporable water content of the cement paste was found to be very limited, around 1.17% and 3.90% for cement pastes containing 0.02% and 0.04% by weight GO, respectively. The sorptivity of cement paste, especially the secondary sorptivity, was notably reduced for GO incorporated cement paste. The tensile strength was significantly improved by GO aggregates. Incorporation of 0.04% by weight GO increased the tensile strength by 67% compared to that of plain cement paste.
Li, X, Mo, Y, Li, J, Guo, W & Ngo, HH 2017, 'In-situ monitoring techniques for membrane fouling and local filtration characteristics in hollow fiber membrane processes: A critical review', Journal of Membrane Science, vol. 528, pp. 187-200.
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Li, X, Tao, M, Wu, C, Du, K & Wu, Q 2017, 'Spalling strength of rock under different static pre-confining pressures', International Journal of Impact Engineering, vol. 99, pp. 69-74.
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© 2016 Elsevier Ltd A testing method of spalling strength at different static pre-confining pressure is proposed in this paper. Using a modified split Hopkinson bar facility, a static pre-confining pressure was loaded before dynamic loading. The pull-back method is used to calculate the spalling strength and the free surface velocities of the specimen were measured by a laser detector system. The experimental results indicate that the spalling strength is related to the static pre-confining pressures. When the impact loading and rate effect are almost the same, the results demonstrated that the spalling strength decreases with an increase in the confining pressure.
Li, X, Wang, L, Liu, Z & Dong, D 2017, 'Lower Bounds on the Proportion of Leaders Needed for Expected Consensus of 3-D Flocks', IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 11, pp. 2555-2565.
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Li, Y & Li, J 2017, 'On rate-dependent mechanical model for adaptive magnetorheological elastomer base isolator', Smart Materials and Structures, vol. 26, no. 4, pp. 045001-045001.
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© 2017 IOP Publishing Ltd. This paper presents research on the phenomenological model of an adaptive base isolator. The adaptive base isolator is made of field-dependent magnetorheological elastomer (MRE) which can alter its physical property under application of magnetic field. Experimental testing demonstrated that the developed MRE base isolator possesses an amazing ability to vary its stiffness under applied magnetic field. However, several challenges have been encountered when it comes modeling such novel device. For example, under a large deformation, the MRE base isolator exhibits a clear strain stiffening effect and this behavior escalates with the increasing of applied current. In addition, the MRE base isolator has also shown typical rate-dependent behavior. Following a review on mechanical models for viscos-elastic rubber devices, a novel rate-dependent model is proposed in this paper to capture the behavior of the new MRE base isolator. To develop a generalized model, the proposed model was evaluated using its performance under random displacement input and a seismic input. It shows that the proposed rate-dependent model can successfully describe the complex behavior of the device.
Li, Y & Qiao, Y 2017, 'On rank-critical matrix spaces', Differential Geometry and its Applications, vol. 55, pp. 68-77.
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© 2017 Elsevier B.V. A matrix space of size m×n is a linear subspace of the linear space of m×n matrices over a field F. The rank of a matrix space is defined as the maximal rank over matrices in this space. A matrix space A is called rank-critical, if any matrix space which properly contains it has rank strictly greater than that of A. In this note, we first exhibit a necessary and sufficient condition for a matrix space A to be rank-critical, when F is large enough. This immediately implies the sufficient condition for a matrix space to be rank-critical by Draisma (2006) [5], albeit requiring the field to be slightly larger. We then study rank-critical spaces in the context of compression and primitive matrix spaces. We first show that every rank-critical matrix space can be decomposed into a rank-critical compression matrix space and a rank-critical primitive matrix space. We then prove, using our necessary and sufficient condition, that the block-diagonal direct sum of two rank-critical matrix spaces is rank-critical if and only if both matrix spaces are primitive, when the field is large enough.
Li, Z, Nie, F, Chang, X & Yang, Y 2017, 'Beyond Trace Ratio: Weighted Harmonic Mean of Trace Ratios for Multiclass Discriminant Analysis', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 10, pp. 2100-2110.
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© 1989-2012 IEEE. Linear discriminant analysis (LDA) is one of the most important supervised linear dimensional reduction techniques which seeks to learn low-dimensional representation from the original high-dimensional feature space through a transformation matrix, while preserving the discriminative information via maximizing the between-class scatter matrix and minimizing the within class scatter matrix. However, the conventional LDA is formulated to maximize the arithmetic mean of trace ratios which suffers from the domination of the largest objectives and might deteriorate the recognition accuracy in practical applications with a large number of classes. In this paper, we propose a new criterion to maximize the weighted harmonic mean of trace ratios, which effectively avoid the domination problem while did not raise any difficulties in the formulation. An efficient algorithm is exploited to solve the proposed challenging problems with fast convergence, which might always find the globally optimal solution just using eigenvalue decomposition in each iteration. Finally, we conduct extensive experiments to illustrate the effectiveness and superiority of our method over both of synthetic datasets and real-life datasets for various tasks, including face recognition, human motion recognition and head pose recognition. The experimental results indicate that our algorithm consistently outperforms other compared methods on all of the datasets.
Liang, B & Zheng, L 2017, 'Specificity and Latent Correlation Learning for Action Recognition Using Synthetic Multi-View Data From Depth Maps', IEEE Transactions on Image Processing, vol. 26, no. 12, pp. 5560-5574.
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© 1992-2012 IEEE. This paper presents a novel approach to action recognition using synthetic multi-view data from depth maps. Specifically, multiple views are first generated by rotating 3D point clouds from depth maps. A pyramid multi-view depth motion template is then adopted for multi-view action representation, characterizing the multi-scale motion and shape patterns in 3D. Empirically, despite the view-specific information, the latent information between multiple views often provides important cues for action recognition. Concentrating on this observation and motivated by the success of the dictionary learning framework, this paper proposes to explicitly learn a view-specific dictionary (called specificity) for each view, and simultaneously learn a latent dictionary (called latent correlation) across multiple views. Thus, a novel method, specificity and latent correlation learning, is put forward to learn the specificity that captures the most discriminative features of each view, and learn the latent correlation that contributes the inherent 3D information to multiple views. In this way, a compact and discriminative dictionary is constructed by specificity and latent correlation for feature representation of actions. The proposed method is evaluated on the MSR Action3D, the MSR Gesture3D, the MSR Action Pairs, and the ChaLearn multi-modal data sets, consistently achieving promising results compared with the state-of-the-art methods based on depth data.
Liang, C, Lin, C-T, Yao, S-N, Chang, W-S, Liu, Y-C & Chen, S-A 2017, 'Visual attention and association: An electroencephalography study in expert designers', Design Studies, vol. 48, pp. 76-95.
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© 2016 Elsevier Ltd Extant research on the visual attention and association of designers is limited, and scientific evidence differentiating among the effects of diverse visual stimuli on design thinking is insufficient. The current study invited 12 healthy expert designers and analysed their experiences of visual attention and association in addition to exploring the differences caused by three types of pictorial representation. The results of this electroencephalography (EEG) experiment indicated that the frontoparietal region was particularly activated when the designers engaged in visual attention tasks, whereas the brainwaves were particularly activated in the distributed prefrontal, frontocentral, and parietooccipital regions during the visual association tasks. In addition, there were no significant differences in the brainwave energy resulting from the three types of pictorial representation applied in this study. The research outcomes linking design studies to cognitive neuroscience establish a concrete foundation for developing future applied research and diverse educational practices.
Liang, D, He, X & Zhang, J-X 2017, 'An ISPH model for flow-like landslides and interaction with structures', Journal of Hydrodynamics, vol. 29, no. 5, pp. 894-897.
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Liang, J, Su, S, Zhang, X, Li, L & Luo, Y 2017, 'A NONINVASIVE METHOD TO EVALUATE THE DEGREE OF UPPER AIRWAY STENOSIS', Biomedical Engineering: Applications, Basis and Communications, vol. 29, no. 05, pp. 1750035-1750035.
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Purpose: This paper presented a new approach to noninvasively evaluate the upper airway stenosis for obstructive sleep apnea syndrome (OSAS) patients. Methods: In the proposed method, thoracic and abdominal movements were selected to calculate the respiratory movement (RM) and to indicate the change of lung volume. Due to the cumulative effect of thermal sensor, the oronasal-thermistor signal (T_flow) is applied to estimate the air mass change in lung. Based on the mathematical relationship, the “RM–T_flow curves”, drawn by RM and T_flow, together with the correlation coefficients ([Formula: see text] were used to analyze the upper airway stenosis. Results: This method was verified through portable monitoring (PM) based experiments, and numerical analysis of the polysomnography (PSG) data from 20 OSAS patients and 15 non-OSAS controls. Our results indicate the [Formula: see text] values decrease with the narrowing of the upper airway. At each sleep stage, the [Formula: see text] mean values of OSAS subjects are significantly ([Formula: see text]) smaller than those of the controls. These facts demonstrate that the [Formula: see text] value can be used to quantify the upper airway stenosis and the analysis of “RM–T_flow curves” is an efficient way to assess upper airway condition associated with the breathing phase. Conclusions: As this method can be used in spontaneous sleep and home sleep testing, we believe it will benefit the popularity of the diagnosis and evaluation of OSAS.
Liao, Y, Kodagoda, S, Wang, Y, Shi, L & Liu, Y 2017, 'Place Classification With a Graph Regularized Deep Neural Network', IEEE Transactions on Cognitive and Developmental Systems, vol. 9, no. 4, pp. 304-315.
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Lim, S, Park, MJ, Phuntsho, S, Tijing, LD, Nisola, GM, Shim, W-G, Chung, W-J & Shon, HK 2017, 'Dual-layered nanocomposite substrate membrane based on polysulfone/graphene oxide for mitigating internal concentration polarization in forward osmosis', Polymer, vol. 110, pp. 36-48.
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© 2016 Elsevier Ltd A novel thin-film composite (TFC) forward osmosis (FO) membrane with dual-layered substrate membrane was fabricated by a double-blade casting technique using different polysulfone (PSf) concentrations for top (15 wt%) and bottom (7 wt%) substrate layers. Graphene oxide (GO) was incorporated in the substrate layer, and the dual casting approach resulted in a membrane support with a highly porous bottom structure and a dense top skin layer on which the polyamide active layer was effectively formed. The dual-layered TFC PSf/GO membrane (TFC-PSfdGO) exhibited high water permeability, and ion selectivity was enhanced by the presence of well dispersed hydrophilic GO in the PSf substrate. The TFC-PSfdGO also exhibited the lowest specific reverse salt flux (Js/Jv = 0.19 g L-1) and a more favorable structural parameter (S = 130 μm) compared to GO-free membranes. Using deionized water as feed solution and 1 M NaCl as draw solution (DS), TFC-PSfdGO had Jv = 33.8 L m−2 h−1 and Js = 6.9 g−2 h−1 under AL-FS mode, and Jv = 61.5 L m−2h−1 and Js = 14.0 g−2 h−1 under AL-DS mode. The potential of TFC-PSfdGO for commercial application was further evaluated by fabricating it with a fabric backing support (denoted as TFC-PSfdGOf). Compared to TFC-PSfdGO, TFC-PSfdGOf exhibited only 14% decline in its water flux. The overall results reveal that, fabrication of TFC substrate membrane via dual-blade casting approach along with GO incorporation produced high-performance TFC FO membranes which likely reduced the internal concentration polarization effects.
Lin, C-T, Chuang, C-H, Cao, Z, Singh, AK, Hung, C-S, Yu, Y-H, Nascimben, M, Liu, Y-T, King, J-T, Su, T-P & Wang, S-J 2017, 'Forehead EEG in Support of Future Feasible Personal Healthcare Solutions: Sleep Management, Headache Prevention, and Depression Treatment', IEEE Access, vol. 5, pp. 10612-10621.
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© 2013 IEEE. There are current limitations in the recording technologies for measuring EEG activity in clinical and experimental applications. Acquisition systems involving wet electrodes are time-consuming and uncomfortable for the user. Furthermore, dehydration of the gel affects the quality of the acquired data and reliability of long-term monitoring. As a result, dry electrodes may be used to facilitate the transition from neuroscience research or clinical practice to real-life applications. EEG signals can be easily obtained using dry electrodes on the forehead, which provides extensive information concerning various cognitive dysfunctions and disorders. This paper presents the usefulness of the forehead EEG with advanced sensing technology and signal processing algorithms to support people with healthcare needs, such as monitoring sleep, predicting headaches, and treating depression. The proposed system for evaluating sleep quality is capable of identifying five sleep stages to track nightly sleep patterns. Additionally, people with episodic migraines can be notified of an imminent migraine headache hours in advance through monitoring forehead EEG dynamics. The depression treatment screening system can predict the efficacy of rapid antidepressant agents. It is evident that frontal EEG activity is critically involved in sleep management, headache prevention, and depression treatment. The use of dry electrodes on the forehead allows for easy and rapid monitoring on an everyday basis. The advances in EEG recording and analysis ensure a promising future in support of personal healthcare solutions.
Lin, C-T, Liu, Y-T, Wu, S-L, Cao, Z, Wang, Y-K, Huang, C-S, King, J-T, Chen, S-A, Lu, S-W & Chuang, C-H 2017, 'EEG-Based Brain-Computer Interfaces: A Novel Neurotechnology and Computational Intelligence Method', IEEE Systems, Man, and Cybernetics Magazine, vol. 3, no. 4, pp. 16-26.
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This article presents the latest BCI-related research done in our group. Our previous work applied computational intelligence technology in BCIs to inspire detailed investigations of practical issues in real-life applications. Novel EEG devices featuring dry electrodes facilitate and speed up electrode positioning before recording and allow subjects to move freely in operational environments. We also demonstrate the feasibility of applying CCA, RBFNs, effective connectivity measurements, and D-S theory to help BCIs extract informative knowledge from brain signals. Two recent trends in research in the computational and artificial intelligence community, big data and deep learning, are expected to impact the direction and development of BCIs.
Ling, SH, San, PP, Lam, HK & Nguyen, HT 2017, 'Hypoglycemia detection: multiple regression-based combinational neural logic approach', Soft Computing, vol. 21, no. 2, pp. 543-553.
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© 2015 Springer-Verlag Berlin Heidelberg Hypoglycemia is a common and serious side effect of type 1 diabetes. We measure physiological parameters continuously to provide detection of hypoglycemic episodes in type 1 diabetes mellitus patients using a multiple regression-based combinational neural logic approach. In this work, a neural logic network with multiple regression is applied to the development of non-invasive hypoglycemia monitoring system. It is an alarm system which measures the physiological parameters of electrocardiogram signal (heart rate and corrected QT interval) and determine the onset of hypoglycemia by the use of proposed hybrid neural logic approach. In this clinical application, a combinational neural logic network with multiple regression is systematically designed to hypoglycemia detection based on the characteristic of this application. To optimize the parameter of the hybrid combinational neural logic system, hybrid particle swarm optimization with wavelet mutation is applied to tuned the parameters of the system. To illustrate the effectiveness of the proposed method, hypoglycemia monitoring system which will be practically analyzed using real data sets collected from 15 children ((Formula presented.) years) with type 1 diabetes at the Department of Health, Government of Western Australia. With the use of proposed method, the best testing sensitivity of 79.07 % and specificity of 53.64 % were obtained.
Ling, Y, Li, C, Feng, K, Palmer, S, Appleton, PL, Lang, S, McGloin, D, Huang, Z & Nabi, G 2017, 'Second harmonic generation (SHG) imaging of cancer heterogeneity in ultrasound guided biopsies of prostate in men suspected with prostate cancer', Journal of Biophotonics, vol. 10, no. 6-7, pp. 911-918.
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Prostate cancer is a multifocal disease with characteristic heterogeneity and foci that can range from low grade indolent to aggressive disease. The latter is characterised by the well‐established histopathological Gleason grading system used in the current clinical care. Nevertheless, a large discrepancy exists on initial biopsy and after the final radical prostatectomy. Moreover, there is no reliable imaging modality to study these foci, in particular at the level of the cells and surrounding matrix. Extracellular matrix (ECM) remodelling is significant in cancer progression with collagen as the dominant structural component providing mechanical strength and flexibility of tissue. In this study, the collagen assembly in prostate tissue was investigated with second harmonic generation (SHG) microscopy: malignant foci demonstrated a reticular pattern, with a typical collagen pattern for each Gleason score. The orientation of collagen for each biopsy was computed by applying a ratio of the anisotropic and isotropic collagen fibres. This value was found to be distinct for each Gleason score. The findings suggest that this approach can not only be used to detect prostate cancer, but also can act as a potential biomarker for cancer aggressiveness.magnified image
Liu, B, Xiao, Y & Cao, L 2017, 'SVM-based multi-state-mapping approach for multi-class classification', Knowledge-Based Systems, vol. 129, pp. 79-96.
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© 2017.Traditional SVM-based multi-class classification algorithms mainly adopt the strategy of mapping the data set with all classes into a single feature space via a kernel function, in which SVM is constructed for each decomposed binary classification problem. However, it is not always possible to find an appropriate kernel function to render all the classes distinguishable in a single feature space, since each class is always derived from different data distributions. Consequently, the performance is not always as good as expected. To improve the performance of multi-class classification, this paper proposes an improved approach, called multi-state-mapping (MSM) with SVM based on hierarchical architecture, which maps the data set with all classes into different feature spaces at the different states of the decomposition of a multi-class classification problem in terms of a binary tree architecture. We prove that the computational complexity of MSM at its worst lies between that of the one-against-all scheme and one-against-one scheme. Substantial experiments have been conducted on sixteen UCI data sets to show the performance of our method. The statistical results show that MSM outperforms state-of-the-art methods in terms of accuracy and standard deviation.
Liu, C, Lei, G, Wang, T, Guo, Y, Wang, Y & Zhu, J 2017, 'Comparative Study of Small Electrical Machines With Soft Magnetic Composite Cores', IEEE Transactions on Industrial Electronics, vol. 64, no. 2, pp. 1049-1060.
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© 1982-2012 IEEE. In this paper, various kinds of electrical machines with soft magnetic composite (SMC) cores are compared, based on the qualitative and quantitative comparison methods. In the first part, the performances of five typical electrical machines with SMC cores are qualitatively compared. Simplified power equations for transverse flux, axial flux, and radial flux electrical machines are deduced to show the main difference among them and key design points of each machine. In the second part, the outer rotor claw pole machine (CPM) and outer rotor transverse flux machine (TFM) are comprehensively compared in a quantitative way, based on the three-dimensional finite-element method. It shows that the power capability of the outer rotor CPM is much higher than that of the TFM. On the other hand, the outer rotor CPM has higher cogging torque and no-load losses than the TFM. Furthermore, the four outer rotor radial flux machines are optimized and compared with the outer rotor CPM. The calculated results of the outer rotor TFM are compared with the experiment results, showing that the analysis results match well with the experiment ones. Several useful and interesting conclusions have been obtained for the electrical machines with SMC cores.
Liu, C, Talaei-Khoei, A, Zowghi, D & Daniel, J 2017, 'Data Completeness in Healthcare: A Literature Survey', PACIFIC ASIA JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS, vol. 9, no. 2, pp. 75-100.
Liu, C, Wang, Y, Lei, G, Guo, Y & Zhu, J 2017, 'Design and analysis of a 3D-flux flux-switching permanent magnet machine with SMC cores and ferrite magnets', AIP Advances, vol. 7, no. 5, pp. 056632-056632.
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Since permanent magnets (PM) are stacked between the adjacent stator teeth and there are no windings or PMs on the rotor, flux-switching permanent magnet machine (FSPMM) owns the merits of good flux concentrating and robust rotor structure. Compared with the traditional PM machines, FSPMM can provide higher torque density and better thermal dissipation ability. Combined with the soft magnetic composite (SMC) material and ferrite magnets, this paper proposes a new 3D-flux FSPMM (3DFFSPMM). The topology and operation principle are introduced. It can be found that the designed new 3DFFSPMM has many merits over than the traditional FSPMM for it can utilize the advantages of SMC material. Moreover, the PM flux of this new motor can be regulated by using the mechanical method. 3D finite element method (FEM) is used to calculate the magnetic field and parameters of the motor, such as flux density, inductance, PM flux linkage and efficiency map. The demagnetization analysis of the ferrite magnet is also addressed to ensure the safety operation of the proposed motor.
Liu, C, Zhang, YX & Ye, L 2017, 'High velocity impact responses of sandwich panels with metal fibre laminate skins and aluminium foam core', International Journal of Impact Engineering, vol. 100, pp. 139-153.
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Liu, F, Zhang, G & Lu, J 2017, 'Heterogeneous domain adaptation: An unsupervised approach', IEEE transactions on neural networks and learning systems, vol. 31, no. 12, pp. 5588-5602.
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Domain adaptation leverages the knowledge in one domain - the source domain -to improve learning efficiency in another domain - the target domain. Existingheterogeneous domain adaptation research is relatively well-progressed, butonly in situations where the target domain contains at least a few labeledinstances. In contrast, heterogeneous domain adaptation with an unlabeledtarget domain has not been well-studied. To contribute to the research in thisemerging field, this paper presents: (1) an unsupervised knowledge transfertheorem that guarantees the correctness of transferring knowledge; and (2) aprincipal angle-based metric to measure the distance between two pairs ofdomains: one pair comprises the original source and target domains and theother pair comprises two homogeneous representations of two domains. Thetheorem and the metric have been implemented in an innovative transfer model,called a Grassmann-Linear monotonic maps-geodesic flow kernel (GLG), that isspecifically designed for heterogeneous unsupervised domain adaptation (HeUDA).The linear monotonic maps meet the conditions of the theorem and are used toconstruct homogeneous representations of the heterogeneous domains. The metricshows the extent to which the homogeneous representations have preserved theinformation in the original source and target domains. By minimizing theproposed metric, the GLG model learns the homogeneous representations ofheterogeneous domains and transfers knowledge through these learnedrepresentations via a geodesic flow kernel. To evaluate the model, five publicdatasets were reorganized into ten HeUDA tasks across three applications:cancer detection, credit assessment, and text classification. The experimentsdemonstrate that the proposed model delivers superior performance over theexisting baselines.
Liu, H & Zhang, J-M 2017, 'Effect of two identical 3d transition-metal atoms M doping (M = V, Cr, Mn, Fe, Co, and Ni) on the structural, electronic, and magnetic properties of ZnO', physica status solidi (b), vol. 254, no. 10, pp. 1700098-1700098.
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Liu, H & Zhang, J-M 2017, 'Structural, electronic, magnetic and optical properties of Zn 1-x Ni x O from first-principles', Journal of Physics and Chemistry of Solids, vol. 104, pp. 267-275.
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Liu, H, Chen, J-G, Wang, C, Liu, Z-T, Li, Y, Liu, Z-W, Xiao, J & Lu, J 2017, 'Immobilization of Cyclometalated Iridium Complex onto Multiwalled Carbon Nanotubes for Dehydrogenation of Indolines in Aqueous Solution', Industrial & Engineering Chemistry Research, vol. 56, no. 40, pp. 11413-11421.
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Liu, J, Miao, Z, Ji, J & Zhou, J 2017, 'Group Regional Consensus of Networked Lagrangian Systems With Input Disturbances', Journal of Dynamic Systems, Measurement, and Control, vol. 139, no. 9.
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Networked multirobot systems under the coordinated control can perform tasks more effectively than a group of individually operating robots. This paper studies the group regional consensus of networked multirobot systems (formulated by second-order Lagrangian dynamics) having input disturbances under directed acyclic topology. An adaptive control protocol is designed to achieve group regional consensus of the networked Lagrangian systems with parametric uncertainties for both leader and leaderless cases. Sufficient conditions are established to guarantee group regional consensus for any prior given desired consensus errors. Compared with the existing work, a distinctive feature of the proposed control algorithm is that the stability analysis indicates the global validity of the obtained consensus results. Numerical examples are provided to demonstrate the effectiveness of the proposed scheme.
Liu, J, Wu, C & Chen, X 2017, 'Numerical study of ultra-high performance concrete under non-deformable projectile penetration', Construction and Building Materials, vol. 135, pp. 447-458.
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© 2017 Elsevier Ltd This paper presents a numerical study in evaluating impact response of ultra-high performance concrete (UHPC) cylinder targets under ogive-nosed projectile penetration with broad striking velocities from 300 m/s to 1000 m/s. Steel ogive-nosed projectiles with an average mass of 360 g are launched to penetrate UHPC cylinder targets with 750 mm diameter and 1000 mm length. The Karagozian & Case (K&C) cementitious material model, namely, MAT_Concrete_Damage_Rel3 (Mat_72R3), is implemented into finite element package LS-DYNA for UHPC. In order to accurately predict depth of penetration (DOP) and cratering damage of UHPC cylinder targets, uniaxial compressive and four-point bending testing results are used to validate 3D finite element material model. With the validated numerical model incorporating dynamic increase factors (DIF) of UHPC, parametric studies are conducted to investigate effects of UHPC compressive strength, projectile striking velocity and projectile caliber-radius-head (CRH) ratio on both DOP and cratering damage of UHPC targets. Moreover, an empirical formula to predict DOP is derived according to the simulated data.
Liu, J, Wu, C, Li, J, Su, Y, Shao, R, Liu, Z & Chen, G 2017, 'Experimental and numerical study of reactive powder concrete reinforced with steel wire mesh against projectile penetration', International Journal of Impact Engineering, vol. 109, pp. 131-149.
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© 2017 Elsevier Ltd This paper presents experimental and numerical studies on impact resistance of reactive powder concrete (RPC) targets reinforced with 44-layer steel wire meshes. Steel ogive-nosed projectiles with an average mass of 330 g and striking velocities ranging from 550 m/s to 800 m/s were launched against the cylindrical RPC targets with 750 mm diameter and 700 mm thickness. The impact responses observed in the tests, including depth of penetration (DOP), crater diameter and volume loss, were investigated and discussed, which indicates an effective impact resistance of steel wire mesh reinforced RPC in comparison with the previous studies on ultra-high performance based cement composites (UHPCC) with additions of fibres and basalt aggregates. Numerical studies based on validated material and element models are also conducted to simulate the impact responses of reinforced RPC targets against high-velocity projectile penetration in explicit hydro-code LS-DYNA. The impact responses, especially for the DOP, are well predicted by using the numerical models. Moreover, further investigation based on the verified numerical models is discussed in the present paper to explore the influence of mechanical and physical properties of steel wire mesh reinforcement on the resistance of projectile penetration.
Liu, K, Beck, D, Thoms, JAI, Liu, L, Zhao, W, Pimanda, JE & Zhou, X 2017, 'Annotating function to differentially expressed LincRNAs in myelodysplastic syndrome using a network-based method', Bioinformatics, vol. 33, no. 17, pp. 2622-2630.
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Abstract Motivation Long non-coding RNAs (lncRNAs) have been implicated in the regulation of diverse biological functions. The number of newly identified lncRNAs has increased dramatically in recent years but their expression and function have not yet been described from most diseases. To elucidate lncRNA function in human disease, we have developed a novel network based method (NLCFA) integrating correlations between lncRNA, protein coding genes and noncoding miRNAs. We have also integrated target gene associations and protein-protein interactions and designed our model to provide information on the combined influence of mRNAs, lncRNAs and miRNAs on cellular signal transduction networks. Results We have generated lncRNA expression profiles from the CD34+ haematopoietic stem and progenitor cells (HSPCs) from patients with Myelodysplastic syndromes (MDS) and healthy donors. We report, for the first time, aberrantly expressed lncRNAs in MDS and further prioritize biologically relevant lncRNAs using the NLCFA. Taken together, our data suggests that aberrant levels of specific lncRNAs are intimately involved in network modules that control multiple cancer-associated signalling pathways and cellular processes. Importantly, our method can be applied to prioritize aberrantly expressed lncRNAs for functional validation in other diseases and biological contexts. Availability and implementation The method is implemented in R language and Matlab. Supplementary information ...
Liu, K, Law, SS & Zhu, XQ 2017, 'System parameter identification from projection of inverse analysis', Journal of Sound and Vibration, vol. 396, pp. 83-107.
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© 2017 Elsevier Ltd The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.
Liu, M, Dou, W & Yu, S 2017, 'How to shutdown a cloud: a DDoS attack in a private infrastructure-as-a-service cloud', International Journal of Autonomous and Adaptive Communications Systems, vol. 10, no. 1, pp. 1-1.
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Cloud computing has become a hot spot in both industry and academia due to its rapid elasticity and on demand service. However, with outsourcing the data and business applications to a third party, security and privacy issues have become a critical concern. To decrease cloud availability, which is one of the most representative security attributes, DDoS attacks can be launched. In this paper, we try to show how a hacker can launch a DDoS attack based on virtual machine (VM) co-residence to deny the service of cloud data centre in a private infrastructure-as-a-service (IaaS) cloud. We first introduce how to launch this attack. Then we build a Markov-chain model to simulate this attack and analyse performance of cloud data centre. Finally, we also conduct several experiments to show how VM co-residence has impact on performance of physical machines (PMs).
Liu, MD & Indraratna, B 2017, 'Strength Criterion for Intact Rock', Indian Geotechnical Journal, vol. 47, no. 3, pp. 261-264.
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© 2016, Indian Geotechnical Society. Based on studies of the peak strength for soil by the authors, a simple strength criterion for intact rock is obtained in the general principal stress space. There are two material parameters in the equation. One is the uniaxial compression strength of the rock; the other describes the influence of stress level, and similar parameters are well studied in soil mechanics. It is seen that the proposed general strength criterion represents well the strength of various rocks and can provide a useful tool for geotechnical engineering practice.
Liu, T, Ma, B, Chen, X, Ni, B-J, Peng, Y & Guo, J 2017, 'Evaluation of mainstream nitrogen removal by simultaneous partial nitrification, anammox and denitrification (SNAD) process in a granule-based reactor', Chemical Engineering Journal, vol. 327, pp. 973-981.
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© 2017 Elsevier B.V. The mainstream anaerobic ammonium oxidation (anammox) has attracted extensive attention recently, particularly due to its potential of transforming current wastewater treatment plants from energy consuming to energy neutral or positive. However, the presence of biodegradable chemical oxygen demanding (COD, 20–80 mg COD L−1) in the mainstream anammox reactor stimulates the growth of heterotrophic bacteria, which would compete for oxygen with ammonia-oxidizing bacteria (AOB) and for nitrite with anammox bacteria, thus interfering with the autotrophic nitrogen removal process. In the present work, with consideration of granule size distribution, a one-dimensional model describing the mainstream simultaneous partial nitrification, anammox and denitrification (SNAD) in a granule-based reactor was established, calibrated and validated, based on the long-term experimental results. Through applying the verified model, simulation studies were conducted and the results showed that the effluent total nitrogen concentration of <5 mg N L−1 could be achieved at C/N ratio of 0.2–0.6, DO concentration of 0.2–0.4 mg L−1 and granule radius of 300–600 μm. The combined effects indicated that the SNAD process with TN removal efficiency >90% was obtained at C/N ratio and DO concentration of 0.2–1.0 and 0.2–0.4 mg O2 L−1 respectively. Finally, the various granule size distribution patterns were simulated, which confirmed that the size distribution needed to be incorporated in the model to accurately describe the granular anammox system, considering a model based on a uniform granule size does not reflect the real situations. These results provide guides to optimize the operation of mainstream granular autotrophic nitrogen removal process.
Liu, W & Tsang, IW 2017, 'Making decision trees feasible in ultrahigh feature and label dimensions', Journal of Machine Learning Research, vol. 18, pp. 1-36.
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Due to the non-linear but highly interpretable representations, decision tree (DT) models have significantly attracted a lot of attention of researchers. However, it is difficult to understand and interpret DT models in ultrahigh dimensions and DT models usually suffer from the curse of dimensionality and achieve degenerated performance when there are many noisy features. To address these issues, this paper first presents a novel data-dependent generalization error bound for the perceptron decision tree (PDT), which provides the theoretical justification to learn a sparse linear hyperplane in each decision node and to prune the tree. Following our analysis, we introduce the notion of budget-aware classifier (BAC) with a budget constraint on the weight coefficients, and propose a supervised budgeted tree (SBT) algorithm to achieve non-linear prediction performance. To avoid generating an unstable and complicated decision tree and improve the generalization of the SBT, we present a pruning strategy by learning classifiers to minimize cross-validation errors on each BAC. To deal with ultrahigh label dimensions, based on three important phenomena of real-world data sets from a variety of application domains, we develop a sparse coding tree framework for multi-label annotation problems and provide the theoretical analysis. Extensive empirical studies verify that 1) SBT is easy to understand and interpret in ultrahigh dimensions and is more resilient to noisy features. 2) Compared with state-of-the-art algorithms, our proposed sparse coding tree framework is more efficient, yet accurate in ultrahigh label and feature dimensions.
Liu, W, Chen, X, Yang, J & Wu, Q 2017, 'Robust Color Guided Depth Map Restoration', IEEE Transactions on Image Processing, vol. 26, no. 1, pp. 315-327.
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© 1992-2012 IEEE. One of the most challenging issues in color guided depth map restoration is the inconsistency between color edges in guidance color images and depth discontinuities on depth maps. This makes the restored depth map suffer from texture copy artifacts and blurring depth discontinuities. To handle this problem, most state-of-the-art methods design complex guidance weight based on guidance color images and heuristically make use of the bicubic interpolation of the input depth map. In this paper, we show that using bicubic interpolated depth map can blur depth discontinuities when the upsampling factor is large and the input depth map contains large holes and heavy noise. In contrast, we propose a robust optimization framework for color guided depth map restoration. By adopting a robust penalty function to model the smoothness term of our model, we show that the proposed method is robust against the inconsistency between color edges and depth discontinuities even when we use simple guidance weight. To the best of our knowledge, we are the first to solve this problem with a principled mathematical formulation rather than previous heuristic weighting schemes. The proposed robust method performs well in suppressing texture copy artifacts. Moreover, it can better preserve sharp depth discontinuities than previous heuristic weighting schemes. Through comprehensive experiments on both simulated data and real data, we show promising performance of the proposed method.
Liu, W, Chen, X, Yang, J & Wu, Q 2017, 'Variable Bandwidth Weighting for Texture Copy Artifact Suppression in Guided Depth Upsampling', IEEE Transactions on Circuits and Systems for Video Technology, vol. 27, no. 10, pp. 2072-2085.
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© 2017 IEEE. In this paper, we mathematically analyze one of the most challenging issues in color image-guided depth upsampling: the texture copy artifacts. The optimal guidance weights denoted by balanced weights are proposed to best suppress texture copy artifacts. To both suppress texture copy artifacts and preserve depth discontinuities, a new general weighting scheme called variable bandwidth weighting is proposed. The variable bandwidth weighting scheme is able to adjust guidance weights according to the local depth smoothness. A new concept called relative smoothness is proposed for measuring the local depth smoothness. Given this quantitative smoothness measurement, the proposed weighting scheme can adaptively adjust the bandwidth for calculating the guidance weights in the existing methods. As we use the computationally efficient balanced weights instead of the guidance weights of a large bandwidth, the proposed method can speed up the upsampling process for about 2× ∼ 5× when compared with the original upsampling methods. Experimental results show the effectiveness and efficiency of the proposed method in suppressing texture copy artifacts, preserving the depth discontinuities and reducing the computational cost at the same time.
Liu, W, Gao, Y, Ma, H, Yu, S & Nie, J 2017, 'Online multi-objective optimization for live video forwarding across video data centers', Journal of Visual Communication and Image Representation, vol. 48, pp. 502-513.
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The proliferation of video surveillance has led to surveillance video forwarding services becoming a basic server in video data centers. End users in diverse locations require live video streams from the IP cameras through the inter-connected video data centers. Consequently, the resource scheduler, which is set up to assign the resources of the video data centers to each arriving end user, is in urgent need of achieving the global optimal resource cost and forwarding delay. In this paper, we propose a multi-objective resource provisioning (MORP) approach to minimize the resource provisioning cost during live video forwarding. Different from existed works, the MORP optimizes the resource provisioning cost from both the resource cost and forwarding delay. Moreover, as an approximate optimal approach, MORP adaptively assigns the proper media servers among video data centers, and connects these media servers together through network connections to provide system scalability and connectivity. Finally, we prove that the computational complexity of our online approach is only O(log(|U|)) (|U| is the number of arrival end users). The comprehensive evaluations show that our approach not only significantly reduces the resource provisioning cost, but also has a considerably shorter computational delay compared to the benchmark approaches.
Liu, W, Luo, X, Xuan, J, Jiang, D & Xu, Z 2017, 'Association link network based semantic coherence measurement for short texts of web events', Journal of Web Engineering, vol. 16, no. 1-2, pp. 39-62.
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As novel web social Media emerges on the web, large-scale short texts are springing up. Although these massive short texts contain rich information, their disorder nature makes users difficult to obtain the desired knowledge from them, especially the semantic coherent knowledge. Different orders of these short texts often express different semantic coherence states. Therefore, how to automatically measure semantic coherence of short texts is a fundamental and significant problem for web knowledge services. Existing related works on the semantic coherence measurement of different orders of short texts/sentences seldom focus on graph structure of semantic link network for reecting coherence change, measuring coherence by these graph-based features and discovering some interesting coherence patterns. In this paper, we propose an association link network based semantic coherence measurement for short texts of web events. Our method firstly construct an association link network from which some graph-based features are then extracted to measure semantic coherence of different orders and lastly some coherence patterns are discovered for guiding automatically text ordering/generation. To validate correctness of our method, we conduct a series of experiments including sentence order permutation, sentence removal and adding/replacing sentence and compare with other two methods. The results show that our method can measure semantic coherence with higher accuracy and outperforms other methods in some experiments. Such method can be widely applied in web text automatic generation, web short text organization and web event summarization etc.
Liu, W, Luo, X, Zhang, J, Xue, R & Xu, RYD 2017, 'Semantic summary automatic generation in news event', Concurrency and Computation: Practice and Experience, vol. 29, no. 24, pp. e4287-e4287.
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SummaryHow to generate summary with more novel and rich semantics is a challenging issue in the area of multi‐document automatic summary. In this paper, a core semantics extraction model (CSEM) is proposed to improve the novel and rich semantics of multi‐document summary. Firstly, for improving the rich semantics, semantic units, which are a group of association relations of keywords, are used to express texts' semantics. Secondly, for improving the novel semantics, an attenuation function is introduced to adjust the importance of semantic units according to the appearing times that semantic units in the candidate of summary sentences. Thirdly, in order to maximize the novel and rich semantics of summary, the generating process of summary is converted into the optimization process on how to find a set of sentences with a higher importance. Finally, CSEM extracts the least number of sentences to cover the most core semantics in corpus as summary. Experimental results on the benchmark DUC 2004 show that our model outperforms the state‐of‐art approaches (eg, OCCAMS_V, JS‐Gen‐2) under official metric. Especially, the recall of our model in ROUGE‐1 is 40.684%, which is better than other approaches (eg, OCCAMS_V 38.497% and JS‐Gen‐2 36.739%).
Liu, W, Tsang, IW & Müller, KR 2017, 'An easy-to-hard learning paradigm for multiple classes and multiple labels', Journal of Machine Learning Research, vol. 18, no. 94, pp. 1-38.
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Many applications, such as human action recognition and object detection, can be formulated as a multiclass classification problem. One-vs-rest (OVR) is one of the most widely used approaches for multiclass classification due to its simplicity and excellent performance. However, many confusing classes in such applications will degrade its results. For example, hand clap and boxing are two confusing actions. Hand clap is easily misclassified as boxing, and vice versa. Therefore, precisely classifying confusing classes remains a challenging task. To obtain better performance for multiclass classifications that have confusing classes, we first develop a classifier chain model for multiclass classification (CCMC) to transfer class information between classifiers. Then, based on an analysis of our proposed model, we propose an easy-to-hard learning paradigm for multiclass classification to automatically identify easy and hard classes and then use the predictions from simpler classes to help solve harder classes. Similar to CCMC, the classifier chain (CC) model is also proposed by Read et al. (2009) to capture the label dependency for multi-label classification. However, CC does not consider the order of difficulty of the labels and achieves degenerated performance when there are many confusing labels. Therefore, it is non-trivial to learn the appropriate label order for CC. Motivated by our analysis for CCMC, we also propose the easy-to-hard learning paradigm for multi-label classi cation to automatically identify easy and hard labels, and then use the predictions from simpler labels to help solve harder labels. We also demonstrate that our proposed strategy can be successfully applied to a wide range of applications, such as ordinal classi cation and relationship prediction. Extensive empirical studies validate our analysis and the e-ectiveness of our proposed easy-to-hard learning strategies.
Liu, X, Lv, J, Gao, C, Chen, Z, Guo, Y, Gao, Z & Tai, B 2017, 'A Novel Diode-Clamped Modular Multilevel Converter With Simplified Capacitor Voltage-Balancing Control', IEEE Transactions on Industrial Electronics, vol. 64, no. 11, pp. 8843-8854.
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© 1982-2012 IEEE. Multilevel converters have become very attractive for high-voltage-level power conversion in renewable power generation applications. The converter topology is an important issue in the studies of multilevel converter. Many multilevel topologies have been developed, but few of them are qualified with capacitor voltage self-balancing capability. This paper proposes a novel diode-clamped modular multilevel converter with simplified capacitor voltage-balancing control. In this topology, low-power rating diodes are used to clamp the capacitor voltages of the converter. Only the top submodule in each arm of the converter requires capacitor voltage control. Consequently, very few voltage sensors are needed for voltage control and the control computation burden is reduced greatly when the quantity of the submodules is high. A simple voltage-balancing control method with carrier phase-shifted modulation strategy is developed for this topology. Experiments based on a laboratory prototype were carried out and the results validated the capacitor-balancing performance of the proposed topology.
Liu, Y, Huang, ML, Huang, W & Liang, J 2017, 'A physiognomy based method for facial feature extraction and recognition', Journal of Visual Languages & Computing, vol. 43, pp. 103-109.
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© 2017 Elsevier Ltd This paper proposes a novel calculation method of personality based on Chinese physiognomy. The proposed solution combines ancient and modern physiognomy to understand the relationship between personality and facial features and to model a baseline to shape facial features. We compute a histogram of image by searching for threshold values to create a binary image in an adaptive way. The two-pass connected component method indicates the feature's region. We encode the binary image to remove the noise point, so that the new connected image can provide a better result. According to our analysis of contours, we can locate facial features and classify them by means of a calculation method. The number of clusters is decided by a model and the facial feature contours are classified by using the k-means method. The validity of our method was tested on a face database and demonstrated by a comparative experiment.
Liu, Y, Ngo, HH, Guo, W, Sun, J, Wang, D, Peng, L & Ni, B-J 2017, 'Modeling aerobic biotransformation of vinyl chloride by vinyl chloride-assimilating bacteria, methanotrophs and ethenotrophs', Journal of Hazardous Materials, vol. 332, pp. 97-103.
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© 2017 Elsevier B.V. Recent studies have investigated the potential of enhanced groundwater Vinyl Chloride (VC) remediation in the presence of methane and ethene through the interactions of VC-assimilating bacteria, methanotrophs and ethenotrophs. In this study, a mathematical model was developed to describe aerobic biotransformation of VC in the presence of methane and ethene for the first time. It examines the metabolism of VC by VC-assimilating bacteria as well as cometabolism of VC by both methanotrophs and ethenotrophs, using methane and ethene respectively, under aerobic conditions. The developed model was successfully calibrated and validated using experimental data from microcosms with different experimental conditions. The model satisfactorily describes VC, methane and ethene dynamics in all microcosms tested. Modeling results describe that methanotrophic cometabolism of ethene promotes ethenotrophic VC cometabolism, which significantly enhances aerobic VC degradation in the presence of methane and ethene. This model is expected to be a useful tool to support effective and efficient processes for groundwater VC remediation.
Liu, Y, Ngo, HH, Guo, W, Zhou, J, Peng, L, Wang, D, Chen, X, Sun, J & Ni, B-J 2017, 'Optimizing sulfur-driven mixotrophic denitrification process: System performance and nitrous oxide emission', Chemical Engineering Science, vol. 172, pp. 414-422.
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© 2017 Nitrate contamination of groundwater has been recognized as a significant environmental problem world widely. Sulfur-driven mixotrophic denitrification has been demonstrated as a promising groundwater treatment process, which though plays an important role in nitrous oxide (N2O) emissions, significantly contributing to the overall carbon footprint of the system. However, the current process optimizations only focus on nitrate removal and excess sulfate control, with the N2O emission being ignored. In this work, an integrated mathematical model was proposed to evaluate the N2O emission as well as the excess sulfate production and carbon source utilization in sulfur-driven mixotrophic denitrification process. In this model, autotrophic and heterotrophic denitrifiers use their corresponding electron donors (sulfur and organic matter, respectively) to reduce nitrate to nitrogen gas, with each modeled as three-step denitrification (NO3− to N2 via NO2− and N2O) driven by sulfur or organic matter to describe all potential N2O accumulation steps. The developed model, employing model parameters previously reported in literature, was successfully validated using N2O and sulfate data from two mixotrophic denitrification systems with different initial conditions. Modeling results revealed substantial N2O accumulation due to the relatively low autotrophic N2O reduction activity as compared to heterotrophic N2O reduction activity, explaining the observation that higher carbon source addition resulted in lower N2O accumulation in sulfur-driven mixotrophic denitrifying system. Based on the validated model, optimizations of the overall system performance were carried out. Application of the model to simulate long-term operations of sulfur-driven mixotrophic denitrification process indicates that longer sludge retention time reduces N2O emission due to better retention of active biomass. High-level total nitrogen removal with significant N2O emission mitigation, a...
Liu, Y, Pan, Y, Huang, D & Wang, Q 2017, 'Fault prognosis of filamentous sludge bulking using an enhanced multi-output gaussian processes regression', Control Engineering Practice, vol. 62, pp. 46-54.
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The activated sludge process (ASP) is widely adopted to remove pollutants in wastewater treatment plants (WWTPs). However, the occurrence of filamentous sludge bulking often compromises the stable operation of the ASP. For timely diagnosis of filamentous sludge bulking for an activated sludge process in advance, this study proposed a Multi-Output Gaussian Processes Regression (MGPR) model for multi-step prediction and presented the Vector auto-regression (VAR) to learn the MGPR modelling deviation. The resulting models and associated uncertainty levels are used to monitor the filamentous sludge bulking related parameter, sludge volume index (SVI), such that the evolution of SVI can be predicted for both one-step and multi-step ahead. This methodology was validated with SVI data collected from one full-scale WWTP. Online diagnosis and prognosis of filamentous bulking sludge with real-time SVI prediction were tested through a simulation study. The results demonstrated that the proposed methodology was capable of predicting future SVI with good accuracy, thereby providing sufficient time for filamentous sludge bulking.
Liu, Y, Peng, H, Wong, L & Li, J 2017, 'High-speed and high-ratio referential genome compression', Bioinformatics, vol. 33, no. 21, pp. 3364-3372.
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Abstract Motivation The rapidly increasing number of genomes generated by high-throughput sequencing platforms and assembly algorithms is accompanied by problems in data storage, compression and communication. Traditional compression algorithms are unable to meet the demand of high compression ratio due to the intrinsic challenging features of DNA sequences such as small alphabet size, frequent repeats and palindromes. Reference-based lossless compression, by which only the differences between two similar genomes are stored, is a promising approach with high compression ratio. Results We present a high-performance referential genome compression algorithm named HiRGC. It is based on a 2-bit encoding scheme and an advanced greedy-matching search on a hash table. We compare the performance of HiRGC with four state-of-the-art compression methods on a benchmark dataset of eight human genomes. HiRGC takes <30 min to compress about 21 gigabytes of each set of the seven target genomes into 96–260 megabytes, achieving compression ratios of 217 to 82 times. This performance is at least 1.9 times better than the best competing algorithm on its best case. Our compression speed is also at least 2.9 times faster. HiRGC is stable and robust to deal with different reference genomes. In contrast, the competing methods’ performance varies widely on different reference genomes. More experiments on 100 human genomes from the 1000 Genome Project and on genomes of several other species again demonstrate that HiRGC’s performance is consistently excellent. Availability and implementation The C +...
Liu, Y, Zhang, Y, Zhao, Z, Ngo, HH, Guo, W, Zhou, J, Peng, L & Ni, B-J 2017, 'A modeling approach to direct interspecies electron transfer process in anaerobic transformation of ethanol to methane', Environmental Science and Pollution Research, vol. 24, no. 1, pp. 855-863.
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© 2016, Springer-Verlag Berlin Heidelberg. Recent studies have shown that direct interspecies electron transfer (DIET) plays an important part in contributing to methane production from anaerobic digestion. However, so far anaerobic digestion models that have been proposed only consider two pathways for methane production, namely, acetoclastic methanogenesis and hydrogenotrophic methanogenesis, via indirect interspecies hydrogen transfer, which lacks an effective way for incorporating DIET into this paradigm. In this work, a new mathematical model is specifically developed to describe DIET process in anaerobic digestion through introducing extracellular electron transfer as a new pathway for methane production, taking anaerobic transformation of ethanol to methane as an example. The developed model was able to successfully predict experimental data on methane dynamics under different experimental conditions, supporting the validity of the developed model. Modeling predictions clearly demonstrated that DIET plays an important role in contributing to overall methane production (up to 33 %) and conductive material (i.e., carbon cloth) addition would significantly promote DIET through increasing ethanol conversion rate and methane production rate. The model developed in this work will potentially enhance our current understanding on syntrophic metabolism via DIET.
Liu, Y-T, Pal, NR, Marathe, AR, Wang, Y-K & Lin, C-T 2017, 'Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources', Frontiers in Neuroscience, vol. 11, no. JUN, pp. 1-10.
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© 2017 Liu, Pal, Marathe, Wang and Lin. A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance...
Liu, Z, Ju, X, Wu, C & Liang, J 2017, 'Scattering of plane P 1 waves and dynamic stress concentration by a lined tunnel in a fluid-saturated poroelastic half-space', Tunnelling and Underground Space Technology, vol. 67, pp. 71-84.
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Liu, Z, Liang, J, Wu, C, Zhao, R & Li, Y 2017, 'The method of fundamental solution for elastic wave scattering and dynamic stress concentration in a fluid-saturated poroelastic layered half-plane', Engineering Analysis with Boundary Elements, vol. 84, pp. 154-167.
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© 2017 Elsevier Ltd A meshless method based on the method of fundamental solution (MFS) is developed to solve elastic-wave scattering and dynamic stress concentration in a fluid-saturated poroelastic layered half-plane, by utilizing the line sources of cylindrical P I , P II , and SV waves in a poroelastic layered half-plane. The numerical accuracy and stability of the MFS is verified by examining the boundary conditions and comparison with other methods. Subsequently, the amplification effects on displacement, surface hoop stress and fluid pore pressure around a cavity in a three-layered poroelastic half-plane are investigated. Numerical results indicate that the scattering characteristics strongly depend on parameters including the incident frequency and angle, soil-layer porosity and boundary drainage condition. The amplification effects of a cavity in the poroelastic layered half-plane appear to be more significant than the corresponding case of a homogenous half-plane. The amplitude of the fluid pore pressure on the surface of the cavity is amplified up to five times that of the free field, which also considerably aggravates the dynamic stress concentration around the cavity.
Liu, Z, Wang, L, Wang, J, Dong, D & Hu, X 2017, 'Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks', Automatica, vol. 77, pp. 170-179.
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Llopis-Albert, C, Merigó, JM, Xu, Y & Liao, H 2017, 'Improving Regional Climate Projections by Prioritized Aggregation via Ordered Weighted Averaging Operators', Environmental Engineering Science, vol. 34, no. 12, pp. 880-886.
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© Copyright 2017, Mary Ann Liebert, Inc. 2017. Decision makers express a strong need for reliable information on future climate changes to develop with the best mitigation and adaptation strategies to address impacts. These decisions are based on future climate projections that are simulated by using different Representative Concentration Pathways (RCPs), General Circulation Models (GCMs), and downscaling techniques to obtain high-resolution Regional Climate Models. RCPs defined by the Intergovernmental Panel on Climate Change entail a certain combination of the underlying driving forces behind climate and land use/land cover changes, which leads to different anthropogenic Greenhouse Gases concentration trajectories. Projections of global and regional climate change should also take into account relevant sources of uncertainty and stakeholders' risk attitudes when defining climate polices. The goal of this article is to improve regional climate projections by their prioritized aggregation through the ordered weighted averaging (OWA) operator. The aggregated projection is achieved by considering the similarity of the projections obtained by combining different GCMs, RCPs, and downscaling techniques. Relative weights of different projections to be aggregated by the OWA operator are obtained by regular increasing monotone fuzzy quantifiers, which enables modeling the stakeholders' risk attitudes. The methodology provides a robust decision-making tool to evaluate performance of future climate projections and to design sustainable policies under uncertainty and risk tolerance, which has been successfully applied to a real-case study.
Loganathan, P, Naidu, G & Vigneswaran, S 2017, 'Mining valuable minerals from seawater: a critical review', Environmental Science: Water Research & Technology, vol. 3, no. 1, pp. 37-53.
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Methods of extracting valuable minerals from seawater and seawater brines generated in desalination plants are critically reviewed in this paper.
Lotfi, F, Chekli, L, Phuntsho, S, Hong, S, Choi, JY & Shon, HK 2017, 'Understanding the possible underlying mechanisms for low fouling tendency of the forward osmosis and pressure assisted osmosis processes', Desalination, vol. 421, pp. 89-98.
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© 2017 Elsevier B.V. We investigated the possible underlying mechanism of the low fouling potential in the forward osmosis (FO) process during the osmotic dilution of seawater as part of the simultaneous desalination and wastewater reuse by FO and reverse osmosis hybrid system. Long-term experiments revealed an interesting water flux pattern highly dependent on the different operating parameters. The most interesting observation made was the spontaneous increase in the FO permeate flux at regular time interval during the FO operation using synthetic wastewater as feed and seawater. This sinusoidal FO flux pattern related well with the build-up of loose fouling layer and their natural peel-off from the membrane surface upon reaching certain layer thickness due to crossflow velocity shear. This flux pattern was more prominent at higher cross-flow velocity rates, lower feed water pH, for a smoother membrane surface and at lower operating pressure during pressure assisted osmosis (PAO) mode. Based on these results, membrane cleaning strategies were proposed by targeting a higher cross-flow velocity shear at a time when the permeate flux started to just increase. The approach of physical membrane cleaning was observed efficient and was able to almost fully restore the initial flux even under the PAO operation at 4 bar.
Lu, D, Sang, J, Chen, Z, Xu, M & Mei, T 2017, 'Who Are Your “Real” Friends: Analyzing and Distinguishing Between Offline and Online Friendships From Social Multimedia Data', IEEE Transactions on Multimedia, vol. 19, no. 6, pp. 1299-1313.
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Lu, L, Sun, H, Wu, M, Zhu, Q & Yang, J 2017, 'A modified electro-acoustical reciprocity method for measuring low-frequency sound source in arbitrary surroundings', Applied Acoustics, vol. 116, pp. 1-8.
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Lu, M, Lai, C, Ye, T, Liang, J & Yuan, X 2017, 'Visual Analysis of Multiple Route Choices Based on General GPS Trajectories', IEEE Transactions on Big Data, vol. 3, no. 2, pp. 234-247.
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There are often multiple routes between regions. Drivers choose different routes with different considerations. Such considerations, have always been a point of interest in the transportation area. Studies of route choice behaviour are usually based on small range experiments with a group of volunteers. However, the experiment data is quite limited in its spatial and temporal scale as well as the practical reliability. In this work, we explore the possibility of studying route choice behaviour based on general trajectory dataset, which is more realistic in a wider scale. We develop a visual analytic system to help users handle the large-scale trajectory data, compare different route choices, and explore the underlying reasons. Specifically, the system consists of: 1. the interactive trajectory filtering which supports graphical trajectory query; 2. the spatial visualization which gives an overview of all feasible routes extracted from filtered trajectories; 3. the factor visual analytics which provides the exploration and hypothesis construction of different factors' impact on route choice behaviour, and the verification with an integrated route choice model. Applying to real taxi GPS dataset, we report the system's performance and demonstrate its effectiveness with three cases.
Lu, Z, Chen, Y, Dunstan, C, Roohani-Esfahani, S & Zreiqat, H 2017, 'Priming Adipose Stem Cells with Tumor Necrosis Factor-Alpha Preconditioning Potentiates Their Exosome Efficacy for Bone Regeneration', Tissue Engineering Part A, vol. 23, no. 21-22, pp. 1212-1220.
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Lund, AP, Bremner, MJ & Ralph, TC 2017, 'Quantum Sampling Problems, BosonSampling and Quantum Supremacy', npj Quantum Information (2017) 3:15, vol. 3, no. 1, pp. 1-8.
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There is a large body of evidence for the potential of greater computationalpower using information carriers that are quantum mechanical over thosegoverned by the laws of classical mechanics. But the question of the exactnature of the power contributed by quantum mechanics remains only partiallyanswered. Furthermore, there exists doubt over the practicality of achieving alarge enough quantum computation that definitively demonstrates quantumsupremacy. Recently the study of computational problems that produce samplesfrom probability distributions has added to both our understanding of the powerof quantum algorithms and lowered the requirements for demonstration of fastquantum algorithms. The proposed quantum sampling problems do not require aquantum computer capable of universal operations and also permit physicallyrealistic errors in their operation. This is an encouraging step towards anexperimental demonstration of quantum algorithmic supremacy. In this paper, wewill review sampling problems and the arguments that have been used to deducewhen sampling problems are hard for classical computers to simulate. Twoclasses of quantum sampling problems that demonstrate the supremacy of quantumalgorithms are BosonSampling and IQP Sampling. We will present the details ofthese classes and recent experimental progress towards demonstrating quantumsupremacy in BosonSampling.
Luo, L, Duan, N, Wang, XC, Guo, W & Ngo, HH 2017, 'New thermodynamic entropy calculation based approach towards quantifying the impact of eutrophication on water environment', Science of The Total Environment, vol. 603-604, pp. 86-93.
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Luo, L, Jiang, Z & Wei, D 2017, 'Influences of micro-friction on surface finish in micro deep drawing of SUS304 cups', Wear, vol. 374-375, pp. 36-45.
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© 2017 Elsevier B.V. Surface asperities take a large part of a thin blank in micro-sheet forming processes. Contact and friction significantly affect micro-sheet forming and cannot be simplified as homogeneous in simulation. Material heterogeneity of the blank further affects the friction and its impact becomes significant in micro-scale. In this study, a FE model representing surface morphology of SUS304 sheets was built for micro deep drawing simulation. Each node on the blank model had the same height as an asperity. Key surface morphological characters of the blank can be presented with a proper mesh density. The material size effects were presented via refined material properties assignment based on sheets’ microstructures. Due to the initial surface morphology, wear accumulation and thickness distribution were significantly affected. Experimental results well validated prediction of worst worn area on drawn cup mouth in simulation. Surface roughening which affects shape accuracy in the micro-scale was affected by the wear behaviour during the drawing process. Thus, different roughening behaviours at three divided areas on the drawn cup were wall explained.
Luo, L, Jiang, Z & Wei, D 2017, 'Reprint of ‘‘Influences of micro-friction on surface finish in micro deep drawing of SUS304 cups’’', Wear, vol. 376-377, pp. 1147-1155.
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© 2017 Elsevier B.V. Surface asperities take a large part of a thin blank in micro-sheet forming processes. Contact and friction significantly affect micro-sheet forming and cannot be simplified as homogeneous in simulation. Material heterogeneity of the blank further affects the friction and its impact becomes significant in micro-scale. In this study, a FE model representing surface morphology of SUS304 sheets was built for micro deep drawing simulation. Each node on the blank model had the same height as an asperity. Key surface morphological characters of the blank can be presented with a proper mesh density. The material size effects were presented via refined material properties assignment based on sheets' microstructures. Due to the initial surface morphology, wear accumulation and thickness distribution were significantly affected. Experimental results well validated prediction of worst worn area on drawn cup mouth in simulation. Surface roughening which affects shape accuracy in the micro-scale was affected by the wear behaviour during the drawing process. Thus, different roughening behaviours at three divided areas on the drawn cup were wall explained.
Luo, L, Jiang, ZY, Wei, DB, Sato, H, Furushima, T & Manabe, K 2017, 'Effects of Hydraulic Pressure on Shape Accuracy of Drawn Circular Cups during Micro Hydro Deep Drawing', Materials Science Forum, vol. 879, pp. 2274-2279.
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Micro hydro deep drawing is a promising technology to fabricate micro metal products with complex 3D shapes. However, the size effects in the micro hydro deep drawing become considerable and significantly influence shape accuracy of drawn cups. In this study, a Voronoi micro scale simulation model was developed to consider the size effects of SUS304 foils. A surface layer model was additionally applied in the simulation to further explain the size effects. The micro hydro deep drawing experiments were conducted with annealed SUS304 foils and the drawn cups were examined. The wrinkling phenomenon was generally aggravated with the hydraulic pressure. Simulation results also show that the high hydraulic pressure does not improve the shape accuracy of the drawn cups as that in the normal scale hydro deep dawning process does. The simulation results are in accordance with the experimental results.
Luo, L, Wei, D, Jiang, Z, Zhou, C, Huang, Q & Huang, Z 2017, 'Study of micro hydromechanical deep drawing of SUS304 circular cups by an ALE model', Procedia Engineering, vol. 207, pp. 1039-1044.
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© 2017 The Authors. Published by Elsevier Ltd. Accurate estimation of hydraulic pressure on the blank is important for micro hydromechanical deep drawing simulation. An Arbitrary Lagrange Eulerian (ALE) simulation model that considers strong fluid-solid interaction (FSI) was generated to accurately predict the hydraulic pressure on the blank. The changeable pressure significantly affects the drawn cup's quality regarding wall thickness. Both the minimum and the maximum wall thicknesses in the ALE model are significantly different from that in a conventional model with a simple pressure load. The relationship between the maximum thickness and the hydraulic pressure in the ALE model is similar to that from the experimental results while reverse to that from the conventional simulation model. The ALE model provides more precise hydraulic pressure on the blank and accurate prediction of the drawn cups' quality compared with the conventional model.
Luo, L, Wei, D, Wang, X, Zhou, C, Huang, Q, Xu, J, Wu, D & Jiang, Z 2017, 'Effects of hydraulic pressure on wrinkling and earing in micro hydro deep drawing of SUS304 circular cups', The International Journal of Advanced Manufacturing Technology, vol. 90, no. 1-4, pp. 189-197.
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© 2016, Springer-Verlag London. Influences of hydraulic pressure on forming features in micro hydro deep drawing are different from those in normal drawing due to the small size of specimens. In this study, micro hydro deep drawing of SUS304 sheets was carried out in order to study the impacts of the hydraulic pressure on the quality of the drawn cup. Experimental results indicate that there is a critical hydraulic pressure range from 3 to 6 % of the blank’s initial yield stress, where wrinkling and earing development trends change twice. The wrinkling and the earing of the drawn cup also reach their local extremes in the critical pressure range. The cup earing value moves in the opposite direction from the wrinkling value. Hydraulic pressure affects the wrinkling and the earing of the drawn cup through changes in the micro-frictional condition, the shape of the blank and its strain-stress state. Micro-finite element (FE) simulation which takes these factors as well as the material size effects into consideration showed similar results to the experimental ones, thus validating the experimental results and the suitability of the micro-simulation model for micro-forming FE simulation. The experimental and simulation results indicate that the critical hydraulic pressure based on the blank’s initial yield stress can restrict the wrinkling and the earing of the drawn cup. Ultra-high pressure has the potential to avoid the cup wrinkling and earing.
Luo, M, Chang, X, Li, Z, Nie, L, Hauptmann, AG & Zheng, Q 2017, 'Simple to complex cross-modal learning to rank', Computer Vision and Image Understanding, vol. 163, pp. 67-77.
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© 2017 Elsevier Inc. The heterogeneity-gap between different modalities brings a significant challenge to multimedia information retrieval. Some studies formalize the cross-modal retrieval tasks as a ranking problem and learn a shared multi-modal embedding space to measure the cross-modality similarity. However, previous methods often establish the shared embedding space based on linear mapping functions which might not be sophisticated enough to reveal more complicated inter-modal correspondences. Additionally, current studies assume that the rankings are of equal importance, and thus all rankings are used simultaneously, or a small number of rankings are selected randomly to train the embedding space at each iteration. Such strategies, however, always suffer from outliers as well as reduced generalization capability due to their lack of insightful understanding of procedure of human cognition. In this paper, we involve the self-paced learning theory with diversity into the cross-modal learning to rank and learn an optimal multi-modal embedding space based on non-linear mapping functions. This strategy enhances the model's robustness to outliers and achieves better generalization via training the model gradually from easy rankings by diverse queries to more complex ones. An efficient alternative algorithm is exploited to solve the proposed challenging problem with fast convergence in practice. Extensive experimental results on several benchmark datasets indicate that the proposed method achieves significant improvements over the state-of-the-arts in this literature.
Luo, M, Nie, F, Chang, X, Yang, Y, Hauptmann, AG & Zheng, Q 2017, 'Avoiding Optimal Mean ℓ2,1-Norm Maximization-Based Robust PCA for Reconstruction', Neural Computation, vol. 29, no. 4, pp. 1124-1150.
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Robust principal component analysis (PCA) is one of the most important dimension-reduction techniques for handling high-dimensional data with outliers. However, most of the existing robust PCA presupposes that the mean of the data is zero and incorrectly utilizes the average of data as the optimal mean of robust PCA. In fact, this assumption holds only for the squared [Formula: see text]-norm-based traditional PCA. In this letter, we equivalently reformulate the objective of conventional PCA and learn the optimal projection directions by maximizing the sum of projected difference between each pair of instances based on [Formula: see text]-norm. The proposed method is robust to outliers and also invariant to rotation. More important, the reformulated objective not only automatically avoids the calculation of optimal mean and makes the assumption of centered data unnecessary, but also theoretically connects to the minimization of reconstruction error. To solve the proposed nonsmooth problem, we exploit an efficient optimization algorithm to soften the contributions from outliers by reweighting each data point iteratively. We theoretically analyze the convergence and computational complexity of the proposed algorithm. Extensive experimental results on several benchmark data sets illustrate the effectiveness and superiority of the proposed method.
Luo, Q & Tong, L 2017, 'A deformation mechanism based material model for topology optimization of laminated composite plates and shells', Composite Structures, vol. 159, pp. 246-256.
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Luo, W, Li, J, Yang, J, Xu, W & Zhang, J 2017, 'Convolutional Sparse Autoencoders for Image Classification', IEEE Transactions on Neural Networks and Learning Systems, pp. 1-6.
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Luo, W, Phan, HV, Li, G, Hai, FI, Price, WE, Elimelech, M & Nghiem, LD 2017, 'An Osmotic Membrane Bioreactor–Membrane Distillation System for Simultaneous Wastewater Reuse and Seawater Desalination: Performance and Implications', Environmental Science & Technology, vol. 51, no. 24, pp. 14311-14320.
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Luo, W, Phan, HV, Xie, M, Hai, FI, Price, WE, Elimelech, M & Nghiem, LD 2017, 'Osmotic versus conventional membrane bioreactors integrated with reverse osmosis for water reuse: Biological stability, membrane fouling, and contaminant removal', Water Research, vol. 109, pp. 122-134.
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This study systematically compares the performance of osmotic membrane bioreactor - reverse osmosis (OMBR-RO) and conventional membrane bioreactor - reverse osmosis (MBR-RO) for advanced wastewater treatment and water reuse. Both systems achieved effective removal of bulk organic matter and nutrients, and almost complete removal of all 31 trace organic contaminants investigated. They both could produce high quality water suitable for recycling applications. During OMBR-RO operation, salinity build-up in the bioreactor reduced the water flux and negatively impacted the system biological treatment by altering biomass characteristics and microbial community structure. In addition, the elevated salinity also increased soluble microbial products and extracellular polymeric substances in the mixed liquor, which induced fouling of the forward osmosis (FO) membrane. Nevertheless, microbial analysis indicated that salinity stress resulted in the development of halotolerant bacteria, consequently sustaining biodegradation in the OMBR system. By contrast, biological performance was relatively stable throughout conventional MBR-RO operation. Compared to conventional MBR-RO, the FO process effectively prevented foulants from permeating into the draw solution, thereby significantly reducing fouling of the downstream RO membrane in OMBR-RO operation. Accumulation of organic matter, including humic- and protein-like substances, as well as inorganic salts in the MBR effluent resulted in severe RO membrane fouling in conventional MBR-RO operation.
Luong, NC, Hoang, DT, Wang, P, Niyato, D & Han, Z 2017, 'Applications of Economic and Pricing Models for Wireless Network Security: A Survey', IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2735-2767.
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© 1998-2012 IEEE. This paper provides a comprehensive literature review on applications of economic and pricing theory to security issues in wireless networks. Unlike wireline networks, the broadcast nature and the highly dynamic change of network environments pose a number of nontrivial challenges to security design in wireless networks. While the security issues have not been completely solved by traditional or system-based solutions, economic and pricing models recently were employed as one efficient solution to discourage attackers and prevent attacks to be performed. In this paper, we review economic and pricing approaches proposed to address major security issues in wireless networks including eavesdropping attack, denial-of-service (DoS) attack such as jamming and distributed DoS, and illegitimate behaviors of malicious users. Additionally, we discuss integrating economic and pricing models with cryptography methods to reduce information privacy leakage as well as to guarantee the confidentiality and integrity of information in wireless networks. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to wireless security issues.
Lusis, P, Khalilpour, KR, Andrew, L & Liebman, A 2017, 'Short-term residential load forecasting: Impact of calendar effects and forecast granularity', Applied Energy, vol. 205, no. C, pp. 654-669.
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Literature is rich in methodologies for “aggregated” load forecasting which has helped electricity network operators and retailers in optimal planning and scheduling. The recent increase in the uptake of distributed generation and storage systems has generated new demand for “disaggregated” load forecasting for a single-customer or even down at an appliance level. Access to high resolution data from smart meters has enabled the research community to assess conventional load forecasting techniques and develop new forecasting strategies suitable for demand-side disaggregated loads.
Lynch, CR, Murphy, T, Kaplan, DL, Ireland, M & Bell, ME 2017, 'A search for circularly polarized emission from young exoplanets', Monthly Notices of the Royal Astronomical Society, vol. 467, no. 3, pp. 3447-3453.
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We report the results of a 154 MHz survey to search for emission from exoplanets located in the Upper Scorpius subgroup of the Sco Cen OB2 Association, the closest substantial region of recent star formation. This survey is different from previous efforts in that it is the first to target exoplanets orbiting Myr-old stars. Young exoplanet systems are expected to be the best candidates for radio detections given the higher magnetic field strengths predicted for young planets as well as the stronger and more dense stellar wind expected for the host stars. The radio emission from exoplanets is expected to be highly circularly polarized therefore we restricted our search to the circular polarization images rather than the total intensity images. We carried out two different search methods using this data. The first method was a targeted search for exoplanet emission using catalogues of known stars and Hot Jupiters within the Upper Scorpius field. The second search method was a blind search for highly circularly polarized sources in the field and for sources identified only in our polarization images. Both the blind and targeted search resulted in non-detections with typical 3σ flux density limits of 4–235 mJy over time-scales of 1.87–1000 min. In particular, we place the first limits on low-frequency emission from the Hot Jupiter systems WASP-17 b and K2-33 b. These are the first results from a larger program to systematically search for low-frequency radio emission from planets orbiting young stars.
Lyu, M, Zhu, X & Yang, Q 2017, 'Bilinear connection stiffness identification of heritage timber buildings with limited strain measurements', Engineering Structures, vol. 151, pp. 665-681.
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© 2017 Elsevier Ltd ‘Que-Ti’ is an important component connecting the beam and column in typical Tibetan historic timber buildings. It transfers shear, compression and bending moment by slippage and deformation of components as well as a limited joint rotation. A rigorous analytical model of ‘Que-Ti’ is needed for predicting the behaviour of a timber structure under loading. However, few researches have been conducted in this area, particularly on the effect of key parameters on the performance of the joint under loading. In this paper, a new method has been proposed to identify both the thermal load on the structure and the bilinear connection stiffness of the semi-rigid joint from limited measured strain responses by integrating the temperature-based response sensitivity analysis with the dual Kalman filter. A novel bilinear rotational spring model has been developed for the joint to take into account the friction slip at the interface, the shear in the tenon, and the gap between the tenon and the mortise of the ‘Que-Ti’ in typical heritage Tibetan buildings. The semi-rigid connection is modeled as two bilinear rotational springs and one compressive spring. The temperature is treated as the input of the structure and the thermal loading on the structure can be determined based on the proposed method. The numerical results show that the method is effective and reliable to identify the thermal loading, unknown boundary conditions and the connection stiffness of the ‘Que-Ti’ accurately even with 10% noise in measurements. A long-term monitoring system has also been installed in a typical heritage Tibetan building and the monitoring data have been used to further verify the method. The experimental results show that the identified stiffness by the proposed method with bilinear connection stiffness model can get better results than that with linear connection stiffness model.
Lyu, M, Zhu, X & Yang, Q 2017, 'Condition assessment of heritage timber buildings in operational environments', Journal of Civil Structural Health Monitoring, vol. 7, no. 4, pp. 505-516.
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© 2017, Springer-Verlag GmbH Germany. Due to changing environments and aging, the structural resistance of the heritage buildings has been reduced significantly. It has become crucial to monitor and protect the architectural heritage buildings. The objective of this research is to monitor and assess the performance of the heritage Tibetan timber building in operational environments. A three-storey corridor part of the typical heritage building was chosen in the study. A long-term monitoring system was installed in the building to collect the structural response and temperature. Detailed finite element model was built based on site investigation and existing documents, and updated based on the temperature-based response sensitivity using the field-monitoring data. The updated model was further evaluated using the static and dynamic analysis for condition assessment of the building in operational environments. The results show that the updated model is effective and accurate to predict the structural behaviour of the building in operational environments. Based on temperature-based response sensitivity, it is capable of tracking structure performance throughout the life-cycle allowing for condition-based maintenance and structural protection.
Lyu, M, Zhu, X & Yang, Q 2017, 'Connection stiffness identification of historic timber buildings using Temperature-based sensitivity analysis', Engineering Structures, vol. 131, pp. 180-191.
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© 2016 Elsevier Ltd The beam-column connection, called ‘Que Ti’, is the key component of historic Tibetan timber buildings to transfer shear, compression and bending loads from one structural element to another. This kind of connections can reduce the internal forces and improve the structure's ability to resist earthquakes. Its structure is very complicated and there is little information about the behaviour of this kind of semi-rigid connections. In this paper, a temperature-based response sensitivity method is proposed to identify the connection stiffness of the ‘Que-Ti’ in typical historical Tibetan buildings from temperature and strain response measurements. The semi-rigid connection is modeled as two rotational springs and one compressive spring. The temperature is treated as a measurable input and the thermal loading on the structure can be determined from the temperature variation. The numerical results show the method is effective and reliable to identify both unknown boundary conditions and the connection stiffness of the structure accurately even with 10% noise in measurements. A long-term monitoring system has also been installed in a typical historical Tibetan building and the monitoring data are used to further verify the proposed method. The experimental results show that the identified stiffnesses by the proposed method are consistent with that by finite element model updating from ambient vibration measurements.
Lyu, X, Ni, W, Tian, H, Liu, RP, Wang, X, Giannakis, GB & Paulraj, A 2017, 'Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information', IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, pp. 2606-2615.
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© 1983-2012 IEEE. Mobile edge computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can get complex tasks offloaded to and processed at powerful infrastructure. Scheduling is challenging due to stochastic task arrivals and wireless channels, congested air interface, and more prominently, prohibitive feedbacks from thousands of devices. In this paper, we generate asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks. A perturbed Lyapunov function is designed to stochastically maximize a network utility balancing throughput and fairness. A knapsack problem is solved per slot for the optimal schedule, provided up-to-date knowledge on the data and energy backlogs of all devices. The knapsack problem is relaxed to accommodate out-of-date network states. Encapsulating the optimal schedule under up-to-date network knowledge, the solution under partial out-of-date knowledge preserves asymptotic optimality, and allows devices to self-nominate for feedback. Corroborated by simulations, our approach is able to dramatically reduce feedbacks at no cost of optimality. The number of devices that need to feed back is reduced to less than 60 out of a total of 5000 IoT devices.
Lyu, X, Tian, H, Ni, W, Liu, RP & Zhang, P 2017, 'Adaptive Centralized Clustering Framework for Software-Defined Ultra-Dense Wireless Networks', IEEE Transactions on Vehicular Technology, vol. 66, no. 9, pp. 8553-8557.
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© 2017 IEEE. This paper develops a new centralized clustering framework to mitigate strong intercell interference in a software-defined ultra-dense network, where the number of clusters can be adapting to network conditions. A directed interference graph is designed to capture the dominant interference resulting from user mobility. An asymptotically optimal Max-K-Cut method is proposed to partition the graph, achieving a ( $1-1/K$) approximation of the optimum in a polynomial time-complexity, where $K$ is the number of clusters. As a result, $K$ can be adaptively adjusted to leverage among the optimality loss, throughput, and complexity. Numerical results show that our adaptive centralized framework performs significantly better than other centralized or semidistributed clustering schemes in terms of throughput.
Ma, B, Yang, L, Wang, Q, Yuan, Z, Wang, Y & Peng, Y 2017, 'Inactivation and adaptation of ammonia-oxidizing bacteria and nitrite-oxidizing bacteria when exposed to free nitrous acid', Bioresource Technology, vol. 245, no. Pt A, pp. 1266-1270.
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Inactivation and adaptation of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) to free nitrous acid (FNA) was investigated. Batch test results showed that AOB and NOB were inactivated when treated with FNA. After an 85-day operating period, AOB in a continuous pre-denitrification reactor did not adapt to the FNA that was applied to treat some of the return activated sludge. In contrast, NOB did adapt to FNA. NOB activity in the seed sludge was only 11% of the original activity after FNA batch treatment, at 0.75mg HNO2-N/L. NOB activity in the pre-denitrification reactor was not affected after being exposed to this FNA level. Nitrosomonas was the dominant AOB before and after long-term FNA treatment. However, dominant NOB changed from Nitrospira to Candidatus Nitrotoga, a novel NOB genus, after long-term FNA treatment. This adaptation of NOB to FNA may be due to the shift in NOB population makeup.
Ma, C, Tsang, IW, Peng, F & Liu, C 2017, 'Partial Hash Update via Hamming Subspace Learning', IEEE Transactions on Image Processing, vol. 26, no. 4, pp. 1939-1951.
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© 2017 IEEE. Hashing technique has become an effective method for information retrieval due to the fast calculation of the Hamming distance. However, with the continuous growth of data coming from the Internet, the online update of hashing on the massive social data becomes very time-consuming. To alleviate this issue, in this paper, we propose a novel updating technique for hashing methods, namely Hamming Subspace Learning (HSL). The motivation of HSL is to generate a low-dimensional Hamming subspace from a high-dimensional Hamming space by selecting representative hash functions. Through HSL, we aim to improve the speed of updating binary codes for all samples. We present a method for Hamming subspace learning based on greedy selection strategy and the Distribution Preserving Hamming Subspace learning (DHSL) algorithm by designing a novel loss function. The experimental results demonstrate that the HSL is effective to improve the speed of online updating and the performance of hashing algorithm.
Ma, C, Xu, X, Wang, F, Zhou, Z, Liu, D, Zhao, J, Guan, M, Lang, CI & Jin, D 2017, 'Optimal Sensitizer Concentration in Single Upconversion Nanocrystals', Nano Letters, vol. 17, no. 5, pp. 2858-2864.
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© 2017 American Chemical Society. Each single upconversion nanocrystal (UCNC) usually contains thousands of photon sensitizers and hundreds of photon activators to up-convert near-infrared photons into visible and ultraviolet emissions. Though in principle further increasing the sensitizers’ concentration will enhance the absorption efficiency to produce brighter nanocrystals, typically 20% of Yb3+ ions has been used to avoid the so-called “concentration quenching” effect. Here we report that the concentration quenching effect does not limit the sensitizer concentration and NaYbF4 is the most bright host matrix. Surface quenching and the large size of NaYbF4 nanocrystals are the only factors limiting this optimal concentration. Therefore, we further designed sandwich nanostructures of NaYbF4 between a small template core to allow an epitaxial growth of the size-tunable NaYbF4 shell enclosed by an inert shell to minimize surface quenching. As a result, the suspension containing 25.2 nm sandwich structure UCNCs is 1.85 times brighter than the homogeneously doped ones, and the brightness of each single 25.2 nm heterogeneous UCNC is enhanced by nearly 3 times compared to the NaYF4: 20% Yb3+, 4% Tm3+ UCNCs in similar sizes. Particularly, the blue emission intensities of the UCNCs with the sandwich structure in the size of 13.6 and 25.2 nm are 1.36 times and 3.78 times higher than that of the monolithic UCNCs in the similar sizes. Maximizing the sensitizer concentration will accelerate the development of brighter and smaller UCNCs as more efficient biomolecule probes or photon energy converters.
Ma, J, Xu, F & Saha, SC 2017, 'Flows and heat transfer of the transition to an unsteady state in a finned cavity for different Prandtl numbers', International Communications in Heat and Mass Transfer, vol. 88, pp. 220-227.
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© 2017 Elsevier Ltd Flows and heat transfer of the transition to an unsteady state in a finned cavity are studied for Prandtl numbers (Pr) from 0.1 to 100 and Rayleigh numbers (Ra) from 10 7 to 10 10 . Transient flows are described in the finned cavity. Critical Rayleigh numbers of the transition to an unsteady state are obtained for different Prandtl numbers and the relation between two dimensionless parameters is given. The spectral analysis is applied for the oscillations of unsteady flows and the dominant frequency dependent on governing parameters is presented. Heat transfer of the transition to an unsteady flow is quantified and the corresponding relations dependent on the Prandtl number and Rayleigh number are gained. It is demonstrated that the flow rate and the Nusselt number of the finned cavity significantly increase due to the presentence of the fin, which depend on the Prandtl number and the Rayleigh number.
Ma, T, Zhang, Y, Huang, L, Shang, L, Wang, K, Yu, H & Zhu, D 2017, 'Text mining to gain technical intelligence for acquired target selection: A case study for China's computer numerical control machine tools industry', Technological Forecasting and Social Change, vol. 116, pp. 162-180.
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Technology strategy plays an increasingly important role in today’s Mergers and Acquisitions (M&A) activities. Informing that strategy with empirical intelligence offers great potential value to R&D managers and technology policy makers, this paper proposes a methodology, based on patent analysis, to extract technical intelligence to identify technology M&A target technologies and evaluate relevant target companies to facilitate M&A target selection. We apply the term clumping process and a trend analysis together with policy and market information to profile present R&D status and capture future development signals and trends in order to grasp a range of significant domain-based technologies. Furthermore, a comparison between a selected acquirer and leading players is used to identify significant technologies and sub-technologies for specific strategy-oriented technology M&A activities. Finally, aiming to recommend appropriate M&A target companies, we set up an index-based system to evaluate the acquired target candidates from both firms-side perspective and target firm-side perspective and differentially weigh for specific M&A situations. We provide an empirical study in the field of computer numerical control machine tools (CNCMT) in China to identify technology M&A targets for an emerging Chinese CNCMT company – Estun Automation under different M&A strategies.
Ma, W, Luo, X, Xuan, J, Xue, R & Guo, Y 2017, 'Discover semantic topics in patents within a specific domain', Journal of Web Engineering, vol. 16, no. 7-8, pp. 653-675.
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Patent topic discovery is critical for innovation-oriented enterprises to hedge the patent application risks and raise the success rate of patent application. Topic models are commonly recognized as an efficient tool for this task by researchers from both academy and industry. However, many existing well-known topic models, e.g., Latent Dirichlet Allocation (LDA), which are particularly designed for the documents represented by word-vectors, exhibit low accuracy and poor interpretability on patent topic discovery task. The reason is that 1) the semantics of documents are still under-explored in a specific domain 2) and the domain background knowledge is not successfully utilized to guide the process of topic discovery. In order to improve the accuracy and the interpretability, we propose a new patent representation and organization with additional inter-word relationships mined from title, abstract, and claim of patents. The representation can endow each patent with more semantics than word-vector. Meanwhile, we build a Backbone Association Link Network (Backbone ALN) to incorporate domain background semantics to further enhance the semantics of patents. With new semantic-rich patent representations, we propose a Semantic LDA model to discover semantic topics from patents within a specific domain. It can discover semantic topics with association relations between words rather than a single word vector. At last, accuracy and interpretability of the proposed model are verified on real-world patents datasets from the United States Patent and Trademark Office. The experimental results show that Semantic LDA model yields better performance than other conventional models (e.g., LDA). Furthermore, our proposed model can be easily generalized to other related text mining corpus.
Ma, Y, Saha, S, Miller, W & Guan, L 2017, 'Comparison of Different Solar-Assisted Air Conditioning Systems for Australian Office Buildings', Energies, vol. 10, no. 10, pp. 1463-1463.
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This study has investigated the feasibility of three different solar-assisted air conditioning systems for typical medium-sized office buildings in all eight Australian capital cities using the whole building energy simulation software EnergyPlus. The studied solar cooling systems include: solar desiccant-evaporative cooling (SDEC) system, hybrid solar desiccant-compression cooling (SDCC) system, and solar absorption cooling (SAC) system. A referenced conventional vapor compression variable-air-volume (VAV) system has also been investigated for comparison purpose. The technical, environmental, and economic performances of each solar cooling system have been evaluated in terms of solar fraction (SF), system coefficient of performance (COP), annual HVAC (heating, ventilation, and air conditioning) electricity consumption, annual CO2 emissions reduction, payback period (PBP), and net present value (NPV). The results demonstrate that the SDEC system consumes the least energy in Brisbane and Darwin, achieving 56.9% and 82.1% annual energy savings, respectively, compared to the conventional VAV system, while for the other six cities, the SAC system is the most energy efficient. However, from both energy and economic aspects, the SDEC system is more feasible in Adelaide, Brisbane, Darwin, Melbourne, Perth, and Sydney because of high annual SF and COP, low yearly energy consumption, short PBP and positive NPV, while for Canberra and Hobart, although the SAC system achieves considerable energy savings, it is not economically beneficial due to high initial cost. Therefore, the SDEC system is the most economically beneficial for most of Australian cities, especially in hot and humid climates. The SAC system is also energy efficient, but is not as economic as the SDEC system. However, for Canberra and Hobart, reducing initial cost is the key point to achieve economic feasibility of solar cooling applications.
Ma, Y, Saha, SC, Miller, W & Guan, L 2017, 'Parametric Analysis of Design Parameter Effects on the Performance of a Solar Desiccant Evaporative Cooling System in Brisbane, Australia', Energies, vol. 10, no. 7, pp. 849-849.
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Solar desiccant cooling is widely considered as an attractive replacement for conventional vapor compression air conditioning systems because of its environmental friendliness and energy efficiency advantages. The system performance of solar desiccant cooling strongly depends on the input parameters associated with the system components, such as the solar collector, storage tank and backup heater, etc. In order to understand the implications of different design parameters on the system performance, this study has conducted a parametric analysis on the solar collector area, storage tank volume, and backup heater capacity of a solid solar desiccant cooling system for an office building in Brisbane, Australia climate. In addition, a parametric analysis on the outdoor air humidity ratio control set-point which triggers the operation of the desiccant wheel has also been investigated. The simulation results have shown that either increasing the storage tank volume or increasing solar collector area would result in both increased solar fraction (SF) and system coefficient of performance (COP), while at the same time reduce the backup heater energy consumption. However, the storage tank volume is more sensitive to the system performance than the collector area. From the economic aspect, a storage capacity of 30 m3/576 m2 has the lowest life cycle cost (LCC) of $405,954 for the solar subsystem. In addition, 100 kW backup heater capacity is preferable for the satisfaction of the design regeneration heating coil hot water inlet temperature set-point with relatively low backup heater energy consumption. Moreover, an outdoor air humidity ratio control set-point of 0.008 kgWater/kgDryAir is more reasonable, as it could both guarantee the indoor design conditions and achieve low backup heater energy consumption.
Ma, Z, Chang, X, Xu, Z, Sebe, N & Hauptmann, AG 2017, 'Joint Attributes and Event Analysis for Multimedia Event Detection', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 1-10.
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© 2012 IEEE. Semantic attributes have been increasingly used the past few years for multimedia event detection (MED) with promising results. The motivation is that multimedia events generally consist of lower level components such as objects, scenes, and actions. By characterizing multimedia event videos with semantic attributes, one could exploit more informative cues for improved detection results. Much existing work obtains semantic attributes from images, which may be suboptimal for video analysis since these image-inferred attributes do not carry dynamic information that is essential for videos. To address this issue, we propose to learn semantic attributes from external videos using their semantic labels. We name them video attributes in this paper. In contrast with multimedia event videos, these external videos depict lower level contents such as objects, scenes, and actions. To harness video attributes, we propose an algorithm established on a correlation vector that correlates them to a target event. Consequently, we could incorporate video attributes latently as extra information into the event detector learnt from multimedia event videos in a joint framework. To validate our method, we perform experiments on the real-world large-scale TRECVID MED 2013 and 2014 data sets and compare our method with several state-of-the-art algorithms. The experiments show that our method is advantageous for MED.
Ma, Z, Chang, X, Yang, Y, Sebe, N & Hauptmann, AG 2017, 'The Many Shades of Negativity', IEEE Transactions on Multimedia, vol. 19, no. 7, pp. 1558-1568.
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© 1999-2012 IEEE. Complex event detection has been progressively researched in recent years for the broad interest of video indexing and retrieval. To fulfill the purpose of event detection, one needs to train a classifier using both positive and negative examples. Current classifier training treats the negative videos as equally negative. However, we notice that many negative videos resemble the positive videos in different degrees. Intuitively, we may capture more informative cues from the negative videos if we assign them fine-grained labels, thus benefiting the classifier learning. Aiming for this, we use a statistical method on both the positive and negative examples to get the decisive attributes of a specific event. Based on these decisive attributes, we assign the fine-grained labels to negative examples to treat them differently for more effective exploitation. The resulting fine-grained labels may be not optimal to capture the discriminative cues from the negative videos. Hence, we propose to jointly optimize the fine-grained labels with the classifier learning, which brings mutual reciprocality. Meanwhile, the labels of positive examples are supposed to remain unchanged. We thus additionally introduce a constraint for this purpose. On the other hand, the state-of-the-art deep convolutional neural network features are leveraged in our approach for event detection to further boost the performance. Extensive experiments on the challenging TRECVID MED 2014 dataset have validated the efficacy of our proposed approach.
Mahalleh, MKK, Ashjari, B, Yousefi, F & Saberi, M 2017, 'A Robust Solution to Resource-Constraint Project Scheduling Problem', INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, vol. 17, no. 3, pp. 221-227.
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© The Korean Institute of Intelligent Systems. This paper aims to propose a solution to the resource-constraint project scheduling problem (RCPSP). RCPSP is a significant scheduling problem in project management. Currently, there are insufficient studies dealing with the robustness of RCPSP. This paper improves the robustness of RCPSP and develops a Robust RCPSP, namely RRCSP. RRCSP is structured with relaxing a fundamental assumption that is 'the tasks start on time as planned'. Relaxing this assumption makes the model more realistic. The proposed solution minimizes the makespan while maximizing the robustness. Maximizing the robustness requires maximizing floating time of activities (it is NP hard). This creates more stability in the project finishing time. RCPSP stands as the root cause of many other problems such as multi-mode resourceconstrained project scheduling problems (MRCPSP), multi-skill resource-constrained project scheduling problem (MSRCPSP), or similar problems and hence proposing a solution to this problem contributes to pave a new line for future research in other mentioned areas. The applicability of the proposed model is examined through a numerical example.
Mahdavi, A, Saberi, M, Jeloudar, GA & Shahroozian, E 2017, 'Effects of different levels of Aloe Vera gel on some of hematological, biochemical and immunological parameters in the chicken model', Koomesh, vol. 19, no. 1, pp. 135-143.
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Introduction: The present study was conducted to investigate the effects of subchronic administration of different levels of Aloe Vera gel on some biochemical and immunological factors in the chicken model. Material and Methods: Two hundred and forty-one-day old Ross 308 (male and female) broilers were used on a completely randomized design in 5 groups with 4 replicates, and each replicate was consisting of 12 broilers. The groups included one control group (basal diet) and four experimental groups with basal diet mixed with different levels of Aloe Vera gel (1%, 2% and 3%) plus virginiamycin antibiotic. Results: No significant difference between experimental groups was observed in serum albumin level and ALP activity on days 14, 28 and 42. On the day 14, the variation of albumin and total protein levels were significant. In the days 28 and 42, the level of blood glucose in the group receiving 3% Aloe Vera and in the group receiving 1% Aloe Vera on the day 28 was decreased significantly. On the day 28, the count of lymphocytes was raised significantly in the group receiving 3% Aloe Vera. Also in this day, the most count of heterophils was found in the control and virginiamycin groups. On the day 42, the significant rise of lymphocyte count was observed in all groups receiving Aloe Vera gel. On the day 28, the level of antibody titers against sheep red blood cell was raised significantly. Conclusion: Daily supplementation with 1% Aloe Vera gel markedly potentiates cellular and humeral immunity in chickens and can be used as a food additive in order to prevent infections.
Mahdiyar, A, Hasanipanah, M, Armaghani, DJ, Gordan, B, Abdullah, A, Arab, H & Majid, MZA 2017, 'A Monte Carlo technique in safety assessment of slope under seismic condition', Engineering with Computers, vol. 33, no. 4, pp. 807-817.
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Mahlia, TMI, Masjuki, HH, Choudhury, IA & R. Saidur, ARS 2017, 'A review on energy efficiency standards and labels: present status and implementation possibilities in malaysia', ASEAN Journal on Science and Technology for Development, vol. 18, no. 1, pp. 71-84.
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This article is a review on energy efficiency standards and labels for household electrical appliances around the world. Through the review of other country experiences on energy efficiency standards and labels, we attempt to identify savings possibilities in Malaysian households. The implementation possibilities of standards and labels for various household electrical appliances in Malaysia are also examined. It is found that various household appliances in Malaysia offer some potential in reducing electricity consumption. Finally, it is concluded that there are many advantages for Malaysia to implement the standards and labels for household electrical appliances as soon as possible in order to reduce electricity bills and energy consumption in Malaysian households.
Mahmud, MA, Hossain, MJ, Pota, HR & Oo, AMT 2017, 'Robust Partial Feedback Linearizing Excitation Controller Design for Multimachine Power Systems', IEEE Transactions on Power Systems, vol. 32, no. 1, pp. 3-16.
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This paper presents a new robust nonlinear excitation controller design for synchronous generators in multimachine power systems to enhance the transient stability. The mismatches between the original power system model and formulated mathematical model are considered as uncertainties, which are modeled through the satisfaction of matching conditions. The exogenous noises appearing from measurements are incorporated with the power system model including the two-axis model of synchronous generators. The partial feedback linearization technique is used to design the controller which transforms the original nonlinear multimachine power system model into several reduced-order linear and autonomous subsystems. The desired control law is obtained for each subsystem and implemented in a decentralized manner provided that the dynamics of the autonomous subsystems have no effects on the overall stability of the system. The analysis related to the dynamics of noisy autonomous subsystems is also included and the proposed controller has the excellent capability to decouple these noises. Finally, the performance of the proposed control scheme is evaluated on an IEEE 39-bus benchmark power system following different types of large disturbances. The performance of the proposed controller is compared to that of a partial feedback linearizing controller, which is designed without robustness properties, to verify the effectiveness of the proposed control scheme.
Makki Alamdari, M, Samali, B, Li, J, Lu, Y & Mustapha, S 2017, 'Structural condition assessment using entropy-based time series analysis', Journal of Intelligent Material Systems and Structures, vol. 28, no. 14, pp. 1941-1956.
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We present a time-series-based algorithm to identify structural damage in the structure. The method is in the context of non-model-based approaches; hence, it eliminates the need of any representative numerical model of the structure to be built. The method starts by partitioning the state space into a finite number of subsets which are mutually exclusive and exhaustive and each subset is identified by a distinct symbol. Partitioning is performed based on a maximum entropy approach which takes into account the sparsity and distribution of information in the time series. After constructing the symbol space, the time series data are uniquely transformed from the state space into the constructed symbol space to create the symbol sequences. Symbol sequences are the simplified abstractions of the complex system and describe the evolution of the system. Each symbol sequence is statistically characterized by its entropy which is obtained based on the probability of occurrence of the symbols in the sequence. As a consequence of damage occurrence, the entropy of the symbol sequences changes; this change is implemented to define a damage indicative feature. The method shows promising results using data from two experimental case studies subject to varying excitation. The first specimen is a reinforced concrete jack arch which replicates one of the major structural components of the Sydney Harbor Bridge and the second specimen is a three-story frame structure model which has been tested at Los Alamos National Laboratory. The method not only could successfully identify the presence of damage but also has potential to localize it.
Manjunath, SV, Kumar, SM, Ngo, HH & Guo, W 2017, 'Metronidazole removal in powder-activated carbon and concrete-containing graphene adsorption systems: Estimation of kinetic, equilibrium and thermodynamic parameters and optimization of adsorption by a central composite design', Journal of Environmental Science and Health, Part A, vol. 52, no. 14, pp. 1269-1283.
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Metronidazole (MNZ) removal by two adsorbents, i.e., concrete-containing graphene (CG) and powder-activated carbon (PAC), was investigated via batch-mode experiments and the outcomes were used to analyze the kinetics, equilibrium and thermodynamics of MNZ adsorption. MNZ sorption on CG and PAC has followed the pseudo-second-order kinetic model, and the thermodynamic parameters revealed that MNZ adsorption was spontaneous on PAC and non-spontaneous on CG. Subsequently, two-parameter isotherm models, i.e., Langmuir, Freundlich, Temkin, Dubinin-Radushkevich and Elovich models, were applied to evaluate the MNZ adsorption capacity. The maximum MNZ adsorption capacities ([Formula: see text]) of PAC and CG were found to be between 25.5-32.8 mg/g and 0.41-0.002 mg/g, respectively. Subsequently, the effects of pH, temperature and adsorbent dosage on MNZ adsorption were evaluated by a central composite design (CCD) approach. The CCD experiments have pointed out the complete removal of MNZ at a much lower PAC dosage by increasing the system temperature (i.e., from 20°C to 40°C). On the other hand, a desorption experiment has shown 3.5% and 1.7% MNZ removal from the surface of PAC and CG, respectively, which was insignificant compared to the sorbed MNZ on the surface by adsorption. The overall findings indicate that PAC and CG with higher graphene content could be useful in MNZ removal from aqueous systems.
Mannan, A, Mohd Sabri, MF, Kalam, MA & Masjuki, HH 2017, 'Tribological properties of hydrogen free DLC in self-mated contacts against ZDDP-added oil', Industrial Lubrication and Tribology, vol. 69, no. 6, pp. 938-944.
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PurposeThe purpose of this study is to investigate the tribological properties of tetrahedral diamond-like carbon (DLC) films in self-mated contacts in the presence of additivated and non-additivated vegetable oils. DLC films have high practical value due to low friction and low wear properties. On the other hand, vegetable oils are considered to be lubricants for future due to its resource renewability and biodegradability. Sometimes different chemical agents are added to vegetable oils to further improve its tribological properties. Thus, the tribological study of DLC films against additivated oils becomes important.Design/methodology/approachThe tribology tests were conducted in a four ball tribo-meter under the boundary lubricated conditions.FindingsTa-C DLC exhibited 80 per cent lower wear rate under Zinc dialkyldithiophosphates (ZDDP)-added oil compared to that of base oil. In contrast, the friction coefficient under additivated oil was slightly higher than the base oil lubricated case. Moreover, the carbonyl band area as well as the viscosity change of ZDDP-added oil was much smaller than that of base oil. Therefore, ZDDP reduced the wear of DLC film and prevented the oxidation of base oil during tribotests.Originality/valueThis is the first work on the tribological properties of ta-C DLC lubricated with corn oil with and without anti-wear additives.
Mans, B & Mathieson, L 2017, 'Incremental Problems in the Parameterized Complexity Setting', Theory of Computing Systems, vol. 60, no. 1, pp. 3-19.
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© 2016, Springer Science+Business Media New York. Dynamic systems are becoming steadily more important with the profusion of mobile and distributed computing devices. Coincidentally incremental computation is a natural approach to deal with ongoing changes. We explore incremental computation in the parameterized complexity setting and show that incrementalization leads to non-trivial complexity classifications. Interestingly, some incremental versions of hard problems become tractable, while others remain hard. Moreover tractability or intractability is not a simple function of the problem’s static complexity, every level of the W-hierarchy exhibits complete problems with both tractable and intractable incrementalizations. For problems that are already tractable in their static form, we also show that incrementalization can lead to interesting algorithms, improving upon the trivial approach of using the static algorithm at each step.
Mao, M, Lu, J, Zhang, G & Zhang, J 2017, 'Multirelational Social Recommendations via Multigraph Ranking', IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4049-4061.
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© 2016 IEEE. Recommender systems aim to identify relevant items for particular users in large-scale online applications. The historical rating data of users is a valuable input resource for many recommendation models such as collaborative filtering (CF), but these models are known to suffer from the rating sparsity problem when the users or items under consideration have insufficient rating records. With the continued growth of online social networks, the increased user-to-user relationships are reported to be helpful and can alleviate the CF rating sparsity problem. Although researchers have developed a range of social network-based recommender systems, there is no unified model to handle multirelational social networks. To address this challenge, this paper represents different user relationships in a multigraph and develops a multigraph ranking model to identify and recommend the nearest neighbors of particular users in high-order environments. We conduct empirical experiments on two real-world datasets: 1) Epinions and 2) Last.fm, and the comprehensive comparison with other approaches demonstrates that our model improves recommendation performance in terms of both recommendation coverage and accuracy, especially when the rating data are sparse.
Mao, Q, Wang, L & Tsang, IW 2017, 'A unified probabilistic framework for robust manifold learning and embedding', Machine Learning, vol. 106, no. 5, pp. 627-650.
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© 2016, The Author(s). This paper focuses on learning a smooth skeleton structure from noisy data—an emerging topic in the fields of computer vision and computational biology. Many dimensionality reduction methods have been proposed, but none are specially designed for this purpose. To achieve this goal, we propose a unified probabilistic framework that directly models the posterior distribution of data points in an embedding space so as to suppress data noise and reveal the smooth skeleton structure. Within the proposed framework, a sparse positive similarity matrix is obtained by solving a box-constrained convex optimization problem, in which the sparsity of the matrix represents the learned neighborhood graph and the positive weights stand for the new similarity. Embedded data points are then obtained by applying the maximum a posteriori estimation to the posterior distribution expressed by the learned similarity matrix. The embedding process naturally provides a probabilistic interpretation of Laplacian eigenmap and maximum variance unfolding. Extensive experiments on various datasets demonstrate that our proposed method obtains the embedded points that accurately uncover inherent smooth skeleton structures in terms of data visualization, and the method yields superior clustering performance compared to various baselines.
Mao, Q, Wang, L, Tsang, IW & Sun, Y 2017, 'Principal Graph and Structure Learning Based on Reversed Graph Embedding', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 11, pp. 2227-2241.
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© 2017 IEEE. Many scientific datasets are of high dimension, and the analysis usually requires retaining the most important structures of data. Principal curve is a widely used approach for this purpose. However, many existing methods work only for data with structures that are mathematically formulated by curves, which is quite restrictive for real applications. A few methods can overcome the above problem, but they either require complicated human-made rules for a specific task with lack of adaption flexibility to different tasks, or cannot obtain explicit structures of data. To address these issues, we develop a novel principal graph and structure learning framework that captures the local information of the underlying graph structure based on reversed graph embedding. As showcases, models that can learn a spanning tree or a weighted undirected ℓ1 graph are proposed, and a new learning algorithm is developed that learns a set of principal points and a graph structure from data, simultaneously. The new algorithm is simple with guaranteed convergence. We then extend the proposed framework to deal with large-scale data. Experimental results on various synthetic and six real world datasets show that the proposed method compares favorably with baselines and can uncover the underlying structure correctly.
Mao, R, Liang, C, Zhang, Y, Hao, X & Li, J 2017, '50/50 Expressional Odds of Retention Signifies the Distinction between Retained Introns and Constitutively Spliced Introns in Arabidopsis thaliana', Frontiers in Plant Science, vol. 8, pp. 1-16.
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© 2017 Mao, Liang, Zhang, Hao and Li. Intron retention, one of the most prevalent alternative splicing events in plants, can lead to introns retained in mature mRNAs. However, in comparison with constitutively spliced introns (CSIs), the relevantly distinguishable features for retained introns (RIs) are still poorly understood. This work proposes a computational pipeline to discover novel RIs from multiple next-generation RNA sequencing (RNA-Seq) datasets of Arabidopsis thaliana. Using this pipeline, we detected 3,472 novel RIs from 18 RNA-Seq datasets and re-confirmed 1,384 RIs which are currently annotated in the TAIR10 database. We also use the expression of intron-containing isoforms as a new feature in addition to the conventional features. Based on these features, RIs are highly distinguishable from CSIs by machine learning methods, especially when the expressional odds of retention (i.e., the expression ratio of the RI-containing isoforms relative to the isoforms without RIs for the same gene) reaches to or larger than 50/50. In this case, the RIs and CSIs can be clearly separated by the Random Forest with an outstanding performance of 0.95 on AUC (the area under a receiver operating characteristics curve). The closely related characteristics to the RIs include the low strength of splice sites, high similarity with the flanking exon sequences, low occurrence percentage of YTRAY near the acceptor site, existence of putative intronic splicing silencers (ISSs, i.e., AG/GA-rich motifs) and intronic splicing enhancers (ISEs, i.e., TTTT-containing motifs), and enrichment of Serine/Arginine-Rich (SR) proteins and heterogeneous nuclear ribonucleoparticle proteins (hnRNPs).
Mao, X, Wang, Y, Liu, X & Guo, Y 2017, 'An adaptive weighted least square support vector regression for hysteresis in piezoelectric actuators', Sensors and Actuators A: Physical, vol. 263, pp. 423-429.
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© 2017 Elsevier B.V. To overcome the low positioning accuracy of piezoelectric actuators (PZAs) caused by the hysteresis nonlinearity, this paper proposes an adaptive weighted least squares support vector regression (AWLSSVR) to model the rate-dependent hysteresis of PZA. Firstly, the AWLSSVR hyperparameters are optimized by using particle swarm optimization. Then an adaptive weighting strategy is proposed to eliminate the effects of noises in the training dataset and reduce the sample size at the same time. Finally, the proposed approach is applied to predict the hysteresis of PZA. The results show that the proposed method is more accurate than other versions of least squares support vector regression for training samples with noises, and meanwhile reduces the sample size and speeds up calculation.
Mardhiah, HH, Ong, HC, Masjuki, HH, Lim, S & Lee, HV 2017, 'A review on latest developments and future prospects of heterogeneous catalyst in biodiesel production from non-edible oils', Renewable and Sustainable Energy Reviews, vol. 67, pp. 1225-1236.
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Mardhiah, HH, Ong, HC, Masjuki, HH, Lim, S & Pang, YL 2017, 'Investigation of carbon-based solid acid catalyst from Jatropha curcas biomass in biodiesel production', Energy Conversion and Management, vol. 144, pp. 10-17.
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Marjanovic, O & Cecez-Kecmanovic, D 2017, 'Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems.', J. Strateg. Inf. Syst., vol. 26, no. 3, pp. 210-232.
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Government agencies worldwide continue their commitment to providing open data in order to increase transparency of education, healthcare and other public services. Focusing on open government information systems (IS) that provide performance-related data, this paper explores the ongoing tension between government's goal of transparency and the resulting largely opaque datification effects. Our research insights are derived from an empirical longitudinal study of a controversial open government IS called My School, currently providing performance data on almost 10,000 schools in Australia. We investigate the tension between transparency intended with schools’ open performance data and datification effects they create within the education system and a broader society, through the theoretical lens of Complex Adaptive Systems (CAS). Our study reveals how the tension emerges due to unpredictable use, propagation and reinterpretation of open data by more and more users. Consequently, the original meaning of data gets distorted, as these users continue to reconstruct and reinterpret ‘data’ in their own contexts and adapt their behavior in pursuit of their strategic goals. We also identify and theorize seven datification patterns underlying the tension and the ways they produce various social consequences. Based on these research contributions we discuss important strategic implications for government decision makers and identify new opportunities for future research on open government IS.
Martens, W, Poffet, Y, Soria, PR, Fitch, R & Sukkarieh, S 2017, 'Geometric Priors for Gaussian Process Implicit Surfaces', IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 373-380.
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© 2016 IEEE. This paper presents an extension of Gaussian process implicit surfaces (GPIS) by the introduction of geometric object priors. The proposed method enhances the probabilistic reconstruction of objects from three-dimensional (3-D) pointcloud data, providing a rigorous way of incorporating prior knowledge about objects expected in a scene. The key ideas, including the systematic use of surface normal information, are illustrated with one-dimensional and two-dimensional examples, and then applied to simulated and real pointcloud data for 3-D objects. The performance of our method is demonstrated in two different application scenarios, using complete and partial surface observations. Qualitative and quantitative analysis of the results reveals the superiority of the proposed approach over existing GPIS configurations that do not exploit prior knowledge.
Matekovits, L, Huang, J, Peter, I & Esselle, KP 2017, 'Mutual Coupling Reduction Between Implanted Microstrip Antennas on a Cylindrical Bio-Metallic Ground Plane', IEEE Access, vol. 5, pp. 8804-8811.
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McArdle, J, Smyth, W, Wicking, K & Gardner, A 2017, 'Haemodialysis central venous catheter exit site dressings in the tropics: a crossover randomised controlled trial', WOUND PRACTICE AND RESEARCH, vol. 25, no. 4, pp. 200-207.
McGloin, D 2017, 'Droplet lasers: a review of current progress', Reports on Progress in Physics, vol. 80, no. 5, pp. 054402-054402.
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© 2017 IOP Publishing Ltd. It is perhaps surprising that something as fragile as a microscopic droplet could possibly form a laser. In this article we will review some of the underpinning physics as to how this might be possible, and then examine the state of the art in the field. The technology to create and manipulate droplets will be examined, as will the different classes of droplet lasers. We discuss the rapidly developing fields of droplet biolasers, liquid crystal laser droplets and explore how droplet lasers could give rise to new bio and chemical sensing and analysis. The challenges that droplet lasers face in becoming robust devices, either as sensors or as photonic components in the lab on chip devices, is assessed.
McGregor, C & Bonnis, B 2017, 'New Approaches for Integration: Integration of Haptic Garments, Big Data Analytics, and Serious Games for Extreme Environments', IEEE Consumer Electronics Magazine, vol. 6, no. 4, pp. 92-96.
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© 2012 IEEE. Haptic garments present new opportunities to increase realism in gaming. As Real As It Gets (ARAIG) is a new form of haptic garment that uses muscle stimulation, vibration, and 7.1 surround sound to provide a new level of realism in gaming. The integration of new haptic garments like ARAIG with big data analytics and serious games presents new opportunities for more realistic virtual training that has application in many domains. In particular, there is great potential to support repeatable virtual training for extreme environments. In 2016, the IEEE Life Sciences Technical Community worked across the IEEE Societies to demonstrate this interdisciplinary nature, with a focus on solving life science problems in extreme environments. This article is based on our keynote address at the International Conference on Consumer Electronics (ICCE)-Berlin in 2016. It provides an example of this interdisciplinary case study research in action.
McKenzie, TG, Colombo, E, Fu, Q, Ashokkumar, M & Qiao, GG 2017, 'Sono‐RAFT Polymerization in Aqueous Medium', Angewandte Chemie International Edition, vol. 56, no. 40, pp. 12302-12306.
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AbstractThe ultrasonic irradiation of aqueous solution is demonstrated to be a suitable source of initiating radicals for a controlled radical polymerization when conducted in the presence of a thiocarbonylthio‐containing reversible addition–fragmentation chain transfer (RAFT) agent. This allows for a highly “green” method of externally regulated/controlled polymerization with a potentially broad scope for polymerizable monomers and/or polymer structures.
McKenzie, TG, Colombo, E, Fu, Q, Ashokkumar, M & Qiao, GG 2017, 'Sono‐RAFT Polymerization in Aqueous Medium', Angewandte Chemie, vol. 129, no. 40, pp. 12470-12474.
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AbstractThe ultrasonic irradiation of aqueous solution is demonstrated to be a suitable source of initiating radicals for a controlled radical polymerization when conducted in the presence of a thiocarbonylthio‐containing reversible addition–fragmentation chain transfer (RAFT) agent. This allows for a highly “green” method of externally regulated/controlled polymerization with a potentially broad scope for polymerizable monomers and/or polymer structures.
McPhee, MJ, Walmsley, BJ, Skinner, B, Littler, B, Siddell, JP, Cafe, LM, Wilkins, JF, Oddy, VH & Alempijevic, A 2017, 'Live animal assessments of rump fat and muscle score in Angus cows and steers using 3-dimensional imaging1', Journal of Animal Science, vol. 95, no. 4, pp. 1847-1857.
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© 2017 American Society of Animal Science. All rights reserved. The objective of this study was to develop a proof of concept for using off-the-shelf Red Green Blue-Depth (RGB-D) Microsoft Kinect cameras to objectively assess P8 rump fat (P8 fat; mm) and muscle score (MS) traits in Angus cows and steers. Data from low and high muscled cattle (156 cows and 79 steers) were collected at multiple locations and time points. The following steps were required for the 3-dimensional (3D) image data and subsequent machine learning techniques to learn the traits: 1) reduce the high dimensionality of the point cloud data by extracting features from the input signals to produce a compact and representative feature vector, 2) perform global optimization of the signatures using machine learning algorithms and a parallel genetic algorithm, and 3) train a sensor model using regression-supervised learning techniques on the ultrasound P8 fat and the classified learning techniques for the assessed MS for each animal in the data set. The correlation of estimating hip height (cm) between visually measured and assessed 3D data from RGB-D cameras on cows and steers was 0.75 and 0.90, respectively. The supervised machine learning and global optimization approach correctly classified MS (mean [SD]) 80 (4.7) and 83% [6.6%] for cows and steers, respectively. Kappa tests of MS were 0.74 and 0.79 in cows and steers, respectively, indicating substantial agreement between visual assessment and the learning approaches of RGB-D camera images. A stratified 10-fold cross-validation for P8 fat did not find any differences in the mean bias (P = 0.62 and P = 0.42 for cows and steers, respectively). The root mean square error of P8 fat was 1.54 and 1.00 mm for cows and steers, respectively. Additional data is required to strengthen the capacity of machine learning to estimate measured P8 fat and assessed MS. Data sets for Bos indicus and continental cattle are also required to broaden the use...
Mei, P, Pramanik, M, Young, C, Huang, Z, Hossain, MSA, Sugahara, Y & Yamauchi, Y 2017, 'Synthesis of mesostructured manganese phosphonate and its promising energy storage application', Journal of Materials Chemistry A, vol. 5, no. 44, pp. 23259-23266.
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Mesostructured manganese phosphonate (MnP) with a uniform nanorod morphology has been prepared through an easy surfactant-mediated procedure.
Meng, D, Huang, T, Zhang, YX & Lee, CK 2017, 'Mechanical behaviour of a polyvinyl alcohol fibre reinforced engineered cementitious composite (PVA-ECC) using local ingredients', Construction and Building Materials, vol. 141, pp. 259-270.
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Meng, D, Lee, CK & Zhang, YX 2017, 'Flexural and shear behaviours of plain and reinforced polyvinyl alcohol-engineered cementitious composite beams', Engineering Structures, vol. 151, pp. 261-272.
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Meng, J, Huang, J, Sheng, D & Sloan, SW 2017, 'Granular contact dynamics with elastic bond model', Acta Geotechnica, vol. 12, no. 3, pp. 479-493.
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Meng, J, Huang, J, Sheng, D & Sloan, SW 2017, 'Quasi-Static Rheology of Granular Media Using the Static DEM', International Journal of Geomechanics, vol. 17, no. 11, pp. 04017094-04017094.
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Meng, Q, Catchpoole, D, Skillicorn, D & Kennedy, PJ 2017, 'DBNorm: normalizing high-density oligonucleotide microarray data based on distributions', BMC Bioinformatics, vol. 18, no. 1.
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© 2017 The Author(s). Background: Data from patients with rare diseases is often produced using different platforms and probe sets because patients are widely distributed in space and time. Aggregating such data requires a method of normalization that makes patient records comparable. Results: This paper proposed DBNorm, implemented as an R package, is an algorithm that normalizes arbitrarily distributed data to a common, comparable form. Specifically, DBNorm merges data distributions by fitting functions to each of them, and using the probability of each element drawn from the fitted distribution to merge it into a global distribution. DBNorm contains state-of-the-art fitting functions including Polynomial, Fourier and Gaussian distributions, and also allows users to define their own fitting functions if required. Conclusions: The performance of DBNorm is compared with z-score, average difference, quantile normalization and ComBat on a set of datasets, including several that are publically available. The performance of these normalization methods are compared using statistics, visualization, and classification when class labels are known based on a number of self-generated and public microarray datasets. The experimental results show that DBNorm achieves better normalization results than conventional methods. Finally, the approach has the potential to be applicable outside bioinformatics analysis.
Meng, X, Cao, L, Zhang, X & Shao, J 2017, 'Top-k coupled keyword recommendation for relational keyword queries', Knowledge and Information Systems, vol. 50, no. 3, pp. 883-916.
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© 2016 Springer-Verlag LondonProviding top-k typical relevant keyword queries would benefit the users who cannot formulate appropriate queries to express their imprecise query intentions. By extracting the semantic relationships both between keywords and keyword queries, this paper proposes a new keyword query suggestion approach which can provide typical and semantically related queries to the given query. Firstly, a keyword coupling relationship measure, which considers both intra- and inter-couplings between each pair of keywords, is proposed. Then, the semantic similarity of different keyword queries can be measured by using a semantic matrix, in which the coupling relationships between keywords in queries are reserved. Based on the query semantic similarities, we next propose an approximation algorithm to find the most typical queries from query history by using the probability density estimation method. Lastly, a threshold-based top-k query selection method is proposed to expeditiously evaluate the top-k typical relevant queries. We demonstrate that our keyword coupling relationship and query semantic similarity measures can capture the coupling relationships between keywords and semantic similarities between keyword queries accurately. The efficiency of query typicality analysis and top-k query selection algorithm is also demonstrated.
Meo, PD, Musial-Gabrys, K, Rosaci, D, Sarnè, GML & Aroyo, L 2017, 'Using Centrality Measures to Predict Helpfulness-Based Reputation in Trust Networks', ACM Transactions on Internet Technology, vol. 17, no. 1, pp. 1-20.
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In collaborative Web-based platforms, user reputation scores are generally computed according to two orthogonal perspectives: (a) helpfulness-based reputation (HBR) scores and (b) centrality-based reputation (CBR) scores. In HBR approaches, the most reputable users are those who post the most helpful reviews according to the opinion of the members of their community. In CBR approaches, a “who-trusts-whom” network—known as a trust network —is available and the most reputable users occupy the most central position in the trust network, according to some definition of centrality. The identification of users featuring large HBR scores is one of the most important research issue in the field of Social Networks, and it is a critical success factor of many Web-based platforms like e-marketplaces, product review Web sites, and question-and-answering systems. Unfortunately, user reviews/ratings are often sparse, and this makes the calculation of HBR scores inaccurate. In contrast, CBR scores are relatively easy to calculate provided that the topology of the trust network is known. In this article, we investigate if CBR scores are effective to predict HBR ones, and, to perform our study, we used real-life datasets extracted from CIAO and Epinions (two product review Web sites) and Wikipedia and applied five popular centrality measures—Degree Centrality, Closeness Centrality, Betweenness Centrality, PageRank and Eigenvector Centrality—to calculate CBR scores. Our analysis provides a positive answer to our research question: CBR scores allow for predicting HBR ones and Eigenvector Centrality was found to be the most important predictor. Our findings prove that we can leverage trust relationships to spot those users producing the most helpful reviews for the whole community.
Merigó, JM & Yang, J 2017, 'Accounting Research: A Bibliometric Analysis', Australian Accounting Review, vol. 27, no. 1, pp. 71-100.
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Bibliometrics is a fundamental field of information science that studies bibliographic material quantitatively. It is very useful for organising available knowledge within a specific scientific discipline. This study presents a bibliometric overview of accounting research using the Web of Science database, identifying the most relevant research in the field classified by papers, authors, journals, institutions and countries. The results show that the most influential journals are: The Journal of Accounting and Economics, Journal of Accounting Research, The Accounting Review and Accounting, Organizations and Society. It also shows that US institutions are the most influential worldwide. However, it is important to note that some very good research in this area, including a small number of papers and citations, may not show up in this study due to the specific characteristics of different subtopics.
Merigó, JM & Yang, J-B 2017, 'A bibliometric analysis of operations research and management science', Omega, vol. 73, pp. 37-48.
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© 2016 Bibliometric analysis is the quantitative study of bibliographic material. It provides a general picture of a research field that can be classified by papers, authors and journals. This paper presents a bibliometric overview of research published in operations research and management science in recent decades. The main objective of this study is to identify some of the most relevant research in this field and some of the newest trends according to the information found in the Web of Science database. Several classifications are made, including an analysis of the most influential journals, the two hundred most cited papers of all time and the most productive and influential authors. The results obtained are in accordance with the common wisdom, although some variations are found.
Merigó, JM, Blanco-Mesa, F, Gil-Lafuente, AM & Yager, RR 2017, 'Thirty Years of theInternational Journal of Intelligent Systems: A Bibliometric Review', International Journal of Intelligent Systems, vol. 32, no. 5, pp. 526-554.
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© 2016 Wiley Periodicals, Inc. The International Journal of Intelligent Systems was created in 1986. Today, the journal is 30 years old. To celebrate this anniversary, this study develops a bibliometric review of all of the papers published in the journal between 1986 and 2015. The results are largely based on the Web of Science Core Collection, which classifies leading bibliographic material by using several indicators including total number of publications and citations, the h-index, cites per paper, and citing articles. The work also uses the VOS viewer software for visualizing the main results through bibliographic coupling and co-citation. The results show a general overview of leading trends that have influenced the journal in terms of highly cited papers, authors, journals, universities and countries.
Merigó, JM, Linares-Mustarós, S & Ferrer-Comalat, JC 2017, 'Guest editorial', Kybernetes, vol. 46, no. 1, pp. 2-7.
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Merigó, JM, Palacios-Marqués, D & Soto-Acosta, P 2017, 'Distance measures, weighted averages, OWA operators and Bonferroni means', Applied Soft Computing, vol. 50, pp. 356-366.
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© 2016 Elsevier B.V. The ordered weighted average (OWA) is an aggregation operator that provides a parameterized family of operators between the minimum and the maximum. This paper presents the OWA weighted average distance operator. The main advantage of this new approach is that it unifies the weighted Hamming distance and the OWA distance in the same formulation and considering the degree of importance that each concept has in the analysis. This operator includes a wide range of particular cases from the minimum to the maximum distance. Some further generalizations are also developed with generalized and quasi-arithmetic means. The use of Bonferroni means under this framework is also studied. The paper ends with an application of the new approach in a group decision making problem with Dempster-Shafer belief structure regarding the selection of strategies.
Mezaal, MR, Pradhan, B, Sameen, MI, Mohd Shafri, HZ & Yusoff, ZM 2017, 'Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data', Applied Sciences, vol. 7, no. 7, pp. 730-730.
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An accurate inventory map is a prerequisite for the analysis of landslide susceptibility, hazard, and risk. Field survey, optical remote sensing, and synthetic aperture radar techniques are traditional techniques for landslide detection in tropical regions. However, such techniques are time consuming and costly. In addition, the dense vegetation of tropical forests complicates the generation of an accurate landslide inventory map for these regions. Given its ability to penetrate vegetation cover, high-resolution airborne light detection and ranging (LiDAR) has been used to generate accurate landslide maps. This study proposes the use of recurrent neural networks (RNN) and multi-layer perceptron neural networks (MLP-NN) in landscape detection. These efficient neural architectures require little or no prior knowledge compared with traditional classification methods. The proposed methods were tested in the Cameron Highlands, Malaysia. Segmentation parameters and feature selection were respectively optimized using a supervised approach and correlation-based feature selection. The hyper-parameters of network architecture were defined based on a systematic grid search. The accuracies of the RNN and MLP-NN models in the analysis area were 83.33% and 78.38%, respectively. The accuracies of the RNN and MLP-NN models in the test area were 81.11%, and 74.56%, respectively. These results indicated that the proposed models with optimized hyper-parameters produced the most accurate classification results. LiDAR-derived data, orthophotos, and textural features significantly affected the classification results. Therefore, the results indicated that the proposed methods have the potential to produce accurate and appropriate landslide inventory in tropical regions such as Malaysia.
Mezaal, MR, Pradhan, B, Shafri, HZM & Yusoff, ZM 2017, 'Automatic landslide detection using Dempster–Shafer theory from LiDAR-derived data and orthophotos', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1935-1954.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. A good landslide inventory map is a prerequisite for landslide hazard and risk analysis. In tropical countries, such as Malaysia, preparation of the landslide inventory is a challenging task because of the rapid growth of vegetation. Thus, it is crucial to use rapid and accurate technique and effective parameters. For this purpose, Dempster Shafer theory (DST) was applied in fusing high resolution LiDAR derived data products and Greenness index derived from orthophoto imagery. Two sites were selected, for the implementation and evaluation of the DST model; site “A” for DST implementation and site “B” for the comparison. For model implementation, vegetation index, slope and height were used as effective parameters for identifying automatic landslide detection. Two type of DST based fusions were evaluated; (greenness and height) and (greenness and slope). Furthermore, validation techniques were used to validate the accuracy are confusion matrix and area under the curve. The overall accuracy of the first and second evaluated fusions were (73.4% and 84.33%), and area under the curve were (0.76 and 0.81) respectively. Additionally, the result was compa red with Random Forest (RF) based detection approach. The results showed that DST does not require a priori knowledge.
Miao, G, Alonso-Marroquin, F & Airey, D 2017, 'A spheropolygonal-based DEM study into breakage under repetitive compression', EPJ Web of Conferences, vol. 140, pp. 07007-07007.
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Mihăiţă, AS, Cai, C & Chen, F 2017, 'Event-triggered control for improving the positioning accuracy of connected vehicles equipped with DSRC', IFAC-PapersOnLine, vol. 50, no. 1, pp. 8518-8524.
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Vehicle-to-Vehicle communication and Dedicated Short Range Communication (DSRC) systems have gained an increasing popularity in building vehicular applications for improving road safety, but the high level of positioning accuracy at the centimetre level is still far from being achieved. Various outages in transmitting the positioning information between neighbouring vehicles and errors in broadcasting their current locations can lead to a fail in generating accurate collision alerts that would affect the road safety. The goal of this paper is to propose a modelling framework for applying an event-triggered control when the location transmitted by connected vehicles equipped with DSRC is lost due to unforeseen events. Firstly, we model the evolution of the DSRC transmitted positioning as a multi-state stochastic switching system by taking into consideration the distance from the transmitted location to the road center. A control interval is defined for the evolution of the positioning signal by using the road width to define the boundaries. Secondly, we propose an analytic method for determining the exit probabilities from the control interval, with the scope of anticipating any position anomalies and help applying the event triggered control in advance rather than when the control boundaries have been already reached. Thirdly, we apply a cooperative location estimation method for improving the broadcast position information by using the accumulating trajectory segments from the moment of the anomaly alert.
Miller, HD, Mesgari, S, Akbarnezhad, A & Foster, S 2017, 'Safety Risks Associated with Carbon Nanotube-Reinforced Mortar', ACI Materials Journal, vol. 114, no. 6, pp. 897-909.
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Carbon nanotube (CNT) reinforcement has been reported to improve mechanical properties and durability of concrete. However, numerous health concerns have been attributed to CNTs, forming a major barrier to their widespread use. Human exposure to CNTs is considered unlikely while CNTs are dispersed in liquid or embedded in a concrete matrix. However, respirable CNT-contaminated particles, including free CNTs and CNTs attached to hydrated cement products, may be released during production, processing, or demolition of CNT-reinforced concrete. In this paper, the risk of presence of respirable CNT-contaminated particles in the wastewater generated during mixing and dusts generated during crushing of CNT-reinforced mortar is investigated by varying the type (singlewalled and multi-walled CNTs), concentration, and dispersion method of CNTs. A considerably lower risk of presence of CNTs in respirable particles generated during mortar production and demolition is found for multi-walled CNTs versus single-walled CNTs. Furthermore, functionalization of CNTs is identified as an effective method to reduce the health and safety risks associated with mixing and demolition of the CNT-reinforced cementitious materials. The presence of CNTs in the respirable particles generated is found to increase with an increase in concentration of CNTs.
Mills, N, Lu, W, Li, JJ & Al Muderis, M 2017, 'Osseointegration as Treatment for a Knee Disarticulation Because of a Congenital Femoral Deficiency', JBJS Case Connector, vol. 7, no. 4, pp. e76-e76.
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Case:A 25-year-old woman underwent osseointegration surgery as treatment for an amputation that had been performed because of congenital femoral deficiency. The undersized custom-designed implant for the congenitally hypoplastic femur subsequently loosened, causing substantial pain and loss of function. The patient underwent revision surgery with a larger standard-sized osseointegration implant, and experienced no additional complications.Conclusion:This case demonstrates the possibility of stimulating a hypertrophic response in underdeveloped bone, which allows the subsequent insertion of a larger implant with greater stability. Similar procedures can be considered for the treatment of patients who had amputations because of congenital deficiencies, in order to produce improved outcomes and reduce the risk of additional complications.
Mirjalili, S & Gandomi, AH 2017, 'Chaotic gravitational constants for the gravitational search algorithm', Applied Soft Computing, vol. 53, pp. 407-419.
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In a population-based meta-heuristic, the search process is divided into two main phases: exploration versus exploitation. In the exploration phase, a random behavior is fruitful to explore the search space as extensive as possible. In contrast, a fast exploitation toward the promising regions is the main objective of the latter phase. It is really challenging to find a proper balance between these two phases because of the stochastic nature of population-based meta-heuristic algorithms. The literature shows that chaotic maps are able to improve both phases. This work embeds ten chaotic maps into the gravitational constant (G) of the recently proposed population-based meta-heuristic algorithm called Gravitational Search Algorithm (GSA). Also, an adaptive normalization method is proposed to transit from the exploration phase to the exploitation phase smoothly. As case studies, twelve shifted and biased benchmark functions evaluate the performance of the proposed chaos-based GSA algorithms in terms of exploration and exploitation. A statistical test called Wilcoxon rank-sum is done to judge about the significance of the results as well. The results demonstrate that sinusoidal map is the best map for improving the performance of GSA significantly.
Mirjalili, S, Gandomi, AH, Mirjalili, SZ, Saremi, S, Faris, H & Mirjalili, SM 2017, 'Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems', Advances in Engineering Software, vol. 114, pp. 163-191.
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This work proposes two novel optimization algorithms called Salp Swarm Algorithm (SSA) and Multi-objective Salp Swarm Algorithm (MSSA) for solving optimization problems with single and multiple objectives. The main inspiration of SSA and MSSA is the swarming behaviour of salps when navigating and foraging in oceans. These two algorithms are tested on several mathematical optimization functions to observe and confirm their effective behaviours in finding the optimal solutions for optimization problems. The results on the mathematical functions show that the SSA algorithm is able to improve the initial random solutions effectively and converge towards the optimum. The results of MSSA show that this algorithm can approximate Pareto optimal solutions with high convergence and coverage. The paper also considers solving several challenging and computationally expensive engineering design problems (e.g. airfoil design and marine propeller design) using SSA and MSSA. The results of the real case studies demonstrate the merits of the algorithms proposed in solving real-world problems with difficult and unknown search spaces.
Mirtalaie, MA, Hussain, OK, Chang, E & Hussain, FK 2017, 'A decision support framework for identifying novel ideas in new product development from cross-domain analysis', Information Systems, vol. 69, pp. 59-80.
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In current competitive times, product manufacturers need not only to retain their existing customer base, but also to increase their market share. One way they can achieve this is by generating new ideas and developing novel products with new features. As highlighted in the literature, in generating new ideas to develop novel and innovative products, it is important that product designers satisfy the needs of both current customers and new customers. However, despite the large number of existing studies that identify novel features in the ideation phase, product designers do not have a systematic framework that utilises additional information relating to products from either far-field or related domains to generate such new ideas in the ideation phase. This paper presents our proposed framework FEATURE which provides just such a systemic framework for product designers in the ideation phase of new product development. FEATURE has three phases. The first phase identifies and recommends to the product designers novel features that can be added to the next version of a reference product. In order to incorporate the customer's voice into the ideation phase, the second phase ascertains the popularity of the proposed features by using social media. The third phase ranks the proposed features based on the designer's decision criteria to select those that should be considered further in the next phases of new product development. We explain the importance of each phase of FEATURE and show the working of its first module in detail.
Mirzaghorbanali, A, Rasekh, H, Aziz, N, Yang, G, Khaleghparast, S & Nemcik, J 2017, 'Shear strength properties of cable bolts using a new double shear instrument, experimental study, and numerical simulation', Tunnelling and Underground Space Technology, vol. 70, pp. 240-253.
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© 2017 Elsevier Ltd A newly developed double shear apparatus without contact between concrete blocks was developed to conduct a series of double shear tests. This new double shear apparatus is capable of determining the pure shear strength of pre-tensioned fully grouted cable bolt without friction between sheared concrete blocks. Five different types of cable bolt, with various pretension loads, were tested to investigate the influence of surface profile type and pretension load on the shear strength of cable bolt. Concrete blocks of 40 MPa strength and the Stratabinder HS grout were used for consistency across the entire tests. The results showed that the plain cable bolts had higher peak shear load compared with the indented and spiral strand cable bolts. The shear displacement and peak shear load decreased by increasing the pretension load. A numerical analysis was carried out, based on the Fast Lagrangian Analysis of Continua (FLAC 2D) and the result was compared with the experimental data. It was observed that FLAC 2D is capable of simulating the performance of cable bolt satisfactorily.
Mishra, N, Boeckl, JJ, Tadich, A, Jones, RT, Pigram, PJ, Edmonds, M, Fuhrer, MS, Nichols, BM & Iacopi, F 2017, 'Solid source growth of graphene with Ni–Cu catalysts: towards high qualityin situgraphene on silicon', Journal of Physics D: Applied Physics, vol. 50, no. 9, pp. 095302-095302.
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We obtain a monolayer graphene on epitaxial silicon carbide on silicon substrates via solid source growth mediated by a thin Ni-Cu alloy. Raman spectroscopy consistently shows an I D /I G band ratio as low as ∼0.2, indicating that the graphene obtained through this method is to-date the best quality monolayer grown on epitaxial silicon carbide films on silicon. We describe the key steps behind the graphene synthesis on the basis of extensive physical, chemical and morphological analyses. We conclude that (1) the oxidation, amorphisation and silicidation of the silicon carbide surface mediated by the Ni, (2) the liquid-phase epitaxial growth of graphene as well as (3) the self-limiting graphitization provided the molten Cu catalyst, are key characteristics of this novel synthesis method.
Mohamad, ET, Armaghani, DJ, Mahdyar, A, Komoo, I, Kassim, KA, Abdullah, A & Majid, MZA 2017, 'Utilizing regression models to find functions for determining ripping production based on laboratory tests', Measurement, vol. 111, pp. 216-225.
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Mohamad, ET, Faradonbeh, RS, Armaghani, DJ, Monjezi, M & Majid, MZA 2017, 'An optimized ANN model based on genetic algorithm for predicting ripping production', Neural Computing and Applications, vol. 28, no. S1, pp. 393-406.
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Mohammed, TU, Das, HK, Mahmood, AH, Rahman, MN & Awal, MA 2017, 'Flexural performance of RC beams made with recycled brick aggregate', Construction and Building Materials, vol. 134, pp. 67-74.
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Mojaddadi, H, Pradhan, B, Nampak, H, Ahmad, N & Ghazali, AHB 2017, 'Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1080-1102.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. In this paper, an ensemble method, which demonstrated efficiency in GIS based flood modeling, was used to create flood probability indices for the Damansara River catchment in Malaysia. To estimate flood probability, the frequency ratio (FR) approach was combined with support vector machine (SVM) using a radial basis function kernel. Thirteen flood conditioning parameters, namely, altitude, aspect, slope, curvature, stream power index, topographic wetness index, sediment transport index, topographic roughness index, distance from river, geology, soil, surface runoff, and land use/cover (LULC), were selected. Each class of conditioning factor was weighted using the FR approach and entered as input for SVM modeling to optimize all the parameters. The flood hazard map was produced by combining the flood probability map with flood-triggering factors such as; averaged daily rainfall and flood inundation depth. Subsequently, the hydraulic 2D high-resolution sub-grid model (HRS) was applied to estimate the flood inundation depth. Furthermore, vulnerability weights were assigned to each element at risk based on their importance. Finally flood risk map was generated. The results of this research demonstrated that the proposed approach would be effective for flood risk management in the study area along the expressway and could be easily replicated in other areas.
Mojumder, JC, Ong, HC, Chong, WT, Izadyar, N & Shamshirband, S 2017, 'The intelligent forecasting of the performances in PV/T collectors based on soft computing method', Renewable and Sustainable Energy Reviews, vol. 72, pp. 1366-1378.
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Mojumder, JC, Ong, HC, Chong, WT, Leong, KY & Izadyar, N 2017, 'An empirical analysis on photovoltaic thermal system with fin design by forced air circulation', Journal of Mechanical Science and Technology, vol. 31, no. 5, pp. 2549-2557.
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Mokhtar, ES, Pradhan, B, Ghazali, AH & Shafri, HZM 2017, 'Comparative assessment of water surface level using different discharge prediction models', Natural Hazards, vol. 87, no. 2, pp. 1125-1146.
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Discharge is traditionally measured at gauge stations located at discrete positions along the river course. When the volume of water discharge is higher than the river bank, inundation to adjacent land occurs. Flood inundation mapping has largely relied on in situ discharge data. However, it cannot be accessed at ungauged sites. In recent literature, no comparative study on the impact of water level using different discharge models has been carried out. This paper evaluates the performance of three empirical formulas for discharge measurement to model flood inundation along Padang Terap River in Kedah, Malaysia, between October 31, 2010 and November 4, 2010. Water discharge was computed using three models, and the Manning-n values were assigned to the types of land use. Further, the rainfall obtained from gauge stations was interpolated using the Kriging interpolation method. Relative error and RMSE methods were used to evaluate the measured and predicted water surface elevation. The impact of predicted water surface elevation (WSE) from different land use types and terrain information was assessed. Dingman and Sharma’s model significantly presented good agreement between measured and predicted WSE with R 2 = 0.8034, followed by Manning and Bjerklie equations with 0.8024 and 0.7997, respectively. Moreover, Dingman and Sharma’s model produced less RE and RMSE with 13.09% and 2.27 m compared with the others. Therefore, the estimated discharge can be used in ungauged sites for flood inundation modeling. Manning-n, elevation, and slope affected the WSE.
Monirul, IM, Kalam, MA, Masjuki, HH, Zulkifli, NWM, Shahir, SA, Mosarof, MH & Ruhul, AM 2017, 'Influence of poly(methyl acrylate) additive on cold flow properties of coconut biodiesel blends and exhaust gas emissions', Renewable Energy, vol. 101, pp. 702-712.
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Biodiesel comprises fatty acid esters and is used as an alternative fuel for diesel engines. However, biodiesel has poor cold flow properties (i.e., CP, CFPP and PP) than mineral diesel fuel. This study aims to reduce the PP, CFPP and CP of coconut biodiesel (CB) blends using poly(methyl acrylate) (PMA) additives and investigate their effects on single-cylinder four-stroke diesel engine performance and exhaust gas emission. DSC and TGA were used to observe crystal behavior and thermal stability of the biodiesel fuel blends. Engine performance and emission were analyzed by Dynomax-2000 software and gas analyzer, respectively. Results showed that 20% of CB blended with diesel and 0.03 wt% of PMA showed significant improvement in the PP, CFPP and CP. Other properties of B20 with additives met the requirements of ASTM D6751. The BSFC of B20 with PMA was reduced by 3.247%, whereas the BTE was increased by 2.16%, compared with those of B20. Burning B20 with PMA increased the NO emission by 2.15%, whereas HC, CO and smoke emissions were 19.81%, 13.35% and 3.93% lower than those of B20, respectively. Therefore, CB20 blend with 0.03 wt% PMA can be used as an alternative fuel in cold regions without compromising fuel quality.
Monirul, IM, Masjuki, HH, Kalam, MA, Zulkifli, NWM & Shancita, I 2017, 'Influence of polymethyl acrylate additive on the formation of particulate matter and NOX emission of a biodiesel–diesel-fueled engine', Environmental Science and Pollution Research, vol. 24, no. 22, pp. 18479-18493.
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Montiel, F, Chung, H, Karimi, M & Kessissoglou, N 2017, 'An analytical and numerical investigation of acoustic attenuation by a finite sonic crystal', Wave Motion, vol. 70, pp. 135-151.
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Sonic crystals are scatterers arranged periodically in a homogeneous fluid medium, for which sound does not transmit through the crystal in certain frequency bands known as stop bands. Acoustic wave transmission through a two-dimensional sonic crystal composed of a finite array of scatterers is investigated. Two types of scatterers are considered: sound-hard cylinders and C-shaped locally resonant scatterers. An analytical method is devised to solve the corresponding multiple scattering problems. The method combines an integral equation technique for the single scatterer with an enhanced multipole method using domain decomposition into slabs. A numerical approach using commercial software is also considered for validation and is based on the finite element method. Simulations of sound transmission through an array of 5 by 51 scatterers show remarkably good agreement with the corresponding infinite system. For an array comprising locally resonant scatterers, an approximate band gap around the resonator natural frequency is observed in addition to the band gap due to the overall periodicity of the finite sonic crystal.
Moreira, C & Wichert, A 2017, 'Are Quantum Models for Order Effects Quantum?', International Journal of Theoretical Physics, vol. 56, no. 12, pp. 4029-4046.
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Moreira, C & Wichert, A 2017, 'Exploring the relations between Quantum-Like Bayesian Networks and decision-making tasks with regard to face stimuli', Journal of Mathematical Psychology, vol. 78, pp. 86-95.
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Morosan, DE, Gallagher, PT, Fallows, RA, Reid, H, Mann, G, Bisi, MM, Magdalenić, J, Rucker, HO, Thidé, B, Vocks, C, Anderson, J, Asgekar, A, Avruch, IM, Bell, ME, Bentum, MJ, Best, P, Blaauw, R, Bonafede, A, Breitling, F, Broderick, JW, Brüggen, M, Cerrigone, L, Ciardi, B, de Geus, E, Duscha, S, Eislöffel, J, Falcke, H, Garrett, MA, Grießmeier, JM, Gunst, AW, Hoeft, M, Iacobelli, M, Juette, E, Kuper, G, McFadden, R, McKay-Bukowski, D, McKean, JP, Mulcahy, DD, Munk, H, Nelles, A, Orru, E, Paas, H, Pandey-Pommier, M, Pandey, VN, Pizzo, R, Polatidis, AG, Reich, W, Schwarz, DJ, Sluman, J, Smirnov, O, Steinmetz, M, Tagger, M, ter Veen, S, Thoudam, S, Toribio, MC, Vermeulen, R, van Weeren, RJ, Wucknitz, O & Zarka, P 2017, 'The association of aJ-burst with a solar jet', Astronomy & Astrophysics, vol. 606, pp. A81-A81.
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© ESO, 2017. Context. The Sun is an active star that produces large-scale energetic events such as solar flares and coronal mass ejections, and numerous smaller scale events such as solar jets. These events are often associated with accelerated particles that can cause emission at radio wavelengths. The reconfiguration of the solar magnetic field in the corona is believed to be the cause of the majority of solar energetic events and accelerated particles. Aims. Here, we investigate a bright J-burst that was associated with a solar jet and the possible emission mechanism causing these two phenomena. Methods. We used data from the Solar Dynamics Observatory (SDO) to observe a solar jet and radio data from the Low Frequency Array (LOFAR) and the Nançay Radioheliograph (NRH) to observe a J-burst over a broad frequency range (33-173 MHz) on 9 July 2013 at ~11:06 UT. Results. The J-burst showed fundamental and harmonic components and was associated with a solar jet observed at extreme ultraviolet wavelengths with SDO. The solar jet occurred in the northern hemisphere at a time and location coincident with the radio burst and not inside a group of complex active regions in the southern hemisphere. The jet occurred in the negative polarity region of an area of bipolar plage. Newly emerged positive flux in this region appeared to be the trigger of the jet. Conclusions. Magnetic reconnection between the overlying coronal field lines and the newly emerged positive field lines is most likely the cause of the solar jet. Radio imaging provides a clear association between the jet and the J-burst, which shows the path of the accelerated electrons. These electrons travelled from a region in the vicinity of the solar jet along closed magnetic field lines up to the top of a closed magnetic loop at a height of ~360 Mm. Such small-scale complex eruptive events arising from magnetic reconnection could facilitate accelerated electrons to produce continuously the large numbers...
Morshed, KM, Karmokar, DK & Esselle, KP 2017, 'Low profile single-layer U-slot loaded shorted-patch antenna for wireless communications', Microwave and Optical Technology Letters, vol. 59, no. 9, pp. 2224-2226.
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© 2017 Wiley Periodicals, Inc. A U-slot loaded single-layer compact shorted-patch antenna is presented for wireless communications in the 5.8 GHz band. The size of the prototyped antenna is only 30 mm × 30 mm, which is very small compared to single-layer antennas for the same frequency band. The measured −10 dB reflection coefficient bandwidth of the antenna is 140 MHz (5.67–5.81 GHz). The peak measured boresight gain and directivity of the antenna are 7.4 and 8 dBi, respectively, and their variation within the band is less than 1 dB. The measured 3-dB beamwidths of the antenna at 5.8 GHz are 79° and 69° in the E-plane and H-plane, respectively. An easy way to shift the antenna resonance frequency is also investigated.
Morstyn, T, Hredzak, B, Aguilera, RP & Agelidis, VG 2017, 'Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems', IEEE Transactions on Control Systems Technology, vol. 26, no. 3, pp. 1107-1114.
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This paper proposes a new convex model predictive control strategy fordynamic optimal power flow between battery energy storage systems distributedin an AC microgrid. The proposed control strategy uses a new problemformulation, based on a linear d-q reference frame voltage-current model andlinearised power flow approximations. This allows the optimal power flows to besolved as a convex optimisation problem, for which fast and robust solversexist. The proposed method does not assume real and reactive power flows aredecoupled, allowing line losses, voltage constraints and converter currentconstraints to be addressed. In addition, non-linear variations in the chargeand discharge efficiencies of lithium ion batteries are analysed and includedin the control strategy. Real-time digital simulations were carried out for anislanded microgrid based on the IEEE 13 bus prototypical feeder, withdistributed battery energy storage systems and intermittent photovoltaicgeneration. It is shown that the proposed control strategy approaches theperformance of a strategy based on non-convex optimisation, while reducing therequired computation time by a factor of 1000, making it suitable for areal-time model predictive control implementation.
Muhammad, KS, Baharom, R, Seroji, MN & Lu, DDC 2017, 'Totem-pole bridgeless boost PFC rectifier using series-parallel resonant network', Journal of Telecommunication, Electronic and Computer Engineering, vol. 9, no. 2-7, pp. 83-88.
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A new series-parallel resonant bridgeless boost (SPBBR) power factor correction (PFC) rectifier is proposed in this paper. It is based on a totem-pole bridgeless boost (TPBLB) configuration which allows bi-directional current to flow during resonance to provide soft-switching for all semiconductor devices. Therefore, no additional active switch is needed. The resonant is produced by a resonant network which is placed before the output capacitor. A detailed analysis of the converter operation and control is presented. Design considerations and parameter values determination are also given. Simulation results is used to verify the theoretical analysis of the SPBBR.
Mukhopadhyay, P & Qiao, Y 2017, 'Sparse multivariate polynomial interpolation on the basis of Schubert polynomials', computational complexity, vol. 26, no. 4, pp. 881-909.
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© 2016, Springer International Publishing. Schubert polynomials were discovered by A. Lascoux and M. Schützenberger in the study of cohomology rings of flag manifolds in 1980s. These polynomials generalize Schur polynomials and form a linear basis of multivariate polynomials. In 2003, Lenart and Sottile introduced skew Schubert polynomials, which generalize skew Schur polynomials and expand in the Schubert basis with the generalized Littlewood–Richardson coefficients. In this paper, we initiate the study of these two families of polynomials from the perspective of computational complexity theory. We first observe that skew Schubert polynomials, and therefore Schubert polynomials, are in #P (when evaluating on nonnegative integral inputs) and VNP. Our main result is a deterministic algorithm that computes the expansion of a polynomial f of degree d in Z[ x1, ⋯ , xn] on the basis of Schubert polynomials, assuming an oracle computing Schubert polynomials. This algorithm runs in time polynomial in n, d, and the bit size of the expansion. This generalizes, and derandomizes, the sparse interpolation algorithm of symmetric polynomials in the Schur basis by Barvinok and Fomin (Adv Appl Math 18(3):271–285, 1997). In fact, our interpolation algorithm is general enough to accommodate any linear basis satisfying certain natural properties. Applications of the above results include a new algorithm that computes the generalized Littlewood–Richardson coefficients.
Murphy, T, Kaplan, DL, Bell, ME, Callingham, JR, Croft, S, Johnston, S, Dobie, D, Zic, A, Hughes, J, Lynch, C, Hancock, P, Hurley-Walker, N, Lenc, E, Dwarakanath, KS, For, B-Q, Gaensler, BM, Hindson, L, Johnston-Hollitt, M, Kapińska, AD, McKinley, B, Morgan, J, Offringa, AR, Procopio, P, Staveley-Smith, L, Wayth, R, Wu, C & Zheng, Q 2017, 'Low-Frequency Spectral Energy Distributions of Radio Pulsars Detected with the Murchison Widefield Array', Publications of the Astronomical Society of Australia, vol. 34.
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AbstractWe present low-frequency spectral energy distributions of 60 known radio pulsars observed with the Murchison Widefield Array telescope. We searched the GaLactic and Extragalactic All-sky Murchison Widefield Array survey images for 200-MHz continuum radio emission at the position of all pulsars in the Australia Telescope National Facility (ATNF) pulsar catalogue. For the 60 confirmed detections, we have measured flux densities in 20 × 8 MHz bands between 72 and 231 MHz. We compare our results to existing measurements and show that the Murchison Widefield Array flux densities are in good agreement.
Murray, A, Gilbert, RI & Castel, A 2017, 'A New Approach to Modeling Tension Stiffening in Reinforced Concrete', ACI Structural Journal, vol. 115, no. 1, pp. 127-137.
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A novel approach to the modeling of tension stiffening is proposed based on considerations of the highly non-uniform strain regions that occur in the concrete surrounding embedded reinforcement bars near the primary cracks. A finite element study is undertaken to determine the effect of these disturbed regions on the overall deformation of reinforced concrete tension members. Simple hand calculations are presented to determine an effective cross-sectional area of concrete, which describes the overall contribution to axial rigidity of the cracked concrete for the ideal case of perfect bond. A scalar damage parameter is then introduced to account for the additional reduction in the tension stiffening effect caused by deterioration of bond at the reinforcement-concrete interface. Experimental tension stiffening studies in the literature (including a recent study by the authors) are used to calibrate the evolution of interface damage according to factors such as applied loading and shrinkage.
Musa, GMB, Al-Jumaily, A, Alnajjar, F & Shimoda, S 2017, 'Analyze the Human Movements to Help CNS to Shape the Synergy using CNMF and Pattern Recognition', Procedia Computer Science, vol. 105, pp. 170-176.
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© 2017 The Authors. The Biomedical Signals have been studied for developing human control systems to improving the quality of life. The EMG signal is one of the main types of biomedical signals. It is a convoluted signal. This signal (EMG signal) controlled by the Central nervous system (CNS). It has been a long time expected that the human central nervous system (CNS) uses flexible combinations of some muscles synergy (MS) to solve and control redundant movements. Synergy muscles activities are different in a single muscle. In the concept of Synergy muscle, the CNS does not directly control the activation of a large number of muscles. There are two main movements can help CNS to shape the synergy. The automatic body response and the voluntary actions. These activities remain not too bright. Some studies support the hypothesis that the automatic body responses could be used as a reference to familiarize the voluntary efforts. It has been validating by analyzing the human voluntary movement and the automatic mechanical motions from the muscle synergy. Based on the validation, there was a proposition that the automatic synergy motion may express some features which could support the CNS to shape the voluntary synergy motion using the nonnegative matrix factorization (NMF). Thus the target of the presenting work is to analyses the human movements from the muscle synergy to help CNS shapes the synergy movement by suggestion using the concatenated non-negative matrix factorization (CNMF) method and the pattern recognition method. Then compare the two results and see if that help CNS to shape the synergy movements and which method has more accuracy.
Musial, K, Bródka, P & De Meo, P 2017, 'Analysis and Applications of Complex Social Networks', Complexity, vol. 2017, pp. 1-2.
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Naghibi, SA, Moghaddam, DD, Kalantar, B, Pradhan, B & Kisi, O 2017, 'A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping', Journal of Hydrology, vol. 548, pp. 471-483.
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In recent years, application of ensemble models has been increased tremendously in various types of natural hazard assessment such as landslides and floods. However, application of this kind of robust models in groundwater potential mapping is relatively new. This study applied four data mining algorithms including AdaBoost, Bagging, generalized additive model (GAM), and Naive Bayes (NB) models to map groundwater potential. Then, a novel frequency ratio data mining ensemble model (FREM) was introduced and evaluated. For this purpose, eleven groundwater conditioning factors (GCFs), including altitude, slope aspect, slope angle, plan curvature, stream power index (SPI), river density, distance from rivers, topographic wetness index (TWI), land use, normalized difference vegetation index (NDVI), and lithology were mapped. About 281 well locations with high potential were selected. Wells were randomly partitioned into two classes for training the models (70% or 197) and validating them (30% or 84). AdaBoost, Bagging, GAM, and NB algorithms were employed to get groundwater potential maps (GPMs). The GPMs were categorized into potential classes using natural break method of classification scheme. In the next stage, frequency ratio (FR) value was calculated for the output of the four aforementioned models and were summed, and finally a GPM was produced using FREM. For validating the models, area under receiver operating characteristics (ROC) curve was calculated. The ROC curve for prediction dataset was 94.8, 93.5, 92.6, 92.0, and 84.4% for FREM, Bagging, AdaBoost, GAM, and NB models, respectively. The results indicated that FREM had the best performance among all the models. The better performance of the FREM model could be related to reduction of over fitting and possible errors. Other models such as AdaBoost, Bagging, GAM, and NB also produced acceptable performance in groundwater modelling. The GPMs produced in the current study may facilitate groundwater exploitati...
Naidu, G, Jeong, S, Choi, Y & Vigneswaran, S 2017, 'Membrane distillation for wastewater reverse osmosis concentrate treatment with water reuse potential', Journal of Membrane Science, vol. 524, pp. 565-575.
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© 2016 Elsevier B.V. Membrane distillation (MD) was evaluated as a treatment option of wastewater reverse osmosis concentrate (WWROC) discharged from wastewater reclamation plants (WRPs). A direct contact MD (DCMD), at obtaining 85% water recovery of WWROC showed only 13–15% flux decline and produced good quality permeate (10–15 µS/cm, 99% ion rejection) at moderate feed temperature of 55 °C. Prevalent calcium carbonate (CaCO 3 ) deposition on the MD membrane occurred in treating WWROC at elevated concentrations. The combination of low salinity and loose CaCO 3 adhesion on the membrane did not significantly contribute to DCMD flux decline. Meanwhile, high organic content in WWROC (58–60 mg/L) resulted in a significant membrane hydrophobicity reduction (70% lower water contact angle than virgin membrane) attributed to low molecular weight organic adhesion onto the MD membrane. Granular activated carbon (GAC) pretreatment helped in reducing organic contents of WWROC by 46–50%, and adsorbed a range of hydrophobic and hydrophilic micropollutants. This ensured high quality water production by MD (micropollutants-free) and enhanced its reuse potential. The MD concentrated WWROC was suitable for selective ion precipitation, promising a near zero liquid discharge in WRPs.
Naidu, G, Jeong, S, Johir, MAH, Fane, AG, Kandasamy, J & Vigneswaran, S 2017, 'Rubidium extraction from seawater brine by an integrated membrane distillation-selective sorption system', Water Research, vol. 123, pp. 321-331.
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© 2017 Elsevier Ltd The ultimate goal of seawater reverse osmosis (SWRO) brine management is to achieve minimal liquid discharge while recovering valuable resources. The suitability of an integrated system of membrane distillation (MD) with sorption for the recovery of rubidium (Rb+) and simultaneous SWRO brine volume reduction has been evaluated for the first time. Polymer encapsulated potassium copper hexacyanoferrate (KCuFC(PAN)) sorbent exhibited a good selectivity for Rb+ sorption with 10–15% increment at 55 °C (Langmuir Qmax = 125.11 ± 0.20 mg/g) compared to at 25 °C (Langmuir Qmax = 108.71 ± 0.20 mg/g). The integrated MD-KCuFC(PAN) system with periodic membrane cleaning, enabled concentration of SWRO brine to a volume concentration factor (VCF) of 2.9 (65% water recovery). A stable MD permeate flux was achieved with good quality permeate (conductivity of 15–20 μS/cm). Repeated cycles of MD-KCuFC(PAN) sorption with SWRO brine enabled the extraction of 2.26 mg Rb+ from 12 L of brine (equivalent to 1.9 kg of Rb/day, or 0.7 tonne/yr from a plant producing 10,000 m3/day brine). KCuFC(PAN) showed a high regeneration and reuse capacity. NH4Cl air stripping followed by resorcinol formaldehyde (RF) resin filtration enabled to recover Rb+ from the desorbed solution.
Naidu, G, Shim, WG, Jeong, S, Choi, Y, Ghaffour, N & Vigneswaran, S 2017, 'Transport phenomena and fouling in vacuum enhanced direct contact membrane distillation: Experimental and modelling', Separation and Purification Technology, vol. 172, pp. 285-295.
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© 2016 Elsevier B.V. The application of vacuum to direct contact membrane distillation (vacuum enhanced direct contact membrane distillation, V-DCMD) removed condensable gasses and reduced partial pressure in the membrane pores, achieving 37.6% higher flux than DCMD at the same feed temperature. Transfer mechanism and temperature distribution profile in V-DCMD were studied. The empirical flux decline (EFD) model represented fouling profiles of V-DCMD. In a continuous V-DCMD operation with moderate temperature (55 °C) and permeate pressure (300 mbar) for treating wastewater ROC, a flux of 16.0 ± 0.3 L/m 2 h and high quality distillate were achieved with water flushing, showing the suitability of V-DCMD for ROC treatment.
Nam, E, Wong, EHH, Tan, S, Fu, Q, Blencowe, A & Qiao, GG 2017, 'Antifogging Surface Facilitated by Nanoscale Coatings with Controllable Hydrophobicity and Cross‐Linking Density', Macromolecular Materials and Engineering, vol. 302, no. 1, pp. 1600199-1600199.
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Antifogging and frost-resistant coatings can be used in a wide range of applications and enable high light transmission through substrates even under changes in environmental conditions. In this study, surface confined and cross-linked antifogging thin films are fabricated on glass slides via catalyst induced cross-linking (CIC), which has been recently introduced as an easy and efficient cross-linking methodology. Four different poly(ethylene glycol) (PEG)-based polymers with different hydrophilicity are synthesized and used to prepare films via CIC. Films prepared from the most hydrophilic PEG-based polymers display the best antifogging performances when exposed to a temperature change from −20 to 22 °C. Furthermore, several parameters including cross-linking density, surface roughness, hydrophobicity, and exposure time are also evaluated in terms of film transparency. Through these measurements, it is determined that, more loosely cross-linked films retain antifogging ability for longer time periods due to higher film swellability as compared to, more highly cross-linked films. This study signifies the crucial role of the film cross-linking density and hydrophilicity on the antifogging function. (Figure presented.).
Nam, TM, Thanh, NH, Hieu, HT, Manh, NT, Huynh, NV & Tuan, HD 2017, 'Joint network embedding and server consolidation for energy–efficient dynamic data center virtualization', Computer Networks, vol. 125, pp. 76-89.
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© 2017 Elsevier B.V. Cloud computing has emerged in recent years as a promising paradigm that facilitates such new service models as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). As the number of cloud service provider increases, there exists a demand to dynamically provision virtual data centers (VDC) on top of the infrastructure provider's physical data centers. This research addresses problems related to energy and resource efficiently embedding virtual data centers inside physical data centers under dynamic resource allocation conditions, in which VDCs continuously join and leave the system. Dynamic VDC embedding is challenging as it is an NP-hard problem that should meet multiple objectives. In this article, we propose heuristic joint VDC embedding – server consolidation approaches as one solution for that problem. Evaluation results show that the joint approach outperforms existing ones in terms of resource and energy efficiency and can keep system complexity acceptable.
Narayan, N, Morenos, L, Phipson, B, Willis, SN, Brumatti, G, Eggers, S, Lalaoui, N, Brown, LM, Kosasih, HJ, Bartolo, RC, Zhou, L, Catchpoole, D, Saffery, R, Oshlack, A, Goodall, GJ & Ekert, PG 2017, 'Functionally distinct roles for different miR-155 expression levels through contrasting effects on gene expression, in acute myeloid leukaemia', Leukemia, vol. 31, no. 4, pp. 808-820.
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Enforced expression of microRNA-155 (miR-155) in myeloid cells has been shown to have both oncogenic or tumour-suppressor functions in acute myeloid leukaemia (AML). We sought to resolve these contrasting effects of miR-155 overexpression using murine models of AML and human paediatric AML data sets. We show that the highest miR-155 expression levels inhibited proliferation in murine AML models. Over time, enforced miR-155 expression in AML in vitro and in vivo, however, favours selection of intermediate miR-155 expression levels that results in increased tumour burden in mice, without accelerating the onset of disease. Strikingly, we show that intermediate and high miR-155 expression also regulate very different subsets of miR-155 targets and have contrasting downstream effects on the transcriptional environments of AML cells, including genes involved in haematopoiesis and leukaemia. Furthermore, we show that elevated miR-155 expression detected in paediatric AML correlates with intermediate and not high miR-155 expression identified in our experimental models. These findings collectively describe a novel dose-dependent role for miR-155 in the regulation of AML, which may have important therapeutic implications.
Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2017, 'Secrecy Rate Beamforming for Multicell Networks With Information and Energy Harvesting', IEEE Transactions on Signal Processing, vol. 65, no. 3, pp. 677-689.
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© 2016 IEEE. Considering a multicell network for the secure wireless information and power transfer, this paper studies the joint design of transmit beamformers at the base stations (BSs) and receive signal splitting ratios at the end users' equipment (UE). The primary concern in this work is the network internal security, where there may be a single multiantenna eavesdropper or there is a risk that any near user may accidentally eavesdrop on the received signal of any far user. The objective is to maximize the minimum secrecy user rate under BS transmit power and UE minimum harvested energy constraints. New path-following algorithms are proposed for computational solutions of these difficult nonconvex optimization problems. Each iteration involves one simple convex quadratic program. Numerical results confirm that the proposed algorithms converge quickly after few iterations having a low computational complexity.
Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2017, 'Secure and Energy-Efficient Beamforming for Simultaneous Information and Energy Transfer', IEEE Transactions on Wireless Communications, vol. 16, no. 11, pp. 7523-7537.
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© 2017 IEEE. Some next-generation wireless networks will likely involve the energy-efficient transfer of information and energy over the same wireless channel. Moreover, densification of such networks will make the physical layer more vulnerable to cyber attacks by potential multi-antenna eavesdroppers. To address these issues, this paper considers transmit time-switching (TS) mode, in which energy and information signals are transmitted separately in time by the base station (BS). This protocol is not only easy to implement but also delivers the opportunity for multi-purpose beamforming, in which energy beamformers can be used to jam eavesdroppers during wireless power transfer. In the presence of imperfect channel estimation and multi-antenna eavesdroppers, the energy and information beamformers and the transmit TS ratio are jointly optimized to maximize the worst-case user secrecy rate subject to energy constrained users' harvested energy thresholds and a BS transmit power budget. New robust path-following algorithms, which involve one simple convex quadratic program at each iteration are proposed for computational solutions of this difficult optimization problem and also the problem of secure energy efficiency maximization. The latter adds further complexity due to additional optimization variables appearing in the denominator of the secrecy rate function. Numerical results confirm that the performance of the proposed computational solutions is robust against channel uncertainties.
Nasir, AA, Tuan, HD, Ngo, DT, Duong, TQ & Poor, HV 2017, 'Beamforming Design for Wireless Information and Power Transfer Systems: Receive Power-Splitting Versus Transmit Time-Switching', IEEE Transactions on Communications, vol. 65, no. 2, pp. 876-889.
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© 1972-2012 IEEE. Information and energy can be transferred over the same radio-frequency channel. In the power-splitting (PS) mode, they are simultaneously transmitted using the same signal by the base station (BS) and later separated at the user (UE)'s receiver by a power splitter. In the time-switching (TS) mode, they are either transmitted separately in time by the BS or received separately in time by the UE. In this paper, the BS transmit beamformers are jointly designed with either the receive PS ratios or the transmit TS ratios in a multicell network that implements wireless information and power transfer (WIPT). Imposing UE-harvested energy constraints, the design objectives include: 1) maximizing the minimum UE rate under the BS transmit power constraint, and 2) minimizing the maximum BS transmit power under the UE data rate constraint. New iterative algorithms of low computational complexity are proposed to efficiently solve the formulated difficult nonconvex optimization problems, where each iteration either solves one simple convex quadratic program or one simple second-order-cone-program. Simulation results show that these algorithms converge quickly after only a few iterations. Notably, the transmit TS-based WIPT system is not only more easily implemented but outperforms the receive PS-based WIPT system as it better exploits the beamforming design at the transmitter side.
Navaratnarajah, SK & Indraratna, B 2017, 'Use of Rubber Mats to Improve the Deformation and Degradation Behavior of Rail Ballast under Cyclic Loading', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017015-04017015.
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Nemoto, K, Devitt, S & Munro, WJ 2017, 'Noise management to achieve superiority in quantum information systems', Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 375, no. 2099, pp. 20160236-20160236.
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Quantum information systems are expected to exhibit superiority compared with their classical counterparts. This superiority arises from the quantum coherences present in these quantum systems, which are obviously absent in classical ones. To exploit such quantum coherences, it is essential to control the phase information in the quantum state. The phase is analogue in nature, rather than binary. This makes quantum information technology fundamentally different from our classical digital information technology. In this paper, we analyse error sources and illustrate how these errors must be managed for the system to achieve the required fidelity and a quantum superiority. This article is part of the themed issue ‘Quantum technology for the 21st century’.
Neshat, A & Pradhan, B 2017, 'Evaluation of groundwater vulnerability to pollution using DRASTIC framework and GIS', Arabian Journal of Geosciences, vol. 10, no. 22, pp. 1-8.
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© 2017, Saudi Society for Geosciences. Groundwater management has a prominent role in the world especially in arid and semi-arid areas which have a shortage of water, and due to this serious problem, many researchers work on that for prevention and managing the water recourses to conserve and monitor sources. DRASTIC index can be put forward for estimating of groundwater vulnerability to such pollution. The main purpose of using the groundwater vulnerability model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, disregarding the effects of pollution type and characteristics. Thus, this technique must be standardized and approved for Kerman plain. Vulnerability evaluation to explain areas that are more vulnerable to contamination from anthropogenic sources has become a prominent element for land use planning and tangible resource management. This contribution aims at evaluating groundwater vulnerability by applying the DRASTIC index as well as employ sensitivity analyses to evaluate the comparative prominent of the model parameters for groundwater vulnerability in Kerman plain in the southeastern part of Iran. Moreover, the potential of vulnerability to pollution is more accurately assessed by optimizing the weights of the DRASTIC parameters with the single-parameter sensitivity analysis (SPSA). The new weights were calculated. The result of the study revealed that the DRASTIC-Sensitivity analysis exhibit more efficiently than the traditional method for a nonpoint source pollution. Observation of ultimate nitrate showed the result of DRASTIC-SPSA has more accuracy. The GIS method offers an efficient environment for carrying out assessments and greater capabilities for dealing with a huge quantity of spatial data.
Nghia, NT, Tuan, HD, Duong, TQ & Poor, HV 2017, 'MIMO Beamforming for Secure and Energy-Efficient Wireless Communication', IEEE Signal Processing Letters, vol. 24, no. 2, pp. 236-239.
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Considering a multiple-user multiple-input multiple-output (MIMO) channelwith an eavesdropper, this letter develops a beamformer design to optimize theenergy efficiency in terms of secrecy bits per Joule under secrecyquality-of-service constraints. This is a very difficult design problem with noavailable exact solution techniques. A path-following procedure, whichiteratively improves its feasible points by using a simple quadratic program ofmoderate dimension, is proposed. Under any fixed computational tolerance theprocedure terminates after finitely many iterations, yielding at least alocally optimal solution. Simulation results show the superior performance ofthe obtained algorithm over other existing methods.
Nghiem, LD, Koch, K, Bolzonella, D & Drewes, JE 2017, 'Full scale co-digestion of wastewater sludge and food waste: Bottlenecks and possibilities', Renewable and Sustainable Energy Reviews, vol. 72, pp. 354-362.
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© 2017 Wastewater treatment plants in many countries use anaerobic digesters for biosolids management and biogas generation. Opportunities exist to utilise the spare capacity of these digesters to co-digest food waste and sludge for energy recovery and a range of other economic and environmental benefits. This paper provides a critical perspective for full-scale implementation of co-digestion of food waste and wastewater sludge. Data compiled from full-scale facilities and the peer-reviewed literature revealed several key bottlenecks hindering full-scale implementation of co-digestion. Indeed, co-digestion applications remain concentrated mostly in countries or regions with favourable energy and waste management policies. Not all environmental benefits from waste diversion and resource recovery can be readily monetarised into revenue to support co-digestion projects. Our field surveys also revealed the important issue of inert impurities in food waste with significant implication to the planning, design, and operation of food waste processing and co-digestion plants. Other pertinent issues include regulatory uncertainty regarding gate fee, the lack of viable options for biogas utilisation, food waste collection and processing, impacts of co-digestion on biosolids reuse and downstream biogas utilisation, and lack of design and operation experience. Effort to address these bottlenecks and promote co-digestion requires a multi-disciplinary approach.
Nghiem, LD, Wickham, R & Ohandja, D-G 2017, 'Enhanced biogas production and performance assessment of a full-scale anaerobic digester with acid phase digestion', International Biodeterioration & Biodegradation, vol. 124, pp. 162-168.
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© 2017 Acid phase digestion pretreatment resulted in an increase in biogas production and volatile solids (VS) removal at the West Camden plant which was fed with only waste activated sludge. Without the acid phase digesters, the specific methane yield of waste activated sludge (WAS) was 190 L/kgVS added , whereas a specific methane yield of WAS of 231 L/kg VS added was observed from sludge sampled from the acid phase digester. The specific methane yield obtained from BioWin ® simulation was 331 L/kgVS added and was slightly higher than that from BMP assessment (231 L/kgVS added ). In addition, the overall VS removal values obtained from BioWin ® simulation (44%) and biomethane potential (BMP) evaluation (49%) were close to the actual VS removal value (45%) achieved by the plant. The consistency between full scale evaluation data, BioWin ® simulation, and BMP assessment suggests that BioWin ® simulation and BMP study can be used to guide future design and optimisation of acid phase digestion pretreatment to intensify anaerobic digestion of sewage sludge.
Ngo, NT 2017, 'DEM MODELLING OF GEOCELL-STABILISED SUB-BALLAST UNDER CYCLIC LOADING', International Journal of GEOMATE, vol. 12, no. 31, pp. 23-29.
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Upon repeated train loading, sub-ballast aggregates, placed underneath a ballast layer in rail track, become degraded and fouled by the progressive accumulation of external fine particles such as mud-pumping of soft subgrade, seriously decreasing the shear strength and drainage capacity of the track. This paper presents a study of the load-deformation response of geocell-reinforced sub-ballast under cyclic loads using laboratory tests and discrete element method (DEM). A series of large-scale cubical triaxial tests with and without geocell inclusions are conducted in the laboratory and simulated in DEM to investigate the beneficial effect of the geocells in decreasing the lateral and vertical deformations of railway subballast. Irregularly-shaped particles of sub-ballast are modelled by connecting and bonding of many circular balls together at appropriate sizes and positions. The geogcell was simulated by bonding many small spheres together to build a desired geometry and structure. The load-deformation behaviour of the geocell-stabilised sub-ballast specimen at varied load cycles predicted from the DEM modelling agrees well with those measured experimentally, showing that the proposed DEM model in this study is able to capture the deformation behaviour of the sub-ballast stabilised by the geocell. Additionally, the DEM modelling also provides insight into the distribution of contact forces, average contact normal and shear forces, which cannot be determined experimentally. These observations clearly prove the reinforcement effect of the geocell in eliminating the deformation of sub-ballast from a micromechanical perspective.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'A study of the geogrid–subballast interface via experimental evaluation and discrete element modelling', Granular Matter, vol. 19, no. 3, pp. 1-16.
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This paper presents a study of the interface of geogrid reinforced subballast through a series of large-scale direct shear tests and discrete element modelling. Direct shear tests were carried out for subballast with and without geogrid inclusions under varying normal stresses of σn= 6.7 to 45kPa. Numerical modelling with three-dimensional discrete element method (DEM) was used to study the shear behaviour of the interface of subballast reinforced by geogrids. In this study, groups of 25–50 spherical balls are clumped together in appropriate sizes to simulate angular subballast grains, while the geogrid is modelled by bonding small spheres together to form the desired grid geometry and apertures. The calculated results of the shear stress ratio versus shear strain show a good agreement with the experimental data, indicating that the DEM model can capture the interface behaviour of subballast reinforced by geogrids. A micromechanical analysis has also been carried out to examine how the contact force distributions and fabric anisotropy evolve during shearing. This study shows that the shear strength of the interface is governed by the geogrid characteristics (i.e. their geometry and opening apertures). Of the three types of geogrid tested, triaxial geogrid (triangular apertures) exhibits higher interface shear strength than the biaxial geogrids; and this is believed due to multi-directional load distribution of the triaxial geogrid.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Micromechanics-Based Investigation of Fouled Ballast Using Large-Scale Triaxial Tests and Discrete Element Modeling', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 2, pp. 04016089-04016089.
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Railway ballast comprises unbounded discrete grains that are often used to form a load-bearing platform for tracks. Ballast degradation as trains pass over the tracks and infiltration of external fines including slurried (pumped) fine subgrade soils are two of the main reasons for ballast fouling. Fouling causes tracks to settle and also reduces the load-bearing capacity, which is associated with a reduction in internal friction and increased lateral spreading of the ballast layer. This paper presents a study of mobilized friction angle, volumetric behavior, and associated evolutions of contact and fabric anisotropy of fouled ballast subjected to monotonic triaxial loading using a series of large-scale triaxial tests and discrete element modeling. Monotonically loaded and drained triaxial tests were carried out on ballast with levels of clay fouling that varied from 10 to 50% void contamination index (VCI) subjected to three confining pressures of 10, 30, and 60 kPa. The results showed that an increase in the level of fouling decreased the mobilized friction angle and increased the ballast dilation. The discrete element method (DEM) was used to study the mobilized friction angle and fabric anisotropy of fresh and fouled ballast by simulating actual large-scale triaxial tests. Irregular shaped grains of ballast were simulated by clumping bonded circular balls with appropriate sizes and positions together. Ballast fouling was approximately simulated in DEM by adding 1-mm particles into the pore spaces of the fresh ballast. The predicted mobilized friction angles and volumetric changes obtained from the DEM simulations agreed well with those measured in the laboratory, indicating that the peak friction angle of fouled ballast and dilation decreased as the degree of fouling increased. The DEM simulations provided an insight into the distribution of contact force chains, contact orientations, and evolution of fabric anisotropy of fresh and fouled ballast tha...
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Simulation Ballasted Track Behavior: Numerical Treatment and Field Application', International Journal of Geomechanics, vol. 17, no. 6, pp. 1-12.
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The load deformation of ballasted rail tracks subjected to cyclic loading is investigated experimentally using a large-scale track process simulation apparatus and numerically through a combined discrete element-finite-difference approach. Laboratory tests were performed to examine the deformation and degradation of ballast subjected to cyclic loading at 15 Hz and a lateral confinement of 10 kPa. The laboratory results reveal that ballast undergoes significant deformation during the initial load cycles, followed by gradually increasing deformation attaining a steady value toward the end of testing. A numerical model based on a combined discrete element method (DEM) and finite-difference method (FDM) is introduced to study the load-deformation response of the ballast assembly while considering interaction between the ballast aggregates and the subgrade layer. In this coupled model, the discrete ballast grains are modeled by DEM, and the subgrade domain is modeled as a continuum by FDM. Interface elements are introduced to transmit the interacting forces and displacements between adjoining material domains in which the DEM transfers contact forces to the FDM, and then the FDM updates the displacements, which provides subsequent input into the DEM. This computational cycle continues with the increasing number of loading cycles. The numerical model is validated by comparing the predicted cyclic load-deformation response with the laboratory measurements. Contact force distributions and stress contours in the assembly are analyzed and presented graphically to interpret the behavior of the model track, and the effects that subgrade stiffness have on the axial strain and bond breakage of the ballast are investigated. This combined DEM-FDM analysis is also used to analyze the load deformation of an instrumented track in the town of Singleton, Australia, and the numerical predictions are compared with the field data.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Stabilization of track substructure with geo-inclusions—experimental evidence and DEM simulation', International Journal of Rail Transportation, vol. 5, no. 2, pp. 63-86.
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This article reviews on current knowledge of rail track geomechanics, including several important concepts and topics related to laboratory testing and computational modelling, to study the shear stress-strain and deformation of ballast improved by geosynthetics and recycled rubber mats. The effect that impact loads have on ballast degradation and its mitigation due to resilient synthetic mats (i.e. rubber mats) between the ballast and the subballast is investigated using large-scale impact-testing apparatus. Computational modelling with finite element and discrete element methods are increasingly being used to model ballasted tracks reinforced with geosynthetics to capture the continuum media of formation soils and the discrete nature of ballast aggregates. The article focuses on reviewing previous studies by the University of Wollongong on ballasted track substructure and highlights some practical implications whereby innovation progresses from theory to practice.
Ngo, QH, Nguyen, NP, Nguyen, CN, Tran, TH & Ha, QP 2017, 'Fuzzy sliding mode control of an offshore container crane', Ocean Engineering, vol. 140, pp. 125-134.
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© 2017 A fuzzy sliding mode control strategy for offshore container cranes is investigated in this study. The offshore operations of loading and unloading containers are performed between a mega container ship, called the mother ship, and a smaller ship, called the mobile harbor (MH), which is equipped with a container crane. The MH is used to transfer the containers, in the open sea, and deliver them to a conventional stevedoring port, thereby minimizing the port congestion and also eliminating the need of expanding outwards. The control objective during the loading and unloading process is to keep the payload in a desired tolerance in harsh conditions of the MH motion. The proposed control strategy combines a fuzzy sliding mode control law and a prediction algorithm based on Kalman filtering for the MH roll angle. Here, the sliding surface is designed to incorporate the desired trolley trajectory while suppressing the sway motion of the payload. To improve the control performance, the discontinuous gain of the sliding control is adjusted with fuzzy logic tuning schemes with respect to the sliding function and its rate of change. Chattering is further reduced by a saturation function. Simulation and experimental results are provided to verify the effectiveness of the proposed control system for offshore container cranes.
Ngoc, PHA & Ha, Q 2017, 'On exponential stability of linear non-autonomous functional differential equations of neutral type', International Journal of Control, vol. 90, no. 3, pp. 438-446.
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© 2016 Informa UK Limited, trading as Taylor & Francis Group. General linear non-autonomous functional differential equations of neutral type are considered. A novel approach to exponential stability of neutral functional differential equations is presented. Consequently, explicit criteria are derived for exponential stability of linear non-autonomous functional differential equations of neutral type. A brief discussion to the obtained results and illustrative examples are given.
Nguyen, DD, Chang, SW, Cha, JH, Jeong, SY, Yoon, YS, Lee, SJ, Tran, MC & Ngo, HH 2017, 'Dry semi-continuous anaerobic digestion of food waste in the mesophilic and thermophilic modes: New aspects of sustainable management and energy recovery in South Korea', Energy Conversion and Management, vol. 135, pp. 445-452.
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© 2016 Elsevier Ltd In this study, parallel, bench-scale, mesophilic and thermophilic, dry, semi-continuous anaerobic digestion (DScAD) of Korea food waste (FW, containing 22% total solids (TS) and 20% volatile solids (VS)) was investigated thoroughly under varying operational conditions, including hydraulic retention times (HRTs) and organic loading rates (OLRs). The aim was to evaluate the start-up, stability, overall removal efficiency, and inhibitory effects of toxic compounds on process performance over a long-term operation lasting 100 days. The results from both digesters indicate that the simultaneous reduction of VS and the production of gas improved as the HRT decreased or the OLR increased. The highest average rates of VS reduction (79.67%) and biogas production (162.14 m 3 biogas/ton of FW, 61.89% CH 4 ), at an OLR of 8.62 ± 0.34 kg VS/m 3 day (25 days of HRT), were achieved under thermophilic DScAD. In addition, the average rates of reduction of VS and the production of biogas in thermophilic DScAD were higher by 6.88% and 16.4%, respectively, than were those in mesophilic DScAD. The inhibitory effects of ammonia, H 2 S, and volatile fatty acids (VFAs) on methane production was not clear from either of the digesters, although, apparently, their concentrations did fluctuate. This fluctuation could be attributed to the self-adaptation of the microbial well. However, digestion that was more stable and faster was observed under thermophilic conditions compared with that under mesophilic conditions. Based on our results, the optimum operational parameters to improve FW treatment and achieve higher energy yields could be determined, expanding the application of DScAD in treating organic wastes.
Nguyen, DD, Yeop, JS, Choi, J, Kim, S, Chang, SW, Jeon, B-H, Guo, W & Ngo, HH 2017, 'A new approach for concurrently improving performance of South Korean food waste valorization and renewable energy recovery via dry anaerobic digestion under mesophilic and thermophilic conditions', Waste Management, vol. 66, pp. 161-168.
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Dry semicontinuous anaerobic digestion (AD) of South Korean food waste (FW) under four solid loading rates (SLRs) (2.30-9.21kg total solids (TS)/m(3)day) and at a fixed TS content was compared between two digesters, one each under mesophilic and thermophilic conditions. Biogas production and organic matter reduction in both digesters followed similar trends, increasing with rising SLR. Inhibitor (intermediate products of the anaerobic fermentation process) effects on the digesters' performance were not observed under the studied conditions. In all cases tested, the digesters' best performance was achieved at the SLR of 9.21kg TS/m(3)day, with 74.02% and 80.98% reduction of volatile solids (VS), 0.87 and 0.90m(3) biogas/kg VSremoved, and 0.65 (65% CH4) and 0.73 (60.02% CH4) m(3) biogas/kg VSfed, under mesophilic and thermophilic conditions, respectively. Thermophilic dry AD is recommended for FW treatment in South Korea because it is more efficient and has higher energy recovery potential when compared to mesophilic dry AD.
Nguyen, DD, Yoon, YS, Bui, XT, Kim, SS, Chang, SW, Guo, W & Ngo, HH 2017, 'Influences of operational parameters on phosphorus removal in batch and continuous electrocoagulation process performance', Environmental Science and Pollution Research, vol. 24, no. 32, pp. 25441-25451.
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© 2017, Springer-Verlag GmbH Germany. Performance of an electrocoagulation (EC) process in batch and continuous operating modes was thoroughly investigated and evaluated for enhancing wastewater phosphorus removal under various operating conditions, individually or combined with initial phosphorus concentration, wastewater conductivity, current density, and electrolysis times. The results revealed excellent phosphorus removal (72.7–100%) for both processes within 3–6 min of electrolysis, with relatively low energy requirements, i.e., less than 0.5 kWh/m 3 for treated wastewater. However, the removal efficiency of phosphorus in the continuous EC operation mode was better than that in batch mode within the scope of the study. Additionally, the rate and efficiency of phosphorus removal strongly depended on operational parameters, including wastewater conductivity, initial phosphorus concentration, current density, and electrolysis time. Based on experimental data, statistical model verification of the response surface methodology (RSM) (multiple factor optimization) was also established to provide further insights and accurately describe the interactive relationship between the process variables, thus optimizing the EC process performance. The EC process using iron electrodes is promising for improving wastewater phosphorus removal efficiency, and RSM can be a sustainable tool for predicting the performance of the EC process and explaining the influence of the process variables.
Nguyen, DD, Yoon, YS, Nguyen, ND, Bach, QV, Bui, XT, Chang, SW, Le, HS, Guo, W & Ngo, HH 2017, 'Enhanced efficiency for better wastewater sludge hydrolysis conversion through ultrasonic hydrolytic pretreatment', Journal of the Taiwan Institute of Chemical Engineers, vol. 71, pp. 244-252.
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© 2016 Taiwan Institute of Chemical Engineers.The major requirements for accelerating the process of anaerobic digestion and energy production are breaking the structure of waste activated sludge (WAS), and transforming it into a soluble form suitable for biodegradation. This work investigated and analysed a novel bench-scale ultrasonic system for WAS disruption and hydrolysis using ultrasonic homogenization. Different commercial sonoreactors were used at low frequencies under a variety of operating conditions (intensity, density, power, sonication time, and total suspended solids) to evaluate the effects of the equipment on sludge hydrolysis and to generate new insights into the empirical models and mechanisms applicable to the real-world processing of wastewater sludge. A relationship was established between the operating parameters and the experimental data. Results indicated an increase in sonication time or ultrasonic intensity correlated with improved sludge hydrolysis rates, sludge temperature, and reduction rate of volatile solids (33.51%). It also emerged that ultrasonication could effectively accelerate WAS hydrolysis to achieve disintegration within 5-10 min, depending on the ultrasonic intensity. This study also determined multiple alternative parameters to increase the efficiency of sludge treatment and organic matter reduction, and establish the practicality of applying ultrasonics to wastewater sludge pretreatment.
Nguyen, H, Cai, C & Chen, F 2017, 'Automatic classification of traffic incident's severity using machine learning approaches', IET Intelligent Transport Systems, vol. 11, no. 10, pp. 615-623.
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During daily work at a Transport Management Centre (TMC), the operators have to record and process a large volume of traffic information especially incident records. Their tasks involve manual classification of the data and then decide appropriate operations to clear the incidents on time. A real‐time automatic decision support system can minimise an operator's responded time and hence reduce congestion. Besides standard descriptions (e.g. incident location, date, time, lanes affected), severity is an important criteria that operators have to evaluate based on all available information before any control commands can be issued. The NSW TMC and the research organisation Data61 in Sydney have collaborated to discover and visualise frequent patterns in historical incident response records, leading to the automatic classification of severity levels among past incidents using advanced machine learning, active learning and outlier detection techniques. The experiments were executed using 4 years TMC's incident logs from 2011 to 2014 which includes >40,000 records. The classification model achieved nearly 90% accuracy in five‐fold cross‐validation and is expected to help the TMC to improve its procedures, response plans, and resource allocations.
Nguyen, H, Liu, W & Chen, F 2017, 'Discovering Congestion Propagation Patterns in Spatio-Temporal Traffic Data.', IEEE Trans. Big Data, vol. 3, no. 2, pp. 169-180.
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Traffic congestion is a condition of a segment in the road network where the traffic demand is greater than the available
road capacity. The detection of unusual traffic patterns including congestions is a significant research problem in the data mining and
knowledge discovery community. However, to the best of our knowledge, the discovery of propagations, or causal interactions among
detected traffic congestions has not been appropriately investigated before. In this research, we introduce algorithms which construct
causality trees from congestions and estimate their propagation probabilities based on temporal and spatial information of the
congestions. Frequent sub-structures of these causality trees reveal not only recurring interactions among spatio-temporal
congestions, but potential bottlenecks or flaws in the designs of existing traffic networks. Our algorithms have been validated by
experiments on a travel time data set recorded from an urban road network.
Nguyen, L, Fatahi, B & Khabbaz, H 2017, 'Development of a Constitutive Model to Predict the Behavior of Cement-Treated Clay during Cementation Degradation: C3 Model', International Journal of Geomechanics, vol. 17, no. 7, pp. 04017010-04017010.
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© 2017 American Society of Civil Engineers. Many researchers have indicated how cementation allows treated soft clays to sustain a higher yield mean effective stress at the same void ratio as its reconstituted state, and thus, the strength of clay treated with cement increases because the cement and clay particles bond together. However, the void ratio of cement-treated clay decreases significantly in isotropic consolidation and triaxial conditions when subjected to a high mean effective stress, particularly beyond the initial yield stress. Laboratory experiments have shown that the cementation of clay gradually diminishes as the mean effective stress increases as a result of the degradation of cementation bonds. Thus, the failure envelope of cement-treated clay gradually merges with the reconstituted clay-cement mixture at high mean effective stresses. Furthermore, the shear strength of cement-treated clay is influenced by the shear degradation induced by shear deformation. In this study, by combining the mean effective stress and shear degradation, a constitutive model, referred to as the C3 model, based on the critical state framework, was developed to simulate the behavior of cement-treated clay. The proposed model includes a modified mean effective stress, a nonlinear failure envelope, a nonassociated plastic potential function, and a general stress-strain relationship to simulate the prepeak and postpeak deviatoric stress states, including the softening behavior of cement-treated clay. In this study, triaxial tests (drained and undrained) were conducted on Ballina clay treated with 10 and 12% cement and Kaolin clay treated with 5 and 10% cement, and the results are reported and discussed. The proposed model was evaluated by comparing its predictions with the triaxial test results reported on the cement-treated Ballina clay and Kaolin clay. The proposed constitutive model gave reliable predictions that agreed with the experimental results and captu...
Nguyen, LN, Hai, FI, McDonald, JA, Khan, SJ, Price, WE & Nghiem, LD 2017, 'Continuous transformation of chiral pharmaceuticals in enzymatic membrane bioreactors for advanced wastewater treatment', Water Science and Technology, vol. 76, no. 7, pp. 1816-1826.
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This study demonstrates continuous enantiomeric inversion and further biotransformation of chiral profens including ibuprofen, naproxen and ketoprofen by an enzymatic membrane bioreactor (EMBR) dosed with laccase. The EMBR showed non-enantioselective transformations, with high and consistent transformation of both (R)- and (S)-ibuprofen (93 ± 6%, n= 10), but lower removals of both enantiomers of naproxen (46 ± 16%, n= 10) and ketoprofen (48 ± 17%, n= 10). Enantiomeric analysis revealed a bidirectional but uneven inversion of the profens, for example 14% inversion of (R)- to (S)- compared to 4% from (S)- to (R)-naproxen. With redox-mediator addition, the enzymatic chiral inversion of both (R)- and (S)-profens remained unchanged, although the overall conversion became enantioselective; except for (S)-naproxen, the addition of redox mediator promoted the degradation of (R)-profens only.
Nguyen, LV, Kodagoda, S, Ranasinghe, R & Dissanayake, G 2017, 'Adaptive Placement for Mobile Sensors in Spatial Prediction Under Locational Errors', IEEE Sensors Journal, vol. 17, no. 3, pp. 794-802.
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This paper addresses the problem of driving robotic sensors for an energy-constrained mobile wireless network in efficiently monitoring and predicting spatial phenomena, under data locational errors. The paper first discusses how errors of mobile sensor locations affect estimating and predicting the spatial physical processes, given that spatial field to be monitored is modeled by a Gaussian process. It then proposes an optimality criterion for designing optimal sampling paths for the mobile robotic sensors given the localization uncertainties. Although the optimization problem is optimally intractable, it can be resolved by a polynomial approximation algorithm, which is proved to be practically feasible in an energy-constrained mobile sensor network. More importantly, near-optimal solutions of this navigation problem are guaranteed by a lower bound within 1-(1/e) of the optimum. The performance of the proposed approach is evaluated on simulated and real-world data sets, where impact of sensor location errors on the results is demonstrated by comparing the results with those obtained by using noise-less data locations.
Nguyen, M, Kim, S, Tran, TT, Xu, Z-Q, Kianinia, M, Toth, M & Aharonovich, I 2017, 'Nanoassembly of quantum emitters in hexagonal boron nitride and gold nanospheres', Nanoscale, vol. 10, no. 5, pp. 2267-2274.
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Assembly of quantum nanophotonic systems with plasmonic resonators areimportant for fundamental studies of single photon sources as well as foron-chip information processing. In this work, we demonstrate controllablenanoassembly of gold nanospheres with ultra-bright quantum emitters in 2Dlayered hexagonal boron nitride (hBN). We utilize an atomic force microscope(AFM) tip to precisely position gold nanospheres to close proximity of thequantum emitters and observe the resulting emission enhancement andfluorescence lifetime reduction. A fluorescence enhancement of over 300% isachieved experimentally for quantum emitters in hBN, with a radiative quantumefficiency of up to 40% and a saturated count rate in excess of 5 millioncounts/s. Our results are promising for future employment of quantum emittersin hBN for integrated nanophotonic devices and plasmonic based nanosensors.
Nguyen, N-P, Ngo, HQ, Duong, TQ, Tuan, HD & da Costa, DB 2017, 'Full-Duplex Cyber-Weapon With Massive Arrays', IEEE Transactions on Communications, vol. 65, no. 12, pp. 5544-5558.
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© 2017 IEEE. In order to enhance secrecy performance of protecting scenarios, understanding the illegitimate side is crucial. In this paper, from the perspective of the illegitimate side, the security attack from a full-duplex cyber-weapon equipped with massive antenna arrays is considered. To evaluate the behavior of the proposed cyber-weapon, we develop a closed-form, a tight approximation, and asymptotic expressions of the achievable ergodic secrecy rate with taking into consideration imperfect channel estimation at the cyber-weapon. The results show that even under some disadvantage conditions, i.e., imperfect channel estimation and self-interference, the full-duplex massive array cyber-weapon can disable traditional physical layer protecting schemes, i.e., increasing the transmit power and the number of antennas at the legitimate transmitter. In addition, when a transmit power optimization scheme for maximizing the difference between the eavesdropping rate and the legitimate rate is applied at the full-duplex cyber-weapon, the malicious attack is even more dangerous. The results also reveal that when the legitimate side faces an advance adversary, it is essential to prevent important information in the training phases exposing to the illegitimate side.
Nguyen, TN, Nguyen, TT & Pansuk, W 2017, 'Experimental study of the punching shear behavior of high performance steel fiber reinforced concrete slabs considering casting directions', Engineering Structures, vol. 131, pp. 564-573.
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Nguyen, TT & Indraratna, B 2017, 'Experimental and numerical investigations into hydraulic behaviour of coir fibre drain', Canadian Geotechnical Journal, vol. 54, no. 1, pp. 75-87.
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Over many decades, natural fibre bundles have been widely used for drainage and filtration applications because of their favourable hydraulic conductivity and abundance in Asian countries. In recent times, natural (biodegradable) coir and jute drains, which are environmentally friendly, have been considered in lieu of conventional geosynthetic wick drains for soft clay consolidation in Australian coastal regions. However, there is a lack of a computational framework to predict the hydraulic behaviour of fibre drains on the basis of micromechanical (fabric) characteristics. Employing computational fluid dynamics (CFD) coupled with the discrete element method (DEM) to model the hydraulic behaviour of fibrous materials has shown promise in an earlier 2016 study by Nguyen and Indraratna, which considered an idealized parallel arrangement of fibres for simplicity. This paper aims to broaden the application of the coupled CFD–DEM technique to real fibres (coconut coir) considering both nontwisted and twisted fibre bundles that have more complex porous structure. The hydraulic conductivity determined from the numerical approach is validated with the experimental results, and also compared with the analytical prediction based on the conventional Kozeny–Carmen (KC) approach. The current study shows that the CFD–DEM technique can capture well the fluid flow characteristics of a nonuniform fibrous structure, including dense twisted coir bundles.
Nguyen, TT & Indraratna, B 2017, 'The permeability of natural fibre drains, capturing their micro-features', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 170, no. 3, pp. 123-136.
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Natural fibres such as jute and coir are emerging as distinct alternatives to synthetic geomaterials, and in recent years they have been used increasingly for drainage and filtration in field applications. However, these naturally occurring materials are extremely variable in micro-characteristics such as the size, uniformity and shape of their fibres, while there is a lack of studies addressing how these differences can affect the hydraulic behaviour of fibrous media. This paper offers a laboratory study of the influence of micro-features on the hydraulic conductivity of fibre drain. Non-twisted and twisted fibre drains made from jute and coir were subjected to hydraulic conductivity testing and micro-analyses. Experimental results show a considerable contribution of the size characteristics of fibre to the hydraulic behaviour of the drain. A less-rounded shape of fibre and a larger twisting angle of the drain can increase the fluid–fibre contact area and the corresponding tortuosity of flow, which significantly reduces the drain permeability. The way in which the Kozeny–Carmen analytical approach can be adopted to predict the permeability of a fibre drain is discussed based on the experimental results, considering various micro-factors including the size of fibre, uniformity and the associated porosity.
Nguyen, T-T, Bui, X-T, Luu, V-P, Nguyen, P-D, Guo, W & Ngo, H-H 2017, 'Removal of antibiotics in sponge membrane bioreactors treating hospital wastewater: Comparison between hollow fiber and flat sheet membrane systems', Bioresource Technology, vol. 240, pp. 42-49.
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© 2017 Elsevier Ltd Hollow fiber (HF) and flat sheet (FS) Sponge MBRs were operated at 10–20 LMH flux treating hospital wastewater. Simultaneous nitrification denitrification (SND) occurred considerably with TN removal rate of 0.011–0.020 mg TN mg VSS−1 d−1. Furthermore, there was a remarkable removal of antibiotics in both Sponge MBRs, namely Norfloxacin (93–99% (FS); 62–86% (HF)), Ofloxacin (73–93% (FS); 68–93% (HF)), Ciprofloxacin (76–93% (FS); 54–70% (HF)), Tetracycline (approximately 100% for both FS and HF) and Trimethoprim (60–97% (FS); 47–93% (HF). Whereas there was a quite high removal efficiency of Erythromycin in Sponge MBRs, with 67–78% (FS) and 22–48% (HF). Moreover, a slightly higher removal of antibiotics in FS than in HF achieved, with the removal rate being of 0.67–32.40 and 0.44–30.42 µg mg VSS−1 d−1, respectively. In addition, a significant reduction of membrane fouling of 2–50 times was achieved in HF-Sponge MBR for the flux range.
Nguyen, TV 2017, 'Individualized Assessment of Fracture Risk: Contribution of “Osteogenomic Profile”', Journal of Clinical Densitometry, vol. 20, no. 3, pp. 353-359.
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Over the past decade, several genetic variants or genes for osteoporosis have been identified through genome-wide association studies and candidate gene association studies. These genetic variants are common in the general population but have modest effect sizes, with odds ratio ranging from 1.1 to 1.5. Thus, the utility of any single variant is limited. However, theoretical and empirical studies have suggested that a profiling of multiple variants that are associated with bone phenotypes (i.e., "osteogenomic profile") can improve the accuracy of fracture prediction and classification beyond that obtained by conventional clinical risk factors. These results support the view that an osteogenomic profile, when integrated into existing models, can help clinicians and patients alike to better assess the risk fracture for an individual, and raise the possibility of personalized osteoporosis care.
Nguyen, TV & Eisman, JA 2017, 'Fracture Risk Assessment: From Population to Individual', Journal of Clinical Densitometry, vol. 20, no. 3, pp. 368-378.
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© 2017 The International Society for Clinical Densitometry Fracture caused by osteoporosis remains a major public health burden on contemporary populations because fracture is associated with a substantial increase in the risk of mortality. Early identification of high-risk individuals for prevention is a priority in osteoporosis research. Over the past decade, few risk prediction models, including the Garvan Fracture Risk Calculator (Garvan) and FRAX®, have been developed to provide absolute (individualized) risk of fracture. Recent validation studies suggested that the area under the receiver operating characteristic curve in fracture discrimination ranged from 0.61 to 0.83 for FRAX® and from 0.63 to 0.88 for Garvan, with hip fractures having a better discrimination than fragility fractures as a group. Although the prognostic performance of Garvan and FRAX® for fracture prediction is not perfect and there is room for further improvement, these predictive models can aid patients and doctors communicate about fracture risk in the medium term and to make rational decisions. However, the application of these predictive models in making decisions for an individual should take into account the individual's perception of the importance of fracture relative to other diseases.
Nguyen, TV, Ho-Le, TP & Le, UV 2017, 'International collaboration in scientific research in Vietnam: an analysis of patterns and impact', Scientometrics, vol. 110, no. 2, pp. 1035-1051.
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Nguyen, V-D, Duong, TQ, Tuan, HD, Shin, O-S & Poor, HV 2017, 'Spectral and Energy Efficiencies in Full-Duplex Wireless Information and Power Transfer', IEEE Transactions on Communications, vol. 65, no. 5, pp. 2220-2233.
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© 2017 IEEE. A communication system is considered consisting of a full-duplex multiple-antenna base station (BS) and multiple single-antenna downlink users (DLUs) and single-antenna uplink users (ULUs), where the latter need to harvest energy for transmitting information to the BS. The communication is thus divided into two phases. In the first phase, the BS uses all available antennas for conveying information to DLUs and wireless energy to ULUs via information and energy beamforming, respectively. In the second phase, ULUs send their independent information to the BS using their harvested energy while the BS transmits the information to the DLUs. In both the phases, the communication is operated at the same time and over the same frequency band. The aim is to maximize the sum rate and energy efficiency under ULU achievable information throughput constraints by jointly optimizing beamforming and time allocation. The utility functions of interest are nonconcave and the involved constraints are nonconvex, so these problems are computationally troublesome. To address them, path-following algorithms are proposed to arrive at least at local optima. The proposed algorithms iteratively improve the objectives with convergence guaranteed. Simulation results demonstrate that they achieve rapid convergence and outperform conventional solutions.
Nguyen, V-D, Tuan, HD, Duong, TQ, Poor, HV & Shin, AO-S 2017, 'Precoder Design for Signal Superposition in MIMO-NOMA Multicell Networks', IEEE Journal on Selected Areas in Communications, vol. 35, no. 12, pp. 2681-2695.
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The throughput of users with poor channel conditions, such as those at a celledge, is a bottleneck in wireless systems. A major part of the power budgetmust be allocated to serve these users in guaranteeing their quality-of-service(QoS) requirement, hampering QoS for other users and thus compromising thesystem reliability. In nonorthogonal multiple access (NOMA), the messageintended for a user with a poor channel condition is decoded by itself and byanother user with a better channel condition. The message intended for thelatter is then successively decoded by itself after canceling the interferenceof the former. The overall information throughput is thus improved by thisparticular successive decoding and interference cancellation. This paper aimsto design linear precoders/beamformers for signal superposition at the basestations of NOMA multi-input multi-output multi-cellular systems to maximizethe overall sum throughput subject to the users' QoS requirements, which areimposed independently on the users' channel condition. This design problem isformulated as the maximization of a highly nonlinear and nonsmooth functionsubject to nonconvex constraints, which is very computationally challenging.Path-following algorithms for its solution, which invoke only a simple convexproblem of moderate dimension at each iteration are developed. Generating asequence of improved points, these algorithms converge at least to a localoptimum. Extensive numerical simulations are then provided to demonstrate theirmerit.
Nguyen, V-D, Tuan, HD, Duong, TQ, Shin, O-S & Poor, HV 2017, 'Joint Fractional Time Allocation and Beamforming for Downlink Multiuser MISO Systems', IEEE Communications Letters, vol. 21, no. 12, pp. 2650-2653.
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It is well-known that the traditional transmit beamforming at a base station(BS) to manage interference in serving multiple users is effective only whenthe number of users is less than the number of transmit antennas at the BS.Non-orthogonal multiple access (NOMA) can improve the throughput of users withpoorer channel conditions by compromising their own privacy because other userswith better channel conditions can decode the information of users in poorerchannel state. NOMA still prefers that the number of users is less than thenumber of antennas at the BS transmitter. This paper resolves such issues byallocating separate fractional time slots for serving the users with similarchannel conditions. This enables the BS to serve more users within the timeunit while the privacy of each user is preserved. The fractional times andbeamforming vectors are jointly optimized to maximize the system's throughput.An efficient path-following algorithm, which invokes a simple convex quadraticprogram at each iteration, is proposed for the solution of this challengingoptimization problem. Numerical results confirm its versatility.
Ni, W, Abolhasan, M, Hagelstein, B, Liu, RP & Wang, X 2017, 'A New Trellis Model for MAC Layer Cooperative Retransmission Protocols', IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3448-3461.
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© 1967-2012 IEEE. Comparison studies on timer-based distributed cooperative retransmission protocols are challenging, given a variety of backoff techniques. We propose a new unified model, which can characterize a wide range of cooperative retransmission protocols. The key idea is a new trellis diagram that extrapolates the retransmission probabilities in each timeslot to the entire cooperative process. Following the trellis, performance metrics, such as success rate and collision intensity, can be derived in a structured manner. The new trellis model, coupled with Markov techniques, can be also extended to analyze the distributed binary exponential backoff processes of cooperative retransmissions. Confirmed by simulations, the proposed trellis model accurately reveals the impact of the relays' relative locations and density on different protocols. Our model also has the potential to be used as a management tool to adaptively configure protocol parameters.
Ni, W, Wu, W & Li, K 2017, 'A message efficient intersection control algorithm for intelligent transportation in smart cities', Future Generation Computer Systems, vol. 76, pp. 339-349.
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Ni, W, Ye, J, Guo, Y, Cheng, C, Lin, Z, Li, Y, Wang, H, Yu, Y, Li, Q, Huang, S, Shao, Z & Wang, C 2017, 'Decisive role of mixed‐valence structure in colossal dielectric constant of LaFeO3', Journal of the American Ceramic Society, vol. 100, no. 7, pp. 3042-3049.
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AbstractThe role of mixed‐valence structure in colossal dielectric constant (CDC) behavior has been investigated in LaFeO3 ceramics by tuning the ratio of Fe2+/Fe3+ through substituting Al for Fe. The ratio of Fe2+/Fe3+ is decreased gradually from 1.0 to 0.0 by increasing the concentration of Al3+. Two clear‐cut correlations have been found: (i) the relationship between the CDC behavior and the ratio of Fe2+/Fe3+ follows an exponential function and (ii) the activation energy of the polaron relaxation is proportional to , where is the intrinsic dielectric constant. These findings underscore the role of the mixed‐valence structure in CDC behavior and suggest that adjusting the mixed‐valence structure through doping/alloying can be a promising strategy to achieve superior CDC behavior in transition‐metal oxides.
Niazi, M, Mahmood, S, Alshayeb, M, Baqais, AAB & Gill, AQ 2017, 'Motivators for adopting social computing in global software development: An empirical study', Journal of Software: Evolution and Process, vol. 29, no. 8, pp. e1872-e1872.
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Copyright © 2017 John Wiley & Sons, Ltd. Managing communication in collaborative global software development (GSD) projects is both critical and challenging. While social computing has received much attention from practitioners, social computing adoption is still an emerging research area in GSD. This research paper provides a review of the academic research in social computing and identifies motivators for adopting social computing in the GSD context. We applied the systematic literature review (SLR) and questionnaire survey with 35 software industry experts to address the research objective. Firstly, we implemented a formal SLR approach and identified an initial set of social computing adoption motivators. Secondly, a questionnaire survey was developed based on the SLR and was tested by means of a pilot study. The findings of this combined SLR and questionnaire survey indicate that real-time communication and coordination, knowledge acquisition, expert feedback, and information sharing are the key factors that motivate social computing adoption in GSD projects. The results of t test (ie, t =.558, P =.589) show that there is no significant difference between the findings of SLR and questionnaire. The results of this study suggest the need for developing social computing strategies and policies to guide the strategic adoption of social computing tools in GSD projects.
Nicholson, AP, Irfansyah, AN, Jenkins, J, Hamilton, TJ & Lehmann, T 2017, 'A Statistical Design Approach Using Fixed and Variable Width Transconductors for Positive-Feedback Gain-Enhancement OTAs', IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 25, no. 6, pp. 1966-1977.
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© 2017 IEEE. The positive-feedback gain-enhancement operational transconductance amplifier (OTA) design is a promising architecture to scale into deep submicron CMOS. Ever smaller CMOS process nodes require analog circuit designs that can overcome the area-power-matching relation. We introduce a Nauta OTA with a split architecture consisting of fixed width and digitally programmable variable width transconductors utilizing the minimum grid-spacing of the CMOS process enabling an active mismatch cancelation technique. A variation-aware statistical design practice is introduced to analyze the sizing of transconductors, computing code-word solutions for statistically likely solutions, and estimating average maximum dc gain over the entire code-space of many simulated OTAs. Prototypes of a 8-bit differential OTA in 180-nm CMOS designed using the Nauta structure fixed width and digitally programmable variable width architecture achieves an average maximum dc gain of 60 dB, simulated unity gain frequency of 4.6 GHz, and a figure-of-merit of 1 GHz/mW.
Nie, L, Zhang, L, Yan, Y, Chang, X, Liu, M & Shaoling, L 2017, 'Multiview Physician-Specific Attributes Fusion for Health Seeking', IEEE Transactions on Cybernetics, vol. 47, no. 11, pp. 3680-3691.
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© 2013 IEEE. Community-based health services have risen as important online resources for resolving users health concerns. Despite the value, the gap between what health seekers with specific health needs and what busy physicians with specific attitudes and expertise can offer is being widened. To bridge this gap, we present a question routing scheme that is able to connect health seekers to the right physicians. In this scheme, we first bridge the expertise matching gap via a probabilistic fusion of the physician-expertise distribution and the expertise-question distribution. The distributions are calculated by hypergraph-based learning and kernel density estimation. We then measure physicians attitudes toward answering general questions from the perspectives of activity, responsibility, reputation, and willingness. At last, we adaptively fuse the expertise modeling and attitude modeling by considering the personal needs of the health seekers. Extensive experiments have been conducted on a real-world dataset to validate our proposed scheme.
Niktash, A & Huynh, BP 2017, 'ICCM2015: A Comparison of RANS and LES Computational Methods in Analyzing Ventilation Flow Through a Room Fitted with a Two-Sided Windcatcher', International Journal of Computational Methods, vol. 14, no. 03, pp. 1750021-1750021.
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A windcatcher is a structure for providing natural ventilation using wind power; it is usually fitted on the roof of a building to exhaust the inside stale air to the outside and supplies the outside fresh air into the building interior space working by pressure difference between outside and inside of the building. In this paper, the behavior of free wind flow through a three-dimensional room fitted with a centered position two-canal bottom shape windcatcher model is investigated numerically, using a commercial computational fluid dynamics (CFD) software package and LES (Large Eddy Simulation) CFD method. The results have been compared with the obtained results for the same model but using RANS (Reynolds Averaged Navier–Stokes) CFD method. The model with its surrounded space has been considered in both method. It is found that the achieved results for the model from LES method are in good agreement with RANS method’s results for the same model.
Nimmy, SF, Kamal, MS, Hossain, MI, Dey, N, Ashour, AS & Shi, F 2017, 'Neural Skyline Filtering for Imbalance Features Classification', International Journal of Computational Intelligence and Applications, vol. 16, no. 03, pp. 1750019-1750019.
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In the current digitalized era, large datasets play a vital role in features extractions, information processing, knowledge mining and management. Sometimes, existing mining approaches are not sufficient to handle large volume of datasets. Biological data processing also suffers for the same issue. In the present work, a classification process is carried out on large volume of exons and introns from a set of raw data. The proposed work is designed into two parts as pre-processing and mapping-based classification. For pre-processing, three filtering techniques have been used. However, these traditional filtering techniques face difficulties for large datasets due to the long required time during large data processing as well as the large required memory size. In this regard, a mapping-based neural skyline filtering approach is designed. Randomized algorithm performed the mapping for large volume of datasets based on objective function. The objective function determines the randomized size of the datasets according to the homogeneity. Around 200 million DNA base pairs have been used for experimental analysis. Experimental result shows that mapping centric filtering outperforms other filtering techniques during large data processing.
Niyato, D, Hoang, DT, Wang, P & Han, Z 2017, 'Cyber Insurance for Plug-In Electric Vehicle Charging in Vehicle-to-Grid Systems', IEEE Network, vol. 31, no. 2, pp. 38-46.
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© 1986-2012 IEEE. V2G systems bring many benefits to power systems in stabilizing energy demand and supply fluctuations as well as to PEV users in reducing energy costs. To achieve the maximum efficiency of V2G systems, data communication plays an important role. However, it is subject to cyber attack and failure, which hinder the effectiveness of V2G systems. In this article, we introduce a novel concept of using cyber insurance to transfer cyber risk from a user to a third party in PEV charging. We first introduce V2G systems and briefly discuss the cyber risks. Additionally, the basic concepts of cyber insurance are presented. We then introduce the use of cyber insurance to remove the risk of paying high energy costs of PEV charging due to the unavailability of data communication. We show that the PEV user can achieve the maximum benefit in deciding to charge its PEV and to buy insurance.
No, Y, Li, J & Zreiqat, H 2017, 'Doped Calcium Silicate Ceramics: A New Class of Candidates for Synthetic Bone Substitutes', Materials, vol. 10, no. 2, pp. 153-153.
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Doped calcium silicate ceramics (DCSCs) have recently gained immense interest as a new class of candidates for the treatment of bone defects. Although calcium phosphates and bioactive glasses have remained the mainstream of ceramic bone substitutes, their clinical use is limited by suboptimal mechanical properties. DCSCs are a class of calcium silicate ceramics which are developed through the ionic substitution of calcium ions, the incorporation of metal oxides into the base binary xCaO–ySiO2 system, or a combination of both. Due to their unique compositions and ability to release bioactive ions, DCSCs exhibit enhanced mechanical and biological properties. Such characteristics offer significant advantages over existing ceramic bone substitutes, and underline the future potential of adopting DCSCs for clinical use in bone reconstruction to produce improved outcomes. This review will discuss the effects of different dopant elements and oxides on the characteristics of DCSCs for applications in bone repair, including mechanical properties, degradation and ion release characteristics, radiopacity, and biological activity (in vitro and in vivo). Recent advances in the development of DCSCs for broader clinical applications will also be discussed, including DCSC composites, coated DCSC scaffolds and DCSC-coated metal implants.
Nobbs, M & Blamires, SJ 2017, 'Fiddler crab spatial distributions are influenced by physiological stressors independent of sympatric interactions', Journal of Experimental Marine Biology and Ecology, vol. 491, pp. 19-26.
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Nobis, M, Herrmann, D, Warren, SC, Kadir, S, Leung, W, Killen, M, Magenau, A, Stevenson, D, Lucas, MC, Reischmann, N, Vennin, C, Conway, JRW, Boulghourjian, A, Zaratzian, A, Law, AM, Gallego-Ortega, D, Ormandy, CJ, Walters, SN, Grey, ST, Bailey, J, Chtanova, T, Quinn, JMW, Baldock, PA, Croucher, PI, Schwarz, JP, Mrowinska, A, Zhang, L, Herzog, H, Masedunskas, A, Hardeman, EC, Gunning, PW, del Monte-Nieto, G, Harvey, RP, Samuel, MS, Pajic, M, McGhee, EJ, Johnsson, A-KE, Sansom, OJ, Welch, HCE, Morton, JP, Strathdee, D, Anderson, KI & Timpson, P 2017, 'A RhoA-FRET Biosensor Mouse for Intravital Imaging in Normal Tissue Homeostasis and Disease Contexts', Cell Reports, vol. 21, no. 1, pp. 274-288.
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Norjannah, B, Ong, HC & Masjuki, HH 2017, 'Effects of methanol and enzyme pretreatment to Ceiba pentandra biodiesel production', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 39, no. 14, pp. 1548-1555.
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Norouzi, M, Miro, JV & Dissanayake, G 2017, 'Planning Stable and Efficient Paths for Reconfigurable Robots On Uneven Terrain', Journal of Intelligent & Robotic Systems, vol. 87, no. 2, pp. 291-312.
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© 2017, Springer Science+Business Media Dordrecht. An analytical strategy to generate stable paths for reconfigurable mobile robots such as those equipped with manipulator arms and/or flippers, operating in an uneven environment whilst also meeting additional navigational objectives is hereby proposed. The suggested solution looks at minimising the length of the traversed path and the energy expenditure in changing postures, and also accounts for additional constraints in terms of sensor visibility and traction. This is particularly applicable to operations such as search and rescue where observing the environment for locating victims is the major objective, although this technique can be generalised to incorporate other potentially conflicting objectives (e.g. maximising ground clearance for a legged robot). The validity of the proposed approach is evaluated with two popular graph-based planners (A* and RRT) on a multi-tracked robot fitted with a manipulator arm and a range camera. Two challenging 3D terrain data sets have been employed: one obtained whilst operating the robot in a mock-up urban search and rescue (USAR) arena, and a second one, a reference on-line data set acquired on the quasi-outdoor rover testing facility at the University of Toronto Institute for Aerospace Studies (UTIAS).
Nourbakhsh, N, Chen, F, Wang, Y & Calvo, RA 2017, 'Detecting Users’ Cognitive Load by Galvanic Skin Response with Affective Interference', ACM Transactions on Interactive Intelligent Systems, vol. 7, no. 3, pp. 1-20.
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Experiencing high cognitive load during complex and demanding tasks results in performance reduction, stress, and errors. However, these could be prevented by a system capable of constantly monitoring users’ cognitive load fluctuations and adjusting its interactions accordingly. Physiological data and behaviors have been found to be suitable measures of cognitive load and are now available in many consumer devices. An advantage of these measures over subjective and performance-based methods is that they are captured in real time and implicitly while the user interacts with the system, which makes them suitable for real-world applications. On the other hand, emotion interference can change physiological responses and make accurate cognitive load measurement more challenging. In this work, we have studied six galvanic skin response (GSR) features in detection of four cognitive load levels with the interference of emotions. The data was derived from two arithmetic experiments and emotions were induced by displaying pleasant and unpleasant pictures in the background. Two types of classifiers were applied to detect cognitive load levels. Results from both studies indicate that the features explored can detect four and two cognitive load levels with high accuracy even under emotional changes. More specifically, rise duration and accumulative GSR are the common best features in all situations, having the highest accuracy especially in the presence of emotions.
Nur, T, Loganathan, P, Kandasamy, J & Vigneswaran, S 2017, 'Removal of strontium from aqueous solutions and synthetic seawater using resorcinol formaldehyde polycondensate resin', Desalination, vol. 420, pp. 283-291.
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© 2017 Elsevier B.V. Strontium (Sr) is a valuable metal found in abundance in seawater. However, its recovery from seawater has received little attention despite its many industrial applications. Batch and column adsorption experiments were conducted on the removal of Sr by resorcinol formaldehyde (RF) resin in the presence of co-existing cations at pH 7.5–8.5, where maximum adsorption was found. Batch adsorption capacities of cations followed the decreasing order of Sr > Ca > Mg > K, the order being the same as that of reduction of negative zeta potential. The adsorption data for Sr, Ca and Mg satisfactorily fitted to the Langmuir adsorption model with maximum adsorption capacities of 2.28, 1.25 and 1.15 meq/g, respectively. Selectivity coefficients for Sr with respect to other metals showed that Sr was selectively adsorbed on RF. Column adsorption data for Sr only solution fitted well to the Thomas model. Sr adsorption capacity in the presence of seawater concentrations of Ca, Mg, K and Na was reduced in both batch and column experiments with highest effect from Ca and Mg. However, if Ca and Mg are removed prior to RF adsorption process by precipitation, the negative effect of these ions on Sr removal can be significantly reduced.
Nurhadi, M, Chandren, S, Yuan, LS, Ho, CS, Indra Mahlia, TM & Nur, H 2017, 'Titania-Loaded Coal Char as Catalyst in Oxidation of Styrene with Aqueous Hydrogen Peroxide', International Journal of Chemical Reactor Engineering, vol. 15, no. 1, pp. 45-55.
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AbstractTitania-loaded coal char catalyst was successfully prepared. The preparation steps involved pyrolysis of low rank coal at different temperatures and durations, sulfonation, impregnation of titanium(IV) isopropoxide, and then heating at 110 °C. It is found that the coal chars’ surfaces were rough after sulfonation and impregnation, while large pore volume, high surface area and carbon composition were observed at low pyrolysis temperature for short duration. These properties contributed to high selectivity towards benzaldehyde (> 90 %) at 600 °C (0.5–2 h)) in styrene oxidation using aqueous hydrogen peroxide as the oxidant.
Nuryani, NA, Harjito, B, Yahya, I, Solikhah, M, Chai, R & Lestari, A 2017, 'Atrial fibrillation detection using support vector machine and electrocardiographic descriptive statistics', International Journal of Biomedical Engineering and Technology, vol. 24, no. 3, pp. 225-225.
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This paper proposes a new technique for detecting atrial fibrillation (AF). The method employs electrocardiographic features and support vector machine (SVM). The features include descriptive statistics of electrocardiographic RR interval. The RR interval is the distance in time between two consecutive R-peaks of electrocardiogram. AF detections using SVM with different electrocardiographic features and different SVM free parameters are explored. Employing SVM with the optimal free parameters and all the proposed electrocardiographic features, we find an AF detection technique with a comparable performance. The best performance obtained by the technique is 98.47% and 97.84%, in terms of sensitivity and specificity.
Oakes, SR, Gallego-Ortega, D, Stanford, PM, Junankar, S, Au, WWY, Kikhtyak, Z, von Korff, A, Sergio, CM, Law, AMK, Castillo, LE, Allerdice, SL, Young, AIJ, Piggin, C, Whittle, B, Bertram, E, Naylor, MJ, Roden, DL, Donovan, J, Korennykh, A, Goodnow, CC, O’Bryan, MK & Ormandy, CJ 2017, 'A mutation in the viral sensor 2’-5’-oligoadenylate synthetase 2 causes failure of lactation', PLOS Genetics, vol. 13, no. 11, pp. e1007072-e1007072.
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Oberst, S, Bann, G, Lai, JCS & Evans, TA 2017, 'Cryptic termites avoid predatory ants by eavesdropping on vibrational cues from their footsteps', Ecology Letters, vol. 20, no. 2, pp. 212-221.
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AbstractEavesdropping has evolved in many predator–prey relationships. Communication signals of social species may be particularly vulnerable to eavesdropping, such as pheromones produced by ants, which are predators of termites. Termites communicate mostly by way of substrate‐borne vibrations, which suggest they may be able to eavesdrop, using two possible mechanisms: ant chemicals or ant vibrations. We observed termites foraging within millimetres of ants in the field, suggesting the evolution of specialised detection behaviours. We found the termite Coptotermes acinaciformis detected their major predator, the ant Iridomyrmex purpureus, through thin wood using only vibrational cues from walking, and not chemical signals. Comparison of 16 termite and ant species found the ants‐walking signals were up to 100 times higher than those of termites. Eavesdropping on passive walking signals explains the predator detection and foraging behaviours in this ancient relationship, which may be applicable to many other predator–prey relationships.
Oberst, S, Marburg, S & Hoffmann, N 2017, 'Determining periodic orbits via nonlinear filtering and recurrence spectra in the presence of noise', Procedia Engineering, vol. 199, pp. 772-777.
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Olmati, P, Vamvatsikos, D & Stewart, MG 2017, 'Safety factor for structural elements subjected to impulsive blast loads', International Journal of Impact Engineering, vol. 106, pp. 249-258.
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Design of blast loaded structures is usually carried out following a deterministic rather than a probabilistic approach. The design load scenario would cover the plausible load conditions (typically some conservative estimate) that a structure would experience if an explosion occurs but the probability that the structure will satisfy the design performances for the considered scenario remains unknown. Applying a performance-based design framework typically requires arduous Monte Carlo simulations, but a probabilistic design could also be achieved by a single structural analysis when consistent safety factors are applied to the load and the structural resistance. Such a factor is proposed herein for the case of components subjected to impulsive blast loads. The dependence of the safety factor on the amount of explosive, stand-off distance and their variability is estimated numerically and provided by means of regression formulas. A design example using the proposed safety factor is carried out and Monte Carlo simulation is used for verification. The results confirm the validity of the proposed safety factor approach and its applicability for the performance-based design of blast loaded structures using the current design practice methods.
Ong, ZC, Mohd Mishani, MB, Chong, WT, Soon, RS, Ong, HC & Ismail, Z 2017, 'Identification of optimum Calophyllum inophyllum bio-fuel blend in diesel engine using advanced vibration analysis technique', Renewable Energy, vol. 109, pp. 295-304.
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Ovalle, A, Hably, A, Bacha, S, Ramos, G & Hossain, JM 2017, 'Escort Evolutionary Game Dynamics Approach for Integral Load Management of Electric Vehicle Fleets', IEEE Transactions on Industrial Electronics, vol. 64, no. 2, pp. 1358-1369.
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This paper proposes an application of an evolutionary game dynamics called the escort dynamics (ED) for the decentralized load management of plug-in electric vehicles (PEV). Different from earlier contributions, in the present approach, PEVs work together in a fair scheme in order to provide several ancillary services to the grid: Load shifting, active power balancing, and partial supply of reactive power demand on each phase of the distribution transformer. Meanwhile, batteries are guaranteed to be fully charged according to the constraints imposed by the owners. In the proposed formulation, chargers can be either three phase or single phase; however, in this paper, only three-phase chargers are considered. The key concepts behind ED, especially for escort functions, are provided at the beginning of this paper. Based on these concepts, the assumptions and analogies followed for the construction of the proposed approach are explained in detail, especially for the proposed definition of escort functions. A multipopulation scenario is proposed for the interaction of several PEVs using local ED routines. This interaction among populations follows another well-known evolutionary game dynamics called the best reply dynamics. Performance is evaluated using real data measured from a distribution transformer from the SOREA utility grid company in the region of Savoie, France.
Pagano, D & Liu, D 2017, 'An approach for real-time motion planning of an inchworm robot in complex steel bridge environments', Robotica, vol. 35, no. 6, pp. 1280-1309.
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SUMMARYPath planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach.
Paimin, AN, Hadgraft, RG, Prpic, JK & Alias, M 2017, 'Learning strategies as an enabler of study success', Pertanika Journal of Social Sciences and Humanities, vol. 25, no. May, pp. 157-165.
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Engineering students enrol in engineering without a clear understanding of how they can achieve success in the field. The current study explores study strategies of engineering undergraduates across two geographical locations, Malaysia and Australia. Qualitative data were collected using semi-structured interviews, in which 16 final-year engineering undergraduates volunteered to participate. Data were analysed using a thematic coding approach and the NVivo software was used to assist with the coding process. The results suggested that engineering students at universities in both locations used very similar learning strategies to achieve different success outcomes such as to fulfil assessment criteria, to achieve a personal goal or success, to endure with challenges, to overcome challenges, to survive after failure and to keep persisting in the programme. Integrating knowledge, visualising engineering applications, optimising the use of learning materials and mastering engineering skills are examples of strategies that were frequently used by the students. The level of importance of each strategy is context dependent.
Pain, A, Chen, Q, Nimbalkar, S & Zhou, Y 2017, 'Evaluation of seismic passive earth pressure of inclined rigid retaining wall considering soil arching effect', Soil Dynamics and Earthquake Engineering, vol. 100, pp. 286-295.
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© 2017 Elsevier Ltd Evaluation of seismic passive earth pressure is an important topic of research in geotechnical engineering. In this study seismic passive pressure on an inclined rigid retaining wall supporting horizontal cohesionless backfill is estimated considering arching effect. A planar failure surface is considered in the present analysis. Seismic forces are considered to be pseudo-static in nature. The effect of different parameters on the seismic passive earth pressure is studied in details. The normal stress distribution along the depth of the backfill is found to be nonlinear in nature. Friction angle between wall and the backfill soil has the most significant effect on the distribution of normal stress along the depth of the backfill. The point of application of seismic passive pressure shifts gradually downward for higher seismic forces. Present method is validated with the experimental results available in the literature for static conditions. Comparison of present method with other theories is also presented showing the merit of the present study. Arching effect in the backfill should be considered for high values of wall inclination angle as the present seismic passive resistance is found to be the lowest as compared to other theoretical solutions.
Palmer, S, Litvinova, K, Dunaev, A, Yubo, J, McGloin, D & Nabi, G 2017, 'Optical redox ratio and endogenous porphyrins in the detection of urinary bladder cancer: A patient biopsy analysis', Journal of Biophotonics, vol. 10, no. 8, pp. 1062-1073.
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© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Bladder cancer is among the most common cancers in the UK and conventional detection techniques suffer from low sensitivity, low specificity, or both. Recent attempts to address the disparity have led to progress in the field of autofluorescence as a means to diagnose the disease with high efficiency, however there is still a lot not known about autofluorescence profiles in the disease. The multi-functional diagnostic system “LAKK-M” was used to assess autofluorescence profiles of healthy and cancerous bladder tissue to identify novel biomarkers of the disease. Statistically significant differences were observed in the optical redox ratio (a measure of tissue metabolic activity), the amplitude of endogenous porphyrins and the NADH/porphyrin ratio between tissue types. These findings could advance understanding of bladder cancer and aid in the development of new techniques for detection and surveillance. (Figure presented.).
Pan, S, Wu, J, Zhu, X, Long, G & Zhang, C 2017, 'Boosting for graph classification with universum', Knowledge and Information Systems, vol. 50, no. 1, pp. 53-77.
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© 2016, Springer-Verlag London. Recent years have witnessed extensive studies of graph classification due to the rapid increase in applications involving structural data and complex relationships. To support graph classification, all existing methods require that training graphs should be relevant (or belong) to the target class, but cannot integrate graphs irrelevant to the class of interest into the learning process. In this paper, we study a new universum graph classification framework which leverages additional “non-example” graphs to help improve the graph classification accuracy. We argue that although universum graphs do not belong to the target class, they may contain meaningful structure patterns to help enrich the feature space for graph representation and classification. To support universum graph classification, we propose a mathematical programming algorithm, ugBoost, which integrates discriminative subgraph selection and margin maximization into a unified framework to fully exploit the universum. Because informative subgraph exploration in a universum setting requires the search of a large space, we derive an upper bound discriminative score for each subgraph and employ a branch-and-bound scheme to prune the search space. By using the explored subgraphs, our graph classification model intends to maximize the margin between positive and negative graphs and minimize the loss on the universum graph examples simultaneously. The subgraph exploration and the learning are integrated and performed iteratively so that each can be beneficial to the other. Experimental results and comparisons on real-world dataset demonstrate the performance of our algorithm.
Pan, S, Wu, J, Zhu, X, Long, G & Zhang, C 2017, 'Task Sensitive Feature Exploration and Learning for Multitask Graph Classification', IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 744-758.
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© 2016 IEEE. Multitask learning (MTL) is commonly used for jointly optimizing multiple learning tasks. To date, all existing MTL methods have been designed for tasks with feature-vector represented instances, but cannot be applied to structure data, such as graphs. More importantly, when carrying out MTL, existing methods mainly focus on exploring overall commonality or disparity between tasks for learning, but cannot explicitly capture task relationships in the feature space, so they are unable to answer important questions, such as what exactly is shared between tasks and what is the uniqueness of one task differing from others? In this paper, we formulate a new multitask graph learning problem, and propose a task sensitive feature exploration and learning algorithm for multitask graph classification. Because graphs do not have features available, we advocate a task sensitive feature exploration and learning paradigm to jointly discover discriminative subgraph features across different tasks. In addition, a feature learning process is carried out to categorize each subgraph feature into one of three categories: 1) common feature; 2) task auxiliary feature; and 3) task specific feature, indicating whether the feature is shared by all tasks, by a subset of tasks, or by only one specific task, respectively. The feature learning and the multiple task learning are iteratively optimized to form a multitask graph classification model with a global optimization goal. Experiments on real-world functional brain analysis and chemical compound categorization demonstrate the algorithm's performance. Results confirm that our method can be used to explicitly capture task correlations and uniqueness in the feature space, and explicitly answer what are shared between tasks and what is the uniqueness of a specific task.
Pan, Y, Dong, D & Petersen, IR 2017, 'Dark Modes of Quantum Linear Systems', IEEE Transactions on Automatic Control, vol. 62, no. 8, pp. 4180-4186.
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Panahian, M, Ghosh, S & Ding, G 2017, 'Assessing Potential for Reduction in Carbon Emissions in a Multi-unit of Residential Development in Sydney', Procedia Engineering, vol. 180, pp. 591-600.
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© 2017 The Authors. There is an increase in the construction of multi-unit residential buildings around inner Sydney in the past few years. The energy consumption in Australia has increased by approximately 30% and associated carbon dioxide emissions. This research examines a large multi-unit residential case study located close to the Sydney's Central Business District (CBD). Current energy consumption for the common areas such as the basement, car parks, lobbies, etc. and water usage for gardens are estimated using the actual data on electricity and water usage. Potential for reduction in energy consumption and their equivalent carbon footprint values are examined. Three carbon emissions reduction strategies include: savings from electricity generation from roof solar PV installation; rainwater harvesting from the roof and minimising annual water loss by evaporation in swimming pools reducing energy demand for water supply. In addition, carbon benefits provided by the trees are calculated using an urban forest assessment tool. Recommendations suggest that installation of solar PV on the roof, using an appropriate swimming pool cover, rainwater harvesting and a better tree canopy cover collectively could improve the overall CO2 footprint performance of the selected case study.
Pang, T, Li, Y, Kang, H, Sun, G, Fang, J & Li, Q 2017, 'On functionally-graded crashworthy shape of conical structures for multiple load cases', Journal of Mechanical Science and Technology, vol. 31, no. 6, pp. 2861-2873.
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© 2017, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany. Many studies on energy absorbers have been focused on tapered tubes because they have significant advantages in crashworthiness and provide a desired constant load-deflection response. However, few studies have been reported on tapered tubes with nonlinearlyvariable diameters along the longitudinal direction. This paper presents thin-walled Functionally graded tapered tube (FGTT) with a diameter varying nonlinearly subject to axial (0°) and oblique (10°, 20°, 30°) impacts. To explore the advantages of FGTT, conventional Straight/Conical circular tube (SCT/CCT) with the same mass are compared; and FGTTs with a gradient exponent n > 1 are found to be preferable to others in terms of energy absorption capacity under small impact angles. Then, crashworthiness analyses of different crushing distances are conducted and it is found that under a large impact angle (e.g. 20°, 30°), FGTT with a short crushing distance (e.g. 40 mm) have a higher mean crashing force than long crushing distance (e.g. 120 mm), especially for n > 1. In addition, the effect of geometric parameters, such as the gradient exponent n and diameter range ΔD between top (incident) and bottom (distal) diameters of FGTTs, are also studied and it is found that the FGTT with ΔD = 40 mm and n > 1 exhibits better crashworthiness than the others under small impact angles (0°, 10°). This paper demonstrates that such FGTT structures have a certain potential to be an energy absorber.
Pansuk, W, Nguyen, TN, Sato, Y, Den Uijl, JA & Walraven, JC 2017, 'Shear capacity of high performance fiber reinforced concrete I-beams', Construction and Building Materials, vol. 157, pp. 182-193.
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© 2017 Elsevier Ltd An experimental program was carried out to investigate the shear capacity of High-Performance Fiber-Reinforced Concrete (HPFRC) I-beams. The main parameters were assigned as the fiber content and presence of shear reinforcement. To study the effect of these main parameters on the shear capacity, testing of six I-beams and other control specimens was conducted. It can be observed from the results of the experimental study that the presence of fibers and shear reinforcement significantly improves the ultimate capacity and structural behavior of HPFRC members. Finally, the experimental results are discussed, and the shear capacity of HPFRC can be estimated by extending the code provisions stated in AFGC-Sétra 2013.
Pathak, N, Chekli, L, Wang, J, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Shon, H 2017, 'Performance of a novel baffled osmotic membrane bioreactor-microfiltration hybrid system under continuous operation for simultaneous nutrient removal and mitigation of brine discharge', Bioresource Technology, vol. 240, pp. 50-58.
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© 2017 Elsevier Ltd The present study investigated the performance of an integrated osmotic and microfiltration membrane bioreactor system for wastewater treatment employing baffles in the reactor. Thus, this reactor design enables both aerobic and anoxic processes in an attempt to reduce the process footprint and energy costs associated with continuous aeration. The process performance was evaluated in terms of water flux, salinity build up in the bioreactor, organic and nutrient removal and microbial activity using synthetic reverse osmosis (RO) brine as draw solution (DS). The incorporation of MF membrane was effective in maintaining a reasonable salinity level (612–1434 mg/L) in the reactor which resulted in a much lower flux decline (i.e. 11.48–6.98 LMH) as compared to previous studies. The stable operation of the osmotic membrane bioreactor–forward osmosis (OMBR-FO) process resulted in an effective removal of both organic matter (97.84%) and nutrient (phosphate 87.36% and total nitrogen 94.28%), respectively.
Pathak, P & Zhang, YX 2017, 'Nonlinear finite element analyses of fiber‐reinforced polymer‐strengthened steel‐reinforced concrete beams under cyclic loading', Structural Concrete, vol. 18, no. 6, pp. 929-937.
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A new finite element model is developed for nonlinear finite element analyses of structural behavior of fiber‐reinforced polymer (FRP)‐strengthened steel‐reinforced concrete (RC) beams under cyclic loading in this paper. All the components of the beam, including concrete, steel rebar, FRP sheet, adhesive, and shear strengthening stirrups, are included in the model. Material nonlinear properties of concrete and steel rebars are accounted for, while the FRP and adhesive are considered to be linearly elastic until rupture. The degradation of each material under cyclic loading is considered and defined using the user‐programmable features in ANSYS. The developed finite element model is validated against experimental results, and demonstrated to be effective for structural analyses of FRP‐strengthened RC beams under cyclic loading. Furthermore, parametric studies are carried out to learn the effects of types, thickness, and length of FRP on the structural behavior of FRP‐strengthened RC beams based on the new model. Research findings are summarized finally.
Pathak, P, Zhang, YX & Teng, X 2017, 'Nonlinear Finite Element Analysis of FRP Strengthened RC Beams with Bond-Slip Effect', International Journal of Computational Methods, vol. 14, no. 03, pp. 1750032-1750032.
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This paper investigates the structural behavior of fiber reinforced polymer (FRP) strengthened reinforced concrete (RC) beams by developing a new simple, efficient and accurate finite element model (FEM-B). In addition to the FRP, concrete and steel rebars, the adhesive and stirrups which have been generally ignored in the reported models from literatures are considered in the new models. At first, a finite element model (FEM-P) is developed assuming perfect bond between concrete, FRP and adhesive interfaces. Then the FEM-P model is expanded to form the FEM-B model by including the bond-slip effect between concrete, FRP and adhesive interfaces. The developed new finite element models (FEM-B and FEM-P) are validated against experimental results and demonstrate to be effective for the structural analysis of FRP strengthened RC beams. Furthermore, parametric studies are carried out to learn the effects of types and thickness of FRP on the structural behavior of FRP strengthened RC beams based on the FEM-B model. The research findings are summarized finally.
Peng, G, Nakamura, S, Zhu, X, Wu, Q & Wang, H 2017, 'An experimental and numerical study on temperature gradient and thermal stress of CFST truss girders under solar radiation', Computers and Concrete, vol. 20, no. 5, pp. 605-616.
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Concrete filled steel tubular (CFST) composite girder is a new type of structures for bridge constructions. The existing design codes cannot be used to predict the thermal stress in the CFST truss girder structures under solar radiation. This study is to develop the temperature gradient curves for predicting thermal stress of the structure based on field and laboratory monitoring data. An in-field testing had been carried out on Ganhaizi Bridge for over two months. Thermal couples were installed at the cross section of the CFST truss girder and the continuous data was collected every 30 minutes. A typical temperature gradient mode was then extracted by comparing temperature distributions at different times. To further verify the temperature gradient mode and investigate the evolution of temperature fields, an outdoor experiment was conducted on a 1:8 scale bridge model, which was installed with both thermal couples and strain gauges. The main factors including solar radiation and ambient temperature on the different positions were studied. Laboratory results were consistent with that from the in-field data and temperature gradient curves were obtained from the in-field and laboratory data. The relationship between the strain difference at top and bottom surfaces of the concrete deck and its corresponding temperature change was also obtained and a method based on curve fitting was proposed to predict the thermal strain under elevated temperature. The thermal stress model for CFST composite girder was derived. By the proposed model, the thermal stress was obtained from the temperature gradient curves. The results using the proposed model were agreed well with that by finite element modelling.
Peng, H, Lan, C, Zheng, Y, Hutvagner, G, Tao, D & Li, J 2017, 'Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite', BMC Bioinformatics, vol. 18, no. 1, pp. 1-17.
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© 2017 The Author(s). Background: MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics. Methods and results: We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs. Conclusions: With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.
Peng, L, Kassotaki, E, Liu, Y, Sun, J, Dai, X, Pijuan, M, Rodriguez-Roda, I, Buttiglieri, G & Ni, B-J 2017, 'Modelling cometabolic biotransformation of sulfamethoxazole by an enriched ammonia oxidizing bacteria culture', Chemical Engineering Science, vol. 173, pp. 465-473.
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© 2017 Elsevier Ltd Antibiotics such as sulfamethoxazole (SFX) are environmentally hazardous after being released into the aquatic environment and challenges remain in the development of engineered prevention strategies. In this work, a mathematical model was developed to describe and evaluate cometabolic biotransformation of SFX and its transformation products (TPs) in an enriched ammonia oxidizing bacteria (AOB) culture. The growth-linked cometabolic biodegradation by AOB, non-growth transformation by AOB and non-growth transformation by heterotrophs were considered in the model framework. The production of major TPs comprising 4-Nitro-SFX, Desamino-SFX and N4-Acetyl-SFX was also specifically modelled. The validity of the model was demonstrated through testing against literature reported data from extensive batch tests, as well as from long-term experiments in a partial nitritation sequencing batch reactor (SBR) and in a combined SBR + membrane aerated biofilm reactor performing nitrification/denitrification. Modelling results revealed that the removal efficiency of SFX increased with the increase of influent ammonium concentration, whereas the influent organic matter, hydraulic retention time and solid retention time exerted a limited effect on SFX biodegradation with the removal efficiencies varying in a narrow range. The variation of influent SFX concentration had no impact on SFX removal efficiency. The established model framework enables interpretation of a range of experimental observations on SFX biodegradation and helps to identify the optimal conditions for efficient removal.
Peng, L, Liu, Y, Sun, J, Wang, D, Dai, X & Ni, B-J 2017, 'Enhancing immobilization of arsenic in groundwater: A model-based evaluation', Journal of Cleaner Production, vol. 166, pp. 449-457.
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© 2017 Elsevier Ltd The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation.
Peng, L, Stewart, MG & Melchers, RE 2017, 'Corrosion and capacity prediction of marine steel infrastructure under a changing environment', Structure and Infrastructure Engineering, vol. 13, no. 8, pp. 988-1001.
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The deterioration of marine steel infrastructure caused by corrosion may be influenced by a changing climate and/or pollution level which may lead to its serviceability and structural failure. However, almost all corrosion research until recently assumed time-invariant environmental conditions. A structural reliability analysis is applied here to simulate steel sheet piles in sea water conditions under a changing environment. Corrosion of marine steel infrastructure is modelled as a spatial time-dependent process including sea water temperature and sea level rise due to global warming and dissolved inorganic nitrogen concentration increase caused by pollution. The steel sheet piles are divided vertically into 70 elements to consider the spatial variability of different corrosion zones and sea level rise effects. Two limit states are considered: (i) stress of steel sheet piles reaches their yield stress and (ii) pitting corrosion perforation to provide an alert to repair or maintenance. The results show that ignoring the effects of a changing environment can underestimate structural capacity failure risks, and pollution will have a more significant effect on capacity of steel sheet piles than sea water temperature and sea level rise caused by global warming.
Peng, S, Yang, A, Cao, L, Yu, S & Xie, D 2017, 'Social influence modeling using information theory in mobile social networks', Information Sciences, vol. 379, pp. 146-159.
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Social influence analysis has become one of the most important technologies in modern information and service industries. Thus, how to measure social influence of one user on other users in a mobile social network is also becoming increasingly important. It is helpful to identify the influential users in mobile social networks, and also helpful to provide important insights into the design of social platforms and applications. However, social influence modeling is an open and challenging issue, and most evaluation models are focused on online social networks, but fail to characterize indirect influence. In this paper, we present a mechanism to quantitatively measure social influence in mobile social networks. We exploit the graph theory to construct a social relationship graph that establishes a solid foundation for the basic understandings of social influence. We present an evaluation model to measure both direct and indirect influence based on the social relationship graph, by introducing friend entropy and interaction frequency entropy to describe the complexity and uncertainty of social influence. Based on the epidemic model, we design an algorithm to characterize propagation dynamics process of social influence, and to evaluate the performance of our solution by using a customized program on the basis of a real-world SMS/MMS-based communication data set. The real world numerical simulations and analysis show that the proposed influence evaluation strategies can characterize the social influence of mobile social networks effectively and efficiently.
Peng, X-F, Liu, J, Han, J-T & Wei, D-B 2017, 'Effect of hot/warm roll-forming process on microstructural evolution and mechanical properties of local thickened U-rib for orthotropic steel deck', Journal of Iron and Steel Research International, vol. 24, no. 3, pp. 335-342.
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© 2017 Central Iron and Steel Research Institute To improve the strength-toughness of traditional U-rib (TUR) and solve the problem of insufficient penetration between TUR and deckplate, a new local thickened U-rib (LTUR) has been proposed to improve the fatigue resistance of the weld joint under the premise of not increasing thickness and strength of the TUR material. And a hot/warm roll-forming process (RFP) adopting partially induction heating to 700—1000 °C was carried out to fabricate LTUR. The deformation behaviors in the forming process and microstructure of LTUR have been investigated. Mechanical properties and fracture mechanism of the LTUR after hot/warm RFP have been systematically discussed. Moreover, the results are compared with those obtained in cold RFP. Mechanical properties of the LTUR deformed above the critical transformation temperature (A c3) show high performance characteristics with marked fatigue resistance and superior toughness. Upon increasing the heating temperature from 700 to 900 °C, the initial coarse ferrite-pearlite structure transform into equiaxed ultrafine ferrite (1—3 μm) and precipitates such as (Nb, Ti)(C, N) are uniformly distributed in the matrix. The average dislocation density of the specimens after hot roll-forming at heating temperature of 900 °C decreases dramatically compared with those of the specimens subjected to the cold RFP. Furthermore, a typical characteristic of ductile fracture mechanism and the high impact energy are more convinced that the specimens deformed above 900 °C have obtained an optimal combination of strength and toughness.
Perera, D, Indraratna, B, Leroueil, S, Rujikiatkamjorn, C & Kelly, R 2017, 'Analytical model for vacuum consolidation incorporating soil disturbance caused by mandrel-driven drains', Canadian Geotechnical Journal, vol. 54, no. 4, pp. 547-560.
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When vacuum preloading is applied with vertical drains, the rate of consolidation can be increased, and the stability of an embankment is enhanced due to the inward lateral movement. The aim of this study is to develop an analytical solution for vacuum preloading that accurately captures the more realistic variations in compressibility and permeability in actual ground conditions as a result of drain installation. The soil samples were obtained from various locations after drain installation to determine the characteristics of soil surrounding the vertical drain in terms of compressibility and permeability. The main differences between the proposed and conventional models are described by considering the stress history and preloading pressure. The effect of pre-consolidation pressure and the magnitude of applied preloading are examined through the dissipation of average excess pore pressure and associated settlement. The analysis of a selected case history employing the writers’ solution indicates improved accuracy of the predictions in comparison to the field measurements.
Pettit, T, Irga, PJ, Abdo, P & Torpy, FR 2017, 'Do the plants in functional green walls contribute to their ability to filter particulate matter?', Building and Environment, vol. 125, pp. 299-307.
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© 2017 Elsevier Ltd Indoor air quality has become a growing concern as people are spending more time indoors, combined with the construction of highly sealed buildings that promote thermal efficiency. Particulate matter (PM) is a common indoor air pollutant, with exposure to high concentrations associated with several detrimental health outcomes. Active botanical biofilters or functional green walls are becoming increasingly efficient and have the potential to mitigate high suspended PM concentrations. These systems, however, require further development before they become competitive with industry standard in-room air filters. Whilst the plant growth substrate in active biofilters can act as a filter medium, it was previously not known whether the plant component of these systems played a function in PM filtration. This study thus examines the influence of the botanical component on active green wall PM single pass removal efficiency (SPRE), with a focus on evaluating the air filtration features of different plant species in green wall modules. All tested botanical biofilters outperformed biofilters that consisted only of substrate. Green walls using different plant species had different single pass removal efficiencies, with fern species recording the highest removal efficiencies across all measured particle sizes (Nephrolepis exaltata bostoniensis SPRE for PM0.3-0.5 and PM5-10 = 45.78% and 92.46% respectively). Higher removal efficiencies were associated with increased pressure drop across the biofilter. An assessment of plant morphological data suggested that the root structure of the plants strongly influenced removal efficiency. These findings demonstrate the potential to enhance active botanical biofiltration technology with appropriate plant species selection.
Pham, HM, Nguyen, SC, Ho-Le, TP, Center, JR, Eisman, JA & Nguyen, TV 2017, 'Association of Muscle Weakness With Post-Fracture Mortality in Older Men and Women: A 25-Year Prospective Study', Journal of Bone and Mineral Research, vol. 32, no. 4, pp. 698-707.
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ABSTRACT Osteoporotic fracture increases the risk of premature mortality. Muscle weakness is associated with both increased fracture risk and low bone mineral density (BMD). However, the role of muscle strength in post-fracture mortality is not well understood. This study examines the change of muscle strength measured at quadriceps (QS) before and after fracture and defines the relationship between muscle strength and post-fracture mortality. The study involved 889 women and 295 men (who were participating in the Dubbo Osteoporosis Study) who had at least one low-trauma fracture (ascertained from X-ray reports) after the age of 50 years. Median follow-up time was 11 years (range 1 to 24). To determine the change in muscle strength before and after a fracture, we selected a subset of 344 women and 99 men who had had at least two muscle strength measurements before the fracture event and a subset of 407 women and 105 men who had had at least two measurements after the fracture. During the follow-up period, 366 (41.2%) women and 150 (50.9%) men died. The annual rate of decrease in height-adjusted muscle strength before fracture was 0.27 kg/m (1.85%) in women and 0.40 kg/m (1.79%) in men. Strength loss after fracture was not significantly different from that before fracture. In women, after adjusting for baseline age and BMD, each SD (5 kg/m) lower height-adjusted pre- and post-fracture quadriceps strength was associated with a 27% (hazard ratio [HR] = 1.27; 95% confidence interval [CI] 1.07, 1.50) and 18% (HR = 1.18; 95% CI 1.01, 1.38) increase in post-fracture mortality risk, respectively. Similarly, in men, each SD (5 kg/m) lower height-adjusted pre- and post-fracture QS was associated with increased mortality before fracture (HR = 1.33; 95% CI 1.09, 1.63) and after fracture (HR = 1.43; 95% CI 1.16, 1.78). Muscle weakness accounted f...
Pham, TT, Leong, PHW, Robinson, PD, Gutzler, T, Jee, AS, King, GG & Thamrin, C 2017, 'Automated quality control of forced oscillation measurements: respiratory artifact detection with advanced feature extraction', Journal of Applied Physiology, vol. 123, no. 4, pp. 781-789.
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The forced oscillation technique (FOT) can provide unique and clinically relevant lung function information with little cooperation with subjects. However, FOT has higher variability than spirometry, possibly because strategies for quality control and reducing artifacts in FOT measurements have yet to be standardized or validated. Many quality control procedures rely on either simple statistical filters or subjective evaluation by a human operator. In this study, we propose an automated artifact removal approach based on the resistance against flow profile, applied to complete breaths. We report results obtained from data recorded from children and adults, with and without asthma. Our proposed method has 76% agreement with a human operator for the adult data set and 79% for the pediatric data set. Furthermore, we assessed the variability of respiratory resistance measured by FOT using within-session variation (wCV) and between-session variation (bCV). In the asthmatic adults test data set, our method was again similar to that of the manual operator for wCV (6.5 vs. 6.9%) and significantly improved bCV (8.2 vs. 8.9%). Our combined automated breath removal approach based on advanced feature extraction offers better or equivalent quality control of FOT measurements compared with an expert operator and computationally more intensive methods in terms of accuracy and reducing intrasubject variability. NEW & NOTEWORTHY The forced oscillation technique (FOT) is gaining wider acceptance for clinical testing; however, strategies for quality control are still highly variable and require a high level of subjectivity. We propose an automated, complete breath approach for removal of respiratory artifacts from FOT measurements, using feature extraction and an interquartile range filter. Our approach offers better or equivalent performance compared with an expert operator, in terms of accuracy and reducing intrasubject variability.
Pham, TT, Moore, ST, Lewis, SJG, Nguyen, DN, Dutkiewicz, E, Fuglevand, AJ, McEwan, AL & Leong, PHW 2017, 'Freezing of Gait Detection in Parkinson's Disease: A Subject-Independent Detector Using Anomaly Scores', IEEE Transactions on Biomedical Engineering, vol. 64, no. 11, pp. 2719-2728.
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© 2012 IEEE. Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of 96% (79%). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of 94% (84%) for ankle and 89% (94%) for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., 3 s versus 7.5 s) and/or lower tolerance (e.g., 0.4 s versus 2 s).
Pham, TT, Thamrin, C, Robinson, PD, McEwan, AL & Leong, PHW 2017, 'Respiratory Artefact Removal in Forced Oscillation Measurements: A Machine Learning Approach', IEEE Transactions on Biomedical Engineering, vol. 64, no. 8, pp. 1679-1687.
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Goal: Respiratory artefact removal for the
forced oscillation technique can be treated as an anomaly
detection problem. Manual removal is currently considered
the gold standard, but this approach is laborious and subjective.
Most existing automated techniques used simple
statistics and/or rejected anomalous data points. Unfortunately,
simple statistics are insensitive to numerous artefacts,
leading to low reproducibility of results. Furthermore,
rejecting anomalous data points causes an imbalance between
the inspiratory and expiratory contributions. Methods:
From a machine learning perspective, such methods
are unsupervised and can be considered simple feature extraction.
We hypothesize that supervised techniques can
be used to find improved features that are more discriminative
and more highly correlated with the desired output.
Features thus found are then used for anomaly detection
by applying quartile thresholding, which rejects complete
breaths if one of its features is out of range. The thresholds
are determined by both saliency and performance
metrics rather than qualitative assumptions as in previous
works. Results: Feature ranking indicates that our new landmark
features are among the highest scoring candidates
regardless of age across saliency criteria. F1-scores, receiver
operating characteristic, and variability of the mean
resistance metrics show that the proposed scheme outperforms
previous simple feature extraction approaches. Our
subject-independent detector, 1IQR-SU, demonstrated approval
rates of 80.6% for adults and 98% for children, higher
than existing methods. Conclusion: Our new features are
more relevant. Our removal is objective and comparable to
the manual method. Significance: This is a critical work to
automate forced oscillation technique quality control.
Pham, VN, Turner, B, Huang, J & Kelly, R 2017, 'Long-term strength of soil-cement columns in coastal areas', Soils and Foundations, vol. 57, no. 4, pp. 645-654.
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Phan, TN, Van Truong, TT, Ha, NB, Nguyen, PD, Bui, XT, Dang, BT, Doan, VT, Park, J, Guo, W & Ngo, HH 2017, 'High rate nitrogen removal by ANAMMOX internal circulation reactor (IC) for old landfill leachate treatment', Bioresource Technology, vol. 234, pp. 281-288.
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© 2017 Elsevier Ltd This study aimed to evaluate the performance of a high rate nitrogen removal lab-scale ANAMMOX reactor, namely Internal Circulation (IC) reactor, for old landfill leachate treatment. The reactor was operated with pre-treated leachate from a pilot Partial Nitritation Reactor (PNR) using a high nitrogen loading rate ranging from 2 to 10 kg N m−3 d−1. High rate removal of nitrogen (9.52 ± 1.11 kg N m−3 d−1) was observed at an influent nitrogen concentration of 1500 mg N L−1. The specific ANAMMOX activity was found to be 0.598 ± 0.026 gN2-N gVSS−1 d−1. Analysis of ANAMMOX granules suggested that 0.5–1.0 mm size granular sludge was the dominant group. The results of DNA analysis revealed that Candidatus Kueneniastuttgartiensis was the dominant species (37.45%) in the IC reactor, whereas other species like uncultured Bacteroidetes bacterium only constituted 5.37% in the system, but they were still responsible for removing recalcitrant organic matter.
Phung, MD, Quach, CH, Dinh, TH & Ha, Q 2017, 'Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection', Automation in Construction, vol. 81, pp. 25-33.
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© 2017 In built infrastructure monitoring, an efficient path planning algorithm is essential for robotic inspection of large surfaces using computer vision. In this work, we first formulate the inspection path planning problem as an extended travelling salesman problem (TSP) in which both the coverage and obstacle avoidance were taken into account. An enhanced discrete particle swarm optimization (DPSO) algorithm is then proposed to solve the TSP, with performance improvement by using deterministic initialization, random mutation, and edge exchange. Finally, we take advantage of parallel computing to implement the DPSO in a GPU-based framework so that the computation time can be significantly reduced while keeping the hardware requirement unchanged. To show the effectiveness of the proposed algorithm, experimental results are included for datasets obtained from UAV inspection of an office building and a bridge.
Phuntsho, S, Kim, JE, Hong, S, Ghaffour, N, Leiknes, T, Choi, JY & Shon, HK 2017, 'A closed-loop forward osmosis-nanofiltration hybrid system: Understanding process implications through full-scale simulation', Desalination, vol. 421, pp. 169-178.
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© 2016 Elsevier B.V. This study presents simulation of a closed-loop forward osmosis (FO)-nanofiltration (NF) hybrid system using fertiliser draw solution (DS) based on thermodynamic mass balance in a full-scale system neglecting the non-idealities such as finite membrane area that may exist in a real process. The simulation shows that the DS input parameters such as initial concentrations and its flow rates cannot be arbitrarily selected for a plant with defined volume output. For a fixed FO-NF plant capacity and feed concentration, the required initial DS flow rate varies inversely with the initial DS concentration or vice-versa. The net DS mass flow rate, a parameter constant for a fixed plant capacity but that increases linearly with the plant capacity and feed concentration, is the most important operational parameter of a closed-loop system. Increasing either of them or both increases the mass flow rate to the system directly affecting the final concentration of the diluted DS with direct energy implications to the NF process. Besides, the initial DS concentration and flow rates are also limited by the optimum recovery rates at which NF process can be operated which otherwise also have direct implications to the NF energy. This simulation also presents quantitative analysis of the reverse diffusion of fertiliser nutrients towards feed brine and the gradual accumulation of feed solutes within the closed system.
Pi, S, Li, A, Wei, W, Feng, L, Zhang, G, Chen, T, Zhou, X, Sun, H & Ma, F 2017, 'Synthesis of a novel magnetic nano-scale biosorbent using extracellular polymeric substances from Klebsiella sp. J1 for tetracycline adsorption', Bioresource Technology, vol. 245, pp. 471-476.
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Pietroni, N, Tarini, M, Vaxman, A, Panozzo, D & Cignoni, P 2017, 'Position-based tensegrity design.', ACM Trans. Graph., vol. 36, pp. 172:1-172:1.
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Pileggi, SF & Hunter, J 2017, 'An ontological approach to dynamic fine-grained Urban Indicators', Procedia Computer Science, vol. 108, pp. 2059-2068.
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© 2017 The Authors. Published by Elsevier B.V. Urban indicators provide a unique multi-disciplinary data framework which social scientists, planners and policy makers employ to understand and analyze the complex dynamics of metropolitan regions. Indicators provide an independent, quantitative measure or benchmark of an aspect of an urban environment, by combining different metrics for a given region. While the current approach to urban indicators involves the systematic accurate collection of the raw data required to produce reliable indicators and the standardization of well-known commonly accepted or widely adopted indicators, the next generation of indicators is expected to support a more dynamic, customizable, fine-grained approach to indicators, via a context of interoperability and linked open data. Within this paper, we address these emerging requirements through an ontological approach aimed at (i) establishing interoperability among heterogeneous data sets, (ii) expressing the high-level semantics of the indicators, (iii) supporting indicator adaptability and dynamic composition for specific applications and (iv) representing properly the uncertainties of the resulting ecosystem.
Plattner, J, Naidu, G, Wintgens, T, Vigneswaran, S & Kazner, C 2017, 'Fluoride removal from groundwater using direct contact membrane distillation (DCMD) and vacuum enhanced DCMD (VEDCMD)', Separation and Purification Technology, vol. 180, pp. 125-132.
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© 2017 Elsevier B.V. Groundwater resources are under growing pressures in water scarce countries. Membrane distillation (MD) is an interesting option for drinking water production from groundwater with elevated salinity and fluoride (F) contamination. A direct contact MD (DCMD) at a moderate feed temperature of 55 °C was able to concentrate a synthetic solution representing F contaminated groundwater. An average initial flux of 13.3 L/m2/h was achieved at 75% water recovery, resulting in only 15–17% flux decline, while producing high quality permeate (96–99% F rejection). Membrane autopsy showed presence of Ca, Na, S and Mg on the used membrane. Particularly, 51–53% F precipitation was estimated in line with the saturation index (SI) model. The used MD membrane with groundwater showed only 10–12% reduction in membrane hydrophobicity, which was largely recovered with simple cleaning. Meanwhile, synthetic groundwater solution spiked with humic substances resulted in brownish deposition on MD membrane, reducing the membrane hydrophobicity significantly by 37–40%. Additionally, DCMD operation with vacuum at the permeate side (vacuum enhanced DCMD; VEDCMD) was beneficial in increasing the permeate flux by 42%. Continuous VEDCMD operation with intermediate membrane cleaning showed positive results in treating F contained groundwater while producing good quality permeate at 67% water recovery.
Polonchuk, L, Chabria, M, Badi, L, Hoflack, J-C, Figtree, G, Davies, MJ & Gentile, C 2017, 'Cardiac spheroids as promising in vitro models to study the human heart microenvironment', Scientific Reports, vol. 7, no. 1, pp. 1-12.
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AbstractThree-dimensional in vitro cell systems are a promising alternative to animals to study cardiac biology and disease. We have generated three-dimensional in vitro models of the human heart (“cardiac spheroids”, CSs) by co-culturing human primary or iPSC-derived cardiomyocytes, endothelial cells and fibroblasts at ratios approximating those present in vivo. The cellular organisation, extracellular matrix and microvascular network mimic human heart tissue. These spheroids have been employed to investigate the dose-limiting cardiotoxicity of the common anti-cancer drug doxorubicin. Viability/cytotoxicity assays indicate dose-dependent cytotoxic effects, which are inhibited by the nitric oxide synthase (NOS) inhibitor L-NIO, and genetic inhibition of endothelial NOS, implicating peroxynitrous acid as a key damaging agent. These data indicate that CSs mimic important features of human heart morphology, biochemistry and pharmacology in vitro, offering a promising alternative to animals and standard cell cultures with regard to mechanistic insights and prediction of toxic effects in human heart tissue.
Popp, J, Matthews, D, Martinez-Coll, A, Mayerhöfer, T & Wilson, BC 2017, 'Challenges in translation: models to promote translation', Journal of Biomedical Optics, vol. 23, no. 02, pp. 1-1.
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We first discuss the main obstacles for clinical translation of biophotonics technologies, in particular, the different valleys of death, after which we present different examples of ways to bridge these gaps, remove the obstacles, and promote clinical translation.
Pourashraf, P, Safaei, F & Franklin, DR 2017, 'A Study of User Perception of the Quality of Video Content Rendered Inside a 3-D Virtual Environment.', IEEE J. Sel. Top. Signal Process., vol. 11, no. 1, pp. 125-137.
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This paper reports on the result of a user study to assess the impact of resolution and frame rate of video on the Quality of Experience of the users, when the video is rendered inside a 3D virtual space, and consequently viewed from arbitrary perspectives. A mathematical model for video rate is presented that expresses the total rate as the product of separate functions of spatial and temporal resolutions. Results from the user study are combined with the model to predict the rate parameters which will result in perceptually acceptable quality using the 3D features of the virtual environment. The results show that by exploiting the insensitivity of users to controlled quality degradation, the downstream network load for the client can be significantly reduced with little or no perceptual impact on the clients.
Pradhan, B, Mohsen Mousavi, S, Golkarian, A, Amir Naghibi, S & Kalantar, B 2017, 'GIS-based Groundwater Spring Potential Mapping Using Data Mining Boosted Regression Tree and Probabilistic Frequency Ratio Models in Iran', AIMS Geosciences, vol. 3, no. 1, pp. 91-115.
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Pradhan, B, Sameen, MI & Kalantar, B 2017, 'Optimized Rule-Based Flood Mapping Technique Using Multitemporal RADARSAT-2 Images in the Tropical Region', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 7, pp. 3190-3199.
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Flood is one of the most common natural disasters in Malaysia. Preparing an accurate flood inventory map is the basic step in flood risk management. Flood detection is a complex process because of the limitation of methodological approaches and cloud coverage over tropical areas. An efficient approach is proposed to identify flooded areas using multitemporal RADARSAT-2 imageries. First, multispectral Landsat image was used to extract and subtract permanent water bodies, and this image was later utilized to extract the same information from multitemporal RADARSAT-2 imageries. Next, water bodies during a flood event were extracted from RADARSAT-2 images. Permanent water bodies, shadow, and paddy were detected from synthetic aperture radar (SAR) images by analyzing their temporal backscattering values. During feature extraction, rule-based object-oriented technique was applied to classify both SAR and Landsat images. Image segmentation during object-based analysis was performed to distinguish the boundaries of various dimensions and scales of objects. Moreover, a Taguchibased method was employed to optimize the segmentation parameters. After segmentation, the rules were defined and images were classified to produce an accurate flood inventory map for the 2014 Kelantan flood. A confusion matrix was generated to evaluate the performance of the classification method. The overall accuracy of 86.16% was achieved for RADARSAT-2 using rule-based classification and optimization technique. The resulting flood inventory map using the proposed approach supported the efficiency of the proposed methodology.
Prasad, M, Lin, C-T, Li, D-L, Hong, C-T, Ding, W-P & Chang, J-Y 2017, 'Soft-Boosted Self-Constructing Neural Fuzzy Inference Network', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 3, pp. 584-588.
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© 2013 IEEE. This correspondence paper proposes an improved version of the self-constructing neural fuzzy inference network (SONFIN), called soft-boosted SONFIN (SB-SONFIN). The design softly boosts the learning process of the SONFIN in order to decrease the error rate and enhance the learning speed. The SB-SONFIN boosts the learning power of the SONFIN by taking into account the numbers of fuzzy rules and initial weights which are two important parameters of the SONFIN, SB-SONFIN advances the learning process by: 1) initializing the weights with the width of the fuzzy sets rather than just with random values and 2) improving the parameter learning rates with the number of learned fuzzy rules. The effectiveness of the proposed soft boosting scheme is validated on several real world and benchmark datasets. The experimental results show that the SB-SONFIN possesses the capability to outperform other known methods on various datasets.
Prasad, M, Liu, Y-T, Li, D-L, Lin, C-T, Shah, RR & Kaiwartya, OP 2017, 'A New Mechanism for Data Visualization with Tsk-Type Preprocessed Collaborative Fuzzy Rule Based System', Journal of Artificial Intelligence and Soft Computing Research, vol. 7, no. 1, pp. 33-46.
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Abstract A novel data knowledge representation with the combination of structure learning ability of preprocessed collaborative fuzzy clustering and fuzzy expert knowledge of Takagi- Sugeno-Kang type model is presented in this paper. The proposed method divides a huge dataset into two or more subsets of dataset. The subsets of dataset interact with each other through a collaborative mechanism in order to find some similar properties within each-other. The proposed method is useful in dealing with big data issues since it divides a huge dataset into subsets of dataset and finds common features among the subsets. The salient feature of the proposed method is that it uses a small subset of dataset and some common features instead of using the entire dataset and all the features. Before interactions among subsets of the dataset, the proposed method applies a mapping technique for granules of data and centroid of clusters. The proposed method uses information of only half or less/more than the half of the data patterns for the training process, and it provides an accurate and robust model, whereas the other existing methods use the entire information of the data patterns. Simulation results show the proposed method performs better than existing methods on some benchmark problems.
Pratama, M, Lu, J, Lughofer, E, Zhang, G & Er, MJ 2017, 'An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks', IEEE Transactions on Fuzzy Systems, vol. 25, no. 5, pp. 1175-1192.
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© 2017 IEEE. The age of online data stream and dynamic environments results in the increasing demand of advanced machine learning techniques to deal with concept drifts in large data streams. Evolving fuzzy systems (EFS) are one of recent initiatives from the fuzzy system community to resolve the issue. Existing EFSs are not robust against data uncertainty, temporal system dynamics, and the absence of system order, because a vast majority of EFSs are designed in the type-1 feedforward network architecture. This paper aims to solve the issue of data uncertainty, temporal behavior, and the absence of system order by developing a novel evolving recurrent fuzzy neural network, called evolving type-2 recurrent fuzzy neural network (eT2RFNN). eT2RFNN is constructed in a new recurrent network architecture, featuring double recurrent layers. The new recurrent network architecture evolves a generalized interval type-2 fuzzy rule, where the rule premise is built upon the interval type-2 multivariate Gaussian function, whereas the rule consequent is crafted by the nonlinear wavelet function. The eT2RFNN adopts a holistic concept of evolving systems, where the fuzzy rule can be automatically generated, pruned, merged, and recalled in the single-pass learning mode. eT2RFNN is capable of coping with the problem of high dimensionality because it is equipped with online feature selection technology. The efficacy of eT2RFNN was experimentally validated using artificial and real-world data streams and compared with prominent learning algorithms. eT2RFNN produced more reliable predictive accuracy, while retaining lower complexity than its counterparts.
Punetha, P, Mohanty, P & Samanta, M 2017, 'Microstructural investigation on mechanical behavior of soil-geosynthetic interface in direct shear test', Geotextiles and Geomembranes, vol. 45, no. 3, pp. 197-210.
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Puthal, D, Mohanty, SP, Nanda, P & Choppali, U 2017, 'Building Security Perimeters to Protect Network Systems Against Cyber Threats [Future Directions]', IEEE Consumer Electronics Magazine, vol. 6, no. 4, pp. 24-27.
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© 2012 IEEE. Due to the wide variety of devices used in computer network systems, cybersecurity plays a major role in securing and improving the performance of the network or system. Although cybersecurity has received a large amount of global interest in recent years, it remains an open research space. Current security solutions in network-based cyberspace provide an open door to attackers by communicating first before authentication, thereby leaving a black hole for an attacker to enter the system before authentication. This article provides an overview of cyberthreats, traditional security solutions, and the advanced security model to overcome current security drawbacks.
Qi, F, Dong, Z, Lamb, D, Naidu, R, Bolan, NS, Ok, YS, Liu, C, Khan, N, Johir, MAH & Semple, KT 2017, 'Effects of acidic and neutral biochars on properties and cadmium retention of soils', Chemosphere, vol. 180, pp. 564-573.
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© 2017 Elsevier Ltd In this study, an acidic biochar and a neutral biochar were applied at 5 wt% into two soils for an 11-month incubation experiment. One Ferrosol soil (Ba) was slightly acidic with low organic matter and the other Dermosol soil (Mt) was slightly alkaline with high organic matter. The acidic (pH = 3.25) wood shaving (WS) biochar had no marked impact on nutrient levels, cation exchange capacity (CEC), pH and acid neutralization capacity (ANC) of either soil. By contrast, the neutral (pH = 7.00) chicken litter (CL) biochar significantly increased major soluble nutrients, pH, ANC of soil Ba. In terms of C storage, 87.9% and 69.5% WS biochar-C can be sequestrated as TOC by soil Ba and Mt, respectively, whereas only 24.0% of CL biochar-C stored in soil Ba and negligible amount in Mt as TOC. Biochars did not have significant effects on soil sorption capacity and sorption reversibility except that CL biochar increased sorption of soil Ba by around 25.4% and decreased desorption by around 50.0%. Overall, the studied acidic C rich WS biochar held little agricultural or remedial values but was favourable for C sequestration. The neutral mineral rich CL biochar may provide short-term agricultural benefit and certain sorption capacities of lower sorption capacity soils, but may be unlikely to result in heightened C sequestration in soils. This is the first study comprehensively examining functions of acidic and neutral biochars for their benefits as a soil amendment and suggests the importance of pre-testing biochars for target purposes prior to their large scale production.
Qi, J & Lu, DD-C 2017, 'A Preventive Approach for Solving Battery Imbalance Issue by Using a Bidirectional Multiple-Input Ćuk Converter Working in DCVM', IEEE Transactions on Industrial Electronics, vol. 64, no. 10, pp. 7780-7789.
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© 1982-2012 IEEE. State of charge (SoC) imbalance among batteries in a battery energy storage system (BESS) degrades the system performance and may lead to safety issue. A bidirectional multiple-input Ćuk converter for the BESS is proposed to prevent batteries from SoC imbalance issue. Compared to the traditional BESS, the battery balancing and voltage/current regulation subsystems are combined into one. As a result, the overall system complexity is significantly reduced. Moreover, the current flow of each battery is self-adjusted according to its terminal voltage. Therefore, the system does not require sophisticated control algorithm for battery balancing. Moreover, the proposed system has no energy dumping and energy transferring between batteries, which avoids unnecessary energy lose. Due to the nature of multiple-input converter structure, the proposed system can handle certain component failure. The proposed approach of designing the BESS has been investigated through simulation and validated experimentally.
Qi, M, Sun, T, Zhang, H, Zhu, M, Yang, W, Shao, D & Voinov, A 2017, 'Maintenance of salt barrens inhibited landward invasion ofSpartinaspecies in salt marshes', Ecosphere, vol. 8, no. 10, pp. e01982-e01982.
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AbstractSpartinaspp. (cordgrasses) often dominates intertidal mudflats and/or low marshes. The landward invasion of these species was typically thought to be restrained by low tidal inundation frequencies and interspecific competition. We noticed that the reported soil salinity levels in some salt marshes were much higher than those at the mean higher high water level, which might inhibit the landward invasion of cordgrass. To test this possibility, we transplantedSpartina alternifloraacross an elevational gradient in an invaded salt marsh in the Yellow River Delta National Nature Reserve, where a salt accumulation zone (i.e., salt barren) was previously observed. We found thatS. alterniflorawas significantly inhibited by the salt barren in high marsh regions, although it performed better at upland and low marsh regions. A common garden experiment further elucidated thatS. alternifloraperformed best at low salinity levels and that this species is less sensitive to inundation frequency. Our results indicated that the salt barren inhibited the landward invasion ofS. alterniflorain salt marshes and provided a natural barrier to protect the upland from invasion. Though field observations suggest thatS. alternifloracould propagate along tidal channels, which provide low‐salinity corridors for the dispersal of propagules, natural salt barrens can inhibit the landward invasion ofSpartinain salt marshes. However, artificial disturbances that break the salt barren band in salt marshes (e.g., artificial ditches) might accelerate the invasion ofSpartinaspp. This new finding should alert salt marsh managers to pay attention to artificial ditches and/or other human activities when attempting to controlSpartin...
Qian, J, Wang, L, Wu, Y, Bond, PL, Zhang, Y, Chang, X, Deng, B, Wei, L, Li, Q & Wang, Q 2017, 'Free sulfurous acid (FSA) inhibition of biological thiosulfate reduction (BTR) in the sulfur cycle-driven wastewater treatment process', Chemosphere, vol. 176, pp. 212-220.
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A sulfur cycle-based bioprocess for co-treatment of wet flue gas desulfurization (WFGD) wastes with freshwater sewage has been developed. In this process the removal of organic carbon is mainly associated with biological sulfate or sulfite reduction. Thiosulfate is a major intermediate during biological sulfate/sulfite reduction, and its reduction to sulfide is the rate-limiting step. In this study, the impacts of saline sulfite (the ionized form: HSO3- + SO32-) and free sulfurous acid (FSA, the unionized form: H2SO3) sourced from WGFD wastes on the biological thiosulfate reduction (BTR) activities were thoroughly investigated. The BTR activity and sulfate/sulfite-reducing bacteria (SRB) populations in the thiosulfate-reducing up-flow anaerobic sludge bed (UASB) reactor decreased when the FSA was added to the UASB influent. Batch experiment results confirmed that FSA, instead of saline sulfite, was the true inhibitor of BTR. And BTR activities dropped by 50% as the FSA concentrations were increased from 8.0 × 10-8 to 2.0 × 10-4 mg H2SO3-S/L. From an engineering perspective, the findings of this study provide some hints on how to ensure effective thiosulfate accumulation in biological sulfate/sulfite reduction for the subsequent denitrification/denitritation. Such manipulation would result in higher nitrogen removal rates in this co-treatment process of WFGD wastes with municipal sewage.
Qian, J, Wei, L, Wu, Y, Wang, Q, Fu, X, Zhang, X, Chang, X, Wang, L & Pei, X 2017, 'A comparative study on denitrifying sludge granulation with different electron donors: Sulfide, thiosulfate and organics', Chemosphere, vol. 186, pp. 322-330.
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A comparative study on denitrifying sludge granulation with different electron donors (sulfide, thiosulfate and organics) was carried out. Longer time was spent on sulfide-denitrifying granular sludge (DGS) cultivation (88 days) than thiosulfate- and organics-DGS cultivations (57 days). All the three DGS were characterized in terms of particle size distribution, sludge settling ability (indicated by sludge volume index and settling velocity), permeability (indicated by fractal dimension) and extracellular polymeric substances (EPS, including polysaccharide and protein) secretion. Sludge productions in the three DGS-reactors were also monitored. The key functional microorganisms in three granular reactors were revealed via high through-put pyrosequencing analysis. Batch tests were performed to measure the denitrification activities of each DGS, including both denitratation (NO3- → NO2-) and denitritation (NO2- → N2). We found that thiosulfate-driven denitrifying sludge granulation (TDDSG) should be the most efficient and compact technology for effective BNR in municipal wastewater treatment. The findings of this study suggests the TDDSG could further increase the nitrogen removal potential in an enhanced sulfur cycle-driven bioprocess for co-treatment of wet flue gas desulfurization wastes with fresh sewage depending on three short-cut biological reactions, including: 1) short-cut biological sulfur reduction (SO42-/SO32- → S2O32-); 2) thiosulfate-driven denitritation (S2O32- + NO2- → SO42- + N2↑); and 3) nitritation (NH4+ + O2 → NO2-).
Qian, J, Zhou, J, Wang, L, Wei, L, Li, Q, Wang, D & Wang, Q 2017, 'Direct Cr (VI) bio-reduction with organics as electron donor by anaerobic sludge', Chemical Engineering Journal, vol. 309, pp. 330-338.
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Industrial activities produce lots of Cr (VI)-containing wastewater. This study presented a detailed work on direct Cr (VI) bio-reduction (i.e. Cr (VI) is reduced with organics as electron donor directly) by anaerobic sludge through both batch and long-term experiments. Effects of pH and initial Cr (VI) concentrations on direct Cr (VI) bio-reduction activity were evaluated. The highest direct Cr (VI) bio-reduction rate was achieved at pH 8.0 at 104 mg Cr (VI)/g MLVSS/d (MLVSS: mixed liquor volatile suspended solids), corresponding to the highest protein release (124 mg/g MLVSS) and cell viability (71%). In contrast, the direct Cr (VI) bio-reduction rates were 46, 70 and 82 mg Cr (VI)/g MLVSS/d, respectively, at pH 6.0, 7.0 and 9.0. Also, the direct Cr (VI) bio-reduction activity decreased by 74% when initial Cr (VI) concentration increased from 10 mg/L to 50 mg/L. The contribution of chemical adsorption to Cr (VI) removal was found to be negligible, whereas biosorption played a role in Cr (VI) removal although its role was insignificant. Indirect Cr (VI) bio-reduction (i.e. Cr (VI) is chemically reduced by sulfide produced from biological sulfate reduction) rate (990 mg Cr (VI)/g MLVSS/d) was faster than that (210 mg Cr (VI)/g MLVSS/d) of direct Cr (VI) bio-reduction, indicating that indirect Cr (VI) bio-reduction would dominate the Cr (VI) bio-reduction pathway if both Cr (VI) and sulfate were present. The direct Cr (VI) bio-reduction was then successfully demonstrated in an up-flow anaerobic sludge bed (UASB) reactor, where the Cr (VI) was completely removed with a Cr (VI) removal rate of 1.0 mg Cr (VI)/L/h. 454 pyrosequencing results revealed that direct Cr (VI) bio-reduction related genera were Desulfovibrio, Ochrobactrum and Anaerovorax.
Qiao, M, Liu, L, Yu, J, Xu, C & Tao, D 2017, 'Diversified dictionaries for multi-instance learning', Pattern Recognition, vol. 64, pp. 407-416.
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© 2016 Elsevier Ltd Multiple-instance learning (MIL) has been a popular topic in the study of pattern recognition for years due to its usefulness for such tasks as drug activity prediction and image/text classification. In a typical MIL setting, a bag contains a bag-level label and more than one instance/pattern. How to bridge instance-level representations to bag-level labels is a key step to achieve satisfactory classification accuracy results. In this paper, we present a supervised learning method, diversified dictionaries MIL, to address this problem. Our approach, on the one hand, exploits bag-level label information for training class-specific dictionaries. On the other hand, it introduces a diversity regularizer into the class-specific dictionaries to avoid ambiguity between them. To the best of our knowledge, this is the first time that the diversity prior is introduced to solve the MIL problems. Experiments conducted on several benchmark (drug activity and image/text annotation) datasets show that the proposed method compares favorably to state-of-the-art methods.
Qiao, M, Xu, F & Saha, SC 2017, 'Scaling analysis and numerical simulation of natural convection from a duct', Numerical Heat Transfer, Part A: Applications, vol. 72, no. 5, pp. 355-371.
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Qiao, M, Xu, RYD, Bian, W & Tao, D 2017, 'Fast Sampling for Time-Varying Determinantal Point Processes', ACM Transactions on Knowledge Discovery from Data, vol. 11, no. 1, pp. 1-24.
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Determinantal Point Processes (DPPs) are stochastic models which assign each subset of a base dataset with a probability proportional to the subset’s degree of diversity. It has been shown that DPPs are particularly appropriate in data subset selection and summarization (e.g., news display, video summarizations). DPPs prefer diverse subsets while other conventional models cannot offer. However, DPPs inference algorithms have a polynomial time complexity which makes it difficult to handle large and time-varying datasets, especially when real-time processing is required. To address this limitation, we developed a fast sampling algorithm for DPPs which takes advantage of the nature of some time-varying data (e.g., news corpora updating, communication network evolving), where the data changes between time stamps are relatively small. The proposed algorithm is built upon the simplification of marginal density functions over successive time stamps and the sequential Monte Carlo (SMC) sampling technique. Evaluations on both a real-world news dataset and the Enron Corpus confirm the efficiency of the proposed algorithm.
Qin, C, Ni, W, Tian, H & Liu, RP 2017, 'Fronthaul Load Balancing in Energy Harvesting Powered Cloud Radio Access Networks', IEEE Access, vol. 5, pp. 7762-7775.
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© 2013 IEEE. Enhanced with wireless power transfer capability, cloud radio access network (C-RAN) enables energy-restrained mobile devices to function uninterruptedly. Beamforming of C-RAN has potential to improve the efficiency of wireless power transfer, in addition to transmission data rates. In this paper, we design the beamforming jointly for data transmission and energy transfer, under finite fronthaul capacity of C-RAN. A non-convex problem is formulated to balance the fronthaul requirements of different remote radio heads (RRHs). Norm approximations and relaxations are carried out to convexify the problem to second-order cone programming (SOCP). To improve the scalability of the design to large networks, we further decentralize the SOCP problem using the alternating direction multiplier method (ADMM). A series of reformulations and transformations are conducted, such that the resultant problem conforms to the state-of-The-Art ADMM solver and can be efficiently solved in real time. Simulation results show that the distributed algorithm can remarkably reduce the time complexity without compromising the fronthaul load balancing of its centralized counterpart. The proposed algorithms can also reduce the fronthaul bandwidth requirements by 25% to 50%, compared with the prior art.
Qin, C, Ni, W, Tian, H & Liu, RP 2017, 'Joint Rate Maximization of Downlink and Uplink in Multiuser MIMO SWIPT Systems', IEEE Access, vol. 5, pp. 3750-3762.
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© 2013 IEEE. Beamforming has the potential to improve the efficiency of simultaneous wireless information and power transfer (SWIPT) systems. Existing beamforming techniques have been focused on the downlink of SWIPT systems. In this paper, we optimize the beamformers and transmit duration to maximize the weighted sum rate of both the downlink and uplink in a multiuser multiple-input multiple-output (MIMO) SWIPT system. Specifically, we formulate and transform the problem into a weighted sum mean square error minimization, conduct difference of convex programming to decouple the downlink and uplink, and convert the problem to quadratic programming (QP), which can be solved iteratively in a centralized fashion. We also decentralize the QP problem using dual decompositions, and reduce the time-complexity without compromising the data rate. Moreover, our algorithms are extended to the case under imperfect channel state information. Confirmed by simulations, the proposed decentralization can dramatically reduce the time-complexity by orders of magnitude. The scalability of the proposed approach can be substantially enhanced to support medium to large networks.
Qu, F, Jiang, Z, Wei, D, Chen, Q & Lu, H 2017, 'Study of micro flexible rolling based on grained inhomogeneity', International Journal of Mechanical Sciences, vol. 123, pp. 324-339.
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© 2017 Elsevier Ltd This paper shows an analytical, numerical and experimental investigation to comprehend the role of grained inhomogeneity which plays in micro flexible rolling in terms of the average rolling force and the thickness directional springback of the workpiece after it exits the roll bite zone. Miniature tensile tests and micro hardness tests are accomplished to identify the scattered stress-strain curves for 500 μm thick aluminium alloy 1060 samples with grain size of approximately 23-71 µm and to determine the weighted heterogeneity coefficient for each sample separately, according to which the theoretical calculations and numerical simulations based upon 3D Voronoi tessellation technique have been performed under actual experimental conditions where reductions of 25 to 50 % are selected. The scattering effect associated with the anisotropic nature of single grains has been perceived in the micro flexible rolling process and both the analytical and finite element models developed have been validated via experimental data to hold promise for predicting the rolling force and the thickness directional springback of the workpiece, as well as boosting the thickness profile control performance of the micro flexible rolling mill.
Quin, P, Paul, G & Liu, D 2017, 'Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments.', IEEE Trans Autom. Sci. Eng., vol. 14, no. 2, pp. 869-880.
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© 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection.
Rafeie, M, Welleweerd, M, Hassanzadeh-Barforoushi, A, Asadnia, M, Olthuis, W & Ebrahimi Warkiani, M 2017, 'An easily fabricated three-dimensional threaded lemniscate-shaped micromixer for a wide range of flow rates', Biomicrofluidics, vol. 11, no. 1, pp. 014108-014108.
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Mixing fluid samples or reactants is a paramount function in the fields of micro total analysis system (μTAS) and microchemical processing. However, rapid and efficient fluid mixing is difficult to achieve inside microchannels because of the difficulty of diffusive mass transfer in the laminar regime of the typical microfluidic flows. It has been well recorded that the mixing efficiency can be boosted by migrating from two-dimensional (2D) to three-dimensional (3D) geometries. Although several 3D chaotic mixers have been designed, most of them offer a high mixing efficiency only in a very limited range of Reynolds numbers (Re). In this work, we developed a 3D fine-threaded lemniscate-shaped micromixer whose maximum numerical and empirical efficiency is around 97% and 93%, respectively, and maintains its high performance (i.e., >90%) over a wide range of 1 < Re < 1000 which meets the requirements of both the μTAS and microchemical process applications. The 3D micromixer was designed based on two distinct mixing strategies, namely, the inducing of chaotic advection by the presence of Dean flow and diffusive mixing through thread-like grooves around the curved body of the mixers. First, a set of numerical simulations was performed to study the physics of the flow and to determine the essential geometrical parameters of the mixers. Second, a simple and cost-effective method was exploited to fabricate the convoluted structure of the micromixers through the removal of a 3D-printed wax structure from a block of cured polydimethylsiloxane. Finally, the fabricated mixers with different threads were tested using a fluorescent microscope demonstrating a good agreement with the results of the numerical simulation. We envisage that the strategy used in this work would expand the scope of the micromixer technology by broadening the range of efficient working flow rate and providing an easy way to the fabrication of 3D convoluted microstru...
Rafi, FHM, Hossain, MJ & Lu, J 2017, 'Improved Neutral Current Compensation With a Four-Leg PV Smart VSI in a LV Residential Network', IEEE Transactions on Power Delivery, vol. 32, no. 5, pp. 2291-2302.
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Rafiee, A, Panahi, M & Khalilpour, KR 2017, 'CO 2 utilization through integration of post-combustion carbon capture process with Fischer-Tropsch gas-to-liquid (GTL) processes', Journal of CO2 Utilization, vol. 18, pp. 98-106.
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Graphical abstract: Carbon capture is addressed as a medium term solution while industry and society are in their path towards future clean energies. However, in the absence of demand market and a revenue source for the recovered almost-pure CO2, the remained option, i.e. storage, does not seem to justify the economic feasibility of this climate change mitigation approach. In our current integration study, we consider existence of a Fischer-Tropsch Gas-to-liquid (GTL) plant in the vicinity of a fossil-fuel based power plant. The captured CO2 with post-combustion carbon capture technologies is fed into the GTL plants’ reformer, i.e. a steam reformer or an auto-thermal reformer. We have presented a few case-studies based on optimal process simulation in Aspen Hysys software package. Unlike most of the studies, our objective is to maximize the wax production rate as upgrading could be carried out at demand market side. The results for a 300MW coal-fired plant, and a GTL plant with the capacity of one train of Sasol Oryx GTL plant in Qatar show that an auto-thermal reformer (ATR) based GTL process does not have flexibility for CO2 intake, while all of the captured CO2 fed into the steam-methane reformer (SMR) process could be consumed. In summary, one train of Sasol Oryx GTL plant with a SMR reactor can utilize a net quantity of 105.5tonnes-CO2/h with subtracting the purged CO2. The paper provides a detailed optimization-based data.
Raja Shoib, RSNS, Rashid, ASA & Armaghani, DJ 2017, 'Shaft resistance of bored piles socketed in Malaysian granite', Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, vol. 170, no. 4, pp. 335-352.
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In this paper, an attempt is made to demonstrate the applicability of previously published models for granite formations in Malaysia. A programme of field testing was conducted to measure the axial response of bored piles, with a total of seven bored piles of diameter 1000–1500 mm constructed in decomposed granite, using techniques including the advancing of temporary casing and drilling slurry composed of bentonite fluids. These bored piles were subjected to static load testing in order to verify their integrity and performance, with the results of these load tests evaluated here. It was assumed that the strength of the soil was fully mobilised by the static loading test. The results revealed that the method proposed by Horvath and Kenny provided the best prediction of rock shaft resistance for decomposed granite. Based on the results obtained, it can be deduced that the proposed models based on sedimentary rocks are applicable to decomposed granite and that maximum rock shaft resistance can mobilise up to 1850 kPa in material of rock quality designation >60%.
Raka, A, Naik, G & Chai, R 2017, 'Computational Algorithms Underlying the Time-Based Detection of Sudden Cardiac Arrest via Electrocardiographic Markers', Applied Sciences, vol. 7, no. 9, pp. 954-954.
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Early detection of sudden cardiac arrest (SCA) is critical to prevent serious repercussion such as irreversible neurological damage and death. Currently, the most effective method involves analyzing electrocardiogram (ECG) features obtained during ventricular fibrillation. In this study, data from 10 normal patients and 10 SCA patients obtained from Physiobank were used to statistically compare features, such as heart rate, R-R interval duration, and heart rate variability (HRV) features from which the HRV features were then selected for classification via linear discriminant analysis (LDA) and linear and fine Gaussian support vector machines (SVM) in order to determine the ideal time-frame in which SCA can be accurately detected. The best accuracy was obtained at 2 and 8 min prior to SCA onset across all three classifiers. However, accuracy rates of 75–80% were also obtained at time-frames as early as 50 and 40 min prior to SCA onset. These results are clinically important in the field of SCA, as early detection improves overall patient survival.
Ramalingam, N, Warkiani, ME & Gong, TH-Q 2017, 'Acetylated bovine serum albumin differentially inhibits polymerase chain reaction in microdevices', Biomicrofluidics, vol. 11, no. 3, pp. 034110-034110.
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Bovine serum albumin (BSA) is widely used as an additive in polymerase chain reaction (PCR)-based microfluidic devices to passivate reactors and alleviate nucleic-acid amplification. BSA is available commercially in two types: either acetylated or non-acetylated. A survey of literature indicates that both types of BSA are used in PCR-based microfluidic devices. Our study results reveal that the use of acetylated BSA in PCR micro-devices leads to differential inhibition of PCR, compared to non-acetylated BSA. This result is noticed for the first time, and the differential inhibition generally goes un-noticed, as compared to complete PCR inhibition.
Ramezani, F, Lu, J, Taheri, J & Zomaya, AY 2017, 'A Multi-Objective Load Balancing System for Cloud Environments', The Computer Journal, vol. 60, no. 9, pp. 1316-1337.
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© 2017 The British Computer Society. All rights reserved. Virtual machine (VM) live migration has been applied to system load balancing in cloud environments for the purpose of minimizing VM downtime and maximizing resource utilization. However, the migration process is both time-and cost-consuming as it requires the transfer of large size files or memory pages and consumes a huge amount of power and memory for the origin and destination physical machine (PM), especially for storage VM migration. This process also leads to VM downtime or slowdown. To deal with these shortcomings, we develop a Multi-objective Load Balancing (MO-LB) system that avoids VM migration and achieves system load balancing by transferring extra workload from a set of VMs allocated on an overloaded PM to other compatible VMs in the cluster with greater capacity. To reduce the time factor even more and optimize load balancing over a cloud cluster, MO-LB contains a CPU Usage Prediction (CUP) sub-system. The CUP not only predicts the performance of the VMs but also determines a set of appropriate VMs with the potential to execute the extra workload imposed on the VMs of an overloaded PM. We also design a Multi-Objective Task Scheduling optimization model using Particle Swarm Optimization to migrate the extra workload to the compatible VMs. The proposed method is evaluated using a VMware-vSphere-based private cloud in contrast to the VM migration technique applied by vMotion. The evaluation results show that the MO-LB system dramatically increases VM performance while reducing service response time, memory usage, job makespan, power consumption and the time taken for the load balancing process.
Rana, M, Li, L & Su, SW 2017, 'Distributed State Estimation Over Unreliable Communication Networks With an Application to Smart Grids', IEEE Transactions on Green Communications and Networking, vol. 1, no. 1, pp. 89-96.
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© 2017 IEEE. In contrast to the traditional centralized power system state estimation methods, this paper investigates the interconnected optimal filtering problem for distributed dynamic state estimation considering packet losses. Specifically, the power system incorporating microgrids is modeled as a state-space linear equation where sensors are deployed to obtain measurements. Basically, the sensing information is transmitted to the energy management system through a lossy communication network where measurements are lost. This can seriously deteriorate the system monitoring performance and even lose network stability. Second, as the system states are unavailable, so the estimation is essential to know the overall operating conditions of the electricity network. Availability of the system states provides designers with an accurate picture of the power network, so a suitable control strategy can be applied to avoid massive blackouts due to losing network stability. Particularly, the proposed estimator is based on the mean squared error between the actual state and its estimate. To obtain the distributed estimation, the optimal local and neighboring gains are computed to reach a consensus estimation after exchanging their information with the neighboring estimators. Then, the convergence of the developed algorithm is theoretically proved. Afterward, a distributed controller is designed based on the semidefinite programming approach. Simulation results demonstrate the accuracy of the developed approaches under the condition of missing measurements.
Rana, MM, Li, L & Su, S 2017, 'Design a distributed controller for microgrids', International Journal of Innovative Computing, Information and Control, vol. 13, no. 3, pp. 1055-1060.
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This paper addresses the problem of distributed energy management system (EMS) design considering network-induced delays. First of all, the distribution power network incorporating solar panels is modelled as a discrete-time linear state-space equation and its measurements/control information is obtained using a set of sensors and actuators. These electronic devices send the observation information to the EMS via un-reliable communication links. In order to stabilize the system, we propose discrete-time distributed static output feedback control strategies based on the linear matrix inequality and semi definite programming approaches. Using the Taylor series method, delays are integrated into the closed loop system so that the proposed controller runs with less energy resources and computation. Simulation results demonstrate that the proposed method is able to stabilize the system in a fairly short time.
Rana, MM, Li, L & Su, SW 2017, 'Distributed State Estimation of Smart Grids with Packet Losses', Asian Journal of Control, vol. 19, no. 4, pp. 1306-1315.
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AbstractThis paper explores the problem of distributed state estimation including packet losses for the environment‐friendly renewable microgrid incorporating electricity generating circuits. The problem is becoming critical due to the global warming, increasing green house gas emissions, and practical infeasibility with computational burden of the large‐scale centralized power system monitoring. To address the impending problem, a novel distributed state estimation algorithm is derived in the context of smart grids. Specifically, after modelling the microgrid, this paper proposes a local state estimation algorithm considering packet losses. Then a novel optimal weighting factor calculation method for the global state estimation is proposed. Particularly, it can automatically adjust the optimal weighting factors for different sensor measurements based on the observation. Simulations results show that the desired state estimation accuracy is achieved.
Rangel, L, Lospitao, E, Ruiz-Sáenz, A, Alonso, MA & Correas, I 2017, 'Alternative polyadenylation in a family of paralogousEPB41genes generates protein 4.1 diversity', RNA Biology, vol. 14, no. 2, pp. 236-244.
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Ranji-Burachaloo, H, Karimi, F, Xie, K, Fu, Q, Gurr, PA, Dunstan, DE & Qiao, GG 2017, 'MOF-Mediated Destruction of Cancer Using the Cell’s Own Hydrogen Peroxide', ACS Applied Materials & Interfaces, vol. 9, no. 39, pp. 33599-33608.
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A novel reduced iron metal-organic framework nanoparticle with cytotoxicity specific to cancer cells is presented. This nanoparticle was prepared via a hydrothermal method, reduced using hydroquinone, and finally conjugated with folic acid (namely, rMOF-FA). The synthesized nanoparticle shows the controlled release of iron in an acidic ex-vivo environment. Iron present on the rMOF-FA and released into solution can react with high levels of hydrogen peroxide found specifically in cancer cells to increase the hydroxyl radical concentration. The hydroxyl radicals oxidize proteins, lipids, and/or DNA within the biological system to decrease cell viability. In vitro experiments demonstrate that this novel nanoparticle is cytotoxic to cancer cells (HeLa) through generation of OH• inside the cells. At low concentrations of rMOF-FA, the cancer cell viability decreases dramatically, with no obvious reduction of normal cell (NIH-3T3) viability. The calculated half-maximum inhibitory concentration value (IC50) was 43 μg/mL for HeLa cells, which was significantly higher than 105 μg/mL for NIH-3T3. This work thus demonstrates a new type of agent for controlled hydroxyl radical generation using the Fenton reaction to kill the tumor cells.
Rao, P, Chen, Q, Nimbalkar, S & Liu, Y 2017, 'Laboratory study on impulse current characteristics of clay', Environmental Geotechnics, vol. 4, no. 3, pp. 199-208.
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Lightning is recognised as one of the most detrimental natural disasters. While numerous research studies were carried out on the lightning impulse characteristics of the grounding system and the critical breakdown characteristics of soil, little attention was paid to the impulse current characteristics of soils when lightning strikes. In this study, the performance of typical soft soil in Shanghai under the action of lightning is analyzed. Different factors, including the impulse current waveforms, the front time and half peak time of impulse current, the quantity of electric charge and absorption of unit heat, have been studied by performing a series of laboratory tests. The test results show that the variation of impulse current due to lightning strike is time dependent. The higher the soil temperature, the larger the peak impulse current produced during lightning strike. The value of the front time decreases exponentially, while the value of the half peak time decreases linearly with the rise of soil temperature. Novel empirical relationships between the impulse current characteristics of soil and soil temperature are proposed, with the aim of providing useful practical references for the design of a grounding system for lightning strikes.
Rao, P-P, Chen, Q, Li, L, Nimbalkar, S & Cui, J 2017, 'Elastoplastic Solution for Spherical Cavity Expansion in Modified Cam-Clay Soil under Drained Condition', International Journal of Geomechanics, vol. 17, no. 8, pp. 06017005-06017005.
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© 2017 American Society of Civil Engineers. This paper presents an innovative semianalytical solution for the expansion of a drained spherical cavity with finite initial radius. The widely known modified Cam-clay model is adopted to capture the nonlinear elastoplastic behavior of soil. The rigorous definitions for the mean and deviator stresses are adopted. The problem is then formulated as a set of first-order ordinary differential equations in the Lagrangian form. The radial and tangential stress and specific volume distribution around the cavity are determined. Extensive parametric study is undertaken to investigate effects of the overconsolidation ratio and relative positioning of elastoplastic interface, among others. The applicability of the proposed theoretical approach is demonstrated by a comparison with laboratory test results.
Rasekh, H, Mirzaghorbanali, A, Nemcik, J, Aziz, N & Li, X 2017, 'A New Equation for the Shear Strength of Cable Bolts Incorporating the Energy Balance Theory', Geotechnical and Geological Engineering, vol. 35, no. 4, pp. 1529-1548.
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© 2017, Springer International Publishing Switzerland. The application of cable bolts as a secondary support system is an increasing trend in underground coal mines worldwide. The performances of cable bolts have been evaluated under both axial and shear loading conditions. Two methods of testing cables for shear, single and double shear, have been recognised. This paper examines the shear behaviour of a variety of cable bolts under different pre-tension loads by double shear testing. Plain, spiral and the combination of both cable types were used in this study. The initial axial load and the type of cable bolts are the main factors affecting their shear strength. By increasing the axial pre-tension load, the peak shear load occurs at lower shear displacement. The failure angle due to cable bending across the joint at different pre-tension loads varied between 41° and 49°. This demonstrates that the ratio of axial and perpendicular displacements is almost constant and on average the failure occurs at about 45°. A novel analytical model is proposed to evaluate the shear behaviour of pre-tensioned fully grouted cable bolts subjected to double shearing. Energy and Fourier Series methods were incorporated in the model to simulate the shear behaviour of cable bolts. The comparison of the experimental results with the proposed model shows a good agreement.
Rashedul, HK, Kalam, MA, Masjuki, HH, Teoh, YH, How, HG, Monirul, IM & Imdadul, HK 2017, 'Attempts to minimize nitrogen oxide emission from diesel engine by using antioxidant-treated diesel-biodiesel blend', Environmental Science and Pollution Research, vol. 24, no. 10, pp. 9305-9313.
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Rashid, MH-O, Triani, G, Scales, N, in het Panhuis, M, Nghiem, LD & Ralph, SF 2017, 'Nanofiltration applications of tough MWNT buckypaper membranes containing biopolymers', Journal of Membrane Science, vol. 529, pp. 23-34.
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� 2017 Elsevier B.V. The ability of biopolymers (bovine serum albumin, lysozyme, chitosan, gellan gum and DNA) to facilitate formation of aqueous dispersions of MWNTs was investigated using a combination of absorption spectrophotometry and optical microscopy. Subsequently, self-supporting carbon nanotube membranes, known as buckypapers (BPs), were prepared by vacuum filtration of the dispersions. Microanalytical data obtained from the BPs confirmed the retention of biopolymers within their structures. Tensile test measurements performed on the BPs showed that incorporation of the biopolymers resulted in significant improvements in mechanical properties, compared to analogous BPs containing MWNTs and the low molecular mass dispersant Triton X-100. For example, MWNT/CHT BPs (CHT=chitosan) exhibited values for tensile strength, ductility, Young's modulus and toughness of 28�2�MPa, 5.3�2.7%, 0.9�0.3�GPa and 1.7�0.3�J g −1 , respectively. Each of these values are significantly greater than those obtained for MWNT/Trix BPs, prepared using a low molecular weight dispersant (6�3�MPa, 1.3�0.2%, 0.6�0.3�GPa and 0.10�0.06�J g −1 , respectively). This significant improvement in mechanical properties is attributed to the ability of the long biopolymer molecules to act as flexible bridges between the short CNTs. All BPs possessed hydrophilic surfaces, with contact angles ranging from 29�2� to 57�5�. Nitrogen gas porosimetry showed that the BPs have highly porous internal structures, while scanning electron microscopy (SEM) showed their surface morphologies have numerous pore openings. The permeability of the BPs towards water, inorganic salts, and dissolved trace organic contaminants (TrOCs), such as pharmaceuticals, personal care products, and pesticides, was investigated through filtration experiments. Of the twelve TrOCs investigated in this study, nine were rejected by more than 95% by BPs composed of MWNTs and chitosan. The latter BPs...
Raza, A, Khan, MU & Tahir, FA 2017, 'A Frequency Reconfigurable MIMO Antenna System for Cognitive Radio Applications', Frequenz, vol. 71, no. 11-12.
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AbstractIn this paper, a two element frequency reconfigurable multiple-input-multiple-output (MIMO) antenna system is presented. The proposed antenna consists of miniaturized patch antenna elements, loaded with varactor diodes to achieve frequency reconfigurability. The antenna has bandwidth of 30 MHz and provides a smooth frequency sweep from 2.12 GHz to 2.4 GHz by varying the reverse bias voltage of varactor diode. The antenna is designed on an FR4 substrate and occupies a space of 50×100 × 0.8 mm
Razmjou, A, Asadnia, M, Ghaebi, O, Yang, H-C, Ebrahimi Warkiani, M, Hou, J & Chen, V 2017, 'Preparation of Iridescent 2D Photonic Crystals by Using a Mussel-Inspired Spatial Patterning of ZIF-8 with Potential Applications in Optical Switch and Chemical Sensor', ACS Applied Materials & Interfaces, vol. 9, no. 43, pp. 38076-38080.
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© 2017 American Chemical Society. In this work, spatial patterning of a thin, dense, zeolitic imidazolate framework (ZIF-8) pattern was generated using photolithography and nanoscale (60 nm) dopamine coating. A bioinspired, unique, reversible, two-color iridescent pattern can be easily obtained for potential applications in sensing and photonics.
Reis, R, Duke, M, Merenda, A, Winther-Jensen, B, Puskar, L, Tobin, MJ, Orbell, JD & Dumée, LF 2017, 'Customizing the surface charge of thin-film composite membranes by surface plasma thin film polymerization', Journal of Membrane Science, vol. 537, pp. 1-10.
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Solute-surface interactions are critical in membrane science and dominate a number of diffusion and selectivity parameters. In water treatment particularly, the charge on the membrane has been shown to affect ion transport selectivity as well as fouling mechanisms. The development of advanced surface technologies that allow for potential customization of the surface charge for specific applications, without compromising the essential performance of the membrane, is therefore desirable. In this paper, a novel plasma polymerization strategy was applied to commercial reverse osmosis membrane in order to tune the surface charge. Two monomers, maleic anhydride and vinylimidazole, were plasma polymerized onto the membrane resulting in a modification of the surface energy with resultant isoelectric points of approximately pH 3 and pH 7 respectively. This required only a short 5 min plasma polymerization treatment in each case. Thus, in addition to enhancing the water permeation by up to 10%, in comparison to the reference membranes, the overall charge of the membranes was shifted from highly negatively charged upon maleic anhydride polymerization to highly positively charged upon vinylimidazole polymerization. A comprehensive morphological and chemical analysis was performed to correlate the changes to the presence of functional groups and the alteration of the surface texture. Short treatments were found to smooth the surface whilst enriching the surface with either carboxylic or amine/amide groups. This work opens new avenues to engineer advanced membranes with improved performance and selectivity.
Reis, R, Dumée, LF, Merenda, A, Orbell, JD, Schütz, JA & Duke, MC 2017, 'Plasma-induced physicochemical effects on a poly(amide) thin-film composite membrane', Desalination, vol. 403, pp. 3-11.
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Helium and water gas plasma were used to modify the surface morphology and chemistry of commercial thin film composite membranes. Such surface treatment is a convenient tool to alter performance of the membranes and subsequently reduce interactions with contaminants in solution. Plasma reactions such as etching and re-deposition resulted in surface functionalization and texturation which were correlated with membrane flux and salt rejection changes. Investigations conducted using atomic force microscopy revealed morphology alterations which were apparent as either smoother surfaces or rougher surfaces. While the smoothing was attributed to a re-deposition of polymer material, which originated most likely from vaporization of surface polymer, the roughening was a result from balanced plasma surface reactions. The beneficial etching can occur under certain conditions when helium is used in conjunction with low excitation power, which resulted in flux enhancements up to 66% (i.e. from 30 L.m− 2.h− 1 to 50 L.m− 2.h− 1) with 98% rejection. The hydrophilicity was dramatically increased from 46.6° to as low as 8.9° after 5 min of helium plasma duration. The impact that plasma treatments have on the nascent structure was discussed in order to highlight its application as a convenient tool to functionalize the surface of thin film composite membranes.
Reitsma, L & van den Hoven, E 2017, 'Wrapping Cultural Values: using Social Embodiment as Stimulus in Designs', The Design Journal, vol. 20, no. sup1, pp. S401-S410.
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Ren, F, Yu, Y, Cao, M, Li, Y, Xin, C & He, Y 2017, 'Effect of pneumatic spreading on impregnation and fiber fracture of continuous fiber-reinforced thermoplastic composites', Journal of Reinforced Plastics and Composites, vol. 36, no. 21, pp. 1554-1563.
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The fiber pre-spreading is of great importance when the continuous fiber-reinforced thermoplastic composites are produced by the melt impregnation process. In this paper, an improved spreading device is introduced, in which via grooving the pins for the airflow, the fiber is pre-spread by the combination of the airflow and the rolls. The objective of this operation is to reduce the contact friction between the fiber bundle and the pins surface, thereby reducing fiber fracture during the pre-spreading process. The influence of airflow on the pre-spreading of the fiber bundle is also investigated in this paper. It is found that the effect of airflow on the impregnation is significant and the fiber fracture rate is reduced effectively by analyzing the water absorption rate, interlayer shear strength and fiber fracture rate of the prepreg. When the air pressure is 0.2 MPa, the performance of the prepreg is optimal.
Ren, F, Yu, Y, Yang, J, Xin, C & He, Y 2017, 'A Mathematical Model for Continuous Fiber Reinforced Thermoplastic Composite in Melt Impregnation', Applied Composite Materials, vol. 24, no. 3, pp. 675-690.
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© 2016, Springer Science+Business Media Dordrecht. Through the combination of Reynolds equation and Darcy’s law, a mathematical model was established to calculate the pressure distribution in wedge area, which contributed to the forecast effect of processing parameters on impregnation degree of the fiber bundle. The experiments were conducted to verify the capacity of the proposed model with satisfactory results, which means that the model is effective in predicting the influence of processing parameters on impregnation. From the mathematical model, it was known that the impregnation degree of the fiber bundle would be improved by increasing the processing temperature, number and radius of pins, or decreasing the pulling speed and the center distance of pins, which provided a possible solution to the difficulty of melt with high viscosity in melt impregnation and optimization of impregnation processing.
Ren, F, Zhang, C, Yu, Y, Xin, C, Tang, K & He, Y 2017, 'A Modeling Approach to Fiber Fracture in Melt Impregnation', Applied Composite Materials, vol. 24, no. 1, pp. 193-207.
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© 2016, Springer Science+Business Media Dordrecht. The effect of process variables such as roving pulling speed, melt temperature and number of pins on the fiber fracture during the processing of thermoplastic based composites was investigated in this study. The melt impregnation was used in this process of continuous glass fiber reinforced thermoplastic composites. Previous investigators have suggested a variety of models for melt impregnation, while comparatively little effort has been spent on modeling the fiber fracture caused by the viscous resin. Herein, a mathematical model was developed for impregnation process to predict the fiber fracture rate and describe the experimental results with the Weibull intensity distribution function. The optimal parameters of this process were obtained by orthogonal experiment. The results suggest that the fiber fracture is caused by viscous shear stress on fiber bundle in melt impregnation mold when pulling the fiber bundle.
Ren, J, Song, J, Ellis, J & Li, J 2017, 'Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences', BMC Genomics, vol. 18, no. S2.
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© 2017 The Author(s). Background: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by diverse species, extra heterogeneity can also be introduced by various data sources, adding another layer of complexity and further confounding the research. Results: This work proposed a staged heterogeneity learning method, which learns both characteristics and heterogeneity of data in a phased manner. The method was applied to identify antigenic residues of heterogenous conformational B-cell epitopes based on antigen sequences. In the first stage, the model learns the general epitope patterns of each kind of propensity from a large data set containing computationally defined epitopes. In the second stage, the model learns the heterogenous complementarity of these propensities from a relatively small guided data set containing experimentally determined epitopes. Moreover, we designed an algorithm to cluster the predicted individual antigenic residues into conformational B-cell epitopes so as to provide strong potential for real-world applications, such as vaccine development. With heterogeneity well learnt, the transferability of the prediction model was remarkably improved to handle new data with a high level of heterogeneity. The model has been tested on two data sets with experimentally determined epitopes, and on a data set with computationally defined epitopes. This proposed sequence-based method achieved outstanding performance - about twice that of existing methods, including the sequence-based predictor CBTOPE and three other structure-based predictors. Conclusions: The proposed method uses only antigen sequence information, and thus has much broader applications.
Ren, J, Tijing, LD & Shon, HK 2017, '“Robbing behavior” and re-immobilization of nanoscale zero-valent iron (nZVI) onto electrospun polymeric nanofiber mats for trichloroethylene (TCE) remediation', Separation and Purification Technology, vol. 189, pp. 375-381.
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© 2017 Elsevier B.V. In this study, we first revealed a “robbing behavior” during the immobilization of nZVI particles onto an electrospun polyacrylic acid (PAA)-polyvinyl alcohol (PVA) nanofiber mat. The robbing behavior can significantly reduce the number of nZVI particles immobilized onto the mat and hence weaken the performance of mitigating contaminated water. To minimize the undesirable effect of robbing behavior, we developed a dipping method that enables exposure of enough free Fe (II) as electron acceptors to the Fe (II)-complexed PAA-PVA mat for the subsequent reduction. The result indicates that the mat with dipping can immobilize more than 1.7 times the weight percentage of nZVI particles for the mat without dipping. Moreover, the dipping method can also re-immobilize or enrich nZVI particles on the mat that has already partially immobilized nZVI particles. The nZVI-immobilized mat dipped once into the FeSO4 solution with a very little concentration (0.32 g/L) had an excellent performance for trichloroethylene (TCE) degradation (more than 92% TCE removed). Here, the developed dipping method shows great potential for nZVI immobilization and groundwater remediation.
Ren, J, Tijing, LD & Shon, HK 2017, 'Effect of polymer ratio on nZVI loading onto Electrospun nanofiber mat for mitigating groundwater contaminants', Advanced Materials - TechConnect Briefs 2017, vol. 2, pp. 265-268.
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Nanoscale zero-valent iron (nZVI) has been widely used for the reduction of halogenated organics and heavy metals in the groundwater. However, individual nZVI particles are mobile and prone to aggregate, thereby reducing the reaction sites exposed to contaminants. Electrospun polymer nanofiber mat is an ideal carrier to immobilize and distribute nZVI particles after its merits of high specific area, size-controllable and material-compatible properties. In this study, nZVI particles were loaded onto the polyacrylic acid (PAA)-polyvinyl alcohol (PVA) electrospun nanofiber mats with different PAA/PVA ratios. The results indicate that mat with the PAA/PVA ratio of 3:1 loaded the most nZVI particles (∼48 wt%) and had the highest removals to methylene blue at 94% and Cu (II) ions at 84% respectively. The nZVI-loaded electrospun nanofiber mat has promising application for the groundwater contaminants mitigation.
Ren, J, Woo, YC, Yao, M, Tijing, LD & Shon, HK 2017, 'Enhancement of nanoscale zero-valent iron immobilization onto electrospun polymeric nanofiber mats for groundwater remediation', Process Safety and Environmental Protection, vol. 112, no. Part B, pp. 200-208.
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© 2017 Institution of Chemical Engineers A new approach that combines nanoscale zero-valent iron (nZVI) with electrospinning technology has been put forward to avoid nZVI agglomeration and a secondary pollution. In this study, to enhance the immobilization of nZVI particles onto the polyacrylic acid (PAA)/polyvinyl alcohol (PVA) electrospun nanofiber mat, mats (M1, M2 and M3) with different PAA/PVA mass ratios (1:1, 2:1 and 3:1) were tested for the immobilization of nZVI particles and their performance of removing contaminants. The results indicate that M3 immobilized the most nZVI particles (48.4 wt% on the mat, ∼2.5 times the figure for previous study) and had the highest removals to methylene blue and Cu(II) ions at 94% and 83.6% respectively, resulting from more free carboxylic groups available on the cross-linked nanofibers as well as a higher porosity into the mat. Therefore, increasing the PAA/PVA ratio is effective to boost the performance of nZVI–PAA/PVA electrospun nanofiber mat, which has a great potential for the application of nZVI-targeted contaminants remediation.
Reyhani, A, McKenzie, TG, Ranji‐Burachaloo, H, Fu, Q & Qiao, GG 2017, 'Fenton‐RAFT Polymerization: An “On‐Demand” Chain‐Growth Method', Chemistry – A European Journal, vol. 23, no. 30, pp. 7221-7226.
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AbstractFine control over the architecture and/or microstructure of synthetic polymers is fast becoming a reality owing to the development of efficient and versatile polymerization techniques and conjugation reactions. However, the transition of these syntheses to automated, programmable, and high‐throughput operating systems is a challenging step needed to translate the vast potential of precision polymers into machine‐programmable polymers for biological and functional applications. Chain‐growth polymerizations are particularly appealing for their ability to form structurally and chemically well‐defined macromolecules through living/controlled polymerization techniques. Even using the latest polymerization technologies, the macromolecular engineering of complex functional materials often requires multi‐step syntheses and purification of intermediates, and results in sub‐optimal yields. To develop a proof‐of‐concept of a framework polymerization technique that is readily amenable to automation requires several key characteristics. In this study, a new approach is described that is believed to meet these requirements, thus opening avenues toward automated polymer synthesis.
Riayatsyah, TMI, Ong, HC, Chong, WT, Aditya, L, Hermansyah, H & Mahlia, TMI 2017, 'Life Cycle Cost and Sensitivity Analysis of Reutealis trisperma as Non-Edible Feedstock for Future Biodiesel Production', Energies, vol. 10, no. 7, pp. 877-877.
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The use of non-edible, second-generation feedstocks for the production of biodiesel has been an active area of research, due to its potential in replacing fossil diesel as well as its environmentally friendly qualities. Despite this, more needs to be done to remove the technical barriers associated with biodiesel production and usage, to increase its quality as well as to widen the choice of available feedstocks; so as to avoid over-dependence on limited sources. This paper assesses the feasibility of using a local plant, Reutealis trisperma, whose seeds contain a high percentage of oil of up to 51%, as one of the possible feedstocks. The techno-economic and sensitivity analysis of biodiesel production from Reutealis trisperma oil as well as implementation aspects and environmental effects of the biodiesel plant are discussed. Analysis indicates that the 50 kt Reutealis trisperma biodiesel production plant has a life cycle cost of approximately $710 million, yielding a payback period of 4.34 years. The unit cost of the biodiesel is calculated to be $0.69/L with the feedstock cost accounting for the bulk of the cost. The most important finding from this study is that the biodiesel from Reutealis trisperma oil can compete with fossil diesel, provided that appropriate policies of tax exemptions and subsidies can be put in place. To conclude, further studies on biodiesel production and its limitations are necessary before the use of biodiesel from Reutealis trisperma oil may be used as a fuel source to replace fossil diesel.
Riis, JO, Achenbach, M, Israelsen, P, Kyvsgaard Hansen, P, Johansen, J & Deuse, J 2017, 'Dealing with complex and ill-structured problems: results of a Plan-Do-Check-Act experiment in a business engineering semester', European Journal of Engineering Education, vol. 42, no. 4, pp. 396-412.
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© 2016 SEFI. Challenged by increased globalisation and fast technological development, we carried out an experiment in the third semester of a global business engineering programme aimed at identifying conditions for training student in dealing with complex and ill-structured problems of forming a new business. As this includes a fuzzy front end, learning cannot be measured in traditional, quantitative terms; therefore, we have explored the use of reflection to convert tacit knowledge to explicit knowledge. The experiment adopted a Plan-Do-Check-Act approach and concluded with developing a plan for new learning initiatives in the subsequent year’s semester. The findings conclude that (1) problem-based learning develops more competencies than ordinarily measured at the examination, especially, the social/communication and personal competencies are developed; (2) students are capable of dealing with a complex and ambiguous problem, if properly guided. Four conditions were identified; (3) most students are not conscious of their learning, but are able to reflect if properly encouraged; and (4) improving engineering education should be considered as an organisational learning process.
Ritter, SM & Ferguson, S 2017, 'Happy creativity: Listening to happy music facilitates divergent thinking', PLOS ONE, vol. 12, no. 9, pp. e0182210-e0182210.
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Creativity can be considered one of the key competencies for the twenty-first century. It provides us with the capacity to deal with the opportunities and challenges that are part of our complex and fast-changing world. The question as to what facilitates creative cognition-the ability to come up with creative ideas, problem solutions and products-is as old as the human sciences, and various means to enhance creative cognition have been studied. Despite earlier scientific studies demonstrating a beneficial effect of music on cognition, the effect of music listening on creative cognition has remained largely unexplored. The current study experimentally tests whether listening to specific types of music (four classical music excerpts systematically varying on valance and arousal), as compared to a silence control condition, facilitates divergent and convergent creativity. Creativity was higher for participants who listened to 'happy music' (i.e., classical music high on arousal and positive mood) while performing the divergent creativity task, than for participants who performed the task in silence. No effect of music was found for convergent creativity. In addition to the scientific contribution, the current findings may have important practical implications. Music listening can be easily integrated into daily life and may provide an innovative means to facilitate creative cognition in an efficient way in various scientific, educational and organizational settings when creative thinking is needed.
Romeo, M, Yepes-Baldó, M, Boria-Reverter, S & Merigó, JM 2017, 'Twenty-five years of research on work and organizational psychology: A bibliometric perspective', Anuario de Psicología, vol. 47, no. 1, pp. 32-44.
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© 2017 Universitat de Barcelona The research aims to analyze the scientific productivity in the field of work/organizational psychology (WOP) in the last 25 years. We focus our analysis on the most influential journals and articles, generally and for 5-year periods, as well as structures of co-citation among the highest quality journals based on their h-index. We found that a high percentage of papers published each year receive between 5 and 10 cites. Secondly, we observe an exponential increase in the number of papers published, citations, and h-index. Additionally, the number of self-citations significantly increases in the last 5 years. In this sense, we consider that the most recent papers need more time to increase their level of citation and, subsequently, to correct the bias on self-citation. This research shows the status of research in the field of work/organizational psychology, analyzing the scientific journals and papers published in the Web of Science.
Roobavannan, M, Kandasamy, J, Pande, S, Vigneswaran, S & Sivapalan, M 2017, 'Allocating Environmental Water and Impact on Basin Unemployment: Role of A Diversified Economy', Ecological Economics, vol. 136, pp. 178-188.
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© 2017 Elsevier B.V. Water diversion for environmental pu rposes threatens many agricultural communities. This paper focuses on the water-agriculture-environment nexus in the Murrumbidgee River Basin, Australia, and attempts to explain how reduced water allocation to agriculture aimed at protecting the environment in turn impacted the wider economy and the community. Predictably reduced water allocation saw declines in agriculture production and employment. Despite this, paradoxically, the basin unemployment rate declined and basin median household income increased. To understand and interpret this, we first analyze available labour, economic and hydrology data, and then develop a simple dynamic model to interpret the observed pattern of basin employment and unemployment. Data analysis revealed the likely causes behind the paradox as (a) out-migration of people from the basin, and (b) absorption of the labour force in the fast growing non-agricultural sectors of the diversified basin economy. The model simulations reinforced this interpretation. Further model simulations under alternative realities of out-migration and sectoral transformation indicated that basins embedded in faster growing national economies, and are more diversified to begin with, are likely to be more conducive to agriculture sector reform (e.g., reduced water allocation) and environmental regeneration. This is a sobering message for other regions experiencing environmental degradation due to extensive agricultural development.
Roobavannan, M, Kandasamy, J, Pande, S, Vigneswaran, S & Sivapalan, M 2017, 'Role of Sectoral Transformation in the Evolution of Water Management Norms in Agricultural Catchments: A Sociohydrologic Modeling Analysis', Water Resources Research, vol. 53, no. 10, pp. 8344-8365.
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AbstractThis study is focused on the water‐agriculture‐environment nexus as it played out in the Murrumbidgee River Basin, eastern Australia, and how coevolution of society and water management actually transpired. Over 100 years of agricultural development the Murrumbidgee Basin experienced a “pendulum swing” in terms of water allocation, initially exclusively for agriculture production changing over to reallocation back to the environment. In this paper, we hypothesize that in the competition for water between economic livelihood and environmental wellbeing, economic diversification was the key to swinging community sentiment in favor of environmental protection, and triggering policy action that resulted in more water allocation to the environment. To test this hypothesis, we developed a sociohydrology model to link the dynamics of the whole economy (both agriculture and industry composed of manufacturing and services) to the community's sensitivity toward the environment. Changing community sensitivity influenced how water was allocated and governed and how the agricultural sector grew relative to the industrial sector (composed of manufacturing and services sectors). In this way, we show that economic diversification played a key role in influencing the community's values and preferences with respect to the environment and economic growth. Without diversification, model simulations show that the community would not have been sufficiently sensitive and willing enough to act to restore the environment, highlighting the key role of sectoral transformation in achieving the goal of sustainable agricultural development.
Roohani-Esfahani, S-I & Zreiqat, H 2017, 'Nanoparticles: a Promising New Therapeutic Platform for Bone regeneration?', Nanomedicine, vol. 12, no. 5, pp. 419-422.
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Roohani-Esfahani, S-I, Lin, K & Zreiqat, H 2017, 'Fabrication of bioinspired structured glass–ceramics with enhanced fracture toughness', Journal of Materials Science, vol. 52, no. 15, pp. 9202-9210.
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Rothberg, SJ, Allen, MS, Castellini, P, Di Maio, D, Dirckx, JJJ, Ewins, DJ, Halkon, BJ, Muyshondt, P, Paone, N, Ryan, T, Steger, H, Tomasini, EP, Vanlanduit, S & Vignola, JF 2017, 'An international review of laser Doppler vibrometry: Making light work of vibration measurement', Optics and Lasers in Engineering, vol. 99, pp. 11-22.
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© 2016 In 1964, just a few years after the invention of the laser, a fluid velocity measurement based on the frequency shift of scattered light was made and the laser Doppler technique was born. This comprehensive review paper charts advances in the development and applications of laser Doppler vibrometry (LDV) since those first pioneering experiments. Consideration is first given to the challenges that continue to be posed by laser speckle. Scanning LDV is introduced and its significant influence in the field of experimental modal analysis described. Applications in structural health monitoring and MEMS serve to demonstrate LDV's applicability on structures of all sizes. Rotor vibrations and hearing are explored as examples of the classic applications. Applications in acoustics recognise the versatility of LDV as demonstrated by visualisation of sound fields. The paper concludes with thoughts on future developments, using examples of new multi-component and multi-channel instruments.
Rufangura, P & Sabah, C 2017, 'Graphene-based wideband metamaterial absorber for solar cells application', Journal of Nanophotonics, vol. 11, no. 3, pp. 036008-036008.
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A wideband metamaterial (MTM) absorber based on a concentric ring resonator is discussed at visible frequencies. The proposed structure offers a wideband absorption response, where absorption of <70% is gained for the frequency ranging from 537.91 to 635.73 THz. The analysis is conducted on the components of the proposed structure to understand the origin of wideband absorption. Furthermore, a graphene monolayer sheet is integrated to the proposed MTM absorber to optimize its absorptivity, where the studies show enhancement of the absorptivity of the proposed structure up to 26% from its initial absorptivity. MTM absorbers of this kind have potential applications in solar cells.
Ruhul, AM, Kalam, MA, Masjuki, HH, Shahir, SA, Alabdulkarem, A, Teoh, YH, How, HG & Reham, SS 2017, 'Evaluating combustion, performance and emission characteristics of Millettia pinnata and Croton megalocarpus biodiesel blends in a diesel engine', Energy, vol. 141, pp. 2362-2376.
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Ruppert, MG & Yong, YK 2017, 'Note: Guaranteed collocated multimode control of an atomic force microscope cantilever using on-chip piezoelectric actuation and sensing', Review of Scientific Instruments, vol. 88, no. 8, pp. 086109-086109.
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The quality (Q) factor is an important parameter of the resonance of the microcantilever as it determines both imaging bandwidth and force sensitivity. The ability to control the Q factor of multiple modes is believed to be of great benefit for atomic force microscopy techniques involving multiple eigenmodes. In this paper, we propose a novel cantilever design employing multiple piezoelectric transducers which are used for separated actuation and sensing, leading to guaranteed collocation of the first eight eigenmodes up to 3 MHz. The design minimizes the feedthrough usually observed with these systems by incorporating a guard trace on the cantilever chip. As a result, a multimode Q controller is demonstrated to be able to modify the quality factor of the first two eigenmodes over up to four orders of magnitude without sacrificing robust stability.
Ruppert, MG, Fowler, AG, Maroufi, M & Moheimani, SOR 2017, 'On-Chip Dynamic Mode Atomic Force Microscopy: A Silicon-on-Insulator MEMS Approach', Journal of Microelectromechanical Systems, vol. 26, no. 1, pp. 215-225.
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Ruppert, MG, Maroufi, M, Bazaei, A & Moheimani, SOR 2017, 'Kalman Filter Enabled High-Speed Control of a MEMS Nanopositioner', IFAC-PapersOnLine, vol. 50, no. 1, pp. 15554-15560.
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Ryan, PC & Stewart, MG 2017, 'Cost-benefit analysis of climate change adaptation for power pole networks', Climatic Change, vol. 143, no. 3-4, pp. 519-533.
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Power distribution pole networks are vulnerable to a changing climate. Climate change can increase wind speeds, and changes in rainfall and temperature can accelerate timber decay, affecting residual capacity of timber power poles. The present paper utilises advanced stochastic simulation methods to examine climate change impacts, and possible climate change adaptation strategies, for Australian power distribution networks. The assessment framework developed, which is applicable to a wide variety of infrastructure types and research areas, utilises probabilistic methods to investigate the appropriateness of climate adaptation strategies aimed at ameliorating the impact of climate change on critical infrastructure. Measures investigated include alterations to design or maintenance practices through, for example, installation of larger poles, more frequent inspections, or changes to pole replacement criteria. A cost-benefit decision analysis is developed herein using the latest AR5 climate projections, network vulnerability, adaptation measures, and cost and loss data for both direct and indirect costs. The net present value and benefit-to-cost ratio is calculated for different adaptation strategies over the life cycle of the assets up to the year 2090. An adaptation measure that allows for the installation of larger poles but less stringent pole replacement criteria has the highest net benefit—with a mean potential saving of hundreds of millions of dollars.
Saadat, A, Ni, W & Vesilo, R 2017, 'Collaborative Spectrum Sharing Through Non-Collaborative Gaming for Next-Generation Small Cells', IEEE Access, vol. 5, pp. 10182-10192.
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© 2013 IEEE. Existing spectrum-sharing schemes either allow the secondary-network users (SUs) to utilize the spectrum when primary-network users (PUs) remain idle, or require the SUs to coordinate with the PUs, causing signaling overhead. In this paper, we propose a game-theoretic spectrum-sharing scheme, which enables the SUs and PUs to utilize the spectrum simultaneously, without compromising the quality of service (QoS) of the PUs and ensuring reduced signaling overhead. We formulate a multi-priority non-cooperative power-control game by considering a scenario where multiple small cell base stations belonging to either the primary network or secondary network utilize the available spectrum resources at the same time. The base stations are empowered to adjust their transmit powers in an automated manner based on measured interference, until their transmit powers are stabilized. As a key idea, a game parameter, dynamic price coefficient, is designed to give the primary network priority over the secondary network for accessing the spectrum. We determine appropriate bounds for the game parameters to ensure the existence and uniqueness of the Nash equilibrium of the proposed game. Furthermore, we propose a novel dual-mode solution to reduce the real-time signaling overhead between the networks, by minimizing the information exchange during the game required to reach an equilibrium point. Extensive simulation results are presented to prove the convergence of the game to a Nash equilibrium, along with a throughput performance analysis.
Saberi, M, Khadeer Hussain, O & Chang, E 2017, 'Past, present and future of contact centers: a literature review', Business Process Management Journal, vol. 23, no. 3, pp. 574-597.
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PurposeContact centers (CCs) are one of the main touch points of customers in an organization. They form one of the inputs to customer relationship management (CRM) to enable an organization to efficiently resolve customer queries. CCs have an important impact on customer satisfaction and are a strategic asset for CRM systems. The purpose of this paper is to review the current literature on CCs and identify their shortcomings to be addressed in the current digital age.Design/methodology/approachThe current literature on CCs can be classified into the analytical and the managerial aspects of CCs. In the former, data mining, text mining, and voice recognition techniques are discussed, and in the latter, staff training, CC performance, and outsourced CCs are discussed.FindingsWith the growth of information and communication technologies, the information that CCs must handle both in terms of type and volume, has changed. To deal with such changes, CCs need to evolve in terms of their operation and public relations. The authors present a state-of-the-art review of the challenges in identifying the gaps in order to have the next generation of CCs. Lack of an interactive CC and lack of data integrity for CCs are highlighted as important issues that need to be dealt with properly by CCs.Originality/valueAs far as the authors know, this is the first paper that reviews CCs’ literature by providing the comprehensive survey, critical evaluation, and future research.
Saberi, M, Pu, Q, Valasek, P, Norizadeh-Abbariki, T, Patel, K & Huang, R 2017, 'The hypaxial origin of the epaxially located rhomboid muscles', Annals of Anatomy - Anatomischer Anzeiger, vol. 214, pp. 15-20.
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Saha, G & Paul, MC 2017, 'Transition of nanofluids flow in an inclined heated pipe', International Communications in Heat and Mass Transfer, vol. 82, pp. 49-62.
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Sahebi, S, Phuntsho, S, Tijing, L, Han, G, Han, DS, Abdel-Wahab, A & Shon, HK 2017, 'Thin-film composite membrane on a compacted woven backing fabric for pressure assisted osmosis', Desalination, vol. 406, pp. 98-108.
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© 2016 Elsevier B.V. The water flux in forward osmosis (FO) process declines substantially when the draw solution (DS) concentration reaches closer to the point of osmotic equilibrium with the feed solution (FS). Using external hydraulic pressure alongside the osmotic driving force in the pressure assisted osmosis (PAO) has been found effective in terms of enhancing water flux and even potentially diluting the DS beyond osmotic equilibrium. The net gain in water flux due to the applied pressure in the PAO process closely depends on the permeability of the FO membrane. The commercial flat sheet cellulose triacetate (CTA) FO membrane has low water permeability and hence the effective gain in water flux in the PAO process is low. In this study, a high performance thin film composite membrane was developed especially for the PAO process through casting polyethersulfone (PES) polymer solution on a compacted woven fabric mesh support followed by interfacial polymerisation for polyamide active layer. This PAO membrane possesses a water flux of 37 L m2h− 1using 0.5 M NaCl as DS and deionised water as the feed at an applied hydraulic pressure of 10 bar. Besides, the membrane was able to endure the external hydraulic pressure required for the PAO process owing to the embedded backing fabric support. While the membranes with low structural parameters are essential for higher water flux, this study shows that for PAO process, polymeric membranes with larger structural parameters may not be suitable for PAO. They generally resulted in compaction and poor mechanical strength to withstand hydraulic pressure.
Saidur, RS, Masjuki, HH, Mahlia, TMI & Nasrudin, AR 2017, 'FACTORS AFFECTING REFRIGERATOR-FREEZERS ENERGY CONSUMPTION', ASEAN Journal on Science and Technology for Development, vol. 19, no. 2, pp. 57-67.
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Two frost-free household refrigerator-freezers, one with 492 liter capacity and one with 460 liter capacity were tested in the laboratory to determine the sensitivity of several variables those influence consumption refrigerator-freezers energy consumption greatly. The effects of single variables such as room temperature, thermostat setting positions, and door openings on the energy consumption were investigated. Using Response Surface Methodology (RSM), a mathematical model has been developed to investigate the combined effect of room temperature, thermostat setting positions, and door opening on the energy consumption of refrigerator-freezers. From the mathematical model, it has been observed that room-temperature has the highest effect on the energy consumption followed by the thermostat setting position. The door opening has lowest on the energy consumption. More detailed tests were performed under different room temperature, thermostat setting positions, and door opening conditions and presented in this paper.
Sajedi, S, Huang, Q, Gandomi, AH & Kiani, B 2017, 'Reliability-Based Multiobjective Design Optimization of Reinforced Concrete Bridges Considering Corrosion Effect', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 3, no. 3, pp. 1-10.
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Chloride-induced corrosion is known as the dominant cause of premature damage in reinforced concrete (RC) bridges in the United States. However, the current corrosion management strategies do not suggest an optimum design procedure for RC bridges in corrosive environments considering both reliability and cost. In this paper, a module based on a reliability-based multiobjective design optimization (RB-MODO) technique using a nondominated sorting genetic algorithm is proposed for the optimum design of RC bridge beams considering corrosion. The procedure simultaneously maximizes the reliability of the structure and minimizes the material costs, given a design service life. As an illustration, the developed procedure is used for flexural design of interior T beams of a RC bridge with and without considering corrosion effect subjected to various design constraints and service lives. Three types of materials are used in the design process: normal strength concrete with black steel rebars, normal strength concrete with epoxy-coated rebars, and high-performance concrete with black steel rebars. Lastly, the optimum design strategy is selected among the considered materials based on the Pareto front results obtained from the proposed RB-MODO procedure.
Saletta, F, Vilain, RE, Gupta, AK, Nagabushan, S, Yuksel, A, Catchpoole, D, Scolyer, RA, Byrne, JA & McCowage, G 2017, 'Programmed Death-Ligand 1 Expression in a Large Cohort of Pediatric Patients With Solid Tumor and Association With Clinicopathologic Features in Neuroblastoma', JCO Precision Oncology, vol. 1, no. 1, pp. 1-12.
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Purpose Programmed death-ligand 1 (PD-L1) expression represents a potential predictive biomarker of immune checkpoint blockade response. However, literature about the prevalence of PD-L1 expression in the pediatric cancer setting is discordant. Methods PD-L1 expression was analyzed using immunohistochemistry in 500 pediatric tumors (including neuroblastoma, sarcomas, and brain cancers). Tumors with ≥ 1% cells showing PD-L1 membrane staining of any intensity were scored as positive. Positive cases were further characterized, with cases with weak intensity PD-L1 staining reported as having low PD-L1 expression and cases with a moderate or strong intensity of staining considered to have high PD-L1 expression. Results PD-L1–positive staining was identified in 13% of cases, whereas high PD-L1 expression was found in 3% of cases. Neuroblastoma (n = 254) showed PD-L1 expression of any intensity in 18.9% of cases and was associated with longer overall survival ( P = .045). However, high PD-L1 expression in neuroblastoma (3.1%) was significantly associated with an increased risk of relapse ( P = .002). Positive PD-L1 staining was observed more frequently in low- and intermediate-risk patients ( P = .037) and in cases lacking MYCN amplification ( P = .002). Conclusion In summary, high PD-L1 expression in patients with neuroblastoma may represent an unfavorable prognostic factor associated with a higher risk of cancer relapse. This work proposes PD-L1 immunohistochemical assessment as a novel parameter for identifying patients with an increased likelihood of cancer recurrence.
Saller, BD, Sha, G, Yang, LM, Liu, F, Ringer, SP & Schoenung, JM 2017, 'Iron in solution with aluminum matrix after non-equilibrium processing: an atom probe tomography study', Philosophical Magazine Letters, vol. 97, no. 3, pp. 118-124.
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Sameen, M & Pradhan, B 2017, 'Severity Prediction of Traffic Accidents with Recurrent Neural Networks', Applied Sciences, vol. 7, no. 6, pp. 476-476.
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In this paper, a deep learning model using a Recurrent Neural Network (RNN) was developed and employed to predict the injury severity of traffic accidents based on 1130 accident records that have occurred on the North-South Expressway (NSE), Malaysia over a six-year period from 2009 to 2015. Compared to traditional Neural Networks (NNs), the RNN method is more effective for sequential data, and is expected to capture temporal correlations among the traffic accident records. Several network architectures and configurations were tested through a systematic grid search to determine an optimal network for predicting the injury severity of traffic accidents. The selected network architecture comprised of a Long-Short Term Memory (LSTM) layer, two fully-connected (dense) layers and a Softmax layer. Next, to avoid over-fitting, the dropout technique with a probability of 0.3 was applied. Further, the network was trained with a Stochastic Gradient Descent (SGD) algorithm (learning rate = 0.01) in the Tensorflow framework. A sensitivity analysis of the RNN model was further conducted to determine these factors’ impact on injury severity outcomes. Also, the proposed RNN model was compared with Multilayer Perceptron (MLP) and Bayesian Logistic Regression (BLR) models to understand its advantages and limitations. The results of the comparative analyses showed that the RNN model outperformed the MLP and BLR models. The validation accuracy of the RNN model was 71.77%, whereas the MLP and BLR models achieved 65.48% and 58.30% respectively. The findings of this study indicate that the RNN model, in deep learning frameworks, can be a promising tool for predicting the injury severity of traffic accidents.
Sameen, MI & Pradhan, B 2017, 'A Novel Road Segmentation Technique from Orthophotos Using Deep Convolutional Autoencoders', KOREAN JOURNAL OF REMOTE SENSING, vol. 33, no. 4, pp. 423-436.
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This paper presents a deep learning-based road segmentation framework from very high resolution orthophotos.The proposed method usesDeep Convolutional Autoencoders for end-to-end mapping
of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the
model outputs GIS-ready data that could be useful for various applications. The optimization of the model’s
parameters is explained whichwas conducted via grid search method.The modelwas trained and implemented
in Keras, a high-level deep learning framework run on top of Tensorflow. The results show thatthe proposed
model with the best-obtained hyperparameters could segment road objects from orthophotos at an average
accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation
function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU),
respectively. In addition,the best numbers of convolutional filters were found to be 8 for the first and second
layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis
on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on
1024 high-resolution images of size 106 × 106 pixels, and segment road objects from similar size and
resolution images in around 14 minutes.The results show that the deep learning models such as Convolutional
Autoencoders could be a best alternative to traditional machine learning models for road segmentation from
aerial photographs.
Sameen, MI & Pradhan, B 2017, 'A Simplified Semi-Automatic Technique for Highway Extraction from High-Resolution Airborne LiDAR Data and Orthophotos', Journal of the Indian Society of Remote Sensing, vol. 45, no. 3, pp. 395-405.
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Information on highways is an essential input for various geospatial applications, including car navigation, forensic analysis on highway geometries, and intelligent transportation systems. Semi-automatic and automatic extractions of highways are critical for the regular updating of municipal databases and for highway maintenance. This study presents a semi-automatic data processing approach for extracting highways from high-resolution airborne LiDAR height information and aerial orthophotos. The method was developed based on two data sets. Experimental results for the first testing site showed that the accuracy of the proposed method for highway extraction was 74.50 % for completeness and 73.13 % for correctness. Meanwhile, the completeness and correctness for the second testing site were 71.20 and 70.72 %, respectively. The proposed method was compared with an object-based approach on a different data set. The accuracy for highway extraction of the object-based approach was 64.29 % for completeness and 63.11 % for correctness, whereas that of the proposed method was 67.14 % for completeness and 65.08 % for correctness. This research aims to promote semi-automatic highway extraction from LiDAR data and orthophotos by proposing a new approach and a multistep post-processing technique. The proposed method provides an accurate final output that is valuable for a wide range of geospatial applications.
Sameen, MI & Pradhan, B 2017, 'A Two-Stage Optimization Strategy for Fuzzy Object-Based Analysis Using Airborne LiDAR and High-Resolution Orthophotos for Urban Road Extraction', Journal of Sensors, vol. 2017, pp. 1-17.
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In the last decade, object-based image analysis (OBIA) has been extensively recognized as an effective classification method for very high spatial resolution images or integrated data from different sources. In this study, a two-stage optimization strategy for fuzzy object-based analysis using airborne LiDAR was proposed for urban road extraction. The method optimizes the two basic steps of OBIA, namely, segmentation and classification, to realize accurate land cover mapping and urban road extraction. This objective was achieved by selecting the optimum scale parameter to maximize class separability and the optimum shape and compactness parameters to optimize the final image segments. Class separability was maximized using the Bhattacharyya distance algorithm, whereas image segmentation was optimized using the Taguchi method. The proposed fuzzy rules were created based on integrated data and expert knowledge. Spectral, spatial, and texture features were used under fuzzy rules by implementing the particle swarm optimization technique. The proposed fuzzy rules were easy to implement and were transferable to other areas. An overall accuracy of 82% and a kappa index of agreement (KIA) of 0.79 were achieved on the studied area when results were compared with reference objects created via manual digitization in a geographic information system. The accuracy of road extraction using the developed fuzzy rules was 0.76 (producer), 0.85 (user), and 0.72 (KIA). Meanwhile, overall accuracy was decreased by approximately 6% when the rules were applied on a test site. A KIA of 0.70 was achieved on the test site using the same rules without any changes. The accuracy of the extracted urban roads from the test site was 0.72 (KIA), which decreased to approximately 0.16. Spatial information (i.e., elongation) and intensity from LiDAR were the most interesting properties for urban road extraction. The proposed method can be applied to a wide range of real applicatio...
Sameen, MI & Pradhan, B 2017, 'Assessment of the effects of expressway geometric design features on the frequency of accident crash rates using high-resolution laser scanning data and GIS', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 733-747.
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Sameen, MI, Pradhan, B, Shafri, HZM, Mezaal, MR & Hamid, HB 2017, 'Integration of Ant Colony Optimization and Object-Based Analysis for LiDAR Data Classification', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 5, pp. 2055-2066.
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© 2017 IEEE. Light detection and ranging (LiDAR) data classification provides useful thematic maps for numerous geospatial applications. Several methods and algorithms have been proposed recently for LiDAR data classification. Most studies focused on object-based analysis because of its advantages over per-pixel-based methods. However, several issues, such as parameter optimization, attribute selection, and development of transferable rulesets, remain challenging in this topic. This study contributes to LiDAR data classification by developing an approach that integrates ant colony optimization (ACO) and rule-based classification. First, LiDAR-derived digital elevation and digital surface models were integrated with high-resolution orthophotos. Second, the processed raster was segmented with the multiresolution segmentation method. Subsequently, the parameters were optimized with a supervised technique based on fuzzy analysis. A total of 20 attributes were selected based on general knowledge on the study area and LiDAR data; the best subset containing 12 attributes was then selected via ACO. These attributes were utilized to develop rulesets through the use of a decision tree algorithm, and a thematic map was generated for the study area. Results revealed the robustness of the proposed method, which has an overall accuracy of ∼95% and a kappa coefficient of 0.94. The rule-based approach with all attributes and the k nearest neighbor (KNN) classification method were applied to validate the results of the proposed method. The overall accuracy of the rule-based method with all attributes was ∼88% (kappa = 0.82), whereas the KNN method had an overall accuracy of <70% and produced a poor thematic map. The selection of the ACO algorithm was justified through a comparison with three well-known feature selection methods. On the other hand, the transferability of the developed rules was evaluated by using a second LiDAR dataset at another study area. The overall ...
Saputra, YM & Yun, J-H 2017, 'E-MICE: Energy-Efficient Concurrent Exploitation of Multiple Wi-Fi Radios', IEEE Transactions on Mobile Computing, vol. 16, no. 7, pp. 1870-1880.
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© 2002-2012 IEEE. The concurrent use of multiple Wi-Fi radios in individual frequency channels is a solution readily available today to the increase of a mobile station's communication capacity, but at the expense of occasional performance deterioration (when the heterogeneity of capacity between interfaces gets severe) and additional power consumption. This paper proposes a mobile-side solution for the concurrent use of multiple radios in a performance-aware and energy-efficient manner, with which a mobile station activates and deactivates radio interfaces dynamically according to traffic demands and a predicted capacity gain. To this end, the proposed solution is composed of multiple prediction algorithms and a control algorithm. Prediction when activating an additional radio interface is relatively difficult since no information of the disabled interface's current status (and the corresponding frequency channel's) is available at the time of prediction. Our experiments show that, despite different types and used channels, different radio interfaces have a strong correlation of received signal strengths and used PHY rates between them. Based on this observation, the proposed solution learns a correlation pattern between interfaces whenever multiple interfaces are active and makes prediction of the coverage, expected PHY rate and capacity impact of an inactive interface based on the learned correlation with a currently active interface. The design of the prediction algorithms are based on a simple or machine-learning technique (SVM). The control algorithm then keeps monitoring the utilization of active interfaces and, if any of them has utilization over a threshold, checks if each inactive interface is within coverage and a valid rate range based on an active interface's received signal strength. Finally, an action of a configuration change (either activation, deactivation, or no change) selected based on the prediction of the resulting capacity is app...
Sarkheil, H, Rahbari, S, Rad, MH & Tavakoli, J 2017, 'Development of a three-step hierarchical screening matrix to optimize inherently safety design index and inherently safety design cost (A case study in Acetic acid production process)', JOURNAL OF HEALTH AND SAFETY AT WORK, vol. 7, no. 3, pp. 245-254.
Sathyamoorthy, D, Pradhan, B, Voon Chet, K & Chuah, HT 2017, 'IEEE GRSS Malaysia Chapter [Chapters]', IEEE Geoscience and Remote Sensing Magazine, vol. 5, no. 2, pp. 100-102.
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Sato, H, Manabe, K, Furushima, T, Wei, DB, Jiang, ZY & Alexandrov, S 2017, 'On the Scale Dependence of Micro Hydromechanical Deep Drawing', Key Engineering Materials, vol. 725, pp. 689-694.
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Tooling feature size to minimum thickness becomes small in micro scale products and its ratio affects the deformation behavior in micro sheet forming significantly. In this study, the effect of this relative tooling feature size on drawing characteristics and effects to improve the drawability, such as friction holding effect, hydrodynamic lubrication effect and compression effect by blank edge radial pressure, in micro hydromechanical deep drawing (MHDD) are investigated using plasticity theory and numerical simulation. The results show that the micro drawing characteristics in MHDD can be improved by applying counter pressure. However, the required fluid pressures for friction holding and hydrodynamic lubrication effects increase as the relative punch diameter and/or die shoulder radius to thickness decrease, although the compression effect by radial pressure on the blank edge is independent of the relative tooling feature size.
Saxena, A, Prasad, M, Gupta, A, Bharill, N, Patel, OP, Tiwari, A, Er, MJ, Ding, W & Lin, C-T 2017, 'A review of clustering techniques and developments', Neurocomputing, vol. 267, pp. 664-681.
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© 2017 Elsevier B.V. This paper presents a comprehensive study on clustering: exiting methods and developments made at various times. Clustering is defined as an unsupervised learning where the objects are grouped on the basis of some similarity inherent among them. There are different methods for clustering the objects such as hierarchical, partitional, grid, density based and model based. The approaches used in these methods are discussed with their respective states of art and applicability. The measures of similarity as well as the evaluation criteria, which are the central components of clustering, are also presented in the paper. The applications of clustering in some fields like image segmentation, object and character recognition and data mining are highlighted.
Schell, AW, Takashima, H, Tran, TT, Aharonovich, I & Takeuchi, S 2017, 'Coupling Quantum Emitters in 2D Materials with Tapered Fibers', ACS Photonics, vol. 4, no. 4, pp. 761-767.
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© 2017 American Chemical Society. Realization of integrated photonic circuits on a single chip requires controlled manipulation and integration of solid-state quantum emitters with nanophotonic components. Previous works focused on emitters embedded in a three-dimensional crystal, such as nanodiamonds or quantum dots. In contrast, in this work we demonstrate coupling of a single emitter in a two-dimensional (2D) material, namely, hexagonal boron nitride, with a tapered optical fiber and find a collection efficiency of the system of 10%. Furthermore, due to the single dipole character of the emitter, we were able to analyze the angular emission pattern of the coupled system via back focal plane imaging. The good coupling efficiency to the tapered fiber even allows excitation and detection in a fully fiber coupled way, yielding a true integrated system. Our results provide evidence of the feasibility to efficiently integrate quantum emitters in 2D materials with photonic structures.
Schwarzer, A, Emmrich, S, Schmidt, F, Beck, D, Ng, M, Reimer, C, Adams, FF, Grasedieck, S, Witte, D, Käbler, S, Wong, JWH, Shah, A, Huang, Y, Jammal, R, Maroz, A, Jongen-Lavrencic, M, Schambach, A, Kuchenbauer, F, Pimanda, JE, Reinhardt, D, Heckl, D & Klusmann, J-H 2017, 'The non-coding RNA landscape of human hematopoiesis and leukemia', Nature Communications, vol. 8, no. 1, pp. 1-17.
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AbstractNon-coding RNAs have emerged as crucial regulators of gene expression and cell fate decisions. However, their expression patterns and regulatory functions during normal and malignant human hematopoiesis are incompletely understood. Here we present a comprehensive resource defining the non-coding RNA landscape of the human hematopoietic system. Based on highly specific non-coding RNA expression portraits per blood cell population, we identify unique fingerprint non-coding RNAs—such as LINC00173 in granulocytes—and assign these to critical regulatory circuits involved in blood homeostasis. Following the incorporation of acute myeloid leukemia samples into the landscape, we further uncover prognostically relevant non-coding RNA stem cell signatures shared between acute myeloid leukemia blasts and healthy hematopoietic stem cells. Our findings highlight the importance of the non-coding transcriptome in the formation and maintenance of the human blood hierarchy.
Sebayang, A, Hassan, M, Ong, H, Dharma, S, Silitonga, A, Kusumo, F, Mahlia, T & Bahar, A 2017, 'Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology', Energies, vol. 10, no. 1, pp. 35-35.
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Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications of the ASTM D4806 standard. The good quality of ethanol produced from this study indicates that Manihot glaziovii (M. glaziovii) has great potential as bioethanol feedstock.
Sebayang, AH, Hasan, MH, Chyuan, OH, Dharma, S, Bahar, AH, Silitonga, AS & Kusumo, F 2017, 'Enzymatic hydrolysis using ultrasound for bioethanol production from durian (durio zibethinus) seeds as potential bio fuel', Chemical Engineering Transactions, vol. 56, pp. 553-558.
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The appealing second generation bioethanol production brings a good promise to achieve a fuel production that is renewable and sustainable; this makes durian (Durio zibethinus) seed interesting to take advantage of, especially for a tropical country like Malaysia. This paper aims to produce bioethanol from durian seed by utilizing ultrasound technique in its enzymatic hydrolysis process. 9 % (w/v) pre-Treated durian seed was brought into the ultrasound-Assisted glass reactor to begin the liquefaction and saccharification processes. Bacillus licheniformis Type XII-A was employed, and ultrasound at 50% amplitude for 60 min was set for liquefaction process; while amyloglucosidase from Aspergillus niger was used, and ultrasound at 40% amplitude for 120 min was run for saccharification process. The sum of both processes in hydrolysis yielded 41.07 g/L of reducing sugar, which was immediately brought to fermentation stage. Saccharomyces cerevisiae was employed for fermentation and resulted 18.48 g/L (0.44 g ethanol/g glucose), which is equivalent to 86.27 % of theoretical ethanol yield (0.51 g ethanol/g glucose) after 84 h of fermentation at 37 °C with 150 rpm incubator shaker. The ethanol purity was improved in the next stage, distillation. Using zeolite as adsorbent, ethanol with purity of 95.7% (v/v) was produced. From the acquired results, durian seed shows a justifiably potential as a second generation bioethanol feedstock. To further improve its potential, studies of optimization using this feedstock is highly encouraged.
Sebayang, AH, Masjuki, HH, Ong, HC, Dharma, S, Silitonga, AS, Kusumo, F & Milano, J 2017, 'Optimization of bioethanol production from sorghum grains using artificial neural networks integrated with ant colony', Industrial Crops and Products, vol. 97, pp. 146-155.
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In this study, an artificial neural networks (ANN) model is developed to investigate the relationship between bioethanol production and the operating parameters of enzymatic hydrolysis and fermentation processes. The operating parameters of the hydrolysis process which influence the reducing sugar concentration are the substrate loading, α-amylase concentration, amyloglucosidase concentration and strokes speed. The operating parameters of the fermentation process which influence the ethanol concentration are the yeast concentration, reaction temperature and agitation speed. The desirability function of the model is integrated with ant colony optimization (ACO) in order to determine the optimum operating parameters which will maximize reducing sugar and ethanol concentrations. The optimum substrate loading, α-amylase concentration, amyloglucosidase concentration and strokes speed is determined to be 20% (w/v), 109.5 U/g, 36 U/mL and 50 spm, respectively. The reducing sugar obtained at these optimum conditions is 175.94 g/L, which is close to the average value from experiments (174.29 g/L). The optimum yeast concentration, reaction temperature and agitation speed is found to be 1.3 g/L, 35.6 °C and 181 rpm, respectively. The ethanol concentration obtained from the fermentation of sorghum starch by Saccharomyces cerevisiae yeast at these optimum conditions is 82.11 g/L, which is in good agreement with the average value from experiments (81.52 g/L). Based on the results, it can be concluded that the model developed in this study model is an effective method to optimize bioethanol production, and it reduces the cost, time and effort associated with experimental techniques.
Sebayang, AH, Masjuki, HH, Ong, HC, Dharma, S, Silitonga, AS, Kusumo, F & Milano, J 2017, 'Prediction of engine performance and emissions with Manihot glaziovii bioethanol − Gasoline blended using extreme learning machine', Fuel, vol. 210, pp. 914-921.
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Bioethanol can potentially replace gasoline because of its lower exhaust emissions. The purpose of this study was to investigate the engine performance and exhaust emissions of Manihot glaziovii bioethanol–gasoline blends at different blend ratios (5%, 10%, 15%, and 20%). Tests were performed on a single-cylinder, four-stroke spark-ignition engine with engine speed was varied from 1600 to 3400 rpm, and the properties of the Manihot glaziovii bioethanol–gasoline blends were measured and analysed. The vapour pressure increased for fuel blends with low concentrations of bioethanol due to the oxygen within the bioethanol molecules and the contribution of the flame speed which can enhance the combustion and improved the engine efficiency. In addition, the engine torque, brake power, and brake-specific fuel consumption (BSFC) were measured, as well as the carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide emissions. For a fuel blend containing 20% bioethanol at an engine speed of 3200 rpm, the BSFC decreased, with maximum values of 270.7 g/kWh. The CO and HC emissions were lower for the Manihot glaziovii bioethanol–gasoline blends. In addition, an extreme learning machine (ELM) model was developed for application in the automotive and industrial sectors. This tool reduces the cost, time, and effort associated with experimental data. The blend ratio of the bioethanol–gasoline blends and the engine speed were used as the input data of the model, and the engine performance and exhaust emissions parameters were used as the output data. The coefficient of determination (R2) was within a range of 0.980–1.000, and the mean absolute percentage error was within a range of 0.411%−2.782% for all the parameters. The results indicate that the ELM model is capable of predicting the engine performance and exhaust emissions of bioethanol–gasoline fuel blends.
Sefidan, AM, Sojoudi, A & Saha, SC 2017, 'Nanofluid-based cooling of cylindrical lithium-ion battery packs employing forced air flow', International Journal of Thermal Sciences, vol. 117, pp. 44-58.
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© 2017 Elsevier Masson SAS Efficient cooling strategies are very important issues in thermal management of lithium-Ion battery system and these techniques should provide cost effective and energy saving solutions for temperature rise of the system during battery operation. A pseudo 2D electrochemical model has been used to investigate the electrochemical and thermal condition of commercial 18650 Lithium-Ion battery. This analysis was compared to previous experimental studies and results showed that the model predicts the temperature rise and thermal power generation very well. Results from the electro-thermal analysis were used to examine a cooling method. In this strategy, the cylindrical Li-ion cell is submersed within a thin cylindrical tank containing water-Al2O3 nanofluid. Air flow is employed to remove the heat from the system during discharge process. After testing this method for a single cell with various sizes of the secondary cylinder, critical and thermally dangerous arrangements of Li-ion cells were analyzed employing the new technique. 3D transient Computational Fluid Dynamics (CFD) simulations were used to see the effect of presence of the secondary cylinder on temperature rise. Results revealed that the new method reduces the maximum temperature of the cells efficiently.
Sefidan, AM, Sojoudi, A, Saha, SC & Cholette, M 2017, 'Multi-layer PCM solidification in a finned triplex tube considering natural convection', Applied Thermal Engineering, vol. 123, pp. 901-916.
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© 2017 Elsevier Ltd Efficient latent heat storage systems represent an important opportunity to improve the thermal performance and operational capability of industrial systems (e.g. solar thermal). In this paper, numerical study is performed to evaluate the heat transfer and solidification features, phase change period and temperature distribution of double-layer Phase Changing Materials (PCM) in a finned triplex tube. A two-dimensional finite volume numerical technique is used to solve the governing equations considering conduction and convection heat transfer mechanisms at a fixed Rayleigh number of 106. After comparing the results for single and double layer configurations, possible arrangements of two different PCMs are discussed in terms of different thicknesses of each PCM, fin sizes and different heat transfer fluid temperatures. Results are illustrated as the form of temperature, liquid fraction, stream function and velocity magnitude contours and their changes over the freezing time. Variation of liquid fraction values, average and minimum temperatures of layers in a double-layer PCM are reported for better insight into the heat transfer features of the latent heat thermal energy storage system to enable uniform discharging designs and balance the phase changing rate within the whole annulus.
Sehgal, RR, Roohani-Esfahani, SI, Zreiqat, H & Banerjee, R 2017, 'Nanostructured gellan and xanthan hydrogel depot integrated within a baghdadite scaffold augments bone regeneration', Journal of Tissue Engineering and Regenerative Medicine, vol. 11, no. 4, pp. 1195-1211.
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Semblante, GU, Hai, FI, Dionysiou, DD, Fukushi, K, Price, WE & Nghiem, LD 2017, 'Holistic sludge management through ozonation: A critical review', Journal of Environmental Management, vol. 185, pp. 79-95.
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This paper critically reviews the multidimensional benefits of ozonation in wastewater treatment plants. These benefits include sludge reduction, removal of emerging trace organic contaminants (TrOC) from wastewater and sludge, and resource recovery from sludge. Literature shows that ozonation leads to sludge solubilisation, reducing overall biomass yield. Sludge solubilisation is primarily influenced by ozone dosage, which, in turn, depends on the fraction of ozonated sludge, ozone concentration, and sludge concentration. Additionally, sludge ozonation facilitates the removal of TrOCs from wastewater. On the other hand, by inducing cell lysis, ozonation increases the chemical oxygen demand (COD) and nutrient concentration of the sludge supernatant, which deteriorates effluent quality. This issue can be resolved by implementing resource recovery. Thus far, successful retrieval of phosphorous from ozonated sludge supernatant has been performed. The recovery of phosphorous and other resources from sludge could help offset the operation cost of ozonation, and give greater incentive for wastewater treatment plants to adapt this approach.
Semblante, GU, Hai, FI, McDonald, J, Khan, SJ, Nelson, M, Lee, D-J, Price, WE & Nghiem, LD 2017, 'Fate of trace organic contaminants in oxic-settling-anoxic (OSA) process applied for biosolids reduction during wastewater treatment', Bioresource Technology, vol. 240, pp. 181-191.
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This study investigated the fate of trace organic contaminants (TrOCs) in an oxic-settling-anoxic (OSA) process consisting of a sequencing batch reactor (SBR) with external aerobic/anoxic and anoxic reactors. OSA did not negatively affect TrOC removal of the SBR. Generally, low TrOC removal was observed under anoxic and low substrate conditions, implicating the role of co-metabolism in TrOC biodegradation. Several TrOCs that were recalcitrant in the SBR (e.g., benzotriazole) were biodegraded in the external aerobic/anoxic reactor. Some hydrophobic TrOCs (e.g., triclosan) were desorbed in the anoxic reactor possibly due to loss of sorption sites through volatile solids destruction. In OSA, the sludge was discharged from the aerobic/anoxic reactor which contained lower concentration of TrOCs (e.g., triclosan and triclocarban) than that of the control aerobic digester, suggesting that OSA can also help to reduce TrOC concentration in residual biosolids.
Semblante, GU, Phan, HV, Hai, FI, Xu, Z-Q, Price, WE & Nghiem, LD 2017, 'The role of microbial diversity and composition in minimizing sludge production in the oxic-settling-anoxic process', Science of The Total Environment, vol. 607-608, pp. 558-567.
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© 2017 Elsevier B.V. The oxic-settling-anoxic (OSA) process, which involves an aerobic tank attached to oxygen- and substrate-deficient external anoxic reactors, minimizes sludge production in biological wastewater treatment. In this study, the microbial community structure of OSA was determined. Principal coordinate analysis showed that among the three operational factors, i.e., (i) redox condition, (ii) external reactor sludge retention time (SRText), and (iii) sludge interchange between aerobic and anoxic reactors, redox condition had the greatest impact on microbial diversity. Generally, reactors with lower oxidation-reduction potential had higher microbial diversity. The main aerobic sequencing batch reactor of OSA (SBROSA) that interchanged sludge with an external anoxic reactor had greater microbial diversity than SBRcontrol which did not have sludge interchange. SBROSA sustained high abundance of the slow-growing nitrifying bacteria (e.g., Nitrospirales and Nitrosomondales) and consequently exhibited reduced sludge yield. Specific groups of bacteria facilitated sludge autolysis in the external reactors. Hydrolyzing (e.g., Bacteroidetes and Chloroflexi) and fermentative (e.g., Firmicutes) bacteria, which can break down cellular matter, proliferated in both the external aerobic/anoxic and anoxic reactors. Sludge autolysis in the anoxic reactor was enhanced with the increase of predatory bacteria (e.g., order Myxobacteriales and genus Bdellovibrio) that can contribute to biomass decay. Furthermore, β- and γ-Proteobacteria were identified as the bacterial phyla that primarily underwent decay in the external reactors.
Seneviratne, S, Hu, Y, Nguyen, T, Lan, G, Khalifa, S, Thilakarathna, K, Hassan, M & Seneviratne, A 2017, 'A Survey of Wearable Devices and Challenges', IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2573-2620.
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© 1998-2012 IEEE. As smartphone penetration saturates, we are witnessing a new trend in personal mobile devices-wearable mobile devices or simply wearables as it is often called. Wearables come in many different forms and flavors targeting different accessories and clothing that people wear. Although small in size, they are often expected to continuously sense, collect, and upload various physiological data to improve quality of life. These requirements put significant demand on improving communication security and reducing power consumption of the system, fueling new research in these areas. In this paper, we first provide a comprehensive survey and classification of commercially available wearables and research prototypes. We then examine the communication security issues facing the popular wearables followed by a survey of solutions studied in the literature. We also categorize and explain the techniques for improving the power efficiency of wearables. Next, we survey the research literature in wearable computing. We conclude with future directions in wearable market and research.
Sengupta, D, Kottapalli, AGP, Chen, SH, Miao, JM, Kwok, CY, Triantafyllou, MS, Warkiani, ME & Asadnia, M 2017, 'Characterization of single polyvinylidene fluoride (PVDF) nanofiber for flow sensing applications', AIP Advances, vol. 7, no. 10, pp. 105205-105205.
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The use of Polyvinylidene Fluoride (PVDF) based piezoelectric nanofibers for sensing and actuation has been reported widely in the past. However, in most cases, PVDF piezoelectric nanofiber mats have been used for sensing applications. This work fundamentally characterizes a single electrospun PVDF nanofiber and demonstrates its application as a sensing element for nanoelectromechanical sensors (NEMS). PVDF nanofiber mats were spun by far field electrospinning (FFES) process and complete material characterization was conducted by means of scanning electron microscope (SEM) imaging, Raman Spectroscopy and FTIR spectroscopy. An optimized recipe was developed for spinning a single suspended nanofiber on a specially designed MEMS substrate which allows the nano-mechanical and electrical characterization of a single PVDF nanofiber. Electrical characterization is conducted using a single suspended nanofiber to determine the piezoelectric coefficient (d33) of the nanofiber to be -58.77 pm/V. Also the mechanical characterization conducted using a nanoindenter revealed a Young’s Modulus and hardness of 2.2 GPa and 0.1 GPa respectively. Finally, an application that utilizes the single PVDF nanofiber as a sensing element to form a NEMS flow sensor is demonstrated. The single nanofiber flow sensor is tested in presence of various oscillatory flow conditions.
Shahbazi, B, Chehreh Chelgani, S & Matin, SS 2017, 'Prediction of froth flotation responses based on various conditioning parameters by Random Forest method', Colloids and Surfaces A: Physicochemical and Engineering Aspects, vol. 529, pp. 936-941.
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Shahnazar, A, Nikafshan Rad, H, Hasanipanah, M, Tahir, MM, Jahed Armaghani, D & Ghoroqi, M 2017, 'A new developed approach for the prediction of ground vibration using a hybrid PSO-optimized ANFIS-based model', Environmental Earth Sciences, vol. 76, no. 15.
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SHAHRARA, N, ÇELIK, T & GANDOMI, AH 2017, 'GENE EXPRESSION PROGRAMMING APPROACH TO COST ESTIMATION FORMULATION FOR UTILITY PROJECTS', JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, vol. 23, no. 1, pp. 85-95.
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This article utilizes gene expression programming (GEP) technique to develop a prediction model in order to automate estimating the construction cost of water and sewer replacement/rehabilitation projects. A database gathered for developing the model was established on the basis of data related to 210 actual water and sewer projects obtained from the City of San Diego, California, USA. To verify the predictability of the GEP model, it was examined to estimate the cost of the projects that were not included in the modelling process. Sensitivity analysis technique and professional experiences were employed to determine the contributions of the qualitative factors and quantifiable parameters affecting the cost estimate. The proposed model with correlation coefficient of 0.8467 is adequately capable of estimating the cost of water and sewer replacement/rehabilitation projects. The GEP-based design equation can easily be used for predesign purposes to help allocate budgets and available limited resources effectively.
Shakeel Syed, M, Rafeie, M, Henderson, R, Vandamme, D, Asadnia, M & Ebrahimi Warkiani, M 2017, 'A 3D-printed mini-hydrocyclone for high throughput particle separation: application to primary harvesting of microalgae', Lab on a Chip, vol. 17, no. 14, pp. 2459-2469.
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3D-printed hydrocyclones are low-cost microdevices which be part of a library of standardized active and passive microfluidic components, suitable for particle–liquid separation.
Shakor, P, Sanjayan, J, Nazari, A & Nejadi, S 2017, 'Modified 3D printed powder to cement-based material and mechanical properties of cement scaffold used in 3D printing', Construction and Building Materials, vol. 138, pp. 398-409.
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© 2017 Elsevier Ltd Additive manufacturing is a common technique used to produce 3D printed structures. These techniques have been used as precise application geometry in different fields such as architecture and medicine, and the food, mechanics and chemical industries. However, in most cases only a limited amount of powder has been used to fabricate scaffold (structure). In this study, a unique mix of cements (calcium aluminate cement passed through a 150 μm sieve and ordinary Portland cement) was developed for Z-Corporation's three-dimensional printing (3DP) process. This cement mix was blended and the resulting composite powders were printed with a water-based binder using a Z-Corporation 3D printer. Moreover, some samples were added lithium carbonate to reduce the setting time for the cement mixture. The aims of the study were to firstly, find the proper cementitious powder close to the targeted powder (Z-powder); and secondly, evaluate the mechanical properties of this material. Cubic specimens of two different batches with varying saturation levels were cast and cured in various scenarios to enhance the best mechanical properties. The samples were characterised by porosity analyses, compression tests, Olympus BX61 Microscope imaging, 3D profiling Veeco (Dektak) and the Scanning Electronic Microscope (SEM). The maximum compressive strength of the cubic specimens for cementitious 3DP was 8.26 MPa at the saturation level of 170% for both the shell and core. The minimum porosity obtained was 49.28% at the saturation level of 170% and 340% for the shell and the core, respectively.
Shanmuganathan, S, Loganathan, P, Kazner, C, Johir, MAH & Vigneswaran, S 2017, 'Submerged membrane filtration adsorption hybrid system for the removal of organic micropollutants from a water reclamation plant reverse osmosis concentrate', DESALINATION, vol. 401, pp. 134-141.
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© 2016 Elsevier B.V. Reverse osmosis (RO) is a widespread water treatment process utilised in water reuse applications. However, the improper discharge of RO concentrate (ROC) containing organic micropollutants such as pharmaceuticals into the environment may cause potential health risks to non-target species and particularly those in aquatic environments. A study was conducted using a submerged membrane-filtration/granular activated carbon (GAC) adsorption hybrid system to remove organic micropollutants from a water treatment plant ROC by initially adding 10 g GAC /L of membrane reactor volume with 10% daily GAC replacement. The percentage of dissolved organic carbon removal varied from 60% to 80% over an operation lasting 10 days. Removal of organic micropollutants was almost complete for virtually all compounds. Of the 19 micropollutants tested, only two remained (the less hydrophobic DEET 27 ng/L and the hydrophilic sulfamethoxazole 35 ng/L) below 80% removal on day 1, while five of the most hydrophobic micropollutants were detectable in very small concentrations (< 5–10 ng/L) with > 89%–> 99% being removed. High percentages of micropollutants were removed probably because of their high hydrophobicity or they had positive or neutral charges and therefore they were electrostatically adsorbed to the negatively charged GAC.
Shannon, AG 2017, 'Mathematical contributions to the study of Diabetes Mellitus', International Journal Bioautomation, vol. 21, no. 3, pp. 261-268.
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The purpose of the studies outlined in this paper is to describe some indicative and non-standard, but not exhaustive, quantitative contributions to the collection of diseases within the Diabetes Mellitus (DM) spectrum. While the paper has implications for bioinformatics related to DM, the paper is broader than that; it is more about DM-related bioprocesses illuminated by bioinformatics than about the bioinformatics per se. In effect it is an argument against being locked into one particular paradigm in the laudable study of this complicated set of diseases which increasingly dominate public health budgets, not to mention the lives of the patients with DM and their families.
Shannon, AG 2017, 'Primitive Pythagorean triples and generalized Fibonacci sequences', Notes on Number Theory and Discrete Mathematics, vol. 23, no. 1, pp. 54-62.
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It is proved that infinite sequences of generalized Fibonacci sequences obtained fromgeneralizations of the Golden Ratio can generate all primitive Pythagorean triples. This is aconsequence of the integer structure since the major component of a primitive Pythagorean triplealways has the form (4r1 + 1) where r1 belongs to the class in the modular ring Z4.
Shannon, AG & Deveci, Ö 2017, 'Pell–Padovan-circulant sequences and their applications', Notes on Number Theory and Discrete Mathematics, vol. 23, no. 3, pp. 100-114.
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This paper develops properties of recurrence sequences defined from circulant matrices obtained from the characteristic polynomial of the Pell-Padovan sequence. The study of these sequences modulo m yields cyclic groups and semigroups from the generating matrices. Finally, we obtain the lengths of the periods of the extended sequences in the extended triangle groups E(2, n, 2), E(2, 2, n) and E(n, 2, 2) for n ≥ 3 as applications of the results obtained.
Shannon, AG, Aküzüm, Y & Deveci, Ö 2017, 'On the Pell p-circulant sequences', Notes on Number Theory and Discrete Mathematics, vol. 23, no. 2, pp. 91-103.
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In this paper, we define the generalized Pell p-circulant sequence and the Pell pcirculantsequence by using the circulant matrices which are obtained from the characteristicpolynomial of the generalized Pell ( p,i)-sequence and then, we obtain miscellaneousproperties of these sequences. Also, we consider the cyclic groups which are generated by thegenerating matrices and the auxiliary equations of the defined recurrence sequences and then,we study the orders of these groups. Furthermore, we extend the Pell p-circulant sequence togroups. Finally, we obtain the lengths of the periods of Pell p-circulant sequences in thesemidihedral group 2 SD m for m ≥ 4 as applications of the results obtained.
Sharma, S, Puthal, D, Tazeen, S, Prasad, M & Zomaya, AY 2017, 'MSGR: A Mode-Switched Grid-Based Sustainable Routing Protocol for Wireless Sensor Networks', IEEE Access, vol. 5, pp. 19864-19875.
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© 2013 IEEE. A Wireless Sensor Network (WSN) consists of enormous amount of sensor nodes. These sensor nodes sense the changes in physical parameters from the sensing range and forward the information to the sink nodes or the base station. Since sensor nodes are driven with limited power batteries, prolonging the network lifetime is difficult and very expensive, especially for hostile locations. Therefore, routing protocols for WSN must strategically distribute the dissipation of energy, so as to increase the overall lifetime of the system. Current research trends from areas, such as from Internet of Things and fog computing use sensors as the source of data. Therefore, energy-efficient data routing in WSN is still a challenging task for real-Time applications. Hierarchical grid-based routing is an energy-efficient method for routing of data packets. This method divides the sensing area into grids and is advantageous in wireless sensor networks to enhance network lifetime. The network is partitioned into virtual equal-sized grids. The proposed mode-switched grid-based routing protocol for WSN selects one node per grid as the grid head. The routing path to the sink is established using grid heads. Grid heads are switched between active and sleep modes alternately. Therefore, not all grid heads take part in the routing process at the same time. This saves energy in grid heads and improves the network lifetime. The proposed method builds a routing path using each active grid head which leads to the sink. For handling the mobile sink movement, the routing path changes only for some grid head nodes which are nearer to the grid, in which the mobile sink is currently positioned. Data packets generated at any source node are routed directly through the data disseminating grid head nodes on the routing path to the sink.
Shehabat, A, Mitew, T & Alzoubi, Y 2017, 'Encrypted Jihad: Investigating the Role of Telegram App in Lone Wolf Attacks in the West', Journal of Strategic Security, vol. 10, no. 3, pp. 27-53.
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The study aims to capture links between the use of encrypted communication channel -Telegram and lone wolf attacks occurred in Europe between 2015-2016. To understand threads of ISIS communication on Telegram we used digital ethnography approach which consists of the self-observation of information flows on four of ISIS’s most celebrated telegram Channels. We draw on public sphere theory and coined the term terror socio-sphere 3.0 as the theoretical background of this study. The collected data is presented as screenshots to capture a visual evidence of ISIS communication threads. This study shows that ISIS Telegram channels play critical role in personal communication between potential recruits and dissemination of propaganda that encourage ‘lone wolves’ to carry attacks in the world at large. This study was limited to the number of the channels that have been widely celebrated.
Shekarchian, M, Moghavvemi, M, Zarifi, F, Moghavvemi, S, Motasemi, F & Mahlia, TMI 2017, 'Impact of infrastructural policies to reduce travel time expenditure of car users with significant reductions in energy consumption', Renewable and Sustainable Energy Reviews, vol. 77, pp. 327-335.
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© 2017 Elsevier Ltd The increasing number of vehicles and drivers have led to a marked increase in travel time expenditure (TTE), congestion, demand for fossil fuels, and adverse environmental impacts. Improving energy efficiency in the transportation sector, public awareness of the behavior of the people vis-à-vis energy efficiency, implementing policies that encourage other modes of transportation (e.g., public transit, ride-sharing, bicycles, and walking, etc.) that decrease vehicle dependency are some effective approaches that mitigate the aforementioned negative effects, which will lead to significant reductions in the total energy consumption. This article investigates the effect of governmental policies on vehicle dependency reduction and the decrease of TTE by vehicle owners, and propose a novel method to calculate the current and future TTEs by individuals. The effect of demographic variables and the region on vehicle dependency and TTE for students of three of the most populated universities in Malaysia (University of Malaya, University Putra Malaysia, and University Technology Malaysia) were investigated as well. The peoples’ expectations from individual modes of transportation such as cycling and walking were also analyzed. The results showed that all demographic factors, except nationality, affect the levels of vehicle ownership, while income levels and nationality affects TTE by personal vehicles. The results show that the average TTE can be reduced by 89% if the recommended infrastructure (e.g., increase bus routes, train routes, train services, frequencies of buses and train, and facilities for cyclists, etc.) is provided. These outcomes can assist policy makers to efficiently manage transportation budgets, and would also help people decrease vehicle usage, which will subsequently decrease their corresponding TTE and fuel consumption.
Shen, F, Yang, Y, Liu, L, Liu, W, Tao, D & Shen, HT 2017, 'Asymmetric Binary Coding for Image Search', IEEE Transactions on Multimedia, vol. 19, no. 9, pp. 2022-2032.
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© 2017 IEEE. Learning to hash has attracted broad research interests in recent computer vision and machine learning studies, due to its ability to accomplish efficient approximate nearest neighbor search. However, the closely related task, maximum inner product search (MIPS), has rarely been studied in this literature. To facilitate the MIPS study, in this paper, we introduce a general binary coding framework based on asymmetric hash functions, named asymmetric inner-product binary coding (AIBC). In particular, AIBC learns two different hash functions, which can reveal the inner products between original data vectors by the generated binary vectors. Although conceptually simple, the associated optimization is very challenging due to the highly nonsmooth nature of the objective that involves sign functions. We tackle the nonsmooth optimization in an alternating manner, by which each single coding function is optimized in an efficient discrete manner. We also simplify the objective by discarding the quadratic regularization term which significantly boosts the learning efficiency. Both problems are optimized in an effective discrete way without continuous relaxations, which produces high-quality hash codes. In addition, we extend the AIBC approach to the supervised hashing scenario, where the inner products of learned binary codes are forced to fit the supervised similarities. Extensive experiments on several benchmark image retrieval databases validate the superiority of the AIBC approaches over many recently proposed hashing algorithms.
Sheng, Z, Tuan, HD, Duong, TQ & Poor, HV 2017, 'Joint Power Allocation and Beamforming for Energy-Efficient Two-Way Multi-Relay Communications', IEEE Transactions on Wireless Communications, vol. 16, no. 10, pp. 6660-6671.
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This paper considers the joint design of user power allocation and relaybeamforming in relaying communications, in which multiple pairs ofsingle-antenna users exchange information with each other via multiple-antennarelays in two time slots. All users transmit their signals to the relays in thefirst time slot while the relays broadcast the beamformed signals to all usersin the second time slot. The aim is to maximize the system's energy efficiency(EE) subject to quality-of-service (QoS) constraints in terms of exchangethroughput requirements. The QoS constraints are nonconvex with many nonlinearcross-terms, so finding a feasible point is already computationallychallenging. The sum throughput appears in the numerator while the totalconsumption power appears in the denominator of the EE objective function. Theformer is a nonconcave function and the latter is a nonconvex function, makingfractional programming useless for EE optimization. Nevertheless, efficientiterations of low complexity to obtain its optimized solutions are developed.The performances of the multiple-user and multiple-relay networks under variousscenarios are evaluated to show the merit of the paper development.
Sheng, Z, Tuan, HD, Nguyen, HH & Debbah, M 2017, 'Optimal Training Sequences for Large-Scale MIMO-OFDM Systems', IEEE Transactions on Signal Processing, vol. 65, no. 13, pp. 3329-3343.
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© 1991-2012 IEEE. This paper considers the optimal design of training sequences for channel estimation in large-scale multiple-input multiple-output orthogonal frequency-division multiplexing systems. The application scenario of interest is when the number of transmit antennas for the downlink (or the number of receive antennas for the uplink) is large, but not large enough to benefit the asymptotical optimality of using equipower training sequences (e.g., due to practical constraints on deployment costs, space, and antenna size). Under the criterion of minimizing the mean square error of the channel estimate, the optimal design of training sequences for such systems poses a truly large-scale optimization problem, to which existing optimization solvers are not applicable. We develop a fast convex programming (FCP) procedure to find its global optimal solution. In each iteration of the proposed FCP procedure, a solution is found in a scalable and closed form. The singularity and ill-conditionedness of the channel correlation matrices are also exploited to improve the computation efficiency. Furthermore, we also examine the design of reduced-length training sequences and develop a successive quadratic programming procedure to find the solutions. Intensive simulation results are provided to illustrate the performance of our methods.
Sheng, Z, Tuan, HD, Nguyen, HH & Fang, Y 2017, 'Pilot Optimization for Estimation of High-Mobility OFDM Channels', IEEE Transactions on Vehicular Technology, vol. 66, no. 10, pp. 8795-8806.
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© 2017 IEEE. Obtaining channel state information is very crucial for realizing high-performance high-rate wireless communications. For an orthogonal frequency-division multiplexing (OFDM) system operating in a high-mobility environment such as in high-speed trains, a sequence of pilot samples is inserted in each OFDM symbol to track the fast-varying channel responses. For such a high-mobility environment, the design of pilot sequence to minimize the mean squared error (MSE) of the channel estimate under a linear minimum mean squared error (LMMSE) estimator poses a difficult polynomial fractional optimization problem. In this paper, we develop a path-following optimization procedure, which improves the MSE in every iteration and quickly converges at least to its locally-optimal solution. Each iterative solution is given in a closed form with very low computational complexity. The developed path-following procedure can also be adapted to design pilot sequences for the least-square and maximum-likelihood estimators. Extensive simulation results demonstrate the effectiveness and superior performance of the proposed solutions and algorithms when compared to the state-of-The-Art algorithms in the literature.
Sheng, Z, Tuan, HD, Tam, HHM, Nguyen, HH & Fang, Y 2017, 'Energy-efficient precoding in multicell networks with full-duplex base stations', EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 1, pp. 1-13.
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© 2017, The Author(s). This paper considers multi-input multi-output (MIMO) multicell networks, where the base stations (BSs) are full-duplex transceivers, while uplink and downlink users are equipped with multiple antennas and operate in a half-duplex mode. The problem of interest is to design linear precoders for BSs and users to optimize the network’s energy efficiency. Given that the energy efficiency objective is not a ratio of concave and convex functions, the commonly used Dinkelbach-type algorithms are not applicable. We develop a low-complexity path-following algorithm that only invokes one simple convex quadratic program at each iteration, which converges at least to the local optimum. Numerical results demonstrate the performance advantage of our proposed algorithm in terms of energy efficiency.
Shi, B, Du, X, Chen, J, Fu, L, Morsch, M, Lee, A, Liu, Y, Cole, N & Chung, R 2017, 'Multifunctional Hybrid Nanoparticles for Traceable Drug Delivery and Intracellular Microenvironment‐Controlled Multistage Drug‐Release in Neurons', Small, vol. 13, no. 20, pp. 1603966-1603966.
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Innovative nanoparticles hold promising potential for disease therapy as drug delivery systems. For brain‐disease therapy, a drug delivery system that can sustainably control drug‐release and monitor fluorescence of the drug cargos is highly desirable. In this study, a light‐traceable and intracellular microenvironment‐responsive drug delivery system was developed based on the combination of glutathione‐responsive autoflurescent nanogel, dendrimer‐like mesoporous silica nanoparticles, and gold nanoparticles. The resulting hybrid nanoparticles represent a new class of delivery system that can efficiently load, transport, and control multistage‐release of sulfydryl‐containing drugs into neurons, with light‐traceable monitoring for future brain‐disease therapy.
Shi, B, Zheng, M, Tao, W, Chung, R, Jin, D, Ghaffari, D & Farokhzad, OC 2017, 'Challenges in DNA Delivery and Recent Advances in Multifunctional Polymeric DNA Delivery Systems', Biomacromolecules, vol. 18, no. 8, pp. 2231-2246.
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© 2017 American Chemical Society. After more than 20 years of intensive investigations, gene therapy has become one of the most promising strategies for treating genetic diseases. However, the lack of ideal delivery systems has limited the clinical realization of gene therapy's tremendous potential, especially for DNA-based gene therapy. Over the past decade, considerable advances have been made in the application of polymer-based DNA delivery systems for gene therapy, especially through multifunctional systems. The core concept behind multifunctional polymeric DNA delivery systems is to endow one single DNA carrier, via materials engineering and surface modification, with several active functions, e.g., good cargo DNA protection, excellent colloidal stability, high cellular uptake efficiency, efficient endo/lysosome escape, effective import into the nucleus, and DNA unpacking. Such specially developed vectors would be capable of overcoming multiple barriers to the successful delivery of DNA. In this review, we first provide a comprehensive overview of the interactions between the protein corona and DNA vectors, the mechanisms and challenges of nonviral DNA vectors, and important concepts in the design of DNA carriers identified via past reports on DNA delivery systems. Finally, we highlight and discuss recent advances in multifunctional polymeric DNA delivery systems based on 'off-the-shelf' polycations including polyethylenimine (PEI), poly-l-lysine (PLL), and chitosan and offer perspectives on future developments.
Shi, S, Ni, W & Liu, RP 2017, 'Performance analysis of XOR two‐way relay with finite buffers and instant scheduling', IET Communications, vol. 11, no. 4, pp. 507-513.
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This study investigates the performance of practical wireless exclusive OR (XOR) two‐way relay (TWR) system, in which finite buffer, lossy wireless channels and non‐negligible signalling overhead are considered. Specifically, the authors develop a new analytical model to explicitly characterise the transmissions of both the end‐nodes and the relay. The impact of scheduling on the throughput, queuing delay, power consumption and buffer overflow probability of XOR‐TWR is evaluated. Validated by simulations, the model can precisely quantify the performance of XOR‐TWR and adequately allocate the relay's buffer adapting to the wireless link qualities and signalling overhead.
Shi, W, Chen, Q, Nimbalkar, S & Liu, W 2017, 'A new mixing technique for solidifier and dredged fill in coastal area', Marine Georesources & Geotechnology, vol. 35, no. 1, pp. 52-61.
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2016 Copyright © Taylor & Francis Group, LLCOne of the major drawbacks of the conventional method of land reclamation, which involves mixing cement with the dredged soils at the disposal site, is the high cost associated with its manufacturing and transportation. In this study, a new solidified dredged fill (SDF) technique and a new additive are proposed and their practical applications are discussed. Unlike the conventional approach, the dredged marine soils were mixed with the solidifiers using a newly designed mixing technique prior to its transport to site, which would significantly reduce the cost of site machinery and effectively reclaim land with adequate engineering properties necessary for the construction of infrastructure. To evaluate the performance of the reclaimed land using the proposed technique, a series of laboratory and field tests (namely, static and dynamic cone penetration tests, and plate load tests) were conducted on grounds filled with and without solidified dredged marine soils, respectively. The results showed that the engineering behavior of the reclaimed land with dredged marine soils using SDF technique had significantly improved. The SDF technique combined with the newly designed mixing system improved the performance of ground and has thus proved to be both cost-effective and safe.
Shi, Y, Tuan, HD & Apkarian, P 2017, 'Nonconvex spectral optimization algorithms for reduced‐order LPV‐LFT controllers', International Journal of Robust and Nonlinear Control, vol. 27, no. 18, pp. 4421-4442.
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SummaryA novel sequential semi‐definite programming method is developed for optimization subject to rank constraints on matrix‐valued nonlinear functions of matrix decision variables, which arise in reduced‐order linear parameter varying‐linear fractional transformational control synthesis. The global convergence of the method is easily proven without any step size control. An intensive simulation shows the clear advantage of the proposed method over the state‐of‐the‐art nonlinear matrix inequality solvers. Copyright © 2017 John Wiley & Sons, Ltd.
Shi, Y, Tuan, HD, Tuy, H & Su, S 2017, 'Global optimization for optimal power flow over transmission networks', Journal of Global Optimization, vol. 69, no. 3, pp. 745-760.
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© 2017, Springer Science+Business Media New York. The optimal power flow (OPF) problem for power transmission networks is an NP-hard optimization problem with nonlinear constraints on complex bus voltages. The existing nonlinear solvers may fail in yielding a feasible point. Semi-definite relaxation (SDR) could provide the global solution only when the matrix solution of the relaxed semi-definite program (SDP) is of rank-one, which does not hold in general. Otherwise, the point found by SDR is infeasible. High-order SDR has recently been used to find the global solution, which leads to explosive growth of the matrix variable dimension and semi-definite constraints. Consequently, it is suitable only for OPF over very small networks with a few buses. In this paper, we follow our previously developed nonsmooth optimization approach to address this difficult OPF problem, which is an iterative process to generate a sequence of improved points that converge to a global solution in many cases. Each iteration calls an SDP of moderate dimension. Simulations are provided to demonstrate the efficiency of our approach.
Shirani, E, Razmjou, A, Tavassoli, H, Landarani-Isfahani, A, Rezaei, S, Abbasi Kajani, A, Asadnia, M, Hou, J & Ebrahimi Warkiani, M 2017, 'Strategically Designing a Pumpless Microfluidic Device on an “Inert” Polypropylene Substrate with Potential Application in Biosensing and Diagnostics', Langmuir, vol. 33, no. 22, pp. 5565-5576.
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© 2017 American Chemical Society. This study is an attempt to make a step forward to implement the very immature concept of pumpless transportation of liquid into a real miniaturized device or lab-on-chip (LOC) on a plastic substrate. 'Inert' plastic materials such as polypropylene (PP) are used in a variety of biomedical applications but their surface engineering is very challenging. Here, it was demonstrated that with a facile innovative wettability patterning route using fluorosilanized UV-independent TiO2 nanoparticle coating it is possible to create wedge-shaped open microfluidic tracks on inert solid surfaces for low-cost biomedical devices (lab-on-plastic). For the future miniaturization and integration of the tracks into a device, a variety of characterization techniques were used to not only systematically study the surface patterning chemistry and topography but also to have a clear knowledge of its biological interactions and performance. The effect of such surface architecture on the biological performance was studied in terms of static/dynamic protein (bovine serum albumin) adsorption, bacterial (Staphylococcus aureus and Staphylococcus epidermidis) adhesion, cell viability (using HeLa and MCF-7 cancer cell lines as well as noncancerous human fibroblast cells), and cell patterning (Murine embryonic fibroblasts). Strategies are discussed for incorporating such a confined track into a diagnostic device in which its sensing portion is based on protein, microorganism, or cells. Finally, for the proof-of-principle of biosensing application, the well-known high-affinity molecular couple of BSA-antiBSA as a biological model was employed.
Shon, HK, Nghiem, LD, Kim, S, Chiemchaisri, C, Tijing, L, Shu, L & Jegatheesan, V 2017, 'Editorial', Desalination and Water Treatment, vol. 96, pp. 1-2.
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Shrestha, A, Naidu, G, Johir, MAH, Kandasamy, J & Vigneswaran, S 2017, 'Performance of flocculation titanium salts for seawater reverse osmosis pretreatment', Desalination and Water Treatment, vol. 98, pp. 92-97.
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© 2017 Desalination Publications. All rights reserved. This study evaluated the performance of titanium tetrachloride (TiCl4) and titanium sulphate (Ti(SO4)2) as coagulants to remove organic matter and solids from actual seawater. The coagulant performances were evaluated at different doses in terms of turbidity, dissolved organic carbon (DOC), humics (UV254), zeta potential and pH of the solution. The performance of Ti-salts were compared to ferric chloride (FeCl3), a commonly used coagulant. The results showed that at pH of 8.0 (closely similar to seawater pH), TiCl4 showed relatively better performance over FeCl3 and Ti(SO4)2 for the same coagulant dose of 20 mg/L. TiCl4 achieved a 70% DOC and UV254 removal. This was approximately two times higher than achieved by FeCl3 and Ti(SO4)2. Based on a floc zeta potential evaluation, the difference in performance of the coagulants were attributed to the coagulation mechanism. The coagulation mechanisms of Ti-salts were mainly charge neutralization while FeCl3was adsorption mechanism.
Shu, C-C, Dong, D & Yuan, K-J 2017, 'Single-laser-induced quantum interference in photofragmentation reaction of D+ 2', Molecular Physics, vol. 115, no. 15-16, pp. 1908-1915.
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Shu, C-C, Yuan, K-J, Dong, D, Petersen, IR & Bandrauk, AD 2017, 'Identifying Strong-Field Effects in Indirect Photofragmentation Reactions', The Journal of Physical Chemistry Letters, vol. 8, no. 1, pp. 1-6.
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Shuhimi, FF, Abdollah, MFB, Kalam, MA, Masjuki, HH, Mustafa, A, Mat Kamal, SE & Amiruddin, H 2017, 'Effect of operating parameters and chemical treatment on the tribological performance of natural fiber composites: A review', Particulate Science and Technology, vol. 35, no. 5, pp. 512-524.
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Siedelhofer, C, Henke, T, Bellmann, A, Litterscheidt, J & Deuse, J 2017, 'Konzept zur Rekonfiguration flexibler Montagesysteme', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 112, no. 3, pp. 141-145.
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Kurzfassung Verkürzte Produktlebenszyklen und die Volatilität des Produktmixes resultieren im Montagebereich produzierender Unternehmen in hohem Aufwand durch Rekonfiguration. Es wird ein Rahmenmodell vorgestellt, welches die Effektivität der Rekonfiguration von Montagesystemen durch einen modularen, von Veränderungstreibern abhängigen Planungsprozess erhöht. Die Effizienz wird durch eine Planungsdatenbank gesteigert, welche die standardisierte Bereitstellung und Wiederverwendung von Planungsdaten ermöglicht.
Silitonga, AS, Hassan, MH, Ong, HC & Kusumo, F 2017, 'Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine', Environmental Science and Pollution Research, vol. 24, no. 32, pp. 25383-25405.
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The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machine (KELM) model is developed in this study using MATLAB software in order to predict the performance, combustion and emission characteristics of the engine. To acquire the data for training and testing the KELM model, the engine speed was selected as the input parameter, whereas the performance, exhaust emissions and combustion characteristics were chosen as the output parameters of the KELM model. The performance, emissions and combustion characteristics predicted by the KELM model were validated by comparing the predicted data with the experimental data. The results show that the coefficient of determination of the parameters is within a range of 0.9805-0.9991 for both the KELM model and the experimental data. The mean absolute percentage error is within a range of 0.1259-2.3838. This study shows that KELM modelling is a useful technique in biodiesel production since it facilitates scientists and researchers to predict the performance, exhaust emissions and combustion characteristics of internal combustion engines with high accuracy.
Silitonga, AS, Mahlia, TMI, Ong, HC, Riayatsyah, TMI, Kusumo, F, Ibrahim, H, Dharma, S & Gumilang, D 2017, 'A comparative study of biodiesel production methods for Reutealis trisperma biodiesel', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 39, no. 20, pp. 2006-2014.
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© 2017 Taylor & Francis Group, LLC. In this study, three types of biodiesel production methods are compared in order to maximize Reutealis trisperma biodiesel yields and it is found that the best method is esterification-neutralization-transesterification. The optimum methanol to oil molar ratio, catalyst concentration, reaction temperature, and reaction time are also determined from laboratory experiments and modeling using response surface methodology. There is excellent agreement between the predicted and experimental Reutealis trisperma biodiesel yields under optimum process conditions, with a value of 99.23 and 98.72%, respectively. The physicochemical properties of the Reutealis trisperma biodiesel also fulfill the fuel specifications of the ASTM D6751 standard.
Silitonga, AS, Masjuki, HH, Ong, HC, Mahlia, TMI & Kusumo, F 2017, 'Optimization of extraction of lipid from Isochrysis galbana microalgae species for biodiesel synthesis', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 39, no. 11, pp. 1167-1175.
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© 2017 Taylor & Francis Group, LLC. Microalgae are promising alternative plant sources for biodiesel production because of the significant increase in lipid yield through heterotrophic cultivation and genetic engineering approaches. This study aims to evaluate the extraction and conversion of lipids from Isochrysis galbana. Response surface methodology (RSM) was used to optimize lipid extraction and thereby obtain high yields from the four microalgae species. The optimal lipid yields for Isochrysis galbana is 8.41 wt%. Moreover, the dominant lipid composition found from Isochrysis galbana extractions was palmitic acid (C16:0) at 22.3%. The high saturated acid of Isochrysis galbana contributed to the improved biodiesel properties because biodiesel quality is influenced by the lipid composition of microalgae species. The study employed the two-step esterification–transesterification process to convert the microalgae oil into biodiesel, glycerol, and water. The FAME content is 99.7% under the methanol to oil molar mass of 12:1, 1 wt%, 65°C, and 800 rpm. Furthermore, the main biodiesel properties, such as viscosity, higher heating value, and iodine value, were measured according to ASTM D6751 and EN 14124. Results show that microalgae oil can potentially be used as biofuel in future applications.
Simorangkir, RBVB, Yang, Y, Matekovits, L & Esselle, KP 2017, 'Dual-Band Dual-Mode Textile Antenna on PDMS Substrate for Body-Centric Communications', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 677-680.
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© 2017 IEEE. A dual-band antenna for off- and on-body communications in the 2.45- and 5.8-GHz Industrial, Scientific, and Medical bands is presented. The two radiation characteristics, i.e., patch-like radiation for the off-body link and monopole-like radiation for the on-body link, are achieved by utilizing inherently generated TM11 and TM02 modes of a circular patch antenna. A shorting pin and two arc-shaped slots are employed to tune both modes to the desired operating frequencies. This approach allows a realization of a dual-band dual-mode antenna with a very simple structure, i.e., a single radiator with a simple feed. A further advantage of the proposed antenna is its realization using a silver fabric integrated onto a flexible polydimethylsiloxane substrate that makes it more practical for wearable applications. An experimental investigation of the antenna performance has been carried out in free space and on a semisolid human muscle equivalent phantom, which shows a robust performance against the human body loading effect. When placed on the phantom, the measured bandwidths of 84 and 247 MHz in the 2.45- and 5.8-GHz bands, respectively, are achieved with the corresponding peak gains of 4.16 and 4.34 dBi, indicating a promising candidate for body-centric communications.
Siwakoti, YP & Blaabjerg, F 2017, 'Single Switch Nonisolated Ultra-Step-Up DC–DC Converter With an Integrated Coupled Inductor for High Boost Applications', IEEE Transactions on Power Electronics, vol. 32, no. 11, pp. 8544-8558.
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© 1986-2012 IEEE. This paper introduces a new single-switch nonisolated dc-dc converter with very high voltage gain and reduced semiconductor voltage stress. The converter utilizes an integrated autotransformer and a coupled inductor on the same core in order to achieve a very high voltage gain without using extreme duty cycle. Furthermore, a passive lossless clamp circuit recycles the leakage energy of the coupled magnetics and alleviates the voltage spikes across the main switch. This feature along with low stress on the switching device enables the designer to use a low voltage and low R DS-on MOSFET, which reduces cost, as well as conduction and turn on losses of the switch. The principle of operation, theoretical analysis, and comparison supported by some key simulation and experimental results of a 500 W prototype are presented.
Siyari, P, Krunz, M & Nguyen, DN 2017, 'Friendly Jamming in a MIMO Wiretap Interference Network: A Nonconvex Game Approach', IEEE Journal on Selected Areas in Communications, vol. 35, no. 3, pp. 601-614.
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© 1983-2012 IEEE. We consider joint optimization of artificial noise (AN) and information signals in a MIMO wiretap interference network, wherein the transmission of each link may be overheard by several MIMO-capable eavesdroppers. Each information signal is accompanied with AN, generated by the same user to confuse nearby eavesdroppers. Using a noncooperative game, a distributed optimization mechanism is proposed to maximize the secrecy rate of each link. The decision variables here are the covariance matrices for the information signals and ANs. However, the nonconvexity of each link's optimization problem (i.e., best response) makes conventional convex games inapplicable, even to find whether a Nash equilibrium (NE) exists. To tackle this issue, we analyze the proposed game using a relaxed equilibrium concept, called quasi-NE (QNE). Under a constraint qualification condition for each player's problem, the set of QNEs includes the NE of the proposed game. We also derive the conditions for the existence and uniqueness of the resulting QNE. It turns out that the uniqueness conditions are too restrictive, and do not always hold in typical network scenarios. Thus, the proposed game often has multiple QNEs, and convergence to a QNE is not always guaranteed. To overcome these issues, we modify the utility functions of the players by adding several specific terms to each utility function. The modified game converges to a QNE even when multiple QNEs exist. Furthermore, players have the ability to select a desired QNE that optimizes a given social objective (e.g., sum rate or secrecy sum rate). Depending on the chosen objective, the amount of signaling overhead as well as the performance of resulting QNE can be controlled. Simulations show that not only can we guarantee the convergence to a QNE, but also due to the QNE selection mechanism, we can achieve a significant improvement in terms of secrecy sum rate and power efficiency, especially in dense networks.
Sokolowski, M, Colegate, T, Sutinjo, AT, Ung, D, Wayth, R, Hurley-Walker, N, Lenc, E, Pindor, B, Morgan, J, Kaplan, DL, Bell, ME, Callingham, JR, Dwarakanath, KS, For, B-Q, Gaensler, BM, Hancock, PJ, Hindson, L, Johnston-Hollitt, M, Kapińska, AD, McKinley, B, Offringa, AR, Procopio, P, Staveley-Smith, L, Wu, C & Zheng, Q 2017, 'Calibration and Stokes Imaging with Full Embedded Element Primary Beam Model for the Murchison Widefield Array', Publications of the Astronomical Society of Australia, vol. 34.
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AbstractThe Murchison Widefield Array (MWA), located in Western Australia, is one of the low-frequency precursors of the international Square Kilometre Array (SKA) project. In addition to pursuing its own ambitious science programme, it is also a testbed for wide range of future SKA activities ranging from hardware, software to data analysis. The key science programmes for the MWA and SKA require very high dynamic ranges, which challenges calibration and imaging systems. Correct calibration of the instrument and accurate measurements of source flux densities and polarisations require precise characterisation of the telescope’s primary beam. Recent results from the MWA GaLactic Extragalactic All-sky Murchison Widefield Array (GLEAM) survey show that the previously implemented Average Embedded Element (AEE) model still leaves residual polarisations errors of up to 10–20% in Stokes Q. We present a new simulation-based Full Embedded Element (FEE) model which is the most rigorous realisation yet of the MWA’s primary beam model. It enables efficient calculation of the MWA beam response in arbitrary directions without necessity of spatial interpolation. In the new model, every dipole in the MWA tile (4 × 4 bow-tie dipoles) is simulated separately, taking into account all mutual coupling, ground screen, and soil effects, and therefore accounts for the different properties of the individual dipoles within a tile. We have applied the FEE beam model to GLEAM observations at 200–231 MHz and used false Stokes parameter leakage as a metric to compare the models. We have determined that the FEE model reduced the magnitude and declination-dependent behaviour of false polarisation in Stokes Q and V while retaining low levels of false polarisation in Stokes U.
Song, JF, Nghiem, LD, Li, X-M & He, T 2017, 'Lithium extraction from Chinese salt-lake brines: opportunities, challenges, and future outlook', Environmental Science: Water Research & Technology, vol. 3, no. 4, pp. 593-597.
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Chinese salt-lake brine is mainly of the magnesium sulfate subtype with a high Mg/Li ratio. To extract high purity lithium chloride from Chinese brine has been a decade-long challenge. This review summarizes the state-of-the-art of lithium extraction from Chinese salt-lake brine.
Song, K, Konstantinou, G, Mingli, W, Acuna, P, Aguilera, RP & Agelidis, VG 2017, 'Windowed SHE-PWM of Interleaved Four-Quadrant Converters for Resonance Suppression in Traction Power Supply Systems', IEEE Transactions on Power Electronics, vol. 32, no. 10, pp. 7870-7881.
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© 1986-2012 IEEE. AC electric locomotives that use a number of interleaved four-quadrant converters generate high-frequency switching harmonics which may stimulate certain resonances in traction power supply systems (TPSSs). A windowed selective harmonic elimination pulse-width modulation (SHE-PWM) method is proposed to suppress such resonances. Owing to the windowed design and the precalculated solutions, the proposed method covers the wide potential resonant frequency range and addresses the resonant frequency variation while keeping the low switching frequency of the traction converters. The proposed windowed SHE-PWM is fully tested with a closed-loop controller in a simulation model with the TPSS and the ac electric locomotive. Comparative simulation results show that the windowed SHE-PWM is an effective alternative that overcomes the resonance suppression limitations of the conventional phase-shifted PWM (PS-PWM). The performance of proposed windowed SHE-PWM on an experimental equivalent resonant circuit is further evaluated and compared with PS-PWM. Both simulation and experimental results verify the effectiveness and feasibility of the proposed method.
Song, K, Xie, G-J, Qian, J, Bond, PL, Wang, D, Zhou, B, Liu, Y & Wang, Q 2017, 'Improved degradation of anaerobically digested sludge during post aerobic digestion using ultrasonic pretreatment', Environmental Science: Water Research & Technology, vol. 3, no. 5, pp. 857-864.
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We propose that ultrasonic pretreatment could significantly improve the degradation of anaerobically digested sludge with economic favorability in post aerobic digestion.
Song, Y, Wang, Y, Liu, F & Zhang, Y 2017, 'Development of a hybrid model to predict construction and demolition waste: China as a case study', Waste Management, vol. 59, pp. 350-361.
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© 2016 Elsevier Ltd Construction and demolition waste (C&DW) is currently a worldwide issue, and the situation is the worst in China due to a rapid increase in the construction industry and the short life span of China's buildings. To create an opportunity out of this problem, comprehensive prevention measures and effective management strategies are urgently needed. One major gap in the literature of waste management is a lack of estimations on future C&DW generation. Therefore, this paper presents a forecasting procedure for C&DW in China that can forecast the quantity of each component in such waste. The proposed approach is based on a GM-SVR model that improves the forecasting effectiveness of the gray model (GM), which is achieved by adjusting the residual series by a support vector regression (SVR) method and a transition matrix that aims to estimate the discharge of each component in the C&DW. Through the proposed method, future C&DW volume are listed and analyzed containing their potential components and distribution in different provinces in China. Besides, model testing process provides mathematical evidence to validate the proposed model is an effective way to give future information of C&DW for policy makers.
Sountharajah, DP, Kus, B, Kandasamy, J & Vigneswaran, S 2017, 'Quantifying the Reduction in Water Demand due to Rainwater Tank Installations at Residential Properties in Sydney', Journal of Sustainable Development of Energy, Water and Environment Systems, vol. 5, no. 2, pp. 202-218.
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© 2017, International Centre for Sustainable Development of Energy, Water and Environment Systems SDEWES. All rights reserved. This paper examines data on actual reductions in consumption of water supply due to the widespread installation of rainwater tanks at residential properties in the Sydney metropolitan area and surrounding areas connected to Sydney Water Corporation water supply mains. The water consumption was based on metered potable water usage between 2002 and 2009. The number of properties in the study database totalled 962,697 single residential dwellings. Of this a total of 52,576 or 5.5% of Sydney’s households had a rainwater tank registered with Sydney Water Corporation. The water usage consumption before and after the installation of the rainwater tank was analysed to quantify the extent to which rainwater tanks reduced mains water consumption. The average percentage of water savings by installing rainwater tanks across all 44 local government authorities was 9%. In some Sydney localities this reduction was up to 15%. On average, a household was able to save around 24 kilolitre of water annually by installing a rainwater tank even without considering other factors that affect water usage. The results were compared against socio-demographic factors using variables such as household size, educational qualifications, taxable income, rented properties, and non-English-speaking background, etc., to gain an appreciation of how these factors may have influenced the outcomes evident in the data. Among the co-relations found were that most properties within inner Sydney with a rainwater tank achieved at least a 9 to 11% additional reduction in water usage, with more than half of those local government authorities achieving more than 11%; properties with larger land area were more likely to have a rainwater tank installed; local government authorities with more people born in non-English speaking countries had lower reduction in water consumption reduction...
Sounthararajah, DP, Loganathan, P, Kandasamy, J & Vigneswaran, S 2017, 'Removing heavy metals using permeable pavement system with a titanate nano-fibrous adsorbent column as a post treatment', Chemosphere, vol. 168, pp. 467-473.
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© 2016 Elsevier Ltd Permeable pavement systems (PPS) are a widely-used treatment measure in sustainable stormwater management and groundwater recharge. However, PPS are not very efficient in removing heavy metals from stormwater. A pilot scale study using zeolite or basalt as bed material in PPS removed 41–72%, 67–74%, 38–43%, 61–72%, 63–73% of Cd, Cu, Ni, Pb, and Zn, respectively, from synthetic stormwater (pH 6.5; Cd, Cu, Ni, Pb, and Zn concentrations of 0.04, 0.6, 0.06, 1.0, and 2.0 mg L−1, respectively) over a period of 80 h. The total volume of stormwater that passed through the PPS was equivalent to runoff in 10 years of rainfall in Sydney, Australia. The concentrations of metals in the PPS effluent failed fresh and marine water quality trigger values recommended in the Australian and New Zealand guidelines. An addition of a post-treatment of a horizontal filter column containing a titanate nano-fibrous (TNF) material with a weight < 1% of zeolite weight and mixed in with granular activated carbon (GAC) at a GAC:TNF weight ratio of 25:1 removed 77% of Ni and 99–100% of all the other metals. The effluent easily met the required standards of marine waters and just met those concerning fresh waters. Batch adsorption data from solutions of metals mixtures fitted the Langmuir model with adsorption capacities in the following order, TNF ≫ zeolite > basalt; Pb > Cu > Cd, Ni, Zn.
Steendam, H, Wang, TQ & Armstrong, J 2017, 'Theoretical Lower Bound for Indoor Visible Light Positioning Using Received Signal Strength Measurements and an Aperture-Based Receiver', Journal of Lightwave Technology, vol. 35, no. 2, pp. 309-319.
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© 1983-2012 IEEE. Indoor visible light positioning (VLP) using signals transmitted by lighting LEDs is a topic attracting increasing interest within the research community. In the recent years, VLP techniques using a range of receiver structures and positioning algorithms have been described. In this paper, we analyze the performance of a VLP system, which uses an aperture-based receiver and measurements of received signal strength. An aperture-based receiver has a number of receiving elements, each consisting of a photodiode and an associated aperture. It has been shown that receivers of this form can be designed which are compact and provide both a wide overall field-of-view and good angular diversity. As a result, they can efficiently extract position-related information from light transmitted by nondirectional LEDs. In our approach, we correlate the signals at the outputs of the photodiodes with a set of reference signals. The resulting observations include information on the received signal strength as well as the angle-of-arrival, and are used to directly estimate the receiver's position. In order to assess the performance of positioning algorithms based on this approach, we derive the Cramer-Rao lower bound on the position estimate. We show that the Cramer-Rao bound depends on the selected reference signal, and that subcentimetre to centimetre accuracy can be obtained, using only a limited number of nondirectional LEDs.
Stewart, MG 2017, 'Risk of Progressive Collapse of Buildings from Terrorist Attacks: Are the Benefits of Protection Worth the Cost?', Journal of Performance of Constructed Facilities, vol. 31, no. 2.
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The paper describes a probabilistic risk assessment model to identify the risks associated with vehicle-borne improvised explosive device (VBIED) attacks to large federal government buildings in the United States. Probability of terrorist threat, hazard, damage, fatality, and economic and social loss for progressive collapse are modeled as stochastic variables. It was found that the existing annual fatality risk for building occupants is lower than acceptable risk criteria, and that progressive collapse is an exceedingly rare event in Western countries. A performance-based design using cost-benefit analysis of U.S. design provisions to mitigate against progressive collapse showed that these design measures only becomes cost-effective when the threat likelihood is a very high 1 in 1,000 per building per year. However, such provisions are more likely to be cost-effective in regions of high seismicity due to a lower cost premium.
Stewart, MG & Mueller, J 2017, 'Risk and economic assessment of expedited passenger screening and TSA PreCheck', Journal of Transportation Security, vol. 10, no. 1-2, pp. 1-22.
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The Transportation Security Administration’s PreCheck program allows airline passengers assessed as low risk to be directed to faster screening lanes. The paper assesses the scenario of a terrorist plot to down an airliner with a passenger-borne bomb. There are four main conclusions. First, we find that the layered system currently in place reduces the risk of such an attack by 98% - and probably by quite a bit more. Second, this level of risk reduction is very robust: security remains high even when the parameters that make it up are varied considerably. In particular, because of the large array of other security layers, overall risk reduction is relatively insensitive to how effective checkpoint screening is. Third, under most realistic combinations of parameter values PreCheck actually increases risk reduction, perhaps up to 1%, while under the worst assumptions, it lowers risk reduction by some 0.3%. Fourth, the co-benefits of the PreCheck program are very substantial: by greatly reducing checkpoint costs and by improving the passenger experience, this benefit can exceed several billion dollars per year. We also find that adding random exclusion and managed inclusion to the PreCheck program has little effect on the program’s risk reducing capability one way or the other. TSA PreCheck thus seems likely to bring efficiencies to the screening process and great benefits to passengers, airports, and airlines while actually enhancing security.
Stone, BW, Harland, AR, Jones, JA, Mitchell, SR, Sherratt, PJ, Ranson, CA & Halkon, BJ 2017, 'On the dynamic response of an instrumented headform for alternative mounting stiffnesses when subjected to ballistic impacts', Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, vol. 231, no. 4, pp. 324-335.
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The current British Standard for head protectors for cricketers has been recently revised to include a projectile-based battery of tests, the intention being to ensure that a certified helmet will also prevent contact of the ball or grille with the specified headform facial region. The purpose of this study was to characterise the dynamic response of the headform to direct ballistic impacts for alternative headform mounting arrangements. On one hand, and in accordance with the relevant sections of the Standard, what might be described as a ‘Constrained’ setup was evaluated while, on the other hand, an arrangement with significantly reduced stiffness, in line with that previously reported for the passive human neck, was subject to equivalent appraisal. For each mounting scenario, an air cannon was used to project a cricket training ball at three speeds towards the instrumented headform at three locations with five repeats per speed/location combination. High-rate/resolution video and piezoelectric accelerometer data were collected and processed to determine the headform response. While differences between specific ball impact speed and location scenarios are set out in detail later in the article, overall observations are summarised as follows. From a ball/headform contact duration standpoint, video derived results showed ranges of 1.30–1.45 ms (Constrained) versus 1.26–1.41 ms. Maximum ball deformations, the timing of which enabling the event to be subdivided into ‘loading’ and ‘unloading’ phases, were found to be 82.5%–86.2% (Constrained) versus 82.8%–86.4% of original ball diameter; mean peak headform accelerations during loading were found to be 860–1615 m/s2 (Constrained) versus 967–1638 m/s2; and headform speeds at the end of the loading phase were found to be 0.5–0.92 m/s (Constrained) versus 0.54–0.93 m/s. Differences between headform response for the two mounting arrangements were observed to be...
Strauß, P, Barthelmey, A & Deuse, J 2017, 'Cyber-physical systems for predictive maintenance', Productivity Management, vol. 22, no. 1, pp. 12-15.
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For an integral and constantly up-to-date image of adaptable production plants, sensor and process data as well as information on structure are required. Thus, the authors combine a low-cost sensor system for data acquisition in the production’s environment and an architecture for the automatic creation and maintenance of technical plant documentation. The effi cacy and relevance of the overall system will be demonstrated based on an application example concerning an electric monorail conveyor in automotive engineering.
Stuart, BH & Thomas, PS 2017, 'Pigment characterisation in Australian rock art: a review of modern instrumental methods of analysis', Heritage Science, vol. 5, no. 1, pp. 1-6.
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Abstract The many thousands of Aboriginal rock art sites extending across Australia represent an important cultural record. The styles and materials used to produce such art are of great interest to archaeologists and those concerned with the protection of these significant works. Through an analysis of the mineral pigments utilised in Australian rock art, insight into the age of paintings and practices employed by artists can be gained. In recent years, there has been an expansion in the use of modern analytical techniques to investigate rock art pigments and this paper provides a review of the application of such techniques to Australian sites. The types of archaeological information that may be extracted via chemical analysis of specimens collected from or at rock art sites across the country are discussed. A review of the applicability of the techniques used for elemental analysis and structural characterisation of rock art pigments is provided and how future technological developments will influence the discipline is investigated.
Su, H, Hurley-Walker, N, Jackson, CA, McClure-Griffiths, NM, Tingay, SJ, Hindson, L, Hancock, P, Wayth, RB, Gaensler, BM, Staveley-Smith, L, Morgan, J, Johnston-Hollitt, M, Lenc, E, Bell, ME, Callingham, JR, Dwarkanath, KS, For, B-Q, Kapińska, AD, McKinley, B, Offringa, AR, Procopio, P, Wu, C & Zheng, Q 2017, 'Erratum: Galactic synchrotron emissivity measurements between 250° < l < 355° from the GLEAM survey with the MWA', Monthly Notices of the Royal Astronomical Society, vol. 472, no. 1, pp. 828-834.
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© 2017 The Authors. This is an erratum to the paper 'Galactic synchrotron emissivity measurements between 250° < l < 355° from the GLEAM survey with the MWA', published in MNRAS, 465, 3163 (2017).
Su, H, Hurley-Walker, N, Jackson, CA, McClure-Griffiths, NM, Tingay, SJ, Hindson, L, Hancock, P, Wayth, RB, Gaensler, BM, Staveley-Smith, L, Morgan, J, Johnston-Hollitt, M, Lenc, E, Bell, ME, Callingham, JR, Dwarkanath, KS, For, B-Q, Kapińska, AD, McKinley, B, Offringa, AR, Procopio, P, Wu, C & Zheng, Q 2017, 'Galactic synchrotron emissivity measurements between 250° <l< 355° from the GLEAM survey with the MWA', Monthly Notices of the Royal Astronomical Society, vol. 465, no. 3, pp. 3163-3174.
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© 2016 The Authors. Synchrotron emission pervades the Galactic plane at low radio frequencies, originating from cosmic ray electrons interacting with the Galactic magnetic field. Using a low-frequency radio telescope, the Murchison Widefield Array (MWA), we measure the free-free absorption of this Galactic synchrotron emission by intervening HII regions along the line of sight. These absorption measurements allow us to calculate the Galactic cosmic ray electron emissivity behind and in front of 47 detected HII regions in the region 250° < l < 355°, |b| < 2°.We find that all average emissivities between the HII regions and the Galactic edge along the line of sight (εb) are in the range of 0.39 ~ 1.45 K pc-1 with a mean of 0.77 K pc-1 and a variance of 0.14 K pc-1 at 88 MHz. Our best model, the two-circle model, divides the Galactic disc into three regions using two circles centring on the Galactic Centre. It shows a high emissivity region near the Galactic Centre, a low emissivity region near the Galactic edge, and a medium emissivity region between these two regions, contrary to the trend found by previous studies.
Su, QP, Du, W, Ji, Q, Xue, B, Jiang, D, Zhu, Y, Ren, H, Zhang, C, Lou, J, Yu, L & Sun, Y 2017, 'Correction: Corrigendum: Vesicle Size Regulates Nanotube Formation in the Cell', Scientific Reports, vol. 7, no. 1, p. 40108.
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Scientific Reports 6: Article number: 24002; published online: 07 April 2016; updated: 09 February 2017 He Ren and Chuanmao Zhang were omitted from the author list in the original version of this Article. This has been corrected in the PDF and HTML versions of the Article, as well as the Supplementary Information that now accompanies the Article.
Su, Y, Li, J, Wu, C, Wu, P, Tao, M & Li, X 2017, 'Mesoscale study of steel fibre-reinforced ultra-high performance concrete under static and dynamic loads', Materials & Design, vol. 116, pp. 340-351.
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© 2016 Elsevier Ltd In this paper, a three-dimensional numerical model to study the static and dynamic behaviour of ultra-high performance steel fibre reinforced concrete is developed. Ultra-high performance steel fibre reinforced concrete is assumed to be a two-phase model consisting of concrete matrix and steel fibres. The concrete matrix is modelled with homogeneous material and the straight round steel fibres are assumed to be dispersed with random locations and orientations in the matrix. The interfacial transition zone (ITZ) effect is studied based on the single fibre pull-out tests, and parameters describing the fibre-matrix one dimensional bond-slip behaviour are obtained and discussed based on both experimental and theoretical results. After the three-dimensional model is validated with static split tensile tests, split Hopkinson pressure bar (SHPB) split tensile tests are numerically modelled and the stress-time history is interpreted in the mesoscale level. The proposed model qualitatively and quantitatively predicts the material static and dynamic behaviours, and also gives insights on the fibre reinforcement effect in the concrete matrix.
Su, Y, Wu, C, Li, J, Li, Z-X & Li, W 2017, 'Development of novel ultra-high performance concrete: From material to structure', Construction and Building Materials, vol. 135, pp. 517-528.
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© 2017 Elsevier Ltd This paper investigates effects of nanoscale materials and steel fibres on properties of ultra-high performance concrete (UHPC). Different types of steel fibres including twisted steel fibre (TF), waved steel fibre (WF), and micro steel fibre (MF) together with different kinds of nano materials including Nano-CaCO3, Nano-SiO2, Nano-TiO2 and Nano-Al2O3 are studied in the present research. Material compressive stress–strain relationships, strain energy absorption, the flexural strength and fracture energy absorption of UHPC with different nanoscale materials and steel fibres were compared and discussed. Laboratory static bending tests and field blast tests on structural components made of selected UHPC material composition were carried out, and the results highlighted the superior material ductility and blast resistant capacity of UHPC material developed in the present study.
Sun, B, Guo, Y, Fang, G & Dutkiewicz, E 2017, 'An efficient dictionary refinement algorithm for multiple target counting and localization in wireless sensor networks', International Journal of Distributed Sensor Networks, vol. 13, no. 8, pp. 155014771772380-155014771772380.
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Many applications provided by wireless sensor networks rely heavily on the location information of the monitored targets. Since the number of targets in the region of interest is limited, localization benefits from compressive sensing, sampling number can be greatly reduced. Despite many compressive sensing–based localization methods proposed, existing solutions are based on the assumption that all targets fall on a sampled and fixed grid, performing poorly when there are targets deviating from the grid. To address such a problem, in this article, we propose a dictionary refinement algorithm where the grid is iteratively adjusted to alleviate the deviation. In each iteration, the representation coefficient and the grid parameters are updated in turn. After several iterations, the measurements can be sparsely represented by the representation coefficient which indicates the number and locations of multiple targets. Extensive simulation results show that the proposed dictionary refinement algorithm achieves more accurate counting and localization compared to the state-of-the-art compressive sensing reconstruction algorithms.
Sun, G, Cui, T, Beydoun, G, Chen, S, Dong, F, Xu, D & Shen, J 2017, 'Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem', Sustainability, vol. 9, no. 6, pp. 898-898.
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Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs. In this paper, we focus on constructing a knowledge base to support the decision-making process of MLaaS. MLaas is built using a top-down approach. A conceptual graph-based ontology construction is first developed. An educational data mining and learning analytic strategy is then proposed for the data level. The learning resource adaptation still requires learners’ historical information. To compensate for the absence of this information initially (aka ‘cold start’), we set up a predictive ontology-based mechanism. As the first resource is delivered to the beginning of a learner’s learning journey, the micro OER recommendation is also optimized using a tailored heuristic.
Sun, G, Pang, T, Fang, J, Li, G & Li, Q 2017, 'Parameterization of criss-cross configurations for multiobjective crashworthiness optimization', International Journal of Mechanical Sciences, vol. 124-125, pp. 145-157.
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© 2017 Elsevier Ltd Thin-walled tubes have exhibited extraordinary advantages in lightweight and energy absorption for crashing scenarios. Geometric configuration of such tubal structures is of decisive effects on crashing behaviors. In this study, crashing characteristics of conventional square tube and a criss-cross tube were first conducted using both experimental and numerical analyses, through which the finite element (FE) models were well validated. It was also revealed that the energy absorption of the criss-cross sectional tube was about 150% higher than that of square column with the same weight. Further, a range of criss-cross sections were parametrically modeled with spline curves and a parametric study was subsequently performed to explore the effects of different parameterized shapes on crashing characteristics. It was found that the geometric parameters significantly affected crashworthiness of the criss-cross tubes, and the criss-cross tubes with a spline curve (CCT_SPL) surpass the criss-cross tubes with a straight line (CCT_STR) in crashworthiness with the same weight. Finally, to optimize the crashwo rthiness of parameterized criss-cross tubes, the non-dominated sorting genetic algorithm II (NSGA-II) was adopted to seek optimal criss-cross shapes for improving specific energy absorption (SEA) and reducing the peak crashing force (F max ), simultaneously. The optimization results indicate that the CCT_SPL profiles with reasonable geometric parameters are superior to the CCT_STR counterparts with an increase of 11.1% in specific energy absorption.
Sun, G, Zhang, H, Fang, J, Li, G & Li, Q 2017, 'Multi-objective and multi-case reliability-based design optimization for tailor rolled blank (TRB) structures', Structural and Multidisciplinary Optimization, vol. 55, no. 5, pp. 1899-1916.
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© 2016 Springer-Verlag Berlin HeidelbergLight weight and crashworthiness signify two main challenges facing in vehicle industry, which often conflict with each other. In order to achieve light weight while improving crashworthiness, tailor rolled blank (TRB) has become one of the most potential lightweight technologies. To maximize the characteristics of TRB structures, structural optimization has been adopted extensively. Conventional optimization studies have mainly focused on a single loading case (SLC). In practice, however, engineering structures are often subjected to multiple loading cases (MLC), implying that the optimal design under a certain condition may no longer be an optimum under other loading cases. Furthermore, traditional deterministic optimization could become less meaningful or even unacceptable when uncertainties of design variables and noises of system parameters are present. To address these issues, a multi-objective and multi-case reliability-based design optimization (MOMCRBDO) was developed in this study to optimize the TRB hat-shaped structure. The radial basis function (RBF) metamodel was adopted to approximate the responses of objectives and constraints, the non-dominated sorting genetic algorithm II (NSGA-II), coupled with Monte Carlo Simulation (MCS), was employed to seek optimal reliability solutions. The optimal results show that the proposed method is not only capable of improving the reliability of Pareto solutions, but also enhancing the robustness under MLC.
Sun, H, Ding, C, Jones, B & Guo, YJ 2017, 'A Wideband Base Station Antenna Element With Stable Radiation Pattern and Reduced Beam Squint', IEEE Access, vol. 5, pp. 23022-23031.
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© 2017 IEEE. This paper presents the design procedure, optimization strategy, theoretical analysis, and experimental results of a wideband dual-polarized base station antenna element with superior performance. The proposed antenna element consists of four electric folded dipoles arranged in an octagon shape that are excited simultaneously for each polarization. It provides ±45° slant-polarized radiation that meets all the requirements for base station antenna elements, including stable radiation patterns, low cross polarization level, high port-to-port isolation, and excellent matching across the wide band. The problem of beam squint for beam-tilted arrays is discussed and it is found that the geometry of this element serves to reduce beam squint. Experimental results show that this element has a wide bandwidth of 46.4% from 1.69 to 2.71 GHz with ≥15-dB return loss and 9.8 ± 0.9-dBi gain. Across this wide band, the variations of the half-power-beamwidths of the two polarizations are all within 66.5° ± 5.5°, the port-to-port isolation is >28 dB, the cross-polarization discrimination is >25 dB, and most importantly, the beam squint is <4° with a maximum 10° down-tilt.
Sun, J, Dai, X, Liu, Y, Peng, L & Ni, B-J 2017, 'Sulfide removal and sulfur production in a membrane aerated biofilm reactor: Model evaluation', Chemical Engineering Journal, vol. 309, pp. 454-462.
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© 2016 Elsevier B.V. Sulfide removal from wastewater is essential, in view of the toxic, malodor and corrosive property of sulfide. The oxidation of sulfide by chemolithotrophic sulfide oxidation bacteria can produce elemental sulfur, an important chemical material. A membrane aerated biofilm reactor (MABR) has been successfully implemented and demonstrated for enhanced sulfide oxidation and sulfur production, owning to its counter-diffusion design of oxygen supply. In this work, a mathematical model was developed to evaluate the sulfide oxidation and sulfur production in the MABR in the presence of residual organics in the influent. The model was calibrated and validated using the experimental data from the long-term operation of the sulfide-oxidation MABR at different operational stages. The results suggested that the developed model could satisfactorily describe sulfide oxidation, sulfur production, sulfate accumulation and organics conversion in the MABR. The modelling results indicated that with the optimal combinations of sulfide loading and oxygen pressure, over 90% of sulfide removal and over 75% of sulfur recovery could be achieved. The sulfide oxidation and sulfur production would also be affected by the biofilm area to reactor volume (A/V) ratio in the MABR, with high A/V ratio might deteriorate the sulfur production efficiency depending on the oxygen pressure applied. Further, the increase of volatile fatty acids in the wastewater would not affect the sulfide oxidation efficiency but could enhance the sulfur production efficiency by decreasing the amount of sulfur oxidized to sulfate.
Sun, J, Dai, X, Peng, L, Liu, Y, Wang, Q & Ni, B-J 2017, 'A biofilm model for assessing perchlorate reduction in a methane-based membrane biofilm reactor', Chemical Engineering Journal, vol. 327, pp. 555-563.
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© 2017 Elsevier B.V. Perchlorate (ClO4−) is recognized as an important contaminant in surface water and groundwater, which would pose health risks at very low concentrations. A methane-based membrane biofilm reactor (MBfR) has been successfully demonstrated for perchlorate reduction, which provided an alternative solution for perchlorate remediation with low cost. In this work, a multispecies biofilm model was developed to evaluate perchlorate reduction in the methane-based MBfR under different operational conditions. The model was calibrated and validated using the experimental data from the long-term operation of the MBfR at seven distinct stages. The results suggested that the developed model could satisfactorily describe perchlorate reduction and denitrification performances in the MBfR (R2 > 0.9). The modeling results provided insight into the microbial community distribution in the biofilm, with aerobic methanotrophs and perchlorate reduction bacteria being mainly located at the membrane side (∼60%) and heterotrophic bacteria being situated near the liquid side (∼50%). The model simulations indicated that over 80% of perchlorate removal efficiency could be achieved through controlling the optimal combinations of methane pressure (PCH4) and perchlorate loading (LClO4) (e.g., applying a PCH4 of 30 kPa at a LClO4 of 0.08 g Cl/m2/d). In addition, the perchlorate reduction would be inhibited by the presence of nitrate and nitrite in the MBfR, which should be appropriately controlled during the future practical application of the promising process.
Sun, W-J, Zong, F-Y, Sun, D-A, Wei, Z-F, Schanz, T & Fatahi, B 2017, 'Swelling prediction of bentonite-sand mixtures in the full range of sand content', Engineering Geology, vol. 222, pp. 146-155.
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© 2017 Elsevier B.V. The swelling prediction of bentonite–sand mixtures due to wetting is very important in evaluating the long term performance of the engineered barrier in the high level radioactive waste disposal system and the hydraulic barriers in geoenvironmental constructions. Sun et al. (2015) proposed the swelling prediction model of bentonite-sand mixtures due to full hydration, and predicted the swelling of different types of bentonite-sand mixtures, which was verified, to be consistent with the swelling test results. However, the predicted swelling results of bentonite-sand mixtures with extremely high sand content obtained by the original swelling prediction model have a large deviation from the test results. The reason is that the original model is based on an assumption that all the pores and available water are only associated with bentonite/montmorillonite fraction. However, for mixtures with extremely high sand content, the sand skeleton exists and resists the external stress from the very beginning. At the same time, the bentonite, dispersing in the sand skeleton, in contact with the pore fluid, swells freely to fully saturated state, however, still fails to fill the sand skeleton voids completely. In this research, the original swelling prediction model is extended by introducing the concept of critical filling sand content and critical contact stress. When sand content is more than the critical filling sand content, the deformation of the mixture is mainly due to the sand skeleton deformation. After the stress increases greater than the critical contact stress, the saturated bentonite fills the sand skeleton voids completely, and the swelling can still be predicted by the original swelling prediction model. In the extended model, the swelling prediction can be divided into three zones according to the two limit values of critical sand content and critical filling sand content. In different zones, the distribution ratio of the vertical stress ...
Sun, Y, Chen, C & Nimbalkar, S 2017, 'Identification of ballast grading for rail track', Journal of Rock Mechanics and Geotechnical Engineering, vol. 9, no. 5, pp. 945-954.
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© 2017 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences Grading has long been recognised to critically influence the mechanical behaviour of ballast. To identify the ballast grading for heavy-haul rail track, monotonic and cyclic triaxial tests are conducted to assess the performances of different gradings. Permanent deformations, aggregates degradation, resilience, shear resistance, maximum and minimum densities are recorded and analysed. The grading is found to affect the behaviour of ballast in that coarser gradings exhibit relatively better strength, resilience and therefore less permanent deformation. However, ballast degradation increases with the overall aggregate size. Therefore, to identify the grading for ballast with different performance objectives, a grey relational theory is used to convert the multi-objective into single-objective, i.e. grey relational grade. A relatively optimal grading that provides the highest grey relational grade is thus suggested for the improved ballast performance.
Sun, Y, Indraratna, B, Carter, JP, Marchant, T & Nimbalkar, S 2017, 'Application of fractional calculus in modelling ballast deformation under cyclic loading', Computers and Geotechnics, vol. 82, pp. 16-30.
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Surawski, NC, Bezantakos, S, Barmpounis, K, Dallaston, MC, Schmidt-Ott, A & Biskos, G 2017, 'A tunable high-pass filter for simple and inexpensive size-segregation of sub-10-nm nanoparticles', Scientific Reports, vol. 7, no. 1.
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AbstractRecent advanced in the fields of nanotechnology and atmospheric sciences underline the increasing need for sizing sub-10-nm aerosol particles in a simple yet efficient way. In this article, we develop, experimentally test and model the performance of a High-Pass Electrical Mobility Filter (HP-EMF) that can be used for sizing nanoparticles suspended in gaseous media. Experimental measurements of the penetration of nanoparticles having diameters down to ca 1nm through the HP-EMF are compared with predictions by an analytic, a semi-empirical and a numerical model. The results show that the HP-EMF effectively filters nanoparticles below a threshold diameter with an extremely high level of sizing performance, while it is easier to use compared to existing nanoparticle sizing techniques through design simplifications. What is more, the HP-EMF is an inexpensive and compact tool, making it an enabling technology for a variety of applications ranging from nanomaterial synthesis to distributed monitoring of atmospheric nanoparticles.
Sutton, GJ, Liu, RP & Guo, YJ 2017, 'Harmonising Coexistence of Machine Type Communications With Wi-Fi Data Traffic Under Frame-Based LBT', IEEE Transactions on Communications, vol. 65, no. 9, pp. 4000-4011.
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© 1972-2012 IEEE. The existence of relatively long LTE data blocks within the licensed-assisted access (LAA) framework results in bursty machine-type communications (MTC) packet arrivals, which cause system performance degradation and present new challenges in Markov modeling. We develop an embedded Markov chain to characterize the dynamic behavior of the contention arising from bursty MTC and Wi-Fi data traffic in the LAA framework. Our theoretical model reveals a high-contention phenomenon caused by the bursty MTC traffic, and quantifies the resulting performance degradation for both MTC and Wi-Fi data traffic. The Markov model is further developed to evaluate three potential solutions aiming to alleviate the contention. Our analysis shows that simply expanding the contention window, although successful in reducing congestion, may cause unacceptable MTC data loss. A TDMA scheme instead achieves better MTC packet delivery and overall throughput, but requires centralized coordination. We propose a distributed scheme that randomly spreads the MTC access processes through the available time period. Our model results, validated by simulations, demonstrate that the random spreading solution achieves a near TDMA performance, while preserving the distributed nature of the Wi-Fi protocol. It alleviates the MTC traffic contention and improves the overall throughput by up to 10%.
Sweetser, P, Johnson, D, Wyeth, P, Anwar, A, Meng, Y & Ozdowska, A 2017, 'GameFlow in Different Game Genres and Platforms', Computers in Entertainment, vol. 15, no. 3, pp. 1-24.
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The GameFlow model strives to be a general model of player enjoyment, applicable to all game genres and platforms. Derived from a general set of heuristics for creating enjoyable player experiences, the GameFlow model has been widely used in evaluating many types of games, as well as non-game applications. Initial applications of the GameFlow model were limited to real-time strategy games. However, in order to be considered a general model of player enjoyment in games, the GameFlow model needs to be applied to a more varied set of play experiences. In this article, we revisit the design of the GameFlow model, review the various applications and derivative models, and discuss on-going analysis of the model. Subsequently, we describe a study that aims to extend the initial validation of the GameFlow model to incorporate additional game types. We report the results of expert reviews conducted using the GameFlow criteria to evaluate first person shooter games on Sony PlayStation 3 and adventure games on Apple iPhone. Our findings provide insight into the manifestation of the GameFlow elements in these types of games and also highlight some of the genre-specific considerations in the application of the GameFlow model. Key issues are raised and discussed in relation to immersion, social interaction, and multiplayer games.
Syahir, AZ, Zulkifli, NWM, Masjuki, HH, Kalam, MA, Alabdulkarem, A, Gulzar, M, Khuong, LS & Harith, MH 2017, 'A review on bio-based lubricants and their applications', Journal of Cleaner Production, vol. 168, pp. 997-1016.
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In transportation and industrial sectors, the world relies heavily on petroleum-based products which may cause grave concern related to future energy security. On certain cases, these products would end up back to the environment causing serious environmental pollution and hazards. Recognized as potential substitutes to mineral-based lubricants, bio-based lubricants have received growing interest as they play a significant role in overcoming above problems. Bio-based lubricants have been found to exhibit superior lubricant properties over the conventional mineral lubricants, with renewability and biodegradability being their strongest suit. There is a strong need to review the available literature to explore the potential of bio-based lubricants for various applications. In this regard, the goal of this paper is to highlight the potential of biolubricants for a broad range of applications based upon the published researches over the past decade. The correlation between molecular structures, physicochemical properties and lubrication performance of natural oil were reviewed which is essential for lubricant development and selection. This review also acknowledged some applications of which the potential use of bio-based lubricant has been explored. Based on the key findings, it can be concluded that bio-based lubricant is a promising substitute for various applications due to their availability in wide arrays of properties which are essential for some applications. However, for certain applications, prior chemical modification is required to overcome the limitations including substandard low temperature characteristics and oxidative stability. With proper base oil and additive packages formulation, bio-based lubricants can perform better than the conventional lubricants.
T. Chorsi, H, Zhu, Y & Zhang, JXJ 2017, 'Patterned Plasmonic Surfaces—Theory, Fabrication, and Applications in Biosensing', Journal of Microelectromechanical Systems, vol. 26, no. 4, pp. 718-739.
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Low-profile patterned plasmonic surfaces are synergized with a broad class of silicon microstructures to greatly enhance near-field nanoscale imaging, sensing, and energy harvesting coupled with far-field free-space detection. This concept has a clear impact on several key areas of interest for the MEMS community, including but not limited to ultra-compact microsystems for sensitive detection of small number of target molecules, and 'surface' devices for optical data storage, micro-imaging and displaying. In this paper, we review the current state-of-the-art in plasmonic theory as well as derive design guidance for plasmonic integration with microsystems, fabrication techniques, and selected applications in biosensing, including refractive-index based label-free biosensing, plasmonic integrated lab-on-chip systems, plasmonic near-field scanning optical microscopy and plasmonics on-chip systems for cellular imaging. This paradigm enables low-profile conformal surfaces on microdevices, rather than bulk material or coatings, which provide clear advantages for physical, chemical and biological-related sensing, imaging, and light harvesting, in addition to easier realization, enhanced flexibility, and tunability.
Tabassum, H, Hossain, E & Hossain, MJ 2017, 'Modeling and Analysis of Uplink Non-Orthogonal Multiple Access (NOMA) in Large-Scale Cellular Networks Using Poisson Cluster Processes', IEEE Transactions on Communications, vol. 65, no. 8, pp. 1-1.
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Using the theory of Poisson cluster process (PCP), this paper provides a framework to analyze multi-cell uplink non-orthogonal multiple access (NOMA) systems. Specifically, we characterize the rate coverage probability of an NOMA user who is at rank m (in terms of the distance from its serving base station) among all users in a cell and the mean rate coverage probability of all users in a cell. Since the signal-to-interference-plus-noise ratio of the m th user relies on efficient successive interference cancellation (SIC), we consider three scenarios, i.e., perfect SIC (in which the signals of m-1 interferers who are stronger than the m th user are decoded successfully), imperfect SIC (in which the signals of m-1 interferers who are stronger than the m th user may or may not be decoded successfully), and imperfect worst case SIC (in which the decoding of the signal of the m th user is always unsuccessful whenever the decoding of its relative m-1 stronger users is unsuccessful). To derive the rate coverage expressions, we first characterize the Laplace transforms of the intra-cluster interferences in closed-form considering various SIC scenarios. The Laplace transform of the inter-cluster interference is then characterized by exploiting distance distributions from geometric probability. The derived expressions are customized for an equivalent OMA system. Finally, numerical results are presented to validate the derived expressions. The worst case SIC assumption provides remarkable simplifications in the mathematical analysis and is found to be highly accurate for higher user target rate requirements. A comparison of Poisson point process-based and PCP-based modeling is also conducted.
Tabatabaiefar, HR 2017, 'Development of synthetic soil mixture for experimental shaking table tests on building frames resting on soft soils', Geomechanics and Geoengineering, vol. 12, no. 1, pp. 28-35.
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In this study, a synthetic soil mixture has been developed and proposed for experimental soil-structure interaction shaking table tests on building frames with shallow foundations resting on soft soil deposits. To find the most appropriate mixture, different mixes with different proportion of mix components were examined in soils laboratory. Performing bender element tests, shear wave velocity of the soil specimens were acquired at different cure ages and the results were examined and compared. Based on the test results, a synthetic clay mixture consisting of kaolinite clay, bentonite, fly ash, lime and water has been proposed for experimental shaking table tests. The proposed mix provides adequate undrained shear strength to mobilise the required shallow foundation bearing capacity underneath the structural model while meeting both criteria of dynamic similarity between the model and the prototype to model soft soils in shaking table tests.
Tabatabaiefar, HR, Mansoury, B, Khadivi Zand, MJ & Potter, D 2017, 'Mechanical properties of sandwich panels constructed from polystyrene/cement mixed cores and thin cement sheet facings', Journal of Sandwich Structures & Materials, vol. 19, no. 4, pp. 456-481.
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Sandwich panels are made of two materials that are relatively weak in their separated state, but are improved when they are constructed together in a sandwich panel. Sandwich panels can be used for almost any section of a building including roofs, walls and floors. These building components are regularly required to provide insulation properties, weatherproofing properties and durability in addition to providing structural load bearing characteristics. Polystyrene/cement mixed cores and thin cement sheet facings sandwich panels are Australian products made of cement-polystyrene beaded mixture encapsulated between two thick cement board sheets. The structural properties of sandwich panels constructed of polystyrene/cement cores and thin cement sheet facings are relatively unknown. Therefore, in this study, to understand the mechanical behaviour and properties of those sandwich panels, a series of experimental tests have been performed and the outcomes have been explained and discussed. Based on the results of this study, values for modulus of elasticity and ultimate strength of the sandwich panels in dry and saturated conditions have been determined and proposed for practical applications.
Tam, HHM, Tuan, HD, Nasir, AA, Duong, TQ & Poor, HV 2017, 'MIMO Energy Harvesting in Full-Duplex Multi-User Networks', IEEE Transactions on Wireless Communications, vol. 16, no. 5, pp. 3282-3297.
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© 2002-2012 IEEE. This paper considers the efficient design of precoding matrices for sum throughput maximization under throughput quality of service (QoS) constraints and energy harvesting (EH) constraints for energy-constrained devices in a full-duplex (FD) multicell multi-user multiple-input-multiple-output network. Both time splitting (TS) and power splitting are considered to ensure practical EH and information decoding. These problems are quite complex due to non-concave objectives and nonconvex constraints. Especially, with TS, which is implementation-wise quite simple, the problem is even more challenging because the time splitting variable is not only coupled with the downlink throughput function but also coupled with the self-interference in the uplink throughput function. New path-following algorithms are developed for their solutions, which require only a single convex quadratic program for each iteration and ensure rapid convergence. Moreover, the FD EH maximization problem under throughput QoS constraints with TS is also considered. The performance of the proposed algorithms is compared with that of the modified problems assuming half-duplex systems. Finally, the merit of the proposed algorithms is demonstrated through extensive simulations.
TAM, HHM, TUAN, HD, NGO, DT & NGUYEN, HH 2017, 'Precoding Design for Han-Kobayashi's Signal Splitting in MIMO Interference Networks', IEICE Transactions on Communications, vol. E100.B, no. 6, pp. 1010-1016.
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© 2017 The Institute of Electronics, Information and Communication Engineers. For a multiuser multi-input multi-output (MU-MIMO) multicell network, the Han-Kobayashi strategy aims to improve the achievable rate region by splitting the data information intended to a serviced user (UE) into a common message and a private message. The common message is decodable by this UE and another UE from an adjacent cell so that the corresponding intercell interference is cancelled off. This work aims to design optimal precoders for both common and private messages to maximize the network sum-rate, which is a highly nonlinear and nonsmooth function in the precoder matrix variables. Existing approaches are unable to address this difficult problem. In this paper, we develop a successive convex quadratic programming algorithm that generates a sequence of improved points. We prove that the proposed algorithm converges to at least a local optimum of the considered problem. Numerical results confirm the advantages of our proposed algorithm over conventional coordinated precoding approaches where the intercell interference is treated as noise.
Tam, HHM, Tuan, HD, Ngo, DT, Duong, TQ & Poor, HV 2017, 'Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity', IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 872-884.
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© 2016 IEEE. In this paper, new strategies are devised for joint load balancing and interference management in the downlink of a heterogeneous network, where small cells are densely deployed within the coverage area of a traditional macrocell. Unlike existing work, the limited backhaul capacity at each base station (BS) is taken into account. Here, users (UEs) cannot be offloaded to any arbitrary BS, but only to ones with sufficient backhaul capacity remaining. Jointly designed with traffic offload, transmit power allocation mitigates the intercell interference to further support the quality of service of each UE. The objective here is either: 1) to maximize the network sum rate subject to minimum throughput requirements at individual UEs, or 2) to maximize the minimum UE throughput. Both formulated problems belong to the difficult class of mixed-integer nonconvex optimization problems. The inherently binary BS-UE association variables are strongly coupled with the transmit power variables, making the problems even more challenging to solve. New iterative algorithms are developed based on an exact penalty method combined with successive convex programming, where the binary BS-UE association problem and the nonconvex power allocation problem are dealt with one at a time. At each iteration of the proposed algorithms, only two simple convex problems need to be solved at the same time scale. It is proven that the algorithms improve the objective functions at each iteration and converge eventually. Numerical results demonstrate the efficiency of the proposed algorithms in both traffic offloading and interference mitigation.
Tan, ES, Anwar, M, Kumaran, P, Indra, TM & Yoshikawa, K 2017, 'Air assist atomization characterization of palm biodiesel through experimental investigation and CFD simulation', Biofuels, vol. 8, no. 5, pp. 571-577.
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© 2016 Informa UK Limited, trading as Taylor & Francis Group. The depletion of fossil fuel and environmental concerns have elevated biodiesel to emerge as a suitable alternative fuel to substitute diesel fuel. The study of spray formation is essential to improve the combustion systems of internal combustion engines and gas turbines. This paper aims to study the atomization characteristics of biodiesel derived from palm biodiesel through experimental test and simulation. The chemical fuel properties of biodiesel such as viscosity and density, will adversely affect the spray characteristics such as spray pattern, spray length, spray angle and Sauter Mean Diameter. The biodiesel fuels are blended with diesel in various ratios before being tested in an atomization test rig. Modelling of the atomizer are presented using computational fluid dynamics whereby comparisons are made with respect to the experimental results carried out in the atomizer test rig. There is no large discrepancy with the simulation results. The results showed that the higher content of biodiesel gives a larger droplet size and longer spray length. However, it produces smaller spray angle and spray width but with clearer vortex shape of spray pattern.
Tan, ES, Kumaran, P, Indra, TM & Yoshikawa, K 2017, 'Effect of Non-Edible Biodiesel Physical and Chemical Properties as Microturbine Fuel', Energy Procedia, vol. 142, pp. 413-418.
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The world is facing critical energy concern, in view of depleting fossil fuel reserves and increasing environment pollution. Biodiesel can potentially substitute fossil fuel, and is produced through the transesterification of vegetable oils. This paper will emphasize on the transition from first generation derived from waste cooking oil, to second generation biodiesel derived from calophyllum inophyllum, which is a non-edible plant. The objective of this paper is to optimize the performance of biodiesel blends with diesel in a 30 kW microturbine. The characterization of chemical fuel properties of distillate and biodiesel blends will be conducted to determine if it meets international standards for power generation. Temperature profiles, pressure, and flame imaging will be closely monitored to detect possible problems in operability of the combustor caused by the differences in fuel characteristics. The findings may provide useful information towards optimization of microturbine performance, considering the wide range of biodiesel feedstock that exist. The paper outcome will show the potential of non-edible biodiesel blends to be used as alternative fuel in microturbines for power generation.
Tang, J, Wang, XC, Hu, Y, Ngo, HH & Li, Y 2017, 'Dynamic membrane-assisted fermentation of food wastes for enhancing lactic acid production', Bioresource Technology, vol. 234, pp. 40-47.
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A dynamic membrane (DM) module was inserted into a fermentation reactor to separate soluble products from the fermented mixture to increase lactic acid (LA) production from food wastes under acidogenic conditions (uncontrolled pH, pH 4 and 5). With a high total suspended solid content (20-40g/L) in the fermenter, a stable DM could be maintained through regular backwashing. By effectively intercepting suspended solids and lactic acid bacteria (LAB), the fermenter was able to increase microbial activity and largely promote LA yield. Hydrolysis and acidogenesis rates increased with pH, and the highest LA yield (as high as 0.57g/g-TS) was obtained at pH 4. The microbial community analysis showed that the relative abundance of Lactobacillus increased to 96.4% at pH 4, but decreased to 43.3% at pH 5. In addition, the DM could be easily recovered by intercepting larger particles in less than 2h after each cycle of periodic backwashing.
Tang, J, Wang, XC, Hu, Y, Ngo, HH, Li, Y & Zhang, Y 2017, 'Applying fermentation liquid of food waste as carbon source to a pilot-scale anoxic/oxic-membrane bioreactor for enhancing nitrogen removal: Microbial communities and membrane fouling behaviour', Bioresource Technology, vol. 236, pp. 164-173.
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Fermentation liquid of food waste (FLFW) was applied as an external carbon source in a pilot-scale anoxic/oxic-membrane bioreactor (A/O-MBR) system to enhance nitrogen removal for treating low COD/TN ratio domestic wastewater. Results showed that, with the FLFW addition, total nitrogen removal increased from lower than 20% to 44-67% during the 150days of operation. The bacterial metabolic activities were obviously enhanced, and the significant change in microbial community structure promoted pollutants removal and favored membrane fouling mitigation. By monitoring transmembrane pressure and characterizing typical membrane foulants, such as extracellular polymeric substances (EPS), dissolved organic matter (DOM), and inorganics and biopolymers in the cake layer, it was confirmed that FLFW addition did not bring about any additional accumulation of membrane foulants, acceleration of fouling rate, or obvious irreversible membrane fouling in the whole operation period. Therefore, FLFW is a promising alternative carbon source to enhance nitrogen removal for the A/O-MBR system.
Tavakoli, J 2017, 'Physico-mechanical, morphological and biomedical properties of a novel natural wound dressing material', Journal of the Mechanical Behavior of Biomedical Materials, vol. 65, pp. 373-382.
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Wound healing as a complex biological process greatly affects the quality of patients׳ lives. The high initial cost of wound treatment using advanced wound dressing is a major concern that warrants more attention. Because of the similarities between body macromolecules and polysaccharides and proteoglycans, gelatin and starch were used extensively as wound dressings; however their solubility in aqueous environment is known as a major drawback. Crosslinking, as a common method for enhancing mechanical properties, has its own limitation as some chemical cross-likers reduce biocompatibility. In this research, a simple and economical method for the fabrication of a novel wound dressing foam based on natural polymers of starch and gelatin with borax as the crosslinking agent is introduced. To evaluate the utility of the foams for wound dressing application, morphology, swelling behaviour and kinetics of swelling, vapour permeability, dimension stability, their mechanical properties and cytotoxicity as well as their ability to control release properties were examined as a function of crosslinking density. It was found that however, all borax-induced-samples show acceptable biocompatibility, incorporation of 30% borax solution optimises their mechanical properties.
Tavakoli, J 2017, 'Region–media coupling in characterization and modelling of the disc annulus single lamella swelling', Medical & Biological Engineering & Computing, vol. 55, no. 8, pp. 1483-1492.
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The annulus fibrosus (AF) swelling property, which is correlated with its rheological and viscoelastic properties, plays a significant role in disc nutrition and mechanical loading justification during daily activities as well as designing scaffolds for tissue engineering applications. The objective of this study was twofold: firstly to characterize the AF single lamella swelling kinetics in different regions and solutions at the temperature range of 35-40 °C and secondly to use the swelling results as a baseline to model (independent to swelling media and anatomic region) the AF single lamella swelling. It was found that the AF single lamella swelling kinetics (equilibrium swelling ratio and swelling rate) depends on anatomic region and swelling media; however, its trend for different swelling media (ionic and molecular solution) is similar and the majority of hydration occurs during first 20% of equilibrium swelling time (about 20 min). Change in swelling rate constant in circumferential direction depends on the solution type. It decreases from anterior to lateral regions for water, PBS and glucose solution and remains constant-or its change is negligible-from lateral to posterolateral regions. The effect of temperature (in the range of 35-40 °C) on swelling kinetics was seen to be negligible. It was also understood that it is possible to present a model (independent to swelling media type) to predict the swelling kinetics of posterior and posterolateral AF single lamella, as these locations are less sensitive to the swelling media.
Tavakoli, J 2017, 'Tissue Engineering of the Intervertebral Disc’s Annulus Fibrosus: A Scaffold-Based Review Study', Tissue Engineering and Regenerative Medicine, vol. 14, no. 2, pp. 81-91.
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Tissue engineering as a high technology solution for treating disc's problem has been the focus of some researches recently; however, the upcoming successful results in this area depends on understanding the complexities of biology and engineering interface. Whereas the major responsibility of the nucleus pulposus is to provide a sustainable hydrated environment within the disc, the function of the annulus fibrosus (AF) is more mechanical, facilitating joint mobility and preventing radial bulging by confining of the central part, which makes the AF reconstruction important. Although the body of knowledge regarding the AF tissue engineering has grown rapidly, the opportunities to improve current understanding of how artificial scaffolds are able to mimic the AF concentric structure-including inter-lamellar matrix and cross-bridges-addressed unresolved research questions. The aim of this literature review was to collect and discuss, from the international scientific literature, information about tissue engineering of the AF based on scaffold fabrication and material properties, useful for developing new strategies in disc tissue engineering. The key parameter of this research was understanding if role of cross-bridges and inter-lamellar matrix has been considered on tissue engineering of the AF.
Tavakoli, J & Costi, JJ 2017, 'Development of a rapid matrix digestion technique for ultrastructural analysis of elastic fibers in the intervertebral disc', Journal of the Mechanical Behavior of Biomedical Materials, vol. 71, pp. 175-183.
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Collagen and elastic fibers are two major fibrous constituents of the annulus fibrosus (AF) in the disc that contribute to its mechanical and viscoelastic properties. It was thought that elastic fibers play no substantial role in the function and properties of the disc as these fibers were irregularly distributed. Studies that have revealed highly organized elastic fibers with different regional orientation and distribution, while being strongly crosslinked with matrix, suggesting their contribution to disc structure-function properties. These studies that were performed by light microscopic analysis of histologically prepared samples, have not been able to reveal the fine-scale architectural details of the elastic fiber network. Since elastic fibers are intermingled with other fibrous components of the disc and mostly obscured by the extracellular matrix, it is difficult to demonstrate their ultra-structural organization using scanning electron microscopy (SEM). Therefore the aim of this study was to develop a rapid matrix digestion technique for ultrastructural analysis of the disc elastic fibers. This study provides a new method for fundamental visualization of elastic fibers and their architecture in the disc. Through the ultra-structural analysis, the relationship between structure and function, as well as the role of elastic fibers on AF mechanical properties can be studied. This method may be used to develop a three-dimensional map of elastic fibers distribution within the disc, which would provide valuable information for designing tissue engineered scaffolds for AF repair and replacement.
Tavakoli, J & Tang, Y 2017, 'Honey/PVA hybrid wound dressings with controlled release of antibiotics: Structural, physico-mechanical and in-vitro biomedical studies', Materials Science and Engineering: C, vol. 77, pp. 318-325.
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Hydrogel/honey hybrids manifest an attractive design with an exclusive therapeutic property that promotes wound healing process. The greater the concentration of honey within the formulation, the better the biomedical properties that will be achieved. However, an increase in the percentage of honey can negatively affect the physico-chemical and mechanical properties of hybrid hydrogels. The need exists, therefore, to prepare wound dressings that contain high honey density with optimal biomedical, mechanical and physicochemical properties. In this study, a simple method for the preparation of a highly concentrated honey/PVA hybrid hydrogel with borax as the crosslinking agent is reported. Comprehensive evaluations of the morphology, swelling kinetics, permeability, bio-adhesion, mechanical characteristics, cytotoxicity, antibacterial property, cell proliferation ability and their controlling release properties were conducted as a function of crosslinking density. All the borax-induced hydrogels showed acceptable biocompatibility, and the incorporation of 1% borax in the hydrogel formulation produced optimal behaviours for wound addressing applications.
Tavakoli, J & Tang, Y 2017, 'Hydrogel Based Sensors for Biomedical Applications: An Updated Review', Polymers, vol. 9, no. 8, pp. 364-364.
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Biosensors that detect and convert biological reactions to a measurable signal have gained much attention in recent years. Between 1950 and 2017, more than 150,000 papers have been published addressing the applications of biosensors in different industries, but to the best of our knowledge and through careful screening, critical reviews that describe hydrogel based biosensors for biomedical applications are rare. This review discusses the biomedical application of hydrogel based biosensors, based on a search performed through Web of Science Core, PubMed (NLM), and Science Direct online databases for the years 2000–2017. In this review, we consider bioreceptors to be immobilized on hydrogel based biosensors, their advantages and disadvantages, and immobilization techniques. We identify the hydrogels that are most favored for this type of biosensor, as well as the predominant transduction strategies. We explain biomedical applications of hydrogel based biosensors including cell metabolite and pathogen detection, tissue engineering, wound healing, and cancer monitoring, and strategies for small biomolecules such as glucose, lactate, urea, and cholesterol detection are identified.
Tavakoli, J, Elliott, DM & Costi, JJ 2017, 'The ultra-structural organization of the elastic network in the intra- and inter-lamellar matrix of the intervertebral disc', Acta Biomaterialia, vol. 58, pp. 269-277.
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The inter-lamellar matrix (ILM)-located between adjacent lamellae of the annulus fibrosus-consists of a complex structure of elastic fibers, while elastic fibers of the intra-lamellar region are aligned predominantly parallel to the collagen fibers. The organization of elastic fibers under low magnification, in both inter- and intra-lamellar regions, was studied by light microscopic analysis of histologically prepared samples; however, little is known about their ultrastructure. An ultrastructural visualization of elastic fibers in the inter-lamellar matrix is crucial for describing their contribution to structural integrity, as well as mechanical properties of the annulus fibrosus. The aims of this study were twofold: first, to present an ultrastructural analysis of the elastic fiber network in the ILM and intra-lamellar region, including cross section (CS) and in-plane (IP) lamellae, of the AF using Scanning Electron Microscopy (SEM) and second, to -compare the elastic fiber orientation between the ILM and intra-lamellar region. Four samples (lumbar sheep discs) from adjacent sections (30μm thickness) of anterior annulus were partially digested by a developed NaOH-sonication method for visualization of elastic fibers by SEM. Elastic fiber orientation and distribution were quantified relative to the tangential to circumferential reference axis. Visualization of the ILM under high magnification revealed a dense network of elastic fibers that has not been previously described. Within the ILM, elastic fibers form a complex network, consisting of different size and shape fibers, which differed to those located in the intra-lamellar region. For both regions, the majority of fibers were oriented near 0° with respect to tangential to circumferential (TCD) direction and two minor symmetrical orientations of approximately±45°. Statistically, the orientation of elastic fibers between the ILM and intra-lamellar region was not different (p=0.171). The present stud...
Tawfik, SA, Ali, S, Fronzi, M, Kianinia, M, Tran, TT, Stampfl, C, Aharonovich, I, Toth, M & Ford, MJ 2017, 'First principles investigation of quantum emission from hBN defects', Nanoscale, vol. 9, no. 36, pp. 13575-13582.
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Hexagonal boron nitride (hBN) has recently emerged as a fascinating platformfor room-temperature quantum photonics due to the discovery of robust visiblelight single-photon emitters. In order to utilize these emitters, it isnecessary to have a clear understanding of their atomic structure and theassociated excitation processes that give rise to this single photon emission.Here we perform density-functional theory (DFT) and constrained DFTcalculations for a range of hBN point defects in order to identify potentialemission candidates. By applying a number of criteria on the electronicstructure of the ground state and the atomic structure of the excited states ofthe considered defects, and then calculating the Huang-Rhys (HR) factor, wefind that the CBVN defect, in which a carbon atom substitutes a boron atom andthe opposite nitrogen atom is removed, is a potential emission source with a HRfactor of 1.66, in good agreement with the experimental HR factor. We calculatethe photoluminescence (PL) line shape for this defect and find that itreproduces a number of key features in the the experimental PL lineshape.
Teh, SH, Wiedmann, T, Castel, A & de Burgh, J 2017, 'Hybrid life cycle assessment of greenhouse gas emissions from cement, concrete and geopolymer concrete in Australia', Journal of Cleaner Production, vol. 152, pp. 312-320.
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Teng, X & Zhang, YX 2017, 'Structural behavior FRP-strengthened steel-reinforced concrete slabs under moving-wheel cyclic loads', Australian Journal of Structural Engineering, vol. 18, no. 2, pp. 86-94.
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Thebuwana, H, Hadgraft, R & Alam, F 2017, 'Addressing Graduate Competencies: Understanding the Contextual Factors Impacting the Engineering Discipline', Energy Procedia, vol. 110, pp. 359-364.
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© 2017 The Authors. The knowledge of contextual factors that impact the engineering discipline is one of sixteen competencies that must be demonstrated by engineering graduates upon completion of an accredited engineering degree in Australia. This research critically analyses learning outcomes, learning activities and assessment tasks associated with the knowledge of contextual factors for the Mechanical Engineering (Honours) degrees at two universities to determine how this competency is perceived and addressed within the curriculum. In the majority of cases, the learning outcomes do not address the competency and there are instances where this competency has been misunderstood and misrepresented. Various assessment tasks are used in the subjects that address this competency, including exams, tests, assignments, reports, presentations, tutorials, reflective journals and others. Universities and accreditation providers must review their processes for addressing this competency to ensure it is achieved. Further research is required to define this competency for better alignment and understanding of learning outcomes.
Tian, H & Zhang, YX 2017, 'Ageing effect on tensile and shrinkage behaviour of new green hybrid fibre-reinforced cementitious composites', Cement and Concrete Composites, vol. 75, pp. 38-50.
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Tian, H, Cui, YH, Zhang, YX & Yang, C 2017, 'The application of general self-consistent model on mechanical behaviour of fibre-reinforced cementitious composites', Construction and Building Materials, vol. 146, pp. 114-121.
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Tien Bui, D, Bui, Q-T, Nguyen, Q-P, Pradhan, B, Nampak, H & Trinh, PT 2017, 'A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area', Agricultural and Forest Meteorology, vol. 233, pp. 32-44.
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© 2016 Elsevier B.V. This paper proposes and validates a novel hybrid artificial intelligent approach, named as Particle Swarm Optimized Neural Fuzzy (PSO-NF), for spatial modeling of tropical forest fire susceptibility. In the proposed approach, a Neural Fuzzy inference system (NF) was used to establish the forest fire model whereas Particle Swarm Optimization (PSO) was adopted to investigate the best values for the model parameters. Tropical forest at the province of Lam Dong (Central Highland of Vietnam) was used as a case study. For this purpose, historic forest fires and ten ignition factors (slope, aspect, elevation, land use, Normalized Difference Vegetation Index, distance to road, distance to residence area, temperature, wind speed, and rainfall) were collected from various sources to construct a GIS database, and then, the database was used to develop and validate the proposed model. The performance of the forest model was assessed using the Receiver Operating Characteristic curve, area under the curve (AUC), and several statistical measures. The results showed that the proposed model performs well, both on the training dataset (AUC = 0.932) and the validation dataset (AUC = 0.916). The usability of the proposed model was further assessed through comparisons with those derived from two benchmark state-of-the art machine learning methods, Random Forests (RF) and Support Vector Machine (SVM). Because the performance of the proposed model is better than the two benchmark models, we concluded that the PSO-NF model is a valid alternative tool that should be considered for tropical forest fire susceptibility modeling. The result in this study is useful for forest planning and management in forest fire prone areas.
Tin, MMM, Anioke, G, Nakagoe, O, Tanabe, S, Kodamatani, H, Nghiem, LD & Fujioka, T 2017, 'Membrane fouling, chemical cleaning and separation performance assessment of a chlorine-resistant nanofiltration membrane for water recycling applications', Separation and Purification Technology, vol. 189, pp. 170-175.
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© 2017 Elsevier B.V. The effectiveness of hypochlorite cleaning for fouling mitigation of a prototype chlorine-resistant nanofiltration (NF) membrane was assessed for direct filtration of a secondary treated effluent. The chlorine resistance and separation performance of the prototype NF membrane were also compared to commercial NF and reverse osmosis membranes. The prototype chlorine resistant NF membrane did not show any changes in permeability and conductivity rejection after exposing a NaOCl solution for up to 5 × 10 4 ppm-h. By contrast, a considerable deterioration in rejection was observed for the other two commercial membranes. Direct filtration of a secondary treated effluent by the prototype NF membrane resulted in a progressive permeability reduction by up to 25% after 10 h of filtration. The membrane permeability was fully restored by hypochlorite cleaning with a 2000 ppm NaOCl solution for 1 h. Effective permeability recovery by hypochlorite cleaning was demonstrated with multiple hypochlorite cleaning cycles. Membrane fouling and hypochlorite cleaning were also simulated using solutions containing a model foulant (sodium alginate, humic acids or bovine serum albumin). Among them, an insufficient permeability recovery was observed for membrane fouling caused by humic acids. Further research is recommended to develop an improved hypochlorite cleaning protocol to control various membrane fouling.
Ting, SRS, Min, EH, Lau, BKF & Hutvagner, G 2017, 'Acetyl‐α‐d‐mannopyranose‐based cationic polymer via RAFT polymerization for lectin and nucleic acid bindings', Journal of Applied Polymer Science, vol. 134, no. 24, pp. 1-11.
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ABSTRACTFunctional cationic polymers carrying mannose moieties were synthesized in a facile manner by employing RAFT polymerization. Initially, a protected carbohydrate based monomer, [2‐(2,3,4,6‐tetra‐O‐acetyl‐α‐d‐mannopyranosyloxy)ethyl methacrylate (AcManEMA)], was prepared by the O‐glycosylation of 2‐hydroxyethyl methacrylate (HEMA). Subsequently, a macroRAFT agent of poly[2‐(dimethyl)amino ethyl methacrylate] (PDMAEMA) was generated, and a further chain extension polymerization with AcManEMA was carried out in dioxane to form a acetylated mannose cationic diblock copolymer, PDMAEMA‐b‐PAcManEMA. It was attained in high yields and displayed low dispersity (Ð). Acetylated mannose moieties on the polymer were deprotected with sodium methoxide and the amines from the DMAEMA block were protonated to yield a cationic diblock glycopolymer, PDMAEMA‐b‐PManEMA. The cationic property of polymers were characterized by mixing with a negatively charged siRNA duplex and a pDNA, and aggregates of 102 and 233 nm were obtained, respectively. Agarose gel shift assay revealed that the polymers were able to retain the nucleic acids as large polymer complexes. Lectin binding assay proved that the mannose residue on the polymers were only able to bind specifically with ConA. PNA lectin was employed as a control and did not show specific binding. The cationic glycopolymer could be advantageous in targeted nucleic acids delivery in specific cells. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44947.
Tong, L & Luo, Q 2017, 'A novel algorithm using an orthotropic material model for topology optimization', Engineering Optimization, vol. 49, no. 9, pp. 1523-1540.
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Tong, X, Ji, Y, Lin, J, Zhu, J, Sun, F, Zhong, Y, Yang, Y & Zhu, X 2017, 'Cooperative spectrum sensing based on a modified shuffled frog leaping algorithm in 5G network', Physical Communication, vol. 25, no. Part 2, pp. 438-444.
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© 2017 Elsevier B.V. The explosion of different types of wireless communications is leading to an impending spectrum famine. As a result, spectrum sensing has gained increasing interest from governments, industry and regulators. In this paper, a novel approach for cooperative spectrum sensing is proposed based on a modified shuffled frog leaping algorithm (SFLA). This approach is to fuse the perceived results of multiple nodes, and to improve the detection reliability. Simulations are used to compare the performance of the modified SFLA to the conventional one. The performance of the proposed cooperative spectrum sensing method based on the modified SFLA and that of the cooperative spectrum sensing method using modified deflection coefficient (MDC) are also compared. Results show that the proposed SFLA outperforms the traditional SFLA, and the proposed cooperative spectrum sensing method based on the modified SFLA gives higher miss detection probability than the MDC-based method, which validates the effectiveness of the modified SFLA-based cooperative sensing method.
Tong, X, Yang, Y, Zhong, Y, Zhu, X, Lin, J & Dutkiewicz, E 2017, 'Design of an On-Chip Highly Sensitive Misalignment Sensor in Silicon Technology', IEEE Sensors Journal, vol. 17, no. 5, pp. 1211-1212.
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© 2016 IEEE. Advanced micromachining technology has made magnificent progress for fabrication of non-planar circuits. Using this technology, circuits and systems can be implemented in a more cost-effective way. Unlike the conventional planar circuit, low-cost and highly sensitive misalignment sensor is required to detect imperfect placement of different micro-devices, which may be of the order of sub-micrometers. Currently, this is hardly to be achieved by using the existing approaches. In this letter, we present a novel sensor design approach utilizing the parasitic capacitance of an integrated coupled-line resonator for misalignment sensing. Due to vertical misalignment between two metal strips, the parasitic capacitance of the sensor varies, which results in a resonance shift from 53 to 68 GHz, while a reasonably strong transmission notch is still maintained. Taking advantage of this principle, misalignment can be effectively detected. To prove the concept, several devices are fabricated in a standard silicon technology. Three samples with the same structure are used to evaluate the reliability, while eight different structures are used to verify the concept. All results are extensively validated through both simulation and measurements.
Tonks, KT, White, CP, Center, JR, Samocha-Bonet, D & Greenfield, JR 2017, 'Bone Turnover Is Suppressed in Insulin Resistance, Independent of Adiposity', The Journal of Clinical Endocrinology & Metabolism, vol. 102, no. 4, pp. 1112-1121.
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Tonnizam Mohamad, E, Jahed Armaghani, D, Ghoroqi, M, Yazdani Bejarbaneh, B, Ghahremanians, T, Abd Majid, MZ & Tabrizi, O 2017, 'Ripping Production Prediction in Different Weathering Zones According to Field Data', Geotechnical and Geological Engineering, vol. 35, no. 5, pp. 2381-2399.
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Torpy, FR, Zavattaro, M & Irga, PJ 2017, 'Green wall technology for the phytoremediation of indoor air: a system for the reduction of high CO2 concentrations', Air Quality, Atmosphere & Health, vol. 10, no. 5, pp. 575-585.
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© 2016, Springer Science+Business Media Dordrecht. Along with the growing requirement to reduce building carbon emissions, a need has arisen to find energy efficient means of improving the quality of indoor air. Indoor plants have been shown to be capable of reducing most air pollutants; however, practical numbers of potted plants will not have the capacity to control many forms of air pollution, especially CO2. Green walls are space-efficient means of increasing the density of indoor plants. We assessed an active green wall for its potential to reduce CO2 in chambers and a test room. Chlorophytum comosum and Epipremnum aureum were both effective cultivars for CO2 removal at light densities greater than 50 μmol m−2 s−1. Substrate ventilation increased the rate of CO2 draw down from chambers, possibly due to increased leaf gas exchange rates. Green walls were then tested in a 15.65-m3 sealed simulation room, allowing the calculation of clean air delivery rate (CADR) and air changes per hour (ACH) equivalents based on CO2 draw down. Rates of CO2 draw down were modest under typical brightly lit indoor conditions (50 μmol m−2 s−1); however, when light intensity was increased to relatively bright levels, similar to indoor conditions next to a window or with the addition of supplementary lighting (250 μmol m−2 s−1), a 1-m2 green wall was capable of significant quantifiable reductions of high CO2 concentrations within a sealed room environment. Extrapolating these findings indicates that a 5-m2 green wall containing C. comosum could balance the respiratory emissions of a full-time occupant.
Tran, GM, Ho-Le, TP, Ha, DT, Tran-Nguyen, CH, Nguyen, TSM, Pham, TTN, Nguyen, TA, Nguyen, DA, Hoang, HQ, Tran, NV & Nguyen, TV 2017, 'Patterns of antimicrobial resistance in intensive care unit patients: a study in Vietnam', BMC Infectious Diseases, vol. 17, no. 1, pp. 1-7.
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© The Author(s). 2017. Background: Antimicrobial resistance has emerged as a major concern in developing countries. The present study sought to define the pattern of antimicrobial resistance in ICU patients with ventilator-associated pneumonia. Methods: Between November 2014 and September 2015, we enrolled 220 patients (average age ~ 71 yr) who were admitted to ICU in a major tertiary hospital in Ho Chi Minh City, Vietnam. Data concerning demographic characteristics and clinical history were collected from each patient. The Bauer-Kirby disk diffusion method was used to detect the antimicrobial susceptibility. Results: Antimicrobial resistance was commonly found in ceftriaxone (88%), ceftazidime (80%), ciprofloxacin (77%), cefepime (75%), levofloxacin (72%). Overall, the rate of antimicrobial resistance to any drug was 93% (n = 153/164), with the majority (87%) being resistant to at least 2 drugs. The three commonly isolated microorganisms were Acinetobacter (n = 75), Klebsiella (n = 39), and Pseudomonas aeruginosa (n = 29). Acinetobacter baumannii were virtually resistant to ceftazidime, ceftriaxone, piperacilin, imipenem, meropenem, ertapenem, ciprofloxacin and levofloxacin. High rates ( > 70%) of ceftriaxone and ceftazidime-resistant Klebsiella were also observed. Conclusion: These data indicated that critically ill patients on ventilator in Vietnam were at disturbingly high risk of antimicrobial resistance. The data also imply that these Acinetobacter, Klebsiella, and Pseudomonas aeruginosa and multidrug resistance pose serious therapeutic problems in ICU patients. A concerted and systematic effort is required to rapidly identify high risk patients and to reduce the burden of antimicrobial resistance in developing countries.
Tran, HN, You, S-J, Nguyen, TV & Chao, H-P 2017, 'Insight into the adsorption mechanism of cationic dye onto biosorbents derived from agricultural wastes', Chemical Engineering Communications, vol. 204, no. 9, pp. 1020-1036.
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© 2017 Taylor & Francis. This study investigated the phenomenon and mechanism of adsorption of methylene green 5 (MG5) on three pristine biosorbents: golden shower pod (GS), coconut shell (CC), and orange peel (OP). The results showed that the biosorbents possessed low specific surface areas, but abundant functional groups. Adsorption was strongly affected by the solution’s pH and ionic strength. As revealed in the kinetic study, equilibrium was rapidly established, requiring low activation energies; a removal rate of 30%–87% was achieved within 1 min. The maximum Langmuir adsorption capacities at 30°C exhibited the following order: GS (106 mg/g) > OP (92 mg/g) > CC (59 mg/g). Thermodynamic experiments suggested that the adsorption occurred spontaneously and exothermically The primary adsorption mechanisms involved electrostatic attraction, hydrogen bonding formations, and n-π interaction. Thermogravimetric analysis (TGA) revealed that three biopolymer components (i.e., hemicellulose, cellulose, and lignin) played controlling roles in the adsorption process. Thus, these three agricultural residues can be considered potential low-cost adsorbents for efficient dye adsorption applications.
Tran, T, Bliuc, D, van Geel, T, Adachi, JD, Berger, C, van den Bergh, J, Eisman, JA, Geusens, P, Goltzman, D, Hanley, DA, Josse, RG, Kaiser, SM, Kovacs, CS, Langsetmo, L, Prior, JC, Nguyen, TV & Center, JR 2017, 'Population-Wide Impact of Non-Hip Non-Vertebral Fractures on Mortality', Journal of Bone and Mineral Research, vol. 32, no. 9, pp. 1802-1810.
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ABSTRACT Data on long-term consequences of non-hip non-vertebral (NHNV) fractures, accounting for approximately two-thirds of all fragility fractures, are scanty. Our study aimed to quantify the population-wide impact of NHNV fractures on mortality. The national population-based prospective cohort study (Canadian Multicentre Osteoporosis Study) included 5526 community dwelling women and 2163 men aged 50 years or older followed from July 1995 to September 2013. Population impact number was used to quantify the average number of people for whom one death would be attributable to fracture and case impact number to quantify the number of deaths out of which one would be attributable to a fracture. There were 1370 fragility fractures followed by 296 deaths in women (mortality rate: 3.49; 95% CI, 3.11 to 3.91), and 302 fractures with 92 deaths in men (5.05; 95% CI, 4.12 to 6.20). NHNV fractures accounted for three-quarters of fractures. In women, the population-wide impact of NHNV fractures on mortality was greater than that of hip and vertebral fractures because of the greater number of NHNV fractures. Out of 800 women, one death was estimated to be attributable to a NHNV fracture, compared with one death in 2000 women attributable to hip or vertebral fracture. Similarly, out of 15 deaths in women, one was estimated to be attributable to a NHNV fracture, compared with one in over 40 deaths for hip or vertebral fracture. The impact of forearm fractures (ie, one death in 2400 women and one out of 42 deaths in women attributable to forearm fracture) was similar to that of hip, vertebral, or rib fractures. Similar, albeit not significant, results were noted for men. The study highlights the important contribution of NHNV fractures on mortality because many NHNV fracture types, except for the most distal fractures, have serious adverse consequ...
Tran, TT, Choi, S, Scott, JA, Xu, Z, Zheng, C, Seniutinas, G, Bendavid, A, Fuhrer, MS, Toth, M & Aharonovich, I 2017, 'Room‐Temperature Single‐Photon Emission from Oxidized Tungsten Disulfide Multilayers', Advanced Optical Materials, vol. 5, no. 5, pp. 1600939-1600939.
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Robust quantum emitters fabricated by thermal oxidation of tungsten disulfide multilayers are reported. The emitters show robust, optically stable, linearly polarized luminescence at room temperature, can be modeled using a three‐level system, and exhibit moderate bunching. Overall, the results provide important insights into understanding of defect formation and quantum emitter activation in two‐dimensional materials.
Tran, TT, Kianinia, M, Bray, K, Kim, S, Xu, Z-Q, Gentle, A, Sontheimer, B, Bradac, C & Aharonovich, I 2017, 'Nanodiamonds with photostable, sub-gigahertz linewidths quantum emitters', APL Photonics, vol. 2, no. 11, pp. 116103-116103.
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Single photon emitters with narrow linewidths are highly sought after forapplications in quantum information processing and quantum communications. Inthis letter, we report on a bright, highly polarized near infrared singlephoton emitter embedded in diamond nanocrystals with a narrow, sub GHz opticallinewidths at 10K. The observed zero phonon line at ~ 780 nm is opticallystable under low power resonant excitation and blue shifts as the excitationpower increases. Our results highlight the prospect for using new near infraredcolor centers in nanodiamonds for quantum applications.
Tran, TT, Kianinia, M, Nguyen, M, Kim, S, Xu, Z-Q, Kubanek, A, Toth, M & Aharonovich, I 2017, 'Resonant Excitation of Quantum Emitters in Hexagonal Boron Nitride', ACS Photonics, vol. 5, no. 2, pp. 295-300.
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Quantum emitters in layered hexagonal boron nitride (hBN) have recentlyattracted a great attention as promising single photon sources. In this work,we demonstrate resonant excitation of a single defect center in hBN, one of themost important prerequisites for employment of optical sources in quantuminformation application. We observe spectral linewidths of hBN emitter narrowerthan 1 GHz while the emitter experiences spectral diffusion. Temporalphotoluminescence measurements reveals an average spectral diffusion time ofaround 100 ms. On-resonance photon antibunching measurement is also realized.Our results shed light on the potential use of quantum emitters from hBN innanophotonics and quantum information.
Tran, TT, Wang, D, Xu, Z-Q, Yang, A, Toth, M, Odom, TW & Aharonovich, I 2017, 'Deterministic Coupling of Quantum Emitters in 2D Materials to Plasmonic Nanocavity Arrays', Nano Letters, vol. 17, no. 4, pp. 2634-2639.
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© 2017 American Chemical Society. Quantum emitters in two-dimensional materials are promising candidates for studies of light-matter interaction and next generation, integrated on-chip quantum nanophotonics. However, the realization of integrated nanophotonic systems requires the coupling of emitters to optical cavities and resonators. In this work, we demonstrate hybrid systems in which quantum emitters in 2D hexagonal boron nitride (hBN) are deterministically coupled to high-quality plasmonic nanocavity arrays. The plasmonic nanoparticle arrays offer a high-quality, low-loss cavity in the same spectral range as the quantum emitters in hBN. The coupled emitters exhibit enhanced emission rates and reduced fluorescence lifetimes, consistent with Purcell enhancement in the weak coupling regime. Our results provide the foundation for a versatile approach for achieving scalable, integrated hybrid systems based on low-loss plasmonic nanoparticle arrays and 2D materials.
Tran, VH, Phuntsho, S, Park, H, Han, DS & Shon, HK 2017, 'Sulfur-containing air pollutants as draw solution for fertilizer drawn forward osmosis desalination process for irrigation use', Desalination, vol. 424, pp. 1-9.
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© 2017 Elsevier B.V. This study investigated suitability and performance of the sulfur-based seed solution (SBSS) as a draw solution (DS), a byproduct taken from the photoelectrochemical (PEC) process where the SBSS is used as an electrolyte for H2 production. This SBSS DS is composed of a mixture of ammonium sulfate ((NH4)2SO4) and ammonium sulfite ((NH4)2SO3), and it can be utilized as fertilizer for fertilizer drawn forward osmosis (FDFO) desalination of saline water. The FDFO process employed with thin-film composite (TFC) membrane and showed that the process performance (i.e. water flux and reverse salt flux) is better than that with cellulose triacetate (CTA) membrane. In addition, it produced high water flux of 19 LMH using SBSS as DS at equivalent concentration at 1 M and 5 g/L NaCl of feed solution (model saline water). Experimental results showed that the reverse salt flux of SBSS increased with the increase in pH of the DS and that lowering the concentration of ammonium sulfite in the SBSS led to the higher water flux of feed solution. The result also demonstrated that this SBSS is practically suitable for the FDFO process toward development of water-energy-food nexus technology using sulfur chemicals-containing air pollutant.
Tran, VS, Ngo, HH, Guo, W, Ton-That, C, Li, J, Li, J & Liu, Y 2017, 'Removal of antibiotics (sulfamethazine, tetracycline and chloramphenicol) from aqueous solution by raw and nitrogen plasma modified steel shavings', Science of The Total Environment, vol. 601-602, pp. 845-856.
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© 2017 Elsevier B.V. The removal of sulfamethazine (SMT), tetracycline (TC) and chloramphenicol (CP) from synthetic wastewater by raw (M3) and nitrogen plasma modified steel shavings (M3-plN2) was investigated using batch experiments. The adsorption kinetics could be expressed by both pseudo-first-order kinetic (PFO) and pseudo-second-order kinetic (PSO) models, where correlation coefficient r2 values were high. The values of PFO rate constant k1p and PSO rate constant k2p decreased as SMT-M3 > SMT-M3-plN2 > TC-M3-plN2 > TC-M3 > CP-M3 > CP-M3-plN2 and SMT-M3 > SMT-M3-plN2 > TC-M3 > TC-M3-plN2 > CP-M3 > CP-M3-plN2, respectively. Solution pH, adsorbent dose and temperature exerted great influences on the adsorption process. The plasma modification with nitrogen gas cleaned and enhanced 1.7-fold the surface area and 1.4-fold the pore volume of steel shavings. Consequently, the removal capacity of SMT, TC, CP on the adsorbent rose from 2519.98 to 2702.55, 1720.20 to 2158.36, and 2772.81 to 2920.11 μg/g, respectively. Typical chemical states of iron (XPS in Fe2p3 region) in the adsorbents which are mainly responsible for removing antibiotics through hydrogen bonding, electrostatic and non- electrostatic interactions and redox reaction were as follows: Fe3O4/Fe2 +, Fe3O4/Fe3 +, FeO/Fe2 + and Fe2O3/Fe3 +.
Trianni, A, Cagno, E & Neri, A 2017, 'Modelling barriers to the adoption of industrial sustainability measures', Journal of Cleaner Production, vol. 168, pp. 1482-1504.
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© 2017 Elsevier Ltd Sustainability is constantly gaining relevance among industrial decision makers, policy makers and scholars. In order to be sustainable, firms need to implement industrial sustainability measures, however there are many barriers to doing this. This work is based on a review of literature on barriers to the areas of occupational health and safety, eco efficiency, energy efficiency and to sustainability, and contributes to industrial sustainability research by presenting a novel, integrated theoretical model of barriers to the implementation of sustainability measures. The model encompasses previous literature review contributions and is intended to characterize and evaluate barriers to the adoption of industrial sustainability measures in all its areas. We have conducted a preliminary validation of the model investigating eight northern Italian manufacturing firms, looking at its ability to represent barriers to sustainability, usefulness and ease of use. We conducted semi-structured interviews to people responsible of the different areas of industrial sustainability, complemented by questionnaires and secondary materials. Results show a positive overall judgment of the model by all the interviewees. Moreover, the model was able to be applied to issues deriving from different perspectives and different areas of industrial sustainability. The findings can help firms and policy makers overcome barriers and they also provide insight into the different perspectives on the adoption of industrial sustainability measures than can be used to promote their adoption.
Trianni, A, Cagno, E, Marchesani, F & Spallina, G 2017, 'Classification of drivers for industrial energy efficiency and their effect on the barriers affecting the investment decision-making process', Energy Efficiency, vol. 10, no. 1, pp. 199-215.
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© 2016, Springer Science+Business Media Dordrecht. Industrial energy efficiency represents a priority for European industrial competitiveness. Many studies offer contributions providing evidence of the existence of driving forces supporting the adoption of energy efficiency measures, but a structured approach to drivers for industrial energy efficiency is still lacking. Therefore, in the present study, we propose a definition of drivers, making emphasis on the industrial decision-maker perspective, that is needed for their classification here proposed. Focus is given to point out the difference between internal and external drivers, highlighting the major stakeholders responsible for their promotion. Drivers are further categorized into: regulatory, economic, informative, and vocational training. Moreover, we propose a framework describing the effect of drivers on barriers in the decision-making process, as well as a preliminary identification of the major stakeholders to promote drivers. The study opens several opportunities for further research in the area of industrial energy efficiency.
Trung Ngo, N, Indraratna, B & Rujikiatkamjorn, C 2017, 'Closure to “Micromechanics-Based Investigation of Fouled Ballast Using Large-Scale Triaxial Tests and Discrete Element Modeling” by Ngoc Trung Ngo, Buddhima Indraratna, and Cholachat Rujikiatkamjorn', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 9, pp. 07017027-07017027.
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Tsai, Z-R, Chang, Y-Z, Zhang, H-W & Lin, C-T 2017, 'Relax the chaos-model-based human behavior by electrical stimulation therapy design', Computers in Human Behavior, vol. 67, pp. 151-160.
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© 2016 Elsevier Ltd The brain's electrical activity is chaotic and unpredictable yet has a hidden order that is attracted to a certain region. There are numerous fractal strange attractors in the brain that change as thinking processes vary. Further, the thinking processes change the human behaviors, especially in schizophrenia or internet addiction. The proposed chaos modelling and control theory may offer useful and relevant information on electrical stimulation therapy design to change this thinking processes through stimulating the brain's electrical activities. The experimental result of relaxing body from a lots of electrotherapy clinics helps mental disorders relax the thinking chaos in mind to replace their chaotic behaviors from the brain's electrical activities. This paper tries to explain the above claim in the aspect of the electrotherapy and control theory to suggest the control signal of electrotherapy based on an assumption for chaos model of patient and its control signals design according to multiple stabilization solutions. In the future, the electrical stimulation therapy will be proof in the Raphael Humanistic Clinic or the other electrotherapy clinics.
Tsai, Z-R, Zhang, H-W & Lin, C-T 2017, 'A study on an energy consumption model correlated to abnormal behavior by contactless method', Computers in Human Behavior, vol. 74, pp. 53-62.
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© 2017 Elsevier Ltd The anxiety disorders, major depressive illness, substance use disorder, false beliefs, confused thinking, reduced social engagement, reduced emotional expression, a lack of motivation, and refusing to accept the wearable medical devices have happened in schizophrenia patients. Of course, a methodological critique of wearable medical devices towards a behavior model is suffering from a refusing action of schizophrenia patient. Hence, a novel real-time and robust application on correlation of stereo vision and abnormal behavior in schizophrenia is proposed in this paper. A robust image process is key to further exploring the behavior of schizophrenia patient by contactless surveillance, and from any view of patient to predict the abnormal sign of patient. This abnormal sign of energies consumption may be caused by inappropriate prescription or other medical negligence. An indicator for this abnormal sign of single specific patient should be designed by comparing with the past normal records of this patient. This study aims to provide a predictive diagnosis of patient. This diagnosis is obtained by this indicator to inform the hospital workers to make the preventing medical treatment. It enhances the secure healthcare, and will be proof in the Chang Bing Show Chwan Memorial hospital since first author has completed training and submitted proof with Institutional Review Board (IRB) in Taiwan in the past.
Tu, C & Lee, JE-Y 2017, 'Enhancing quality factor by etch holes in piezoelectric-on-silicon lateral mode resonators', Sensors and Actuators A: Physical, vol. 259, pp. 144-151.
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Tu, C, Frank, A, Michael, S, Stegner, J, Stehr, U, Hein, M & Lee, JE-Y 2017, 'Applying laser Doppler vibrometry to probe anchor losses in MEMS AlN-on-Si contour mode resonators', Sensors and Actuators A: Physical, vol. 263, pp. 188-197.
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Tuan, HD, Ngo, DT & Tam, HHM 2017, 'Joint power allocation for MIMO-OFDM full-duplex relaying communications', EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 1, pp. 1-17.
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© 2017, The Author(s). In this paper, we address the problem of joint power allocation in a two-hop MIMO-OFDM network, where two full-duplex users communicate with each other via an amplify-and-forward relay. We consider a general model in which the full-duplex relay can forward the received message in either one-way or two-way mode. Our aim is to maximize the instantaneous end-to-end total throughput, subject to (i) the separate sum-power constraints at individual nodes or (ii) the joint sum-power constraint of the whole network. The formulated problems are large-scale nonconvex optimization problems, for which efficient and optimal solutions are currently not available. Using the successive convex approximation approach, we develop novel iterative algorithms of extremely low complexity which are especially suitable for large-scale computation. In each iteration, a simple closed-form solution is derived for the approximated convex program. The proposed algorithms guarantee to converge to at least a local optimum of the nonconvex problems. Numerical results verify that the devised solutions converge quickly, and that our optimal power allocation schemes significantly improve the throughput of MIMO-OFDM full-duplex one-way/two-way relaying over the conventional half-duplex relaying strategy.
Tuan, HD, Tam, HHM, Nguyen, HH, Duong, TQ & Poor, HV 2017, 'Superposition Signaling in Broadcast Interference Networks', IEEE Transactions on Communications, vol. 65, no. 11, pp. 4646-4656.
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© 1972-2012 IEEE. It is known that superposition signaling in Gaussian interference networks is capable of improving the achievable rate region. However, the problem of maximizing the rate gain offered by superposition signaling is computationally prohibitive, even in the simplest case of two-user single-input single-output interference networks. This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks. The problem of maximizing either the sum rate or the minimal user's rate under superposition signaling and dirty paper coding is solved by a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution. Numerical results demonstrate the substantial performance advantage of the proposed approach.
Tuyen Le, A, Tran, LC & Huang, X 2017, 'Cyclostationary Analysis of Analog Least Mean Square Loop for Self-Interference Cancellation in In-Band Full-Duplex Systems', IEEE Communications Letters, vol. 21, no. 12, pp. 2738-2741.
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© 2017 IEEE. Analog least mean square (ALMS) loop is a promising mechanism to suppress self-interference (SI) in an in-band full-duplex (IBFD) system. In this letter, a general solution for the weighting error function is derived to investigate the performance of the ALMS loop employed in any IBFD system. The solution is then applied to IBFD systems with single carrier and multicarrier signaling. Due to the cyclostationary property of the transmitted signal, the weighting error function in the multicarrier system varies more significantly than in the single carrier. Therefore, if the ALMS loop can perfectly mimic the SI channel, SI in the single carrier system can be suppressed to a much smaller level than that in the multi-carrier counterpart.
Uchiyama, M, Satoh, K, McKenzie, TG, Fu, Q, Qiao, GG & Kamigaito, M 2017, 'Diverse approaches to star polymers via cationic and radical RAFT cross-linking reactions using mechanistic transformation', Polymer Chemistry, vol. 8, no. 38, pp. 5972-5981.
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Core cross-linked star polymers were synthesizedviacationic RAFT polymerization and three different approaches in combination with a radical RAFT mechanism.
Uddin, MT, Mahmood, AH, Kamal, MRI, Yashin, SM & Zihan, ZUA 2017, 'Effects of maximum size of brick aggregate on properties of concrete', Construction and Building Materials, vol. 134, pp. 713-726.
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Ulapane, N, Alempijevic, A, Vidal Calleja, T & Valls Miro, J 2017, 'Pulsed Eddy Current Sensing for Critical Pipe Condition Assessment', Sensors, vol. 17, no. 10, pp. 2208-2208.
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Pulsed Eddy Current (PEC) sensing is used for Non-Destructive Evaluation (NDE) of the structural integrity of metallic structures in the aircraft, railway, oil and gas sectors. Urban water utilities also have extensive large ferromagnetic structures in the form of critical pressure pipe systems made of grey cast iron, ductile cast iron and mild steel. The associated material properties render NDE of these pipes by means of electromagnetic sensing a necessity. In recent years PEC sensing has established itself as a state-of-the-art NDE technique in the critical water pipe sector. This paper presents advancements to PEC inspection in view of the specific information demanded from water utilities along with the challenges encountered in this sector. Operating principles of the sensor architecture suitable for application on critical pipes are presented with the associated sensor design and calibration strategy. A Gaussian process-based approach is applied to model a functional relationship between a PEC signal feature and critical pipe wall thickness. A case study demonstrates the sensor’s behaviour on a grey cast iron pipe and discusses the implications of the observed results and challenges relating to this application.
Unanue, IJ, Borzeshi, EZ & Piccardi, M 2017, 'Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition', Journal of Biomedical Informatics, vol. 76, no. December 2017, pp. 102-109.
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Background. Previous state-of-the-art systems on Drug Name Recognition (DNR)and Clinical Concept Extraction (CCE) have focused on a combination of text'feature engineering' and conventional machine learning algorithms such asconditional random fields and support vector machines. However, developing goodfeatures is inherently heavily time-consuming. Conversely, more modern machinelearning approaches such as recurrent neural networks (RNNs) have provedcapable of automatically learning effective features from either randomassignments or automated word 'embeddings'. Objectives. (i) To create a highlyaccurate DNR and CCE system that avoids conventional, time-consuming featureengineering. (ii) To create richer, more specialized word embeddings by usinghealth domain datasets such as MIMIC-III. (iii) To evaluate our systems overthree contemporary datasets. Methods. Two deep learning methods, namely theBidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF modelis set as the baseline to compare the deep learning systems to a traditionalmachine learning approach. The same features are used for all the models.Results. We have obtained the best results with the Bidirectional LSTM-CRFmodel, which has outperformed all previously proposed systems. The specializedembeddings have helped to cover unusual words in DDI-DrugBank and DDI-MedLine,but not in the 2010 i2b2/VA IRB Revision dataset. Conclusion. We present astate-of-the-art system for DNR and CCE. Automated word embeddings has allowedus to avoid costly feature engineering and achieve higher accuracy.Nevertheless, the embeddings need to be retrained over datasets that areadequate for the domain, in order to adequately cover the domain-specificvocabulary.
Unnikrishnan, A, Papaemmanuil, E, Beck, D, Deshpande, NP, Verma, A, Kumari, A, Woll, PS, Richards, LA, Knezevic, K, Chandrakanthan, V, Thoms, JAI, Tursky, ML, Huang, Y, Ali, Z, Olivier, J, Galbraith, S, Kulasekararaj, AG, Tobiasson, M, Karimi, M, Pellagatti, A, Wilson, SR, Lindeman, R, Young, B, Ramakrishna, R, Arthur, C, Stark, R, Crispin, P, Curnow, J, Warburton, P, Roncolato, F, Boultwood, J, Lynch, K, Jacobsen, SEW, Mufti, GJ, Hellstrom-Lindberg, E, Wilkins, MR, MacKenzie, KL, Wong, JWH, Campbell, PJ & Pimanda, JE 2017, 'Integrative Genomics Identifies the Molecular Basis of Resistance to Azacitidine Therapy in Myelodysplastic Syndromes', Cell Reports, vol. 20, no. 3, pp. 572-585.
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© 2017 The Author(s) Myelodysplastic syndromes and chronic myelomonocytic leukemia are blood disorders characterized by ineffective hematopoiesis and progressive marrow failure that can transform into acute leukemia. The DNA methyltransferase inhibitor 5-azacytidine (AZA) is the most effective pharmacological option, but only ∼50% of patients respond. A response only manifests after many months of treatment and is transient. The reasons underlying AZA resistance are unknown, and few alternatives exist for non-responders. Here, we show that AZA responders have more hematopoietic progenitor cells (HPCs) in the cell cycle. Non-responder HPC quiescence is mediated by integrin α5 (ITGA5) signaling and their hematopoietic potential improved by combining AZA with an ITGA5 inhibitor. AZA response is associated with the induction of an inflammatory response in HPCs in vivo. By molecular bar coding and tracking individual clones, we found that, although AZA alters the sub-clonal contribution to different lineages, founder clones are not eliminated and continue to drive hematopoiesis even in complete responders.
Uzair, M & Dony, RD 2017, 'Estimating just‐noticeable distortion for images/videos in pixel domain', IET Image Processing, vol. 11, no. 8, pp. 559-567.
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Existing pixel‐based just noticeable distortion (JND) models only take into account luminance adaptation and texture masking (TM). Similarly, existing discrete cosine transform (DCT) based models do not take into account foveal vision effects and do not estimate TM efficiently. As human visual system (HVS) is not sensitive to distortion below the JND threshold, estimation of the perceptual visibility threshold is widely used in digital and video processing applications. The authors propose a comprehensive and efficient pixel‐based JND model incorporating all major factors which contribute to the JND estimation. The evaluation of contrast masking (CM) is done by distinguishing the edge and TM with respect to the entropy masking properties of the HVS. Similarly, the foveal vision effects are also taken into account for the comprehensive estimation of contrast sensitivity function (CSF). Hence, the proposed pixel‐based JND model incorporates the spatio‐temporal CSF, foveal vision effects, influence of eye‐movement, luminance adaptation and CM to be more consistent with human perception. The incorporation of these important factors makes the proposed model the most comprehensive and efficient in the current literature. Psychophysical experiments were performed to test the proposed model. The results show the proposed model comprehensively outperforms other existing models proving its efficiency.
Vahedian, A, Shrestha, R & Crews, K 2017, 'Effective bond length and bond behaviour of FRP externally bonded to timber', Construction and Building Materials, vol. 151, pp. 742-754.
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Despite a large number of studies on estimating the effective bond length from the characteristics of the component materials, key parameters governing the effective bond length for FRP-to-timber joint have not been suggested by any of the current Codes and developed theories to date mostly cover FRP-to-concrete joints. Also, most theoretical bond strength models have been derived based on effective bond length. Therefore, to achieve a satisfactory bonded joint, the effectiveness of bond length is required to be accurately considered. This research study investigates 136 FRP-to-timber joints subjected to pull-out tests in order to determine the stress and strain distribution profiles along the interface and subsequently analyses the results to undertake direct measurement of the effective bond length. In addition, a modified test set up has been developed and is presented. A novel theoretical model has been established through regression analysis of bond length data and accordingly a new predictive model for effective bond length for FRP-to-timber joints has been developed. A comparative analysis between the results of the experimental pull-out tests results and those predicted from the analytical model indicates a satisfactory correlation is achieved between measured and predicted effective bond length, verifying the validity of the new model.
Vakhshouri, B & Nejadi, S 2017, 'Compressive strength and mixture proportions of self-compacting light weight concrete', Computers and Concrete, vol. 19, no. 5, pp. 555-566.
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Copyright © 2017 Techno-Press, Ltd. Recently some efforts have been performed to combine the advantages of light-weight and self-compacting concrete in one package called Light-Weight Self-Compacting Concrete (LWSCC). Accurate prediction of hardened properties from fresh state characteristics is vital in design of concrete structures. Considering the lack of references in mixture design of LWSCC, investigating the proper mixture components and their effects on mechanical properties of LWSCC can lead to a reliable basis for its application in construction industry. This study utilizes wide range of existing data of LWSCC mixtures to study the individual and combined effects of the components on the compressive strength. From sensitivity of compressive strength to the proportions and interaction of the components, two equations are proposed to estimate the LWSCC compressive strength. Predicted values of the equations are in good agreement with the experimental data. Application of lightweight aggregate to reduce the density of LWSCC may bring some mixing problems like segregation. Reaching a higher strength by lowered density is a challenging problem that is investigated as well. The results show that, the compressive strength can be improved by increasing the of mixture density of LWSCC, especially in the range of density under 2000 Kg/m3.
Vakhshouri, B & Nejadi, S 2017, 'Instantaneous deflection of light-weight concrete slabs', Frontiers of Structural and Civil Engineering, vol. 11, no. 4, pp. 412-423.
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© 2017, Higher Education Press and Springer-Verlag GmbH Germany. Construction loading before the age of 28 d can have the most significant effects on the slabs, especially for multi-story structures. The changing properties of the young concrete complicate the prediction of serviceability design requirements also. An experimental investigation is performed on four simply supported Light-Weight Concrete (LWC) one-way slabs subjected to immediate loading at 14 d. Effects of aggregate type, loading levels and cracking moment together with the influences of ultimate moment capacity and service moment on the instantaneous deflection of slabs are studied. Comparison of the obtained results with predictions of existing models in the literature shows considerable differences between the recorded and estimated instantaneous deflection of LWC slabs. Based on sensitivity analysis of the effective parameters, a new equation is proposed and verified to predict the instantaneous deflection of LWC slabs subjected to loading at the age of 14 d.
Vakhshouri, B & Nejadi, S 2017, 'Sensitivity of Compressive Strength of Self-Compacting Concrete to Mixture Proportions and Slump Flow in ANFIS Models', International Journal of Structural and Civil Engineering Research, pp. 57-64.
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Valdés-Mora, F, Gould, CM, Colino-Sanguino, Y, Qu, W, Song, JZ, Taylor, KM, Buske, FA, Statham, AL, Nair, SS, Armstrong, NJ, Kench, JG, Lee, KML, Horvath, LG, Qiu, M, Ilinykh, A, Yeo-Teh, NS, Gallego-Ortega, D, Stirzaker, C & Clark, SJ 2017, 'Acetylated histone variant H2A.Z is involved in the activation of neo-enhancers in prostate cancer', Nature Communications, vol. 8, no. 1.
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AbstractAcetylation of the histone variant H2A.Z (H2A.Zac) occurs at active promoters and is associated with oncogene activation in prostate cancer, but its role in enhancer function is still poorly understood. Here we show that H2A.Zac containing nucleosomes are commonly redistributed to neo-enhancers in cancer resulting in a concomitant gain of chromatin accessibility and ectopic gene expression. Notably incorporation of acetylated H2A.Z nucleosomes is a pre-requisite for activation of Androgen receptor (AR) associated enhancers. H2A.Zac nucleosome occupancy is rapidly remodeled to flank the AR sites to initiate the formation of nucleosome-free regions and the production of AR-enhancer RNAs upon androgen treatment. Remarkably higher levels of global H2A.Zac correlate with poorer prognosis. Altogether these data demonstrate the novel contribution of H2A.Zac in activation of newly formed enhancers in prostate cancer.
Valdés-Mora, F, Locke, WJ, Bandrés, E, Gallego-Ortega, D, Cejas, P, García-Cabezas, MA, Colino-Sanguino, Y, Feliú, J, del Pulgar, TG & Lacal, JC 2017, 'Clinical relevance of the transcriptional signature regulated by CDC42 in colorectal cancer', Oncotarget, vol. 8, no. 16, pp. 26755-26770.
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Valenzuela Fernández, L, Merigó, JM & Nicolas, C 2017, 'Universidades influyentes en investigación sobre orientación al mercado. Una visión general entre 1990 y 2014', Estudios Gerenciales, vol. 33, no. 144, pp. 221-227.
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El objetivo de este estudio es identificar las universidades más productivas e influyentes para la comunidad científica sobre el tópico de orientación al mercado. Lo anterior se realiza principalmente a través de indicadores bibliométricos —como el índice h— y la relación total citas/total artículos para el periodo 1990-2014, a partir de la información encontrada en Web of Science. Dentro de los hallazgos se destaca el interés de la comunidad científica en esta temática, lo que se ve reflejado en el aumento considerado en la contribución que se ha generado durante los últimos 25 años. Además, se determina un ranking de las 30 universidades más influyentes, junto con un ranking que relaciona universidades y revistas con mayor influencia en temas de orientación al mercado.
Valenzuela, LM, Merigó, JM, Johnston, WJ, Nicolas, C & Jaramillo, JF 2017, 'Thirty years of the Journal of Business & Industrial Marketing: a bibliometric analysis', Journal of Business & Industrial Marketing, vol. 32, no. 1, pp. 1-17.
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PurposeThe aim of this study is to reveal the contribution that Journal of Business & Industrial Marketing has to scientific research and its most influential thematic work in B-to-B since its beginning in 1986 until 2015, in commemoration of the 30th anniversary.Design/methodology/approachThe paper begins with a qualitative introduction: the emergence of the magazine, its origins, editorial and positioning. Subsequently, it is based on bibliometric methodologies to develop quantitative analysis. The distribution of annual publications is analyzed, the most cited papers, the keywords that are mostly used, the influence on the publishing industry and authors, universities and the countries that have the most publications.FindingsThe predominant role of the USA at all levels is highlighted. It also highlights the presence (given its size and population) of the countries of Northern Europe. There is great interest in appreciating the evolution of the number of publications that are always increasing which demonstrates the growing and sustained interest in these types of articles, with certain times of retreat (often coincide with economic crisis).Research limitations/implicationsThe Scopus database gives one unit to each author, university or country involved in the paper, without distinguishing whether it was one or more authors in the study. Therefore, this may bring some deviations in the analysis. However, the study considers some figures with fractional counting to partially solve these limitations.
Van Ngoc, P, Turner, B, Huang, J & Kelly, R 2017, 'Experimental study on the durability of soil-cement columns in coastal areas', Geotechnical Engineering, vol. 48, no. 4, pp. 138-143.
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Deep soil mixing is one of the most commonly used ground improvement techniques. With high sulphate content in soil and seawater, stabilised soil in coastal areas can deteriorate due to sulphate attack. In this research, the degradation in strength of cement treated soil exposed to synthetic seawater is measured by uniaxial compression and needle penetration testing. Three exposure conditions, namely 100% seawater, 200% seawater and sealed condition (control samples), were used to measure the deterioration level due to the effect of sulphate. In addition, the extent of the portlandite consumption was also measured by Thermogravimetric Analysis which reflects the calcium distribution in the soil-cement columns. The test results show that the deterioration occurs deeper and faster in higher seawater environments. Furthermore, in contact with increasing sulphate concentration, the deterioration shows a close relation with calcium distribution.
Van Nguyen, Q, Fatahi, B & Hokmabadi, AS 2017, 'Influence of Size and Load-Bearing Mechanism of Piles on Seismic Performance of Buildings Considering Soil–Pile–Structure Interaction', International Journal of Geomechanics, vol. 17, no. 7, pp. 04017007-04017007.
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© 2017 American Society of Civil Engineers. Pile foundations are usually used to transmit foundation loads through soil strata of low bearing capacity to deeper soil or rock strata with a higher bearing capacity and stiffness. The type and size of a pile foundation that supports midrise buildings in high-risk seismic zones can alter the dynamic characteristics of the soil-pile-foundation system during an earthquake due to soil-structure interaction. To investigate these phenomena, a 15-story moment-resisting frame sitting on differently sized end-bearing and floating pile foundations was simulated numerically. The present paper describes a numerical modeling technique for the simulation of complex seismic soil-pile-structure interaction phenomena. By adopting a method of direct calculation, the numerical model can perform a fully nonlinear time history dynamic analysis to realistically simulate the dynamic behavior of soil, pile foundations, and structure under seismic excitations. This three-dimensional (3D) numerical model accounts for the nonlinear behavior of the soil medium, the piles, and the structural elements. Results show that the type and size of the pile elements influence the dynamic characteristics and seismic response of the building due to interaction between the soil, pile foundations, and the structure. The findings of this study can help engineers select the correct size and type of pile foundation while considering the seismic performance of buildings sitting on soft soil and aim at optimizing their design.
Vanhauwaert, S, Durinck, K, Janssens, E, Dewyn, G, Wilde, BD, Laureys, G, Carter, D, Belamy, C, Preter, KD, Vanneste, C & Speleman, F 2017, 'Abstract 4886: The BRIP1 DNA helicase is a 17q dosage sensitive cooperative driver in neuroblastoma', Cancer Research, vol. 77, no. 13_Supplement, pp. 4886-4886.
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Abstract Neuroblastoma (NB) is an aggressive pediatric tumor arising from sympathetic neuronal progenitors. NBs have a low mutation burden while copy number alterations are highly recurrent: MYCN amplification is present in half of high risk tumors often accompanied by 1p deletions while MYCN non-amplified aggressive NB frequently exhibit 11q deletions. Remarkably, both high risk groups show almost invariably chromosome 17q gain and we also reported that the mouse syntenic chromosome 11 region was gained during MYCN driven tumor formation. We propose that one or more dosage sensitive genes on 17q act as cooperative drivers during NB development. Using an integrated bioinformatics analysis, we identified several candidate drivers implicated in DNA repair including BRIP1, also known as FANCJ and located on 17q23.2. BRIP1 acts as a DNA helicase in unwinding of stable G-quadruplex (G4) structures in single stranded DNA during replication ensuring timely progression through S-phase. We show that BRIP1 knock down causes increased replicative stress in MYCN overexpressing NB cells as evidenced as shown by increased RPA32 levels and reduced replication fork velocity. Overexpression of BRIP1 in dβh-MYCN-eGFP transgenic zebrafish caused accelerated tumor formation supporting its role as cooperative driver gene. Gene expression profiling after BRIP1 knock down confirmed enrichment for gene sets implicated in DNA replication and repair and are indicative for perturbation of G4 enriched genes. We also identified further additional 17q dosage sensitive genes implicated in replication fork dynamics including BRCA1, BRCA2, EME1 and TOP2A. We propose that 17q gain acts as an amplifier for expression of multiple genes implicated in control of replicative stress and replication fork dynamics. Finally, we explored whether this replicative stress resistance phenotype could represent a novel therapeutic vulnerability for NB cel...
Vennin, C, Chin, VT, Warren, SC, Lucas, MC, Herrmann, D, Magenau, A, Melenec, P, Walters, SN, del Monte-Nieto, G, Conway, JRW, Nobis, M, Allam, AH, McCloy, RA, Currey, N, Pinese, M, Boulghourjian, A, Zaratzian, A, Adam, AAS, Heu, C, Nagrial, AM, Chou, A, Steinmann, A, Drury, A, Froio, D, Giry-Laterriere, M, Harris, NLE, Phan, T, Jain, R, Weninger, W, McGhee, EJ, Whan, R, Johns, AL, Samra, JS, Chantrill, L, Gill, AJ, Kohonen-Corish, M, Harvey, RP, Biankin, AV, Evans, TRJ, Anderson, KI, Grey, ST, Ormandy, CJ, Gallego-Ortega, D, Wang, Y, Samuel, MS, Sansom, OJ, Burgess, A, Cox, TR, Morton, JP, Pajic, M & Timpson, P 2017, 'Transient tissue priming via ROCK inhibition uncouples pancreatic cancer progression, sensitivity to chemotherapy, and metastasis', Science Translational Medicine, vol. 9, no. 384.
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Fine-tuned manipulation of tumor tension and vasculature enhances response to chemotherapy and impairs metastatic spread in pancreatic cancer.
Vessalas, K, Sirivivatnanon, V & Baweja, D 2017, 'Influence of Permeability-Reducing Admixtures on Water Penetration in Concrete', ACI Materials Journal, vol. 114, no. 6, pp. 911-922.
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Copyright © 2017, American Concrete Institute. All rights reserved. An experimental investigation was carried out on concrete into the effectiveness of integral permeability-reducing admixtures as possible alternatives to the traditional external waterproofers. The efficiency of hydrophobic water repellents and crystalline pore blockers were evaluated in concretes incorporating fixed water-cementitious materials ratio (w/cm) and different cementitious material types covering OPC, fly ash, and granulated blast-furnace slag. Three different test methods were employed to evaluate the water penetration resistance of concrete. To isolate the benefits that are achieved by varying the mixture design parameters, statistical factorial analysis of variances was carried out to discover the significance of each variable. Results indicated that the effect of w/cm and cementitious material is more pronounced compared to the addition of permeability-reducing admixtures. It was also demonstrated that the admixtures can be effective in reducing water penetration; however, their effect is varied in different mixtures. Caution must be exercised when using such admixtures in different concrete mixtures.
Vieira, GC, Chockalingam, S, Melegh, Z, Greenhough, A, Malik, S, Szemes, M, Park, JH, Kaidi, A, Zhou, L, Catchpoole, D, Morgan, R, Bates, DO, Gabb, PJ & Malik, K 2017, 'Correction: LGR5 regulates pro-survival MEK/ERK and proliferative Wnt/β-catenin signalling in neuroblastoma', Oncotarget, vol. 8, no. 19, pp. 32381-32381.
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Present: The originally supplied Figure 5 contains duplicate total-ERK panels. Correct: The proper Figure 5 appears below. The authors sincerely apologize for this error.
Vongphachanh, S, Das Gupta, A, Milne-Home, W, Ball, JE & Pavelic, P 2017, 'Hydrogeological reconnaissance of Sukhuma district, Champasak Province, Southern Laos', Journal of Hydrology New Zealand, vol. 56, no. 2, pp. 79-96.
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Sparse hydrogeological data is a significant limitation to the study of groundwater in many areas. The objective of this study was to assess the hydrogeology in Sukhuma District of Champasak Province in Southern Laos where such a limitation occurs. The connection between surface water and groundwater was assessed by comparing groundwater levels and river bed elevations. Groundwater recharge was estimated by the water table fluctuation method. The feasibility of remote sensing to address data limitations for the future study of groundwater in the region was also investigated by comparing the Mekong River flow and rainfall data with the Equivalent Water Height derived from the Gravity Recovery and Climate Experiment; soil moisture data obtained from the Global Land Data Assimilation System was also compared with rainfall and groundwater levels in Sukhuma District. The results show that some parts of Khamouan River bed are disconnected from the water table during the dry season, whereas the river bed is fully connected to the water table during the wet season. However, in the Pheung River, which flows into the Khamouan River upstream of the river gauge, the groundwater level is fully disconnected from the river bed in the dry season and partially connected in the wet season. Groundwater recharge estimates vary according to the specific yield values used for the aquifer. The comparison between in-situ hydrological measurement and remote sensing data provides insights into the general hydrogeological conditions. The comparison also provides useful information for future studies of the hydrogeology in Sukhuma District and Southern Laos, where field observation data are sparse, to support sustainable groundwater development in the region.
Vu, TM, Trinh, VT, Doan, DP, Van, HT, Nguyen, TV, Vigneswaran, S & Ngo, HH 2017, 'Removing ammonium from water using modified corncob-biochar', Science of The Total Environment, vol. 579, pp. 612-619.
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© 2016 Elsevier B.V. Ammonium pollution in groundwater and surface water is of major concern in many parts of the world due to the danger it poses to the environment and people's health. This study focuses on the development of a low cost adsorbent, specifically a modified biochar prepared from corncob. Evaluated here is the efficiency of this new material for removing ammonium from synthetic water (ammonium concentration from 10 to 100 mg/L). The characteristics of the modified biochar were determined by Brunauer-Emmett-Teller (BET) test, Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM). It was found that ammonium adsorption on modified biochar strongly depended on pH. Adsorption kinetics of NH4+-N using modified biochar followed the pseudo-second order kinetic model. Both Langmuir and Sips adsorption isotherm models could simulate well the adsorption behavior of ammonium on modificated biochar. The highest adsorption capacity of 22.6 mg NH4+-N/g modified biochar was obtained when the biochar was modified by soaking it in HNO3 6 M and NaOH 0.3 M for 8 h and 24 h, respectively. The high adsorption capacity of the modified biochar suggested that it is a promising adsorbent for NH4+-N remediation from water.
Walsh, L, Bluff, A & Johnston, A 2017, 'Water, image, gesture and sound: composing and performing an interactive audiovisual work', Digital Creativity, vol. 28, no. 3, pp. 177-195.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. Performing and composing for interactive audiovisual system presents many challenges to the performer. Working with visual, sonic and gestural components requires new skills and new ways of thinking about performance. However, there are few studies that focus on performer experience with interactive systems. We present the work Blue Space for oboe and interactive audiovisual system, highlighting the evolving process of the collaborative development of the work. We consider how musical and technical demands interact in this process, and outline the challenges of performing with interactive systems. Using the development of Blue Space as a self-reflective case study, we examine the role of gestures in interactive audiovisual works and identify new modes of performance.
Wang, C, Gao, B, Zhao, P, Li, R, Yue, Q & Shon, HK 2017, 'Exploration of polyepoxysuccinic acid as a novel draw solution in the forward osmosis process', RSC Advances, vol. 7, no. 49, pp. 30687-30698.
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Polyepoxysuccinic acid (PESA) is a green corrosion scale inhibitor.
Wang, C, Ni, W, Sun, X, Wang, L, Wang, C & Jin, K 2017, 'Relaxor‐like behaviors in Na1/2Bi1/2Cu3Ti4O12 ceramics', Journal of the American Ceramic Society, vol. 100, no. 5, pp. 2016-2023.
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AbstractDielectric properties of Na1/2Bi1/2Cu3Ti4O12 ceramics were evaluated over the temperature range 300‐720 K. Two relaxor‐like dielectric anomalies were found. The low‐temperature anomaly was confirmed to be an oxygen‐vacancy‐related relaxation process. It is a pseudo‐relaxor behavior caused by a bulk relaxation and a Maxwell‐Wagner relaxation. The high‐temperature one was evidenced to be an electric ferroelectric phase‐transition process resulting from the oxygen‐vacancy ordering.
Wang, D, Fu, Q, Xu, Q, Liu, Y, Hao Ngo, H, Yang, Q, Zeng, G, Li, X & Ni, B-J 2017, 'Free nitrous acid-based nitrifying sludge treatment in a two-sludge system enhances nutrient removal from low-carbon wastewater', Bioresource Technology, vol. 244, no. Part 1, pp. 920-928.
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© 2017 Elsevier Ltd A new method to enhance nutrient removal from low carbon-wastewater was developed. The method consists of a two-sludge system (i.e., an anaerobic-anoxic-oxic reactor coupled to a nitrifying reactor (N-SBR)) and a nitrifying-sludge treatment unit using free nitrous acid (FNA). Initially, 65.1 ± 2.9% in total nitrogen removal and 69.6 ± 3.4% in phosphate removal were obtained without nitrite accumulation. When 1/16 of the nitrifying sludge was daily treated with FNA at 1.1 mg N/L for 24 h, ∼28.5% of nitrite was accumulated in the N-SBR, and total nitrogen and phosphate removal increased to 72.4 ± 3.2% and 76.7 ± 2.9%, respectively. About 67.8% of nitrite was accumulated at 1.9 mg N/L FNA, resulting in 82.9 ± 3.8% in total nitrogen removal and 87.9 ± 3.5% in phosphate removal. Fluorescence in-situ hybridization analysis showed that FNA treatment reduced the abundance of nitrite oxidizing bacteria (NOB), especially that of Nitrospira sp.
Wang, D, Liu, Y, Ngo, HH, Zhang, C, Yang, Q, Peng, L, He, D, Zeng, G, Li, X & Ni, B-J 2017, 'Approach of describing dynamic production of volatile fatty acids from sludge alkaline fermentation', Bioresource Technology, vol. 238, pp. 343-351.
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© 2017 Elsevier Ltd In this work, a mathematical model was developed to describe the dynamics of fermentation products in sludge alkaline fermentation systems for the first time. In this model, the impacts of alkaline fermentation on sludge disintegration, hydrolysis, acidogenesis, acetogenesis, and methanogenesis processes are specifically considered for describing the high-level formation of fermentation products. The model proposed successfully reproduced the experimental data obtained from five independent sludge alkaline fermentation studies. The modeling results showed that alkaline fermentation largely facilitated the disintegration, acidogenesis, and acetogenesis processes and severely inhibited methanogenesis process. With the pH increase from 7.0 to 10.0, the disintegration, acidogenesis, and acetogenesis processes respectively increased by 53%, 1030%, and 30% while methane production decreased by 3800%. However, no substantial effect on hydrolysis process was found. The model also indicated that the pathway of acetoclastic methanogenesis was more severely inhibited by alkaline condition than that of hydrogentrophic methanogenesis.
Wang, D, Wang, Y, Liu, Y, Ngo, HH, Lian, Y, Zhao, J, Chen, F, Yang, Q, Zeng, G & Li, X 2017, 'Is denitrifying anaerobic methane oxidation-centered technologies a solution for the sustainable operation of wastewater treatment Plants?', Bioresource Technology, vol. 234, pp. 456-465.
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With the world's increasing energy crisis, society is growingly considered that the operation of wastewater treatment plants (WWTPs) should be shifted in sustainable paradigms with low energy input, or energy-neutral, or even energy output. There is a lack of critical thinking on whether and how new paradigms can be implemented in WWTPs based on the conventional process. The denitrifying anaerobic methane oxidation (DAMO) process, which uses methane and nitrate (or nitrite) as electron donor and acceptor, respectively, has recently been discovered. Based on critical analyses of this process, DAMO-centered technologies can be considered as a solution for sustainable operation of WWTPs. In this review, a possible strategy with DAMO-centered technologies was outlined and illustrated how this applies for the existing WWTPs energy-saving and newly designed WWTPs energy-neutral (or even energy-producing) towards sustainable operations.
Wang, H, Nguyen, DN, Dutkiewicz, E, Fang, G & Mueck, MD 2017, 'Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework', IEEE Transactions on Cognitive Communications and Networking, vol. 3, no. 3, pp. 390-403.
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© 2015 IEEE. Auction-based spectrum sharing is a promising solution to improve the spectrum utilization in 5G networks. Along with the spatial reuse, we observe that the ability to adjust the coverage of a spectrum bidder can provide room to itself for further negotiation while auctioning. In this paper, we propose a novel economic tool, size-negotiable auction mechanism (SNAM), which provides a hybrid solution between auction and negotiation for multi-buyers sharing spectrum chunks from a common database. Unlike existing auction-based spectrum sharing models, each bidder of the SNAM submits its bid for using the spectrum per unit space and a set of coverage ranges over which the bidder is willing to pay for the spectrum. The auctioneer then coordinates the interference areas (or coverage negotiation) to ensure no two winners interfere with each other while aiming to maximize the auction's total coverage area or revenue. In this scenario, the undirected graph used by existing auction mechanisms fails to model the interference among bidders. Instead, we construct a mixed interference graph and prove that SNAM's auctioning on the mixed graph is truthful and individually rational. Simulation results show that, compared with existing auction approaches, the proposed SNAM dramatically improves the spatial efficiency, hence leads to significantly higher seller revenue and buyer satisfaction under various setups. Thanks to its low complexity and low overhead, SNAM can target fine timescale trading (in minutes or hours) with a large number of bidders and requested coverages.
Wang, H, Wu, C, Zhang, F, Fang, Q, Xiang, H, Li, P, Li, Z, Zhou, Y, Zhang, Y & Li, J 2017, 'Experimental study of large-sized concrete filled steel tube columns under blast load', Construction and Building Materials, vol. 134, pp. 131-141.
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© 2016 This paper investigates blast resistance and residual strength of concrete-filled steel tube (CFST) columns under close-range blast loads. A total of 8 CFST columns, including 4 with circular cross sections and 4 with square cross sections, were tested under close-range blasts. LVDTs were used to record displacement histories and pressure sensors were used to measure pressure histories. The influence of explosive charge weight, steel tube thickness and cross section geometry on dynamic response of CFST columns was analyzed and failure modes of CFST columns were also investigated. Following the blast tests, an experimental study was conducted to investigate residual strength of blast-damaged CFST columns. It was found that the CFST columns were still able to retain a large portion of their axial load capacities even after close-range blast events.
Wang, H, Wu, J, Pan, S, Zhang, P & Chen, L 2017, 'Towards large-scale social networks with online diffusion provenance detection', Computer Networks, vol. 114, pp. 154-166.
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© 2016 Elsevier B.V. In this paper we study a new problem of online discovering diffusion provenances in large networks. Existing work on network diffusion provenance identification focuses on offline learning where data collected from network detectors are static and a snapshot of the network is available before learning. However, an offline learning model does not meet the need for early warning, real-time awareness, or a real-time response to malicious information spreading in networks. To this end, we propose an online regression model for real-time diffusion provenance identification. Specifically, we first use offline collected network cascades to infer the edge transmission weights, and then use an online l1 non-convex regression model as the identification model. The proposed methods are empirically evaluated on both synthetic and real-world networks. Experimental results demonstrate the effectiveness of the proposed model.
Wang, H, Zhang, P, Zhu, X, Tsang, IW-H, Chen, L, Zhang, C & Wu, X 2017, 'Incremental Subgraph Feature Selection for Graph Classification', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 1, pp. 128-142.
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Graph classification is an important tool for analyzing data with structure dependency, where subgraphs are often used as features for learning. In reality, the dimension of the subgraphs crucially depends on the threshold setting of the frequency support parameter, and the number may become extremely large. As a result, subgraphs may be incrementally discovered to form a feature stream and require the underlying graph classifier to effectively discover representative subgraph features from the subgraph feature stream. In this paper, we propose a primal-dual incremental subgraph feature selection algorithm (ISF) based on a max-margin graph classifier. The ISF algorithm constructs a sequence of solutions that are both primal and dual feasible. Each primal-dual pair shrinks the dual gap and renders a better solution for the optimal subgraph feature set. To avoid bias of ISF algorithm on short-pattern subgraph features, we present a new incremental subgraph join feature selection algorithm (ISJF) by forcing graph classifiers to join short-pattern subgraphs and generate long-pattern subgraph features. We evaluate the performance of the proposed models on both synthetic networks and real-world social network data sets. Experimental results demonstrate the effectiveness of the proposed methods.
Wang, J, Merigó, JM & Jin, L 2017, 'S-H OWA Operators with Moment Measure', International Journal of Intelligent Systems, vol. 32, no. 1, pp. 51-66.
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© 2016 Wiley Periodicals, Inc. Step-like or Hurwicz-like ordered weighted averaging (OWA) (S-H OWA) operators connect two fundamental OWA operators, step OWA operators and Hurwicz OWA operators. S-H OWA operators also generalize them and some other well-know OWA operators such as median and centered OWA operators. Generally, there are two types of determination methods for S-H OWA operators: One is from the motivation of some existed mathematical results; the other is by a set of “nonstrict” definitions and often via some intermediate elements. For the second type, in this study we define two sets of strict definitions for Hurwitz/step degree, which are more effective and necessary for theoretical studies and practical usages. Both sets of definitions are useful in different situations. In addition, they are based on the same concept moment of OWA operators proposed in this study, and therefore they become identical in limit forms. However, the Hurwicz/step degree (HD/SD) puts more concerns on its numerical measure and physical meaning, whereas the relative Hurwicz/step degree (rHD/rSD), still being accurate numerically, sometimes is more reasonable intuitively and has larger potential in further studies and practical applications.
Wang, J, Pathak, N, Chekli, L, Phuntsho, S, Kim, Y, Li, D & Shon, H 2017, 'Performance of a Novel Fertilizer-Drawn Forward Osmosis Aerobic Membrane Bioreactor (FDFO-MBR): Mitigating Salinity Build-Up by Integrating Microfiltration', Water, vol. 9, no. 1, pp. 21-21.
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In this paper, three different fertilizer draw solutions were tested in a novel forward osmosis-microfiltration aerobic membrane bioreactor (MF-FDFO-MBR) hybrid system and their performance were evaluated in terms of water flux and reverse salt diffusion. Results were also compared with a standard solution. Results showed that ammonium sulfate is the most suitable fertilizer for this hybrid system since it has a relatively high water flux (6.85 LMH) with a comparatively low reverse salt flux (3.02 gMH). The performance of the process was also studied by investigating different process parameters: draw solution concentration, FO draw solution flow rate and MF imposed flux. It was found that the optimal conditions for this hybrid system were: draw solution concentration of 1 M, FO draw solution flow rate of 200 mL/min and MF imposed flux of 10 LMH. The salt accumulation increased from 834 to 5400 μS/cm during the first four weeks but after integrating MF, the salinity dropped significantly from 5400 to 1100 μS/cm suggesting that MF is efficient in mitigating the salinity build up inside the reactor. This study demonstrated that the integration of the MF membrane could effectively control the salinity and enhance the stable FO flux in the OMBR.
Wang, J, Yang, G, Liu, H, Shrawan Nimbalkar, S, Tang, X & Xiao, Y 2017, 'Seismic response of concrete-rockfill combination dam using large-scale shaking table tests', Soil Dynamics and Earthquake Engineering, vol. 99, pp. 9-19.
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Wang, J, Zhang, X, Guo, Z & Lu, H 2017, 'Developing an early-warning system for air quality prediction and assessment of cities in China', Expert Systems with Applications, vol. 84, pp. 102-116.
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© 2017 Elsevier Ltd Air quality has received continuous attention from both environmental managers and citizens. Accordingly, early-warning systems for air pollution are very useful tools to avoid negative health effects and develop effective prevention programs. However, developing robust early-warning systems is very challenging, as well as necessary. This paper develops a reliable and effective early-warning system that consists of air quality prediction and assessment modules. In the prediction module, a hybrid forecasting method is developed for predicting pollutant concentrations that effectively estimates future air quality conditions. In developing this proposed model, we suggest the use of a back propagation neural network algorithm, combined with a probabilistic parameter model and data preprocessing techniques, to address the uncertainties involved in future air quality prediction. Meanwhile, a pre-analysis is implemented, primarily by using optimized distribution functions to examine and analyze statistical characteristics and emission behaviors of air pollutants. The second method, which is developed as part of the second module, is based on fuzzy set theory and the Analytic Hierarchy Process, and it performs air quality assessments to provide a clear and intelligible description of air quality conditions. Using data from the Ministry of Environmental Protection of China and six stages of air quality classification levels, specifically good, moderate, lightly polluted, moderately polluted, heavily polluted and severely polluted, two cities in China, Chengdu and Hangzhou, are used as illustrative examples to verify the effectiveness of the developed early-warning system. The results demonstrate that the proposed methods are effective and reliable for use by environmental supervisors in air pollution monitoring and management.
Wang, JJ-Y, Tsang, IW-H, Cui, X, Lu, Z & Gao, X 2017, 'Multi-instance dictionary learning via multivariate performance measure optimization', Pattern Recognition, vol. 66, pp. 448-459.
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© 2017 Elsevier Ltd The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.
Wang, L, Ren, L, Mitchell, D, Casillas-Garcia, G, Ren, W, Ma, C, Xu, XX, Wen, S, Wang, F, Zhou, J, Xu, X, Hao, W, Dou, SX & Du, Y 2017, 'Enhanced energy transfer in heterogeneous nanocrystals for near infrared upconversion photocurrent generation', Nanoscale, vol. 9, no. 47, pp. 18661-18667.
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A heterogeneous NaYF4:Yb,Tm@ZnO nanoparticle with an epitaxial interface is prepared, and it possesses an enhanced upconversion emission intensity and an excellent photocurrent response.
Wang, L, Yang, Q, Chen, Y, Chai, Y, Li, JJ, Du, L, Tan, R, Yang, S, Tu, M & Yu, B 2017, 'A reformative shear precipitation procedure for the fabrication of vancomycin-loaded poly(lactide-co-glycolide) microspheres', Journal of Biomaterials Applications, vol. 31, no. 7, pp. 995-1009.
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This study reports the encapsulation of vancomycin, as a model hydrophilic drug, into poly(lactide-co-glycolide) microspheres using a novel reformative shear precipitation procedure. In contrast to the external aqueous phase used in the conventional microencapsulation technique based on emulsion solvent evaporation/extraction, the reformative shear precipitation procedure explored in this study uses a shear medium composed of glycerol as the viscous medium and ethanol as polymer antisolvent, which is relatively immiscible with the hydrophilic drug. This limits drug diffusion and leads to rapid microsphere solidification, which allows a large proportion of the hydrophilic drug to be encapsulated within the microspheres. The influence of various processing parameters, including polymer concentration, volume ratio of ethanol to glycerol in the shear medium, volume of aqueous drug solution, initial drug loading, and injecting rate of the drug–polymer emulsion, on the encapsulation efficiency and characteristics of resulting microspheres were investigated. The morphology and release characteristics, as well as mechanical, in vitro and in vivo behaviour of vancomycin-loaded poly(lactide-co-glycolide) microspheres prepared using the novel procedure were also investigated. The results demonstrated that the reformative shear precipitation procedure could achieve the loading of hydrophilic drugs into poly(lactide-co-glycolide) microspheres with high encapsulation efficiency, and the success of the procedure was largely influenced by the volume ratio of ethanol to glycerol in the shear medium. Vancomycin-loaded poly(lactide-co-glycolide) microspheres prepared using this procedure demonstrated favourable mechanical characteristics, antibacterial activity, and in vivo degradation behaviour which suggested their suitability for use as a sustained delivery system.
Wang, P-H, Yan, H, Xue, Y, Lu, G, Ni, W, Xu, M & Yan, Y-M 2017, 'Surfactant-assisted freeze-drying synthesis of porous graphene for high-performance capacitive deionization', Desalination and Water Treatment, vol. 84, pp. 8-18.
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Wang, Q 2017, 'A Roadmap for Achieving Energy-Positive Sewage Treatment Based on Sludge Treatment Using Free Ammonia', ACS Sustainable Chemistry & Engineering, vol. 5, no. 11, pp. 9630-9633.
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This letter proposes an innovative roadmap for achieving energy-positive sewage treatment based on sludge treatment using free ammonia (FA, i.e., NH3). This FA technology is able to enhance anaerobic energy recovery in the form of methane via pretreatment of primary sludge and/or secondary sludge. It can also achieve stable mainstream nitrogen removal via nitrite instead of nitrate, thereby increasing organics availability for energy recovery. Energy evaluation suggests that the FA technology could transform sewage treatment plants from energy consumers (energy consumption at 0.27 kWh/m3 sewage treated) to energy exporters (energy export at 0.14 kWh/m3 sewage treated). Economic and environmental evaluations indicate that the FA technology would reduce sewage treatment cost and CO2 emission by $0.056/m3 sewage treated and 0.40 kg CO2/m3 sewage treated, respectively. This FA technology is a sustainable and closed-loop technology, which requires negligible chemical/energy input with FA being a byproduct of sewage treatment. It is also easy to implement in any existing and new sewage treatment plants by adding a simple sludge mixing tank.
Wang, Q, Duan, H, Wei, W, Ni, B-J, Laloo, A & Yuan, Z 2017, 'Achieving Stable Mainstream Nitrogen Removal via the Nitrite Pathway by Sludge Treatment Using Free Ammonia', Environmental Science & Technology, vol. 51, no. 17, pp. 9800-9807.
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© 2017 American Chemical Society. Biological nitrogen removal through the nitrite pathway (NH4+ → NO2- → N2) is favorable for wastewater treatment plants without sufficient carbon sources. This study demonstrates an innovative approach for attaining the nitrite pathway based on sludge treatment using free ammonia (FA, i.e., NH3). This approach is based on our innovative discovery in this study that FA at 210 mg NH3-N/L is far less biocidal to ammonium-oxidizing bacteria (AOB) than to nitrite-oxidizing bacteria (NOB). A total of 22% of the activated sludge from the sequencing batch reactor (SBR) receiving synthetic domestic wastewater was treated in an FA treatment unit at 210 mg NH3-N/L for 1 day. The FA-treated sludge was afterward recirculated back to the SBR. A nitrite accumulation ratio of above 90% was quickly achieved (in 40 days) and maintained stably in the SBR, indicating the establishment of the nitrite pathway. The NOB population and activity after implementing FA treatment was less than 5% of those without FA treatment, suggesting the washout of NOB. In contrast, the AOB population and activity in the SBR were not affected. The nitrogen-removal performance was significantly improved after incorporating the FA approach. The FA approach is a closed-loop approach and is economically and environmentally attractive.
Wang, Q, Wei, W, Gong, Y, Yu, Q, Li, Q, Sun, J & Yuan, Z 2017, 'Technologies for reducing sludge production in wastewater treatment plants: State of the art', Science of The Total Environment, vol. 587-588, pp. 510-521.
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This review presents the state-of-the-art sludge reduction technologies applied in both wastewater and sludge treatment lines. They include chemical, mechanical, thermal, electrical treatment, addition of chemical un-coupler, and predation of protozoa/metazoa in wastewater treatment line, and physical, chemical and biological pretreatment in sludge treatment line. Emphasis was put on their effect on sludge reduction performance, with 10% sludge reduction to zero sludge production in wastewater treatment line and enhanced TS (total solids) or volatile solids removal of 5-40% in sludge treatment line. Free nitrous acid (FNA) technology seems good in wastewater treatment line but it is only under the lab-scale trial. In sludge treatment line, thermal, ultrasonic (<4400kJ/kg TS), FNA pretreatment and temperature-phased anaerobic digestion (TPAD) are promising if pathogen inactivation is not a concern. However, thermal pretreatment and TPAD are superior to other pretreatment technologies when pathogen inactivation is required. The new wastewater treatment processes including SANI®, high-rate activated sludge coupled autotrophic nitrogen removal and anaerobic membrane bioreactor coupled autotrophic nitrogen removal also have a great potential to reduce sludge production. In the future, an effort should be put on the effect of sludge reduction technologies on the removal of organic micropollutants and heavy metals.
Wang, Q, Ye, X, Wang, S, Sloan, S & Sheng, D 2017, 'Development of a Model Test System for Studying the Behaviour of a Compaction Grouted Soil Nail under Unsaturated Conditions', Geotechnical Testing Journal, vol. 40, no. 5, pp. 20160229-20160229.
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Wang, Q, Ye, X, Wang, S, Sloan, SW & Sheng, D 2017, 'Experimental investigation of compaction-grouted soil nails', Canadian Geotechnical Journal, vol. 54, no. 12, pp. 1728-1738.
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An innovative compaction-grouted soil nail was designed by injecting grout into a special latex balloon (grouting bag) to avoid bleeding and penetration of grout into the surrounding soil. A series of large-scale model tests was performed to study the surrounding soil responses due to grouting and the subsequent pull-out resistance of the soil nail. The experimental results show that grouting pressure plays an important role in the enhancement of the density and (or) strength of the surrounding soil. In addition, during the pull-out process, the compaction-grouted soil nail exhibits a strain-hardening behaviour without a yield point. This is a significant advantage of this new soil nail, indicating that it can enable soil masses to remain stable against a relatively large deformation before ultimate failure. The main factors behind the improvement of the pull-out resistance of the new soil nail are, first, the compaction–densification of the soil near the grouting bag due to grouting, resulting in the enhancement of the shear strength of the soil, and, second, the enlargement of the grouting bag, causing the increase of the interface shear and end resistance to the pull-out of the soil nail.
Wang, R, Nie, F, Hong, R, Chang, X, Yang, X & Yu, W 2017, 'Fast and Orthogonal Locality Preserving Projections for Dimensionality Reduction', IEEE Transactions on Image Processing, vol. 26, no. 10, pp. 5019-5030.
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The locality preserving projections (LPP) algorithm is a recently developed linear dimensionality reduction algorithm that has been frequently used in face recognition and other applications. However, the projection matrix in LPP is not orthogonal, thus creating difficulties for both reconstruction and other applications. As the orthogonality property is desirable, orthogonal LPP (OLPP) has been proposed so that an orthogonal projection matrix can be obtained based on a step by step procedure; however, this makes the algorithm computationally more expensive. Therefore, in this paper, we propose a fast and orthogonal version of LPP, called FOLPP, which simultaneously minimizes the locality and maximizes the globality under the orthogonal constraint. As a result, the computation burden of the proposed algorithm can be effectively alleviated compared with the OLPP algorithm. Experimental results on two face recognition data sets and two hyperspectral data sets are presented to demonstrate the effectiveness of the proposed algorithm.
Wang, R, Thakur, CS, Cohen, G, Hamilton, TJ, Tapson, J & van Schaik, A 2017, 'Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition', IEEE Transactions on Biomedical Circuits and Systems, vol. 11, no. 3, pp. 574-584.
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© 2007-2012 IEEE. We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAS) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.
Wang, S & Dong, D 2017, 'Fault-Tolerant Control of Linear Quantum Stochastic Systems', IEEE Transactions on Automatic Control, vol. 62, no. 6, pp. 2929-2935.
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Wang, S, Gao, Q & Dong, D 2017, 'Robust H ∞ controller design for a class of linear quantum systems with time delay', International Journal of Robust and Nonlinear Control, vol. 27, no. 3, pp. 380-392.
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Wang, S, Kodagoda, S, Shi, L & Wang, H 2017, 'Road-Terrain Classification for Land Vehicles: Employing an Acceleration-Based Approach', IEEE Vehicular Technology Magazine, vol. 12, no. 3, pp. 34-41.
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© 2017 IEEE. The perception of the environment around a land vehicle plays a crucial role for its driving assistant system. Knowledge of the road terrain is useful for handling its characteristics while driving the vehicles and improving passengers' safety and comfort. In this article, an approach to classifying road-terrain vehicles is presented. An accelerometer is mounted on the suspension of the vehicle to measure the vibration that represents the characteristics of the road terrain, and the road profile can be calculated by knowing the speed and one-quarter-dynamic model of the vehicle. The optimized classifier and features, speed independency, and the effect of employing principal component analysis (PCA) are investigated, and the simulation shows that this acceleration-based approach is feasible for land vehicles in a range of outdoor scenarios.
Wang, S, Kodagoda, S, Shi, L & Xu, N 2017, 'Lidar-based road terrain recognition for passenger vehicles', International Journal of Vehicle Design, vol. 74, no. 2, pp. 153-153.
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Copyright © 2017 Inderscience Enterprises Ltd. The road terrain type is important information about a passenger vehicle’s surroundings. It suggests an appropriate control algorithm and driving strategy. In this paper, a Lidar sensor is employed to reconstruct the road surface and extract features for terrain classification. The experiment vehicle was driven on four specific road terrains at a variety of speeds. The speed dependency and the effect of using principal component analysis were investigated. The simulation experimental results show that this Lidar sensor-based approach is feasible and robust for passenger vehicles in a range of outdoor scenarios.
Wang, S, Li, X, Chang, X, Yao, L, Sheng, QZ & Long, G 2017, 'Learning Multiple Diagnosis Codes for ICU Patients with Local Disease Correlation Mining', ACM Transactions on Knowledge Discovery from Data, vol. 11, no. 3, pp. 1-21.
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In the era of big data, a mechanism that can automatically annotate disease codes to patients’ records in the medical information system is in demand. The purpose of this work is to propose a framework that automatically annotates the disease labels of multi-source patient data in Intensive Care Units (ICUs). We extract features from two main sources, medical charts and notes. The Bag-of-Words model is used to encode the features. Unlike most of the existing multi-label learning algorithms that globally consider correlations between diseases, our model learns disease correlation locally in the patient data. To achieve this, we derive a local disease correlation representation to enrich the discriminant power of each patient data. This representation is embedded into a unified multi-label learning framework. We develop an alternating algorithm to iteratively optimize the objective function. Extensive experiments have been conducted on a real-world ICU database. We have compared our algorithm with representative multi-label learning algorithms. Evaluation results have shown that our proposed method has state-of-the-art performance in the annotation of multiple diagnostic codes for ICU patients. This study suggests that problems in the automated diagnosis code annotation can be reliably addressed by using a multi-label learning model that exploits disease correlation. The findings of this study will greatly benefit health care and management in ICU considering that the automated diagnosis code annotation can significantly improve the quality and management of health care for both patients and caregivers.
Wang, T, Liu, C, Lei, G, Guo, Y & Zhu, J 2017, 'Model predictive direct torque control of permanent magnet synchronous motors with extended set of voltage space vectors', IET Electric Power Applications, vol. 11, no. 8, pp. 1376-1382.
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The finite‐control‐set model predictive direct torque control (FCS‐MPDTC) is a novel control scheme for permanent magnet synchronous motors (PMSMs). A key feature of FCS‐MPDTC is that the eight possible voltage space vectors or switching combinations of the power converters are directly taken into account as the control input of the system. A cost function is used in FCS‐MPDTC to evaluate each possible voltage space vector and the one with minimum cost is applied to the power converter. Due to the considerable torque and flux ripples, to improve the performance of FCS‐MPDTC, this study presents an extended set of 20 modulated voltage space vectors with fixed duty ratio. For further improvement, a larger set size can be chosen, but this requires a larger computing power. To mitigate the computational burden caused by increased number of voltage space vectors, a pre‐selective scheme is designed for the proposed FCS‐MPDTC to filter out the impractical voltage vectors instead of evaluating all 20 voltage space vectors. The drive system efficiencies of conventional direct torque control, conventional FCS‐MPDTC and proposed method are investigated. The theory and simulation are validated by experimental results on a PMSM prototype.
Wang, T, Liu, C, Xu, W, Lei, G, Jafari, M, Guo, Y & Zhu, J 2017, 'Fabrication and Experimental Analysis of an Axially Laminated Flux-Switching Permanent-Magnet Machine', IEEE Transactions on Industrial Electronics, vol. 64, no. 2, pp. 1081-1091.
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© 1982-2012 IEEE. The traditional flux-switching permanent-magnet machines (FSPMMs) with radial lamination have serious partial magnetic saturation for their nonlinear magnetic path, where the maximal flux density is usually more than 2.0 T occurring at the edges/tips of stator teeth or rotor poles. In this case, the core loss of FSPMMs becomes evident especially beyond the rated speed, which leads to decrease of output power, torque/power density, and efficiency. To overcome these problems, an axially laminated flux-switching permanent-magnet machine (ALFSPMM) with high grain-oriented silicon steel stator and rotor cores is proposed. The detailed fabrication procedures are presented in this paper. The theoretical characteristics of the ALFSPMM, such as back electromotive force, self-/mutual inductance, and cogging torque are calculated by the two-dimensional finite-element method (FEM). The influence of misalignment between the stator core and the rotor shaft (a common issue in motor manufacturing) is investigated by the FEM. Experimental measurements of the prototype machine are presented to validate the FEM calculation. In addition, a simple low-cost method to measure the cogging torque is also presented in this paper.
Wang, TQ, He, C & Armstrong, J 2017, 'Performance Analysis of Aperture-Based Receivers for MIMO IM/DD Visible Light Communications', Journal of Lightwave Technology, vol. 35, no. 9, pp. 1513-1523.
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© 2016 IEEE. Aperture-based receivers are a new form of receiver for multiple-input multiple-output (MIMO) intensity-modulated direct-detection visible light communication (VLC). These receivers provide a wide field of view and excellent angular diversity using a compact planar structure and so are ideally suited for integration in hand-held devices such as smartphones. It is shown that in typical scenarios to achieve similar performance the photodiodes in a conventional receiver based on spatial diversity would have to be separated by distances greater than 30 cm. An in-depth analysis of the performance of aperture-based receivers is presented. Expressions are derived for the channel gain between an optical transmitter and each receiving element (RE) as a function of the transmission pattern of the transmitter, the design of the RE, and the relative positions of the transmitter and receiver. It is shown that a well-designed receiver consisting of multiple REs can separate signals received from different directions with low-multistream interference and that the associated MIMO channel matrices are well conditioned. Simulations are performed for a typical indoor VLC scenario in which light-emitting diode luminaires transmit information using asymmetrically clipped optical orthogonal frequency division multiplexing. Results are presented for receivers using both linear and nonlinear equalizers and for both line of sight (LOS) and LOS plus diffuse reception. The diffuse component is shown to improve the bit error rate (BER) performance slightly. It is shown that the BER depends on the receiver position. When a zero-forcing (ZF) linear receiver is used, the BER is dominated by the most attenuated signal, so the performance degrades at the corners of the room. In contrast, the receivers with nonlinear equalizers based on ZF followed by successive interference cancelation achieve low BER throughout the scenario.
Wang, TQ, Li, H & Huang, X 2017, 'Diversity Combining for Layered Asymmetrically Clipped Optical OFDM Using Soft Successive Interference Cancellation', IEEE Communications Letters, vol. 21, no. 6, pp. 1309-1312.
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© 1997-2012 IEEE. In this letter, we present a novel diversity combining receiver for demodulating layered asymmetrically clipped optical orthogonal frequency division multiplexing. The receiver consists of a soft successive interference cancellation (SIC) module which cancels the inter-layer interference (ILI) using the minimum mean square error (MMSE) estimates of the information symbols, and a diversity combining module which extracts the diversity components from the clipping noise. We show that the soft SIC module alone can effectively suppress the ILI, leading to bit error rates (BERs) resembling those of a genie receiver which is free of error propagation. It is also shown that the diversity combining receiver which combines the MMSE estimates with their diversity components outperforms the genie receiver by up to 2 dB at the BER of 10-6.
Wang, W, Yin, H, Chen, L, Sun, Y, Sadiq, S & Zhou, X 2017, 'ST-SAGE', ACM Transactions on Intelligent Systems and Technology, vol. 8, no. 3, pp. 1-25.
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With the rapid development of location-based social networks (LBSNs), spatial item recommendation has become an important mobile application, especially when users travel away from home. However, this type of recommendation is very challenging compared to traditional recommender systems. A user may visit only a limited number of spatial items, leading to a very sparse user-item matrix. This matrix becomes even sparser when the user travels to a distant place, as most of the items visited by a user are usually located within a short distance from the user’s home. Moreover, user interests and behavior patterns may vary dramatically across different time and geographical regions. In light of this, we propose ST-SAGE, a spatial-temporal sparse additive generative model for spatial item recommendation in this article. ST-SAGE considers both personal interests of the users and the preferences of the crowd in the target region at the given time by exploiting both the co-occurrence patterns and content of spatial items. To further alleviate the data-sparsity issue, ST-SAGE exploits the geographical correlation by smoothing the crowd’s preferences over a well-designed spatial index structure called the spatial pyramid . To speed up the training process of ST-SAGE, we implement a parallel version of the model inference algorithm on the GraphLab framework. We conduct extensive experiments; the experimental results clearly demonstrate that ST-SAGE outperforms the state-of-the-art recommender systems in terms of recommendation effectiveness, model training efficiency, and online recommendation efficiency.
Wang, X, Cheng, E, Burnett, IS, Huang, Y & Wlodkowic, D 2017, 'Automatic multiple zebrafish larvae tracking in unconstrained microscopic video conditions', Scientific Reports, vol. 7, no. 1, pp. 1-8.
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AbstractThe accurate tracking of zebrafish larvae movement is fundamental to research in many biomedical, pharmaceutical, and behavioral science applications. However, the locomotive characteristics of zebrafish larvae are significantly different from adult zebrafish, where existing adult zebrafish tracking systems cannot reliably track zebrafish larvae. Further, the far smaller size differentiation between larvae and the container render the detection of water impurities inevitable, which further affects the tracking of zebrafish larvae or require very strict video imaging conditions that typically result in unreliable tracking results for realistic experimental conditions. This paper investigates the adaptation of advanced computer vision segmentation techniques and multiple object tracking algorithms to develop an accurate, efficient and reliable multiple zebrafish larvae tracking system. The proposed system has been tested on a set of single and multiple adult and larvae zebrafish videos in a wide variety of (complex) video conditions, including shadowing, labels, water bubbles and background artifacts. Compared with existing state-of-the-art and commercial multiple organism tracking systems, the proposed system improves the tracking accuracy by up to 31.57% in unconstrained video imaging conditions. To facilitate the evaluation on zebrafish segmentation and tracking research, a dataset with annotated ground truth is also presented. The software is also publicly accessible.
Wang, X, Fang, K & Tomamichel, M 2017, 'On converse bounds for classical communication over quantum channels', IEEE Transactions on Information Theory 65(7): 4609 - 4619, July 2019, vol. 65, no. 7, pp. 4609-4619.
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We explore several new converse bounds for classical communication overquantum channels in both the one-shot and asymptotic regimes. First, we showthat the Matthews-Wehner meta-converse bound for entanglement-assistedclassical communication can be achieved by activated, no-signalling assistedcodes, suitably generalizing a result for classical channels. Second, we derivea new efficiently computable meta-converse on the amount of classicalinformation unassisted codes can transmit over a single use of a quantumchannel. As applications, we provide a finite resource analysis of classicalcommunication over quantum erasure channels, including the second-order andmoderate deviation asymptotics. Third, we explore the asymptotic analogue ofour new meta-converse, the $\Upsilon$-information of the channel. We show thatits regularization is an upper bound on the classical capacity, which isgenerally tighter than the entanglement-assisted capacity and other knownefficiently computable strong converse bounds. For covariant channels we showthat the $\Upsilon$-information is a strong converse bound.
Wang, X, Liu, Y, Zhang, G, Xiong, F & Lu, J 2017, 'Diffusion-based recommendation with trust relations on tripartite graphs', Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 8, pp. 083405-083405.
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Wang, X, Liu, Y, Zhang, G, Zhang, Y, Chen, H & Lu, J 2017, 'Mixed Similarity Diffusion for Recommendation on Bipartite Networks', IEEE Access, vol. 5, pp. 21029-21038.
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© 2013 IEEE. In recommender systems, collaborative filtering technology is an important method to evaluate user preference through exploiting user feedback data, and has been widely used in industrial areas. Diffusion-based recommendation algorithms inspired by diffusion phenomenon in physical dynamics are a crucial branch of collaborative filtering technology, which use a bipartite network to represent collection behaviors between users and items. However, diffusion-based recommendation algorithms calculate the similarity between users and make recommendations by only considering implicit feedback but neglecting the benefits from explicit feedback data, which would be a significant feature in recommender systems. This paper proposes a mixed similarity diffusion model to integrate both explicit feedback and implicit feedback. First, cosine similarity between users is calculated by explicit feedback, and we integrate it with resource-allocation index calculated by implicit feedback. We further improve the performance of the mixed similarity diffusion model by considering the degrees of users and items at the same time in diffusion processes. Some sophisticated experiments are designed to evaluate our proposed method on three real-world data sets. Experimental results indicate that recommendations given by the mixed similarity diffusion perform better on both the accuracy and the diversity than that of most state-of-the-art algorithms.
Wang, X, Qin, L, Lin, X, Zhang, Y & Chang, L 2017, 'Leveraging Set Relations in Exact Set Similarity Join.', Proc. VLDB Endow., vol. 10, no. 9, pp. 925-936.
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© 2017 VLDB. Exact set similarity join, which finds all the similar set pairs from two collections of sets, is a fundamental problem with a wide range of applications. The existing solutions for set similarity join follow a filtering-verification framework, which generates a list of candidate pairs through scanning indexes in the filtering phase, and reports those similar pairs in the verification phase. Though much research has been conducted on this problem, set relations, which we find out is quite effective on improving the algorithm effciency through computational cost sharing, have never been studied. Therefore, in this paper, instead of considering each set individually, we explore the set relations in different levels to reduce the overall computational costs. First, it has been shown that most of the computational time is spent on the filtering phase, which can be quadratic to the number of sets in the worst case for the existing solutions. Thus we explore index-level set relations to reduce the filtering cost to be linear to the size of the input while keeping the same filtering power. We achieve this by grouping related sets into blocks in the index and skipping useless index probes in joins. Second, we explore answer-level set relations to further improve the algorithm based on the intuition that if two sets are similar, their answers may have a large overlap. We derive an algorithm which incrementally generates the answer of one set from an already computed answer of another similar set rather than compute the answer from scratch to reduce the computational cost. Finally, we conduct extensive performance studies using 21 real datasets with various data properties from a wide range of domains. The experimental results demonstrate that our algorithm outperforms all the existing algorithms across all datasets and can achieve more than an order of magnitude speedup against the stateof-the-art algorithms.
Wang, X, Wang, Z, Huang, Y, Chen, Y, Zhang, Y, Ren, H, Li, R & Pang, J 2017, 'Measuring interdisciplinarity of a research system: detecting distinction between publication categories and citation categories', Scientometrics, vol. 111, no. 3, pp. 2023-2039.
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© 2017, Akadémiai Kiadó, Budapest, Hungary. Interdisciplinary research has been a focus in academia, and it is beneficial to understand the properties and structure of interdisciplinary research from the viewpoint of bibliometrics. This paper detects distinctions between publication categories and citation categories to measure the interdisciplinarity of individual publications, and then to measure interdisciplinarity for one research system by the average interdisciplinarity of individual publications, which are taken as elements in the research system. The average and the standard deviation (SD) that reflects the variance of the elements’ interdisciplinarity in one research system, of all the publications’ integration scores and diffusion scores, were then respectively calculated. Sixty of the most productive authors from three Web of Science categories (Mathematics, Applied; Computer Science, Artificial Intelligence; and Operations Research and Management Science) were selected as a case to validate our approach. The results showed that measuring the interdisciplinarity of individual elements effectively lessened the impacts caused by some elements with distinctive citation categories on the research system’s interdisciplinarity (especially those research systems with large SDs). Furthermore, measuring the distinction between publication categories and citation categories is essential for individual publications’ interdisciplinarity when the citation categories do not appear in the categories of the publication itself or the publication has only a single citation category.
Wang, X, Zhang, Y, Zhang, W & Lin, X 2017, 'Efficient Distance-Aware Influence Maximization in Geo-Social Networks', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 3, pp. 599-612.
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© 2016 IEEE. Given a social network G and a positive integer k, the influence maximization problem aims to identify a set of knodes in G that can maximize the influence spread under a certain propagation model. As the proliferation of geo-social networks, location-aware promotion is becoming more necessary in real applications. In this paper, we study the distance-aware influence maximization (DAIM) problem, which advocates the importance of the distance between users and the promoted location. Unlike the traditional influence maximization problem, DAIM treats users differently based on their distances from the promoted location. In this situation, the knodes selected are different when the promoted location varies. In order to handle the large number of queries and meet the online requirement, we develop two novel index-based approaches, MIA-DA and RIS-DA, by utilizing the information over some pre-sampled query locations. MIA-DA is a heuristic method which adopts the maximum influence arborescence (MIA) model to approximate the influence calculation. In addition, different pruning strategies as well as a priority-based algorithm are proposed to significantly reduce the searching space. To improve the effectiveness, in RIS-DA, we extend the reverse influence sampling (RIS) model and come up with an unbiased estimator for the DAIM problem. Through carefully analyzing the sample size needed for indexing, RIS-DA is able to return a 1 - 1/e - ϵ approximate solution with at least 1 - δ probability for any given query. Finally, we demonstrate the efficiency and effectiveness of proposed methods over real geo-social networks.
Wang, X, Zhang, Y, Zhang, W, Lin, X & Chen, C 2017, 'Bring Order into the Samples: A Novel Scalable Method for Influence Maximization', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 2, pp. 243-256.
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© 2016 IEEE. As a key problem in viral marketing, influence maximization has been extensively studied in the literature. Given a positive integer k, a social network G and a certain propagation model, it aims to find a set of k nodes that have the largest influence spread. The state-of-the-art method IMM is based on the reverse influence sampling (RIS) framework. By using the martingale technique, it greatly outperforms the previous methods in efficiency. However, IMM still has limitations in scalability due to the high overhead of deciding a tight sample size. In this paper, instead of spending the effort on deciding a tight sample size, we present a novel bottom-k sketch based RIS framework, namely BKRIS, which brings the order of samples into the RIS framework. By applying the sketch technique, we can derive early termination conditions to significantly accelerate the seed set selection procedure. Moreover, we provide a cost-effective method to find a proper sample size to bound the quality of returned result. In addition, we provide several optimization techniques to reduce the cost of generating samples' order and efficiently deal with the worst-case scenario. We demonstrate the efficiency and effectiveness of the proposed method over 10 real world datasets. Compared with the IMM approach, BKRIS can achieve up to two orders of magnitude speedup with almost the same influence spread. In the largest dataset with 1.8 billion edges, BKRIS can return 50 seeds in 1.3 seconds and return 5,000 seeds in 36.6 seconds. It takes IMM 55.32 second and 3,664.97 seconds, respectively.
Wang, Y, Gao, J, Luo, Z, Brown, T & Zhang, N 2017, 'Level-set topology optimization for multimaterial and multifunctional mechanical metamaterials', Engineering Optimization, vol. 49, no. 1, pp. 22-42.
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© 2016 Informa UK Limited, trading as Taylor & Francis Group. Metamaterials are artificially engineered composites designed to have unusual properties. This article will develop a new level-set based topology optimization method for the computational design of multimaterial metamaterials with exotic thermomechanical properties. In order to generate metamaterials consisting of arrays of microstructures under periodicity, the numerical homogenization method is used to evaluate the effective properties of the microstructure, and a multiphase level-set model is used to evolve the boundaries of the multimaterial microstructure. The proposed method will produce material geometries with distinct interfaces and smoothed boundaries, which may facilitate the fabrication of the topologically optimized designs. Several numerical cases are used to demonstrate the effectiveness of the proposed method.
Wang, Y, He, Q, Zhang, X, Ye, D & Yang, Y 2017, 'Efficient QoS-Aware Service Recommendation for Multi-Tenant Service-Based Systems in Cloud', IEEE Transactions on Services Computing, vol. 13, no. 6, pp. 1-1.
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Wang, Y, Liu, J, Li, Y, Fu, J, Xu, M & Lu, H 2017, 'Hierarchically Supervised Deconvolutional Network for Semantic Video Segmentation', Pattern Recognition, vol. 64, pp. 437-445.
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© 2016 Elsevier Ltd.Semantic video segmentation is a challenging task of fine-grained semantic understanding of video data. In this paper, we present a jointly trained deep learning framework to make the best use of spatial and temporal information for semantic video segmentation. Along the spatial dimension, a hierarchically supervised deconvolutional neural network (HDCNN) is proposed to conduct pixel-wise semantic interpretation for single video frames. HDCNN is constructed with convolutional layers in VGG-net and their mirrored deconvolutional structure, where all fully connected layers are removed. And hierarchical classification layers are added to multi-scale deconvolutional features to introduce more contextual information for pixel-wise semantic interpretation. Besides, a coarse-to-fine training strategy is adopted to enhance the performance of foreground object segmentation in videos. Along the temporal dimension, we introduce Transition Layers upon the structure of HDCNN to make the pixel-wise label prediction consist with adjacent pixels across space and time domains. The learning process of the Transition Layers can be implemented as a set of extra convolutional calculations connected with HDCNN. These two parts are jointly trained as a unified deep network in our approach. Thorough evaluations are performed on two challenging video datasets, i.e., CamVid and GATECH. Our approach achieves state-of-the-art performance on both of the two datasets.
Wang, Y, Wang, C, Guo, H, Wang, Y & Huang, Z 2017, 'A nitrogen-doped three-dimensional carbon framework for high performance sodium ion batteries', RSC Advances, vol. 7, no. 3, pp. 1588-1592.
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A nitrogen-doped three-dimensional carbon framework is synthesized, and shows good Na+ storage performance with excellent rate capability.
Wang, Y, Wang, D, Liu, Y, Wang, Q, Chen, F, Yang, Q, Li, X, Zeng, G & Li, H 2017, 'Triclocarban enhances short-chain fatty acids production from anaerobic fermentation of waste activated sludge', Water Research, vol. 127, pp. 150-161.
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© 2017 Elsevier Ltd Triclocarban (TCC), one typical antibacterial agent being widely used in various applications, was found to be present in waste activated sludge at significant levels. To date, however, its effect on anaerobic fermentation of sludge has not been investigated. This work therefore aims to fill this knowledge gap. Experimental results showed that when TCC content in sludge increased from 26.7 ± 5.3 to 520.5 ± 12.6 mg per kilogram total suspended solids, the maximum concentration of short-chain fatty acids (SCFA) increased from 32.6 ± 2.5 to 228.2 ± 3.6 (without pH control) and from 211.7 ± 2.4 to 378.3 ± 3.2 mg COD/g VSS (initial pH 10), respectively. The large promotion of acetic acid was found to be the major reason for the enhancement of total SCFA production. Although a significant level of TCC was degraded in the fermentation process, SCFA was neither produced from TCC nor affected by its major intermediates at the relevant levels. It was found that TCC facilitated solubilization, acidogenesis, acetogenesis, and homoacetogenesis processes but inhibited methanogenesis process. Microbial analysis revealed that the increase of TCC increased the microbial community diversity, the abundances of SCFA (especially acetic acid) producers, and the activities of key enzymes relevant to acetic acid production.
Wang, Z & Cao, L 2017, 'Coupled Attribute Similarity Learning on Categorical Data for Multi-Label Classification', Journal of Beijing Institute of Technology (English Edition), vol. 26, no. 3, pp. 404-410.
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In this paper a novel coupled attribute similarity learning method is proposed with the basis on the multi-label categorical data (CASonMLCD). The CASonMLCD method not only computes the correlations between different attributes and multi-label sets using information gain, which can be regarded as the important degree of each attribute in the attribute learning method, but also further analyzes the intra-coupled and inter-coupled interactions between an attribute value pair for different attributes and multiple labels. The paper compared the CASonMLCD method with the OF distance and Jaccard similarity, which is based on the MLKNN algorithm according to 5 common evaluation criteria. The experiment results demonstrated that the CASonMLCD method can mine the similarity relationship more accurately and comprehensively, it can obtain better performance than compared methods.
Wang, Z & Cao, L 2017, 'Novel Apriori-Based Multi-Label Learning Algorithm by Exploiting Coupled Label Relationship', Journal of Beijing Institute of Technology (English Edition), vol. 26, no. 2, pp. 206-214.
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It is a key challenge to exploit the label coupling relationship in multi-label classification (MLC) problems. Most previous work focused on label pairwise relations, in which generally only global statistical information is used to analyze the coupled label relationship. In this work, firstly Bayesian and hypothesis testing methods are applied to predict the label set size of testing samples within their k nearest neighbor samples, which combines global and local statistical information, and then apriori algorithm is used to mine the label coupling relationship among multiple labels rather than pairwise labels, which can exploit the label coupling relations more accurately and comprehensively. The experimental results on text, biology and audio datasets shown that, compared with the state-of-the-art algorithm, the proposed algorithm can obtain better performance on 5 common criteria.
Wang, Z, Wu, S, Huang, Y, Chen, Y, Shi, S, Cheng, X & Huang, R 2017, 'Evaporation and Ignition Characteristics of Water Emulsified Diesel under Conventional and Low Temperature Combustion Conditions', Energies, vol. 10, no. 8, pp. 1109-1109.
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The combination of emulsified diesel and low temperature combustion (LTC) technology has great potential in reducing engine emissions. A visualization study on the spray and combustion characteristics of water emulsified diesel was conducted experimentally in a constant volume chamber under conventional and LTC conditions. The effects of ambient temperature on the evaporation, ignition and combustion characteristics of water emulsified diesel were studied under cold, evaporating and combustion conditions. Experimental results showed that the ambient temperature had little effect on the spray structures, in terms of the liquid core length, the spray shape and the spray area. However, higher ambient temperature slightly reduced the Sauter Mean Diameter (SMD) of the spray droplets. The auto-ignition delay time increased significantly with the decrease of the ambient temperature. The ignition process always occurred at the entrainment region near the front periphery of the liquid core. This entrainment region was evolved from the early injected fuel droplets which were heated and mixed by the continuous entrainment until the local temperature and equivalence ratio reached the ignition condition. The maximum value of integrated natural flame luminosity (INFL) reduced by 60% when the ambient temperature dropped from 1000 to 800 K, indicating a significant decrease of the soot emissions could be achieved by LTC combustion mode than the conventional diesel engines.
Watterson, PA 2017, 'A fast noise-tolerant ECG feature recognition algorithm based on probabilistic analysis of gradient discontinuity', Journal of Electrocardiology, vol. 50, no. 4, pp. 491-503.
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© 2017 Elsevier Inc. Purpose Improvement in real-time electrocardiogram (ECG) interpretation is still needed, especially for QT estimation. This paper proposes a fast algorithm for ECG feature recognition, based on locating turning points in the waveform gradient. Methods The algorithm places the fiducial point at the maximal value of a probabilistic decision function, assessing line intervals of best fit before and after the point and the point location relative to R-wave peaks already found. Results Fiducial points were successfully located for the 30 heartbeats annotated by a cardiologist of all 10 normal sinus rhythm records from the PhysioNet QT Database. For a given subject, the algorithm's QT estimation had superior repeatability, with intrasubject QT standard deviation just 5.42 ms, 60% lower than the cardiologist's 13.57 ms. Initial tests suggest immunity to noise of standard deviation up to about 9% of the signal, depending on noise type. Conclusions The proposed algorithm is fast to calculate and noise-tolerant, and has shown improved repeatability in its QT estimation compared to a cardiologist.
Wei, D, Luo, L, Sato, H, Jiang, Z & Manabe, K 2017, 'Simulations of hydro-mechanical deep drawing using Voronoi model and real microstructure model', Procedia Engineering, vol. 207, pp. 1033-1038.
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© 2017 The Authors. Published by Elsevier Ltd. Micro hydroforming is promising for fabricating complex micro components with a high aspect ratio. The aim of this study is to deepen the understanding of the size effects in micro hydroforming. Experimental work and FEM simulations of micro hydro-mechanical deep drawing (MHDD) were conducted. Voronoi model and real microstructure model were established. Real grain morphology can be considered in the real microstructure model. Local thinning in critical area of the drawn cups due to size effects can be predicted by the models. The simulation results agree with the MHDD test results.
Wei, D, Zhang, K, Ngo, HH, Guo, W, Wang, S, Li, J, Han, F, Du, B & Wei, Q 2017, 'Nitrogen removal via nitrite in a partial nitrification sequencing batch biofilm reactor treating high strength ammonia wastewater and its greenhouse gas emission', Bioresource Technology, vol. 230, pp. 49-55.
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© 2017 Elsevier Ltd In present study, the feasibility of partial nitrification (PN) process achievement and its greenhouse gas emission were evaluated in a sequencing batch biofilm reactor (SBBR). After 90 days’ operation, the average effluent NH4+-N removal efficiency and nitrite accumulation rate of PN-SBBR were high of 98.2% and 87.6%, respectively. Both polysaccharide and protein contents were reduced in loosely bound extracellular polymeric substances (LB-EPS) and tightly bound EPS (TB-EPS) during the achievement of PN-biofilm. Excitation-emission matrix spectra implied that aromatic protein-like, tryptophan protein-like and humic acid-like substances were the main compositions of both kinds of EPS in seed sludge and PN-biofilm. According to typical cycle, the emission rate of CO2had a much higher value than that of N2O, and their total amounts per cycle were 67.7 and 16.5 mg, respectively. Free ammonia (FA) played a significant role on the inhibition activity of nitrite-oxidizing bacteria and the occurrence of nitrite accumulation.
Wei, W, Zhou, X, Wang, D, Sun, J & Wang, Q 2017, 'Free ammonia pre-treatment of secondary sludge significantly increases anaerobic methane production', Water Research, vol. 118, pp. 12-19.
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Energy recovery in the form of methane from sludge/wastewater is restricted by the poor and slow biodegradability of secondary sludge. An innovative pre-treatment technology using free ammonia (FA, i.e. NH3) was proposed in this study to increase anaerobic methane production. The solubilisation of secondary sludge was significantly increased after FA pre-treatment at up to 680 mg NH3-N/L for 1 day, under which the solubilisation (i.e. 0.4 mg SCOD/mg VS; SCOD: soluble chemical oxygen demand; VS: volatile solids) was >10 times higher than that without FA pre-treatment (i.e. 0.03 mg SCOD/mg VS). Biochemical methane potential assays showed that FA pre-treatment at above 250 mg NH3-N/L is effective in improving anaerobic methane production. The highest improvement in biochemical methane potential (B0) and hydrolysis rate (k) was achieved at FA concentrations of 420-680 mg NH3-N/L, and was determined as approximately 22% (from 160 to 195 L CH4/kg VS added) and 140% (from 0.22 to 0.53 d-1) compared to the secondary sludge without pre-treatment. More analysis revealed that the FA induced improvement in B0 and k could be attributed to the rapidly biodegradable substances rather than the slowly biodegradable substances. Economic and environmental analyses showed that the FA-based technology is economically favourable and environmentally friendly. Since this FA technology aims to use the wastewater treatment plants (WWTPs) waste (i.e. anaerobic digestion liquor) to enhance methane production from the WWTPs, it will set an example for the paradigm shift of the WWTPs from 'linear economy' to 'circular economy'.
Wei, W, Zhou, X, Xie, G, Duan, H & Wang, Q 2017, 'A novel free ammonia based pretreatment technology to enhance anaerobic methane production from primary sludge', Biotechnology and Bioengineering, vol. 114, no. 10, pp. 2245-2252.
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ABSTRACTThis study proposed a novel free ammonia (FA, i.e., NH3) pretreatment technology to enhance anaerobic methane production from primary sludge for the first time. The solubilization of primary sludge was substantially enhanced following 24 h FA pretreatment (250–680 mg NH3‐N/L), by which the release of soluble chemical oxygen demand (SCOD) (i.e., 0.4 mg SCOD/mg VS added; VS: volatile solids) was approximately 10 times as much as that without pretreatment (i.e., 0.03 mg SCOD/mg VS added). Then, biochemical methane potential (BMP) tests demonstrated that FA pretreatment of 250–680 mg NH3‐N/L was capable of enhancing anaerobic methane production while the digestion time was more than 7 days. Model based analysis indicated that the improved anaerobic methane production was due to an increased biochemical methane potential (B0) of 8–17% (i.e., from 331 to 357–387 L CH4/kg VS added), with the highest B0 achieved at 420 mg NH3‐N/L pretreatment. However, FA pretreatment of 250–680 mg NH3‐N/L decreased hydrolysis rate (k) by 24–38% compared with control (i.e., from 0.29 d−1 to 0.18–0.22 d−1), which explained the lower methane production over the first 7 days’ digestion period. Economic analysis and environmental evaluation demonstrated that FA pretreatment technology was environmentally friendly and economically favorable. Biotechnol. Bioeng. 2017;114: 2245–2252. © 2017 Wiley Periodicals, Inc.
Wen, D, Qin, L, Zhang, Y, Chang, L & Lin, X 2017, 'Efficient Structural Graph Clustering: An Index-Based Approach.', Proc. VLDB Endow., vol. 11, no. 3, pp. 243-255.
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© 2017 VLDB Endowment. Graph clustering is a fundamental problem widely experienced across many industries. The structural graph clustering (SCAN) method obtains not only clusters but also hubs and outliers. However, the clustering results closely depend on two sensitive parameters, ∈ and μ, while the optimal parameter setting depends on different graph properties and various user requirements. Moreover, all existing SCAN solutions need to scan at least the whole graph, even if only a small number of vertices belong to clusters. In this paper we propose an index-based method for SCAN. Based on our index, we cluster the graph for any ∈ and μ in O( ΣC∈C|EC|) time, where C is the result set of all clusters and |EC| is the number of edges in a specific cluster C. In other words, the time expended to compute structural clustering depends only on the result size, not on the size of the original graph. Our index's space complexity is bounded by O(m), wheremis the number of edges in the graph. To handle dynamic graph updates, we propose algorithms and several optimization techniques for maintaining our index. We conduct extensive experiments to practically evaluate the performance of all our proposed algorithms on 10 real-world networks, one of which contains more than 1 billion edges. The experimental results demonstrate that our approaches significantly outperform existing solutions.
Wen, S, Chen, MZQ, Zeng, Z, Huang, T & Li, C 2017, 'Adaptive Neural-Fuzzy Sliding-Mode Fault-Tolerant Control for Uncertain Nonlinear Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 8, pp. 2268-2278.
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This paper proposes an adaptive neural-fuzzy sliding-mode control method for uncertain nonlinear systems with actuator effectiveness faults and input saturation. The parameter dependence of the control scheme is removed from the bound of actuator faults by updating online. A neural-fuzzy model is developed to approximate the uncertain nonlinear terms and a sliding-mode online-updating controller is developed to estimate the bound of the actuator with no prior knowledge of the fault. The asymptotic stability is verified via the Lyapunov method in the presence of actuator faults and saturation. Furthermore, the adaptive neural-fuzzy control method is extended to the uncertain faulty nonlinear systems with integral sliding-mode manifold as well as other popular sliding-mode surfaces. A numerical example is presented to demonstrate the effectiveness of the derived results.
Wen, S, Chen, MZQ, Zeng, Z, Yu, X & Huang, T 2017, 'Fuzzy Control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 1, pp. 24-32.
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This paper investigates the fuzzy control issue for uncertain active suspension systems via dynamic sliding-mode method. The Takagi-Sugeno fuzzy approach is adopted on the background of the varying masses to describe the prescribed nonlinear system in order to achieve the design targets via the method of sector nonlinearity. This paper employs the dynamic sliding-mode scheme to control nonlinear active suspension systems. In the proposed sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. In existing results, the sliding mode is achieved and maintained with no consideration of the system perturbations. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, simulation results are presented to verify the effectiveness of the proposed schemes.
Wen, S, Huang, T, Yu, X, Chen, MZQ & Zeng, Z 2017, 'Sliding-Mode Control of Memristive Chua's Systems via the Event-Based Method', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 64, no. 1, pp. 81-85.
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This brief studies the sliding-mode control (SMC) scheme of uncertain memristive Chua's circuits via the event-based method. The sliding-mode controller possesses the advantage of its strong robustness and fast response over other control techniques. However, this controller is generally required to be executed in a continuous manner in order to make the trajectories of augmented systems drive onto the sliding surface in a finite time. In practice, these control methods are performed in a digital form. Thus, this brief proposes the event-based SMC which is executed only when necessary. Meanwhile, the existence of the lower bound for interexecution time is derived in this brief. Finally, a case study is conducted to illustrate the effectiveness of the derived results.
Wen, S, Jiang, J, Liu, B, Xiang, Y & Zhou, W 2017, 'Using epidemic betweenness to measure the influence of users in complex networks', Journal of Network and Computer Applications, vol. 78, pp. 288-299.
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Wen, S, Zeng, Z, Chen, MZQ & Huang, T 2017, 'Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control', IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 10, pp. 2334-2343.
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This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.
Wickramasooriya Kuruneru, ST, Sauret, E, Saha, SC & Gu, Y 2017, 'A Novel Experimental Method to Assess Particle Deposition in Idealized Porous Channels', Heat Transfer Engineering, vol. 38, no. 11-12, pp. 1008-1017.
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© 2017 Queensland University of Technology. A novel and economical experimental technique has been developed to assess industrial aerosol deposition in various idealized porous channel configurations. This judicious examination of aerosol penetration in porous channels will assist engineers to better optimize designs for various engineering applications. Deposition patterns differ with porosity due to geometric configurations of the channel and superficial inlet velocities. Interestingly, it is found that two configurations of similar porosity exhibit significantly higher deposition fractions. Inertial impaction is profound at the leading edge of all obstacles, whereas particle buildup is observed at the trailing edge of the obstructions. A qualitative analysis shows that the numerical results are in good agreement with experimental results.
Wight, NM, Acosta, E, Vijayaraghavan, RK, McNally, PJ, Smirnov, V & Bennett, NS 2017, 'A universal method for thermal conductivity measurements on micro-/nano-films with and without substrates using micro-Raman spectroscopy', Thermal Science and Engineering Progress, vol. 3, pp. 95-101.
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The ability to measure intrinsic thermal conductivity via a non-contact, non-destructive process is extremely attractive. Micro-Raman spectroscopy has been demonstrated to enable effective non-contact thermometry with further work providing a non-destructive estimation of values for thermal conductivity on suitable materials. However significant limitations remain for nano- and micro-films. Materials that do not meet dimensional requirements for thickness or that are in-situ on a substrate or supporting structure present significant challenges using existing approaches. For such samples, representative measurements must be obtained using alternative methods that can compromise samples and/or require relative complexity in experimental design and analysis. Here an analytical model is shown allowing thermal conductivity to be measured free of such limitations via a straightforward approach using micro-Raman spectroscopy. Results are then obtained experimentally and values compared with those obtained using a complimentary technique demonstrating an improved accuracy over existing micro-Raman approaches. Furthermore, this model enables the effect of any substrate or supporting structure on measured values to be quantified and estimations for thermal conductivity of the sample itself to then be calculated where an influence is determined. Current estimations determining the threshold of substrate influence are shown to be insufficient and the importance of obtaining values of thermal conductivity for samples themselves under such conditions is demonstrated.
Wijayaratna, KP, Dixit, VV, Denant-Boemont, L & Waller, ST 2017, 'An experimental study of the Online Information Paradox: Does en-route information improve road network performance?', PLOS ONE, vol. 12, no. 9, pp. e0184191-e0184191.
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This study investigates the empirical presence of a theoretical transportation paradox, defined as the 'Online Information Paradox' (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.
Wong, S-W, Deng, F, Wu, Y-M, Lin, J-Y, Zhu, L, Chu, Q-X & Yang, Y 2017, 'Individually Frequency Tunable Dual- and Triple-band Filters in a Single Cavity', IEEE Access, vol. 5, pp. 11615-11625.
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© 2013 IEEE. This paper presents a new class of second-order individually and continuously tunable dual- and triple-band bandpass filters in a single metal cavity. Each passband is realized by two identical metal posts. These dual- and triple-band tunable filters are achieved by putting two or three identical sets of metal-post pair in a single metal cavity. Metal screws are co-designed as a part of the metal posts to control their insertion depth inside the cavity. In this way, the resonant frequencies can be continuously controlled and designed at the desired frequency bands. Moreover, the distance between the two metal posts in a post pair can be freely tuned. Thus, the external quality factor (Qe) and coupling coefficient (k) between the adjacent modes can be easily adjusted to meet the specified requirement in synthesis design. At the bottom of the cavity, some grooves are used to extend the tunable frequency range and make the resonant frequency linearly varied with the height of the metal post. The center frequency of each passband can be independently tuned with a frequency range of 0.8-3.2 GHz and tunable ratio of 4. Finally, the continuously tunable dual- and triple-band bandpass filters prototypes with second order response are designed and fabricated, of which each passband can be individually tuned with a large tuning range.
Woo, YC, Tijing, LD, Park, MJ, Yao, M, Choi, J-S, Lee, S, Kim, S-H, An, K-J & Shon, HK 2017, 'Electrospun dual-layer nonwoven membrane for desalination by air gap membrane distillation', Desalination, vol. 403, pp. 187-198.
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© 2015 Elsevier B.V. In the present study, dual-layer nanofiber nonwoven membranes were prepared by a facile electrospinning technique and applied for desalination by air gap membrane distillation (AGMD). Neat single and dual-layer nanofiber membranes composed of a hydrophobic polyvinylidene fluoride-co-hexafluoropropylene (PH) top layer with different supporting hydrophilic layer made of either polyvinyl alcohol (PVA), nylon-6 (N6), or polyacrylonitrile (PAN) nanofibers were fabricated with and without heat-press post-treatment. Surface characterization showed that the active layer (i.e., PH) of all electrospun nanofiber membranes (ENMs) exhibited a rough, highly porous (> 80% porosity), and hydrophobic surface (CA > 140°), while the other side was hydrophilic (CA < 90°) with varying porosity. Heat-pressing the membrane resulted to thinner thickness (from > 129 μm to < 100 μm) and smaller pore sizes (< 0.27 μm). The AGMD experiments in a co-current flow set-up were carried out with constant inlet temperatures at the feed and permeate streams of 60 ± 1.5 and 20 ± 1.5° C, respectively. The AGMD module had a membrane area of 21 cm2 and the thickness of the air gap was 3 mm. The neat single and dual-layer ENMs showed a water permeate flux of about 10.9–15.5 L/m2 h (LMH) using 3.5 wt.% NaCl solution as feed, which was much higher than that of a commercial PVDF membrane (~ 5 LMH). The provision of a hydrophilic layer at the bottom layer enhanced the AGMD performance depending on the wettability and characteristics of the support layer. The PH/N6 dual-layer nanofiber membrane prepared under the optimum condition showed flux and salt rejection of 15.5 LMH and 99.2%, respectively, which has good potential for AGMD application.
Woodside, AG & Sood, S 2017, 'Vignettes in the two-step arrival of the internet of things and its reshaping of marketing management’s service-dominant logic', Journal of Marketing Management, vol. 33, no. 1-2, pp. 98-110.
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© 2016 Westburn Publishers Ltd. This commentary offers vignettes on the introductions of the ‘internet of things’ (IoT) and their impacts on revising the service-dominant (S-D) logic paradigm in marketing. Except smart phones, most consumer households are not participating now in the IoT revolution–but most product-service radical innovations include a 20+ year low-growth start-up. Because the benefits really are enormous and the technical advances in smart devices are now rapidly improving, expect the IoT revolution to hit hard in all areas of daily life before 2025 similar to the great impacts occurring now in business-to-business applications. This study proposes substantial revisions in the S-D logic due to the upcoming take-off stage of adopting radically new IoT innovations.
Wöstmann, R, Strauss, P & Deuse, J 2017, 'Predictive Maintenance in production', WT Werkstattstechnik, vol. 107, no. 7-8, pp. 524-529.
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Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applica- tions and their transferability to production as well as prerequisites for a successful implementation.
Wöstmann, R, Strauss, P & Deuse, JP 2017, 'Predictive Maintenance in der Produktion*/Predictive Maintenance in production', wt Werkstattstechnik online, vol. 107, no. 07-08, pp. 524-529.
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Über neue Möglichkeiten der Vernetzung und Datenverarbeitung von Anlagen und -komponenten gewinnt die prädiktive Instandhaltung stetig an Bedeutung. Während sie insbesondere in der Luftfahrt sowie bei der Versorgungs- und Energietechnik schon seit Jahren zum Einsatz kommt, sind innerhalb der Produktion derzeit noch wenige Anwendungsfälle zu finden. Der Beitrag stellt die bisher ungenutzten Potentiale dar, indem branchenübergreifende Anwendungsfälle sowie deren Übertragbarkeit auf die Produktion und Voraussetzungen für eine erfolgreiche Einführung vorgestellt werden.
Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applications and their transferability to production as well as prerequisites for a successful implementation.
Wu, B, Gao, W, Wu, D & Song, C 2017, 'Probabilistic interval geometrically nonlinear analysis for structures', Structural Safety, vol. 65, pp. 100-112.
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© 2017 Elsevier Ltd This paper presents a new unified Chebyshev surrogate model based hybrid uncertainty analysis method for robustly assessing geometrically nonlinear responses of engineering structures involving both random and interval uncertainties. In this proposed approach, Chebyshev response surface strategy combined with finite element framework is developed to model the nonlinear relationships between the uncertain structural parameters and the corresponding system responses. A comprehensive computational analysis framework, namely generalized unified interval stochastic sampling, is devised to furnish the statistical features, including means, standard deviations, probability density functions and cumulative distribution functions, of the lower and upper bounds of the nonlinear random interval structural behaviours. The applicability and notable performance of the presented approach are elucidated with the help of two practically motivated examples.
Wu, B, Ni, B-J, Horvat, K, Song, L, Chai, X, Dai, X & Mahajan, D 2017, 'Occurrence State and Molecular Structure Analysis of Extracellular Proteins with Implications on the Dewaterability of Waste-Activated Sludge', Environmental Science & Technology, vol. 51, no. 16, pp. 9235-9243.
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© 2017 American Chemical Society. The occurrence state and molecular structure of extracellular proteins were analyzed to reveal the influencing factors on the water-holding capacities of protein-like substances in waste-activated sludge (WAS). The gelation process of extracellular proteins verified that advanced oxidation processes (AOPs) for WAS dewaterability improvement eliminated the water affinity of extracellular proteins and prevented these macromolecules from forming stable colloidal aggregates. Isobaric tags for relative and absolute quantitation proteomics identified that most of the extracellular proteins were originally derived from the intracellular part and the proteins originally located in the extracellular part were mainly membrane-associated. The main mechanism of extracellular protein transformation during AOPs could be represented by the damage of the membrane or related external encapsulating structure and the release of intracellular substances. For the selected representative extracellular proteins, the strong correlation (R2 > 0.97, p < 0.03) between the surface hydrophilicity index and α-helix percentages in the secondary structure indicated that the water affinity relied more on the spatial distribution of hydrophilic functional groups rather than the content. Destructing the secondary structure represented by the α-helix and stretching the polypeptide aggregation in the water phase through disulfide bond removal might be the key to eliminating the inhibitory effects of extracellular proteins on the interstitial water removal from WAS.
Wu, C & Li, J 2017, 'Structural Protective Design with Innovative Concrete Material and Retrofitting Technology', Procedia Engineering, vol. 173, pp. 49-56.
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© 2017 The Authors. Retrofitting technology and high performance construction material are now widely investigated so as to increase structural ductility and robustness under extreme loading conditions. In the present study, some recent developments in structural protection against blast loads are compiled. Metallic foam materials with varying foam density and gradient are used in the cladding design, their energy absorbing capacities and stress-strain relationships are studied based on uniaxial compression tests. These foam material are used to cast sacrificial claddings on the concrete slabs in the field blast tests. Damage and structural deformation are measured to check the effectiveness of the claddings. Besides sacrificial foam cladding, concrete material with new reinforcement scheme including steel wire mesh and micro steel fiber is developed, and the static test results indicates the excellent ductility and crack control ability of this novel design. In the field blast tests, concrete slabs with different steel wire mesh reinforcement are exposed to varying blast loads. The effectiveness of the slab reinforcing design is discussed based on field performance.
Wu, C, Gao, Y, Fang, J, Lund, E & Li, Q 2017, 'Discrete topology optimization of ply orientation for a carbon fiber reinforced plastic (CFRP) laminate vehicle door', Materials & Design, vol. 128, pp. 9-19.
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Wu, C, Qi, B, Chen, C & Dong, D 2017, 'Robust Learning Control Design for Quantum Unitary Transformations', IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4405-4417.
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Wu, D & Gao, W 2017, 'Hybrid uncertain static analysis with random and interval fields', Computer Methods in Applied Mechanics and Engineering, vol. 315, pp. 222-246.
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© 2016 Elsevier B.V. Uncertain static analysis of an engineering structure with diverse type of non-deterministic system parameter is investigated in this study. Unlike the traditional hybrid uncertain static analysis involving random and interval variables, the concept of random and interval fields has been implemented to model the spatially dependent uncertainties associated with the system inputs. A novel computational approach, namely the extended unified interval stochastic sampling (X-UISS) method, is proposed to calculate the statistical characteristics (i.e., mean and standard deviation) of the extreme bounds (i.e., lower and upper bounds) of the concerned responses (e.g., displacement and stress) of engineering structure involving hybrid spatially dependent uncertainties. Subsequently, by utilizing either parametric or nonparametric statistical analysis, the probability density functions (PDFs), as well as the cumulative distribution functions (CDFs), of the extreme bounds of the concerned structural responses can be effectively established. Consequently, the upper and lower bounds of either the concerned responses of the engineering structure at any particular percentile of probability, or the structural reliability against any specified capacities can be effectively secured. The applicability and effectiveness of the proposed computational analysis framework are illustrated through the numerical investigations on various examples.
Wu, D & Gao, W 2017, 'Uncertain static plane stress analysis with interval fields', International Journal for Numerical Methods in Engineering, vol. 110, no. 13, pp. 1272-1300.
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Copyright © 2016 John Wiley & Sons, Ltd. Uncertain static plane stress analysis of continuous structure involving interval fields is investigated in this study. Unlike traditional interval analysis of discrete structure, the interval field is adopted to model the uncertainty, as well as the dependency between the physical locations and degrees of variability, of all interval system parameters presented in the continuous structures. By implementing the flexibility properties of some common structural elements, a new computational scheme is proposed to reformulate the uncertain static plane stress analysis with interval fields into standard mathematical programming problems. Consequently, feasible upper and lower bounds of structural responses can be effectively yet efficiently determined. In addition, the proposed method is adequate to deal with situations involving one-dimensional and two-dimensional interval fields, which enhances the pertinence of the proposed approach by incorporating both discrete and continuous structures. In addition, the proposed computational scheme is able to establish the realizations of the uncertain parameters causing the extreme structural responses at zero computational cost. The applicability and credibility of the established computational framework are rigorously justified by various numerical investigations. Copyright © 2016 John Wiley & Sons, Ltd.
Wu, D, Gao, W & Tangaramvong, S 2017, 'Time-Dependent Buckling Analysis of Concrete-Filled Steel Tubular Arch with Interval Viscoelastic Effects', Journal of Structural Engineering, vol. 143, no. 7, pp. 04017055-04017055.
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In this paper, a finite-element-based computational method is proposed for time-dependent structural stability analysis of a concrete-filled steel tubular (CFST) arch with uncertain parameters. Specifically, the targeted uncertainty includes the mercurial effects of the creep and shrinkage of the concrete core, which inevitably affect the structural performance of the CFST arch. The structural stability of the composite arch is systematically investigated under the influence of uncertain creep and shrinkage in a time-dependent fashion. The proposed computational scheme efficiently establishes the quantitative long-term stability envelope for CFST arches against uncertain viscoelastic effects. In order to demonstrate the effectiveness and efficiency of the proposed time-dependent structural stability analysis for CFST arches, practically motivated numerical examples are thoroughly investigated throughout this work.
Wu, D, Gao, W, Gao, K & Tin-Loi, F 2017, 'Robust safety assessment of functionally graded structures with interval uncertainties', Composite Structures, vol. 180, pp. 664-685.
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© 2017 Elsevier Ltd This paper investigates the problem of non-deterministic static analysis of functionally graded structures involving interval uncertainties through both Euler-Bernoulli and Timoshenko beam theories. Within the generalized analysis framework of the Finite Element Method (FEM), a novel computational scheme is developed to effectively tackle such intricate, yet frequently encountered, engineering problems. The proposed method establishes a unified non-stochastic uncertainty analysis framework, which can incorporate the interval uncertainties of material properties of the functionally graded structural members, the dimensions of structural elements, as well as the externally applied thermal and mechanical loads. By introducing an alternative FEM formulation, the governing equation for the interval uncertain static analysis of functionally graded structures can be meticulously transformed into two standard nonlinear programming (NLP) problems, so the extreme bounds of any concerned structural behaviours can be effectively determined. In addition, the proposed method is able to provide the critical information regarding the uncertain parameters that are actually causing such extreme structural behaviours at zero computational cost. Consequently, such by-products of the analysis can certainly be beneficial for subsequent structural design, and also the physical feasibility of the original problem can be rigorously maintained.
Wu, D, Lance, BJ, Lawhern, VJ, Gordon, S, Jung, T-P & Lin, C-T 2017, 'EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 11, pp. 2157-2168.
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© 2001-2011 IEEE. Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for electroencephalogram (EEG)-based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30%-8.30%, and increase the estimation correlation coefficient by 6.59%-11.13%.
Wu, D, Lawhern, VJ, Gordon, S, Lance, BJ & Lin, C-T 2017, 'Driver Drowsiness Estimation From EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)', IEEE Transactions on Fuzzy Systems, vol. 25, no. 6, pp. 1522-1535.
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© 1993-2012 IEEE. One big challenge that hinders the transition of brain-computer interfaces (BCIs) from laboratory settings to real-life applications is the availability of high-performance and robust learning algorithms that can effectively handle individual differences, i.e., algorithms that can be applied to a new subject with zero or very little subject-specific calibration data. Transfer learning and domain adaptation have been extensively used for this purpose. However, most previous works focused on classification problems. This paper considers an important regression problem in BCI, namely, online driver drowsiness estimation from EEG signals. By integrating fuzzy sets with domain adaptation, we propose a novel online weighted adaptation regularization for regression (OwARR) algorithm to reduce the amount of subject-specific calibration data, and also a source domain selection (SDS) approach to save about half of the computational cost of OwARR. Using a simulated driving dataset with 15 subjects, we show that OwARR and OwARR-SDS can achieve significantly smaller estimation errors than several other approaches. We also provide comprehensive analyses on the robustness of OwARR and OwARR-SDS.
Wu, G, Liu, RP, Ni, W, Sutton, GJ & Xu, P 2017, 'Modeling Channel Switching and Contention Control in Vehicular Networks', IEEE Access, vol. 5, pp. 23102-23110.
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© 2017 IEEE. In vehicular networks, multi-channel operation standard IEEE 1609.4 is designed for vehicular communications across multiple channels. It has been revealed that such multi-channel operations may result in high contention in vehicular communications. However, existing analytical models are unable to capture the dynamic characteristic during channel switching. We develop a novel Markov model that takes into account the dynamic contention behavior during channel switching. In particular, our model reveals the high contention caused by the burst arrivals, which are the results of multi-channel operations. To combat such performance decline, we propose two solutions, a centralized equal-spaced algorithm and a distributed random-spaced algorithm. The key idea is to disperse the burst packet arrivals across the available timeframe in order to alleviate contention. Our model, validated by simulations, accurately characterizes the high contention caused by multi-channel operations. Our results demonstrate our proposed solutions can effectively mitigate packet collision, enhance reliability, and improve system throughput during the multi-channel operations.
Wu, H, Zhang, J, Ngo, HH, Guo, W & Liang, S 2017, 'Evaluating the sustainability of free water surface flow constructed wetlands: Methane and nitrous oxide emissions', Journal of Cleaner Production, vol. 147, pp. 152-156.
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© 2017 Elsevier Ltd Constructed wetlands (CWs) have been used as a green technology to treat various wastewaters for several decades, and greenhouse gases production in these systems attracted increasing attention considering the contributions of methane and nitrous oxide emissions to global warming. However, the detailed knowledge about the contribution of CWs to methane and nitrous oxide emissions in treating sewage treatment plant effluent are still limited in particular for a better understanding of the sustainability of CWs. The fluxes of methane (CH 4 ) and nitrous oxide (N 2 O) from free water surface (FWS) CWs in northern China were measured continuously using the static-stationary chamber technique from 2012 to 2013. The results showed that CWs were the significant source of CH 4 and N 2 O emissions. Average emission rates of CH 4 and N 2 O ranged from −30.2 μg m −2 h −1 to 450.9 μg m −2 h −1 , and -58.8 μg m −2 h −1 to 1251.8 μg m −2 h −1 , respectively. Obvious annual and seasonal variations of CH 4 and N 2 O emissions were observed over the 2-year period. In addition, temperatures and plant species had an impact on CH 4 and N 2 O emissions. The obtained results showed that FWS CWs, improving water quality but emitting lower CH 4 and N 2 O, could be the alternative method for sewage treatment plant effluent.
Wu, J, Luo, Z, Li, H & Zhang, N 2017, 'A new hybrid uncertainty optimization method for structures using orthogonal series expansion', Applied Mathematical Modelling, vol. 45, pp. 474-490.
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© 2017 Elsevier Inc. This paper proposes a new hybrid uncertain design optimization method for structures which contain both random and interval variables simultaneously. The optimization model is formulated with the feasible robustness and the reliability of the worst scenario. The hybrid uncertainty is quantified by using the orthogonal series expansion method that integrates the Polynomial Chaos (PC) expansion method and the Chebyshev interval method within a uniform framework. The design sensitivity of objective and constraints will be developed to greatly facilitate the use of gradient-based optimization algorithms. The numerical results show that this method will be more possible to seek the feasible solution.
Wu, J, Luo, Z, Li, H & Zhang, N 2017, 'Level-set topology optimization for mechanical metamaterials under hybrid uncertainties', Computer Methods in Applied Mechanics and Engineering, vol. 319, pp. 414-441.
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© 2017 Elsevier B.V. This paper proposes a level set-based robust topology optimization (RTO) method for computational design of metamaterials under hybrid uncertainties, e.g. auxetics with negative Poisson's ratio, where the Young's modulus of the solid is described as a random variable while the Poisson's ratio is regarded as an interval variable. Firstly, the robust objective function is formulated by a combination of interval mean and interval variance of the deterministic objective function. Secondly, the interval mean and interval variance are computed by a hybrid uncertain analysis approach, termed as Polynomial Chaos-Chebyshev Interval (PCCI) method. Thirdly, the design sensitivities of the robust objective function are obtained after the implementation of the PCCI method. Finally, a powerful parametric level set method (PLSM) in conjunction with the numerical homogenization method is applied to achieve the robust topological design for the auxetic microstructure. Several numerical cases are used to demonstrate the effectiveness of the proposed method for the robust topology optimization problems. This method is non-intrusive and general, and can be easily extended to a range of design problems of micro-structured metamaterials.
Wu, J, Luo, Z, Zhang, N, Zhang, Y & Walker, PD 2017, 'Uncertain dynamic analysis for rigid-flexible mechanisms with random geometry and material properties', Mechanical Systems and Signal Processing, vol. 85, no. 15, pp. 487-511.
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© 2016 Elsevier Ltd This paper proposes an uncertain modelling and computational method to analyze dynamic responses of rigid-flexible multibody systems (or mechanisms) with random geometry and material properties. Firstly, the deterministic model for the rigid-flexible multibody system is built with the absolute node coordinate formula (ANCF), in which the flexible parts are modeled by using ANCF elements, while the rigid parts are described by ANCF reference nodes (ANCF-RNs). Secondly, uncertainty for the geometry of rigid parts is expressed as uniform random variables, while the uncertainty for the material properties of flexible parts is modeled as a continuous random field, which is further discretized to Gaussian random variables using a series expansion method. Finally, a non-intrusive numerical method is developed to solve the dynamic equations of systems involving both types of random variables, which systematically integrates the deterministic generalized-α solver with Latin Hypercube sampling (LHS) and Polynomial Chaos (PC) expansion. The benchmark slider-crank mechanism is used as a numerical example to demonstrate the characteristics of the proposed method.
Wu, J, Pan, S, Zhu, X, Zhang, C & Wu, X 2017, 'Positive and Unlabeled Multi-Graph Learning', IEEE Transactions on Cybernetics, vol. 47, no. 4, pp. 818-829.
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© 2017 IEEE. In this paper, we advance graph classification to handle multi-graph learning for complicated objects, where each object is represented as a bag of graphs and the label is only available to each bag but not individual graphs. In addition, when training classifiers, users are only given a handful of positive bags and many unlabeled bags, and the learning objective is to train models to classify previously unseen graph bags with maximum accuracy. To achieve the goal, we propose a positive and unlabeled multi-graph learning (puMGL) framework to first select informative subgraphs to convert graphs into a feature space. To utilize unlabeled bags for learning, puMGL assigns a confidence weight to each bag and dynamically adjusts its weight value to select 'reliable negative bags.' A number of representative graphs, selected from positive bags and identified reliable negative graph bags, form a 'margin graph pool' which serves as the base for deriving subgraph patterns, training graph classifiers, and further updating the bag weight values. A closed-loop iterative process helps discover optimal subgraphs from positive and unlabeled graph bags for learning. Experimental comparisons demonstrate the performance of puMGL for classifying real-world complicated objects.
Wu, J, Pan, S, Zhu, X, Zhang, C & Yu, PS 2017, 'Multiple Structure-View Learning for Graph Classification', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 1-16.
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© 2012 IEEE. Many applications involve objects containing structure and rich content information, each describing different feature aspects of the object. Graph learning and classification is a common tool for handling such objects. To date, existing graph classification has been limited to the single-graph setting with each object being represented as one graph from a single structure-view. This inherently limits its use to the classification of complicated objects containing complex structures and uncertain labels. In this paper, we advance graph classification to handle multigraph learning for complicated objects from multiple structure views, where each object is represented as a bag containing several graphs and the label is only available for each graph bag but not individual graphs inside the bag. To learn such graph classification models, we propose a multistructure-view bag constrained learning (MSVBL) algorithm, which aims to explore substructure features across multiple structure views for learning. By enabling joint regularization across multiple structure views and enforcing labeling constraints at the bag and graph levels, MSVBL is able to discover the most effective substructure features across all structure views. Experiments and comparisons on real-world data sets validate and demonstrate the superior performance of MSVBL in representing complicated objects as multigraph for classification, e.g., MSVBL outperforms the state-of-the-art multiview graph classification and multiview multi-instance learning approaches.
Wu, S-L, Liu, Y-T, Hsieh, T-Y, Lin, Y-Y, Chen, C-Y, Chuang, C-H & Lin, C-T 2017, 'Fuzzy Integral With Particle Swarm Optimization for a Motor-Imagery-Based Brain–Computer Interface', IEEE Transactions on Fuzzy Systems, vol. 25, no. 1, pp. 21-28.
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© 2016 IEEE. A brain-computer interface (BCI) system using electroencephalography signals provides a convenient means of communication between the human brain and a computer. Motor imagery (MI), in which motor actions are mentally rehearsed without engaging in actual physical execution, has been widely used as a major BCI approach. One robust algorithm that can successfully cope with the individual differences in MI-related rhythmic patterns is to create diverse ensemble classifiers using the subband common spatial pattern (SBCSP) method. To aggregate outputs of ensemble members, this study uses fuzzy integral with particle swarm optimization (PSO), which can regulate subject-specific parameters for the assignment of optimal confidence levels for classifiers. The proposed system combining SBCSP, fuzzy integral, and PSO exhibits robust performance for offline single-trial classification of MI and real-time control of a robotic arm using MI. This paper represents the first attempt to utilize fuzzy fusion technique to attack the individual differences problem of MI applications in real-world noisy environments. The results of this study demonstrate the practical feasibility of implementing the proposed method for real-world applications.
Wu, Y, Liao, L-D, Pan, H-C, He, L, Lin, C-T & Tan, MC 2017, 'Fabrication and interfacial characteristics of surface modified Ag nanoparticle based conductive composites', RSC Advances, vol. 7, no. 47, pp. 29702-29712.
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Surface modification of Ag nanoparticles with PAA–PVP complex was conducted and successfully improved the dispersion of Ag nanoparticles in PDMS.
Wu, Y, Yang, Q, Zeng, Q, Ngo, HH, Guo, W & Zhang, H 2017, 'Enhanced low C/N nitrogen removal in an innovative microbial fuel cell (MFC) with electroconductivity aerated membrane (EAM) as biocathode', Chemical Engineering Journal, vol. 316, pp. 315-322.
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© 2016 Elsevier B.V. A novel microbial fuel cell (MFC) was developed to enhance simultaneous nitrification and denitrification (SND) by employing electrons from the anode. The cathode chamber of the reactor consisted of a membrane aerated biofilm reactor (MABR) which was made of an electroconductivity aerated membrane. The maximum power density of 4.20 ± 0.12 W m −3 was obtained at a current density of 4.10 ± 0.11 A m −2 (external resistance = 10 Ω). Compared with an open-circuit system, the removal rates of NH 4 + -N and TN were improved by 9.48 ± 0.33% and 19.80 ± 0.84%, respectively, which could be ascribed to the electrochemical denitrification. The anode (chemical oxygen demand, COD) and cathode (NO 3 − ) chambers reached the maximum coulombic efficiencies (CEs) of 40.67 ± 1.05% and 42.84 ± 1.14%, respectively. It suggested that the electroconductivity MABR has some advantages in controlling aeration intensity, thus improving SND and CEs. Overall, EAM-MFC could successfully generate electricity from wastewater whilst showing high capacity for removing nitrogen at a low COD/N ratio of 2.8 ± 0.07 g COD g −1 N.
Wu, Z, Lei, L, Li, G, Huang, H, Zheng, C, Chen, E & Xu, G 2017, 'A topic modeling based approach to novel document automatic summarization', Expert Systems with Applications, vol. 84, pp. 12-23.
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Wu, Z, Zhu, H, Li, G, Cui, Z, Huang, H, Li, J, Chen, E & Xu, G 2017, 'An efficient Wikipedia semantic matching approach to text document classification', Information Sciences, vol. 393, pp. 15-28.
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Xia, Y, Wu, C & Bennett, T 2017, 'An analytical model of linear density foam–protected structure under blast loading', International Journal of Protective Structures, vol. 8, no. 3, pp. 454-472.
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Aluminium foam is widely known as an energy absorptive material which can be used as a protective cladding on structures to enhance blast resistance of the protected structures. Previous studies show that higher density provides larger energy absorption capacity of aluminium foam, but results in a larger transmitted pressure to the protected structure. To lower the transmitted pressure without sacrificing the maximum energy absorption, graded density foam has been examined in this study. An analytical model is developed in this article to investigate the protective effect of linear density foam on response of a structure under blast loading. The model is able to simulate structural deformation with reasonable accuracy compared with experimental data. The sensitivity of density gradient of foam cladding on reinforced concrete structure is tested in the article.
Xiang, C, Petersen, IR & Dong, D 2017, 'Coherent robust H∞ control of linear quantum systems with uncertainties in the Hamiltonian and coupling operators', Automatica, vol. 81, pp. 8-21.
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Xiang, C, Petersen, IR & Dong, D 2017, 'Performance Analysis and Coherent Guaranteed Cost Control for Uncertain Quantum Systems Using Small Gain and Popov Methods', IEEE Transactions on Automatic Control, vol. 62, no. 3, pp. 1524-1529.
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Xiao, F, Dong, L, Li, L & Liao, X 2017, 'A Frequency-Fixed SOGI-Based PLL for Single-Phase Grid-Connected Converters', IEEE Transactions on Power Electronics, vol. 32, no. 3, pp. 1713-1719.
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© 1986-2012 IEEE. Second-order generalized integrator (SOGI) based phase-locked loops (PLLs) are widely used for grid synchronization in single-phase grid-connected power converters. Previously, the estimated frequency of the PLL stage is fed back to the front-end SOGI block to make SOGI-PLLs frequency-Adaptive, which increases the implementation complexity, and makes the tuning sensitive, thus reducing stability margins. Alternatively, a frequency-fixed SOGI-based PLL (briefly called FFSOGI-PLL) is proposed to ensure stability and simple implementation in this letter. It is commonly known that the in-phase and quadrature-phase signals generated by the frequency-fixed SOGI are of different amplitudes in the presence of frequency drifts, which causes second-harmonic ripples in the estimated parameters of the PLL loop. To deal with this issue, a simple yet effective method is developed in FFSOGI-PLL. The standard SOGI-PLL is first introduced, followed by the working principle and small-signal model of FFSOGI-PLL. The FFSOGI-PLL is then compared with the SOGI-PLL in terms of stability and transient performance. Finally, experimental results are presented to demonstrate the effectiveness of FFSOGI-PLL.
Xiao, F, Dong, L, Li, L & Liao, X 2017, 'Fast voltage detection method for grid‐tied renewable energy generation systems under distorted grid voltage conditions', IET Power Electronics, vol. 10, no. 12, pp. 1487-1493.
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A fast voltage detection method to assist with the low‐voltage ride‐through operation of grid‐tied renewable energy generation systems is proposed in this study. It is designed to detect every phase voltage, so that it can be applied in both three‐phase and single‐phase applications. The whole voltage detection approach consists of two stages, the pre‐filtering stage and the voltage detection stage. In the pre‐filtering stage, a cascaded delayed signal cancellation (CDSC) module and a low‐pass filter are connected in series to filter low‐order harmonics and high‐frequency noises. For eliminating the low‐order harmonics of interest, different types of CDSC methods are studied in detail. Subsequently, a new orthogonal signal generator is built to calculate the voltage amplitude in the voltage detection stage. Finally, the proposed voltage detection method is verified by experimental results.
Xiao, T, Nghiem, LD, Song, J, Bao, R, Li, X & He, T 2017, 'Phenol rejection by cellulose triacetate and thin film composite forward osmosis membranes', Separation and Purification Technology, vol. 186, pp. 45-54.
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© 2017 Elsevier B.V. This study aims to elucidate the separation of phenol by reverse osmosis (RO) and forward osmosis (FO) modes and propose strategies to enhance phenol rejection by these two processes. The results show that phenol rejection was strongly influenced by water flux, membrane materials, membrane structure, modes of operation, and feed solution chemistry (i.e. pH). The relationship between phenol rejection and water flux was demonstrated by the irreversible thermodynamic model which could accurately simulate phenol rejection as a function of water flux. At pH 7, phenol rejection by cellulose acetate (CTA) membranes was negligible while the thin film composite (TFC) polyamide (PA) membranes exhibited much higher phenol rejection. Through a systematic static adsorption experiment, results in this study show that phenol adsorption to CTA material was about 20 times higher than that to PA material. Thus, the observed higher phenol rejection by TFC PA compared to CTA membranes was attributed to the significantly higher affinity of phenol toward CTA and the sorption diffusion transport mechanism of phenol through the membrane. In particular, a TFC PA membrane specific for FO operation was prepared in this study. In FO mode, the tailor-made TFC PA membrane showed a slightly higher phenol rejection and a much higher water permeability compared to the commercial membrane. At the same water flux and solution pH, phenol rejection in FO mode was consistently higher than in RO mode. This observation could possibly be attributed to the reverse diffusion of draw solutes in the FO mode which hinders the forward diffusion of phenol through the membrane. A significant increase in phenol rejection was achieved by increasing the feed pH above the dissociation constant of the compound.
Xie, K, Fu, Q, Kim, J, Lu, H, He, Y, Zhao, Q, Scofield, J, Webley, PA & Qiao, GG 2017, 'Increasing both selectivity and permeability of mixed-matrix membranes: Sealing the external surface of porous MOF nanoparticles', Journal of Membrane Science, vol. 535, pp. 350-356.
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A novel approach to improve the selectivity of mixed matrix membrane (MMM) systems was developed. MOF nanoparticles (NPs) were chemical coated by a PEG based shell and then incorporated into a polymer matrix to yield a MMM. The unique design of the core-shell MOF NPs can enhance both the membrane permeability and selectivity simultaneously. This membrane material exhibits excellent CO2/N2 separation performance that surpasses the latest upper bound through the most direct way. This filler was also applied to the thin-film composite membrane system, showing promising performance and placing it in the optimal zone for post-combustion CO2 capture.
Xie, S, Wickham, R & Nghiem, LD 2017, 'Synergistic effect from anaerobic co-digestion of sewage sludge and organic wastes', International Biodeterioration & Biodegradation, vol. 116, pp. 191-197.
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© 2016 Anaerobic mono-digestion and co-digestion of primary sludge and two organic wastes (namely food waste or paper pulp reject) were evaluated by biomethane potential assessment and kinetics modelling to elucidate the synergistic effect. The specific methane yields were 159, 652 and 157 mL/g VS added during mono-digestion of primary sludge, food waste and paper pulp reject, respectively. Co-digestion of primary sludge with either food waste or paper pulp reject resulted in much higher specific methane yields of 799 and 368 mL/g VS, respectively. pH and intermediate inhibitions (e.g. volatile fatty acids and ammonium-N) were not observed. The synergistic effect was also confirmed by examining the VS and COD removals. COD balance also identified and validated the enhanced specific methane yields from both primary sludge and organic waste (i.e. additional 32 and 19% of COD was converted to biogas during co-digestion of primary sludge with food waste or paper pulp reject, respectively). The apparent first order rate constant derived from kinetics modelling increased from 0.18 to 0.63 d−1 during mono-digestion of paper pulp reject and co-digestion of primary sludge with paper pulp reject, which can be attributed to the initial high soluble biodegradable fraction in primary sludge.
Xie, T, Xie, S, Sivakumar, M & Nghiem, LD 2017, 'Relationship between the synergistic/antagonistic effect of anaerobic co-digestion and organic loading', International Biodeterioration & Biodegradation, vol. 124, pp. 155-161.
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© 2017 Results from this study reveal a notable relationship between the synergistic/antagonistic performance of sewage sludge – food waste anaerobic co-digestion (AcoD) and organic loading. At the same sewage sludge content, biomethane potential assays show an increasing specific methane yield as the content of food waste increased to the optimum organic loading of 15 kg VS/m3. Under these conditions, the specific methane yields experimentally measured in this study were considerably higher than those calculated by adding the specific methane individual co-substrates during mono-digestion. On the other hand, at above the optimum organic loading value, the antagonistic effect (i.e. lower specific methane yield compared to mono-digestion) was observed. The relationship between synergistic performance of AcoD and organic loading was also evidenced in the removal of volatile solids as well as chemical oxygen demand. Further analysis of the intermediate products show that methanogenesis was the rate limiting step during AcoD at a high organic loading value. As the organic loading increased, the digestion lag phase increased and the hydrolysis rate decreased.
Xu, B, Ahmed, MB, Zhou, JL, Altaee, A, Wu, M & Xu, G 2017, 'Photocatalytic removal of perfluoroalkyl substances from water and wastewater: Mechanism, kinetics and controlling factors', Chemosphere, vol. 189, pp. 717-729.
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© 2017 Elsevier Ltd This review focuses on heterogeneous photocatalysis of perfluoroalkyl substances (PFAS) which are of worldwide concern as emerging persistent organic contaminants. Heterogeneous photocatalysis is an effective and advanced technology for PFAS removal from water with relatively high efficacy. During photocatalysis, various short chain perfluorocarboxylic acids (PFCA) are produced as intermediates and the efficacy is related to the photo-generated hole (h+) and photo-generated electron (e−). PFAS photodegradation in water under UV irradiation is most effective by using In2O3 as the catalyst, followed by Ga2O3 and TiO2. Significantly, modifying the chemical composition or morphology of the catalyst can improve its efficacy for PFAS removal. In2O3 porous nanoplates were found to have the best performance of 100% PFAS decomposition under UV light with rate constant (kt) and half-time (τ1/2) of 0.158 min−1 and 4.4 min, respectively. Catalysts perform well in acidic solution and increasing temperature to a certain extent. The photocatalytic performance is reduced when treating wastewater due to the presence of dissolved organic matter (DOM), with the catalysts following the order: needle-like Ga2O3 > In2O3 > TiO2. Future studies should focus on the development of novel photocatalysts, and their immobilization and application for PFAS removal in wastewater.
Xu, C, Han, Z, Zhao, G & Yu, S 2017, 'A Sleeping and Offloading Optimization Scheme for Energy-Efficient WLANs', IEEE Communications Letters, vol. 21, no. 4, pp. 877-880.
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In this letter, we propose an access point (AP) sleeping and user offloading optimization scheme to improve energy efficiency in densely deployed WLANs. Through real trace analysis, we investigate AP energy efficiency to obtain the sleep-awake threshold, which is used to select sleep or awake APs according to real-time status information monitored on controller. Moreover, we formulate the user offloading problem as a reverse auction process to optimize energy efficiency of APs involved in offloading. Simulation results demonstrate that, comparing to traditional methods, our scheme can achieve up to 20% energy saving while maintaining effective system coverage and throughput.
Xu, C, Jin, W, Zhao, G, Tianfield, H, Yu, S & Qu, Y 2017, 'A Novel Multipath-Transmission Supported Software Defined Wireless Network Architecture', IEEE Access, vol. 5, pp. 2111-2125.
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The inflexible management and operation of today's wireless access networks cannot meet the increasingly growing specific requirements, such as high mobility and throughput, service differentiation, and high-level programmability. In this paper, we put forward a novel multipath-transmission supported software-defined wireless network architecture (MP-SDWN), with the aim of achieving seamless handover, throughput enhancement, and flow-level wireless transmission control as well as programmable interfaces. In particular, this research addresses the following issues: 1) for high mobility and throughput, multi-connection virtual access point is proposed to enable multiple transmission paths simultaneously over a set of access points for users and 2) wireless flow transmission rules and programmable interfaces are implemented into mac80211 subsystem to enable service differentiation and flow-level wireless transmission control. Moreover, the efficiency and flexibility of MP-SDWN are demonstrated in the performance evaluations conducted on a 802.11 based-testbed, and the experimental results show that compared to regular WiFi, our proposed MP-SDWN architecture achieves seamless handover and multifold throughput improvement, and supports flow-level wireless transmission control for different applications.
Xu, J, Wu, C, Li, J & Cui, J 2017, 'Simplified finite element method analysis of ultra-high-performance fibre-reinforced concrete columns under blast loads', Advances in Structural Engineering, vol. 20, no. 1, pp. 139-151.
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Ultra-high-performance fibre-reinforced concrete has exceptional mechanical properties including high compressive and tensile strength as well as high fracture energy. It has been proved to be much higher blast resistant than normal concrete. In this article, flexural behaviours of ultra-high-performance fibre-reinforced concrete columns were investigated through full-scale tests. Two 200 mm × 200 mm × 2500 mm columns with and without axial loading were investigated under three-point bending tests, and their load–displacement relationships were recorded and the moment curvatures were derived. The derived moment curvature relationships of ultra-high-performance fibre-reinforced concrete columns were then incorporated into a computationally efficient one-dimensional finite element model, which utilized Timoshenko beam theory, to determine flexural response of ultra-high-performance fibre-reinforced concrete columns under blast loading. After that, the one-dimensional finite element model was validated with the real blast testing data. The results show good correlation between the advanced finite element model and experimental results. The feasibility of utilizing the one-dimensional finite element model for simulating both high-strength reinforced concrete and ultra-high-performance fibre-reinforced concrete columns against blast loading conditions is confirmed.
Xu, Q, Li, X, Ding, R, Wang, D, Liu, Y, Wang, Q, Zhao, J, Chen, F, Zeng, G, Yang, Q & Li, H 2017, 'Understanding and mitigating the toxicity of cadmium to the anaerobic fermentation of waste activated sludge', Water Research, vol. 124, pp. 269-279.
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© 2017 Elsevier Ltd Cadmium (Cd) is present in significant levels in waste activated sludge, but its potential toxicities on anaerobic fermentation of sludge remain largely unknown. This work therefore aims to provide such support. Experimental results showed that the impact of Cd on short-chain fatty acids (SCFA) production from sludge anaerobic fermentation was dose-dependent. The presence of environmentally relevant level of Cd (e.g., 0.1 mg/g VSS) enhanced SCFA production by 10.6%, but 10 mg/g VSS of Cd caused 68.1% of inhibition. Mechanism exploration revealed that although all levels of Cd did not cause extra leakage of intracellular substrates, 0.1 mg/g VSS Cd increased the contents of both soluble and loosely-bound extracellular polymeric substances (EPS), thereby benefitting sludge solubilization. On the contrary, 10 mg/g VSS Cd decreased the levels of all EPS layers, which reduced the content of soluble substrates. It was also found that 0.1 mg/g VSS Cd benefited both the hydrolysis and acidogenesis but 10 mg/g VSS Cd inhibited all the hydrolysis, acidogenesis, and methanogenesis processes. Further investigations with microbial community and enzyme analysis showed that the pertinent presence of Cd enhanced the activities of protease, acetate kinase, and oxaloacetate transcarboxylase whereas 10 mg/g VSS Cd decreased the microbial diversity, the abundances of functional microbes, and the activities of key enzymes. Finally, one strategy that could effectively mitigate the adverse impact of high Cd levels on SCFA production was proposed and examined. This work provides insights into Cd-present sludge fermentation systems, and the findings obtained may guide engineers to manipulate sludge treatment systems in the future.
Xu, R, Chen, J & Zhu, X 2017, 'A hybrid approach for parameter optimization of multiple tuned mass dampers in reducing floor vibrations due to occupant walking: Theory and parametric studies', Advances in Structural Engineering, vol. 20, no. 8, pp. 1232-1246.
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This article presents a hybrid approach for determining optimal parameters of multiple tuned mass dampers to reduce the floor vibration due to human walking. The proposed approach consists of two parts. The first one is a partial mode decomposition algorithm to efficiently calculate dynamic responses of the coupled floor–multiple tuned mass damper system subjected to moving walking loads. The second one is an adaptive genetic simulated annealing method for the optimization of multiple tuned mass damper parameters. To establish optimization, certain variables must be considered. These include the mass, natural frequency, and damping ratio of each tuned mass damper in a multiple tuned mass damper system. The objective is to minimize floor responses and remove unreasonable requirements, such as uniform mass distribution and symmetric distribution of the tuned mass damper frequency. The proposed hybrid approach has successfully been applied to optimize the multiple tuned mass damper system to reduce the vibration of a long-span floor with closely spaced modes. By the hybrid approach, an extensive parametric study has been carried out. The results show that different walking load models and uncertainties in the dynamic properties of the floor and each tuned mass damper itself can affect the overall performance of the multiple tuned mass damper system. The proposed hybrid optimization approach is very effective and the resulting multiple tuned mass damper system is robust in reducing floor vibrations under various conditions.
Xu, S, Liu, Z & Wu, C 2017, 'Numerical simulation and test validation for ultra-high performance steel fiber reinforced concrete-filled double skin steel tube column under blast loading', Zhendong yu Chongji/Journal of Vibration and Shock, vol. 36, no. 1, pp. 45-54.
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A 3D FE model was developed to analyze dynamic response and damage mechanism of a UHPSFRCFDST(Ultra-High Performance Steel Fiber Reinforced Concrete Filled Double Skin Steel Tube)column under blast loading, they were validated through comparison of simulated results and blast testing ones of the UHPSFRCFDST column. The effects of main variables including hollow ratios, steel ratios, and thicknesses and strengths of inner steel tube and outer steel one on the blast resistant performance of the UHPSFRCFDST column were investigated by utilizing the 3D FE model. The results indicated that the UHPSFRCFDST column has excellent anti-blast performances, and the proposed 3D FEM model can be used to analyze the dynamic response of the UHPSFRCFDST column under blast loading efficiently; reducing hollow ratio and increasing strength of outer steel tube in certain ranges can enhance effectively the blast resistant performance of the UHPSFRCFDST column; increasing steel ratio and reducing height to thickness ratios of inner and outer steel tubes can significantly improve the blast resistant performance of the UHPSFRCFDST column; the strength of inner steel tube has a little effect on the blast resistant performance of the UHPSFRCFDST column, but increasing the strength of outer steel tube in a certain range can improve the blast resistant performance of the UHPSFRCFDST column significantly.
Xu, S, Wu, C, Liu, Z, Han, K, Su, Y, Zhao, J & Li, J 2017, 'Experimental investigation of seismic behavior of ultra-high performance steel fiber reinforced concrete columns', Engineering Structures, vol. 152, pp. 129-148.
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© 2017 Elsevier Ltd This paper presents an experimental study on seismic behavior of ultra-high performance steel fiber reinforced concrete (UHPSFRC) columns. Based on a series of cyclic loading tests on 14 UHPSFRC specimens subjected to combined static axial loading and cyclic lateral loading, the investigation and analysis have been carried out on crack status, failure modes, hysteretic loops, skeleton curves, strength and stiffness degradation, energy dissipation capacity and ductility of UHPSFRC columns. The influence of stirrup spacing, type of stirrup, axial compression ratio and shear span ratio on the seismic performance of UHPSFRC columns was also investigated in details. The experiment results show that three typical failure modes are observed, i.e., flexural, flexural-shear and shear failure mode. The existence of steel fiber could prevent the cracked concrete from spalling efficiently and delay the bulking of longitudinal reinforcement further. It noteworthy that the limit plastic drift ratio of all columns changes from 0.036 to 0.061, indicating that the UHPSFRC columns represent a good ductility which is obviously different from the conventional high strength concrete columns that exhibit much more brittleness with the increase of strength.
Xu, X, Clarke, C, Ma, C, Casillas, G, Das, M, Guan, M, Liu, D, Wang, L, Tadich, A, Du, Y, Ton-That, C & Jin, D 2017, 'Depth-profiling of Yb3+ sensitizer ions in NaYF4 upconversion nanoparticles', Nanoscale, vol. 9, no. 23, pp. 7719-7726.
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© 2017 The Royal Society of Chemistry. Enhancing the efficiency of upconversion nanoparticles (UCNPs) and therefore their brightness is the critical goal for this emerging material to meet growing demands in many potential applications including sensing, imaging, solar energy conversion and photonics. The distribution of the photon sensitizer and activator ions that form a network of energy transfer systems within each single UCNP is vital for understanding and optimizing their optical properties. Here we employ synchrotron-based X-ray Photoelectron Spectroscopy (XPS) to characterize the depth distribution of Yb3+ sensitizer ions in host NaYF4 nanoparticles and systematically correlate the structure with the optical properties for a range of UCNPs with different sizes and doping concentrations. We find a radial gradient distribution of Yb3+ from the core to the surface of the NaYF4 nanoparticles, regardless of their size or the sensitizer's concentration. Energy dispersive X-ray Spectroscopy (EDX) was also used to further confirm the distribution of the sensitizer ions in the host matrix. These results have profound implications for the upconversion optical property variations.
Xu, X, Liu, Z, Wang, Z, Sheng, QZ, Yu, J & Wang, X 2017, 'S-ABC: A paradigm of service domain-oriented artificial bee colony algorithms for service selection and composition', Future Generation Computer Systems, vol. 68, pp. 304-319.
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Xu, X-J, Chen, C, Wang, A-J, Ni, B-J, Guo, W-Q, Yuan, Y, Huang, C, Zhou, X, Wu, D-H, Lee, D-J & Ren, N-Q 2017, 'Mathematical modeling of simultaneous carbon-nitrogen-sulfur removal from industrial wastewater', Journal of Hazardous Materials, vol. 321, pp. 371-381.
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© 2016 Elsevier B.V. A mathematical model of carbon, nitrogen and sulfur removal (C-N-S) from industrial wastewater was constructed considering the interactions of sulfate-reducing bacteria (SRB), sulfide-oxidizing bacteria (SOB), nitrate-reducing bacteria (NRB), facultative bacteria (FB), and methane producing archaea (MPA). For the kinetic network, the bioconversion of C-N by heterotrophic denitrifiers (NO3− → NO2− → N2), and that of C-S by SRB (SO42− → S2−) and SOB (S2− → S0) was proposed and calibrated based on batch experimental data. The model closely predicted the profiles of nitrate, nitrite, sulfate, sulfide, lactate, acetate, methane and oxygen under both anaerobic and micro-aerobic conditions. The best-fit kinetic parameters had small 95% confidence regions with mean values approximately at the center. The model was further validated using independent data sets generated under different operating conditions. This work was the first successful mathematical modeling of simultaneous C-N-S removal from industrial wastewater and more importantly, the proposed model was proven feasible to simulate other relevant processes, such as sulfate-reducing, sulfide-oxidizing process (SR-SO) and denitrifying sulfide removal (DSR) process. The model developed is expected to enhance our ability to predict the treatment of carbon-nitrogen-sulfur contaminated industrial wastewater.
Xu, Y, Radjenovic, J, Yuan, Z & Ni, B-J 2017, 'Biodegradation of atenolol by an enriched nitrifying sludge: Products and pathways', Chemical Engineering Journal, vol. 312, pp. 351-359.
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© 2016 Elsevier B.V. Biodegradation of β-blocker atenolol was investigated using an enriched nitrifying culture at controlled ammonium concentration and without ammonium addition. Analysis of the kinetics and structural elucidation of biodegradation products showed that atenolol biodegradation was found to be linked to the activity of nitrifying bacteria in the presence of ammonium. Atenolol was degraded cometabolically by ammonia-oxidizing bacteria (AOB), likely due to a broad substrate range of ammonia monooxygenase (AMO). Four products were formed during atenolol biodegradation with ammonia oxidation, including P267 (atenolol acid) and three new products P117 (1-isopropylamino-2-propanol), P167 (1-amino-3-phenoxy-2-propanol), and an unknown product P227 with a nominal molecular mass of 227. In comparison, only P267 and P227 were identified during atenolol biodegradation without ammonia oxidation. Follow-up experiments using atenolol acid as the parent compound indicated the formation of products P117, P167 and P227 in the presence of ammonium. Based on the products identified, a tentative biodegradation pathway of atenolol is suggested, which involves two steps independent of the presence of ammonium: i) microbial amide-bond hydrolysis to carboxyl group and formation of P267 (atenolol acid) and ii) a possible formation of P227 with its unidentified structure and other two cometabolically induced reactions: iii) breakage of ether bond in the alkyl side chain and formation of P117 and iv) a minor pathway through N-dealkylation and loss of acetamide moiety from the aromatic ring, yielding P167. This study provided an important insight regarding the biotransformation pathways under different metabolic conditions.
Xu, Y, Wu, C, Zheng, K, Wang, X, Niu, X & Lu, T 2017, 'Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection', Security and Communication Networks, vol. 2017, pp. 1-14.
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Android malware detection is a complex and crucial issue. In this paper, we propose a malware detection model using a support vector machine (SVM) method based on feature weights that are computed by information gain (IG) and particle swarm optimization (PSO) algorithms. The IG weights are evaluated based on the relevance between features and class labels, and the PSO weights are adaptively calculated to result in the best fitness (the performance of the SVM classification model). Moreover, to overcome the defects of basic PSO, we propose a new adaptive inertia weight method called fitness-based and chaotic adaptive inertia weight-PSO (FCAIW-PSO) that improves on basic PSO and is based on the fitness and a chaotic term. The goal is to assign suitable weights to the features to ensure the best Android malware detection performance. The results of experiments indicate that the IG weights and PSO weights both improve the performance of SVM and that the performance of the PSO weights is better than that of the IG weights.
Xu, Y, Yuan, Z & Ni, B-J 2017, 'Biotransformation of acyclovir by an enriched nitrifying culture', Chemosphere, vol. 170, pp. 25-32.
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© 2016 Elsevier Ltd This work evaluates the biodegradation of the antiviral drug acyclovir by an enriched nitrifying culture during ammonia oxidation and without the addition of ammonium. The study on kinetics was accompanied with the structural elucidation of biotransformation products through batch biodegradation experiments at two different initial levels of acyclovir (15 mg L−1 and 15 μg L−1). The pseudo first order kinetic studies of acyclovir in the presence of ammonium indicated the higher degradation rates under higher ammonia oxidation rates than those constant degradation rates in the absence of ammonium. The positive correlation was found between acyclovir degradation rate and ammonia oxidation rate, confirming the cometabolism of acyclovir by the enriched nitrifying culture in the presence of ammonium. Formation of the product carboxy-acyclovir (P239) indicated the main biotransformation pathway was aerobic oxidation of the terminal hydroxyl group, which was independent on the metabolic type (i.e. cometabolism or metabolism). This enzyme-linked reaction might be catalyzed by monooxygenase from ammonia oxidizing bacteria or heterotrophs. The formation of carboxy-acyclovir was demonstrated to be irrelevant to the acyclovir concentrations applied, indicating the revealed biotransformation pathway might be the dominant removal pathway of acyclovir in wastewater treatment.
Xu, Y, Yuan, Z & Ni, B-J 2017, 'Impact of Ammonium Availability on Atenolol Biotransformation during Nitrification', ACS Sustainable Chemistry & Engineering, vol. 5, no. 8, pp. 7137-7144.
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© 2017 American Chemical Society. The impact of ammonium availability on atenolol biotransformation at an environmentally relevant level of 15 μgL-1 by enriched nitrifying cultures was investigated in terms of atenolol degradation kinetics and biotransformation product formation dynamics. Different concentrations of growth substrate ammonium (0, 25, and 50 mg-NL-1) were applied constantly during batch experiments. The results suggested the higher ammonium concentrations led to lower atenolol removal rates probably due to the substrate competition between ammonium and atenolol. The formation of the biotransformation product atenolol acid was positively related to the ammonium oxidation activity, resulting in a higher amount at the end of experiments at higher ammonium concentrations. Linear correlations between ammonia oxidation rate and atenolol degradation rate at ammonium levels of 25 and 50 mg-NL-1 suggested the cometabolism of atenolol by ammonia oxidizing bacteria (AOB) in the presence of ammonium. The biotransformation reaction, i.e., hydroxylation on amide group to carboxylic group, could be catalyzed by the nonspecific ammonia monooxygenase (AMO) of AOB. Comparison between atenolol degradation at ammonium levels of 0 and 50 mg-NL-1 demonstrated the formation of atenolol acid was independent of the ammonium availability. This work might give further indication of how to prevent pharmaceuticals from entering into the environment.
Xu, Z 2017, 'Crowdsourcing based Timeline Description of Urban Emergency Events using Social Media', International Journal of Ad Hoc and Ubiquitous Computing, vol. 25, no. 1/2, pp. 1-1.
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Crowdsourcing is a newly emerging service platform and business model in theInternet. Analysis and description about urban emergency events, e.g., fires, storms and trafficjams are of great importance to protect the security of humans. Recently, social media feedsare rapidly emerging as a novel platform for providing and dissemination of information that isoften geographic. In this paper, in order to describe the timeline of real-time urban emergencyevents, the new web mining task timeline description (TD) is proposed. Firstly, the relatedinformation of an urban emergency event is extracted from Weibo messages. Secondly, the validmessage including the semantic or spatial information is detected in this step. Thirdly, detectedvalid messages are used to build the TD. Case studies on real datasets show the proposed modelhas good performance and high effectiveness in the analysis and description of urban emergency events.
Xu, Z, Liu, Y, Xuan, J, Chen, H & Mei, L 2017, 'Crowdsourcing based social media data analysis of urban emergency events', Multimedia Tools and Applications, vol. 76, no. 9, pp. 11567-11584.
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Xu, Z, Xuan, J, Liu, Y, Choo, K-KR, Mei, L & Hu, C 2017, 'Building spatial temporal relation graph of concepts pair using web repository', Information Systems Frontiers, vol. 19, no. 5, pp. 1029-1038.
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Xu, Z, Yan, J, Xu, RY & Mei, L 2017, 'Guest Editorial: Visual Multimedia Learning from Big Surveillance Data', Multimedia Tools and Applications, vol. 76, no. 13, pp. 14557-14557.
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Xu, Z-Q, Elbadawi, C, Tran, TT, Kianinia, M, Li, X, Liu, D, Hoffman, TB, Nguyen, M, Kim, S, Edgar, JH, Wu, X, Song, L, Ali, S, Ford, M, Toth, M & Aharonovich, I 2017, 'Single Photon Emission from Plasma Treated 2D Hexagonal Boron Nitride', Nanoscale, vol. 10, no. 17, pp. 7957-7965.
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Artificial atomic systems in solids are becoming increasingly importantbuilding blocks in quantum information processing and scalable quantumnanophotonic networks. Yet, synthesis of color centers that act as singlephoton emitters which are suitable for on-chip applications is still beyondreach. Here, we report a number of plasma and thermal annealing methods for thefabrication of emitters in tape-exfoliated hexagonal boron nitride (hBN)crystals. A two-step process comprised of Ar plasma etching and subsequentannealing in Ar is highly robust, and yields a seven-fold increase in theconcentration of emitters in hBN. The initial plasma etching step generatesemitters that suffer from blinking and bleaching, whereas the two-step processyields emitters that are photostable at room temperature and have an emissionenergy distribution that is red-shifted relative to that of pristine hBN. Ananalysis of emitters fabricated by a range of plasma and annealing treatments,combined with a theoretical investigation of point defects in hBN indicatesthat single photon emitters characterized by a high degree of photostabilityand emission wavelengths greater than ~700 nm are associated with defectcomplexes that contain oxygen. This is further confirmed by generating theemitters by annealing hBN in an oxidative atmosphere. Our findings advancepresent understanding of the structure of quantum emitter in hBN and enhancethe nanofabrication toolkit that is needed to realize integrated quantumnanophotonics based on 2D materials.
Xuan, J, Lu, J, Zhang, G & Xu, RYD 2017, 'Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization', Artificial Intelligence, vol. 271, pp. 43-73.
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The cooperative hierarchical structure is a common and significant datastructure observed in, or adopted by, many research areas, such as: text mining(author-paper-word) and multi-label classification (label-instance-feature).Renowned Bayesian approaches for cooperative hierarchical structure modelingare mostly based on topic models. However, these approaches suffer from aserious issue in that the number of hidden topics/factors needs to be fixed inadvance and an inappropriate number may lead to overfitting or underfitting.One elegant way to resolve this issue is Bayesian nonparametric learning, butexisting work in this area still cannot be applied to cooperative hierarchicalstructure modeling. In this paper, we propose a cooperative hierarchical Dirichlet process (CHDP)to fill this gap. Each node in a cooperative hierarchical structure is assigneda Dirichlet process to model its weights on the infinite hidden factors/topics.Together with measure inheritance from hierarchical Dirichlet process, twokinds of measure cooperation, i.e., superposition and maximization, are definedto capture the many-to-many relationships in the cooperative hierarchicalstructure. Furthermore, two constructive representations for CHDP, i.e.,stick-breaking and international restaurant process, are designed to facilitatethe model inference. Experiments on synthetic and real-world data withcooperative hierarchical structures demonstrate the properties and the abilityof CHDP for cooperative hierarchical structure modeling and its potential forpractical application scenarios.
Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2017, 'A Bayesian nonparametric model for multi-label learning', Machine Learning, vol. 106, no. 11, pp. 1787-1815.
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© 2017, The Author(s). Multi-label learning has become a significant learning paradigm in the past few years due to its broad application scenarios and the ever-increasing number of techniques developed by researchers in this area. Among existing state-of-the-art works, generative statistical models are characterized by their good generalization ability and robustness on large number of labels through learning a low-dimensional label embedding. However, one issue of this branch of models is that the number of dimensions needs to be fixed in advance, which is difficult and inappropriate in many real-world settings. In this paper, we propose a Bayesian nonparametric model to resolve this issue. More specifically, we extend a Gamma-negative binomial process to three levels in order to capture the label-instance-feature structure. Furthermore, a mixing strategy for Gamma processes is designed to account for the multiple labels of an instance. The mixed process also leads to a difficulty in model inference, so an efficient Gibbs sampling inference algorithm is then developed to resolve this difficulty. Experiments on several real-world datasets show the performance of the proposed model on multi-label learning tasks, comparing with three state-of-the-art models from the literature.
Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2017, 'Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 7, pp. 1357-1369.
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© 2016 IEEE. Traditional relational topic models provide a successful way to discover the hidden topics from a document network. Many theoretical and practical tasks, such as dimensional reduction, document clustering, and link prediction, could benefit from this revealed knowledge. However, existing relational topic models are based on an assumption that the number of hidden topics is known a priori, which is impractical in many real-world applications. Therefore, in order to relax this assumption, we propose a nonparametric relational topic model using stochastic processes instead of fixed-dimensional probability distributions in this paper. Specifically, each document is assigned a Gamma process, which represents the topic interest of this document. Although this method provides an elegant solution, it brings additional challenges when mathematically modeling the inherent network structure of typical document network, i.e., two spatially closer documents tend to have more similar topics. Furthermore, we require that the topics are shared by all the documents. In order to resolve these challenges, we use a subsampling strategy to assign each document a different Gamma process from the global Gamma process, and the subsampling probabilities of documents are assigned with a Markov Random Field constraint that inherits the document network structure. Through the designed posterior inference algorithm, we can discover the hidden topics and its number simultaneously. Experimental results on both synthetic and real-world network datasets demonstrate the capabilities of learning the hidden topics and, more importantly, the number of topics.
Xuan, J, Luo, X, Lu, J & Zhang, G 2017, 'Explicitly and implicitly exploiting the hierarchical structure for mining website interests on news events', Information Sciences, vol. 420, pp. 263-277.
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© 2017 Elsevier Inc. After a news event, many different websites publish coverage of that event, each expressing their own unique commentary, perspectives, and viewpoints. Websites form around a specific set of interests to cater to different audiences, and discovering these interests can help audiences C especially people and organizations that are interested in news C select the most appropriate websites to use as their sources of information. This paper presents three methods for formally defining and mining a websites interests, each of which is explicitly or implicitly based on a hierarchial structure: website-webpage-keyword. The first, and most straightforward, method explicitly uses keyword-layer network communities and the mapping relations between websites and keywords. The second method expands upon the first method with an iterative algorithm that combines both the mapping relations and the network relations from the website-webpage-keyword structure to further refine the keyword-layer network communities. In the third method, a website topic model implicitly captures the mapping relations among the websites, webpages, and keywords. The performance of three proposed methods in website interest mining is compared using a bespoke evaluation metric. The experimental results show that the iterative procedure designed in the second method is able to improve website interest mining performance, and the website topic model in the third method achieves the best performance among the three methods.
Yan, Y, Sencadas, V, Jin, T, Huang, X, Chen, J, Wei, D & Jiang, Z 2017, 'Tailoring the wettability and mechanical properties of electrospun poly(l-lactic acid)-poly(glycerol sebacate) core-shell membranes for biomedical applications', Journal of Colloid and Interface Science, vol. 508, pp. 87-94.
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© 2017 Elsevier Inc. Tissue and biomedical engineering fields are in constant mutation and in searching for innovative processing techniques capable to tailor the material properties. In this work, poly(L-lactic acid) (PLLA) and elastomeric poly(glycerol sebacate) (PGS) were dissolved in the same solvents and electrospun together, in a single needle system. A core-shell structure where the hydrophilic PGS was placed onto the surface of the hydrophobic PLLA fibre was obtained for elastomeric concentrations up to 25 wt%. It was found that the PLLA:PGS blends are immiscible and the blends present the melting temperatures of the individual polymers. Moreover, their surface properties were deeply influenced by the presence of the PGS, and a superhydrophilic membrane was obtained, after PGS curing at 120 °C for 48 h. When the concentration of PGS is up to 25 wt%, the blend's Young modulus decreases from ∼35.9 ± 7.1 to 7.5 ± 1.4 MPa and a twofold improvement in the sample stretchability was observed, compared with the pristine PLLA electrospun samples. Finally, in vitro hypothalamus A59 nerve cell culture shows that the core-shell electrospun samples enhanced cell adhesion and proliferation, suggesting that these developed materials have great potentials for nerve regeneration and biomedical engineering applications.
Yan, Y, Sencadas, V, Zhang, J, Wei, D & Jiang, Z 2017, 'Superomniphilic Poly(glycerol sebacate)–Poly(l‐lactic acid) Electrospun Membranes for Oil Spill Remediation', Advanced Materials Interfaces, vol. 4, no. 20, pp. 1700484-1700484.
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AbstractSuperomniphilic materials are defined as materials that can uptake both water and oil‐like liquids. In this study, a facile method to prepare a superomniphilic and biodegradable core–shell structure of poly(glycerol sebacate) (PGS) and poly(l‐lactic acid) (PLLA) is reported. The developed method immobilizes the PGS polymer onto the surface of the PLLA electrospun fibers, increasing the presence of hydroxyl groups on the surface of the membranes. The sample with 25 wt% PGS can uptake polar and apolar solvents, and presents a superhydrophilic behavior. The PGS‐PLLA composite is reusable up to 10 cycles of solvent (water of organic solvents) absorption with a separation efficiency of 99.5%, and its general appearance resembles the first absorption/compression cycle. Finally, this work presents a novel biodegradable polymeric blend membrane with superomniphilic properties, produced by a scalable process, which could be easily implemented to fight against environmental disasters such as large area oil spills.
Yan, Y, Sencadas, V, Zhang, J, Zu, G, Wei, D & Jiang, Z 2017, 'Processing, characterisation and electromechanical behaviour of elastomeric multiwall carbon nanotubes-poly (glycerol sebacate) nanocomposites for piezoresistive sensors applications', Composites Science and Technology, vol. 142, pp. 163-170.
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© 2017 Elsevier Ltd Highly stretchable elastomeric multiwall carbon nanotubes – poly (glycerol sebacate) (MWCNT-PGS) nanocomposites were prepared by mixing conductive multiwall carbon nanotubes (MWCNTs) with PGS prepolymer and curing at 120 °C. The incorporation of conductive filler increases the matrix crosslinking density and mechanical stiffness without loss of the flexibility and elasticity of the polymeric network with low mechanical hysteresis behaviour. The percolation threshold for the electrical conductivity was found to be ∼1 wt% of MWCNTs. The piezoresistive behaviour of the prepared samples shows a negative gauge factor (GF) between −0.5 and −0.8 under uniaxial tensile stress, probably due to geometrical factors, whilst under 3-point bending the calculated GF values were positive and a maximum GF = 42 was achieved for the samples with 2 wt% MWCNTs. Overall, the unique property combination between the MWCNTs and the PGS make them potentially suitable for the development of large deformation piezoresistive sensors, especially for biomedical engineering applications, flexible and wearable devices.
Yan, Y, Wu, Q, Tan, M, Ng, MK, Min, H & Tsang, IW 2017, 'Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 1-12.
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© 2012 IEEE. In this paper, we study the online heterogeneous transfer (OHT) learning problem, where the target data of interest arrive in an online manner, while the source data and auxiliary co-occurrence data are from offline sources and can be easily annotated. OHT is very challenging, since the feature spaces of the source and target domains are different. To address this, we propose a novel technique called OHT by hedge ensemble by exploiting both offline knowledge and online knowledge of different domains. To this end, we build an offline decision function based on a heterogeneous similarity that is constructed using labeled source data and unlabeled auxiliary co-occurrence data. After that, an online decision function is learned from the target data. Last, we employ a hedge weighting strategy to combine the offline and online decision functions to exploit knowledge from the source and target domains of different feature spaces. We also provide a theoretical analysis regarding the mistake bounds of the proposed approach. Comprehensive experiments on three real-world data sets demonstrate the effectiveness of the proposed technique.
Yang, H, Jiang, Z & Lu, H 2017, 'A Hybrid Wind Speed Forecasting System Based on a ‘Decomposition and Ensemble’ Strategy and Fuzzy Time Series', Energies, vol. 10, no. 9, pp. 1422-1422.
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Accurate and stable wind speed forecasting is of critical importance in the wind power industry and has measurable influence on power-system management and the stability of market economics. However, most traditional wind speed forecasting models require a large amount of historical data and face restrictions due to assumptions, such as normality postulates. Additionally, any data volatility leads to increased forecasting instability. Therefore, in this paper, a hybrid forecasting system, which combines the ‘decomposition and ensemble’ strategy and fuzzy time series forecasting algorithm, is proposed that comprises two modules—data pre-processing and forecasting. Moreover, the statistical model, artificial neural network, and Support Vector Regression model are employed to compare with the proposed hybrid system, which is proven to be very effective in forecasting wind speed data affected by noise and instability. The results of these comparisons demonstrate that the hybrid forecasting system can improve the forecasting accuracy and stability significantly, and supervised discretization methods outperform the unsupervised methods for fuzzy time series in most cases.
Yang, J, Jin, X, Wu, X, Acuna, P, Aguilera, RP, Morstyn, T & Agelidis, VG 2017, 'Decentralised control method for DC microgrids with improved current sharing accuracy', IET Generation, Transmission & Distribution, vol. 11, no. 3, pp. 696-706.
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A decentralised control method that deals with current sharing issues in dc microgrids (MGs) is proposed in this study. The proposed method is formulated in terms of ‘modified global indicator’ concept, which was originally proposed to improve reactive power sharing in ac MGs. In this work, the ‘modified global indicator’ concept is extended to coordinate dc MGs, which aims to preserve the main features offered by decentralised control methods such as no need of communication links, central controller or knowledge of the microgrid topology and parameters. This global indicator is inserted between current and voltage variables by adopting a virtual capacitor, which directly produces an output current sharing performance that is less relied on mismatches of the multi‐bus network. Meanwhile, a voltage stabiliser is complementary developed to maintain output voltage magnitude at steady state through a shunt virtual resistance. The operation under multiple dc‐buses is also included in order to enhance the applicability of the proposed controller. A detailed mathematical model including the effect of network mismatches is derived for analysis of the stability of the proposed controller. The feasibility and effectiveness of the proposed control strategy are validated by simulation and experimental results.
Yang, J, Ma, Y, Zhang, X, Li, S & Zhang, Y 2017, 'An Initialization Method Based on Hybrid Distance for k-Means Algorithm', Neural Computation, vol. 29, no. 11, pp. 3094-3117.
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The traditional [Formula: see text]-means algorithm has been widely used as a simple and efficient clustering method. However, the performance of this algorithm is highly dependent on the selection of initial cluster centers. Therefore, the method adopted for choosing initial cluster centers is extremely important. In this letter, we redefine the density of points according to the number of its neighbors, as well as the distance between points and their neighbors. In addition, we define a new distance measure that considers both Euclidean distance and density. Based on that, we propose an algorithm for selecting initial cluster centers that can dynamically adjust the weighting parameter. Furthermore, we propose a new internal clustering validation measure, the clustering validation index based on the neighbors (CVN), which can be exploited to select the optimal result among multiple clustering results. Experimental results show that the proposed algorithm outperforms existing initialization methods on real-world data sets and demonstrates the adaptability of the proposed algorithm to data sets with various characteristics.
Yang, J, Zhang, W, Zhang, Y, Wang, X & Lin, X 2017, 'Categorical top-k spatial influence query', World Wide Web, vol. 20, no. 2, pp. 175-203.
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© 2016 Springer Science+Business Media New York The influence of a spatial facility object depicts the importance of the object in the whole data space. In this paper, we present a novel definition of object influence in applications where objects are of different categories. We study the problem of Spatial Influence Query which considers the contribution of an object in forming functional units consisting of a given set of objects with different categories designated by users. We first show that the problem of spatial influence query is NP-hard with respect to the number of object categories in the functional unit. To tackle the computational hardness, we develop an efficient framework following two main steps, possible participants finding and optimal functional unit computation. Based on this framework, for the first step, novel and efficient pruning techniques are developed based on the nearest neighbor set (NNS) approach. To find the optimal functional unit efficiently, we propose two algorithms, an exact algorithm and an efficient approximate algorithm with performance guarantee. Comprehensive experiments on both real and synthetic datasets demonstrate the effectiveness and efficiency of our techniques.
Yang, N, Yee, J, Zheng, B, Gaiser, K, Reynolds, T, Clemon, L, Lu, WY, Schoenung, JM & Lavernia, EJ 2017, 'Process-Structure-Property Relationships for 316L Stainless Steel Fabricated by Additive Manufacturing and Its Implication for Component Engineering', Journal of Thermal Spray Technology, vol. 26, no. 4, pp. 610-626.
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© 2016, ASM International. We investigate the process-structure-property relationships for 316L stainless steel prototyping utilizing 3-D laser engineered net shaping (LENS), a commercial direct energy deposition additive manufacturing process. The study concluded that the resultant physical metallurgy of 3-D LENS 316L prototypes is dictated by the interactive metallurgical reactions, during instantaneous powder feeding/melting, molten metal flow and liquid metal solidification. The study also showed 3-D LENS manufacturing is capable of building high strength and ductile 316L prototypes due to its fine cellular spacing from fast solidification cooling, and the well-fused epitaxial interfaces at metal flow trails and interpass boundaries. However, without further LENS process control and optimization, the deposits are vulnerable to localized hardness variation attributed to heterogeneous microstructure, i.e., the interpass heat-affected zone (HAZ) from repetitive thermal heating during successive layer depositions. Most significantly, the current deposits exhibit anisotropic tensile behavior, i.e., lower strain and/or premature interpass delamination parallel to build direction (axial). This anisotropic behavior is attributed to the presence of interpass HAZ, which coexists with flying feedstock inclusions and porosity from incomplete molten metal fusion. The current observations and findings contribute to the scientific basis for future process control and optimization necessary for material property control and defect mitigation.
Yang, S, Cheema, MA, Lin, X, Zhang, Y & Zhang, W 2017, 'Reverse k nearest neighbors queries and spatial reverse top-k queries', The VLDB Journal, vol. 26, no. 2, pp. 151-176.
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© 2016, Springer-Verlag Berlin Heidelberg. Given a set of facilities and a set of users, a reverse k nearest neighbors (RkNN) query q returns every user for which the query facility is one of the k closest facilities. Almost all of the existing techniques to answer RkNN queries adopt a pruning-and-verification framework. Regions-based pruning and half-space pruning are the two most notable pruning strategies. The half-space-based approach prunes a larger area and is generally believed to be superior. Influenced by this perception, almost all existing RkNN algorithms utilize and improve the half-space pruning strategy. We observe the weaknesses and strengths of both strategies and discover that the regions-based pruning has certain strengths that have not been exploited in the past. Motivated by this, we present a new regions-based pruning algorithm called Slice that utilizes the strength of regions-based pruning and overcomes its limitations. We also study spatial reverse top-k (SRTk) queries that return every user u for which the query facility is one of the top-k facilities according to a given linear scoring function. We first extend half-space-based pruning to answer SRTk queries. Then, we propose a novel regions-based pruning algorithm following Slice framework to solve the problem. Our extensive experimental study on synthetic and real data sets demonstrates that Slice is significantly more efficient than all existing RkNN and SRTk algorithms.
Yang, S, Liu, X, Liu, Q, Guan, L, Lee, JM & Jung, KH 2017, 'A Study of Storm Surge Disasters Based on Extreme Value Distribution Theory', Journal of Coastal Research, vol. 336, pp. 1423-1435.
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Yang, S, McDonald, J, Hai, FI, Price, WE, Khan, SJ & Nghiem, LD 2017, 'Effects of thermal pre-treatment and recuperative thickening on the fate of trace organic contaminants during anaerobic digestion of sewage sludge', International Biodeterioration & Biodegradation, vol. 124, pp. 146-154.
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© 2017 This study examined the effects of thermal pre-treatment and recuperative thickening on anaerobic digestion of sewage sludge on biogas production and removal of trace organic contaminants (TrOCs). Thermal pre-treatment and recuperative thickening resulted in approximately 15% increase in biogas production. However, the effects of thermal pretreatement and recuperative thickening on anaerobic digestion performance in respect to the removal of TrOCs were less obvious and varied widely depending on the molecular properties of each compound. Of the 40 TrOCs monitored in this study, 16 TrOCs were detected in all primary sludge samples. Removal from the aqueous phase was negligible for most of these 16 TrOCs. Caffeine and paracetamol were the only two TrOCs with a high removal from the aqueous phase. In comparison to the aqueous phase, TrOC removal from the solid phase was considerably higher. Through a mass balance calculation, it was shown that thermal pre-treatment or a combination of thermal pre-treatment and recuperative thickening could enhance the biodegradation of five persistent TrOCs, namely TCEP, verapamil, clozapine, triclosan, and triclocarban by 17–50%.
Yang, S, McDonald, J, Hai, FI, Price, WE, Khan, SJ & Nghiem, LD 2017, 'The fate of trace organic contaminants in sewage sludge during recuperative thickening anaerobic digestion', Bioresource Technology, vol. 240, pp. 197-206.
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The aim of this work was to study the fate of trace organic contaminants (TrOCs) in sewage sludge during recuperative thickening anaerobic digestion. Sludge shearing at 3142s-1 for 5minutes improved biogas production. By contrast, shearing at ≥6283s-1 for 5minutes caused a notable reduction in biogas production and the removal of volatile solids. Results reported here showed the prevalent occurrence of 17 TrOCs in sewage sludge and highlights the importance of assessing TrOC removal via mass balance calculation by taking into account partitioning between the aqueous and solid phase as well as biodegradation. Hydrophilic and readily-biodegradable TrOCs (caffeine, trimethoprim, and paracetamol) were well removed and were not affected by shearing. TrOCs such as carbamazepine, gemfibrozil, and diuron showed biodegradation only at high shearing. It is possible that shearing can facilitate the circulation of TrOCs between aqueous and solid phases, thus, enhancing the biodegradation of some TrOCs.
Yang, S, Phan, HV, Bustamante, H, Guo, W, Ngo, HH & Nghiem, LD 2017, 'Effects of shearing on biogas production and microbial community structure during anaerobic digestion with recuperative thickening', Bioresource Technology, vol. 234, pp. 439-447.
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Recuperative thickening can intensify anaerobic digestion to produce more biogas and potentially reduce biosolids odour. This study elucidates the effects of sludge shearing during the thickening process on the microbial community structure and its effect on biogas production. Medium shearing resulted in approximately 15% increase in biogas production. By contrast, excessive or high shearing led to a marked decrease in biogas production, possibly due to sludge disintegration and cell lysis. Microbial analysis using 16S rRNA gene amplicon sequencing showed that medium shearing increased the evenness and diversity of the microbial community in the anaerobic digester, which is consistent with the observed improved biogas production. By contrast, microbial diversity decreased under either excessive shearing or high shearing condition. In good agreement with the observed decrease in biogas production, the abundance of Bacteroidales and Syntrophobaterales (which are responsible for hydrolysis and acetogenesis) decreased due to high shearing during recuperative thickening.
Yang, T, Yang, L, Guo, YJ & Yuan, J 2017, 'A Non-Orthogonal Multiple-Access Scheme Using Reliable Physical-Layer Network Coding and Cascade-Computation Decoding', IEEE Transactions on Wireless Communications, vol. 16, no. 3, pp. 1633-1645.
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© 2017 IEEE. This paper studies non-orthogonal transmission over a K -user fading multiple access channel. We propose a new reliable physical-layer network coding and cascade-computation decoding scheme. In the proposed scheme, K single-antenna users encode their messages by the same practical channel code and QAM modulation, and transmit simultaneously. The receiver chooses K linear coefficient vectors and computes the associated K layers of finite-field linear message combinations in a cascade manner. Finally, the K users' messages are recovered by solving the K linear equations. The proposed can be regarded as a generalized onion peeling. We study the optimal network coding coefficient vectors used in the cascade computation. Numerical results show the performance of the proposed approaches that of the iterative maximum a posteriori probability detection and decoding scheme, but without using receiver iteration. This results in considerable complexity reduction, processing delay, and easier implementation. Our proposed scheme significantly outperforms the iterative detection and decoding scheme with a single iteration, for example, by 1.7 dB for the two user case. The proposed scheme provides a competitive solution for non-orthogonal multiple access.
Yang, Y, Liu, H, Hou, ZJ, Zhu, X, Dutkiewicz, E & Xue, Q 2017, 'Compact On-Chip Bandpass Filter With Improved In-Band Flatness and Stopband Attenuation in 0.13- $\mu \text{m}$ (Bi)-CMOS Technology', IEEE Electron Device Letters, vol. 38, no. 10, pp. 1359-1362.
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© 1980-2012 IEEE. In this letter, an on-chip miniaturized bandpass filter (BPF) is presented, which is based on a grounded center-Tapped ring resonator (CTRR) with shunt capacitive loading. To analyze the principle of this design, a simple but effective equivalent circuit model is provided. Using this model, it is easy to show that the CTRR-based approach has a potential to generate two transmission poles within the passband. Compared with the conventional single-pole-based approach, this dual-pole design not only possesses a flexibility of controlling the passband width, but also has better flatness of insertion loss in the passband. In addition, this approach is able to significantly improve the stopband performance. To further demonstrate the feasibility of this approach in practice, the structure is implemented and fabricated in a commercial 0.13-μ (Bi)-CMOS SiGe technology. The measured results show that the BPF has a center frequency at 33 GHz with a bandwidth of 42.4%. The minimum insertion loss is 2.6 dB, while the stopband rejection is maintained to be better than 20 dB beyond 58 GHz. The chip, excluding the pads, is very compact at only 0.03 mm2 (0.11 × 0.28 mm2.
Yang, Y, Simorangkir, RBVB, Zhu, X, Esselle, K & Xue, Q 2017, 'A Novel Boresight and Conical Pattern Reconfigurable Antenna With the Diversity of 360° Polarization Scanning', IEEE Transactions on Antennas and Propagation, vol. 65, no. 11, pp. 5747-5756.
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© 1963-2012 IEEE. A novel design of boresight and conical pattern reconfigurable antenna with the capability of 360° polarization scanning is presented in this paper. At boresight mode, the antenna produces a continuously reconfigurable polarization over 360° in the azimuth plane, which provides adaptive-polarization reception between a transmitter and a receiver. The antenna is analyzed in terms of the electric field with an explanation of the generation of TM11 and TM02 resonant modes, which provides an innovative method of designing pattern reconfigurable antennas for the WLAN applications. The proposed method is validated by a good agreement between simulation and experimental results for an antenna designed to provide boresight and conical pattern switching at 2.4 GHz. The gain of 6.05 dBi and efficiency of 86.7% are measured in the boresight mode, corresponding to 4.39 dBi and 82.4% at conical mode.
Yang, Y, Zhu, X, Dutkiewicz, E & Xue, Q 2017, 'Design of a Miniaturized On-Chip Bandpass Filter Using Edge-Coupled Resonators for Millimeter-Wave Applications', IEEE Transactions on Electron Devices, vol. 64, no. 9, pp. 3822-3828.
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© 2017 IEEE. A unique miniaturization technique for on-chip passive device implemented in gallium arsenide (GaAs)-based technology is presented, which is based on edge-coupled cells (ECCs). The principle of an ECC is first studied by means of the equivalent LC circuits. Then, using the ECC as a baseline, a combination of different shorting-ground and tapping methods is fully investigated in terms of their impact on frequency responses. By directly shorting the specific edge-coupled fingers to the ground, an ECC can be converted into a resonator without increasing any physical size. To further demonstrate the feasibility of using this technique for miniaturized monolithic microwave integrated circuit design, an on-chip bandpass filter (BPF) is implemented and fabricated in a commercial 0.1-μ m GaAs technology. The measurement results show that the 3-dB bandwidth of the filter is from 21.2 to 26.5 GHz, while the insertion loss is less than 2.9 dB at 23 GHz. In addition, more than 30 dB of suppression is achieved from 0 to 15 GHz and from 44 to 54 GHz. The size of the BPF is only 640 × 280 μ m2, excluding the pads, which is equivalent to 0.17 × 0.08 λg2. (λg is the guided wavelength at 23.5 GHz.)
Yang, Y-C, Chen, C-C, Huang, C-S, Wang, C-T & Ong, H-C 2017, 'Developments of metallic anodes with various compositions and surfaces for the microbial fuel cells', International Journal of Hydrogen Energy, vol. 42, no. 34, pp. 22235-22242.
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Yao, K, Pradhan, B & Idrees, MO 2017, 'Identification of Rocks and Their Quartz Content in Gua Musang Goldfield Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery', Journal of Sensors, vol. 2017, pp. 1-8.
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Quartz is an important mineral element and the most abundant rock-forming mineral that controls the mineralogy of a reservoir. At the surface, quartz is more stable than most other rock minerals because it is made up of interlocking silica that makes it quite resistant to mechanical weathering. Quartz abundance is an indication of mineralization in many metal deposits; therefore, identification and mapping of quartz in rocks are of great value for exploration and resource potential assessments. In this study, thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery were used to identify quartz contained rocks in Gua Musang. First, the image was corrected for atmospheric effect and the study area subset for further processing. Thereafter, spectral transformation (principal component analysis (PCA)) was implemented on the TIR bands and the resulting principal component (PC) images were analysed. The three optimal PCs were selected using the strength of spectral interaction and the eigenvalues of each band. To discriminate between quartz-rich and quartz-poor rocks, RGB false colour composite and greyscale image of one of the PCs were analysed. The result shows that volcanogenic igneous rock and carbonate sedimentary rocks of Permian formation are quartz-poor while Triassic sedimentary rock made up of organic particles and sandstone is quartz-rich. On the contrary, the quartz content in the metamorphic rock varies across the area but is richer in quartz content than the igneous and carbonate rocks. Classification of the composite image classified using maximum likelihood (ML) supervised classification method produced overall accuracy and Kappa coefficient of 96.53%, and 0.95, respectively.
Yao, M, Woo, Y, Tijing, L, Cesarini, C & Shon, H 2017, 'Improving Nanofiber Membrane Characteristics and Membrane Distillation Performance of Heat-Pressed Membranes via Annealing Post-Treatment', Applied Sciences, vol. 7, no. 1, pp. 78-78.
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Electrospun membranes are gaining interest for use in membrane distillation (MD) due to their high porosity and interconnected pore structure; however, they are still susceptible to wetting during MD operation because of their relatively low liquid entry pressure (LEP). In this study, post-treatment had been applied to improve the LEP, as well as its permeation and salt rejection efficiency. The post-treatment included two continuous procedures: heat-pressing and annealing. In this study, annealing was applied on the membranes that had been heat-pressed. It was found that annealing improved the MD performance as the average flux reached 35 L/m2·h or LMH (>10% improvement of the ones without annealing) while still maintaining 99.99% salt rejection. Further tests on LEP, contact angle, and pore size distribution explain the improvement due to annealing well. Fourier transform infrared spectroscopy and X-ray diffraction analyses of the membranes showed that there was an increase in the crystallinity of the polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) membrane; also, peaks indicating the α phase of polyvinylidene fluoride (PVDF) became noticeable after annealing, indicating some β and amorphous states of polymer were converted into the α phase. The changes were favorable for membrane distillation as the non-polar α phase of PVDF reduces the dipolar attraction force between the membrane and water molecules, and the increase in crystallinity would result in higher thermal stability. The present results indicate the positive effect of the heat-press followed by an annealing post-treatment on the membrane characteristics and MD performance.
Yao, S-N, Lin, C-T, King, J-T, Liu, Y-C & Liang, C 2017, 'Learning in the visual association of novice and expert designers', Cognitive Systems Research, vol. 43, pp. 76-88.
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© 2017 Elsevier B.V. Designers are adept at determining similarities between previously seen objects and new creations using visual association. However, extant research on the visual association of designers and the differences between expert and novice designers when they engage in the visual association task are scant. Using electroencephalography (EEG), this study attempted to narrow this research gap. Sixteen healthy designers—eight experts and eight novices—were recruited, and asked to perform visual association while EEG signals were acquired, subsequently analysed using independent component analysis. The results indicated that strong connectivity was observed among the prefrontal, frontal, and cingulate cortices, and the default mode network. The experts used both hemispheres and executive functions to support their association tasks, whereas the novices mainly used their right hemisphere and memory retrieval functions. The visual association of experts appeared to be more goal-directed than that of the novices. Accordingly, designing and implementing authentic and goal-directed activities for improving the executive functions of the prefrontal cortex and default mode network are critical for design educators and creativity researchers.
Yao, Y, Zhang, J, Shen, F, Hua, X, Xu, J & Tang, Z 2017, 'A new web-supervised method for image dataset constructions', Neurocomputing, vol. 236, pp. 23-31.
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© 2017 The goal of this work is to automatically collect a large number of highly relevant natural images from Internet for given queries. A novel automatic image dataset construction framework is proposed by employing multiple query expansions. In specific, the given queries are first expanded by searching in the Google Books Ngrams Corpora to obtain a richer semantic descriptions, from which the visually non-salient and less relevant expansions are then filtered. After retrieving images from the Internet with filtered expansions, we further filter noisy images by clustering and progressively Convolutional Neural Networks (CNN) based methods. To evaluate the performance of our proposed method for image dataset construction, we build an image dataset with 10 categories. We then run object detections on our image dataset with three other image datasets which were constructed by weak supervised, web supervised and full supervised learning, the experimental results indicated the effectiveness of our method is superior to weak supervised and web supervised state-of-the-art methods. In addition, we do a cross-dataset classification to evaluate the performance of our dataset with two publically available manual labelled dataset STL-10 and CIFAR-10.
Yao, Y, Zhang, J, Shen, F, Hua, X, Xu, J & Tang, Z 2017, 'Exploiting Web Images for Dataset Construction: A Domain Robust Approach', IEEE Transactions on Multimedia, vol. 19, no. 8, pp. 1771-1784.
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Yap, HC, Khabbaz, H & Singh, J 2017, 'Numerical analysis of geosynthetics and engineering fill in performance of reconditioned ballasted track', Australian Geomechanics Journal, vol. 52, no. 1, pp. 43-55.
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Over the past few decades, geosynthetics have been used extensively during track reconditioning to improve soil stability as they offer many advantages including cost effectiveness, ease of installation and minimal earthworks. Among the wide range of products in the market, geogrid remains the most commonly used geosynthetics for soil reinforcement. The aims of this paper are to investigate the effect of varying subgrade properties on track performance and to examine the effectiveness of geogrids and engineering fill for track reconditioning purposes. In the current study, numerical analyses were conducted using engineering software OptumG2, a finite element program for geotechnical stability and deformation analysis. The results of the parametric study indicated that geogrid inclusion within track substructure has considerable effect on settlement reduction and, in particular, increases the bearing capacity of railway track. The results also suggested that increase in axial stiffness of geogrids has minimal impact on track deformation. The most effective and practical location for geogrid reinforcement was achieved at interface between ballast and capping layers irrespective of the subgrade strength and stiffness. Sensitivity analyses showed that both total settlement and the bearing capacity of the railway track were most affected by the changes in the friction angle of subgrade, compared with cohesion and elastic modulus of subgrade, with or without geogrid reinforcement. The findings concluded that proper design of geogrid reinforcement can eliminate the need for or significantly reduce the thickness of engineering fill for ground improvement purposes.
Ye, D, Zhang, M & Vasilakos, AV 2017, 'A Survey of Self-Organization Mechanisms in Multiagent Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 3, pp. 441-461.
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Ye, L, Guo, Y & Su, SW 2017, 'An Efficient Autocalibration Method for Triaxial Accelerometer', IEEE Transactions on Instrumentation and Measurement, vol. 66, no. 9, pp. 2380-2390.
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© 1963-2012 IEEE. This paper investigates the autocalibration of microelectromechanical systems (MEMS) triaxial accelerometer (TA) based on experimental design (DoE). First, for a special 6-parameter second-degree model, a six-point experimental scheme is proposed, and its G-optimality has been proven based on optimal DoE. Then, a new linearization approach is introduced, by which the TA model for autocalibration can be simplified as the expected second-degree form so that the proposed optimal experimental scheme can be applied. To reliably estimate the model parameter, a convergence-guaranteed iterative algorithm is also proposed, which can significantly reduce the bias caused by linearization. Thereafter, the effectiveness and robustness of the proposed approach have been demonstrated by simulation. Finally, the proposed calibration method has been experimentally verified using two typical types of MEMS TA, and desired experimental results effectively demonstrate the efficiency and accuracy of the proposed calibration approach.
Ye, X, Wang, S, Wang, Q, Sloan, SW & Sheng, D 2017, 'Numerical and experimental studies of the mechanical behaviour for compaction grouted soil nails in sandy soil', Computers and Geotechnics, vol. 90, pp. 202-214.
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A model test was conducted for a newly developed soil nail, the result of which was compared to that of a 3D finite element method (FEM) simulation. The shape angle (β) and friction coefficients (μ) contributed to the difference in pull-out force between the model test and the simulation. Further verifications were conducted, during which the pull-out mechanisms of the soil nail for different β and μ were analysed. It was found that both β and μ have a positive influence on the pull-out force; β only affects the increase rate, while μ influences the overall pull-out force level. Three components were found to govern the pull-out force, with the component applied to the expanded cement bulk surface accounting for approximately 80% of the total. This study proves that the optimal approach for increasing pull-out force is to enlarge the diameter of the cement bulk rather than extend the nail length.
Ye, X, Wang, S, Yang, J, Sheng, D & Xiao, C 2017, 'Soil Conditioning for EPB Shield Tunneling in Argillaceous Siltstone with High Content of Clay Minerals: Case Study', International Journal of Geomechanics, vol. 17, no. 4, pp. 1-8.
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Soil clogging occurred in the early construction stage of Nanchang Metro Line 1, China, when an earth balance pressure (EPB) shield passed through the argillaceous siltstone with a total content of clay minerals of 40.5%. This paper presents a new scheme for determining soil conditioning parameters to avoid the occurrence of soil clogging, taking both the slump value and the liquidity index of the soil into account. As indicated by the results of slump tests, the optimum slump value for the soil conditioning ranged from 17 to 20 cm, and a fitting function of slump value against foam injection ratio (FIR) and water content (w) was obtained. Considering the requirement for a liquidity index equal to ~0.4-0.75 to ensure the stability of the excavation face, a chart was proposed for the soil conditioning. Based on the chart, the optimum FIR and w for the soil conditioning for tunneling in argillaceous siltstone were determined to be ~19.2-23.2% and ~14.2-36.6%, respectively. Taking shield parameters, tunnel design, and soil parameters into account, the soil conditioning techniques were implemented in field conditions. The field implementation indicated that soil clogging was effectively avoided in the later section of Nanchang Metro Line 1, and the thrust and torque of the shield were reduced significantly.
Ye, Y, Ngo, HH, Guo, W, Liu, Y, Li, J, Liu, Y, Zhang, X & Jia, H 2017, 'Insight into chemical phosphate recovery from municipal wastewater', Science of The Total Environment, vol. 576, pp. 159-171.
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© 2016 Elsevier B.V. Phosphate plays an irreplaceable role in the production of fertilizers. However, its finite availability may not be enough to satisfy increasing demands for the fertilizer production worldwide. In this scenario, phosphate recovery can effectively alleviate this problem. Municipal wastewater has received high priority to recover phosphate because its quantity is considerable. Therefore, phosphate recovery from municipal wastewater can bring many benefits such as relieving the burden of increasing production of fertilizers and reduction in occurrence of eutrophication caused by the excessive concentration of phosphate in the released effluent. The chemical processes are the most widely applied in phosphate recovery in municipal wastewater treatment because they are highly stable and efficient, and simple to operate. This paper compares chemical technologies for phosphate recovery from municipal wastewater. As phosphate in the influent is transferred to the liquid and sludge phases, a technical overview of chemical phosphate recovery in both phases is presented with reference to mechanism, efficiency and the main governing parameters. Moreover, an analysis on their applications at plant-scale is also presented. The properties of recovered phosphate and its impact on crops and plants are also assessed with a discussion on the economic feasibility of the technologies.
Yin, H, Wang, W, Wang, H, Chen, L & Zhou, X 2017, 'Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 11, pp. 2537-2551.
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© 2017 IEEE. Point-of-interest (POI) recommendation has become an important way to help people discover attractive and interesting places, especially when they travel out of town. However, the extreme sparsity of user-POI matrix and cold-start issues severely hinder the performance of collaborative filtering-based methods. Moreover, user preferences may vary dramatically with respect to the geographical regions due to different urban compositions and cultures. To address these challenges, we stand on recent advances in deep learning and propose a Spatial-Aware Hierarchical Collaborative Deep Learning model (SH-CDL). The model jointly performs deep representation learning for POIs from heterogeneous features and hierarchically additive representation learning for spatial-aware personal preferences. To combat data sparsity in spatial-aware user preference modeling, both the collective preferences of the public in a given target region and the personal preferences of the user in adjacent regions are exploited in the form of social regularization and spatial smoothing. To deal with the multimodal heterogeneous features of the POIs, we introduce a late feature fusion strategy into our SH-CDL model. The extensive experimental analysis shows that our proposed model outperforms the state-of-the-art recommendation models, especially in out-of-town and cold-start recommendation scenarios.
Ying, M, Ying, S & Wu, X 2017, 'Invariants of quantum programs: characterisations and generation', ACM SIGPLAN Notices, vol. 52, no. 1, pp. 818-832.
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Program invariant is a fundamental notion widely used in program verification and analysis. The aim of this paper is twofold: (i) find an appropriate definition of invariants for quantum programs; and (ii) develop an effective technique of invariant generation for verification and analysis of quantum programs. Interestingly, the notion of invariant can be defined for quantum programs in two different ways -- additive invariants and multiplicative invariants -- corresponding to two interpretations of implication in a continuous valued logic: the Lukasiewicz implication and the Godel implication. It is shown that both of them can be used to establish partial correctness of quantum programs. The problem of generating additive invariants of quantum programs is addressed by reducing it to an SDP (Semidefinite Programming) problem. This approach is applied with an SDP solver to generate invariants of two important quantum algorithms -- quantum walk and quantum Metropolis sampling. Our examples show that the generated invariants can be used to verify correctness of these algorithms and are helpful in optimising quantum Metropolis sampling. To our knowledge, this paper is the first attempt to define the notion of invariant and to develop a method of invariant generation for quantum programs.
YongBo, C, YueSong, M, JianQiao, Y, XiaoLong, S & Nuo, X 2017, 'Three-dimensional unmanned aerial vehicle path planning using modified wolf pack search algorithm', Neurocomputing, vol. 266, pp. 445-457.
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You, P, Liu, Y, Chen, S-L, Da Xu, K, Li, W & Liu, QH 2017, 'Synthesis of Unequally Spaced Linear Antenna Arrays With Minimum Element Spacing Constraint by Alternating Convex Optimization', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 3126-3130.
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© 2002-2011 IEEE. A novel method called alternating convex optimization is presented to synthesize unequally spaced linear arrays with minimum element spacing constraint. In this method, the problem of synthesizing an unequally spaced array is formulated as a sequence of alternating convex optimization problems, and the excitation vector and auxiliary weighting vector are alternately chosen as the optimization variables. The minimum spacing constraint for considering the physical element antenna size can be easily imposed in this alternating optimization process. Two examples for synthesizing unequally spaced linear arrays with focused and shaped patterns are provided to validate the effectiveness and advantages of the proposed method.
Young, C, Salunkhe, RR, Alshehri, SM, Ahamad, T, Huang, Z, Henzie, J & Yamauchi, Y 2017, 'High energy density supercapacitors composed of nickel cobalt oxide nanosheets on nanoporous carbon nanoarchitectures', Journal of Materials Chemistry A, vol. 5, no. 23, pp. 11834-11839.
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This work demonstrates a simple approach to the development of NiCo2O4 and nanoporous carbon composites for high-performance supercapacitor application.
Yu, J, Ji, J, Miao, Z & Zhou, J 2017, 'Adaptive formation control of networked Lagrangian systems with a moving leader', Nonlinear Dynamics, vol. 90, no. 4, pp. 2755-2766.
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© 2017, Springer Science+Business Media B.V. This paper investigates the formation control problem of networked Lagrangian systems with a moving leader under the directed network topology. A special form of geometric pattern is introduced to design the desired formation for such systems. Three adaptive control strategies are proposed for the networked Lagrangian systems to achieve the formation for the cases of the absence and presence of time delays. Some simple yet general algebraic criteria are developed to ensure that the networked Lagrangian systems can always achieve desired geometric formation. Furthermore, the effect of communication time delays on the performance of formation control is numerically investigated. Finally, numerical examples are given to illustrate and visualize the effectiveness of the theoretical results.
Yu, KL, Lau, BF, Show, PL, Ong, HC, Ling, TC, Chen, W-H, Ng, EP & Chang, J-S 2017, 'Recent developments on algal biochar production and characterization', Bioresource Technology, vol. 246, pp. 2-11.
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Yu, KL, Show, PL, Ong, HC, Ling, TC, Chi-Wei Lan, J, Chen, W-H & Chang, J-S 2017, 'Microalgae from wastewater treatment to biochar – Feedstock preparation and conversion technologies', Energy Conversion and Management, vol. 150, pp. 1-13.
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Yu, L, Huang, Z, Shen, F, Song, J, Shen, HT & Zhou, X 2017, 'Bilinear Optimized Product Quantization for Scalable Visual Content Analysis', IEEE Transactions on Image Processing, vol. 26, no. 10, pp. 5057-5069.
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© 1992-2012 IEEE. Product quantization (PQ) has been recognized as a useful technique to encode visual feature vectors into compact codes to reduce both the storage and computation cost. Recent advances in retrieval and vision tasks indicate that high-dimensional descriptors are critical to ensuring high accuracy on large-scale data sets. However, optimizing PQ codes with high-dimensional data is extremely time-consuming and memory-consuming. To solve this problem, in this paper, we present a novel PQ method based on bilinear projection, which can well exploit the natural data structure and reduce the computational complexity. Specifically, we learn a global bilinear projection for PQ, where we provide both non-parametric and parametric solutions. The non-parametric solution does not need any data distribution assumption. The parametric solution can avoid the problem of local optima caused by random initialization, and enjoys a theoretical error bound. Besides, we further extend this approach by learning locally bilinear projections to fit underlying data distributions. We show by extensive experiments that our proposed method, dubbed bilinear optimization product quantization, achieves competitive retrieval and classification accuracies while having significant lower time and space complexities.
Yu, N, Duan, R & Xu, Q 2017, 'Bounds on the Distance Between a Unital Quantum Channel and the Convex Hull of Unitary Channels', IEEE Transactions on Information Theory, vol. 63, no. 2, pp. 1299-1310.
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© 2016 IEEE. Motivated by the recent resolution of asymptotic quantum birkhoff conjecture (AQBC), we attempt to estimate the distance between a given unital quantum channel and the convex hull of unitary channels. We provide two lower bounds on this distance by employing techniques from quantum information and operator algebras, respectively. We then show how to apply these results to construct some explicit counterexamples to AQBC. We also point out an interesting connection between the Grothendieck's inequality and AQBC.
Yu, S, Liu, M, Dou, W, Liu, X & Zhou, S 2017, 'Networking for Big Data: A Survey', IEEE Communications Surveys & Tutorials, vol. 19, no. 1, pp. 531-549.
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Complementary to the fancy big data applications, networking for big data is an indispensable supporting platform for these applications in practice. This emerging research branch has gained extensive attention from both academia and industry in recent years. In this new territory, researchers are facing many unprecedented theoretical and practical challenges. We are therefore motivated to solicit the latest works in this area, aiming to pave a comprehensive and solid starting ground for interested readers. We first clarify the definition of networking for big data based on the cross disciplinary nature and integrated needs of the domain. Second, we present the current understanding of big data from different levels, including its formation, networking features, mathematical representations, and the networking technologies. Third, we discuss the challenges and opportunities from various perspectives in this hopeful field. We further summarize the lessons we learned based on the survey. We humbly hope this paper will shed light for forthcoming researchers to further explore the uncharted part of this promising land.
Yu, S, Muller, P & Zomaya, A 2017, 'Editorial: special issue on “big data security and privacy”', Digital Communications and Networks, vol. 3, no. 4, pp. 211-212.
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Yu, Y & Yan, N 2017, 'Numerical Study on Guided Wave Propagation in Wood Utility Poles: Finite Element Modelling and Parametric Sensitivity Analysis', Applied Sciences, vol. 7, no. 10, pp. 1063-1063.
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Recently, guided wave (GW)-based non-destructive evaluation (NDE) techniques have been developed and considered as a potential candidate for integrity assessment of wood structures, such as wood utility poles. However, due to the lack of understanding on wave propagation in such structures, especially under the effect of surroundings such as soil, current GW-based NDE methods fail to properly account for the propagation of GWs and to contribute reliable and correct results. To solve this critical issue, this work investigates the behaviour of wave propagation in the wood utility pole with the consideration of the influence of soil. The commercial finite element (FE) analysis software ANSYS is used to simulate GW propagation in a wood utility pole. In order to verify the numerical findings, the laboratory testing is also conducted in parallel with the numerical results to experimentally verify the effectiveness of developed FE models. Finally, sensitivity analysis is also carried out based on FE models of wood pole under different material properties, boundary conditions and excitation types.
Yu, Y & Zhang, YX 2017, 'Coupling of chemical kinetics and thermodynamics for simulations of leaching of cement paste in ammonium nitrate solution', Cement and Concrete Research, vol. 95, pp. 95-107.
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Yu, Y, Konstantinou, G, Townsend, CD, Aguilera, RP & Agelidis, VG 2017, 'Delta-Connected Cascaded H-Bridge Multilevel Converters for Large-Scale Photovoltaic Grid Integration', IEEE Transactions on Industrial Electronics, vol. 64, no. 11, pp. 8877-8886.
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© 1982-2012 IEEE. The cascaded H-bridge (CHB) converter is becoming a promising candidate for use in next generation large-scale photovoltaic (PV) power plants. However, solar power generation in the three converter phase-legs can be significantly unbalanced, especially in a large geographically-dispersed plant. The power imbalance between the three phases defines a limit for the injection of balanced three-phase currents to the grid. This paper quantifies the performance of, and experimentally confirms, the recently proposed delta-connected CHB converter for PV applications as an alternative configuration for large-scale PV power plants. The required voltage and current overrating for the converter is analytically developed and compared against the star-connected counterpart. It is shown that the delta-connected CHB converter extends the balancing capabilities of the star-connected CHB and can accommodate most imbalance cases with relatively small overrating. Experimental results from a laboratory prototype are provided to validate the operation of the delta-connected CHB converter under various power imbalance cases.
Yuan, K-J, Shu, C-C, Dong, D & Bandrauk, AD 2017, 'Attosecond Dynamics of Molecular Electronic Ring Currents', The Journal of Physical Chemistry Letters, vol. 8, no. 10, pp. 2229-2235.
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Yuan, L, Qin, L, Lin, X, Chang, L & Zhang, W 2017, 'Effective and Efficient Dynamic Graph Coloring.', Proc. VLDB Endow., vol. 11, no. 3, pp. 338-351.
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Graph coloring is a fundamental graph problem that is widely applied
in a variety of applications. The aim of graph coloring is to
minimize the number of colors used to color the vertices in a graph
such that no two incident vertices have the same color. Existing
solutions for graph coloring mainly focus on computing a good coloring
for a static graph. However, since many real-world graphs are
highly dynamic, in this paper, we aim to incrementally maintain the
graph coloring when the graph is dynamically updated. We target
on two goals: high effectiveness and high efficiency. To achieve
high effectiveness, we maintain the graph coloring in a way such
that the coloring result is consistent with one of the best static graph
coloring algorithms for large graphs. To achieve high efficiency,
we investigate efficient incremental algorithms to update the graph
coloring by exploring a small number of vertices. We design a
color-propagation based algorithm which only explores the vertices
within the 2-hop neighbors of the update-related and color-changed
vertices. We then propose a novel color index to maintain some
summary color information and, thus, bound the explored vertices
within the neighbors of these vertices. Moreover, we derive some
effective pruning rules to further reduce the number of propagated
vertices. The experimental results demonstrate the high effectiveness
and efficiency of our approach.
Yuan, L, Qin, L, Lin, X, Chang, L & Zhang, W 2017, 'I/O efficient ECC graph decomposition via graph reduction.', VLDB J., vol. 26, no. 2, pp. 275-300.
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© 2016, Springer-Verlag Berlin Heidelberg. The problem of computing k-edge connected components (k-ECCs) of a graph G for a specific k is a fundamental graph problem and has been investigated recently. In this paper, we study the problem of ECC decomposition, which computes the k-ECCs of a graph G for all possible k values. ECC decomposition can be widely applied in a variety of applications such as graph-topology analysis, community detection, Steiner Component Search, and graph visualization. A straightforward solution for ECC decomposition is to apply the existing k-ECC computation algorithm to compute the k-ECCs for all k values. However, this solution is not applicable to large graphs for two challenging reasons. First, all existing k-ECC computation algorithms are highly memory intensive due to the complex data structures used in the algorithms. Second, the number of possible k values can be very large, resulting in a high computational cost when each k value is independently considered. In this paper, we address the above challenges, and study I/O efficient ECC decomposition via graph reduction. We introduce two elegant graph reduction operators which aim to reduce the size of the graph loaded in memory while preserving the connectivity information of a certain set of edges to be computed for a specific k. We also propose three novel I/O efficient algorithms, Bottom-Up, Top-Down, and Hybrid, that explore the k values in different orders to reduce the redundant computations between different k values. We analyze the I/O and memory costs for all proposed algorithms. In addition, we extend our algorithm to build an efficient index for Steiner Component Search. We show that our index can be used to perform Steiner Component Search in optimal I/Os when only the node information of the graph is allowed to be loaded in memory. In our experiments, we evaluate our algorithms using seven real large datasets with various graph properties, one of which conta...
Yuan, S, Hao, H, Zong, Z & Li, J 2017, 'A study of RC bridge columns under contact explosion', International Journal of Impact Engineering, vol. 109, pp. 378-390.
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© 2017 This paper presents a study on reinforced concrete (RC) bridge columns under contact detonation. Two 1/3 scale RC bridge columns with circular and square cross-sections are studied both experimentally and numerically. Field tests were performed on two types of columns under 1 kg TNT contact explosion, and acceleration data at different heights of the columns were collected by accelerometers. Investigation of the damage evolution and structural local response is conducted by high-fidelity physics-based numerical models that are developed in the commercial program LS-DYNA through the Arbitrary Lagrangian–Eulerian (ALE) algorithm. The results from the numerical simulation are compared with the experimental results. Field blast tests showed that for both columns the cover concrete on the proximal and side surfaces close to the explosive charge suffered serious damage, while the cover concrete on the distal face remained almost intact. Due to the column geometry, the contact explosion caused larger blast loads on the square column leading to more severe damage. The damage mechanism of the two columns is discussed based on numerical simulations. The results from the numerical model match well with those from the tests except for the back-surface damage in both cases. Field data obtained from accelerometers also show reasonable agreement with results from the numerical modelling and confirm the localized structural response of the columns under contact blast loads. It is shown that the numerical models established in this study provide reliable predictions for the structural response of bridge columns under contact explosion.
Yuan, X, Zhang, H, Zheng, Z, Rao, C, Zhao, Y, Wang, Y, Krumholz, HM & Hu, S 2017, 'Trends in mortality and major complications for patients undergoing coronary artery bypass grafting among Urban Teaching Hospitals in China: 2004 to 2013', European Heart Journal - Quality of Care and Clinical Outcomes, vol. 3, no. 4, pp. 312-318.
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Yusoff, B, Merigó, JM & Ceballos, D 2017, 'Owa-based aggregation operations in multi-expert mcdm model', Economic Computation and Economic Cybernetics Studies and Research, vol. 51, no. 2, pp. 211-230.
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This paper presents an analysis of multi-expert multi-criteria decision making (ME-MCDM) model based on the ordered weighted averaging (OWA) operators. Two methods of modeling the majority opinion are studied as to aggregate the experts’ judgments, in which based on the induced OWA operators. Then, an overview of OWA with the inclusion of different degrees of importance is provided for aggregating the criteria. An alternative OWA operator with a new weighting method is proposed which termed as alternative OWAWA (AOWAWA) operator. Some extensions of ME-MCDM model with respect to two-stage aggregation processes are developed based on the classical and alternative schemes. A comparison of results of different decision schemes then is conducted. Moreover, with respect to the alternative scheme, a further comparison is given for different techniques in integrating the degrees of importance. A numerical example in the selection of investment strategy is used as to exemplify the model and for the analysis purpose.
Yusoff, MNAM, Zulkifli, NWM, Masjuki, HH, Harith, MH, Syahir, AZ, Kalam, MA, Mansor, MF, Azham, A & Khuong, LS 2017, 'Performance and emission characteristics of a spark ignition engine fuelled with butanol isomer-gasoline blends', Transportation Research Part D: Transport and Environment, vol. 57, pp. 23-38.
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Zahid, R, Hassan, MBH, Varman, M, Mufti, RA, Kalam, MA, Zulkifli, NWBM & Gulzar, M 2017, 'A Review on Effects of Lubricant Formulations on Tribological Performance and Boundary Lubrication Mechanisms of Non-Doped DLC/DLC Contacts', Critical Reviews in Solid State and Materials Sciences, vol. 42, no. 4, pp. 267-294.
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Zamani, R, Brown, RBK, Beydoun, G & Tibben, W 2017, 'The architecture of an effective software application for managing enterprise projects', Journal of Modern Project Management, vol. 5, no. 1, pp. 114-122.
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This paper presents the architecture of an effective software application for managing enterprise projects. Viewing the execution of an enterprise project as a highly complex system in which many delicate trade-offs among completion time, cost, safety, and quality are required, the architecture has been designed based on the fact that any action in one part of such a project can highly impact its other parts. Highlighting the complexity of the system, and the way computational intelligence should be employed in making these trade-offs are the base of the presented architecture. The architecture is also based on the fact that developing a software application for appropriate managing of such trade-offs is not a trivial task, and a robust application for this purpose should be involved with an array of sophisticated optimization techniques. A multi-agent system (MAS), as a software application composed of multiple interacting modules, has been used as the main component of architecture. In this multi-agent system, modules interact with environment on-line, and resolve various resource conflicts which are complex and hard-to-resolve on daily basis. Based on the proposed architecture, the paper also provides a template software application in which an array of optimization techniques show how the necessary trade-offs can be made. The template is the result of the integration of several highly sophisticated recent procedures for single and multimode resource-constrained projects scheduling problems.
Zare, M, Mohammady, M & Pradhan, B 2017, 'Modeling the effect of land use and climate change scenarios on future soil loss rate in Kasilian watershed of northern Iran', Environmental Earth Sciences, vol. 76, no. 8, pp. 1-15.
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Accelerated erosion processes caused by global climate and land use changes in many regions of the world constitute a major restrictive factor in their sustainability. This study proposes a method to estimate soil loss rate under changes in future land use and climate in Kasilian watershed of northern Iran within two periods. The first period is related to current climate and land use (1991–2010), and the second concerns climate and land use scenarios (2011–2030). Downscaling global climate model projections of future climate was applied at the regional scale. A statistical downscaling model was then used to downscale precipitation for three scenarios, i.e., 10% increase in rainfall, 10% decrease in rainfall, and unchanged rainfall. Next, cellular automata–Markov model was used for characterization based on two scenarios of land use future that were designed using suitability maps. The soil loss mean for the current period was found to be 6.3 t ha−1year−1 , thereby indicating a low sustainability of soils. The results of simulated soil loss maps indicate a similar pattern in spatial distribution of loss rates compared with those of current periods, but the amount of risk has increased such that simulated erosion mean was 31–58% higher than the current period in all scenarios. Soil loss is thoroughly influenced by climate and land cover patterns in future. In other words, rainfall erosivity has increased by 20 MJ mm ha−1h−1year−1 , based on unchanged rainfall scenario and National Centers for Environmental Prediction data, simulated that cover management factor has increased by 35% compared with the current period. However, simulations indicated that land use changes may potentially induce much larger changes in erosion. The results also showed that soil loss is closely related to land use change and various scenarios of climate change and that revised universal soil loss equation is suitable model to investigate these relationships.
Zeng, S, Merigó, JM, Palacios-Marqués, D, Jin, H & Gu, F 2017, 'RETRACTED: Intuitionistic fuzzy induced ordered weighted averaging distance operator and its application to decision making', Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 11-22.
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© 2017 - IOS Press and the authors. In this paper, we develop a new method for intuitionistic fuzzy decision making problems with induced aggregation operators and distance measures. Firstly, we introduce the intuitionistic fuzzy induced ordered weighted averaging distance (IFIOWAD) operator. It is an extension of the ordered weighted averaging (OWA) operator that uses the main characteristics of the induced OWA (IOWA), the distance measures and uncertain information represented by intuitionistic fuzzy numbers. The main advantage of this operator is that it is able to consider complex attitudinal characters of the decision-maker by using order-inducing variables in the aggregation of the distance measures. We further generalize the IFIOWAD by using weighted average. The result is the intuitionistic fuzzy induced ordered weighted averaging weighted average distance (IFIOWAWAD) operator. Finally, a practical example about the selection of investments is provided to illustrate the developed intuitionistic fuzzy aggregation operators.
Zha, X, Ni, W, Zheng, K, Liu, RP & Niu, X 2017, 'Collaborative Authentication in Decentralized Dense Mobile Networks With Key Predistribution', IEEE Transactions on Information Forensics and Security, vol. 12, no. 10, pp. 2261-2275.
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© 2017 IEEE. Challenges of authentication in decentralized mobile networks arise from frequently changing topologies and unreliable contention-based transmissions. We propose a new protocol to speed up authentications, reduce communication costs, and support opportunistic routing under fast-changing topologies. Key pairs are predistributed across the network. Nodes that predistributed the same pair can instantly verify and route messages for each other in an opportunistic and cooperative fashion, combating fast-changing topologies. We also enable a node to increasingly combine unauthenticated messages and a new message for signature or message authentication code generation, while trying different keys on-the-fly. The messages can be verified altogether, once a key is matched. The communication overhead, thus, becomes independent of the number of keys tried. Closed-form expressions for authentication rate, delay, and throughput are derived through a new three-dimensional Markov model. Validated by simulations, analytical results corroborate the robustness of the proposed protocol against changing topologies, as well as the substantially improved resistance to collusion attacks, as compared with the state of the art.
Zhai, T, Gao, Y, Wang, H & Cao, L 2017, 'Classification of high-dimensional evolving data streams via a resource-efficient online ensemble', Data Mining and Knowledge Discovery, vol. 31, no. 5, pp. 1242-1265.
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© 2017, The Author(s). A novel online ensemble strategy, ensemble BPegasos (EBPegasos), is proposed to solve the problems simultaneously caused by concept drifting and the curse of dimensionality in classifying high-dimensional evolving data streams, which has not been addressed in the literature. First, EBPegasos uses BPegasos, an online kernelized SVM-based algorithm, as the component classifier to address the scalability and sparsity of high-dimensional data. Second, EBPegasos takes full advantage of the characteristics of BPegasos to cope with various types of concept drifts. Specifically, EBPegasos constructs diverse component classifiers by controlling the budget size of BPegasos; it also equips each component with a drift detector to monitor and evaluate its performance, and modifies the ensemble structure only when large performance degradation occurs. Such conditional structural modification strategy makes EBPegasos strike a good balance between exploiting and forgetting old knowledge. Lastly, we first prove experimentally that EBPegasos is more effective and resource-efficient than the tree ensembles on high-dimensional data. Then comprehensive experiments on synthetic and real-life datasets also show that EBPegasos can cope with various types of concept drifts significantly better than the state-of-the-art ensemble frameworks when all ensembles use BPegasos as the base learner.
Zhang, B, Song, X, Nghiem, LD, Li, G & Luo, W 2017, 'Osmotic membrane bioreactors for wastewater reuse: Performance comparison between cellulose triacetate and polyamide thin film composite membranes', Journal of Membrane Science, vol. 539, pp. 383-391.
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© 2017 Elsevier B.V. This study compared the performance of the asymmetric cellulose triacetate (CTA) and polyamide thin film composite (TFC) forward osmosis (FO) membranes in an osmotic membrane bioreactor (OMBR). A reverse osmosis (RO) system was integrated with OMBR to regenerate the draw solution and produce clean water. Results show that the TFC membrane exhibited a higher initial water flux but more dramatic flux decline compared to the CTA membrane when they were used for OMBR. The CTA and TFC membranes also resulted in discernible difference in salinity build-up in the bioreactor and thus biomass characteristics during OMBR operation. All 30 trace organic contaminants (TrOCs) selected in this study were effectively removed by the OMBR-RO hybrid system regardless of the FO membrane type. Compared to the CTA membrane, the TFC membrane contributed more significantly toward the removal of hydrophilic and biologically persistent compounds and thus reduced their accumulation in the draw solution during OMBR-RO operation. In addition, CTA and TFC FO membranes also resulted in considerable differences in TrOC residuals in the sludge during OMBR operation.
Zhang, C, Guo, J, Lian, J, Lu, C, Ngo, HH, Guo, W, Song, Y & Guo, Y 2017, 'Characteristics of electron transport chain and affecting factors for thiosulfate-driven perchlorate reduction', Chemosphere, vol. 185, pp. 539-547.
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The mechanism for perchlorate reduction was investigated using thiosulfate-driven (T-driven) perchlorate reduction bacteria. The influences of various environmental conditions on perchlorate reduction, including pH, temperature and electron acceptors were examined. The maximum perchlorate removal rate was observed at pH 7.5 and 40 °C. Perchlorate reduction was delayed due to the coexistence of perchlorate-chlorate and perchlorate-nitrate. The mechanism of the T-driven perchlorate reduction electron transport chain (ETC) was also investigated by utilizing different inhibitors. The results were as follows: firstly, the NADH dehydrogenase was not involved in the ETC; secondly, the FAD dehydrogenase and quinone loop participated in the ETC; and thirdly, cytochrome oxidase was the main pathway in the ETC. Meanwhile, microbial consortium structure analysis indicated that Sulfurovum which can oxidize sulfur compounds coupled to the reduction of nitrate or perchlorate was the primary bacterium in the T-driven and sulfur-driven consortium. This study generates a better understanding of the mechanism of T-driven perchlorate reduction.
Zhang, D, Han, J, Jiang, L, Ye, S & Chang, X 2017, 'Revealing Event Saliency in Unconstrained Video Collection', IEEE Transactions on Image Processing, vol. 26, no. 4, pp. 1746-1758.
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Recent progresses in multimedia event detection have enabled us to find videos about a predefined event from a large-scale video collection. Research towards more intrinsic unsupervised video understanding is an interesting but understudied field. Specifically, given a collection of videos sharing a common event of interest, the goal is to discover the salient fragments, i.e., the curt video fragments that can concisely portray the underlying event of interest, from each video. To explore this novel direction, this paper proposes an unsupervised event saliency revealing framework. It first extracts features from multiple modalities to represent each shot in the given video collection. Then, these shots are clustered to build the cluster-level event saliency revealing framework, which explores useful information cues (i.e., the intra-cluster prior, inter-cluster discriminability, and inter-cluster smoothness) by a concise optimization model. Compared with the existing methods, our approach could highlight the intrinsic stimulus of the unseen event within a video in an unsupervised fashion. Thus, it could potentially benefit to a wide range of multimedia tasks like video browsing, understanding, and search. To quantitatively verify the proposed method, we systematically compare the method to a number of baseline methods on the TRECVID benchmarks. Experimental results have demonstrated its effectiveness and efficiency.
Zhang, F, Wu, C, Zhao, X-L & Li, Z-X 2017, 'Numerical derivation of pressure-impulse diagrams for square UHPCFDST columns', Thin-Walled Structures, vol. 115, pp. 188-195.
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© 2017 Terrorist activities, especially bomb attacks, have become more and more frequent in the past decades which put thousands of innocent lives in danger. The most common failure mode of structures subjected to blast loading is progressive collapse which is mainly resulted from the failure of load bearing columns. In this paper, finite element analysis tool, LS-DYNA is utilized to study the behaviours of ultra-high performance concrete filled double- skin steel tube (UHPCFDST) columns under blast loading. The numerical model is firstly validated against a series of laboratory and field tests and then used to derive pressure-impulse diagrams for UHPCFDST columns in terms of their residual axial load-carrying capacity after being subjected to blast loading. Different parameters are studied to investigate the effects of axial load ratio, steel tube thickness, column dimension and concrete strength on the pressure-impulse diagrams.
Zhang, F, Wu, C, Zhao, X-L, Heidarpour, A & Li, Z 2017, 'Experimental and numerical study of blast resistance of square CFDST columns with steel-fibre reinforced concrete', Engineering Structures, vol. 149, pp. 50-63.
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© 2016 Elsevier Ltd In recent years, a large number of studies have been carried out to investigate behaviours of concrete filled double skin steel tube (CFDST) members due to its increasing popularity in the construction industry. This paper firstly presents an experimental study on ultra-high performance concrete filled double-skin tubes subjected to close-range blast loading with cross section being square for both inner and outer steel tubes. It is evident that the proposed CFDST column was able to withstand a large blast load without failure so that it has the potential to be used in high-value buildings as well as critical infrastructures. Then, to further investigate the behaviours of the proposed CFDST column, a number of parametric studies were carried out by using a numerical model which was developed and calibrated based on the data acquired from the blast test along with some laboratory tests. Parameters that affect the behaviours of concrete filled double skin steel tube (CFDST) members against blasts are characterised.
Zhang, F, Zhang, W, Zhang, Y, Qin, L & Lin, X 2017, 'OLAK: An Efficient Algorithm to Prevent Unraveling in Social Networks.', Proc. VLDB Endow., vol. 10, no. 6, pp. 649-660.
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In this paper, we study the problem of the anchored k -core. Given a graph G , an integer k and a budget b , we aim to identify b vertices in G so that we can determine the largest induced subgraph J in which every vertex, except the b vertices, has at least k neighbors in J . This problem was introduced by Bhawalkar and Kleinberg e t al. in the context of user engagement in social networks, where a user may leave a community if he/she has less than k friends engaged. The problem has been shown to be NP-hard and inapproximable. A polynomial-time algorithm for graphs with bounded tree-width has been proposed. However, this assumption usually does not hold in real-life graphs, and their techniques cannot be extended to handle general graphs. Motivated by this, we propose an efficient algorithm, namely onion-layer based anchored k-core (OLAK), for the anchored k -core problem on large scale graphs. To facilitate computation of the anchored k -core, we design an onion layer structure, which is generated by a simple onion-peeling-like algorithm against a small set of vertices in the graph. We show that computa...
Zhang, G, Han, E, Zhu, L, Lu, M & Chen, S 2017, 'Synthesis and electrochemical properties of Li (Ni0.56Co0.19Mn0.24Al0.01)1-yAlyO2 as cathode material for lithium-ion batteries', Ionics, vol. 23, no. 9, pp. 2259-2267.
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Zhang, H, Dong, P, Yu, S & Song, J 2017, 'A Scalable and Smart Hierarchical Wireless Communication Architecture Based on Network/User Separation', IEEE Wireless Communications, vol. 24, no. 1, pp. 18-24.
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Due to the dramatic development of mobile devices and technologies, wireless networks have become a convenient and popular means of accessing the Internet for the public. However, the existing wireless networking techniques still face several fundamental inherent problems, such as network scalability, flexibility, and interoperability. As a result, future wireless communication networking, such as 5G, is expected to address these problems. In this article, we present a hierarchical identifier network, a novel and practical hierarchical network architecture based on the idea of network/user separation and mapping. We performed extensive experiments in a realworld high-mobility scenario to evaluate the proposed wireless network architecture. The results demonstrate that the hierarchical identifier network achieves better performance on scalability, flexibility, and interoperability compared to its existing counterparts.
Zhang, H, Qi, Y, Zhou, H, Zhang, J & Sun, J 2017, 'Testing and Defending Methods Against DOS Attack in State Estimation', Asian Journal of Control, vol. 19, no. 4, pp. 1295-1305.
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AbstractIn this paper, we consider a state estimation problem. In this problem, a sensor measures the state of a linear discrete‐time system and sends measurements to an estimator via a packet‐dropping communication link. We are concerned with the effect of Denial‐of‐Service (DoS) attacks on stability of the estimation system, and particularly focus on how to examine whether the communication channel is under DoS attack or not as well as how to defend accordingly, if defense is possible. We formulate the detection problem as a hypothesis testing problem provided that the statistics of the communication channel is known a priori. Two defense countermeasures are proposed: one of which uses a secured packet coding approach to partly compensate the previous packet loss; and in the other the sensor's transmission power is raised to resist the jamming effect brought by the DoS attack. Simulations are provided to demonstrate the main results.
Zhang, J, Sun, H, Wang, W, Hu, Z, Yin, X, Ngo, HH, Guo, W & Fan, J 2017, 'Enhancement of surface flow constructed wetlands performance at low temperature through seasonal plant collocation', Bioresource Technology, vol. 224, pp. 222-228.
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In the present study, a novel seasonal plant collocation system (SPCS), specifically the Potamogeton crispus and Phragmites australis series system, was investigated to enhance the performance of surface flow constructed wetlands (SFCWs) at low temperature. Results of a year-round experiment showed that SPCS conquered the adverse effect of low temperature and achieved sustainable nutrients removal. In addition, during winter, removal efficiencies of NH4-N, TP, COD, and TN in SPCS were 18.1%, 17.6%, 10.1% and 5.2% higher than that in the control, respectively. P. crispus and P. australis complemented each other in terms of plant growth and plant uptake during the experiment period. Furthermore, it emerged that P. crispus could increase the quantity of ammonia oxidizing bacteria by 10.2%, due to its high oxygen enrichment ability. It is suggested that seasonal plant collocation has a promising future in SFCWs of areas being affected by climate change, e.g. northern China.
Zhang, J, Xiao, W, Zhang, S & Huang, S 2017, 'Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction', Sensors, vol. 17, no. 4, pp. 879-879.
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Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach.
Zhang, Q, Wu, D, Lu, J, Liu, F & Zhang, G 2017, 'A cross-domain recommender system with consistent information transfer', Decision Support Systems, vol. 104, pp. 49-63.
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© 2017 Elsevier B.V. Recommender systems provide users with personalized online product and service recommendations and are a ubiquitous part of today's online entertainment smorgasbord. However, many suffer from cold-start problems due to a lack of sufficient preference data, and this is hindering their development. Cross-domain recommender systems have been proposed as one possible solution. These systems transfer knowledge from one domain that has adequate preference information to another domain that does not. The outlook for cross-domain recommendation is promising, but existing methods cannot ensure the knowledge extracted from the source domain is consistent with the target domain, which may impact the accuracy of the recommendations. To address this challenging issue, we propose a cross-domain recommender system with consistent information transfer (CIT). Knowledge consistency is based on user and item latent groups, and domain adaptation techniques are used to map and adjust these groups in both domains to maintain consistency during the transfer learning process. Experiments were conducted on five real-world datasets in three categories: movies, books, and music. The results for nine cross-domain recommendation tasks show that CIT outperforms five benchmarks and increases the accuracy of recommendations in the target domain, especially with sparse data. Practically, our proposed method is applied into a telecom product recommender system and a business partner recommender system (Smart BizSeeker) to enhance personalized decision making for both businesses and individual customers.
Zhang, Q, Wu, J, ZHANG, P, Long, G & Zhang, C 2017, 'Collective Hyping Detection System for Identifying Online Spam Activities', IEEE Intelligent Systems, vol. 32, no. 5, pp. 1-1.
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© 2001-2011 IEEE. Although existing antispam strategies detect traditional spam activities effectively, evolving spam schemes can successfully cheat conventional testing by buying the comments that are written by genuine users and sold by specific web markets. Such spam activities turn into a kind of advertising campaign among business owners to maintain their rank in top positions. This article proposes a new collaborative marketing hyping detection solution that aims to identify spam comments generated by the Spam Reviewer Cloud and detect products that adopt an evolving spam strategy for promotion. The authors propose an unsupervised learning model that combines heterogeneous product review networks in an attempt to discover collective hyping activities. Their experiments validate the existence of the collaborative marketing hyping activities on a real-life ecommerce platform and demonstrate that their model can effectively and accurately identify these advanced spam activities.
Zhang, S, Li, X, Teng, J, Ma, X & Sheng, D 2017, 'A theoretical method for determining sample mass in a sieving test', Computers and Geotechnics, vol. 91, pp. 12-16.
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Zhang, T, Cai, Z, Yang, Y, Bao, J & Wang, Y 2017, 'Compact tunable lowpass filter with sharp roll‐off and low insertion loss', Microwave and Optical Technology Letters, vol. 59, no. 10, pp. 2619-2623.
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AbstractA novel continuously tunable lowpass filter (LPF) with compact size, sharp roll‐off and low insertion loss is presented in this paper. The filter employs two varactor diodes, a pair of open‐ended coupled lines and a U‐shape step impedance line (SIL) with an open‐ended stub loaded at the center of the SIL to form a very compact layout. The odd‐ and even‐mode analysis and equivalent circuit model are demonstrated for estimation of the transmission characteristics. Tuning the DC voltage applied on the varactor diodes, the varactor capacitance accordingly changes leading to a varying cutoff frequency fc. The measured results show that the achieved 3‐dB fc tuning range is 60.6% (1.15–2.15 GHz). The measured insertion loss (IL) and roll‐off rate are 0.2‐0.4 dB and 50–73 dB/GHz, respectively. The overall size of the LPF is only 0.005λg2, which shows a competitive advantage comparing with the state‐of‐the‐art work.
Zhang, T, Gao, X, Wang, W, Du, J, Pegrum, C & Guo, YJ 2017, 'A 36 GHz HTS MMIC Josephson Mixer—Simulation and Measurement', IEEE Transactions on Applied Superconductivity, vol. 27, no. 4, pp. 1-5.
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© 2002-2011 IEEE. Modeling, simulation, and measurement of a compact 36 GHz high-temperature superconducting (HTS) monolithic Josephson junction mixer are presented in this paper. A full HTS microwave monolithic integrated circuit (MMIC) simulation was carried out for the circuit combining HTS passive devices and the Josephson junction. Optimal impedance matching and bias conditions were investigated, and the circuit layout was designed accordingly. The HTS circuit has a compact dimension of 5 × 4 × 0.3 mm 3 , including filters, resonators, and impedance matching circuits. The HTS MMIC mixer was fabricated and packaged with an LNA to realize a receiver front end with a total dimension of 28 × 25 × 15 mm 3 . Measurement result showed an overall conversion gain around 35 dB, with local oscillator driving power around -45 dBm at operating temperature of 40 K.
Zhang, T, Jia, W, He, X & Yang, J 2017, 'Discriminative Dictionary Learning With Motion Weber Local Descriptor for Violence Detection', IEEE Transactions on Circuits and Systems for Video Technology, vol. 27, no. 3, pp. 696-709.
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© 1991-2012 IEEE. Automatic violence detection from video is a hot topic for many video surveillance applications. However, there has been little success in developing an algorithm that can detect violence in surveillance videos with high performance. In this paper, following our recently proposed idea of motion Weber local descriptor (WLD), we make two major improvements and propose a more effective and efficient algorithm for detecting violence from motion images. First, we propose an improved WLD (IWLD) to better depict low-level image appearance information, and then extend the spatial descriptor IWLD by adding a temporal component to capture local motion information and hence form the motion IWLD. Second, we propose a modified sparse-representation-based classification model to both control the reconstruction error of coding coefficients and minimize the classification error. Based on the proposed sparse model, a class-specific dictionary containing dictionary atoms corresponding to the class labels is learned using class labels of training samples. With this learned dictionary, not only the representation residual but also the representation coefficients become discriminative. A classification scheme integrating the modified sparse model is developed to exploit such discriminative information. The experimental results on three benchmark data sets have demonstrated the superior performance of the proposed approach over the state of the arts.
Zhang, T, Jia, W, Yang, B, Yang, J, He, X & Zheng, Z 2017, 'MoWLD: a robust motion image descriptor for violence detection', Multimedia Tools and Applications, vol. 76, no. 1, pp. 1419-1438.
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© 2015, Springer Science+Business Media New York. Automatic violence detection from video is a hot topic for many video surveillance applications. However, there has been little success in designing an algorithm that can detect violence in surveillance videos with high performance. Existing methods typically apply the Bag-of-Words (BoW) model on local spatiotemporal descriptors. However, traditional spatiotemporal features are not discriminative enough, and also the BoW model roughly assigns each feature vector to only one visual word and therefore ignores the spatial relationships among the features. To tackle these problems, in this paper we propose a novel Motion Weber Local Descriptor (MoWLD) in the spirit of the well-known WLD and make it a powerful and robust descriptor for motion images. We extend the WLD spatial descriptions by adding a temporal component to the appearance descriptor, which implicitly captures local motion information as well as low-level image appear information. To eliminate redundant and irrelevant features, the non-parametric Kernel Density Estimation (KDE) is employed on the MoWLD descriptor. In order to obtain more discriminative features, we adopt the sparse coding and max pooling scheme to further process the selected MoWLDs. Experimental results on three benchmark datasets have demonstrated the superiority of the proposed approach over the state-of-the-arts.
Zhang, T, Pegrum, C, Du, J & Guo, YJ 2017, 'Simulation and measurement of a Ka-band HTS MMIC Josephson junction mixer', Superconductor Science and Technology, vol. 30, no. 1, pp. 015008-015008.
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© 2016 IOP Publishing Ltd. We report modeling and simulation results for a Ka band high-temperature superconducting (HTS) monolithic microwave integrated circuit (MMIC) Josephson junction mixer. A Verilog-A model of a Josephson junction is established and imported into the system simulator to realize a full HTS MMIC circuit simulation containing the HTS passive circuit models. Impedance matching optimization between the junction and passive devices is investigated. Junction DC I-V characteristics, current and local oscillator bias conditions and mixing performance are simulated and compared with the experimental results. Good agreement is obtained between the simulation and measurement results.
Zhang, T, Wu, K, Song, J, Huang, S & Dissanayake, G 2017, 'Convergence and Consistency Analysis for a 3-D Invariant-EKF SLAM', IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 733-740.
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© 2016 IEEE. In this letter, we investigate the convergence and consistency properties of an invariant-extended Kalman filter (RI-EKF) based simultaneous localization and mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption that the Jacobians of the motion and observation models need to be evaluated at the ground truth. It is also shown that the output of RI-EKF is invariant under any stochastic rigid body transformation in contrast to SO(3) based EKF SLAM algorithm (SO(3)-EKF) that is only invariant under deterministic rigid body transformation. Implications of these invariance properties on the consistency of the estimator are also discussed. Monte Carlo simulation results demonstrate that RI-EKF outperforms SO(3)-EKF, Robocentric-EKF and the 'First Estimates Jacobian' EKF, for three-dimensional point feature-based SLAM.
Zhang, W, Dong, D, Petersen, IR & Rabitz, HA 2017, 'Robust control of photoassociation of slow O + H collision', Chemical Physics, vol. 483-484, pp. 149-155.
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Zhang, X, Cheng, Z, Lin, R, He, L, Yu, S & Luo, H 2017, 'Local Fast Reroute With Flow Aggregation in Software Defined Networks', IEEE Communications Letters, vol. 21, no. 4, pp. 785-788.
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In this letter, we propose a local fast reroute (LFR) algorithm with flow aggregation in software defined networks (SDN). In LFR, if a link failure is detected, all traffic flows affected by the failure are aggregated to be a new 'big' flow. Then, a local reroute path is dynamically deployed by the SDN controller for the aggregated flow. LFR reduces the number of flow operations between the SDN controller and switches. Numerical results show that the LFR enables fast recovery while minimizing the total number of flow entries in SDN.
Zhang, X, Sheng, D, Sloan, SW & Bleyer, J 2017, 'Lagrangian modelling of large deformation induced by progressive failure of sensitive clays with elastoviscoplasticity', International Journal for Numerical Methods in Engineering, vol. 112, no. 8, pp. 963-989.
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SummaryThis paper presents a Lagrangian formulation of elastoviscoplasticity, on the basis of the particle finite element method, for progressive failure analysis of sensitive clays. The sensitive clay is represented by an elastoviscoplastic model that is a mixture of the Bingham model, for describing rheological behaviour, and the Tresca model with strain softening for capturing the progressive failure behaviour. The finite element formulation for the incremental elastoviscoplastic analysis is reformulated, through the application of the Hellinger–Reissner variational theorem, as an equivalent optimisation program that can be solved efficiently using modern algorithms such as the interior‐point method. The recast formulation is then incorporated into the framework of the particle finite element method for investigating progressive failure problems related to sensitive clays, such as the collapse of a sensitive clay column and the retrogressive failure of a slope in sensitive clays, where extremely large deformation occurs. Copyright © 2017 John Wiley & Sons, Ltd.
Zhang, X, Sloan, SW, Vignes, C & Sheng, D 2017, 'A modification of the phase-field model for mixed mode crack propagation in rock-like materials', Computer Methods in Applied Mechanics and Engineering, vol. 322, pp. 123-136.
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The critical energy release rates for mode I and II fracture for rock-like materials are usually different. In this paper, a modified phase-field model is proposed for simulating mixed mode crack propagation. The model can distinguish between the critical energy release rates for mode I and mode II cracks. For the purpose of validation, rock-like materials with a single flaw or double flaws under compression are studied. The simulated results are compared to experimental data, both qualitatively and quantitatively. It is shown that the proposed model is able to capture the commonly observed propagation pattern of wing crack emergence followed by secondary cracks. Additionally, the typical types of crack coalescence observed in experimental tests are successfully reproduced, including the critical loads at which crack coalescence occurs.
Zhang, X, Song, Z, Guo, W, Lu, Y, Qi, L, Wen, H & Ngo, HH 2017, 'Behavior of nitrogen removal in an aerobic sponge based moving bed biofilm reactor', Bioresource Technology, vol. 245, no. PART A, pp. 1282-1285.
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© 2017 Elsevier Ltd This study aims to investigate the behavior of nitrogen removal in an aerobic sponge based moving bed biofilm reactor by evaluating nitrification and denitrification rates of sponge biocarriers from three aerobic moving bed biofilm reactors (MBBRs) with filling ratios of 10% (R-10), 20% (R-20) and 30% (R-30). Results showed that the highest removal efficiencies of total nitrogen in three reactors were 84.5% (R-10), 93.6% (R-20) and 95.3% (R-30). Correspondingly, simultaneous nitrification and denitrification rate (SND) was 90.9%, 97.6% and 100%, respectively. Although R-20 had the highest attached-growth biomass (AGB) per gram of sponge compared to the other two reactors, R-30 showed the maximum ammonium oxidation rate (AOR) (2.1826 ± 0.0717 mg NH 4 + -N/g AGB/h) and denitrification rate (DNR) (5.0852 ± 0.0891 mg NO 3 − -N/g AGB/h), followed by R-20 and R-10. These results indicated AOR, DNR and AGB were affected by the filling ratio under the same operation mode.
Zhang, X, Vignes, C, Sloan, SW & Sheng, D 2017, 'Numerical evaluation of the phase-field model for brittle fracture with emphasis on the length scale', Computational Mechanics, vol. 59, no. 5, pp. 737-752.
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© 2017, Springer-Verlag Berlin Heidelberg. The phase-field model has been attracting considerable attention due to its capability of capturing complex crack propagations without mesh dependence. However, its validation studies have primarily focused on the ability to predict reasonable, sharply defined crack paths. Very limited works have so far been contributed to estimate its accuracy in predicting force responses, which is majorly attributed to the difficulty in the determination of the length scale. Indeed, accurate crack path simulation can be achieved by setting the length scale to be sufficiently small, whereas a very small length scale may lead to unrealistic force-displacement responses and overestimate critical structural loads. This paper aims to provide a critical numerical investigation of the accuracy of phase-field modelling of brittle fracture with special emphasis on a possible formula for the length scale estimation. Phase-field simulations of a number of classical fracture experiments for brittle fracture in concretes are performed with simulated results compared with experimental data qualitatively and quantitatively to achieve this goal. Furthermore, discussions are conducted with the aim to provide guidelines for the application of the phase-field model.
Zhang, Y, Chen, H, Lu, J & Zhang, G 2017, 'Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016', Knowledge-Based Systems, vol. 133, pp. 255-268.
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© 2017 The journal Knowledge-based Systems (KnoSys) has been published for over 25 years, during which time its main foci have been extended to a broad range of studies in computer science and artificial intelligence. Answering the questions: “What is the KnoSys community interested in?” and “How does such interest change over time?” are important to both the editorial board and audience of KnoSys. This paper conducts a topic-based bibliometric study to detect and predict the topic changes of KnoSys from 1991 to 2016. A Latent Dirichlet Allocation model is used to profile the hotspots of KnoSys and predict possible future trends from a probabilistic perspective. A model of scientific evolutionary pathways applies a learning-based process to detect the topic changes of KnoSys in sequential time slices. Six main research areas of KnoSys are identified, i.e., expert systems, machine learning, data mining, decision making, optimization, and fuzzy, and the results also indicate that the interest of KnoSys communities in the area of computational intelligence is raised, and the ability to construct practical systems through knowledge use and accurate prediction models is highly emphasized. Such empirical insights can be used as a guide for KnoSys submissions.
Zhang, Y, Huang, R, Xu, S, Huang, Y, Huang, S, Ma, Y & Wang, Z 2017, 'The effect of different n-butanol-fatty acid methyl esters (FAME) blends on puffing characteristics', Fuel, vol. 208, pp. 30-40.
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© 2017 Elsevier Ltd The droplet suspension technology was used under the condition of atmospheric pressure and 873 K. The n-butanol concentration ranged from 0% to 75% to investigate the effect of n-butanol concentration on the puffing characteristics of a n-butanol-fatty acid methyl esters (FAME) droplet. Experimental results showed that BUT25, BUT50 and BUT75 (BUT'XX’ represented XX% n-butanol by mass fraction in the n-butanol-FAME blend) underwent three phases, namely the transient heating phase, fluctuation evaporation phase and equilibrium evaporation phase. The temperatures of BUT25, BUT50 and BUT75 were similar at the start and end of the transient heating phase. The duration of BUT75’s transient heating phase was much longer than that of BUT25 and BUT50. Therefore, the evaporation cooling of BUT75 was the most prominent because the temperature growth rate of BUT75 was significantly less than that of BUT25 and BUT50. Furthermore, the fluctuation evaporation phase could be divided into the strong and weak fluctuation stages. The violent fluctuation was only observed in the strong fluctuation stage. The weak fluctuation stage was similar as the stable evaporation. The active rupture was found in the strong fluctuation stage and the passive rupture was found in the weak fluctuation stage. The active and passive ruptures were caused by the fast bubble expansion and surface evaporation respectively. In addition, many periodic processes were contained in the strong fluctuation stage. The similarity degree of the periodic process showed a slump and a gradual increase, which were caused by bubble expansion and droplet recovery respectively. The bubble expansion of BUT50 was greater than that of BUT75. Significant bubble expansion led to the violent deformation after bubble rupture. The recovery time of BUT50 was longer than that of BUT75. Therefore, the similarity degree of BUT50 exhibited a wavy structure and BUT75 displayed a comb-like structure in the...
Zhang, Y, Li, P, Zhu, X, Su, SW, Guo, Q, Xu, P & Yao, D 2017, 'Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition', PLOS ONE, vol. 12, no. 7, pp. e0180526-e0180526.
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The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing), hip extension from a sitting position (sitting) and gait (walking) are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT) based Singular Value Decomposition (SVD) approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM) is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV), Root-Mean-Square (RMS), integrated EMG (iEMG), Zero Crossing (ZC)) and frequency-domain (e.g., Mean Frequency (MNF) and Median Frequency (MDF)) are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85%±0.88% which...
Zhang, Y, Porter, AL & Chiavetta, D 2017, 'Scientometrics for tech mining: an introduction', Scientometrics, vol. 111, no. 3, pp. 1875-1878.
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Tech mining, a special form of “Big Data” analytics, aims to generate Competitive Technical Intelligence (CTI) using bibliometric and text mining software (e.g., VantagePoint, TDA), as well as other analytical and visualization applications, for analyses of Science, Technology & Innovation (ST&I) information resources. The big data boom challenges tech mining. How to advance tech mining techniques to devise CTI from scalable ST&I data and how to address real-world ST&I concerns using such CTI have emerged as issues.
Zhang, Y, Qian, Y, Huang, Y, Guo, Y, Zhang, G & Lu, J 2017, 'An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation', Scientometrics, vol. 111, no. 3, pp. 1925-1946.
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© 2017, Akadémiai Kiadó, Budapest, Hungary. How to evaluate the value of a patent in technological innovation quantitatively and systematically challenges bibliometrics. Traditional indicator systems and weighting approaches mostly lead to “moderation” results; that is, patents ranked to a top list can have only good-looking values on all indicators rather than distinctive performances in certain individual indicators. Orienting patents authorized by the United States Patent and Trademark Office (USPTO), this paper constructs an entropy-based indicator system to measure their potential in technological innovation. Shannon’s entropy is introduced to quantitatively weight indicators and a collaborative filtering technique is used to iteratively remove negative patents. What remains is a small set of positive patents with potential in technological innovation as the output. A case study with 28,509 USPTO-authorized patents with Chinese assignees, covering the period from 1976 to 2014, demonstrates the feasibility and reliability of this method.
Zhang, Y, Su, S, Savkin, A, Celler, B & Nguyen, H 2017, 'Multiloop Integral Controllability Analysis for Nonlinear Multiple-Input Single-Output Processes', Industrial & Engineering Chemistry Research, vol. 56, no. 28, pp. 8054-8065.
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© 2017 American Chemical Society. The decentralized integral controllability (DIC) for linear/nonlinear square processes implies the existence of stable decentralized controllers with integral actions capable of achieving offset-free control and detuning any subset of the control loops independently. However, the current version of the DIC cannot be directly applied to nonsquare processes specifically for multiple-input single-output (MISO) processes. This paper presents the new definition and theorem of multiloop integral controllability (MIC) to nonlinear MISO processes, and proposes the sufficient MIC conditions in order for such processes to guarantee decentralized unconditional stability under control loop failure as well as to achieve offset-free tracking performance. Two examples, the quadruple-tank system (model based) and the temperature control system, are modified as two-input single-output (TISO) plants and given to quantitatively interpret the effectiveness of the proposed MIC analysis where the desirable performance of both applications can be obtained.
Zhang, Y, Zhang, G, Zhu, D & Lu, J 2017, 'Scientific evolutionary pathways: Identifying and visualizing relationships for scientific topics', Journal of the Association for Information Science and Technology, vol. 68, no. 8, pp. 1925-1939.
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Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term‐based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
Zhang, Z, Song, X, Liu, Y, Wu, D & Song, C 2017, 'Three-dimensional mesoscale modelling of concrete composites by using random walking algorithm', Composites Science and Technology, vol. 149, pp. 235-245.
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© 2017 Elsevier Ltd The mechanical performance of concrete is primarily dominated by the characteristics and interrelation of its ingredients, especially the content, shape and grading of coarse aggregates. Consequently, constructing a realistic mesostructure of concrete is essential for adequate mesoscale studies on the corresponding mechanical properties. In this study, a novel three-dimensional coarse aggregate generation scheme, namely the random walking algorithm (RWA), is proposed for constructing physically feasible mesostructures of concrete. The proposed approach is able to generate a series of aggregates within an initial placing domain, and subsequently, move them into the target domain by both translation and rotation. Within the proposed analysis framework, the high compactness of mesostructures with an improved aggregate content can be robustly achieved by randomly shifting previously placed aggregates, such that the later generated ones can be ingeniously blended in. Typical samples of random aggregate structure (RAS) are generated under specified grading curves. Parameters relating to aggregate content and efficiency of modelling are critically evaluated. By thoroughly investigating practically motivated examples, it is evidently illustrated that the present method is capable of obtaining a relatively realistic and random distribution of coarse aggregates, and more importantly, the grading of the generated aggregate samples is in compliance with the Fuller's Curve.
Zhao, H, Cao, Z, Liu, X, Zhan, Y, Zhang, J, Xiao, X, Yang, Y, Zhou, J & Xu, J 2017, 'Seasonal variation, flux estimation, and source analysis of dissolved emerging organic contaminants in the Yangtze Estuary, China', Marine Pollution Bulletin, vol. 125, no. 1-2, pp. 208-215.
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The occurrence and seasonal variation of 24 dissolved emerging organic contaminants in the Yangtze Estuary were studied, including 12 non-antibiotic pharmaceuticals, seven sulfonamides, two macrolides and three chloramphenicols. Sulfadiazine, erythromycin, thiamphenicol and paracetamol were the primary contaminants in sulfonamides, macrolides, chloramphenicols and non-antibiotic pharmaceutical groups, respectively. Compared to the concentrations at Datong, chloramphenicols at Xuliujing were significantly higher in autumn and winter, while macrolides were lower in spring. Based on the flux estimation, approximately 37.1 tons of sulfonamides, 17.4 tons of macrolides, 79.2 tons of chloramphenicols and 14.1 tons of non-antibiotic pharmaceuticals were discharged into the Yangtze Estuary from June 2013 to May 2014. However, the total flux from the Huangpu River only represented 5% of the total. The pharmaceutical sources were speculated on by analyzing the seasonal variations in pharmaceutical concentrations and fluxes at various sites. Both environmental and social factors might affect the fluxes.
Zhao, J, Gui, L, Wang, Q, Liu, Y, Wang, D, Ni, B-J, Li, X, Xu, R, Zeng, G & Yang, Q 2017, 'Aged refuse enhances anaerobic digestion of waste activated sludge', Water Research, vol. 123, pp. 724-733.
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In this work, a low-cost alternative approach (i.e., adding aged refuse (AR) into waste activated sludge) to significantly enhance anaerobic digestion of sludge was reported. Experimental results showed that with the addition dosage of AR increasing from 0 to 400 mg/g dry sludge soluble chemical oxygen demand (COD) increased from 1150 to 5240 mg/L at the digestion time of 5 d, while the maximal production of volatile fatty acids (VFA) increased from 82.6 to 183.9 mg COD/g volatile suspended solids. Although further increase of AR addition decreased the concentrations of both soluble COD and VFA, their contents in these systems with AR addition at any concentration investigated were still higher than those in the blank, which resulted in higher methane yields in these systems. Mechanism studies revealed that pertinent addition of AR promoted solubilization, hydrolysis, and acidogenesis processes and did not affect methanogenesis significantly. It was found that varieties of enzymes and anaerobes in AR were primary reason for the enhancement of anaerobic digestion. Humic substances in AR benefited hydrolysis and acidogenesis but inhibited methanogenesis. The effect of heavy metals in AR on sludge anaerobic digestion was dosage dependent. Sludge anaerobic digestion was enhanced by appropriate amounts of heavy metals but inhibited by excessive amounts of heavy metals. The relative abundances of microorganisms responsible for sludge hydrolysis and acidogenesis were also observed to be improved in the system with AR addition, which was consistent with the performance of anaerobic digestion.
Zhao, L, Chen, Q, Li, W, Jiang, P, Wong, L & Li, J 2017, 'MapReduce for accurate error correction of next-generation sequencing data', Bioinformatics, vol. 33, no. 23, pp. 3844-3851.
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Abstract Motivation Next-generation sequencing platforms have produced huge amounts of sequence data. This is revolutionizing every aspect of genetic and genomic research. However, these sequence datasets contain quite a number of machine-induced errors—e.g. errors due to substitution can be as high as 2.5%. Existing error-correction methods are still far from perfect. In fact, more errors are sometimes introduced than correct corrections, especially by the prevalent k-mer based methods. The existing methods have also made limited exploitation of on-demand cloud computing. Results We introduce an error-correction method named MEC, which uses a two-layered MapReduce technique to achieve high correction performance. In the first layer, all the input sequences are mapped to groups to identify candidate erroneous bases in parallel. In the second layer, the erroneous bases at the same position are linked together from all the groups for making statistically reliable corrections. Experiments on real and simulated datasets show that our method outperforms existing methods remarkably. Its per-position error rate is consistently the lowest, and the correction gain is always the highest. Availability and Implementation The source code is available at bioinformatics.gxu.edu.cn/ngs/mec. Supplementary information Supplementary data are available at Bioinformatics online.
Zhao, S, Cheng, E, Qiu, X, Burnett, I & Liu, JC-C 2017, 'Wind noise spectra in small Reynolds number turbulent flows', The Journal of the Acoustical Society of America, vol. 142, no. 5, pp. 3227-3233.
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Wind noise spectra caused by wind from fans in indoor environments have been found to be different from those measured in outdoor atmospheric conditions. Although many models have been developed to predict outdoor wind noise spectra under the assumption of large Reynolds number [Zhao, Cheng, Qiu, Burnett, and Liu (2016). J. Acoust. Soc. Am. 140, 4178–4182, and the references therein], they cannot be applied directly to the indoor situations because the Reynolds number of wind from fans in indoor environments is usually much smaller than that experienced in atmospheric turbulence. This paper proposes a pressure structure function model that combines the energy-containing and dissipation ranges so that the pressure spectrum for small Reynolds number turbulent flows can be calculated. The proposed pressure structure function model is validated with the experimental results in the literature, and then the obtained pressure spectrum is verified with the numerical simulation and experiment results. It is demonstrated that the pressure spectrum obtained from the proposed pressure structure function model can be utilized to estimate wind noise spectra caused by turbulent flows with small Reynolds numbers.
Zhao, S, Dabin, M, Cheng, E, Qiu, X, Burnett, I & Liu, JC-C 2017, 'On the wind noise reduction mechanism of porous microphone windscreens', The Journal of the Acoustical Society of America, vol. 142, no. 4, pp. 2454-2463.
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This paper investigates the wind noise reduction mechanism of porous microphone windscreens. The pressure fluctuations inside the porous windscreens with various viscous and inertial coefficients are studied with numerical simulations. The viscous and inertial coefficients represent the viscous forces resulting from the fluid–solid interaction along the surface of the pores and the inertial forces imposed on the fluid flow by the solid structure of the porous medium, respectively. Simulation results indicate that the wind noise reduction first increases and then decreases with both viscous and inertial coefficients after reaching a maximum. Experimental results conducted on five porous microphone windscreens with porosity from 20 to 60 pores per inch (PPI) show that the 40 PPI windscreen has the highest wind noise reduction performance, and this supports the simulation results. The existence of the optimal values for the viscous and inertial coefficients is explained qualitatively and it is shown that the design of the porous microphone windscreens should take into account both the turbulence suppression inside and the wake generation behind the windscreen to achieve optimal performance.
Zhao, W, Jin, K, Li, J, Qiu, X & Li, S 2017, 'Delivery of stromal cell-derived factor 1α for in situ tissue regeneration', Journal of Biological Engineering, vol. 11, no. 1.
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Zhao, Y, Di, H, Zhang, J, Lu, Y, Lv, F & Li, Y 2017, 'Region-based Mixture Models for human action recognition in low-resolution videos', Neurocomputing, vol. 247, pp. 1-15.
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© 2017 State-of-the-art performance in human action recognition is achieved by the use of dense trajectories which are extracted by optical flow algorithms. However, optical flow algorithms are far from perfect in low-resolution (LR) videos. In addition, the spatial and temporal layout of features is a powerful cue for action discrimination. While, most existing methods encode the layout by previously segmenting body parts which is not feasible in LR videos. Addressing the problems, we adopt the Layered Elastic Motion Tracking (LEMT) method to extract a set of long-term motion trajectories and a long-term common shape from each video sequence, where the extracted trajectories are much denser than those of sparse interest points (SIPs); then we present a hybrid feature representation to integrate both of the shape and motion features; and finally we propose a Region-based Mixture Model (RMM) to be utilized for action classification. The RMM encodes the spatial layout of features without any needs of body parts segmentation. Experimental results show that the approach is effective and, more importantly, the approach is more general for LR recognition tasks.
Zhao, Y, Phuntsho, S, Gao, B & Shon, H 2017, 'Polytitanium sulfate (PTS): Coagulation application and Ti species detection', Journal of Environmental Sciences, vol. 52, pp. 250-258.
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© 2016 Interest in the development of inorganic polymerized coagulants is growing; however, there are only limited studies on the synthesis of polytitanium coagulants, which are expected to exhibit improved coagulation efficiency with better floc properties. This study presents the synthesis of polytitanium sulfate (PTS) for potential application in water purification, followed by characterization of PTS flocs and titanium species detection. Stable PTS solutions were successfully synthesized and standard jar tests were conducted to evaluate their coagulation efficiency. Electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) speciation analysis revealed that a variety of mononuclear and polynuclear complexes were formed in PTS solution, indicating the polymeric nature of the synthesized coagulant. Floc characteristics were studied through on-line monitoring of floc size using a laser diffraction particle size analyzer. Results showed that PTS had a comparable or in some cases even higher organic matter and particulate removal efficiency than Ti(SO4)2. The effluent pH after PTS coagulation significantly improved toward desirable values closer to neutral pH. Properties of flocs formed by PTS were significantly improved in terms of floc size, growth rate and structure. This study showed that PTS could be an efficient and promising coagulant for water purification, with the additional benefit that its coagulated sludge can be used to recover valuable TiO2 nanoparticles for various commercial applications.
Zheng, C, Wang, X, Zeng, S, Zhou, J, Yin, Y, Feng, D & Fulham, M 2017, 'Topology-guided deformable registration with local importance preservation for biomedical images', Physics in Medicine & Biology, vol. 63, no. 1, pp. 015028-015028.
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The demons registration (DR) model is well recognized for its deformation capability. However, it might lead to misregistration due to erroneous diffusion direction when there are no overlaps between corresponding regions. We propose a novel registration energy function, introducing topology energy, and incorporating a local energy function into the DR in a progressive registration scheme, to address these shortcomings. The topology energy that is derived from the topological information of the images serves as a direction inference to guide diffusion transformation to retain the merits of DR. The local energy constrains the deformation disparity of neighbouring pixels to maintain important local texture and density features. The energy function is minimized in a progressive scheme steered by a topology tree graph and we refer to it as topology-guided deformable registration (TDR). We validated our TDR on 20 pairs of synthetic images with Gaussian noise, 20 phantom PET images with artificial deformations and 12 pairs of clinical PET-CT studies. We compared it to three methods: (1) free-form deformation registration method, (2) energy-based DR and (3) multi-resolution DR. The experimental results show that our TDR outperformed the other three methods in regard to structural correspondence and preservation of the local important information including texture and density, while retaining global correspondence.
Zheng, G, Fang, G, Shankaran, R, Orgun, MA, Zhou, J, Qiao, L & Saleem, K 2017, 'Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks', IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 3, pp. 655-663.
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© 2017 IEEE. Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of $N$ bits, each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, T peaks. Time intervals between them, including RR, RQ, RS, RP, RT intervals, are then calculated based on this arrival time, are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.
Zheng, J, Li, Y & Wang, J 2017, 'Design and multi-physics optimization of a novel magnetorheological damper with a variable resistance gap', Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 231, no. 17, pp. 3152-3168.
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This paper presents the design and multi-physics optimization of a novel multi-coil magnetorheological (MR) damper with a variable resistance gap (VRG-MMD). Enabling four electromagnetic coils (EMs) with individual exciting currents, a simplified magnetic equivalent circuit was presented and the magnetic flux generated by each voltage source passing through each active gap was calculated as vector operations. To design the optimal geometry of the VRG-MMD, the multi-physics optimization problem including electromagnetics and fluid dynamics has been formulated as a multi-objective function with weighting ratios among total damping force, dynamic range, and inductive time constant. Based on the selected design variables (DVs), six cases with different weighting ratios were optimized using Bound Optimization BY Quadratic Approximation (BOBYQA) technique. Finally, the vibration performance of the optimal VRG-MMD subjected to sinusoidal and triangle displacement excitations was compared to that of the typical multi-coil MR damper.
Zheng, Z, Zhang, H, Yuan, X, Rao, C, Zhao, Y, Wang, Y, Normand, S-L, Krumholz, HM & Hu, S 2017, 'Comparing Outcomes of Coronary Artery Bypass Grafting Among Large Teaching and Urban Hospitals in China and the United States', Circulation: Cardiovascular Quality and Outcomes, vol. 10, no. 6.
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Background— Coronary artery disease is prevalent in China, with concomitant increases in the volume of coronary artery bypass grafting (CABG). The present study aims to compare CABG-related outcomes between China and the United States among large teaching and urban hospitals. Methods and Results— Observational analysis of patients aged ≥18 years, discharged from acute-care, large teaching and urban hospitals in China and the United States after hospitalization for an isolated CABG surgery. Data were obtained from the Chinese Cardiac Surgery Registry in China and the National Inpatient Sample in the United States. Analysis was stratified by 2 periods: 2007, 2008, and 2010; and 2011 to 2013 periods. The primary outcome was in-hospital mortality, and the secondary outcome was length of stay. The sample included 51 408 patients: 32 040 from 77 hospitals in the China-CABG group and 19 368 from 303 hospitals in the US-CABG group. In the 2007 to 2008, 2010 period and for all-age and aged ≥65 years, the China-CABG group had higher mortality than the US-CABG group (1.91% versus 1.58%, P =0.059; and 3.12% versus 2.20%, P =0.004) and significantly higher age-, sex-, and comorbidity-adjusted odds of death (odds ratio, 1.58; 95% confidential interval, 1.22–2.04; and odds ratio, 1.73; 95% confidential interval, 1.24–2.40). There were no significant mortality differences in the 2011 to 2013 period. For preoperative, postoperative, and total hospital stay, respectively, the median (interquartile range) length of stay across the entire study period between China-CABG and US-CABG groups were 9 (8) versus 1 (3), 9 (6) versus 6 (3), and 20 (12) versus 7 (5) days (all ...
Zhi, XD & Stewart, MG 2017, 'Damage and Risk Assessment for Single-Layer Reticulated Domes Subject to Explosive Blast Loads', International Journal of Structural Stability and Dynamics, vol. 17, no. 09, pp. 1750108-1750108.
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In order to provide a better understanding of the dynamic behavior of single-layer reticulated domes subjected to explosive blast loads, a number of analyses are carried out on structures with different standoff distances ([Formula: see text]), explosive weights ([Formula: see text]), rise–span ratios ([Formula: see text] and other parameters. An equation for a structural damage factor is proposed to evaluate structural damage quantitatively. The damage states for single-layer reticulated domes are defined based on their structural dynamic performance and corresponding damage factors. Structural reliabilities for different standoff distances are obtained using the Monte-Carlo Analysis. A typical protective measure is bollards which are used to help ensure a minimum standoff distance. To illustrate the cost-effectiveness of such a protective measure, structural damage states and various losses, including direct and indirect economic loss and maimed and fatality loss, are considered for assessing the risk reduction, costs and benefits. It was found that the bollards significantly reduce the likelihood of structural progressive collapse or severe damage, and the optimal standoff distance can be determined.
Zhong, Y, Yang, Y, Zhu, X, Dutkiewicz, E, Shum, KM & Xue, Q 2017, 'An On-Chip Bandpass Filter Using a Broadside-Coupled Meander Line Resonator With a Defected-Ground Structure', IEEE Electron Device Letters, vol. 38, no. 5, pp. 626-629.
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© 2017 IEEE. An on-chip bandpass filter (BPF) is designed and fabricated in a 0.13-μm SiGe (Bi)-CMOS technology. This BPF consists of a broadside-coupled meander-line resonator (BCMLR) in conjunction with a defected-ground structure (DGS). By simply grounding a BCMLR, the resonator can be converted into a BPF. Further applying a DGS to this BPF, an additional transmission zero can be generated in the high-frequency band. To understand the fundamentals of this design, an $LC$-equivalent circuit is given for investigation of the transmission zeros and poles. The measured results show that the BPF has a center frequency at 33 GHz with a bandwidth of 18%. The minimum insertion loss is 2.6 dB, while the maximum stopband attenuation is 44 dB. The chip size, excluding the pads, is only 0.038 mm2 ( 0.126×0.3 mm2).
Zhong, Y, Yang, Y, Zhu, X, Dutkiewicz, E, Zhou, Z & Jiang, T 2017, 'Device-Free Sensing for Personnel Detection in a Foliage Environment', IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 6, pp. 921-925.
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© 2017 IEEE. In this letter, the possibility of using device-free sensing (DFS) technology for personnel detection in a foliage environment is investigated. Although the conventional algorithm that based on statistical properties of the received-signal strength (RSS) for target detection at indoor or open-field environment has come a long way in recent years, it is still questionable if this algorithm is fully functional at outdoor with the changing atmosphere and ground conditions, such as a foliage environment. To answer this question, a variety of the measured data have been taken using different targets in a foliage environment. Applying these data along with support vector machine, the impact on detection accuracy due to different classification algorithms is studied. An algorithm that based on the extraction of the high-order cumulant (HOC) of the signals is presented, while the conventional RSS-based one is used as a benchmark. The measurement results show that the classification accuracy of the HOC-based algorithm is better than the RSS-based one by at least 17%. Moreover, to ensure the reliability of the HOC-based approach, the impact on classification accuracy due to different numbers of training samples and different values of signal-to-noise ratio is extensively verified using experimentally recorded samples. To the best of our knowledge, this is the first time that a DFS-based sensing approach is demonstrated to have a potential to distinguish between human and small-animal targets in a foliage environment.
Zhou, J, Sun, J, Wang, Y & Chen, F 2017, 'Wrapping practical problems into a machine learning framework: using water pipe failure prediction as a case study', International Journal of Intelligent Systems Technologies and Applications, vol. 16, no. 3, pp. 191-191.
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Despite the recognised value of machine learning (ML) techniques and high expectation of applying ML techniques within various applications, users often find it difficult to effectively apply ML techniques in practice because of complicated interfaces between ML algorithms and users. This paper presents a work flow of wrapping practical problems into an ML framework. The water pipe failure prediction is used as a case study to show that the applying process can be divided into various steps: obtain domain data, interview with domain experts, clean/pre-process and preview original domain data, extract ML features, set up ML models, explain ML results and make decisions, as well as make feedback to the system based on decision making. In this process, domain experts and ML developers need to collaborate closely in order to make this workflow more effective.
Zhou, X, Chen, H, Gao, S-H, Han, S, Tu, R, Wei, W, Cai, C, Liu, P, Jin, W & Wang, Q 2017, 'Effects of particle size of zero-valent iron (ZVI) on peroxydisulfate-ZVI enhanced sludge dewaterability', Korean Journal of Chemical Engineering, vol. 34, no. 10, pp. 2672-2677.
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The advanced oxidization process has proven to be an effective conditioning technique for the improvement of sludge dewaterability. Zero-valent iron (ZVI) is often used as the catalyst of the oxidization process. This study applied ZVI with different particle sizes to the ZVI- peroxydisulfate reactions, and investigated their effects on the improvement of sludge dewaterability. It was found that ZVI particles with smaller sizes (100 and 400 meshes) led to slightly higher enhancement of sludge dewaterability (69.1%–72%) than the larger size particles (20–40 meshes) with the reduction rate of CST by 64%. However, after the treatment, the recycle rate of larger size ZVI particles was obviously higher than the small sizes ZVI particles: 98.3% vs. 87.6–89.7%. Different surface areas of the ZVI particles with different sizes might contribute to the phenomenon. For the small ZVI particles with the sizes of 100 and 400 meshes, no obvious differences of oxidization effects and the improvements of sludge dewaterability were found between them, which might be because an oxide layer could have been formed on the surface of fine ZVI particles and led to agglomeration. According to the economical analysis, the small particles (100 and 400 meshes) of ZVI were more economically favorable for the oxidative conditioning process with ZVI-peroxydisulfate than large ZVI particles (20–40 meshes).
Zhou, X, Chen, L, Zhang, Y, Qin, D, Cao, L, Huang, G & Wang, C 2017, 'Enhancing online video recommendation using social user interactions', The VLDB Journal, vol. 26, no. 5, pp. 637-656.
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© 2017, Springer-Verlag Berlin Heidelberg. The creation of media sharing communities has resulted in the astonishing increase of digital videos, and their wide applications in the domains like online news broadcasting, entertainment and advertisement. The improvement of these applications relies on effective solutions for social user access to videos. This fact has driven the research interest in the recommendation in shared communities. Though effort has been put into social video recommendation, the contextual information on social users has not been well exploited for effective recommendation. Motivated by this, in this paper, we propose a novel approach based on the video content and user information for the recommendation in shared communities. A new solution is developed by allowing batch video recommendation to multiple new users and optimizing the subcommunity extraction. We first propose an effective technique that reduces the subgraph partition cost based on graph decomposition and reconstruction for efficient subcommunity extraction. Then, we design a summarization-based algorithm which groups the clicked videos of multiple unregistered users and simultaneously provide recommendation to each of them. Finally, we present a nontrivial social updates maintenance approach for social data based on user connection summarization. We evaluate the performance of our solution over a large dataset considering different strategies for group video recommendation in sharing communities.
Zhou, X, Jin, W, Chen, H, Chen, C, Han, S, Tu, R, Wei, W, Gao, S-H, Xie, G-J & Wang, Q 2017, 'Enhancing dewaterability of waste activated sludge by combined oxidative conditioning process with zero-valent iron and peroxymonosulfate', Water Science and Technology, vol. 76, no. 9, pp. 2427-2433.
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Abstract The enhancement of sludge dewaterability is of great importance for facilitating the sludge disposal during the operation of wastewater treatment plants. In this study, a novel oxidative conditioning approach was applied to enhance the dewaterability of waste activated sludge by the combination of zero-valent iron (ZVI) and peroxymonosulfate (PMS). It was found that the dewaterability of sludge was significantly improved after the addition of ZVI (0–4 g/g TSS) (TSS: total suspended solids) and PMS (0–1 g/g TSS). The optimal addition amount of ZVI and PMS was 0.25 g/g TSS and 0.1 g/g TSS, respectively, under which the capillary suction time of the sludge was reduced by approximately 50%. The decomposition of sludge flocs could contribute to the improved sludge dewaterability. Economic analysis demonstrated that the proposed conditioning process with ZVI and PMS was more economical than the ZVI + peroxydisulfate and the traditional Fenton conditioning processes.
Zhou, X, Wen, Y, Goodale, UM, Zuo, H, Zhu, H, Li, X, You, Y, Yan, L, Su, Y & Huang, X 2017, 'Optimal rotation length for carbon sequestration in Eucalyptus plantations in subtropical China', New Forests, vol. 48, no. 5, pp. 609-627.
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Zhou, Y, Ni, W, Zheng, K, Liu, RP & Yang, Y 2017, 'Scalable Node-Centric Route Mutation for Defense of Large-Scale Software-Defined Networks', Security and Communication Networks, vol. 2017, pp. 1-13.
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Exploiting software-defined networking techniques, randomly and instantly mutating routes can disguise strategically important infrastructure and protect the integrity of data networks. Route mutation has been to date formulated as NP-complete constraint satisfaction problem where feasible sets of routes need to be generated with exponential computational complexities, limiting algorithmic scalability to large-scale networks. In this paper, we propose a novel node-centric route mutation method which interprets route mutation as a signature matching problem. We formulate the route mutation problem as a three-dimensional earth mover’s distance (EMD) model and solve it by using a binary branch and bound method. Considering the scalability, we further propose that a heuristic method yields significantly lower computational complexities with marginal loss of robustness against eavesdropping. Simulation results show that our proposed methods can effectively disguise key infrastructure by reducing the difference of historically accumulative traffic among different switches. With significantly reduced complexities, our algorithms are of particular interest to safeguard large-scale networks.
Zhu, HL, Chung, KL, Ding, C, Wei, G, Zhang, C & Guo, YJ 2017, 'Polarization-Rotated Waveguide Antennas for Base-Station Applications', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 1545-1548.
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© 2017 IEEE. A novel base-station antenna element is proposed. It consists of an artificial surface composed of parallel strips rotating in the polarization direction and a segment of a rectangular waveguide. The surface is designed on a single-sided substrate, which has the same area as the aperture of the waveguide. To achieve the polarization rotation, the parallel strips on the surface are rotated by 45° with respect to the orientation of the waveguide antenna. By adding the surface, the linear polarization direction of the rectangular waveguide antenna rotates by 45° to comply with the requirements of the cellular industry. To verify the simulation results, the proposed antenna was fabricated and measured. Results show that the antenna has an operating bandwidth from 698-960 MHz, where a stable radiation pattern is achieved.
Zhu, L, Wang, R, Wang, Z & Yang, H 2017, 'TagCare: Using RFIDs to Monitor the Status of the Elderly Living Alone', IEEE Access, vol. 5, pp. 11364-11373.
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Zhu, Q, Coleman, P, Wu, M & Yang, J 2017, 'Robust Acoustic Contrast Control with Reduced In-situ Measurement by Acoustic Modeling', Journal of the Audio Engineering Society, vol. 65, no. 6, pp. 460-473.
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Personal audio systems generate a local sound field for a listener while attenuating the sound energy at pre-defined quiet zones. In practice, system performance is sensitive to errors in the acoustic transfer functions between the sources and the zones. Regularization is commonly used to improve robustness, however, selecting a regularization parameter is not always straightforward. In this paper a design framework for robust reproduction is proposed, combining transfer function and error modeling. The framework allows a physical perspective on the regularization required for a system, based on the bound of assumed additive or multiplicative errors, which is obtained by acoustic modeling. Acoustic contrast control is separately combined with worst-case and probability-model optimization, exploiting limited knowledge of the potential error distribution. Monte-Carlo simulations show that these approaches give increased system robustness compared to the state of the art approaches for regularization parameter estimation, and experimental results verify that robust sound zone control is achieved in the presence of loudspeaker gain errors. Furthermore, by applying the proposed framework, in-situ transfer function measurements were reduced to a single measurement per loudspeaker, per zone, with limited acoustic contrast degradation of less than 2 dB over 100-3000 Hz compared to the fully measured regularized case.
Zhu, Q, Coleman, P, Wu, M & Yang, J 2017, 'Robust reproduction of sound zones with local sound orientation', The Journal of the Acoustical Society of America, vol. 142, no. 1, pp. EL118-EL122.
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Pressure matching (PM) and planarity control (PC) methods can be used to reproduce local sound with a certain orientation at the listening zone, while suppressing the sound energy at the quiet zone. In this letter, regularized PM and PC, incorporating coarse error estimation, are introduced to increase the robustness in non-ideal reproduction scenarios. Facilitated by this, the interaction between regularization, robustness, (tuned) personal audio optimization, and local directional performance is explored. Simulations show that under certain conditions, PC and weighted PM achieve comparable performance, while PC is more robust to a poorly selected regularization parameter.
Zhu, Y, Zhang, H, Qin, L & Cheng, H 2017, 'Efficient MapReduce algorithms for triangle listing in billion-scale graphs.', Distributed Parallel Databases, vol. 35, no. 2, pp. 149-176.
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© 2017, Springer Science+Business Media New York. This paper addresses the classical triangle listing problem, which aims at enumerating all the tuples of three vertices connected with each other by edges. This problem has been intensively studied in internal and external memory, but it is still an urgent challenge in distributed environment where multiple machines across the network can be utilized to achieve good performance and scalability. As one of the de facto computing methodologies in distributed environment, MapReduce has been used in some of existing triangle listing algorithms. However, these algorithms usually need to shuffle a huge amount of intermediate data, which seriously hinders their scalability on large scale graphs. In this paper, we propose a new triangle listing algorithm in MapReduce, FTL, which utilizes a light weight data structure to substantially reduce the intermediate data transferred during the shuffle stage, and also is equipped with multiple-round techniques to ease the burden on memory and network bandwidth when dealing with graphs at billion scale. We prove that the size of the intermediate data can be well bounded near to the number of triangles in the graph. To further reduce the shuffle size and memory cost, we also propose improved algorithms based on a compact data structure, and present several optimization techniques to accelerate the computation and reduce the memory consumption. The extensive experimental results show that our algorithms outperform existing competitors by several times on both synthetic graphs and real world graphs.
Zuo, H, Zhang, G, Pedrycz, W, Behbood, V & Lu, J 2017, 'Fuzzy Regression Transfer Learning in Takagi–Sugeno Fuzzy Models', IEEE Transactions on Fuzzy Systems, vol. 25, no. 6, pp. 1795-1807.
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© 1993-2012 IEEE. Data science is a research field concerned with processes and systems that extract knowledge from massive amounts of data. In some situations, however, data shortage renders existing data-driven methods difficult or even impossible to apply. Transfer learning has recently emerged as a way of exploiting previously acquired knowledge to solve new yet similar problems much more quickly and effectively. In contrast to classical data-driven machine learning methods, transfer learning methods exploit the knowledge accumulated from data in auxiliary domains to facilitate predictive modeling in the current domain. A significant number of transfer learning methods that address classification tasks have been proposed, but studies on transfer learning in the case of regression problems are still scarce. This study focuses on using transfer learning techniques to handle regression problems in a domain that has insufficient training data. We propose an original fuzzy regression transfer learning method, based on fuzzy rules, to address the problem of estimating the value of the target for regression. A Takagi-Sugeno fuzzy regression model is developed to transfer knowledge from a source domain to a target domain. Experimental results using synthetic data and real-world datasets demonstrate that the proposed fuzzy regression transfer learning method significantly improves the performance of existing models when tackling regression problems in the target domain.
Zuthi, MFR, Guo, W, Ngo, HH, Nghiem, DL, Hai, FI, Xia, S, Li, J, Li, J & Liu, Y 2017, 'New and practical mathematical model of membrane fouling in an aerobic submerged membrane bioreactor', Bioresource Technology, vol. 238, pp. 86-94.
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This study aimed to develop a practical semi-empirical mathematical model of membrane fouling that accounts for cake formation on the membrane and its pore blocking as the major processes of membrane fouling. In the developed model, the concentration of mixed liquor suspended solid is used as a lumped parameter to describe the formation of cake layer including the biofilm. The new model considers the combined effect of aeration and backwash on the foulants' detachment from the membrane. New exponential coefficients are also included in the model to describe the exponential increase of transmembrane pressure that typically occurs after the initial stage of an MBR operation. The model was validated using experimental data obtained from a lab-scale aerobic sponge-submerged membrane bioreactor (MBR), and the simulation of the model agreed well with the experimental findings.
Zwinkau, R, Müller, P & Deuse, J 2017, 'Korrelierende Prozessparameter bei der Reinigung mit Druckluft in Fließlinien', JOT Journal für Oberflächentechnik, vol. 57, no. 11, pp. 62-65.
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Abbasi, M & Tousi, B 1970, 'Novel controllers based on instantaneous p-q power theory for transformerless SSSC and STATCOM', 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE, Milan, ITALY, pp. 1-10.
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Abbasi, MH, Rajabi, A, Taki, M, Li, L, Zhang, J, Ghavidel, S & Ghadi, MJ 1970, 'Risk-constrained offering strategies for a price-maker demand response aggregator', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. Offering strategy of a price-maker demand response aggregator (DRA) in a two-settlement market is presented in this paper. The aggregator minimizes its cost by offering energy and price bids in the day-ahead market and energy bids in the balancing market. On the other hand, DRA optimally manages the aggregated demands of a large number of electric vehicles and properly distributes them through the time. The problem is formulated as a stochastic mixed-integer nonlinear optimization problem. The risk of the problem is managed by conditional value-at-risk measure and finally, the proposed approach is numerically evaluated through a detailed case study.
Abdo, P & Huynh, BP 1970, 'Effect of Combining Buoyancy Driven and Winddriven Ventilation in a Two Dimensional Room Fitted With a Windcatcher', Volume 7: Fluids Engineering, ASME 2017 International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers, Tampa, Florida, pp. 1-7.
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Natural ventilation is the process of supplying and removing air through an indoor space by natural means. There are two types of natural ventilation occurring in buildings: winddriven ventilation and buoyancy driven ventilation, or stack ventilation. The most efficient design for natural ventilation in buildings should implement both types of natural ventilation. Stack ventilation which is temperature induced is driven by buoyancy making it less dependent on wind and its direction. Heat emitted causes a temperature difference between two adjoining volumes of air, the warmer air will have lower density and be more buoyant thus will rise above the cold air creating an upward air stream. Combining the winddriven and the buoyancy driven ventilation will be investigated in this study through the use of a windcatcher natural ventilation system. Stack driven air rises as it leaves the windcatcher and it is replaced with fresh air from outside as it enters through the positively pressured windward side. To achieve this, CFD (computational fluid dynamics) tool is used to simulate the air flow in a two dimensional room fitted with a windcatcher based on the winddriven ventilation alone and on the combined buoyancy and winddriven ventilation.
Abdo, P, Huynh, BP & Avakian, V 1970, 'Distribution of Air Flow Through a Green Wall Module', Volume 1B, Symposia: Fluid Measurement and Instrumentation; Fluid Dynamics of Wind Energy; Renewable and Sustainable Energy Conversion; Energy and Process Engineering; Microfluidics and Nanofluidics; Development and Applications in Computational Fluid Dynamics; DNS/LES and Hybrid RANS/LES Methods, ASME 2017 Fluids Engineering Division Summer Meeting, American Society of Mechanical Engineers, Waikoloa, Hawaii, USA.
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Green or living walls are active bio-filters developed to enhance air quality. Often, these walls form the base from which plants are grown; and the plant-wall system helps to remove both gaseous and particulate air pollutants. A green wall can be found indoors as well as outdoors, and could be assembled from modules in an arrangement similar to tiling. The module is a rectangular plastic box (dimensions about 500 mm × 500 mm × 130 mm) that holds a permeable bag containing a plant-growing medium (replacement for soil). The front face of the module has multiple openings for plants to protrude out from the bag inside. Plant roots are imbedded in the medium. A fan positioned at a central opening on the module’s back face drives air through the medium-plant-roots mix and then onward through the plants′ canopy; and these would help remove both gaseous and particulate pollutants from the air. Volatile Organic compounds (VOCs) and particulate matters PMs are both reduced by passing through the plant-growing medium, thus reducing the percentage of air flow that passes through the open top face of the module is essential to maximize the capacity of bio-filtration. Drip-irrigation water is dispensed from a tube running along the open top-face of the module. The module has also a small drainage hole on its bottom face. Pressure drop across the module as well as air-flow rate through it have been obtained in a previous work [1], air-flow distribution through the module and the effect of introducing a cover to the module’s open top face are investigated in this work to improve the design of the module and achieve more appropriate flow rate and flow distribution. The top cover essentially includes small holes of 10 mm diameter to allow the necessary irrigation. The measurements help to determine the pattern of flow resistances which in turn will be used in a future CFD (Computational Fluid Dynamics) analysis.
Abedin, B, Erfani, S & Blount, Y 1970, 'Social media adoption framework for aged care service providers in Australia', 2017 International Conference on Research and Innovation in Information Systems (ICRIIS), 2017 5th International Conference on Research and Innovation in Information Systems (ICRIIS), IEEE, Langkawi, Malaysia, pp. 1-6.
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© 2017 IEEE. The aged care sector has been a late adopter of social media platforms for communicating, collaborating, marketing and creating brand awareness. There is little research that examines the adoption of social media by aged care service providers for these purposes. This paper reviews the status of social media adoption in the Australian aged care industry, to understand in what ways social media can serve older people's needs, and to develop recommendations for aged-care service providers to adopt social media applications to empower older people. Through a review of the literature and interviews with Australian experts, this paper suggests aged care providers use a three-phase framework when adopting social media in the aged care sector. The first phase is to adopt a popular public social media platform such as Facebook followed by Instagram and Twitter. The second phase supports interaction by encouraging posts and feedback by locally hosted member forums. The third phase is the adoption of specialised social applications for closed groups and specific functions. The paper concludes with a discussion on the implications of the framework and proposes directions for future research.
Abeywickrama, HV, Jayawickrama, BA, He, Y & Dutkiewicz, E 1970, 'Algorithm for energy efficient inter-UAV collision avoidance', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, Australia, pp. 1-5.
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© 2017 IEEE. Unmanned Aerial Vehicles (UAV) are fast gaining popularity. Due to their many desired features, in the near future, UAVs will be an inevitable part of many fields. This increased use of UAVs, has given rise to the idea of multi-UAV systems, commonly known as UAV swarms, where a number of UAVs ranging from two to hundreds have to collaborate with each other and perform a common shared task or tasks. When sharing a common air space and flying in close proximity of each other, inter-UAV collision avoidance becomes an important factor in UAV swarms. Thus, for effective use of UAV swarms, it is essential to have an efficient inter-UAV collision avoidance mechanism. Although there are a number of suggested techniques, avoiding inter-UAV collisions while minimising the energy consumption of the UAV system is a challenge. In this paper, a Potential Field Method based algorithm to avoid collisions of a UAV system, considering the minimising of system energy usage, is suggested. We consider the energy consumption of a UAV system to depend on the distance travelled and the turns- A ngular changes, in trajectories. Our method reduces the angular changes in trajectories by an average of 36% and total travel distance by 6-8%. The total time taken to achieve targets is reduced by 3-14% depending on the scenario.
Abuhilaleh, M, Li, L, Begum, M & Zhu, J 1970, 'Power management and control strategy for hybrid AC/DC microgrids in autonomous operation mode', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The hybrid AC/DC microgrid structure is considered to be the future trend of power systems, due to the vital necessity of connecting more renewable energy sources and storage elements to supply modern AC and DC loads. This paper proposes a power sharing and control strategy for hybrid AC/DC microgrids using the droop control technique. A new structure of the hybrid microgrid is suggested by connecting different AC, and DC sub-grids by an interlinking converter. This can be symbolized by a bi-directional converter that acts as a rectifier when power flows from the AC sub-grid to the DC subgrid. And operates as an inverter when power flows from the DC subgrid to the AC one. The proposed structure and power management strategy also allow power flows between DC sides of the system through the AC subgrid as a common bus. Five scenarios of transferring power from one sub-grid to another are studied using. MATLAB/Simulink. The results indicate a high level of the system's felexibility in managing th power flow.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Impact of struck-out text on writer identification', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 1465-1471.
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© 2017 IEEE. The presence of struck-out text in handwritten manuscripts may affect the accuracy of automated writer identification. This paper presents a study on such effects of struck-out text. Here we consider offline English and Bengali handwritten document images. At first, the struck-out texts are detected using a hybrid classifier of a CNN (Convolutional Neural Network) and an SVM (Support Vector Machine). Then the writer identification process is activated on normal and struck-out text separately, to ascertain the impact of struck-out texts. For writer identification, we use two methods: (a) a hand-crafted feature-based SVM classifier, and (b) CNN-extracted auto-derived features with a recurrent neural model. For the experimental analysis, we have generated a database from 100 English and 100 Bengali writers. The performance of our system is very encouraging.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Legibility and Aesthetic Analysis of Handwriting', 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), IEEE, Kyoto, Japan, pp. 175-182.
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© 2017 IEEE. This paper deals with computer-based cognitive analysis towards legibility and aesthetics of a handwritten document. The legible text creates a human perception that the writing can be read effortlessly because of its orthographic clarity. The aesthetic property relates to the beautiful appearance of a handwritten document. In this study, we deal with these properties on offline Bengali handwriting. We formulate both legibility and aesthetic analysis tasks as machine learning problems supervised by the human cognitive system. We employ automatically derived feature-based recurrent neural networks to investigate writing legibility. For aesthetics evaluation, we employ hand-crafted feature-based support vector machines (SVMs). We have collected contemporary Bengali handwritings, on which the subjective legibility and aesthetic scores are provided by human readers. On this corpus containing legibility and aesthetic ground-Truth information, we executed our experiments. The experimental results obtained on various handwritings are encouraging.
Afzal, MU & Esselle, KP 1970, 'Application of near-field phase transformation to steer the beam of high-gain antennas in two dimensions', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, pp. 1947-1948.
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Afzal, MU & Esselle, KP 1970, 'The use of near-field phase transformation to design a low-profile azimuthal beam scanning antenna system', 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, Verona, ITALY, pp. 750-753.
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Afzal, MU, Lalbakhsh, A & Esselle, KP 1970, 'Integration of sparse array feed and phase correction to design high gain resonant cavity antennas', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, Singapore, SINGAPORE, pp. 2884-2887.
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Aghayarzadeh, M, Khabbaz, H, Fatahi, B & Terzaghi, S 1970, 'Continuum Numerical Modelling Of Dynamic Load Test For Steel Pipe Piles', Proceedings of the International Conference On Advancement of Pile Technology and Pile Case Histories, International Conference On Advancement of Pile Technology and Pile Case Histories, Universitas Katolik Parahyangan, Bali, Indonesia, pp. 1-10.
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In order to estimate the static axial capacity of driven piles, one-dimensional wave equationanalysis was proposed in 1960, in which pile is simulated by a number of masses attached to each other usingelastic springs, sliders and linear viscous dampers to simulate the visco-elasto-plastic response of the soil. Later,the signal matching technique program, CAPWAP, employing this model, was proposed to overcome theshortcomings of the conventional model. The main objective of this paper is to assess capabilities of so-calledcontinuum numerical model in analyzing dynamic pile load test. In this paper, the static and dynamic load testsof an open-ended steel pipe pile driven into dense sand have been simulated using PLAXIS 2D finite elementsoftware. After carrying out a number of numerical analyses the results of numerical simulation have beencompared to static load test results. The capabilities and challenges of the continuum numerical analysis tosimulate dynamic pile testing of steel pipe piles are briefly discussed.
Aghdam, MM, Aguilera, RP, Li, L & Zhu, J 1970, 'Fuzzy-based self-tuning model predictive direct power control of grid-connected multilevel converters', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power converters. At each sampling instant, a fuzzy logic controller is used to determine online the best weighting factor values for a given operating point. These values are then used to solve the multi-objective optimal control problem associated to the MPDPC. The optimal solution that minimizes the multi-objective cost function is chosen as the input (power switch state). The proposed method is examined through a case study and verified numerically via MAT LAB SIMULINK. A comparative study is conducted to demonstrate the effective performance of this approach. As a result of the proposed weighting factor online tuning, an improved performance in terms of total harmonic distortion and average switching frequency is attained when compared with fixed weighting factors.
Aghdam, MM, Li, L, Zhu, J, He, T & Zhang, J 1970, 'Time-delayed model predictive direct power control for vehicle to grid and grid to vehicle applications', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 4662-4667.
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© 2017 IEEE. This paper presents a time-delayed model predictive control for power converters used in vehicle to grid and grid to vehicle systems. Finite-based model predictive control has proven to be an alternate digital control method for power converters. However, there are some real-time implementation issues, including specifically time delay, that have to be addressed in order to achieve the system reliability and stability as well as better performance. The proposed method compensates the delay time arising from measuring, calculating, and applying the optimal control sequence in the digital processor. In this way, the delay time is considered in the system input and optimal switching states are applied to the converter once they are available. The proposed method is studied through two benchmarks and verified numerically via MATLAB/Simulink.
Aguilera, RP, Acuna, P, Su, X, Lezana, P & McGrath, B 1970, 'Sequential Phase-Shifted Model Predictive Control for multicell power converters', 2017 IEEE Southern Power Electronics Conference (SPEC), 2017 IEEE Southern Power Electronics Conference (SPEC), IEEE, Chile.
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© 2017 IEEE. This paper proposes a sequential Phase-Shifted Model Predictive Control (PS-MPC) strategy for multicell power converters. The key novelty of this proposal lies in the way the predictive control strategy is formulated to fully exploit a phase-shifted pulse width modulation (PS-PWM) stage. Normally, when using a linear controller along with a standard PS-PWM stage, the modulator receives the same duty cycle for all the internal carriers. In contrast, by means of an appropriate choice of synchronized models for each carrier, the proposed predictive controller obtains independent optimal duty cycles for each carrier in a sequential manner. This allows one to formulate the optimal control problem to govern not only the output current but also the internal floating capacitor voltages, similarly to the finite-control-set MPC (FCS-MPC) case. As a result, the proposed sequential PS-MPC can attain a faster floating voltage balancing dynamic when compared to a standard PS-PWM implementation. Moreover, it generates a fixed-spectrum in the steady state with a constant commutation rate, which outperforms a standard FCS-MPC strategy. Simulation results of the proposed sequential PS-MPC strategy governing a single-phase four-level flying capacitor converter are presented to verify its dynamic and steady-state performance.
Ahadi, A, Lister, R, Lal, S, Leinonen, J & Hellas, A 1970, 'Performance and Consistency in Learning to Program', Proceedings of the Nineteenth Australasian Computing Education Conference, ACE '17: Nineteenth Australasian Computing Education Conference, ACM, Geelong, pp. 11-16.
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Performance and consistency play a large role in learning. Decreasing the effort that one invests into course work may have short-term benefits such as reduced stress. However, as courses progress, neglected work accumulates and may cause challenges with learning the course content at hand.
In this work, we analyze students' performance and consistency with programming assignments in an introductory programming course. We study how performance, when measured through progress in course assignments, evolves throughout the course, study weekly fluctuations in students' work consistency, and contrast this with students' performance in the course final exam.
Our results indicate that whilst fluctuations in students' weekly performance do not distinguish poor performing students from well performing students with a high accuracy, more accurate results can be achieved when focusing on the performance of students on individual assignments which could be used for identifying struggling students who are at risk of dropping out of their studies.
Ahmed, F, Chowdhury, MHM & Rahman, AMA 1970, 'A multiband MIMO antenna for future generation handset applications', 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, Coxs Bazar, BANGLADESH, pp. 91-94.
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Ahmed, F, Hasan, N & Chowdhury, MHM 1970, 'A compact low-profile ultra wideband antenna for biomedical applications', 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, Coxs Bazar, BANGLADESH, pp. 87-90.
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Ahmed, F, Hasan, N & Rahman, AMA 1970, 'A compact planar multiple-input multiple-output (MIMO) antenna for ultra-wideband applications', 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), IEEE, Khulna, BANGLADESH, pp. 1-5.
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Ahmed, S, Quinn, J, Catherwood, M, Thornton, P, Bergin, S, Kennedy, P, Elsir, S, Hennessy, B & Murphy, P 1970, 'Unmutated IGHV and Double Negative CD38/CD49d Predict Good Prognosis and Long Treatment Free Survival (TFS) in Chronic Lymphocytic Leukaemia; Regardless of Genetic Mutations', BLOOD, 59th Annual Meeting of the American-Society-of-Hematology (ASH), AMER SOC HEMATOLOGY, GA, Atlanta.
Akter, MP & Lu, DD-C 1970, 'Model Predictive Controlled Active NPC Inverter for Voltage Stress Balancing Among the Semiconductor Power Switches', IOP Conference Series: Earth and Environmental Science, International Conference on Sustainable Energy Engineering, IOP Conference Series: Earth and Environmental Science, IOP Publishing, Perth, Australia, pp. 012019-012019.
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© Published under licence by IOP Publishing Ltd. This paper presents a model predictive controlled three-level three-phase active neutral-point-clamped (ANPC) inverter for distributing the voltage stress among the semiconductor power switches as well as balancing the neutral-point voltage. The model predictive control (MPC) concept uses the discrete variables and effectively operates the ANPC inverter by avoiding any linear controller or modulation techniques. A 4.0 kW three-level three-phase ANPC inverter is developed in the MATLAB/Simulink environment to verify the effectiveness of the proposed MPC scheme. The results confirm that the proposed model predictive controlled ANPC inverter equally distributes the voltage across all the semiconductor power switches and provides lowest THD (0.99%) compared with the traditional NPC inverter. Moreover, the neutral-point voltage balancing is accurately maintained by the proposed MPC algorithm. Furthermore, this MPC concept shows the robustness capability against the parameter uncertainties of the system which is also analyzed by MATLAB/Simulink.
Akter, MP, Lu, DD-C & Jianguo Zhu 1970, 'Model predictive controlled three-level active-neutral-point-clamped inverter with improved computational speed and stability, and balanced DC-link voltages', 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), IEEE, Kaohsiung, Taiwan, pp. 116-121.
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© 2017 IEEE. This paper proposes an advanced model predictive control for the three-level active-neutral-point-clamp (ANPC) inverter in order to improve the system performance with fast dynamic response and ensure the stability of the controller. The proposed scheme is Lyapunov function based voltage mode control which utilizes the discrete behavior of the converter considering the unavoidable quantization errors between the controller and the control actions selected from the finite control set of the ANPC inverter. A three-level three-phase ANPC inverter model is developed in MATLAB/Simulink environment to verify the effectiveness of the proposed MPC scheme. The simulation results confirm the computational speed improvements of the proposed MPC algorithm without compromising the performance such as total harmonic distortion (THD) of the three-level ANPC inverter. Moreover, the stability of the proposed technique is ensured by the nonlinear system model. Furthermore, the dc-link capacitor voltage balancing is also accurately maintained by the proposed controller at all times.
Alambeigi, P, Burry, J & Cheng, E 1970, 'Investigating the effects of the geometry on speech privacy of semi-enclosed meeting spaces', Simulation Series, pp. 1-8.
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This paper investigates the effect of the room geometry on speech privacy of small meeting areas. The aim is to explore different semi-enclosed room shapes within an open plan office and study their influence on speech privacy and the significant parameter and performance metric, Speech Transmission Index (STI). This is a simulation study in the room acoustic modeling software (ODEON). The impact of the geometry on the sound of the large spaces such as concert halls has been widely reported, however, at the scale of the small, particularly semi-enclosed, meeting room the role of geometry in tuning the acoustic performance needs to be studied further. This research investigates the potential impact of room shape on speech privacy by exploring whether this impact lies above or below the Just Noticeable Difference (JND). Matrices of studies have been developed to study diverse variables individually and the results demonstrate how speech privacy might be affected by modifying room shape.
Alammari, A & Chandran, D 1970, 'Impact of Knowledge Sharing Adoption on Universities Virtual Learning Communities', Proceedings of the Annual Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, Hawaii, USA, pp. 4485-4494.
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In new age, knowledge has become a significant
source. Knowledge sharing is a substantial component
of success in any organisation. In various
organisations, knowledge sharing adoption is lacking,
especially among academic staff working in Saudi
universities. This paper investigates collectivism
impact on knowledge-sharing factors among
academics in Saudi e-learning communities. A
conceptual model that will affect the knowledge
sharing behaviour within the e-learning community in
Saudi universities is proposed. Hypotheses have been
accordingly developed. Data was collected in different
Saudi public universities. Partial Least Square
approach has been applied to analyse the data. The
findings of this study provide key factors affecting the
process of knowledge-sharing adoption between
academic staff within the virtual learning communities
in Saudi universities.
Aldebei, K, Farhood, H, Jia, W, Nanda, P & He, X 1970, 'Sequential and Unsupervised Document Authorial Clustering Based on Hidden Markov Model', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, pp. 379-385.
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© 2017 IEEE. Document clustering groups documents of certain similar characteristics in one cluster. Document clustering has shown advantages on organization, retrieval, navigation and summarization of a huge amount of text documents on Internet. This paper presents a novel, unsupervised approach for clustering single-author documents into groups based on authorship. The key novelty is that we propose to extract contextual correlations to depict the writing style hidden among sentences of each document for clustering the documents. For this purpose, we build an Hidden Markov Model (HMM) for representing the relations of sequential sentences, and a two-level, unsupervised framework is constructed. Our proposed approach is evaluated on four benchmark datasets, widely used for document authorship analysis. A scientific paper is also used to demonstrate the performance of the approach on clustering short segments of a text into authorial components. Experimental results show that the proposed approach outperforms the state-of-the-art approaches.
Al-Doghman, F, Chaczko, Z & Jiang, J 1970, 'A Review of Aggregation Algorithms for the Internet of Things', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Piscataway, USA, pp. 480-487.
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© 2017 IEEE. The Internet of Things (IoT) epitomizes the upcoming eminent transition in the world’s economy and human lifestyle where people and various objects are correlated within networks. Data Aggregation is a technique which can be used to mitigate Big Data challenges within IoT. This paper provides an overview of various approaches for aggregation of data in IoT infrastructure. A new class of reliable Data Aggregation algorithm is discussed as well. This new class of algorithm uses a consensus based aggregation with fault tolerance methodology in Fog Computing. The new approach allows promoting adaptive behavior and more efficient delivery of the aggregation outcomes to the ascendant node(s). The proposed method is fault tolerant and deals with nodes reliability issues.
Aleidi, AI & Chandran, D 1970, 'Does institutional environment promote women’s it entrepreneurial intentions in Saudi Arabia? Technological and institutional perspectives', Proceedings ot the 21st Pacific Asia Conference on Information Systems: ''Societal Transformation Through IS/IT'', PACIS 2017, The Pacific Asia Conference on Information Systems, Langkawi, Malaysia.
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From the foregoing studies, they unanimously agreed that women in technological entrepreneurship and innovation are strongly underrepresented. Based on previous literature of female entrepreneurship and Information Systems (IS), the study for the first time aims to propose an integrated model to explain women’s IT entrepreneurial intention as a new driver of IT entrepreneurial behavior. In particular, we aim to investigate the influence of socio-cultural factors as well as technological factors on intention and decision-making processes that lead women to become tech-entrepreneurs in Saudi Arabia. Investigating such factors that affect women’s entrepreneurial intention to become so is beneficial for motivating a new generation of women entrepreneurs in the IT context as well as providing a further understanding to IS researchers and practitioners.
Aleidi, AI & Chandran, D 1970, 'Technological and institutional perspectives of women’s IT entrepreneurial intention in Saudi Arabia', AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation, Americas Conference on Information Systems, Boston, USA.
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Despite the increasing awareness of the importance of technological entrepreneurship and innovation, and the necessity to enhance women participation in such businesses, a comprehensive literature review shows a paucity of research in women’s IT entrepreneurship. Specifically, Information Systems and female entrepreneurship disciplines have ignored the study of women’s IT entrepreneurial behavior. Drawing on previous literature, this research for the first time aims to develop an integrated model of women’s IT entrepreneurship. Particularly, this research in progress aims to examine the influence of institutional and technological factors on intention and decision-making processes that lead women to become tech-entrepreneurs in Saudi Arabia. The investigation reveals that understanding entrepreneurial intention is critical for motivating a new generation of women entrepreneurs in the IT context. Better guidance can be a new driver of IT entrepreneurial behavior among Saudi women which is the aim of this study.
Alenazy, WM & Chaczko, Z 1970, 'ETAM towards ICT teaching and learning studio for interactive learning in Information and Communication Technology', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-11.
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© 2017 IEEE. Recent advances in Information and Communication Technology (ICT) have stimulated the need for adaptation of new models of teaching and learning in educational institutions. Since the beginning, the use of technology in education has gained a lot of attention and has been applied to many areas in the academic domain. The introduction of ICT has motivated scholars to find out how various ICT tools could be deployed and efficiently used. Due to rapid changes in ICT, an extended TAM (ETAM) has been developed to highlight the demand for using advanced ICT tools in the education process. The idea is to support the acceptance of technology implementations by modifying the conventional model with the pre-acknowledgement of additional elements that reflect the state of art technological advances. These additional factors aim to increase the motivation acceptance levels by instructors and students alike towards ICT teaching and learning studio style.
Alexander-Floyd, JJ, Entezari, A, Ying, M, Haroon, S & Gidalevitz, T 1970, 'Natural genetic variation modifies polyglutamine aggregation via an imbalance in autophagy.', MOLECULAR BIOLOGY OF THE CELL, Annual Joint Meeting of the American-Society-for-Cell-Biology and the European-Molecular-Biology-Organization (ASCB/EMBO), AMER SOC CELL BIOLOGY, PA, Philadelphia.
Al-Fatlawi, AH, Fatlawi, HK & Ling, SH 1970, 'Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Seogwipo, South Korea, pp. 2871-2874.
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Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.
Alghamdi, A, Hussain, W, Alharthi, A & Almusheqah, AB 1970, 'The Need of an Optimal QoS Repository and Assessment Framework in Forming a Trusted Relationship in Cloud: A Systematic Review', 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), IEEE, Shanghai, China, pp. 301-306.
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© 2017 IEEE. Due to the cost-effectiveness and scalable features of the cloud the demand of its services is increasing every next day. Quality of Service (QOS) is one of the crucial factor in forming a viable Service Level Agreement (SLA) between a consumer and the provider that enable them to establish and maintain a trusted relationship with each other. SLA identifies and depicts the service requirements of the user and the level of service promised by provider. Availability of enormous service solutions is troublesome for cloud users in selecting the right service provider both in terms of price and the degree of promised services. On the other end a service provider need a centralized and reliable QoS repository and assessment framework that help them in offering an optimal amount of marginal resources to requested consumer. Although there are number of existing literatures that assist the interaction parties to achieve their desired goal in some way, however, there are still many gaps that need to be filled for establishing and maintaining a trusted relationship between them. In this paper we tried to identify all those gaps that is necessary for a trusted relationship between a service provider and service consumer. The aim of this research is to present an overview of the existing literature and compare them based on different criteria such as QoS integration, QoS repository, QoS filtering, trusted relationship and an SLA.
Ali, A & Lee, JE-Y 1970, 'Higher-order wine glass mode piezoelectric square resonator with improved quality factor in water', 2017 IEEE SENSORS, 2017 IEEE SENSORS, IEEE, pp. 1-3.
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Ali, A & Lee, JE-Y 1970, 'Piezoelectric transduction of a button-like mode disk resonator for enhanced quality factor in water', 2017 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium (EFTF/IFC), 2017 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium ((EFTF/IFC), IEEE, pp. 26-29.
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Al-Jubouri, B & Gabrys, B 1970, 'Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach', ADVANCED DATA MINING AND APPLICATIONS, ADMA 2017, International Conference on Advanced Data Mining and Applications (ADMA), Springer International Publishing, Singapore, SINGAPORE, pp. 313-325.
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Alkalbani, AM, Gadhvi, L, Patel, B, Hussain, FK, Ghamry, AM & Hussain, OK 1970, 'Analysing Cloud Services Reviews Using Opining Mining', 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), IEEE, Tamkang Univ, Taipei, TAIWAN, pp. 1124-1129.
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Al-Manasia, M, Chaczko, Z & Ounzar, A 1970, 'AHRC: An Optimized Cache Associativity', Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016, IEEE International Conference on High Performance Computing and Communications, IEEE, Sydney, NSW, Australia, pp. 811-817.
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Hardware resources require efficient scaling because the future of computing technology seems to be intensive multithreaded. One of the main challenges in the scalability of computers hardware is the hierarchy of the memory. Chip-multiprocessors (CMPs) rely on large and multi-level hierarchies of caches to reduce cost of resources and improve systems performance. These multi-level hierarchies are the ones, which also help to solve the issue of limited bandwidth and minimize the latency of the main memory. Almost half of the area of the chip and a large percentage of the system energy is used by caches. One of the main problems limiting the scalability of cache hierarchies is called cache associativity. Caches consume a lot of energy to implement associative lookups. This affects the performance of the system by reducing the efficiency of caches. This paper describes a new design of cache that we called - Adaptive Hashing and Replacement Cache (AHRC). This design has the ability of maintaining high associativity with an advanced method of replacement policy. AHRC can improve associativity and maintain the number of possible locations, where each block is kept as small as possible. Several workloads were simulated on a large-scale CMP with AHRC as the last-level cache. We propose an Adaptive Reuse Interval Prediction (ARIP) scheme for AHRC, which is superior to the NRU scheme that was described by Seznec. Results demonstrate that AHRC has better energy efficiency and higher performance as compared to conventional caches. Additionally, large caches that utilize AHRC are the most suitable in many core CMPs to provide a more significant improvement and scalability than the smaller caches. However, AHRC with a higher-level replacement may lead to loss of energy for workloads that are not sensitive to the policy governing the replacement process.
Al-Soeidat, MR, Lu, DD-C & Jianguo Zhu 1970, 'A more accurate analog voltage-based photovoltaic maximum power point tracking technique', 2017 8th International Renewable Energy Congress (IREC), 2017 8th International Renewable Energy Congress (IREC), IEEE, Amman, Jordan, pp. 1-5.
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© 2017 IEEE. In this paper, an analog voltage based maximum power point tracking (MPPT) algorithm for individual photovoltaic (PV) panel is proposed. The fixed voltage reference method is the simplest method for tracking, but it does not give good MPPT efficiency because the MPP voltage point changes at different solar insolation levels. A roughly linear slope is formed when connecting the MPP points measured from the highest isolation level to the lowest. Utilizing this characteristic, a bipolar junction transistor BJT is used to implement a variable voltage reference that improves the accuracy of the maximum power point voltage when the insolation changes. The proposed circuit is simple and easy to implement and it can easily track the maximum power point without the need of a digital controller or PID controller, so the cost and circuit complexity is reduced.
Alturki, R & Gay, V 1970, 'Usability Testing of Fitness Mobile Application : Methodology and Quantitative Results', Computer Science & Information Technology (CS & IT), 7th International Conference on Computer Science, Engineering & Applications, Academy & Industry Research Collaboration Center (AIRCC), Copenhagen, Denmark.
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Obesity is a major health problem around the world. Saudi Arabia is a nation where obesity is increasing at an alarming rate. Mobile apps could help obese individuals but they need to be usable and personalized to be adopted by those users. This paper aims at testing the usability of a fitness mobile app” Twazon”, an app in Arabic language. This paper presents an extensive literature review on the attributes that improve the usability of fitness apps. Then, it explains our methodology and our set up of a trial to test the usability of Twazon app that is popular in Saudi Arabia. The usability attributes tested are effectiveness, efficiency, satisfaction, memorability, errors, learnability and cognitive load. The trial is done in collaboration with participants from the Armed Forces Hospitals - Taif Region in Saudi Arabia. The results highlight that the app failed to meet with the usability attributes.
Alvarez, JK, Sutjipto, S & Kodagoda, S 1970, 'Validated ground penetrating radar simulation model for estimating rebar location in infrastructure monitoring', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1460-1465.
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© 2017 IEEE. Biogenic sulphide corrosion of reinforced concrete sewer pipes is an ongoing problem for wastewater governing bodies. Ensuring Workplace Health and Safety (WHS) is also an issue due to the harsh nature of sewer environments. As such, research into technologies that allow for automatic unmanned site assessments are of major priority to wastewater managing utilities. The use of Ground Penetrating Radar (GPR) is currently being investigated for it's ability to provide subsurface images. However, the GPR technology has not been tested and validated in harsh sewer environments. It is anticipated that the GPR interpretation can be hindered by low signal to noise ratio. As data driven machine learning techniques have proven to work in higly challenging data, our intenetion is to apply such techniques in GPR data processing. However, this is hindered by the lack of large amount of training data as it is prohibitively hard to collect such real experimental testing data. Thus, the aim of this study is to validate a ground penetrating radar simulation software, gprMax, and test it for suitability in generating realistic, big data sets with which to train the aforementioned data driven machine learning models supplemented with actual sewer crown data. The results of the study is the validation of the GPR simulator, tuned and able to generate reasonably realistic data. A novel concrete analog was also developed to allow for ease of testing of various parameters such as rebar cover depths and rebar spacing.
Alwidyan, F, Al-Ani, A, Kirchner, N & Zeibots, M 1970, 'An effort-based evaluation of pedestrian route choice behaviour', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1844-1849.
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Route Choice is one of the main challenging problems from theoretical and practical viewpoints in the realm of pedestrian behaviour. A prime underlying concern of researchers in this field is to identify criteria or discover principles that pedestrians use to select their routes based on. Despite the fact that there are infinite possible routes between two given destinations in space, pedestrians in real situations tend to choose a certain finite number of available trajectories. As a consequence, there is a high demand for theoretical framework and models to describe route choice. The fundamental assumption is that pedestrians follow a route over which Effort is optimized. The existing criteria in the literature to predict route choice of pedestrians are mainly related to route length and travel time. In this paper, we consider physical effort as a new criterion, which indicates the pedestrian's metabolic energy expenditure that pedestrians may consume during their walking from origin to destination. A case study is included to illustrate the pertinent concepts and ideas introduced. Our discussion concludes with an overview of how this reconceptualization builds the foundations for a model that will enable improved operations, planning, and design of public transport facilities.
Alzahid, Y, Mostaghimi, P, Warkiani, ME, Armstrong, RT, Joekar-Niasar, V & Karadimitriou, N 1970, 'Alkaline Surfactant Polymer Flooding: What Happens at the Pore Scale?', SPE Europec featured at 79th EAGE Conference and Exhibition, SPE Europec featured at 79th EAGE Conference and Exhibition, SPE, pp. 386-402.
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Abstract Alkaline-surfactant-polymer (ASP) flooding is a Chemical Enhanced Oil Recovery (CEOR) method whereby alkali, surfactant and polymer are injected as the same slug. It is one of the most promising world-wide focus of CEOR research and field trials, due to the unique synergy of the three chemical components. Polymers increase the viscosity of injected water, which improves macroscopic sweep efficiency by stabilizing the displacing front and counteracting heterogeneity effects. Surfactants, on the other hand, decrease the interfacial tension between the injected water and crude oil, which improves microscopic displacement efficiency by mobilizing trapped oil. Alkaline chemicals generate soap when reacting with crude oil, which reduces surfactant adsorption to grain surfaces. To fully understand the flow mechanisms in oil reservoirs and develop efficient recovery methods, it is essential to recognize the physics at the pore scale since this is the length scale at which capillary-trapped oil is mobilized. We developed an experimental micro-scale approach in which oil recovery is analyzed using microfluidics. The micromodels are fabricated based on: (1) a pore network generated via a Delaunay triangulation with an average pore size of 60 µm, (2) X-ray micro-Computed Tomography images of Bentheimer sandstone with resolution of 4.95 µm, and (3) a fractured network with a porosity of 10%. The networks are etched into silicon wafers and used to fabricate polydimethylsiloxane (PDMS) microfluidic devices. We compare not only oil recovery with ASP flooding between different porous networks but we also study displacement mechanisms and pore scale emulsion formation for ASP formulations that exhibit Winsor Type II+, II- and III behaviour. Our studies elucidate micro-scale oil recovery mechanisms for different ASP flooding scenarios. Our results provide direct visualization of the micro-scale phenomena occurring d...
Alzughaibi, A & Chaczko, Z 1970, 'A precise human detection model using combination of feature extraction techniques in a dynamic environment', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. This research paper presents a Machine Learning-based human detection model focusing on improving precision of human movement conditions in video frames. The problem is addressed by focusing on pre-processing and an efficient feature extraction methodology. Combination of features are extracted, including histograms of gradients (HoG), histograms of colors (HoC), and histograms of bars (HoB). These featuresets are combined to form the finall feature vector that describes the human shape, and the Support Vector Machine (SVM)-based classifier is used for classification purposes. Improving the precision will allow the human movement detector to make better detections by reducing false positives and missed detections, which are the problems faced by current detection techniques. Training of the algorithm is done using the INRIA dataset and tested on sequences depicting conditions of moving humans in different environments. In the testing phase, the search space is reduced using an upper body detector, which is done using haar features. The reduced space is used to carry out human detection using the proposed feature extraction technique. The proposed detector approach performs well, and the number of missed detections are reduced. However, some false detections are still performed, but this is due the fact that some objects resemble humans. The proposed model is benchmarked with the current state-of-the-art detectors using a challenging test dataset, which is used to test the performance. The Receiver Operating Characteristic (ROC) curves for the precision-recall and true-positive rates are plotted to compare and evaluate the results. The proposed model outperforms most of the current state-of-the-art detectors.
Alzughaibi, A & Chaczko, Z 1970, 'Human Detection Using Illumination Invariant Feature Extraction for Natural Scenes in Big Data Video Frames', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 443-450.
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© 2017 IEEE. This research proposes a reliable machine learning based computational solution for human detection. The proposed model is specifically applicable for illumination-variant natural scenes in big data video frames. In order to solve the illumination variation problem, a new feature set is formed by extracting features using histogram of gradients (HoG) and linear phase quantization (LPQ) techniques, which are combined to form a single feature-set to describe features in illumination variant natural scenes. Pre-processing is applied to reduce the search space and improve results, and as the humans are in constant motion in the frames, a search space pruning algorithm is applied to reduce the search space and improve detection accuracy. Non-maximal suppression is also applied for improved performance. A Support Vector Machine (SVM) based classifier is used for fast and accurate detection. Most of the current state-of-the-art detectors face numerous problems including false, missed, and inaccurate detections. The proposed detector model shows good performance, which was validated using relevant UCF and CDW test data-sets. In order to compare the performance of the proposed methodology with the state-of-the-art detectors, some selected detected frames were chosen considering their Receiver Operating Characteristic (ROC) curves. These curves are plotted to compare and evaluate the results based on miss rates and true positives rates. The results show the proposed model achieves best results.
Anaissi, A, Khoa, NLD, Mustapha, S, Alamdari, MM, Braytee, A, Wang, Y & Chen, F 1970, 'Adaptive One-Class Support Vector Machine for Damage Detection in Structural Health Monitoring', Advances in Knowledge Discovery and Data Mining (LNAI), Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, Springer International Publishing, Jeju, South Korea, pp. 42-57.
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© 2017, Springer International Publishing AG. Machine learning algorithms have been employed extensively in the area of structural health monitoring to compare new measurements with baselines to detect any structural change. One-class support vector machine (OCSVM) with Gaussian kernel function is a promising machine learning method which can learn only from one class data and then classify any new query samples. However, generalization performance of OCSVM is profoundly influenced by its Gaussian model parameter ϭ. This paper proposes a new algorithm named Appropriate Distance to the Enclosing Surface (ADES) for tuning the Gaussian model parameter. The semantic idea of this algorithm is based on inspecting the spatial locations of the edge and interior samples, and their distances to the enclosing surface of OCSVM. The algorithm selects the optimal value of ϭ which generates a hyperplane that is maximally distant from the interior samples but close to the edge samples. The sets of interior and edge samples are identified using a hard margin linear support vector machine. The algorithm was successfully validated using sensing data collected from the Sydney Harbour Bridge, in addition to five public datasets. The designed ADES algorithm is an appropriate choice to identify the optimal value of ϭ for OCSVM especially in high dimensional datasets.
Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 1970, 'Self-advised Incremental One-Class Support Vector Machines: An Application in Structural Health Monitoring', NEURAL INFORMATION PROCESSING, ICONIP 2017, PT I, 24th International Conference on Neural Information Processing (ICONIP), Springer International Publishing, Guangzhou, PEOPLES R CHINA, pp. 484-496.
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Anshu, A, Touchette, D, Yao, P & Yu, N 1970, 'Exponential separation of quantum communication and classical information', Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, STOC '17: Symposium on Theory of Computing, ACM, Montreal, Canada, pp. 277-288.
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© 2017 ACM. We exhibit a Boolean function for which the quantum communication complexity is exponentially larger than the classical information complexity. An exponential separation in the other direction was already known from the work of Kerenidis et. al. [SICOMP 44, pp. 1550-1572], hence our work implies that these two complexity measures are incomparable. As classical information complexity is an upper bound on quantum information complexity, which in turn is equal to amortized quantum communication complexity, our work implies that a tight direct sum result for distributional quantum communication complexity cannot hold. Motivated by the celebrated results of Ganor, Kol and Raz [FOCS 14, pp. 557-566, STOC 15, pp. 977-986], and by Rao and Sinha [ECCC TR15-057], we use the Symmetric k-ary Pointer Jumping function, whose classical communication complexity is exponentially larger than its classical information complexity. In this paper, we show that the quantum communication complexity of this function is polynomially equivalent to its classical communication complexity. The high-level idea behind our proof is arguably the simplest so far for such an exponential separation between information and communication, driven by a sequence of round-elimination arguments, allowing us to simplify further the approach of Rao and Sinha. As another application of the techniques that we develop, we give a simple proof for an optimal trade-off between Alice's and Bob's communication while computing the related Greater-Than function on n bits: say Bob communicates at most b bits, then Alice must send n/2O(b)bits to Bob. This holds even when allowing pre-shared entanglement. We also present a classical protocol achieving this bound.
Antunes, N, Pipiras, V & Veitch, D 1970, 'Skampling for the Flow Duration Distribution', 2017 29th International Teletraffic Congress (ITC 29), 2017 29th International Teletraffic Congress (ITC 29), IEEE, Genoa, Italy, pp. 63-71.
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© 2017 ITC Press. This paper concerns the problem of estimating the Internet flow duration distribution from indirect measurements due to network constraints. The aim is to estimate the distribution from observing: the possible superpositions (collisions) of sampled flow durations, the flow arrivals-to-departures times without identification of sampled flows and the number of sampled flows in progress. For each type of data available, we present estimators of the flow duration distribution, formulating the problem in queueing system terms. We also propose data streaming algorithms using sampling and sketching (through counters) to obtain the considered partial information from flows. At the core of this skampling (i.e. sampling and sketching) approach is the ability to tune the flow sampling probability for 'optimal' flow load onto sketch entries (queues). Finally, we present numerical results comparing the different estimators of the flow duration distribution using two real Internet traces.
Argha, A, Li, L, Ha, Q, Su, SW & Nguyen, HT 1970, 'Strong stability based robust sliding mode control.', ASCC, Asian Control Conference, IEEE, Gold Coast, QLD, Australia, pp. 588-593.
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© 2017 IEEE. In this paper, a new method for designing the robust Discrete-time Sliding Mode Control (DSMC) is proposed. To this end, firstly, the regular form based sliding mode control is reviewed. Then, according to the notion of strong stability and using scaling matrices (similarity transformation), a new method for considering the stability of discrete-time systems in the presence of general uncertainty term (matched and unmatched) is developed. Above all, in this paper, a new method to design the robust sliding surface according to the notion of strong stability is proposed. This problem is studied for both cases which system is or is not 'strongly stabilizable under state-feedback'.
Argha, A, Li, L, Su, SW & Nguyen, H 1970, 'Sparse Observer-Based Sliding Mode Control For Networked Control Systems', IFAC-PapersOnLine, World Congress of the International Federation of Automatic Control, Elsevier BV, Toulouse, France, pp. 12997-13002.
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© 2017 This paper is devoted to the problem of designing a sparse distributed output feedback discrete-time sliding mode control (ODSMC) for the networked systems. A distributed structure is employed in the discrete-time sliding mode control framework by exploiting other sub-systems’ information to improve the performance of each local controller/observer so that it can widen the applicability region of the given scheme. As the first step, a stability condition is derived for the overall closed-loop system obtained from applying ODSMC to the underlying interconnected system, by assuming a given structure for the control/observer network. In the second step, we explore a methodology to obtain a sparse control/observer network structure with the least possible number of communication links that satisfies the stability condition given in the first step. The boundedness of the obtained overall closed-loop system is analyzed and a bound is derived for the augmented system state which includes the closed-loop system state and the switching function.
Argha, A, Ye, L, Cao, K, Su, SW & Celler, BG 1970, 'Real-time identification of heart rate responses via auxiliary-model-based damped RLS scheme', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Seogwipo, South Korea, pp. 1312-1315.
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This study was devoted to developing a new auxiliary-model-based damped recursive least squares (AMB-DRLS) by which the heart rate dynamics can be identified in a real-time manner. Unlike the current conventional schemes for heart rate dynamics modeling, the proposed scheme can simultaneously identify the HR response dynamics and compensate for the existing HR variability while it can also cope with the blowup phenomenon. The performance of the proposed AMB-DRLS scheme was experimentally verified using fifteen healthy male participants who performed treadmill trials following single-cycle square wave protocol. The obtained results revealed a significant difference in goodness-of-fit for the considered parameter estimation schemes. As a result, we conclude that the proposed AMB-DRLS method is able to identify the heart rate response dynamics in a real-time manner while preventing the blowup phenomenon.
Arora, A, Fitch, R & Sukkarieh, S 1970, 'An Approach to Autonomous Science by Modeling Geological Knowledge in a Bayesian Framework', IEEE International Conference on Intelligent Robots and Systems, International Conference on Intelligent Robots and Systems, IEEE, Vancouver, BC, Canada, pp. 3803-3810.
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Autonomous Science is a field of study which aims to extend the autonomy ofexploration robots from low level functionality, such as on-board perceptionand obstacle avoidance, to science autonomy, which allows scientists to specifymissions at task level. This will enable more remote and extreme environmentssuch as deep ocean and other planets to be studied, leading to significantscience discoveries. This paper presents an approach to extend the high levelautonomy of robots by enabling them to model and reason about scientificknowledge on-board. We achieve this by using Bayesian networks to encodescientific knowledge and adapting Monte Carlo Tree Search techniques to reasonabout the network and plan informative sensing actions. The resulting knowledgerepresentation and reasoning framework is anytime, handles large state spacesand robust to uncertainty making it highly applicable to field robotics. Weapply the approach to a Mars exploration mission in which the robot is requiredto plan paths and decide when to use its sensing modalities to study ascientific latent variable of interest. Extensive simulation results show thatour approach has significant performance benefits over alternative methods. Wealso demonstrate the practicality of our approach in an analog Martianenvironment where our experimental rover, Continuum, plans and executes ascience mission autonomously.
Arukgoda, J, Ranasinghe, R, Dantanarayana, L, Dissanayake, G & Furukawa, T 1970, 'Vector Distance Function Based Map Representation for Robot Localisation', Australasian Conference on Robotics and Automation, Australasian Conference on Robotics and Automation, ACRA, Sydney Australia, pp. 1-8.
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This paper introduces the use of the vectordistance function (VDF) for representing environments,particularly for the use in localisationalgorithms. It is shown that VDF hasa continuous derivative at the object boundaryin contrast to unsigned distance transform,and does not require an environment populatedwith closed object as in the case of thesigned distance transforms, the two most commonstrategies reported in the literature forrepresenting environments based on distancesto nearest occupied regions. As such VDF overcomesthe main disadvantages of the existingdistance transform based representations in thecontext of robot localisation. The key propertiesof VDF are demonstrated and the use ofVDF in robot localisation using an optimizationbased algorithm is illustrated using threeexamples. It is shown that the proposed environmentrepresentation and the localisationalgorithm is effective in providing accurate locationestimates as well as the associated uncertainties
Arukgoda, J, Ranasinghe, R, Danthanarayana, L, Dissanayake, G & Furukawa, T 1970, 'Vector distance function based map representation for robot localisation', Australasian Conference on Robotics and Automation, ACRA, pp. 165-172.
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This paper introduces the use of the vector distance function (VDF) for representing environments, particularly for the use in localisation algorithms. It is shown that VDF has a continuous derivative at the object boundary in contrast to unsigned distance transform, and does not require an environment populated with closed object as in the case of the signed distance transforms, the two most common strategies reported in the literature for representing environments based on distances to nearest occupied regions. As such VDF overcomes the main disadvantages of the existing distance transform based representations in the context of robot localisation. The key properties of VDF are demonstrated and the use of VDF in robot localisation using an optimization based algorithm is illustrated using three examples. It is shown that the proposed environment representation and the localisation algorithm is effective in providing accurate location estimates as well as the associated uncertainties.
Asadabadi, MR, Saberi, M & Chang, E 1970, 'A fuzzy game based framework to address ambiguities in performance based contracting', Proceedings of the International Conference on Web Intelligence, WI '17: International Conference on Web Intelligence 2017, ACM, Leipzig, GERMANY, pp. 1214-1217.
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Asadabadi, MR, Saberi, M & Chang, E 1970, 'Logistic informatics modelling using concept of stratification (CST)', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, ITALY, pp. 1-7.
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Asadnia, M, Kottapalli, AGP, Warkiani, ME, Miao, JM & Triantafyllou, MS 1970, 'Engineering miniaturized hair cell sensors for auditory system', 2017 IEEE 30th International Conference on Micro Electro Mechanical Systems (MEMS), 2017 IEEE 30th International Conference on Micro Electro Mechanical Systems (MEMS), IEEE, Las Vegas, NV, pp. 1173-1176.
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© 2017 IEEE. Mechanosensory haircells are well-evolved biological sensors found in nature. In this paper, we present a novel artificial NEMS stereovilli sensor developed through novel fabrication techniques. The NEMS stereovilli sensor fabrication combines soft-polymer material synthesis methods and nanofiber generation techniques with conventional microfabrication methods to form novel flow sensors. The sensor fabrication mainly consists of three major steps which are 1) fabrication of artificial stereovilli of varying aspect ratios, 2) formation of nanofiber tip-links through electrospinning of PVDF material and 3) development of biomimetic HA-MA hydrogel cupula. These artificial sensors closely mimic stereovilli and achieve ultrahigh sensitivities through a biomimetic design. The sensors achieve a sensitivity and threshold detection limit of 300 mV/(m/s) and 8 μm/s, respectively.
Awadallah, M, Tawadros, P, Walker, P & Zhang, N 1970, 'A low-cost and novel approach in gearshift control for a mild-hybrid powertrain', 2017 IEEE Transportation Electrification Conference and Expo (ITEC), 2017 IEEE Transportation Electrification Conference and Expo (ITEC), IEEE, Chicago, Illinois, USA, pp. 754-760.
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© 2017 IEEE. A novel, the low-cost mild hybrid powertrain is described. It relies on a manual, or robotized manual transmission together with a BLDC motor coupled at the output for filling the torque hole between gear changes. In order to keep manufacturing cost low and improve commercial attractiveness, it incorporates gearshift strategies that deliver high-quality gear shifts. A deliberate downsizing of componentry is implemented as far as possible to reduce cost, and control strategies are employed to exploit the maximum potential of the architecture using methods including torque-fill, ICE-assist, and ICE start-stop. The architecture is developed in simulation using an existing conventional platform to investigate system properties and their effect on performance. In particular, we discuss the gear-shift control algorithm design. Until the cost of full hybrids and fuel cell vehicles is significantly reduced, such a mild hybrid may have the potential to provide the right cost-benefit balance to achieve strong market penetration.
Awadallah, M, Tawadros, P, Walker, P, Zhang, N & Tawadros, J 1970, 'A Comparative Fuel Analysis of a Novel HEV with Conventional Vehicle', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Improvements in fuel economy have always been a dominating driver of vehicle engineering. With some exceptions, benefits attained from hybrid powertrains to transient power delivery has not been the emphasis of research and development efforts. Developing cities around the world would realise significant benefits from improvements to fuel economy, which is outlined in this research by assessing the benefits of a novel HEV architecture. These benefits are compared to a conventional ICE-powered vehicle equivalent, which has an advantage in terms lower upfront costs. The commercial success of HEV implementation, therefore, is determined by its price comparison to conventional vehicles and payback over a number of years of use. This becomes especially important in regions of low-middle income, where the market is much more price-sensitive. The fuel economy of a conventional vehicle and mild hybrid electric vehicle are compared in this paper. This analysis includes vehicle modelling and simulation. Fuel economy is assessed and referenced with standard drive cycles provided by the U.S Environmental Protection Agency. Results demonstrate the benefits of a lower ongoing cost for the HEV architecture.
Awadallah, M, Tawadros, P, Walker, P, Zhang, N & Tawadros, J 1970, 'A system analysis and modeling of a HEV based on ultracapacitor battery', 2017 IEEE Transportation Electrification Conference and Expo (ITEC), 2017 IEEE Transportation Electrification Conference and Expo (ITEC), IEEE, Chicago, Illinois, USA, pp. 792-798.
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© 2017 IEEE. There is a clear shift toward the implementation of electrified vehicles in the market, influenced by the introduction of stricter mandatory regulations on fuel economy improvement and emissions reduction. Of these vehicles, the penetration of hybrid vehicles in the market has much potential for growth in the next few years. The adoption of these vehicles has been limited by the high cost of HEV's, which have less uptake in developing regions. Considering this point, developing countries would see the greatest benefit in adopting HEV technology. A mild hybrid system has an observable advantage in these markets due to its maximum benefit/cost ratio when compared to a full hybrid, plug-in hybrid or electric vehicles. This paper discusses the development of a mild hybrid system for such markets with a focus on improving drive performance and efficiency. To achieve this, high power density ultracapacitors are used based on their fast charging and discharging characteristics, together with intelligent drivetrain control taking advantage of the ultracapacitors' characteristics to deliver smooth torque delivery during gear change (torque-filling). A comparison and analysis is undertaken, of both conventional powertrain and an otherwise identical powertrain but for the incorporation of components required for the mild hybrid system. Software models simulated the powertrains in specific driving conditions, with observations made of the advantages of MHEV over conventional drivetrains. The model demonstrated increased fuel efficiency and performance.
Azadeh, A, Pourreza, P, Saberi, M, Hussain, OK & Chang, E 1970, 'An integrated fuzzy cognitive map-Bayesian network model for improving HSEE in energy sector', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, ITALY, pp. 1-7.
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Azizivahed, A, Ghavidel, S, Ghadi, MJ, Li, L & Zhang, J 1970, 'A novel reliability oriented bi-objective unit commitment problem', 2017 Australasian Universities Power Engineering Conference (AUPEC), 2017 Australasian Universities Power Engineering Conference (AUPEC), IEEE, Melbourne, Australia, pp. 1-6.
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© 2017 IEEE. This paper presents a new solution to unit commitment for single-objective and multi-objective frameworks. In the first step, the total expected energy not supplied (TEENS) is proposed as a separate reliability objective function and at the next step, the multi-objective Pareto front strategy is implemented to simultaneously optimize the cost and reliability objective functions. Additionally, an integer based codification of initial solutions is added to reduce the dimension of ON/OFF status variables and also to eliminate the negative influence of penalty factor. The modified invasive weed optimization (MIWO) algorithm is also developed to optimally solve the proposed problem. The obtained solutions are compared with results in the literature which confirms the applicability and superiority of the proposed algorithm for a 10-unit system and 24-hour scheduling horizon.
Azizivahed, A, Ghavidel, S, Ghadi, MJ, Li, L & Zhang, J 1970, 'Multi-area economic emission dispatch considering load uncertainty', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. Multi-area economic emission dispatch problem provides an optimal schedule for active power of generators and interchange active power between different areas by considering the operational limitations such as balance between generation and consumption, tie-line capacity limitation, generators output constraint, and transmission losses. In this paper, a hybrid method based on shuffled frog leaping algorithm (SFLA) and particle swarm optimization (PSO) is presented to achieve better solution. Furthermore, the stochastic nature of energy consumption is modeled as uncertainty source using scenario reduction technique to achieve the results which are closer to the real condition. The performance of the proposed approach is elaborated in two test systems with different scales including 10-generator with three-area and 40-generator with four-area. The obtained results are compared with those available in the literature to show the effectiveness of the proposed approach.
Azizivahed, A, Ghavidel, S, Ghadi, MJ, Li, L & Zhang, J 1970, 'New energy management approach in distribution systems considering energy storages', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. This paper presents a new method for energy management in distribution networks in the presence of energy storage, solar photovoltaic (PV) systems and diesel generators. Achieving optimal charge and discharge pattern for batteries and optimal diesel generator output with minimal operation cost are the main goal of this paper. The innovation of this paper is to consider the network effect on the underlying method with operational limitations and power-flow constraints such as power loss, voltage and current limitation. The proposed problem is solved for 24-hour time horizon, and the modified imperialist competitive algorithm (ICA) is also developed using mutation strategy to optimally solve the problem. Finally, to show the good performance and supremacy of the proposed method, a 33-bus IEEE standard test system is applied.
Baba, AA, Hashmi, RM & Esselle, KP 1970, 'Investigation of large directivity bandwidth in multilayer resonant cavity antennas', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, FRANCE, pp. 1139-1142.
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Baba, AA, Hashmi, RM, Esselle, KP & Weily, AR 1970, 'On the use of external MATLAB-based optimization with full-wave simulation to design resonant cavity antennas (Special session)', 2017 IEEE International Conference on Computational Electromagnetics (ICCEM), 2017 IEEE International Conference on Computational Electromagnetics (ICCEM), IEEE, pp. 333-335.
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© 2017 IEEE. In this paper, a method to combine MATLAB-based optimization with a 3D electromagnetic simulator is described. The work-flow is presented using five main files (.m,.text,.bas,.sig and.rd1), which are required to establish the connection between the two software systems. Speed constrained particle swarm optimization (SMPSO) algorithm was implemented in MATLAB, which utilized the transient 3D simulator of CST Microwave Studio to carry out iterative full-wave analyses during the optimization process. As a design example, this customized optimization method was then employed to maximize the directivity-bandwidth product (DBP) of a mono-slab resonant cavity antenna (RCA). This optimization yielded a compact RCA, with a peak directivity of 21dBi and an extremely large directivity-bandwdith of 56%. The DBP of this optimized RCA is around 6500 and its total area is only 5.6λ20.
Baba, AA, Hashmi, RM, Esselle, KP & Weily, AR 1970, 'Two-level optimization of a stepped dielectric superstrate to increase gain of a resonant cavity antenna', 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, Verona, ITALY, pp. 1131-1133.
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Balaji, S, Patil, M & McGregor, C 1970, 'A Cloud Based Big Data Based Online Health Analytics for Rural NICUs and PICUs in India: Opportunities and Challenges', 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), IEEE, Aristotle Univ Thessaloniki, Thessaloniki, GREECE, pp. 385-390.
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© 2017 IEEE. High frequency physiological data has great potential to provide new insights for many conditions patients can develop in critical care when utilized by Big Data Analytics based Clinical Decision Support Systems, such as Artemis. Artemis was deployed in NICU at SickKids Hospital in Toronto in August 2009. It employs all the potentiality of big data. Both original data together with newly generated analytics is stored in the data persistence component of Artemis. Real-time analytics is performed in the Online Analytics component. The knowledge extraction component of the system takes care of data mining which is enabled to support clinical research for various conditions. Artemis to date has been utilized in three different implementations. However the use of Artemis still holds many challenges for lower resource settings. This research demonstrates the challenges and opportunities to use Artemis cloud as a cloud computing based Health Analytics-as-a-Service approach for the provision of remote real-time patient monitoring for low resource settings. We present case study research to demonstrate the implications, opportunities and challenges of utilizing Artemis in a low resource setting for small and remote pediatric critical care units viz NICU/PICU in India. Utilizing potentiality of big data within pediatric intensive care units has great potential to improve healthcare in these low resource settings.
Ball, JE 1970, 'Urban Flood Modelling - Process or Regression?', 37th IAHR World Congress, 37th IAHR World Congress, IAHR & USAINS HOLDING SDN BHD, Kuala Lumpur, pp. 1998-2007.
Ball, JE, Vongphachanh, S, Milne-Home, W & Das Gupta, A 1970, 'Seasonal Groundwater Level Fluctuations In Sukhuma District Of Southern Laos', Proceedings of the 37th IAHR World Congress, 37th IAHR World Congress, IAHR, Kuala Lumpur, pp. 5006-5014.
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The objective of this study is to investigate the seasonal fluctuation of groundwater level in Sukhuma Districtby using observed data on groundwater, rainfall and streamflow from June 2015 to May 2016 and remotesensing data derived from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land DataAssimilation System (GLDAS) for the period of June 2015 to March 2016. The results show that thegroundwater level in Sukhuma District increased to the peak elevation during the late wet season (September– October) and it started declining from November until reached the lowest elevation during the late dryseason (April – May). Rainfall was found at a significant (P<0.01) factor influencing the groundwater levelfluctuation. The delay time between rainfall and groundwater level rise was also estimated at about 4 weeks.Moreover, the results also show that groundwater level during the study period in Sukhuma District was notyet depleted. However, the time-series for this analysis is very short to investigate the trend of groundwaterlevel in Sukhuma District. The results of this research also showed good correlation between the soil moisturefrom GLDAS and groundwater level measurement in Sukhuma District (R2 = 0.91) and also showed a goodagreement between the soil moisture from GLDAS at a GRACE footprint and the equivalent water height(EWH) derived from GRACE at a GRACE footprint with an R2 value of 0.72. Therefore, regarding the resultsof this study, a further investigation using these remote sensing data for groundwater study in this region willbe carried out to support in groundwater study for Sukhuma and Southern Laos. The products from GRACEand GLDAS will provide pivotal data for the study of hydrogeology in the areas with limited field observationdata.
Bano, M & Zowghi, D 1970, 'Crowd Vigilante - Detecting Sabotage in Crowdsourcing.', APRES, Springer, pp. 114-120.
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© Springer Nature Singapore Pte Ltd. 2018. Crowdsourcing is a complex and sociotechnical problem solving approach for collaboration of geographically distributed volunteer crowd to contribute to the achievement of a common task. One of the major issues faced by crowdsourced projects is the trustworthiness of the crowd. This paper presents a vision to develop a framework with supporting methods and tools for early detection of the malicious acts of sabotage in crowdsourced projects by utilizing and scaling digital forensic techniques. The idea is to utilize the crowd to build the digital evidence of sabotage with systematic collection and analysis of data from the same crowdsourced project where the threat is situated. The proposed framework aims to improve the security of the crowdsourced projects and their outcomes by building confidence about the trustworthiness of the workers.
Bano, M, Zowghi, D & Kearney, M 1970, 'Feature Based Sentiment Analysis for Evaluating the Mobile Pedagogical Affordances of Apps.', WCCE, IFIP TC 3 World Conference on Computers in Education, Springer, Dublin, Ireland, pp. 281-291.
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© 2017, IFIP International Federation for Information Processing. The launch of millions of apps has made it challenging for teachers to select the most suitable educational app to support students’ learning. Several evaluation frameworks have been proposed in the research literature to assist teachers in selecting the right apps for their needs. This paper presents preliminary results of an innovative technique for evaluating educational mobile apps by analysing the feedback of past app users through the lens of a mobile pedagogical perspective. We have utilized a sentiment analysis tool to assess the opinions of the app users through the lens of the criteria offered by a rigorous mobile learning pedagogical framework highlighting the learners’ experience of Personalization, Authenticity and Collaboration (iPAC). The investigation has provided initial confirmation of the powerful utility of the feature based sentiment analysis technique for evaluating the mobile pedagogical affordances of learning apps.
Barua, S & Braun, R 1970, 'A Markovian Approach to the Mobility Management for the D2D Communication in 5G Cellular Network System', The Fifth Asia-Pacific.
Barua, S & Braun, R 1970, 'Mobility management of D2D communication for the 5G cellular network system: A study and result', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-6.
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© 2017 IEEE. Wireless devices connected to the networks have been increasing remarkably for the last couple of decades. Ubiquitous voice and data connection are the key requisite for the next generation of wireless technology. Device to Device communication is widely known as D2D communication which is a new paradigm of cellular communication, and it was initially proposed to boost the network performance. It takes place when two devices communicate directly without taking significant help from the base station. Similar to other wireless communication systems, mobility management for the D2D communication is a big challenge which is yet to explore properly. Mobility management of D2D communications was enlightened in few papers. It should be managed in such a smart way in a cellular network that should enable lower latency, lower power consumptions, less complexity and last but not the least possible uninterrupted data connections which are primarily the requirements of next generations mobile cellular network. This paper extends our algorithm paradigm of mobility management of D2D communication that was proposed and published previously. We come up with the simulation results in this paper that validate our proposed model. However, we also highlight the D2D communications and mobility issues within it.
Bashir, MR & Gill, AQ 1970, 'IoT enabled smart buildings: A systematic review', 2017 Intelligent Systems Conference (IntelliSys), 2017 Intelligent Systems Conference (IntelliSys), IEEE, London, UK, pp. 151-159.
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© 2017 IEEE. There is an increasing interest in the Internet of Things (IoT) enabled smart buildings. The main question is: What are the key challenges, which must be addressed to effectively manage and analyze the big data for IoT enabled smart buildings. There is a need for the systematic literature review to understand the challenges and the solutions to overcome such challenges. Using the SLR approach, 22 relevant studies were identified and reviewed in this paper. The data from these selected studies were extracted to identify the challenges and relevant solutions. The findings from this research paper will serve as a knowledge base for researchers and practitioners for conducting further research and development in this important area.
Basnet, S, Jayawickrama, BA, He, Y & Dutkiewicz, E 1970, 'Considering switching overhead for transmit power allocation for GAA in spectrum access system', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-5.
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© 2017 IEEE. To enable spectrum sharing the Federal Communication Commission (FCC) has proposed the Spectrum Access System (SAS). In SAS General Authorised Access (GAA) can opportunistically access any part of the 3.5 GHz band. In SAS prior information regarding the time usage of spectrum is not provided by Priority Access Licensee (PAL) and when PAL operation starts the GAA needs to ensure they do not cause interference above a predetermined threshold. In this work we propose a method for GAA Citizen Broadband Radio Service Devices (CBSDs) to switch to different channel considering the probability of spectrum utilisation of GAA. Switching overhead is the time delay when switching the channel from one to another. In our work we proposed the method to calculate switching overhead and maximised average sum capacity of GAA CBSDs considering switching overhead and Root Mean Square (RMS) interference at PAL protection area. Simulations result shows that average sum capacity of GAA CBSDs can be maximised using the proposed method.
Basnet, S, Jayawickrama, BA, He, Y, Dutkiewicz, E & Mueck, MD 1970, 'Opportunistic Access to PAL Channel for Multi-RAT GAA Transmission in Spectrum Access System', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Spectrum Access System (SAS) is a three tier spectrum sharing framework proposed by the FCC. In this framework the aggregate interference of tier-3 General Authorised Access (GAA) users should be below a predetermined threshold anywhere within the tier-2 Priority Access Licensee (PAL) exclusion zone. GAA are expected to use a diverse range of Radio Access Technologies (RATs) with different levels of loading. We propose an optimal transmit power and probability of spectrum utilisation allocation scheme for GAA users that meets the average aggregate interference constraint within the GAA network. Most of the capacity maximisation studies consider the instantaneous aggregated interference from secondary users. In this paper we present an average aggregated interference method to optimise the capacity of GAA users in a single channel. Simulation results suggest that we can significantly increase the capacity of the channel by considering the probability spectrum utilisation of GAA users.
Bautista, MG, Dutkiewicz, E & Yang, Y 1970, 'Design of a compact self-coupled resonator and dual-band bandpass filter in 0.13-μm CMOS technology for millimetre-wave application', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, Singapore, Singapore, pp. 2653-2658.
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© 2018 Electromagnetics Academy. All rights reserved. Design of a miniaturized resonator and its application for dual-band bandpass filter design for millimeter-wave application is presented in this paper. Both the resonator and filter are implemented in a standard 0.13-μm (Bi)-CMOS technology. The performance is extensively verified using an EM simulator from NI-AWR. Using the presented resonator structure, two transmission zeros can be generated and effectively controlled. By feeding the resonator using a capacitive coupling technique, a dual-band bandpass filter that operated at 40 GHz with insertion loss of −0.7 dB and at 71 GHz with insertion loss of −1.5 dB, respectively. The proposed design achieves a reduced layout size of 302 μm × 131 μm.
Bautista, MG, Yang, Y & Dutkiewicz, E 1970, 'Compact on-chip 60 GHz resonator with ring defected ground structure for millimetre-wave applications', 2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), 2017 IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), IEEE, Manila, Philippines, pp. 1-4.
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© 2017 IEEE. This paper presents a design of a miniaturized resonator for millimeter-wave applications. The resonator is implemented in a standard 0.13μm (Bi)CMOS technology. Its performance is verified using an EM simulator from NI-AWR. The designed resonator is based on a unique structure, a combination of spiral loop and meander line structure. The ground plane is characteristically altered with a ring defected ground structure (DGS) to enhance the overall performance. The resonator design exhibits tuning flexibility at its resonance frequency within the mm-wave spectrum that is proportional to its design dimension. By using capacitive feeding, the designed resonator generates one transmission zero at 60 GHz with insertion loss of -2.7 dB and -29.4 dB return loss respectively. The chip size of the resonator excluding the pads is only 116 μm × 236 μm (0.027mm2).
Bautista, MG, Zhu, F, Nguyen, DN & Dutkiewicz, E 1970, 'Double-Balanced Gilbert Mixer with Current Bleeding for RF Front-End Using 0.13µm SiGe BiCMOS Technology', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. This paper presents the design of a differential double-balanced Gilbert mixer in 0.13 um SiGe BiCMOS technology. A current-bleeding injection technique is adopted to increase the bias current at the driver stage without causing overvoltage headroom at the differential pair stage. This mechanism improves the performance in terms of conversion gain, linearity and noise figure. The proposed mixer achieves 10.7 dB conversion gain, 15 dB noise figure, -1.67 dBm 1-dB compression point, and 5 dBm IIP3. The designed double balanced Gilbert mixer with current bleeding is part of an integrated RF front-end for full duplex radio applications in the 2.4 GHz band and occupies an area of 0.1002 × 0.0748 mm2 excluding the pads.
Bautista, MG, Zhu, JB, Zhu, F, Yang, Y & Dutkiewicz, E 1970, 'Design of on-chip quadrature hybrid (3dB) branch-line couplers in 0.13-μm SiGe technology for millimetre-wave applications', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-5.
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© 2017 IEEE. In this paper, design of miniaturized on-chip quadrature hybrid branch-line coupler is investigated. The motivation of this work is to minimize the footprint of the designed coupler while maintaining high performance of the circuit in the mm-wave band spectrum. Three examples are implemented in a standard (Bi)-CMOS process for millimetre wave applications. Excluding the pads, the chip size of the conventional design is 0.35 mm2, and the proposed two other designs structures are 0.26 mm2 and 0.21 mm2, respectively, which indicates an area reduction by 13% and 30% respectively.
Baynes, TM, Wen, T, Nguyen, H & Chen, F 1970, 'Getting to work: Smart work centers reduce morning peak traffic flow', Proceedings - 22nd International Congress on Modelling and Simulation, MODSIM 2017, pp. 804-810.
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Current transport planning in Australia appears to concentrate on increasing supply of transport infrastructure and services and we invert the problem and consider a transport demand management option: smart work centers or hubs located ‘close to load’. Smart work centres are an alternative to CBD office space or home-based work or “third space” options like libraries and cafes. Well-equipped, connected and secure, they are small scale and designed to accommodate small businesses, collaborations and corporate employees working closer to where they live. In principle this is the workplace analogue of water saving devices in the home or distributed energy generation. However, the implementation of smart work centers (SWC) is sparse or close to existing major workplace locations. The research question of this paper is: if SWCs were specifically located near where commuting populations reside (rather than where they work) how would multiple SWCs influence traffic flow on a key arterial road in Sydney? We selected Sydney CBD as a destination zone from the NSW Bureau of Transport Statistics’ origin-destination peak AM data on trips and travel time. We selected only trips by non-mass transit passenger vehicles and used census data to further selected for occupation types that would use a SWC (exclusively Managers, Professionals, Clerical and administrative workers). From this we ranked the origin zones that had the greatest potential for a SWC based on peak AM person hours commuting. For this proof of principle exercise, we selected two segments of Parramatta Road (Sydney’s main western arterial road), which have AM peak flows of ~ 1600 vehicles/hour. From the Sydney Coordinated Adaptive Traffic System (SCATS) we obtained vehicle flow rate and speed data for 15minute intervals over the AM peak for the study segments. From this we derived an elasticity of travel time with flow rate with a parabolic regression function. Based on detailed census and traffic flow ...
Beaudoin, G, Nowamooz, A, Assima, GP, Lechat, K, Gras, A, Entezari, A, Kandji, EHB, Awoh, A-S, Horswill, M, Turcotte, S, Larachi, F, Dupuis, C, Molson, J, Lemieux, J-M, Maldague, X, Plante, B, Bussière, B, Constantin, M, Duchesne, J, Therrien, R & Fortier, R 1970, 'Passive Mineral Carbonation of Mg-rich Mine Wastes by Atmospheric CO2', Energy Procedia, Elsevier BV, pp. 6083-6086.
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Begum, M, Abuhilaleh, M, Li, L & Zhu, J 1970, 'Distributed secondary voltage regulation for autonomous microgrid', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-6.
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© 2017 IEEE. This research addresses the control problem of microgrids and presents a robust distributed secondary control system for voltage regulation of an islanded microgrid with droop-controlled and inverter-based distributed generators (DGs). A consensus-based distributed control approach is proposed to restore the voltage and frequency of the islanded microgrid to the reference values for all DGs within a very short time. The proposed method is flexible to system topology variations which AIDS the plug-and-play operation of microgrid. An autonomous micogrid test system consisting of four DGs is constructed in MATLAB using SimPowerSystem Toolbox to test the proposed design method, and the simulation results show the effectiveness of the proposed control strategy. The performance of the proposed controller is shown through several test case studies.
Begum, M, Li, L & Zhu, J 1970, 'Distributed control techniques for autonomous AC Microgrid-A brief review', 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), IEEE, Dhaka, Bangladesh, pp. 357-362.
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© 2017 IEEE. Distributed generation (DG) is performing progressively significant part in modern power systems. The main objective of this research is to provide a brief review of distributed control structures used so far to control an autonomous AC microgrid system. The distributed control for both grid-connected and autonomous microgrid is current developments for their several advantages compared to conventional central control system comprising the system trustworthiness, lessening its sensitivity to failures, and removing the necessity for a central computing and communication unit. The complete control scheme is divided into three basic control levels, such as primary, secondary and tertiary control level and control structures are considered here for autonomous operation mode. Trends and different approaches used until now, in above control levels are distinctly stated for understanding a brief overview.
Bei, X, Qiao, Y & Zhang, S 1970, 'Networked Fairness in Cake Cutting', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 3632-3638.
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We introduce a graphical framework for fair division in cake cutting, where comparisons between agents are limited by an underlying network structure. We generalize the classical fairness notions of envy-freeness and proportionality in this graphical setting. An allocation is called envy-free on a graph if no agent envies any of her neighbor's share, and is called proportional on a graph if every agent values her own share no less than the average among her neighbors, with respect to her own measure. These generalizations enable new research directions in developing simple and efficient algorithms that can produce fair allocations under specific graph structures.On the algorithmic frontier, we first propose a moving-knife algorithm that outputs an envy-free allocation on trees. The algorithm is significantly simpler than the discrete and bounded envy-free algorithm introduced in [Aziz and Mackenzie, 2016] for compete graphs. Next, we give a discrete and bounded algorithm for computing a proportional allocation on transitive closure of trees, a class of graphs by taking a rooted tree and connecting all its ancestor-descendant pairs.
Beiranvand, A, Abuhilaleh, M & Li, L 1970, 'A novel method for optimizing distributed generation in distribution networks using the game theory', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-5.
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© 2017 IEEE. In this paper, a novel method is presented to optimize distributed generation (DG) in distribution networks. The suggested method shows how DGs should change their sizes and places, if it is necessary, to improve the voltage profile and total power loss of distribution networks. For this purpose, game theory is applied to model the optimization problem. At the first step, an appropriate game based on the Nash equilibrium is suggested. Using the specific features of game theory, the procedure of decision making in the operator centers of distribution grids is considered. Then, the optimization problem is solved by finding Nash equilibrium point. To solve the Nash equilibrium, a specific kind of genetic algorithm (GA) called Nash GA is applied.
Bell, J & Leong, TW 1970, 'Collaborative futures', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, Brisbane, Australia, pp. 397-401.
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© 2017 Association for Computing Machinery. All rights reserved. This paper presents insights into Younger Onset Dementia (YOD) offering clear differentiation in the circumstances, needs and challenges of people with YOD from those with late onset dementia. We point to opportunities for the potential role of digital technology to improve the experiences of people living with YOD. This is important because while HCI has long engaged with dementia, these efforts have been predominantly focused on designing technologies for elderly people experiencing dementia. In particular, this paper highlights concerns raised by people with YOD which have significant impact for HCI researchers when engaging people with YOD in research and in technology design. As such, this paper argues for a broadening of HCI research to include YOD and to rethink current research and design methods in 'dementia and technology' settings.
Belotti, Y, Conneely, M, Huang, T, McKenna, S, Nabi, G & McGloin, D 1970, 'Microfluidics-based, time-resolved mechanical phenotyping of cells using high-speed imaging', SPIE Proceedings, European Conferences on Biomedical Optics, SPIE, Munich, GERMANY, pp. 1041305-1041305.
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Belotti, Y, Huang, T, McKenna, S, Nabi, G & McGloin, D 1970, 'High-throughput, imaging based mechanical phenotyping of prostate cancer cells', 2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2017 Conference on Lasers and Electro-Optics Europe (CLEO/Europe) & European Quantum Electronics Conference (EQEC), IEEE, Munich, GERMANY, pp. 1-1.
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Belovs, A, Ivanyos, G, Qiao, Y, Santha, M & Yang, S 1970, 'On the polynomial parity argument complexity of the combinatorial nullstellensatz', Leibniz International Proceedings in Informatics, LIPIcs.
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The complexity class PPA consists of NP-search problems which are reducible to the parity principle in undirected graphs. It contains a wide variety of interesting problems from graph theory, combinatorics, algebra and number theory, but only a few of these are known to be complete in the class. Before this work, the known complete problems were all discretizations or combinatorial analogues of topological fixed point theorems. Here we prove the PPA-completeness of two problems of radically different style. They are PPA-Circuit CNSS and PPA-Circuit Chevalley, related respectively to the Combinatorial Nullstellensatz and to the Chevalley-Warning Theorem over the two elements field F2. The input of these problems contain PPA-circuits which are arithmetic circuits with special symmetric properties that assure that the polynomials computed by them have always an even number of zeros. In the proof of the result we relate the multilinear degree of the polynomials to the parity of the maximal parse subcircuits that compute monomials with maximal multilinear degree, and we show that the maximal parse subcircuits of a PPA-circuit can be paired in polynomial time.
Berry, DM, Cleland-Huang, J, Ferrari, A, Maalej, W, Mylopoulos, J & Zowghi, D 1970, 'Panel: Context-Dependent Evaluation of Tools for NL RE Tasks: Recall vs. Precision, and Beyond', 2017 IEEE 25th International Requirements Engineering Conference (RE), 2017 IEEE 25th International Requirements Engineering Conference (RE), IEEE, Lisbon, Portugal, pp. 570-573.
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© 2017 IEEE. Context and Motivation Natural language processing has been used since the 1980s to construct tools for performing natural language (NL) requirements engineering (RE) tasks. The RE field has often adopted information retrieval (IR) algorithms for use in implementing these NL RE tools. Problem Traditionally, the methods for evaluating an NL RE tool have been inherited from the IR field without adapting them to the requirements of the RE context in which the NL RE tool is used. Principal Ideas This panel discusses the problem and considers the evaluation of tools for a number of NL RE tasks in a number of contexts. Contribution The discussion is aimed at helping the RE field begin to consistently evaluate each of its tools according to the requirements of the tool’s task.
Binh, HTT, Trung, VK, Son, NH, Dutkiewicz, E & Nguyen, DN 1970, 'A Local Search Algorithm for Saving Energy Cost in Duty-Cycle Wireless Sensor Network', INTELLIGENT AND EVOLUTIONARY SYSTEMS, IES 2016, Asia Pacific Symposium, Intelligent and Evolutionary Systems, Springer International Publishing, Univ New S Wales, Canberra Campus, Australian Def Force Acad, Canberra, AUSTRALIA, pp. 45-59.
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Wireless Sensor Networks (WSNs) have been recently used for various applications. Due to the distributed and (often) unattended nature of the nodes after deployment, the lack of energy and the interruptive process in each sensor are the two major problems of WSN systems. Hence, designing a protocol which not only improves system performance but also lowers sensors’ energy consumption so as to maximize the network lifetime is very much desirable. The network lifetime maximization problem was known to be NP-Hard. This paper addresses the Minimum Energy-Multicasting (MEM) problem in Duty-Cycle Wireless Sensor Networks (DC-WSNs) in which sensors cyclically switch between on/off (wake/sleep) modes. To that end, we propose a local search algorithm and compare its performance with the best algorithm so far called GS-MEM over the four datasets designated for the MEM problem. The experimental results show that our proposed algorithm significantly outperforms GS-MEM in terms of energy cost
Binsawad, M, Sohaib, O & Hawryszkiewycz, IT 1970, 'Knowledge-Sharing in Technology Business Incubator.', ISD, International Conference on Information Systems Development, Association for Information Systems, Cyprus, pp. 1-12.
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Given the economic growth challenges facing countries all around the world, the importance of the initiative of technology business incubators in developing the economic growth of countries has been recognized. Technology business incubators are included in many of the processes that support economic growth, such as job creation and developing innovative technologies. This research paper examined how the knowledge sharing aspects impact technology business incubator performance in Saudi Arabia. The findings provide key factors affecting knowledge-sharing process towards technology incubator performance.
Bluff, A & Johnston, A 1970, 'Storytelling with Interactive Physical Theatre', Proceedings of the 4th International Conference on Movement Computing, MOCO '17: 4th International Conference on Movement Computing, ACM, London, United Kingdom, pp. 1-8.
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© 2017 ACM. This paper examines the way movement based interactive visuals were used as a storytelling device in the physical theatre production of Creature: Dot and the Kangaroo. A number of performers and artists involved in the production were interviewed and their perceptions of the interactive technology have been contrasted against a similar study into abstract dance. The animated backgrounds and interactive animal graphics projected onto the stage were found to reduce the density of script by describing the location of action and spirit of the character, reducing the necessity for this to be spoken. Peak moments of the show were identified by those interviewed and a scene analysis revealed that the most successful scenes featured a more integrated storytelling where the interaction between performers and the digital projections portrayed a key narrative message.
Bonthu, RK, Pham, H, Aguilera, RP & Ha, QP 1970, 'Minimization of building energy cost by optimally managing PV and battery energy storage systems', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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The combination of residential photovoltaic (PV) panels and battery energy storage system (BESS) is a promising solution in a building's microgrid. This paper presents an optimal energy management system (EMS) to minimize the electricity bill of residential buildings. The objective is to achieve peak shaving and electrical energy cost minimization for the owner, making use of a dynamic energy pricing model. Due to variability of PV generation and limitations of BESS, the optimization method should account for the utilisation of PV power generation and the conversion losses of power electronics converters. To deal with non-linearities involved, a particle swarm optimization (PSO) algorithm has been developed for minimization of the cost function. Simulation results show that the PSO-based EMS can achieve, as compared to standard schedule for a 24 hour period, a significant saving of daily electricity cost, which prompts for a suitable on-line control strategy
Booth, E 1970, 'Reconsidering the Classics', Stranger in a Strange Land Conference: A Festschrift for Prof. Andrew Jakubowicz, University of Technology Sydney.
Booth, E & Narayan, B 1970, 'Towards diversity in young adult fiction in Australia: a discourse analysis of YA authors’ experiences', Research Applications, Information and Library Studies, University of South Australia, Adelaide, SA.
Boudali, AM, Kong, FH, Martinez, J, Tang, JZ & Manchester, IR 1970, 'Design and modeling of an open platform for dynamic walking research', 2017 IEEE International Conference on Mechatronics (ICM), 2017 IEEE International Conference on Mechatronics (ICM), IEEE, pp. 85-92.
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In this paper we outline the design and parameter identification of a low-cost "compass-gait" bipedal robot for dynamic walking experiments. A compass gait walker exhibits a desirable balance of complexity in the dynamics and mechanical simplicity, making it a good candidate for a physical realization. In the hope of making the hardware of such walking robot more accessible to other researchers, we describe the the mechanical design, the software interface, as well as the dynamic modelling and parameter identification of a planar compass gait walker. Controlled walking experiments have also been performed to validate our model.
Braun, R & Chaczko, Z 1970, 'Using Matlab modeling in cody to teach Teletraffic engineering', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, pp. 1-5.
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© 2017 IEEE. Engineering students are having to model increasingly complex constructed environments at the same time that their traditional mathematical skills are decreasing[?]. New approaches to modeling are needed. We started with the premise that students find mathematical modeling of Teletraffic problems challenging, and that this can be replaced through modeling in a 'computational' environment such as Matlab. In this paper, we show how the Teletraffic Engineering part of a Network Management subject can be made more interesting and accessible. We plot the student satisfaction scores to show the effectiveness of the approach.
Braytee, A, Liu, W & Kennedy, PJ 1970, 'Supervised context-aware non-negative matrix factorization to handle high-dimensional high-correlated imbalanced biomedical data', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 4512-4519.
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© 2017 IEEE. Traditional feature selection techniques are used to identify a subset of the most useful features, and consider the rest as unimportant, redundant or noisy. In the presence of highly correlated features, many variable selection methods consider correlated features as redundant and need to be removed. In this paper, a novel supervised feature selection algorithm SCANMF is proposed by jointly integrating correlation analysis and structural analysis of the balanced supervised non-negative matrix factorization (NMF). Furthermore, ℓ2,1-norm minimization constraint is incorporated into the objective function to guarantee sparsity in the feature matrix rows and reduce noisy features. Our algorithm exploits the discriminative information, feature combinations, and the original features in the context of a supervised NMF method which can be beneficial for both classification and interpretation. An efficient iterative algorithm is designed to solve the constrained optimization problem with guaranteed convergence. Finally, a series of extensive experiments are conducted on 8 complex datasets. Promising results using multiple classifiers demonstrate the effectiveness and efficiency of our algorithm over state-of-the-art methods.
Braytee, A, Liu, W, Catchpoole, DR & Kennedy, PJ 1970, 'Multi-Label Feature Selection using Correlation Information', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, Singapore, Singapore, pp. 1649-1656.
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© 2017 ACM. High-dimensional multi-labeled data contain instances, where each instance is associated with a set of class labels and has a large number of noisy and irrelevant features. Feature selection has been shown to have great benefits in improving the classification performance in machine learning. In multi-label learning, to select the discriminative features among multiple labels, several challenges should be considered: interdependent labels, different instances may share different label correlations, correlated features, and missing and .awed labels. This work is part of a project at .e Children's Hospital at Westmead (TB-CHW), Australia to explore the genomics of childhood leukaemia. In this paper, we propose a CMFS (Correlated-and Multi-label Feature Selection method), based on non-negative matrix factorization (NMF) for simultaneously performing feature selection and addressing the aforementioned challenges. Significantly, a major advantage of our research is to exploit the correlation information contained in features, labels and instances to select the relevant features among multiple labels. Furthermore, l2;1-norm regularization is incorporated in the objective function to undertake feature selection by imposing sparsity on the feature matrix rows. We employ CMFS to decompose the data and multi-label matrices into a low-dimensional space. To solve the objective function, an efficient iterative optimization algorithm is proposed with guaranteed convergence. Finally, extensive experiments are conducted on high-dimensional multi-labeled datasets. The experimental results demonstrate that our method significantly outperforms state-of-the-art multi-label feature selection methods.
Brennan, MJ, Karimi, M, Almeida, FCL, de Lima, FK, Ayala, PC, Obata, D, Paschoalini, AT & Kessissoglou, N 1970, 'On the role of vibro-acoustics in leak detection for plastic water distribution pipes', Procedia Engineering, Elsevier BV, pp. 1350-1355.
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Brereton, M, Chai, MZ, Soro, A, Ambe, AH, Johnson, D, Wyeth, P, Roe, P & Rogers, Y 1970, 'Make and connect', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, pp. 612-616.
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Broekhuijsen, M, van den Hoven, E & Markopoulos, P 1970, 'Design Directions for Media-Supported Collocated Remembering Practices', Proceedings of the Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, TEI '17: Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, ACM, Yokohama, Japan, pp. 21-30.
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Since the widespread adoption of digital photography, people create many digital photos, often with the intention to use them for shared remembering. Practices around digital photography have changed along with advances in media sharing technologies such as smartphones, social media, and mobile connectivity. Although much research was done at the start of digital photography, commercially available tools for media-supported shared remembering still have many limitations. The objective of our research is to explore spatial and material design directions to better support the use of personal photos for collocated shared remembering. In this paper, we present seven design requirements that resulted from a redesign workshop with fifteen participants, and four design concepts (two spatial, two material) that we developed based on those requirements. By reflecting on the requirements and designs we conclude with challenges for interaction designers to support collocated remembering practices.
Brookes, W 1970, 'Transdisciplinary learning in technology degrees', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-6.
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This paper outlines a new kind of degree that has technology at its core, but is transdisciplinary in nature. Rather than students learning knowledge in discrete disciplinary blocks, they are exposed to ideas and practices from a wide variety of disciplines, and use these to create new ways of working that are underpinned by capabilities in computational thinking, complex systems, data and reasoning.
Bubb, KJ, Tang, O, Hansen, T, Gentile, C & Figtree, GA 1970, 'FXYD1 Protects Against Reactive Oxygen Species-Dependent Cardiac Remodelling and Fibrosis', CIRCULATION, Scientific Sessions of the American-Heart-Association / Resuscitation Science Symposium, LIPPINCOTT WILLIAMS & WILKINS, Anaheim, CA.
Buchan, J, Bano, M, Zowghi, D, MacDonell, SG & Shinde, A 1970, 'Alignment of Stakeholder Expectations about User Involvement in Agile Software Development.', EASE, International Conference on Evaluation and Assessment in Software Engineering, ACM, Karlskrona, Sweden, pp. 334-343.
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© 2017 Association for Computing Machinery. Context: User involvement is generally considered to contributing to user satisfaction and project success and is central to Agile software development. In theory, the expectations about user involvement, such as the PO's, are quite demanding in this Agile way of working. But what are the expectations seen in practice, and are the expectations of user involvement aligned among the development team and users? Any misalignment could contribute to conflict and miscommunication among stakeholders that may result in ineffective user involvement. Objective: Our aim is to compare and contrast the expectations of two stakeholder groups (software development team, and software users) about user involvement in order to understand the expectations and assess their alignment. Method: We have conducted an exploratory case study of expectations about user involvement in an Agile software development. Qualitative data was collected through interviews to design a novel method for the assessing the alignment of expectations about user involvement by applying Repertory Grids (RG). Results: By aggregating the results from the interviews and RGs, varying degrees of expectation alignments were observed between the development team and user representatives. Conclusion: Alignment of expectations can be assessed in practice using the proposed RG instrument and can reveal misalignment between user roles and activities they participate in Agile software development projects. Although we used RG instrument retrospectively in this study, we posit that it could also be applied from the start of a project, or proactively as a diagnostic tool throughout a project to assess and ensure that expectations are aligned.
Burdon, S, Mooney, G & Kang, K 1970, 'A reputation for enterprise innovation: Do you know what your peers are thinking?', Proceedings of the 30th International Business Information Management Association Conference, IBIMA 2017 - Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth, International Business Information Management Association Conference, International Business Information Management Association (IBIMA Publishing), Madrid, Spain, pp. 5475-5488.
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This paper addresses organisational success and prevailing values of innovative firms as perceived by peer/competitor enterprises. Partnering with the Information Industry Association of Australia (AIIA), surveys were undertaken and 244 responses from 102 member organisations statistically analysed. In-depth follow-up with selected enterprises then more closely examined factors deemed important to corporates comparing achievements. Outcomes indicate that high-growth firms often prioritise realisation of innovation over simply making money - yet high cash flows are still generated.Findings also show that having a strong reputation for innovation is a competitive advantage in its own right, attracting invitation to cross-enterprise ecosystems and beneficial partner alliances. Interestingly, topics around outsider/peer perceptions of other enterprises accrue comparatively little precedence within innovation discussions. What our study shows is that balancing an internal reality of innovation with the external perception for innovation can lead to significant improvements in commercial performance and rising market leadership.
Burdon, STEVE 1970, 'A Tool Box for Success from Using Disruptive Technology and Creating an Innovation Culture'.
Burdon, STEVE 1970, 'Decoding Disruptive Technology and Fostering an Innovation Culture', Disruptive Technology and Creating an Innovation Culture, Disruptive Technology and Creating an Innovation Culture, Grand Hyatt, Melbourne.
Burdon, SW 1970, 'The Essential Role Played by Boards in Harnessing Disruptive Technology for Organisational Success', https://www.governanceinstitute.com.au/education-training/calendar-of-events/annual-conferences/corporate-governance-forum-2017/, Corporate Governance Forum 2017, Governance Institute, Four Season Sydney.
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A recent survey of 185 CEOs and non-executive directors came up with a conclusion that there were five key technology issues that really count in terms of success and failure of organisations. One of the most important was the level of board support and engagement for digital strategy.
Butler, A, Xu, G & He, X 1970, 'What comes first the Co-authorship Network or the Citation?', Proceedings of the 4th Multidisciplinary International Social Networks Conference, MISNC '17: 4th Multidisciplinary International Social Networks Conference, ACM, Bangkok, Thailand, pp. 1-5.
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For many decades citation counting has been used as the way to quantify the nebulous notion of research "quality". Indeed, in conversation the terms "research quality", "impact" or "excellence in research" are simply a reference to a scientific document’s citation count. Moreover, the commonly used journal "impact" factors are simply manipulated forms of citation counting. In recent times, the word "impact" has morphed into the new ’mot du jour’. This paper investigates and discusses the association between co-Authorship networks and citations of institutions within an arbitrary, but defined, subject area. The data examined is readily available and the analytical techniques employed are deliberately simple. The simplicity of this analysis is driven by the desire to show that citation counts are not explicitly related to the quality of research but that citations are a result of multifaceted author networks that are inherent in scientific endeavor. The paper presents an argument that the improved ability to conduct effective network analysis and related research shows that the notion of high citations being the same as "research quality" has run its course. Citation performance is more likely to be a result of co-Authorship network dynamics rather than any perceived notion of "quality". Moreover, it is time the folly of citation counting is put to rest and that if one wants know what "impact" one is having that you need look no further than your co-Authorship network and the reach it has across whatever subject area you are interested in. The discussion and results herein highlight that rather than counting citations, the "impact" of research is driven by connections through networks of people. © 2017 ACM.
Cai, Y, Zhang, Y, Ding, C, Qian, Z & Liu, J 1970, 'Design of multilayer SIW cavity-backed slot antenna array', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, France, pp. 1189-1193.
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© 2017 Euraap. In this paper, a multilayer substrate integrated waveguide (SIW) cavity-backed slot antenna array with wideband performance is proposed. In order to broaden the operating bandwidth of SIW slot antenna, multilayer cavities with gradually decreased permittivity and expanded aperture sizes are loaded above the slot, which realizes a smooth transition between SIW slot and free space. A wideband feeding network employing slot coupling is designed to excite the array elements. Results indicate the proposed array operates with 28.4% bandwidth ranging from 22.4 to 29.8 GHz. Besides, stable broadside radiation patterns are obtained across the operating band.
Calderon-Vizcarra, G, Nimbalkar, S, Casagrande, M & Velloso, R 1970, 'Discrete element modelling of compression test on coarse granular aggregates used in railroad', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 821-829.
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This paper demonstrates results of numerical simulations based on discrete element approach. The triaxial compression behaviour of coarse granular particles that represent railroad ballast is simulated. During laboratory testing, the vertical deformation of ballast layer prepared with two different gradations was assessed under vertical loading. One specimen was simulated using particle size distribution (PSD) recommended by Indraratna and co-workers in the past as an improvement to Australian Standard and the other was prepared with PSD in accordance with Brazilian standard. The discrete element method offers a new resource for accurate investigation of response of railway ballast as evident in controlled laboratory environment as well as field conditions. In this paper, the discrete element method of analysis is used to simulate the geotechnical behaviour of ballast observed during compression testing. The numerical analysis captured the evolution of inter-particle forces as a granular material is subjected to compression test. The article showed a procedure to model ballast testing using DEM, where useful features of the micromechanical analyses such as coordination number, velocity vectors of particles are exhibited.
Candra, H, Yuwono, M, Chai, R, Nguyen, HT & Su, S 1970, 'EEG emotion recognition using reduced channel wavelet entropy and average wavelet coefficient features with normal Mutual Information method', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 463-466.
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© 2017 IEEE. Recognizing emotion from EEG signals is a complicated task that requires complex features and a substantial number of EEG channels. Simple algorithms to analyse the feature and reduce the EEG channel number will give an indispensable advantages. Therefore, this study explores a combination of wavelet entropy and average wavelet coefficient (WEAVE) as a potential EEG-emotion feature to classify valence and arousal emotions with the advantage of the ability to identify the occurrence of a pattern while at the same time identify the shape of a pattern in EEG emotion signal. The complexity of the feature was reduced using the Normalized Mutual Information (NMI) method to obtain a reduced number of channels. Classification with the WEAVE feature achieved 76.8% accuracy for valence and 74.3% for arousal emotion, respectively. The analysis with NMI shows that the WEAVE feature has linear characteristics and offers possibilities to reduce the EEG channels to a certain number. Further analysis also reveals that detection of valence emotion with reduced EEG channels has a different combination of EEG channels compared to arousal emotion.
Cao, L 1970, 'Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management', Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, pp. 15-16.
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Cao, Y, Wen, S, Zeng, Z & Huang, T 1970, 'Nonlinear model reference control via aperiodic sampling', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, PEOPLES R CHINA, pp. 7457-7462.
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Cao, Z, Prasad, M & Lin, C-T 1970, 'Estimation of SSVEP-based EEG complexity using inherent fuzzy entropy', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-5.
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© 2017 IEEE. This study considers the dynamic changes of complexity feature by fuzzy entropy measurement and repetitive steady-state visual evoked potential (SSVEP) stimulus. Since brain complexity reflects the ability of the brain to adapt to changing situations, we suppose such adaptation is closely related to the habituation, a form of learning in which an organism decreases or increases to respond to a stimulus after repeated presentations. By a wearable electroencephalograph (EEG) with Fpz and Oz electrodes, EEG signals were collected from 20 healthy participants in one resting and five-times 15 Hz SSVEP sessions. Moreover, EEG complexity feature was extracted by multi-scale Inherent Fuzzy Entropy (IFE) algorithm, and relative complexity (RC) was defined the difference between resting and SSVEP. Our results showed the enhanced frontal and occipital RC was accompanied with increased stimulus times. Compared with the 1st SSVEP session, the RC was significantly higher than the 5th SSVEP session at frontal and occipital areas (p < 0.05). It suggested that brain has adapted to changes in stimulus influence, and possibly connected with the habituation. In conclusion, effective evaluation of IFE has a potential EEG signature of complexity in the SSEVP-based experiment.
Carmichael, MG, Aldini, S & Liu, D 1970, 'Human user impressions of damping methods for singularity handling in human-robot collaboration', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 107-113.
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Kinematic singularity is a fundamental and well understood problem of robot manipulators, with many methods having been developed to ensure safe and robust operation in proximity to singularity. However little attention has been given to the scenario where the robot and human are working in physical contact to collaboratively perform a task. In such a scenario the feelings and impressions of the human operator should be considered when developing solutions for handling singularity. This work presents an experimental study comparing three modes of handling kinematic singularities with respect to the impressions of the human operator. Two of the modes are based on traditional Damped-Least-Squares. The third method uses an asymmetric damping behavior proposed as being well suited for applications involving physical human-robot interaction. The three modes are tested and compared by subjects performing a mock industrial task, and feedback from the subjects analyzed to identify the preferred mode. Results indicate that the choice of method used affects the user's impressions of the interaction, and the asymmetrical damping behavior can produce a preferred interaction experience with human operators during tasks.
Carter, M, Petter, S, Chudoba, K, Windeler, J, Kenny, G, Marjanovic, O & Coleman, E 1970, 'Social inclusion in practice: Supporting diversity, inclusion, and engagement in the AIS', AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation.
Castel, A, Foster, S & Gilbert, RI 1970, 'SERVICEABILITY OF LOW CREEP FLY ASH GEOPOLYMER CONCRETE BEAMS', Proceedings of International Structural Engineering and Construction, ISEC Press.
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In reinforced concrete construction, deflection control is an important performance criterion for their serviceability. The aim of the research described in this paper is to assess the deformation of cracked reinforced geopolymer concrete beams under long term service loading. The geopolymer binder is Portland cement free, using 85% of low calcium fly ash, 15% of GGBFS (Ground Granulated Blast Furnace Slag) and a sodium silicate/sodium hydroxide based activator. Firstly, geopolymer concrete drying shrinkage and creep were measured. Different curing conditions at elevated temperature were used. All experimental results are compared to predictions made using the Eurocode 2. Secondly, geopolymer concrete beams were subjected to short time bending tests leading to concrete cracking (pre-cracking tests). Beams were then stored under sustained loading for a period of four months. Both deflection and cracks were monitored versus time. Results show that, providing an appropriate heat curing regime, geopolymer concrete creep is much lower than that observed for OPC concrete and predicted by the Eurocode 2. As a result, the time-dependent deflection of geopolymer concrete beams measured after 4 months under sustained loading was always significantly lower than that of traditional OPC concrete beams. All results are showing that the crack widths of geopolymer concrete beams are significantly smaller than those expected for OPC concrete beams according to fib model code 2010 for both short and long terms tests. It is concluded that low calcium fly ash-based geopolymer concrete is a promising option for precast applications.
Castel, A, Foster, S & Gilbert, RI 1970, 'SERVICEABILITY OF LOW CREEP FLY ASH GEOPOLYMER CONCRETE BEAMS', Proceedings of International Structural Engineering and Construction.
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In reinforced concrete construction, deflection control is an important performance criterion for their serviceability. The aim of the research described in this paper is to assess the deformation of cracked reinforced geopolymer concrete beams under long term service loading. The geopolymer binder is Portland cement free, using 85% of low calcium fly ash, 15% of GGBFS (Ground Granulated Blast Furnace Slag) and a sodium silicate/sodium hydroxide based activator. Firstly, geopolymer concrete drying shrinkage and creep were measured. Different curing conditions at elevated temperature were used. All experimental results are compared to predictions made using the Eurocode 2. Secondly, geopolymer concrete beams were subjected to short time bending tests leading to concrete cracking (pre-cracking tests). Beams were then stored under sustained loading for a period of four months. Both deflection and cracks were monitored versus time. Results show that, providing an appropriate heat curing regime, geopolymer concrete creep is much lower than that observed for OPC concrete and predicted by the Eurocode 2. As a result, the time-dependent deflection of geopolymer concrete beams measured after 4 months under sustained loading was always significantly lower than that of traditional OPC concrete beams. All results are showing that the crack widths of geopolymer concrete beams are significantly smaller than those expected for OPC concrete beams according to fib model code 2010 for both short and long terms tests. It is concluded that low calcium fly ash-based geopolymer concrete is a promising option for precast applications.
Castro-Wunsch, K, Ahadi, A & Petersen, A 1970, 'Evaluating Neural Networks as a Method for Identifying Students in Need of Assistance', Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE '17: The 48th ACM Technical Symposium on Computer Science Education, ACM, Washington, USA, pp. 111-116.
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© 2017 ACM. Course instructors need to be able to identify students in need of assistance as early in the course as possible. Recent work has suggested that machine learning approaches applied to snapshots of small programming exercises may be an effective solution to this problem. However, these results have been obtained using data from a single institution, and prior work using features extracted from student code has been highly sensitive to differences in context. This work provides two contributions: first, a partial reproduction of previously published results, but in a different context, and second, an exploration of the efficacy of neural networks in solving this problem. Our findings confirm the importance of two features (the number of steps required to solve a problem and the correctness of key problems), indicate that machine learning techniques are relatively stable across contexts (both across terms in a single course and across courses), and suggest that neural network based approaches are as effective as the best Bayesian and decision tree methods. Furthermore, neural networks can be tuned to be reliably pessimistic, so they may serve a complementary role in solving the problem of identifying students who need assistance.
Cetindamar, D & Beyhan, B 1970, 'Social Innovation Assessment at the University Level', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Portland, OR, USA, pp. 1-4.
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© 2017 PICMET. Based on a literature review, our paper points out the need for an assessment model that could account social aspect of technological innovations generated in universities. Rather than quantitative metrics, using cases seems an appropriate approach to evaluate social innovations at universities to capture the richness of social impact. We further suggest the consideration of gathering information on four dimensions of social innovation to complement case approach: (1) the categories of beneficiaries who will benefit from social innovations, (2) the geographic location of impact, (3) the type of social innovations in terms of their output, and (4) the social benefit that innovation will bring. This paper ends with a few suggestions for further studies.
Chaczko, Z & Braun, R 1970, 'Learning data engineering: Creating IoT apps using the node-RED and the RPI technologies', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-8.
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© 2017 IEEE. This paper demonstrates the suitability and the practicality of using the advanced open source tools such as the Raspberry Pi and the Node-RED for teaching and learning in the Internet of Things (IOT) subject within a newly created major of Data Engineering in the Faculty of Engineering and IT at University of Technology, Sydney. Understanding and practicing of the Internet of Things largely depend on the high availability of tools, their low cost, and ease of use that can accelerate learning processes. This paper demonstrates relatively uncomplicated practical lab exercises involving the Raspberry Pi hardware, firmware and the Node-RED programming environment that students can execute to stimulate their learning, understanding of the Internet of Things technology and acquire fundamental data engineering skills.
Chaczko, Z, Jiang, F & Ahmed, B 1970, 'Road Vehicle Alert System Using IOT', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 488-493.
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© 2017 IEEE. The consequence of road accidents that involves a motorcycle is far more fatal for the rider than the other drivers. Yet, there has not been an effective vehicle alert system that can eliminate these avoidable motorcycle accidents caused by other drivers where they fail to notice the motorcycles. One of the major flaws with the existing vehicle alert systems is that it should not treat motorcycles as same as other vehicles as they take much longer time to brake than a cars do. Therefore, this project aimed to find an effective method to identify motorcycles and alert the other drivers when motorcyclists are around them in 20-meter radius. After extensive literature review, the best method to solve the problem is to use road side infrastructure based Internet of Things (IOT) that divides the network into a set of clusters. In this method to identify a vehicle, it is identifying the driver and the rider from their smartphone application that beacons custom, unique Media Access Control (MAC) addresses via Bluetooth or Wi-Fi to the IOT probes. The probe differentiates the users, registers them when they arrive into the network, alerts the driver about motorcycles around them and removes them from the database when they move to other cluster. The whole scenario is simulated using the OMNET++ simulator and INET framework to demonstrate how the methodology works. If the concept is implemented in real-life, many valuable lives of motorists will be much safer on the road.
Chai, R, Naik, GR, Ling, SH, Tran, Y, Craig, A & Nguyen, HT 1970, 'Channels selection using independent component analysis and scalp map projection for EEG-based driver fatigue classification', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 1808-1811.
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This paper presents a classification of driver
fatigue with electroencephalography (EEG) channels selection
analysis. The system employs independent component analysis
(ICA) with scalp map back projection to select the dominant of
EEG channels. After channel selection, the features of the
selected EEG channels were extracted based on power spectral
density (PSD), and then classified using a Bayesian neural
network. The results of the ICA decomposition with the backprojected
scalp map and a threshold showed that the EEG
channels can be reduced from 32 channels into 16 dominants
channels involved in fatigue assessment as chosen channels,
which included AF3, F3, FC1, FC5, T7, CP5, P3, O1, P4, P8,
CP6, T8, FC2, F8, AF4, FP2. The result of fatigue vs. alert
classification of the selected 16 channels yielded a sensitivity of
76.8%, specificity of 74.3% and an accuracy of 75.5%. Also,
the classification results of the selected 16 channels are
comparable to those using the original 32 channels. So, the
selected 16 channels is preferable for ergonomics improvement
of EEG-based fatigue classification system.
Chang, L, Zhang, C, Lin, X & Qin, L 1970, 'Scalable Top-K Structural Diversity Search.', ICDE, International Conference on Data Engineering, IEEE Computer Society, San Diego, CA, USA, pp. 95-98.
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© 2017 IEEE. This paper studies the problem of top-k structural diversity search, which is to compute k users with the highest structural diversities that is measured by the number of connected components in the neighborhood of a user. As the existing algorithms are not scalable for processing large graphs due to their limits, in this paper we propose a scalable algorithm Div-TriE to improve the efficiency. Div-TriE has two optimal features compared with the existing algorithms. Firstly, we show that as a key building block, we only need to enumerate each triangle at most once in Div-TriE, in contrast to the up-To three times in the existing techniques. Secondly, we develop efficient techniques so that the computation against each enumerated triangle is (amortized) constant, in contrast to the non-constant costs in the corresponding costs of the existing techniques. Extensive experimental results on real graphs show that Div-TriE outperforms the existing techniques by one order of magnitude.
Chang, X, Yu, Y-L & Yang, Y 1970, 'Robust Top- k Multiclass SVM for Visual Category Recognition', Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, Halifax, Nova Scotia, Canada, pp. 75-83.
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© 2017 Association for Computing Machinery. Classification problems with a large number of classes inevitably involve overlapping or similar classes. In such cases it seems reasonable to allow the learning algorithm to make mistakes on similar classes, as long as the true class is still among the top-k (say) predictions. Likewise, in applications such as search engine or ad display, we are allowed to present k predictions at a time and the customer would be satisfied as long as her interested prediction is included. Inspired by the recent work of [15], we propose a very generic, robust multiclass SVM formulation that directly aims at minimizing a weighted and truncated combination of the ordered prediction scores. Our method includes many previous works as special cases. Computationally, using the Jordan decomposition Lemma we show how to rewrite our objective as the difference of two convex functions, based on which we develop an eficient algorithm that allows incorporating many popular regularizers (such as the l2 and l1 norms). We conduct extensive experiments on four real large-scale visual category recognition datasets, and obtain very promising performances.
Chang, Y-C, Wang, Y-K, Wu, D & Lin, C-T 1970, 'Generating a fuzzy rule-based brain-state-drift detector by riemann-metric-based clustering', 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, Banff, AB, Canada, pp. 1220-1225.
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© 2017 IEEE. Brain-state drifts could significantly impact on the performance of machine-learning algorithms in brain computer interface (BCI). However, less is understood with regard to how brain transition states influence a model and how it can be represented for a system. Herein we are interested in the hidden information of brain state-drift occurring in both simulated and real-world human-system interaction. This research introduced the Riemann metric to categorize EEG data, and visualized the clustering result so that the distribution of the data can be observable. Moreover, to defeat subjective uncertainty of electroencephalography (EEG) signals, fuzzy theory was employed. In this study, we built a fuzzy rule-based brain-statedrift detector to observe the brain state and imported data from different subjects to testify the performance. The result of the detection is acceptable and shown in this paper. In the future, we expect that brain-state drifting can be connected with human behaviors via the proposed fuzzy rule-based classification. We also will develop a new structure for a fuzzy rule-based brain-statedrift detector to improve the detection accuracy.
Chao, MY, Ali, A, Ghosh, S & Lee, JE-Y 1970, 'An Aluminum Nitride on Silicon resonant MEMS accelerometer operating in ambient pressure', 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), IEEE, pp. 607-610.
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Chauhan, J, Hu, Y, Seneviratne, S, Misra, A, Seneviratne, A & Lee, Y 1970, 'BreathPrint', Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys'17: The 15th Annual International Conference on Mobile Systems, Applications, and Services, ACM, pp. 278-291.
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Chehrazad, S, Aghdasi, HS, Shariati, N & Abolhasan, M 1970, 'Addressing coverage problem in wireless sensor networks based on evolutionary algorithms', 2017 23rd Asia-Pacific Conference on Communications (APCC), 2017 23rd Asia-Pacific Conference on Communications (APCC), IEEE, Perth, WA, Australia, pp. 1-5.
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Wireless Sensor Networks (WSNs) are the key part of Internet of Things, as they provide the physical interface between on-field information and backbone analytic engines. An important role of WSNs-when collecting vital information-is to provide a consistent and reliable coverage. To Achieve this, WSNs must implement a highly reliable and efficient coverage recovery algorithm. In this paper, we take a fresh new approach to coverage recovery based on evolutionary algorithms. We propose EMACB-SA, which introduces a new evolutionary algorithm that selects coverage sets using a fitness function that balances energy efficiency and redundancy. The proposed algorithm improves network's coverage and lifetime in areas with heterogeneous event rate in comparison to previous works and hence, it is suitable for using in disaster management.
Chen, S, Chen, S, Lin, L, Yuan, X, Liang, J & Zhang, X 1970, 'E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media', 2017 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), IEEE Conference on Visual Analytics Science and Technology (VAST), IEEE, AZ, Phoenix, pp. 36-47.
Chen, S, Chen, S, Lin, L, Yuan, X, Liang, J & Zhang, X 1970, 'E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media', 2017 IEEE Conference on Visual Analytics Science and Technology (VAST), 2017 IEEE Conference on Visual Analytics Science and Technology (VAST), IEEE, Phoenix, Arizona, USA, pp. 36-47.
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Significant events are often discussed and spread through social
media, involving many people. Reposting activities and opinions
expressed in social media offer good opportunities to understand
the evolution of events. However, the dynamics of reposting activities
and the diversity of user comments pose challenges to understand
event-related social media data. We propose E-Map, a visual
analytics approach that uses map-like visualization tools to help
multi-faceted analysis of social media data on a significant event
and in-depth understanding of the development of the event. E-Map
transforms extracted keywords, messages, and reposting behaviors
into map features such as cities, towns, and rivers to build a structured
and semantic space for users to explore. It also visualizes
complex posting and reposting behaviors as simple trajectories and
connections that can be easily followed. By supporting multi-level
spatial temporal exploration, E-Map helps to reveal the patterns
of event development and key players in an event, disclosing the
ways they shape and affect the development of the event. Two
cases analysing real-world events confirm the capacities of E-Map
in facilitating the analysis of event evolution with social media data
Chen, S-L, Qin, P-Y & Guo, YJ 1970, 'Multi-linear polarization reconfigurable center-fed circular patch antenna with shorting posts', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, USA, pp. 2209-2210.
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© 2017 IEEE. In this paper, a novel multi-linear polarization reconfigurable antenna with shorting posts, which can achieve four linear polarizations (0°, 45°, 90°, 135°), has been proposed. By switching the diodes between two groups of shorting posts, four linear polarizations can be realized. The dimensions of the proposed antenna are about 0.56λ× 0.56λ×0.07λ at 2.4 GHz. The measured results agree well with the simulated ones.
Chen, S-L, Qin, P-Y, Guo, YJ, Liu, Y & You, P 1970, 'Array pattern synthesis using numerical pattern synthesis algorithm including mutual coupling', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, USA, pp. 2295-2296.
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© 2017 IEEE. In this paper, numerical pattern synthesis (NPS) algorithm integrated with seeded region growing (SRG) method is proposed to synthesize the array in the presence of mutual coupling. In order to obtain the mutual coupling between the array elements, active pattern technique is used to find active element patterns. A 4 × 8 microstrip antenna array is employed to validate the effectiveness of the proposed algorithm including mutual coupling.
Chen, S-L, Qin, P-Y, Guo, YJ, Liu, Y & You, P 1970, 'Array Pattern Synthesis Using Numerical Pattern Synthesis Algorithm Including Mutual Coupling', 2017 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION & USNC/URSI NATIONAL RADIO SCIENCE MEETING, International Symposium of IEEE-Antennas-and-Propagation-Society / USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, pp. 2291-2292.
Chen, W-H, Liu, G, Su, SW, Jiang, Q & Nguyen, HT 1970, 'A CHF detection method based on deep learning with RR intervals.', EMBC, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Seogwipo, South Korea, pp. 3369-3372.
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© 2017 IEEE. There are extensive studies investigating congestive heart failure (CHF) detection based on heart rate variability. Although a high level of accuracy has been achieved, its robustness under different conditions is not guaranteed. To improve the robustness, we applied sparse auto-encoder-based deep learning algorithm in CHF detection with RR intervals. A total data size of 30,592 (5-min RR interval) was obtained from 72 healthy persons and 44 CHF patients. The deep learning algorithm first extracts unsupervised features using a sparse auto-encoder from raw RR intervals, then constructs a deep neural network model with various hidden nodes combinations. Results showed that the model achieved 72.41% accuracy. This demonstrated that RR intervals have potential in CHF detection but cannot fully reflect dynamic change in 24-h.
Chen, X, Ni, W, Chen, T, Collings, IB, Wang, X, Liu, RP & Giannakis, GB 1970, 'Distributed Stochastic Optimization of Network Function Virtualization', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. Decoupling network services from underlying hardware, network function virtualization (NFV) is expected to significantly improve agility and reduce network cost. However, network services, sequences of network functions, need to be processed in specific orders at specific types of virtual machines (VMs), which couples decisions of VMs on processing or routing network services. Built on a new stochastic dual gradient method, our approach suppresses the couplings, minimizes the time-average cost of NFV, stabilizes queues at VMs, and reduces the backlogs of unprocessed services through online learning and adaptation. Asymptotically optimal decisions are instantly generated at individual VMs, with a cost-delay tradeoff [(ϵ)/√ϵ]. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 30% and reduce the queue length (or delay) by 83%, as compared to existing non-stochastic approaches.
Chen, X, Wang, X, Ni, W & Collings, IB 1970, 'Two-way energy trading and online planning for fifth-generation communications with renewables', 2017 23rd Asia-Pacific Conference on Communications (APCC), 2017 23rd Asia-Pacific Conference on Communications (APCC), IEEE, Perth, WA, Australia, pp. 1-6.
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© 2017 University of Western Australia. Future fifth-generation (5G) cellular networks, equipped with energy harvesting devices, are uniquely positioned to closely interoperate with smart grid. New interoperable functionalities are discussed in stochastic two-way energy trading and online planning to improve efficiency and productivity. Challenges lie in the unavailability of a-priori knowledge on future wireless channels, energy pricing and harvesting. Lyapunov optimization techniques are utilized to address the challenges and stochastically optimize energy trading and planning. Particularly, it is able to decouple the optimization of energy trading and planning during individual time slots, hence eliminating the need for joint optimization across a large number of slots.
Chen, Y, Huang, S, Fitch, R & Yu, J 1970, 'Efficient active SLAM based on submap joining', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney, Australia, pp. 141-147.
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This paper considers the active SLAM problem where a robot is required to cover a given area while at the same time performing simultaneous localization and mapping (SLAM) for understanding the environment and localizing the robot itself. We propose a model predictive control (MPC) framework, and the minimization of uncertainty in SLAM and coverage problems are solved respectively by the Sequential Quadratic Programming (SQP) method. Then, a decision making process is used to control the switching of two control inputs. In order to reduce the estimation and planning time, we use Linear SLAM, which is a submap joining approach. Simulation results are presented to validate the effectiveness of the proposed active SLAM strategy.
Chen, Y-C, Chen, W-H, Lin, B-J, Chang, J-S & Ong, HC 1970, 'Fuel Property Variation of Biomass Undergoing Torrefaction', Energy Procedia, 8th International Conference on Applied Energy (ICAE), Elsevier BV, Beijing Inst Technol, Beijing, PEOPLES R CHINA, pp. 108-112.
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Chen, Z, Li, J, Chen, Z & You, X 1970, 'Generic Pixel Level Object Tracker Using Bi-Channel Fully Convolutional Network', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 666-676.
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© Springer International Publishing AG 2017. As most of the object tracking algorithms predict bounding boxes to cover the target, pixel-level tracking methods provide a better description of the target. However, it remains challenging for a tracker to precisely identify detailed foreground areas of the target. In this work, we propose a novel bi-channel fully convolutional neural network to tackle the generic pixel-level object tracking problem. By capturing and fusing both low-level and high-level temporal information, our network is able to produce pixel-level foreground mask of the target accurately. In particular, our model neither updates parameters to fit the tracked target nor requires prior knowledge about the category of the target. Experimental results show that the proposed network achieves compelling performance on challenging videos in comparison with competitive tracking algorithms.
Chen, Z, You, X & Li, J 1970, 'Learning to focus for object proposals', 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), IEEE, Shenzhen, China, pp. 439-444.
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© 2017 IEEE. Object proposal generators address the wasteful exhaustive search of the sliding window scheme in visual object detection and have been shown effective. However, the number of candidate windows is still large in order to ensure full coverage of potential objects. This paper presents a complementary technique that aims to work with any proposal generating system, amending the workflow from 'propose-assess' to 'propose-adjust-assess'. The adjustment serves as an auto-focus mechanism for the system and reduces the number of object proposals to be processed. The auto-focus is realized by two learning-based transformation models, one translating and the other deforming the windows towards better alignments of the objects, which are trained for identifying generic objects using image cues. Experiments on reallife image data sets show that the proposed technique can reduce the number of proposals without loss of performance.
Chen, Z, Zhou, J, Wang, X, Swanson, J, Chen, F & Feng, D 1970, 'Neural net-based and safety-oriented visual analytics for time-spatial data', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, pp. 1133-1140.
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Cheng, D, Chang, X, Liu, L, Hauptmann, AG, Gong, Y & Zheng, N 1970, 'Discriminative Dictionary Learning With Ranking Metric Embedded for Person Re-Identification', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, AUSTRALIA, pp. 964-970.
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The goal of person re-identification (Re-Id) is to match pedestrians captured from multiple non-overlapping cameras. In this paper, we propose a novel dictionary learning based method with the ranking metric embedded, for person Re-Id. A new and essential ranking graph Laplacian term is introduced, which minimizes the intra-personal compactness and maximizes the inter-personal dispersion in the objective. Different from the traditional dictionary learning based approaches and their extensions, which just use the same or not information, our proposed method can explore the ranking relationship among the person images, which is essential for such retrieval related tasks. Simultaneously, one distance measurement has been explicitly learned in the model to further improve the performance. Since we have reformulated these ranking constraints into the graph Laplacian form, the proposed method is easy-to-implement but effective. We conduct extensive experiments on three widely used person Re-Id benchmark datasets, and achieve state-of-the-art performances.
Cheng, E-J, Prasad, M, Puthal, D, Sharma, N, Prasad, OK, Chin, P-H, Lin, C-T & Blumenstein, M 1970, 'Deep Learning Based Face Recognition with Sparse Representation Classification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 24th International Conference on Neural Information Processing (ICONIP), Springer International Publishing, Guangzhou, PEOPLES R CHINA, pp. 665-674.
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Feature extraction is an essential step in solving real-world pattern recognition and classification problems. The accuracy of face recognition highly depends on the extracted features to represent a face. The traditional algorithms uses geometric techniques, comprising feature values including distance and angle between geometric points (eyes corners, mouth extremities, and nostrils). These features are sensitive to the elements such as illumination, variation of poses, various expressions, to mention a few. Recently, deep learning techniques have been very effective for feature extraction, and deep features have considerable tolerance for various conditions and unconstrained environment. This paper proposes a two layer deep convolutional neural network (CNN) for face feature extraction and applied sparse representation for face identification. The sparsity and selectivity of deep features can strengthen sparseness for the solution of sparse representation, which generally improves the recognition rate. The proposed method outperforms other feature extraction and classification methods in terms of recognition accuracy.
Cheng, H-C, Hsieh, M-H & Tomamichel, M 1970, 'Sphere-packing bound for classical-quantum channels', 2017 IEEE Information Theory Workshop (ITW), 2017 IEEE Information Theory Workshop (ITW), IEEE, Kaohsiung, Taiwan, pp. 479-483.
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© 2017 IEEE. We study lower bounds on the optimal error probability in channel coding at rates below capacity, commonly termed sphere-packing bounds. In this work, we establish a sphere-packing bound for classical-quantum channels, which significantly improves previous prefactor from the order of subexponential to polynomial. Furthermore, the gap between the obtained error exponent for constant composition codes and the best known classical random coding exponent vanishes in the order of o(log n/n), indicating our sphere-packing bound is almost exact in the high rate regime. The main technical contributions are two converse Hoeffding bounds for quantum hypothesis testing and the saddle-point properties of error exponent functions.
Cheng, H-C, Hsieh, M-H & Tomamichel, M 1970, 'Sphere-Packing Bound for Symmetric Classical-Quantum Channels', IEEE International Symposium on Information Theory - Proceedings, IEEE International Symposium on Information Theory, IEEE, Aachen, Germany, pp. 286-290.
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We provide a sphere-packing lower bound for the optimal error probability infinite blocklengths when coding over a symmetric classical-quantum channel. Ourresult shows that the pre-factor can be significantly improved from the orderof the subexponential to the polynomial. The established pre-factor isessentially optimal because it matches the best known random coding upper boundin the classical case. Our approaches rely on a sharp concentration inequalityin strong large deviation theory and crucial properties of the error-exponentfunction.
Cheng, L, Acuna, P, Aguilera, RP, Jiang, J, Flecther, J & Baier, C 1970, 'Model predictive control for Energy Management of a hybrid energy storage system in Light Rail Vehicles', 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG), 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG), IEEE, pp. 683-688.
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© 2017 IEEE. A model predictive control (MPC) for an onboard hybrid energy storage system (HESS) in Light Rail Vehicles is proposed. The HESS uses batteries and supercapacitors (SCs). The main objective of the controller is to reduce the system losses while maintaining the supercapacitors state-of-charge (SOC) in a suitable range. To do this, a hierarchical control (Master/Slave) is proposed: a master energy management MPC controller which generates the battery current reference and an slave MPC algorithm controls the power switches of the converters. Additionally, the capability to constraint the battery current reference and battery current is achieved by both controllers respectively. Simulation results, carried out in MATLAB/Simulink, show that the SC SOC is maintained in a suitable range.
Cheng, P, Chen, Z, Zhang, JA, Li, Y & Vucetic, B 1970, 'Low-Complexity Precoding for Spatial Modulation', 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), IEEE, Toronto, ON, Canada, pp. 1-5.
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© 2017 IEEE. In this paper, we investigate linear precoding for spatial modulation (SM) over multiple-input-multiple-output (MIMO) fading channels. With channel state information available at the transmitter, our focus is to maximize the minimum Euclidean distance among all candidates of SM symbols. We prove that the precoder design is a large-scale non-convex quadratically constrained quadratic program (QCQP) problem. However, the conventional methods, such as semi-definite relaxation and iterative concave-convex process, cannot tackle this challenging problem effectively or efficiently. To address this issue, we leverage augmented Lagrangian and dual ascent techniques, and transform the original large-scale non-convex QCQP problem into a sequence of subproblems. These subproblems can be solved in an iterative manner efficiently. Numerical results show that the proposed method can significantly improve the system error performance relative to the SM without precoding, and features extremely fast convergence rate with very low computational complexity.
Cheng, Q, Dutkiewicz, E, Fang, G, Shi, Z, Nguyen, DN & Wang, H 1970, 'A Novel Full-Duplex Spectrum Sensing Algorithm for OFDM Signals in Cognitive Radio Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, pp. 1-6.
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© 2017 IEEE. Full duplex (FD) capability enables a 'listen and talk' protocol for spectrum sensing that has been used as a new paradigm to increase the spectrum utilization in cognitive radio networks (CRNs). However, the spectrum sensing performance suffers from the imperfect self-interference suppression (SIS). This could significantly degrade the performance of FD systems in CRNs. In this paper, we investigate the issue of spectrum sensing with imperfect SIS in FD systems. By drawing support from a cyclic prefix (CP) of Orthogonal Frequency Division Modulation (OFDM) signals, we propose a novel spectrum sensing mechanism that is robust to self-interference. Comparing with other conventional sensing approaches in FD systems, the proposed method is independent of timing delay. That significantly improves the sensing performance, even without requiring a complex process for timing delay estimation. As a result, it also reduces the overhead of spectrum sensing. Extensive simulation results indicate that even with serious self-interference and timing delay, the presented approach is still able to achieve much higher performance than the conventional energy detection and waveform-based detection approaches.
Cheng, Q, Nguyen, DN, Dutkiewicz, E & Mueck, MD 1970, 'Preserving operational information in spectrum access system with dishonest users', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-6.
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© 2017 IEEE. Privacy has been regarded as one of the most critical issues in light of promoting the development of centralized spectrum management, hence attracting wide attention. However, researchers in the current literature are usually protecting users' privacy based on the assumption that all users are honest, which is reasonable but not practical. In this paper, we investigate the privacy issue among different tiers of users in the centralized spectrum access system (SAS), mainly focusing on honest Priority Access Licenses (PALs) and dishonest General Authorized Accesses (GAAs). To that end, we propose an authentication scheme to prevent GAAs from using other users' information by the aid of a public key cryptosystem. Moreover, we propose a 'punishment and forgiveness' scheme, which draws support from GAAs' reputation stores (RSs) and reputation histories (RHs), to encourage GAAs to engage in positive and true activities. Besides, we propose a privacy preservation scheme cooperating with the 'punishment and forgiveness' scheme (PS-PFS) in order to effectively mitigate the impact of dishonest users while fully preserving all users' privacy as well as successfully realizing spectrum sharing.
Chiem, QT, Wilkinson, RH, Lech, M & Cheng, E 1970, 'Investigating Keypoint Repeatability for 3D Correspondence Estimation in Cluttered Scenes', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, NSW, Australia, pp. 1-7.
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© 2017 IEEE. In 3D object recognition, local feature-based recognition is known to be robust against occlusion and clutter. Local feature estimation requires feature correspondences, including feature extraction and matching. Feature extraction is normally a two-stage process that estimates keypoints and keypoint descriptors, and existing studies show repeatability to be a good indicator of keypoint feature detector robustness. However, the impact of keypoint repeatability on feature correspondence estimation and overall feature matching accuracy has not yet been studied. In this paper, local features are extracted at both regular and repeatable 3D keypoints using leading keypoint detectors combined with the SHOT descriptor to estimate a set of correspondences. When using a keypoint detector of high repeatability, experimental results show improved feature matching accuracy and reduced computational requirements for the feature description and matching, and overall correspondence estimation process.
Chiu, C-Y, Singh, AK, Wang, Y-K, King, J-T & Lin, C-T 1970, 'A wireless steady state visually evoked potential-based BCI eating assistive system.', IJCNN, International Joint Conference on Neural Networks, IEEE, Anchorage, AK, USA, pp. 3003-3007.
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© 2017 IEEE. Brain-Computer interface (BCI) which aims at enabling users to perform tasks through their brain waves has been a feasible and worth developing solution for growing demand of healthcare. Current proposed BCI systems are often with lower applicability and do not provide much help for reducing burdens of users because of the time-consuming preparation required by adopted wet sensors and the shortage of provided interactive functions. Here, by integrating a state visually evoked potential (SSVEP)-based BCI system and a robotic eating assistive system, we propose a non-invasive wireless steady state visually evoked potential (SSVEP)-based BCI eating assistive system that enables users with physical disabilities to have meals independently. The analysis compared different methods of classification and indicated the best method. The applicability of the integrated eating assistive system was tested by an Amyotrophic Lateral Sclerosis (ALS) patient, and a questionnaire reply and some suggestion are provided. Fifteen healthy subjects engaged the experiment, and an average accuracy of 91.35%, and information transfer rate (ITR) of 20.69 bit per min are achieved. For online performance evaluation, the ALS patient gave basic affirmation and provided suggestions for further improvement. In summary, we proposed a usable SSVEP-based BCI system enabling users to have meals independently. With additional adjustment of movement design of the robotic arm and classification algorithm, the system may offer users with physical disabilities a new way to take care of themselves.
Choi, Y & McGregor, C 1970, 'A Flexible Parental Engaged Consent Model for the Secondary Use of Their Infant’s Physiological Data in the Neonatal Intensive Care Context', 2017 IEEE International Conference on Healthcare Informatics (ICHI), 2017 IEEE International Conference on Healthcare Informatics (ICHI), IEEE, Park City, UT, USA, pp. 502-507.
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© 2017 IEEE. The secondary use of health data, especially the use of physiological data for research holds many opportunities for improving the current understanding of neonatal conditions. As a neonate is unable to provide their consent regarding participation in research studies, a substitute decision maker (SDM) must provide parental or legal guardian consent. However it has been well documented that there are many emotional, mental and physical challenges associated with the parental consent process in the neonatal intensive care unit (NICU). It is proposed that a flexible parental engaged consent model could help alleviate some of these issues by providing parents with the ability to choose and change their clinical engagement level preference for their infant's participation in research at their convenience at any point in time. In this paper, an extension to Service based Multidimensional Temporal Data Mining Framework (STDMn0) to allow for the functionality of flexible patient or surrogate consent is presented based on the use of a flexible consent model initially proposed by Heath [1]. This functionality is demonstrated via an example implementation for a generic retrospective research study in the NICU setting.
Chou, K-P, Li, D-L, Prasad, M, Lin, C-T & Lin, W-C 1970, 'A method to enhance the deep learning in an aerial image', 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), IEEE, Xiamen, China, pp. 724-728.
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© 2017 IEEE. In this paper, we propose a kind of pre-processing method which can be applied to the depth learning method for the characteristics of aerial image. This method combines the color and spatial information to do the quick background filtering. In addition to increase execution speed, but also to reduce the rate of false positives.
Chou, K-P, Li, D-L, Prasad, M, Pratama, M, Su, S-Y, Lu, H, Lin, C-T & Lin, W-C 1970, 'Robust Facial Alignment for Face Recognition', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017 International Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 497-504.
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© 2017, Springer International Publishing AG. This paper proposes a robust real-time face recognition system that utilizes regression tree based method to locate the facial feature points. The proposed system finds the face region which is suitable to perform the recognition task by geometrically analyses of the facial expression of the target face image. In real-world facial recognition systems, the face is often cropped based on the face detection techniques. The misalignment is inevitably occurred due to facial pose, noise, occlusion, and so on. However misalignment affects the recognition rate due to sensitive nature of the face classifier. The performance of the proposed approach is evaluated with four benchmark databases. The experiment results show the robustness of the proposed approach with significant improvement in the facial recognition system on the various size and resolution of given face images.
Chou, K-P, Prasad, M, Gupta, D, Sankar, S, Xu, T-W, Sundaram, S, Lin, C-T & Lin, W-C 1970, 'Block-based feature extraction model for early fire detection', 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Honolulu, HI, USA, pp. 1-8.
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© 2017 IEEE. Every year the fire disaster always causes a lot of casualties and property damage. Many researchers are involved in the study of related disaster prevention. Early warning systems and stable fire can significantly reduce the damage caused by fire. Many existing image-based early warning systems can perform well in a particular field. In this paper, we propose a general framework that can be applied in most realistic environments. The proposed system is based on a block-based feature extraction method, which analyses local information in separate regions leading to a reduction in computing data. Local features of fire block are extracted from the detailed characteristics of fire objects, which include fire color, fire source immobility, and disorder. Each local feature has high detection rate and filter out different false-positive cases. Global analysis with fire texture and non-moving properties are applied to further reduce false alarm rate. The proposed system is composed of algorithms with low computation. Through a series of experiments, it can be observed that Experimental results show that the proposed system has higher detection rate and low false alarm rate under various environment.
Chou, K-P, Prasad, M, Gupta, D, Sankar, S, Xu, T-W, Sundaram, S, Lin, C-T & Lin, W-C 1970, 'Block-based Feature Extraction Model for Early Fire Detection', 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), IEEE Symposium Series on Computational Intelligence (IEEE SSCI), IEEE, HI, Honolulu, pp. 3540-3547.
Chou, K-P, Prasad, M, Li, D-L, Bharill, N, Lin, Y-F, Hussain, F, Lin, C-T & Lin, W-C 1970, 'Automatic Multi-view Action Recognition with Robust Features', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 554-563.
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© 2017, Springer International Publishing AG. This paper proposes view-invariant features to address multi-view action recognition for different actions performed in different views. The view-invariant features are obtained from clouds of varying temporal scale by extracting holistic features, which are modeled to explicitly take advantage of the global, spatial and temporal distribution of interest points. The proposed view-invariant features are highly discriminative and robust for recognizing actions as the view changes. This paper proposes a mechanism for real world application which can follow the actions of a person in a video based on image sequences and can separate these actions according to given training data. Using the proposed mechanism, the beginning and ending of an action sequence can be labeled automatically without the need for manual setting. It is not necessary in the proposed approach to re-train the system if there are changes in scenario, which means the trained database can be applied in a wide variety of environments. The experiment results show that the proposed approach outperforms existing methods on KTH and WEIZMANN datasets.
Chou, K-P, Prasad, M, Puthal, D, Chen, P-H, Vishwakarma, DK, Sundarami, S, Lin, C-T & Lin, W-C 1970, 'Fast Deformable Model for Pedestrian Detection with Haar-like features', 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Honolulu, HI, USA, pp. 1-8.
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© 2017 IEEE. This paper proposes a novel Fast Deformable Model for Pedestrian Detection (FDMPD) to detect the pedestrians efficiently and accurately in the crowded environment. Despite of multiple detection methods available, detection becomes difficult due to variety of human postures and perspectives. The proposed study is divided into two parts. First part trains six Adaboost classifiers with Haar-like feature for different body parts (e.g., head, shoulders, and knees) to build the response feature maps. Second part uses these six response feature maps with full-body model to produce spatial deep features. The combined deep features are used as an input to SVM to judge the existence of pedestrian. As per the experiments conducted on the INRIA person dataset, the proposed FDMPD approach shows greater than 44.75 % improvement compared to other state-of-the-art methods in terms of efficiency and robustness.
Chu, C, Brownlow, J, Meng, Q, Fu, B, Culbert, B, Zhu, M, Xu, G & He, X 1970, 'Combining heterogeneous features for time series prediction', 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), IEEE, Krakow, Poland, pp. 1-2.
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© 2017 IEEE. Time series prediction is a challenging task in reality, and various methods have been proposed for it. However, only the historical series of values are exploited in most of existing methods. Therefore, the predictive models might be not effective in some cases, due to: (1) the historical series of values is not sufficient usually, and (2) features from heterogeneous sources such as the intrinsic features of data samples themselves, which could be very useful, are not take into consideration. To address these issues, we proposed a novel method in this paper which learns the predictive model based on the combination of dynamic features extracted from series of historical values and static features of data samples. To evaluate the performance of our proposed method, we compare it with linear regression and boosted trees, and the experimental results validate our method's superiority.
Chu, VW, Wong, RK, Chen, F & Chi, C-H 1970, 'Prediction-as-a-Service for Meme Popularity', 2017 IEEE International Conference on Services Computing (SCC), 2017 IEEE International Conference on Services Computing (SCC), IEEE, Honolulu, HI, pp. 386-393.
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Chub, A, Siwakoti, Y, Vinnikov, D & Blaabjerg, F 1970, 'Sheppard-Taylor isolated high boost DC-DC converter', 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), IEEE, pp. 1695-1699.
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© 2017 IEEE. This paper presents a new galvanically isolated step-up dc-dc converter intended for low-power but high step-up applications. The proposed converter is capable of regulating output voltage within a wide range of the input voltage or load variations. In contrast to competitors, the converter can be implemented with fewer passive components. Soft-switching in semiconductors allows achieving high efficiency. In addition, the input side current is continuous. The operating principle and the design guidelines derived for the converter are presented. Theoretical results are supported with experimental results obtained using a 100 W prototype. The converter proposed can be used in photovoltaic module level power electronics applications, where a wide input voltage and load regulation range are highly demanded.
Chubb, CT, Tan, VYF & Tomamichel, M 1970, 'Moderate deviation analysis for classical communication over quantum channels', 2017 IEEE International Symposium on Information Theory (ISIT), 2017 IEEE International Symposium on Information Theory (ISIT), IEEE, Vail, CO, USA, pp. 1544-1548.
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Chung, H, Montiel, F, Karimi, M & Kessissoglou, N 1970, 'Acoustic pressure fields of 2D elastic cylindrical shells', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, 46th International Congress and Exposition on Noise Control Engineering, Hong Kong, China.
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The acoustic pressure field of a 2D elastic cylindrical shell excited by an incident plane wave is analytically and numerically presented. The pressure field is computed by solving the Helmholtz and elastic thin shell equations that are coupled by the kinematic conditions on both the interior and exterior surfaces of the shell. The acoustic pressure is expressed as series of Bessel and Hankel functions that are the eigenfunctions of the Helmholtz equation in 2D polar coordinates. As a result, the solution can be computed without discretization of the physical domains and the cylindrical shell. The method is then implemented to compute the acoustic fields around a C-shaped cylinder, which has the Helmholtz resonator configuration. Results from the analytical model are compared to results from a finite element solution.
Coddington, A, Mann, L, Chandrasekaran, S, Cook, E, Crossin, E, Daniel, S, Mazzurco, A, Smith, T & Turner, J 1970, 'Grounded by values: An emergent engineering practice', Proceedings of the 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), Sydney, 10-13 December 2017/Nazmul Huda, David Inglis, Nicholas Tse, Graham Town (eds.), pp. 910-910.
Coenen, MJ, Vos, HI, Groothuismink, JM, van der Graaf, WT, Flucke, U, Schreuder, BH, Hagleitner, MM, Gelderblom, H, van der Straaten, T, de Bont, ES, Kremer, LC, Bras, J, Caron, HN, Windsor, R, Whelan, JS, Patino-Garcia, A, Gonzalez-Neira, A, McCowage, G, Nagabushan, S, Catchpoole, D, van Leeuwen, FN, Guchelaar, H-J & te Loo, MD 1970, 'PHARMACOGENETICS OF CHEMOTHERAPY RESPONSE IN OSTEOSARCOMA: A GENETIC VARIANT IN SLC7A8 IS ASSOCIATED WITH PROGRESSIVE DISEASE', CLINICAL PHARMACOLOGY & THERAPEUTICS, Annual Meeting of the American-Society-for-Clinical-Pharmacology-and-Therapeutics (ASCPT), WILEY-BLACKWELL, DC, Washington, pp. S16-S16.
Collart, J, Fitch, R & Alempijevic, A 1970, 'Motion states inference through 3D shoulder gait analysis and Hierarchical Hidden Markov Models', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney, Australia, pp. 173-180.
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Automatically inferring human intention from walking movements is an important research concern in robotics and other fields of study. It is generally derived from temporal motion of limb position relative to the body. These changes can also be reected in the change of stance and gait. Conventional systems relying on gait are usually based on tracking the lower body motion (hip, foot) and are extracted from monocular camera data. However, such data can be inaccessible in crowded environments where occlusions of the lower body are prevalent. This paper proposes a novel approach to utilize upper body 3D-motion and Hierarchical Hidden Markov Models to estimate human ambulatory states, such as quietly standing, starting to walk (gait initiation), walking (gait cycle), or stopping (gait termination). Methods have been tested on real data acquired through a motion capture system where foot measurements (heels and toes) were used as ground truth data for labeling the states to train and test the models. Current results demonstrate the feasibility of using such a system to infer lower-body motion states and sub-states through observations of 3D shoulder motion online. Our results enable applications in situations where only upper body motion is readily observable.
Coluccia, A, Ghenescu, M, Piatrik, T, De Cubber, G, Schumann, A, Sommer, L, Klatte, J, Schuchert, T, Beyerer, J, Farhadi, M, Amandi, R, Aker, C, Kalkan, S, Saqib, M, Sharma, N, Daud, S, Makkah, K & Blumenstein, M 1970, 'Drone-vs-Bird detection challenge at IEEE AVSS2017', 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE, Lecce, Italy, pp. 1-6.
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© 2017 IEEE. Small drones are a rising threat due to their possible misuse for illegal activities, in particular smuggling and terrorism. The project SafeShore, funded by the European Commission under the Horizon 2020 program, has launched the 'drone-vs-bird detection challenge' to address one of the many technical issues arising in this context. The goal is to detect a drone appearing at some point in a video where birds may be also present: the algorithm should raise an alarm and provide a position estimate only when a drone is present, while not issuing alarms on birds. This paper reports on the challenge proposal, evaluation, and results1.
Cong, HP, Perry, S, Vu, TA & HoangVan, X 1970, 'Joint exploration model based light field image coding: A comparative study', 2017 4th NAFOSTED Conference on Information and Computer Science, 2017 4th NAFOSTED Conference on Information and Computer Science, IEEE, Hanoi, Vietnam, pp. 308-313.
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The recent light field imaging technology has been attracting a lot of interests due to its potential applications in a large number of areas including Virtual Reality, Augmented Reality (VR/AR), Teleconferencing, and E-learning. Light Field (LF) data is able to provide rich visual information such as scene rendering with changes in depth of field, viewpoint, and focal length. However, Light Field data usually associates to a critical problem — the massive data. Therefore, compressing LF data is one of the main challenges in LF research. In this context, we present in this paper a comparative study for compressing LF data with not only the widely used image/video coding standards, such as JPEG-2000, H.264/AVC, HEVC and Google/VP9 but also with the most recent image/video coding solution, the Joint Exploration Model. In addition, this paper also proposes a LF image coding flow, which can be used as a benchmark for future LF compression evaluation. Finally, the compression efficiency of these coding solutions is thoroughly compared throughout a rich set of test conditions.
Cook, EJ, Mann, LMW & Daniel, SA 1970, 'Co-designing a new engineering curriculum with industry', Proceedings of the 45th SEFI Annual Conference 2017 - Education Excellence for Sustainability, SEFI 2017, pp. 303-310.
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Global changes in technology and culture have drastically altered the needs of industry and society and thus the graduate engineering workforce required to fulfil those needs. With access to the whole body of human knowledge at the touch of a fingertip, learning is moving away from merely accumulating a body of facts. Instead, future engineering graduates need skills in assimilating and applying knowledge, thinking creatively, working collaboratively and in being agile and embracing change. As the mind-sets, skill-sets and knowledge-sets needed by engineering graduates shift, so too must higher education curricula, shifting to an experience-based curriculum that stimulates students to develop personal qualities and professional skills alongside the specialist knowledge of their field. Authentic, relevant student experiences that give engineering students employable skills cannot be created in isolation in universities thus a new curriculum is needed, to be co-designed with employers, industry experts, professional bodies and education specialists. This paper describes efforts underway to develop a new engineering curriculum with industry-led and project-based learning experiences running throughout the course and will propose a model for the co-design of this curriculum with industry and other key stakeholders.
Cui, H, Wang, X, Zhou, J, Gong, G, Yin, Y & Feng, D 1970, 'Computational boundary definition by geodesic graph model', 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), IEEE, Melbourne, AUSTRALIA, pp. 1201-1204.
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Dang, DNM, Ngo, QT, Dang, HN, Vo, PL & Hong, CS 1970, 'Directional Multi-channel MAC for VANETs', Springer International Publishing, pp. 803-812.
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Dang, LC, Dang, CC & Khabbaz, H 1970, 'Behaviour of columns and fibre reinforced load transfer platform supported embankments built on soft soil', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, the 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, Wuhan, China, pp. 1233-1246.
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This paper presents the findings of a numerical study on the behaviour of fibre reinforced load transfer platform (FRLTP) and cement-soil columns supported (CS) embankment constructed on soft soil. An array of numerical analyses based on finite element method incorporated in PLAXIS was conducted on the full geometry of an embankment reinforced without or with an FRLTP over cement-soil columns for different improvement depth in a two-dimensional plane strain condition to examine the effectiveness of the FRLTP inclusion into the CS embankment system. The beneficial effects of lime-fibre-soil inclusion as a load transfer platform (LTP) and cement-soil columns supported embankment on the total and differential settlements, stress transfer mechanism, and lateral displacement have been analyzed and discussed in detail. Subsequently, a detailed parametric study on the influence of the shear strength parameters of the FRLTP has also been performed and discussed to provide a better understanding of the interaction between FRLTP, cement-soil columns and embankment over soft soil. The findings reveal that the CS embankment with FRLTP inclusion can provide the effective improvement in minimising the total and differential settlements, and the lateral displacement, meanwhile enhance the embankment stability and the stress concentration ratio to a great extent. Moreover, the numerical simulation results display that the increase in the improvement depth of the embankment reinforced with an FRLTP over cement-soil columns accelerate the consolidation progress of soft soils subjected to embankment loads. The numerically predicted results from the parametric study indicate that the cohesion and friction angle of the FRLTP have notable influence on the investigated embankment behaviour in terms of improving stress concentration ratio and differential settlement. However, the cohesion of FRLTP appears to be the most influential factor to be considered in the design procedu...
Dang, LC, Khabbaz, H & Fatahi, B 1970, 'An experimental study on engineering behaviour of lime and bagasse fibre reinforced expansive soils', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, the 19th International Conference on Soil Mechanics and Geotechnical Engineering, ISSMGE, Seoul, Republic of Korea, pp. 2497-2500.
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This investigation exhibits a series of laboratory tests conducted to evaluate the influences of bagasse fibre and hydrated lime addition on the engineering properties and swelling behaviour of stabilised expansive soils. Bagasse fibre is industrial waste byproduct left after crushing of sugar-cane for juice extraction, used in this study as a reinforcing component for expansive soil stabilisation. The expansive soils used in this investigation were collected from Queensland, Australia. Varying proportions of randomly distributed bagasse fibre of 0.5%, 1.0%, and 2.0% were added to expansive soil and lime-treated expansive soil to investigate the influences of bagasse fibre on the engineering characteristics of stabilised soil. Results of California bearing capacity (CBR), swell potential and one-dimensional consolidation tests after various curing time are presented and discussed in detail. The findings of this experimental investigation indicate that expansive soil reinforcement, blended with bagasse fibre and lime leads to a significant increase in the compressive strength and the bearing capacity of expansive soil. Meanwhile, the swell potential and compressibility of stabilised expansive soils decreased with increasing lime and bagasse fibre contents.
Dang, S, Cai, X, Wang, Y, Zhang, J & Chen, F 1970, 'Unsupervised Matrix-valued Kernel Learning For One Class Classification', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, Singapore, SINGAPORE, pp. 2031-2034.
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Dang, TD & Hoang, D 1970, 'A data protection model for fog computing', 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), IEEE, Valencia, SPAIN, pp. 32-38.
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Daniel, S & Mann, L 1970, 'Integrating social impact throughout an engineering curriculum', 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), Australasian Association for Engineering Education, pp. 932-932.
Daniel, S, Mann, L & Mazzolini, A 1970, 'Defending interpretivist knowledge claims in engineering education research', 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), Australasian Association for Engineering Education, pp. 889-889.
Daniel, SA & Mann, LMW 1970, 'Embedding social impact in engineering curriculum', Proceedings of the 45th SEFI Annual Conference 2017 - Education Excellence for Sustainability, SEFI 2017, pp. 935-945.
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The prospect of having a positive social impact motivates many students to study engineering. However, this motivation is largely ignored in engineering curricula, which have traditionally focused on the transmission of content knowledge. The growth of humanitarian engineering education in recent years is part of a trend towards addressing social impact in engineering education and appealing to this student motivation. For example, many Australian universities now offer the Engineers without Borders (EWB) Design Challenge, humanitarian engineering research projects, or even entire degree specialisations. However, despite the success of these programs, what is lacking is a way of embedding social impact in all engineering curricula. At Swinburne University of Technology, this lack is being addressed with a new curriculum being co-designed with industry partners, grounded in education research, and built around work-oriented pedagogies including project-based learning. Projects will be aligned with 4 Pillars: Emerging Technologies, Entrepreneurship, research & Development, and Social Impact. In this paper, we will report on the development of our new Social Impact curriculum pillar, drawing on research from the fields of social science, engineering education, and humanitarian engineering, and from real-world case studies of how engineering has been used to achieve lasting positive social impact.
Dasgupta, A & Gill, AQ 1970, 'Fog computing challenges: A systematic review', Proceedings of the 28th Australasian Conference on Information Systems, ACIS 2017, Australasian Conference on Information Systems, Hobart, Australia.
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Internet of Things (IoT) applications continue to grow at a rapid scale. However, current cloud centric IoT architectures are not feasible to support the mobility needs as well as latency requirements of time critical IoT applications. This has restricted the growth of IoT in certain sectors. This paper investigates the fog-computing paradigm as an alternative for IoT applications. There is a need to systematically review and synthesize fog computing concerns or challenges for IoT applications. This paper aims to address this important research need using a well-known systematic literature review (SLR) approach. Using the SLR approach and applying customized search criteria derived from the research question, 17 relevant studies were identified and reviewed in this regard from an initial set of 439 papers. In addition, 4 papers were manually identified based on their relevance. The data was organized into four major challenge categories. The findings of this research paper can help practitioners and researchers to understand fog computing related concerns, and provide a number of useful insights for future work. The scope of this paper is limited to the number of reviewed studies from chosen database.
Davis, QT, Tanaka, T & McGloin, D 1970, 'Transport of intensity microscopy for distinguishing single and bundled microtubules', 2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), IEEE, Munich, Germany, pp. 1-1.
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Microtubules are filamentous protein polymers about 25 nm in diameter, ubiquitous in eukaryotes and providing key functionality in cellular biology. Although microtubules may span many microns in length, their slender width places them well below the diffraction limit. Unlabeled microtubules lack any meaningful absorption of a passing wavefront, and are therefore sub-resolution phase objects.
Derlon, AB, Berger, C, Castet, S-M, Chamouni, P, Desprez, D, De Raucourt, E, Frotscher, B, Gay, V, Huguenin, Y, Lambert, T, Marques-Verdier, A & Trossaert, M 1970, 'Monitoring for Inhibitor in Patients with Haemophilia a When Switching to a New Factor VIII (FVIII), Turoctocog Alfa: Medical Practice in France?', HAEMOPHILIA, WILEY, pp. 40-40.
Dibs, H, Mansor, S, Ahmad, N & Pradhan, B 1970, 'Registration model for near-equatorial earth observation satellite images using automatic extraction of control points'.
Dickson-Deane, C, Kaur, J, Dyki, M & Edwards, M 1970, 'Redefining close quarters: Discussing transitioning business academics from traditional to blended delivery', ASCILITE 2018 - Conference Proceedings - 35th International Conference of Innovation, Practice and Research in the use of Educational Technologies in Tertiary Education: Open Oceans: Learning Without Borders, pp. 555-556.
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The partnership between designers and subject matter experts creates an ill-structured problem whereby the marrying of design skills with discipline knowledge are not always seamlessly combined. The meaning of definitions and by association interpretations can become blurred in this partnership and understanding the different perspectives contributing to the activity can assist in guiding design activities. Each participant in the partnership has a contextual journey that is guided by their own perspectives, discipline specific experiences as knowledge and interpretation of such and this can result in a unique experience for this problem-solving activity of design. This panel allows academics to share their own interpretations of the process as a way to alert all participants to the blurred understandings that occur in design processes.
Diesner, J, Ferrari, E & Xu, G 1970, 'Welcome from the ASONAM 2017 program chairs', Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, p. xviii.
Ding, C, Jones, B, Sun, H, Qin, P-Y, Guo, YJ & Ji, L 1970, 'Wideband feeding method for full-wave dipole', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, USA, pp. 2131-2132.
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© 2017 IEEE. This paper introduces a wide-band feeding method for full-wave dipole antennas. A full-wave dipole is designed to cover the band from 698 MHz to 960 MHz for cellular base station applications. Its matching circuit consists of a laddertype filter design and a quasi-quarter-wavelength resistance transformer. The proposed matching circuit can provide balanced feeding as a balun and has a compact size. The matching circuit is designed and optimized using a circuit theory model and then physically realized using microstrip lines based on full-wave simulation. The simulated reflection coefficient |S11| is < -15 dB across the entire target band, exhibiting a bandwidth of 32%.
Do, Q, Liu, W & Chen, F 1970, 'Discovering Both Explicit and Implicit Similarities for Cross-Domain Recommendation', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific Asia Conference on Advances in Knowledge Discovery and Data Mining, Springer International Publishing, Jeju, South Korea, pp. 618-630.
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© 2017, Springer International Publishing AG. Recommender System has become one of the most important techniques for businesses today. Improving its performance requires a thorough understanding of latent similarities among users and items. This issue is addressable given recent abundance of datasets across domains. However, the question of how to utilize this cross-domain rich information to improve recommendation performance is still an open problem. In this paper, we propose a cross-domain recommender as the first algorithm utilizing both explicit and implicit similarities between datasets across sources for performance improvement. Validated on real-world datasets, our proposed idea outperforms the current cross-domain recommendation methods by more than 2 times. Yet, the more interesting observation is that both explicit and implicit similarities between datasets help to better suggest unknown information from cross-domain sources.
Dong, D & Wang, Y 1970, 'Several recent developments in estimation and robust control of quantum systems', 2017 Australian and New Zealand Control Conference (ANZCC), 2017 Australian and New Zealand Control Conference (ANZCC), IEEE, pp. 190-195.
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Dong, F, Lu, J, Li, K & Zhang, G 1970, 'Concept drift region identification via competence-based discrepancy distribution estimation', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Nanjing, China, pp. 1-7.
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© 2017 IEEE. Real-world data analytics often involves cumulative data. While such data contains valuable information, the pattern or concept underlying these data may change over time and is known as concept drift. When learning under concept drift, it is essential to know when, how and where the context has evolved. Most existing drift detection methods focus only on triggering a signal when drift is detected, and little research has endeavored to explain how and where the data changes. To address this issue, we introduce kernel density estimation into competence-based drift detection method, and invent competence-based discrepancy distribution estimation to identify specific regions in the data feature space where drift has occurred. Two experiments demonstrate that our proposed approach, competence-based discrepancy density estimation, can quantitatively highlight drift regions through data feature space, and produce results that are very close to preset drift regions.
Dong, L, Niyato, D, Kim, DI & Hoang, DT 1970, 'A Joint Scheduling and Content Caching Scheme for Energy Harvesting Access Points with Multicast', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - 2017 IEEE Global Communications Conference, IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. In this work, we investigate a system where users are served by an access point that is equipped with energy harvesting and caching mechanism. Focusing on the design of an efficient content delivery scheduling, we propose a joint scheduling and caching scheme. The scheduling problem is formulated as a Markov decision process and solved by an on-line learning algorithm. To deal with large state space, we apply the linear approximation method to the state-Action value functions, which significantly reduces the memory space for storing the function values. In addition, the preference learning is incorporated to speed up the convergence when dealing with the requests from users that have obvious content preferences. Simulation results confirm that the proposed scheme outperforms the baseline scheme in terms of convergence and system throughput, especially when the personal preference is concentrated to one or two contents.
Dong, Y, Li, D, Fatahi, B, Zhang, X & Khabbaz, H 1970, 'Small-strain shear modulus of soft clay treated with Saccharomyces cerevisiae and cement', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2507-2510.
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Soil stabilisation by means of microorganisms is an emerging and novel technique in geotechnical engineering. On the other hand, cementation, as one of the conventional ground improvement techniques, has been proved to be an effective method to enhance the engineering properties of soils. Hence, it is believed that the combination of these two approaches can be extremely valuable and offer a novel, cost effective, environmentally friendly and practical engineering solution. In this study, the Saccharomyces cerevisiae, a species of yeast, has been selected owing to abundance and production cost to conduct the experiment in order to investigate its influence on the shear wave velocity and the small-strain shear modulus of cement stabilised clays using bender element test. It is observed that an appropriate amount of Saccharomyces cerevisiae can adequately improve the stiffness of soft clays treated with cement and microorganisms in long term.
Dou, W, Xu, X, Meng, S, Zhang, X, Hu, C, Yu, S & Yang, J 1970, 'An energy‐aware virtual machine scheduling method for service QoS enhancement in clouds over big data', Concurrency and Computation: Practice and Experience, Wiley, pp. e3909-e3909.
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SummaryBecause of the strong demands of physical resources of big data, it is an effective and efficient way to store and process big data in clouds, as cloud computing allows on‐demand resource provisioning. With the increasing requirements for the resources provisioned by cloud platforms, the Quality of Service (QoS) of cloud services for big data management is becoming significantly important. Big data has the character of sparseness, which leads to frequent data accessing and processing, and thereby causes huge amount of energy consumption. Energy cost plays a key role in determining the price of a service and should be treated as a first‐class citizen as other QoS metrics, because energy saving services can achieve cheaper service prices and environmentally friendly solutions. However, it is still a challenge to efficiently schedule Virtual Machines (VMs) for service QoS enhancement in an energy‐aware manner. In this paper, we propose an energy‐aware dynamic VM scheduling method for QoS enhancement in clouds over big data to address the above challenge. Specifically, the method consists of two main VM migration phases where computation tasks are migrated to servers with lower energy consumption or higher performance to reduce service prices and execution time. Extensive experimental evaluation demonstrates the effectiveness and efficiency of our method. Copyright © 2016 John Wiley & Sons, Ltd.
Dutkiewicz, E 1970, 'VTC2017-Spring Welcome from the General Chair', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference: VTC2017-Spring, IEEE, Sydney, NSW, Australia, pp. i-i.
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Dutkiewicz, E, He, Y, Jayawickrama, BA & Abeywickrama, HV 1970, 'Radio environment maps generation and spectrum sensing testbed for spectrum sharing in 5G networks', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Verona, ITALY, pp. 33-36.
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© 2017 IEEE. To deliver on the data rate and latency promises of 5G, more spectrum resources below 6 GHz are required. Therefore the regulators are now promoting spectrum sharing. Having access to realtime spatio-Temporal spectrum usage information enables efficient decision making and monitoring. This knowledge can be represented in Radio Environment Maps constructed through geolocation aware spectrum measurements. In this paper, we give an overview of the spectrum sharing concept and its emergence in 5G standardisation. We also present our research on spectrum sharing including methods for efficient and accurate generation of Radio Environment Maps and a practical radio spectrum measurements testbed.
Dutkiewicz, E, Jayawickrama, BA & He, Y 1970, 'Radio spectrum maps for emerging IoT and 5G networks: Applications to smart buildings', 2017 International Conference on Electrical Engineering and Computer Science (ICECOS), 2017 International Conference on Electrical Engineering and Computer Science (ICECOS), IEEE, Palembang, Indonesia, pp. 7-9.
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© 2017 IEEE. The high demand for wireless Internet including emerging Internet of Things (IoT) applications is putting extreme pressure on better utilisation of the available radio spectrum. The expected spectrum 'crunch' requires highly efficient radio resource management schemes with low complexity and high responsiveness to the changing network conditions. Spectrum sharing is regarded as an essential approach to regaining access to otherwise unused spectrum and it is considered an essential component in the development of IoT and 5G networks. Spectrum sharing can be conducted at different time scales. As the time scale of the operation of spectrum sharing decreases, the possibility for utilising more available spectrum holes increases. However, the shorter time scale brings with it challenges. Efficient decisions regarding the use of spectrum sharing require accurate knowledge of the spatial and temporal spectrum use in a geographical area of interest. This knowledge can be represented in Radio Spectrum Maps which need to be generated efficiently and accurately. In this paper we give an overview of the spectrum sharing concept for IoT and 5G networks. We also present our research on spectrum sharing to enable Smart Building IoT applications.
Ebadi, A & Ji, J 1970, 'Investigation & comparison of the integration of flywheel energy storage in hybrid electric and electric vehicles using bond graphs', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. Over the past few years Hybrid Electric and Electric propulsion systems have found significant attention as the most plausible substitute to fossil fuel based engines. Hybrid Electric Vehicles (HEV) have been around for more than a decade and extensive research has been taken out to make these vehicles more efficient. With advances in technology, manufacturers such as Tesla and Chevrolet have successfully launched a number of Electric Vehicles (EV) in the past 5 years. In despite of all this success, HEVs and EVs currently face challenges in energy storage systems (ESS) with regard to a variety of parameters and to overcome these issues research has been done on different types of ESS systems to extend the range of such vehicles. Flywheel Energy Storage Systems (FESS) have regained interest in the last decade and the application of kinetic energy recovery system (KERS) in the Formula 1 has reinforced the case of using FESS in HEV and EV. In this study, the integration of an FESS system within a hybrid electric propulsion and an electric propulsion system is considered and with the help of Bond-Graphs as a multidisciplinary modelling tool the impact of this integration is analyzed and compared with each other.
Ebrahimi, M, ShafieiBavani, E, Wong, R & Chen, F 1970, 'Exploring Celebrities on Inferring User Geolocation in Twitter', Advances in Knowledge Discovery and Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, Jeju, South Korea, pp. 395-406.
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Location information of social media users provides crucial context to monitor real-time events such as natural disasters, terrorism and epidemics. Since only a small amount of social media data are geotagged, inference techniques play a substantial role to predict user spatial locations by incorporating characteristics of their behavior. Based on utilized source of information, related works are divided into text-based (based on text posted by users), network-based (based on the friendship network), and some hybrid methods. In this paper, we propose a novel approach based on the notion of celebrities to infer the location of Twitter users. We categorize highly-mentioned users (celebrities) into local and global, and consequently utilize local celebrities as a major location indicator for inference. A label propagation algorithm is then utilized over a refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text-based method as a back-off strategy into our network-based approach. Empirical experiments using three standard Twitter benchmark datasets demonstrate the superior performance of our approach over the state-of-the-art methods.
Ee, TZ, Lim, S, Ling, PY, Huei, WK & Chyuan, OH 1970, 'Synthesis of seaweed based carbon acid catalyst by thermal decomposition of ammonium sulfate for biodiesel production', AIP Conference Proceedings, GREEN AND SUSTAINABLE TECHNOLOGY: 2nd International Symposium (ISGST2017), Author(s), MALAYSIA, pp. 020009-020009.
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ElShaweesh, O, Hussain, FK, Lu, H, Al-Hassan, M & Kharazmi, S 1970, 'Personalized Web Search Based on Ontological User Profile in Transportation Domain', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 24th International Conference on Neural Information Processing 2017, Springer International Publishing, Guangzhou, China, pp. 239-248.
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© 2017, Springer International Publishing AG. Current conventional search engines deliver similar results to all users for the same query. Because of the variety of user interests and preferences, personalized search engines, based on semantics, hold the promise of providing more efficient information that better reflects users’ needs. The main feature of building a personalized web search is to represent user interests in terms of user profiles. This paper proposes a personalized search approach using an ontology-based user profile. The aim of this approach is to build user profiles based on user browsing behavior and semantic knowledge of specific domain ontology to enhance the quality of the search results. The proposed approach utilizes a re-ranked algorithm to sort the results returned by the search engine to provide a search result that best relates to the user query. This algorithm evaluates the similarity between a user query, the retrieved search results and the ontological concepts. This similarity is computed by taking into account a user’s explicit browsing behavior, semantic knowledge of concepts, and synonyms of term-based vectors extracted from the WordNet API. A set of experiments using a case study from a transport service domain validates the effectiveness of the proposed approach and demonstrates promising results.
Erfani, SS, Lawrence, C, Abedin, B, Beydoun, G & Malimu, L 1970, 'Indigenous people living with cancer: Developing a mobile health application for improving their psychological well-being', AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation, Americas Conference on Information Systems, AIS Electronic Library, Boston, pp. 1-5.
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Poor cancer outcomes experienced by Indigenous Australians result from advanced cancer stages at diagnosis, poorer uptake of and adherence to treatments, higher levels of co-morbidity, and poorer access to inclusive and culturally appropriate care compared with non-Indigenous Australians. Socio-economics and social support can mitigate these problems. Technology-based interventions hold considerable promise for enhancing social support. This paper asks what are the key features of a mobile health application designed to improve the social support and consequently psychological well-being of Indigenous Australians living with cancer? To answer this question, a comprehensive literature review of studies conducted in information systems and health disciplines has been undertaken and a theoretical model is proposed. This study contributes to the existing knowledge base through the development of a new theoretical model and the introduction of the features of a mobile health application that may have a positive impact among Indigenous Australian cancer patients’ psychological well-being.
Esselle, KP 1970, 'Leaky-wave antennas: From niche applications to mass market', 2017 IEEE Radio and Antenna Days of the Indian Ocean (RADIO), 2017 IEEE Radio and Antenna Days of the Indian Ocean (RADIO), IEEE, pp. 1-1.
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Every, J, Li, L & Dorrell, DG 1970, 'Economic optimization of hybrid PV-battery systems using hourly satellite insolation and daily temperature data: A case study', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-6.
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© 2017 IEEE. This paper presents an economic optimization case study for a medium-scale hybrid PV-battery system. PV energy yield and battery operation models based on hourly satellite insolation and daily temperature data form the basis of an underlying objective function aiming to maximize the net present value of potential energy cost savings. Forecasted system prices and energy tariffs over a nine-year period are considered enabling the opportune year to invest and the characteristics of the corresponding optimal system to be determined.
Every, J, Li, L & Dorrell, DG 1970, 'Optimal selection of small-scale hybrid PV-battery systems to maximize economic benefit based on temporal load data', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 471-476.
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© 2017 IEEE. Continued advances in PV and battery energy storage technologies have made hybrid PV-battery systems an attractive prospect for residential energy consumers. However the process to select an appropriate system is complicated by the relatively high cost of batteries, a multitude of available retail electricity plans and the removal of PV installation incentive schemes. In this paper, an optimization strategy based on an individual customer's temporal load profile is established to maximize electricity cost savings through optimal selection of PV-battery system size, orientation and retail electricity plan. Quantum-behaved particle swarm optimization is applied as the underlying algorithm given its well-suited application to problems involving hybrid energy system specification. The optimization strategy is tested using real-world residential consumption data, current system pricing and available retail electricity plans to establish the efficacy of a hybrid PV-battery solution.
Fan, H, Chang, X, Cheng, D, Yang, Y, Xu, D & Hauptmann, AG 1970, 'Complex Event Detection by Identifying Reliable Shots from Untrimmed Videos', 2017 IEEE International Conference on Computer Vision (ICCV), 2017 IEEE International Conference on Computer Vision (ICCV), IEEE, Venice, Italy, pp. 736-744.
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© 2017 IEEE. The goal of complex event detection is to automatically detect whether an event of interest happens in temporally untrimmed long videos which usually consist of multiple video shots. Observing some video shots in positive (resp. negative) videos are irrelevant (resp. relevant) to the given event class, we formulate this task as a multi-instance learning (MIL) problem by taking each video as a bag and the video shots in each video as instances. To this end, we propose a new MIL method, which simultaneously learns a linear SVM classifier and infers a binary indicator for each instance in order to select reliable training instances from each positive or negative bag. In our new objective function, we balance the weighted training errors and a l1-l2 mixed-norm regularization term which adaptively selects reliable shots as training instances from different videos to have them as diverse as possible. We also develop an alternating optimization approach that can efficiently solve our proposed objective function. Extensive experiments on the challenging real-world Multimedia Event Detection (MED) datasets MEDTest-14, MEDTest-13 and CCV clearly demonstrate the effectiveness of our proposed MIL approach for complex event detection.
Fan, M, Chang, X & Tao, D 1970, 'Structure Regularized Unsupervised Discriminant Feature Analysis', Proceedings of the AAAI Conference on Artificial Intelligence, Thirty-First AAAI Conference on Artificial Intelligence 2017, Association for the Advancement of Artificial Intelligence (AAAI), California, USA, pp. 1870-1876.
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Feature selection is an important technique in machine learning research. An effective and robust feature selection method is desired to simultaneously identify the informative features and eliminate the noisy ones of data. In this paper, we consider the unsupervised feature selection problem which is particularly difficult as there is not any class labels that would guide the search for relevant features. To solve this, we propose a novel algorithmic framework which performs unsupervised feature selection. Firstly, the proposed framework implements structure learning, where the data structures (including intrinsic distribution structure and the data segment) are found via a combination of the alternative optimization and clustering. Then, both the intrinsic data structure and data segmentation are formulated as regularization terms for discriminant feature selection. The results of the feature selection also affect the structure learning step in the following iterations. By leveraging the interactions between structure learning and feature selection, we are able to capture more accurate structure of data and select more informative features. Clustering and classification experiments on real world image data sets demonstrate the effectiveness of our method.
Fan, M, Chang, X, Zhang, X, Wang, D & Du, L 1970, 'Top-k Supervise Feature Selection via ADMM for Integer Programming', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, AUSTRALIA, pp. 1646-1653.
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Recently, structured sparsity inducing based feature selection has become a hot topic in machine learning and pattern recognition. Most of the sparsity inducing feature selection methods are designed to rank all features by certain criterion and then select the k top ranked features, where k is an integer. However, the k top features are usually not the top k features and therefore maybe a suboptimal result. In this paper, we propose a novel supervised feature selection method to directly identify the top k features. The new method is formulated as a classic regularized least squares regression model with two groups of variables. The problem with respect to one group of the variables turn out to be a 0-1 integer programming, which had been considered very hard to solve. To address this, we utilize an efficient optimization method to solve the integer programming, which first replaces the discrete 0-1 constraints with two continuous constraints and then utilizes the alternating direction method of multipliers to optimize the equivalent problem. The obtained result is the top subset with k features under the proposed criterion rather than the subset of k top features. Experiments have been conducted on benchmark data sets to show the effectiveness of proposed method.
Fan, X, Sui, Y, Liao, X & Xue, J 1970, 'Boosting the precision of virtual call integrity protection with partial pointer analysis for C++', Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA '17: International Symposium on Software Testing and Analysis, ACM, Santa Barbara, CA, USA, pp. 329-340.
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© 2017 Association for Computing Machinery. We present, Vip, an approach to boosting the precision of Virtual call Integrity Protection for large-scale real-world C++ programs (e.g., Chrome) by using pointer analysis for the first time. Vip introduces two new techniques: (1) a sound and scalable partial pointer analysis for discovering statically the sets of legitimate targets at virtual callsites from separately compiled C++ modules and (2) a lightweight instrumentation technique for performing (virtual call) integrity checks at runtime. Vip raises the bar against vtable hijacking attacks by providing stronger security guarantees than the CHA-based approach with comparable performance overhead. Vip is implemented in LLVM-3.8.0 and evaluated using SPEC programs and Chrome. Statically, Vip protects virtual calls more effectively than CHA by significantly reducing the sets of legitimate targets permitted at 20.3% of the virtual callsites per program, on average. Dynamically, Vip incurs an average (maximum) instrumentation overhead of 0.7% (3.3%), making it practically deployable as part of a compiler tool chain.
Fang, L, Li, H, David Huang, D & Huang, X 1970, 'A low cost interpolation based detection algorithm for medium-size massive MIMO-OFDM systems', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, Australia, pp. 1-5.
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© 2017 IEEE. The great potential of exploiting millimeter wave (mmwave) frequency spectrum for emerging fifth-generation (5G) wireless networks has motivated the study of massive multiple-input multiple-output (MIMO) for achieving high data rate. For medium-size massive MIMO with orthogonal frequency division multiplexing (OFDM) uplink systems, the minimum mean square error (MMSE) based soft-output detector is often used due to its better bit error rate (BER) performance compared to the matched filter detector. Although the multipath channel can be converted into a set of parallel flat-fading channels by using OFDM thus reducing the complexity of receiver design, the tone by tone (per subcarrier) detection methods based on the state-of-The-Art low complexity MMSE still incur considerably high computational complexity since the number of tones is typically very large. To reduce the complexity, the interpolation-based matrix inversion algorithms for small-size MIMO-OFDM systems have been proposed, which compute the matrix inversion by interpolating separately the adjoint and determinant. In this paper, we find that the (regularized) Gram matrix inversions have strong correlation between different subcarriers. By exploiting this strong correlation, we propose a linear interpolation based MMSE detection algorithm that directly interpolates the inverted MMSE matrices for a small number of subcarriers to obtain matrix inversions for all other subcarriers, thereby significantly reducing the number of matrix inversion required. Extensive simulations show that with small BER performance loss compared to the exact MMSE detector, the proposed algorithm can reduce the complexity to the level of the matched filter algorithm.
Fang, XS, Sheng, QZ, Wang, X & Ngu, AHH 1970, 'Value Veracity Estimation for Multi-Truth Objects via a Graph-Based Approach', Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion, the 26th International Conference, ACM Press, pp. 777-778.
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Fang, XS, Sheng, QZ, Wang, X, Barhamgi, M, Yao, L & Ngu, AHH 1970, 'SourceVote: Fusing Multi-valued Data via Inter-source Agreements', CONCEPTUAL MODELING, ER 2017, 36th International Conference on Conceptual Modeling (ER), Springer International Publishing, Valencia, SPAIN, pp. 164-172.
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Farahmandian, S & Hoang, DB 1970, 'SDS2: A Novel Software-Defined Security Service for Protecting Cloud Computing Infrastructure', The 16th IEEE International Symposium on Network Computing and Applications17), The 16th IEEE International Symposium on Network Computing and Applications17), Cambridge, MA, USA.
Farhood, H, He, X, Jia, W, Blumenstein, M & Li, H 1970, 'Counting People Based on Linear, Weighted, and Local Random Forests', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, pp. 1-7.
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© 2017 IEEE. Recently, many works have been published for counting people. However, when being applied to real-world train station videos, they have exposed many limitations due to problems such as low resolution, heavy occlusion, various density levels and perspective distortions. In this paper, following the recent trend of regression-based density estimation, we present a linear regression approach based on local Random Forests for counting either standing or moving people on station platforms. By dividing each frame into sub-windows and extracting features with ground truth densities as well as learned weights, we perform a linear transformation for counting people to overcome the perspective problems of the existing patch-based approaches. We present improvements against several recent baselines on the UCSD dataset and a dataset of CCTV videos taken from a train station. We also show improvements in speed compared with the state-of-the-art models based on detection and Deep Learning.
Farrok, O, Islam, MR, Sheikh, MRI, Guo, Y, Zhu, J & Lei, G 1970, 'A novel method to avoid degradation due to demagnetization of PM linear generators for oceanic wave energy extraction', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, AUSTRALIA, pp. 1-6.
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© 2017 IEEE. Demagnetization is one of the noticeable problems in almost every permanent magnet linear generator (PMLG) for oceanic wave energy conversion. To avoid the degradation of electrical power generation capability, a PMLG with a new feature of variable air gap length is proposed in this paper. To verify the effectiveness of the proposed method, a PMLG has been designed which is simulated for both the fixed and variable air gaps. The finite element analysis is performed for simulation for analysis of the PMLG with the conventional and the proposed methods by using the software package ANSYS/Ansoft. The voltage, current, power, magnetic flux density, and force components of the PMLG are analyzed and discussed. The simulation results show that the new method can effectively avoid the demagnetization problem.
Feng, VX & Leong, TW 1970, 'Digital meaning', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, Brisbane, pp. 366-370.
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Ferguson, S & Bown, O 1970, 'Creative Coding for the Raspberry Pi using the HappyBrackets Platform', Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition, C&C '17: Creativity and Cognition, ACM, Singapore, Singapore.
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This workshop will introduce creative coding audio for the Raspberry Pi, using the 'beads' platform for audio programming, and the 'HappyBrackets' platform for inter-device communication and sensor data acquisition. We will demonstrate methods to allow each self-contained battery-powered device to acquire sensor data about its surroundings and the way it is being interacted with, as well as methods for designing systems where groups of these devices wirelessly communicate their state, allowing new interaction possibilities and approaches.
Ferguson, S, Rowe, A, Bown, O, Birtles, L & Bennewith, C 1970, 'Networked Pixels', Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition, C&C '17: Creativity and Cognition, ACM, Singapore, pp. 299-308.
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This paper describes the development of the hardware and software for Bloom, a light installation installed at Kew Gardens, London in December of 2016. The system is made up of a set of nearly 1000 distributed pixel devices each with LEDs, GPS sensor, and sound hardware, networked together with WiFi to form a display system. Media design for this system required consideration of the distributed nature of the devices. We outline the software and hardware designed for this system, and describe two approaches to the software and media design, one whereby we employ the distributed devices themselves for computation purposes (the approach we ultimately selected), and another whereby the devices are controlled from a central server that is performing most of the computation necessary. We then review these approaches and outline possibilities for future research.
Fernandez, E, Jamborsalamati, P, Hossain, MJ & Amin, U 1970, 'A Communication-enhanced Price-based Control Scheme for HVAC Systems', 2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 7th IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, Univ Auckland, Auckland, NEW ZEALAND, pp. 214-219.
Fernandez, E, Jamborsalamati, P, Hossain, MJ & Amin, U 1970, 'A communication-enhanced price-based control scheme for HVAC systems', 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, pp. 1-6.
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© 2017 IEEE. Real-time electricity pricing has been a key issue in Australia's national electricity markets. The average electricity bill paid by a consumer is influenced by the amount of energy consumption by different loads and their time of use. Certain loads such as dishwashers and pool pumps are deferrable while loads such as lighting and refrigeration are non-deferable. HVAC (heating, ventilation and air conditioning) systems contribute to a major part of the energy consumption of a building. This paper discusses the design of real-time energy pricing in a transactive environment where the key players will be the consumers. The designed real-time control scheme in this paper is to define the final thermostat set-point for each HVAC based on the bidding price. In addition, this paper proposes the communication architecture to implement the designed control scheme through two-way communication between HVACs, data aggregator and the central controller. The proposed architecture utilizes the Message Queue Telemetry Transport (MQTT) protocol which is the state-of-the-art lightweight messaging protocol for use on top of the TCP/IP protocol. From the analysis, it is evident that the proposed algorithm enables customers to reduce energy costs and increases energy efficiency.
Fernando, KES, McGregor, C & James, AG 1970, 'CRISP-TDM<inf>0</inf> for standardized knowledge discovery from physiological data streams: Retinopathy of prematurity and blood oxygen saturation case study', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 226-229.
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© 2017 IEEE. The CRoss Industry Standard Process for Temporal Data Mining (CRISP-TDM) that supports physiological stream temporal data mining and CRISP-DM0 that supports null hypothesis driven confirmatory data mining in combination was proposed by prior research. This combined CRISP-TDM0 is utilised as the standardised approach to managing, reporting and performing retrospective clinical research and is designed to solve the limitation in knowledge discovery amongst physiological data streams [1]. The temporal abstractions (TA) of high fidelity blood oxygenation saturation (SpO2) levels of nine premature neonates are analysed using data collected by the Artemis Platform that complies with the Big Data concept [2] and correlated with Retinopathy of Prematurity (ROP) data. The hourly SpO2, TA pattern visualisation manifested three clusters and this is further supported by mathematical review of time percentage spent in target, below and over oxygenation. Clustering based on ROP stage and gestational age identified probable association within these three clusters. However known risk factors showed no association with ROP.
Fernando, WA & Dah-Chuan Lu, D 1970, 'Feasibility study on using pipe type cables and CoAxial cables for HFAC power distribution in data centre applications', 2017 IEEE International Telecommunications Energy Conference (INTELEC), 2017 IEEE International Telecommunications Energy Conference (INTELEC), IEEE, Broadbeach, QLD, Australia, pp. 208-214.
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This paper investigates into the power cable used in HFAC Power Distribution Systems (PDSs) and recommends new cable types that could be used to improve the performance. While using the same materials and trying not to increase the weight per unit length, the cross section of the cable has been modified to minimize the losses observed in HFAC applications. With higher operating frequencies, the skin effect of conductors dominate and the cable impedance increase exponentially, overcasting the benefits of using HFAC. Upto now, cables manufactured with DC ratings have been used in AC applications with various de-rating factors to account for the additional impedance. Although this approach has worked well with 50/60Hz applications, when extended to HFAC the PDSs become bulky and heavy, thus not effective and even question the benefits of using HFAC in PDSs. Therefore, a new approach of using different cross sections of cables for HFAC applications is proposed. Optimal sizes could be selected in accordance with manufacturing limitations leaving the fine adjustments to be made with the HFAC grid parameters for extracting the maximum benefits out of HFAC PDSs.
Fernando, WA & Lu, DD-C 1970, 'Bi-directional converter for interfacing appliances with HFAC enabled power distribution systems in critical applications', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. A new topology for a robust HFAC enabled bi-directional AC-AC converter is presented in this paper. HFAC PDSs are gaining traction in critical applications within outer space, aerospace and ground transportation PDSs as well as in renewable energy systems due to their advantages of being light deadweight, high power density, smaller capacitors and low arc-flash fault risk etc. Due to prominent adverse factors such as high impedance due to skin effect etc., the grid parameters (frequency, voltage etc.) selected for HFAC PDSs vary depending on the PDS length and power rating. Many of the electrical appliances available today cannot be cross matched and used in PDSs with other parameters, therefore the use of power converters as interfacing devices has been recommended. Currently there are only a few types of HFAC converters available in the market; out of which a majority uses resonant filters for sinewave generation whereas the remainder generates non-sinusoidal waveforms requiring complex controllers for voltage and frequency regulation along the PDS. The proposed two-stage symmetrical topology converter with low-pass filters provide the operation flexibility within a band of voltages and frequencies. The stage-1 H-bridge is PWM switched to boost the DC link voltage, whereas the stage-2 H-bridge is SPWM switched followed by the lowpass filter to generate sinewave output. The two separate PWM controllers used are implemented on a single microcontroller board and swapped for bidirectional operation. Therefore, the new bi-directional converter could be used in multiple applications; thus, supports mass production leading to availability in abundance at low cost.
Ferrari, A, Spoletini, P, Donati, B, Zowghi, D & Gnesi, S 1970, 'Interview Review: Detecting Latent Ambiguities to Improve the Requirements Elicitation Process', 2017 IEEE 25th International Requirements Engineering Conference (RE), 2017 IEEE 25th International Requirements Engineering Conference (RE), IEEE, Lisbon, pp. 400-405.
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The review of software process artifacts, which include requirements as well as source code [1], is an effective practice to improve the quality of products [2]–[3][4][5]. In particular, the benefits of requirements reviews have been highlighted by several studies, especially for what concerns the identification of defects in requirements specifications [3], [6], [7]. Nevertheless, despite the usage of requirements reviews dates back at least 40 years [6], challenges exist for their widespread application in the software industry [8], [9]. Among the challenges, Salger highlights that “Software requirements are based on flawed ‘upstream’ requirements and reviews on requirements specifications are thus in vain” [8]. This observation poses an emphasis on the need to ameliorate early requirements elicitation activities, especially to improve the completeness of the specifications, a quality attribute that is recognised to be hard to assess by means of reviews [10].
Figgemeier, E, Wells, L, Becker, L & Sick, N 1970, 'Implications of Cycle Stability of Silicon Alloy Anodes on Driving Range, Costs and Business Models of Electric Vehicles', Batteries Event 2017, Nice, France.
Fisher, KE, Talhouk, R, Yefimova, K, Al-Shahrabi, D, Yafi, E, Ewald, S & Comber, R 1970, 'Za'atari Refugee Cookbook', Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, CHI '17: CHI Conference on Human Factors in Computing Systems, ACM, pp. 2576-2583.
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Forouzesh, M, Shen, Y, Yari, K, Siwakoti, Y, Blaabjerg, F & Wang, H 1970, 'A new soft-switched high step-up DC-DC converter with dual coupled inductors', 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS), 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS), IEEE, Honolulu, HI, USA, pp. 863-868.
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© 2017 IEEE. This paper introduces a new efficient high step-up DC-DC converter with a shared input path and dual series coupled inductors at the output. This converter is suitable for high power applications due to its shared input current that puts low current stresses on the low voltage side switches. The proposed converter uses active clamp circuits with a shared clamp capacitor for main switches. In addition to the active clamp circuit, the leakage energy is recycled to the output by the act of an integrated regenerative snubber. Both active and passive switching devices operate with soft-switching performance i.e. Zero Voltage Switching (ZVS) and Zero Current Switching (ZCS). Principle of operation and mathematical derivation are presented and verified through simulation and experimental results of a 1kW prototype.
Frawley, JK & Burdon, SW 1970, 'How technology companies are revitalizing Management by Values for innovation', http://ispim.org/vienna_/ISPIM_Vienna_Proceedings/index.html, The XXVIII ISPIM Innovation Conference 2017, LUT Scientific and Expertise Publications–Reports, Vienna, Austria.
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Despite their prevalence, little is understood about the role of organizational values within the high technology sector. This paper extends the authors‟ existing research on management by values (MBV) as a pathway to fostering innovation culture. This empirical mixed-methods approach analyses three industry narratives on innovation culture and the value statements of twenty-four listed technology companies. Values are thematically coded in Nvivo and quantitative and categorical metadata also recorded. This study provides one of the first empirical studies of value statements within the high-tech sector. Findings from this research highlight the re-emergence of MBV as a key prerequisite for creating an innovation culture and changing the focus of these values more strongly to reflect the attitudes and actions required to establish an innovation culture. The paper concludes with a model of the conditions and properties needed to establish innovation culture through an MBV approach.
Fu, LB, Shi, BY, Jin, DY & Chung, R 1970, 'Versatile upconversion surfaces evaluation platform for bio-nano surface selection for nervous system', 2017 IEEE 17th International Conference on Nanotechnology (IEEE-NANO), 2017 IEEE 17th International Conference on Nanotechnology (IEEE-NANO), IEEE, Pittsburgh, PA, USA, pp. 932-933.
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© 2017 IEEE. Neurodegenerative disorder diseases have been perplexing physicians and scientists for many years. There is considerable interest in developing diagnostic nanotools for diagnosis and therapeutic treatment strategies for the neuron diseases. However, a key challenge remains in selection of suitable surface to overcome the nano-bio interface issue as many nanoparticles indicate instability when administered into biological environments and show serious cytotoxicity to sensitive central nervous system. We have developed new-generation upconversion nanoparticles (UCNPs) which represent a promising model nanoparticle for suitable evaluation due to its superior properties in bio photonics.
Fu, Z, Li, H, Jiang, Z, Ni, W & Zhang, Y 1970, 'Design of a strategy for UAV to avoid obstacle and its verification in VR', 2017 IEEE 7TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), IEEE, HI, Honolulu, pp. 1015-1020.
Furukawa, T, Kang, C, Li, B & Dissanayake, G 1970, 'Multi-stage Bayesian target estimation by UAV using fisheye lens camera and pan/tilt camera', 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver, BC, Canada, pp. 4167-4172.
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© 2017 IEEE. This paper presents a generalized multi-stage Bayesian approach for an unmanned aerial vehicle to estimate the location of a mobile target. The major hardware components of the proposed approach are a camera with a fisheye lens and another camera with a normal lens and a pan/tilt unit. With wide angle of view (AOV), the fisheye lens camera first detects the bearing of the target, and the PT camera next captures the target in its AOV. The recursive Bayesian estimation steadily locates the target in a globally defined space. The paper also proposes a multi-stage detection method for the fisheye lens camera. The level of confidence is defined in association with the probability of detection (POD) for each detection technique, and the fisheye lens enables continuous detection by gradually increasing the POD. The observation likelihood is finally derived from the POD in a generalized manner. The proposed approach was applied to the detection of a mobile target by a multi-rotor helicopter, and results have demonstrated the effectiveness of both the proposed multi-stage Bayesian approach and multi-stage fisheye lens detection method.
Gadalla, B, Schaltz, E, Siwakoti, Y & Blaabjerg, F 1970, 'Loss distribution and thermal behaviour of the Y-source converter for a wide power and voltage range', 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), IEEE, Kaohsiung, Taiwan, pp. 878-883.
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© 2017 IEEE. The Y-source converter is one of the recent proposed impedance source converters. It has some advantages as having a high voltage gain between the input and output voltage sides using very small duty cycle ratios. For many applications, the input voltage needs to be boosted to higher output voltage, such as for fuel cell, battery electric vehicles and renewable energy applications. Understanding the loss distribution and thermal performance is very important in order to be able to design a reliable converter with longer lifetime. In this paper, the loss distribution of a Y-source converter for a wide voltage and power range is presented. The influence of the heat losses generated in the converter is also considered for different analysis. A simulation model is developed and verified experimentally rated at 300 W.
Gallagher, S, Sixsmith, A, Leveaux, R & Simpson, H 1970, 'Transitioning the classroom: The shift towards blended and flipped learning', Proceedings of the 30th International Business Information Management Association Conference, IBIMA 2017 - Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth, International Business Information Management Association Conference,, Madrid, Spain, pp. 4581-4592.
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The predominant focus of eLearning information systems remains distance delivery and the blending of this distance education within the classroom. Comparatively, little work has been (or is being) undertaken to advance the use of technologies (eLearning) within the ‘classroom only’ situation as eLearning is not solely for distance education. Designing effective technologically founded, educational learning that addresses the specific needs of class-based tertiary teaching is the main contribution of this article. Having online content that actively engages students both inside and outside the classroom can only occur following the critical evaluation of the modes of content selection and delivery. Furthermore, perfecting facilitator choices into the future about what technology and content used in which capacity, including whether it is online or face-to-face, would inevitably be valuable to both the learner and the teacher.
Gao, F, Musial, K & Gabrys, B 1970, 'A Community Bridge Boosting Social Network Link Prediction Model', Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, ASONAM '17: Advances in Social Networks Analysis and Mining 2017, ACM, pp. 683-689.
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Link prediction in social networks is a very challenging research problem. The majority of existing approaches are based on the assumption that a given network evolves following a single phenomenon, e.g.”rich get richer” or”friend of my friend is my friend”. However, dynamics of network dynamic changes over time and different parts of the network evolve in different manner. Because of that, we hypothesise that the prediction accuracy can be improved by providing different treatment to different nodes and links. Building on that assumption, we propose a Community Bridge Boosting Prediction Model (CBBPM) that treats certain bridge nodes differently depending on their structural position. For such bridge nodes their similarity score obtained using traditional link-based prediction methods is boosted. By doing so the importance of these nodes is increased and at the same time ensuring that the CBBPM can be used with any existing link prediction method. Our experimental results show that such bridge node similarity boosting mechanism can improve the accuracy of traditional link prediction methods.
Gao, X, Du, J, Zhang, T & Guo, YJ 1970, 'Design of a monolithic-integrated circularly-polarized antenna-coupled high-T<inf>c</inf> superconducting terahertz harmonic mixer', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Verona, ITALY, pp. 324-325.
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Gautam, S, Lu, DD-C, Lu, Y & Xiao, W 1970, 'Fast identification of active and reactive current component for single phase grid interconnection', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Single phase grid connected converters in Photo-voltaic(PV) and Electric Vehicles(EV) are finding their application in reactive power support to grid. A power feedback is generally integrated in the control loop for this purpose. Fast and accurate calculation of active and reactive power of the converter is necessary for swift response of controller in regulating output power. This also prevents converter from being overloaded. This paper presents a fast and simple technique to measure the active and reactive power component utilizing wave-shape similarity of sine and cosine function. The performance of the proposed method is compared with dq transformation based approach. The discussions and simulations show superiority of the proposed method in dynamics and implementation.
Gay, V, Favre, V & Brandelong, S 1970, 'Water Aerobics Exercises, a Way to Move Again for Senior Patients With Haemophilia', HAEMOPHILIA, WILEY-BLACKWELL, pp. 136-136.
Ghamry, AM, Alkalbani, AM, Tran, V, Tsai, Y-C, Hoang, ML & Hussain, FK 1970, 'Towards a Public Cloud Services Registry', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 18th International Conference Web Information Systems Engineering, Springer International Publishing, Puschino, Russia, pp. 290-295.
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© 2017, Springer International Publishing AG. Cloud services registry is a cloud services datadase which contains thousands of records of cloud consumers’ reviews and cloud services, such as Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). The data set is harvested from a web portal called www.serchen.com. Each record holds detail information about the service such as service name, service description, categories, key features, service provider link and review list. Each review contains reviewer name, review date and review content. This work is an extension of our previous work Blue Pages data set [6]. The data set is valuable for future research in cloud service identification, discovery, comparison and selection.
Ghantous, GB & Gill, AQ 1970, 'DevOps: Concepts, practices, tools, benefits and challenges', Proceedings ot the 21st Pacific Asia Conference on Information Systems: ''Societal Transformation Through IS/IT'', PACIS 2017, PACIS2017, AIS Electronic Library (AISeL), Malaysia.
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DevOps, originated in the context of agile software development, seems an appropriate approach to enable the continuous delivery and deployment of working software in small releases. Organizations are taking significant interest in adopting DevOps ways of working. The interest is there, however the challenge is how to effectively adopt DevOps in practice? Before disembarking on the journey of DevOps, there is a need to clearly understand the DevOps concepts, practice, tools, benefits and underlying challenges. Thus, in order to address the research question in hand, this paper adopts a Systematic Literature Review (SLR) approach to identify, review and synthesize the relevant studies published in public domain between: 2010-2016. SLR approach was applied to initially identify a set of 450 papers. Finally, 30 of 450 relevant papers were selected and reviewed to identify the eight key DevOps concepts, twenty practices, and a twelve categories tools. The research also identified seventeen benefits of using DevOps approach for application development and encountered four known challenges. The results of this review will serve as a knowledge base for researchers and practitioners, which can be used to effectively understand and establish the integrated DevOps capability in the local context.
Gharehchaei, M, Akbarnezhad, A, Lazenby, H, Castel, A, Lloyd, R & Foster, SJ 1970, 'Precision of existing hydration heat models for Portland cement in capturing the effects of supplementary cementitious materials and retarders', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, pp. 1853-1858.
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A great deal of effort has been made in previous studies to develop numerical simulation models to predict the risk of early age thermal cracking in concrete. A major input to such models, which significantly affects the temperature rise predictions and thus, the results of the analysis, is the hydration heat estimate. The precision of hydration heat estimation models for different cement compositions has been extensively verified in previous studies. However, little has been done to investigate the accuracy of such models for concrete mixes containing supplementary cementitious materials and retarders, which are commonly used in practice to minimize the risk of thermal cracking. In this paper, the results of an experimental study conducted to evaluate the capability of existing hydration heat prediction models in capturing the effects of Supplementary Cementitious Materials (SCMs) and retarders on hydration heat of general purpose Portland cement are presented. The effects of addition of various amounts of Class F Fly ash, Ground Granulated Blast Furnace Slag (GGBFS), as well as a number of common retarders including Citrate, Retardant N (Sika) and Sucrose on the hydration heat profile of cement over a period of six days was investigated using a TAM Air isothermal calorimeter. Comparing the experimental results and predictions of existing hydration heat models reveals the possibility of considerable errors in estimating the hydration heat and, thus the risk of early age thermal cracking, for concrete mixes containing SCMs and retarders.
Ghavidel, S, Azizivahed, A, Barani, M, Aghaei, J, Li, L & Zhang, J 1970, 'Static Var Compensator allocation considering transient stability, voltage profile and losses', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The purpose of this paper is to determine the optimal location, size and controller parameters of Static Var Compensator (SVC) to simultaneously improve static and dynamic objectives in a power system. Four goals are considered in this paper including transient stability, voltage profile, SVC investment cost and power loss reduction. Along with the SVC allocation for improving the system transient stability, an additional controller is used and adjusted to improve the SVC performance. Also, an estimated annual load profile including three load levels is utilized to accurately find the optimal location and capacity of SVC. By considering three load levels, the cost of power losses in the power system is decreased significantly. The combination of the active power loss cost and SVC investment cost is considered as a single objective to obtain an accurate and practical solution, while the improvement of transient stability and voltage profile of the system are considered as two separate objectives. The problem is therefore formulated as a multi-objective optimization problem, and Multi Objective Particle Swarm Optimization (MOPSO) algorithm is utilized to find the best solutions. The suggested technique is verified on a 10-generator 39-bus New England test system. The results of the nonlinear simulation indicate that the optimal sizing, location and controller parameters setting of SVC can improve significantly both static and dynamic performance of the system.
Ghavidel, S, Barani, M, Azizivahed, A, Ghadi, MJ, Li, L & Zhang, J 1970, 'Hybrid power plant offering strategy to deal with the stochastic nature and outage of wind generators', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The stochastic nature of wind power generators and their possible outage are crucial issues which make them difficult to participate in electricity markets. However, demand side as a decent balancing resource can be used to compensate the challenges of lack of supply-demand balance or state of outage for wind generators. This paper firstly models the outage of wind generators. Then an offering strategy with a three-stage stochastic programming is presented for a hybrid power plant which includes a wind power producer and a demand response provider. Three electricity markets are considered including day-ahead, adjustment and balancing market. The conditional value-at-risk is also added to the offering strategy to control the profit risk. The offering strategy is tested in a wind farm and electricity market located in Spain. The result shows that the hybrid power plant offering strategy can effectively assist with the balancing and outage problem of the wind power producer and increase the overall profit of the joint operation.
Ghavidel, S, Ghadi, MJ, Azizivahed, A, Barani, M, Aghaei, J, Li, L & Zhang, J 1970, 'Hybrid power plant bidding strategy including a commercial compressed air energy storage aggregator and a wind power producer', 2017 Australasian Universities Power Engineering Conference (AUPEC), 2017 Australasian Universities Power Engineering Conference (AUPEC), IEEE, Melbourne, AUSTRALIA, pp. 1-6.
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© 2017 IEEE. In this paper, a commercial compressed air energy storage (CAES) aggregator equipped with a simple cycle mode operation having the ability to work like a gas turbine is coordinated with a wind power aggregator (WPA) as a hybrid power plant to participate in electricity markets. In the proposed approach, the WPA uses the CAES to tackle its stochastic input and uncertainties related to different electricity market prices, and CAES can also use WPA to manage its charging/discharging and simple cycle modes more economically. A three-stage stochastic decision-making method is used to model the mentioned optimization problem which considers three electricity markets including day-ahead, intraday and balancing markets. The problem is formulated as a mixed integer linear programming which can be solved with available commercial solvers. Also, conditional value-at-risk is added to the problem to control the financial risk of the problem and offer different operation strategies for different financials risk levels. The proposed method can provide both bidding quantity and bidding curves to be submitted to the electricity markets which is tested on a realistic case study based on a wind farm and electricity market located in Spain. The results confirm that the proposed method can provide extra profit in joint operation, have more flexibility and reduce the financial risks.
Ghorbani, S, Razavi Bazaz, S, Ebrahimi Warkiani, M, Soleimani, M & Abouei Mehrizi, A 1970, 'Evaluation of Nanofiber PLA Scaffolds Using Dry-and Wet-Electro Spinning Methods', 2017 24th National and 2nd International Iranian Conference on Biomedical Engineering (ICBME), 2017 24th National and 2nd International Iranian Conference on Biomedical Engineering (ICBME), IEEE, Tehran, IRAN, pp. 1-6.
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© 2017 IEEE. Investigating the fabrication of a favorable scaffold is a continuing sconcern and an essential step within tissue engineering. An ideal scaffold should mimic the structure of extracellular matrix (ECM) which has considerable impacts on its function. To meet this demands, in this study, three-dimensional scaffolds by polylactic acid (PLA) polymer 10%, 13%, 15%, 17% and 20% (w/v) with a novel architecture produced by a wet-electrospinning process have been fabricated and compared with dry-electrospun scaffolds that have been developed for tissue engineering applications. In the wet-electrospinning method, an aqueous solution of sodium hydroxide (NaOH) (pH∼13) has been used as the coagulation bath instead of the aluminum collector which is used in the dry method. Comparing with usual nanofiber non-woven PLA fabric prepared by a conventional electrospinning method, wet-electrospun spongiform PLA nanofiber scaffolds have low apparent density and high porosity. The porosity of the scaffolds has been examined in this two methods and their mechanical properties as well as their morphology are investigated. All in all, it is shown that the novel nanofiber fabrication system would be amazingly useful for the structure control of the nanofiber fabric.
Ghosh, S & Lee, JE-Y 1970, 'A lorentz force magnetometer based on a piezoelectric-on-silicon radial-contour mode disk', 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), IEEE, pp. 830-833.
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Ghosh, S & Lee, JE-Y 1970, 'An ultra-sensitive piezoelectric-on-silicon flapping mode MEMS lateral field magnetometer', 2017 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium (EFTF/IFC), 2017 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium ((EFTF/IFC), IEEE, pp. 502-505.
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Ghosh, S & Lee, JE-Y 1970, 'Resonant tuning fork strain gauge operating in air with decoupled piezoelectric transducers', 2017 IEEE SENSORS, 2017 IEEE SENSORS, IEEE, pp. 1-3.
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Giampietro, C, Chaczko, Z, De La Villefromoy, M & Braun, R 1970, 'A new strategy for higher education and training: Peer support system for practical laboratories', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-4.
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© 2017 IEEE. One of the many challenges facing practical student workshops is the proliferation of rapid prototyping and similar technologies. 3D printers have enabled students to take ideas and concepts further than ever before and sometimes to completion. The only limitations at this stage are the materials available for the manufacture of components and prototypes on 3D printers. Traditional manufacturing processes like fabrication and machining are still sometimes required to complete projects. This has seen a greater demand and workload for traditional machine shops and trades people. Some of the manufacturing work has to still be completed by skilled experienced trade's people but some of the simpler less complex machining and fabrication tasks could be easily completed by unskilled students with basic training and minimal supervision. We needed to come up with a system that provided students access to industrial fabrication and machining equipment in a safe and productive environment. The peer support system provides a framework enabling students with little or no machine operating skills to safely access industrial equipment with minimal staff, supervision and danger of injury. This paper is a justification of these concepts, interest, approaches, and practices of the peers support framework and philosophy.
Gill, AQ, Behbood, V, Ramadan-Jradi, R & Beydoun, G 1970, 'IoT architectural concerns: a systematic review.', ICC, International Conference on Internet of things and Cloud Computing, ACM, Cambridge, United Kingdom, pp. 117:1-117:1.
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© 2017 ACM. There is increasing interest in studying and applying Internet of Things (IoT) within the overall context of digital-physical ecosystems. Most recently, much has been published on the benefits and applications of IoT. The main question is: what are the key IoT architectural concerns, which must be addressed to effectively develop and implement an IoT architecture? There is a need to systematically review and synthesize the literature on IoT architectural challenges or concerns. Using the SLR approach and applying customised search criteria derived from the research question, 22 relevant studies were identified and reviewed in this paper. The data from these papers were extracted to identify the IoT architectural challenges and relevant solutions. These results were organised into to 9 major challenge and 7 solution categories. The results of this research will serve as a resource for practitioners and researchers for the effective adoption, and setting future research priorities and directions in this emerging area of IoT architecture.
Gineste, M, Deleu, T, Cohen, M, Chuberre, N, Saravanan, V, Frascolla, V, Mueck, M, Strinati, EC & Dutkiewicz, E 1970, 'Narrowband IoT Service Provision to 5G User Equipment via a Satellite Component', 2017 IEEE Globecom Workshops (GC Wkshps), 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, Singapore, SINGAPORE, pp. 1-4.
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© 2017 IEEE. Today an estimated 15 billion of connected objects communicate with each other's. These connected objects that compose the Internet of Things (IoT) are expected to extend to 50 or 80 billion worldwide by 2020. Bringing wide-area connectivity for the IoT using satellite technology is therefore an attractive solution to complement terrestrial networks, allowing densification and coverage extension in remote areas. This paper deals with seamless integration of satellites and high altitude platforms (HAPS) into 5G networks. It describes the necessary modifications to operate on 5G systems in order to take satellite and HAPS specifics into account. Link budget calculations and system dimensioning, including channel modeling, are provided to determine the required satellite and HAPS performance as well as to estimate the number of served users per km.
Goldsmith, R & Willey, K 1970, 'Using practice architectures to investigate the invisibility of writing practices in the engineering curriculum', 2017 IEEE Frontiers in Education Conference (FIE), 2017 IEEE Frontiers in Education Conference (FIE), IEEE, Indianapolis, IN, USA, pp. 1-6.
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© 2017 IEEE. Written communication is neither systematically developed nor practised in the engineering curriculum, despite expectations by universities and employers that engineering graduates will be proficient communicators, and despite interventions to develop students' writing. The gap in the development of students' written communication calls for an investigation into the continuing invisibility of writing practices in the engineering curriculum. The lens of practice architectures theory was used to explore how engineering academics view writing in their engineering subjects, and how they develop the writing practices of their students. Practice architectures theory sees practices as shaped by and shaping cultural-discursive, material-economic, and social-political arrangements. A qualitative study examined engineering academics' teaching practices and the extent to which writing is practised and developed within the subjects they teach. Results show the majority of engineering academics in this study view writing as separate from technical engineering knowledge. This impacts the prevailing teaching and assessment practices by not providing opportunities for writing to be practised and developed within the context of engineering education. Unless there is conscious inclusion of writing practices, prevailing teaching and assessment practices will continue to focus on the acquisition of propositional knowledge to the exclusion of the development of writing practices.
Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 1970, 'Red-Edge indices to diagnose orange spotting disease of oil palm in Malaysia', 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, Asian Conference on Remote Sensing, New Delhi, India.
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The use of hyperspectral remote sensing techniques for plant disease diagnosis is gaining much prominence due to its non-destructive feature. The steep gradient in reflectance between visible and near-infrared region is known as the red-edge, which is located between 680 and 780 nm. Red-edge is a stress diagnostic indicator that provides for non-destructive diagnosis of plant disease. This paper investigates the potential of two selected red-edge wavebands (680 nm and 754 nm) in diagnosing Orange Spotting (OS) disease of oil palm. OS is a fast emerging disease in Malaysian oil palm plantations. Coconut cadang-cadang viroid (CCCVd) is the causal agent of OS disease. Four well-known red-edge indices namely Ratio Vegetation Index (RVI), Red Edge Position (REP), Normalized Difference Red Edge Index (NDREI) and Chlorophyll Index (CI) were evaluated using selected wavebands. A spectroradiometer (Model: ASD FieldSpec® HandHeld 2), which operates in the spectral range of 325-1075 nm, was deployed to measure leaf reflectance of fifteen inoculated and five healthy oil palm seedlings grown under glasshouse conditions. A highly infective CCCVd variant, OP246, was used to inoculate the seedlings. Reflectance was measured at 15, 30, 45 and 60 days after inoculation. This work was aimed at investigation of variations on red-edge indices within the specific intervals of inoculation. Red-edge indices were calculated from inoculated and healthy seedlings and analyzed using one-way analysis of variance. Mean differences were interpreted at 0.05 significance level using Latin Square design. REP was selected as best red-edge index as multiple comparison of means values for healthy and inoculated seedlings were significantly different at 95% confidence level at all intervals.
Gordon, LC & Chaczko, Z 1970, 'Ontological Metamodel for Consistency of Data Heritage Preservation (DHP)', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 438-442.
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© 2017 IEEE. In this stage of Data Preservation the challenge is how to keep the attributes of the data and how to preserve the originality. It is like to keep the living part of the data. It is how the concepts of Heritage have sense. Heritage is the concrete data, it gives the interconnection to other aspects of the reality. Nowadays the physical value and the aspects of items complete the relevance of information. The relation between Preservation and Digital patterns of Heritage is well related because of the two aspects to consider: Accessibility and Context.
Gorji, SA, Mostaan, A, Ektesabi, M & Lu, D 1970, 'A novel bridgeless flyback power factor correction rectifier with single output winding and reduced components voltage stress', 2017 19th European Conference on Power Electronics and Applications (EPE'17 ECCE Europe), 2017 19th European Conference on Power Electronics and Applications (EPE'17 ECCE Europe), IEEE, Warsaw, Poland, pp. P.1-P.9.
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© 2017 Assigned jointly to the European Power Electronics and Drives Association & the Institute of Electrical and Electronics Engineers (IEEE). In this paper, a novel bridgeless Flyback power factor correction rectifier is presented. Two active power switches, rather than the line-voltage diode bridge, are used to provide the bidirectional power flow. In comparison with the existing Flyback rectifiers, the proposed topology uses less number of transformer windings which simplifies the complexity of implementation in terms of magnetic utilization. Besides, the voltage stress on the output diodes and capacitors is reduced. After carrying out a detailed theoretical analysis, performance of the proposed converter was verified by simulations and experiments. The experimental tests on a 110 V to 48 V, 50W prototype reveal that an average efficiency at 90% and a high power factor can be achieved.
Gu, L, Wang, K, Liu, X, Guo, S & Liu, B 1970, 'A reliable task assignment strategy for spatial crowdsourcing in big data environment', 2017 IEEE International Conference on Communications (ICC), ICC 2017 - 2017 IEEE International Conference on Communications, IEEE, pp. 1-6.
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© 2017 IEEE. With the ubiquitous deployment of the mobile devices with increasingly better communication and computation capabilities, an emerging model called spatial crowdsourcing is proposed to solve the problem of unstructured big data by publishing location-based tasks to participating workers. However, massive spatial data generated by spatial crowdsourcing entails a critical challenge that the system has to guarantee quality control of crowdsourcing. This paper first studies a practical problem of task assignment, namely reliability aware spatial crowdsourcing (RA-SC), which takes the constrained tasks and numerous dynamic workers into consideration. Specifically, the worker confidence is introduced to reflect the completion reliability of the assigned task. Our RA-SC problem is to perform task assignments such that the reliability under budget constraints is maximized. Then, we reveal the typical property of the proposed problem, and design an effective strategy to achieve a high reliability of the task assignment. Besides the theoretical analysis, extensive experimental results also demonstrate that the proposed strategy is stable and effective for spatial crowdsourcing.
Gu, S, Lu, Y, Zhang, L & Zhang, J 1970, 'RGB-D Tracking Based on Kernelized Correlation Filter with Deep Features', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information ProcessingConference on Neural Information Processingtional Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 105-113.
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© 2017, Springer International Publishing AG. This paper proposes a new RGB-D tracker which is upon Kernelized Correlation Filter(KCF) with deep features. KCF is a high-speed target tracker. However, the HOG feature used in KCF shows some weaknesses, such as not robust to noise. Therefore, we consider using RGB-D deep features in KCF, which refer to deep features of RGB and depth images and the deep features contain abundant and discriminated information for tracking. The mixture of deep features highly improves the performance of the tracker. Besides, KCF is sensitive to scale variations while depth images benefit for handling this problem. According to the principle of similar triangle, the ratio of scale variation can be observed simply. Tested over Princeton RGB-D Tracking Benchmark, Our RGB-D tracker achieves the highest accuracy when no occlusion happens. Meanwhile, we keep the high-speed tracking even if deep features are calculated during tracking and the average speed is 10 FPS.
Guan, D, Ding, C & Guo, YJ 1970, 'A compact multi-beam antenna without beam forming network', ISAP 2016 - International Symposium on Antennas and Propagation, International Symposium on Antennas and Propagation (ISAP), IEEE, Okinawa, Japan, pp. 404-405.
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A novel approach to design a multi-beam array antenna without a beam forming network (BFN) is presented. The proposed antenna consists of 3×3 microstrip patches that are tightly coupled through microstrip lines. By exciting any one of these patches, the energy can be coupled to all the patches. Nine beams towards different directions are obtained by selecting different feeding ports. The resultant gain varies from 10 dBi to 11 dBi. The scanning ranges of the beams are ±24° and ±45° in the elevation and horizontal directions, respectively. The proposed antenna has a single-layered structure without complex feeding network, which significantly lowers its cost.
Guertler, MR, Kriz, A, McGregor, C, Bankins, S & Bucolo, S 1970, '“And Action!” – Rigour Meets Relevance in Action Innovation Management (AIM)', ISPIM, The XXVIII ISPIM Innovation Conference, Vienna, Austria, pp. 1-1.
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Innovation management comprises a complex interplay of various actors and processes within a socio-technical quadruple-helix. Traditional research approaches often struggle to manage this complexity and risk irrelevance and “so what results”. Use of merely mono-disciplinary methods forces researchers to choose between research depth and breadth. This results in isolated views and missing links between phenomena. Action Research (AR) represents interdisciplinary research, in collaboration with industry clients in real world settings. AR combines and extends scientific knowledge and theory development through client-researcher practical problem solving and competence building. This paper discusses benefits and challenges of AR in innovation management and presents an “Action Innovation Management (AIM)” process-model to encourage purposeful application of AR within the domain of innovation management. Along with supporting the use of AR, the goal is to foster scientific discussion of how AIM can still achieve “good science” with twin benefits of rigour and relevance.
Guertler, MR, O'Donnell, M & MacCarthy, A 1970, 'Enabling Open Innovation in Defence through design-thinking', yes, The ISPIM Innovation Summit – Building the Innovation Century, ISPIM, Melbourne, pp. 1-19.
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Open Innovation (OI) has gained increasing popularity and application in varies areas. However, there have still been areas with only limited OI application, which have been traditionally considered as “closed” such as Defence. Due to changing governmental agendas, Defence – in particular the Australian Defence Forces – sees an increasing benefit to opening up and engaging more fully with external partners. As part of a larger research program, this paper presents a pilot project, which explores the application of OI in the context of procurement in Defence. In this respect, it particularly analyses the role of design-thinking as an enabler for collaboration between actors from different disciplines, for building a mutual understanding and co-creating a novel solution. Our results prove the successful application of OI in Defence, and the enabling role of design-thinking on an operational problem solving level as well as on a strategic level to achieve a sustainable organisational change in Defence.
Gunawardane, K, Xie, S & Kularatna, N 1970, 'Back-to-back MOSFET switches to reduce the losses in SCALDO implementation', 2017 IEEE International Conference on Industrial Technology (ICIT), 2017 IEEE International Conference on Industrial Technology (ICIT), IEEE, pp. 54-59.
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Guo, J, Yuan, J & Zhang, JA 1970, 'Wireless Device-to-Device Caching Networks with Distributed MIMO and Hierarchical Cooperations', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. In this paper, we propose a new caching scheme for a random wireless device-to-device (D2D) network of n nodes with local caches, where each node intends to download files from a prefixed library via D2D links. Our proposed caching delivery includes two stages, employing distributed MIMO and hierarchical cooperations respectively. The distributed MIMO is applied to the first stage between source nodes and neighbours of the destination node. The induced multiplexing gain and diversity gain increase the number of simultaneous transmissions, improving the throughput of the network. The hierarchical cooperations are applied to the second stage to facilitate the transmissions between the destination node and its neighbours. The two stages together exploit spatial degrees of freedom as well as spatial reuse. We develop an uncoded random caching placement strategy to serve this cooperative caching delivery. Analytical results show that the average aggregate throughput of the network scales almost linearly with n, with a vanishing outage probability.
Guo, J, Yue, B, Xu, G, Yang, Z & Wei, J-M 1970, 'An Enhanced Convolutional Neural Network Model for Answer Selection', Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion, the 26th International Conference, ACM Press, Perth, Western Australia, pp. 789-790.
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Answer selection is an important task in question answering (QA) from the Web. To address the intrinsic difficulty in encoding sentences with semantic meanings, we introduce a general framework, i.e., Lexical Semantic Feature based Skip Convolution Neural Network (LSF-SCNN), with several op- timization strategies. The intuitive idea is that the granular representations with more semantic features of sentences are deliberately designed and estimated to capture the similar- ity between question-answer pairwise sentences. The experi- mental results demonstrate the effectiveness of the proposed strategies and our model outperforms the state-of-the-art ones by up to 3.5% on the metrics of MAP and MRR.
Guo, K, Candra, H, Yu, H, Li, H, Nguyen, HT & Su, SW 1970, 'EEG-based emotion classification using innovative features and combined SVM and HMM classifier', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 489-492.
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Emotion classification is one of the state-of-theart
topics in biomedical signal research, and yet a significant
portion remains unknown. This paper offers a novel approach
with a combined classifier to recognise human emotion states
based on electroencephalogram (EEG) signal. The objective is
to achieve high accuracy using the combined classifier designed,
which categorises the extracted features calculated from time
domain features and Discrete Wavelet Transform (DWT). Two
innovative designs are involved in this project: a novel variable
is established as a new feature and a combined SVM and
HMM classifier is developed. The result shows that the joined
features raise the accuracy by 5% on valence axis and 1.5% on
arousal axis. The combined classifier can improve the accuracy
by 3% comparing with SVM classifier. One of the important
applications for high accuracy emotion classification system is
offering a powerful tool for psychologists to diagnose emotion
related mental diseases and the system developed in this project
has the potential to serve such purpose.
Guo, YJ & Qin, P-Y 1970, 'Single-layer reflectarrays — Past, present and future', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, France, France, pp. 92-94.
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© 2017 IEEE. This paper presents an overview of the advances in single layer reflectarrays. In particular, it reports the progress in wideband reflectarrays and reconfigurable reflectarrays.
Gupta, D, Borah, P & Prasad, M 1970, 'A fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM)', 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Honolulu, HI, USA, pp. 1-7.
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© 2017 IEEE. In the spirit of twin parametric-margin support vector machine (TPMSVM) and support vector machine based on fuzzy membership values (FSVM), a new method termed as fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM) is proposed in this paper to reduce the effect of the outliers. In FLTPMSVM, we assign the weights to each data samples on the basis of fuzzy membership values to reduce the effect of outliers. Also, we consider the square of the 2-norm of slack variables to make the objective function strongly convex and find the solution of the proposed FLTPMSVM by solving simple linearly convergent iterative schemes instead of solving a pair of quadratic programming problems as in case of SVM, TWSVM, FTSVM and TPMSVM. No need of external toolbox is required for FLTPMSVM. The numerical experiments are performed on artificial as well as well known real-world datasets which show that our proposed FLTPMSVM is having better generalization performance and less training cost in comparison to support vector machine, twin support vector machine, fuzzy twin support vector machine and twin parametric-margin support vector machine.
Ha, TV & Hoang, DB 1970, 'An assistive healthcare platform for both social and service networking for engaging elderly people', 2017 23rd Asia-Pacific Conference on Communications (APCC), 2017 23rd Asia-Pacific Conference on Communications (APCC), IEEE, Perth, Australia, pp. 1-6.
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Most countries around the globe are facing the same issue - an aging population. As an individual move from their working life to a retirement life, multiple socio-economic issues can occur as their social life has also significantly changed. This shift often affects an individual's mental health and well-being. As a result, the aging population requires a solution that does reduce not only its impact on the government but also harvests its contribution to the society. Existing solutions are based on utilizing online platforms such as social network or service network as a medium to reduce social isolation and improve the mental health of elderly people. However, these solutions fail on two accounts: 1) they fail to see older people as active contributors and 2) older people do not see the needs or benefits of using them. This paper proposes a solution that addresses those two issues by engaging people actively and collaboratively as contributors of services and/or receivers of social benefits through an assistive platform that integrates a service network with a social network. This model combines the advantages of both platforms, offers many opportunities for seniors to not only utilize their skills and knowledge to exchange benefits with other users but also expand their social life. The proposed model can be used as a mean to engage older adults to the community, making them become more active, improve their mental well-being and subsequently reduce the cost of health services to the society.
Hadgraft, RG 1970, 'Rethinking Accreditation Criteria to focus on Design', 2017 7th World Engineering Education Forum (WEEF), 2017 7th World Engineering Education Forum (WEEF), IEEE, Malaysia, pp. 802-807.
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© 2017 IEEE. Accreditation criteria in most countries imply that mathematics and science are the key elements of engineering. This tends to support traditional engineering curricula that emphasise lecture-driven topics in engineering science, such as statics, dynamics, materials, circuits, control, and so on, giving students in four year programs little time to really develop engineering problem solving skills for a world of sustainability and complexity. There is a pressing need to redesign engineering curricula around design and problem solving if new engineers are to grapple with complex challenges such as climate change and the need for continuous and relentless innovation. This paper proposes that a good place to start is to reimagine the accreditation criteria for engineering programs.
Hadgraft, RG 1970, 'Transforming engineering education: DESIGN must be the core', Proceedings of the 45th SEFI Annual Conference 2017 - Education Excellence for Sustainability, SEFI 2017, 45th SEFI Annual Conference, Terceira Island, Azores, Portugal, pp. 245-253.
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There have been many reviews of engineering education over the last 15 years, yet most engineering curricula remain traditionally focused on the development of technical outcomes, with a small emphasis on design. This paper reviews many of the international reviews, to seek the common themes that need to be addressed. Examples of new curricula are provided. Although the design of new curricula is difficult enough, it is the implementation of change within our existing academic structures that is really the difficult problem to be solved.
Hadgraft, RG & Jin, X 1970, 'Understanding Engineering Competencies in Practice and the Educational Implications', Proceedings of the 28th Annual Conference of the Australasian Association for Engineering Education, Annual Conference of the Australasian Association for Engineering Education, AAEE, Sydney, Australia.
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Context: Engineering professionals and educators have different interpretations or perspectives on certain engineering competency items, for example, mathematical modelling. The question here is how such differences impact the structuring and interpretation of engineering competencies at the general level. Purpose: This paper responds to the following questions: How can certain engineering competency items be clustered with others? Is there empirical evidence to support such structures? Approach: The research questions stems from a comparative literature review of existing national and international engineering competency standards. Empirical data used in this paper was collected from a small-scale survey. Social Network Analysis (SNA) was used as the method for data analysis - engineering competency mapping. Results: A set of conceptual maps have been made to depict the clustering of 60 engineering competency items identified in a real-life engineering company in China. Conclusions: It is argued that the Social Network Analysis algorithm can be appropriated for the study of engineering competencies. This algorithm provides indicators of identifying relatively 'important' competency items, which create implications for undergraduate engineering practice programs.
Hadgraft, RG, Francis, B, Lawson, J, Jarman, R, Stewart, C, Hsieh, I & Jenkins, G 1970, 'Curriculum transformation with students as partners', Proceedings of the 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), Annual Conference of the Australasian Association for Engineering, Australasian Association for Engineering Education, Manly, Australia, pp. 1-9.
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8732142. That was my student ID as an undergraduate (now one of the authors).It was a number, not a name. It distinguished students from professors and all other teachingstaff and, in a symbolic way, reminded us all of our firm place as students, as learners. Therewas a big power differential between students and teachers in the 1980s. What we learnedwas prescribed, transmitted and tested in implicit ways (no rubrics or marking criteria in thosedays) and rarely were our skills tested – just what we knew and could recall at a given time.Sometimes people say that teaching is an act. Indeed, sage on the stage suggests thisprecisely. But being a student is also an act. Students also assume roles and personas.If we want curriculum transformation, we seek to put a stop to acting – to engage studentsand staff in authentic learning.MIDAS is our curriculum transformation project in the Faculty of Engineering and InformationTechnology (FEIT) at UTS – More Innovative Design-Able Students. In MIDAS, we wantstudents and teachers to be their authentic selves in a true teaching and learningpartnership. MIDAS seeks mutual respect in people, not the fulfilment of roles.MIDAS doesn’t see students as numbers, but as partners, as people who can learn,contribute, inspire, teach and create … and it sees teachers as people who also learn,contribute, inspire, teach and create
Haider, N, Dutkiewicz, E, Nguyen, DN, Mueck, M & Srikanteswarae, S 1970, 'The Impact on Full Duplex D2D Communication of Different LTE Transmission Techniques', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. To augment capacity of spectrum limited cellular systems, 3GPP proposed Licensed Assisted Access (LAA-LTE) while efforts are underway to standardize the standalone MulteFire (a small cell standalone version of LTE). LAA is expected to boost capacity of LTE via unlicensed spectrum (5GHz). On the other hand, recent advances in Self Interference Suppression (SIS) techniques allow radios to transmit and receive simultaneously on the same channel (i.e., in-band Full-Duplex, FD). As part of future wireless networks, Device-to-device (D2D) communications would find its great potential through this FD capability. However, due to high induced aggregate interference from FD and its impact on medium access probability, the rigorous and critical analysis is needed to find an optimum trade-off between performance efficiency and overheads. Using stochastic geometry and the random graph theory, in this article, we analyze the impact of different LTE network paradigms with HD/FD D2D devices. Moreover, the impact of state- of-the-art coexistence techniques (discontinuous transmission and listen-before-talk) recommended for LTE in unlicensed spectrum over HD/FD D2D network is also discussed. The analysis is supported with extensive simulation results that reveal insights of the coexistence mechanism efficiency employed by LTE, the impact of SIS and the cost of FD operation in D2D.
Haider, ST, Al-Kilidar, H & Leveaux, R 1970, 'Critical success factors for quality implementation in the manufacturing industry', Proceedings of the 30th International Business Information Management Association Conference, IBIMA 2017 - Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth, International Business Information Management Association Conference, Spain, pp. 4568-4580.
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Quality directly influences organizational performance in the manufacturing industry. Through an examination of literature, critical success factors that lead to the implementation of six-sigma in the manufacturing industry are identified for organisations of differing sizes: SMEs, large enterprises and general/ unspecified organisations (not specified as either SMEs or Large in literature). It is found that general success factors across organisations (unspecified) include Employee Education/Training, Top Management Commitment, Project Selection, Employee Involvement/Communication, Project Management/Leadership. While for large enterprises the following factors were identified: Project Selection, Alignment with Customer Requirements, Employee Education/Training, Senior Management Commitment, Use of Quality Tools, Visible Cost Saving. The results serve as a guide for a better understanding of the requirements leading to the successful implementation of six-sigma in organizations and where to best direct resources.
Hakami, H & Chaczko, Z 1970, 'Reversible Color Compression Transform for Big Data System Using Human Visual System', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 459-465.
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© 2017 IEEE. In today’s life, images play a significant role in many Big Data application fields for various purposes. Image processing has to face the huge challenges because of images created in a digital format which leads to huge data volumes. Using Joint Photographic Experts Group 2000 (JPEG2000) compression techniques to meet the diverse type of real-time applications. Lossless compression JPEG2000 and others are used to minimize the expenditure of possessions such as hard disk space and transmission bandwidth. This experimental work shows an improved lossless color image compression that uses a wavelet based Human Visual System. This Reversible Color Compression Transform method (RCCT) produces an efficient algorithm to compress the image without loss of information. JPEG2000 as a lossless mode is utilized for bit-preserving and to refer globally for encoding and decoding processes. The Reversible Color Transform (RCT) is used in JPEG 2000 using wavelets which provide a mathematical way to encode the information in such a way that it is layered according to the level of detail by using HVS attributes in the stage of quantization. In this research, the goal of lossless image compression is to decrease the number of bits required to demand computing resources such as store and transmit images without any loss of information.
Han, H, Paul, G & Matsubara, T 1970, 'Model-based reinforcement learning approach for deformable linear object manipulation', 2017 13th IEEE Conference on Automation Science and Engineering (CASE), 2017 13th IEEE Conference on Automation Science and Engineering (CASE 2017), IEEE, Xi'an, China, pp. 750-755.
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© 2017 IEEE. Deformable Linear Object (DLO) manipulation has wide application in industry and in daily life. Conventionally, it is difficult for a robot to manipulate a DLO to achieve the target configuration due to the absence of the universal model that specifies the DLO regardless of the material and environment. Since the state variable of a DLO can be very high dimensional, identifying such a model may require a huge number of samples. Thus, model-based planning of DLO manipulation would be impractical and unreasonable. In this paper, we explore another approach based on reinforcement learning. To this end, our approach is to apply a sample-efficient model-based reinforcement learning method, so-called PILCO [1], to resolve the high dimensional planning problem of DLO manipulation with a reasonable number of samples. To investigate the effectiveness of our approach, we developed an experimental setup with a dual-arm industrial robot and multiple sensors. Then, we conducted experiments to show that our approach is efficient by performing a DLO manipulation task.
Han, J, Wan, S, Lu, J & Zhang, G 1970, 'Tri-level multi-follower decision-making in a partial-cooperative situation', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Nanjing, China, pp. 1-6.
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© 2017 IEEE. Tri-level decision-making addresses compromises between interactive decision entities that are distributed throughout a three-level hierarchy. These decision entities are respectively termed as the top-level leader, the middle-level follower and the bottom-level follower. This paper considers a tri-level multi-follower (TLMF) decision problem where both cooperative and uncooperative relationships coexist between multiple followers at the same level. In this situation, followers share some decision variables with their counterparts and also control individual decision variables to achieve their respective goals; this is also known as partial-cooperative TLMF decision-making. To support this category of decision-making, this paper first presents a linear model to characterize the partial-cooperative TLMF decision-making process. It then develops a vertex enumeration algorithm to obtain a solution to the resulting model. Lastly, we apply the proposed TLMF decision techniques to handle an inventory management problem in applications.
Han, L, Zhang, D, Huang, D, Chang, X, Ren, J, Luo, S & Han, J 1970, 'Self-paced Mixture of Regressions', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, AUSTRALIA, pp. 1816-1822.
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Mixture of regressions (MoR) is the well-established and effective approach to model discontinuous and heterogeneous data in regression problems. Existing MoR approaches assume smooth joint distribution for its good anlaytic properties. However, such assumption makes existing MoR very sensitive to intra-component outliers (the noisy training data residing in certain components) and the inter-component imbalance (the different amounts of training data in different components). In this paper, we make the earliest effort on Self-paced Learning (SPL) in MoR, i.e., Self-paced mixture of regressions (SPMoR) model. We propose a novel self-paced regularizer based on the Exclusive LASSO, which improves inter-component balance of training data. As a robust learning regime, SPL pursues confidence sample reasoning. To demonstrate the effectiveness of SPMoR, we conducted experiments on both the sythetic examples and real-world applications to age estimation and glucose estimation. The results show that SPMoR outperforms the state-of-the-arts methods.
Han, Y, Wan, Y, Chen, L, Xu, G & Wu, J 1970, 'Exploiting Geographical Location for Team Formation in Social Coding Sites', PAKDD 2017: Advances in Knowledge Discovery and Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, Jeju Island, Korea, pp. 499-510.
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© 2017, Springer International Publishing AG. Social coding sites (SCSs) such as GitHub and BitBucket are collaborative platforms where developers from different background (e.g., culture, language, location, skills) form a team to contribute to a shared project collaboratively. One essential task of such collaborative development is how to form a optimal team where each member makes his/her greatest contribution, which may have a great effect on the efficiency of collaboration. To the best of knowledge, all existing related works model the team formation problem as minimizing the communication cost among developers or taking the workload of individuals into account, ignoring the impact of geographical location of each developer. In this paper, we aims to exploit the geographical proximity factor to improve the performance of team formation in social coding sites. Specifically, we incorporate the communication cost and geographical proximity into a unified objective function and propose a genetic algorithm to optimize it. Comprehensive experiments on a real-world dataset (e.g., GitHub) demonstrate the performance of the proposed model with the comparison of some state-of-the-art ones.
Haque, MN, Mathieson, L & Moscato, P 1970, 'A memetic algorithm for community detection by maximising the connected cohesion', 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Honolulu, Hawaii, USA, pp. 1-8.
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© 2017 IEEE. Community detection is an exciting field of research which has attracted the interest of many researchers during the last decade. While many algorithms and heuristics have been proposed to scale existing approaches a relatively smaller number of studies have looked at exploring different measures of quality of the detected community. Recently, a new score called 'cohesion' was introduced in the computing literature. The cohesion score is based comparing the number of triangles in a given group of vertices to the number of triangles only partly in that group. In this contribution, we propose a memetic algorithm that aims to find a subset of the vertices of an undirected graph that maximizes the cohesion score. The associated combinatorial optimisation problem is known to be NP-Hard and we also prove it to be W[1]-hard when parameterized by the score. We used a Local Search individual improvement heuristic to expand the putative solution. Then we removed all vertices from the group which are not a part of any triangle and expand the neighbourhood by adding triangles which have at least two nodes already in the group. Finally we compute the maximum connected component of this group. The highest quality solutions of the memetic algorithm have been obtained for four real-world network scenarios and we compare our results with ground-truth information about the graphs. We also compare the results to those obtained with eight other community detection algorithms via interrater agreement measures. Our results give a new lower bound on the parameterized complexity of this problem and give novel insights on its potential usefulness as a new natural score for community detection.
Harcombe, DM, Ruppert, MG, Ragazzon, MRP & Fleming, AJ 1970, 'Higher-harmonic AFM imaging with a high-bandwidth multifrequency Lyapunov filter', 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), IEEE, pp. 725-730.
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Hashmi, RM & Esselle, KP 1970, 'Aperture field transformation in resonant cavity antennas by transverse permittivity gradient superstrates', 2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), 2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), IEEE, pp. 1-3.
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© 2017 URSI. Single-feed resonant cavity antennas (RCAs) with transverse permittivity gradient (TPG) superstrates exhibit very wideband directivity enhancement. In this paper, we study the transformation of transverse electric field that is achieved by the TPG superstrate. This provides physical insight into the operating principle of such RCAs. Two fictitious apertures are used to record and compare the phase of the field within the cavity of the RCA as well as above its TPG superstrate. It is found that the TPG superstrate significantly reduces the phase variation of the aperture field over most of the operating bandwidth, thus resulting in wideband directive characteristics. Numerical results as well as measurements are presented showing wideband antenna performance with a peak directivity exceeding 16 dBi.
Hayati, H, Eager, D, Brown, T & Jusufi, A 1970, 'STRIDE LENGTH AS A SPEED INDICATOR IN FAST QUADRUPEDS', International Society of Biomechanics, International Society of Biomechanics, Brisbane, Australia.
Hayati, H, Eager, D, Jusufi, A & Brown, T 1970, 'A NOVEL APPROACH TO ANALYZING RAPID TETRAPOD LOCOMOTION USING INERTIAL MEASUREMENT UNITS', International Society of Biomechanics, International Society of Biomechanics, Brisbane, Australia.
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Rapid quadrupedal movement on granular media and other irregular terrain is an interesting area of research which is under-explored. Current methods of studying rapid quadrupedal movement involve the measurement of ground reaction forces (GRF) using a force plate and a simultaneous kinematics analysis by a High Frame Rate video (HFR). Although force plates provides highly accurate kinetic data, it is not always practical to deploy in the study of animal locomotion. For instance, it is often not possible to embed force plates in irregular terrains [1] characteristic of most ecologically relevant animals’ natural habitats [2]. An alternative method is to utilize an inertial measurement unit (IMU) equipped with a tri-axial accelerometer to analyze accelerations associated with different quadruped gaits. In this study, a tri-axial accelerometer is used to analyze sprinting locomotion dynamics of a greyhound in a simulated racing condition. Kinematics data from videography of the entire race was recorded in each trial for data calibration. In addition, the paw prints of the greyhound on a sandy-loam surface of a race track are also analyzed to sync acceleration data with each individual paw print.
Hayati, H, Eager, D, Jusufi, A & Brown, T 1970, 'A Study of Rapid Tetrapod Running and Turning Dynamics Utilizing Inertial Measurement Units in Greyhound Sprinting', Volume 3: 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices, ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers, Cleveland, Ohio, USA, pp. 1-5.
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Understanding the biomechanics of rapid running locomotion plays an important role in comparative biomechanics and bio-inspired engineering and is an integral part of animal welfare. However, this is not easily achieved using conventional methods of gait analysis: measuring ground reaction forces using a force plate, mainly on irregular granular terrain i.e. greyhounds in racing conditions or in animal’s natural habitats i.e. cheetahs in natural terrain. An alternative to measuring forces externally via force platforms embedded in track ways, we can attach inertial measurement units to agile quadrupeds to measure the effects of rapid running and turning. Here we deployed an IMU equipped with a tri-axial accelerometer on sprinting greyhounds to analyze rapid locomotion behaviors like dynamic banking and turning in conditions equivalent to racing. High speed videography and paw print analysis of the entire race were used for calibration. The results are beneficial in locomotion analysis and welfare of greyhounds.
Hayati, H, Eager, D, Stephenson, R, Brown, T & Arnott, E 1970, 'The impact of track related parameters on catastrophic injury rate of racing greyhounds', 9th Australasian Congress on Applied Mechanics, ACAM 2017, Australasian Congress on Applied Mechanics, Engineers Australia, Sydney, Australia.
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Greyhounds can travel twice as fast as human athletes, attaining constant average running speeds of ~65 km/h vs ~29 km/h. Their locomotion is also different from human sprinters, and more similar to cyclists. Unlike human sprinters where the muscles powering the locomotion are also supporting the weight, locomotion of greyhound are powered by torque about the hip. Agile, high-speed quadrupeds, such as the greyhound, experience extreme ground-limb contact forces while negotiating turns; leading to an increased susceptibility to injuries. Added to this, rapid, high velocity changes in direction and extreme turning angles magnify the lateral acceleration forces experienced on the limbs and torso. In this paper, the rate of severe musculoskeletal injuries of racing greyhounds at 34 tracks in New South Wales, Australia, were obtained for the year of 2016. The correlation of parameters, namely bend radius, bend camber, bend length and back straight length and the catastrophic injury rate are statistically analyzed . Track injury locations were obtained from race video footage No correlation was seen between catastrophic injury rate and bend radius, bend camber, bend length and back straight length. Analyses revealed the highest injury rate based on location to be at the first turn. Footage lends support to this being caused by the immediate clustering of the greyhounds towards the inner ‘lure’ rail.” The results of this study support previous findings that greyhounds racing in an anti-clockwise direction most commonly suffer musculoskeletal injuries to their right hind limbs which is consistent with knowledge of the forces that occur on the leading limbs of these dogs as they maintain their speed around bends.
He, Q, Zhou, R, Zhang, X, Wang, Y, Ye, D, Chen, F, Chen, S, Grundy, J & Yang, Y 1970, 'Efficient Keyword Search for Building Service-Based Systems Based on Dynamic Programming', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 462-470.
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The advances in service-oriented architecture (SOA) have fueled the demand for building service-based systems (SBSs) by composing existing services. Finding appropriate component services is a key step during the process for building SBSs. However, existing approaches require that system engineers have detailed knowledge of SOA techniques, which is often too demanding. A recent approach has been proposed to address this issue. However, it suffers from poor efficiency, which is increasingly critical as the service repository continues to grow. To address this issue, this paper proposes KS3+, a new, highly efficient approach that allows a system engineer to query for a system solution with a few keywords that represent the required system tasks. Modeling the problem of answering such a keyword query as a dynamic programming problem, KS3+ can quickly find a system solution composed of services that perform the required system tasks. It offers an efficient paradigm that significantly reduces the time and effort during the process for building SBSs. The results of extensive experiments on a real-world web service dataset demonstrate the high efficiency and effectiveness of KS3+.
He, T, Lu, D, Zheng, L & Zhu, J 1970, 'Moving average filter-based model predictive control for electric vehicles bidirectional chargers', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. The paper proposes a moving average filter (MAF)-based model predictive control (MPC) for the electric vehicles (EVs) bidirectional chargers. Grid virtual flux is used to estimate the grid voltage through a low pass filter (LPF). An MAF, which acts as an ideal LPF, can eliminate the effect of unbalanced/distorted grid voltage and unknown characteristic harmonics. Both the two-cascaded LPF-based and the proposed MAF-based MPC strategies can achieve bi-directional power flow for EV batteries. Compared with the system results obtained from the two-cascaded LPF based MPC algorithm, the proposed control method can improve the system performance by reducing the current total harmonic distortion under a balance/unbalance grid voltage. The reactive power performance can be improved when the active power reference varies.
He, T, Zhu, J, Dah-Chuan Lu, D, Zheng, L, Aghdam, MM & Zhang, J 1970, 'Comparison study of electric vehicles charging stations with AC and DC buses for bidirectional power flow in smart car parks', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 4609-4614.
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© 2017 IEEE. This paper presents a comparison study of AC bus and DC bus topologies for electric vehicle (EV) battery chargers in smart car parks. The two charger systems are compared from two aspects: the features from the user side and the power quality on the grid side. Considering the system reliability, cost, size and conversion stage, the pros and cons of AC and DC buses systems are introduced and summarized. To compare the electric parameters of the power quality, model predictive control (MPC) algorithm is proposed and applied to operate in grid-to-vehicle (G2V), vehicle-to-grid (V2G), vehicle-for-grid (V4G) modes. An cost function is designed in MPC to track the active and reactive powers references provided by the main grid. The controllers for AC and DC buses to determine the the active and reactive powers relationships among the grid, charging stations and the storage system are designed, respectively. In terms of power ripple, total harmonic distortion (THD) and execute time, comparative simulations of the two topologies are performed under the proposed operations in Matlab/Simulink. The obtained results show that both the two system structures can operate effectively and the commands from the grid and EVs customers can be satisfied. Fast dynamic performance and good steady-state response are achieved in two systems. However, the power ripple, THD, and the execute time obtained from DC bus topology are much lower compared with the AC bus system.
He, Y, Wu, J & Wang, H 1970, 'Clickthrough refinement for improved graph ranking', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 3288-3295.
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© 2017 IEEE. Graph ranking is a promising technique for image retrieval, but its effectiveness is limited by the so-called semantic gap. To mitigate this gap, clickthroughs, which are helpful to perceive the visual content of images, are adopted by graph ranking models recently. However, few existing models take both sparseness and noisiness of clickthroughs into account, which are important in refining the clickthrough-based search results. In this paper, we propose a novel solution to clickthrough refinement that consists of two key components. The first one is to prune the noisy clickthroughs by a neighbor voting strategy, and the second one is to enrich the incomplete clickthroughs by a Tri-CF (collaborative filtering) algorithm. Furthermore, we devise four solutions to affinity matrices fusion in order to leverage the clickthroughs and visual features within a unified graph ranking model. Our extensive experiments for clickthrough prediction and image retrieval validate the effectiveness of the proposed techniques in comparison to state-of-the-art approaches.
Heitor, A, Indraratna, B, Rujikiatkamjorn, C & McIntosh, GW 1970, 'Influence of compaction history on the shear strength behaviour of compacted soil', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1361-1364.
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The condition under which soil is compacted governs its shear strength, which is why the shear strength parameters of specimens compacted at a given state are usually evaluated and tested for different post-compaction loading conditions. While this enables the behaviour to be predicted in service, the impact of the compaction history is usually ignored. This is an important aspect because how compacted soil behaves during shearing is strongly influenced by its structure and suction, and thus its compaction and loading history. In this paper the aspects related to the compaction history of a silty sand soil prepared by dynamic compaction and then tested with a direct shearing box are examined. To replicate an as-compacted condition, the specimens are tested under constant water content. To investigate the compaction history the specimens were prepared under different levels of compaction energy and then tested under the same vertical stress. The results confirm how important the initial stress state of the soil is in relation to its compaction history, in governing the mechanical response during direct shearing.
Henderson, H & Leong, TW 1970, 'Lessons learned', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, pp. 533-537.
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© 2017 Association for Computing Machinery. All rights reserved. This paper presents a study on user difficulties with parking meters. Using known Human-Computer Interaction (HCI) concepts as a guide, we explore the reasons for these difficulties and propose recommendations for designers of parking meters to improve the usability and experience. This paper also considers the applicability of these learnings to similar technologies that are of interest to HCI.
Herrmann, D, Erami, Z, Warren, S, Nobis, M, Magenau, A, Lucas, M, Vennin, C, McGhee, EJ, Leung, W, Reischmann, N, Mrowinska, A, Schwarz, JP, Kadir, S, Karim, SA, Campbell, AD, Gallego-Ortega, D, Evans, J, Sansom, OJ, Morton, JP, Anderson, KI & Timpson, P 1970, 'Abstract PR07: A biosensor mouse to predict the dissociation and spread of pancreatic cancer', Cancer Research, Abstracts: AACR Special Conference: Engineering and Physical Sciences in Oncology; June 25-28, 2016; Boston, MA, American Association for Cancer Research (AACR), Boston, MA, pp. PR07-PR07.
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Abstract E-cadherin-mediated cell-cell junctions play a physical role in maintaining normal epithelial architecture. The disruption or deregulation of these adhesions in cancer can lead to the collapse of tumor epithelia that precedes invasion and subsequent metastasis. Here, we have generated an E-cadherin-GFP(FRAP) biosensor mouse, which enables intravital photobleaching and quantification of E-cadherin mobility in live tissue, without affecting normal biology. We demonstrate using FRAP or FLIP, the broad applications of this mouse to examine E-cadherin regulation in multiple tissues including mammary, brain, liver and kidney, while specifically monitoring E-cadherin mobility during disease progression in the pancreas. We assess E-cadherin stability in native pancreatic tissue, upon genetic manipulation involving Kras and p53 or in response to anti-invasive drug treatment, and reveal new insights into the dynamic remodeling of E-cadherin during in situ cancer progression. Photobleaching in the E-cadherin-GFP(FRAP) mouse correlate directly with epithelial integrity and mechanical strength making the biosensor mouse a valuable tool to fundamentally expand our understanding of E-cadherin-mediated events in native micro-environments. This abstract is also being presented as Poster B23. Citation Format: David Herrmann, Zahra Erami, Sean Warren, Max Nobis, Astrid Magenau, Morghan Lucas, Claire Vennin, Ewan J. McGhee, Wilfred Leung, Nadine Reischmann, Agata Mrowinska, Juliane P. Schwarz, Shereen Kadir, Saadia A. Karim, Andrew D. Campbell, David Gallego-Ortega, Jeffry Evans, Owen J. Sansom, Jennifer P. Morton, Kurt I. Anderson, Paul Timpson. A biosensor mouse to predict the dissociation and spread of pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston,...
Herron, D, Moncur, W & van den Hoven, E 1970, 'Digital Decoupling and Disentangling', Proceedings of the 2017 Conference on Designing Interactive Systems, DIS '17: Designing Interactive Systems Conference 2017, ACM, Edinburgh, United Kingdom, pp. 1175-1185.
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Romantic relationships are often facilitated through digital technologies, such as social networking sites and communication services. They are also facilitated through "digital possessions", such as messages sent to mobile devices and photos shared through social media. When individuals break up, digitally disconnecting can be facilitated by using those digital technologies and managing or curating these digital possessions. This research explores the break up stories of 13 individuals aged between 18 and 52. The aim of this work is to inform the design of systems focused on supporting individuals to decouple and disentangle digitally in the wake of a break up. Four areas of interest emerged from the data: communication, using digital possessions, managing digital possessions, and experiences of technology. Opportunities for design were identified in decoupling and disentangling, and designing around guilt.
Hjerrild, NE, Mesgari, S, Crisostomo, F, Scott, JA, Amal, R & Taylor, RA 1970, 'Spectrum splitting using gold and silver nanofluids for photovoltaic/thermal collectors', 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), 2017 IEEE 44th Photovoltaic Specialists Conference (PVSC), IEEE, USA, pp. 1-6.
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© 2017 IEEE. The thermal yield of hybrid photovoltaic/thermal (PV/T) collectors is presently limited to low temperatures to prevent degradation of PV efficiency and thermal damage to the cells. This work reports a nanofluid optical filter, which transmits only the portion of the solar spectrum which is most efficiently converted to electricity by the underlying solar cell. This is achieved by suspending both core-shell silver-silica nanodiscs (Ag-SiO 2 NDs) and gold nanorods (AuNRs) in an aqueous base fluid to absorb visible light and infrared wavelengths, respectively. The transmission spectrum of each nanofluid can be tailored according to PV cell spectral response and to accommodate for electricity and gas price fluctuations.
Ho, L, Li, D, Fatahi, B & Khabbaz, H 1970, 'Analytical solution to one-dimensional consolidation in unsaturated soil due to time-dependent exponential temperature and external step loading', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 757-760.
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Recent experimental studies demonstrate that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for the unsaturated consolidation capturing non-isothermal effects. This paper introduces analytical solutions to predict the one-dimensional (1D) consolidation of unsaturated soil deposit while incorporating the time-dependent exponential temperature variation. The one-way drainage boundary system and the uniform initial condition are adopted for the mathematical derivation. In this study, governing equations under the non-isothermal condition are first obtained. Then, Fourier sine series and the Laplace transform technique are used to solve these governing equations and obtain the final solutions. This study highlights the combined effects of time-dependent exponential temperature and an external step loading on the excess pore pressures at various depths. It is predicted that the effects of exponential temperature on the dissipation process would be much attenuated at a lower depth.
Hoang, D & Dang, TD 1970, 'FBRC: Optimization of task Scheduling in Fog-Based Region and Cloud', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, NSW, Australia, pp. 1109-1114.
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© 2017 IEEE. Fog computing preserves benefits of cloud computing and is strategically positioned to address effectively many local and performance issues because its resources and specific services are virtualized and located at the edge of the customer premises. Resource management is a critical issue affecting system performance significantly. Due to the complex distribution and high mobility of fog devices, computation resources still experience high latencies in fog's large coverage area. This paper considers a Fog-based Region and Cloud (FBRC) in which requests are locally handled not just by a region but multiple regions when additional resources are needed. An efficient task scheduling mechanism is thus essential to minimize the completion time of tasks and improve user experiences. To this end, two issues are investigated in the paper: 1) designing a fog-based region architecture to provide nearby computing resources; 2) investigating efficient scheduling algorithms to distribute tasks among regions and remote clouds. To deal with the complexity of scheduling tasks, a heuristic-based algorithm is proposed based on our formulation and validated by extensive simulations.
Hoang, DT, Niyato, D & Wang, P 1970, 'Optimal Cost-Based Cyber Insurance Policy Management for Mobile Services', 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), IEEE, Toronto, ON, Canada, pp. 1-5.
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© 2017 IEEE. This paper introduces a cyber insurance policy management for the mobile networks in which if a mobile user agrees to purchase an insurance policy from an insurer, the loss of the mobile user, i.e., the insured, will be covered by the insurance policy when the risks happen. To protect mobile users from cyber attacks, the insurer can deploy security protection solutions, e.g., anti-virus software or personal firewall, to the insureds, thereby reducing the risks for mobile users. However, when the solutions are deployed, they will incur a certain cost to the insurer. Therefore, we propose a stochastic optimization based on the reserve state of the insurer and the number of active mobile users to determine whether the protection solutions should be deployed or not to maximize the revenue for the insurer. The performance evaluation reveals that the optimal policy can achieve significantly higher revenue than those of baseline schemes for the insurer. Alternatively, the coalitional game is studied to share the reward among the insurers, and we show that the insurers can gain higher individual rewards through the cooperation.
Hoang, DT, Niyato, D, Wang, P & Kim, DI 1970, 'Optimal time sharing in RF-powered backscatter cognitive radio networks', 2017 IEEE International Conference on Communications (ICC), ICC 2017 - 2017 IEEE International Conference on Communications, IEEE, Paris, France, pp. 1-6.
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© 2017 IEEE. In this paper, we propose a novel network model for RF-powered cognitive radio networks and ambient backscatter communications. In the network under consideration, each secondary transmitter is able to backscatter primary signals to the gateway for data transfer or to harvest energy from the primary signals and then use that energy to transmit data to the gateway. To maximize overall network throughput of the network, we formulate an optimization problem with the aim of finding not only an optimal tradeoff between data backscattering time and energy harvesting time, but also time sharing among multiple secondary transmitters. Through the numerical results, we demonstrate that the solution of the optimization problem always achieves the best performance compared with two other baseline schemes.
Hoang, DT, Niyato, D, Wang, P, Domenico, AD & Strinati, EC 1970, 'Optimal Cross Slice Orchestration for 5G Mobile Services', IEEE Vehicular Technology Conference, IEEE Vehicular Technology Conference, IEEE, Chicago, IL, USA, USA.
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5G mobile networks encompass the capabilities of hosting a variety ofservices such as mobile social networks, multimedia delivery, healthcare,transportation, and public safety. Therefore, the major challenge in designingthe 5G networks is how to support different types of users and applicationswith different quality-of-service requirements under a single physical networkinfrastructure. Recently, network slicing has been introduced as a promisingsolution to address this challenge. Network slicing allows programmable networkinstances which match the service requirements by using network virtualizationtechnologies. However, how to efficiently allocate resources across networkslices has not been well studied in the literature. Therefore, in this paper,we first introduce a model for orchestrating network slices based on theservice requirements and available resources. Then, we propose a Markovdecision process framework to formulate and determine the optimal policy thatmanages cross-slice admission control and resource allocation for the 5Gnetworks. Through simulation results, we show that the proposed framework andsolution are efficient not only in providing slice-as-a-service based on theservice requirements, but also in maximizing the provider's revenue.
Hoang, DT, Niyato, D, Wang, P, Kim, DI & Le, LB 1970, 'Overlay RF-powered backscatter cognitive radio networks: A game theoretic approach', 2017 IEEE International Conference on Communications (ICC), ICC 2017 - 2017 IEEE International Conference on Communications, IEEE, Paris, France, pp. 1-6.
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© 2017 IEEE. In this paper, we study an overlay RF-powered cognitive radio network with ambient backscatter communications. In the network, when the channel is occupied, the secondary transmitter (ST) can perform either energy harvesting or data transmission using ambient backscattering technique to a gateway. We consider the case that the gateway charges the ST a certain price if the ST transmits information. This leads to questions of how to determine the best price for the gateway and how to find the optimal backscatter time. To address this problem, we propose a Stackelberg game in which the gateway is the leader adapting the price to maximize its profit in the first stage. Meanwhile, the ST chooses its backscatter time to maximize its utility in the second stage. To analyze the game, we apply the backward induction technique. We show that the game always has a unique subgame perfect Nash equilibrium. Additionally, our results provide insights on the impact of the competition on the players' profit and utility.
Hoang, DT, Niyato, D, Wang, P, Wang, SS, Nguyen, D & Dutkiewicz, E 1970, 'A Stochastic Programming Approach for Risk Management in Mobile Cloud Computing', IEEE Wireless Communications and Networking Conference, WCNC, IEEE Wireless Communications and Networking Conference, IEEE, Barcelona, Spain, pp. 1-6.
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The development of mobile cloud computing has brought many benefits to mobileusers as well as cloud service providers. However, mobile cloud computing isfacing some challenges, especially security-related problems due to the growingnumber of cyberattacks which can cause serious losses. In this paper, wepropose a dynamic framework together with advanced risk management strategiesto minimize losses caused by cyberattacks to a cloud service provider. Inparticular, this framework allows the cloud service provider to selectappropriate security solutions, e.g., security software/hardware implementationand insurance policies, to deal with different types of attacks. Furthermore,the stochastic programming approach is adopted to minimize the expected totalloss for the cloud service provider under its financial capability anduncertainty of attacks and their potential losses. Through numericalevaluation, we show that our approach is an effective tool in not only dealingwith cyberattacks under uncertainty, but also minimizing the total loss for thecloud service provider given its available budget.
Hoang, TM, Tuan, HD & Duong, TQ 1970, 'Secure Massive MIMO Amplify-and-Forward Relaying Networks in Poisson Field', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. We consider a cooperative relay network in the presence of many eavesdroppers whose locations are distributed according to a homogeneous Poisson point process. The relay, which operates in amplify-and-forward protocol, has very large transmit and receive antenna arrays, while other nodes are equipped with a single antenna. We assume that the relay exploits maximum ratio combing (MRC) in the uplink and maximum ration transmission in the downlink, while all eavesdroppers are able to exploit MRC to maximize the received signals. In addition, there is no perfect channel state information of any eavesdroppers since all eavesdroppers in practice tend to hide from the legitimate users. Furthermore, we suppose that there are direct links between source and eavesdroppers, while a direct link between source and destination does not exist. Under such assumptions, which are totally biased towards eavesdroppers, we examine the security performance of the proposed system throughout secrecy outage probability and connection outage probability.
Hoang, VT, Singh, AM, Phung, MD & Ha, Q 1970, 'Adaptive Second-Order Sliding Mode Control of UAVs for Civil Applications', Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC), 34th International Symposium on Automation and Robotics in Construction, Tribun EU, s.r.o., Brno, Taipei, pp. 816-822.
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Quadcopters, as unmanned aerial vehicles (UAVs), have great potential in civil applications such as surveying, building monitoring, and infrastructure condition assessment. Quadcopters however are relatively sensitive to rotational noises so that their performance may be quickly downgraded in the case of inadequate control, system uncertainties and/or disturbances. In this study, we deal with the quadrotor control problem by proposing a new control scheme named the adaptive second-order quasi-continuous sliding mode control (adaptive 2-QCSM). The goal is to achieve robust attitude control for the task of monitoring and inspection of built infrastructure. We first formulate the mathematical model of the quadcopter, incorporating nonlinearity, strong coupling, uncertain dynamics and external disturbances. We then use a Lyapunov function to derive the adaptive 2-QCSM control laws. We further tune it to ensure finite-time reaching under these control laws. Extensive simulations have been carried out for evaluation. Results show that the proposed control scheme can attenuate chattering to obtain stable operations under large parameter variations and strong disturbance conditions.
Ho-Le, T, Tran, T, Center, J, Eisman, J & Nguyen, T 1970, 'Burden of fractures attributable to low bone mineral density.', JOURNAL OF BONE AND MINERAL RESEARCH, Annual Meeting of the American-Society-for-Bone-and-Mineral-Research (ASBMR), WILEY, CO, Denver, pp. S364-S364.
Ho-Le, TP, Center, JR, Eisman, JA, Nguyen, TV & Nguyen, HT 1970, 'Prediction of hip fracture in post-menopausal women using artificial neural network approach', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 4207-4210.
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Hip fracture is one of the most serious health
problems among post-menopausal women with osteoporosis. It
is very difficult to predict hip fracture, because it is affected by
multiple risk factors. Existing statistical models for predicting
hip fracture risk yield area under the receiver operating
characteristic curve (AUC) ~0.7-0.85. In this study, we trained
an artificial neural network (ANN) to predict hip fracture in
one cohort, and validated its predictive performance in another
cohort. The data for training and validation included age, bone
mineral density (BMD), clinical factors, and lifestyle factors
which had been obtained from a longitudinal study that
involved 1167 women aged 60 years and above. The women had
been followed up for up to 10 years, and during the period, the
incidence of new hip fractures was ascertained. We applied
feed-forward neural networks to learn from the data, and then
used the learning for predicting hip fracture. Results of
prediction showed that the accuracy of model I (which included
only lumbar spine and femoral neck BMD) and model II
(which included non-BMD factors) was 82% and 84%,
respectively. When both BMD and non-BMD factors were
combined (Model III), the accuracy increased to 87%. The
AUC for model III was 0.94. These findings indicate that ANNs
are able to predict hip fracture more accurately than any
existing statistical models, and that ANNs can help stratify
individuals for clinical management.
Hossain, MM, Zafreen, KR, Rahman, A, Zamee, MA & Aziz, T 1970, 'An effective algorithm for demand side management in smart grid for residential load', 2017 4th International Conference on Advances in Electrical Engineering (ICAEE), 2017 4th International Conference on Advances in Electrical Engineering (ICAEE ), IEEE, pp. 336-340.
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Hosseini, SM, Al-Jumaily, A & Kalhori, H 1970, 'Tremor suppression in wrist joint using active force control method', 9th Australasian Congress on Applied Mechanics, ACAM 2017, Australasian Congress on Applied Mechanics, Engineers Australia, Sydney, NSW.
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Tremor is a neurological disorder characterized by involuntary oscillations. Difficulties associated with tremor in patients with Parkinson’s disease have motivated the researchers to work on developing various methods for tremor suppression. Active Force Control (AFC) method for tremor attenuation in human body parts is considered in this work. This paper proposes a new AFC system based on a piezoelectric actuator. A three-degree-of-freedom musculoskeletal model including wrist flexion-extension (FE), radial-ulnar deviation (RUD), and pronation supination (PS) is developed for studying tremor in the wrist joint. The musculoskeletal model for this study contains four muscles; extensor carpi radialis longus, extensor carpi ulnaris, flexor carpi ulnaris and flexor carpi radialis. Also, the muscle model is developed from the classic Hill-type muscle model. First, simulation of the tremor generation in the model is performed and then the performance of AFC system for suppressing wrist joint tremor is investigated. A single piezoelectric actuator is embedded in AFC system for controlling the behavior of the classic proportional-derivative controller. MATLAB Simulink is used to analyze the model. Results show that the AFC-based system with a piezoelectric actuator and a PD controller is very effective in suppressing the human hand tremor.
Hou, ZJ, Xue, Q, Yang, Y, Zhu, X & Dutkiewicz, E 1970, 'Miniaturized millimeter-wave on-chip bandpass filter design in 0.13-μm SiGe BiCMOS technology', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-5.
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© 2017 IEEE. The full potential of active device in current Si-based technology has almost reached its limit. However, the passive devices that are integrated with transistors in the same technology have yet been fully explored. Improving the quality of on-chip passive devices is not only beneficial for energy efficiency, but also has significant meaning in cost reduction for a system-on-chip (SoC) solution while the passive circuits are miniaturized. A review of on-chip circuit miniaturization techniques for bandpass filter (BPF) design is demonstrated in this paper. Although the recently presented broadside-coupled meander line resonator (BCMLR) is very compact, the stopband attenuation is quite limited. To solve this issue, a ring-based structure is studied in this work. Using this approach, the size of the proposed millimeter-wave on-chip BPF can be significantly reduced due to the multi-mode characteristics of the proposed resonators, of which the equivalent circuits can be effectively modeled through the accurately extracted lumped components values. Our works exhibit excellent performance comparing with the state-of-the-art designs.
Hou, ZJ, Yang, Y, Zhu, X, Liao, S, Man, SK & Xue, Q 1970, 'A 320 GHz On-Chip Slot Antenna Array Using CBCPW Feeding Network in 0.13-mu m SiGe Technology', 2017 IEEE MTT-S INTERNATIONAL MICROWAVE SYMPOSIUM (IMS), IEEE-Microwave-Theory-and-Techniques-Society International Microwave Symposium (IMS) / Session on Women in Microwaves (WIM), IEEE, HI, Honolulu, pp. 839-842.
Hou, ZJ, Yang, Y, Zhu, X, Liao, S, Man, SK & Xue, Q 1970, 'A 320 GHz on-chip slot antenna array using CBCPW feeding network in 0.13-μm SiGe technology', 2017 IEEE MTT-S International Microwave Symposium (IMS), 2017 IEEE/MTT-S International Microwave Symposium - IMS 2017, IEEE, Honolulu, Hawaii, pp. 843-846.
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© 2017 IEEE. A 320 GHz on-chip 2 × 2 antenna array employing a compact feeding network is presented in this paper. The feeding network is designed based on the conducted-back coplanar waveguide (CBCPW) transmission line with a compact size, which has the full shielding performance providing good isolation from circuits around or below the CBCPW transmission lines. The proposed on-chip feeding network and antenna array are fabricated using standard 0.13-μm SiGe process. The antenna array is measured using a specially designed backside radiation measurement system. The simulated and measured results show that the backside radiation on-chip antenna array has a measured peak gain of 7.9 dBi at 320 GHz.
Hu, D, Xu, W, Lei, G & Zhu, J 1970, 'Design and control optimization of linear induction motor drive for efficiency improvement', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Linear induction motor (LIM) drive suffers heavily from low efficiency due to its large air-gap length, the end-effects, and the partial load working conditions. Therefore, an optimization method is proposed in this paper to improve the LIM drive operating efficiency from both design and control levels. First, the genetic algorithm (GA) is applied to design optimization of LIM to attain higher efficiency and power factor. Second, a novel loss model for LIM drive is proposed to analyze both LIM loss and inverter loss. Third, efficiency optimization control (EOC) scheme based on the loss model is put forward to improve the LIM drive working efficiency. Simulations and experimental results validate the effectiveness of the proposed method in efficiency improvement of LIM drive under various operation conditions.
Hu, L, Cao, L, Wang, S, Xu, G, Cao, J & Gu, Z 1970, 'Diversifying Personalized Recommendation with User-session Context', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 1858-1864.
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Recommender systems (RS) have become an integral part of our daily life. However, most current RS often repeatedly recommend items to users with similar profiles. We argue that recommendation should be diversified by leveraging session contexts with personalized user profiles. For this, current session-based RS (SBRS) often assume a rigidly ordered sequence over data which does not fit in many real-world cases. Moreover, personalization is often omitted in current SBRS. Accordingly, a personalized SBRS over relaxedly ordered user-session contexts is more pragmatic. In doing so, deep-structured models tend to be too complex to serve for online SBRS owing to the large number of users and items. Therefore, we design an efficient SBRS with shallow wide-in-wide-out networks, inspired by the successful experience in modern language modelings. The experiments on a real-world e-commerce dataset show the superiority of our model over the state-of-the-art methods.
Hu, R, Pan, S, Jiang, J & Long, G 1970, 'Graph Ladder Networks for Network Classification', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, ACM, pp. 2103-2106.
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© 2017 ACM. Numerous network representation-based algorithms for network classification have emerged in recent years, but many suffer from two limitations. First, they separate the network representation learning and node classification in networks into two steps, which may result in sub-optimal results because the node representation may not fit the classification model well, and vice versa. Second, they are mostly shallow methods that can only capture the linear and simple relationships in the data. In this paper, we propose an effective deep learning model, Graph Ladder Networks (GLN), for node classification in networks. Our model learns a ladder network which unifies the representation learning and network classification into one single framework by exploiting both labeled and unlabeled nodes in a network. To integrate both structure and node content information in the networks, the most recently developed graph convolution network, is further employed. The experiments on the most popular academic network dataset, Citeseer, demonstrate that our approach reaches outstanding performance compared to other state-of-the-art algorithms.
Hu, R, Yu, CP, Fung, S-F, Pan, S, Wang, H & Long, G 1970, 'Universal network representation for heterogeneous information networks', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 388-395.
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© 2017 IEEE. Network representation aims to represent the nodes in a network as continuous and compact vectors, and has attracted much attention in recent years due to its ability to capture complex structure relationships inside networks. However, existing network representation methods are commonly designed for homogeneous information networks where all the nodes (entities) of a network are of the same type, e.g., papers in a citation network. In this paper, we propose a universal network representation approach (UNRA), that represents different types of nodes in heterogeneous information networks in a continuous and common vector space. The UNRA is built on our latest mutually updated neural language module, which simultaneously captures inter-relationship among homogeneous nodes and node-content correlation. Relationships between different types of nodes are also assembled and learned in a unified framework. Experiments validate that the UNRA achieves outstanding performance, compared to six other state-of-the-art algorithms, in node representation, node classification, and network visualization. In node classification, the UNRA achieves a 3% to 132% performance improvement in terms of accuracy.
Huan, H, Wei, Z, Liang, L & Yang, L 1970, 'Collaborative Filtering Recommendation Model based on Convolutional Denoising Auto Encoder', Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW '17: Chinese Conference on Computer Supported Cooperative Work and Social Computing, ACM, pp. 64-71.
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Huang, B, Fatahi, B & Khabbaz, H 1970, 'Influence of Underground Opening with Stiff Lining on Seismic Response of Buildings', International Conference on Geomechanics and Geoenvironmental Engineering, International Conference on Geomechanics and Geoenvironmental Engineering, Science, Technology and Management Crest 12 Boyer Pl, Minto, New South Wales 2565, Sydney, Australia, Sydney, pp. 125-131.
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In this study, the influence of an underground opening at different depths on seismic performance of a 15-storey moment resisting building subjected to the 1995 Kobe earthquake is investigated. The numerical model consists of a superstructure, soil medium, and an underground opening, all simulated using finite element method in time domain considering soil nonlinearity and soil-structure interaction. The results are presented in terms of foundation rocking angle, distribution of maximum shear force developed in the structure, maximum lateral deflection as well as inter-storey drifts of the building. The results indicate that the underground opening has a notable influence on seismic response of the building. Particularly, the maximum foundation rocking angle is reduced with the presence of the underground opening with stiff concrete lining and the reduction is more significant when the underground opening is constructed at a lower depth. In addition, for a shallower underground opening, as the foundation rocking decreases, seismic energy dissipation is reduced, which in turn, causes more seismic energy transmitted to the structure and consequently larger shear forces are developed in the structure, which reveals the importance of consideration of underground structure in the seismic design of superstructures. Moreover, according to the results, the building constructed above a shallow underground opening experiences relatively smaller lateral displacement and inter-storey drifts subjected to earthquake excitation.
Huang, C, Yao, L, Wang, X, Benatallah, B & Sheng, QZ 1970, 'Expert as a Service: Software Expert Recommendation via Knowledge Domain Embeddings in Stack Overflow', 2017 IEEE International Conference on Web Services (ICWS), 2017 IEEE International Conference on Web Services (ICWS), IEEE, Honolulu, HI, pp. 317-324.
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Huang, L, Miao, W, Zhang, Y, Yu, H & Wang, K 1970, 'Network community-based Technological cooperation identification', ISSI 2017 - 16th International Conference on Scientometrics and Informetrics, Conference Proceedings, 16th International Conference on Scientometrics and Informetrics (ISSI), INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI, Wuhan Univ, Wuhan, PEOPLES R CHINA, pp. 1754-1765.
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Technological cooperation becomes necessary in extending technological application and improving market competitiveness, and thus, it is important to identify collaborative technologies that meet strategic purposes. This paper aims to construct a technological network based on the core terms derived from patent documents to help technology owners achieve such target. A four-step analytic framework is constructed, including: 1) community division, which allows the selection of cooperative technology to be controlled within a more relevant technical range; 2) indicator analysis that can be used to understand the technological situation within the community from three main aspects, i.e., degree, clustering coefficient and line weight; 3) the purpose of cooperation, which is an important basis for the selection of cooperative technology; and 4) technology selection, which is to combine cooperation purposes and indicator analysis to select technology. Finally, a case study on China's artificial intelligence (AI) technology is conducted to demonstrate the feasibility of this method, and the findings will help decision making in related AI fields.
Huang, L, Miao, W, Zhang, Y, Yu, H & Wang, K 1970, 'Patent Network Analysis for Identifying Technological Evolution: A Case Study of China's Artificial Intelligence Technologies', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Portland, OR, USA, pp. 1-9.
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© 2017 PICMET. Identifying technological evolution is a crucial way to assist in technology management. Since modern technology has become more and more complex and dynamic, general statistical techniques can hardly capture the underlying information of technological interconnection in the process of technology evolution. However, complex network analysis can be considered to be a powerful tool to investigate this issue. At the same time, patent documents containing rich information to indicate technological evolution in sequential time period can be a significant data source. This paper, based on the core terms derived from patent documents, constructs technological networks, to present the distribution of technologies. The comparison between the networks in sequential time periods can not only provide a way to understand technological evolution in detail, but also forecast technology opportunities, which can be used to help understand the development of selected technologies quickly and provide insights to research and development (R&D) plan and technological commercialization. A case study on exploring the evolution of China's artificial intelligence technologies is conducted to demonstrate the feasibility of this method.
Huang, Y, Hong, G & Zhou, J 1970, 'Numerical Modelling of Ethanol Direct Injection (EDI) Sprays of a Multi-Hole Injector under Non-Evaporating, Transition and Flash-Boiling Conditions', SAE Technical Paper Series, International Powertrains, Fuels & Lubricants Meeting, SAE International.
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Copyright © 2017 SAE International. Ethanol direct injection (EDI) has great potential in facilitating the downsizing technologies in spark ignition engines due to its strong anti-knock ability. The fuel temperature may vary widely from non-evaporating to flash-boiling sprays in real engine conditions. In this study, a CFD spray model was developed in the ANSYS Fluent environment, which was capable to simulate the EDI spray and evaporation characteristics under non-evaporating, transition and flash-boiling conditions. The turbulence was modelled by the realizable k-μ model. The Rinzic heterogeneous nucleation model was applied to simulate the primary breakup droplet size at the nozzle exit. The secondary breakup process was modelled by the Taylor Analogy Breakup model. The evaporation process was modelled by the Convection/Diffusion Controlled Model. The droplet distortion and drag, collision and droplet-wall interaction were also included. The spray model was verified against the spray experimental results in a constant volume chamber. The developed spray model well simulated the EDI spray evolution and evaporation processes under non-evaporating, transition and flash-boiling conditions. The simulation results showed that the non-evaporating spray's characteristics were similar to those of the normal-evaporating spray in terms of spray structure and spray tip penetration. The spray plumes converged towards the middle one with the increase of fuel temperature and finally collapsed completely when the spray superheat degree was higher than 9 K. This was caused by the increased ambient air speed and stronger vortices entrained by the spray jet, and additionally by the significantly reduced droplet size. The EDI spray could be considered as non-evaporating when the fuel temperature was lower than 325 K at 1 bar. The evaporation rate increased slightly with the fuel temperature increased from 275 to 360 K, but significantly from 360 to 400 K. Although it re...
Huang, Y, Porter, A, Zhang, Y, Guo, Y & Zhu, D 1970, 'Validating the Earlier Analyses and Forecasting on Dye-Sensitized Solar Cells (DSSCs)', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Portland, OR, USA, pp. 1-9.
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Newly Emerging Science and Technologies (NESTs) bring numerous innovation opportunities and challenges. At the same time, the highly uncertain dynamics of NESTs pose special challenges to traditional technology forecasting tools. Dye-Sensitized solar cells (DSSCs), a promising third-generation photovoltaic technology, can add functionality and lower costs, enhancing the value proposition of solar power generation in the early years of the 21st century. We have analyzed DSSCs R&D activity patterns and trends through a series of studies in the past several years, and come to realize the validation analyses is useful to improve the Science, Technology & Innovation (ST&I) policy processes. Yet, rarely do we revisit forecasts or projections to ascertain how well they fared. One of our aim is to check accuracy, to gain some sense of how valid those studies were and whether they proved useful to others in some ways. Additionally, we want to assess the degree to which such future-oriented analyses did or did not make good use of available information. Moreover, we seek indications of what information is key, and how Future-oriented technology analyses (FTA) processes can better utilize such information.
Huang, Z, Lin, X, Zhang, W & Zhang, Y 1970, 'Efficient Matrix Sketching over Distributed Data', Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, SIGMOD/PODS'17: International Conference on Management of Data, ACM, Chicago, Illinois, pp. 347-359.
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© 2017 ACM. A sketch or synopsis of a large dataset captures vital properties of the original data while typically occupying much less space. In this paper, we consider the problem of computing a sketch of a massive data matrix A ϵ ℝn×d, which is distributed across a large number of s servers. Our goal is to output a matrix B ϵ ℝℓ × dwhich is significantly smaller than but still approximates A well in terms of covariance error, i.e., ||ATA - BTB||2. Here, for a matrix A, ||A||2 is the spectral norm of A, which is defined as the largest singular value of A. Following previous works, we call B a covariance sketch of A. We are mainly focused on minimizing the communication cost, which is arguably the most valuable resource in distributed computations. We show a gap between deterministic and randomized communication complexity for computing a covariance sketch. More specifically, we first prove a tight deterministic lower bound, then show how to bypass this lower bound using randomization. In Principle Component Analysis (PCA), the goal is to find a low-dimensional subspace that captures as much of the variance of a dataset as possible. Based on a well-known connection between covariance sketch and PCA, we give a new algorithm for distributed PCA with improved communication cost. Moreover, in our algorithms, each server only needs to make one pass over the data with limited working space.
Hung, Y-C, Wang, Y-K, Prasad, M & Lin, C-T 1970, 'Brain dynamic states analysis based on 3D convolutional neural network', 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, Banff, AB, Canada, pp. 222-227.
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© 2017 IEEE. Drowsiness driving is one major factor of traffic accident. Monitoring the changes of brain signals provides an effective and direct way for drowsiness detection. One 3D convolutional neural network (3D CNN)-based forecasting system has been proposed to monitor electroencephalography (EEG) signals and predict fatigue level during driving. The limited weight sharing and channel-wise convolution were both applied to extract the significant phenomenon in various frequency bands of brain signals and the spatial information of EEG channel location, respectively. The proposed 3D CNN with limited weight sharing and channel-wise convolution has been demonstrated to predict reaction time (RT) of driving with low root mean square error (RMSE) through the brain dynamics. This proposed approach outperforms with the state-of-the-art algorithms, such as traditional CNN, Neural Network (NN), and support vector regression (SVR). Compared with traditional CNN and Artificial Neural Network, the RMSE of 3D CNN-based RT prediction has been improved 9.5% (RMSE from 0.6322 to 0.5720) and 8% (RMSE from 0.6217 to 0.5720), respectively. We envision that this study might open a new branch between deep learning application in neuro-cognitive analysis and real world application.
Huo, H, Liu, X, Zheng, D, Wu, Z, Yu, S & Liu, L 1970, 'Collaborative Filtering Fusing Label Features Based on SDAE', Springer International Publishing, pp. 223-236.
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Hussain, W, Hussain, FK & Hussain, OK 1970, 'Risk Management Framework to Avoid SLA Violation in Cloud from a Provider’s Perspective', ADVANCES ON P2P, PARALLEL, GRID, CLOUD AND INTERNET COMPUTING, Advances on P2P, Parallel, Grid, Cloud and Internet Computing, Springer International Publishing, Soonchunhyang Univ, Asan, SOUTH KOREA, pp. 233-241.
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Managing risk is an important issue for a service provider to avoid SLA violation in any business. The elastic nature of cloud allows consumers to use a number of resources depending on their business needs. Therefore, it is crucial for service providers; particularly SMEs to first form viable SLAs and then manage them. When a provider and a consumer execute an agreed SLA, the next step is monitoring and, if a violation is predicted, appropriate action should be taken to manage that risk. In this paper we propose a Risk Management Framework to avoid SLA violation (RMF-SLA) that assists cloud service providers to manage the risk of service violation. Our framework uses a Fuzzy Inference System (FIS) and considers inputs such as the reliability of a consumer; the attitude towards risk of the provider; and the predicted trajectory of consumer behavior to calculate the amount of risk and the appropriate action to manage it. The framework will help small-to-medium sized service providers manage the risk of service violation in an optimal way.
Hussein, F & Piccardi, M 1970, 'Minimum-Risk Structured Learning of Video Summarization', 2017 IEEE International Symposium on Multimedia (ISM), 2017 IEEE International Symposium on Multimedia (ISM), IEEE, Taichung, Taiwan, pp. 248-251.
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Video summarization is an important multimedia task for applications such as video indexing and retrieval, video surveillance, human-computer interaction and video "storyboarding". In this paper, we present a new approach for automatic summarization of video collections that leverages a structured minimum-risk classifier and efficient submodular inference. To test the accuracy of the predicted summaries we utilize a recently-proposed measure (V-JAUNE) that considers both the content and frame order of the original video. Qualitative and quantitative tests over two action video datasets - the ACE and the MSR DailyActivity3D datasets - show that the proposed approach delivers more accurate summaries than the compared minimum-risk and syntactic approaches.
Huynh, TV, Wilkinson, RH, Lech, M & Cheng, E 1970, 'A Comparison Between Anatomy-Based and Data-Driven Tree Models for Human Pose Estimation', 2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), International Conference on Digital Image Computing - Techniques and Applications (DICTA), IEEE, AUSTRALIA, Sydney, pp. 807-813.
Inan, DI & Beydoun, G 1970, 'Facilitating disaster knowledge management with agent-based modelling', Proceedings ot the 21st Pacific Asia Conference on Information Systems: ''Societal Transformation Through IS/IT'', PACIS 2017.
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In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. Nevertheless, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. In this paper, we introduce an Agent-Based (AB) knowledge analysis framework to convert DISPLANs into a collection of knowledge units that can be stored in a unified repository. The repository of DM actions then enables the mixing and matching knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF) to allow the free flow access to the knowledge across the layers. We use the flood DISPLAN of the SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and validate the developed framework.
Inan, DI, Beydoun, G & Opper, S 1970, 'Customising Agent Based Analysis Towards Analysis of Disaster Management Knowledge', Australasian Conference on Information Systems, University of Wollongong, Wollongong NSW, pp. 1-12.
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In developed countries such as Australia, for recurring disasters (e.g.floods), there are dedicated document repositories of Disaster Management Plans(DISPLANs), and supporting doctrine and processes that are used to prepareorganisations and communities for disasters. They are maintained on an ongoingcyclical basis and form a key information source for community education,engagement and awareness programme in the preparation for and mitigation ofdisasters. DISPLANS, generally in semi-structured text document format, arethen accessed and activated during the response and recovery to incidents tocoordinate emergency service and community safety actions. However, accessingthe appropriate plan and the specific knowledge within the text document fromacross its conceptual areas in a timely manner and sharing activities betweenstakeholders requires intimate domain knowledge of the plan contents and itsdevelopment. This paper describes progress on an ongoing project with NSW StateEmergency Service (NSW SES) to convert DISPLANs into a collection of knowledgeunits that can be stored in a unified repository with the goal to form thebasis of a future knowledge sharing capability. All Australian emergencyservices covering a wide range of hazards develop DISPLANs of various structureand intent, in general the plans are created as instances of a template, forexample those which are developed centrally by the NSW and Victorian SESs Stateplanning policies. In this paper, we illustrate how by using selected templatesas part of an elaborate agent-based process, we can apply agent-orientedanalysis more efficiently to convert extant DISPLANs into a centralisedrepository. The repository is structured as a layered abstraction according toMeta Object Facility (MOF). The work is illustrated using DISPLANs along theflood-prone Murrumbidgee River in central NSW.
Indraratna, B 1970, 'Recent advances in vertical drains and vacuum preloading for soft ground stabilisation', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 141-166.
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Much of the world’s essential infrastructure is built along congested coastal belts that are composed of weak and highly compressible soils to significant depths. Soft alluvial and marine clay deposits have very low bearing capacity and excessive settlement characteristics. This has design and maintenance implications for tall structures, large commercial buildings, as well as port and transport infrastructure constructed on such poor soils. Stabilising these very soft deposits is essential before commencing construction of infrastructure. A system of vertical drains combined with vacuum pressure and surcharge preloading has become an efficient and cost effective ground improvement option. This technique accelerates consolidation by promoting rapid radial flow which decreases the excess pore pressure while increasing the effective stress. This 4th Louis Menard lecture presents an overview of the theoretical and practical developments of soft ground improvement via prefabricated vertical drains, PVD (including natural fibre drains) and vacuum preloading, with application to selected case studies in Australia.
Indraratna, B, Heitor, A & Pathirage, P 1970, 'Acidic Groundwater Remediation in the Shoalhaven Floodplain', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 518-525.
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Indraratna, B, Shahin, MA & Salim, W 1970, 'A study of geotechnical characteristics of particulate media in rail track substructures', Geomechanics and Geotechnics of Particulate Media, International Symposium on Geomechanics and Geotechnics of Particulated Media, CRC Press, Ube, JAPAN, pp. 381-387.
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Inibhunu, C, Schauer, A, Redwood, O, Clifford, P & McGregor, C 1970, 'Predicting hospital admissions and emergency room visits using remote home monitoring data', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, pp. 282-285.
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© 2017 IEEE. The costs of lengthy hospital admissions (HA) and multiple emergency room visits (ER Visits) from patients with conditions such as heart failure (HF) and chronic obstructive pulmonary disease (COPD) can place a significant burden on healthcare systems. Understanding the various factors contributing to hospitalization and ER visits could aid cost-effective management in the delivery of services leading to potential improvement on quality of life for patients. This can be facilitated by collecting data using remoting patient monitoring (RPM) services and using analytics to discover important factors about patients. This paper presents our research that utilizes predictive modeling to determine key factors that are significant determinant to hospitalization and multiple ER Visits. The results shows that gender, past medical history and vital status are key factors to hospital admissions and ER Visits. Additionally, when a factor to indicate the period before, during and after an ER Visits was included, the resulting model shows a very high likelihood ratio and improved p values on all vital status. Our results shows that more research is needed to fully understand the temporal patterns among variables during hospitalization or ER visit.
Inibhunu, C, Schauer, A, Redwood, O, Clifford, P & McGregor, C 1970, 'The impact of gender, medical history and vital status on emergency visits and hospital admissions: A remote patient monitoring case study', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 278-281.
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© 2017 IEEE. Remote Program Monitoring (RPM) is considered to have potential to improve the quality of life on patients diagnosed with cardiac conditions such as heart failure (HF) and chronic obstructive pulmonary disease (COPD). Remote collection and analysis of patients data could aid in effective decision making on necessary care needed by patients monitored. This could lead to reduction on healthcare costs as well as improved outcomes for the patients. As a component of our predictive analytics research, this paper presents results of remote patient monitoring study of patients from the Cardiac Clinic of Southlake Regional Health Centre who were referred to WeCare for home based monitoring. Results indicate statistically significant evidence on impact of gender, medical history and vital status as risk factors for subsequent hospitalization and multiple emergency room visits.
Irga, PJ & Torpy, FR 1970, 'Can urban forestry really reduce air pollution? A field study on a city scale.', Green Infrastructure: Nature Based Solutions for Sustainable and Resilient Cities, Green Infrastructure: Nature Based Solutions for Sustainable and Resilient Cities, Orvieto, Italy.
Islam, M, Nadarajah, M & Hossain, J 1970, 'Dynamic behavior of transformerless PV system on the short-term voltage stability of distribution network', 2017 IEEE Power & Energy Society General Meeting, 2017 IEEE Power & Energy Society General Meeting (PESGM), IEEE, Chicago, IL, pp. 1-5.
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Islam, MA, Ball, JE, Zaman, AM & Rahman, SMM 1970, 'Challenge in Flood Forecasting Using Rating Curve of Unstable River Systems: The Brahmaputra', 37th World Congress of IAHR (International Association for Hydro-Environment Engineering and Research), World Congress of International Association for Hydro-Environment Engineering and Research, IAHR & USAINS HOLDING SDN BHD, Kuala Lumpur, pp. 4331-4336.
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A reliable and comprehensive flood warning system is one of the key factors to minimize damage anddisruption create by a flood. Ganges and Brahmaputra is the major river system of Bangladesh and authoritiesof Bangladesh use gauging data of this two rivers for their flood forecasting. This study only focuses onBrahmaputra River, which is still a morphologically very active river. This paper discusses how the predictioncan be biased using conventional method for flood prediction, i.e. using only stage-discharge relationship. Inthis study, we used 1,687 observations (discharge, water level, river width and cross-sectional area) atBahadurabad station of Brahmaputra River selected from 1976 to 2009. We examined the stationarity of rivercross-section and water level-discharge relationship. The study shows that the relationship between waterlevel and river flow changes every year significantly and without any indication which way it may change in thenext year. The relationship of stage discharge is so wide that the river may experience approximately doubleof the calculated flow. Therefore, river water management and flood forecasting would require comprehensivemethod rather than relying only on stage discharge correlation. Moreover, there is also trend in river geometrywhich may create more uncertainty in flood forecasting.
Islam, MS, Saha, SC, Sauret, E, Gu, YT & Molla, MM 1970, 'Numerical investigation of diesel exhaust particle transport and deposition in the CT-scan based lung airway', AIP Conference Proceedings, 7TH BSME INTERNATIONAL CONFERENCE ON THERMAL ENGINEERING, Author(s), Dhaka, Bangladesh.
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© 2017 Author(s). Diesel exhaust particulates matter (DEPM) is a compound mixture of gasses and fine particles that contain more than 40 toxic air pollutants including benzene, formaldehyde, and nitrogen oxides. Exposure of DEPM to human lung airway during respiratory inhalation causes severe health hazards like diverse pulmonary diseases. This paper studies the DEPM transport and deposition in upper three generations of the realistic lung airways. A 3-D digital airway bifurcation model is constructed from the computerized tomography (CT) scan data of a healthy adult man. The Euler-Lagrange approach is used to solve the continuum and disperse phases of the calculation. Local averaged Navier-Stokes equations are solved to calculate the transport of the continuum phase. Lagrangian based Discrete Phase Model (DPM) is used to investigate the particle transport and deposition in the current anatomical model. The effects of size specific monodispersed particles on deposition are extensively investigated during different breathing pattern. The numerical results illustrate that particle diameter and breathing pattern have a substantial impact on particles transport and deposition in the tracheobronchial airways. The present realistic bifurcation model also depicts a new deposition hot spot which could advance the understanding of the therapeutic drug delivery system to the specific position of the respiratory airways.
Islam, MZ, Yasmin Koli, MN & Esselle, KP 1970, 'Design and Improvement of Pattern Quality in Circularly Polarised Slot Array Antenna for Direct Broadcast Satellite Applications', 2017 2nd International Conference on Electrical & Electronic Engineering (ICEEE), 2017 2nd International Conference on Electrical & Electronic Engineering (ICEEE), IEEE, pp. 1-4.
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© 2017 IEEE. A circularly polarised radial line slot array antenna (CP-RLSA) is proposed in this paper for direct broadcast satellite applications. A new design suggestion has been introduced and investigated in this study to improve the performance and pattern quality of the antenna. The antenna is composed of spiral rings on the top plate and made with several thousand of slot pairs. The antenna supports waveguide like structure which is composed of air cavity and dielectric materials. An antenna prototype operating at 20 GHz was designed and simulated. The experimental measurements and simulation results show that the antenna has successfully satisfied the required technical specification. The antenna has achieved a maximum gain of 32.2 dBic at 19.4 GHz. The CP-RLSA antenna has demonstrated an radiation efficiency of 95.3% and a total efficiency of 90.3% at 20 GHz. The antenna has also fulfilled the condition of circular polarisation, i.e. axial ratio is below 3-dB level with appropriate radiation patterns. At the operating frequency 20 GHz, the antenna has achieved a gain of 28.1 dBic with side lobe level as low as-14.4 dB.
Ismaiel, B, Abolhasan, M, Smith, DB, Ni, W & Franklin, DR 1970, 'A Survey and Comparison of Device-to-Device Architecture Using LTE Unlicensed Band.', VTC Spring, IEEE Vehicular Technology Conference, IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Due to the rapid increase in data traffic, one of the solutions provided by mobile operators is to operate Long Term Evolution (LTE) in the unlicensed 5GHz band, as the licensed spectrum is becoming scarce. Mobile operators can expand their network capacity by operating LTE in the unlicensed band at lower cost when compared with using other licensed bands. Device to Device (D2D) communication, proven to be another effective way to enhance the capacity of a network, enables direct data exchange of localized traffic of users in proximity. Applying D2D communication to LTE unlicensed 5GHz band will further improve the network performance and user experience. In this article, we will discuss the new type of solutions that have been proposed for LTE operating in an unlicensed 5GHz band that includes; LTE-Unlicensed (LTE-U), LTE-License Assisted Access (LTE-LAA), LTE WiFi Link Aggregation (LWA), and MuLTEfire. We will discuss the important features along with their advantages and disadvantages and compare these technologies as well. We simulate LTE-LAA, LWA and MuLTEfire technologies in the presence of Wi-Fi hotspot and compare their results. Furthermore, we apply D2D communication to these technologies and from the results we conclude that MuLTEfire can increase the throughput drastically but network saturates quickly. Whereas, applying D2D communication with LWA is beneficial for a scalable network as it will not only increase the network throughput but will increase the network capacity as well.
Ismaiel, B, Abolhasan, M, Smith, DB, Ni, W & Franklin, DR 1970, 'Scalable MAC protocol for D2D communication for future 5G networks.', CCNC, 2017 14th IEEE Annual Consumer Communications & Networking Conference, IEEE, Las Vegas, NV, USA, pp. 542-547.
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© 2017 IEEE. Device-to-device communication (D2D) will be an integral part of 5G wireless networks. Device-to-Device (D2D) communication provide the additional resources to the cellular users for spatially reusing licensed/unlicensed spectrum by establishing direct communication. Although, D2D communication is gaining significant attention towards offloading traffic in heterogeneous networks in licensed band, no attention has been given to offload traffic in an unlicensed band in a centralized manner. However, a major challenge of D2D communication is managing resources in an efficient manner in a heterogeneous network. This paper will direct a new approach to D2D Communication and will present a scalable MAC protocol for D2D communications based on Point Coordination Function (PCF) access mechanism. The importance of PCF access mechanism is that it operates in a centralized manner and highly suitable for the dense environment, hence, can create a centralized control in a distributive manner. In this article, we propose an innovative three tier 5G architecture for D2D communication, which will offload cellular traffic from the cellular network to the WLAN in a dense environment. Moreover, we will present a new centralized scalable MAC protocol for D2D communication between WLAN users, based on the IEEE 802.11 Point Coordination Function (PCF) access mechanism. Our simulation results show that the proposed MAC scheme can increase the capacity of the network and perform better relative to the legacy Distributed coordination Function (DCF) defined in IEEE 802.11.
Israr, J, Indraratna, B & Rujikiatkamjorn, C 1970, 'Effect of the Level of Compaction on the Internal Erosion Potential for Granular Soils', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 1-10.
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Ivanyos, G, Qiao, Y & Venkata Subrahmanyam, K 1970, 'Constructive non-commutative rank computation is in deterministic polynomial time', Leibniz International Proceedings in Informatics, LIPIcs, Innovations in Theoretical Computer Science Conference, Schloss Dagstuhl, Berkeley, CA, USA, pp. 1-18.
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Let B be a linear space of matrices over a field F spanned by n × n matrices B1, . . . ,Bm. The non-commutative rank of B is the minimum r € N such that there exists U < Fn satisfying dim(U) - dim(B(U)) n - r, where B(U) := span(Ui2€[m]Bi (U)). Computing the non-commutative rank generalizes some well-known problems including the bipartite graph maximum matching problem and the linear matroid intersection problem. In this paper we give a deterministic polynomial-Time algorithm to compute the non-commutative rank over any field F. Prior to our work, such an algorithm was only known over the rational number field Q, a result due to Garg et al, [20]. Our algorithm is constructive and produces a witness certifying the non-commutative rank, a feature that is missing in the algorithm from [20]. Our result is built on techniques which we developed in a previous paper [24], with a new reduction procedure that helps to keep the blow-up parameter small. There are two ways to realize this reduction. The first involves constructivizing a key result of Derksen and Makam [12] which they developed in order to prove that the null cone of matrix semi-invariants is cut out by generators whose degree is polynomial in the size of the matrices involved. We also give a second, simpler method to achieve this. This gives another proof of the polynomial upper bound on the degree of the generators cutting out the null cone of matrix semi-invariants. Both the invariant-Theoretic result and the algorithmic result rely crucially on the regularity lemma proved in [24]. In this paper we improve on the constructive version of the regularity lemma from [24] by removing a technical coprime condition that was assumed there.
Iversen, TF, Ellekilde, L-P & Miro, JV 1970, 'Adaptive motion planning in bin-picking with object uncertainties', 2017 17th International Conference on Control, Automation and Systems (ICCAS), 2017 17th International Conference on Control, Automation and Systems (ICCAS), IEEE, Jeju, South Korea, pp. 921-928.
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© 2017 Institute of Control, Robotics and Systems - ICROS. Doing motion planning for bin-picking with object uncertainties requires either a re-grasp of picked objects or an online sensor system. Using the latter is advantageous in terms of computational time, as no time is wasted doing an extra pick and place action. It does, however, put extra requirements on the motion planner, as the target position may change on-the-fly. This paper solves that problem by using a state adjusting Partial Observable Markov Decision Process, where the state space is modified between runs, to better fit earlier solved problems. The approach relies on a set of waypoints, containing information about which parts of the state space may contain feasible solutions. Waypoints are pushed around the state space by observing which states in the neighborhood lead to successfully solved problems. Two bin-picking scenarios are modeled with the proposed method. One scenario in which the system receives an object pose update while moving towards the place position. Another where the update includes the object type being grasped out of a fixed number of options, each class to be deposited in a different place. When an online POMDP solver is utilized, the state adjusting POMDP is improving performance by up to 28% on execution times compared to a not adjusted POMDP.
Jadidi, MG, Patel, M & Miro, JV 1970, 'Gaussian processes online observation classification for RSSI-based low-cost indoor positioning systems', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, Singapore, pp. 6269-6275.
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© 2017 IEEE. In this paper, we propose a real-time classification scheme to cope with noisy Radio Signal Strength Indicator (RSSI) measurements utilized in indoor positioning systems. RSSI values are often converted to distances for position estimation. However due to multipathing and shadowing effects, finding a unique sensor model using both parametric and non-parametric methods is highly challenging. We learn decision regions using the Gaussian Processes classification to accept measurements that are consistent with the operating sensor model. The proposed approach can perform online, does not rely on a particular sensor model or parameters, and is robust to sensor failures. The experimental results achieved using hardware show that available positioning algorithms can benefit from incorporating the classifier into their measurement model as a meta-sensor modeling technique.
Jamborsalamati, P, Fernandez, E, Hossain, MJ & Rafi, FHM 1970, 'Design and implementation of a cloud-based IoT platform for data acquisition and device supply management in smart buildings', 2017 Australasian Universities Power Engineering Conference (AUPEC), 2017 Australasian Universities Power Engineering Conference (AUPEC), IEEE, pp. 1-6.
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© 2017 IEEE. Increased numbers of installed IoT devices and more complex building management algorithms make vital a secure, reliable, and cloud-based IoT platform, offering provisions for devices to communicate and react to predefined situations. This platform facilitates data acquisition, management, and interactions among IoT devices in order to exchange information including measurement data and control signals with controllers via a two-way communication mechanism. In this paper, an IoT platform to implement a device-supply management algorithm in a smart building, aiming to supply higher-priority devices from solar power and to maximize solar-power utilization, has been designed and implemented. Message Queue Telemetry Transport (MQTT), which is the state-of-the-art Internet of Things (IoT) protocol, has been adopted in this work to incorporate communications between the devices and the controller. MQTT publisher and subscriber are deployed in the Python programming language. A cloud-based data aggregation platform has been used with an interface to MATLAB, in which the device management algorithm runs. From the results, it could be observed that the IoT platform successfully achieves the goals of the designed device-supply management algorithm.
Jamborsalamati, P, Sadu, A, Ponci, F, Monti, A & Hossain, MJ 1970, 'Improvement of supply restoration in multi-spare-feeder active distribution grids using IEC 61850', 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, pp. 1-5.
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© 2017 IEEE. Automating the entire process of Fault Location, Isolation, and Service Restoration (FLISR) can significantly reduce the minutes of interruption (caused by a fault) in distribution grids. Consequently, it can reduce the penalties paid by utilities for the outage of the end customers. This could be achieved through implementation of cyber-physical systems (CPS) which are made of Intelligent Electronic Devices (IEDs) capable of reliable and fast communications. This paper proposes a novel distributed FLISR algorithm which optimizes previously developed supply restoration strategies in terms of minimizing the losses in the grid. Furthermore, the test-case scenario considered in this paper is closer to real-world scenarios wherein there are multiple spare feeders which could be utilized in supply restoration strategies after fault occurrence. The proposed algorithm is paired with the GOOSE communication protocol presented in IEC61850 and is implemented in a real-time Hardware-in-the-Loop (HIL) platform using the Real Time Digital Simulator (RTDS). From results it can be concluded that the improved service restoration algorithm in this paper successfully selects the spare feeder with less losses and connects that to the non-faulty loads properly.
Jamborsalamati, P, Sadu, A, Ponci, F, Monti, A & Hossain, MJ 1970, 'Improvement of Supply Restoration in Multi-Spare-Feeder Active Distribution Grids using IEC 61850', 2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 7th IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, NEW ZEALAND, Univ Auckland, Auckland, pp. 67-71.
Jayan Chirayath Kurian, J, Watkins, J & Macallum, K 1970, 'User-generated content on the Facebook page of Emergency Management Organizations: Perspectives of Emergency Management Administrators', Sydney.
Ji, L-Y, Zhu, H-L, Qin, P-Y & Guo, YJ 1970, 'Broadband partially reflective surface antenna with tapered corrugated ground', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, USA, pp. 509-510.
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© 2017 IEEE. This paper proposes a broadband Partially Reflective Surface antenna. It consists of a U-slot microstrip antenna as the source, an FR4 superstrate as the partially reflective surface, and a tapered corrugated ground structure. By employing the corrugated ground, the 3dB gain bandwidth is improved from 17% to 24% with the maximum realized gain and the 10dB impedance bandwidth unchanged. Therefore, the corrugated ground structure can be a good candidate to enhance the gain bandwidth of PRS antennas.
Ji, Z 1970, 'Compression of quantum multi-prover interactive proofs', Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, STOC '17: Symposium on Theory of Computing, ACM, Montreal, Canada, pp. 289-302.
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© 2017 ACM. We present a protocol that transforms any quantum multi-prover interactive proof into a nonlocal game in which questions consist of logarithmic number of bits and answers of constant number of bits. As a corollary, it follows that the promise problem corresponding to the approximation of the nonlocal value to inverse polynomial accuracy is complete for QMIP∗, and therefore NEXP-hard. This establishes that nonlocal games are provably harder than classical games without any complexity theory assumptions. Our result also indicates that gap amplification for nonlocal games may be impossible in general and provides a negative evidence for the feasibility of the gap amplification approach to the multi-prover variant of the quantum PCP conjecture.
Jia, M, Srinivasan, R, Ries, R, Bharathy, G, Silverman, B & Weyer, N 1970, 'An Agent-Based Model Approach for Simulating Interactions between Occupants and Building Systems', Building Simulation Conference Proceedings, 2017 Building Simulation Conference, IBPSA, pp. 1787-1793.
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Building occupants are one of the most dominant variable factors in building energy consumption. However, current building performance simulation engines incorporate occupant information as simple, static profiles, which lead to discrepancy in actual energy use as occupants interact with building systems in an active manner, i.e., occupant behavior over time is not captured by simulation algorithms. The need for modeling energy-related occupant behavior dynamically in energy simulation tools to increase prediction capability cannot be understated. This paper proposes a possible solution by discussing the use of a Performance Moderator Functions testbed (PMFserv) - a well-tested Agent-Based Modeling (ABM) tool, for occupant behavior modeling and its potential integration with energy simulation engine, EnergyPlus'. In order to extend PMFserv to buildings for improving energy estimation, a thermal zone in an educational building is tested and observed using sensing technologies. The study explores the interactions between occupants and building using cognitively detailed ABM, as well as the impact of occupant behavior on building energy use.
Jian, S, Cao, L, Pang, G, Lu, K & Gao, H 1970, 'Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 1937-1943.
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Learning the representation of categorical data with hierarchical value coupling relationships is very challenging but critical for the effective analysis and learning of such data. This paper proposes a novel coupled unsupervised categorical data representation (CURE) framework and its instantiation, i.e., a coupled data embedding (CDE) method, for representing categorical data by hierarchical value-to-value cluster coupling learning. Unlike existing embedding- and similarity-based representation methods which can capture only a part or none of these complex couplings, CDE explicitly incorporates the hierarchical couplings into its embedding representation. CDE first learns two complementary feature value couplings which are then used to cluster values with different granularities. It further models the couplings in value clusters within the same granularity and with different granularities to embed feature values into a new numerical space with independent dimensions. Substantial experiments show that CDE significantly outperforms three popular unsupervised embedding methods and three state-of-the-art similarity-based representation methods.
Jiang, J, Chaczko, Z, Al-Doghman, F & Narantaka, W 1970, 'New LQR Protocols with Intrusion Detection Schemes for IOT Security', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 466-474.
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© 2017 IEEE. Link quality protocols employ link quality estimators to collect statistics on the wireless link either independently or cooperatively among the sensor nodes. Furthermore, link quality routing protocols for wireless sensor networks may modify an estimator to meet their needs. Link quality estimators are vulnerable against malicious attacks that can exploit them. A malicious node may share false information with its neighboring sensor nodes to affect the computations of their estimation. Consequently, malicious node may behave maliciously such that its neighbors gather incorrect statistics about their wireless links. This paper aims to detect malicious nodes that manipulate the link quality estimator of the routing protocol. In order to accomplish this task, MINTROUTE and CTP routing protocols are selected and updated with intrusion detection schemes (IDSs) for further investigations with other factors. It is proved that these two routing protocols under scrutiny possess inherent susceptibilities, that are capable of interrupting the link quality calculations. Malicious nodes that abuse such vulnerabilities can be registered through operational detection mechanisms. The overall performance of the new LQR protocol with IDSs features is experimented, validated and represented via the detection rates and false alarm rates.
Jiang, J, Gao, L, Jin, J, Luan, TH, Yu, S, Yuan, D, Xiang, Y & Yuan, D 1970, 'Towards an Analysis of Traffic Shaping and Policing in Fog Networks Using Stochastic Fluid Models', Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2017: Computing, Networking and Services, ACM, Melbourne, AUSTRALIA, pp. 196-204.
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Jiang, J, Gao, L, Yu, S, Jin, J & Yuan, D 1970, 'Preferential attachment and the spreading influence of users in online social networks', 2017 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), IEEE/CIC International Conference on Communications in China (ICCC), IEEE, PEOPLES R CHINA, Qingdao, pp. 690-695.
Jiang, J, Wen, S, Yu, S, Xiang, Y, Zhou, W & Hassan, H 1970, 'The structure of communities in scale‐free networks', Concurrency and Computation: Practice and Experience, Wiley, pp. e4040-e4040.
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SummaryScale‐free networks are often used to model a wide range of real‐world networks, such as social, technological, and biological networks. Understanding the structure of scale‐free networks evolves into a big data problem for business, management, and protein function prediction. In the past decade, there has been a surge of interest in exploring the properties of scale‐free networks. Two interesting properties have attracted much attention: the assortative mixing and community structure. However, these two properties have been studied separately in either theoretical models or real‐world networks. In this paper, we show that the structural features of communities are highly related with the assortative mixing in scale‐free networks. According to the value of assortativity coefficient, scale‐free networks can be categorized into assortative, disassortative, and neutral networks, respectively. We systematically analyze the community structure in these three types of scale‐free networks through six metrics: node embeddedness, link density, hub dominance, community compactness, the distribution of community sizes, and the presence of hierarchical communities. We find that the three types of scale‐free networks exhibit significant differences in these six metrics of community structures. First, assortative networks present high embeddedness, meaning that many links lying within communities but few links lying between communities. This leads to the high link density of communities. Second, disassortative networks exhibit great hubs in communities, which results in the high compactness of communities that nodes can reach each other via short paths. Third, in neutral networks, a big portion of links act as community bridges, so they display sparse and less compact communities. In addition, we find that (dis)assortative networks show hierarchical community structure with power‐law‐distributed community sizes, while neutral ...
Jiang, S, Zhang, C, Zhang, Y, Zhang, W, Lin, X, Cheema, MA & Wang, X 1970, 'DSKQ: A System for Efficient Processing of Diversified Spatial-Keyword Query', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Australasian Database Conference, Springer International Publishing, Brisbane, QLD, Australia, pp. 280-284.
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© 2017, Springer International Publishing AG. With the rapid development of mobile portable devices and location positioning technologies, massive amount of geo-textual data are being generated by a huge number of web users on various social platforms, such as Facebook and Twitter. Meanwhile, spatial-textual objects that represent Point-of-interests (POIs, e.g., shops, cinema, hotel or restaurant) are increasing pervasively. Consequently, how to retrieve a set of objects that best matches the user’s submitted spatial keyword query (SKQ) has been intensively studied by the research communities and commercial organisations. Existing works only focus on returning the nearest matching objects, although we observe that many real-life applications are now using diversification to enhance the quality of the query results. Thus, existing methods fail to solve the problem of diversified SKQ efficiently. In this demonstration, we introduce DSKQ, a diversified in-memory spatial-keyword query system, which considers both the textual relevance and the spatial diversity of the results processing on road network. We present a prototype of DSKQ which provides users with an application-based interface to explore the diversified spatial-keyword query system.
Jiang, Z, Huynh, DQ, Zhang, J & Wu, Q 1970, 'Part-Based Data Association for Visual Tracking', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, NSW, Australia, pp. 1-8.
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© 2017 IEEE. We present a method that integrates a part-based sparse appearance model in a Bayesian inference framework for tracking targets in video sequences. We formulate the sparse appearance model as a set of smoothed colour histograms corresponding to the object windows detected by the Deformable Part Model (DPM) detector. The data association of each body part between frames is solved based on the position constraint, appearance coherence, and motion consistency. To deal with missing and noisy observations, the part detection window in the following frame is also predicted using an interacting multiple model (IMM) tracker. We have tested our tracking method on all the video sequences that involve people in upright poses from the TB-50 and TB-100 benchmark videos datasets. Our experimental results show that our tracking method outperforms six state-of-the-art tracking techniques.
Jiao, S, Zhang, X, Yu, S, Song, X & Xu, Z 1970, 'Joint Virtual Network Function Selection and Traffic Steering in Telecom Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-7.
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© 2017 IEEE. Following the trend of Network Function Virtualization (NFV), telecom operators widely deploy diverse types of Virtual Network Functions (VNF) (such as firewall, load balancer, and proxy, etc.) on specified software-defined middlebox at various network locations. Traffic needs to go through the desired VNFs according to pre-defined policies, which forms a Service Function Chain (SFC). However, how to maximize traffic throughput with end-to-end latency guaranteed when steering SFC requests is still an open problem. To this end, we study a joint optimization of VNF selection and traffic steering problem in telecom networks. Firstly, we formulate this problem as an Integer Linear Programming (ILP) model. Then, we design an efficient heuristic algorithm based on dynamic programming. Extensive simulation results show that compared with the previous algorithms, our algorithm can increase 30.86% throughput of SFC requests while guaranteeing end-to-end latency requirement.
Jupp, J 1970, '4D BIM for Environmental Planning and Management', Procedia Engineering, Elsevier BV, Sydney, pp. 190-201.
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© 2017 The Authors. For more than a decade research has shown that 4D Building Information Modelling (BIM) can improve construction planning, scheduling and production control as well as the onsite management of safety, workspaces and waste. The increasing use of 4D BIM in construction highlights opportunities for utilising these capabilities in new digital management systems replete with role reorganization, new practices and workflows, and not solely as a tool for constructability analysis and onsite monitoring of construction progress. Continued focus on construction-based environmental impacts provides an impetus to leverage 4D BIM to improve communication and information flow throughout environmental planning and management tasks. This paper explores how environmental planning and management can be supported by 4D capabilities. 4D modelling and analysis technologies combined with structured workflows are presented as the basis for developing a tailored framework for environmental planning and management. Five functional prerequisites necessary to the collaborative development and onsite monitoring of environmental management systems are identified before laying out the directions for future research.
Jupp, J & Awad, R 1970, 'BIM-FM and Information Requirements Management: Missing Links in the AEC and FM Interface', IFIP Advances in Information and Communication Technology, 14th IFIP WG 5.1 International Conference on Product Lifecycle Management, Springer International Publishing, Seville, Spain, pp. 311-323.
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© IFIP International Federation for Information Processing 2017. A steady shift in the value added from building information modelling (BIM) to architectural, engineering and construction (AEC) activities to those of facilities management (FM) is seeing increasing emphasis on whole-of-life thinking and associated information requirements management practices. Little is known about the process of identifying, documenting, generating and harmonizing BIM data inputs with FM data outputs in the Australian construction industry. Grounded on empirical evidence from a case study that transverses client and project team perspectives, this exploratory paper identifies missing links in the AEC and FM interface. The study describes the issues surrounding the collection and harmonization of BIM data inputs (as-built deliverables at handover) and the identification of (and connection to) FM data outputs. With the limitation of an exploratory and interpretive case study, the intention is to provide a contribution to academics and practitioners with grounded, stakeholder-related insights.
Jusufi, A, Hayati, HH, Eager, DE & Tucker, BT 1970, 'Exploration of Rapid Sprinting Dynamics of Tetrapod utilizing IMUs', The 8th International Symposium on Adaptive Motion of Animals and Machines (AMAM 2017) Japan, The 8th International Symposium on Adaptive Motion of Animals and Machines (AMAM 2017) Japan.
Kabir, MA, Monjurul Hasan, ASM, Hasan Sakib, T & J Hamim, S 1970, 'Challenges of photovoltaic based hybrid minigrid for off-grid rural electrification in Bangladesh', 2017 4th International Conference on Advances in Electrical Engineering (ICAEE), 2017 4th International Conference on Advances in Electrical Engineering (ICAEE ), IEEE, pp. 686-690.
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Kafle, YR, Hasan, SU, Kashif, M, Hossain, J & Town, GE 1970, 'A new PWM Shoot-through control for voltage-fed quasi-z-source DC/DC converters', 2017 IEEE International Telecommunications Energy Conference (INTELEC), 2017 IEEE International Telecommunications Energy Conference (INTELEC), IEEE, Gold Coast, AUSTRALIA, pp. 494-497.
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Kalantar, B, Moneir, AAA, Mansor, SB & Pradhan, B 1970, 'The use of random forest and object-based image classification for thematic map creation: A case study of Kelantan, Malaysia', 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, 38th Asian Conference on Remote Sensing 2017, New Delhi, India.
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This paper presented results of creation of thematic map for Kelantan city using an integration of object-based analysis and random forest algorithm. The thematic map was generated based on SPOT image with a spatial resolution of 5 m. Object-based analysis was used for its advantages over per-pixel based methods. On the other hand, random forest algorithm was selected because it was suggested in very recent literature and it has advantages ofgood generalization.A thematic map with sixclasses was generated with an overall accuracy and kappa index of 92% and 0.90, respectively using the proposed method. Other details are included in the paper.
Kale, A & Chaczko, Z 1970, 'iMuDS: An Internet of Multimodal Data Acquisition and Analysis Systems for Monitoring Urban Waterways', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 431-437.
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© 2017 IEEE. Freshwater monitoring is becoming an essential activity due to limited availability of drinking water and an increasing presence of various pollutants. Tons of toxic waste added to water sources everyday contributes to the decrease in the planet's biodiversity and even an extinction of many species of animals and marine life. Many millions of birds perish each year due to waterway pollution. New technologies such as the Internet of Things (IoT), Wireless Sensor Networks and computer vision allow us to monitor fresh water sources in a continuous mode. To minimize the effects of pollution, various monitoring activities can be planned and executed for very large areas and geographical regions. This work presents a system architecture for the IoT-based multimodal data acquisition and analysis system. The idea is to deploy sensor clusters in various locations of a waterway to create a network of sensing and measuring smart devices. Every cluster of such devices can be perceived as a 'thing'. Such a 'thing' or a node has camera sensing modalities for a macro level pollution detection with analog sensors to measure microlevel water parameters. Our solution involves a low power microprocessor devices provisioned to capture raw data, extract features from the raw data and then transmit these data to the Cloud for further analysis and reporting. A 5G mobile network communication is used for data transmission. The Cloud server runs a software framework that supports a sophisticated analysis and trending of various environmental parameters such as surface density of water, salinity, temperature, etc. The proposed software framework has a set of computational algorithms to process features supplied by each node. These algorithms can classify features into various classes like floating objects, water salinity level, etc. An experiment to simulate the 'IoT' data acquisition is conducted to validate the proposed solution. Based on a case study, this soluti...
Kamal, MS, Parvin, S, Saleem, K, Al-Hamadi, H & Gawanmeh, A 1970, 'Efficient low cost supervisory system for Internet of Things enabled smart home', 2017 IEEE International Conference on Communications Workshops (ICC Workshops), 2017 IEEE International Conference on Communications Workshops (ICC Workshops), IEEE, pp. 864-869.
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Karamanakos, P, Geyer, T & Aguilera, RP 1970, 'Computationally efficient long-horizon direct model predictive control for transient operation', 2017 IEEE Energy Conversion Congress and Exposition (ECCE), 2017 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Cincinnati, OH, USA, pp. 4642-4649.
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© 2017 IEEE. In this paper we present modifications in the sphere decoder initially introduced in [1] and modified in [2] that allow for its implementation in transient operation. By investigating the geometry of the integer problem underlying direct model predictive control (MPC), a new sphere that guarantees feasibility and includes a significant smaller number of candidate solutions is computed. In a first analysis, the computational complexity can be reduced by up to 99.7% when a variable speed drive system consisting of a three-level neutral point clamped (NPC) voltage source inverter and a medium-voltage induction machine is examined. As also shown, optimality is sacrificed only to a limited extent, thus maintaining the very fast transient response inherent to direct MPC.
Karimi, M, Croaker, P, Skvortsov, A & Kessissoglou, N 1970, 'Computation of flow-generated sound of a flat plate using a hybrid RANS-BEM technique', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, 46th International Congress and Exposition on Noise Control Engineering, Hong Kong, China.
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A hybrid computational fluid dynamics - boundary element method (BEM) technique is used to predict the self-noise generated by a flat plate immersed in low Mach number flow. Reynolds-Averaged Navier-Stokes equations are used to estimate the turbulent boundary layer parameters such as convective velocity, boundary layer thickness and wall shear stress over the surface of the flat plate. The spectrum of the wall pressure fluctuations is evaluated from the turbulent boundary layer parameters and by using semi-empirical models. The cross spectrum density function of turbulent boundary layer pressure is represented as the result of a combination of uncorrelated wall pressure plane waves. An acoustic BEM solver is then used to compute acoustic pressure scattered by the flat plate from the synthesised wall pressure field corresponding to each realisation of uncorrelated wall plane waves. Finally, the acoustic response of the plate subject to turbulent boundary layer excitation is obtained by an ensemble average of the different realisations. The results from the hybrid technique are presented for turbulent flow past a flat plate, with Reynolds number based on chord Rec =4:9x105. The computed aeroacoustic results are compared with experimental data from literature.
Karmokar, DK & Guo, YJ 1970, 'Planar leaky-wave antennas for low-cost radar', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Verona, ITALY, pp. 112-115.
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Kashif, M, Hossain, MJ, Kafle, YR & Rahman, MS 1970, 'A comparative study of two current-control techniques applied to a three-phase three-level active power filter', 2017 IEEE International Telecommunications Energy Conference (INTELEC), 2017 IEEE International Telecommunications Energy Conference (INTELEC), IEEE, Gold Coast, AUSTRALIA, pp. 357-362.
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Kashif, M, Hossain, MJ, Zhuo, F, Shuhuai Shi & Soon, JL 1970, 'An advanced harmonic extraction technique applied to a three-phase three-level active power filter', 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), IEEE, Kaohsiung, TAIWAN, pp. 364-369.
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Katare, KK, Biswas, A & Esselle, KP 1970, 'Directive array based pattern reconfigurable antenna', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, FRANCE, pp. 2029-2032.
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Katare, KK, Biswas, A & Esselle, KP 1970, 'Gain enhancement of pattern diversity antenna by improving phase uniformity', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, FRANCE, pp. 2033-2036.
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Katic, M, Agarwal, R & Al-Kilidar, H 1970, 'The Interplay Between Flexibility and Innovation within High-Variety, Low-Volume Manufacturing', Production and Operations Management Society 2017 International Conference, Sydney, Australia.
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Innovation and flexibility have long been understood as key elements in the competitive repertoire of todays’ manufacturing SME (Small to Medium Sized Enterprise). For SME’s that produce a high variety of customised products at low volumes (HVLV), the necessity to innovate and simultaneously maintain flexibility poses a significant organisational challenge.HVLV manufacturers are typically designed in such a manner to enable the manufacture of a wide range of highly customised products. The organisational success of the HVLV manufacturer, then, largely depends on its’ ability to reconfigure resources and adapt to new circumstances (in other words, the ability to be flexible). In fact, it is in the pursuit of flexibility that HVLV manufacturers choose to adopt the job-shop style of production and “project-based” organisational structure. There is evidence which suggests flexibility and innovation are complementary in the realm of mass-customisation. Yet, authors investigating the adoption of “project-based” organisational forms (as observed in HVLV manufacturing) warn the quest for “fast, flat and flexible” organisational designs often result in environments which hinder innovation. Indeed, the applicability of organisational practices designed to foster flexibility and its effects on the ability of a HVLV manufacturer to innovate requires further investigation – thus, a core objective of this paper.In order to achieve this objective, this paper provides two outcomes. Firstly, a comparative analysis based on a literature review is undertaken between HVLV manufacturers and those adopting lesser, more standardised, forms of customisation. This will determine key differences in both flexibility dimensions and the organisational practices designed to facilitate this flexibility. Secondly, a conceptual model is developed (based on the comparative analysis) to demonstrate the relationship between key flexibility dimensions and the likelihood of developing suc...
Katic, M, Al-Kilidar, H & Agarwal, R 1970, 'Exploring the Effect of Customisation on Management Practices in High-Variety, Low-Volume Manufacturing', 24th International Annual EUROMA Conference, EUROMA International Conference, Edinburgh.
Kha, VA, Nguyen, DN, Kha, HH & Dutkiewicz, E 1970, 'Dynamic stopping using eSVM scores analysis for event-related potential brain-computer interfaces', 2017 11th International Symposium on Medical Information and Communication Technology (ISMICT), 2017 11th International Symposium on Medical Information and Communication Technology (ISMICT), IEEE, Lisbon, Portugal, pp. 82-85.
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© 2017 IEEE. In brain-computer interface (BCI) research, there must be a trade-off between accuracy and speed of the BCI system, especially those based on event-related potentials (ERPs). This paper proposes a novel method which can significantly increase the spelling bit rate while also maintaining the desired accuracy. We provide an adaptive real-time stopping method based on the scores of ensemble support vector machine classifiers. We apply a criteria assessment process on the classifiers' scores to dynamically stop the ERP-evoked paradigms at any flashing sequence. Our experiments were conducted on three different P300-Speller data sets (BCI Competition II, BCI Competition III and Akimpech). Our proposed framework significantly outperformed the related state-of-the-art studies in terms of character output accuracy and elicitation bit rate rise between static and dynamic stopping schemes. We improve the average bit rate by over 80% while perfectly maintaining the best original static accuracy of over 96%.
Khademlahashy, A, Li, L, Every, J & Zhu, J 1970, 'A review on protection issues in micro-grids embedded with distribution generations', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 913-918.
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© 2017 IEEE. According to recent developments, the application of distributed generations (DGs) has become popular especially in distribution systems. The high utilization of distributed generating resources in modern power systems can cause new challenges from protection coordination perspectives. Changing the distribution system structure from single-supply radial system to multi-source ring network, leads to the bidirectional power flow and also has a vital impact on protection coordination issues. In addition, micro-grids can be operated under grid-connected as well as islanded mode, and fault current is extensively different for these two operation modes. Therefore, traditional protection algorithms cannot be used in the advancement of power systems. In recent years, several research studies have been conducted to investigate the improvement of protection schemes in micro-grids. This paper presents a comprehensive review on protection problems resulting from micro-grids embedded with DGs, and discusses some alternate protection strategies.
Khademlahashy, A, Mehta, G, Li, L & Zhu, J 1970, 'Impact of using current limiting reactor on the existing circuit breakers in micro-grids', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. Recently, distributed generations (DGs) have been widely used in distribution networks. Using DGs in the grid-connected mode leads to increase of the fault current level. This increase can affect the existing equipment especially circuit breakers (CBs) and operation of overcurrent relays. Current limiting reactor (CLR) has been proposed to reduce the effect of micro-grids (MGs) on the existing protection scheme during fault conditions by many researchers. However, there are some factors for interrupting the current by CBs which do not only depend on the fault current magnitude. Transient recovery voltage (TRV) and rate of rise recovery voltage (RRRV) can also affect the operation of CBs. This paper presents the equivalent analysis of the TRV and RRRV across a CB connected with a CLR. The transient stability is studied through simulation of a practical network, which shows the impact of using CLRs on the burden of CBs. In addition, some possible solutions are studied in this paper.
Khademlahashy, A, Mehta, G, Li, L & Zhu, J 1970, 'Lifetime evaluation of HV transformers', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-5.
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© 2017 IEEE. Power transformers are one of the most important equipment in power substations and distribution systems. As its price is about 55% of the whole substation price, it can be called the valuable element in the power grid. Thus, the lifetime management based on economical and technical indexes is highly essential for facilitating asset management and achieving higher reliability in the power system. This study presents the factors that can affect ageing transformers and analyzes oil test parameters. Dissolved gas analysis (DGA) is performed and some existing methods for evaluating of transformer operation based on DGA are compared. The pros and cons of each method are shown and a simple method to assess transformer condition is found. Also, three power transformers with real values and oil samples are studied for lifetime evaluation, and some possible solutions are proposed for better operation and maintenance.
Khalifa, NH, Nguyen, QV, Simoff, S & Catchpoole, D 1970, 'Interaction Visualisation of Complex Genomic Data with Game Engines', 2017 21st International Conference Information Visualisation (IV), 2017 21st International Conference on Information Visualisation (IV), IEEE, pp. 133-139.
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Graphic game engines have introduced even more advanced technologies to improve the rendering, image quality, ergonomics, and user experience of their creations by providing user-friendly yet powerful tools to design and develop new games. There are thousands of genes in the human genome that contain information about specific individual patients and the biological mechanisms of their diseases. The complexity in biomedical and genomic data usually requires effective visual information processing and analytics. Unfortunately, available visualisation techniques for this domain are limited, many in static forms. The open study questions here are as follow: Are there lessons to be learnt from these video games? Or could the game technology help us explore new graphic ideas accessible to non-specialists? This paper presents a visual analytics model that enables the analysis of large and complex genomic data using Unity3D game technology. This includes an interactive visualisation, providing an overview of the patient cohort with a detailed view of the individual genes. We illustrate the effectiveness of our approach in guiding the effective treatment decision in the cohort through datasets from the childhood cancer B-Cell acute lymphoblastic leukaemia.
Khallaf, M & Jupp, J 1970, 'Performance-based Design of Tall Building Envelopes using Competing Wind Load and Wind Flow Criteria', Procedia Engineering, Elsevier BV, Sydney, pp. 99-109.
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This paper investigates performance-based tall building design and the development of an architectural and urban design method that focus on the effects of wind loads on- and wind flows around tall buildings. The paper provides an overview of related buildings codes and city development design guidelines that define the requirements of structural façade wind loading and urban ventilation. A review of performance-based design methods for the generation, analysis and optimization of buildings is also presented. Within this frame, an approach to performancebased tall building envelope design is proposed. The approach is aimed at addressing wind loading and wind impact requirements based on generative parametric modelling and performance analysis that integrates physical parameters at the architectural and urban scales and performance criteria can support filtering and optimization relative to prevailing wind conditions.
Khan, I, Castel, A & Gilbert, RI 1970, 'Early-age tensile creep and drying shrinkage in GGBFS concrete', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, pp. 91-96.
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This study aims to observe the effect of supplementary cementitious materials (in this case, Ground Granulated Blast Furnace Slag GGBFS) on early age shrinkage, tensile creep and the age of cracking in restrained elements. Dog-bone shaped specimens were tested in portable creep rigs specifically designed to undertake direct tension tests. The specimens were loaded at the age of 2 days and shrinkage was measured on accompanying specimens. Restrained ring tests were also performed. Two concrete mixes were used in this study. The first contained 100% Ordinary Portland Cement (OPC), while in the second mix, 30% OPC by weight was replaced by GGBFS. Tensile creep and drying shrinkage were found to be significantly larger for the GGBFS concrete than for OPC concrete. The cracking age of GGBFS concrete was found to be less than that of the OPC concrete.
Khan, M, Castel, A, Akbarnezhad, A, Foster, SJ & Smith, M 1970, 'Performance of low calcium fly ash geopolymer concrete with steel furnace slag coarse aggregate', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, pp. 1847-1851.
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This paper evaluates the performance of Steel Furnace Slag (SFS) coarse aggregate in blended slag and low calcium fly ash geopolymer concrete (GPC). The geopolymer binder is composed of 90% of low calcium fly ash and 10% of Ground Granulated Blast Furnace Slag (GGBFS). Mechanical properties, shrinkage, and detailed microstructure analysis were carried out. The results showed that geopolymer concrete with SFS aggregate offered higher compressive strength and elastic modulus than that of GPC with traditional aggregate. The shrinkage results showed no expansion or swelling due to delayed calcium oxide (CaO) hydration after 320 days. No traditional porous Interfacial Transition Zone (ITZ) was detected using scanning electron microscopy, indicating a better bond between SFS aggregate and geopolymer matrix. Energy dispersive spectroscopy results further revealed calcium (Ca) diffusion at the vicinity of ITZ. Raman spectroscopy results showed no new crystalline phase formed due to Ca diffusion. The incorporation of Ca into the geopolymer structure and better bond between SFS aggregate and geopolymer matrix are the most likely reason for the higher compressive strength observed in GPC with SFS aggregate.
Khoa, NLD, Anaissi, A & Wang, Y 1970, 'Smart Infrastructure Maintenance Using Incremental Tensor Analysis', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM.
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Khokle, R, Esselle, K, Heimlich, M & Bokor, D 1970, 'Orthopaedic implant micromotion sensing using an eddy current sensor', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, AUSTRALIA, pp. 125-128.
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Khokle, RP, Esselle, KP, Heimlich, M & Bokor, D 1970, 'Design of a miniaturized bone implantable antenna for a wireless implant monitoring device', Loughborough Antennas & Propagation Conference (LAPC 2017), Loughborough Antennas & Propagation Conference (LAPC 2017), Institution of Engineering and Technology.
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© 2017 Institution of Engineering and Technology. All rights reserved. In this paper, we present a spiral loop type antenna, implanted in the tibial bone. The antenna has been designed for fabrication on commercially available RT Duroid 6010 (Hr =10.2) substrate and encapsulated in biologically compatible Polydimethylsiloxane (PDMS) material (Hr=2.6). The antenna has a footprint of 2.6mm x 2.6 mm and a height of 1.94 mm. The antenna operates at the 2.4 GHz ISM band with the peak gain of -36.2 dBi.
Khonasty, R, Carmichael, MG, Liu, D & Aldini, S 1970, 'Effect of external force and bimanual operation on upper limb pose during human-robot collaboration', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 81-89.
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During physical Human-Robot Interaction (pHRI) in industrial applications such as human-robot collaborative abrasive blasting, the operator often interacts with the robot using two hands, exchanging forces through handle bars. For the robot to provide appropriate assistance to the operator and for safe interaction, it would be benefficial for the robot to know the pose of the user. This problem is often challenging due to environmental factors, limited sensing capability in the environment and the robot, and redundancy of the human upper-limb. This paper presents experimental study on how two-hand interaction and force exchange affect the operators upper-limb pose, which can be characterized by swivel angle. The poses of ten subjects were recorded as they interacted with a collaborative robot. Differences in the adopted upper limb pose were analyzed with respect to factors such as unimanual versus bimanual operation, and the amplitude of interaction force between an operator and the robot. The results discovered that the the effect of bimanual operation on the upper limb pose differs between individuals and the magnitude of the force had a varying effect on the pose. The requirement of applying a force forward produced an overall lower swivel angle.
Khonasty, R, Carmichael, MG, Liu, D & Waldron, KJ 1970, 'Upper body pose estimation utilizing kinematic constraints from physical human-robot interaction', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 90-99.
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In physical Human-Robot Interaction (pHRI), knowing the pose of the operator is beneficial and may allow the robot to better accommodate the human operator. Due to a large redundancy in the human body, determining the pose of the human operator is difficult to achieve in unstructured environments especially in human-robot collaborative operations where the robot often occludes the human from vision-based sensors. This work presents an upper body pose estimation method based on exploiting known positions of the human operator's hands while performing a task with the robot. Upper body pose is estimated using upper limb kinematic models alongside sensor information and model approximations to produce solutions that are biomechanically feasible. The pose estimation method was compared to upper body poses obtained using a motion capture system. It was shown to be able to perform robustly with varying amounts of available information. This approach is well suited in applications where robots are controlled using well-defined interfaces such as handlebars, operating in unstructured environments.
Kianinia, M, Tawfik, SA, Regan, B, Tran, TT, Ford, MJ, Aharonovich, I & Toth, M 1970, 'Robust Solid State Quantum System Operating at 800 K', Conference on Lasers and Electro-Optics, CLEO: Applications and Technology, OSA, pp. JTu5A.24-JTu5A.24.
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Kim, J & Chen, W 1970, 'Optimal sensing geometry for pseudorange and bearing-elevation observations', Australasian Conference on Robotics and Automation, ACRA, pp. 272-277.
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In this paper, we investigate the sensing geometry in the context of tightly-coupled simultaneous localisation and mapping, which fuses pseudoranges from GPS satellites and the bearing-elevation observations from ground landmarks. The concept of geometrical dilution of precision has been widely applied for the pseudorange observations but needs to be generalised to account for the angular measurements. In this work, we derive a closed-form solution for the determinant of the Fisher information matrix using a minimal set of observations, which offers insights on the optimal sensing geometry and thus the effective sensing strategy.
Kirby, R, Duan, W, Karimi, M, Brennan, M & Kessissoglou, N 1970, 'Detecting sound waves generated by leaks in buried water distribution pipes', Proceedings of ACOUSTICS 2017 Perth: Sound, Science and Society - 2017 Annual Conference of the Australian Acoustical Society, AAS 2017.
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It is common to use guided sound waves to detect leaks or cracks in pipelines. Applications include the nondestructive testing of oil and gas pipelines, which normally takes places at ultrasonic frequencies, as well as the detection of leaks and ruptures in water filled pipes at much lower audio frequencies. However, if the pipe is buried then sound leaks out of the pipe into the surrounding medium and this lowers the acoustic energy travelling along the pipe wall. This has the potential to limit the applications of this technology, and so it is necessary to develop knowledge of the acoustic properties of the guided waves in order to optimise detection techniques. Accordingly, this work examines the properties of sound waves propagating in an infinitely long fluid-filled buried pipe, with application to leak detection at low audio frequencies. A parametric study is undertaken to examine the sensitivity of sound propagation to the properties of the internal liquid, pipe walls and of the surrounding medium.
Kodagoda, S 1970, 'Keynote speech: Infrastructure robotics: A better way ofmanaging old infrastructure', 2017 6th National Conference on Technology and Management (NCTM), 2017 6th National Conference on Technology and Management (NCTM), IEEE, pp. x-xi.
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Kolade, AT, Zuhairi, MF, Yafi, E & Zheng, CL 1970, 'Performance analysis of black hole attack in MANET', Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM '17: The 11th International Conference on Ubiquitous Information Management and Communication, ACM, pp. 1-7.
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Kolamunna, H, Chauhan, J, Hu, Y, Thilakarathna, K, Perino, D, Makaroff, D & Seneviratne, A 1970, 'Are Wearables Ready for HTTPS? On the Potential of Direct Secure Communication on Wearables', 2017 IEEE 42nd Conference on Local Computer Networks (LCN), 2017 IEEE 42nd Conference on Local Computer Networks (LCN), IEEE, pp. 321-329.
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Kong, F, Sun, X, Leung, VCM, Guo, YJ, Zhu, Q & Zhu, H 1970, 'Queue-Aware Small Cell Activation for Energy Efficiency in Two-Tier Heterogeneous Networks', 2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, San Francisco, CA, USA, pp. 1-6.
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© 2017 IEEE. In heterogeneous networks (HetNets), the network energy efficiency is critically determined by the base station (BS) deployment density. In this paper, we consider a BS density optimization problem by turning on only a fraction of micro BSs according to an activation ratio to minimize the network average power consumption per area in a 2- tier HetNet. In contrast to previous studies where a BS is assumed to be transmitting packets all the time, such that the network power consumption monotonically increases as the BS density increases, we assume that each BS can be busy or idle depending on the dynamic packet arrivals. The network power consumption is thus closely related to the average traffic intensity of each tier. With the assumption of universal spectrum reuse, the average traffic intensity of each tier is found to be uniquely determined by a set of fixed-point equations, based on which the network average power consumption per area is characterized. Simulation results demonstrate that the network average power consumption per area can be minimized by properly tuning the activation ratio. It is further revealed that the optimal activation ratio increases as the mean packet arrival rate of each user increases.
Kong, S, Lee, JH & Li, S 1970, 'A deterministic distributed algorithm for reasoning with connected row-convex constraints', Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, International Conference on Autonomous Agents and Multiagent System, International Foundation for Autonomous Agents and Multiagent Systems, São Paulo, Brazil, pp. 203-211.
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The class of CRC constraints generalizes several tractable classes of constraints and is expressive enough to model problems in domains such as temporal reasoning, geometric reasoning, and scene labelling. This paper presents the first distributed deterministic algorithm for connected row-convex (CRC) constraints. Our distributed (partial) path consistency algorithm efficiently transforms a CRC constraint network into an equivalent constraint network, where all constraints are minimal (i.e., they are the tightest constraints) and generating all solutions can be done in a backtrack- free manner. When compared with the state-of-ihe-Art distributed algorithm for CRC constraints, which is a randomized one, our algorithm guarantees to generate a solution for satisfiable CRC constraint networks and it is applicable to solve large networks in real distributed systems. The experimental evaluations show that our algorithm outperforms the statc-of-Thc-Art algorithm in both practice and theory.
Kovaleva, M, Bulger, D & Esselle, KP 1970, 'Efficient optimization of a simple compact resonant cavity antenna', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, pp. 345-346.
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Kovář, V, Beránek, M & Feuerlicht, G 1970, 'Modelling Enterprise Applications using Business Artifacts', Proceedings of the 19th International Conference on Enterprise Information Systems, 19th International Conference on Enterprise Information Systems, SCITEPRESS - Science and Technology Publications, pp. 419-425.
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Most of the existing modeling languages such as UML, BPML, etc. that attempt to capture the semantics of real-world objects produce complex technical models that are not suitable for business professionals. Another important limitation of traditional modeling approaches is the lack of a mechanism for modeling the lifecycle of business objects. These limitations have motivated recent interest in alternative approaches such as business artefact modelling that provide a unified representation of data and processes in the form of business artifacts. In this paper we describe the Unicorn Universe Process method that uses business artifacts as a fundamental building block of information systems. We illustrate the application of this method using a University Assignment Submission case study scenario.
Kraetzig, O & Sick, N 1970, 'A patent-based approach for the identification of technology strategies - The case of emerging battery technologies', PICMET’17 'Technology Management for the Interconnected World', Portland, Oregon, USA.
Kraetzig, O & Sick, N 1970, 'Overcoming the barrier of non-willingness towards technology commercialization – The case of German battery research', The XXVIII ISPIM conference “Composing the innovation symphony”, Vienna, Austria.
Kratzig, O & Sick, N 1970, 'A Patent-Based Approach for the Identification of Strategic Reactions to Technological Change: The Case of Emerging Battery Technologies', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Melbourne, VIC, Australia, pp. 1-10.
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© 2017 IEEE. Assessments regarding the strategic reactions of companies towards technological change are highly complex and often lack generalization. Methods for analyzing company resources were rather applied than methods directly focusing on the respective strategic reactions. There is, however, a need for a methodology that provides a more comprehensive overview and enables an early recognition of strategic reactions to technological change, for example through the use of easily available secondary data. Thus, the aim of our study is the development of a patent-based approach to identify particular strategic reactions of respective companies towards technological change. Achieving this objective involves an analysis of patent activities for the case of relevant cell manufacturing companies of lithium-ion and post-lithium-ion battery technologies. The developed methodological approach could be applied successfully to the identification of strategic reactions in the battery field. From a practical point of view, our findings give detailed and above all early insights in strategic decisions and enable technology managers to better assess investment options in different technologies.
Kridalukmana, R, Lu, HY & Naderpour, M 1970, 'An object oriented Bayesian network approach for unsafe driving maneuvers prevention system', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Nanjing, China, pp. 1-6.
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© 2017 IEEE. As the main contributor to the traffic accidents, unsafe driving maneuvers have taken attentions from automobile industries. Although driving feedback systems have been developed in effort of dangerous driving reduction, it lacks of drivers awareness development. Therefore, those systems are not preventive in nature. To cover this weakness, this paper presents an approach to develop drivers awareness to prevent dangerous driving maneuvers. The approach uses Object-Oriented Bayesian Network to model hazardous situations. The result of the model can truthfully reflect a driving environment based upon situation analysis, data generated from sensors, and maneuvers detectors. In addition, it also alerts drivers when a driving situation that has high probability to cause unsafe maneuver to be detected. This model then is used to design a system, which can raise drivers awareness and prevent unsafe driving maneuvers.
Kuppili Venkata, S, Musial, K, Mahmoud, S & Keppens, J 1970, 'Demonstration: Multi-agent System for Distributed Cache Maintenance', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 364-368.
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© Springer International Publishing AG 2017. Innovations in science and technology is increasing the demand on huge data transfers and hence number of data caches. In this paper, we consider the community caching solution, CommCache, where many groups of users are working together on related projects distributed all over the world. We demonstrate the use of proactive caches for data placement problem with the help of multi-agent coordination.
Kuppili Venkata, S, Musial, K, Mahmoud, S & Keppens, J 1970, 'Multi-Agent System for Distributed Cache Maintenance', ADVANCES IN PRACTICAL APPLICATIONS OF CYBER-PHYSICAL MULTI-AGENT SYSTEMS: THE PAAMS COLLECTION, PAAMS 2017, 15th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), Springer International Publishing, Porto, PORTUGAL, pp. 157-169.
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Kusakunniran, W, Qiang Wu, Ritthipravad, P & Zhang, J 1970, 'Three-stages hard exudates segmentation in retinal images', 2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE), 2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE), IEEE, Phuket, Thailand, pp. 1-6.
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© 2017 IEEE. This paper proposes a three-stages method of hard exudate segmentation in retinal images. The first stage is the pre-processing. The color transfer is applied to make all retinal images to have the same color characteristics, based on statistical analysis. Then, only a yellow channel of each image is used in the further analysis. The second stage is the blob initialization. The blob detection based on color, size, and shape including circularity and convexity is used to identify initial pixels of hard exudates. The detected blobs must not be inside the optic disk. The third stage is the segmentation. The graph cut is iteratively applied on partitions of the image. The fine-tune segmentation in sub-images is necessary because the portion of hard exudates is significantly less than the portion of non-hard exudates. The proposed method is evaluated using the two well-known datasets, namely e-ophtha and DIARETDB1, in both aspects of pixel-level and image-level. Based on the comprehensive comparisons with the existing works, the proposed method is shown to be very promising. In the image-level, it achieves 96% sensitivity and 94% specificity for the e-ophtha dataset, and 96% sensitivity and 98% specificity for the DIARETDB1 dataset.
Kusakunniran, W, Wu, Q & Zhang, J 1970, 'Action Recognition Based on Correlated Codewords of Body Movements', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, Australia, pp. 1-8.
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© 2017 IEEE. Using spatio-temporal features is popular for action recognition. However, existing methods embed these local features into a global representation. Orders and correlations among local motions of each action are missing. This can make it difficult to distinguish closely related actions. This paper proposes a solution to address this challenge by encoding correlations of movements. Space-time interest points are detected in each action video. Then, feature descriptors are extracted from these key points and clustered into different codewords implicitly representing different characteristics of motions. The final representation of each action video is a combination of a bag of words and correlations between codewords. Then, the support vector machine is used as a classification tool. Based on the experimental results, the proposed method achieves a very promising performance and particularly outperforms the other existing methods that rely on spatio-temporal features.
Kutay, CM & Lawrence, C 1970, 'Enduring Engineering for our Water Resources', Putting Water to Work: Australian Engineering Heritage, Mildura.
Kutay, CM & Lawrence, C 1970, 'Language Located', Information Technologies for Indigenous Communities, Melbourne September 2017.
La Fontaine, A, Piazolo, S, Trimby, P, Yang, L & Cairney, JM 1970, 'Laser-Assisted Atom Probe Tomography of Deformed Minerals: A Zircon Case Study', Microscopy and Microanalysis, Oxford University Press (OUP), pp. 404-413.
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AbstractThe application of atom probe tomography to the study of minerals is a rapidly growing area. Picosecond-pulsed, ultraviolet laser (UV-355 nm) assisted atom probe tomography has been used to analyze trace element mobility within dislocations and low-angle boundaries in plastically deformed specimens of the nonconductive mineral zircon (ZrSiO4), a key material to date the earth’s geological events. Here we discuss important experimental aspects inherent in the atom probe tomography investigation of this important mineral, providing insights into the challenges in atom probe tomography characterization of minerals as a whole. We studied the influence of atom probe tomography analysis parameters on features of the mass spectra, such as the thermal tail, as well as the overall data quality. Three zircon samples with different uranium and lead content were analyzed, and particular attention was paid to ion identification in the mass spectra and detection limits of the key trace elements, lead and uranium. We also discuss the correlative use of electron backscattered diffraction in a scanning electron microscope to map the deformation in the zircon grains, and the combined use of transmission Kikuchi diffraction and focused ion beam sample preparation to assist preparation of the final atom probe tip.
Lai, W, Ni, W, Wang, H & Liu, RP 1970, 'Decentralized Relaying and Performance Analysis in Vehicular Ad Hoc Networks', 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), IEEE, Toronto, ON, Canada, pp. 1-5.
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© 2017 IEEE. Vehicular Ad Hoc Networks (VANET) is an important network technology. Relay communication can effectively improve the connectivity and coverage of VANET, especially in distributed environments. Challenges arise from intense collision resulting from inherently synchronized relays. In this paper, we propose a decentralized relay scheme without collecting neighbor nodes' information. Particularly, we design a new score function to prioritize the relays based on their reception quality from source and channel conditions towards intended destination. A closed-form expression for packet delivery ratio (PDR) is derived based on time-out probabilities. Our analyses, validated by simulations, show that the proposed scheme, in terms of PDR, is much better than DAFMAC protocol.
Lalbakhsh, A, Afzal, MU, Esselle, KP & Smith, S 1970, 'Design of an artificial magnetic conductor surface using an evolutionary algorithm', 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, Verona, ITALY, pp. 885-887.
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Lalbakhsh, A, Afzal, MU, Esselle, KP & Smith, SL 1970, 'A fast design procedure for quadrature reflection phase', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, Singapore, SINGAPORE, pp. 2364-2366.
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Lalbakhsh, A, Esselle, KP & Smith, SL 1970, 'Design of a single-slab low-profile frequency selective surface', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, Singapore, SINGAPORE, pp. 2360-2363.
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Lattouf, D & Huynh, BP 1970, 'Flow Across a Butterfly Valve in a Dam Penstock', Volume 7: Fluids Engineering, ASME 2017 International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers, Tampa, Florida, USA, pp. 1-10.
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Butterfly valves are typically used as emergency closure devices in dam penstocks; these valves must be capable of closing if a penstock bursts. This paper summarizes a 3D CFD (Computational Fluid Dynamics) study that was conducted on the water flow across a sizable butterfly valve (1.6m in diameter) in a dam penstock with 57m of water head. The main aim is to determine the maximum torque required to close the valve. Thus semi steady flow conditions across the valve at various degrees of closure were investigated and the corresponding torque calculated. A maximum torque of about 87 700 N-m has been obtained, occurring at valve angle 40° (with valve totally closed at 0°, and fully open at 90°). Visual results were analyzed at each valve angle to understand the nature of the flow through the butterfly valve using various 2D contours and streamline images. The CFD software ANSYS Fluent has been used employing a Finite Volume Method. The RANS (Reynolds-Averaged Navier-Stokes) approach with Realizable K-epsilon turbulence model was employed. A grid independence study with up to 10 million cells has also been carried out, resulting in the adoption of 7.5 million cells in all models. Comparison with other available data was also completed, adding to the reliability of the computational results. Distribution of pressure, flow velocity, and turbulence parameters are also presented.
Law, Y, Swa Thi, S, Chen, XM, Nguyen, TQN, Seviour, TW, Williams, RBH, Ni, B & Wuertz, S 1970, 'The Start-up of Mainstream Anammox Process Is Limited Only by Nitrite Supply', Frontiers in Wastewater Treatment and Modelling FICWTM 2017, Frontiers International Conference on Wastewater Treatment, Springer International Publishing, Palermo, Italy, pp. 18-21.
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In this study, we investigated start-up of an Anammox bioprocess from a secondary activated sludge seed fed primary effluent from a domestic used water reclamation plant (WRP). To test the hypothesis that an anammox-enriched sludge could still be achieved under such conditions given enough nitrite and ammonium, nitrite was supplemented at a molar ratio of 2:1 to ammonium. Anammox activity was observed within 50 d of operation and the relative abundance of Anammox bacteria increased from <0.1% gradually up to 4% after 100 d of operation, concomitant with complete ammonium removal. Despite consumption of chemical oxygen demand (COD) by heterotrophic denitrifiers, the Anammox biomass continued to accumulate up to 20% of relative abundance, contributing to biofilm and granule formation in the reactor. Thus, a high influent COD concentration is not inhibitory to the start-up of an Anammox system as long as sufficient nitrite is provided.
Lawrence, C, Leong, TW, Gay, V, Woods, A & Wadley, G 1970, '#thismymob', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, Brisbane, pp. 646-647.
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© 2017 Association for Computing Machinery. All rights reserved. We propose to hold a one-day workshop on developing projects relating to #thismymob: Digital Land Rights and Reconnecting Indigenous Communities at OzCHI 2017 Brisbane. See http://www.arc.gov.au/newsmedia/ news/thismymob-digital-land-rights-andreconnecting-indigenous-communities.
Le, AT, Tran, LC & Huang, X 1970, 'On Performance of Analog Least Mean Square Loop for Self-Interference Cancellation in In-Band Full-Duplex OFDM Systems', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. This paper evaluates the performance of an analog least mean square (ALMS) loop employed to cancel self-interference in in-band full-duplex (IBFD) orthogonal frequency division multiplexing (OFDM) systems. Cyclostationary analysis is applied to investigate the behavior of the ALMS filter. It is revealed that the performance of the ALMS filter for OFDM systems primarily depends on windowing function rather than pulse shaping as in single carrier systems. It is also noticed that the ALMS loop in OFDM systems provides a much higher level of sel-interference (SI) suppression because OFDM signals lead to reduced the error of the interference channel modelling with the adaptive filter. Simulations are then conducted to verify the theoretical findings.
Lee, JE-Y 1970, 'Engineering high Q-factor MEMS resonators and probing losses', 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), IEEE, pp. 439-443.
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Lee, JJH, Yoo, C, Hall, R, Anstee, S & Fitch, R 1970, 'Energy-optimal kinodynamic planning for underwater gliders in flow fields', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney, Australia, pp. 42-51.
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We consider energy-optimal navigation planning in ow fields, which is a long-standing optimisation problem with no known analytical solution. Using the motivating example of an underwater glider subject to ocean currents, we present an asymptotically optimal planning framework that considers realistic vehicle dynamics and provably returns an optimal solution in the limit. One key idea that we introduce is to reformulate the dynamic control problem as a kinematic problem with trim states, which encapsulate the dynamics over suitably long distances. We report simulation examples that, surprisingly, contravene the use of regular 'sawtooth' paths currently in widespread use. We show that, when internal control mechanics are taken into account, energy-efficient paths do not necessarily follow a regular up-and-down pattern. Our work represents a principled planning framework for underwater gliders that will enable improved navigation capability for both commercial and defence applications.
Leighton, B, Zhao, L, Huang, S & Dissanayake, G 1970, 'Extending parallax parameterised bundle adjustment to stereo', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, University of Technology, Sydney, pp. 194-202.
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The main contribution of this paper is the extension of the ParllaxBA algorithm proposed by [Zhao et al., 2015] into stereo. Simulated and experimental datasets are used to evaluate Cartesian and parallax angle parameterisation for stereo bundle adjustment. It is demonstrated that, like monocular ParallaxBA, under normal conditions the two algorithms perform similarly. However, when the parallax angle of landmarks is low, parallax parameterisation can converge to a lower cost and in less time than the traditional Cartesian parameterisation.
Li, B, Fan, X, Zhang, J, Wang, Y, Chen, F, Kodagoda, S, Wells, T, Vorreiter, L, Vitanage, D, Iori, G, Cunningham, D & Chen, T 1970, 'Predictive Analytics Toolkit for H2S Estimation and Sewer Corrosion', OZWater, OZWater, Australian Water Association, Sydney.
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This paper presents a predictive analytics toolkit, which is based on the emerging spatiotemporal data analysis techniques, for the estimation of hydrogen sulphide (H2S) gas distribution and prediction of sewer concrete corrosion level. The toolkit is an easy-to-use desktop application with a user-friendly interface for querying and producing output results on GIS. The inputs to the toolkit are the sewer network geometry, monitored factors, and hydraulic information; the outputs of the toolkit are spatiotemporal estimates of H2S gas concentration and concrete corrosion levels on the entire sewer network with uncertainties of the predictions. The toolkit is also able to integrate experts’ domain knowledge or existing physical model’s results as prior knowledge into the analytics model. The final outcomes of the toolkit can be used to prioritise high risk areas, recommend chemical dosing locations, and suggest deployment of sensors. A simulation of H2S and corrosion level prediction on a subsystem of the sewer network in the greater Sydney area is reported to demonstrate the capability of the toolkit
Li, B, Xiong, J, Liu, B, Gui, L, Qiu, M & Shi, Z 1970, 'On services pushing and caching in high-speed train by using converged broadcasting and cellular networks', 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), IEEE, pp. 1-7.
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© 2017 IEEE. This paper proposes a services pushing and caching algorithm in high-speed train (HST) by using converged wireless broadcasting and cellular networks (CWBCN). Services pushing and caching on the HST is an efficient way to improve the capacity of the network; and it can also lead to better user experience. In the proposed services pushing and caching model, the most popular services are delivered and cached on the vehicle relay station (VRS) of the train ahead the departure time. Then, the most popular services are broadcasted and cached on the User Equipments (UEs) after all the passengers are on the train; the less popular services are transmitted to the user by p2p mode by the relayed cellular network on the train. In order to maximize the network capacity in limited time slots, we transform the issue into the 0-1 Knapsack problem. Dynamic programming algorithm is adopted to solve it in polynomial time. As the passengers may get on or get off the train when pushing the most popular services, an information retransfer algorithm is also proposed when more intermediate stations are considered. Simulations show that the proposed algorithms can efficiently improve the capacity of the converged network.
Li, B, Xiong, J, Liu, B, Gui, L, Qiu, M & Shi, Z 1970, 'On Services Pushing and Caching in High-speed Train by Using Converged Broadcasting and Cellular Networks', 2017 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), 12th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), IEEE, Cagliari, ITALY, pp. 457-463.
Li, H, Wang, TQ, Huang, X & Zhang, JA 1970, 'Low-Complexity Uplink Multiuser Receivers for MIMO System with Massive Hybrid Array', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. Due to the enormous needs for signal processing and hardware constraints, the full digital implementation for a large antenna array at mmWave frequencies becomes intractable. Hence, receiver design for MIMO system with massive hybrid array is very demanding, particularly for subarray structure. In this paper, we propose two low- complexity uplink multiuser receiver design schemes (single-beam and multi-beam) under the circumstances of only users' angles of arrival (AOAs) available at base station, which greatly simplify the analog beamforming structure and reduce the complexity of channel estimation especially when the number of antenna elements is considerably large. In the single-beam scheme, subarrays are mapped to different users one by one such that each subarray serves a specific user. In the multibeam scheme, all subarrays use the same analog beamforming and any subarray's beamforming signal potentially points at all users. Digital beamforming is then employed to combine all subarray signals followed by equalization. Simulations are performed to compare the proposed schemes with other schemes that need channel information available at the subarray output. Since only AOAs are required for analog and digital beamformings, the proposed schemes are more suitable for mmWave MIMO system with massive hybrid array in spite of slight sum-rate loss.
Li, H, Zhou, H, Quan, W, Feng, B, Zhang, H & Yu, S 1970, 'HCaching: High-Speed Caching for Information-Centric Networking', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. Information-Centric Networking (ICN) introduces ubiquitous in-network caching to reduce network load and improve Quality of Service (QoS). This peculiarity requires high-speed caching technologies to support wire-speed and large-amount data forwarding, which brings new challenges to existing routers. To promote practical ICN deployment, many emerging researches focus on how to accelerate caching. In this paper, we propose a novel two-layer High-speed Caching scheme (HCaching), which leverages the characteristics of both SRAM and DRAM to accelerate caching for ICN routers. In particular, using DRAM as a primary cache and SRAM as a secondary one, HCaching is able to: (i) reduce excessive utilization of high-cost SRAM, (ii) speed up access of DRAM, (iii) and improve total network throughput. We implement and analyze HCaching performance by comparing with another two state-of-the-art solutions. The results show that HCaching achieves an improved throughput by 3-10 times faster than the compared solutions.
Li, J & Wu, C 1970, 'Fibre-reinforced strain hardening concrete under static and blast loads', 15th East Asia-Pacific Conference on Structural Engineering and Construction, Xi'an.
Li, J & Wu, CQ 1970, 'Experimental study on steel wire mesh reinforced concrete slabs against close-in detonations', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press, Perth, Australia, pp. 567-570.
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High performance and aesthetic appearance of a structural design is the motivation behind high strength concrete development. As a notable representative, high performance steel fibre reinforced concrete is characterized by a much higher compressive and tensile strength compared with conventional concrete, the low water-cement ratio effectively warrants a low porosity microstructure which in turn enhances its durability. In recent years, with threat from terrorism activities, protection of structures against malicious loads such like explosive detonation is attracting more public concern. Due to its excellent mechanical performance and energy absorption capacity, high performance steel fibre reinforced concrete can be used in the construction of key load-carrying components to mitigate the blast induced structural damage. In current study, slabs made of high strength concrete material are field tested under close-in detonations, different reinforcement schemes including steel fibre reinforcement and steel wire mesh reinforcement are used in the slab design. Comparisons are made with normal strength concrete slab. Brief discussion on the different slab design against blast loads are presented.
Li, JT, Zhu, XQ & Samali, B 1970, 'Extraction of bridge modal parameters using a moving instrumented vehicle by SSI technique', SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings, The 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Brisbane, pp. 1195-1204.
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Research on indirect bridge structural identification from the dynamic response of a moving instrumented vehicle has been very attractive in recent years. Unlike conventional bridge structural health monitoring methods that many sensors are installed directly on a bridge to obtain structural dynamic responses, the indirect bridge monitoring utilises an instrumented vehicle to capture the bridge dynamic information during its moving over the bridge. The bridge response often exhibits an inherent randomness due to the road surface roughness as well as the traffic excitation. It is suggested stochastic analysis should be performed. In this paper, the stochastic subspace identification (SSI) method is used for the structural dynamic parameter identification from the vehicle dynamic response only. To reduce the blurring effect of road surface roughness on the indirect structural model identification, two connected identical vehicles are adopted. The white noise support excitation is added to briefly simulate the traffic excitation to the bridge. Cases studies show that the improved SSI using the subtraction residual of the two connected vehicles' responses is very effective. The bridge frequencies can be successfully identified from dynamic responses of the instrumented vehicles.
Li, K, Ni, W, Duan, L, Abolhasan, M & Niu, J 1970, 'SWPT: A Joint-Scheduling Model for Wireless Powered Sensor Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the others waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called Scheduled WPT (SWPT), aiming to minimize data packet loss from a network of wireless powered sensor nodes by jointly considering the sensor nodes' energy consumption and data queue state information. The scheduling problem is formulated by a MDP model, assuming that the complete states of each sensor node are well known by the base station. This presents the best effort performance of the scheduling that can be collected in a wireless powered sensor network. The simulation results show that, in terms of network throughput and packet loss rate, the proposed scheduling model significantly improves the network performance.
Li, M, Liu, Y, Chen, S-L, Qin, P-Y & Guo, YJ 1970, 'Low sidelobe synthesis of dipole arrays by element orientation selection using binary codec genetic algorithm', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, France, France, pp. 2838-2840.
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© 2017 Euraap. Selecting appropriate element orientations can significantly reduce the sidelobe level of the antenna array. In this paper, a binary coded genetic algorithm (BCGA) which selects the element orientations from specified discrete angles, is proposed to reduce the sidelobe level (SLL) of the array. Compared to the conventional GA, the BCGA is much faster in this application. Synthesis results show the effectiveness and efficiency of the proposed method.
Li, Q, Tan, Z, Jamdagni, A, Nanda, P, He, X & Han, W 1970, 'An Intrusion Detection System Based on Polynomial Feature Correlation Analysis', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, pp. 978-983.
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© 2017 IEEE. This paper proposes an anomaly-based Intrusion Detection System (IDS), which flags anomalous network traffic with a distance-based classifier. A polynomial approach was designed and applied in this work to extract hidden correlations from traffic related statistics in order to provide distinguishing features for detection. The proposed IDS was evaluated using the well-known KDD Cup 99 data set. Evaluation results show that the proposed system achieved better detection rates on KDD Cup 99 data set in comparison with another two state-of-the-art detection schemes. Moreover, the computational complexity of the system has been analysed in this paper and shows similar to the two state-of-the-art schemes.
Li, S, Long, Z, Liu, W, Duckham, M & Both, A 1970, 'On Redundant Topological Constraints (Extended Abstract)', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 5020-5024.
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Redundancy checking is an important task in AI subfields such as knowledge representation and constraint solving. This paper considers redundant topological constraints, defined in the region connection calculus RCC8. We say a constraint in a set C of RCC8 constraints is redundant if it is entailed by the rest of C. A prime subnetwork of C is a subset of C which contains no redundant constraints and has the same solution set as C. It is natural to ask how to compute such a prime subnetwork, and when it is unique. While this problem is in general intractable, we show that, if S is a subalgebra of RCC8 in which weak composition distributes over nonempty intersections, then C has a unique prime subnetwork, which can be obtained in cubic time by removing all redundant constraints simultaneously from C. As a by-product, we show that any path-consistent network over such a distributive subalgebra is minimal.
Li, W, Ni, W, Liu, D, Liu, RP, Wang, P & Luo, S 1970, 'Fine-Grained Access Control for Personal Health Records in Cloud Computing', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. This paper presents a novel access control scheme for personal health record(PHR) data in cloud computing. The scheme utilizes attribute-based encryption(ABE), hash function and symmetric encryption to realize a fine-grained, multi- privilege access control to PHR. The patients can share their PHR with medical staff from various departments with different privileges securely. The experimental results show the efficiency of our scheme in terms of running-time, communication cost and storage overhead.
Li, Y & Qiao, Y 1970, 'Linear Algebraic Analogues of the Graph Isomorphism Problem and the Erdős-Rényi Model', 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), IEEE, Berkeley, CA, USA, pp. 463-474.
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© 2017 IEEE. A classical difficult isomorphism testing problem is to test isomorphism of p-groups of class 2 and exponent p in time polynomial in the group order. It is known that this problem can be reduced to solving the alternating matrix space isometry problem over a finite field in time polynomial in the underlying vector space size. We propose a venue of attack for the latter problem by viewing it as a linear algebraic analogue of the graph isomorphism problem. This viewpointleads us to explore the possibility of transferring techniques for graph isomorphism to this long-believed bottleneck case of group isomorphism.In 1970s, Babai, Erds, and Selkow presented the first average-case efficient graph isomorphism testing algorithm (SIAM J Computing, 1980). Inspired by that algorithm, we devise an average-case efficient algorithm for the alternating matrix space isometry problem over a key range of parameters, in a random model of alternating matrix spaces in vein of the Erdos-R4;enyi model of random graphs. For this, we develop a linear algebraic analogue of the classical individualisation technique, a technique belonging to a set of combinatorial techniques that has been critical for the progress on the worst-case time complexity for graph isomorphism, but was missing in the group isomorphism context. This algorithm also enables us to improve Higmans 57-year-old lower bound on the number of p-groups (Proc. of the LMS, 1960). We finally show that Luks dynamic programming technique for graph isomorphism (STOC 1999) can be adapted to slightly improve the worst-case time complexity of the alternating matrix space isometry problem in a certain range of parameters.Most notable progress on the worst-case time complexity of graph isomorphism, including Babais recent breakthrough (STOC 2016) and Babai and Luks previous record (STOC 1983), has relied on both group theoretic and combinatorial techniques. By developing a linear algebraic analogue of the individu...
Li, Y, Lei, G, He, L, Chen, J & Zhang, A 1970, 'Sequential multi-objective optimization method for electromagnetic inverse problems', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-4.
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© 2017 IEEE. Sequential multiobjective optimization method based on radial basis function model is presented in this work to deal with the multiobjective design and optimization problems of engineering electromagnetic devices. Firstly, the initial sample set can be generated by using the sequential optimization method (SOM). SOM can greatly reduce the sample size by integrating the advantages of optimization algorithms and approximate models. Secondly, the optimal Pareto solutions of the multiobjective design problems can be obtained by updating the samples and approximate models sequentially. Thereafter, we calculate the root mean square error for each objective to determine whether it has achieved the default value. Finally, to illustrate the performance of the new method, a classic mathematic test function and a design example of permanent magnet synchronous machine are investigated. It can be found that the proposed method combined the advantages of effectiveness of sequential optimization strategy and lower computation cost of approximate models. The obtained solutions are satisfactory while the computation cost of finite element analysis needed by the new method is less than 1/5 compare with that of direct optimization algorithm.
Lian, D, Liu, R, Ge, Y, Zheng, K, Xie, X & Cao, L 1970, 'Discrete Content-aware Matrix Factorization', Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, Halifax, CANADA, pp. 325-334.
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© 2017 ACM. Precisely recommending relevant items from massive candidates to a large number of users is an indispensable yet computationally expensive task in many online platforms (e.g., Amazon.com and Netfix.com). A promising way is to project users and items into a Hamming space and then recommend items via Hamming distance. However, previous studies didn't address the cold-start challenges and couldn't make the best use of preference data like implicit feedback. To fill this gap, we propose a Discrete Content-aware Matrix Factorization (DCMF) model, 1) to derive compact yet informative binary codes at the presence of user/item content information; 2) to support the classification task based on a local upper bound of logit loss; 3) to introduce an interaction regularization for dealing with the sparsity issue. We further develop an eficient discrete optimization algorithm for parameter learning. Based on extensive experiments on three real-world datasets, we show that DCFM outperforms the state-of-the-arts on both regression and classification tasks.
Liang, B, Zheng, L & Han, J 1970, 'Face Retrieval in Video Sequences Using a Single Face Sample', 2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), International Conference on Digital Image Computing - Techniques and Applications (DICTA), IEEE, AUSTRALIA, Sydney, pp. 647-652.
Liang, B, Zheng, L & Han, J 1970, 'Face Retrieval in Video Sequences Using a Single Face Sample', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-6.
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Liang, X & Wu, CQ 1970, 'Effect of steel fibre on thermal behavior of concrete under elevated temperature', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC press, Perth, Australia, pp. 79-84.
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Steel fibre concrete is considered as an ideal material for fire-resistant structures. However, how addition of steel fibre affects thermal behaviors of concrete has rarely been reported. In this study, a meso-scale modelling approach is successfully developed, which models steel fibre and concrete separately rather than treats them as a homogeneous material. Then simulations on how steel fibre content and aspect ratio influence thermal behaviors of concrete are conducted. Simulation results reveal greater steel fibre content contributes to more even temperature distribution but more uneven thermal gradient and flux distributions especially on some local regions where fibre ends present. Besides, bigger fibre aspect ratio has the same effect as greater fibre content, as phenomena observed for mechanical properties. The study also shows that addition of steel fibre up to 2.5% volume fraction has only slight effect on thermal properties of concrete.
Liao, Y, Huang, L, Wang, Y, Kodagoda, S, Yu, Y & Liu, Y 1970, 'Parse geometry from a line: Monocular depth estimation with partial laser observation', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, pp. 5059-5066.
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Many standard robotic platforms are equipped
with at least a fixed 2D laser range finder and a monocular camera.
Although those platforms do not have sensors for 3D depth
sensing capability, knowledge of full geometry is an essential
part in many robotics activities. Therefore, recently, there is an
increasing interest in depth estimation using monocular images,
of which the estimated depth might be unreliable in robotics
applications as this task is inherently ambiguous. In this paper,
we have attempted to improve the precision of monocular
depth estimation by introducing 2D planar observation from the
remaining laser range finder without extra cost. Specifically, we
construct a dense reference map from the sparse laser range
data, redefining the depth estimation task as estimating the
distance between the real and the reference depth. To solve
the problem, we construct a novel residual of residual neural
network, and tightly combine the classification and regression
losses for continuous depth estimation. Experimental results
suggest that our method achieves considerable promotion compared
to the state-of-the-art methods on both NYUD2 and
KITTI, validating the effectiveness of our method on leveraging
the additional sensory information. We further demonstrate the
potential usage of our method in obstacle avoidance where
our methodology provides comprehensive depth information
compared to the solution using monocular camera or 2D laser
range finder alone.
Lin, S, Yu, J, Ni, W & Liu, R 1970, 'Radio Resource Management for Ultra-Dense Smallcell Networks: A Hybrid Spectrum Reuse Approach', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-7.
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© 2017 IEEE. Smallcells have great potential to enhance cellular networks, complementing macrocells. Severe interference may occur, as smallcells are expected to be deployed and operated uncoordinatedly. However, existing resource management methods require significant overhead to suppress interference. We propose a new resource management approach which is able to mitigate the cross-tier and co-tier interference with substantially reduced overhead. The key idea is to categorize the smallcells into two regions based on a judiciously designed cross-tier interference criterion. Smallcells in the high-interference zone occupy orthogonal radio resources with the macrocell; smallcells in the other zone can reuse the resources that the macrocell is using. Another crucial aspect is that we formulate the resource sharing between the macrocell and smallcells in the low-interference zone to a multi-agent Q-learning process which assigns adequate transmit power levels in a decentralized manner to suppress the co/cross-tier interference. As a result, our approach is able to reduce the outage probabilities of macrocell users significantly to 0%, respectively, in a dense smallcell deployment (200 smallcells), as evidenced by simulation results.
Lin, S, Yu, J, Ni, W & Liu, RP 1970, 'A Decoupled 5G Network Control Framework: Distributed Adaptation and Centralized Coordination', 2017 IEEE Globecom Workshops (GC Wkshps), 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. A promising and cost-e ective way to connect massively and densely deployed 5G smallcells is through existing Internet infrastructure. However, severe delays of hundreds of milliseconds over Internet and signi cantly increased complexity due to massive networks impose critical challenges to 5G network control. Traditional centralized network control can neither cope with such delays nor scale to massive networks. Excessive inter-smallcell interfer- ence would occur. We introduce a new 5G network control structure which is tolerant to the severe delay and massive network scale. The key idea is to decouple delay-sensitive power control from the delay-tolerant channel assignment. The delay-sensitive power control can be decentralized, and formulated as a non-cooperative game. As a result, timely control with stringent delay requirements is eliminated. The delay-tolerant channel assignment is modelled as an evolutionary clustering game, so that the control complex- ity can be distributed among the smallcells and becomes practically acceptable. Performance studies show that the new decoupled 5G network control is e ective for timely interference mitigation. The stability and scalability of the new 5G network control are also demonstrated.
Liu, A, Song, Y, Zhang, G & Lu, J 1970, 'Regional Concept Drift Detection and Density Synchronized Drift Adaptation', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 2280-2286.
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In data stream mining, the emergence of new patterns or a pattern ceasing to exist is called concept drift. Concept drift makes the learning process complicated because of the inconsistency between existing data and upcoming data. Since concept drift was first proposed, numerous articles have been published to address this issue in terms of distribution analysis. However, most distribution-based drift detection methods assume that a drift happens at an exact time point, and the data arrived before that time point is considered not important. Thus, if a drift only occurs in a small region of the entire feature space, the other non-drifted regions may also be suspended, thereby reducing the learning efficiency of models. To retrieve non-drifted information from suspended historical data, we propose a local drift degree (LDD) measurement that can continuously monitor regional density changes. Instead of suspending all historical data after a drift, we synchronize the regional density discrepancies according to LDD. Experimental evaluations on three public data sets show that our concept drift adaptation algorithm improves accuracy compared to other methods.
Liu, A, Zhang, G & Lu, J 1970, 'Fuzzy time windowing for gradual concept drift adaptation', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. The aim of machine learning is to find hidden insights into historical data, and then apply them to forecast the future data or trends. Machine learning algorithms optimize learning models for lowest error rate based on the assumption that the historical data and the data to be predicted conform to the same knowledge pattern (data distribution). However, if the historical data is not enough, or the knowledge pattern keeps changing (data uncertainty), this assumption will become invalid. In data stream mining, this phenomenon of knowledge pattern changing is called concept drift. To address this issue, we propose a novel fuzzy windowing concept drift adaptation (FW-DA) method. Compared to conventional windowing-based drift adaptation algorithms, FW-DA achieves higher accuracy by allowing the sliding windows to keep an overlapping period so that the data instances belonging to different concepts can be determined more precisely. In addition, FW-DA statistically guarantees that the upcoming data conforms to the inferred knowledge pattern with a certain confidence level. To evaluate FW-DA, four experiments were conducted using both synthetic and real-world data sets. The experiment results show that FW-DA outperforms the other windowing-based methods including state-of-the-art drift adaptation methods.
Liu, B, Chen, L, Zhu, X, Zhang, Y, Zhang, C & Qiu, W 1970, 'Protecting location privacy in spatial crowdsourcing using encrypted data', Advances in Database Technology - EDBT, International Conference on Extending Database Technology, Open Proceedings, Venice, Italy, pp. 478-481.
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In spatial crowdsourcing, spatial tasks are outsourced to a set of workers in proximity of the task locations for efficient assignment. It usually requires workers to disclose their locations, which inevitably raises security concerns about the privacy of the workers’ locations. In this paper, we propose a secure SC framework based on encryption, which ensures that workers’ location information is never released to any party, yet the system can still assign tasks to workers situated in proximity of each task’s location. We solve the challenge of assigning tasks based on encrypted data using homomorphic encryption. Moreover, to overcome the efficiency issue, we propose a novel secure indexing technique with a newly devised SKD-tree to index encrypted worker locations. Experiments on real-world data evaluate various aspects of the performance of the proposed SC platform.
Liu, B, Zhou, W, Yu, S, Wang, K, Wang, Y, Xiang, Y & Li, J 1970, 'Home Location Protection in Mobile Social Networks: A Community Based Method (Short Paper)', INFORMATION SECURITY PRACTICE AND EXPERIENCE, ISPEC 2017, 13th International Conference on Information Security Practice and Experience (ISPEC) / 3rd International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec), Springer International Publishing, Melbourne, AUSTRALIA, pp. 694-704.
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Liu, F, Zhang, G & Lu, J 1970, 'Heterogeneous unsupervised domain adaptation based on fuzzy feature fusion', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Domain adaptation is a transfer learning approach that has been widely studied in the last decade. However, existing works still have two limitations: 1) the feature spaces of the domains are homogeneous, and 2) the target domain has at least a few labeled instances. Both limitations significantly restrict the domain adaptation approach when knowledge is transferred across domains, especially in the current era of big data. To address both issues, this paper proposes a novel fuzzy-based heterogeneous unsupervised domain adaptation approach. This approach maps the feature spaces of the source and target domains onto the same latent space constructed by fuzzy features. In the new feature space, the label spaces of two domains are maintained to reduce the probability of negative transfer occurring. The proposed approach delivers superior performance over current benchmarks, and the heterogeneous unsupervised domain adaptation (HeUDA) method provides a promising means of giving a learning system the associative ability to judge unknown things using related knowledge.
Liu, H, Zheng, Q, Luo, M, Zhang, D, Chang, X & Deng, C 1970, 'How Unlabeled Web Videos Help Complex Event Detection?', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, AUSTRALIA, pp. 4040-4046.
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The lack of labeled exemplars is an important factor that makes the task of multimedia event detection (MED) complicated and challenging. Utilizing artificially picked and labeled external sources is an effective way to enhance the performance of MED. However, building these data usually requires professional human annotators, and the procedure is too time-consuming and costly to scale. In this paper, we propose a new robust dictionary learning framework for complex event detection, which is able to handle both labeled and easy-to-get unlabeled web videos by sharing the same dictionary. By employing the lq-norm based loss jointly with the structured sparsity based regularization, our model shows strong robustness against the substantial noisy and outlier videos from open source. We exploit an effective optimization algorithm to solve the proposed highly non-smooth and non-convex problem. Extensive experiment results over standard datasets of TRECVID MEDTest 2013 and TRECVID MEDTest 2014 demonstrate the effectiveness and superiority of the proposed framework on complex event detection.
Liu, J, Hossain, MJ & Lu, J 1970, 'Switching performance optimization for a hybrid AC/DC microgrid using an improved VSG control strategy', 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, pp. 1-5.
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© 2017 IEEE. The hybrid AC/DC microgrid gains a great attention in recent years as it can improve the energy efficiency and ensure the reliability of the system. This paper makes an investigation on the operation mode switching performance of an AC/DC combined hybrid microgrid based on a real system at Griffith University, Queensland, Australia. An improved virtual synchronous generator (VSG) control strategy is developed to optimize the switching performance from the grid-tied mode to the islanding mode. The basic VSG principle is described and the improved VSG model is introduced. Based on the improved model, a pre-synchronization method is proposed. Comparison of the microgrid performance between conventional droop control and the improved VSG control is carried out by simulation on Matlab/SIMULINK environment. Simulation results show the advantage of VSG control strategy and the validity of the pre-synchronization method.
Liu, J, Hossain, MJ & Lu, J 1970, 'Switching Performance Optimization for a Hybrid AC/DC Microgrid using an Improved VSG Control Strategy', 2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 7th IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, Univ Auckland, Auckland, NEW ZEALAND, pp. 72-76.
Liu, L, Wang, Y, Zhao, L & Huang, S 1970, 'Evaluation of different SLAM algorithms using Google tangle data', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia., pp. 1954-1959.
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© 2017 IEEE. In this paper, we evaluate three state-of-the-art Simultaneous Localization and Mapping (SLAM) methods using data extracted from a state-of-the-art device for indoor navigation - the Google Tango tablet. The SLAM algorithms we investigated include Preintegration Visual Inertial Navigation System (VINS), ParallaxBA and ORB-SLAM. We first describe the detailed process of obtaining synchronized IMU and image data from the Google Tango device, then we present some of the SLAM results obtained using the three different SLAM algorithms, all with the datasets collected from Tango. These SLAM results are compared with that obtained from Tango's inbuilt motion tracking system. The advantages and failure modes of the different SLAM algorithms are analysed and illustrated thereafter. The evaluation results presented in this paper are expected to provide some guidance on further development of more robust SLAM algorithms for robotic applications.
Liu, Q, Huang, H, Lut, J, Gao, Y & Zhang, G 1970, 'Enhanced word embedding similarity measures using fuzzy rules for query expansion', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, ITALY, pp. 1-6.
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Liu, S, Pang, N, Xu, G & Liu, H 1970, 'Collaborative Filtering via Different Preference Structures', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Knowledge Science, Engineering and Management, Springer International Publishing, Melbourne, Australia, pp. 309-321.
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© Springer International Publishing AG 2017. Recently, social network websites start to provide third-parity sign-in options via the OAuth 2.0 protocol. For example, users can login Netflix website using their Facebook accounts. By using this service, accounts of the same user are linked together, and so does their information. This fact provides an opportunity of creating more complete profiles of users, leading to improved recommender systems. However, user opinions distributed over different platforms are in different preference structures, such as ratings, rankings, pairwise comparisons, voting, etc. As existing collaborative filtering techniques assume the homogeneity of preference structure, it remains a challenge task of how to learn from different preference structures simultaneously. In this paper, we propose a fuzzy preference relation-based approach to enable collaborative filtering via different preference structures. Experiment results on public datasets demonstrate that our approach can effectively learn from different preference structures, and show strong resistance to noises and biases introduced by cross-structure preference learning.
Liu, S, Xu, G, Zhu, X & Zhou, Z 1970, 'Towards simplified insurance application via sparse questionnaire optimization', 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), IEEE, Poland, pp. 1-2.
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© 2017 IEEE. Life insurance application requires in-person meetings with underwriters, tedious paperwork, and an average waiting period of six weeks before an offer can be made. This outdated process has become a barrier for broader consumer adoption, resulting large coverage gap. In this work, we aim to closing this gap by leveraging data mining techniques to optimize the insurance questionnaire form. Our experiment on 10 years of insurance application data has identified that only ∼2% of all questions have shown high relevancy to determining the risks of applicants, resulting a significantly simplified questionnaire.
Liu, W, Chang, X, Chen, L & Yang, Y 1970, 'Early Active Learning with Pairwise Constraint for Person Re-identification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Springer International Publishing, Skopje, Macedonia, pp. 103-118.
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© 2017, Springer International Publishing AG. Research on person re-identification (re-id) has attached much attention in the machine learning field in recent years. With sufficient labeled training data, supervised re-id algorithm can obtain promising performance. However, producing labeled data for training supervised re-id models is an extremely challenging and time-consuming task because it requires every pair of images across no-overlapping camera views to be labeled. Moreover, in the early stage of experiments, when labor resources are limited, only a small number of data can be labeled. Thus, it is essential to design an effective algorithm to select the most representative samples. This is referred as early active learning or early stage experimental design problem. The pairwise relationship plays a vital role in the re-id problem, but most of the existing early active learning algorithms fail to consider this relationship. To overcome this limitation, we propose a novel and efficient early active learning algorithm with a pairwise constraint for person re-identification in this paper. By introducing the pairwise constraint, the closeness of similar representations of instances is enforced in active learning. This benefits the performance of active learning for re-id. Extensive experimental results on four benchmark datasets confirm the superiority of the proposed algorithm.
Liu, W, Shen, X & Tsang, IW 1970, 'Sparse embedded k-means clustering', Advances in Neural Information Processing Systems, Thirty-first Annual Conference on Neural Information Processing Systems, Long Beach, California, USA, pp. 3320-3328.
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The k-means clustering algorithm is a ubiquitous tool in data mining and machine learning that shows promising performance. However, its high computational cost has hindered its applications in broad domains. Researchers have successfully addressed these obstacles with dimensionality reduction methods. Recently, [1] develop a state-of-the-art random projection (RP) method for faster k-means clustering. Their method delivers many improvements over other dimensionality reduction methods. For example, compared to the advanced singular value decomposition based feature extraction approach, [1] reduce the running time by a factor of min{n, d}ϵ2log(d)/k for data matrix X ϵ ℝn×d with n data points and d features, while losing only a factor of one in approximation accuracy. Unfortunately, they still require O (ndk/ϵ2log (d) for matrix multiplication and this cost will be prohibitive for large values of n and d. To break this bottleneck, we carefully build a sparse embedded k-means clustering algorithm which requires O(nnz(X)) (nnz(X) denotes the number of non-zeros in X) for fast matrix multiplication. Moreover, our proposed algorithm improves on [1]'s results for approximation accuracy by a factor of one. Our empirical studies corroborate our theoretical findings, and demonstrate that our approach is able to significantly accelerate k-means clustering, while achieving satisfactory clustering performance.
Liu, Z & Tsang, I 1970, 'Approximate Conditional Gradient Descent on Multi-Class Classification', Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, pp. 2301-2307.
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Conditional gradient descent, aka the Frank-Wolfe algorithm,regains popularity in recent years. The key advantage of Frank-Wolfe is that at each step the expensive projection is replaced with a much more efficient linear optimization step. Similar to gradient descent, the loss function of Frank-Wolfe scales with the data size. Training on big data poses a challenge for researchers. Recently, stochastic Frank-Wolfe methods have been proposed to solve the problem, but they do not perform well in practice. In this work, we study the problem of approximating the Frank-Wolfe algorithm on the large-scale multi-class classification problem which is a typical application of the Frank-Wolfe algorithm. We present a simple but effective method employing internal structure of data to approximate Frank-Wolfe on the large-scale multiclass classification problem. Empirical results verify that our method outperforms the state-of-the-art stochastic projection free methods.
Liu, Z & Zhang, G 1970, 'The Study in Edge IOT Era: A Software Framework Based on the Knowledge', 2017 International Conference on Computational Science and Computational Intelligence (CSCI), 2017 International Conference on Computational Science and Computational Intelligence (CSCI), IEEE, pp. 1345-1350.
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Loban, R 1970, 'Digitising Diplomacy: Grand Strategy Video Games as an Introductory Tool for Learning Diplomacy and International Relations', Proceedings of DiGRA 2017 Conference, Melbourne.
Lodi, F, Bodisco, T, Surawski, N, Brown, RJ & Yousef, Y 1970, 'Modelling the effects of ethanol fumigation on engine performance and emissions in a six-cylinder, common rail diesel engine', 11th Asia-Pacific Conference on Combustion, ASPACC 2017, Asia-Pacific Conference on Combustion.
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This paper describes a one-dimensional thermodynamic model developed using AVL BOOST with the objective of analysing the performance, combustion parameters and NOx emissions of a Euro III, six-cylinder turbocharged Cummins diesel engine. The model was validated against experimental data obtained from the same engine run at a constant speed of 2000 rpm at varying load conditions (full, three quarter (3Q) and half load) using low sulphur diesel fuel (D100), as well as fumigated ethanol at 10% (D90), 20% (D80) and 30% (D70) substitutions (by energy). The results for D100, D90, D80 and D70 were found to be in good agreement with the experimental data. The percentage variation for engine performance parameters such as: brake power (BP), indicated power (IP), indicated torque (IT) and mean effective pressure (MEP) for D100 have been found to be approximately in the range of -5% to 1.5% for all loads, whereas, the fuel energy variation was only 0.33% for all loads. With increasing ethanol fumigation, a rise in peak pressure of the cycle, more rapid initial heat release rate and a reduction in the NOx emissions were observed in this study.
Lovatt, HC, Watterson, PA, Schroth, JG, Perry, TA & de Vries, L 1970, 'Non-rotating high-accuracy iron loss measurements on motor stator stacks', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-5.
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A new and improved technique is presented for the measurement of iron loss in motor stators. The most accurate existing technique rotates dummy-test rotors, one for each field strength of interest, inside the stators to be tested and measures the reaction torque on the stators. The new technique uses a wound `rotor' component that does not rotate mechanically but does rotate electrically. Therefore, the speed and magnitude of the rotating flux can be controlled electrically without the inherent difficulties of rotating mechanically at high speed and without building different dummy-test rotors for each field strength test
Lu, DD-C 1970, 'Comparison of DC/DC converters in DCM for reducing low-frequency input current ripple of single-phase two-stage inverters', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-4.
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© 2017 IEEE. Single-phase two-stage inverters generally use an intermediate capacitor to buffer the power imbalance between DC input and AC output. However, the resultant low-frequency voltage ripple on this intermediate capacitor may produce low-frequency ripple at the source side, especially when the front-end dc/dc converter operates in continuous conduction mode (CCM). Some common solutions to reducing this ripple are feedforward control and power decoupling circuits. Alternatively, this paper analyzes a two-stage inverter where the front-end is a dc/dc converter operating in discontinuous conduction mode (DCM). In general dc/dc converters operating in DCM have inherent natural capability to reduce this low-frequency input current ripple, without needing a sophisticated control or complex circuitry as compared with its CCM operation. Analysis with simulation verification is reported to demonstrate such capability.
Lu, H, Heng, J & Wang, C 1970, 'An AI-Based Hybrid Forecasting Model for Wind Speed Forecasting', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 221-230.
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© 2017, Springer International Publishing AG. Forecasting of wind speed plays an important role in wind power prediction for management of wind energy. Due to intermittent nature of wind, accurately forecasting of wind speed has been a long standing research challenge. Artificial neural networks (ANNs) is one of promising approaches to predict wind speed. However, since the results of ANN-based models are strongly dependent on the initial weights and thresholds values which are usually randomly generated, the stability of forecasting results is not always satisfactory. This paper presents a new hybrid model for short term forecasting of wind speed with high accuracy and strong stability by optimizing the parameters in a generalized regression neural network (GRNN) using a multi-objective firefly algorithm (MOFA). To evaluate the effectiveness of this hybrid algorithm, we apply it for short-term forecasting of wind speed from four wind power stations in Penglai, China, along with four typical ANN-based models, which are back propagation neural network (BPNN), radical basis function neural network (RBFNN), wavelet neural network (WNN) and GRNN. The comparison results clearly show that this hybrid model can significantly reduce the impact of randomness of initialization on the forecasting results and achieve good accuracy and stability.
Lu, W & Liu, D 1970, 'Active task design in adaptive control of redundant robotic systems', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 8-15.
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This paper seeks to use robots' kinematic redundancy to excite the system persistently, through actively designing a secondary task in the null space of a primary task. Resulted convergence of unknown parameters in adaptive control leads to better system stability and performance. A measure in Grassmannian, referred to as Subspace Discrepancy Measure (SDM), is proposed for evaluating the additional benefit from the secondary task in converging unknown parameters to their true values. This measure evaluates the angles among subspaces that the parameter estimations are converging to, given different secondary tasks. The subspaces are obtained from Principal Component Analysis (PCA) on a small amount of samples of parameter estimations. The SDM is used to determine the choice of the secondary task online through a trial-and-evaluation procedure actively. Numerical simulations demonstrated that the secondary task chosen by SDM enhances the parameter convergence.
Lucassen, G, Dalpiaz, F, van der Werf, JMEM, Brinkkemper, S & Zowghi, D 1970, 'Behavior-Driven Requirements Traceability via Automated Acceptance Tests', 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW), 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW), IEEE, Lisbon, pp. 431-434.
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Although information retrieval advances significantly improved automated traceability tools, their accuracy is still far from 100% and therefore they still need human intervention. Furthermore, despite the demonstrated benefits of traceability, many practitioners find the overhead for its creation and maintenance too high. We propose the Behavior Driven Traceability Method (BDT) that takes a different standpoint on automated traceability: we establish ubiquitous traceability between user story requirements and source code by taking advantage of the automated acceptance tests that are created as part of the Behavior Driven Development process.
Luo, L, Li, B, Berkovsky, S, Koprinska, I & Chen, F 1970, 'Online Engagement for a Healthier You', Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion, the 26th International Conference, ACM Press, Perth Australia, pp. 1053-1061.
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© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Obesity is a growing problem affecting millions of people. Various behavior change programs have been designed to reduce its prevalence. An Australian supermarket has recently run a web-based health program to motivate people to eat healthily and do more physical activity. The program offered discounts on fresh products and a website, HealthierU, providing interactive support tools for participants. The stakeholders desire to evaluate if the program is effective and if the supporting website is useful to facilitate behavior changes. To answer these questions, in this work we propose a method to: (1) model individual purchase rate from sparse recorded transactions through a mixture of Non-Homogeneous Poisson Processes (NHPP), (2) design criteria for partitioning participants based on their interactions with the HealthierU website, (3) evaluate the program impact by comparing behavior changes across different groups of participants. Our case study shows that during the program the participants significantly increased their purchases of some fresh products. Both the distribution of behavior patterns and impact scores show that the program imposed relatively strong impact on the participants who logged activities and tracked weights. Our method can facilitate the enhancement of personalized health programs, especially aiming to maximize the program impact and targeting participants through web or mobile applications.
Luo, L, Li, B, Koprinska, I, Berkovsky, S & Chen, F 1970, 'Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 2414-2420.
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Customer behavior modeling is important for businesses in order to understand, attract and retain customers. It is critical that the models are able to track the dynamics of customer behavior over time. We propose FC-CSM, a Customer Segmentation Model based on a Fragmentation-Coagulation process, which can track the evolution of customer segmentation, including the splitting and merging of customer groups. We conduct a case study using transaction data from a major Australian supermarket chain, where we: 1) show that our model achieves high fitness of purchase rate, outperforming models using mixture of Poisson processes; 2) compare the impact of promotions on customers for different products; and 3) track how customer groups evolve over time and how individual customers shift across groups. Our model provides valuable information to stakeholders about the different types of customers, how they change purchase behavior, and which customers are more receptive to promotion campaigns.
Luo, L, Liu, W, Koprinska, I & Chen, F 1970, 'DAAR: A Discrimination-Aware Association Rule Classifier for Decision Support', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Conference on Big Data Analytics and Knowledge Discovery (DAWAK), Springer Berlin Heidelberg, Spain, pp. 47-68.
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© Springer-Verlag GmbH Germany 2017. Undesirable correlations between sensitive attributes (such as race, gender or personal status) and the class label (such as recruitment decision and approval of credit card), may lead to biased decision in data analytics. In this paper, we investigate how to build discrimination-aware models even when the available training set is intrinsically discriminating based on the sensitive attributes. We propose a new classification method called Discrimination-Aware Association Rule classifier (DAAR), which integrates a new discrimination-aware measure and an association rule mining algorithm. We evaluate the performance of DAAR on three real datasets from different domains and compare DAAR with two non-discrimination-aware classifiers (a standard association rule classification algorithm and the state-of-the-art association rule algorithm SPARCCC), and also with a recently proposed discrimination-aware decision tree method. Our comprehensive evaluation is based on three measures: predictive accuracy, discrimination score and inclusion score. The results show that DAAR is able to effectively filter out the discriminatory rules and decrease the discrimination severity on all datasets with insignificant impact on the predictive accuracy. We also find that DAAR generates a small set of rules that are easy to understand and applied by users, to help them make discrimination-free decisions.
Luo, M, Nie, F, Chang, X, Yang, Y, Hauptmann, A & Zheng, Q 1970, 'Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling', Proceedings of the AAAI Conference on Artificial Intelligence, Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, California USA, pp. 2308-2314.
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Traditional topic model with maximum likelihood estimate inevitably suffers from the conditional independence of words given the document’s topic distribution. In this paper, we follow the generative procedure of topic model and learn the topic-word distribution and topics distribution via directly approximating the word-document co-occurrence matrix with matrix decomposition technique. These methods include: (1) Approximating the normalized document-word conditional distribution with the documents probability matrix and words probability matrix based on probabilistic non-negative matrix factorization (NMF); (2) Since the standard NMF is well known to be non-robust to noises and outliers, we extended the probabilistic NMF of the topic model to its robust versions using l21-norm and capped l21-norm based loss functions, respectively. The proposed framework inherits the explicit probabilistic meaning of factors in topic models and simultaneously makes the conditional independence assumption on words unnecessary. Straightforward and efficient algorithms are exploited to solve the corresponding non-smooth and non-convex problems. Experimental results over several benchmark datasets illustrate the effectiveness and superiority of the proposed methods.
Luo, M, Zhang, L, Nie, F, Chang, X, Qian, B & Zheng, Q 1970, 'Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, AUSTRALIA, pp. 2421-2427.
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Semi-supervised learning plays a significant role in multi-class classification, where a small number of labeled data are more deterministic while substantial unlabeled data might cause large uncertainties and potential threats. In this paper, we distinguish the label fitting of labeled and unlabeled training data through a probabilistic vector with an adaptive parameter, which always ensures the significant importance of labeled data and characterizes the contribution of unlabeled instance according to its uncertainty. Instead of using traditional least squares regression (LSR) for classification, we develop a new discriminative LSR by equipping each label with an adjustment vector. This strategy avoids incorrect penalization on samples that are far away from the boundary and simultaneously facilitates multi-class classification by enlarging the geometrical distance of instances belonging to different classes. An efficient alternative algorithm is exploited to solve the proposed model with closed form solution for each updating rule. We also analyze the convergence and complexity of the proposed algorithm theoretically. Experimental results on several benchmark datasets demonstrate the effectiveness and superiority of the proposed model for multi-class classification tasks.
Luo, S, Chu, VW, Zhou, J, Chen, F, Wong, RK & Huang, W 1970, 'A Multivariate Clustering Approach for Infrastructure Failure Predictions', 2017 IEEE International Congress on Big Data (BigData Congress), 2017 IEEE International Congress on Big Data (BigData Congress), IEEE, Honolulu, HI, pp. 274-281.
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Luo, S, Zhou, J, Duh, HB-L & Chen, F 1970, 'BVP Feature Signal Analysis for Intelligent User Interface', Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, CHI '17: CHI Conference on Human Factors in Computing Systems, ACM, pp. 1861-1868.
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The Blood Volume Pulse (BVP) sensor has been becoming increasingly common in devices such as smart phones and smart watches. These devices often use BVP to monitor the heart rate of an individual. There has been a large amount of research linking the mental and emotional changes with the physiological changes. The BVP sensor measures one of these physiological changes known as Heart Rate Variability (HRV). HRV is known to be closely related to Respiratory Sinus Arrhythmia (RSA) which can be used as a measurement to quantify the activity of the parasympathetic activity. However, the BVP sensor is highly susceptible to noise and therefore BVP signals often contain a large number of artefacts which make it difficult to extract meaningful features from the BVP signals. This paper proposes a new algorithm to filter artefacts from BVP signals. The algorithm is comprised of two stages. The first stage is to detect the corrupt signal using a Short Term Fourier Transform (STFT). The second stage uses Lomb-Scargle Periodogram (LSP) to approximate the Power Spectral Density (PSD) of the BVP signal. The algorithm has shown to be effective in removing artefacts which disrupt the signal for a short period of time. This algorithm provides the capability for BVP signals to be analysed for frequency based features in HRV which traditionally could be done from the cleaner signals from electrocardiogram (ECG) in medical applications.
Lv, J, Wang, Y, Wu, K, Dissanayake, G, Kobayashi, Y & Xiong, R 1970, 'Planar scan matching using incident angle', 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver, CANADA, pp. 4049-4056.
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© 2017 IEEE. The main contribution of this paper is a planar scan matching algorithm that makes use of the incident angle of a scan point as a feature to enhance the robustness to large relative transformations, particularly in orientation. A new definition of the incident angle is introduced and its consistency with respect to relative transformation between scans is demonstrated. A method that uses the Radial distance and Incident Angle (RIA) for scan alignment, that can efficiently estimate the relative transformation between two scans, is proposed. This approach is designed as a preprocessor for fine scan matching and it is able to pre-align scans that have large angular but limited translational displacement. Scans collected with aggressive robot motion in two typical indoor environments as well as benchmark datasets, are used to demonstrate the effectiveness of RIA when compared with a range of scan matching algorithms reported in the literature.
Ly Ha, VK, Chai, R & Nguyen, HT 1970, 'Real-time WebRTC-based design for a telepresence wheelchair', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 2676-2679.
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This paper presents a novel approach to the
telepresence wheelchair system which is capable of real-time
video communication and remote interaction. The investigation
of this emerging technology aims at providing a low-cost and
efficient way for assisted-living of people with disabilities. The
proposed system has been designed and developed by deploying
the JavaScript with Hyper Text Markup Language 5 (HTML5)
and Web Real-time Communication (WebRTC) in which the
adaptive rate control algorithm for video transmission is
invoked. We conducted experiments in real-world
environments, and the wheelchair was controlled from a
distance using the Internet browser to compare with existing
methods. The results show that the adaptively encoded video
streaming rate matches the available bandwidth. The video
streaming is high-quality with approximately 30 frames per
second (fps) and round trip time less than 20 milliseconds (ms).
These performance results confirm that the WebRTC approach
is a potential method for developing a telepresence wheelchair
system.
Ly, QT, Handojoseno, AMA, Gilat, M, Chai, R, Ehgoetz Martens, KA, Georgiades, M, Naik, GR, Tran, Y, Lewis, SJG & Nguyen, HT 1970, 'Detection of gait initiation Failure in Parkinson's disease based on wavelet transform and Support Vector Machine', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 3048-3051.
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© 2017 IEEE. Gait initiation Failure (GIF) is the situation in which patients with Parkinson's disease (PD) feel as if their feet get 'stuck' to the floor when initiating their first steps. GIF is a subtype of Freezing of Gait (FOG) and often leads to falls and related injuries. Understanding of neurobiological mechanisms underlying GIF has been limited by difficulties in eliciting and objectively characterizing such gait phenomena in the clinical setting. Studies investigating the effects of GIF on brain activity using EEG offer the potential to study such behavior. In this preliminary study, we present a novel methodology where wavelet transform was used for feature extraction and Support Vector Machine for classifying GIF events in five patients with PD and FOG. To deal with the large amount of EEG data, a Principal Component Analysis (PCA) was applied to reduce the data dimension from 15 EEG channels into 6 principal components (PCs), retaining 93% of the information. Independent Component Analysis using Entropy Bound Minimization (ICA-EBM) was applied to 6 PCs for source separation with the aim of improving detection ability of GIF events as compared to the normal initiation of gait (Good Starts). The results of this analysis demonstrated the correct identification of GIF episodes with an 83.1% sensitivity, 89.5% specificity and 86.3% accuracy. These results suggest that our proposed methodology is a promising non-invasive approach to improve GIF detection in PD and FOG.
Ly, QT, Handojoseno, AMA, Gilat, M, Chai, R, Ehgoetz Martens, KA, Georgiades, M, Naik, GR, Tran, Y, Lewis, SJG & Nguyen, HT 1970, 'Detection of turning freeze in Parkinson's disease based on S-transform decomposition of EEG signals', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 3044-3047.
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© 2017 IEEE. Freezing of Gait (FOG) is a highly debilitating and poorly understood symptom of Parkinson's disease (PD), causing severe immobility and decreased quality of life. Turning Freezing (TF) is known as the most common sub-type of FOG, also causing the highest rate of falls in PD patients. During a TF, the feet of PD patients appear to become stuck whilst making a turn. This paper presents an electroencephalography (EEG) based classification method for detecting turning freezing episodes in six PD patients during Timed Up and Go Task experiments. Since EEG signals have a time-variant nature, time-frequency Stockwell Transform (S-Transform) techniques were used for feature extraction. The EEG sources were separated by means of independent component analysis using entropy bound minimization (ICA-EBM). The distinctive frequency-based features of selected independent components of EEG were extracted and classified using Bayesian Neural Networks. The classification demonstrated a high sensitivity of 84.2%, a specificity of 88.0% and an accuracy of 86.2% for detecting TF. These promising results pave the way for the development of a real-time device for detecting different sub-types of FOG during ambulation.
Ma, B, Lei, G & Zhu, J 1970, 'Design, Manufacturing and Optimization of PM-SMC Motors', 2017 7TH INTERNATIONAL ELECTRIC DRIVES PRODUCTION CONFERENCE (EDPC), 7th International Electric Drives Production Conference (EDPC), IEEE, Wuerzburg, GERMANY, pp. 163-168.
Machet, T & Lowe, D 1970, 'Non-Expert Sensor-Based Laboratory Development: A Prototype Mobile Application for Rapid Development, Deployment, and Sharing of Laboratory Experiments', 2017 ASEE Annual Conference & Exposition Proceedings, 2017 ASEE Annual Conference & Exposition, ASEE Conferences.
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Laboratory activities are ubiquitous in schools and universities and allow students to investigate the relationship between real-world phenomena and theoretical models in a controlled setting. As well as traditional 'hands-on' laboratories, both simulations and increasingly remote laboratories are widely used and their educational benefits have been supported by the research. Despite the prevalence of laboratories across educational programs, both the number of new experiments being designed and the sharing of the design of these new experiments has been more limited than might be considered desirable. However, developments in sensor and actuator technology, fuelled by the increasing interest in the Internet of Things (IoT), mean that more data is accessible from a range of 'things' which have been specifically designed to easily share information about themselves and their environments. This presents an opportunity for the design and delivery of laboratory activities based on the real world data available from IoT enabled 'things' without long lead times and expert technical knowledge of the sensors or interconnection technology. This 'non-expert' design of sensor based laboratories has application for both remote and hands on laboratories in schools and universities, but is only valuable if teachers are both willing and able to make use of the solutions. This paper reports on the results of a case study into an educational mobile application which makes use of IoT enabled wireless sensor technology to allow educators to easily design, deliver and share laboratory activities based on real world sensor data. Of particular interest is whether teachers would be willing and able to make use of the framework. The prototype developed is an Android application that makes use of TI SensorTag sensors and provides a low cost, flexible solution for the rapid non-expert design, deployment and sharing of laboratory activity design and data. Initial feedback from hi...
Madhisetty, S & Williams, M-A 1970, 'Framework for Privacy in Photos and Videos When using Social Media', Proceedings of the 19th International Conference on Enterprise Information Systems, 19th International Conference on Enterprise Information Systems, SCITEPRESS - Science and Technology Publications, Porto, Portugal, pp. 331-336.
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Privacy is a social construct. Having said that, how can it be contextualised and studied scientifically? This research contributes by investigating how to manage privacy better in the context of sharing and storing photos and videos using social media. Social media such as Facebook, Twitter, WhatsApp and many more applications are becoming popular. The instant sharing of tacit information via photos and videos makes the problem of privacy even more critical.The main problem was, nobody could define the actual meaning of privacy. Though there are definitions about privacy and Acts to protect it, there is no clear consensus as to what it actually means. I asked myself a question, how do I manage something when I don't know what it means exactly? I then decided to do this research by asking questions about privacy in particular categories of photos so that I could arrive at a general consensus. The data has been processed using the principles of Grounded Theory (GT) to develop a framework which assists in the effective management of privacy in photos and videos.
Maggs, CA & Musial-Gabrys, K 1970, 'LINNEAN SYSTEMATICS IN THE AGE OF BIG DATA', PHYCOLOGIA, INT PHYCOLOGICAL SOC, pp. 123-124.
Magpili, L, Pinto, CA, Bharathy, G & Babiker, M 1970, 'Systematic Capacity‐Based Risk Assessment: Application to Water Service Project in Kassala, Sudan', INCOSE International Symposium, Wiley, pp. 1782-1794.
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AbstractInhabitants of sub‐Saharan Africa suffer disproportionately from lack of access to improved drinking water sources than the rest of the world. Previous studies have established capacity‐related success factors (or enablers) of infrastructure development projects, including drinking water supply. However, these enablers when not well established can also be indicators of risks to the sustainability and overall success of such water projects. The riskiness for success of a water project in Kassala, Sudan was assessed using the eight enablers, resulting in explicit documentation of capacity deficiencies, which may be considered as risk factors for the sustainability, and ultimately, the overall success of the water project. These capacity deficiencies may also serve as risk checklist for project managers and systems engineers involved in projects in similar environments.
Mahmud, K, Morsalin, S, Hossain, MJ & Town, GE 1970, 'Domestic peak-load management including vehicle-to-grid and battery storage unit using an artificial neural network', 2017 IEEE International Conference on Industrial Technology (ICIT), 2017 IEEE International Conference on Industrial Technology (ICIT), IEEE, Toronto, CANADA, pp. 586-591.
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Mahmud, K, Town, GE & Hossain, MJ 1970, 'Mitigating the impact of rapid changes in photovoltaic power generation on network voltage', 2017 IEEE Power and Energy Conference at Illinois (PECI), 2017 IEEE Power and Energy Conference at Illinois (PECI), IEEE, Champaign, IL, pp. 1-6.
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Mai, TC, Hoang, TM, Tuan, HD, Di Renzo, M & Duong, TQ 1970, 'Modeling and Analysis of Interference for Diffusion-Based Nanoscale Networks with Spatially Distributed Transmitters', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. We consider a diffusion-based nano-network with N spatially distributed transmitters and one receiver. While the transmitters are linked in a unified entity to perform one transmission, the receiver is large enough to be viewed as a plane. Messages are encoded into the number of nano-scale molecules. Based on these assumptions, we analyze the signal-to-interference ratio, which is based on the average numbers of absorbed molecules. Moreover, we present an approach to interference alignment for molecular communications.
Malik, N, Puthal, D & Nanda, P 1970, 'An Overview of Security Challenges in Vehicular Ad-Hoc Networks', 2017 International Conference on Information Technology (ICIT), 2017 8th International Conference on Information Technology (ICIT), IEEE, Bhubaneswar, India, pp. 208-213.
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© 2017 IEEE. Vehicular Ad hoc Networks (VANET) is emerging as a promising technology of the Intelligent Transportation systems (ITS) due to its potential benefits for travel planning, notifying road hazards, cautioning of emergency scenarios, alleviating congestion, provisioning parking facilities and environmental predicaments. But, the security threats hinder its wide deployment and acceptability by users. This paper gives an overview of the security threats at the various layers of the VANET communication stack and discuss some of the existing solutions, thus concluding why designing a security framework for VANET needs to consider these threats for overcoming security challenges in VANET.
Manzoor, S, Manzoor, M & Hussain, W 1970, 'An Analysis of Energy-Efficient Approaches Used for Virtual Machines and Data Centres', 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), IEEE, Shanghai, China, pp. 91-96.
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© 2017 IEEE. The adoption of cloud computing has increased significantly, but this has given rise to the problem of efficient energy usage. The efficient use of energy by data centers and the use of virtual machines can help to minimize cost deadlines, resources, and utilization and execution times. There is a consequent need for different approaches that can reduce energy consumption whilst still achieving the multiple objectives of cloud computing. In this study, we examine a number of different approaches that have been discussed in the recent literature w.r.t. energy-efficient cloud workflow management, and we compare these approaches for energy-efficient usage of data centers and virtual machines. The results show that virtual machine scheduling and virtual machine allocation approaches are the most commonly used approaches that achieve an optimal energy consumption.
Marcote, B, Ribó, M, Paredes, JM, Ishwara-Chandra, CH, Swinbank, JD, Broderick, JW, Markoff, S, Fender, R, Wijers, RAMJ, Pooley, GG, Stewart, AJ, Bell, ME, Breton, RP, Carbone, D, Corbel, S, Eislöffel, J, Falcke, H, Grießmeier, J-M, Kuniyoshi, M, Pietka, M, Rowlinson, A, Serylak, M, van der Horst, AJ, van Leeuwen, J, Wise, MW & Zarka, P 1970, 'Measuring the expansion velocity of the outflows of LS I +61 303 through low-frequency radio observations', AIP Conference Proceedings, HIGH ENERGY GAMMA-RAY ASTRONOMY: 6th International Meeting on High Energy Gamma-Ray Astronomy, Author(s), Heidelberg, GERMANY, pp. 040018-040018.
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Marjanovic, O & Cecez-Kecmanovcic, D 1970, 'Understanding datafication effects of open government information systems - A contemporary systems thinking approach', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 2731-2740.
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This paper contributes to an improved understanding of datafication effects of open government Information Systems (IS). We focus on a particular category of these IS that is designed to provide open performance data of a public sector (education, health, social services) in the name of accountability and transparency. While acknowledging possible positive datafication effects, in this paper we investigate the negative ones caused by propagation and reuse of open performance data. Using contemporary systems thinking as a theoretical lens, we identify three main types of datafication mechanisms, explain their underlying systemic manifestations and illustrate their societal effects. Drawing insights from a longitudinal research case study of a large-scale open government IS in Australia, we 'unpack' mutually-shaping relationships between technology and human behavior, reinforced by various feedback loops within a wider societal system.
Marjanovic, O & Cecez-Kecmanovic, D 1970, 'Understanding Datafication Effects of Open Government Information Systems - A Contemporary Systems Thinking Approach.', HICSS, ScholarSpace / AIS Electronic Library (AISeL), pp. 1-10.
Marjanovic, O & Dinter, B 1970, '25+ Years of Business Intelligence and Analytics Minitrack at HICSS: A Text Mining Analysis.', HICSS, ScholarSpace / AIS Electronic Library (AISeL), pp. 1-10.
Marjanovic, O & Dinter, B 1970, '25+ years of the business intelligence and analytics minitrack at HICSS: A text mining analysis', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5338-5347.
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This research project is inspired by the occasion of the 50th anniversary of the Hawaii International Conferences on Systems Sciences (HICSS). As the current co-chairs of the longest-running minitrack on Business Intelligence (BI), Business Analytics (BA) and Big Data (as it is currently known) at HICSS, we report on its 27-year history of relevant and interesting research. Our insights into the key research themes and their progress over time were obtained through a semantic text mining of all research publications included in this minitrack since 1990. We also illustrate a practical method of using a sophisticated text-mining tool (Leximancer) so that it could be replicated by other researchers interested in content analysis methods in other research fields.
Marjanovic, O, Dinter, B & Ariyachandra, T 1970, 'Introduction to Organizational Issues of Business Intelligence, Business Analytics and Big Data Minitrack', Proceedings of the Annual Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, p. 5034.
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Marjanovic, O, Dinter, B & Ariyachandra, T 1970, 'Introduction to Organizational Issues of Business Intelligence, Business Analytics and Big Data Minitrack.', HICSS, ScholarSpace / AIS Electronic Library (AISeL), pp. 1-1.
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Marjanovic, O, Dinter, B & Ariyachandra, T 1970, 'Introduction to the HICSS-50 organizational issues of business intelligence, Business analytics and big data minitrack', Proceedings of the Annual Hawaii International Conference on System Sciences, p. 5337.
Maroufi, M, Ruppert, MG, Fowler, AG & Moheimani, SOR 1970, 'Design and control of a single-chip SOI-MEMS atomic force microscope', 2017 American Control Conference (ACC), 2017 American Control Conference (ACC), IEEE, pp. 2869-2874.
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Mateos, MK, Trahair, TN, Mayoh, C, Barbaro, PM, George, C, Sutton, R, Revesz, T, Barbaric, D, Giles, J, Alvaro, F, Mechinaud, FM, Catchpoole, DR, Kotecha, RS, Quinn, MCJ, Chenevix-Trench, G, MacGregor, S, Dalla-Pozza, L & Marshall, GM 1970, 'Clinical and Germline Risk Factors for the Occurrence of Multiple Treatment Toxicities during Childhood Acute Lymphoblastic Leukemia (ALL) Therapy', BLOOD, 59th Annual Meeting of the American-Society-of-Hematology (ASH), AMER SOC HEMATOLOGY, GA, Atlanta.
McGregor, C, Bonnis, B, Stanfield, B & Stanfield, M 1970, 'Integrating Big Data analytics, virtual reality, and ARAIG to support resilience assessment and development in tactical training', 2017 IEEE 5th International Conference on Serious Games and Applications for Health (SeGAH), 2017 IEEE 5th International Conference on Serious Games and Applications for Health (SeGAH), IEEE, pp. 1-7.
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© 2017 IEEE. Combat tactical training activities utilising virtual reality environments are being used increasingly to create training scenarios to promote resilience against stressors and to enable standardized training scenarios to allow trainees to learn techniques for various stressors. Resilience is an important component for mental health. However, assessment of the trainees' response to these training activities has either been limited to various pre and post training assessment metrics or collected in parallel during experiments and analysed after collection rather than in real-time. New Big Data approaches have the potential to provide real-time analytics. We have created a Big Data analytics platform, Athena, that in real-time acquires data from a first person shooter military combat simulation game, ArmA 3, as well as the data ArmA 3 sends to the muscle stimulation component of a multisensory garment, ARAIG that provides on the body feedback to the wearer for communications, weapon fire and being hit and integrates that data with physiological response data such as heart rate, breathing behaviour and blood oxygen saturation. We present results from our initial pilot study from an ethics approved equipment integration study. Our approach is equally applicable for Virtual Reality Graded Exposure Therapy with physiological monitoring.
McGregor, C, Orlov, O, Baevsky, R, Chernikova, A & Rusanov, V 1970, 'A Method for the Integration of Real-time Probabilistic Approaches for Astronaut Wellness in Human in the Loop Related Missions and Situations with Big Data Analytics', 19th AIAA Non-Deterministic Approaches Conference, 19th AIAA Non-Deterministic Approaches Conference, American Institute of Aeronautics and Astronautics, Grapevine, Texas.
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© 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. The man-instrumentation-equipment-vehicle-environment ecosystem is complex in aerospace missions. Health status of the individual has important implications on decision making and performance that should be factored into assessments for probability of success/risk of failure both in offline and real-time models. To date probabilistic models have not considered the dynamic nature of health status. Big Data analytics is enabling new forms of analytics to assess health status in real-time. There is great potential to integrate dynamic health status information with platforms assessing risk and the probability of success for dynamic individualized real-time probabilistic predictive risk assessment. In this research we present an approach utilizing Big Data analytics to enable continuous assessment of astronaut health risk and show its implications for integration with HITL related aerospace mission.
Meng, J, Huang, J, Sheng, D, Sloan, SW, Cao, P & Fan, W 1970, 'Mathematical programming based DEM for geomaterials', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 315-321.
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In this paper, a discrete numerical model using second-order cone programming is presented. The resulting optimisation problem is solved using an off-the-shelf interior-point algorithm. In contrast to the classical DEM, the purely static problem can be formulated directly without using artificial damping. The proposed approach can also be readily extended to dynamics problems. Due to the implicit time integration scheme adopted, large time steps can be employed. Importantly, the proposed approach is more general than the classical DEM because rigid particles and rigid-cementation in geomaterials can also be considered. The capabilities of the proposed method are demonstrated through (1) a biaxial compression test on granular media using circular particles; and (2) the simulation of brittle rock failure using polygonal particles.
Meng, Q, Catchpoole, D, Skillicom, D & Kennedy, PJ 1970, 'Relational autoencoder for feature extraction', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 364-371.
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© 2017 IEEE. Feature extraction becomes increasingly important as data grows high dimensional. Autoencoder as a neural network based feature extraction method achieves great success in generating abstract features of high dimensional data. However, it fails to consider the relationships of data samples which may affect experimental results of using original and new features. In this paper, we propose a Relation Autoencoder model considering both data features and their relationships. We also extend it to work with other major autoencoder models including Sparse Autoencoder, Denoising Autoencoder and Variational Autoencoder. The proposed relational autoencoder models are evaluated on a set of benchmark datasets and the experimental results show that considering data relationships can generate more robust features which achieve lower construction loss and then lower error rate in further classification compared to the other variants of autoencoders.
Meng, Q, Wu, J, Ellis, J & Kennedy, PJ 1970, 'Dynamic island model based on spectral clustering in genetic algorithm', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 1724-1731.
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© 2017 IEEE. How to maintain relative high diversity is important to avoid premature convergence in population-based optimization methods. Island model is widely considered as a major approach to achieve this because of its flexibility and high efficiency. The model maintains a group of sub-populations on different islands and allows sub-populations to interact with each other via predefined migration policies. However, current island model has some drawbacks. One is that after a certain number of generations, different islands may retain quite similar, converged sub-populations thereby losing diversity and decreasing efficiency. Another drawback is that determining the number of islands to maintain is also very challenging. Meanwhile initializing many sub-populations increases the randomness of island model. To address these issues, we proposed a dynamic island model (DIM-SP) which can force each island to maintain different sub-populations, control the number of islands dynamically and starts with one sub-population. The proposed island model outperforms the other three state-of-the-art island models in three baseline optimization problems including job shop scheduler, travelling salesmen, and quadratic multiple knapsack.
Mi, J, Wang, K, Liu, B, Ding, F, Sun, Y & Huang, H 1970, 'A Multiobjective Evolution Algorithm Based Rule Certainty Updating Strategy in Big Data Environment', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, YourSingapore, Singapore, SINGAPORE, pp. 1-6.
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Mihăiţă, AS, Tyler, P, Menon, A, Wen, T, Ou, Y, Cai, C & Chen, F 1970, 'An investigation of positioning accuracy transmitted by connected heavy vehicles using DSRC', Transportation Research Board - 96th Annual Meeting, Washington, D.C..
Mihăiţă, AS, Tyler, P, MWall, J, Vecovsky, V & Cai, C 1970, 'Positioning and collision alert investigation for DSRC-equipped light vehicles through a case study in CITI', ITS World Congress 2017, Montreal.
Min Lu, Jie Liang, Yu Zhang, Guozheng Li, Siming Chen, Zongru Li & Yuan, X 1970, 'Interaction+: Interaction enhancement for web-based visualizations', 2017 IEEE Pacific Visualization Symposium (PacificVis), 2017 IEEE Pacific Visualization Symposium (PacificVis), IEEE, Seoul, Korea, pp. 61-70.
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© 2017 IEEE. In this work, we present Interaction+, a tool that enhances the interactive capability of existing web-based visualizations. Different from the toolkits for authoring interactions during the visualization construction, Interaction+ takes existing visualizations as input, analyzes the visual objects, and provides users with a suite of interactions to facilitate the visual exploration, including selection, aggregation, arrangement, comparison, filtering, and annotation. Without accessing the underlying data or process how the visualization is constructed, Interaction+ is application-independent and can be employed in various visualizations on the web. We demonstrate its usage in two scenarios and evaluate its effectiveness with a qualitative user study.
Ming, C, Rizwanul Fattah, IM, Chan, QN, Medwell, PR, Kook, S, Hawkes, ER & Yeoh, GH 1970, 'Combustion measurements of waste cooking oil biodiesel', 11th Asia-Pacific Conference on Combustion, ASPACC 2017.
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An experimental investigation was performed to assess the combustion characteristics of a waste cooking oil (WCO) biodiesel fuel under simulated compression-ignition engine conditions. A conventional diesel was used as a base fuel for comparison purpose. The fuels were injected into the quiescent steady environment inside a constant-volume combustion chamber (CVCC) of 19.4 kg/m3 ambient density, 6 MPa ambient pressure, and 1100 K bulk temperature. A range of optical diagnostics were performed, to compare the fuels over ambient O2 concentrations of 10-21 vol.%, and injection pressures of 70-130 MPa. The results reveal that for the investigated test conditions (i) the lift-off lengths and the first soot distances of the biodiesel are consistently longer than that of diesel; (ii) the peak soot level of the flame increases with the relative distance between the first soot formation and flame liftoff; and (iii) the WCO biodiesel has a lower soot formation propensity than diesel. The fuel liquid lengths were also measured to be shorter than their lift-off distances, indicating no interaction between their spray and combustion processes.
Mishra, DK, Mohanty, A & Ray, P 1970, 'MATLAB/Simulink based FA for optimizing TCSC controller in a power system', 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS), 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE, pp. 1-7.
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Mishra, DK, Mohanty, A, Viswavandya, M, Ray, PK & Panigrahi, TK 1970, 'Optimization of TCSC with multi objective firefly algorithm for enhancing SMIB system', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, pp. 1215-1222.
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Mishra, DK, Panigrahi, TK, Mohanty, A & Ray, PK 1970, 'A comparative analysis of load frequency control of two-area interconnected hybrid power system using LabVIEW', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, pp. 1953-1960.
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Mishra, DK, Panigrahi, TK, Mohanty, A & Ray, PK 1970, 'Multi-area interconnected automatic generation control with IPFC and TDOFPID controller', 2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), IEEE, pp. 279-284.
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Mishra, DK, Panigrahi, TK, Ray, PK & Mohanty, A 1970, 'Application of integral double derivative with filter for load frequency control in multi area power system', 2017 IEEE Calcutta Conference (CALCON), 2017 IEEE Calcutta Conference (CALCON), IEEE, pp. 220-225.
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Mishra, DK, Panigrahi, TK, Ray, PK & Mohanty, A 1970, 'Application of tilt integral derivative filter for load frequency control of three area interconnecetd system', 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), IEEE, pp. 2059-2066.
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Mols, I, van den Hoven, E & Eggen, B 1970, 'Balance, Cogito and Dott', Proceedings of the Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, TEI '17: Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, ACM, Yokohama, Japan, pp. 427-433.
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© 2017 ACM. Reflection in and on everyday life can provide selfinsight, increase gratitude and have a positive effect on well-being. To integrate reflection in everyday life, media technologies can provide support. In this paper, we explore how both media creation & use in different modalities can support reflection. We present the ongoing work of designing and building Balance, Cogito, and Dott, focusing on media in audible, textual and visual form. We discuss our research-Through-design process and address the differences between modalities in terms of interaction, tangibility, and the integration in everyday life.
Mooney, GR & Burdon, S 1970, 'Organisational Ideation: Engaging Motivation as a Creative Catalyst', BAM2017 Conference Proceedings, British Academy of Management Conference 2017, British Academy of Management, Warwick University, Warwick U.K..
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Is there a secret to creative success? This paper presents the results of two studies examining the origins of ideas within two sectors where victory is premised upon repeatedly producing novel and distinctive outcomes for consumers: namely, high-technology and broadcast television. Using interviews and statistical analysis the authors investigated the idea practices of 19 enterprises founded as creative technology endeavours, as well as the managerial and creative talent behind three successful television production teams. Findings showed that both groups, while engaged in different markets, had remarkably similar need for ever-refreshed pools of ideas from which to draw and the need to provision these well. Understanding how to support and encourage creative genesis in the areas of goals, imaginative thought, knowledge growth and staff motivation, was essential to ongoing success. In particular, owning a resonant passion was a major catalyst for whether new ideas emerged.
Moore, SI, Ruppert, MG & Yong, YK 1970, 'Design and analysis of piezoelectric cantilevers with enhanced higher eigenmodes for atomic force microscopy', 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), IEEE, pp. 719-724.
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Morshed, KM, Karmokar, DK & Esselle, KP 1970, 'Highly Efficient Leaky-Wave Antenna Array for 28-GHz Millimeter-Wave Terminals', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-4.
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© 2017 IEEE. A highly efficient leaky-wave antenna (LWA) array is presented in this paper. The proposed LWA array covers 28-GHz millimeter-wave frequency band and can be useful for 5G terminals. The antenna has been designed to be integrated to a substrate of dimensions 120 mm × 70 mm and occupies a small area of 24.5 mm × 24.5 mm. A dielectric load is used to increase the antenna efficiency. The efficiency of the array varies between 97% and 98% within the 28-GHz millimeter-wave band. It has a wide operating bandwidth of 6 GHz (26 - 32 GHz) and a peak gain of 9.1 dBi at 28 GHz. Within the 28-GHz millimeter-wave band the proposed LWA array has stable boresight radiation in the x-z and y-z planes.
Movassaghi, S, Maleki, B, Smith, DB & Abolhasan, M 1970, 'Biologically inspired self-organization and node-level interference mitigation amongst multiple coexisting wireless body area networks', 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, Valencia, Spain, pp. 1221-1226.
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© 2017 IEEE. This paper presents a node-level self-organizing interference avoidance scheme (SIAC) between multiple coexisting wireless body area networks (WBANs) that incorporates self-organization and smart spectrum allocation. It follows a biologically inspired approach based on the theory of pulse-coupled oscillators for self-organization. The proposed scheme makes three major contributions as compared to the current literature. Firstly, it considers node-level interference for internetwork interference mitigation rather than considering each WBAN as a whole. Secondly, it allocates synchronous and parallel transmission intervals for interference avoidance in an optimal manner and dynamically adapts to changes in their coexistence. Finally, it achieves collision-free, self-organized communication with only information of the firing signal of each WBAN and does not require a global coordinator to manage its communications. It operates on a nodes traffic priority, signal strength, and density of sensors in a WBAN. Simulation results show that our proposal achieves a fast convergence time despite the little information it receives. Moreover, SIAC is shown to be robust to variations in signal strength, number of coexisting WBANs and number of sensor nodes within each WBAN.
Mueck, M, Choi, S, Bender, P, Ivanov, V, Jin, Y, Ahn, H, Kim, K & Dutkiewicz, E 1970, 'Radio Equipment Directive - A Novel Software Reconfiguration Framework', 2017 IEEE Globecom Workshops (GC Wkshps), 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, Singapore, Singapore, pp. 1-5.
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The European Commission recently published the revision of the novel Radio Equipment Directive 2014/53/EU replacing the R&TTE Directive which has been in force since 1999. This Directive represents the basic regulation framework for the making available of radio equipment on the Single European Market. Among several changes, the new RED includes specific provisions enabling the usage Software Reconfiguration for Radio Equipment in Europe. At the same time, ETSI has developed a novel Software Radio Reconfiguration framework specifically meeting the requirements of the Directive and encompassing technical, certification and security solutions. This paper introduces and comments the related changes on the regulation level and introduces the ETSI solution which is ready to be applied for new type of radio equipment to be introduced in Europe.
Mukhtar, NM & Dah-Chuan Lu, D 1970, 'A bidirectional flyback converter with cross-coupled non-dissipative snubber circuits', 2017 IEEE International Telecommunications Energy Conference (INTELEC), 2017 IEEE International Telecommunications Energy Conference (INTELEC), IEEE, Broadbeach, QLD, Australia, pp. 476-481.
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This paper proposed a novel isolated bidirectional flyback converter integrated with two non-dissipative LC snubbers. In the proposed topology, the main flyback transformer and the LC snubbers are crossed-coupled to reduce current circulation and recycle the leakage energy. The proposed isolated bidirectional flyback converter can step-up the voltage of the battery (Vbat = 12V) to a high voltage side (VHV = 200V) for the load demand and vice versa. The main goal of this paper is to demonstrate the performances of this topology to achieve high voltage gain with less switching losses and reduce components stresses. The circuit analysis conferred in detail for Continuous Conduction Mode (CCM). Lastly, a laboratory prototype constructed to compare with simulation result.
Mukunthan, A, Cooper, CS, Safaei, F, Franklin, DR & Abolhasan, M 1970, 'Leveraging the Propagation Model to Make Greedy Routing Decisions in Urban Environments.', VTC Spring, IEEE Vehicular Technology Conference, IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The CORNER propagation model, first proposed in 2010, has been previously validated and found to be a reasonably accurate representation of propagation scenarios in urban Vehicular Ad Hoc Networks (VANETs). This paper considers the impact of the propagation environment on routing performance and reveals a pressing need to consider more accurate propagation models when designing urban VANET routing protocols. A greedy routing protocol, which uses CORNER's propagation estimates for neighbour selection, is then presented. The new protocol, named Corner Propagation Stateless Routing (CPSR) is compared to GPSR, a benchmark protocol for VANETs, showing between 87% and 300% improvement in packet delivery ratio at higher network loads.
Munoz, F, Miro, JV, Dissanayake, G, Ulapane, N & Nguyen, L 1970, 'Design of a lock-in amplifier integrated with a coil system for eddy-current non-destructive inspection', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1948-1953.
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© 2017 IEEE. Eddy-current non-destructive inspections of conductive components are of great interest in several industries including civil infrastructure and the mining industry. In this work, we have used a driver-pickup coil system as the probe to carry out inspection of ferromagnetic plates. The specific geometric configuration of the probe generates weak electric signals that are buried in a noisy environment. In order to detect these weak signals, we have designed and implemented a lock-in amplifier as part of the signal processing technique to increase the signal-to-noise ratio and also improve the sensitivity of the probe. We have used Comsol as a finite element method (FEM) to design the probe and conducted experiments with the probe and the lock-in amplifier. The experimental results, which are in agreement with the FEM results, indicate that the designed probe along with a lock-in amplifier can potentially be used to estimate the thickness of thin plates.
Murray, A, Gilbert, RAYMONDI & Castel, A 1970, 'Reinforced concrete crack model based on stiffness analysis of tension members', Proceedings of International Structural Engineering and Construction.
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The average spacing of primary cracks in a reinforced concrete (RC) member greatly influences its in-service behavior, especially with regard to stiffness and average crack width. Accurate predictions of the average crack spacing are therefore crucial for satisfying serviceability requirements in RC structures. This is particularly the case when relying on analytical models that treat cracks discretely rather than in a smeared fashion. Popular code-based models for primary crack spacing are often wildly inaccurate and may lead to poor predictions of in-service behavior. In this paper, the problem or primary crack formation is approached from a stiffness perspective. The proposed model is based on the results of several experimental tension stiffening studies in the literature, as well as a previous numerical study dealing with the effect on stiffness of non-plane deformation in the neighborhood of primary cracks. The proposed model is compared to some popular code-based models and is shown to better predict average crack spacing for a wide variety of beams, slabs, and tension members.
Murray, A, Gilbert, RI & Castel, A 1970, 'REINFORCED CONCRETE CRACK MODEL BASED ON STIFFNESS ANALYSIS OF TENSION MEMBERS', Proceedings of International Structural Engineering and Construction, ISEC Press.
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The average spacing of primary cracks in a reinforced concrete (RC) member greatly influences its in-service behavior, especially with regard to stiffness and average crack width. Accurate predictions of the average crack spacing are therefore crucial for satisfying serviceability requirements in RC structures. This is particularly the case when relying on analytical models that treat cracks discretely rather than in a smeared fashion. Popular code-based models for primary crack spacing are often wildly inaccurate and may lead to poor predictions of in-service behavior. In this paper, the problem or primary crack formation is approached from a stiffness perspective. The proposed model is based on the results of several experimental tension stiffening studies in the literature, as well as a previous numerical study dealing with the effect on stiffness of non-plane deformation in the neighborhood of primary cracks. The proposed model is compared to some popular code-based models and is shown to better predict average crack spacing for a wide variety of beams, slabs, and tension members.
Murray, A, Gilbert, RI & Castel, A 1970, 'Study of disturbed strain regions for serviceability analysis of cracked RC flexural members', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, pp. 97-102.
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In analysing cracked Reinforced Concrete (RC) flexural members at the service level, some of the simplifying assumptions commonly made in the literature are poorly justified and do not properly account for the significant disturbed strain regions in the neighbourhood of the cracks. This may lead to misunderstandings and poor interpretations of the in-service behaviour of RC structures. For instance, in determining the contribution to flexural stiffness of the intact concrete between primary cracks, it is usual to assume a linear variation of strain despite warping of these cross-sections. Another example is the use of an effective area of tensile concrete to assess the flexural stiffness of a cracked member. It is unlikely that a single value of the effective concrete area could accurately model the stiffness of a cracked tension zone without due consideration of the spacing of cracks and the complex strain field that arises in the concrete around the embedded bars. This paper presents an analytical model for the estimation of instantaneous flexural stiffness of cracked RC members, making use of the results of two Finite Element (FE) studies of disturbed strain regions near cracks.
Musa, IA, Mashiri, FR & Zhu, X 1970, 'Investigation on stress concentration factor in concrete-filled steel tubular T-joints under out-of-plane bending moment', CRC Press, pp. 443-448.
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Mustapha, S, Braytee, A & Ye, L 1970, 'Detection of surface cracking in steel pipes based on vibration data using a multi-class support vector machine classifier', SPIE Proceedings, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, SPIE, Portland, OR.
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Nagar, U, Nanda, P, He, X & Tan, ZT 1970, 'A framework for data security in cloud using collaborative intrusion detection scheme', Proceedings of the 10th International Conference on Security of Information and Networks, SIN '17: Security of Information and Networks, ACM, Jaipur, India, pp. 188-193.
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© 2017 Association for Computing Machinery. Cloud computing offers an on demand, elastic, global network access to a shared pool of resources that can be configured on user demand. The advantages of cloud computing are lucrative for well-established organizations looking to reduce infrastructure cost overheads. However, the users are not quite confident in entrusting their data to the cloud due to security threats and risks perceived in the cloud domain. Issues involving privacy requirements for the cloud and best practices in the cloud are suggested in this paper. Although the cloud provider ensures security in the cloud yet the flow of data, storage location, data computing process and security breaches are not transparent to the cloud customer. This distrust and lack of control on data is a major hindrance for potential cloud customers in adopting the cloud models for their businesses. Intrusion Detection Systems (IDSs) are widely used to detect malicious activities. However existing solutions with IDSs involving DDoS and other non-detectable events may not be suitable in applying to the cloud due to distributed data storage and a major shift in Internet access mechanisms offered by cloud providers. Hence there is a strong need to analyze an appropriate IDS to counter DDoS attacks in the cloud. In this paper we propose a novel framework for data security in the cloud using Collaborative Intrusion Detection (CIDS) scheme. The benefits of CIDS scheme in cloud are enabling the end user to get comprehensive information in the event of a distributed attack on cloud.
Naik, GR, Pratihast, M, Chai, R, Al-Ani, A, Acharyya, A & Nguyen, HT 1970, 'Differences in lower limb muscle activation patterns during Sit to Stand Task for different heel heights', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 2486-2489.
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The purpose of this study was to investigate
differences in lower limb muscle activation patterns for females
wearing shoes with different heel heights during Sit to Stand
Task (STS). Ten female participants with no prior history of
neurological disorders participated in this study. Surface
electromyography (sEMG) characteristics were recorded for
four different heel heights (ranging from 4cm to 10cm) while
performing the STS task. Signal processing analysis suggests
that muscle activities increases on elevated heel heights, which
may induce muscle imbalance for frequent STS tasks. In
addition, results of muscle utilisation (percentage) for different
heel heights suggest that lower limb muscles tend to compensate
in order to maintain postural balance.
Naik, T, McGregor, C & James, A 1970, 'Automated partial premature infant pain profile scoring using big data analytics', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 246-249.
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© 2017 IEEE. Lack of valid and reliable pain assessment in the neonatal population has become a significant challenge in the Neonatal Intensive Care Unit (NICU). In an attempt to forego the manual pain scoring system, this paper presents an initial framework to automate a partial pain score for newborn infants using big data analytics that automates the analysis of high speed physiological data. An ethically approved retrospective clinical research study was performed to calculate Artemis Premature Infant Pain Profile (APIPP) scores from premature infant data collected from the Artemis platform. Using the Premature Infant Pain Profile (PIPP) as the gold standard scale, scoring techniques were automated to create data abstractions from gestational age and the physiological streams of Heart Rate (HR) and Oxygen Saturation (SpO2). These were then brought together to compute an automated partial pain score. APIPP was retrospectively compared with the PIPP which was manually scored by nursing staff at The Hospital for Sick Children, Toronto. Differences within both the scales were evaluated and analysed by creating a data model. Future research will focus on the clinical validation of this work by implementing this work into a clinical decision support system (CDSS) named Artemis.
Namvar, A, Ghazanfari, M & Naderpour, M 1970, 'A customer segmentation framework for targeted marketing in telecommunication', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, China, pp. 1-6.
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© 2017 IEEE. Telecommunication industry is highly competitive, and mass marketing is not applicable anymore. Moreover, Mobile customers have different behaviors that urge telecom industries to differentiate their strategies to meet customers' needs. At the same time, mobile operators have an enormous amount of customer records, and data-driven approaches can help them to draw insights from this huge amount of data. Therefore, a data-driven segmentation approach can support marketing strategies to tailor their marketing plans. In this research, we adopt behavior and beneficial segmentation in a two-dimensional framework to segment customers. The results indicate that our method has an outstanding performance for customer segmentation. Moreover, we have recommended some marketing strategies based on each segment's behavior with the aim of increasing in Average Revenue Per User (ARPU) and decreasing in marketing expenses.
Nan, Y, Huang, X & Guo, YJ 1970, 'A Generalized Continuous Wave Synthetic Aperture Radar', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. Attention has been devoted to Synthetic Aperture Radar (SAR) for half a century. Though it is a well-proven remote sensing technique, conventional pulsed SAR has several inherent limitations. In this paper, we present a new SAR concept, called Generalized Continuous Wave SAR (GCW-SAR). By using continuous wave signaling, the GCW-SAR system achieves better performance and overcomes the limitations such as the minimum antenna area in conventional SAR. Unlike the frequency modulated continuous wave SAR (FMCW-SAR) system, the GCW-SAR image is reconstructed by correlation between the sampled raw data and the location dependent reference signals. A fast image reconstruction algorithm is also presented in the paper. The principle of GCW-SAR and the effectiveness of the proposed algorithm are validated by numerical simulation results.
Nan, Y, Huang, X & Guo, YJ 1970, 'Passive synthetic aperture radar imaging with piecewise constant Doppler algorithm', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Veorna, Italy, pp. 41-44.
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© 2017 IEEE. This paper presents a non-cooperative space-surface bistatic synthetic aperture radar (SS-BSAR) with a novel image reconstruction algorithm. Exploiting the continuous wave signal from the transmitters of opportunity, the new algorithm produces better imaging performance. Unlike the conventional passive SAR, the image reconstruction is achieved by correlation in time-domain without distinction between fast time and slow time. With the movement of the radar, the range curve can be linearized within multiple segments. In each segment, the Doppler frequency shift incurred in the reflected signal from a target can be assumed to be constant and thus the SAR image can be reconstructed recursively. The proposed piecewise constant Doppler (PCD) algorithm is validated by the simulation results.
Nanda, A, Nanda, P, He, X, Jamdagni, A & Puthal, D 1970, 'Secure-GLOR: An Adaptive Secure Routing Protocol for Dynamic Wireless Mesh Networks', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, Australia, pp. 269-276.
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© 2017 IEEE. With the dawn of a new era, digital security has become one of the most essential part of any network. Be it a physical network, virtual network or social network, the demand for secure data transmission is ever increasing. Wireless mesh networks also stand the same test of security as the legacy networks. This paper presents a secure version of the Geo-Location Oriented Routing (GLOR) protocol for wireless mesh networks, incorporating a multilevel security framework. It implements authentication using the new features of the network model and enables encryption throughout the network to provide high levels of security.
Nanda, P, Xiang, Y & Mu, Y 1970, 'Message from the IEEE TrustCom 2017 Program Chairs', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, pp. xvii-xvii.
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Nascimben, M, Wang, YK, Singh, AK, King, JT & Lin, CT 1970, 'Influence of EEG tonic changes on Motor Imagery performance', 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), IEEE, Shanghai, PEOPLES R CHINA, pp. 46-49.
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© 2017 IEEE. In Motor Imagery literature, performance predictors are commonly divided in four categories: personal, psychological, anatomical and neurophysiological. However these predictors are limited to inter-subjects changes. To overcome this limitation and evaluate intra-subjects performance, we tried to combine two groups of these measures: psychological and neurophysiological. As neurophysiological variables tonic changes in resting EEG theta and alpha sub-bands were considered. As psychological parameter we analyzed internalized attention and its correlates in lower alpha. We found that when internalized attention doesn't decrease, Motor Imagery performance outcome can be correctly predicted by resting EEG tonic variations.
Nassir, S & Leong, TW 1970, 'Traversing Boundaries', Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI '17: CHI Conference on Human Factors in Computing Systems, ACM, Denver, Colorado, USA, pp. 6386-6397.
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© 2017 ACM. This is a methods paper that draws from our fieldwork experiences of conducting qualitative research in Saudi Arabia where we used interviews and probes to understand ageing people's experiences. The aim of this paper is to present insights gained about conducting qualitative research in Saudi. We present a range of the cultural considerations that shaped the design of the fieldwork and highlight opportunities, challenges, and issues that we faced when conducting interviews and deploying research probes. Influences of social-cultural practices and religion presented interesting challenges for recruitment, conducting cross-gender communications, and how participants reported their experiences. This paper offers methodological considerations that include the influences of local culture, gender, religion, etc. We also discuss how we shaped our fieldwork tools based upon considerations of local cultural and religious contexts. In particular, we highlight the usefulness of probes in traversing cultural boundaries when conducting fieldwork in Saudi Arabia.
Nejad, MZ, Lu, J & Behbood, V 1970, 'Applying dynamic Bayesian tree in property sales price estimation', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, NanJing, JiangSu, China, pp. 1-6.
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© 2017 IEEE. Accurate prediction of Residential Property Sale Price is very important and significant in the operation of the real estate market. Property sellers and buyers/Investors wish to know a fair value for their properties in particular at the time of the sales transaction. The main reason to build an Automated Valuation Model is to be accurate enough to replace human. To select a most suitable model for the property sale price prediction, this paper examined seven Tree-based machine learning models including Dynamic Bayesian Tree (online learning method), Random Forest, Stochastic Gradient Boosting, CART, Bagged CART, Tree Bagged Ensembles and Boosted Tree (batch learning methods) by comparing their RMSE and MAE performances. The performance of these models are tested on 1967 records of unit sales from 19 suburbs of Sydney, Australia. The main purpose of this study is to compare the performance of batch models with the online model. The results demonstrated that Dynamic Bayesian Tree as an online model stands in the middle of batch models based on the root mean square error (RMSE) and mean absolute error (MAE). It shows using online model for estimating the property sale price is reasonable for real world application.
Ng, Y, Kim, J & Li, H 1970, 'Robust dense optical flow with uncertainty for monocular pose-graph SLAM', Australasian Conference on Robotics and Automation, ACRA, pp. 156-164.
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In this paper, we propose how to use dense optical ow field as opposed to sparse feature matches to improve large-displacement monocular visual odometry. The principled framework we developed incorporates uncertainties in the construction of a four-dimensional cost volume for dense ow computation. A novel weighted eight-point algorithm is derived which robustly estimates inter-frame camera motions by using the obtained dense correspondences with uncertainties. This initial motion estimation is subsequently employed to achieve potential loop closing operation, optimised jointly in a robust pose-graph SLAM framework. Performance of the proposed new method has been validated on standard benchmark dataset - KITTI dataset. Experimental results demonstrate that the accuracy of our method is on par with other state-of-the-art methods without relying on commonly used priors such as motion constraint or ground plane segmentation.
Ng, Y, Wei, J, Yu, C & Kim, J 1970, 'Measurement-wise recursive TDoA-based localization using local straight line approximation', 2017 Australian and New Zealand Control Conference (ANZCC), 2017 Australian and New Zealand Control Conference (ANZCC), IEEE, IEEE, pp. 184-189.
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Ngo, NT, Indraratna, B & Biabani, MM 1970, 'Performance Assessment of Geocell-Reinforced Subballast: Modeling and Design Implications', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 374-383.
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This paper presents a study of the load-deformation behavior of geocell-stabilised subballast subjected to cyclic loads using a large-scale track process simulation apparatus and numerical modelling. The tests and numerical simulations were conducted to mimic the actual track conditions. Subjected to a given frequency and cyclic loads the predicted load-deformation behavior of the subballast with and without geocell inclusions match reasonably with those measured in the laboratory, and show that geocell could effectively decrease the lateral and axial deformations of the reinforced subballast. The results also provide an insight to design of rail tracks capturing the roles of geocell in decreasing lateral deformation of subballast. Additionally, the numerical modelling carried out in this study can be applied in the preliminary design of track substructure where a wide range of subballast aggregates and geocell mattresses with varying strengths and stiffness can be considered.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 1970, 'Coupled DEM-FEM analysis for simulating ballasted rail tracks', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 528-539.
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Ballasted tracks play an essential role in its economy through transporting freight and bulk commodities between major cities and ports, and carrying passengers, particularly in urban areas. Ballast usually consists of hard and strong angular particles, which are derived from high strength unweathered rocks. Ballast aggregates undergo gradual and continuing degradation under cyclic train loadings. In this study, the load-deformation responses of ballasted rail tracks subjected to cyclic loading are studied experimentally using a large-scale Track Process Simulation Apparatus (TPSA), and numerically through a coupled discrete-continuum approach, namely, coupled DEM-FEM. Laboratory tests are carried out to examine the deformation and degradation responses of ballast subjected to cyclic train loading under a frequency of f=15 Hz and a lateral confinement of σxx=10 kPa. Test results reveal that significant settlements are observed during the initial load cycles, followed by gradually increased deformation, arriving at a steady value towards the end of testing. A rigorous coupling model based on discrete element method (DEM) and finite element method (FEM) is introduced to predict the load-deformation behaviour of the ballast assembly considering the interaction of discrete ballast grains and continuum subgrade. In this coupled model, the discrete ballast grains are modelled by DEM and the subgrade domain is modelled as a continuum by FEM. Interface elements are introduced to transmit the interacting forces and displacements between adjoining material domains (i.e. discrete and continuum) whereby the DEM transfers contact forces to the FEM, and then the FEM updates the displacements back to the DEM. The coupled model is validated by comparing the predicted ballast settlement responses with those obtained experimentally. Contact force distributions, stress contours and a corresponding number of broken bonds are analysed. This combined DEM-FEM model is also us...
Ngo, NT, Indraratna, B, Rujikiatkamjorn, C & Neville, T 1970, 'DEM modelling of geocells reinforced subballast in rail tracks', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1403-1406.
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This paper presents a study of the load-deformation behaviour of geocell-reinforced subballast under cyclic loads using laboratory tests and discrete element method (DEM). A series of large-scale laboratory tests with and without geocell inclusions are carried out using a track process simulation apparatus to study the beneficial effect of the geocells in decreasing the lateral and vertical deformations of railway subballast. Numerical studies conducted in the DEM can capture the reinforcement effect of geocells, considering micromechanical analysis subjected to a given frequency and load cycles, the predicted load-settlement response of the subballast with and without geocell agrees well with those measured experimentally. This finding indicates that the proposed DEM model is able to capture the deformation behaviour of the subballast reinforced by the geocells. These observations clearly emphasise the beneficial effects of the geocell in decreasing the deformation of subballast from a micromechanical perspective.
Ngo, QT & Dang, DNM 1970, 'A Dynamic Cooperative MAC Protocol for Vehicular Ad-hoc Networks', Springer International Publishing, pp. 780-790.
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Ngoc, TP, Li, D, Fatahi, B & Khabbaz, H 1970, 'A review on the influence of degree of saturation on small strain shear modulus of unsaturated soils', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, International Conference on Soil Mechanics and Geotechnical Engineering, ISSMGE, Seoul, Korea, pp. 1225-1228.
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Small-strain shear modulus (Gmax) is an important parameter in the analysis and design of structures resting on liquefiable soils, particularly under dynamic loads such as earthquakes. In real condition, soil layers near the ground surface consistently undergo variation of degree of saturation (Sr) due to the change of weather or loading-unloading processes that lead to the variation of Gmax. To date, this area has received limited attention and still encounters difficulties in evaluating the influence of Sr on Gmax as well as capturing the effect of hysteresis on water retention behaviour. This study concentrates on the relationship between Sr and Gmax based on available experimental data in literature. The results of the analysis show that Sr plays an important role in the magnitude of Gmax for both cohesionless and cohesive unsaturated soils, while it has a greater influence on the latter. In order to predict Gmax for cohesive soils within the full range of degree of saturation, apart from the influence of Sr on the contribution of matric suction (ym), the influence of Sr on the contribution of plastic fines, salt concentration and van der Waals attraction should be additionally included.
Nguyen, HH, Khabbaz, H, Fatahi, B & Hsi, J 1970, 'Effects of installing controlled modulus columns on previously installed columns', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, the 19th International Conference on Soil Mechanics and Geotechnical Engineering, Seoul, South Korea, pp. 2611-2614.
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Controlled modulus columns (CMC) ground improvement technique is an attractive geotechnical solution for modification of soft soils. This technique uses a displacement auger during column installation, aiming to reduce the construction cost and disposal of excavated materials. However, lateral and vertical soil movement induced by the installation process may pose potential risks to the adjacent previously installed columns. Only a handful of studies have been attempted in quantifying such effects. This paper presents the results of a numerical investigation on the effects of CMC installation sequence on the already installed columns using the three-dimensional finite difference software package FLAC3D. The results indicate that the installation sequence should be taken into account in the design process to minimise any adverse effects of installing new CMCs on the existing columns.
Nguyen, H-P, Do, T-TN & Kim, J 1970, 'Exponential coordinates based rotation stabilization for panoramic videos', 2017 IEEE International Conference on Image Processing (ICIP), 2017 IEEE International Conference on Image Processing (ICIP), IEEE, Beijing, PEOPLES R CHINA, pp. 46-50.
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Nguyen, K-D & Liu, D 1970, 'Robust control of a brachiating robot', 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver Canada, pp. 6555-6560.
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© 2017 IEEE. This paper investigates the robust control of an underactuated brachiating robot. Inspired by the pendulumlike movements in gibbons' arboreal locomotion, the controllers are designed to synchronize the brachiator with a virtual oscillator. Two schemes are proposed: a model-dependent feedback linearization scheme and a sliding-mode scheme that is independent of the system model. The simulation results illustrate that the proposed schemes are robust to the arbitrary initial configurations of the brachiator and the limitation in the motor torque at the elbow joint. Furthermore, both controllers enable the underactuated robot to brachiate along a structural member with an upward slope.
Nguyen, KK, Hoang, DT, Niyato, D, Wang, P, Nguyen, D & Dutkiewicz, E 1970, 'Cyberattack Detection in Mobile Cloud Computing: A Deep Learning Approach', IEEE Wireless Communications and Networking Conference, WCNC, IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, Spain, pp. 1-6.
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With the rapid growth of mobile applications and cloud computing, mobilecloud computing has attracted great interest from both academia and industry.However, mobile cloud applications are facing security issues such as dataintegrity, users' confidentiality, and service availability. A preventiveapproach to such problems is to detect and isolate cyber threats before theycan cause serious impacts to the mobile cloud computing system. In this paper,we propose a novel framework that leverages a deep learning approach to detectcyberattacks in mobile cloud environment. Through experimental results, we showthat our proposed framework not only recognizes diverse cyberattacks, but alsoachieves a high accuracy (up to 97.11%) in detecting the attacks. Furthermore,we present the comparisons with current machine learning-based approaches todemonstrate the effectiveness of our proposed solution.
Nguyen, L, Ulapane, N, Miro, JV, Dissanayake, G & Munoz, F 1970, 'Improved signal interpretation for cast iron thickness assessment based on pulsed eddy current sensing', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 2005-2010.
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© 2017 IEEE. This paper presents a novel signal processing approach for computing thickness of ferromagnetic cast iron material, widely employed in older infrastructure such as water mains or bridges. Measurements are gathered from a Pulsed Eddy Current (PEC) based sensor placed on top of the material, with unknown lift-off, as commonly used during non-destructive testing (NDT). The approach takes advantage of an analytical logarithmic model proposed in the literature for the decaying voltage induced at the PEC sensor pick-up coil. An increasingly more accurate and robust algorithm is proven here by means of an Adaptive Least Square Fitting Line (ALSFL) recursive strategy, suitable to recognize the most linear part of the sensor's logarithmic output voltage for subsequent gradient computation, from which thickness is then derived. Moreover, efficiency is also gained as processing can be carried out on only one decaying voltage signal, unlike averaging over multiple measurements as is usually done in the literature. Importantly, the new signal processing methodology demonstrates highest accuracies at the lower thicknesses, a circumstance most relevant to NDT evaluation. Experiments that verify the proposed method in real-world thickness assessment of cast iron material are presented and compared with current practices, showing promising results.
Nguyen, LD, Tuan, HD, Duong, TQ & Poor, HV 1970, 'Beamforming and power allocation for energy-efficient massive MIMO', 2017 22nd International Conference on Digital Signal Processing (DSP), 2017 22nd International Conference on Digital Signal Processing (DSP), IEEE, London, UK, pp. 1-6.
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© 2017 IEEE. Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.
Nguyen, T, Hoang, D, Nguyen, D & Seneviratne, A 1970, 'Initial trust establishment for personal space IoT systems', 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2017 IEEE Conference on Computer Communications: Workshops (INFOCOM WKSHPS), IEEE, Atlanta, USA, pp. 784-789.
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© 2017 IEEE. Increasingly, trust has played a crucial role in the security of an IoT system from its inception to the end of its lifecycle. A device has to earn some level of trust even before it is authenticated for admission to the system. Furthermore, once the device is admitted to the system, it may behave maliciously over time; hence its behavior must be evaluated constantly in the form of trust to ensure the integrity of the system. Currently, no mechanism exists to establish an initial trust on a device, without prior knowledge, before its admission to an IoT system. Even when trust is applicable, trust evaluation models require direct/indirect observations over time, historical data on past encounters, or third party recommendations. However, this type of past data is not available in the first encounter between the system and the device. The question is how to establish whether a device can be trusted to a level that merits further evaluation for admission into a mobile and dynamic IoT system when it encounters the system for the first time? This paper addresses this challenge by proposing a challenge-response method and a trust assessment model to establish, without prior knowledge, the initial trust that a device places on another in a mobile and dynamic environment called personal space IoT. The initial trust is established before further interaction can take place and under the assumption that only a limited window of time is available for the trust assessment. The paper describes and evaluates the proposed model theoretically and by simulation. It also describes a practical scheme for realizing the proposed solution.
Nguyen, T, Indraratna, B & Rujikiatkamjorn, C 1970, 'Finite element modelling of biodegradable jute drains', In Proceedings of the 15th IACMAG, Wuhan.
Nguyen, TT, Indraratna, B & Rujikiatkamjorn, C 1970, 'A numerical investigation into the transverse permeability of fibrous geomaterials', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 821-824.
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Fibrous geomaterials are widely used in geo-engineering practices for stabilisation, filtration and drainage. Most applications rely on their exceptional hydraulic conductivity despite the current paucity of numerical methods which can simultaneously capture the behaviour of fibre and fluid. In this paper, a coupling numerical approach is proposed where fibres are modelled by Discrete Element Method (DEM) and fluid is simulated by Finite Volume Method (FVM). The Parallel Bond Model incorporated in DEM will reasonably capture the linear stress-strain behaviour of natural fibres such as jute, but unlike previous studies where the fibres are either pre-formed and have an unchanged geometry, the coupling technique provides a good agreement in predicting the hydraulic behaviour of fibrous porous media. The motion of fibres due to fluid flow is also analysed.
Nguyen, V, Pineda, J & Sheng, D 1970, 'Effects on Air Permeability of the Initial Fabric in Compacted Clay', Poromechanics VI, Sixth Biot Conference on Poromechanics, American Society of Civil Engineers, Paris, FRANCE, pp. 1413-1419.
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Nguyen, V-D, Tuan, HD, Duong, TQ, Poor, HV & Shin, O-S 1970, 'Convex Quadratic Programming for Maximizing Sum Throughput in MIMO-NOMA Multicell Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. This paper aims to design linear precoders for signal superposition at the base stations of non-orthogonal multiple access multiple-input multiple-output multi-cellular systems to maximize the overall sum throughput subject to the users' quality-of-service requirements, which are imposed independently on the users' channel conditions. This design problem is formulated as the maximization of a highly nonlinear and nonsmooth function subject to nonconvex constraints, which is very computationally challenging. A path-following algorithm for its solution, which invokes only a simple convex problem of moderate dimension at each iteration, is developed. Generating a sequence of improved points, this algorithm converges at least to a local optimum. Numerical results are then provided to demonstrate its merit.
Nguyen, VV, Li, J, Yu, Y, Dackermann, U & Alamdari, MM 1970, 'Simulation of various damage scenarios using finite element modelling for structural health monitoring systems', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press/Balkema, Australia, pp. 1541-1546.
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Structural Health Monitoring (SHM) is a developing technology for asset management of structures including bridge assets. A crucial benefit of SHM is its ability to monitor the health status of structures using continuous measurements. As a key in SHM, the application of damage detection algorithms to assess the condition of a structure using vibration measurements can be enhanced by providing structural information under various damaged scenarios, which can be obtained from updated numerical models that realistically represent the in-situ structure. However, the dynamic characteristics of a structure are sensitive to uncertainties of various parameters, including material properties and boundary conditions, which require updating in the Finite Element (FE) model to ensure that the model replicates the actual structure. This study focuses on the development of an FE model for the accurate simulation of a jack arch replica structure of the Sydney Harbour Bridge. An experimental jack arch replica is produced to simulate various damage scenarios for laboratory testing. A matching FE model of the jack arch replica is generated and updated using Genetic Algorithm (GA) based on experimental measurements. Damage is simulated in the updated model and the results are validated using the experimental test results. The successful simulation of damage using updated FE models enables the generation of a large number of damage cases that can be trained into an SHM system to improve its damage detection capabilities.
Nie, L, Jiang, D, Yu, S & Song, H 1970, 'Network Traffic Prediction Based on Deep Belief Network in Wireless Mesh Backbone Networks', 2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, pp. 1-5.
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© 2017 IEEE. Wireless mesh network is prevalent for providing a decentralized access for users. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep belief network and a Gaussian model. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then a prediction model is built by learning a deep belief network from the extracted low-pass component. Otherwise, for the rest high-pass component that expresses the gusty and irregular fluctuations of network traffic, a Gaussian model is used to model it. We estimate the parameters of the Gaussian model by the maximum likelihood method. Then we predict the high-pass component by the built model. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.
Ning, X, Yao, L, Wang, X & Benatallah, B 1970, 'Calling for Response: Automatically Distinguishing Situation-Aware Tweets During Crises', ADVANCED DATA MINING AND APPLICATIONS, ADMA 2017, International Conference on Advanced Data Mining and Applications (ADMA), Springer International Publishing, Singapore, SINGAPORE, pp. 195-208.
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Nizami, MSH & Hossain, J 1970, 'Optimal scheduling of electrical appliances and DER units for home energy management system', 2017 Australasian Universities Power Engineering Conference (AUPEC), 2017 Australasian Universities Power Engineering Conference (AUPEC), IEEE, Melbourne, AUSTRALIA, pp. 1-6.
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Ojha, S, Vitale, J & Williams, MA 1970, 'A Domain-Independent Approach of Cognitive Appraisal Augmented by Higher Cognitive Layer of Ethical Reasoning', CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, Annual Meeting of the Cognitive Science Society, Cognitive Science Society, London, pp. 2833-2838.
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According to cognitive appraisal theory, emotion in an individual is the result of how a situation/event is evaluated by the individual. This evaluation has different outcomes among people and it is often suggested to be operationalised by a set of rules or beliefs acquired by the subject throughout development. Unfortunately, this view is particularly detrimental for computational applications of emotion appraisal. In fact, it requires providing a knowledge base that is particularly difficult to establish and manage, especially in systems designed for highly complex scenarios, such as social robots. In addition, according to appraisal theory, an individual might elicit more than one emotion at a time in reaction to an event. Hence, determining which emotional state should be attributed in relationship to a specific event is another critical issue not yet fully addressed by the available literature. In this work, we show that: (i) the cognitive appraisal process can be realised without a complex set of rules; instead, we propose that this process can be operationalised by knowing only the positive or negative perceived effect the event has on the subject, thus facilitating extensibility and integrability of the emotional system; (ii) the final emotional state to attribute in relation to a specific situation is better explained by ethical reasoning mechanisms. These hypotheses are supported by our experimental results. Therefore, this contribution is particularly significant to provide a more simple and generalisable explanation of cognitive appraisal theory and to promote the integration between theories of emotion and ethics studies, currently often neglected by the available literature.
Orlov, O, McGregor, C, Baevsky, R, Chernikova, A, Prysyazhnyuk, A & Rusanov, V 1970, 'Perspective use of the technologies for big data analysis in manned space flights on the international space station', Proceedings of the International Astronautical Congress, IAC, pp. 1951-1960.
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Recent technologies in the area of Big Data analytics which provide fast and effective review of various and diverse files of information arriving from different sources are being developed increasingly. Various new software are being proposed to provide useful results in this area. Such technologies are the important stimulus of modern scientific and technical progress, in particular in the field of development of piloted space flights. In this publication we present the prospects of the use of Big Data analytics technology in a system of medical control of crews of the International space station (ISS). Today there is an active accumulation of experience of piloted space flights on ISS where the international scientific and technical cooperation actively develops. An important step withm this direction is the organisation of a new joint Russian-Canadian space experiment 'Cosmocard 2018' It will build on the Russian experiment 'Cosmocard' which is currently being carried out on the ISS since September, 2014. In this project we have begun work for the modernisation of the software for the onboard computer which will enable the estimation in real-time of a mode of state of health of members of the crew. The Artemis platform, a Big Data analytics platform proposed by McGregor for the analysis of great volumes of physiological and other environmental data, will be used for this purpose. We have begun to reengrneer algorithms for definition of a functional condition of an organism and risk of development of diseases developed previously by the Institute of Biomedical Problems of the Russian Academy of Sciences to run in real-time within the structure of the new software for the onboard computer that is based on Artemis. These new algorithms will be tested, in the beginning, during simulation experiments with long isolation using the same 'Cosmocard' physiological monitoring devices, currently used on the ISS as part of the current 'Cosmocard' experiments. T...
Owen, R 1970, 'Understanding the Need and Application of 5G in a Ubiquitous 4G World', The 85th IEEE Vehicular Technology Conference VTC2017-Spring Sydney Programme, Sydney, Australia.
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With 4G wireless services in the maturity phase, 5G wireless is on the horizon with Phase 1 standardisation end 2017. This talk will explore the different applications for 5G over and above the 4G available today. The 4G applications have evolved quickly to take advantage of broadband connectivity. Using 5G there will be a next generation of applications taking advantage of extremely low latency and even higher broadband connectivity performance. The Pacific region is expected to lead in advanced automation and advanced analytics for “connected” innovation. The presentation will focus on the needs of different applications and the business rational for going beyond 4G wireless into 5G. Finally the presentation will consider the steps to 5G including architecture changes and the air interface changes to support the 2020 commercial launch of 5G.
Padmanabha, AGA, Appaji, MA, Prasad, M, Lu, H & Joshi, S 1970, 'Classification of diabetic retinopathy using textural features in retinal color fundus image', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Nanjing, China, pp. 1-5.
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© 2017 IEEE. Early, diagnosis is essential for diabetic patients to avoid partial or complete blindness. This work presents a new analysis method of texture features for classification of Diabetic Retinopathy (DR). The proposed method masks the blood vessels and optic disk segmented and directly extracts the textural features from the remaining retinal region. The proposed method is much simpler with comparison of the other methods that detect the defective regions first and then extract the required features for classification. The Haralick texture measures calculated are used for classification of DR. The proposed method is evaluated through a classification of DR using both Support Vector Machine (SVM) and Artificial Neural Network (ANN). The results of SVM have a better accuracy (87.5%) over ANN (79%). The performance of the proposed method is presented also in terms of sensitivity and specificity.
Paimin, AN, Alias, M, Prpic, JK & Hadgraft, RG 1970, 'Developing an instrument to measure the cognitive- affective-conative profile of engineering students', 2017 IEEE 9th International Conference on Engineering Education (ICEED), 2017 IEEE 9th International Conference on Engineering Education (ICEED), IEEE, Kanazawa, Japan, pp. 101-105.
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© 2017 IEEE. Learning strategies (cognition), emotion (affection) and conation are suggested as important elements of success for engineering students. Identifying student learning profile may help improve successful rate in engineering program. An instrument that can be used for reliably assessing the cognitive- affective-conative profile of students is needed. This paper report the development and initial testing of the questionnaire (CACQ). Quantitative procedures were used. The set of questionnaire was distributed to 207 final year engineering students after being reviewed by four experts. Each of the constructs reached a good reliability value. Strong and positive correlations were established between learning strategy, emotion, conation and achievement motivation measures. The strength of correlations between the constructs also provides an indicator to the unidimensionality of the constructs. This new questionnaire is a promising measure for assessing the cognitive, affective and conative profile of engineering students.
Pan, P, Feng, J, Chen, L & Yang, Y 1970, 'Online compressed robust PCA', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 1041-1048.
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© 2017 IEEE. In this work, we consider the problem of robust principal component analysis (RPCA) for streaming noisy data that has been highly compressed. This problem is prominent when one deals with high-dimensional and large-scale data and data compression is necessary. To solve this problem, we propose an online compressed RPCA algorithm to efficiently recover the low-rank components of raw data. Though data compression incurs severe information loss, we provide deep analysis on the proposed algorithm and prove that the low-rank component can be asymptotically recovered under mild conditions. Compared with other recent works on compressed RPCA, our algorithm reduces the memory cost significantly by processing data in an online fashion and reduces the communication cost by accepting sequential compressed data as input.
Pang, G, Cao, L, Chen, L & Liu, H 1970, 'Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 2585-2591.
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This paper introduces a novel wrapper-based outlier detection framework (WrapperOD) and its instance (HOUR) for identifying outliers in noisy data (i.e., data with noisy features) with strong couplings between outlying behaviors. Existing subspace or feature selection-based methods are significantly challenged by such data, as their search of feature subset(s) is independent of outlier scoring and thus can be misled by noisy features. In contrast, HOUR takes a wrapper approach to iteratively optimize the feature subset selection and outlier scoring using a top-k outlier ranking evaluation measure as its objective function. HOUR learns homophily couplings between outlying behaviors (i.e., abnormal behaviors are not independent - they bond together) in constructing a noise-resilient outlier scoring function to produce a reliable outlier ranking in each iteration. We show that HOUR (i) retains a 2-approximation outlier ranking to the optimal one; and (ii) significantly outperforms five state-of-the-art competitors on 15 real-world data sets with different noise levels in terms of AUC and/or P@n. The source code of HOUR is available at https://sites.google.com/site/gspangsite/sourcecode.
Pang, G, Xu, H, Cao, L & Zhao, W 1970, 'Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, Singapore, Singapore, pp. 807-816.
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© 2017 Association for Computing Machinery. This paper introduces a novel framework, namely SelectVC and its instance POP, for learning selective value couplings (i.e., interactions between the full value set and a set of outlying values) to identify outliers in high-dimensional categorical data. Existing outlier detection methods work on a full data space or feature subspaces that are identified independently from subsequent outlier scoring. As a result, they are significantly challenged by overwhelming irrelevant features in high-dimensional data due to the noise brought by the irrelevant features and its huge search space. In contrast, SelectVC works on a clean and condensed data space spanned by selective value couplings by jointly optimizing outlying value selection and value outlierness scoring. Its instance POP defines a value outlierness scoring function by modeling a partial outlierness propagation process to capture the selective value couplings. POP further defines a top-k outlying value selection method to ensure its scalability to the huge search space. We show that POP (i) significantly outperforms five state-of-the-art full space or subspace-based outlier detectors and their combinations with three feature selection methods on 12 real-world high-dimensional data sets with different levels of irrelevant features; and (ii) obtains good scalability, stable performance w.r.t. k, and fast convergence rate.
Parnell, J & Hartcher, A 1970, 'Setting noise objectives for outdoor events at the Sydney Opera House', Proceedings of ACOUSTICS 2017 Perth: Sound, Science and Society - 2017 Annual Conference of the Australian Acoustical Society, AAS 2017.
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Unwanted music from outdoor events is considered a form of noise pollution which presents a unique set of challenges for regulators when compared to other environmental noise sources. Unlike noise generated by sources such as transport or industry where lower levels are always desirable, there is a minimum level of music below which patron experience will be unacceptable. The challenge for regulators therefore lies in balancing the need for entertainment against the impacts of outdoor music on the surrounding population. Regulators and venue operators of outdoor music events in urban environments are also often required to comply with receiver based noise limits in noise catchments complicated by high levels of extraneous noise from ferries, trains, traffic, pedestrians, restaurants and the like. With this in mind, this paper describes the approach undertaken to review and contemporise the noise criteria for outdoor events held on the steps and forecourt of the Sydney Opera House by adopting Front of House (i.e. at the source) limits rather than receiver based noise objectives.
Parr, AJ & Jin, X 1970, 'Researching reflection in an engineering internship program', Proceedings of the 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), AAEE, Sydney, Australia, pp. 1185-1192.
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Context: At the University of Technology Sydney, engineering students undergo a 2 phase internship program consisting of a junior and a senior 6 month internship. Students are taught a framework for reflecting on their internship experiences based on an adaption of the 4 stage Kolb cycle process informed by the work of Schon and Jarvis. Previously reported analysis of students' reflective writing has established that such writing can be taught. However, further study is required to determine if the framework used is actually achieving the intended goals of students identifying their learning, widening their understanding of its application, affecting transformation of behaviour and adopting reflection into practice as a lifelong learning skill. Purpose: This paper seeks to answer the question: How can rigorous research be undertaken to test whether this reflective framework is achieving its intended goals and where may teaching processes need to be improved? Approach: The research design in this paper is based on multiple data collection methods. Grades, reflective writing submissions, interviews, questionnaire survey, and observations serve as the major sources of data. Results: Grades can be related to feedback from students and their employers and plots made from which implications about the efficacy of the framework and teaching methods can be drawn. Correlation between students' reflective writing and observation can also reveal if the framework is creating 'reflective-learners'. Other observation may help reveal if reflection is adopted to establish a lifelong learning skill. Conclusions: Whilst it has been established that frameworks for reflection can be taught, this may not necessarily indicate the framework used is actually achieving the intended goals. The research approach proposed in this paper may help to answer the question of how rigorous research can be undertaken to test whether the reflective framework used is achieving its in...
Patnaik, P, Mishra, DK, Mohapatra, A & Mohanty, A 1970, 'Modelling and Analysis of a harmonic filter for a Grid connected DFIG under fault condition', 2017 RECENT DEVELOPMENTS IN CONTROL, AUTOMATION AND POWER ENGINEERING (RDCAPE), Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE), IEEE, Amity Sch Engn & Technol, Noida, INDIA, pp. 521-526.
Peng, J, Kessissoglou, N & Parnell, J 1970, 'Evaluation of calculation of road traffic noise in Australia', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet.
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Noise prediction for the assessment of operational road traffic noise impact in Australia has been made largely using United Kingdom's Calculation of Road Traffic Noise (CoRTN), initially published in 1975, with a number of crude adjustments to suit Australian conditions. Since the majority of the noise measurements forming the data used to develop CoRTN was taken prior to 1973 and the Australian adjustments were derived in 1983, the noise prediction accuracy has reduced over the years as considerable changes have taken place not only in the design of vehicles and motor vehicle noise regulation, but also in the variety of vehicles and the increased presence of larger trucks on the Australian road network. In this present study, the prediction performance of CoRTN under Australian conditions was examined using statistical and sensitivity analyses. The statistical analysis demonstrates that the Australian adjustments are no longer suitable and identifies the presence of heavy vehicles as being the primary influence on the performance of CoRTN with temperature having a secondary, but notable effect. A subsequent sensitivity analysis is presented and shows that the ability for CoRTN to predict daytime and night-Time noise levels accurately is highly sensitive to the mix of heavy vehicles, and temperature to a lesser extent. Some modifications to current modelling practice are introduced, although results demonstrate that current practice is over simplistic.
Peng, Y, Yu, G, Ni, W, Lv, Z, Jiang, Y & Chen, J 1970, 'Design and Development of Intelligent Operation and Maintenance Training System for Substation Based on Augmented Reality', 2017 CHINESE AUTOMATION CONGRESS (CAC), Chinese Automation Congress (CAC), IEEE, PEOPLES R CHINA, Jinan, pp. 4765-4769.
Perera, A, Arukgoda, J, Ranasinghe, R & Dissanayake, G 1970, 'Localization system for carers to track elderly people in visits to a crowded shopping mall', 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), IEEE, Sapporo, Japan, pp. 1-8.
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© 2017 IEEE. This work presents a real-time localization system developed for professional care givers to track residents of an aged care facility during their visits to a crowded, multi-story shopping mall. The proposed system consists of a Wi-Fi based self-localization platform integrated into a wheeled walking frame and an application installed in a hand-held tablet device for displaying the locations of walker users. The density of people in the shopping mall changes significantly during the day thus the expected Wi-Fi signal strength at a given location is subject to large variations. However, Identifying the location to be within a given area is adequate and the average speed of motion is less than 0.5 m/sec. In this paper, an algorithm that addresses these unique requirements is presented. We exploit the signal strength characteristics of existing Wi-Fi network and prior knowledge of the building floor plans for developing our core algorithm. The environments is divided in to cells that are either enclosed spaces or divisions of larger open regions. The probability density function of the Wi-Fi signal strength of each cell is estimated using Kernel Density Estimation (KDE) and is used in a probabilistic framework to estimate the user location. Motion model of the users as well as the detection of floor transition events are used to enhance the performance of the location estimator. The algorithm was implemented using an Odroid-C1 computer and a tablet with Android operating system. Results obtained during field trials at Roselands Shopping Mall in Sydney are presented.
Perera, A, Ranasinghe, R & Dissanayake, G 1970, 'A neural network based place recognition technique for a crowded indoor environment', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1937-1942.
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© 2017 IEEE. Place recognition in a crowded and cluttered environment is a challenging task due to its dynamic characteristics such as moving obstacles, varying lighting conditions and occlusions. This work presents a robust place recognition technique that could be applied into a similar environment, by combining well known Bag of Words technique with a feedforward neural network. The feedforward neural network we use have three layers with a single hidden layer and it relies on rectifier and softmax activation functions. We employ cross entropy function to model the cost of our neural network and utilize Adam algorithm for minimizing this cost at the training phase. The output layer with softmax activation in the neural network, produces a vector of probabilities which represent the likelihood of test image being captured from a given region. These values are further improved by incorporating a transition matrix which is based on the building layout. We have evaluated our neural network based place recognition technique with data collected from a crowded indoor shopping mall and promising results have been observed by this approach. We also have analyzed the behavior of neural network for changes in hyper-parameters and presented the results.
Perry, R, Bandara, M, Kutay, C & Rabhi, F 1970, 'Visualising complex event hierarchies using relevant domain ontologies', Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems, DEBS '17: The 11th ACM International Conference on Distributed and Event-based Systems, ACM, Barcelona Spain, pp. 351-354.
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© 2017 Copyright held by the owner/author(s). With the growth of data available for analysis, people in many sectors are looking for tools to assist them in collating and visualising patterns in that data. We have developed an event based visualisation system which provides an interactive interface for experts to filter and analyse data. We show that by thinking in terms of events, event hierarchies, and domain ontologies, that we can provide unique results that display patterns within the data being investigated. The proposed system uses a combination of Complex Event Processing (CEP) concepts and domain knowledge via RDF based ontologies. In this case we combine an event model and domain model based on the Financial Industry Business Ontology (FIBO) and conduct experiments on financial data. Our experiments show that, by thinking in terms of event hierarchies, and pre-existing domain ontologies, that certain new relationships between events are more easily discovered.
Pham, L, Irfansyah, AN, Hamilton, TJ & Lehmann, T 1970, 'The effect of source resistance on the linearity of Nauta structure OTA', 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), IEEE, Tufts Univ, Medford Somerville Campus, Boston, MA, pp. 1208-1211.
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Pham, NH 1970, 'Direct storage hybrid (DSH) inverter: A new concept of intelligent hybrid inverter', 2017 IEEE Energy Conversion Congress and Exposition (ECCE), 2017 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Cincinnati, OH, USA, pp. 5529-5536.
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This paper proposes a new configuration of a single-phase hybrid inverter with an integrated battery energy storage, which is suitable for residential households to maximize local consumption of solar energy and thus reduce dependency on grid support. The hybrid inverter is called Direct Storage Hybrid (DSH) Inverter. A transformer-less topology such as HERIC, operating at low frequency to generate a three-level rectangular output voltage, is adopted to connect a photovoltaic (PV) panel to the load and/or the grid. A series active filter is employed to compensate the high harmonic components from the rectangular voltage and provide a sinusoidal voltage. A bidirectional dc/dc converter connects the battery to the PV panel to control the battery state of charge (SoC) and optimize the PV panel operation during both off-grid and grid-connected modes. The DSH inverter can let the battery bypass the dc/dc converter and connect directly to the inverter stage, leading to a significant improvement in throughput efficiency in battery utilization. This paper discusses the operation and loss analysis of the DSH inverter in off-grid mode.
Pham, NH 1970, 'New design concept of a bidirectional wireless power transfer system using dual active bridge topology', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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This paper proposes a new design concept of small air-gap bidirectional Wireless Power Transfer (WPT) system using Dual Active Bridge (DAB) topology. The wireless charging coils are considered as a weakly coupled transformer having relatively high leakage inductance, and thus the new design can obtain soft switching without implementing resonant capacitor or external inductor. This design has a simple construction and can enable bidirectional inductive power transfer with superior performance compared to the traditional large air-gap system. The new system can transfer high power via a compact coil structure thanks to smaller air gap. Moreover, soft-switching operation enables significant improvement in efficiency. The proposed design enables electrical vehicles and smart wheels to use batteries for supporting grid silently and seamlessly. This paper considers the application of smart wheel charger and presents an analytical design of the system using finite element analysis and circuit simulation. As a result, the design can achieve 97% efficiency at 3-kW, 85-kHz operation.
Pham, PV, Mashiri, F & Zhu, X 1970, 'Wheel and rail damage and detection – a review', 9th Australasian Congress on Applied Mechanics, ACAM 2017.
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There are many factors that affect rail/wheel life due to wheel-rail interface causing wheel-rail defects such as rail corrugation, squats, rolling contact fatigue, scaled wheel, crack initiation and growth. This paper is first to review the effect of the wear and fatigue mechanisms in the wheel and rail contact. Various detection methods for rail and wheel defects have been developed. Capturing the damage features is a vital part of any condition monitoring approaches for the inspection of railway wheel defects. There are different types of sensing techniques to be adopted and data can be collected under in-service conditions or during the maintenance in the workshop. This paper summarizes sensing techniques used for detecting wheel and rail damage. The advantages and disadvantages of each method are also presented. Based on these methods, an effective way to detect wheel and rail damage is proposed.
Pham, TT, Nguyen, DN, Dutkiewicz, E, McEwan, AL & Leong, PHW 1970, 'An anomaly detection technique in wearable wireless monitoring systems for studies of gait freezing in Parkinson's disease', 2017 International Conference on Information Networking (ICOIN), 2017 International Conference on Information Networking (ICOIN), IEEE, Da Nang, Vietnam, pp. 41-45.
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© 2017 IEEE. Wearable monitoring systems have been in need for studies of gaits especially freezing of gait detection in patients with Parkinson's disease. The causality of gait freezing is still not fully understood. The histogram of gait freezing is the key assessment of the disease, thus monitoring them in patients' daily life is much appreciated. A real-Time signal processing platform for wearable sensors can help record freezing time instances. However, current monitor systems are calibrated with offline training (patient-dependent) that is cumbersome and time-consuming. In this work, by using acceleration data and spectral analysis, we propose an online/real-Time detection technique. Periods of low acceleration and low spectral coherence are identified and patient-independent parameters are then extracted. Using this set of new features, we validated our method by comparing it with clinicians' labels. The proposed approach achieved an overall mean (±SD) sensitivity (specificity) of 87 ± 0.3% (94±0.3%). To our best knowledge, this is the best performance for automated subject-independent approaches.
Pham, TT, Nguyen, DN, Dutkiewicz, E, McEwan, AL & Leong, PHW 1970, 'Wearable healthcare systems: A single channel accelerometer based anomaly detector for studies of gait freezing in Parkinson's disease', 2017 IEEE International Conference on Communications (ICC), ICC 2017 - 2017 IEEE International Conference on Communications, IEEE, Paris, France, pp. 1-5.
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© 2017 IEEE. The causality of gait freezing in patients with advanced Parkinson's disease is still not fully understood. Clinicians are interested in investigating the freezing of gait (FoG) histogram of patients in their daily life. To that end, one needs a real-time signal processing platform that can help record freezing information (e.g., timing and the duration of every gait freezing occurrences). Wearable wireless sensors have been proposed to monitor FoG epochs. Existing automated methods using accelerometers have been introduced with high accuracy performance only for subject-dependent settings (e.g., an individual offline training process). This is a troublesome for large scale out-of-lab deployment and time-consuming. In this work, we used spectral coherence analysis for accelerometer data to apply an anomaly detection approach. Conventional features such as energy and freezing index are introduced to help refine normal epochs while the anomaly scores from spectral coherence measures define FoG epochs. Using this new set of features, our new FoG detector for subject-independent settings achieves the mean ±SD sensitivity (specificity) of 89.2±0.3% (95.6 ± 0.3%). To our best knowledge, this is the best performance for automated subject-independent approaches in literature of freezing of gait detection.
Phung, MD, De La Villefromoy, M & Ha, Q 1970, 'Management of solar energy in microgrids using IoT-based dependable control', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Solar energy generation requires efficient monitoring and management in moving towards technologies for net-zero energy buildings. This paper presents a dependable control system based on the Internet of Things (IoT) to control and manage the energy flow of renewable energy collected by solar panels within a microgrid. Data for optimal control include not only measurements from local sensors but also meteorological information retrieved in real-time from online sources. For system fault tolerance across the whole distributed control system featuring multiple controllers, dependable controllers are developed to control and optimise the tracking performance of photovoltaic arrays to maximally capture solar radiation and maintain system resilience and reliability in real time despite failures of one or more redundant controllers due to a problem with communication, hardware or cybersecurity. Experimental results have been obtained to evaluate the validity of the proposed approach.
Phung, MD, Dinh, TH, Hoang, VT & Ha, Q 1970, 'Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles', Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC), 34th International Symposium on Automation and Robotics in Construction, Tribun EU, s.r.o., Brno, Taipei, Taiwan, pp. 823-829.
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This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.
Phung, VD, Hawryszkiewycz, I & Ha, BM 1970, 'The influence of knowledge sharing behavior and transactive memory systems on innovative work behavior: A conceptual model', 2017 9th International Conference on Knowledge and Systems Engineering (KSE), 2017 9th International Conference on Knowledge and Systems Engineering (KSE), IEEE, Hue, Vietnam, pp. 227-232.
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Although knowledge sharing (KS), the key to creativity and innovation, are increasingly common in organisations, research on the relationship between knowledge sharing behaviour (KSB) and transactive memory system (TMS) and its effect on innovative work behaviour (IWB) is relatively rare. Prior studies have reported that KS influences IWB in organisations. However, the effect of KSB on IWB and the join influence between TMS on KS and IWB have not been adequately investigated in past research. Therefore, the goal of this research-in-progress is to propose a conceptual model comprising three construct domains including KSB, TMS quality and IWB to examine the impact of the KS practices of employees on their IWB in organisations. We advance to conduct a survey to examine our discussion of the proposed conceptual model. It is expected that this research will contribute to the deeper understanding of the effects of KSB and TMS on IBW within organisation. Implications and future research are also proposed.
Phung, VD, Hawryszkiewycz, I, Chandran, D & Ha, BM 1970, 'Knowledge sharing and innovative work behaviour: A case study from vietnam', Proceedings of the 28th Australasian Conference on Information Systems, ACIS 2017, Australasian Conference on Information Systems, University of Tasmania, Tasmania, Australia.
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This study aims to examine the influence of environmental and personal factors on knowledge-sharing behaviour (KSB) and whether more leads to superior innovative work behaviour (IWB) at tertiary level in Vietnam. Our case is Hanoi University (HANU), one of the Leading Public Universities in Vietnam. This study applies the structural equation modelling (SEM) to investigate the research model based on social cognitive theory. Based on a survey of 320 academic staff at HANU, the results show that two environmental factors (subjective norm, trust) and three personal factors (knowledge self-efficacy, enjoyment in helping others, and reciprocity) significantly influence KSB. The results also indicate that employee willingness to share knowledge enable the organisation to promote IWB. It is hoped that academic staff and university leaders from other countries may find the case study useful for deeper understanding of the effects of social influences, personal perceptions and KSB on IBW in the future.
Pickrell, M, van den Hoven, E & Bongers, B 1970, 'Exploring in-hospital rehabilitation exercises for stroke patients', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, Brisbane, Australia, pp. 228-237.
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© 2017 Association for Computing Machinery. All rights reserved. Rehabilitation 1 exercises following stroke are by necessity repetitive and consequently can be tedious for patients. Hospitals are set up with equipment such as clothes pegs, wooden blocks and mechanical hand counters, which patients use to re-learn how to manipulate objects. The aim of this study is to understand the context of stroke patients rehabilitation as well as which types of feedback are most appropriate for patients when performing their rehabilitation exercises. Over 60 hours were spent observing stroke patients undergoing rehabilitation. Fourteen stroke patients who had attended a balance class were interviewed about their experiences and the feedback they received. From this fieldwork, a set of design guidelines has been developed to guide researchers and designers developing computer-based equipment for stroke patient rehabilitation.
Pileggi, S & Hunter, J 1970, 'An Ontology-Based, Linked Open Data Framework to support the Publishing, Re-use and Dynamic Calculation of Urban Planning Indicators', 15th International Conference on Computers in Urban Planning and Urban Management, Adelaide, Australia.
Poon, J, Cui, Y, Miro, JV, Matsubara, T & Sugimoto, K 1970, 'Local driving assistance from demonstration for mobility aids', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, pp. 5935-5941.
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© 2017 IEEE. Active assistive mobility systems are largely limited to a-priori mapped environments, whereas their reactive assistive counterparts are in general location independent and focus on the provision of collision avoidance in the immediate space surrounding the platform. This paper presents a framework capable of providing active short-term navigation, combining the intelligence of active assistance with the freedom of location independence. Demonstration data from an able expert while driving the mobility aid in a standard indoor setting is used off-line to learn reference behavioral models of navigation given perceptual information from the platform surroundings and the input controls exerted by the user while navigating. These serve as the foundation for on-line probabilistic short-term destination inference using the instantaneously available data from the user and on-board sensors. This is coupled with a real-time stochastic optimal path generation able to exploit the same short term demonstration paths from the expert with the belief they capture both the driver's awareness of the platform's physical geometry and appropriate behaviors for their surroundings. Experimental results with users of varying proficiency in a setting unvisited in training data show promise in using the framework in assisting users experiencing difficulty in safe power mobility aid use.
Popovic, M, Vidal-Calleja, T, Hitz, G, Sa, I, Siegwart, R & Nieto, J 1970, 'Multiresolution mapping and informative path planning for UAV-based terrain monitoring', 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver, Canada, pp. 1382-1388.
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© 2017 IEEE. Unmanned aerial vehicles (UAVs) can offer timely and cost-effective delivery of high-quality sensing data. However, deciding when and where to take measurements in complex environments remains an open challenge. To address this issue, we introduce a new multiresolution mapping approach for informative path planning in terrain monitoring using UAVs. Our strategy exploits the spatial correlation encoded in a Gaussian Process model as a prior for Bayesian data fusion with probabilistic sensors. This allows us to incorporate altitude-dependent sensor models for aerial imaging and perform constant-time measurement updates. The resulting maps are used to plan information-rich trajectories in continuous 3-D space through a combination of grid search and evolutionary optimization. We evaluate our framework on the application of agricultural biomass monitoring. Extensive simulations show that our planner performs better than existing methods, with mean error reductions of up to 45% compared to traditional 'lawnmower' coverage. We demonstrate proof of concept using a multirotor to map color in different environments.
Pourzeynali, S, Zhu, X, Samali, B & Rashidi, M 1970, 'Dynamic analysis of Vehicle-bridge systems based on Explicit Form of Newmark-β Method', SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings, pp. 1233-1242.
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In the present study, a new method is proposed to analyse dynamic responses of the bridge subjected to a moving vehicle. Analysing the vehicle-bridge interaction system is useful for moving load identification and bridge structural damage detection. In this study, the algorithm based on explicit form of Newmark-β is proposed for dynamic analysis of the vehicle-bridge system. A three-span continuous bridge is used as a numerical example to investigate the efficiency of the proposed method and the results are compared with the existing results by the conventional state-space method. From the results, the proposed method is reliable and efficient for the vehicle-bridge interaction analysis.
Pradhan, S 1970, 'Analysis of Impact Sourcing by Infusing Social Innovation in Outsourcing for Nepal', Information and Communication Technologies for Development, International Conference on Social Implications of Computers in Developing Countries, Springer International Publishing, Yogyakarta, Indonesia,, pp. 829-834.
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© IFIP International Federation for Information Processing 2017. Outsourcing is a popular term in the business world for last several decades. Information Technology Outsourcing (ITO) and Business Process Outsourcing (BPO) have been dominating the outsourcing jobs to developing countries. Recently, a new shift of outsourcing to impact sourcing have emerged through which digitally-enabled jobs are given to marginalized individuals so that their conditions would be improved. However, only limited studies have been done to explore the recruiting process of marginalized communities and the impacts to the workers and their families. Cloud Factory, as one of the pioneer impact sourcing service providers in Nepal, is targeted to conduct further research. Initial investigation has shown that flexibility to work from any place such as their own home or internet cafes on flexible hours have attracted college students to this impact sourcing model in Nepal. In the future, further analysis on improvement on employees’ lives by impact sourcing will be conducted.
Pradhan, S, Gurca, A & Hawryszkiewycz, I 1970, 'Value co-creation and service ecosystem for developing countries to promote development and inclusive growth: Home-based workers’ case', International Conference on Serviceology, Vienna, Austria.
Pratama, M, Angelov, PP, Lu, J, Lughofer, E, Seera, M & Lim, CP 1970, 'A randomized neural network for data streams', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 3423-3430.
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© 2017 IEEE. Randomized neural network (RNN) is a highly feasible solution in the era of big data because it offers a simple and fast working principle in processing dynamic and evolving data streams. This paper proposes a novel RNN, namely recurrent type-2 random vector functional link network (RT2McRVFLN), which provides a highly scalable solution for data streams in a strictly online and integrated framework. It is built upon the psychologically inspired concept of metacognitive learning, which covers three basic components of human learning: what-to-learn, how-to-learn, and when-to-learn. The what-to-learn selects important samples on the fly with the use of online active learning scenario, which renders our algorithm an online semi-supervised algorithm. The how-to-learn process combines an open structure of evolving concept and a randomized learning algorithm of random vector functional link network (RVFLN). The efficacy of the RT2McRVFLN has been numerically validated through two real-world case studies and comparisons with its counterparts, which arrive at a conclusive finding that our algorithm delivers a tradeoff between accuracy and simplicity.
Prysyazhnyuk, A, Baevsky, R, Berseneva, A, Chernikova, A, Luchitskaya, E, Rusanov, V & McGregor, C 1970, 'Big data analytics for enhanced clinical decision support systems during spaceflight', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 296-299.
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© 2017 IEEE. Recent advancements in the field of space medicine and technology have extended the boundaries of space travel, presenting humankind with the ability to explore undiscovered habitats. As humans embark on long range missions, adaptation mechanisms will be put to the test, challenging provision of medical care in space. To date, a vast amount of knowledge has been accumulated through a series of experiments, both in terrestrial simulation environments and space missions on the ISS. As a result, functional health state algorithm has been developed and validated by IBMP, to identify transitional states between health and disease. Significant limitations on provision of medical care in space are imposed due to retrospective data processing and analysis techniques. Some of these limitations can be addressed by the proposed instantiation of the functional state algorithm within the Online Analytics component of the Artemis platform, to enhance clinical decision support systems during spaceflight.
Qi, J & Dah-Chuan Lu, D 1970, 'A flyback converter based partial power processing structure for BESS with voltage/current regulation and battery balancing functionalities', 2017 IEEE International Telecommunications Energy Conference (INTELEC), 2017 IEEE International Telecommunications Energy Conference (INTELEC), IEEE, Broadbeach, QLD, Australia, pp. 381-386.
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This paper presents a flyback converter based partial power processing structure for battery energy storage system (BESS). It combines both of the battery balancing functionality and power stage regulation functionality into one system. The proposed BESS only have one control variable which is the common duty cycle for all the flyback converters. It is used for the voltage or current regulation. There is no active control for the battery balancing because the current sharing of individual battery is directly proportional to the battery terminal voltage in discharging mode and inversely proportional in charging mode. The unbalanced battery terminal voltages will gradually converge while system running. Beyond these, only a small portion of the total discharging/charging power is processed by the converters. The overall system efficiency can be significantly improved compared to traditional BESSs. Experimental results of a prototype with two batteries verified that the proposed BESS provides satisfied performance.
Qi, Y, Indraratna, B, Heitor, A & Vinod, J 1970, 'Developing an Energy Absorbing Layer Using Waste Materials', International Conference of Ground Improvement (ICGI2017), Hangzhou, China.
Qiao, M, Yu, J, Bian, W, Li, Q & Tao, D 1970, 'Improving Stochastic Block Models by Incorporating Power-Law Degree Characteristic', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 2620-2626.
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Stochastic block models (SBMs) provide a statistical way modeling network data, especially in representing clusters or community structures. However, most block models do not consider complex characteristics of networks such as scale-free feature, making them incapable of handling degree variation of vertices, which is ubiquitous in real networks. To address this issue, we introduce degree decay variables into SBM, termed power-law degree SBM (PLD-SBM), to model the varying probability of connections between node pairs. The scale-free feature is approximated by a power-law degree characteristic. Such a property allows PLD-SBM to correct the distortion of degree distribution in SBM, and thus improves the performance of cluster prediction. Experiments on both simulated networks and two real-world networks including the Adolescent Health Data and the political blogs network demonstrate the validity of the motivation of PLD-SBM, and its practical superiority.
Qin, M, Jin, D, He, D, Gabrys, B & Musial, K 1970, 'Adaptive Community Detection Incorporating Topology and Content in Social Networks', Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, ASONAM '17: Advances in Social Networks Analysis and Mining 2017, ACM, pp. 675-682.
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In social network analysis, community detection is a basic step to understand the structure, function and semantics of networks. Some conventional community detection methods may have limited performance because they merely focus on topological structure of networks. In addition to topology, content information is another significant aspect of social networks. Some state-of-the-art methods started to combine these two aspects of information, but they often assume that topology and content share the same characteristics. However, for some examples of social networks, content may mismatch with topological structure. In order to better cope with such situations, we introduce a novel community detection method under the framework of nonnegative matrix factorization (NMF). Our proposed method integrates topology and content of networks, and introduces a novel adaptive parameter for controlling the contribution of content with respect to the identified mismatch degree between the topological and content information. The case study using real social networks show that our new method can simultaneously obtain community partition and the corresponding semantic descriptions. Experiments on both artificial networks and real social networks further indicate that our method outperforms some state-of-the-art methods while exhibiting more robust behaviour when the mismatch topological and content information is observed.
Qin, P-Y, Chen, S-L & Guo, YJ 1970, 'A compound reconfigurable microstrip antenna with agile polarizations and steerable beams', 2017 International Symposium on Antennas and Propagation (ISAP), 2017 International Symposium on Antennas and Propagation (ISAP), IEEE, Phuket, Thailand, pp. 1-2.
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© 2017 IEEE. Achieving both polarization switching and beam steering independently, in a compact antenna structure, is a major challenge for compound reconfigurable antennas. In this paper, a new cavity-backed proximity-coupled reconfigurable microstrip antenna provides an efficient solution. Three different linear polarizations (0°, 45°, 90°) can be obtained by switching PIN diodes on a proximity-coupled feed network. For each polarization state, the main beam can be steered in three directions by using a reconfigurable parasitic-element network. The antenna has nine different working states in total. For all states, the measured input reflection coefficients are below -10 dB, with the measured realized gains ranging from 7.2-8 dBi.
Qin, P-Y, Guo, YJ & Ji, L-Y 1970, 'Reconfigurable partially reflective surface antennas', 2017 Sixth Asia-Pacific Conference on Antennas and Propagation (APCAP), 2017 Sixth Asia-Pacific Conference on Antennas and Propagation (APCAP), IEEE, Xi'an, China, pp. 1-3.
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© 2017 IEEE. In this paper, the research of reconfigurable partially reflective surface (PRS) antennas at University of Technology Sydney (UTS) is introduced. Two reconfigurable PRS antennas are described that can achieve beam scanning and wideband polarization switch, respectively.
Qu, Y, Xu, J & Yu, S 1970, 'Privacy preserving in big data sets through multiple shuffle', Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2017: Australasian Computer Science Week 2017, ACM, pp. 1-8.
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© 2017 ACM. Big data privacy-preserving has attracted increasing attention of researchers in recent years. But existing models are so complicated and time-consuming that they are not easy to implement. In this paper, we propose a more feasible and efficient model for big data sets privacy-preserving using shuffling multiple attributes(M-Shuffle) to achieve a tradeoff between data utility and privacy. Our strategy is firstly categorize all the records into some groups using K-means algorithm according to the sensitive attributes. Then we choose the columns to be shuffled using entropy. At last we intro- duce the random shuffle algorithm to our model to break the correlation among the columns of big data sets. Experiments on real-world datasets show that our framework achieves excellent data utility and efficiency while satisfying privacy-preserving.
Qu, Y, Yu, S, Gao, L, Peng, S, Xiang, Y & Xiao, L 1970, 'FuzzyDP: Fuzzy-based big data publishing against inquiry attacks', 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2017 IEEE Conference on Computer Communications: Workshops (INFOCOM WKSHPS), IEEE, Atlanta, GA, pp. 7-12.
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Qureshi, JA, Lie, TT, Gunawardane, K, Kularatna, N & Qureshi, WA 1970, 'AC source vs DC source: Charging efficiency in battery storage systems for residential houses', 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, pp. 1-6.
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Qureshi, JA, Lie, TT, Gunawardane, K, Kularatna, N & Qureshi, WA 1970, 'AC Source vs DC Source: Charging Efficiency in Battery Storage Systems for Residential Houses', 2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 7th IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, NEW ZEALAND, Univ Auckland, Auckland, pp. 364-369.
Rafiei, A, Abolhasan, M, Franklin, DR, Safaei, F, Smith, S & Ni, W 1970, 'Cooperative recovery of coverage holes in WSNs via disjoint spanning trees.', ICSPCS, International Conference on Signal Processing and Communication Systems, IEEE, Gold Coast, QLD, Australia, pp. 1-10.
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© 2017 IEEE. Large scale coverage holes (CHs) resulting from correlated node failures, can significantly degrade quality of service and also jeopardise the integrity of WSNs. In the absence of centralised control, the distributed relocation of deployed nodes becomes a promising solution especially in harsh and hostile environments. In this paper, a distributed method is proposed that enables a network to partially or entirely repair itself through a collection of distributed movements of disjoint spanned trees (DS-Trees) towards the CHs. DS-Trees are spanned based on the nodes distances from the CHs, which are autonomously perceived by the nodes and their one-hop neighbours. DS-Trees around the CHs are spanned in a downstream style outwards from the holes, as nodes select their parents based on the minimum distance to the CH from their neighbours; nodes then decide whether or not to follow the movements of their DS-Trees parents. To examine the efficiency of the proposed model, its performance is compared with two Voronoi-based and one force-based node relocation algorithms. Results show that the proposed DS-Tree model either outperforms or matches the alternative approaches across a wide range of scenarios.
Rafiei, A, Abolhasan, M, Franklin, DR, Safaei, F, Smith, S & Ni, W 1970, 'Effect of the number of participating nodes on recovery of WSN coverage holes.', ITNAC, International Telecommunication Networks and Applications Conference, IEEE Computer Society, Melbourne, VIC, Australia, pp. 1-8.
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© 2017 IEEE. Coverage holes (CHs) due to the correlated node failures, if not appropriately addressed in a timely manner, not only disrupt network's operation but also can compromise its integrity. In the absence of centralised control, distributed node relocation can be an effective solution to recover CHs. Relocation algorithms that mainly applied to all nodes to address networks' coverage and unbalanced deployments problems, are not efficient as participating nodes beyond a certain distance and depth from the CHs do not significantly contribute to recovery of CHs. Here, the effects of the number of participating nodes and movement iterations on recovery of CHs are examined in two Voronoi-based and one force-based node relocation algorithms.
Rahman, MA, Islam, MR, Guo, Y, Zhu, J & Lei, G 1970, 'Modified carrier-based over-modulation technique for improved switching performance of multilevel converters', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. A modified over-modulation (OVM) scheme with phase disposed carriers to improve switching performance of cascaded H-bridge multilevel converter is depicted in this article. With the regular OVM techniques, pulse dropping region has higher conduction loss, greater signal distortion and voltage gain. In the proposed OVM method, the switching and conduction loss scenario is improved with lower harmonic distortion. Also, the voltage gain can be increased up to limited range. Four types of reference signals, such as pure sinusoidal signal, sinusoidal 60° bus clamped signal, third harmonic injected signal and third harmonic injected 60° bus clamped signal are used to investigate the overall performance with the proposed OVM method. The OVM technique is applied to a 3.0 kV, 120 kW, 5-level cascaded H-bridge converter and simulated in MATLAB/Simulink environment. The results demonstrate reduced output harmonic distortion, increased voltage gain, lower switching and conduction loss as well as improved efficiency on the whole.
Rahman, ML, Zhang, JA, Huang, X & Quo, YJ 1970, 'Analog antenna array based sensing in perceptive mobile networks', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Veorna, Italy, pp. 199-202.
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© 2017 IEEE. In this paper, we consider an alternative low-cost and flexible solution of using an analog antenna array for radio sensing at the base station receiver in the recently proposed perceptive mobile networks. We provide receiver beamforming design, and advanced compressive sensing (CS) signal processing techniques for sensing parameter estimation in a multiuser-MIMO (MU-MIMO) communications system. Simulation results are provided and validate the effectiveness of the proposed solution and sensing algorithms.
Rajabi, A, Li, L, Zhang, J & Zhu, J 1970, 'Aggregation of small loads for demand response programs — Implementation and challenges: A review', 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE, Milan, Italy, pp. 1-6.
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© 2017 IEEE. The concepts of demand response (DR) and demand side management have been in practice by power utilities for many decades. Due to fundamental changes in the electricity structure in recent years, the provision of DR from small loads like residential buildings or electric vehicles has become possible. However, there are still many challenges to the real implementation of DR programs for such customers. Based on a detailed survey of the literature, this paper tries to illustrate the role of aggregators in the implementation and expansion of DR in future smart grids. Then different technical and managerial challenges of DR aggregation for residential customers will be discussed thoroughly.
Rajabi, A, Li, L, Zhang, J, Zhu, J, Ghavidel, S & Ghadi, MJ 1970, 'A review on clustering of residential electricity customers and its applications', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Clustering is a well-recognized data mining technique which enables the determination of underlying patterns in datasets. In electric power systems, it has been traditionally utilized for different purposes like defining customer load profiles, tariff designs and improving load forecasting. Some surveys summarized different clustering techniques which were traditionally used for customer segmentation and load profiling. The recent changes in power system structure and introduction of new technologies necessitate the new investigation of applications and benefits of clustering methods for power systems. In this regard, this paper aims at reviewing the new research for clustering techniques for residential customers.
Ramezani, F & Naderpour, M 1970, 'A fuzzy virtual machine workload prediction method for cloud environments', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Due to the dynamic nature of cloud environments, the workload of virtual machines (VMs) fluctuates leading to imbalanced loads and utilization of virtual and physical cloud resources. It is, therefore, essential that cloud providers accurately forecast VM performance and resource utilization so they can appropriately manage their assets to deliver better quality cloud services on demand. Current workload and resource prediction methods forecast the workload or CPU utilization pattern of the given web-based applications based on their historical data. This gives cloud providers an indication of the required number of resources (VMs or CPUs) for these applications to optimize resource allocation for software as a service (SaaS) or platform as a service (PaaS), reducing their service costs. However, historical data cannot be used as the only data source for VM workload predictions as it may not be available in every situation. Nor can historical data provide information about sudden and unexpected peaks in user demand. To solve these issues, we have developed a fuzzy workload prediction method that monitors both historical and current VM CPU utilization and workload to predict VMs that are likely to be performing poorly. This model can also predict the utilization of physical machine (PM) resources for virtual resource discovery.
Rana, MM, Li, L & Su, SW 1970, 'Distributed State Estimation for Interconnected Synchronous Generators', IFAC-PapersOnLine, IFAC World Congress, Elsevier BV, Toulouse, France, pp. 5418-5423.
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© 2017 In contrast to the traditional centralised power system state estimation methods, this paper investigates the optimal filtering problem for distributed dynamic systems. Specifically, the interconnected synchronous generators are modelled as a state-space linear equation where sensors are deployed to obtain measurements. As the synchronous generator states are unknown, the estimation is required to know the overall operating conditions of large-scale complex power networks. Basically, the proposed algorithm is based on the minimization of the mean squared estimation error, and the optimal gain is computed by exchanging information with their neighboring estimators. Afterwards, the convergence of the developed algorithm is proved so that it can be applied to real-time applications in modern smart grids. Finally, simulation results demonstrate the efficacy of the developed approach.
Rana, MM, Li, L & Su, SW 1970, 'Distributed State Estimation for Microgrids', IFAC-PapersOnLine, the 20th IFAC World Congress, Elsevier BV, Toulouse, France, pp. 10202-10207.
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© 2017 This paper proposes a novel distributed consensus filter based dynamic state estimation algorithm with its convergence analysis for modern power systems. The novelty of the scheme is that the algorithm is designed based on the mean squared error and semidefinite programming approaches. Specifically, the optimal local gain is computed after minimizing the mean squared error between the true and estimated states. The consensus gain is determined by a convex optimization process with a given sub-optimal local gain. Furthermore, the convergence of the proposed schemed is analysed after stacking all the estimation error dynamics. The Laplacian operator is used to represent the interconnected filter structure as a compact error dynamic for deriving the convergence condition of the algorithm. The developed approach is verified by using the mathematical dynamic model of the renewable microgrid. It shows that the proposed distributed scheme is effective to properly estimate the system states.
Ranasinghe, R, Dissanayake, G, Furukawa, T, Arukgoda, J & Dantanarayana, L 1970, 'Environment representation for mobile robot localisation', 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), IEEE, Peradeniya, Sri Lanka, pp. 1-6.
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© 2017 IEEE. An adequate representation of the environment is an essential component of a mobile robot navigation system. This paper reviews the techniques reported in the literature for capturing the geometry of the space surrounding a mobile robot. In particular, the use of distance functions that combine some of the advantages of feature based and occupancy grid based representations for mobile robot localisation is described in detail. The effectiveness of various distance function based representations is demonstrated using a number of practical examples for localising ground and air vehicles.
Rasekh, H, Aziz, N, Mirza, A, Nemcik, J, Li, X, Yang, G & Khaleghparast, S 1970, 'Double Shear Testing of Cable Bolts with No Concrete Face Contacts', Procedia Engineering, Elsevier BV, pp. 1169-1177.
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© 2017 Published by Elsevier Ltd. A new series of double shear tests were carried out using a newly modified double shear apparatus which prevented contacts between concrete block surfaces during shearing. 13 double shear tests were carried out using 21 mm diameter 19 (9 × 9 × 1) seal construction wire strand cable (also called Superstrand cable), Plain SUMO, Indented SUMO, Spiral MW9 and Plain MW10 cable bolts. These cables were tested subjected to different pretension loads. Concrete blocks with Uniaxial Compressive Strength (UCS) of 40 MPa and Stratabinder grout were used for all the tests to maintain test consistency. The results show that the peak shear load and the corresponding shear displacement decrease by increasing the pretension load of the tested cable. The Ultimate tensile strength, lay length, number of wires and cable bolt surface profile type (plain and spiral/indented) are important factors in total shear strength of the cable bolt.
Rashidi, M, Samali, B, Zhu, X, Azad, A & Ghodrat, M 1970, 'Case study: Structural health monitoring of timber bridges using dynamic frequency analysis (DFA)', SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings, pp. 1262-1271.
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Australia has numerous ageing timber bridges in service. The structural efficiency of the majority of them have been impaired over time and their capacity is not known. There is, therefore, a critical need to develop new methods that will enable the load carrying capacity of these bridges to be estimated. In this paper, an established testing method known as Dynamic Frequency Analysis (DFA) and its application for monitoring of bridges is described throughout a case study (Mongarlowe Bridge). The testing procedure involves the attachment of sensors (accelerometers) underneath the bridge. The natural frequency and vibration response of the bridge superstructure is measured when a “calibrated sledgehammer” is used to excite the unloaded deck, and again with a relatively small mass applied at mid-span. The difference in response allows load carrying capacity of the bridge to be estimated. Furthermore, by regular monitoring of the bridge and its natural frequency, the potential degradation of the structure and the existing load bearing capacity can be determined.
Ray, PK, Panigrahi, BK, Rout, PK, Mohanty, A & Dubey, H 1970, 'Fault detection in an IEEE 14-bus power system with DG penetration using wavelet transform', CRC Press, pp. 221-225.
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Raza, A, Hussain, R, Tahir, FA, Khan, MU & Sharawi, MS 1970, 'Dual-band frequency reconfigurable MIMO antenna with continuous tuning range', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, pp. 1373-1374.
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Ren, Z, Lin, D, Zhang, G & Nie, Z 1970, 'Off Line Arc Current Detection and Active Control of Pantograph-catenary System', 2017 63RD IEEE HOLM CONFERENCE ON ELECTRICAL CONTACTS, 63rd IEEE Holm Conference on Electrical Contacts, IEEE, CO, Denver, pp. 194-199.
Reza, CMFS, Lu, DD-C & Qin, L 1970, 'Single-inductor multiple-source mixer for DC power packet dispatching system', 2017 IEEE Second International Conference on DC Microgrids (ICDCM), 2017 IEEE Second International Conference on DC Microgrids (ICDCM), IEEE, Nuremburg, Germany, pp. 553-557.
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© 2017 IEEE. DC power packet dispatching system is reported recently aiming to deliver power in a packet form. It can utilize less power conversion stages which increases power distribution efficiency and monitor load demand intelligently from source side to keep the system stable. A multiple-energy-source mixer based on a multiple-input single-inductor buck converter for DC power packet dispatching system is proposed. It is capable of generating power packets at different voltage levels by time sharing of multiple power sources. In this work, three different sources including a PV panel and two DC voltage sources are used for the power packet dispatching system. A control strategy is devised in order that the PV panel can track maximum power point (MPP) approximately and the PV is given a priority to share power in each power packet generation. Experimental results are reported to verify the proposed mixer and its control strategy for DC power packet dispatching system.
Riaz, MH, Rashid, U, Ali, M & Li, L 1970, 'Internet of Things Based Wireless Patient Body Area Monitoring Network', 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), IEEE, Exeter, England, UK, pp. 970-973.
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© 2017 IEEE. Wireless body area network is a climbing innovation in machine world and assumes an exceptionally lively part in general public. By using this technology, medical specialists can check complete subtle elements of a patient from a remote area and can prescribe a suitable solution. The primary motivation behind this innovation is to decrease the work load at doctor's facilities and give proficient medical services. For this purpose, different body sensors are used to monitor the physical parameters such as electro-cardiogram, heart rate, blood pressure and body temperature of patients, and use wireless sensor network (WSN) in conjunction with internet of things (IoT) to continuously monitor the patient condition. Health parameters data is also sent to the medical personnel with the help of wireless technology module such as a Zigbee (S2 module) and internet cloud computing. The proposed system is not only economically viable but also offers enough portability to be used in remote under-privileged areas for better health facilities.
Rizoiu, M-A & Xie, L 1970, 'Online Popularity under Promotion: Viral Potential, Forecasting, and the Economics of Time', Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017, pp. 182-191.
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Modeling the popularity dynamics of an online item is an important openproblem in computational social science. This paper presents an in-depth studyof popularity dynamics under external promotions, especially in predictingpopularity jumps of online videos, and determining effective and efficientschedules to promote online content. The recently proposed Hawkes IntensityProcess (HIP) models popularity as a non-linear interplay between exogenousstimuli and the endogenous reactions. Here, we propose two novel metrics basedon HIP: to describe popularity gain per unit of promotion, and to quantify thetime it takes for such effects to unfold. We make increasingly accurateforecasts of future popularity by including information about the intrinsicproperties of the video, promotions it receives, and the non-linear effects ofpopularity ranking. We illustrate by simulation the interplay between theunfolding of popularity over time, and the time-sensitive value of resources.Lastly, our model lends a novel explanation of the commonly adopted periodicand constant promotion strategy in advertising, as increasing the perceivedviral potential. This study provides quantitative guidelines about settingpromotion schedules considering content virality, timing, and economics.
Rizoiu, M-A, Mishra, S, Kong, Q, Carman, M & Xie, L 1970, 'SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations', Proceedings of WWW 2018, 27th World Wide Web (WWW) Conference, ASSOC COMPUTING MACHINERY, Lyon, FRANCE, pp. 419-428.
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Among the statistical tools for online information diffusion modeling, bothepidemic models and Hawkes point processes are popular choices. The formeroriginate from epidemiology, and consider information as a viral contagionwhich spreads into a population of online users. The latter have roots ingeophysics and finance, view individual actions as discrete events incontinuous time, and modulate the rate of events according to the self-excitingnature of event sequences. Here, we establish a novel connection between thesetwo frameworks. Namely, the rate of events in an extended Hawkes model isidentical to the rate of new infections in the Susceptible-Infected-Recovered(SIR) model after marginalizing out recovery events -- which are unobserved ina Hawkes process. This result paves the way to apply tools developed for SIR toHawkes, and vice versa. It also leads to HawkesN, a generalization of theHawkes model which accounts for a finite population size. Finally, we derivethe distribution of cascade sizes for HawkesN, inspired by methods instochastic SIR. Such distributions provide nuanced explanations to the generalunpredictability of popularity: the distribution for diffusion cascade sizestends to have two modes, one corresponding to large cascade sizes and anotherone around zero.
Robson, E, Wijayaratna, K & Dixit, VV 1970, 'From CBA to CGE: A review of computable general equilibrium modelling for transport appraisal', ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings.
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© 2017 ATRF, Commonwealth of Australia. All rights reserved. In the transport planning process, decision makers require reliable and informative appraisals to facilitate comparisons and determine if a proposal is worthwhile to society. The cost benefit analysis is the most common form of appraisal, but the consumer surplus metric used in cost benefit analyses will only reflect total social welfare if markets operate perfectly. There may be significant uncaptured impacts, known as wider economic impacts, which agencies are beginning to incorporate in appraisals using ad-hoc methods. Computable general equilibrium (CGE) models are an increasingly popular method for assessing the economic impacts of transport, including both direct and wider economic impacts, as they can determine the distribution of impacts among every market and agent in the economy. By simulating the behaviour of households, firms and others from microeconomic first principles, they can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews CGE models that have been applied to transport issues, and discusses the general role of CGE modelling in transport appraisal as well as theoretical and practical concerns regarding CGE modelling practice.
Robson, E, Wijayaratna, K & Dixit, VV 1970, 'From CBA to CGE: A review of computable general equilibrium modelling for transport appraisal', ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings.
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In the transport planning process, decision makers require reliable and informative appraisals to facilitate comparisons and determine if a proposal is worthwhile to society. The cost benefit analysis is the most common form of appraisal, but the consumer surplus metric used in cost benefit analyses will only reflect total social welfare if markets operate perfectly. There may be significant uncaptured impacts, known as wider economic impacts, which agencies are beginning to incorporate in appraisals using ad-hoc methods. Computable general equilibrium (CGE) models are an increasingly popular method for assessing the economic impacts of transport, including both direct and wider economic impacts, as they can determine the distribution of impacts among every market and agent in the economy. By simulating the behaviour of households, firms and others from microeconomic first principles, they can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews CGE models that have been applied to transport issues, and discusses the general role of CGE modelling in transport appraisal as well as theoretical and practical concerns regarding CGE modelling practice.
Roselin, AG, Nanda, P & Nepal, S 1970, 'Lightweight Authentication Protocol (LAUP) for 6LoWPAN Wireless Sensor Networks', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, pp. 371-378.
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© 2017 IEEE. 6LoWPAN networks involving wireless sensors consist of resource starving miniature sensor nodes. Since secured authentication of these resource-constrained sensors is one of the important considerations during communication, use of asymmetric key distribution scheme may not be the perfect choice to achieve secure authentication. Recent research shows that Lucky Thirteen attack has compromised Datagram Transport Layer Security (DTLS) with Cipher Block Chaining (CBC) mode for key establishment. Even though EAKES6Lo and S3K techniques for key establishment follow the symmetric key establishment method, they strongly rely on a remote server and trust anchor for secure key distribution. Our proposed Lightweight Authentication Protocol (LAUP) used a symmetric key method with no preshared keys and comprised of four flights to establish authentication and session key distribution between sensors and Edge Router in a 6LoWPAN environment. Each flight uses freshly derived keys from existing information such as PAN ID (Personal Area Network IDentification) and device identities. We formally verified our scheme using the Scyther security protocol verification tool for authentication properties such as Aliveness, Secrecy, Non-Injective Agreement and Non-Injective Synchronization. We simulated and evaluated the proposed LAUP protocol using COOJA simulator with ContikiOS and achieved less computational time and low power consumption compared to existing authentication protocols such as the EAKES6Lo and SAKES.
Roser, C, Lorentzen, K, Lenze, D, Deuse, J, Klenner, F, Richter, R, Schmitt, J & Willats, P 1970, 'Bottleneck Prediction Using the Active Period Method in Combination with Buffer Inventories', IFIP Advances in Information and Communication Technology, Springer International Publishing, pp. 374-381.
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© 2017, IFIP International Federation for Information Processing. Knowing the bottleneck is one of the keys to improving a production system. The active period method is one approach to detect shifting bottlenecks that most other bottleneck detection methods have problems with. Yet, like many other methods, these detections are limited to detecting the past and present bottlenecks. In this paper, we combined the active period method with the buffer inventories and free buffer spaces of the adjacent inventories to statistically predict not only an upcoming change of the bottleneck, but also where the bottleneck will move to.
Royel, S & Ha, Q 1970, 'Frequency shaped sliding mode control of magnetorheological smart structure systems', 2017 IEEE International Conference on Mechatronics (ICM), 2017 IEEE International Conference on Mechatronics (ICM), IEEE, Churchill, VIC, Australia, pp. 117-122.
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This paper addresses the problem of controlling
multi-degree-of-freedom (MDoF) smart structures integrated
with magnetorheological (MR) devices that are subject to non-
linearity and hysteresis. A fluid based device, namely the MR
damper (MRD), is considered in this study, where hysteresis
appears in both force-displacement and force-velocity relation-
ships of the smart device. Such nonlinear dynamics limit the
performance of the device when embedded in smart structures.
The describing function (DF) technique is employed using only
the displacement as input to the nonlinearity to characterize
this multivalued mechanism. By incorporating the proposed
model into the system dynamics, frequency shaped sliding mode
control (FSSMC) is developed to achieve structural resilience
and sustainability against nonlinearities, modeling uncertainties,
and disturbances from dynamic loadings. Frequency response
functions (FRFs) are obtained for possible analysis of system
conditional assessment in the frequency domain. Simulations
are reported for a three-story building model integrated with
two identical current-dependent MR dampers subject to one-
dimensional quake-induced vibration to investigate lateral dy-
namic responses, as produced by earthquakes or strong winds.
Rujikiatkamjorn, C & Indraratna, B 1970, 'An Evaluation of vacuum consolidation performance using observational techniques', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2643-2646.
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Soft clays in coastal areas normally have low shear strength and high compressibility. The construction activities for near shore infrastructure on these deposits often pose geotechnical problems due to large time dependent settlement and lateral movement. Ground improvement techniques are used in this terrain to reduce the water content of soft clays by preloading with vertical drains. Depending on the magnitude of the surcharge, substantial and immediate settlement with lateral movement can occur during preloading, which then causes problems of undrained stability in the loaded areas. Vacuum assisted preloading has now become a popular method of ground improvement in Australia where substantial loads must be applied to meet a desired rate of settlement and mitigate undrained failure. To assist vacuum propagation at significant depths, vertical drains are usually used in conjunction. At the Port of Brisbane and the Ballina Bypass, Australia, vacuum assisted surcharge preloading and conventional surcharge preloading schemes were used to reduce the time required for consolidation and long term settlement in soft Holocene clays. The design of the combined vacuum and surcharge fill system and construction of the embankment are described in this paper. Field monitoring data are presented to demonstrate how the embankment performed during construction. The paper also evaluates the relative performance of the two contrasting preloading systems (i.e. vacuum and non-vacuum system) using a dimensionless analysis. Here the dimensionless parameter can be considered to act as a 'filter' to distinguish the relative performance of the improved foundations for vacuum combined surcharge loading, even if the shape of the time settlement curves and the degree of consolidation are similar.
Ruppert, MG, Harcombe, DM, Ragazzon, MRP, Moheimani, SOR & Fleming, AJ 1970, 'Frequency domain analysis of robust demodulators for high-speed atomic force microscopy', 2017 American Control Conference (ACC), 2017 American Control Conference (ACC), IEEE, pp. 1562-1567.
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Saadat, A, Ni, W & Vesilo, R 1970, 'Spectrum sharing in femtocell based networks using an equal priority power control game', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-6.
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© 2017 IEEE. In order to keep pace with the recent proliferation of wireless services and mobile applications, efficient and flexible radio spectrum utilization needs to be ensured in next-generation mobile networks. In this regard, we present a game-Theoretic spectrum-sharing scheme, by considering coexistence of a set of femtocells, belonging to multiple networks, in a coverage area where all cells have an equal priority of accessing the spectrum. We formulate a non-cooperative transmit-power-control game, in which all the femtocells share the spectrum by adjusting their transmit powers according to the interference, until the transmit power is stabilized. We prove that a Nash equilibrium exists for the proposed non-cooperative game, verify that it is unique and highlight the role of specific game parameters in this regard. A novel dual-mode solution is proposed for implementation of the game, which ensures that an equilibrium point can be reached having minimum coordination among the network elements. Finally, we present simulation results to show that the game converges to a Nash equilibrium and provide a throughput performance analysis.
Saberi, M, Hussain, OK & Chang, E 1970, 'An online statistical quality control framework for performance management in crowdsourcing', Proceedings of the International Conference on Web Intelligence, WI '17: International Conference on Web Intelligence 2017, ACM, Leipzig, GERMANY, pp. 476-482.
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Saberi, Z, Hussain, OK, Saberi, M & Chang, E 1970, 'Online Retailer Assortment Planning and Managing under Customer and Supplier Uncertainty Effects Using Internal and External Data', 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), IEEE, Shanghai, PEOPLES R CHINA, pp. 7-14.
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Sadeghi, S, Kalhori, H, Tabassum, M, Fu, K, Ye, L & Kinloch, A 1970, 'Characterization of Mode I fracture behavior of a shear thickening fluid using a cohesive zone model', 9th Australasian Congress on Applied Mechanics, ACAM 2017.
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The fracture behavior of double cantilever-beam (DCB) specimens with a shear thickening fluid (STF) as an adhesive layer is investigated numerically. The mode I fracture toughness of the STF appears to increase with an increase in the opening displacement rate, showing brittle fracture at high loading rates. In this study, a rate-dependent cohesive zone model (CZM), following a bilinear traction-separation behavior, is introduced, in which the rate-dependency of the fracture toughness, initial stiffness, and cohesive stress are incorporated. A linear dependence of the CZM parameters on the strain rate based on a logarithmic relationship is proposed. The model is then validated by comparing the predictions with the experimental results, and good agreement is found. It is shown that the use of a well-founded rate-dependent numerical model is crucial for modeling a shear thickening fluid as an adhesive material subjected to various loading rates.
Sadra, S & Abolhasan, M 1970, 'On improving the saturation performance of IEEE802.15.6-based MAC protocols in Wireless Body Area Networks', 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, Valencia, Spain, pp. 1233-1238.
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© 2017 IEEE. Wireless Body Area Networks (WBANs) were designed to collect and transfer vital physiological parameters within a short distance of the human body by employing low-power, light-weight, small-sized and smart implantable or wearable sensor devices. Lately, WBANs are expected to support various types of applications with data rates from a few Kbps upto 10 Mbps and satisfy the heterogeneous requirements of both medical and consumer electronics applications. Hence, novel communication protocols that consider a unique set of constraints and demands of these networks need to be developed to provide optimum system efficiency and data transmission reliability. As the IEEE 802.15.6 Medium Access Control (MAC) protocol based on the latest WBANs standard, cannot maintain the balance between the strict energy limitation and Quality of Service (QoS) requirements of such networks, this paper focuses on developing MAC protocols to improve the performance of WBANs specifically in the saturation condition. Two IEEE802.15.6-based MAC protocols are proposed to enhance channel access for the highest user priority and the other user priorities in saturated networks. The simulation results show better network performance as well as lower energy consumption in the proposed MAC protocols compared to the IEEE 802.15.6 MAC protocol.
Salah, A, Guo, Y & Dorrell, D 1970, 'Monitoring and damping unbalanced magnetic pull due to eccentricity fault in induction machines: A review', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. Condition monitoring can diagnose the inception of fault mechanisms in induction motors, thus avoiding failure and expensive repairs. Therefore, there is a strong need to develop an efficient condition monitoring. The main target is to achieve a relatively low cost and/or non-invasive system which is still powerful in terms of monitoring for online detection of developing faults. The presented paper addresses rotor eccentricity faults and studies conventional monitoring techniques for induction motors. In order to reduce the unbalanced magnetic pull (UMP) in case of an eccentric rotor, the eccentricity-generated additional airgap flux waves should be reduced. The radial forces in an induction motor are calculated, and the characteristics of unbalanced magnetic pull are described.
Salah, AA, Guo, Y & Dorrell, DG 1970, 'Analysis of DFIG machine with rotor-wound faults', 2017 IEEE AFRICON, 2017 IEEE AFRICON, IEEE, Cape Town, South Africa, pp. 1301-1306.
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© 2017 IEEE. The round rotor induction machine (WRIM) can be described as a doubly fed induction generator (DFIG) when driven above the synchronous speed, and the stator and rotor windings are connected to the whole system. The work in this paper develops a relatively simple powerful model that can accurately analysis the behavior of DFIG with rotor-wound faults. The model is based upon the calculation of the stator current components, which are needed to the build impedance matrix. This method is used here to detect the rotor asymmetry fault on a four-pole wound rotor. Measured torque, current, and power loss results are compared with computer predictions for the machine with a rotor connected to symmetrical or asymmetrical external resistance. An equivalent circuit for a wound rotor induction machine, which includes external resistances, is derived. This is essential for building a better understanding of the fault components computed from the matrix. Simulation and experimental results evidence the validity of the suggested method, leading to an improved condition monitoring system for diagnosing faults in WRIMs.
Salama, U, Yao, L, Wang, X, Paik, H-Y & Beheshti, A 1970, 'Multi-Level Privacy-Preserving Access Control as a Service for Personal Healthcare Monitoring', 2017 IEEE International Conference on Web Services (ICWS), 2017 IEEE International Conference on Web Services (ICWS), IEEE, Honolulu, HI, pp. 878-881.
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Salvador, MM, Budka, M & Gabrys, B 1970, 'Modelling multi-component predictive systems as petri nets', 15th International Industrial Simulation Conference 2017, ISC 2017, pp. 17-23.
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Building reliable data-driven predictive systems requires a considerable amount of human effort, especially in the data preparation and cleaning phase. In many application domains, multiple preprocessing steps need to be applied in sequence, constituting a 'workflow' and facilitating reproducibility. The concatenation of such workflow with a predictive model forms a Multi-Component Predictive System (MCPS). Automatic MCPS composition can speed up this process by taking the human out of the loop, at the cost of model transparency (i.e. not being comprehensible by human experts). In this paper, we adopt and suitably re-define the Well-handled with Regular Iterations Work Flow (WRI-WF) Petri nets to represent MCPSs. The use of such WRI-WF nets helps to increase the transparency of MCPSs required in industrial applications and make it possible to automatically verify the composed workflows. We also present our experience and results of applying this representation to model soft sensors in chemical production plants.
Saqib, M, Daud Khan, S, Sharma, N & Blumenstein, M 1970, 'A study on detecting drones using deep convolutional neural networks', 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE, Lecce, Italy, pp. 1-5.
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© 2017 IEEE. The object detection is a challenging problem in computer vision with various potential real-world applications. The objective of this study is to evaluate the deep learning based object detection techniques for detecting drones. In this paper, we have conducted experiments with different Convolutional Neural Network (CNN) based network architectures namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16) etc. Due to sparse data available for training, networks are trained with pre-trained models using transfer learning. The snapshot of trained models is saved at regular interval during training. The best models having high mean Average Precision (mAP) for each network architecture are used for evaluation on the test dataset. The experimental results show that VGG16 with Faster R-CNN perform better than other architectures on the training dataset. Visual analysis of the test dataset is also presented.
Saqib, M, Daud Khan, S, Sharma, N & Blumenstein, M 1970, 'Extracting descriptive motion information from crowd scenes', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. An important contribution that automated analysis tools can generate for management of pedestrians and crowd safety is the detection of conflicting large pedestrian flows: this kind of movement pattern, in fact, may lead to dangerous situations and potential threats to pedestrian's safety. For this reason, detecting dominant motion patterns and summarizing motion information from the scene are inevitable for crowd management. In this paper, we develop a framework that extracts motion information from the scene by generating point trajectories using particle advection approach. The trajectories obtained are then clustered by using unsupervised hierarchical clustering algorithm, where the similarity is measured by the Longest Common Sub-sequence (LCS) metric. The achieved motions patterns in the scene are summarized and represented by using color-coded arrows, where speeds of the different flows are encoded with colors, the width of an arrow represents the density (number of people belonging to a particular motion pattern) while the arrowhead represents the direction. This novel representation of crowded scene provides a clutter free visualization which helps the crowd managers in understanding the scene. Experimental results show that our method outperforms state-of-the-art methods.
Saqib, M, Khan, SD & Blumenstein, M 1970, 'Detecting dominant motion patterns in crowds of pedestrians', SPIE Proceedings, Eighth International Conference on Graphic and Image Processing, SPIE, Tokyo, Japan, pp. 102251L-102251L.
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© 2017 SPIE. As the population of the world increases, urbanization generates crowding situations which poses challenges to public safety and security. Manual analysis of crowded situations is a tedious job and usually prone to errors. In this paper, we propose a novel technique of crowd analysis, the aim of which is to detect different dominant motion patterns in real-time videos. A motion field is generated by computing the dense optical flow. The motion field is then divided into blocks. For each block, we adopt an Intra-clustering algorithm for detecting different flows within the block. Later on, we employ Inter-clustering for clustering the flow vectors among different blocks. We evaluate the performance of our approach on different real-time videos. The experimental results show that our proposed method is capable of detecting distinct motion patterns in crowded videos. Moreover, our algorithm outperforms state-of-the-art methods.
Schell, AW, Takashima, H, Tran, TT, Aharonovich, I & Takeuchi, S 1970, 'Spectroscopy of Single Quantum Emitters in Hexagonal Boron Nitride Using Linear and Non-Linear Excitation', Conference on Lasers and Electro-Optics, CLEO: QELS_Fundamental Science, OSA, San Jose, CA, USA, pp. FTu3E.4-FTu3E.4.
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© 2017 IEEE. Excitation of single photon emitters via a two-photon process can be employed for high resolution imaging and has applications in quantum optics. Here, we present one- and two-photon excitation of single defects in hexagonal boron.
Schell, AW, Tran, TT, Aharonovich, I, Takashima, H & Takeuchi, S 1970, 'Nonlinear excitation of single quantum emitters in hexagonal boron nitride (Conference Presentation)', Ultrafast Phenomena and Nanophotonics XXI, Ultrafast Phenomena and Nanophotonics XXI, SPIE, pp. 39-39.
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Schwendimann, BA, Rodriguez-Triana, MJ, Vozniuk, A, Prieto, LP, Boroujeni, MS, Holzer, A, Gillet, D & Dillenbourg, P 1970, 'Perceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research', IEEE Transactions on Learning Technologies, Institute of Electrical and Electronics Engineers (IEEE), pp. 30-41.
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Scopigno, R, Cignoni, P, Pietroni, N, Callieri, M & Dellepiane, M 1970, 'Digital Fabrication Techniques for Cultural Heritage: A Survey.', Comput. Graph. Forum, pp. 6-21.
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Setiadi, H, Mithulananthan, N & Hossain, MJ 1970, 'Impact of battery energy storage systems on electromechanical oscillations in power systems', 2017 IEEE Power & Energy Society General Meeting, 2017 IEEE Power & Energy Society General Meeting (PESGM), IEEE, pp. 1-5.
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© 2017 IEEE. Due to high penetrations of renewable energy systems (RESs), deployment of energy storage is significantly increased in recent years. Among varieties of energy storage options, battery energy storage systems (BESSs) are getting popular as they provide reliable performance with low-inertia RESs. Although BESS smooth out RES energy, they can negatively influence low-frequency oscillations of power systems due to inertia-less characteristics. However, a very scant attention has been paid to understand the BESS impact on low frequency oscillation of power systems. Hence, this paper investigates the impact of BESSs on the low-frequency oscillation. In order to analyse the impact of BESS's control and its dynamic interaction, a single machine infinite bus, popularly known as 'Philip-Heffron model' is used. Eigenvalue, nonlinear time domain simulation and participation factor analyses are used to examine system's behaviours with BESS. From simulation results, it is found that the gain of BESS's controller changes the dynamic behaviour of synchronous machines and optimally tuned gain can enhance system's damping.
Shahzad, K, Guo, Y, Li, L & Dorrell, D 1970, 'Design of high speed permanent magnet generator for solar co-generation system using motor-CAD', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-6.
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© 2017 IEEE. High speed brushless permanent-magnet generators (HSBPMGs) may be the most suitable choice for small solar co-generation systems due to a variety of merits. For instance, they offer substantial reduction in size, and thermally excellent high-power density, which reduces the running costs with good performance and reliability. Moreover, high efficiencies i.e. over 90%, light-weight, low operating temperature, high insulation, no brushes/slip rings and almost negligible cogging torque make HSBPMGs ideal for co-generation systems. However, because of the very high rotor speed and high stator frequency, the design of HSBPMG is quite different from designing a conventional generator with low speed and low frequency. As the speed increases, the losses and temperature go up, and thus careful attention is needed while selecting the design parameters and material for the machine. This paper is aimed to use the basic design process for HSBPMGs running at 60,000rpm, with 6.6kW capacity keeping the losses minimum by using an appropriate material and cooling method. Finite element analysis of the machine is carried by using Motor-CAD simulation software, and modeling of a prototype machine is presented.
Shakor, P & Nejadi, S 1970, '3D Printed Concrete Evaluations by Using Different Concrete Mix Designs', Recent Trends in Engineering and Technology, IEEE, Bangkok, Thailand, pp. 212-217.
Shakor, P, Renneberg, J, Nejadi, S & Paul, G 1970, 'Optimisation of Different Concrete Mix Designs for 3D Printing by Utilizing 6DOF Industrial Robot', Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC), 34th International Symposium on Automation and Robotics in Construction, Tribun EU, s.r.o., Brno, Taipei, Taiwan, pp. 268-275.
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Additive Manufacturing (AM) technologies are becoming increasingly viable for commercial and research implementation into various applications. AM refers to the process of forming structures layer upon layer and finds application in prototyping and manufacturing for building construction. It has recently begun to be considered as a viable and attractive alternative in certain circumstances in the construction industry. This paper focuses on the utilisation of different concrete mixtures paired with extrusion techniques facilitated by a six Degree of Freedom (DOF) industrial robot. Using methods of Damp Least Squares (DLS) in conjunction with Resolved Motion Rate Control (RMRC), it is possible to plan stable transitions between several waypoints representing the various print cross-sections. Calculated paths are projected via 'spline' interpolation into the manipulator controlled by custom software. This article demonstrates the properties of different concrete mixture designs, showing their performance when used as a filament in 3D Printing and representing a comparison of the results that were found. In this study, the prepared materials consist of ordinary Portland cement, fine sand between (425-450) micron, coarse aggregate ranges (3) mm and chemical admixtures which have been used to accelerate setting times and reduce water content. Numerous tests were performed to check the buildability, flowability, extrudability and moldability of the concrete mixtures. The horizontal test was used to determine the flowability and consistency, while the vertical and squeeze-flow tests were used to determine the buildability of the layers. The extrudability and moldability of the concrete mixtures were controlled by the robot and associated extruder speeds.
Shang, D, Zhang, G & Lu, J 1970, 'Fast concept drift detection using singular vector decomposition', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Nanjing, China, pp. 1-6.
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© 2017 IEEE. Data stream mining is widely used in online applications such as sensor networks, financial transactions, etc. Such systems generate data at high velocity and their underlying distributions may change over time. This is referred to as concept drift problem and it is considered to be the root cause of performance degradation of online machine learning models. To tackle this problem, a reliable and fast drift detection method is required to achieve real time responsiveness to the drifts. This paper presents a fast and accurate drift detection method, namely KS-SVD test - KSSVD, to monitor the distribution changes of the data stream. Our method employs the SVD technique to first check the direction change of the data, followed by a KS test on each direction to detect the univariate distribution changes. Experiments show that our method is efficient and accurate, especially in high dimension situation.
Sharbaf, M, Ghafoori, N & Dumitru, N 1970, 'Geogrid in paved and unpaved road systems: A review of mechanisms and design mehods', Bearing Capacity of Roads, Railways and Airfields - Proceedings of the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields, BCRRA 2017, International Conference on the Bearing Capacity of Roads, Railways and Airfields, CRC Press, Athens, Greece, pp. 1161-1168.
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© 2017 Taylor & Francis Group, London. This study has focused on the effect of using Lime (L) from 1.5% to 6.25%; Bagasse Ash (BA) between 6% and 25% and combination of BA-L reached up to 25% on the consolidation characteristic of expansive after the swelling pressure has been determined. The results indicated that the swelling pressure was reduced with increasing BA or L. Furthermore, the results were improved when BA was added to soil treated with L. The swelling pressure of untreated soil decreased from 80 kPa (untreated soil) to 7 kPa (treated with 25% BA-L). In consolidation tests, the pre-consolidation stress has been developed from 180 kPa with untreated soil to 290 kPa with 6.25% lime and 350 kPa when 18.75% BA was added to soil-6.25% L. Furthermore, better results were ascertained when soft clay stabilized with 25% BA-L in comparison with compacted virgin soft clay samples. In addition, the compression indices, and swelling indices decreased 97% and 56%, respectively.
Sharma, N, Sengupta, A, Sharma, R, Pal, U & Blumenstein, M 1970, 'Pincode detection using deep CNN for postal automation', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. Postal automation has been a topic of research over a decade. The challenges and complexity involved in developing a postal automation system for a multi-lingual and multi-script country like India are many-fold. The characteristics of Indian postal documents include: multi-lingual behaviour, unconstrained handwritten addresses, structured/unstructured envelopes and postcards, being among the most challenging aspects. This paper examines the state-of-the-art Deep CNN architectures for detecting pin-code in both structured and unstructured postal envelopes and documents. Region-based Convolutional Neural Networks (RCNN) are used for detecting the various significant regions, namely Pin-code blocks/regions, destination address block, seal and stamp in a postal document. Three network architectures, namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16), and VGG M were considered for analysis and identifying their potential. A dataset consisting of 2300 multilingual Indian postal documents of three different categories was developed and used for experiments. The VGG-M architecture with Faster-RCNN performed better than others and promising results were obtained.
Shen, F, Mu, Y, Yang, Y, Liu, W, Liu, L, Song, J & Shen, HT 1970, 'Classification by Retrieval', Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '17: The 40th International ACM SIGIR conference on research and development in Information Retrieval, ACM, Shinjuku, Tokyo, Japan, pp. 595-604.
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© 2017 Copyright held by the owner/author(s). This paper proposes a generic formulation that significantly expedites the training and deployment of image classification models, particularly under the scenarios of many image categories and high feature dimensions. As the core idea, our method represents both the images and learned classifiers using binary hash codes, which are simultaneously learned from the training data. Classifying an image thereby reduces to retrieving its nearest class codes in the Hamming space. Specifically, we formulate multiclass image classification as an optimization problem over binary variables. The optimization alternatingly proceeds over the binary classifiers and image hash codes. Profiting from the special property of binary codes, we show that the sub-problems can be efficiently solved through either a binary quadratic program (BQP) or a linear program. In particular, for attacking the BQP problem, we propose a novel bit-flipping procedure which enjoys high efficacy and a local optimality guarantee. Our formulation supports a large family of empirical loss functions and is, in specific, instantiated by exponential and linear losses. Comprehensive evaluations are conducted on several representative image benchmarks. The experiments consistently exhibit reduced computational and memory complexities of model training and deployment, without sacrificing classification accuracy.
Shen, L, Dah-Chuan Lu, D & Fu, J 1970, 'Sliding mode control of a bidirectional grid connected three phase two-stage PV system with space vector PWM', 2017 36th Chinese Control Conference (CCC), 2017 36th Chinese Control Conference (CCC), IEEE, Dalian, China, pp. 3553-3558.
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© 2017 Technical Committee on Control Theory, CAA. A bidirectional grid connected three phase two-stage PV system with DC loads is studied in this paper. The dq frame model is derived in detail, which simplifies the analysis and the controller design. With the dq frame state space model, the switching signals are also converted to the dq frame, which decouples the control input under the dq frame. An adaptive law is designed to estimate the unknown reference value of direct-axis current. The three phase converter can work bidirectionally according to the signal of the direct-axis current. Then the power balance between the PV generation and grid can be realized dynamically. Simulation results show the effectiveness of the proposed control scheme.
Shen, T, Zhou, T, Long, G, Jiang, J, Pan, S & Zhang, C 1970, 'DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding', 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, AAAI Conference on Artificial Intelligence, AAAI, New Orleans, USA, pp. 5446-5455.
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Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widelyused on NLP tasks to capture the long-term and local dependencies,respectively. Attention mechanisms have recently attracted enormous interestdue to their highly parallelizable computation, significantly less trainingtime, and flexibility in modeling dependencies. We propose a novel attentionmechanism in which the attention between elements from input sequence(s) isdirectional and multi-dimensional (i.e., feature-wise). A light-weight neuralnet, 'Directional Self-Attention Network (DiSAN)', is then proposed to learnsentence embedding, based solely on the proposed attention without any RNN/CNNstructure. DiSAN is only composed of a directional self-attention with temporalorder encoded, followed by a multi-dimensional attention that compresses thesequence into a vector representation. Despite its simple form, DiSANoutperforms complicated RNN models on both prediction quality and timeefficiency. It achieves the best test accuracy among all sentence encodingmethods and improves the most recent best result by 1.02% on the StanfordNatural Language Inference (SNLI) dataset, and shows state-of-the-art testaccuracy on the Stanford Sentiment Treebank (SST), Multi-Genre natural languageinference (MultiNLI), Sentences Involving Compositional Knowledge (SICK),Customer Review, MPQA, TREC question-type classification and Subjectivity(SUBJ) datasets.
Shen, X, Liu, W, Tsang, I, Shen, F & Sun, Q-S 1970, 'Compressed K-Means for Large-Scale Clustering', Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, USA, pp. 2527-2533.
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Large-scale clustering has been widely used in many applications, and has received much attention. Most existing clustering methods suffer from both expensive computation and memory costs when applied to large-scale datasets. In this paper, we propose a novel clustering method, dubbed compressed k-means (CKM), for fast large-scale clustering. Specifically, high-dimensional data are compressed into short binary codes, which are well suited for fast clustering. CKM enjoys two key benefits: 1) storage can be significantly reduced by representing data points as binary codes; 2) distance computation is very efficient using Hamming metric between binary codes. We propose to jointly learn binary codes and clusters within one framework. Extensive experimental results on four large-scale datasets, including two million-scale datasets demonstrate that CKM outperforms the state-of-the-art large-scale clustering methods in terms of both computation and memory cost, while achieving comparable clustering accuracy.
Sheng, Z, Tuan, HD, Nasir, AA & Poor, HV 1970, 'Secrecy Throughput of Wireless Interference Networks with Uncertain Channel State Information', 2017 IEEE Globecom Workshops (GC Wkshps), 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, Singapore, Singapore, pp. 1-7.
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© 2017 IEEE. Considering a multi-user interference network with an eavesdropper, this paper investigates the problem of power allocation to optimize the worst secrecy throughput among the network links. Three scenarios for the access of channel state information are considered: perfect channel state information, partial channel state information with channels from the transmitters to the eavesdropper exponentially distributed, and imperfectly known channels between the transmitters and the users with exponentially distributed errors. The paper develops various path-following procedures of low complexity and rapid convergence for the optimal power allocation. Their effectiveness and viability are illustrated through numerical examples. The power allocation schemes are shown to achieve high secrecy throughput.
Shi, L, Valls Miro, J, Vidal Calleja, T, Vitanage, D & Rajalingam, J 1970, 'Innovative Data-driven “along-the-pipe” Condition Assessment for Critical Water Mains', OZWATER’17 Australia’s International Water Conference & Exhibition, OzWater’17 Australia’s International Water Conference & Exhibition, Australian Water Association, Sydney, pp. 1-8.
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Recent research findings on remaining life prediction for older Cast Iron critical water mains suggest increasing reliability by calculating stress concentration factors from the corrosion patch geometries expected to be present in the asset, not just extreme pitting as is generally carried out within the industry. This study proposes an innovative data-driven “along-the-pipe” framework able to utilise local inspection results further by capturing data correlations present in the remaining wall thickness measurement. This knowledge can in turn be utilised to produce estimates for “along-the-pipe” patch geometry predictions, hence remaining life. Results from inspections in a real pipeline in the Sydney Water network are compared to conventional Extreme Value Analysis (EVA) to validate the improvements of the proposed strategy.
Shi, X, Zhu, J, Dah-Chuan Lu, D & Li, L 1970, 'Advanced multi-functional model predictive control for three-phase AC/DC converters', 19th International Conference on Electrical Machines and Systems, ICEMS 2016, International Conference on Electrical Machines and Systems, IEEE, Chiba, Japan.
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With the conventional model predictive control (MPC) based direct power control of three-phase AC/DC converters, the active and reactive powers can be simultaneously controlled by a single cost function. A change in parameters of either the active or reactive power within the cost function will affect the other, leading to poor dynamic performance of transient response. Besides, the steady state performance of the conventional MPC is affected by one-step-delay of digital implementation. This paper proposes an advanced multi-functional MPC of three-phase full-bridge AC/DC converter for high power applications. It has multiple functions such as one-step-delay compensation, power ripple reduction, switching frequency reduction, and dynamic mutual influence elimination. Using the proposed modified cost function, both the steady state and dynamic performances of the converter can be improved. Finally, the simulation results are reported to validate the advancement of the proposed control strategy in comparison with other control methods.
Shi, Y, Li, W, Gao, Y, Cao, L & Shen, D 1970, 'Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks', Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, USA, pp. 1524-1531.
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Metric learning has been widely employed, especially in various computer vision tasks, with the fundamental assumption that all samples (e.g., regions/superpixels in images/videos) are independent and identically distributed (IID). However, since the samples are usually spatially-connected or temporally-correlated with their physically-connected neighbours, they are not IID (non-IID for short), which cannot be directly handled by existing methods. Thus, we propose to learn and integrate non-IID metrics (NIME). To incorporate the non-IID spatial/temporal relations, instead of directly using non-IID features and metric learning as previous methods, NIME first builds several non-IID representations on original (non-IID) features by various graph kernel functions, and then automatically learns the metric under the best combination of various non-IID representations. NIME is applied to solve two typical computer vision tasks: interactive image segmentation and histology image identification. The results show that learning and integrating non-IID metrics improves the performance, compared to the IID methods. Moreover, our method achieves results comparable or better than that of the state-of-the-arts.
Shi, Y, Tuan, HD & V. Savkin, A 1970, 'Three-phase Optimal Power Flow for Smart Grids by Iterative Nonsmooth Optimization', Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, 6th International Conference on Smart Cities and Green ICT Systems, SCITEPRESS - Science and Technology Publications, Porto, Portugal, pp. 323-328.
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© 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved. Optimal power flow is important for operation and planning of smart grids. The paper considers the so called unbalanced thee-phase optimal power flow problem (TOPF) for smart grids, which involves multiple quadratic equality and indefinite quadratic inequality constraints to model the bus interconnections, hardware capacity and balance between power demand and supply. The existing Newton search based or interior point algorithms are often trapped by a local optimum while semidefinite programming relaxation (SDR) even fails to locate a feasible point. Following our previously developed nonsmooth optimization approach, computational solution for TOPF is provided. Namely, an iterative procedure for generating a sequence of improved points that converges to an optimal solution, is developed. Simulations for TOPF in unbalanced distributed networks are provided to demonstrate the practicability and efficiency of our approach.
Shiozaki, T & Dissanayake, G 1970, 'Monocular 3D metric scale reconstruction using depth from defocus and image velocity', 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver, pp. 6723-6728.
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This paper presents a novel approach to metric scale reconstruction of a three-dimensional (3D) scene using a monocular camera. Using a sequence of images from a monocular camera with a fixed focus lens, metric distance to a set of features in the environment is estimated from image blur due to defocus. The blur texture ambiguity which causes scale errors in depth from defocus is corrected in an EKF framework that exploits image velocity measurements. We show in real experiments that our method converges to a metric scale, accurate, sparse depth map and 3D camera poses with images from a monocular camera. Therefore, the proposed approach has the potential to enhance robot navigation algorithms that rely on monocular cameras.
Shiri, F, Yu, X, Koniusz, P & Porikli, F 1970, 'Face Destylization', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-8.
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Shiri, F, Yu, X, Koniusz, P & Porikli, F 1970, 'Face Destylization', 2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), International Conference on Digital Image Computing - Techniques and Applications (DICTA), IEEE, AUSTRALIA, Sydney, pp. 427-434.
Siahpoosh, MK, Dorrell, D & Li, L 1970, 'Ferroresonance assessment in a case study wind farm with 8 units of 2 MVA DFIG wind turbines', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. This paper studies the transient and sustained ferroresonance phenomenon in wind farms connected to a power distribution system. Ferroresonance can be critical for wind turbines during switching or fault conditions. This results in effects such as harmonics, voltage dips and overvoltage in the system [1]. The ferroresonance current is able to damage the machine and the rotor side converter, and as a consequence, the system must be protected [2]. In this paper, first the existence of ferroresonance in wind farms has been assessed. Software modeling and a validation method has been proposed and the simulation results for different system arrangements have been presented. In general, engineers can often work around nonlinearities using a simplified linear approximation to calculate or predict performance within the 'normal' range of operation. This is not possible in the case of ferroresonance since linearized calculations will not predict it [3][4]. Therefore PSCAD-EMTDC software is used in this study to analyse the behaviour of a wind farm with Doubly Fed Induction Generators (DFIGs) [5][6]. Results show that ferroresonance is a function of network components; specifically, the lengths of cables, types of wind turbine generators, power transformers and transmission lines.
Siahpoosh, MK, Li, L & Dorrell, DG 1970, 'Wind farm grounding system analysis', 2017 IEEE Energy Conversion Congress and Exposition (ECCE), 2017 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Cincinnati, OH, USA, pp. 4780-4785.
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© 2017 IEEE. this paper studies a real-case grounding system design for a wind farm and associated equipment. The design is based on the safety criteria provided by Australian and International guidelines listed in the references [1-5]. The wind farm grounding system consists of wind turbine generators, tower base padmounts, 33 kV cable screen and a primary substation. In this paper, grounding system and ground potential rise analyses are presented and discussed. In this study, the conventional earthing system of a wind farm is assessed. The impacts of turbines foundation reinforcement, tower base substation, inter-connection cables and mutual coupling between neighboring turbines grounding systems were simulated. Several methods of improvement are accordingly proposed. Since it is more likely to have farm animals in the vicinity of a wind turbine during the phase to ground fault, a new method for calculation of safe step voltage for farm animals is also proposed.
Siami, M, Naderpour, M & Lu, J 1970, 'Generating a risk profile for car insurance policyholders: A deep learning conceptual model', Proceedings of the 28th Australasian Conference on Information Systems, ACIS 2017, Australasian Conference on Information Systems, ACIS, Hobart, Australia, pp. 1-8.
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In recent years, technological improvements have provided a variety of new opportunities for insurance companies to adopt telematics devices in line with usage-based insurance models. This paper sheds new light on the application of big data analytics for car insurance companies that may help to estimate the risks associated with individual policyholders based on complex driving patterns. We propose a conceptual framework that describes the structural design of a risk predictor model for insurance customers and combines the value of telematics data with deep learning algorithms. The model's components consist of data transformation, criteria mining, risk modelling, driving style detection, and risk prediction. The expected outcome is our methodology that generates more accurate results than other methods in this area.
Sick, N, Broering, S, Aaldering, L & Figgemeier, E 1970, 'Life cycle patterns and industry clockspeed in energy storage', The XXVIII ISPIM conference “Composing the innovation symphony”, Vienna, Austria.
Sick, N, Guertler, MR & Kriz, A 1970, 'Wicked Problem Sprint Sessions as a Means of Open Innovation – Development and Evaluation at ISPIM Events', The ISPIM Innovation Summit – Building the Innovation Century, Melbourne, pp. 1-15.
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The world is becoming increasingly complex and interconnected, and so are the challenges we face in innovation management – but do our problem solving methods keep pace to deal with such wicked problems? The present study focuses on developing and evaluating an open innovation method named wicked problem sprint sessions (WPSS) to cope with wicked problems in innovation management. This workshop-based method is embedded in the ISPIM conference context and aims at bringing together interdisciplinary experts from the triple helix. The method uses different creativity, design, cross-industry and gamification elements to allow a quick understanding of a focal problem and development of innovative solution ideas and concepts. The contribution is twofold. Firstly, we provide a concise overview of wicked problems with respect to innovation management, linking the multidisciplinary background of wicked problems to the requirements of innovation management. Secondly, we present and evaluate WPSS as a new open innovation method how to solve wicked problems in innovation management, not only in business but also in educational and public domains.
Siddiqi, MWU, Tu, C & Lee, JE-Y 1970, 'Effect of curvature and electrode coverage on the quality factor of biconvex ALN-on-Si MEMS resonators', 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), IEEE, pp. 98-101.
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Simorangkir, RBVB, Yang, Y & Esselle, K 1970, 'Active and Passive Antennas Based on Unconventional Materials, for Next Generation Wearable Wireless Devices (Invited Paper)', 2017 IEEE MTT-S International Microwave Symposium, Honolulu, Hawaii.
Simorangkir, RBVB, Yang, Y & Esselle, KP 1970, 'Performance of embroidered higher-order mode antennas with different stitching patterns', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, France, pp. 177-180.
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© 2017 Euraap. In this paper the performance of TM21 resonance-mode circular patch antennas embroidered with different stitching patterns is discussed and compared. The goal is to investigate the difference in the performance when the antenna is embroidered with stitches following the antenna current paths as opposed to some simple patterns such as horizontal and vertical ones. This creates an alternative solution for embroidering prototypes of wearable antennas with complicated current distributions. The results reveal that by embroidering the antenna in line with the complex TM21 current distribution a good monopole-like radiation pattern is achieved, which is close to an etched copper prototype's used as the reference. However, with a dense horizontal stitching pattern an acceptable monopole-like radiation pattern can also be achieved with quite good gain and efficiency. While simplifying the embroidery process, the use of the simple horizontal pattern with high density suffers from high cross-polarization and thread consumption as compromises.
Simorangkir, RBVB, Yang, Y, Esselle, KP & Diao, Y 1970, 'A varactor-tuned frequency-reconfigurable fabric antenna embedded in polymer: Assessment of suitability for wearable applications', 2017 IEEE MTT-S International Microwave Symposium (IMS), 2017 IEEE/MTT-S International Microwave Symposium - IMS 2017, IEEE, Honolulu, Hawaii, pp. 204-207.
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© 2017 IEEE. In this paper, we present a novel class of wearable antennas that are flexible, electronically tunable, and robust. They consist of conductive fabric parts, used as the radiator, with polydimethylsiloxane (PDMS) polymer utilized to form the substrate as well as the full encapsulation of the radiator including its electronic tuning elements. To validate the concept, a prototype that provides frequency tuning from 2.3 to 2.65 GHz has been fabricated and tested. The fabrication process is detailed and experimental investigations on its suitability for wearable applications are presented. To assess the antenna robustness, its reconfigurability under severe physical deformations has been studied through washing the antenna and also by wrapping it on the head and wrist of a UWB human muscle equivalent phantom. The antenna's effect on body has also been investigated through Specific Absorption Rate (SAR) measurement. The results confirm that the antenna is a promising candidate for modern wearable devices.
Singh, AM, Ha, QP, Wood, DK & Bishop, M 1970, 'Low-latency Vision-based Fiducial Detection and Localization for Object Tracking', Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC), 34th International Symposium on Automation and Robotics in Construction, Tribun EU, s.r.o., Brno, pp. 706-711.
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Real-time vision systems are widely-used in construction and manufacturing industries. A significant proportion of computational resources of such systems is used in fiducial identification and localisation for motion tracking of moving targets. The requirement is to localise a pattern in an image captured by the vision system precisely, accurately, and with a minimum available computation time. As such, this paper presents a class of patterns and, accordingly, proposes an algorithm to fulfil the requirement. Here, the patterns are designed using circular patches of concentric circles to increase the probability of detection and reduce cases of false detection. In the detection algorithm, the image captured by the vision system is first scaled down for computationally-effective processing. The scaled image is then separated by filtering only the colour components, which are made up of outer circular patches in the proposed pattern. A blob detection algorithm is then implemented for identifying inner circular patches. The inner circles are then localised in the image by using the colour information obtained. Finally, the localised pattern, along with the camera and distortion matrix of the vision system, is applied in a perspective-n-point solving algorithm to estimate the marker orientation and position in the global coordinate system. Our system shows significant enhancement in performance of fiducial detection and identification and achieves the required latency of less than ten milliseconds. Thus, it can be used for infrastructure monitoring in many applications that involve high-speed real-time vision systems.
Singh, J, Prasad, M, Daraghmi, YA, Tiwari, P, Yadav, P, Bharill, N, Pratama, M & Saxena, A 1970, 'Fuzzy logic hybrid model with semantic filtering approach for pseudo relevance feedback-based query expansion', 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Honolulu, HI, USA, pp. 1-7.
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© 2017 IEEE. Individual query expansion term selection methods have been widely investigated in an attempt to improve their performance. Each expansion term selection method has its own weaknesses and strengths. To overcome the weaknesses and utilize the strengths of individual methods, this paper combined multiple term selection methods. In this paper, initially the possibility of improving the overall performance using individual query expansion (QE) term selection methods are explored. Secondly, some well-known rank aggregation approaches are used for combining multiple QE term selection methods. Thirdly, a new fuzzy logic-based QE approach that considers the relevance score produced by different rank aggregation approaches is proposed. The proposed fuzzy logic approach combines different weights of each term using fuzzy rules to infer the weights of the additional query terms. Finally, Word2vec approach is used to filter semantically irrelevant terms obtained after applying the fuzzy logic approach. The experimental results demonstrate that the proposed approaches achieve significant improvements over each individual term selection method, aggregated method and related state-of-the-art method.
Sinha, S & Chaczko, Z 1970, 'Concepts and Observations in Artificial Endocrine Systems for IoT Infrastructure', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 427-430.
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© 2017 IEEE. Artificial Endocrine Systems is the study of nature’s highly evolved and advanced resource management system that sustains life. The basic units of the endocrine system are the chemical messengers, otherwise known as hormones, which in enough numbers produce cascading effects in the host organism that promotes growth, maintains metabolism and much more. This behaviour is in effect a living metaphor indicative of the high throughput, constant flux and stochastic interactions that exist in complex topologies such as large scale IoT infrastructures.
Sirivivatnanon, V, Khabbaz, H & Ayton, G 1970, '“Performance-based Specification of sand for skid resistance of concrete pavements”, ASCP 4th Concrete Pavement Conference, 2017.', ASCP 4th Concrete Pavement Conference, 2017, ASCP 4th Concrete Pavement Conference, 2017.
Siwakoti, YP & Blaabjerg, F 1970, 'H-Bridge transformerless inverter with common ground for single-phase solar-photovoltaic system', 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), IEEE, Tampa, FL, pp. 2610-2614.
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Siwakoti, YP, Soltani, M, Blaabjerg, F & Mostaan, A 1970, 'A novel quasi-SEPIC high-voltage boost DC-DC converter', 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), IEEE, Tampa, FL, USA, pp. 2213-2216.
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© 2017 IEEE. This paper proposes a modified coupled-inductor SEPIC dc-dc converter for low power and high voltage gain applications such as for piezoelectric drive systems. The converter uses the same components as of SEPIC converter with an additional diode. Compared to conventional topologies with similar voltage gain expression, the proposed topology uses less components to achieve same or even higher voltage gain. This helps to design a very compact and light weight converter with higher power density at lower cost. Due to brevity, the principle of operation, theoretical analysis and comparison supported by some key experimental results of 5 W prototype are presented in brief.
Siyari, P, Krunz, M & Nguyen, DN 1970, 'Joint transmitter- and receiver-based friendly jamming in a MIMO wiretap interference network', 2017 IEEE International Conference on Communications Workshops (ICC Workshops), 2017 IEEE International Conference on Communications Workshops (ICC Workshops), IEEE, Paris, France, pp. 1323-1328.
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© 2017 IEEE. We consider an interference network tapped by external eavesdropper(s) in which each legitimate transmit-receive pair conceals its communications by using joint transmit-based friendly jamming (TxFJ) and receiver-based friendly jamming (RxFJ). Specifically, TxFJ is realized at the transmit side using MIMO precoding while RxFJ is achieved at the receiver side of each link by leveraging the state-of-the-art self-interference-suppression techniques (allowing a radio to cancel the self-interference effect of its transmit signal). We show that with a careful power allocation between the information signal and TxFJ at the transmit side of each link, the corresponding receiver is able decide on using RxFJ independent of any multi-user interference factor. This ability sets the receivers free from having to measure multi-user interference at eavesdropper(s). With every link following such strategy, we model this interaction as a non-cooperative game. We derive sufficient conditions under which the game admits a unique Nash equilibrium. We then propose a robust version of the game that requires only statistical knowledge of eavesdropping channel.
Siyari, P, Krunz, M & Nguyen, DN 1970, 'Joint Transmitter- and Receiver-based Friendly Jamming in a MIMO Wiretap Interference Network', 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd Workshop on Optical Wireless Communications (OWC), IEEE, FRANCE, Paris, pp. 1323-1328.
Smith, RE, Anderson, DT, Ball, JE, Zare, A & Alvey, B 1970, 'Aggregation of Choquet integrals in GPR and EMI for handheld platform-based explosive hazard detection', SPIE Proceedings, SPIE Defense + Security, SPIE, pp. 1018217-1018217.
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Smith, RE, Anderson, DT, Zare, A, Ball, JE, Smock, B, Fairey, JR & Howington, SE 1970, 'Genetic Programming Based Choquet Integral for Multi-Source Fusion', 2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, ITALY, Naples.
Sockeel, N, Ball, J, Shahverdi, M & Mazzola, M 1970, 'Passive tracking of the electrochemical impedance of a hybrid electric vehicle battery and state of charge estimation through an extended Kalman filter', 2017 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC), IEEE Transportation Electrification Conference and Expo (ITEC), IEEE, IL, Chicago, pp. 479-485.
Sohaib, O & Naderpour, M 1970, 'Decision making on adoption of cloud computing in e-commerce using fuzzy TOPSIS.', FUZZ-IEEE, IEEE International Conference on Fuzzy Systems, IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Cloud computing promises enhanced scalability, flexibility, and cost-efficiency. In practice, however, there are many uncertainties about the usage of cloud computing resources in the e-commerce context. As e-commerce is dependent on a reliable and secure online store, it is important for decision makers to adopt an optimal cloud computing mode (Such as SaaS, PaaS and IaaS). This study assesses the factors associated with cloud-based e-commerce based on TOE (technological, organizational, and environmental) framework using multi-criteria decision-making technique (Fuzzy TOPSIS). The results show that Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach proposes software-as-a-service (SaaS) as the best choice for e-commerce business.
Sohaib, O, Lu, H & Hussain, W 1970, 'Internet of Things (IoT) in E-commerce: For people with disabilities', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Cambodia, pp. 419-423.
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© 2017 IEEE. Internet of Things (IoT) is an interconnection between the physical object and digital world. As a result, many e-commerce companies seize the advantages of the IoT to grow their business. However, the world's largest minority are people with disabilities. IoT can lower barriers for the disabled people by offering assistance in accessing information. Increasing Internet accessibility can help to make that happen for both social and economic benefit. This paper presents the proposed integrated framework of the IoT and cloud computing for people with disabilities such as sensory (hearing and vision), motor (limited use of hands) and cognitive (language and learning disabilities) impairments in the context of business-to-consumer e-commerce context. We conclude that IoT-enabled services offer great potential for success of disabled people in the context of online shopping.
Song, B, Wang, H, Xiao, W, Huang, S & Shi, L 1970, 'Gaussian process model enabled particle filter for device-free localization', 2017 20th International Conference on Information Fusion (Fusion), 2017 20th International Conference on Information Fusion (Fusion), IEEE, Xi'an, China, pp. 1-6.
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© 2017 International Society of Information Fusion (ISIF). Device-free localization (DFL) is an emerging wireless network target localization technique that does not need to attach any electronic device with the target. It is remaining as a challenging research problem due to the weak wireless signals and the uncertain wireless communication environment. In this paper, a novel Gaussian Process (GP) based wireless propagation model is proposed to describe the likelihood relationship between the target location and the changes of the RSS measurement for a wireless link. Sequentially Particle Filter (PF) is applied to the DFL for estimating the location of the target, after the GP model is trained using the experimental measurements of the link. Experimental results demonstrate that the proposed GP-PF algorithm can track the target with much better localization accuracy than the Support Vector Machine (SVM) based PF approach.
Song, B, Wang, H, Xiao, W, Huang, S & Shi, L 1970, 'Gaussian Process Model Enabled Particle Filter for Device-Free Localization', 2017 20TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 20th International Conference on Information Fusion (Fusion), IEEE, Xian, PEOPLES R CHINA, pp. 1134-1139.
Song, H, Wu, Q & Dong, H 1970, 'EMI-based Diagnosis to Grounding Grids by Combining Ensemble Empirical Mode Decomposition and ICA', Proceedings of the 8th International Conference on Computer Modeling and Simulation, ICCMS '17: 8th International Conference on Computer Modeling and Simulation, ACM, Canberra, Australia, pp. 196-200.
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© 2017 ACM. Grounding grids have been performed an essential role in electric transformer substations. The nondestructive diagnosis system applies transforms the condition of the undergrounding conductors to the surficial induced electric signal in sensing coil. However, the induced signal cannot be used directly to diagnosis due to the raw measurement is a mixture of responses from signal of interest, strong interference and other unknown noises. Therefore the separation of individual signatures from the mixture is posed as a blind source separation (BSS) problem. To extract the induced signal corrupted by noise, the independent component analysis (ICA) method is considered. By combining the EEMD and FastICA, the single-channel signal is decomposed into its ICs. The desired signal is then reconstructed to visualize the break point of the grounding grid. The results show this approach can be used to effectively diagnosis grounding gird in harsh electromagnetic environment.
Song, J, wang, J, Zhao, L, Huang, S & Dissanayake, G 1970, 'Deformable Soft-tissue Reconstruction using Stereo Scope for Minimal Invasive Surgery', CARS 2017 -- Computer Assisted Radiology and Surgery, 31st International Congress and Exhibition, CARS 2017 -- Computer Assisted Radiology and Surgery, 31st International Congress and Exhibition.
song, J, wang, J, Zhao, L, huang, S & Dissanayake, G 1970, 'Robust Shape Recovery of Deformable Soft-tissue Based on Information from Stereo Scope for Minimal Invasive Surgery', Hamlyn Symposium on Medical Robotics (HSMR 2017), Hamlyn Symposium on Medical Robotics, Kensington, England.
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Overcoming small field of view of scopes is an important challenge in minimal invasive surgery (MIS). Efforts have been devoted in 3D soft-tissue construction and camera localization [1-2]. This paper proposes arobust strategy for simultaneous camera localization and dense reconstruction of deformable surfaces. The robustness is achieved by: (1) using a sequence of images collected from a stereoscope by consideringuncertainty map; (2) filtering images with low intensity; (3) filtering depth by normals. Our approach greatly reduces depth estimation parameter adjustment efforts while still generates good results and preservestopological details. Experiments reveal that the proposed approach is convenient for dynamically rebuild and visualize the latest shape of soft-tissue to mitigate unnecessary tissue damages in minimalinvasive surgery.
Song, X, Zhang, X, Yu, S, Jiao, S & Xu, Z 1970, 'Resource-Efficient Virtual Network Function Placement in Operator Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, pp. 1-7.
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© 2017 IEEE. Network Function Virtualization (NFV) is an emerging network resource utilization approach which decouples network functions from proprietary hardware. To accommodate Service Function Chain (SFC) requests, service providers offer Virtual Network Function (VNF) instances in operator networks. However, how to efficiently place VNFs at various network locations while jointly optimizing computing and communication resource is still an open problem. To this end, we study the resource-efficient VNF placement problem in operator networks. We firstly formulate this problem as an Integer Linear Programming (ILP) model. Then we design an efficient heuristic algorithm named Resource- efficient Virtual Network Function Placement (RVNFP) based on Hidden Markov Model (HMM). Extensive simulation results show that compared with the previous VNF placement algorithms, RVNFP saves up to 12.51% network cost, and achieves a good tradeoff between computing resource cost and communication resource cost.
Song, Y, Zhang, G, Lu, J & Lu, H 1970, 'A fuzzy kernel c-means clustering model for handling concept drift in regression', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Concept drift, given the huge volume of high-speed data streams, requires traditional machine learning models to be self-adaptive. Techniques to handle drift are especially needed in regression cases for a wide range of applications in the real world. There is, however, a shortage of research on drift adaptation for regression cases in the literature. One of the main obstacles to further research is the resulting model complexity when regression methods and drift handling techniques are combined. This paper proposes a self-adaptive algorithm, based on a fuzzy kernel c-means clustering approach and a lazy learning algorithm, called FKLL, to handle drift in regression learning. Using FKLL, drift adaptation first updates the learning set using lazy learning, then fuzzy kernel c-means clustering is used to determine the most relevant learning set. Experiments show that the FKLL algorithm is better able to respond to drift as soon as the learning sets are updated, and is also suitable for dealing with reoccurring drift, when compared to the original lazy learning algorithm and other state-of-the-art regression methods.
Sood, K, Yu, S & Xiang, Y 1970, 'Are current resources in SDN allocated to maximum performance and minimize costs and maintaining QoS problems?', Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2017: Australasian Computer Science Week 2017, ACM, pp. 1-6.
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© 2017 ACM. In order to maintain application specific Quality of Service (QoS) requirements, the number of resources used in network directly impacts the capital (CAPEX) and operational expenditure (OPEX). Therefore, it is vital to investigate feasible strategies to maintain QoS and minimizing resources provisioning cost. In this paper, we propose a solution in a hierarchical Software-defined network (SDN) architecture that provides ow-balancing (with guaranteed QoS) in proactive operations of SDN controllers, and attempts to optimize the use of instance resources provisioning costs to the controller. Furthermore, in order to validate our findings, we showed results from performance evaluations using appropriate analytical model. We believe that our solution will helps to set-up a network with minimum resources and affordable cost with guaranteed application QoS.
Soon, JL, Lu, DD-C, Ling Qin & Sathiakumar, S 1970, 'Development of multi-mode step down DC/DC converters with fault-tolerant capability', 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), IEEE, Kaohsiung, Taiwan, pp. 127-133.
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© 2017 IEEE. This paper proposes a three-switch step-down DC/DC converter with fault-tolerant capabilities. Detection of faults during power converter switching operations is important to avoid failures. In this paper, fault analysis is based on open circuit fault detection (OCFD) techniques. A numerical solution is developed based on the joule-integral principle to design OCFD hardware protection. Under normal operating conditions, either one of the three switching modes, namely, buck, buck-boost, or flyback, is allowed. The two other switches remain in standby mode. All switches share the same output filter component to achieve a single-switch converter operation in any mode. A microcontroller is used to monitor open circuit faults, and identify MOSFET failure and normal operating conditions. If an open circuit fault occurs on the main switch, the other switch will be activated to provide an alternate current path to maintain output regulation. Simulated and experimental results are demonstrated to verify the design and its fault-tolerant operations.
Soro, A, Brereton, M, Roe, P, Wyeth, P, Johnson, D, Ambe, AH, Morrison, A, Bardzell, S, Leong, TW, Ju, W, Lindtner, S, Rogers, Y & Buur, J 1970, 'Designing the Social Internet of Things', Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, CHI '17: CHI Conference on Human Factors in Computing Systems, ACM, Denver, Colorado, USA, pp. 617-623.
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Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM). What role do people have in the Internet of Things? Compared to the impressive body of research that is currently tackling the technical issues of the Internet of Things, social aspects of agency, engagement, participation, and ethics, are receiving less attention. The goal of this 'Designing the Social Internet of Things' workshop is to contribute by shedding light on these aspects. We invite prospective participants to take a humanistic standpoint, explore people's relations with 'things' first, and then build on such relations so as to support socially relevant goals of engagement, relatedness, participation, and creativity.
Steendam, H, Wang, TQ & Armstrong, J 1970, 'Cramer-Rao bound for AOA-based VLP with an aperture-based receiver', 2017 IEEE International Conference on Communications (ICC), ICC 2017 - 2017 IEEE International Conference on Communications, IEEE, Paris, France, pp. 1-6.
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© 2017 IEEE. Visible light positioning (VLP) for indoor applications has recently received considerable attention. In this paper, an aperture based receiver is considered and the position is estimated based on the angle-of-arrival (AOA), because the AOA can be determined by comparing the relative differences in the received signal strengths (RSS) in the different photodiodes (PDs) of the receiver. Hence, in contrast to RSS based positioning solutions, knowledge of the transmitted signal strengths is not required. The performance of the proposed approach depends on the transmitted signal strength only through the dependency on the signal-to-noise ratio. To evaluate the accuracy of the estimates of the AOA, we derive the Cramer-Rao lower bound, and show that the expected error on the AOA is very small. Applying triangulation to determine the position of the receiver, it follows that centimetre accuracy can be obtained with the aperture-based receiver.
Stegner, J, Stehr, U, Tu, C, Lee, JE-Y & Hein, MA 1970, 'Very-low phase noise RF-MEMS reference oscillator using AlN-on-Si resonators achieved by accurate co-simulation', 2017 IEEE MTT-S International Microwave Symposium (IMS), 2017 IEEE/MTT-S International Microwave Symposium - IMS 2017, IEEE, pp. 1303-1306.
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Stegner, J, Stehr, U, Tu, C, Lee, JE-Y & Hein, MA 1970, 'Very-Low Phase Noise RF-MEMS Reference Oscillator Using AlN-on-Si Resonators Achieved by Accurate Co-Simulation', 2017 IEEE MTT-S INTERNATIONAL MICROWAVE SYMPOSIUM (IMS), IEEE-Microwave-Theory-and-Techniques-Society International Microwave Symposium (IMS) / Session on Women in Microwaves (WIM), IEEE, HI, Honolulu, pp. 1299-1302.
Stephenson, RM, Naik, GR & Chai, R 1970, 'A system for accelerometer-based gesture classification using artificial neural networks', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju island, Korea, pp. 4187-4190.
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A great many people suffer from neurological movement disorders that render typical hardware interface devices ineffective. A need exists for a universal interface device that can be trained to accept a wide range of inputs across varying types and severities of movement disorders. In this regard, this paper details the design, testing and optimization of an accelerometer-based gesture identification system. A Bluetooth-enabled IMU mounted on the wrist provides hand motion trajectory information to a local terminal. Several techniques are applied to decrease the intra-class variance and reduce classifier complexity including filtering, segmentation and temporal scaling. Datasets consisted of 520 training samples, 260 validation samples and a further 520 testing samples. A multi-layer feed forward artificial neural network (ML-FFNN) was used to classify the input space into 26 different classes. Initial system accuracy, using arbitrary hyperparameters was 77.69% with final optimized accuracy at 99.42%.
Stewart, MG, Ginger, JD, Henderson, DJ & Ryan, PC 1970, 'Fragility analysis of Australian contemporary housing roof sheeting failure due to extreme wind', 9th Asia Pacific Conference on Wind Engineering, APCWE 2017.
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The paper considers likelihood and extent of damage to metal roofing of a typical contemporary (new) Australian house subject to non-cyclonic extreme wind loading. A spatial and time-dependent reliability analysis enables fragility curves to be developed that relate likelihood and extent of roof cover loss to gust wind speed. It was found that mean extent of roof damage is less than 1% for a 100-year design wind event, and this estimate includes the effect of a dominant opening and construction defects.
Su, D, Vidal-Calleja, T & Miro, JV 1970, 'Towards real-time 3D sound sources mapping with linear microphone arrays', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, Singapore, pp. 1662-1668.
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© 2017 IEEE. In this paper, we present a method for real-time 3D sound sources mapping using an off-the-shelf robotic perception sensor equipped with a linear microphone array. Conventional approaches to map sound sources in 3D scenarios use dedicated 3D microphone arrays, as this type of arrays provide two degrees of freedom (DOF) observations. Our method addresses the problem of 3D sound sources mapping using a linear microphone array, which only provides one DOF observations making the estimation of the sound sources location more challenging. In the proposed method, multi hypotheses tracking is combined with a new sound source parametrisation to provide with a good initial guess for an online optimisation strategy. A joint optimisation is carried out to estimate 6 DOF sensor poses and 3 DOF landmarks together with the sound sources locations. Additionally, a dedicated sensor model is proposed to accurately model the noise of the Direction of Arrival (DOA) observation when using a linear microphone array. Comprehensive simulation and experimental results show the effectiveness of the proposed method. In addition, a real-time implementation of our method has been made available as open source software for the benefit of the community.
Su, X, Yao, Y, He, Q, Lu, J & Tong, H 1970, 'Personalized Travel Mode Detection with Smartphone Sensors', 2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), IEEE International Conference on Big Data (IEEE Big Data), IEEE, MA, Boston, pp. 1341-1348.
Suankaewmanee, K, Hoang, DT, Niyato, D, Sawadsitang, S, Wang, P & Han, Z 1970, 'Performance Analysis and Application of Mobile Blockchain', 2018 International Conference on Computing, Networking and Communications, ICNC 2018, International Conference on Computing, Networking and Communications, IEEE, Maui, HI, USA, pp. 642-646.
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Mobile security has become more and more important due to the boom of mobilecommerce (m-commerce). However, the development of m-commerce is facing manychallenges regarding data security problems. Recently, blockchain has beenintroduced as an effective security solution deployed successfully in manyapplications in practice, such as, Bitcoin, cloud computing, andInternet-of-Things. However, the blockchain technology has not been adopted andimplemented widely in m-commerce because its mining processes usually requireto be performed on standard computing units, e.g., computers. Therefore, inthis paper, we introduce a new m-commerce application using blockchaintechnology, namely, MobiChain, to secure transactions in the m-commerce.Especially, in the MobiChain application, the mining processes can be executedefficiently on mobile devices using our proposed Android core module. Throughreal experiments, we evaluate the performance of the proposed model and showthat blockchain will be an efficient security solution for future m-commerce.
Suarez-Rodriguez, C, Jayawickrama, BA, He, Y, Bader, F & Heimlich, M 1970, 'Performance analysis of REM-based handover algorithm for multi-tier cellular networks.', PIMRC, Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, IEEE, Montreal, QC, Canada, pp. 1-6.
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© 2017 IEEE. The advent of 5G networks, where a plethora of spectrum-sharing schemes are expected to be adopted as an answer to the ever-growing users' need for data traffic, will require addressing mobility ubiquitously. The trend initiated with the deployment of heterogeneous networks and past standards will give way to a multi-tiered network where different services will coexist, such as device-to-device, vehicle-to-vehicle or massive-machine communications. Because of the high variability in the cell sizes given the different transmit powers, the classical handover process, which relies solely on measurements, will lead to an unbearable network overhead as a consequence of the high number of handovers. The use of spatial databases, also known as radio environment maps (REM), was first introduced as a tool to detect opportunistic spectrum access opportunities in cognitive radio applications. Since then, REM usage has been widely expanded to cover deployment optimization, interference management or resource allocation to name a few. In this paper, we introduce a handover algorithm that can predict the best network connection for the current user's trajectory from a radio environment map. We consider a geometric approach to derive the handover and handover-failure regions and compare the current handover algorithm used in Long-Term Evolution with our proposed one. Results show a drastic reduction in the number of handovers while maintaining a trade-off between the ping-pong handover and the handover-failure probabilities.
Subasinghage, K, Gunawardane, K, Lie, TT & Kularatna, N 1970, 'Single-input, dual polarity, dual output DC-DC converter implementation based on the SCALDO technique', 2017 IEEE International Conference on Industrial Technology (ICIT), 2017 IEEE International Conference on Industrial Technology (ICIT), IEEE, pp. 207-212.
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Sun, G, Cui, T, Beydoun, G, Chen, S, Xu, D & Shen, J 1970, 'Organizing Online Computation for Adaptive Micro Open Education Resource Recommendation.', ICWL, International Conference on Web-Based Learning, Springer, Cape Town, South Africa, pp. 177-182.
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Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile.
Sun, G, Cui, T, Shen, J, Xu, D, Beydoun, G & Chen, S 1970, 'Ontological Learner Profile Identification for Cold Start Problem in Micro Learning Resources Delivery.', ICALT, IEEE 17th International Conference on Advanced Learning Technologies, IEEE Computer Society, Timisoara, Romania, pp. 16-20.
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Open learning is a rising trend in the educational sector and it attracts millions of learners to be engaged to enjoy massive latest and free open education resources (OERs). Through the use of mobile devices, open learning is often carried out in a micro learning mode, where each unit of learning activity is commonly shorter than 15 minutes. Learners are often at a loss in the process of choosing OER leading to their long term objectives and short term demands. Our pilot work, namely MLaaS, proposed a smart system to deliver personalized OER with micro learning to satisfy their real-time needs, while its decision-making process is scarcely supported due to the lack of historical data. Inspired by this, MLaaS now embeds a new solution to tackle the cold start problem, by opening up a brand new profile for each learner and delivering them the first resources in their fresh start learning journey. In this paper, we also propose an ontology-based mechanism for learning prediction and recommendation.
Sun, H, Ding, C, Guo, YJ & Mittra, R 1970, 'A wideband dipole antenna based on a non-uniformly segmented structure', 2017 11th European Conference on Antennas and Propagation (EUCAP), 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE, Paris, France, pp. 3572-3574.
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© 2017 Euraap. The design of a wideband, vertically polarized omnidirectional dipole antenna based on a non-uniformly segmented structure is presented. The proposed non-uniformly segmented configuration mitigates the phase change of the currents flowing in the long dipole arms, so that the reverse currents which deteriorate the radiation pattern can be avoided, and a stable omnidirectional pattern can be maintained over a wide frequency band. Simulation results show that the proposed dipole has a wide pattern bandwidth of 66%, ranging from 1.96 GHz to 3.90 GHz, with S11 less than -10 dB. Within the band, the main lobe of the dipole remains in the broadside direction in the E-plane and the antenna achieves the desirable omnidirectional radiation pattern, with a gain flatness of less than 0.3 dB in the H-plane.
Sun, L, Vidal-Calleja, T & Miro, JV 1970, 'Coupling conditionally independent submaps for large-scale 2.5D mapping with Gaussian Markov Random Fields', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, Singapore, pp. 3131-3137.
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© 2017 IEEE. Building large-scale 2.5D maps when spatial correlations are considered can be quite expensive, but there are clear advantages when fusing data. While optimal submapping strategies have been explored previously in covariance-form using Gaussian Process for large-scale mapping, this paper focuses on transferring such concepts into information form. By exploiting the conditional independence property of the Gaussian Markov Random Field (GMRF) models, we propose a submapping approach to build a nearly optimal global 2.5D map. In the proposed approach data is fused by first fitting a GMRF to one sensor dataset; then conditional independent submaps are inferred using this model and updated individually with new data arrives. Finally, the information is propagated from submap to submap to later recover the fully updated map. This is efficiently achieved by exploiting the inherent structure of the GMRF, fusion and propagation all in information form. The key contribution of this paper is the derivation of the algorithm to optimally propagate information through submaps by only updating the common parts between submaps. Our results show the proposed method reduces the computational complexity of the full mapping process while maintaining the accuracy. The performance is evaluated on synthetic data from the Canadian Digital Elevation Data.
Sun, L, Zhang, N, Awadallah, M & Walker, P 1970, 'An innovative control strategy for a hybrid energy storage system (HESS)', 2017 IEEE International Conference on Mechatronics (ICM), 2017 IEEE International Conference on Mechatronics (ICM), IEEE, Gippsland, Victoria, Australia, pp. 434-439.
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© 2017 IEEE. Electric Vehicles (EVs) adopting both batteries and supercapacitors have attracted a significant amount of attention in research communities due to its unique power sharing capabilities. A Hybrid Energy Storage System (HESS) can effectively reduce power stress that would otherwise be applied to batteries alone, and whose weight and size is still a common concern when competing against conventional ICE-powered cars. In this paper, a high-level control strategy is developed to adaptively split the load between two sources for an electric vehicle adopting HESS under real-life load fluctuations. A converter - Supercapacitor Pack (SP) coupled HESS upon which such an algorithm is deployed on, is proposed to divert excess power into the SP via a smart Power Converter (PC) which is located in between in order to regulate both behaviors. Such a power split strategy (PSS) is designed in such a way to track real-time load profiles and determines one important variable - the cut-off frequency. A simplified HESS model is first developed. The power split algorithm is coded in Matlab and then applied to this HESS model. Finally, the overall system is tested comprehensively over 4 EPA driving cycles. Simulation results prove its effectiveness in coping with even the harshest driving scenarios in real life.
Sun, WJ, Liu, C, Wei, G, Sun, DA, Wei, ZF, Liu, SQ & Fatahi, B 1970, 'Effect of sand content on undrained behaviour of GMZ bentonite-sand mixtures', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 1497-1503.
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The hydro-mechanical behaviour was studied by carrying out the constant water content triaxial tests on Gaomiaozi (GMZ) bentonite-sand mixtures with sand content of 70% and 50%, and the stress-strain relationship, deformation and pore water pressure under undrained shear state were obtained, together with the changes of the initial suction, compressibility, suction and strength with the sand content in mixtures. Moreover, the control mechanism was analyzed in microscopic level. The research provides the experimental basis to establish the hydro-mechanical model for unsaturated expansive soils under undrained state, and can be available for reference in proportional optimization design in bentonite based materials used in deep geological disposal system and waste landfills projects.
Sun, X, Kuang, S & Dong, D 1970, 'Rapid control of two-qubit systems based on measurement feedback', 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, pp. 310-315.
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Sun, Y, Bautista, MG, Zhu, F & Dutkiewicz, E 1970, 'Design of an Elliptic Filter Using Multiple-Loop Feedback Structure in CMOS Technology for Analogue Signal Processing', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Design of high-performance continuous- time filter (CTF) for analogue signal processing is presented in this paper. To demonstrate of using a novel voltage-mode multiple-loop feedback (MLF) approach for CTF design, a 5th-order elliptic lowpass filter (LPF) is implemented in a standard 0.18-μm CMOS technology. The LPF is based on an inverse-follow-the-leader feedback structure with an input distribution network to generate the required transmission zeros. The LPF consumes 35 mA from a single 1.8 V power supply and it has a cut-off frequency of 30 MHz with less than 0.7 dB passband ripple and more than 60 dB stopband attenuation. In addition, a 65 dB dynamic range is achieved.
Sun, Y, Li, L, Xie, Z, Xie, Q, Li, X & Xu, G 1970, 'Co-training an Improved Recurrent Neural Network with Probability Statistic Models for Named Entity Recognition', Database Systems for Advanced Applications (LNCS), International Conference on Database Systems for Advanced Applications, Springer International Publishing, Suzhou, China, pp. 545-555.
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Named Entity Recognition (NER) is a subtask of information extraction in Natural Language Processing (NLP) field and thus being wildly studied. Currently Recurrent Neural Network (RNN) has become a popular way to do NER task, but it needs a lot of train data. The lack of labeled train data is one of the hard problems and traditional co-training strategy is a way to alleviate it. In this paper, we consider this situation and focus on doing NER with co-training using RNN and two probability statistic models i.e. Hidden Markov Model (HMM) and Conditional Random Field (CRF). We proposed a modified RNN model by redefining its activation function. Compared to traditional sigmoid function, our new function avoids saturation to some degree and makes its output scope very close to [0, 1], thus improving recognition accuracy. Our experiments are conducted ATIS benchmark. First, supervised learning using those models are compared when using different train data size. The experimental results show that it is not necessary to use whole data, even small part of train data can also get good performance. Then, we compare the results of our modified RNN with original RNN. 0.5% improvement is obtained. Last, we compare the co-training results. HMM and CRF get higher improvement than RNN after co-training. Moreover, using our modified RNN in co-training, their performances are improved further.
Sun, Y, Zhu, X & Bautista, MG 1970, 'Design of fifth-order LF 0.05° equiripple linear phase lowpass filter with gain boost using nauta transcondutor', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-4.
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© 2017 IEEE. In this paper a leapfrog feedback filter architecture that uses only single-ended input and single-ended output (SISO) transconductors and grounded capacitors is described. The filter structure has all circuit nodes containing a grounded capacitor and requires only simple transconductors, thus suitable for higher frequency applications. To show the high frequency capability, a fifth-order linear phase UHF filter with gain boost has been designed using Nauta transconductor. This may be the first time that Nauta transcodunctors are used in HDD read channels.
Sung, CK, Li, S, Hedley, M, Nikolic, N & Ni, W 1970, 'Skew log-normal channel model for indoor cooperative localization', 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), IEEE, Montreal, QC, Canada, pp. 1-5.
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© 2017 IEEE. The performance of cooperative localization using received signal strength (RSS) benefits from accurate radio channel modeling. While log-normal shadowing is commonly used to model the relationship between RSS and range, the RSS error distribution in indoor environments has been observed to be neither normal nor symmetric. In this paper, we propose a skew log-normal channel model, which includes the standard log-normal model as a special case. We further propose an algorithm for using this model for RSS based cooperative localization. The algorithm was evaluated using data from an electro-magnetic simulation of an aircraft cabin, and was shown to generate more accurate node locations compared to the use of log-normal shadowing in the same localization algorithm.
Surawski, N, Van, TC, Ristovski, Z, Cong, NL, Lan, HN, Yuan, CSJ, Rahman, SMA, Hossain, FM, Guo, Y, Milic, A, Rainey, T, Garaniya, V & Brown, RJ 1970, 'Effects of sulphur and vanadium contents in diesel fuel on engine performance and emissions: Principal component analysis (PCA)', 11th Asia-Pacific Conference on Combustion, ASPACC 2017.
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Marine diesel engines using Heavy Fuel Oil (HFO) produce emissions of toxic compounds that have a negative impact on the environment and human health. A very limited number of on-board ship emission measurement studies have been undertaken due their logistical and regulatory complexity. An alternative way to investigate some issues relating to HFO fuels is by the use of a proxy fuel for HFO in a laboratory based diesel engine. Sulphur (S) and vanadium (V) are two elements of particular interest in HFO because of their relationship to particle formation and corrosive salt properties, respectively. An experimental engine campaign has been conducted on a heavy duty high speed six-cylinder turbocharged and after-cooled diesel engine with a common rail injection system. Principal Component Analysis has been applied in this study to investigate the relationships between: (i) measured engine performance and emissions variables and (ii) fuel S and V content and engine load.
Sutter, D, Berta, M & Tomamichel, M 1970, 'Quantum Markov chains and logarithmic trace inequalities', 2017 IEEE International Symposium on Information Theory (ISIT), 2017 IEEE International Symposium on Information Theory (ISIT), IEEE, Aachen, Germany, pp. 1988-1992.
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© 2017 IEEE. A Markov chain is a tripartite quantum state ρABC where there exists a recovery map RB→BC such that ρABC = RB→BC(ρAB). More generally, an approximate Markov chain ρABC is a state whose distance to the closest recovered state RB→BC(ρAB) is small. Recently it has been shown that this distance can be bounded from above by the conditional mutual information I(A: C|B)ρ of the state. We improve on this connection by deriving the first bound that is tight in the commutative case and features an explicit recovery map that only depends on the reduced state pBC. The key tool in our proof is a multivariate extension of the Golden-Thompson inequality, which allows us to extend logarithmic trace inequalities from two to arbitrarily many matrices.
Tahmassebi, A, Gandomi, AH & Meyer-Bäse, A 1970, 'High Performance GP-Based Approach for fMRI Big Data Classification', Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact, PEARC17: Practice and Experience in Advanced Research Computing 2017, ACM, pp. 1-4.
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© 2017 Copyright is held by the owner/author(s). We consider resting-state Functional Magnetic Resonance Imaging (fMRI) of two classes of patients: one that took the drug Nacetylcysteine (NAC) and the other one a placebo before and after a smoking cessation treatment. Our goal was to classify the relapse in nicotine-dependent patients as treatment or non-Treatment based on their fMRI scans. 80% accuracy was obtained using Independent Component Analysis (ICA) along with Genetic Programming (GP) classifier using High Performance Computing (HPC) which we consider significant enough to suggest that there is a difference in the resting-state fMRI images of a smoker that undergoes this smoking cessation treatment compared to a smoker that receives a placebo.
Tahmassebi, A, Gandomi, AH, McCann, I, Schulte, MHJ, Schmaal, L, Goudriaan, AE & Meyer-Baese, A 1970, 'An evolutionary approach for fMRI big data classification', 2017 IEEE Congress on Evolutionary Computation (CEC), 2017 IEEE Congress on Evolutionary Computation (CEC), IEEE, SPAIN, pp. 1029-1036.
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Takalkar, MA & Xu, M 1970, 'Image Based Facial Micro-Expression Recognition Using Deep Learning on Small Datasets', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, Australia, pp. 1-7.
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© 2017 IEEE. Facial micro-expression refers to split-second muscle changes in the face, indicating that a person is either consciously or unconsciously suppressing their true emotions and even mental health. Therefore, micro-expression recognition attracts increasing research efforts in both fields of psychology and computer vision. Existing research on micro-expression recognition has mainly used hand-crafted features, for example, Local Binary Pattern-Three Orthogonal Planes (LBP-TOP), Gabor filter and optical flow. Recently, Deep Convolutional neural systems have demonstrated a high degree effectiveness for difficult face recognition tasks. This paper explores the possible use of deep learning for micro-expression recognition. To develop a reliable deep neural network extensive training sets are required with a huge number of labeled image samples. However, micro-expression recognition is a challenging task due to the repressed facial appearance and short duration, which results in the lack of training data. In this paper, we propose to generate extensive training datasets of synthetic images using data augmentation on CASME and CASME II databases. Then, these datasets are combined to tune a satisfactory CNN-based micro-expression recognizer. Experimental results demonstrate the effectiveness of the proposed CNN approach in image based micro- expression recognition and present comparable results with the best-related works.
Tam, HHM, Tuan, HD, Nasir, AA & Duong, TQ 1970, 'Power splitting for MIMO energy harvesting in multi-user networks', 2017 International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), 2017 International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), IEEE, Da Nang, Vietnam, pp. 217-222.
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© 2017 IEEE. We consider a multicell multi-user multiple-input-multiple-output (MU-MIMO) network and propose the efficient design of precoding matrices for the sum throughput maximization under throughput QoS constraints and energy harvesting (EH) constraints for energy-constrained devices in both downlink (DL) and uplink (UL) transmissions. We employ power splitting (PS) approach at the receiver to ensure practical EH and information decoding (ID). The considered practical problem is quite complex due to highly non-convex objective and constraints. Towards this end, we develop a new path-following algorithm for its solution, which just requires a convex quadratic program at each iteration and promises quick convergence.
Tan, Z, Jamdagni, A & Liu, RP 1970, 'Message from the SECSOC 2017 Workshop Chairs', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, pp. xxxi-xxxi.
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Tapas, M, Vessalas, K, Thomas, P & Sirivivatnanon, V 1970, 'Role of Supplementary Cementitious Material Composition in its Efficacy to Mitigate Alkali-Silica Reaction', Concrete 2017 Advances in Materials and Structures, Concrete 2017 Advances in Materials and Structures, Adelaide, Australia.
Tavakoli, A, Najafi, A, Haque, ME, Hossain, MJ & Negnevitsky, M 1970, 'Voltage regulation for off-peak and peak conditions in distribution networks with the high penetration of PV units', 2017 Australasian Universities Power Engineering Conference (AUPEC), 2017 Australasian Universities Power Engineering Conference (AUPEC), IEEE, pp. 1-6.
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Teng, Q, Cui, H, Duan, J, Zhu, J, Guo, Y & Lei, G 1970, 'Extended state observer-based vector control for PMSM drive system with single phase current sensor', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. A novel extended state observer (ESO)-based vector control (VC) strategy is developed for permanent magnet synchronous motor (PMSM) drive systems with only one phase current sensor. Generally, to achieve high precision control, two phase current sensors are indispensable for successful operation of the feedback control. In response to a phase current sensor fault, by use of technique of ESO, a new observer for estimating both the remaining two phase currents and time-varying stator resistance is put forward. To improve the performance and decrease system high frequency vibration, a nonlinear exponential function is used to replace the switch function in conventional ESO. The resultant ESO-based VC strategy for PMSM drive system with single phase current sensor has strong robustness and satisfactory control performance. Numerical simulation validates the feasibility and effectiveness of the proposed scheme.
Thanh Tu, DT, Ngoc, NT, Zhu, F, Nguyen, DN, Dutkiewicz, E & Van Yem, V 1970, 'Quad-band antenna for GSM/WSN/WLAN/LTE-A application in IoT devices', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, Australia, pp. 1-5.
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We designed, fabricated, and experimented a quad-band Double-PIFA (Planar Inverted-F Antenna) for Internet of Things (IoT) applications. Using the Double-PIFA structure allowed us to fabricate the antenna easily and optimize the operating bands for desired frequencies. Combining DGS (Defected Ground Structure) and two shorting pin of PIFA structure, the antenna is compact in size with radiating patch of 184 mm2 basing on RO4350B substrate with height of 1.52 mm. Operating at 900MHz, 1.8GHz, 2.6GHz and 5GHzwith large bandwidth of 6.67%, 11.11%, 5.77% and 16%, respectively. As the proposed antenna can operate for ZigBee, Z-Wave, RFID (Radio-Frequency Identification), WLAN (Wireless Local Area Network), and LTE-A (Long Term Evolution - Advanced), it is suitable for both IoT devices and wide-band wireless communication systems.
Thiyagarajan, K, Kodagoda, S & Van Nguyen, L 1970, 'Predictive analytics for detecting sensor failure using autoregressive integrated moving average model', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1926-1931.
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© 2017 IEEE. Sensors play a vital role in monitoring the important parameters of critical infrastructure. Failure of such sensors causes destabilization to the entire system. In this regard, this paper proposes a predictive analytics solution for detecting the failure of a sensor that measures surface temperature from an urban sewer. The proposed approach incorporates a forecasting technique based on the past time series of sparse data using an autoregressive integrated moving average (ARIMA) model. Based on the 95% forecast interval and continuity of faulty data, a criterion was set to detect anomalies and to issue a warning for sensor failure. The forecasted and faulty data were assumed Gaussian distributed. By using the probability density of the distribution, the mean and variance were computed for faulty data to examine the abnormality in the variance value of each day to detect the sensor failure. The experimental results on the sewer temperature data are appealing.
Thomas, P, Ha Hau, WF, Vessalas, K, Sirivivatnanon, V & South, W 1970, 'Assessment of Test Methods for ASR Aggregate Reactivity', Concrete 2017 Advances in Materials and Structures, Concrete 2017 Advances in Materials and Structures, Adelaide, Australia.
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The paper reports on the initial stages of a study into the use of phase analysis using typical laboratory techniques; thermogravimetric analysis (TG), infrared spectroscopy (FTIR) and x-ray diffraction (XRD) to investigate the alkali silica reaction (ASR) with a view to classifying the relative reactivity of aggregates. Phase analysis of ground aggregates reacted under AS1141.60.1 accelerated mortar bar test (AMBT) conditions in the presence of calcium hydroxide (CH) are reported for aggregates that have been identified as non-reactive, slowly-reactive and reactive according to the AMBT test. Results of the phase analysis correlated the AMBT classifications. The reactivity of the aggregates was also compared to the reactivity of a quartz flour of similar particle size distribution which was found to be less reactive than the reactive and slowly reactive aggregates. The reactivity of the quartz flour and the reactive and slowly reactive aggregate was attributed to the highly reactive conditions used.
Thuy Do, QN, Hussain, FK & Nguyen, BT 1970, 'A fuzzy approach to detect spammer groups', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Cloud computing has been advancing at an impressive rate in recent years and is likely to increase more and more in the near future. New services are being developed constantly, such as cloud infrastructure, security and platform as a service, to name just a few. Due to the vast pool of available services, review websites have been created to help customers make decisions for their business. This leads to some reviewers taking advantage of these tools to promote the providers that hire them or to discredit competitors. These reviewers can either act individually or cooperate with each other. When reviewers collude to promote one product or defame another, they are called spammer groups. In this paper, we present an approach to identify spammer groups. First, a network-based method is used to identify individual spam reviewers. Then, a fuzzy k-means clustering algorithm is used to find the group that they belong to. A case study that suggests which group an incorrect review belongs to is provided to further understand the new method.
Tian, J, Liu, R-P & Lin, S-J 1970, 'A Markov Chain Analysis Model of IEEE 802.11p', Proceedings of the 2017 International Conference on Wireless Communications, Networking and Applications, WCNA 2017: 2017 International Conference on Wireless Communications, Networking and Applications, ACM, Shenzhen, China, pp. 1-5.
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© 2017 Association for Computing Machinery. Quality of Service (QoS) is a critical issue for the broadcast scheme of IEEE 802.11p systems in Vehicular Ad hoc Networks (VANETs)1. We present a 3-dimensional (3-D) Markov chain model to accurately solve for the broadcast scheme of 802.11p systems. The 3th dimension models remaining frozen time in the deferring period. The 3-D model solutions are validated by key simulations. Our analyses reveal that the lack of retransmission in the 802.11p system results in poor QoS performance during heavy traffic load, particularly for large VANETs.
Toan, TT, Elbadawi, C, Totonjian, D, Lobo, CJ, Grosso, G, Moon, H, Englund, DR, Ford, MJ, Aharonovich, I & Toth, M 1970, 'Robust Multicolor Single Photon Emission from Point Defects in Hexagonal Boron Nitride', 2017 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), Conference on Lasers and Electro-Optics (CLEO), IEEE, CA, San Jose.
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We demonstrates engineering of quantum emitters in hBN multi-layers using either electron beam irradiation or annealing. The defects exhibit a broad range of multicolor room-temperature single photon emissions across the visible and the near-infrared ranges.
Tonkin, M, Vitale, J, Ojha, S, Clark, J, Pfeiffer, S, Judge, W, Wang, X & Williams, M-A 1970, 'Embodiment, Privacy and Social Robots: May I Remember You?', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Social Robotics, Springer International Publishing, Tsukuba, Japan, pp. 506-515.
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© 2017, Springer International Publishing AG. As social robots move from the laboratory into public settings the possibility of unwanted intrusion into a user’s personal privacy is magnified. The actual social interaction between human and robot may involve anthropomorphising of the robot by the user, and this may prompt the user to disclose private or sensitive information. To comprehend possible impacts we conducted an exploratory study with a novel privacy measure to understand changes to users’ privacy considerations when interacting with an embodied robotic system vs a disembodied system. In this paper we measure the difference in personal information provided to such systems, and discuss the idea that embodiment may increase users’ risk tolerance and reduce their privacy concerns.
Tonkin, M, Vitale, J, Ojha, S, Williams, M-A, Fuller, P, Judge, W & Wang, X 1970, 'Would you like to sample? Robot engagement in a shopping centre', 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), IEEE, Lisbon, Portugal, pp. 42-49.
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© 2017 IEEE. Nowadays, robots are gradually appearing in public spaces such as libraries, train stations, airports and shopping centres. Only a limited percentage of research literature explores robot applications in public spaces. Studying robot applications in the wild is particularly important for designing commercially viable applications able to meet a specific goal. Therefore, in this paper we conduct an experiment to test a robot application in a shopping centre, aiming to provide results relevant for today's technological capability and market. We compared the performance of a robot and a human in promoting food samples in a shopping centre, a well known commercial application, and then analysed the effects of the type of engagement used to achieve this goal. Our results show that the robot is able to engage customers similarly to a human as expected. However unexpectedly, while an actively engaging human was able to perform better than a passively engaging human, we found the opposite effect for the robot. In this paper we investigate this phenomenon, with possible explanation ready to be explored and tested in subsequent research.
Trad, JJ, Zeb, BA, Esselle, KP & Afzal, MU 1970, 'Preliminary investigations into a simple and effective rectenna for RF energy harvesting', 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, San Diego, CA, pp. 1095-1096.
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Trivedi, IN, Gandomi, AH, Jangir, P & Jangir, N 1970, 'Study of Different Boundary Constraint Handling Schemes in Interior Search Algorithm', ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2016, International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES), Springer Singapore, SRM Univ, Chennai, INDIA, pp. 547-564.
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Trivedi, IN, Gandomi, AH, Jangir, P, Kumar, A, Jangir, N & Totlani, R 1970, 'Adaptive Krill Herd Algorithm for Global Numerical Optimization', Advances in Intelligent Systems and Computing, Springer Singapore, pp. 517-525.
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© Springer Nature Singapore Pte Ltd. 2017. A recent bio-inspired optimization algorithm, that is, based on the Lagrangian and evolutionary behavior of krill individuals in nature is called the Krill Herd (KH) Algorithm. Randomization has a key role in both exploration and exploitation of a problem using KH algorithm. A new randomization technique termed adaptive technique is integrated with Krill Herd algorithm and tested on several global numerical functions. The KH uses Lagrangian movement which includes induced movement, random diffusion, and foraging motion, and therefore, it covers a vast area in the exploration phase. And then adding the powerful adaptive randomization technique potent the adaptive KH (AKH) algorithm to attain global optimal solution with faster convergence as well as less parameter dependency. The proposed AKH outperforms the standard KH in terms of both statistical results and best solution.
Tsai, W-C, Orth, D & van den Hoven, E 1970, 'Designing Memory Probes to Inform Dialogue', Proceedings of the 2017 Conference on Designing Interactive Systems, DIS '17: Designing Interactive Systems Conference 2017, ACM, Edinburgh, United Kingdom, pp. 889-901.
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To investigate the phenomenon that occurs during
interactions between used objects and autobiographical
memories, which are both ever-changing and imbedded
with personal significance, an adapted probing method
capable of managing these complex qualities is
needed. This pictorial is our attempt to find a nuanced
indication of how probes could go beyond common
usage to facilitate complex felt experience, and how
probes can be used in less prescriptive ways to instead
promote reminiscent dialogues that are rich and open to
interpretation for both participants and researchers. It
illustrates our exploration into potential Memory Probes
and how this might be done that reflects the value we
see in creating restrictions or limitations in technology mediated
interactions to encourage active participation
by users in social acts such as memory creation and
remembrance.
Tyack, A & Wyeth, P 1970, 'Adapting EPIC theatre principles for the design of games for learning', Proceedings of the 2017 DiGRA International Conference, DiGRA 2017.
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Educational games are primarily developed for use in formal education, which limits both their typical audience and the subject matter they may address. This paper presents recommendations for designing games for learning to be played outside the context of formal education, which explore the ways complex systems influence real human lives. Existing work from within the field and epic theatre principles form the basis for these guidelines. In this framework, the context of educational game play is considered alongside game content as essential to encouraging reflective play behaviour. Educational aims are made explicit throughout game involvement, and each aspect of the game directly contributes to stimulating reflection on the topics at hand. Complex subject matter — for example, the ways systems such as economics affect players in real life — may be fruitfully explored using this approach.
Tyack, A & Wyeth, P 1970, 'Exploring relatedness in single-player video game play', Proceedings of the 29th Australian Conference on Computer-Human Interaction, OzCHI '17: 29th Australian Conference on Human-Computer Interaction, ACM, pp. 422-427.
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Ulapane, N, Nguyen, L, Miro, JV, Alempijevic, A & Dissanayake, G 1970, 'Designing a pulsed eddy current sensing set-up for cast iron thickness assessment', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 901-906.
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© 2017 IEEE. Pulsed Eddy Current (PEC) sensors possess proven functionality in measuring ferromagnetic material thickness. However, most commercial PEC service providers as well as researchers have investigated and claim functionality of sensors on homogeneous structural steels (steel grade Q235 for example). In this paper, we present design steps for a PEC sensing set-up to measure thickness of cast iron, which is unlike steel, is a highly inhomogeneous and non-linear ferromagnetic material. The setup includes a PEC sensor, sensor excitation and reception circuits, and a unique signal processing method. The signal processing method yields a signal feature which behaves as a function of thickness. The signal feature has a desirable characteristic of being lowly influenced by lift-off. Experimental results show that the set-up is usable for Non-destructive Evaluation (NDE) applications such as cast iron water pipe assessment.
Ullah, A, Lie, TT, Gunawardane, K & Nair, NKC 1970, 'Mitigation of residual flux for high-temperature superconductor (HTS) transformer by controlled switching of HTS breaker arc model', 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, pp. 1-6.
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Ullah, A, Lie, TT, Gunawardane, K & Nair, NKC 1970, 'Mitigation of Residual Flux for High-Temperature Superconductor (HTS) Transformer by Controlled Switching of HTS Breaker Arc Model', 2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 7th IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), IEEE, NEW ZEALAND, Univ Auckland, Auckland, pp. 820-825.
Ullah, A, Lie, TT, Gunawardane, K & Nair, NKC 1970, 'The improvement of Rate of Rise of Recovery Voltage (RRRV) for an HTS breaker', 2017 IEEE Manchester PowerTech, 2017 IEEE Manchester PowerTech, IEEE, pp. 1-6.
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Umair, A, Nanda, P & He, X 1970, 'Online Social Network Information Forensics: A Survey on Use of Various Tools and Determining How Cautious Facebook Users are?', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, Australia, pp. 1139-1144.
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© 2017 IEEE. Online Social Networks (OSN) such as Facebook, Twitter, LinkedIn, and Instagram are heavily used to socialize, entertain or gain insights on people behavior and their activities. Everyday terabytes of data is generated over these networks, which is then used by the businesses to generate revenue or misused by the wrongdoers to exploit vulnerabilities of these social network platforms. Specifically social network information helps in extracting various important features such as; user association, access pattern, location information etc. Recent research shows, many such features could be used to develop novel attack models and investigate further into defending the users from exposing their information to outsiders. This paper analyzes some of the available tools to extract OSN information and discusses research work on similar type of unstructured data. Recent research works, which focus on gathering bits and pieces of information to extract meaningful results for digital forensics, has been discussed. An online survey is conducted to gauge the cautiousness of users in social media usage in terms of personal information dissemination.
Unicomb, J, Dantanarayana, L, Arukgoda, J, Ranasinghe, R, Dissanayake, G & Furukawa, T 1970, 'Distance function based 6DOF localization for unmanned aerial vehicles in GPS denied environments.', IROS, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vancouver, BC, Canada, pp. 5292-5297.
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© 2017 IEEE. This paper presents an algorithm for localizing an unmanned aerial vehicle (UAV) in GPS denied environments. Localization is performed with respect to a pre-built map of the environment represented using the distance function of a binary mosaic, avoiding the need for extraction and explicit matching of visual features. Edges extracted from images acquired by an on-board camera are projected to the map to compute an error metric that indicates the misalignment between the predicted and true pose of the UAV. A constrained extended Kalman filter (EKF) framework is used to generate an estimate of the full 6-DOF location of the UAV by enforcing the condition that the distance function values are zero when there is no misalignment. Use of an EKF also makes it possible to seamlessly incorporate information from any other system on the UAV, for example, from its auto-pilot, a height sensor or an optical flow sensor. Experiments using a hexarotor UAV both in a simulation environment and in the field are presented to demonstrate the effectiveness of the proposed algorithm.
Vaghjiani, K, Oppermann, I, Moon, J, Rogers, E & Stacey, H 1970, 'A case study of lean data driven innovation in government', Proceedings of the 5th International Conference on Innovation and Entrepreneurship, ICIE 2017, pp. 170-177.
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The New South Wales Data Analytics Centre (NSW DAC) was set up by the NSW Government to explore government-based data innovation projects addressing key opportunities within Australia's largest state by economic and Gross Domestic Product (GDP) size according to the Nicholls and Rosewell (2015) from the Reserve Bank of Australia (RBA). The specific charter of the DAC was to explore 'wicked problems' that cross interdepartmental boundaries using evidence or data-based decision making. Wicked challenges are ill-defined (Rittel and Webber, 1984), subtle and ultimately have people's behaviour at their core. They manifest across multiple agencies and are a challenge for all governments in all jurisdictions, complex, intractable, open-ended and very different in nature to routine problems (Head, 2008) Core to this paper is exploring the challenge of providing better services to the citizens of NSW using data driven approaches. This is achieved through lean methodology: an approach that so far appears to be a unique combination of the use of data analytics and science to solve complex, citizen-centric service challenges. A world first, the DAC has so far been assigned twenty-five complex, multi-layered projects covering fields such as human services, transport, industry, health justice and community services to highlight the importance and the value of unlocking data assets. Further, the Lean Approach has been used to define, challenge, and scope projects to better understand, communicate and deliver outcomes - very likely another world first. Providing unique insight into innovation within government structure in a space that has never been traversed before; our research is an ongoing exploration of work undertaken by the NSW DAC in high impact, high agility areas. Through exploring learning gained from a number of projects, following our adapted model for innovation, we will detail the process of engaging, ideating and executing high impact projects with big...
Venemyr, GO, Bakken, BT, Kionig, L, Ranglund, OJS, Holen, S, Haave, H, Vold, T & Braun, R 1970, 'Flipped gaming for enhanced learning outcome crisis preparedness courses', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology-Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-4.
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© 2017 IEEE. Preparing for crisis and incidents have gained an increased focus, also within the educational system. At The Inland University of Applied Sciences, Campus Rena, in Norway, a Bachelor study is developed to cater for the increased need for educating staff not only in municipalities, but also in private organizations. Regulations and governmental instructions have also created a void between staff that can and know how to handle crisis and staff that need to know how to handle crisis. In addition, the preparedness issue, in order to avoid crisis, has received a lot of attention. The study has until recently been a mix of ordinary classroom education and exercises, both live and table top exercises, both which is costly and time consuming both in planning and execution. Two years ago, some faculty staff and a small group of students started to look into using games for educational purposes. Some of the games were free ware and downloadable from the internet, another game was developed by Bohemia Interactive Simulations (https://bisimulations.com/). Combining using MeTracker (http://www.concorde-project.eu/index.php/results/developments/the-training-tools/1-metracker) for organizing the work during a training process, and the developed game, this has proved to be a powerful tool for learning about how to be prepared for and handle crisis. Even if the initial costs for development and licenses have been somewhat substantial, the tools will provide the students with a unique possibility of simulating crisis in a higher volume than what is possible using live exercises. So far, the faculty staff has developed the scenarios for the students to play. The change from this is now to use a game based environment to play scenarios developed by the students themselves. The students that have tested this is in the third year of their study and the preliminary feedback from the students on this approach has been positive. The paper presents the results fro...
Venkata, SK, Keppens, J & Musial, K 1970, 'Adaptive Caching Using Sub-query Fragmentation for Reduction in Data Transfers from Distributed Databases', ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XXV, 25th Annual Conference on Astronomical Data Analysis Software and Systems (ADASS XXV), ASTRONOMICAL SOC PACIFIC, ARC Ctr Excellence All Sky Astrophys (CAASTRO), Sydney, AUSTRALIA, pp. 85-88.
Verma, S, Liu, W, Wang, C & Zhu, L 1970, 'Extracting highly effective features for supervised learning via simultaneous tensor factorization', 31st AAAI Conference on Artificial Intelligence, AAAI 2017, AAAI Conference on Artificial Intelligence, AAAI, San Francisco, USA, pp. 4995-4996.
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Real world data is usually generated over multiple time periods associated with multiple labels, which can be represented as multiple labeled tensor sequences. These sequences are linked together, sharing some common features while exhibiting their own unique features. Conventional tensor factorization techniques are limited to extract either common or unique features, but not both simultaneously. However, both types of these features are important in many machine learning systems as they inherently affect the systems' performance. In this paper, we propose a novel supervised tensor factorization technique which simultaneously extracts ordered common and unique features. Classification results using features extracted by our method on CIFAR-10 database achieves significantly better performance over other factorization methods, illustrating the effectiveness of the proposed technique.
Vitale, J, Johnston, B & Williams, MA 1970, 'Facial Motor Information is Sufficient for Identity Recognition', CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, The 39th Annual Meeting of the Cognitive Science Society, Cognitive Science Society, London, pp. 3447-3452.
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The face is a central communication channel providing information about the identities of our interaction partners and their potential mental states expressed by motor configurations. Although it is well known that infants ability to recognise people follows a developmental process, it is still an open question how face identity recognition skills can develop and, in particular, how facial expression and identity processing potentially interact during this developmental process. We propose that by acquiring information of the facial motor configuration observed from face stimuli encountered throughout development would be sufficient to develop a face-space representation. This representation encodes the observed face stimuli as points of a multidimensional psychological space able to assist facial identity and expression recognition. We validate our hypothesis through computational simulations and we suggest potential implications of this understanding with respect to the available findings in face processing.
Vizcarra, G, Casagrande, M & Nimbalkar, S 1970, 'DEM Three-dimensional modeling of triaxial testing on railway ballast', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1443-1446.
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This article presents the results of numerical simulations of cyclic loading tests conducted on particles that simulate railroad ballast. The objective of this study was to evaluate the deformation of ballast under a large number of loading cycles and to study the influence of the two different particle size distributions. One of them was according to particle size distribution recommended by Indraratna and co-workers in the past as an improvement to Australian Standard and the other was prepared in accordance with Brazilian standard. The discrete element method offers a new means of studying the response characteristics of railway ballast. The basic idea of discrete element method (DEM) is that arbitrary discontinuities are divided into a set of rigid elements, making each rigid element satisfy the equations of motion, use time step iteration method for solving the equations of motion of rigid elements, and then obtain the overall movement patterns of arbitrary discontinuities. In this study, the discrete element method of analysis has been used to simulate the geotechnical behaviour of railway ballast observed during the testing.
Vo, BT, Nguyen, HH & Tuan, HD 1970, 'Constellation Design for Quadrature Spatial Modulation', 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), IEEE, Toronto, ON, Canada, pp. 1-5.
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© 2017 IEEE. This paper considers constellation design for quadrature spatial modulation (QSM) to minimize the average probability of error. Different than the constellation design previously obtained for spatial modulation (SM), it is shown that, the error performance of QSM not only depends on the Euclidean distances between the amplitude-phase modulation (APM) symbols and the energies of APM symbols, but also on the in-phase and quadrature components of the QSM symbols. The analysis of the union bound of the average error probability reveals that at a very large number of transmit antennas, the optimal constellations for QSM converge to a quadrature phaseshift keying (QPSK) constellation. Simulation results demonstrate the performance superiority of the obtained constellations over the standard PSK and QAM constellations, as well as the constellations specifically designed for SM.
Vo, K, Nguyen, DN, Kha, HH & Dutkiewicz, E 1970, 'Real-time analysis on ensemble SVM scores to reduce P300-Speller intensification time', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Korea, pp. 4383-4386.
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© 2017 IEEE. In most Brain-Computer Interface systems, especially the P300-Speller, there must be a harmonized balance between the accuracy and the spelling time. One major drawback of the classical 36-choice P300-Speller is the slow rate of character elicitation. This paper aims to propose a real-time signal processing method to decrease the spelling time by exploiting the score margins of the ensemble Support Vector Machine classifiers during real-time P300-Speller flashes, rather than just getting the classifiers' highest scores. Our experiments were conducted on the dataset of the BCI Competition III and resulted in a successful character rate of over 96% with just approximately 15 to 20 seconds for each character spelling session. As compared with the fixed 31.5 seconds of the best original approach of the competition, our proposed method significantly reduces the required spelling time by over 30% while maintaining the desired classification accuracy.
Vo, K, Nguyen, DN, Kha, HH & Dutkiewicz, E 1970, 'Subject-Independent P300 BCI Using Ensemble Classifier, Dynamic Stopping and Adaptive Learning', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, pp. 1-7.
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Brain-computer interfaces (BCIs) are used to assist people, especially those with verbal or physical disabilities, communicate with the computer to indicate their selections, control a device or answer questions only by their mere thoughts. Due to the noisy nature of brain signals, the required time for each experimental session must be lengthened to reach satisfactory accuracy. This is the trade-off between the speed and the precision of a BCI system. In this paper, we propose a unified method which is the integration of ensemble classifier, dynamic stopping, and adaptive learning. We are able to both increase the accuracy, as well as to reduce the spelling time of the P300-Speller. Another merit of our study is that it does not require the training phase for any new subject, hence eliminates the extensively time-consuming process for learning purposes. Experimental results show that we achieve the averaged bit rate boost up of 182% on 15 subjects. Our best achieved accuracy is 95.95% by using 7.49 flashing iterations and our best achieved bit rate is 40.87 bits/min with 83.99% accuracy and 3.64 iterations. To the best of our knowledge, these results outperformed most of the related P300-based BCI studies.
Vo, NNY & Xu, G 1970, 'The volatility of Bitcoin returns and its correlation to financial markets', 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), IEEE, Krakow, Poland, pp. 1-6.
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The 2008 financial crisis had scattered incredulity around the globe regarding traditional financial systems, which made investors and non-financial customers turn to other alternative such as digital banking systems. The existence and development of blockchain technology make cryptocurrency in recent years believably become a complete alternative to traditional ones. Bitcoin is the world's first peer-to-peer and decentralized digital cash system initiated by Nakamoto [1]. Though being the most prominent cryptocurrency, Bitcoin has not been a legal trading currency in various countries. Its exchange rate has appeared to be an exceptionally high-risk portfolio with extreme volatility, which requires a more detailed evaluation before making any decision. This paper utilizes knowledge of statistics for financial time series and machine learning to (i) fit the parametric distribution and (ii) model and forecast the volatility of Bitcoin returns, and (iii) analyze its correlation to other financial market indicators. The fitted parametric time series model significantly outperforms other standard models in explaining the stylized facts and statistical variances in the behavior of Bitcoin returns. The model forecast also outperforms some machine learning methodologies, which would benefit policy makers, banks and financial investors in trading activities for both long-term and short-term strategies.
Vold, T, Bergum, S, Ranglund, OJS, Kionig, L, Bakken, G, Kaloudis, A & Braun, R 1970, 'Student input — A case of an extended flipped classroom', 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Ohrid, Macedonia, pp. 1-6.
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© 2017 IEEE. The idea from Socrates about the knowledge being a part of the students' knowledge base or ability of combining accessible knowledge forms the backdrop for how the most recent course in Knowledge Management (spring of 2017) was conducted. The course is 7,5 ECTS and the students are primarily adults in a worklife. The course is net and seminar based, with three seminars per semester. During the seminars the concept of Flipped Classroom is used. This means that the students are provided with a recorded lecture in beforehand and only highlights are presented. The rest of the time during the seminar is used to activate the students through tasks and problem solving. However, the tasks are not predefined and prefabricated. The way this course is structured, the students themselves are giving the input to the tasks and assignments. This is based on the idea that the students themselves, coming from a worklife where knowledge management is a part of their every day worklife, should reflect upon their own practice. Also, it is important to share knowledge and by utilizing each students own experiences it is possible to enrich the 'database' of cases or tasks for the students to solve and work with in order to incorporate the new theory from the course curriculum. Basing the problem solving on student input provide the lecturer AND the students with a richer knowledge base and case portfolio. This does, however, require some effort from the lecturers side. The input from the students are generally key words and fragments. The session is facilitated by the lecturer, encouraging the students to bring forward own experiences or situations they would like resolved, either real or fiction. The key words and fragments are discussed amongst the students and the lecturer makes notes on a blackboard or on a digital canvas (MS PowerPoint or similar). The students are given a break and the lecturer collects the key words and synthesizes this into a case. Upon ...
Vu, H, Cheng, E, Wilkinson, R & Lech, M 1970, 'On the use of convolutional neural networks for graphical model-based human pose estimation', 2017 International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), 2017 International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), IEEE, Da Nang, Vietnam, pp. 88-93.
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© 2017 IEEE. The recent application of Convolutional Neural Networks (CNNs) to Human Pose Estimation (HPE) from static images have improved estimation accuracy compared to traditional HPE approaches. In particular, a recent novel HPE approach combines a traditional graphical model with CNNs to result in state-of-the-art HPE accuracy, improving the estimation accuracy compared to using either approach alone. However, the accuracy of the CNN used in the hybrid model has not yet been explored, and this paper evaluates the use of CNNs in the hybrid model through investigating different network configurations and fine-tuning the network using pre-trained weights obtained from a large labeled dataset. The proposed CNN configurations not only improve the accuracy of the existing network by up to 2% but also uses fewer parameters, resulting in a higher HPE accuracy and simpler network structure.
Vu, HT, Wilkinson, RH, Lech, M & Cheng, E 1970, 'A Comparison between Anatomy-Based and Data-Driven Tree Models for Human Pose Estimation', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, NSW, Australia, pp. 1-7.
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© 2017 IEEE. Tree structures are commonly used to model relationships between body parts for articulated Human Pose Estimation (HPE). Tree structures can be used to model relationships among feature maps of joints in a structured learning framework using Convolutional Neural Networks (CNNs). This paper proposes new data-driven tree models for HPE. The data-driven tree structures were obtained using the Chow-Liu Recursive Grouping (CLRG) algorithm, representing the joint distribution of human body joints and tested using the Leeds Sports Pose (LSP) dataset. The paper analyzes the effect of the variation of the number of nodes on the accuracy of the HPE. Experimental results showed that the data-driven tree model obtained 1% higher HPE accuracy compared to the traditional anatomy-based model. A further improvement of 0.5% was obtained by optimizing the number of nodes in the traditional anatomy-based model.
Wang, C, Pan, S, Long, G, Zhu, X & Jiang, J 1970, 'MGAE', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, ACM, pp. 889-898.
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© 2017 ACM. Graph clustering aims to discover community structures in networks, the task being fundamentally challenging mainly because the topology structure and the content of the graphs are dicult to represent for clustering analysis. Recently, graph clustering has moved from traditional shallow methods to deep learning approaches, thanks to the unique feature representation learning capability of deep learning. However, existing deep approaches for graph clustering can only exploit the structure information, while ignoring the content information associated with the nodes in a graph. In this paper, we propose a novel marginalized graph autoencoder (MGAE) algorithm for graph clustering. The key innovation of MGAE is that it advances the autoencoder to the graph domain, so graph representation learning can be carried out not only in a purely unsupervised se.ing by leveraging structure and content information, it can also be stacked in a deep fashion to learn effective representation. From a technical viewpoint, we propose a marginalized graph convolutional network to corrupt network node content, allowing node content to interact with network features, and marginalizes the corrupted features in a graph autoencoder context to learn graph feature representations. The learned features are fed into the spectral clustering algorithm for graph clustering. Experimental results on benchmark datasets demonstrate the superior performance of MGAE, compared to numerous baselines.
Wang, D, Xu, G & Deng, S 1970, 'Music recommendation via heterogeneous information graph embedding', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, Alaska, USA, pp. 596-603.
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© 2017 IEEE. Traditional music recommendation techniques suffer from limited performance due to the sparsity of user-music interaction data, which is addressed by incorporating auxiliary information. In this paper, we study the problem of personalized music recommendation that takes different kinds of auxiliary information into consideration. To achieve this goal, a Heterogeneous Information Graph (HIG) is first constructed to encode different kinds of heterogeneous information, including the interactions between users and music pieces, music playing sequences, and the metadata of music pieces. Based on HIG, a Heterogeneous Information Graph Embedding method (HIGE) is proposed to learn the latent low-dimensional representations of music pieces. Then, we further develop a context-aware music recommendation method. Extensive experiments have been conducted on real-world datasets to compare the proposed method with other state-of-the-art recommendation methods. The results demonstrate that the proposed method significantly outperforms those baselines, especially on sparse datasets.
Wang, G, Zhang, G, Choi, K-S, Lam, K-M & Lu, J 1970, 'An output-based knowledge transfer approach and its application in bladder cancer prediction', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 356-363.
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© 2017 IEEE. Many medical applications face a situation that the on-hand data cannot fully fit an existing predictive model or on-line tool, since these models or tools only use the most common predictors and the other valuable features collected in the current scenario are not considered altogether. On the other hand, the training data in the current scenario is not sufficient to learn a predictive model effectively yet. In order to overcome these problems and construct an efficient classifier, for these real situations in medical fields, in this work we present an approach based on the least squares support vector machine (LS-SVM), which utilizes a transfer learning framework to make maximum use of the data and guarantee its enhanced generalization capability. The proposed approach is capable of effectively learning a target domain with limited samples by relying on the probabilistic outputs from the other previously learned model using a heterogeneous method in the source domain. Moreover, it autonomously and quickly decides how much output knowledge to transfer from source domain to the target one using a fast leave-one-out cross validation strategy. This approach is applied on a real-world clinical dataset to predict 5-year mortality of bladder cancer patients after radical cystectomy, and the experimental results indicate that the proposed method can achieve better performances compared to traditional machine learning methods, consistently showing the potential of the proposed method under the circumstances with insufficient data.
Wang, H, Dutkiewicz, E, Jayawickrama, BA & Mueck, MD 1970, 'Design of Contour Based Protection Zones for Sublicensing in Spectrum Access Systems', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Spectrum Access System (SAS) allows incumbent military systems to share spectrum in a hierarchical manner with tier-2 Priority Access License (PAL) users and tier-3 General Authorized Access (GAA) users. FCC has recently allowed PAL owners to sublicense their channels. Therefore, when GAA channels are congested they can request a sublicense to access the PAL channel on a coordinated basis, which provides interference protection from other GAA users. In this paper, we propose a grid map to measure and monitor the secondary spectrum market for the purpose of spectrum trading with QoS guarantee. This work provides the subsequent spectrum trading models with a reasonable and dedicated interference graph for further optimization of spectrum allocation. Compared with traditional longterm spectrum licensing policy, short-term licensing makes the spectrum allocated effectively. We find the optimal resolution of the discrete grid map that maximizes the profit from sublicensing. Simulation results are provided to demonstrate how fine to grid the region and let the PAL owner achieve monetary benefit, in a given number of sensors.
Wang, H, Dutkiewicz, E, Jayawickrama, BA & Mueck, MD 1970, 'Detection of contour boundary for sublicensing in spectrum access systems', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-5.
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© 2017 IEEE. Associated to database and a local centralized system, the short-term spectrum sublicensing is one of the potential approaches to improve the spectrum efficiency in the 5G networks. If the sublicences are assigned to the heterogeneous base stations that are from different operators, the interference issue becomes challenging to tackle. In this paper, we propose a solution of contour boundary detection for sublicensing to coordinate the interference among heterogeneous base stations in the space domain. As the direct access points to sever the end users, the base stations know and even could predict the traffic requirements over their coverage areas. Therefore, we enable individual base station as a sublicensee based on self-reported protection contour and optimize the best allocation for the system to guarantee the interference-free operations among those who spatially use the same sublicense simultaneously. Considering the selfish behaviours of base stations, we employ the sensor networks to monitor and measure their contours. Then we estimate the contour boundary by detecting the inner and outer contour boundary. Finally we compare the estimation accuracies of different sensor networks and demonstrate an interference-free allocation for the sublicensees.
Wang, H, Dutkiewicz, E, Nguyen, D & Mueck, MD 1970, 'Game theoretic analysis of sublicensing for PAL and GAA bands in spectrum access system', 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), IEEE, Montreal, QC, Canada, pp. 1-5.
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© 2017 IEEE. Motivated by recent efforts in enabling economic models for spectrum sharing systems, in particular, for the Spectrum Access System in the US, we propose a game theoretic analysis of sublicensing between two types of access methods in such system - PAL and GAA. The aim of this paper is to illustrate how the operators' strategies affect their own payoffs and the overall utility in the Sublicenseing Game in a spectrum sharing system. We consider the problem of spectrum sharing among multiple operators who have to pay for a temporary PAL sublicense with the exclusive right to the PAL band or stay in the GAA band and share the spectrum for free with other GAA users. We first formulate this scenario as a non-cooperative game, and then study the existence of a Nash equilibrium. Finally, to reduce the overall utility loss we let the spectrum sharing platform to coordinate individual operators by forming pair coalitions for them. According to our findings, when an operator has a large number of subscribers GAA band is the best response and a high PAL sublicense price holds back operators to access the PAL band. Additionally, making equal coalitions among operators can avoid overall utility loss.
Wang, J, Huang, S, Zhao, L, Ge, J, He, S, Zhang, C & Wang, X 1970, 'High quality 3D reconstruction of indoor environments using RGB-D sensors', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1739-1744.
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© 2017 IEEE. High-quality 3D reconstruction of large-scale indoor scene is the key to combine Simultaneous Localization And Mapping (SLAM) with other applications, such as building inspection and construction monitoring. However, the requirement of global consistency brings challenges to both localization and mapping. In particular, significant localization and mapping error can happen when standard SLAM techniques are used when dealing with the area of featureless walls and roofs. This paper proposed a novel framework aiming to reconstruct a high-quality, globally consistent 3D model for indoor environments using only a RGB-D sensor. We first introduce the sparse and dense feature constraints in the local bundle adjustment. Then, the planar constraints are incorporated in the global bundle adjustment. We fuse the point clouds in a truncated signed distance function volume, from which the high quality mesh can be extracted. Our framework leads to a comprehensive 3D scanning solution for indoor scene, enabling high-quality results and potential applications in building information system. The video of 3D models reconstructed by the method proposed in this paper is available at https://youtu.be/DWMP4YfeNeY.
Wang, J, Huang, S, Zhao, L, Ge, J, He, S, Zhang, C & Wang, X 1970, 'High Quality 3D Reconstruction of Indoor Finvironments using RGB-D Sensors', PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, CAMBODIA, Siem Reap, pp. 1739-1744.
Wang, J, Jiang, C, Ni, Z, Guan, S, Yu, S & Ren, Y 1970, 'Reliability of Cloud Controlled Multi-UAV Systems for On-Demand Services', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - 2017 IEEE Global Communications Conference, IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. Unmanned Aerial Vehicle (UAV) technology has been widely applied in both military and civilian applications. With the increasing complexity of application scenarios, the coordination of multiple UAVs has become a hot topic. However, the limited capability of UAVs make it hard to achieve stable and reliable control. Considering this practical problem, we propose a cloud-based UAV system. It extricates the computing and data storage from UAVs and utilizes the cloud to process the sensor data and to maintain the stable operation of multi-UAV systems. Firstly, we analyze the cloud-based system's on-demand service ability and its impact on UAVs' control procedure. Secondly, we propose a UAV cloud control system (CCS) which serves as a network control system. Moreover, the stable condition of the UAV cloud control system is derived. It reveals the relationship between the acquisition rate of sensor data and the stability of the cloud-based UAV system. Finally, simulations are conducted to verify the effectiveness of previous theoretical analysis.
Wang, JJ, Gowripalan, N, Li, J & Nguyen, VV 1970, 'Close-range photogrammetry for accurate deformation distribution measurement', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, Taylor and Francis, Perth, Australia, pp. 793-799.
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This paper introduces a methodology for improving the accuracy of Deformation Distribution Measurement (DDM) using close-range photogrammetry. After reviewing various algorithms for 2D Digital Image Correlation (DIC), Zero-Normalized Cross-Correlation (ZNCC) is selected for deformation measurement. The impact of several other factors on DIC measurement accuracy has been investigated, including the type of imaging sensors, the contrast and pattern of a specimen, and searching window size. Optimal option of these factors is proposed. The technique is utilized in the experiment of applying static loading on a replica of a concrete structural component used for Sydney Harbour Bridge. Test results presented in the paper include DIC measurements and validation data from conventional sensors.
Wang, L, Mao, Q & Tsang, I 1970, 'Latent Smooth Skeleton Embedding', Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, pp. 2703-2709.
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Learning a smooth skeleton in a low-dimensional space from noisy data becomes important in computer vision and computational biology. Existing methods assume that the manifold constructed from the data is smooth, but they lack the ability to model skeleton structures from noisy data. To overcome this issue, we propose a novel probabilistic structured learning model to learn the density of latent embedding given high-dimensional data and its neighborhood graph. The embedded points that form a smooth skeleton structure are obtained by maximum a posteriori (MAP) estimation. Our analysis shows that the resulting similarity matrix is sparse and unique, and its associated kernel has eigenvalues that follow a power law distribution, which leads to the embeddings of a smooth skeleton. The model is extended to learn a sparse similarity matrix when the graph structure is unknown. Extensive experiments demonstrate the effectiveness of the proposed methods on various datasets by comparing them with existing methods.
Wang, M, Su, D, Shi, L, Liu, Y & Miro, JV 1970, 'Real-time 3D Human Tracking for Mobile Robots with Multisensors', Proceedings - IEEE International Conference on Robotics and Automation, pp. 5081-5087.
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Acquiring the accurate 3-D position of a target person around a robotprovides fundamental and valuable information that is applicable to a widerange of robotic tasks, including home service, navigation and entertainment.This paper presents a real-time robotic 3-D human tracking system whichcombines a monocular camera with an ultrasonic sensor by the extended Kalmanfilter (EKF). The proposed system consists of three sub-modules: monocularcamera sensor tracking model, ultrasonic sensor tracking model and multi-sensorfusion. An improved visual tracking algorithm is presented to provide partiallocation estimation (2-D). The algorithm is designed to overcome severeocclusions, scale variation, target missing and achieve robust re-detection.The scale accuracy is further enhanced by the estimated 3-D information. Anultrasonic sensor array is employed to provide the range information from thetarget person to the robot and Gaussian Process Regression is used for partiallocation estimation (2-D). EKF is adopted to sequentially process multiple,heterogeneous measurements arriving in an asynchronous order from the visionsensor and the ultrasonic sensor separately. In the experiments, the proposedtracking system is tested in both simulation platform and actual mobile robotfor various indoor and outdoor scenes. The experimental results show thesuperior performance of the 3-D tracking system in terms of both the accuracyand robustness.
Wang, S, Hu, L & Cao, L 1970, 'Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Springer International Publishing, Skopje, Macedonia, pp. 285-302.
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© 2017, Springer International Publishing AG. To predict customer’s next choice in the context of what he/she has bought in a session is interesting and critical in the transaction domain especially for online shopping. Precise prediction leads to high quality recommendations and thus high benefit. Such kind of recommendation is usually formalized as transaction-based recommender systems (TBRS). Existing TBRS either tend to recommend popular items while ignore infrequent and newly-released ones (e.g., pattern-based RS) or assume a rigid order between items within a transaction (e.g., Markov Chain-based RS) which does not satisfy real-world cases in most time. In this paper, we propose a neural network-based comprehensive transaction embedding model (NTEM) which can effectively perceive the next choice in a transaction context. Specifically, we learn these comprehensive embeddings of both items and their features from relaxed ordered transactions. The relevance between items revealed by the transactions is encoded into such embeddings. With rich information embedded, such embeddings are powerful to predict the next choices given those already bought items. NTEM is a shallow wide-in-wide-out network, which is more efficient than deep networks considering large numbers of items and transactions. Experimental results on real-world datasets show that NTEM outperforms three typical TBRS models FPMC, PRME and GRU4Rec in terms of recommendation accuracy and novelty. Our implementation is available at https://github.com/shoujin88/NTEM-model.
Wang, S, Nerse, C & Kim, HW 1970, 'Vibro-Acoustic Noise Analysis of a Washing Machine', Conference Proceedings of the Society for Experimental Mechanics Series, 35th IMAC Conference and Exposition on Structural Dynamics, Springer International Publishing, Garden Grove, CA, pp. 47-53.
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This study is a comprehensive effort in analyzing the vibro-acoustic characteristics of a top loaded washing machine, and focuses on the identification of the main noise source. For this purpose, the vibro-acoustic behaviors of components in washing machine are investigated systematically. Modal analysis of the main components in the system (cabinet, tub, and motor) are performed for identification of vibration modes that are related to noise radiation. The cogging torque that is associated with the brushless DC motor is identified with the order analysis. The critical frequency bands are determined with respect to components, and preliminary investigation for the noise source identification is concluded. For a quantitative ranking of contributions from several components to output noise during operation of the washing machine, Operational Transfer Path Analysis method is used. The vibration and acoustic response are measured in a relation to stepwise control of the operation speed of the BLDC motor. Transmissibility functions with respect to transfer paths are calculated, and cross-talk cancellation is applied using principal component analysis. The evaluated synthesized response matched well with the measured noise output through all measurement steps.
Wang, TQ & Huang, X 1970, 'Dimming Compatible Optical OFDM for High Speed Visible Light Communications', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-6.
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© 2017 IEEE. In this paper, we study a novel optical orthogonal frequency division multiplexing (OFDM) scheme, fractional reversed polarity optical OFDM (FRPO- OFDM), which enables dimmable visible light communications. The scheme combines an asymmetrically clipped optical OFDM (ACO-OFDM) sequence with an information-carrying brightness control sequence (BCS). We show that the new scheme can create a wide range of brightness levels whilst transmitting extra information using the BCS to enhance the spectral efficiency. The detector which can recover information from both sequences is derived based on maximum likelihood (ML) detection and estimation. It is shown that the information carried by the BCS using variable on-off keying (VOOK) can be detected with extremely low bit error rate (BER) and that the resulting overall BER of FRPO-OFDM is constant over a wide dimming range.
Wang, W & Wu, C 1970, 'Numerical modelling of FRP-concrete-steel double-skin tubular columns under blast loading', Tubular Structures XVI - Proceedings of the 16th International Symposium on Tubular Structures, ISTS 2017, International Symposium on Tubular Structures, CRC Press, Melbourne, Australia,, pp. 387-393.
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© 2018 Taylor & Francis Group, London. This study presents a numerical study on the behavior of hybrid DSTCs under close-in blast loading. Numerical models of hybrid DSTCs were developed and validated. Afterwards, detailed numerical simulations were conducted to investigate the influences of different parameters on the behavior of hybrid DSTCs under blast loading. The mid-span deflection-time history were recorded and analyzed. The numerical simulation results indicate that the inner steel tube plays a key role in resisting the blast loading, while the contribution from outer FRP tube is less significant. Increasing the inner steel tube thickness and hollowness ratio can lead to a decrease of the maximum deflection of hybrid DSTCs. Under a lower axial load level, the maximum deflection will not increase with the increase of axial load. The influences of concrete strength and outer FRP tube thickness are insignificant.
Wang, X, Cheng, E & Burnett, IS 1970, 'Improved cell segmentation with adaptive bi-Gaussian mixture models for image contrast enhancement pre-processing', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 87-90.
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© 2017 IEEE. The accurate detection and segmentation of cells from time-lapse microscopic video sequences provides a critical foundation for understanding dynamic cell behaviours and cell characteristics when using automatic cell tracking systems. However, general object segmentation methods in computer vision are susceptible to errors due to the severe microscopic imaging conditions in time-lapse cell videos. To address the low image intensity contrast typical in cell images, this paper investigates the use of an adaptive, shifted bi-Gaussian mixture model to enhance the contrast prior to cell segmentation. Rather than using a model with fixed parameters across an entire video sequence as in existing approaches, this paper proposes the adaptive derivation of the mixture model parameters to match the intensity histogram for each video frame to adaptively address changes in the video background. Experimental results across a cell database show improved segmentation accuracy compared with existing image contrast enhancement methods. The pre-processed cell image exhibits greater differentiation between the cell foreground and background, whilst also maintaining the original intensity histogram features.
Wang, X, Cheng, E, Burnett, IS, Huang, Y & Wlodkowic, D 1970, 'Crowdsourced generation of annotated video datasets: A zebrafish larvae dataset for video segmentation and tracking evaluation', 2017 IEEE Life Sciences Conference (LSC), 2017 IEEE Life Sciences Conference (LSC), IEEE, Sydney, NSW, Australia, pp. 274-277.
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© 2017 IEEE. Video segmentation research has emerged over the last decade for biomedical image and video processing, especially in biological organism tracking. However, due to the difficulties in generating the video segmentation ground truth, the general lack of segmentation datasets with annotated ground-truth severely limits the evaluation of segmentation algorithms. This paper proposes an efficient and scalable crowdsourced approach to generate video segmentation ground-Truth to facilitate database generation for general biological organism segmentation and tracking algorithm evaluation. To illustrate the proposed approach, an annotated zebrafish larvae video segmentation dataset has been generated and made freely available online. To enable the evaluation of algorithms against a ground-Truth, a set of segmentation evaluation metrics are also presented. The segmentation performance of five leading segmentation algorithms is then evaluated by the metrics on the generated zebrafish video segmentation dataset.
Wang, Y, Dong, D & Petersen, IR 1970, 'An approximate quantum Hamiltonian identification algorithm using a Taylor expansion of the matrix exponential function', 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017 IEEE 56th Annual Conference on Decision and Control (CDC), IEEE, pp. 5523-5528.
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Wang, Y, He, Q, Ye, D & Yang, Y 1970, 'Formulating Criticality-Based Cost-Effective Monitoring Strategies for Multi-Tenant Service-Based Systems', 2017 IEEE International Conference on Web Services (ICWS), 2017 IEEE International Conference on Web Services (ICWS), IEEE, Honolulu, HI, pp. 325-332.
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Wang, Y, He, Q, Ye, D & Yang, Y 1970, 'Service Selection Based on Correlated QoS Requirements', 2017 IEEE International Conference on Services Computing (SCC), 2017 IEEE International Conference on Services Computing (SCC), IEEE, Honolulu, HI, pp. 241-248.
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Wang, Y, Yin, Q, Dong, D, Qi, B, Petersen, IR, Hou, Z, Yonezawa, H & Xiang, G-Y 1970, 'Efficient identification of unitary quantum processes', 2017 Australian and New Zealand Control Conference (ANZCC), 2017 Australian and New Zealand Control Conference (ANZCC), IEEE, pp. 196-201.
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Watterson, PA 1970, 'Electrical field generation by high speed rotation of a bipole magnet configuration for nerve activation', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, International Convention Centre, Sydney, Australia, pp. 1-6.
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A bipole magnet configuration comprising two cylindrical magnets with opposite magnetisation directions is rotated to high speed to create electric fields of high gradient in adjacent tissue, in order to activate nerves within the tissue. Theoretical and finite element calculations are presented for the electric field generated in a rectangular volume of conducting fluid, and a revised circuit model is given for the electric potential established inside nerve fibres within the fluid (or tissue)
Wazirali, R, Chaczko, Z & Chiang, E 1970, 'Steganographic Authentication in Cloud Storage for Mitigation of Security Risks', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 451-458.
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© 2017 IEEE. Identity theft is a serious crime where the criminals steal user's identity to access their bank accounts, personal hospital records and etc. The usage of cloud storage has allowed the hackers to attack the victims easily by accessing the victim's data stored in a remote location. Cloud storage may be convenient to allow users to store any data files and access those files from different devices and in different locations around the world. However, it can still pose security threats as with a lot of important data stored in one location is very appealing to cunning hackers. The solution of using image steganography application to hide important data or documents under an image before uploading them to the cloud storage will avoid the risks of attracting hackers or outsiders to discover the importance of the data hidden. The application uses one of simplest image steganography approach 'LSB algorithm' to achieve best quality of encoded image/stego-image. Besides, the application can be deployed via offline or online depending whether they want to upload the encoded image/stego-image to the cloud storage.
Wazirali, R, Chaczko, Z & Gibbon, J 1970, 'Steganographic Image Sharing App', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 494-499.
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© 2017 IEEE. With the advent of smartphones, many people have the ability to take a photo and upload it to the internet whenever they want. Most smartphones will include basic metadata in the image file; however, this is usually limited to information about the camera itself, and not the content of the photo. This data is also easy to access, as there are many websites and applications that will extract the metadata from an image, thus it is unsuitable for personal information. While there are many applications out there which will allow a user to take and upload photos for their friends or the public to view, such as Facebook or Instagram, these applications rely on information provided along side the image for privacy settings, commenting, and image searching. Other search engines would have difficulty categorising the pictures they find on various sites, and if the image is saved and re-uploaded somewhere else, the information about them would likely be lost. Steganography provides a feasible and viable solution to these problems. By embedding information directly into the image, the information about the image will not be lost, if it is separated from its original source. The aim of the capstone is to demonstrate this aspect via an image sharing app that allows users to exchange messages and personalised information that is embedded in the image such that it is inaccessible without knowing their keys, and metadata that can be used by search engines to categorise the image and its contents. The developed application will provide a platform for users to create an account, share images, embed information within the image, and search for images other users have uploaded.
Wegman-Ostrosky, T, Patidar, R, Sindiri, S, Shern, J, Hawkins, DS, Catchpoole, D, Wei, JS, Skapek, S, Khan, J & Stewart, DR 1970, 'Abstract 3003: Exome analysis of known hereditary cancer genes in 122 children with rhabdomyosarcoma', Cancer Research, American Association for Cancer Research (AACR), pp. 3003-3003.
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Abstract Introduction. Rhabdomyosarcoma (RMS) accounts for 5% of all pediatric cancer and is the most prevalent soft tissue tumor in childhood and adolescents. RMS is thought to arise from primitive mesenchymal stem cells directed towards myogenesis. Between 7-33% of RMS cases arise from a hereditary cancer syndrome, like LFS or NF1. We analyzed germline genetic variants in hereditary cancer genes in 122 children with RMS. Methodology. In 122 children with RMS and 1001 cancer-free adults, we examined germline exome data to determine the frequency of genetic variants in 51 cancer genes known to underlie syndromes associated with RMS. DNA was extracted from blood or buccal cells using standard methods. Exome enrichment was performed with NimbleGen SeqCap EZ Human Exome Library v3.0+UTR, on an Illumina HiSeq. Annotation of each exome variant was performed using a custom software pipeline. We evaluated all variants that passed quality controls with a population minor allele frequency (MAF) <0.1%. The cataloging of the variants was based on the ACMG classification as pathogenic (P), likely pathogenic (LP), or variable of unknown significance. Results We compared the age, gender, histologic type and localization of the primary RMS of the patients with and without P/LP variants in the 51 genes. In the patients without P/LP variants, the mean age of diagnosis was 5 years and the most frequent site of diagnosis was head and neck. In the group with P/LP variants, the mean age of diagnosis was 10 years, and the most frequent site was pelvis. In the 51 genes that were analyzed we found 9 P and 12 LP variants in 15 genes: TP53, ATM, MSH6, PMS, DICER1, FANCA, RECQL4, PTEN, WRN, RB1, BUB1B, RET, APC, FANCM and TSC2; genes with 2 variants include WRN, PTEN, BUB1B, FANCA and RET. Most of the variations were stopgain, foll...
Wen, D, Qin, L, Lin, X, Zhang, Y & Chang, L 1970, 'Enumerating k-Vertex Connected Components in Large Graphs.', CoRR, International Conference on Data Engineering, IEEE, Macao, Macao, pp. 52-63.
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In social network analysis, structural cohesion (or vertex connectivity) is a fundamental metric in measuring the cohesion of social groups. Given an undirected graph, a k-vertex connected component (k-VCC) is a maximal connected subgraph whose structural cohesion is at least k. A k-VCC has many outstanding structural properties, such as high cohesiveness, high robustness, and subgraph overlapping. In this paper, given a graph G and an integer k, we study the problem of computing all k-VCCs in G. The general idea for this problem is to recursively partition the graph into overlapped subgraphs. We prove the upper bound of the number of partitions, which implies the polynomial running time algorithm for the k-VCC enumeration. However, the basic solution is costly in computing the vertex cut. To improve the algorithmic efficiency, we observe that the key is reducing the number of local connectivity testings. We propose two effective optimization strategies, namely neighbor sweep and group sweep, to significantly reduce the number of local connectivity testings. We conduct extensive performance studies using ten large real datasets to demonstrate the efficiency of our proposed algorithms. The experimental results demonstrate that our approach can achieve a speedup of up to two orders of magnitude compared to the state-of-the-art algorithm.
Wilde, MM, Tomamichel, M & Berta, M 1970, 'A meta-converse for private communication over quantum channels', 2017 IEEE International Symposium on Information Theory (ISIT), 2017 IEEE International Symposium on Information Theory (ISIT), IEEE, Aachen, Germany, pp. 291-295.
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© 2017 IEEE. We establish a converse bounds on the private transmission capabilities of a quantum channel. The main conceptual development builds firmly on the notion of a private state, which is a powerful, uniquely quantum method for simplifying the tripartite picture of privacy involving local operations and public classical communication to a bipartite picture of quantum privacy involving local operations and classical communication. This approach has previously led to some of the strongest upper bounds on secret key rates, including the squashed entanglement and the relative entropy of entanglement. Here we use this approach along with a "privacy test" to establish a general meta-converse bound for private communication.
Williams, PT, Åbom, M, Kirby, R & Hill, J 1970, 'The influence of higher order incident modes on the performance of a hybrid reactive-dissipative splitter silencer', Proceedings of Meetings on Acoustics, 172nd Meeting of the Acoustical Society of America, Acoustical Society of America, Boston, Massachusetts, pp. 030012-030012.
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© 2017 Acoustical Society of America. A hybrid reactive-dissipative splitter silencer offers the potential to attenuate turbomachinery noise over a wide frequency range, including the problematic low to medium frequencies. This article uses a theoretical model to investigate the performance of a hybrid parallel baffle silencer for different complex incident sound fields. This includes an incident sound field with equal modal energy density, as well as the excitation of individual higher order modes. It is shown that provided horizontal and vertical partitions are used in the reactive element, the sound attenuation performance of the reactive chamber under complex incident sound fields is equivalent to that obtained using plane wave excitation over the frequency range of interest. Furthermore, it is demonstrated that the reactive elements work at frequencies above the first cut-on mode in the inlet duct, and so they are capable of extending sound attenuation into the low to medium frequency range. This delivers an efficient hybrid silencer design that is suitable for use in power generation applications, such as gas turbine exhaust systems.
Williams, PT, Kirby, R, Hill, J & Åbom, M 1970, 'Circular duct hybrid bar silencer insertion loss measurement with comparison to prediction', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet.
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Noise within the exhaust of gas turbine systems is commonly reduced using dissipative silencers. These types of silencers provide a high performance across the mid-frequency range but do little to reduce noise at the low frequencies. Reactive solutions are more effective at targeting low frequency noise, however these silencers must be designed without compromising restrictive pressure drop limitations while remaining operational in large diameter ducts and at high temperatures. A hybrid dissipative-reactive silencer is investigated here allowing for both the broadband and tonal low frequency noise to be reduced. The dissipative elements are regular, perforated baffles containing absorbent material and the reactive elements make use of quarter wave resonators. The hybrid design is applied to a circular duct bar silencer cross-section where the addition of the reactive component will have minimal effect on pressure drop. Insertion loss measurements are presented for a dissipative and hybrid silencer and it is found that the reactive elements increase insertion loss at the targeted frequency and at regular frequencies above this. Such increases in performance are found to persist outside of the duct's plane wave region. A two dimensional finite element model is also used to predict silencer transmission loss and this shows good agreement when compared to experimental data. This model may then be used to develop new bespoke hybrid silencer designs for demanding noise control applications.
Wong, S-W, Lin, J-Y, Guo, Z-C & Yang, Y 1970, 'Flexible control of tranmission zeros using doublet for cavity bandpass filter design', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-5.
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© 2017 IEEE. A variety of multiple-mode narrow-band bandpasss filer is designed, analyzed, and fabricated based on doublet and its properties. Three resonant modes: TE101, TE011 and TM110 modes in a single cavity are excited. The proposed filters use a microstrip line as a feeder then couple to a slot on one side of a single rectangular cavity. By rotating and offsetting two slots at the input port and output port of the rectangular cavity, three fundamental modes are implemented without any cross-coupling. The proposed structure also create two transmission zeros (TZs), by adjusting the positions of the two TZs near the passband, e.g., at lower or upper stopband, high rejection is achieved. Due to emergence of the three resonant modes and realization of a pair of TZs, a high attenuation and sharp filtering selectivity is achieved. Good agreement between measurement and simulation is achieved.
Wu, C & Li, J 1970, 'Structural protective design with innovative concrete material and retrofitting technology', 11th International Symposium on Plasticity and Impact Mechanics, 11th International Symposium on Plasticity and Impact Mechanics, New Delhi.
Wu, D, Sharma, N & Blumenstein, M 1970, 'Recent advances in video-based human action recognition using deep learning: A review', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, Alaska, USA, pp. 2865-2872.
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© 2017 IEEE. Video-based human action recognition has become one of the most popular research areas in the field of computer vision and pattern recognition in recent years. It has a wide variety of applications such as surveillance, robotics, health care, video searching and human-computer interaction. There are many challenges involved in human action recognition in videos, such as cluttered backgrounds, occlusions, viewpoint variation, execution rate, and camera motion. A large number of techniques have been proposed to address the challenges over the decades. Three different types of datasets namely, single viewpoint, multiple viewpoint and RGB-depth videos, are used for research. This paper presents a review of various state-of-the-art deep learning-based techniques proposed for human action recognition on the three types of datasets. In light of the growing popularity and the recent developments in video-based human action recognition, this review imparts details of current trends and potential directions for future work to assist researchers.
Wu, G, Liu, RP, Ni, W & Xu, P 1970, 'Modeling CCH Switch to SCH in IEEE 802.11p/WAVE Vehicular Networks', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Packet collision and packet delay are considered to be critical for safety applications in vehicular networks. This paper designs a new analytical model to evaluate the performance of channel switching for IEEE 802.11p/WAVE in vehicular networks. Under this model, it explicitly expresses the WAVE channel switching, and constructs contention window size and number of vehicles as packet collision probability and packet delay time function of variables. Finally, we evaluate accuracy of the designed model of collision caused by channel switching and transmission delay in vehicular networks. The results show that the model could analyzes perfectly packet collision which is caused by channel switching and packet delay in vehicular networks.
Wu, K, Li, X, Ranasinghe, R, Dissanayake, G & Liu, Y 1970, 'RISAS: A novel rotation, illumination, scale invariant appearance and shape feature', 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Singapore, Singapore, pp. 4008-4015.
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© 2017 IEEE. This paper presents a novel appearance and shape feature, RISAS, which is robust to viewpoint, illumination, scale and rotation variations. RISAS consists of a keypoint detector and a feature descriptor both of which utilise texture and geometric information present in the appearance and shape channels. A novel response function based on the surface normals is used in combination with the Harris corner detector for selecting keypoints in the scene. A strategy that uses the depth information for scale estimation and background elimination is proposed to select the neighbourhood around the keypoints in order to build precise invariant descriptors. Proposed descriptor relies on the ordering of both grayscale intensity and shape information in the neighbourhood. Comprehensive experiments which confirm the effectiveness of the proposed RGB-D feature when compared with CSHOT [1] and LOIND[2] are presented. Furthermore, we highlight the utility of incorporating texture and shape information in the design of both the detector and the descriptor by demonstrating the enhanced performance of CSHOT and LOIND when combined with RISAS detector.
Wu, R, Xu, G, Chen, E, Liu, Q & Ng, W 1970, 'Knowledge or Gaming?', Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion, the 26th International Conference, ACM Press, Perth, Western Australia, pp. 321-329.
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© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Recent decades have witnessed the rapid growth of intelligent tutoring systems (ITS), in which personalized adaptive techniques are successfully employed to improve the learning of each individual student. However, the problem of using cognitive analysis to distill the knowledge and gaming factor from students learning history is still underexplored. To this end, we propose a Knowledge Plus Gaming Response Model (KPGRM) based on multiple-attempt responses. Specifically, we first measure the explicit gaming factor in each multiple-attempt response. Next, we utilize collaborative filtering methods to infer the implicit gaming factor of one-attempt responses. Then we model student learning cognitively by considering both gaming and knowledge factors simultaneously based on a signal detection model. Extensive experiments on two real-world datasets prove that KPGRM can model student learning more effectively as well as obtain a more reasonable analysis.
Wu, S, Rizoiu, M-A & Xie, L 1970, 'Beyond Views: Measuring and Predicting Engagement in Online Videos', 12th International AAAI Conference on Web and Social Media, ICWSM 2018, International AAAI Conference on Web and Social Media, AAAI, Stanford, USA, pp. 434-443.
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The share of videos in the internet traffic has been growing, thereforeunderstanding how videos capture attention on a global scale is also of growingimportance. Most current research focus on modeling the number of views, but weargue that video engagement, or time spent watching is a more appropriatemeasure for resource allocation problems in attention, networking, andpromotion activities. In this paper, we present a first large-scale measurementof video-level aggregate engagement from publicly available data streams, on acollection of 5.3 million YouTube videos published over two months in 2016. Westudy a set of metrics including time and the average percentage of a videowatched. We define a new metric, relative engagement, that is calibratedagainst video properties and strongly correlate with recognized notions ofquality. Moreover, we find that engagement measures of a video are stable overtime, thus separating the concerns for modeling engagement and those forpopularity -- the latter is known to be unstable over time and driven byexternal promotions. We also find engagement metrics predictable from acold-start setup, having most of its variance explained by video context,topics and channel information -- R2=0.77. Our observations imply severalprospective uses of engagement metrics -- choosing engaging topics for videoproduction, or promoting engaging videos in recommender systems.
Wu, T, Fu, K, Zhu, J & Lei, G 1970, 'The influence analysis of thrust and gap magnetic field of a down-to-hole tubular permanent magnet linear hammer due to high temperature in deep hole', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Recently a novel electric hammer driven by tubular permanent magnet linear synchronous motor (TPMLSM) has arouse great interest among researchers in the field of deep drilling for its distinctive advantages compared with hydraulic and pneumatic hammers. The working temperature in deep down-hole is relatively high, so the research of the influence of high temperature in deep hole on the electromagnetic thrust of the linear motor is very important. In this paper, a numerical electromagnetic calculation model of the thrust of the hammer was established to analyze the influence as a result of the loss of permanent magnet, coil resistance variation and coil volume expansion due to the temperature variation from 20°C to 300°C. The calculated results showed from 20°C to 300°C, the increase of the copper loss reduced the thrust by 31%, the loss of permanent magnets reduced the thrust by 18%. And the effect of the air-gap variation by thermal expansion can be neglected.
Wu, W, Li, B, Chen, L & Zhang, C 1970, 'Consistent Weighted Sampling Made More Practical', Proceedings of the 26th International Conference on World Wide Web, WWW '17: 26th International World Wide Web Conference, International World Wide Web Conferences Steering Committee, Perth, Australia, pp. 1035-1043.
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© 2017 International World Wide Web Conference Committee (IW3C2) Min-Hash, which is widely used for efficiently estimating similarities of bag-of-words represented data, plays an increasingly important role in the era of big data. It has been extended to deal with real-value weighted sets – Improved Consistent Weighted Sampling (ICWS) is considered as the state-of-the-art for this problem. In this paper, we propose a Practical CWS (PCWS) algorithm. We first transform the original form of ICWS into an equivalent expression, based on which we find some interesting properties that inspire us to make the ICWS algorithm simpler and more efficient in both space and time complexities. PCWS is not only mathematically equivalent to ICWS and preserves the same theoretical properties, but also saves 20% memory footprint and substantial computational cost compared to ICWS. The experimental results on a number of real-world text data sets demonstrate that PCWS obtains the same (even better) classification and retrieval performance as ICWS with 1/5 ∼ 1/3 reduced empirical runtime.
Wu, W, Liu, R, Ni, W, Kaafar, D & Huang, X 1970, 'AC-PROT: An Access Control Model to Improve Software-Defined Networking Security', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. The logically-centralized controllers have largely operated as the coordination points in software-defined networking(SDN), through which applications submit network operations to manage the global network resource. Therefore, the validity of these network operations from SDN applications are critical for the security of SDN. In this paper, we analyze the mechanism that generates network operations in SDN, and present a fine-grained access control model, called Access Control Protector(AC-PROT),that employs an attribute-based signature scheme for network applications. The simulation result demonstrates that AC-PROT can efficiently identify and reject unauthorized network operations generated by applications.
Xia, H, Zhao, W, Zhou, Z, Jiang, F, Li, H & He, X 1970, 'Deformable Template Matching Using Proposal-Based Best-Buddies Similarity', 2017 IEEE Trustcom/BigDataSE/ICESS, 2017 IEEE Trustcom/BigDataSE/ICESS, IEEE, Sydney, pp. 517-521.
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© 2017 IEEE. We propose a new method for template matching based on the Best-Buddies Similarity (BBS) measure. Our method is able to match objects with large difference in size and hence achieves a deformable template matching. In addition, compared with the original method for template matching based on the BBS, our method significantly cuts down on the computation time. The fast and deformable template matching is implemented by measuring the BBS of only potential areas instead of all positions in an image. The potential areas, which can have different size from the given template, are found by a proposal generation based on edge priors and a selective search among the obtained proposals. The results from the experiments conduct-ed on a challenging dataset demonstrate that our method out-performs the state-of-the-art methods in terms of accuracy.
Xu, J, Wei, W & Cao, L 1970, 'Copula-Based High Dimensional Cross-Market Dependence Modeling', 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA), IEEE, Tokyo, Japan, pp. 734-743.
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© 2017 IEEE. Dependence across multiple financial markets, such as stock and foreign exchange rate markets, is high-dimensional, contains various relationships, and often presents complicated dependence structures and characteristics such as asymmetrical dependence. Modeling such dependence structures is very challenging. Although copula has been demonstrated to be effective in describing dependence between variables in recent studies, building effective dependence structures to address the above complexities significantly challenges existing copula models. In this paper, we propose a new D vine-based model with a bottom-up strategy to construct high-dimensional dependence structures. The new modeling outcomes are applied to trade 15 stock market indices and 10 currency rates over 16 years as a case study. Extensive experimental results show that this model and its intrinsic design significantly outperform typical models and industry baselines, as shown by the log-likelihood and Vuong test, and Value at Risk - a widely used industrial benchmark. Our model provides interpretable knowledge and profound insights into the high-dimensional dependence structures across data sources.
Xu, R, Fatahi, B & Li, D 1970, 'Effects of Soil Stiffness on Seismic Response of Buildings Considering Soil-Pile-Structure Interaction', The 19th International Conference on Soil Mechanics and Geotechnical Engineering, Seoul, Korea.
Xu, Y, Xu, C, Xu, C & Tao, D 1970, 'Multi-Positive and Unlabeled Learning', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 3182-3188.
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The positive and unlabeled (PU) learning problem focuses on learning a classifier from positive and unlabeled data. Some methods have been developed to solve the PU learning problem. However, they are often limited in practical applications, since only binary classes are involved and cannot easily be adapted to multi-class data. Here we propose a one-step method that directly enables multi-class model to be trained using the given input multi-class data and that predicts the label based on the model decision. Specifically, we construct different convex loss functions for labeled and unlabeled data to learn a discriminant function F. The theoretical analysis on the generalization error bound shows that it is no worse than k√k times of the fully supervised multi-class classification methods when the size of the data in k classes is of the same order. Finally, our experimental results demonstrate the significance and effectiveness of the proposed algorithm in synthetic and real-world datasets.
Xu, Z, Zhu, L & Yang, Y 1970, 'Few-Shot Object Recognition from Machine-Labeled Web Images', 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, pp. 5358-5366.
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Xue, X, Nie, F, Wang, S, Chang, X, Stantic, B & Yao, M 1970, 'Multi-View Correlated Feature Learning by Uncovering Shared Component', Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), San Francisco, USA, pp. 2810-2816.
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Learning multiple heterogeneous features from different data sources is challenging. One research topic is how to exploit and utilize the correlations among various features across multiple views with the aim of improving the performance of learning tasks, such as classification. In this paper, we propose a new multi-view feature learning algorithm that simultaneously analyzes features from different views. Compared to most of the existing subspace learning methods that only focus on exploiting a shared latent subspace, our algorithm not only learns individual information in each view but also captures feature correlations among multiple views by learning a shared component. By assuming that such a component is shared by all views, we simultaneously exploit the shared component and individual information of each view in a batch mode. Since the objective function is non-smooth and difficult to solve, we propose an efficient iterative algorithm for optimization with guaranteed convergence. Extensive experiments are conducted on several benchmark datasets. The results demonstrate that our proposed algorithm performs better than all the compared multi-view learning algorithms.
Yamamoto, H, Sheng, D & Sun, D 1970, 'Application of digital image analysis to displacement measurements of sand particles near steel surface in friction tests', Proceedings of the International Symposium on Geomechanics and Geotechnics of Particulate Media - Geomechanics and Geotechnics of Particulate Media, International Symposium on Geomechanics and Geotechnics of Particulated Media, CRC Press, Ube, JAPAN, pp. 341-347.
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In this paper, a digital image technique is used to measure the displacements of sand particles at the soil-steel interface in friction tests. The friction tests are used to study the frictional characteristics between cohesionless soils and mild steel and are carried out using a shear box type apparatus. In order to observe the particle displacements, the front side of the shear box is made of a transparent glass plate and photos can thus be taken continuously by a CCD camera with a magnification of x32 through this observation window. These continuous photos are analyzed by image processing to track the movements and the rotations of soil particles. It is well known that the frictional behavior is influenced by the roughness of the surfaces. Therefore, three kinds of roughness for the steel surface are employed in the tests, i.e. very rough (Rmax ≥ 50 μm), medium (Rmax = 9.3 μm) and very smooth (Rmax = 2.4 μm). The normal stress is kept constant at 100 kPa during the tests. The soil specimen is Toyoura sand with a relative density of D≒r = 90%. The test results show that: (1) The digital image technique is effective in capturing the movements and rotations of soil particles near the steel surface. (2) In the case of a very rough steel surface, the soil particles move very actively, except those adjacent to the frictional boundary. (3) In the case of a very smooth steel surface, the rotation of particle near the interface is limited. (4) The volume change of the soil specimen depends on the rotation of soil particles and very little volume change occurs in the case of a very smooth steel surface. © 2006 Taylor & Francis Group.
Yan, H, Sui, Y, Chen, S & Xue, J 1970, 'Machine-Learning-Guided Typestate Analysis for Static Use-After-Free Detection', Proceedings of the 33rd Annual Computer Security Applications Conference, ACSAC 2017: 2017 Annual Computer Security Applications Conference, ACM, Orlando, FL, USA, pp. 42-54.
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Typestate analysis relies on pointer analysis for detecting temporal memory safety errors, such as use-After-free (UAF). For large programs, scalable pointer analysis is usually imprecise in analyzing their hard "corner cases", such as infeasible paths, recursion cycles, loops, arrays, and linked lists. Due to a sound over-Approximation of the points-To information, a large number of spurious aliases will be reported conservatively, causing the corresponding typestate analysis to report a large number of false alarms. Thus, the usefulness of typestate analysis for heap-intensive clients, like UAF detection, becomes rather limited, in practice. We introduce Tac, a static UAF detector that bridges the gap between typestate and pointer analyses by machine learning. Tac learns the correlations between program features and UAF-related aliases by using a Support Vector Machine (SVM) and applies this knowledge to further disambiguate the UAF-related aliases reported imprecisely by the pointer analysis so that only the ones validated by its SVM classifier are further investigated by the typestate analysis. Despite its unsoundness, Tac represents a practical typestate analysis approach for UAF detection. We have implemented Tac in LLVM-3.8.0 and evaluated it using a set of eight open-source C/C++ programs. The results show that Tac is effective (in terms of finding 5 known CVE vulnerabilities, 1 known bug, and 8 new bugs with a low false alarm rate) and scalable (in terms of analyzing a large codebase with 2,098 KLOC in just over 4 hours).
Yang, G, Dai, Y, Zhao, H, Hirota, K & Lu, H 1970, 'Intelligent web-based experiment management system using multi-agent concept', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 8508-8514.
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© 2017 IEEE. Many web-based online learning systems focus more on textual and/or image based content delivery without including experiment systems, or if included they are usually operated under pre-defined conditions, such as fixed scenarios and pre-determined delivery orders. These limitations hinder personalized learning and collaboration between students and discourage student engagement. To circumvent these limitations, an Intelligent Web-based Experiment Management System (IWEMS) using multi-agent concept is presented. In the system, three kinds of software agents are used: (i) Student-Agent, responsible for assessing the knowledge levels of students. A fuzzy set based algorithm is used and the results are plotted through a dynamic polar chart; (ii) Teacher-Agent, responsible for tracking experiment progress of each student and recommending personalized the next-to-do experiment to him or her; and (iii) Co-Agent, responsible for group formation based on similar knowledge levels to facilitate collaborative learning between students. A prototype of this system is developed using a Java Agent Development Framework(JADE), where a client/server architecture and a MySQL database are used. It demonstrates the validity of the design and effectiveness of this system's functionality, achieves the personalization recommendation of next-to-do experiment and collaborative learning environment.
Yang, J, Zhang, W, Yang, S, Zhang, Y & Lin, X 1970, 'TT-Join: Efficient Set Containment Join', 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017 IEEE 33rd International Conference on Data Engineering (ICDE), IEEE, San Diego, CA, USA, pp. 509-520.
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© 2017 IEEE. In this paper, we study the problem of set containment join. Given two collections R and S of records, the set containment join R ⊆ S retrieves all record pairs {(r, s)} ∈ R × S such that r ⊆ s. This problem has been extensively studied in the literature and has many important applications in commercial and scientific fields. Recent research focuses on the in-memory set containment join algorithms, and several techniques have been developed following intersectionoriented or union-oriented computing paradigms. Nevertheless, we observe that two computing paradigms have their limits due to the nature of the intersection and union operators. Particularly, intersection-oriented method relies on the intersection of the relevant inverted lists built on the elements of S. A nice property of the intersection-oriented method is that the join computation is verification free. However, the number of records explored during the join process may be large because there are multiple replicas for each record in S. On the other hand, the unionoriented method generates a signature for each record in R and the candidate pairs are obtained by the union of the inverted lists of the relevant signatures. The candidate size of the union-oriented method is usually small because each record contributes only one replica in the index. Unfortunately, unionoriented method needs to verify the candidate pairs, which may be cost expensive especially when the join result size is large. As a matter of fact, the state-of-The-Art union-oriented solution is not competitive compared to the intersection-oriented ones. In this paper, we propose a new union-oriented method, namely TT-Join, which not only enhances the advantage of the previous unionoriented methods but also integrates the goodness of intersectionoriented methods by imposing a variant of prefix tree structure. We conduct extensive experiments on 20 real-life datasets by comparing our method with 7 existing methods. Th...
Yang, QS, Lyu, MN & Zhu, XQ 1970, 'Temperature-based stiffness identification of que-Ti’s in a historic Tibetan timber building', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australasian Conference on the Mechanics of Structures and Materials, CRC Press, Perth, Australia, pp. 775-782.
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Que-Ti, like the corbel brackets connecting beam and column in modern structures, is an important component in typical Tibetan historic timber buildings. It transfers shear, compression and bending moment by slippage and deformation of components as well as limited joint rotation. A rigorous analytical model of Que-Ti is needed for predicting the behaviour of a timber structure under load. However, few researches have been done with this model, particularly on the parameters describing the performances of this joint under load. The equivalent stiffness of a Que-Ti connection in its operating state is determined by using ambient temperature variations as a forcing function in the complete input(temperature)-output(local mechanical strains) relationship when it is incorporated in a finite element model of the structure. The identification is done iteratively via correlating the calculated strain responses with measured data.
Yang, R, Huang, J, Griffiths, DV & Sheng, D 1970, 'Probabilistic Stability Analysis of Slopes by Conditional Random Fields', Geo-Risk 2017, Geo-Risk 2017, American Society of Civil Engineers, Denver, CO, pp. 450-459.
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Yang, Y & Li, J 1970, 'Latency estimation for fog-based internet of things', 27th International Telecommunication Networks and Applications Conference, Melbourne.
Yang, Y, Zhu, X & Xue, Q 1970, 'On-chip circuit miniaturization techniques for millimeter-wave bandpass filter design', 2017 10th Global Symposium on Millimeter-Waves, 2017 10th Global Symposium on Millimeter-Waves (GSMM), IEEE, Hong Kong, pp. 24-27.
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© 2017 IEEE. In this paper, the millimeter-wave circuit miniaturization techniques using BCMLR and interdigital resonators are introduced. Using these structures, the physical size of the on-chip filter can be dramatically reduced. The designed BPFs are implemented in standard 0.13-μm SiGe and 0.1-μm GaAs technologies for concept approval. Compared with other state-of-the-art work at millimeter-wave frequencies, our proposed designs have the merits of ultra-compact size as small as 0.038 mm2, competitive insertion loss (1 dB in GaAs BPF) and harmonic suppression of more than 44 dB.
Yanjie Dong, Hossain, J, Julian Cheng & Leung, VCM 1970, 'Joint RRH selection and beamforming in distributed antenna systems with energy harvesting', 2017 International Conference on Computing, Networking and Communications (ICNC), 2017 International Conference on Computing, Networking and Communications (ICNC), IEEE, pp. 582-586.
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© 2017 IEEE. To reduce the transmission power while maintaining quality of service requirements of users, more remote radio heads (RRHs) should be active, and this in turn increases the circuit power in the distributed antenna systems with simultaneous wireless information and power transferring. Yet, the above procedures may lead to an unbalanced power consumption between transmission and circuit; therefore causes extra burden on the operators' power budget. To obtain a balanced transmission power and circuit power, this paper studies the system utility minimization problem in such a system via joint RRH selection and beamforming. The utility is formulated as the weighted sum of transmission power and circuit power. Since the formulated problem is NP-hard, a low complexity iterative algorithm is developed to achieve a near-optimal solution. The complexity of each iteration step is analyzed. Computer simulation results show the convergence of the proposed algorithm and the tradeoff between the transmission power and the circuit power.
Yao, J, Zhang, Y, Tsang, I & Sun, J 1970, 'Discovering User Interests from Social Images', MultiMedia Modeling (LNCS), International Conference on Multimedia Modeling, Springer International Publishing, Reykjavik, Iceland, pp. 160-172.
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© Springer International Publishing AG 2017. The last decades have witnessed the boom of social networks. As a result, discovering user interests from social media has gained increasing attention. While the accumulation of social media presents us great opportunities for a better understanding of the users, the challenge lies in how to build a uniform model for the heterogeneous contents. In this article, we propose a hybrid mixture model for user interests discovery which exploits both the textual and visual content associated with social images. By modeling the features of each content source independently at the latent variable level and unifies them as latent interests, the proposed model allows the semantic interpretation of user interests in both the visual and textual perspectives. Qualitative and quantitative experiments on a Flickr dataset with 2.54 million images have demonstrated its promise for user interest analysis compared with existing methods.
Yao, L, Kusakunniran, W, Wu, Q, Zhang, J & Tang, Z 1970, 'Robust Gait Recognition under Unconstrained Environments Using Hybrid Descriptions', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, Australia, pp. 1-7.
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© 2017 IEEE. Gait is one of the key biometric features that has been widely applied for human identification. Appearance-based features and motion-based features are the two mainly used presentations in the gait recognition. However, appearance-based features are sensitive to the body shape changes and silhouette extraction from real-world images and videos also remains a challenge. As for motion features, due to the difficulty in extracting the underlying models from gait sequences, the localization of human joints lacks of high reliability and strong robustness. This paper proposes a new approach which utilizes Two-Point Gait (TPG) as the motion feature to remedy the deficiency of the appearance feature based on Gait Energy Image (GEI), in order to increase the robustness of gait recognition under the unconstrained environments with view changes and cloth changes. Another contribution of this paper is that this is the first time that TPG has been applied for view change and cloth change issues since it was proposed. The extensive experiments show that the proposed method is more invariant to the view change and cloth change, and can significantly improve the robustness of gait recognition.
Yazdani, D, Nguyen, TT, Branke, J & Wang, J 1970, 'A New Multi-swarm Particle Swarm Optimization for Robust Optimization Over Time', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 99-109.
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Dynamic optimization problems (DOPs) are optimization problems that change over time, and most investigations in this area focus on tracking the moving optimum efficiently. However, continuously tracking a moving optimum is not practical in many real-world problems because changing solutions frequently is not possible or very costly. Recently, another practical way to tackle DOPs has been suggested: robust optimization over time (ROOT). In ROOT, the main goal is to find solutions that can remain acceptable over an extended period of time. In this paper, a new multi-swarm PSO algorithm is proposed in which different swarms track peaks and gather information about their behavior. This information is then used to make decisions about the next robust solution. The main goal of the proposed algorithm is to maximize the average number of environments during which the selected solutions’ quality remains acceptable. The experimental results show that our proposed algorithm can perform significantly better than existing work in this aspect.
Ye, D, He, Q, Wang, Y & Yang, Y 1970, 'An Agent-Based Decentralised Service Monitoring Approach in Multi-Tenant Service-Based Systems', 2017 IEEE International Conference on Web Services (ICWS), 2017 IEEE International Conference on Web Services (ICWS), IEEE, Honolulu, HI, pp. 204-211.
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Ye, L, Argha, A, Celler, BG, Zhang, Y, Nguyen, HT & Su, SW 1970, 'Nonparametric modelling of VO<inf>2</inf> response to exercise', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 1525-1528.
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This paper investigates the modelling of oxygen
consumption (VO2) response to jogging exercise on treadmill.
Unlike most of the previous methods, which often use simple
parametric models, e.g., first order linear time invariant model,
this study applied a nonparametric kernel based regularised
method to estimate VO2 to address the ill-conditioned modelling
problem and achieve accurate estimation. In particular, it is
worthy to be noted that the selection of kernels will affect
the results for different modelling scenarios. Therefore, in this
research, both radial basis kernel and stable spline kernel were
selected for testing. In order to select the favourable kernel
for this system, a simulation related to VO2-jogging speed was
carried out. The results of simulation indicated that spline
kernel can achieve higher accuracy comparing to radial basis
function kernel. Experimentally, the kernel based estimation
method and spline kernel were tested using six participants.
From the results, an average impulse response is obtained. It
showed the VO2 estimation, based on the average finite impulse
response, is fitted well to the six observations collected from the
participants.
Ye, X, Wang, S, Wang, Q, Sloan, S & Sheng, D 1970, 'The study of pull-out resistance improvement for a newly developed soil nail', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2231-2234.
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Soil nailing technique is an effective way to prevent slope collapse, of which the pull-out resistance is the key factor that influences its working performance. In this case, a new soil nail which combines compaction grouting with conventional nailing method was proposed to improve the pull-out resistance. For achieving an ideal compaction grouting, a membrane was used to prevent the cement permeating into or fracturing the soil matrix, so that a relatively regular expanded cement bulb was formed to enhance the resistance during the pull-out process. In order to study the fundamental mechanism of this soil nail, a physical model system was designed and setup, which was then used to conduct the pull-out test. Afterwards, a numerical model was established and verified based on the result of the physical model test, and then more simulations were carried out to investigate the key shape factors (i.e. Length, diameter and shape angle of the cement bulk) that contribute to the improvement of pull-out resistance. The results show that the diameter of cement bulk plays the dominant role in the improvement of pull-out resistance while its length has the least influence. In addition, the shape angle can also affect the pull-out resistance increase.
Yeganeh, N, Fatahi, B & Terzaghi, S 1970, 'Effects of shear wave velocity profile of soil on seismic response of high rise buildings', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, International Conference of the International Association for Computer Methods and Advances in Geomechanics, International Association for Computer Methods and Advances in Geomechanics (IACMAG), Wuhan, China, pp. 920-928.
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There is, nowadays, a conspicuous demand for the high rise buildings in the high-density dwellings of the urban areas; in consequence, harnessing the whiz-bang numerical simulations plus conducting the rigorous experimental studies so as to design and construct such prodigious structures would be essential. Thus, the appropriate parameters for modeling the structure and the soil medium in the Soil-Structure Interaction (SSI) system should be selected. The soil-structure interaction is referred to the process in which the soil response is told on by the structure motion whilst the latter is affected by the soil motion. The current research zeroed in on the soil shear wave velocity and its influence on the superstructure performance. Invoking the weighted average shear wave velocity with the aim of calculating the soil shear modulus, which is closely related to the strength and deformation characteristics of the soil, has been a hotly debated issue since the aforesaid parameter was posited by a plethora of codes and regulations to obtain the soil site classification required for the earthquake design. To that end, the numerical model, having two assorted profiles associated with the shear wave velocity, namely, the in situ non-uniform profile (Case A) and the equivalent uniform profile (Case B), was built by means of FLAC3D, capable of analyzing the complex interaction issues via the direct method whereby the entire system of the structure-foundation-soil is modeled and analyzed in one single step. To put it in a nutshell, employing the weighted average shear wave velocity for the entire soil mass in parsing of the 3D seismic soil-structure interaction problems would be accused for ending up with somewhat unreliable results, e.g., underestimated drift ratio and building deformation, which might be the culprit of the damage to the building and possibly the death of the residents residing in the earthquake-prone zones.
Yi, C, Yu, D, Sun, Y & Liang, J 1970, 'McVA: A Multi-comparison Visual Analysis System for Maximum Residue Limit Standard in Food Safety', Proceedings of ChinaVis 2017, ChinaVis 2017, QingDao, China.
Yin, R, Li, K, Zhang, G & Lu, J 1970, 'Detecting overlapping protein complexes in dynamic protein-protein interaction networks by developing a fuzzy clustering algorithm', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, Italy, pp. 1-6.
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© 2017 IEEE. Protein complexes play important roles in proteinprotein interaction networks. Recent studies reveal that many proteins have multiple functions and belong to more than one different complexes. To get better complex division, we need to consider time-dependent information of networks. However, only few studies can be found to concentrate on detecting overlapping clusters in time-dependent networks. To solve this problem, we propose integrated model of time-dependent network (IM-TDN) to describe time-dependent networks. On the base of this model, we propose similarity based dynamic fuzzy clustering (SDFC) algorithm to detect overlapping clusters. We apply the algorithm to synthetic data and real world protein-protein interaction network dataset. The results showed that our algorithm by using the model which we proposed achieved better results over the state-of-the-art baseline algorithms.
Ying, M, Ying, S & Wu, X 1970, 'Invariants of quantum programs: characterisations and generation.', POPL, ACM SIGPLAN Symposium on Principles of Programming Languages, ACM, Paris, France, pp. 818-832.
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© 2017 ACM. Program invariant is a fundamental notion widely used in program verification and analysis. The aim of this paper is twofold: (i) find an appropriate definition of invariants for quantum programs; and (ii) develop an effective technique of invariant generation for ver- ification and analysis of quantum programs. Interestingly, the no- tion of invariant can be defined for quantum programs in two d- ifferent ways - additive invariants and multiplicative invariants - corresponding to two interpretations of implication in a continuous valued logic: the £ukasiewicz implication and the Godel implica- tion. It is shown that both of them can be used to establish partial correctness of quantum programs. The problem of generating ad- ditive invariants of quantum programs is addressed by reducing it to an SDP (Semidefinite Programming) problem. This approach is applied with an SDP solver to generate invariants of two important quantum algorithms - quantum walk and quantum Metropolis sam- pling. Our examples show that the generated invariants can be used to verify correctness of these algorithms and are helpful in optimis- ing quantum Metropolis sampling. To our knowledge, this paper is the first attempt to define the notion of invariant and to develop a method of invariant generation for quantum programs.
Yoo, C & Belta, C 1970, 'Rich Time Series Classification Using Temporal Logic', Robotics: Science and Systems XIII, Robotics: Science and Systems 2017, Robotics: Science and Systems Foundation, Boston, Massachusetts, USA.
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Yu, H, Guo, K, Luo, J, Cao, K, Nguyen, HT & Su, SW 1970, 'The classification for “equilibrium triad” sensory loss based on sEMG signals of calf muscles', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Jeju Island, Korea, pp. 2142-2145.
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Surface Electromyography (sEMG) has been commonly applied for analysing the electrical activities of skeletal muscles. The sensory system of maintaining posture balance includes vision, proprioception and vestibular senses. In this work, an attempt is made to classify whether the body is missing one of the sense during balance control by using sEMG signals. A trial of combination with different features and muscles is also developed. The results demonstrate that the classification accuracy between vision loss and the normal condition is higher than the one between vestibular sense loss and normal condition. When using different features and muscles, the impact on classification results is also different. The outcomes of this study could aid the development of sEMG
based classification for the function of sensory systems during human balance movement.
Yu, H, Huang, L, Zhang, Y, Wang, K, Miao, W & Zhu, D 1970, 'Cooperation as a Mediator Variable Between Research Fund and Scientific Outputs: Evidence from NSFC-Guangdong Joint Fund', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Portland, OR, USA, pp. 1-8.
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© 2017 IEEE. Recent studies shed light on the key elements that influence the link among research funds, collaborative activities and scientific outputs. However, most researches focused on the effects of research fund, and cooperation was only considered as an independent determinant of research productivity. In this paper we evaluate the mediating role of cooperation in the relationship between research fund and scientific outputs of individuals. We conduct a multiple linear regression study to NSFC-Guangdong Joint Fund. Leveraging 40 interviews to the correlated scientists of NSFC-Guangdong Joint Fund, 16 interviews to research directors from universities, and 12 interviews to program managers in the government of Guangdong Province, we examine how NSFC-Guangdong Joint Fund may affects the scientific outputs of individuals in Guangdong through promoting their cross-regional cooperation. Then, we estimate this effect using Web of Science database and our own application database, and find cross-regional cooperation plays a mediating role in prompting the interaction between the fund and scientific outputs of individuals in Guangdong Province.
Yu, H, Lu, J & Zhang, G 1970, 'Learning a fuzzy decision tree from uncertain data', 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), IEEE, Piscataway, USA, pp. 1-7.
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© 2017 IEEE. Uncertainty in data exists when the value of a data item is not a precise value, but rather by an interval data with a probability distribution function, or a probability distribution of multiple values. Since there are intrinsic differences between uncertain and certain data, it is difficult to deal with uncertain data using traditional classification algorithms. Therefore, in this paper, we propose a fuzzy decision tree algorithm based on a classical ID3 algorithm, it integrates fuzzy set theory and ID3 to overcome the uncertain data classification problem. Besides, we propose a discretization algorithm that enables our proposed Fuzzy-ID3 algorithm to handle the interval data. Experimental results show that our Fuzzy-ID3 algorithm is a practical and robust solution to the problem of uncertain data classification and that it performs better than some of the existing algorithms.
Yu, K, Berkovsky, S, Taib, R, Conway, D, Zhou, J & Chen, F 1970, 'User Trust Dynamics', Proceedings of the 22nd International Conference on Intelligent User Interfaces, IUI'17: 22nd International Conference on Intelligent User Interfaces, ACM, Limassol, CYPRUS, pp. 307-317.
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Yu, Q, Dong, D, Petersen, IR & Gao, Q 1970, 'Hybrid Filtering for a Class of Quantum Systems with Classical Disturbances', IFAC-PapersOnLine, Elsevier BV, pp. 11738-11743.
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Yu, X & Porikli, F 1970, 'Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks', Proceedings of the AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), pp. 4327-4333.
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Conventional face hallucination methods rely heavily on accurate alignment of low-resolution (LR) faces before upsampling them. Misalignment often leads to deficient results and unnatural artifacts for large upscaling factors. However, due to the diverse range of poses and different facial expressions, aligning an LR input image, in particular when it is tiny, is severely difficult. To overcome this challenge, here we present an end-to-end transformative discriminative neural network (TDN) devised for super-resolving unaligned and very small face images with an extreme upscaling factor of 8. Our method employs an upsampling network where we embed spatial transformation layers to allow local receptive fields to line-up with similar spatial supports. Furthermore, we incorporate a class-specific loss in our objective through a successive discriminative network to improve the alignment and upsampling performance with semantic information. Extensive experiments on large face datasets show that the proposed method significantly outperforms the state-of-the-art.
Yu, X & Porikli, F 1970, 'Hallucinating Very Low-Resolution Unaligned and Noisy Face Images by Transformative Discriminative Autoencoders', 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, pp. 5367-5375.
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Yu, Y, Li, J, Dackermann, U & Subhani, M 1970, 'Development of a portable NDE system with advanced signal processing and machine learning for health condition diagnosis of in-service timber utility poles', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press, Perth, Australia, pp. 1547-1552.
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Aiming at current shortcomings of Non-Destructive Evaluation (NDE) in health condition estimation of timber utility poles, this paper put forward a novel testing method via combination of a portable NDE system, advanced signal processing and machine learning techniques. Primarily, the multi-sensing strategy is employed and incorporated in current NDE technique to capture reflected stress wave signals, avoiding difficult interpretation of complicated wave propagation by only one sensor. Secondly, advanced signal processing methods, such as Ensemble Empirical Mode Decomposition (EEMD) and Principal Component Analysis (PCA), are introduced to extract effective wave patterns that are sensitive to structural damage. Moreover, based on captured signal features, the state-of-the-art machine learning techniques are applied to implement the condition assessment. Finally, field testing results of 26 decommissioned timber poles at Mason Park in Sydney are used to validate the effectiveness of the proposed method.
Yu, Y, Li, Y & Li, J 1970, 'Sigmoid function-based hysteresis modeling of magnetorheological pin joints', 2017 3rd International Conference on Control, Automation and Robotics (ICCAR), 2017 3rd International Conference on Control, Automation and Robotics (ICCAR), IEEE, Nagoya, Japan, pp. 514-517.
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© 2017 IEEE. The magnetorheological (MR) pin joint is a semi-active control device which can be installed in the column-beam structures for structural vibration control. Nevertheless, the nonlinear response of the MR pin joint together with its unique rheological nature makes the device modeling difficult and impedes its engineering application. Although many complicated phenomenal models have been proposed to illustrate the dynamic behaviour of MR devices, a large number of model parameters and differential equations bring the challenges for model identification and controller design. In this study, we try to predict the dynamic response of a MR pin joint using a novel and simple phenomenal model, which is comprised of a rotary spring, a rotary damper and a sigmoid function-based hysteresis component. Then, the model parameters are identified using trust-region-reflective least squares algorithm in MATLAB optimization toolbox. Finally, the experimental results under various loading conditions are used to validate the performance of the proposed model.
Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 1970, 'Dynamic modeling of magnetorheological elastomer base isolator based on extreme learning machine', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC press, Perth, Australia, pp. 703-708.
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This paper presents a novel modeling method to describe the nonlinear and hysteretic characteristics of Magnetorheological Elastomer (MRE) isolator, which is a semi-active control device and used in vibration control of engineering structures such as vehicle suspension system, offshore platform and built infrastructure. In the proposed method, a new single-hidden-layer feed-forward neural network algorithm named Extreme Learning Machine (ELM) is adopted to set up the model, in which the captured responses such as displacement and velocity of the device together with applied current level are employed as model inputs while the model output is the shear force generated according to the external excitation. Finally, the experimental data are utilized to validate the performance of the proposed method.
Yu, Z, Chaczko, Z & Jiang, J 1970, 'Development and Optimization of Wireless Indoor Localization Error Modelling', 2017 25th International Conference on Systems Engineering (ICSEng), 2017 25th International Conference on Systems Engineering (ICSEng), IEEE, Las Vegas, NV, USA, pp. 475-479.
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© 2017 IEEE. This paper introduces a new generation an error modelling of wireless indoor localization. A newly designed algorithm modelling by using Kalman Filter is developed to optimize the wireless indoor localization system based on iBeacon sensors. It is designed to detect and minimize the errors. Matlab simulations, implementation, and validation are presented in the paper.
Yuan, X, Wei, Z, Feng, Z & Xu, W 1970, 'Trust connectivity analysis in overlaid unmanned aerial vehicle networks', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, pp. 1-6.
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Zainudin, Z, Ibrahim, MM & Kodagoda, S 1970, 'Non-parametric data optimization for 2D laser based people tracking', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1887-1892.
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Generally, a model on describing human motion patterns should have an ability to enhance tracking performance particularly when dealing with long term occlusions. These patterns can be efficiently learned by applying Gaussian Processes (GPs). However, the GPs can become computationally expensive with increasing training data with time. Thus, with the proposed data selection and management using Mutual Information (MI) and Mahalanobis Distance (MD)approach, we have be able to keep the necessary portion of informative data and discard the others. This approach is then experimented by using the measurements of horizontal 2D scan of public area of our research centre with a stationary laser range finder. Experimental results show that even 90% reduction of data did not contribute to significantly increased Root Mean Square Error (RMSE). Implementation of Gaussian Process - Particle filter tracker for people tracking with long term occlusions produces a remarkable tracking performance when compared to Extended Kalman Filter (EKF) tracker.
Zekveld, J, Bakker, S, Zijlema, A & van den Hoven, E 1970, 'Wobble', Proceedings of the Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, TEI '17: Eleventh International Conference on Tangible, Embedded, and Embodied Interaction, ACM, Yokohama, pp. 31-35.
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© 2017 ACM. Reminders are designed to support remembering actions or intentions to be performed later in time. Most technologies that have a reminding functionality do so by asking attention (e.g., by using auditory alerts or vibration patterns) from users at a certain point in time or location. Because of their obtrusive nature, the reminders of many (digital) prospective memory AIDS we use on a daily basis are hard to ignore, regardless of our ability and motivation to perform the reminded action or intention. In this paper, we present Wobble: An interactive cone-shaped artefact for reminding in the home environment. Wobble was designed to investigate peripheral reminders. Our results imply that wobble is best suitable for reminding intentions that do not require direct action but can be carried out over a period of time, which is a type of reminding currently not met by most electronic memory AIDS.
Zha, X, Wang, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 1970, 'Analytic model on data security in VANETs', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-6.
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© 2017 IEEE. Fast-changing topologies and uncoordinated transmissions are two critical challenges of implementing data security in vehicular ad-hoc networks (VANETs). We propose a new protocol, where transmitters adaptively switch between backing off retransmissions and changing keys to improve success rate. A new 3-dimensional (3-D) Markov model, which can analyze the proposed protocol with symmetric or asymmetric keys in terms of data security and connectivity, is developed. Analytical results, validated by simulations, show that the proposed protocol achieves substantially improved resistance against collusion attacks.
Zhang, F, Zhang, Y, Qin, L, Zhang, W & Lin, X 1970, 'Finding Critical Users for Social Network Engagement: The Collapsed k-Core Problem.', AAAI, AAAI Conference on Artificial Intelligence, AAAI Press, San Francisco, USA, pp. 245-251.
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In social networks, the leave of critical users may significantly
break network engagement, i.e., lead a large number of other
users to drop out. A popular model to measure social network
engagement is k-core, the maximal induced subgraph in which
every vertex has at least k neighbors. To identify critical users
for social network engagement, we propose the collapsed kcore
problem: given a graph G, a positive integer k and a
budget b, we aim to find b vertices in G such that the deletion
of the b vertices leads to the smallest k-core. We prove the
problem is NP-hard. Then, an efficient algorithm is proposed,
which significantly reduces the number of candidate vertices
to speed up the computation. Our comprehensive experiments
on 9 real-life social networks demonstrate the effectiveness
and efficiency of our proposed method.
Zhang, H, Huang, X & Guo, YJ 1970, 'A 20 Gbps Digital Modem for High Speed Wireless Backhaul Applications', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE.
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© 2017 IEEE. The rapid growth of mobile broadband wireless services in recent years demands high speed data transmission for both access and backhaul networks. With the increase of data rate for 5G access to tens of Gigabits per second (Gbps), higher speed transmission for backhaul network is necessary. Current wireless backhaul systems have been able to achieve the data rate of multiple Gbps, but the ability to deal with significant practical impairments such as large carrier frequency offset and IQ mismatch is still a technical challenge. In this paper, a 20 Gbps digital modem for wireless backhaul applications is proposed. Simulation and field programmable gate array implementation show that the the proposed design and signal processing algorithms meet the targeted system performance.
Zhang, H, Zhu, Y, Qin, L, Cheng, H & Yu, JX 1970, 'Efficient Local Clustering Coefficient Estimation in Massive Graphs.', DASFAA (2), Database Systems for Advanced Applications, Springer, China, pp. 371-386.
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© Springer International Publishing AG 2017. Graph is a powerful tool to model interactions in disparate applications, and how to assess the structure of a graph is an essential task across all the domains. As a classic measure to characterize the connectivity of graphs, clustering coefficient and its variants are of particular interest in graph structural analysis. However, the largest of today’s graphs may have nodes and edges in billion scale, which makes the simple task of computing clustering coefficients quite complicated and expensive. Thus, approximate solutions have attracted much attention from researchers recently. However, they only target global and binned degree wise clustering coefficient estimation, and their techniques are not suitable for local clustering coefficient estimation that is of great importance for individual nodes. In this paper, we propose a new sampling scheme to estimate the local clustering coefficient with error bounded, where global and binned degree-wise clustering coefficients can be considered as special cases. Meanwhile, based on our sampling scheme, we propose a new framework to estimate all the three clustering coefficients in a unified way. To make it scalable on massive graphs, we further design an efficient MapReduce algorithm under this framework. Extensive experiments validate the efficiency and effectiveness of our algorithms, which significantly outperform state-of-the-art exact and approximate algorithms on many real graph datasets.
Zhang, J, Li, L, Dorrell, D & Guo, Y 1970, 'A PI controller with current feedforward to improve the steady-state error performance for a current controlled direct matrix converter', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, pp. 1-6.
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© 2017 IEEE. Traditional PI controllers can have poor regulation performance due to steady state errors when tracking sinusoidal signals. Hence synchronous PI controllers are often used, although this controller requires reference frame transformations. In this paper, a modified PI controller, which uses current feedforward, is developed to control the output currents of a matrix converter. The controller is implemented in the natural frame (abc) together with space vector modulation. The output current is then controlled. This controller does not require any frame transformation and it demonstrates improved steady-state tracking performance. The total harmonic distortion is improved at the same time. A constant switching frequency is maintained because of the application of the modulation stage. Simulation results verify the feasibility and effectiveness of the proposed controller.
Zhang, J, Li, L, Dorrell, D & Guo, Y 1970, 'Direct torque control with a modified switching table for a direct matrix converter based AC motor drive system', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The direct matrix converter has been regarded as a promising AC/AC conversion topology and it is being researched. Motor drives are one of the main potential applications of the matrix converter. This paper carries forward the application of matrix converters in AC motor drives using direct torque control (DTC). In the common DTC scheme for the matrix converter, two vectors with the maximum amplitudes are used to control the torque and flux. In the proposed approach, the input voltage vector sectors are redefined, therefore a modified and simplified switching look-up table is obtained. In this case the most appropriate vector to be applied is uniquely determined and the number of switch actions are reduced. The excellent dynamic performance is obtained by selecting the maximum vector. Flux and speed are controlled effectively. Simulation work is carried out for an induction motor and results verify the effectiveness of the proposed DTC control in matrix converter based AC drive systems.
Zhang, J, Li, L, Dorrell, DG & Guo, Y 1970, 'Space vector modulation based proportional resonant current controller with selective harmonics compensation for matrix converter systems', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The matrix converter has emerged as a direct AC/AC converter and has attracted research attention. This work proposes a Proportional Resonant (PR) controller based on the Space Vector Modulation (SVM) method for the three-phase direct matrix converter and its application systems. The PR controller, compared with the widely used PI controller, has better steady-state error performance, specific harmonics compensation capability, and the ability to handle sinusoidal quantities. These enhance the tracking performance of the converters and benefit the current quality improvement and selective harmonics suppression. The PR controller can be implemented in the natural frame in a straightforward manner, which removes the frame transformations involved in the stationary (αβ) and synchronous (dq) reference frame based control strategies. This alleviates the computation burden. Simulation results verify the effectiveness of the proposed PR controller for the matrix converter applications.
Zhang, J, Li, L, He, T, Aghdam, MM & Dorrell, DG 1970, 'Investigation of direct matrix converter working as a versatile converter (AC/AC, AC/DC, DC/AC, DC/DC conversion) with predictive control', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 4644-4649.
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© 2017 IEEE. The three-phase direct matrix converter has been researched exclusively as a direct AC/AC converter, being a competitive alternative to the conventional AC/DC/AC converter. Other possibilities of the matrix converter such as AC/DC, DC/AC and DC/DC conversion still remain unexplored. This paper firstly explores these possibilities and puts forward a concept of the versatile converter. With one matrix converter, different conversion purposes can be accomplished as required. The matrix converter based conversion has some advantages compared with other converters. Model predictive control (MPC) is applied in this work to control the matrix converter to perform the required conversion goals. A generalized model is obtained for all types of conversion in this work. With MPC, different objectives and constraints can be easily included in the control scheme. In addition, the observers are used to reduce the number of voltage and current sensors. Simulation results verify the effectiveness and feasibility of AC/DC, DC/AC and DC/DC conversion with the matrix converter.
Zhang, J, Li, L, Malekjamshidi, Z & Dorrell, DG 1970, 'Predictive voltage control of direct matrix converter with reduced number of sensors for the renewable energy and microgrid applications', 2017 IEEE Energy Conversion Congress and Exposition (ECCE), 2017 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Cincinnati, OH, USA, pp. 3309-3315.
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© 2017 IEEE. This work proposes and investigates a renewable energy distributed generation system involving a matrix converter with an output filter working as a stable voltage supply. This is especially relevant for the stand-alone operation of a renewable energy microgrid where a stable sinusoidal voltage with prescribed amplitude and frequency under various load conditions is the main control objective. A controllable input power factor is preferred. In this paper, the model predictive control is employed to regulate the matrix converter output voltages which in turn are the supply for systems of the following stage. To reduce the number of required measurements and sensors, the work designs observers and makes use of the switch matrix. In addition to the regulation of the sinusoidal output voltages and input power factor, the control scheme deals with the common-mode voltage. The switching frequency is also considered in the controller to reduce the switching losses and keep the average switching frequency constant. In addition, the voltage transfer ratio can be improved at the cost of input current distortion. Supplying DC loads is feasible with this proposed control method. The controller is tested under various conditions including non-linear loads, DC loads and unbalanced input conditions to show it is effective, simple and easy to implement. Simulation results corroborate the effectiveness of the proposed controller and applications.
Zhang, J, Li, L, Zhang, L & Dorrell, DG 1970, 'Hysteresis band current controller based field-oriented control for an induction motor driven by a direct matrix converter', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 4633-4638.
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© 2017 IEEE. This paper presents work on the hysteresis band control for output current regulation in a direct matrix converter in order to drive an induction motor. The hysteresis band controller offers excellent dynamic performance. It has been extensively researched for the voltage source inverter and inverter based drive systems, but it has not been investigated within the context of a matrix converter or a matrix converter based motor drive. Firstly, this paper proposes a fixed-band hysteresis current controller for a matrix converter to track the prescribed current references, and then a sinusoidal-band hysteresis current controller is proposed. Both methods have fast dynamic performance and they inherently integrate the line modulation technique of the virtual rectifier stage into the overall modulation. The extra modulation stage is not required and the surge current is inherently prevented. The sinusoidal-band hysteresis controller demonstrates that it generates lower harmonic content at the expense of the higher average switching frequency. Following this, both methods are tested as a drive for an induction motor with field-oriented control. With the matrix-converter-based drive system, one significant benefit is that the braking chopper is removed due to the bidirectional feature. The methods are simple and have light computation burden. The obtained results demonstrate the effectiveness and feasibility of the proposed scheme. The experimental work is being carried out to support the proposed scheme.
Zhang, J, Sui, Y & Xue, J 1970, 'Incremental Analysis for Probabilistic Programs', Static Analysis (LNCS), International Symposium on Static Analysis, Springer International Publishing, New York, NY, USA, pp. 450-472.
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© 2017, Springer International Publishing AG. This paper presents Icpp, a new data-flow-based InCremental analysis for Probabilistic Programs, to infer their posterior probability distributions in response to small yet frequent changes to probabilistic knowledge, i.e., prior probability distributions and observations. Unlike incremental analyses for usual programs, which emphasize code changes, such as statement additions and deletions, Icpp focuses on changes made to probabilistic knowledge, the key feature in probabilistic programming. The novelty of Icpp lies in capturing the correlation between prior and posterior probability distributions by reasoning about the probabilistic dependence of each data-flow fact, so that any posterior probability affected by newly changed probabilistic knowledge can be incrementally updated in a sparse manner without recomputing it from scratch, thereby allowing the previously computed results to be reused. We have evaluated Icpp with a set of probabilistic programs. Our results show that Icpp is an order of magnitude faster than the state-of-the-art data-flow-based inference in analyzing probabilistic programs under small yet frequent changes to probabilistic knowledge, with an average analysis overhead of around 0.1Â s in response to a single change.
Zhang, J, Zhang, J, Wu, Q, Wu, Q, Xu, J, Lu, J, Phua, R, Curr, K & Tang, Z 1970, 'Historical Image Annotation by Exploring the Tag Relevance', 2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), IEEE, Nanjing, China, pp. 640-645.
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© 2017 IEEE. Historical images usually contain enormous historical research value and are highly related to the history objects, events and background stories etc. Therefore, annotating these images always requires selecting tags within a large set. In this paper, we propose to annotate historical images by exploring the tag relevance. We measure the tag relevance from three different perspectives, including its visual relevance, its dependencies with other tags and its relationship with location based meta-data. By using tag relevance as guidance, we generate three tag sub-sets and use them to fulfill the annotation. Experimental results on the benchmark dataset indicate the significance of exploring the tag relevance by comparing with the baseline experiments.
Zhang, JA, Cantoni, A, Huang, X, Guo, YJ & Heath, RW 1970, 'Joint Communications and Sensing Using Two Steerable Analog Antenna Arrays', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. Beam-steering has great potentials for joint communications and sensing, which is becoming a demanding feature on many emerging platforms such as unmanned aerial vehicles and smart cars. Although beam-steering has been extensively studied for communications and radar sensing respectively, its application in the joint system is not straightforward due to different beamforming requirements by communications and sensing. In this paper, we propose a low-cost system framework which allows seamless operation of communications and sensing, using two small- size steerable analog antenna arrays. We provide system architecture, high-level protocols, detailed signal model, novel beamforming design and advanced 1D compressive sensing algorithms for joint communications and sensing. We also provide preliminary simulation results which validate the effectiveness of the proposed technique in resolving closely located objects.
Zhang, JA, Cantoni, A, Huang, X, Guo, YJ & Jr, RWH 1970, 'Framework for an Innovative Perceptive Mobile Network Using Joint Communication and Sensing', IEEE Vehicular Technology Conference, IEEE Vehicular Technology Conference, IEEE, Sydney, pp. 1-5.
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In this paper, we develop a framework for an innovative perceptive mobile(i.e. cellular) network that integrates sensing with communication, andsupports new applications widely in transportation, surveillance andenvironmental sensing. Three types of sensing methods implemented in thebase-stations are proposed, using either uplink or downlink multiusercommunication signals. The required changes to system hardware and majortechnical challenges are briefly discussed. We also demonstrate the feasibilityof estimating sensing parameters via developing a compressive sensing basedscheme and providing simulation results to validate its effectiveness.
Zhang, JA, Huang, X, Guo, YJ & Rahman, ML 1970, 'Signal stripping based sensing parameter estimation in perceptive mobile networks', 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), IEEE, Verona, Italy, pp. 67-70.
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© 2017 IEEE. We propose signal stripping based approaches for estimating detailed channel composition parameters for sensing in the recently proposed perceptive mobile networks where simultaneous communication and radar sensing is performed. Via reconstructing a (differentiated) channel matrix, we obtain a signal model which can be solved by conventional compressive sensing (CS) techniques. Parameter estimation methods based on a 1-D CS algorithm are proposed and their effectiveness is validated by provided simulation results.
Zhang, JA, Li, H, Huang, X, Guo, YJ & Cantoni, A 1970, 'User-Directed Analog Beamforming for Multiuser Millimeter-Wave Hybrid Array Systems', 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), IEEE, Sydney, Australia, pp. 1-5.
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© 2017 IEEE. Beamforming design for millimeter-Wave hybrid array with the subarray structure is very challenging. There is neither known optimal solution that maximizes the sum rate capacity nor near-optimal solution. This paper proposes some low-complexity user-directed analog radio- frequency (RF) beamforming design schemes. The basic idea is to iteratively allocate different subarrays to different users such that users' channel correlation can be efficiently reduced via RF beamforming. Several new but less efficient schemes are also presented to shed light on RF beamforming design, and to serve as comparisons for the user-directed schemes. Simulation results are provided for these proposed schemes, existing ones in the literature and an upper-bound for hybird array with a fully-connected structure. The user-directed schemes demonstrate significantly better sum-rate and BER performance over other schemes, although the gap to the upperbound is still large.
Zhang, T, Wu, K, Su, D, Huang, S & Dissanayake, G 1970, 'An Invariant-EKF VINS Algorithm for Improving Consistency', IEEE International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Vancouver, Canada, pp. 1578-1585.
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The main contribution of this paper is an invariant extended Kalman filter(EKF) for visual inertial navigation systems (VINS). It is demonstrated thatthe conventional EKF based VINS is not invariant under the stochasticunobservable transformation, associated with translations and a rotation aboutthe gravitational direction. This can lead to inconsistent state estimates asthe estimator does not obey a fundamental property of the physical system. Toaddress this issue, we use a novel uncertainty representation to derive a RightInvariant error extended Kalman filter (RIEKF-VINS) that preserves thisinvariance property. RIEKF-VINS is then adapted to the multistate constraintKalman filter framework to obtain a consistent state estimator. Both MonteCarlo simulations and real-world experiments are used to validate the proposedmethod.
Zhang, W, Dong, D & Petersen, IR 1970, 'Adaptive target scheme for learning control of post-field alignment', 2017 36th Chinese Control Conference (CCC), 2017 36th Chinese Control Conference (CCC), IEEE, pp. 9752-9756.
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Zhang, W, Szymanski, J, Chiu, C, Chaczko, Z, Su, S & Zhou, J 1970, 'How the Internet of Things is Changing Teaching of Technical Subjects at UTS', 5th Asia-Pacific Conference on Computer-Aided System Engineering, Asia-Pacific Conference on Computer Aided System Engineering, APCASE Foundation, Guilin, Guangxi, China, pp. 71-77.
Zhang, X, Sheng, D, Sloan, SW & Oñate, E 1970, 'Particle finite element modelling of retrogressive slope failure in sensitive clays', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 1475-1480.
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In this paper, the slope failure in sensitive clays is studied numerically using the particle finite element method which is a novel approach capable of tackling extreme deformation problems. The sensitive clay is described using an elastoviscoplastic model with strain softening. This model can be considered a mixture of the Tresca model with strain softening and the classical Bingham model. The former is used to capture the solid-like behaviour, for example when the clay is intact, whereas the latter is to describe the semi-fluid behaviour of the fully remolded clay. The complete process of the collapse of a sensitive clay deposit is captured successfully and the widely-observed retrogressive failure mode is reproduced. The mechanism behind the failure is also discovered.
Zhang, X, Yao, L, Huang, C, Sheng, QZ & Wang, X 1970, 'Intent Recognition in Smart Living Through Deep Recurrent Neural Networks', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 748-758.
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© 2017, Springer International Publishing AG. Electroencephalography (EEG) signal based intent recognition has recently attracted much attention in both academia and industries, due to helping the elderly or motor-disabled people controlling smart devices to communicate with outer world. However, the utilization of EEG signals is challenged by low accuracy, arduous and time-consuming feature extraction. This paper proposes a 7-layer deep learning model to classify raw EEG signals with the aim of recognizing subjects’ intents, to avoid the time consumed in pre-processing and feature extraction. The hyper-parameters are selected by an Orthogonal Array experiment method for efficiency. Our model is applied to an open EEG dataset provided by PhysioNet and achieves the accuracy of 0.9553 on the intent recognition. The applicability of our proposed model is further demonstrated by two use cases of smart living (assisted living with robotics and home automation).
Zhang, X, Yao, L, Zhang, D, Wang, X, Sheng, QZ & Gu, T 1970, 'Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis', Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2017: Computing, Networking and Services, ACM, pp. 28-37.
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© 2017 Association for Computing Machinery. An electroencephalography (EEG) based brain activity recognition is a fundamental field of study for a number of significant applications such as intention prediction, appliance control, and neurological disease diagnosis in smart home and smart healthcare domains. Existing techniques mostly focus on binary brain activity recognition for a single person, which limits their deployment in wider and complex practical scenarios. Therefore, multi-person and multi-class brain activity recognition has obtained popularity recently. Another challenge faced by brain activity recognition is the low recognition accuracy due to the massive noises and the low signal-to-noise ratio in EEG signals. Moreover, the feature engineering in EEG processing is time-consuming and highly relies on the expert experience. In this paper, we attempt to solve the above challenges by proposing an approach which has better EEG interpretation ability via raw Electroencephalography (EEG) signal analysis for multi-person and multi-class brain activity recognition. Specifically, we analyze inter-class and inter-person EEG signal characteristics, based on which to capture the discrepancy of inter-class EEG data. Then, we adopt an Autoencoder layer to automatically refine the raw EEG signals by eliminating various artifacts. We evaluate our approach on both a public and a local EEG datasets and conduct extensive experiments to explore the effect of several factors (such as normalization methods, training data size, and Autoencoder hidden neuron size) on the recognition results. The experimental results show that our approach achieves a high accuracy comparing to competitive state-of-the-art methods, indicating its potential in promoting future research on multi-person EEG recognition.
Zhang, Y, Huang, Y, Porter, AL, Zhang, G & Lu, J 1970, 'Discovering Interactions in Big Data Research: A Learning-Enhanced Bibliometric Study', 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE, Portland, OR, USA, pp. 1-12.
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© 2017 PICMET. As one of the most representative emerging technologies, big data analytics and its related applications are rapidly leading the development of information technologies and are significantly shaping thinking and behavior in today's interconnected world. Exploring the technological evolution of big data research is an effective way to enhance technology management and create value for research and development strategies for both government and industry. This paper uses a learning-enhanced bibliometric study to discover interactions in big data research by detecting and visualizing its evolutionary pathways. Concentrating on a set of 5840 articles derived from Web of Science covering the period between 2000 and 2015, text mining and bibliometric techniques are combined to profile the hotspots in big data research and its core constituents. A learning process is used to enhance the ability to identify the interactive relationships between topics in sequential time slices, revealing technological evolution and death. The outputs include a landscape of interactions within big data research from 2000 to 2015 with a detailed map of the evolutionary pathways of specific technologies. Empirical insights for related studies in science policy, innovation management, and entrepreneurship are also provided.
Zhang, Y, Liu, J, Li, S & Zhao, W 1970, 'Synthesis of a Self-intumescent Flame Retardant of Branched Polyphosphoramide and Its Performance for Epoxy Resins', PROCEEDINGS OF THE 2017 6TH INTERNATIONAL CONFERENCE ON MEASUREMENT, INSTRUMENTATION AND AUTOMATION (ICMIA 2017), 6th International Conference on Measurement, Instrumentation and Automation (ICMIA), ATLANTIS PRESS, PEOPLES R CHINA, Zhuhai, pp. 601-604.
Zhang, Y, Saberi, M & Chang, E 1970, 'Semantic-based lightweight ontology learning framework', Proceedings of the International Conference on Web Intelligence, WI '17: International Conference on Web Intelligence 2017, ACM, Leipzig, GERMANY, pp. 1171-1177.
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Zhang, Y, Su, S, Xu, P & Yao, D 1970, 'Performance evaluation of Noise-Assisted Multivariate Empirical Mode Decomposition and its application to multichannel EMG signals', 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Seogwipo, South Korea, pp. 3457-3460.
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© 2017 IEEE. The use of the Empirical Mode Decomposition (EMD) for nonlinear signal processing has been popularized in the recent years. However, its utility for the processing of multichannel Electromyography (EMG) signals is still limited. This paper investigates the decomposition performance of multichannel EMGs by using the EMD-based approaches, Ensemble EMD (EEMD), Multivariate EMD (MEMD), and Noise-Assisted MEMD (NA-MEMD). In the experiment, 11 male subjects undergo three exercise programs, leg extension from a sitting position, flexion of the leg up, and gait, while electrodes are placed on the muscle groups, biceps femoris, vastus medialis, rectus femoris, and semitendinosus. The outcomes are then quantitatively estimated on the basis of three criterions, the number of Intrinsic Mode Functions (IMFs), mode-alignment and mode-mixing. Results show both MEMD and NA-MEMD can guarantee equal numbers of IMFs, whereas for mode-alignment and mode-mixing, NA-MEMD is optimal compared with MEMD and EEMD, and MEMD is merely better than EEMD. This finding implies that NA-MEMD is effective for simultaneously analyzing IMFs based frequency bands. It has a vital clinical implication in exploring the neuromuscular patterns that enable the multiple muscle groups to coordinate while performing functional activities of daily living.
Zhang, Y, Yu, JX, Zhang, Y & Qin, L 1970, 'A Fast Order-Based Approach for Core Maintenance.', ICDE, International Conference on Data Engineering, IEEE Computer Society, Piscataway, USA, pp. 337-348.
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© 2017 IEEE. Graphs have been widely used in many applications such as social networks, collaboration networks, and biological networks. One important graph analytics is to explore cohesive subgraphs in a large graph. Among several cohesive subgraphs studied, k-core is one that can be computed in linear time for a static graph. Since graphs are evolving in real applications, in this paper, we study core maintenance which is to reduce the computational cost to compute k-cores for a graph when graphs are updated from time to time dynamically. We identify drawbacks of the existing efficient algorithm, which needs a large search space to find the vertices that need to be updated, and has high overhead to maintain the index built, when a graph is updated. We propose a new order-based approach to maintain an order, called k-order, among vertices, while a graph is updated. Our new algorithm can significantly outperform the state-of-Theart algorithm up to 3 orders of magnitude for the 11 large real graphs tested. We report our findings in this paper.
Zhang, Z, Oberst, S & Lai, JCS 1970, 'Uncertainty analysis for the prediction of disc brake squeal propensity', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, Internoise 2017, Hong Kong, China.
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ACT Since brake squeal was first investigated in the 1930s, it has been a noise, vibration and harshness (NVH) problem plaguing the automotive industry due to warranty-related claims and customer dissatisfaction. Accelerating research efforts in the last decade, represented by almost 70% of the papers published in the open literature, have improved the understanding of the generation mechanisms of brake squeal, resulting in better analysis of the problem and better development of countermeasures by combining numerical simulations with noise dynamometer tests. However, it is still a challenge to predict brake squeal propensity with any confidence. This is because of modelling difficulties that include the often transient and nonlinear nature of brake squeal, and uncertainties in material properties, operating conditions (brake pad pressure and temperature, speed), contact conditions between pad and disc, and friction. Although the conventional Complex Eigenvalue Analysis (CEA) method, widely used in industry, is a good linear analysis tool for identifying unstable vibration modes to complement noise dynamometer tests, it is not a predictive tool as it may either over-predict or under-predict the number of unstable vibration modes. In addition, there is no correlation between the magnitude of the positive real part of a complex eigenvalue and the likelihood that the unstable vibration mode will squeal. Transient nonlinear simulations are still computationally too expensive to be implemented in industries for even exploratory predictions. In this paper, a stochastic approach, incorporating uncertainties in the surface roughness of the lining, material properties and the friction coefficient, is applied to predict the squeal propensity of a full disc brake system by using CEA on a finite element model updated by experimental modal testing results. Results compared with noise dynamometer squeal tests illustrate the potential of the stochastic CEA approach ov...
Zhao, M, Zhang, J, Porikli, F, Zhang, C & Zhang, W 1970, 'Learning a perspective-embedded deconvolution network for crowd counting', 2017 IEEE International Conference on Multimedia and Expo (ICME), 2017 IEEE International Conference on Multimedia and Expo (ICME), IEEE, Hong Kong, China, pp. 403-408.
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We present a novel deep learning framework for crowd counting
by learning a perspective-embedded deconvolution network.
Perspective is an inherent property of most surveillance
scenes. Unlike the traditional approaches that exploit the perspective
as a separate normalization, we propose to fuse the
perspective into a deconvolution network, aiming to obtain a
robust, accurate and consistent crowd density map. Through
layer-wise fusion, we merge perspective maps at different resolutions
into the deconvolution network. With the injection of
perspective, our network is driven to learn to combine the underlying
scene geometric constraints adaptively, thus enabling
an accurate interpretation from high-level feature maps to the
pixel-wise crowd density map. In addition, our network allows
generating density map for arbitrary-sized input in an
end-to-end fashion. The proposed method achieves competitive
result on the WorldExpo2010 crowd dataset.
Zhao, S, Cheng, E, Qiu, X, Burnett, I & Liu, CC 1970, 'Simulations on the wind noise reduction by spherical shell windscreens', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet.
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Various windscreens are widely used in outdoor acoustic measurements to reduce the effect of the wind induced pressure fluctuations at the microphones and to improve the measurement accuracy. However, the physical mechanism of the wind noise reduction by windscreens remains unclear yet. In this paper, the wind noise reduction performance of spherical shell windscreens is investigatedwith numerical simulations based on the turbulent modeling in porous media. The effects of both the diameter and the thickness of the spherical shell windscreen on the wind noise reduction performance are investigatedfor both uniform and turbulent incoming flows. It is found that the wind noise at the microphone can be reduced by spherical shell windscreens only when the thickness of the spherical shell windscreen is smaller than 0.1 cmfor uniformincoming flow, and the wind noise reduction increases with the diameter but approaches a constant when the windscreen is largerthan 20 cm.Forturbulentincoming flow, the wind noise reduction performance of the spherical shell windscreen increases with the diameter and reaches the best when the shell thickness is around 1.0 cm.
Zhao, S, Cheng, E, Qiu, X, Lacey, J & Maisch, S 1970, 'A method of configuring fixed coefficient active noise controllers for traffic noise reduction', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, Hong Kong, China.
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In practical applications of Active Noise Control (ANC) systems on traffic noise reduction, the noise sources to be controlled are usually far away from the system and are continuously moving, hence there are no fixed noise sources for configuring the controller. This paper proposes a method to configure fixed coefficient ANC systems for the scenario of traffic noise reduction. In the tuning process, a pseudo noise source is proposed to be placed near a single channel ANC system to adjust the controller. After the optimal coefficients of the controller are obtained for this situation, the coefficients are fixed and the ANC system is utilized to cancel the actual noise source in the far-field. Simulation results showed that when the noise source is a point source located very far away from the ANC system, moving the pseudo noise source farther away from the single-channel ANC system can effectively increase the noise reduction. However, if the noise source is closer to the single-channel ANC system than the pseudo noise source, the performance deteriorates quickly. When the primary noise originates from a line array of incoherent point sources far from the ANC system, moving the pseudo noise source farther away from the system can effectively increase the noise reduction; however, the performance of the single channel ANC system decreases with frequency and deteriorates when there are many noise sources present simultaneously as in the traffic noise scenario. Experiments were conducted in a laboratory environment for one noise source and three noise sources, and the results are consistent with the simulations.
Zheng, L, Liang, B & Jiang, A 1970, 'Recent Advances of Deep Learning for Sign Language Recognition', 2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), International Conference on Digital Image Computing - Techniques and Applications (DICTA), IEEE, AUSTRALIA, Sydney, pp. 454-460.
Zheng, L, Liang, B & Jiang, A 1970, 'Recent Advances of Deep Learning for Sign Language Recognition', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-7.
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© 2017 IEEE. To assist the social interaction of deaf and hearing impaired people, efficient interactive communication tools is expected. With the growing research interest in action and gesture recognition in the last years, many successful applications for sign language recognition comprise new types of sensors including low-cost depth camera and advanced machine learning technologies. In this paper, we present a complete overview of deep learning based methodologies for sign language recognition. We discuss various types of such approaches designed for the recognition from viewpoints of available modalities provided by depth sensors, feature extraction and classification. In addition, we summarise the currently available datasets of sign language, including gestures of finger spelling and vocabulary words, which can be used as an assessing tool for those people who are learning sign languages. We then discuss the main current research works with particular interest on how they treat the different types of data, discussing their main features and identify opportunities and challenges for future research.
Zheng, L, Zhu, J, Wang, G, Dah-Chuan Lu, D, McLean, P & He, T 1970, 'Model predictive control based balancing strategy for series-connected lithium-ion battery packs', 2017 19th European Conference on Power Electronics and Applications (EPE'17 ECCE Europe), 2017 19th European Conference on Power Electronics and Applications (EPE'17 ECCE Europe), IEEE, Warsaw, Poland, pp. P.1-P.8.
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© assigned jointly to the European Power Electronics and Drives Association & the Institute of Electrical and Electronics Engineers (IEEE). For reducing the inconsistent state of charges (SOCs) of lithium-ion battery cells and making the full use of battery packs, effective battery balancing technology should be in place for battery management systems. Since aged battery packs usually suffer from not only non-uniform cell SOCs and voltages but also non-uniform cell capacities, it is more challenging to balance an aged battery pack than a new one. This paper proposes a model predictive control (MPC) based balancing strategy to fully charge battery packs under such inconsistent conditions, especially for aged battery packs. The algorithm of the proposed strategy for computing the required average balancing current and the predicted balancing current for each cell is presented, followed by employing a minimum cost function value between these two currents to control the operation model of the equalizer for each cell. The simulation results verify the effectiveness of the proposed approach. Compared with the conventional average SOC strategy, the proposed MPC based strategy can effectively avoid over-equalization during the balancing process, thus reducing balancing energy consumption.
Zheng, L, Zhu, J, Wang, G, Lu, DD-C, McLean, P & He, T 1970, 'Experimental analysis and modeling of temperature dependence of lithium-ion battery direct current resistance for power capability prediction', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, Australia, pp. 1-4.
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© 2017 IEEE. Accurate lithium-ion battery power capability prediction gives an indication for managing power flows in or out of batteries within the safe operating area, which is one of the primary challenging functions of battery management systems (BMSs). The battery direct current resistance (DCR) is typically employed for power capability prediction, but its characteristic depends significantly on the ambient temperature. It is essential to investigate systematically the temperature dependence of battery DCR for achieving reliable power capability prediction. Based on a large amount of battery test data, a battery DCR model is proposed for quantitatively describing its temperature dependence. This model is then applied for battery power capability prediction, and the results are verified by experimental results.
Zheng, Y, Ghosh, S & Li, J 1970, 'An Optimized Drug Similarity Framework for Side-effect Prediction', Computing in Cardiology Conference (CinC), 2017 Computing in Cardiology Conference, Computing in Cardiology, Rennes, France, pp. 1-4.
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© 2017 IEEE Computer Society. All rights reserved. Drug side-effects are crucial issues in both the pre-market drug developing process and post-market drug clinical applications. They contribute to one-third of drug failures and cause significant fatality and severe morbidity. Thus the early identification of potential drug side-effects is of great interests. Most existing methods essentially rely on leveraging few drug similarities directly for side-effect predictions, ignoring the performance improvement by drug similarity integration and optimization. In this study, we proposed an optimized drug similarity framework (ODSF) to improve the performance of side-effect predictions. First, this framework integrates four different drug similarities into a comprehensive similarity. Next, the comprehensive similarity is optimized via clustering and then enhanced by indirect drug similarity. Finally, the optimized drug similarity is employed for side-effect predictions. The performance of ODSF was evaluated on simulative side-effect predictions of 917 drugs from the DrugBank. Extensive comparison experiments demonstrate that ODSF is competent to capture drug features from diverse perspectives and the prediction performance is significantly improved owing to the optimized drug similarity.
Zhenpo, W, Jianyang, W, Jingna, Z, Li, L & Lei, Z 1970, 'Direct yaw-moment control of a FWIA EV based on sliding model control and torque allocation optimization', IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IEEE, Beijing, China, pp. 4615-4620.
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© 2017 IEEE. In this paper, a direct yaw-moment control (DYC) scheme is proposed for a four-wheel-independently-actuated electric vehicle (FWIA EV). An upper controller is based on a reference model with two degrees of freedom (2-DOF) that generates the desired yaw rate for a sliding mode controller to track so as to improve the vehicle dynamic stability. A torque optimization distribution strategy is designed in the lower controller to allocate the required torques to each in-wheel motor for vehicle stability enhancement. The proposed DYC scheme is implemented in a Carmaker vehicle model and a MATLAB/Simulink control model and evaluated in simulations of a snake-lane-change and a double-lane-change maneuver. The results show that the side slip angle and tire load rate have been reduced, on average, by 2/3 using the DYC system compared with those without control. The cases with DYC also provide better tracking of the desired trajectory and yaw rate with smaller steering angle than those without control.
Zhong, R, Indraratna, B, Rujikiatkamjorn, C, Kan, M, Vincent, P & Ryan, G 1970, 'A Model for Vacuum-assisted Soft Soil Consolidation with PVDs', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2685-2688.
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To maintain the ground stability and reduce the post-construction settlement, the soft deposits characterised by high water content, high compressibility and low permeability need to be treated by an appropriate ground improvement method prior to the construction of infrastructure. Application of PVD is a well-practiced ground improvement method for consolidating the soft clays. PVD can be used in conjunction with a fill surcharge, vacuum pressure or a combination of the two. An analytical unit cell model was proposed to capture the large strain geometry and the non-linear soil properties during the large settlement. This model showed an advantage over the traditional model in predicting the soft ground consolidation behaviour. In this paper, this model is used to analyse some case histories.
Zhong, Y, Zhu, JB, Dutkiewicz, E, Jiang, T & Zhou, Z 1970, 'Device-free sensing for classification of human activities using high-order cumulant algorithm', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-4.
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© 2017 IEEE. In this paper, the possibility of using an emerging approach, namely device-free sensing (DFS) technology, for classification of human activities is investigated. To fully evaluate this approach, several samples have been collected in an outdoor open-field environment. Using the collected data along with a classifier, a high-order cumulant (HOC) based feature extraction algorithm is investigated. To demonstrate the improvement of using this algorithm, the classical approach that is based on received-signal strength (RSS) is chosen as a benchmark. The experiment results demonstrated that the classification accuracy of the proposed algorithm is better than the classical approach by at least 15%. In addition, the reliability of the presented approach due to variation of training samples and signal-to-noise ratio (SNR) are also carefully tested using experimentally recorded samples, so that a good reliability can be ensured.
Zhou, J, Arshad, SZ, Luo, S & Chen, F 1970, 'Effects of Uncertainty and Cognitive Load on User Trust in Predictive Decision Making', HUMAN-COMPUTER INTERACTION - INTERACT 2017, PT IV, 16th IFIP TC 13 International Conference on Human-Computer Interaction (INTERACT), Springer International Publishing, Indian Inst Technol, Mumbai, INDIA, pp. 23-39.
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Zhou, J, Arshad, SZ, Luo, S, Yu, K, Berkovsky, S & Chen, F 1970, 'Indexing Cognitive Load using Blood Volume Pulse Features', Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, CHI '17: CHI Conference on Human Factors in Computing Systems, ACM, pp. 2269-2275.
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Physiological responses contain rich affective information even when humans are not expressing any external signs. In this paper, we investigate the use of the Blood Volume Pulse (BVP) signals for indexing cognitive load. An experiment, which introduced cognitive load as a secondary task in a decision making context was conducted in the study. BVP signals were analyzed in order to establish relationships between BVP and cognitive load levels. A set of features (e.g. peak and max features) was found to be significantly distinctive across different cognitive load levels. The identified BVP features can be used to set up machine learning models for the automatic classification of CL levels in intelligent systems.
Zhou, J, Li, Z, Zhi, W, Liang, B, Moses, D & Dawes, L 1970, 'Using Convolutional Neural Networks and Transfer Learning for Bone Age Classification', 2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), International Conference on Digital Image Computing - Techniques and Applications (DICTA), IEEE, Sydney, AUSTRALIA, pp. 17-22.
Zhou, J, Li, Z, Zhi, W, Liang, B, Moses, D & Dawes, L 1970, 'Using Convolutional Neural Networks and Transfer Learning for Bone Age Classification', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1-6.
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© 2017 IEEE. The bone age of a child indicates the skeletal and biological maturity of an individual. The most commonly applied clinical methods for Bone Age Assessment (BAA) are based on the visual examination of ossification of individual bones in radiographs of the left hand and the wrist by comparing with standard hand atlas. This kind of method is highly subjective and the performance extremely depends on practitioners' experiences. This paper investigates the use of Deep Convolutional Neural Networks (DCNNs) for the automatic bone age assessment. As there exists no large-scale annotated medical image dataset comparable to ImageNet for medical image analysis, this paper uses transfer learning within DCNNs to perform bone age classifications making full use of advantages of DCNNs. We define various Regions of Interest (ROIs) based on domain knowledge, for each of which a local bone age classification model is achieved by fine-tuning the pre-trained VGGNet with corresponding ROI patches. A final bone age classification is obtained by fusing multiple regional models. The results show that the proposed approach outperforms the current state-of-the-art classification methods in BAA with small dataset.
Zhou, L & Ying, M 1970, 'Differential Privacy in Quantum Computation.', CSF, IEEE Computer Security Foundations Symposium, IEEE Computer Society, Santa Barbara, CA, USA, pp. 249-262.
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© 2017 IEEE. More and more quantum algorithms have been designed for solving problems in machine learning, database search and data analytics. An important problem then arises: how privacy can be protected when these algorithms are used on private data? For classical computing, the notion of differential privacy provides a very useful conceptual framework in which a great number of mechanisms that protect privacy by introducing certain noises into algorithms have been successfully developed. This paper defines a notion of differential privacy for quantum information processing. We carefully examine how the mechanisms using three important types of quantum noise, the amplitude/phase damping and depolarizing, can protect differential privacy. A composition theorem is proved that enables us to combine multiple privacy-preserving operations in quantum information processing.
Zhou, Y, Ni, W, Zheng, K, Liu, RP & Yang, Y 1970, 'Node-centric route mutation for large-scale SDN based on 3D earth mover's distance model', 2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017 17th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Cairns, QLD, Australia, pp. 1-6.
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© 2017 IEEE. Exploiting software-defined networking techniques, randomly and instantly mutating routes can disguise strategically important infrastructure, and protect the integrity of data networks. Route mutation has been to date formulated as NP-complete constraint satisfaction problems where feasible sets of routes need to be generated with exponential computational complexities, limiting algorithmic scalability to large-scale networks. In this paper, we propose a novel node-centric route mutation method which interprets route mutation as a signature matching problem. We formulate the route mutation problem as a three-dimensional earth mover's distance (EMD) model and solve it by using a binary branch and bound method. Considering the scalability, we further propose a heuristic method yields significantly lower computational complexities with marginal loss of robustness against eavesdropping. Simulation results show that our proposed methods can effectively disguise key infrastructure by reducing the difference of historically accumulative traffic among different switches. With significantly reduced complexities, our algorithms are of particular interest to safeguard large-scale networks.
Zhou, Z, Xu, G, Zhu, W, Li, J & Zhang, W 1970, 'Structure embedding for knowledge base completion and analytics', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, Alaska, USA, pp. 737-743.
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To explore the latent information of Human Knowledge, the analysis for Knowledge Bases (KBs) (e.g. WordNet, Freebase) is essential. Some previous KB element embedding frameworks are used for KBs structure analysis and completion. These embedding frameworks use low-dimensional vector space representation for large scale of entities and relations in KB. Based on that, the vector space representation of entities and relations which are not contained by KB can be measured. The embedding idea is reasonable, while the current embedding methods have some issues to get proper embeddings for KB elements. The embedding methods use entity-relation-entity triplet, contained by most of current KB, as training data to output the embedding representation of entities and relations. To measure the truth of one triplet (The knowledge represented by triplet is true or false), some current embedding methods such as Structured Embedding (SE) project entity vectors into subspace, the meaning of such subspace is not clear for knowledge reasoning. Some other embedding methods such as TransE use simple linear vector transform to represent relation (such as vector add or minus), which can't deal with the multiple relations match or multiple entities match problem. For example, there are multiple relations between two entities, or there are multiple entities have same relation with one entity. Insipred by previous KB element structured embedding methods, we propose a new method, Bipartite Graph Network Structured Embedding (BGNSE). BGNSE combines the current KB embedding methods with bipartite graph network model, which is widely used in many fields including image data compression, collaborative filtering. BGNSE embeds each entity-relation-entity KB triplet into a bipartite graph network structure model, represents each entity by one bipartite graph layer, represents relation by link weights matrix of bipartite graph network. Based on bipartite graph model, our proposed method has followi...
Zhou, Z, Xu, G, Zhu, X & Liu, S 1970, 'Latent factor analysis for low-dimensional implicit preference prediction', 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), IEEE, Poland, pp. 1-2.
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© 2017 IEEE. User preference prediction aims to predict a users future preferences on a large number of items according to his/her preference history. To achieve this goal, many models have been proposed, but mainly for explicit preference data, such as 5-star ratings. Nevertheless, real-world data are often in implicit format, such as purchase action, and the number of items is not always large. In this paper, we demonstrate the use of latent factor models for solving the task of predicting user preferences on implicit and low-dimensional dataset.
Zhu, F, Zhang, G, Lu, J & Zhu, D 1970, 'First-order causal process for causal modelling with instantaneous and cross-temporal relations', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, USA, pp. 380-387.
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© 2017 IEEE. Motivated by the real damped simple harmonic oscillator (SHO) system, in this paper, we propose a process interpretation of causality and the first-order causal process (FoCP) model for temporal causal modelling. Compared with existing causal models that are able to model feedbacks, such as the structural equation model (SEM) and the structure vector autoregressive (SVAR) model, the FoCP model entails a novel 2-stage evolution semantic for instantaneous and cross-temporal causal relations existing in many real world dynamic systems. Graphical representations are developed to illustrate the causal structure compactly. Useful properties of the new model are identified and used to develop a conditional independence based algorithm for learning the causal structure from a multivariate time series dataset. Experiments on both simulated and real data validate the feasibility of the method to discover simple while meaningful causal structures of dynamic systems.
Zhu, HL, Ding, C, Wei, G & Guo, YJ 1970, 'A novel base station antenna based on rectangular waveguide', ISAP 2016 - International Symposium on Antennas and Propagation, International Symposium on Antennas and Propagation (ISAP), IEEE, Okinawa, Japan, pp. 196-197.
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A novel base station antenna element is proposed. It consists of a surface of parallel strips to rotate the polarization direction and a segment of a rectangular waveguide. The surface is designed on a single-sided substrate, which has the same area as the aperture of the waveguide. In assembling, the non-copper side of the substrate is placed in direct contact with the aperture of the waveguide antenna. To achieve the polarization rotation, the parallel strips on the surface are rotated by 45° with respect to the walls of the waveguide antenna. By adding the surface, the linear polarization direction of the rectangular waveguide antenna is rotated by 45° to comply with the requirements of cellular industry. SMA connector with a conical probe is used as the coaxial-to-waveguide adaptor. Results have shown that the proposed antenna has a fractional impedance bandwidth of 35%, and a stable radiation pattern is also achieved.
Zhu, L, Huang, Z, Chang, X, Song, J & Shen, HT 1970, 'Exploring Consistent Preferences', Proceedings of the 25th ACM international conference on Multimedia, MM '17: ACM Multimedia Conference, ACM, Mountain View, California, USA, pp. 726-734.
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© 2017 ACM. Content-based visual landmark search (CBVLS) enjoys great importance in many practical applications. In this paper, we propose a novel discrete hashing with pair-exemplar (DHPE) to support scalable and efficient large-scale CBVLS. Our approach mainly solves two essential problems in scalable landmark hashing: 1) Intralandmark visual diversity, and 2) Discrete optimization of hashing codes. Motivated by the characteristic of landmark, we explore the consistent preferences of tourists on landmark as pair-exemplars for scalable discrete hashing learning. In this paper, a pair-exemplar is comprised of a canonical view and the corresponding representative tags. Canonical view captures the key visual component of landmarks, and representative tags potentially involve landmark-specific semantics that can cope with the visual variations of intra-landmark. Based on pair-exemplars, a unified hashing learning framework is formulated to combine visual preserving with exemplar graph and the semantic guidance from representative tags. Further to guarantee direct semantic transfer for hashing codes and remove information redundancy, we design a novel optimization method based on augmented Lagrange multiplier to explicitly deal with the discrete constraint, the bit uncorrelated constraint and balance constraint. The whole learning process has linear computation complexity and enjoys desirable scalability. Experiments demonstrate the superior performance of DHPE compared with state-of-the-art methods.
Zhu, L, Xu, Z & Yang, Y 1970, 'Bidirectional Multirate Reconstruction for Temporal Modeling in Videos', 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, pp. 1339-1348.
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Zhu, X, Li, L, Zhang, W, Rao, T, Xu, M, Huang, Q & Xu, D 1970, 'Dependency Exploitation: A Unified CNN-RNN Approach for Visual Emotion Recognition', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Twenty-Sixth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, Melbourne, Australia, pp. 3595-3601.
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Visual emotion recognition aims to associate images with appropriate emotions. There are different visual stimuli that can affect human emotion from low-level to high-level, such as color, texture, part, object, etc. However, most existing methods treat different levels of features as independent entity without having effective method for feature fusion. In this paper, we propose a unified CNN-RNN model to predict the emotion based on the fused features from different levels by exploiting the dependency among them. Our proposed architecture leverages convolutional neural network (CNN) with multiple layers to extract different levels of features with in a multi-task learning framework, in which two related loss functions are introduced to learn the feature representation. Considering the dependencies within the low-level and high-level features, a new bidirectional recurrent neural network (RNN) is proposed to integrate the learned features from different layers in the CNN model. Extensive experiments on both Internet images and art photo datasets demonstrate that our method outperforms the state-of-the-art methods with at least 7% performance improvement.
Zhu, XQ, Law, SS & Samali, B 1970, 'Railway track condition monitoring using dynamic measurements on in-service vehicles', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press, Perth, Australia, pp. 1565-1569.
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Railway track is one of the most important parts for the railway system and its condition monitoring is essential to ensure the safety of the system. Currently, the track condition is inspected by the stationary equipments or specified low-speed track inspection vehicle. The track inspection needs close the railway system. An adaptive regularization approach has been developed to identify the parameters of the track substructure from dynamic measurements on the in-service vehicles in this paper. The vehicle-track interaction system is modelled as the discrete mass-spring model on Winkler elastic foundation. The damage is defined as the stiffness reduction of the track that includes the foundation settlement, damaged rail fastener and damaged ballast. Numerical results show that the approach can identify all stiffness parameters successfully at normal moving speed and in high sampling frequency with measurement noise.
Zhu, XQ, Samali, B, Rashidi, M & Alamdari, MM 1970, 'Long-term vibration monitoring of a cable-stayed bridge: Effects of environmental and operational conditions', SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings, International Conference on Structural Health Monitoring of Intelligent Infrastructure, Australia, pp. 1132-1138.
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This study is to investigate the effects of environmental and operational conditions on the dynamic behaviour of bridge structures. A long-term monitoring system has been installed on a cable-stayed bridge and there are 24 accelerometers on bridge deck. Monitoring data from two typical days have been analysed and the modal analysis is also carried out to extract modal parameters. Effects of changes in environmental and operational conditions, such as temperature and traffic, on structural dynamic properties are discussed.
Zhu, Y, Li, Y, Liu, J, Qin, L & Yu, JX 1970, 'GMAlign: A new network aligner for revealing large conserved functional components.', BIBM, IEEE International Conference on Bioinformatics and Biomedicine, IEEE Computer Society, Kansas City, MO, USA, pp. 120-127.
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© 2017 IEEE. The alignment of protein-protein interaction (PPI) networks is an effective approach to uncover the functionally conserved sub-structure between networks. A wealth of approaches have been developed for global PPI network alignment in recent years. However, due to the computational intractability caused by its NP-completeness, global PPI network alignment remains challenging in finding large conserved components stably for various PPI network pairs. In this paper, we introduce a novel global network aligner based on graph matching method called GMAlign. We assess the outperformance of GMAlign over the state-of-the-art network aligners on various PPI network pairs from the largest BioGRID dataset. It is shown that GMAlign not only can produce larger size alignment, but also can find bigger and denser common connected subgraphs robustly for the first time. Moreover, we shows that GMAlign can produce both structurally and functionally meaningful results in detecting large conserved biological pathways between species. The GMAlign software, datasets and supplementary experimental results can be downloaded.
Zijlema A., Van den Hoven E. & Eggen B. 1970, 'Preserving objects, preserving memories: repair professionals and object owners on the relation between memories and traces on personal possessions', PRODUCT LIFETIMES AND THE ENVIRONMENT (PLATE), 2nd Conference on Product Lifetimes and the Environment (PLATE), IOS Press, Delft Univ Technol, Fac Ind Design Engn, Delft, NETHERLANDS, pp. 453-457.
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Traces of ageing and use on the material of products, and memories associated with products, have been found to contribute to product attachment and can stimulate product longevity. We present findings of a qualitative study that focused on the relation between traces of ageing and use on personal possessions and memories and the effects of repair on objects. With this research, we intended to increase our understanding of the role of traces on personal possessions and memories. We interviewed five professionals at their workplace who worked as a restorer or did repairs of personal possessions, and five owners of a repaired or restored possession. The motivations for bringing an object for repair were not only related to the deteriorating condition of the object but were also triggered by situational events or circumstances, such as passing on ownership or knowing someone who could repair the object. We found five different categories of traces among the possessions of the interviewed object owners: Traces of use, traces of ageing, traces of repair, traces of accidents and alterations. We found that objects gained meaning after the repair. When object owners or repair professionals decided not to repair traces, it was often for aesthetical and reminding reasons, but also because it may be how the owner remembered the object. Traces can cue associations to their use in the past, and also to the (imagined) history of the objects. These findings indicate that repair can enhance the cueing of memories and that preservation of meaningful traces may contribute to attachment.
Zijlema, AF, Van den Hoven, E & Eggen, B 1970, 'What comes to mind when being triggered by personal items in the home? A qualitative exploration of cuing responses', Conference of Society for Applied Research in Memory and Cognition, Sydney, Australia.
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We investigated how personal holiday-items affect the retrieval of autobiographical memories. People often keep souvenirs, photos, and other acquired items from their holidays in their home. But what do the holiday-items evoke when people encounter them? We interviewed nine participants during a ‘home tour’, discussing holiday-items from one particular holiday while walking with the participant through their homes. Qualitative analysis resulted in four types of cuing responses: ‘no-memory’ responses, ‘know’ responses, ‘memory evoked think or feel’ responses, and ‘remember’ responses. For each of these responses, we discuss the item types and their characteristics, giving a peek into everyday life remembering.
Zuo, H, Zhang, G, Lu, J & Pedrycz, W 1970, 'Fuzzy rule-based transfer learning for label space adaptation', 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, ITALY, pp. 1-6.
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© 2017 IEEE. As the age of big data approaches, methods of massive scale data management are rapidly evolving. The traditional machine learning methods can no longer satisfy the exponential development of big data; there is a common assumption in these data-driving methods that the distribution of both the training data and testing data should be equivalent. A model built using today's data will not adequately address the classification tasks tomorrow if the distribution of the data item values has changed. Transfer learning is emerging as a solution to this issue, and many methods have been proposed. Few of the existing methods, however, explicitly indicate the solution to the case where the labels' distributions in two domains are different. This work proposes the fuzzy rule-based methods to deal with transfer learning problems where the discrepancy between the two domains shows in the label spaces. The presented methods are validated in both the synthetic and real-world datasets, and the experimental results verify the effectiveness of the introduced methods.
Zuo, Y, Wu, Q, Zhang, J & An, P 1970, 'Minimum spanning forest with embedded edge inconsistency measurement for color-guided depth map upsampling', 2017 IEEE International Conference on Multimedia and Expo (ICME), 2017 IEEE International Conference on Multimedia and Expo (ICME), IEEE, Hong Kong, China, pp. 211-216.
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© 2017 IEEE. Color-guided depth map up-sampling, such as Markov-Random-Field-based (MRF-based) methods, is a popular depth map enhancement solution, which normally assumes edge consistency between color image and corresponding depth map. It calculates the coefficients of smoothness term in MRF according to such assumption. However, such consistency is not always true which leads to texture-copying artifacts and blurring depth edges. In this paper, we propose a novel coefficient computing scheme for smoothness term in MRF which is based on the distance between pixels in the Minimum Spanning Trees (Forest) to better preserve depth edges. The explicit edge inconsistency measurement is embedded into weights of edges in Minimum Spanning Trees, which significantly mitigates texture-copying artifacts. The proposed method is evaluated on Middlebury datasets and ToF-Mark datasets which demonstrates improved results compared with state-of-the-art methods.
