Abbas, SM, Desai, SC, Esselle, KP, Volakis, JL & Hashmi, RM 2018, 'Design and Characterization of a Flexible Wideband Antenna Using Polydimethylsiloxane Composite Substrate', International Journal of Antennas and Propagation, vol. 2018, pp. 1-6.
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The design and characterization of a simple, flexible wideband antenna using polydimethylsiloxane (PDMS) composite are presented. Conductive fibers are used to construct the metallic parts on a PDMS composite. To characterize the performance, two identical antennas are designed, one using the PDMS composite while the other on conventional dielectric materials. It was observed that both antennas behave well in terms of the matched bandwidth; however, the radiation towards the broadside direction is reduced when using the PDMS composite as substrate, particularly at higher frequencies. The antenna exhibits a matched bandwidth of 59.9%, ranging from 3.43 to 11.1 GHz. Moreover, the bending analysis carried out for different scenarios show that the wideband behavior of the antenna is well preserved and the variation reaches a maximum of 1% variation.
Abbasnejad, B, Thorby, W, Razmjou, A, Jin, D, Asadnia, M & Ebrahimi Warkiani, M 2018, 'MEMS piezoresistive flow sensors for sleep apnea therapy', Sensors and Actuators A: Physical, vol. 279, pp. 577-585.
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© 2018 Elsevier B.V. A MEMS liquid crystal polymer (LCP), used in the membrane-based pressure sensor, has been found highly useful as a flow sensor. Here we conducted a set of elaborate experiments using an air flow generator to investigate the potential of our LCP flow sensor for sleep apnea therapy. Critical properties of the LCP flow sensor, including flow range, resolution (sensitivity), accuracy, and response time, have been systematically characterized. As a result, LCP flow sensor achieves a limit of detection of 8 LPM to measure flow rate, better than the commercial flow sensor (>10 LPM). Our LCP flow sensor shows a favourable response in a large flow range (8–160 LPM) with a sensitivity of detecting a linear voltage response of 0.004 V per 1 LPM flow rate. With minimum detectable flow, high sensitivity and resolution, we further demonstrated our LCP flow sensor for detecting human respiration. Moreover, using a two- dimensional simulation in COMSOL Multiphysics, we demonstrated the deformation of LCP membrane in response to different flow velocities which leads to resistance change in sensor's strain gauge.
abbondanza, G & bailo, F 2018, 'the electoral payoff of immigration flows for anti-immigration parties: the case of Italy’s Lega Nord', European Political Science, vol. 17, no. 3, pp. 378-403.
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© 2017, European Consortium for Political Research. The aim of this article is to examine and quantify the relationship between regular immigration and voting for anti-immigration parties in Italy’s eight Northern regions – from 1992 to 2015 – and in Italy’s forty-five Northern provinces from 2004 to 2015. Firstly, we identified the Lega Nord as Italy’s main xenophobic party, then we used a fixed effects regression model for panel data to test our hypothesis, while controlling for a series of social, political and economic variables. Our results suggest that there is a positive and significant effect: an increase of 1 per cent in the number of new regular immigrants is associated with an increase of more than 2 per cent in the votes given to the Lega Nord; voter-turnout is significantly and negatively associated with Lega Nord’s vote-share, and a high perception of crime – but not actual crime – is positively associated with anti-immigration votes. At the provincial level, we also found a positive association between Muslim foreign population and Lega Nord’s vote-share. These results ought to be considered along with the fact that Northern Italy is highly representative of the wealthiest and most densely populated regions of Europe, suggesting the possibility that similar phenomena could be witnessed in other comparable contexts.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 145-162.
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This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC–HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07–0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Review of studies on hydrological modelling in Malaysia', Modeling Earth Systems and Environment, vol. 4, no. 4, pp. 1577-1605.
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Hydrological models are vital component and essential tools for water resources and environmental planning and management. In recent times, several studies have been conducted with a view of examining the compatibility of model results with streamflow measurements. Some modelers are of the view that even the use of complex modeling techniques does not give better assessment due to soil heterogeneity and climatic changes that plays vital roles in the behavior of streamflow. In Malaysia, several public domain hydrologic models that range from physically-based models, empirical models and conceptual models are in use. These include hydrologic modeling system (HEC-HMS), soil water assessment tool (SWAT), MIKE-SHE, artificial neural network (ANN). In view of this, a study was conducted to evaluate the hydrological models used in Malaysia, determine the coverage of the hydrological models in major river basins and to identify the methodologies used (specifically model performance and evaluation). The results of the review showed that 65% of the studies conducted used physical-based models, 37% used empirical models while 6% used conceptual models. Of the 65% of physical-based modelling studies, 60% utilized HEC-HMS an open source models, 20% used SWAT (public domain model), 9% used MIKE-SHE, MIKE 11 and MIKE 22, Infoworks RS occupied 7% while TREX and IFAS occupy 2% each. Thus, indicating preference for open access models in Malaysia. In the case of empirical models, 46% from the total of empirical researches in Malaysia used ANN, 13% used Logistic Regression (LR), while Fuzzy logic, Unit Hydrograph, Auto-regressive integrated moving average (ARIMA) model and support vector machine (SVM) contributed 8% each. Whereas the remaining proportion is occupied by Numerical weather prediction (NWP), land surface model (LSM), frequency ratio (FR), decision tree (DT) and weight of evidence (WoE). Majority of the hydrological modelling studies utilized one or more statistical meas...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 67-84.
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The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Relationship between design floods and land use land cover (LULC) changes in a tropical complex catchment', Arabian Journal of Geosciences, vol. 11, no. 14.
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© 2018, Saudi Society for Geosciences. Rainfall characteristics are directly related to the climate of a basin, but this can only be noticed after a long period. Human activities, such as deforestation, tend to play a major role in transforming the land use land cover (LULC). Knowledge of the relationship between design floods and LULC is important in modeling and designing watershed management strategies. A study was conducted in the Kelantan River basin, Malaysia, to determine the impact of past and present LULC changes on peak discharge and runoff volumes. To achieve this, the basin was delineated into four catchments (Galas, Pergau, Nenggiri, and Lebir) due to its size and increased precision. Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was calibrated based on December 20–30th, 2014, flood in Kelantan. Flood hydrographs corresponding to 1984, 2002, and 2013 LULC conditions were simulated, and relative changes in peak discharge and runoff volume were determined for different return periods (2, 5, 10, 20, 50, 100 years). Results of LULC analysis showed that Galas recorded highest deforestation (54.35%). When the four catchments were compared with respect to highest contribution of outlet peak discharge, Lebir under 2013 LULC condition was the highest with 2847.70 m3/s. This was followed by Nenggiri (2196.90 m3/s), Galas (1252.7 m3/s), and Pergau (328.7 m3/s), all under the 2013 LULC condition. Results of unit response approach applied based on 50-year return period to the catchments for ranking their sub-basins revealed that the novel fa index developed in this study provides a better way of ranking sub-basins with respect to their contribution to the outlet and therefore is recommended for use. Methodologies developed in this study may be useful to land use planners from around the world which when applied can provide alternatives that will minimize the adverse effects of floods.
Abdullahi, S & Pradhan, B 2018, 'Land use change modeling and the effect of compact city paradigms: integration of GIS-based cellular automata and weights-of-evidence techniques', Environmental Earth Sciences, vol. 77, no. 6.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In recent decades, attaining urban sustainability is the primary goal for urban planners and decision makers. Among various aspects of urban sustainability, environmental protection such as agricultural and forest conservations is very important in tropical countries like Malaysia. In this regard, compact urban development due to high density, rural development containment is known as the most sustainable urban forms. This paper attempts to propose an integrated modeling approach to predict the future land use changes by considering city compactness paradigms. First, the cellular automata (CA) were applied for calculating land use conversion. Next, weights-of-evidence (WoE) which is based on Bayes theory was utilized to calibrate CA model and to support the transitional rule assessment. Several urban-related parameters as well as compact city indicators were utilized to estimate the future land use maps. The results showed how compact development parameters and site characteristics can be combined using the WoE model to predict the probability of land use changes. The modeling approach supports the essential logic of probabilistic methods and indicates that spatial autocorrelation of various land use types and accessibility is the main drivers of urban land use changes.
Abdullahi, S, Pradhan, B & Mojaddadi, H 2018, 'City Compactness: Assessing the Influence of the Growth of Residential Land Use', Journal of Urban Technology, vol. 25, no. 1, pp. 21-46.
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© 2017 The Society of Urban Technology. In the urban sprawl paradigm, residential land use exhibits a more significant growth than other categories. Consequently, large proportions of the natural environment are converted to residential areas, particularly in tropical countries. Compact urban development is one of the most sustainable urban forms with environmental perspectives, such as rural development containment and natural environment preservation. However, no proper investigation of the relationship and influence of residential growth and city compactness is available. This study evaluated and forecasted the residential development of Kajang City in Malaysia based on compact development. First, the relationship between residential land use change and city compactness was evaluated. Second, residential growth was projected by utilizing the land transformation model (LTM) and the statistical-based weight of evidence (WoE) using various spatial parameters. Both models were evaluated with respect to observed land use and compactness maps. Results indicated that most of the newly developed residential areas were in zones where the degrees of compactness increase during certain periods. In addition, LTM performed better and provided a more accurate modeling of residential growth than the WoE. However, WoE provided clearer and more informative results than LTM in terms of functional relationships between dependent and independent variables related to city compactness.
Abedin, B & Babar, A 2018, 'Institutional vs. Non-institutional use of Social Media during Emergency Response: A Case of Twitter in 2014 Australian Bush Fire', Information Systems Frontiers, vol. 20, no. 4, pp. 729-740.
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© 2017 Springer Science+Business Media, LLC Social media plays a significant role in rapid propagation of information when disasters occur. Among the four phases of disaster management life cycle: prevention, preparedness, response, and recovery, this paper focuses on the use of social media during the response phase. It empirically examines the use of microblogging platforms by Emergency Response Organisations (EROs) during extreme natural events, and distinguishes the use of Twitter by EROs from digital volunteers during a fire hazard occurred in Australia state of Victoria in early February 2014. We analysed 7982 tweets on this event. While traditionally theories such as World System Theory and Institutional Theory focus on the role of powerful institutional information outlets, we found that platforms like Twitter challenge such notion by sharing the power between large institutional (e.g. EROs) and smaller non-institutional players (e.g. digital volunteers) in the dissemination of disaster information. Our results highlight that both large EROs and individual digital volunteers proactively used Twitter to disseminate and distribute fire related information. We also found that the contents of tweets were more informative than directive, and that while the total number of messages posted by top EROs was higher than the non-institutional ones, non-institutions presented a greater number of retweets.
Abedin, B & Qahri-Saremi, H 2018, 'Introduction to the Special Issue — Social Computing and Service Innovation: A Framework for Research', Journal of Organizational Computing and Electronic Commerce, vol. 28, no. 1, pp. 1-8.
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Abeywickrama, HV, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Comprehensive Energy Consumption Model for Unmanned Aerial Vehicles, Based on Empirical Studies of Battery Performance', IEEE Access, vol. 6, pp. 58383-58394.
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© 2018 IEEE. Unmanned aerial vehicles (UAVs) are fast gaining popularity in a wide variety of areas and are already being used for a range of tasks. Despite their many desirable features, a number of drawbacks hinder the potential of UAV applications. As typical UAVs are powered by on-board batteries, limited battery lifetime is identified as a key limitation in UAV applications. Thus, in order to preserve the available energy, planning UAV missions in an energy efficient manner is of utmost importance. For energy efficient UAV mission planning, it is necessary to predict the energy consumption of specific UAV manoeuvring actions. Accurate energy prediction requires a reliable and realistic energy consumption model. In this paper, we present a consistent and complete energy consumption model for UAVs based on empirical studies of battery usage for various UAV activities. We considered the impact of different flight scenarios and conditions on UAV energy consumption when developing the proposed model. The energy consumption model presented in this paper can be readily used for energy efficient UAV mission planning.
Abolbashari, MH, Chang, E, Hussain, OK & Saberi, M 2018, 'Smart Buyer: A Bayesian Network modelling approach for measuring and improving procurement performance in organisations', Knowledge-Based Systems, vol. 142, pp. 127-148.
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© 2017 Elsevier B.V. Procurement, the act of buying goods or services from an external supplier, plays an important role in any organisation. To measure how well an organisation undertakes this activity, it needs to measure all associated Key Performance Indicators (KPIs). The current literature's major drawback in performing such a measurement is how to integrate the different KPIs, each of which captures a specific aspect of the organisation's performance. In this paper, we highlight this drawback and present our proposed Smart Buyer framework that is based on a Bayesian Network (BN) model capable of capturing and integrating the different KPIs. The measured procurement performance value can then be used by organisations to identify the areas in which they need to improve and develop plans to achieve this. Four scenarios are presented to show how the proposed BN model can be further used for analysis and decision making within organisations. Finally, a recent real-world procurement example is studied to demonstrate the applicability of the proposed Smart Buyer framework.
Abolhasan, M, Abdollahi, M, Ni, W, Jamalipour, A, Shariati, N & Lipman, J 2018, 'A Routing Framework for Offloading Traffic From Cellular Networks to SDN-Based Multi-Hop Device-to-Device Networks', IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1516-1531.
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IEEE Device-to-Device (D2D) Communications are set to form an integral part of future 5G wireless networks. D2D communications have a number of benefits such as improving energy efficiency and spectrum utilization. Until now much of the D2D research in LTE and 5G-type network scenarios have focused on direct (one-hop) communications between two adjacent mobile devices. In this paper, we propose a new routing framework called Virtual Ad hoc Routing Protocol (VARP). This framework introduces significant advantages such as better security, lower routing overheads, and higher scalability, when compared to conventional ad hoc routing protocols. It also reduces traffic overhead in LTE networks using multi-hop D2D communications under management of a SDN-controller. Further, it enables the development of various types of routing protocols for different networking scenarios. To this end, a source-routing based protocol was developed on top of VARP, referred to as VARP-S. We present a detailed analytical study of routing overhead in the VARP-S protocol, as compared to overhead analysis of our previous proposed Hybrid SDN Architecture for wireless distributed networks (HSAW)IEEENetworkMehran. Our results show that VARP-S, compared to HSAW, achieves higher network scalability and lower power consumption for mobile nodes.
Aboutorab, H, Saberi, M, Asadabadi, MR, Hussain, O & Chang, E 2018, 'ZBWM: The Z-number extension of Best Worst Method and its application for supplier development', Expert Systems with Applications, vol. 107, pp. 115-125.
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© 2018 Elsevier Ltd Best Worst Method (BWM) has recently been proposed as a method for Multi Criteria Decision Making (MCDM). Studies show that BWM compared with other methods such as Analytic Hierarchy Process (AHP), leads to lower inconsistency of the results while reducing the number of required pairwise comparisons. MCDM methods such as BWM require accurate information. However, it often happens in practice that a level of uncertainty accompanies the information. The main aim of this paper is to address this problem and provide an integration of BWM and Z-numbers, namely ZBWM. Providing BWM with Z-numbers enables the BWM method to handle the uncertainty of information of a multi-criteria decision. Additionally, the capabilities of the proposed method in the process of utilizing the linguistic information dealing with big data are highlighted. The proposed method is examined to address a supplier development problem. By experimental results, we show that ZBWM results lower inconsistency when compared with BWM. A Z-number contains subjectivity in its fuzzy part, which can be addressed in future applications of ZBWM.
Acosta, E, Wight, NM, Smirnov, V, Buckman, J & Bennett, NS 2018, 'Hydrogenated Nano-/Micro-Crystalline Silicon Thin-Films for Thermoelectrics', Journal of Electronic Materials, vol. 47, no. 6, pp. 3077-3084.
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© 2017, The Minerals, Metals & Materials Society. Thermoelectric technology has not yet been able to reach full-scale market penetration partly because most commercial materials employed are scarce/costly, environmentally unfriendly and in addition provide low conversion efficiency. The necessity to tackle some of these hurdles leads us to investigate the suitability of n-type hydrogenated microcrystalline silicon (μc-Si: H) in the fabrication of thermoelectric devices, produced by plasma enhanced chemical vapour deposition (PECVD), which is a mature process of proven scalability. This study reports an approach to optimise the thermoelectric power factor (PF) by varying the dopant concentration by means of post-annealing without impacting film morphology, at least for temperatures below 550°C. Results show an improvement in PF of more than 80%, which is driven by a noticeable increase of carrier mobility and Seebeck coefficient in spite of a reduction in carrier concentration. A PF of 2.08 × 10−4 W/mK2 at room temperature is reported for n-type films of 1 μm thickness, which is in line with the best values reported in recent literature for similar structures.
Adams, J, Lee, M & Peng, W 2018, 'Critical Review of Complementary and Alternative Medicine Use in Amyotrophic Lateral Sclerosis: Prevalence and Users’ Profile, Decision-Making, Information Seeking, and Disclosure in the Face of a Lack of Efficacy', Neurodegenerative Diseases, vol. 18, no. 4, pp. 225-232.
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<b><i>Background:</i></b> Despite a lack of evidence of clinical efficacy for complementary and alternative medicine (CAM) use in amyotrophic lateral sclerosis (ALS), these medicines remain popular around the world. <b><i>Objective:</i></b> To examine the prevalence and cost of CAM use in ALS and CAM users’ profile, decision-making, information seeking, and disclosure among ALS patients. <b><i>Methods:</i></b> A comprehensive literature search was conducted of MEDLINE, CINAHL/SCOPUS, and AMED databases from their inception to April 2018. This review followed PRISMA guidelines and employed a quality scoring system to assess the included papers. <b><i>Results:</i></b> Seven papers met the inclusion criteria and were thematically analysed. ALS patients utilized a range of CAM therapies and/or products, with acupuncture and vitamins being the most frequently reported. CAM modalities were often employed concurrently with conventional medications throughout the disease process. Although some ALS patients reported positive experience regarding CAM use, many were reluctant to disclose their CAM use to their clinicians. Research focusing on CAM use in ALS remains ad hoc and restricted to only a few countries. The rigour and quality of this research field to date has been varied, predominantly drawing upon regional/localized data and failing to report CAM users’ characteristics. <b><i>Conclusion:</i></b> A proportion of ALS patients report utilizing CAM concurrently with conventional treatments. Such use, set amidst a dearth of evidence for the efficacy of CAM in ALS, poses potential direct and indirect risks to patient care, and medical providers should be mindful of and enquire about CAM use when treating ALS patients.
Afifi, W, Abdel-Rahman, MJ, Krunz, M & MacKenzie, AB 2018, 'Full-Duplex or Half-Duplex: A Bayesian Game for Wireless Networks with Heterogeneous Self-Interference Cancellation Capabilities', IEEE Transactions on Mobile Computing, vol. 17, no. 5, pp. 1076-1089.
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© 2002-2012 IEEE. Recently, tremendous progress has been made in self-interference cancellation (SIC) techniques that enable a wireless device to transmit and receive data simultaneously on the same frequency channel, a.k.a. in-band full-duplex (FD). Although operating in FD mode significantly improves the throughput of a single wireless link, it doubles the number of concurrent transmissions, which limits the potential for coexistence between multiple FD-enabled links. In this paper, we consider the coexistence problem of concurrent transmissions between multiple FD-enabled links with different SIC capabilities; each link can operate in either FD or half-duplex mode. First, we consider two links and formulate the interactions between them as a Bayesian game. In this game, each link tries to maximize its throughput while minimizing the transmission power cost. We derive a closed-form expression for the Bayesian Nash equilibrium and determine the conditions under which no outage occurs at either link. Then, we study the coexistence problem between more than two links, assuming that each link is only affected by its dominant interfering link. We show that under this assumption, no more than two links will be involved in a single game. Finally, we corroborate our analytical findings via extensive simulations and numerical results.
Afzal, MU, Esselle, KP & Lalbakhsh, A 2018, 'A Methodology to Design a Low-Profile Composite-Dielectric Phase-Correcting Structure', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 7, pp. 1223-1227.
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Afzal, MU, Lalbakhsh, A & Esselle, KP 2018, 'Electromagnetic-wave beam-scanning antenna using near-field rotatable graded-dielectric plates', Journal of Applied Physics, vol. 124, no. 23, pp. 234901-234901.
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Agrawal, DP, Gupta, BB, Wang, H, Chang, X, Yamaguchi, S & Perez, GM 2018, 'Guest Editorial Deep Learning Models for Industry Informatics', IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 3166-3169.
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Ahmadirouhani, R, Karimpour, M-H, Rahimi, B, Malekzadeh-Shafaroudi, A, Pour, AB & Pradhan, B 2018, 'Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting', International Journal of Image and Data Fusion, vol. 9, no. 3, pp. 237-262.
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The integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive field and mineralogy studies demonstrates that phyllic alteration zone associated with northwestern (NW)–southeastern (SE) structural fractures is a high potential zone for Cu–Fe–Au vein-type mineralisation in the Bajestan region, the Lut block, east Iran. The fractal pattern was calculated for fractures map using the Box-Counting algorithm to the SPOT-5 data. Statistical parameters of fractures, such as density, intensity and fractures’ intersection were also determined. Band composition, specialised band ratio and Spectral Angle Mapper (SAM) classification methods were implemented to the ASTER dataset for detecting hydrothermal alteration zones, such as propylitic, phyllic, argillic and gossan. Results indicate that the maximum value of the fractal dimension, intensity, density and the intersection of the fractures are concentrated in the NW and SE parts of SPOT image maps. In the other hand, phyllic alteration zone containing sericite, alunite, kaolinite and jarosite mineral assemblages was also identified in several zones of the NW and SE parts of the ASTER image maps. Integration of the results indicates the high potential zones for the occurrence of Cu–Fe–Au mineralisation in the Bajestan region.
Ahmed, A, Abu Bakar, MS, Azad, AK, Sukri, RS & Mahlia, TMI 2018, 'Potential thermochemical conversion of bioenergy from Acacia species in Brunei Darussalam: A review', Renewable and Sustainable Energy Reviews, vol. 82, pp. 3060-3076.
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Ahmed, AA, Pradhan, B, Sameen, MI & Makky, AM 2018, 'An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data', Arabian Journal of Geosciences, vol. 11, no. 11.
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© 2018, Saudi Society for Geosciences. This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene.
Ahmed, JB & Pradhan, B 2018, 'Termite mounds as bio-indicators of groundwater: Prospects and constraints', Pertanika Journal of Science and Technology, vol. 26, no. 2, pp. 479-498.
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Reliance on modern sophisticated equipment for making ‘discoveries’ has limited the human power of observing subtle clues in the environment that are capable of saving cost and labour that come with researching new resources and methods to improve life for all. Due to the growing scarcity of potable water, especially in African and Asian countries, newer, cheaper and reliable methods of investigating groundwater resources are becoming critical. One such potentially promising method is mapping the distribution of termite mounds in the environment. Termite mounds are conspicuous landscape features in tropical and sub-tropical regions of the world. Built from surrounding soils by several species of termite, the properties of mound soil are relatively different from the surrounding soil in most cases, indicating improved hydraulic properties. In this paper, the aim is to review the possibility of employing termite mounds as prospecting tools for groundwater search from three spatial scales of observation. From assessing the smallest to the highest scale of observation, it can be concluded that termite mounds’ prospect as surface indicators of groundwater is apparent. Review findings indicate increased surface water infiltration, presence of riparian tree vegetation and other trees with tap-root system around termite mounds, linear assemblage of termite mounds along aquiferous dykes and seep-lines as well as the dependence of termites on water but avoidance of places with risk of inundation. Whether they indicate permanent groundwater reserves in all cases or whether all species depend largely on water for their metabolism is a subject for further research.
Ahmed, MB, Johir, MAH, Khourshed, C, Zhou, JL, Ngo, HH, Nghiem, DL, Moni, M & Sun, L 2018, 'Sorptive removal of dissolved organic matter in biologically-treated effluent by functionalized biochar and carbon nanotubes: Importance of sorbent functionality', Bioresource Technology, vol. 269, pp. 9-17.
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The sorptive removal of dissolved organic matter (DOM) in biologically-treated effluent was studied by using multi-walled carbon nanotube (MWCNT), carboxylic functionalised MWCNT (MWCNT-COOH), hydroxyl functionalized MWCNT (MWCNT-OH) and functionalized biochar (fBC). DOM was dominated by hydrophilic fraction (79.6%) with a significantly lower hydrophobic fraction (20.4%). The sorption of hydrophobic DOM was not significantly affected by the sorbent functionality (∼10.4% variation) and sorption capacity followed the order of MWCNT > MWCNT-COOH > MWCNT-OH > fBC. In comparison, the sorption of hydrophilic fraction of DOM changed significantly (∼37.35% variation) with the change of sorbent functionality with adsorption capacity decreasing as MWCNT-OH > MWCNT-COOH > MWCNT > fBC. Furthermore, the affinity of adsorbents toward a hydrophilic compound (dinitrobenzene), a hydrophobic compound (pyrene) and humic acid was also evaluated to validate the proposed mechanisms. The results provided important insights on the type of sorbents which are most effective to remove different DOM fractions.
Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH & Sornalingam, K 2018, 'Sorptive removal of phenolic endocrine disruptors by functionalized biochar: Competitive interaction mechanism, removal efficacy and application in wastewater', Chemical Engineering Journal, vol. 335, pp. 801-811.
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Sorptive removal of six phenolic endocrine disrupting chemicals (EDCs) estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2), bisphenol A (BPA) and 4-tert-butylphenol (4tBP) by functionalized biochar (fBC) through competitive interactions was investigated. EDC sorption was pH dependent with the maximum sorption at pH 3.0-3.5 due to hydrogen bonds and π-π interactions as the principal sorptive mechanism. Sorption isotherm of the EDCs was fitted to the Langmuir model. Sorption capacities and distribution coefficient values followed the order E1 > E2 ≥ EE2 > BPA > 4tBP > E3. The findings suggested that EDC sorption occurred mainly through pseudo-second order and external mass transfer diffusion processes, by forming H-bonds along with π-π electron-donor-acceptor (EDA) interactions at different pH. The complete removal of ∼500 μg L-1 of each EDC from different water decreased in the order: deionised water > membrane bioreactor (MBR) sewage effluent > synthetic wastewater. The presence of sodium lauryl sulphonate and acacia gum in synthetic wastewater significantly suppressed sorption affinity of EDCs by 38-50%, hence requiring more fBC to maintain removal efficacy.
Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH, Sun, L, Asadullah, M & Belhaj, D 2018, 'Sorption of hydrophobic organic contaminants on functionalized biochar: Protagonist role of π-π electron-donor-acceptor interactions and hydrogen bonds', Journal of Hazardous Materials, vol. 360, pp. 270-278.
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The sorption of five potent endocrine disruptors as representative hydrophobic organic contaminants (HOCs) namely estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2) and bisphenol A (BPA) on functionalized biochar (fBC) was systematically examined, with a particular focus on the importance of π-electron-donor (phenanthrene: PHEN) and π-electron-acceptors (1,3-dinitrobenzene: DNB, p-amino benzoic acid: PABA) on sorption. Experimental results suggested that hydrogen-bond formation and π-π-electron-donor-acceptor (EDA) interactions were the dominant sorption mechanisms. The sorption of HOCs decreased as E1 > E2 > EE2 > E3 > BPA based on the Freundlich and Polanyi-Mane-models. The comparison of adsorption coefficient (Kd) normalized against hexadecane-water partition coefficient (KHW) between HOCs and PHEN indicated strong π-π-EDA interactions. π-π interactions among DNB, PHEN and HOCs were verified by the observed upfield frequency (Hz) shifts using proton nuclear magnetic resonance (1H NMR) which identified the specific direction of π-π interactions. UV-vis spectra showed charge-transfer bands for π-donors (PHEN and HOCs) with the model π-acceptor (DNB) also demonstrating the role of π-π EDA interactions. The role of π-electron-donor and π-electron-acceptor domains in fBC was identified at different solution pH.
Ahmmad, MS, Haji Hassan, MB & Kalam, MA 2018, 'Comparative corrosion characteristics of automotive materials in Jatropha biodiesel', International Journal of Green Energy, vol. 15, no. 6, pp. 393-399.
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Ait Lamqadem, A, Pradhan, B, Saber, H & Rahimi, A 2018, 'Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco', Sensors, vol. 18, no. 7, pp. 2230-2230.
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Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.
Akbari, MA, Aghaei, J, Barani, M, Niknam, T, Ghavidel, S, Farahmand, H, Korpas, M & Li, L 2018, 'Convex Models for Optimal Utility-Based Distributed Generation Allocation in Radial Distribution Systems', IEEE Systems Journal, vol. 12, no. 4, pp. 3497-3508.
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© 2007-2012 IEEE. This paper introduces various models for optimal and maximal utility-based distributed generation penetration in the radial distribution systems. Several problems with different probabilistic indices as objective functions constrained by power flow equations, distributed generation penetration, voltage, and thermal limits are proposed to obtain the optimal penetration of distributed generations on rural distribution networks. There are tradeoffs between interests and risks that the distribution network operators or distribution companies may be willing to take on. Thus, to have an effective method for maximal allocation of distributed generations, new indices are proposed, and the problems are formulated as a risk-constrained optimization model. The obtained problems have mixed-integer nonlinear programming and nonconvex forms because of nonlinearity and nonconvexity of the optimal power flow (OPF) equations and indices, leading to computationally nondeterministic polynomial-time-hard problems. Accordingly, in this paper, convex relaxations of OPF are introduced instead of the conventional nonlinear equations. Efficient linear equivalents of the objective function and constraints are introduced to reduce the computational burden. Test results of the proposed models on a radial distribution system are presented and discussed.
Akther, N, Daer, S & Hasan, SW 2018, 'Effect of flow rate, draw solution concentration and temperature on the performance of TFC FO membrane, and the potential use of RO reject brine as a draw solution in FO-RO hybrid systems', DESALINATION AND WATER TREATMENT, vol. 136, pp. 65-71.
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Al Muderis, MM, Lu, WY, Li, JJ, Kaufman, K, Orendurff, M, Highsmith, MJ, Lunseth, PA & Kahle, JT 2018, 'Clinically Relevant Outcome Measures Following Limb Osseointegration; Systematic Review of the Literature', Journal of Orthopaedic Trauma, vol. 32, no. 2, pp. e64-e75.
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Alabd, R, Safavi-Naeini, M, Wilson, KJ, Rosenfeld, AB & Franklin, DR 2018, 'A simulation study of BrachyShade, a shadow-based internal source tracking system for HDR prostate brachytherapy', Physics in Medicine & Biology, vol. 63, no. 20, pp. 205019-205019.
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This paper presents a simulation study of BrachyShade, a proposed internal source-tracking system for real time quality assurance in high dose rate prostate brachytherapy. BrachyShade consists of a set of spherical tungsten occluders located above a pixellated silicon photodetector. The source location is estimated by minimising the mean squared error between a parametric model of the shadow image and acquired images of the shadows projected on the detector plane. A novel algorithm is finally employed to correct the systemic error resulting from Compton scattering in the medium. The worst-case error obtained with BrachyShade for a 13.5 ms image acquisition is less than 1.3 mm in the most distant part of the treatment volume, while for 75% of source locations an error of less than 0.42 mm was achieved.
Alajlouni, D, Bliuc, D, Tran, T, Pocock, N, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Nonstandard Lumbar Region in Predicting Fracture Risk', Journal of Clinical Densitometry, vol. 21, no. 2, pp. 220-226.
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Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1-L2 BMD with standard L2-L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1-L2, L2-L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1-L2 BMD T-score was significantly lower than L2-L4 T-score in both genders (p < 0.0001). L1-L2 and L2-L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68-0.79) vs 0.68 (95% confidence interval, 0.62-0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1-L2 or L2-L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1-L2 is as good as but not better than L2-L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed.
Alavi, AH, Cui, Z, Gandomi, AH, Gao, X-Z, Wang, G-G & Lim, M-H 2018, 'Editorial', Memetic Computing, vol. 10, no. 2, pp. 121-122.
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Alazigha, DP, Indraratna, B, Vinod, JS & Heitor, A 2018, 'Mechanisms of stabilization of expansive soil with lignosulfonate admixture', Transportation Geotechnics, vol. 14, pp. 81-92.
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Aldebei, K, He, X, Jia, W & Yeh, W 2018, 'SUDMAD: Sequential and unsupervised decomposition of a multi-author document based on a hidden markov model', Journal of the Association for Information Science and Technology, vol. 69, no. 2, pp. 201-214.
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Decomposing a document written by more than one author into sentences based on authorship is of great significance due to the increasing demand for plagiarism detection, forensic analysis, civil law (i.e., disputed copyright issues), and intelligence issues that involve disputed anonymous documents. Among existing studies for document decomposition, some were limited by specific languages, according to topics or restricted to a document of two authors, and their accuracies have big room for improvement. In this paper, we consider the contextual correlation hidden among sentences and propose an algorithm for Sequential and Unsupervised Decomposition of a Multi‐Author Document (SUDMAD) written in any language, disregarding topics, through the construction of a Hidden Markov Model (HMM) reflecting the authors' writing styles. To build and learn such a model, an unsupervised, statistical approach is first proposed to estimate the initial values of HMM parameters of a preliminary model, which does not require the availability of any information of author's or document's context other than how many authors contributed to writing the document. To further boost the performance of this approach, a boosted HMM learning procedure is proposed next, where the initial classification results are used to create labeled training data to learn a more accurate HMM. Moreover, the contextual relationship among sentences is further utilized to refine the classification results. Our proposed approach is empirically evaluated on three benchmark datasets that are widely used for authorship analysis of documents. Comparisons with recent state‐of‐the‐art approaches are also presented to demonstrate the significance of our new ideas and the superior performance of our approach.
Alderighi, T, Malomo, L, Giorgi, D, Pietroni, N, Bickel, B & Cignoni, P 2018, 'Metamolds: computational design of silicone molds.', ACM Trans. Graph., vol. 37, no. 4, pp. 136:1-136:1.
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Alexander, TB, Gu, Z, Iacobucci, I, Dickerson, K, Choi, JK, Xu, B, Payne-Turner, D, Yoshihara, H, Loh, ML, Horan, J, Buldini, B, Basso, G, Elitzur, S, de Haas, V, Zwaan, CM, Yeoh, A, Reinhardt, D, Tomizawa, D, Kiyokawa, N, Lammens, T, De Moerloose, B, Catchpoole, D, Hori, H, Moorman, A, Moore, AS, Hrusak, O, Meshinchi, S, Orgel, E, Devidas, M, Borowitz, M, Wood, B, Heerema, NA, Carrol, A, Yang, Y-L, Smith, MA, Davidsen, TM, Hermida, LC, Gesuwan, P, Marra, MA, Ma, Y, Mungall, AJ, Moore, RA, Jones, SJM, Valentine, M, Janke, LJ, Rubnitz, JE, Pui, C-H, Ding, L, Liu, Y, Zhang, J, Nichols, KE, Downing, JR, Cao, X, Shi, L, Pounds, S, Newman, S, Pei, D, Guidry Auvil, JM, Gerhard, DS, Hunger, SP, Inaba, H & Mullighan, CG 2018, 'The genetic basis and cell of origin of mixed phenotype acute leukaemia', Nature, vol. 562, no. 7727, pp. 373-379.
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© 2018 Springer Nature Limited. All rights reserved. Mixed phenotype acute leukaemia (MPAL) is a high-risk subtype of leukaemia with myeloid and lymphoid features, limited genetic characterization, and a lack of consensus regarding appropriate therapy. Here we show that the two principal subtypes of MPAL, T/myeloid (T/M) and B/myeloid (B/M), are genetically distinct. Rearrangement of ZNF384 is common in B/M MPAL, and biallelic WT1 alterations are common in T/M MPAL, which shares genomic features with early T-cell precursor acute lymphoblastic leukaemia. We show that the intratumoral immunophenotypic heterogeneity characteristic of MPAL is independent of somatic genetic variation, that founding lesions arise in primitive haematopoietic progenitors, and that individual phenotypic subpopulations can reconstitute the immunophenotypic diversity in vivo. These findings indicate that the cell of origin and founding lesions, rather than an accumulation of distinct genomic alterations, prime tumour cells for lineage promiscuity. Moreover, these findings position MPAL in the spectrum of immature leukaemias and provide a genetically informed framework for future clinical trials of potential treatments for MPAL.
Alfaro-García, VG, Merigó, JM, Gil-Lafuente, AM & Kacprzyk, J 2018, 'Logarithmic aggregation operators and distance measures', International Journal of Intelligent Systems, vol. 33, no. 7, pp. 1488-1506.
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© 2018 Wiley Periodicals, Inc. The Hamming distance is a well-known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi-expert analysis and several of the newly introduced operators are utilized.
Ali, AR, Gabrys, B & Budka, M 2018, 'Cross-domain Meta-learning for Time-series Forecasting', Procedia Computer Science, vol. 126, pp. 9-18.
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Ali, SM, Kim, JE, Phuntsho, S, Jang, A, Choi, JY & Shon, HK 2018, 'Forward osmosis system analysis for optimum design and operating conditions', Water Research, vol. 145, pp. 429-441.
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Low energy consumption and less fouling propensity of forward osmosis (FO) processes have been attractive as a promising water filtration technology. The performance of this process is however significantly influenced by its operating conditions. Moreover, these operating parameters have both favourable and adverse effects on its performance. Therefore, it is very important to optimize its performance for efficient and economic operation. This study aims to develop a software to analyze a full-scale FO system for optimum performance. A comprehensive theoretical framework was developed to estimate the performance of FO system. Analysis results were compared with the experimental results to validate the models. About 5% deviation of simulation results and the experimental findings shows a very good agreement between them. A novel optimization algorithm was then developed to estimate the minimum required draw solution (DS) inlet flowrate and the number of elements in a pressure vessel to attain the design objectives (i.e. desired final DS concentration and recovery rate at a specific feed solution (FS) flowrate). A detailed parametric study was also conducted to determine the optimum operating conditions for different objectives. It showed that for a specific design objective, higher recovery rate can be achieved by increasing the DS flowrate and number of elements in a pressure vessel. In contrast, lower final concentration can be obtained by lowering the DS flowrate and increasing the number of elements. Finally, a MATLAB based software with graphical user interface was developed to make the analysis process easier and efficient.
Alizadeh, M, Hashim, M, Alizadeh, E, Shahabi, H, Karami, M, Beiranvand Pour, A, Pradhan, B & Zabihi, H 2018, 'Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings', ISPRS International Journal of Geo-Information, vol. 7, no. 11, pp. 444-444.
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Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.
Alizadeh, M, Ngah, I, Hashim, M, Pradhan, B & Pour, A 2018, 'A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment', Remote Sensing, vol. 10, no. 6, pp. 975-975.
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© 2018 by the authors. Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to aMultilayer Perceptron (MLP) neural network for producing an Earthquake VulnerabilityMap (EVM). Finally, an EVMwas produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for deci...
Alsahafi, YA & Gay, V 2018, 'An overview of electronic personal health records', Health Policy and Technology, vol. 7, no. 4, pp. 427-432.
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© 2018 Electronic Personal Health Record systems are providing health consumers with greater access and control to their health records by shifting these records from being a health provider-centred Electronic Health Record, to a patient-centred, Electronic Personal Health Record (ePHR). Based on the delivery system, ePHR systems are classified into standalone, tethered, and integrated or unified ePHRs. While national approaches of implementing integrated ePHR vary, the middle out method has been recognised as the ideal approach. It is worth considering the adoption of ePHRs has been slow due to several factors, including technical, individual, environmental, social, and legal factors. This paper provides a representative overview of an ePHR system, outlining its definition, types, architectures, and nationwide approaches of its implementation. Additionally, the drivers and hindrances to health consumer adoption are discussed.
Alshehri, MD, Hussain, FK & Hussain, OK 2018, 'Clustering-Driven Intelligent Trust Management Methodology for the Internet of Things (CITM-IoT)', Mobile Networks and Applications, vol. 23, no. 3, pp. 419-431.
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The growth and adoption of the Internet of Things (IoT) is increasing day by day. The large number of IoT devices increases the risk of security threats such as (but not limited to) viruses or cyber-attacks. One possible approach to achieve IoT security is to enable a trustworthy IoT environment in IoT wherein the interactions are based on the trust value of the communicating nodes. Trust management and trust assessment has been extensively studied in distributed networks in general and the IoT in particular, but there are still outstanding pressing issues such as bad-mouthing of trust values which prevent them from being used in practical IoT applications. Furthermore, there is no research in ensuring that the developed IoT trust solutions are scalable across billions of IoT nodes. To address the above-mentioned issues, we propose a methodology for scalable trust management solution in the IoT. The methodology addresses practical and pressing issues related to IoT trust management such as trust-based IoT clustering, intelligent methods for countering bad-mouthing attacks on trust systems, issues of memory-efficient trust computation and trust-based migration of IoT nodes from one cluster to another. Experimental results demonstrate the effectiveness of the proposed approaches.
Altaee, A 2018, 'Osmotic Power Plant: Process Innovation and Future Potential', Recent Advances in Petrochemical Science, vol. 4, no. 3, pp. 1-1.
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Osmotic power plant operating by Pressure Retarded Osmosis (PRO) is a promising technology for power generation from renewable resources. A wealth of literature has been published in PRO feasibility to replace conventional fossil fuel power plants. In this paper the PRO and the new innovative Dual Stage PRO process are briefly reviewed with the authors’ insight on the future development and application of the PRO power plants.
Altaee, A, Zaragoza, G, Millar, GJ, Sharif, AO & Alanezi, AA 2018, 'Limitations of osmotic gradient resource and hydraulic pressure on the efficiency of dual stage PRO process', DESALINATION AND WATER TREATMENT, vol. 105, pp. 11-22.
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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. The results showed that power density in stage one reached a maximum amount at , but the maximum net power generation occurred at . This result was mainly attributed to the variation of net driving pressure in stage one and two of the PRO process. The dual stage PRO process was found to perform better at high osmotic pressure gradient across the PRO membrane, for example when Dead Sea brine or highly concentrated NaCl was the draw solution. Total power generation in the dual stage PRO process was up to 40% higher than that in the conventional PRO process. This outcome was achieved through harvesting the rest of the energy remaining in the diluted draw solution. Therefore, a dual stage PRO process has the potential of maximizing power generation from a salinity gradient resource.
Alzoubi, YI, Gill, AQ & Moulton, B 2018, 'A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development.', J. Softw. Eng. Res. Dev., vol. 6, no. 4, pp. 4-4.
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Al-Zubaydi, AYT & Hong, G 2018, 'Experimental investigation of counter flow heat exchangers for energy recovery ventilation in cooling mode', International Journal of Refrigeration, vol. 93, pp. 132-143.
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© 2018 Elsevier Ltd and IIR Ventilation heat recovery is a system that requires low power to operate and has a high capacity to reduce the energy consumption and increase the overall efficiency for air conditioning. This paper reports the experimental investigation of air-to-air heat exchangers employed for heat recovery ventilation in cooling mode. The two main objective of this research are to design, fabricate and testing two polymers heat exchangers of different plate geometries and to evaluate and compare the thermal performance two quasi-counter flow plate heat exchangers. The key aims were to evaluate the effect of the surface geometry of the plates heat exchanger on the performance parameters specified in ANSI/ASHRAE Standard 84 and ANSI/AHRI Standard 1060 and narrow the gap of the limited experimental comparison of polymers sensible heat exchanger in cooling mode. The experiments were conducted on two polymer heat exchangers, one with a flat plate and the other with a dimpled surface plate. The experimental results showed that the cooling capacity of the dimpled surface heat exchanger as ventilation heat recovery system in cooling mode was 50–60% better than that of the flat surface plate heat exchanger. In addition, the sensible efficiency of the dimpled surface heat exchanger was higher than that of the flat surface plates heat exchanger at lower air velocities and higher air initial temperatures. The highest COP was 6.6 achieved with dimpled surface heat exchanger under primary air operating temperature of 32.6 °C.
Amjadipour, M, Tadich, A, Boeckl, JJ, Lipton-Duffin, J, MacLeod, J, Iacopi, F & Motta, N 2018, 'Quasi free-standing epitaxial graphene fabrication on 3C–SiC/Si(111)', Nanotechnology, vol. 29, no. 14, pp. 145601-145601.
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Growing graphene on SiC thin films on Si is a cheaper alternative to the growth on bulk SiC, and for this reason it has been recently intensively investigated. Here we study the effect of hydrogen intercalation on epitaxial graphene obtained by high temperature annealing on 3C-SiC/Si(111) in ultra-high vacuum. By using a combination of core-level photoelectron spectroscopy, low energy electron diffraction, and near-edge x-ray absorption fine structure (NEXAFS) we find that hydrogen saturates the Si atoms at the topmost layer of the substrate, leading to free-standing graphene on 3C-SiC/Si(111). The intercalated hydrogen fully desorbs after heating the sample at 850 °C and the buffer layer appears again, similar to what has been reported for bulk SiC. However, the NEXAFS analysis sheds new light on the effect of hydrogen intercalation, showing an improvement of graphene's flatness after annealing in atomic H at 600 °C. These results provide new insight into free-standing graphene fabrication on SiC/Si thin films.
Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 2018, 'Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring', ACM Transactions on Intelligent Systems and Technology, vol. 9, no. 6, pp. 1-20.
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One-class support vector machine (OCSVM) has been widely used in the area of structural health monitoring, where only data from one class (i.e., healthy) are available. Incremental learning of OCSVM is critical for online applications in which huge data streams continuously arrive and the healthy data distribution may vary over time. This article proposes a novel adaptive self-advised online OCSVM that incrementally tunes the kernel parameter and decides whether a model update is required or not. As opposed to existing methods, this novel online algorithm does not rely on any fixed threshold, but it uses the slack variables in the OCSVM to determine which new data points should be included in the training set and trigger a model update. The algorithm also incrementally tunes the kernel parameter of OCSVM automatically based on the spatial locations of the edge and interior samples in the training data with respect to the constructed hyperplane of OCSVM. This new online OCSVM algorithm was extensively evaluated using synthetic data and real data from case studies in structural health monitoring. The results showed that the proposed method significantly improved the classification error rates, was able to assimilate the changes in the positive data distribution over time, and maintained a high damage detection accuracy in all case studies.
Andrade-Valbuena, NA & Merigo, JM 2018, 'Outlining new product development research through bibliometrics', Journal of Strategy and Management, vol. 11, no. 3, pp. 328-350.
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Purpose
New product development (NPD) is a noteworthy field that has attracted the attention of scholars for its relevance for firm success. Based on bibliometric indicators and spatial distance network analysis, the authors outline the general structure overview of NPD research through the last 40 years of scientific production; identify and categorize key articles, authors, journals, institutions, and countries related to NPD research; identify and map the research subareas that have mostly contributed to the construction of NPD intellectual structure. The paper aims to discuss these issues.
Design/methodology/approach
The work uses the Web of Science Core Collection and the visualization of similarities viewer software. The analysis searches for all the documents connected to NPD available in the database. The graphical visualization maps the bibliographic data in terms of bibliographic coupling and co-citation.
Findings
The general NPD citation pattern evidences a construction of knowledge and learning, as evidenced in different subjects, such as biology or physics. Relevant contributions and contributors are highlighted as journals, articles, researchers, countries and institutions in overall NPD research and in its constituent subfields. Five subareas related to the NPD field based on journals and authors network are identified: marketing; operations and production; strategy; industrial engineering and operations; and management.
Originality/value
This paper contributes to the NPD literature by offering a global perspective on the field by using bibliometric data graphical networks, pr...
Ansari, AJ, Hai, FI, He, T, Price, WE & Nghiem, LD 2018, 'Physical cleaning techniques to control fouling during the pre-concentration of high suspended-solid content solutions for resource recovery by forward osmosis', Desalination, vol. 429, pp. 134-141.
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Ansari, AJ, Hai, FI, Price, WE, Ngo, HH, Guo, W & Nghiem, LD 2018, 'Assessing the integration of forward osmosis and anaerobic digestion for simultaneous wastewater treatment and resource recovery', Bioresource Technology, vol. 260, pp. 221-226.
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This study assessed the performance and key challenges associated with the integration of forward osmosis (FO) and anaerobic digestion for wastewater treatment and resource recovery. Using a thin film composite polyamide FO membrane, maximising the pre-concentration factor (i.e. system water recovery) resulted in the enrichment of organics and salinity in wastewater. Biomethane potential evaluation indicated that methane production increased correspondingly with the FO pre-concentration factor due to the organic retention in the feed solution. At 90% water recovery, about 10% more methane was produced when using NaOAc compared with NaCl because of the contribution of biodegradable reverse NaOAc flux. No negative impact on anaerobic digestion was observed when wastewater was pre-concentrated ten-fold (90% water recovery) for both draw solutes. Interestingly, the unit cost of methane production using NaOAc was slightly lower than NaCl due to the lower reverse solute flux of NaOAc, although NaCl is a much cheaper chemical.
Anshar, M & Williams, M-A 2018, 'Evolving robot empathy towards humans with motor disabilities through artificial pain generation', AIMS Neuroscience, vol. 5, no. 1, pp. 56-73.
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© 2018 the Author(s). In contact assistive robots, a prolonged physical engagement between robots and humans with motor disabilities due to shoulder injuries, for instance, may at times lead humans to experience pain. In this situation, robots will require sophisticated capabilities, such as the ability to recognize human pain in advance and generate counter-responses as follow up emphatic action. Hence, it is important for robots to acquire an appropriate pain concept that allows them to develop these capabilities. This paper conceptualizes empathy generation through the realization of synthetic pain classes integrated into a robot's self-awareness framework, and the implementation of fault detection on the robot body serves as a primary source of pain activation. Projection of human shoulder motion into the robot arm motion acts as a fusion process, which is used as a medium to gather information for analyses then to generate corresponding synthetic pain and emphatic responses. An experiment is designed to mirror a human peer's shoulder motion into an observer robot. The results demonstrate that the fusion takes place accurately whenever unified internal states are achieved, allowing accurate classification of synthetic pain categories and generation of empathy responses in a timely fashion. Future works will consider a pain activation mechanism development.
Anshu, A, Berta, M, Jain, R & Tomamichel, M 2018, 'Partially smoothed information measures', IEEE Trans. Inf. Theory, vol. 66, pp. 5022-5036.
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Smooth entropies are a tool for quantifying resource trade-offs in (quantum)
information theory and cryptography. In typical bi- and multi-partite problems,
however, some of the sub-systems are often left unchanged and this is not
reflected by the standard smoothing of information measures over a ball of
close states. We propose to smooth instead only over a ball of close states
which also have some of the reduced states on the relevant sub-systems fixed.
This partial smoothing of information measures naturally allows to give more
refined characterizations of various information-theoretic problems in the
one-shot setting. In particular, we immediately get asymptotic second-order
characterizations for tasks such as privacy amplification against classical
side information or classical state splitting. For quantum problems like state
merging the general resource trade-off is tightly characterized by partially
smoothed information measures as well.
Anshu, A, Hsieh, M-H & Jain, R 2018, 'Noisy quantum state redistribution with promise and the Alpha-bit', IEEE Transactions on Information Theory (IEEE-TIT), Volume: 66, Issue: 12, 2020.
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We consider a variation of the well-studied quantum state redistribution
task, in which the starting state is known only to the receiver Bob and not to
the sender Alice. We refer to this as quantum state redistribution with a
one-sided promise. In addition, we consider communication from Alice to Bob
over a noisy channel $\mathcal{N}$, instead of the noiseless channel, as is
usually considered in state redistribution. We take a natural approach towards
the solution of this problem where we 'embed' the promise as part of the state
and then invoke known protocols for quantum state redistribution composed with
known protocols for transfer of quantum information over noisy channels. Using
our approach, we are able to reproduce the Alpha-bit capacities with or without
entanglement assistance in Ref. [ArXiv:1706.09434], using known protocols for
quantum state redistribution and quantum communication over noisy channels.
Furthermore, we generalize the entanglement assisted classical Alpha-bit
capacity, showing that any quantum state redistribution protocol can be used as
a black box to simulate classical communication.
Anshu, A, Hsieh, M-H & Jain, R 2018, 'Quantifying Resources in General Resource Theory with Catalysts', Physical Review Letters, vol. 121, no. 19.
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A question that is commonly asked in all areas of physics is how a certain property of a physical system can be used to achieve useful tasks and how to quantify the amount of such a property in a meaningful way. We answer this question by showing that, in a general resource-theoretic framework that allows the use of free states as catalysts, the amount of "resources" contained in a given state, in the asymptotic scenario, is equal to the regularized relative entropy of a resource of that state. While we need to place a few assumptions on our resource-theoretical framework, it is still sufficiently general, and its special cases include quantum resource theories of entanglement, coherence, asymmetry, athermality, nonuniformity, and purity. As a by-product, our result also implies that the amount of noise one has to inject locally to erase all the entanglement contained in an entangled state is equal to the regularized relative entropy of entanglement.
Anwar, M, Rasul, M, Ashwath, N & Rahman, M 2018, 'Optimisation of Second-Generation Biodiesel Production from Australian Native Stone Fruit Oil Using Response Surface Method', Energies, vol. 11, no. 10, pp. 2566-2566.
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In this study, the production process of second-generation biodiesel from Australian native stone fruit have been optimised using response surface methodology via an alkali catalysed transesterification process. This process optimisation was performed varying three factors, each at three different levels. Methanol: oil molar ratio, catalyst concentration (wt %) and reaction temperature were the input factors in the optimisation process, while biodiesel yield was the key model output. Both 3D surface plots and 2D contour plots were developed using MINITAB 18 to predict optimum biodiesel yield. Gas chromatography (GC) and Fourier transform infrared (FTIR) analysis of the resulting biodiesel was also done for biodiesel characterisation. To predict biodiesel yield a quadratic model was created and it showed an R2 of 0.98 indicating the satisfactory performance of the model. Maximum biodiesel yield of 95.8% was obtained at a methanol: oil molar ratio of 6:1, KOH catalyst concentration of 0.5 wt % and a reaction temperature of 55 °C. At these reaction conditions, the predicted biodiesel yield was 95.9%. These results demonstrate reliable prediction of the transesterification process by Response surface methodology (RSM). The results also show that the properties of the synthesised Australian native stone fruit biodiesel satisfactorily meet the ASTM D6751 and EN14214 standards. In addition, the fuel properties of Australian native stone fruit biodiesel were found to be similar to those of conventional diesel fuel. Thus, it can be said that Australian native stone fruit seed oil could be used as a potential second-generation biodiesel source as well as an alternative fuel in diesel engines.
Ara, P, Yu, K, Cheng, S, Dutkiewicz, E & Heimlich, MC 2018, 'Human Abdomen Path-Loss Modeling and Location Estimation of Wireless Capsule Endoscope Using Round-Trip Propagation Loss', IEEE Sensors Journal, vol. 18, no. 8, pp. 3266-3277.
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Arabameri, A, Pradhan, B, Pourghasemi, HR & Rezaei, K 2018, 'Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1129-1155.
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Arabameri, A, Pradhan, B, Pourghasemi, HR, Rezaei, K & Kerle, N 2018, 'Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms', Applied Sciences, vol. 8, no. 8, pp. 1369-1369.
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Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), and multivariate adaptive regression spline (MARS)—for gully erosion susceptibility mapping (GESM) in the Shahroud watershed, Iran. Gully locations were identified by extensive field surveys, and a total of 172 GE locations were mapped. Twelve gully-related GEVs: Elevation, slope degree, slope aspect, plan curvature, convergence index, topographic wetness index (TWI), lithology, land use/land cover (LU/LC), distance from rivers, distance from roads, drainage density, and NDVI were selected to model GE. The results of variables importance by RF and BRT models indicated that distance from road, elevation, and lithology had the highest effect on GE occurrence. The area under the curve (AUC) and seed cell area index (SCAI) methods were used to validate the three GE maps. The results showed that AUC for the three models varies from 0.911 to 0.927, whereas the RF model had a prediction accuracy of 0.927 as per SCAI values, when compared to the other models. The findings will be of help for planning and developing the studied region.
Arabameri, A, Pradhan, B, Rezaei, K, Yamani, M, Pourghasemi, HR & Lombardo, L 2018, 'Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function-logistic regression algorithm', Land Degradation & Development, vol. 29, no. 11, pp. 4035-4049.
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© 2018 John Wiley & Sons, Ltd. This study aims to assess gully erosion susceptibility and delineate gully erosion-prone areas in Toroud Watershed, Semnan Province, Iran. Two different methods, namely, logistic regression (LR) and evidential belief function (EBF), were evaluated, and a new ensemble method was proposed using the combination of both methods. We initially created a gully erosion inventory map using different resources, including early reports, Google Earth images, and Global Positioning System-aided field surveys. We subsequently split this information randomly and selected 70% (90) of the gullies for calibration and 30% (38) for validation. The method was constructed using a combination of morphometric and thematic predictors that include 16 conditioning parameters. We also assessed the following: (a) potential multicollinearity issues using tolerance and variance inflation factor indices and (b) covariate effects using LR coefficients and EBF class weights. Results show that land use/land cover, lithology, and distance to roads dominate the method with the greatest effect on gully occurrences. We produced three susceptibility maps and evaluated their predictive power through area under the curve (AUC) and seed cell area index analyses. AUC results revealed that the ensemble method presented a considerably higher performance (AUC = 0.909) than did the individual LR (0.802) and EBF (0.821) methods. Similarly, seed cell area index displayed a constant decrease from the ensemble to single methods. The resulted gully erosion-susceptibility map could be used by decision makers and local managers for soil conservation, and for minimising damages in development activities including construction of infrastructures such as roads and the route of gas and electricity transmission lines.
Arandiyan, H, Wang, Y, Scott, J, Mesgari, S, Dai, H & Amal, R 2018, 'In Situ Exsolution of Bimetallic Rh–Ni Nanoalloys: a Highly Efficient Catalyst for CO2 Methanation', ACS Applied Materials & Interfaces, vol. 10, no. 19, pp. 16352-16357.
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© 2018 American Chemical Society. Unique CO2 methanation catalysts comprising bimetallic Ni-Rh nanoalloy/3DOM LaAlO3 have been successfully prepared via a poly(methyl methacrylate) microsphere colloidal crystal-templating route, followed by the in situ growth of Ni nanoparticles (NPs). Here, we show that unlike traditional Ni particles deposited on a perovskite support, the exsolution of Ni occurs on both the external and internal surface of the porous perovskite substrate, leading to a strong metal-support interaction. Owing to the exsolution of Ni and the formation of Ni-Rh nanoalloys, a 52% enhancement in the methanation turnover frequency was obtained over the Ni-Rh/3DOM LaAlO3 [13.9 mol/(mol h)] compared to Rh/3DOM LaNi0.08Al0.92O3 [9.16 mol/(mol h)] before reduction treatment. The results show that the low-temperature reducibility, rich surface adsorbed oxygen species, and basic sites of the catalyst greatly improve its activity toward CO2 methanation. The hierarchically porous structure of the perovskite support provides a high dispersion of bimetallic Ni-Rh NPs.
Argha, A, Li, L & Su, SW 2018, 'ℋ2-based optimal sparse sliding mode control for networked control systems', International Journal of Robust and Nonlinear Control, vol. 28, no. 1, pp. 16-30.
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This paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note uses a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the urn:x-wiley:rnc:media:rnc3852:rnc3852-math-0004 control. We then use this novel scheme to provide an innovative less‐complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach.
Argha, A, Li, L, Su, SW & Nguyen, H 2018, 'Sparsely distributed sliding mode control for interconnected systems', Journal of the Franklin Institute, vol. 355, no. 14, pp. 6191-6214.
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© 2018 The Franklin Institute This paper proposes a framework for the design of sparsely distributed output feedback discrete-time sliding mode control (ODSMC) for interconnected systems. The major target here is to develop an observer based discrete-time sliding mode controller employing a sparsely distributed control network structure in which local controllers exploit some other sub-systems’ information as well as its own local information. As the local controllers/observers have access to some other sub-systems’ states, the control performance will be improved and the applicability region will be widened compared to the decentralised structure. 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 priori known structure for the control/observer network. The developed LMI based controller design scheme provides the possibility to employ different information patterns such as fully distributed, sparsely distributed and decentralised patterns. In the second step, we propose a methodology to identify 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 analysed and a bound is derived for the augmented system state which includes the closed-loop system state and the switching function.
Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Mixed H2/H∞-based actuator selection for uncertain polytopic systems with regional pole placement', International Journal of Control, vol. 91, no. 2, pp. 320-336.
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© 2017 Informa UK Limited, trading as Taylor & Francis GroupThis paper is devoted to the problem of designing an (Formula presented.) and/or (Formula presented.) row-sparse static output feedback controller for continuous linear time-invariant systems with polytopic uncertainty. The immediate application of the proposed approach lies within the problem of the optimal selection of a subset of available actuators during the fault accommodation stage of a fault-tolerant control scheme. Incorporating an extra term for penalising the number of actuators into the optimisation objective function, we propose an explicit scheme and two iterative procedures according to the reweighted ℓ1 (REL1) and reweighted iterative support detection (RISD) algorithms for the purposes of identifying the favourable row-sparse feedback gains. Furthermore, this problem formulation allows us to incorporate additional constraints into the designing problem such as regional pole placement constraints which provide more control over the satisfactory transient behaviour and closed-loop pole locations. In this paper, we present two examples which demonstrate the remarkable performance and broad applicability of the proposed approaches.
Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Novel frameworks for the design of fault-tolerant control using optimal sliding-mode control', International Journal of Robust and Nonlinear Control, vol. 28, no. 8, pp. 3015-3032.
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Arslanagić, S & Ziolkowski, RW 2018, 'Erratum: Highly Subwavelength, Superdirective Cylindrical Nanoantenna [Phys. Rev. Lett. 120, 237401 (2018)]', Physical Review Letters, vol. 121, no. 24.
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Arslanagić, S & Ziolkowski, RW 2018, 'Highly Subwavelength, Superdirective Cylindrical Nanoantenna', Physical Review Letters, vol. 120, no. 23, pp. 237401-237401.
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A superdirective cylindrical nanoantenna is demonstrated with a multilayered cylindrical metamaterial-inspired structure. Targeting specific scattering coefficients for the dipole and higher-order modes, the ideal limit of needle radiation is demonstrated. A five-layer system is optimized to demonstrate its approach to the theoretical directivity bound. While the resulting structure is scalable to any frequency regime, its highly subwavelength overall size (λ_{0}/10) takes advantage of combinations of positive and negative permittivity materials in the optical regime.
Asadabadi, MR, Saberi, M & Chang, E 2018, 'Targets of Unequal Importance Using the Concept of Stratification in a Big Data Environment', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1373-1384.
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© 2017, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. The concept of stratification (CST) has recently been proposed as an innovative approach in problem solving. CST takes a recursive approach to solve problems. It considers a system which has to transition through states until it arrives to a state which belongs to a desired set of states, namely a target set. The states can be stratified by enlarging the target (absorbing adjacent states). Incremental enlargement is a means to identify possible paths to achieve the target. Such an enlargement can also be used to degrade the target when the original target is not reachable. Although the characteristics of the concept, such as incremental enlargement, enhance its potential application in robotics, artificial intelligence, and planning and monitoring, there is a major shortcoming in the approach, namely its inability to consider targets of unequal importance. This study considers two targets of unequal importance for the system in CST, labelled Bi-Objective CST model (BOCST). In comparison with the original proposed CST model in this research, a version of CST with finite states which is much easier to apply than the original CST is proposed, labelled fuzzy CST. Following that, a combination of Fuzzy CST and BOCST (FBO-CST) is proposed. The model is then employed to address a restaurant selection problem using data from Google. The example illustrates how the model should be applied in a big data environment. By defining finite state CST and considering targets of unequal importance, this study is expected to facilitate future applications of CST.
Asif, MB, Hai, FI, Dhar, BR, Ngo, HH, Guo, W, Jegatheesan, V, Price, WE, Nghiem, LD & Yamamoto, K 2018, 'Impact of simultaneous retention of micropollutants and laccase on micropollutant degradation in enzymatic membrane bioreactor', Bioresource Technology, vol. 267, pp. 473-480.
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Asif, MB, Hai, FI, Kang, J, van de Merwe, JP, Leusch, FDL, Price, WE & Nghiem, LD 2018, 'Biocatalytic degradation of pharmaceuticals, personal care products, industrial chemicals, steroid hormones and pesticides in a membrane distillation-enzymatic bioreactor', Bioresource Technology, vol. 247, pp. 528-536.
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Laccase-catalyzed degradation of a broad spectrum of trace organic contaminants (TrOCs) by a membrane distillation (MD)-enzymatic membrane bioreactor (EMBR) was investigated. The MD component effectively retained TrOCs (94-99%) in the EMBR, facilitating their continuous biocatalytic degradation. Notably, the extent of TrOC degradation was strongly influenced by their molecular properties. A significant degradation (above 90%) of TrOCs containing strong electron donating functional groups (e.g., hydroxyl and amine groups) was achieved, while a moderate removal was observed for TrOCs containing electron withdrawing functional groups (e.g., amide and halogen groups). Separate addition of two redox-mediators, namely syringaldehyde and violuric acid, further improved TrOC degradation by laccase. However, a mixture of both showed a reduced performance for a few pharmaceuticals such as primidone, carbamazepine and ibuprofen. Mediator addition increased the toxicity of the media in the enzymatic bioreactor, but the membrane permeate (i.e., final effluent) was non-toxic, suggesting an added advantage of coupling MD with EMBR.
Asikin-Mijan, N, Lee, HV, Juan, JC, Noorsaadah, AR, Ong, HC, Razali, SM & Taufiq-Yap, YH 2018, 'Promoting deoxygenation of triglycerides via Co-Ca loaded SiO 2 -Al 2 O 3 catalyst', Applied Catalysis A: General, vol. 552, pp. 38-48.
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Askari, G, Pour, A, Pradhan, B, Sarfi, M & Nazemnejad, F 2018, 'Band Ratios Matrix Transformation (BRMT): A Sedimentary Lithology Mapping Approach Using ASTER Satellite Sensor', Sensors, vol. 18, no. 10, pp. 3213-3213.
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Remote sensing imagery has become an operative and applicable tool for the preparation of geological maps by reducing the costs and increasing the precision. In this study, ASTER satellite remote sensing data were used to extract lithological information of Deh-Molla sedimentary succession, which is located in the southwest of Shahrood city, Semnan Province, North Iran. A robust and effective approach named Band Ratio Matrix Transformation (BRMT) was developed to characterize and discriminate the boundary of sedimentary rock formations in Deh-Molla region. The analysis was based on the forward and continuous division of the visible-near infrared (VNIR) and the shortwave infrared (SWIR) spectral bands of ASTER with subsequent application of principal component analysis (PCA) for producing new transform datasets. The approach was implemented to ASTER spectral band ratios for mapping dominated mineral assemblages in the study area. Quartz, carbonate, and Al, Fe, Mg –OH bearing-altered minerals such as kaolinite, alunite, chlorite and mica were appropriately mapped using the BRMT approach. The results match well with geology map of the study area, fieldwork data and laboratory analysis. Accuracy assessment of the mapping result represents a reasonable kappa coefficient (0.70%) and appropriate overall accuracy (74.64%), which verified the robustness of the BRMT approach. This approach has great potential and capability for mapping sedimentary succession with diverse local–geological–physical characteristics around the world.
Aslani, M, Ghasemi, P & Gandomi, AH 2018, 'Constrained mean-variance mapping optimization for truss optimization problems', The Structural Design of Tall and Special Buildings, vol. 27, no. 6, pp. e1449-e1449.
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Atiquzzaman, M & Kandasamy, J 2018, 'Robustness of Extreme Learning Machine in the prediction of hydrological flow series', Computers & Geosciences, vol. 120, pp. 105-114.
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Avilés-Ochoa, E, León-Castro, E, Perez-Arellano, LA & Merigó, JM 2018, 'Government transparency measurement through prioritized distance operators', Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2783-2794.
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© 2018 - IOS Press and the authors. All rights reserved. The prioritized induced probabilistic ordered weighted average distance (PIPOWAD) has been developed. This new operator is an extension of the ordered weighted average (OWA) operator that can be used in cases where we have two sets of data that want to be compared. Some of the main characteristics of this new operator are: 1) Not all the decision makers are equally important, so the information needs to be prioritized, 2) The information has a probability to occur and 3) The decision makers can change the importance of the information based in an induced variable. Additionally, characteristics and families of the PIPOWAD operator are presented. Finally, an application of the PIPOWAD operator in order to measure government transparency in Mexico is presented.
Awadallah, M, Tawadros, P, Walker, P & Zhang, N 2018, 'Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles', Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 232, no. 13, pp. 1846-1862.
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Mild hybrid vehicles have been explored as a potential pathway to reduce vehicle emissions cost-effectively. The use of manual transmissions to develop novel hybrid vehicles provides an alternate route to producing low cost electrified powertrains. In this paper, a comparative analysis examining a conventional vehicle and a mild hybrid electric vehicle is presented. The analysis considers fuel economy, capital and ongoing costs and environmental emissions, and includes developmental analysis and simulation using mathematical models. Vehicle emissions (nitrogen oxides, carbon monoxide and hydrocarbons) and fuel economy are computed, analysed and compared using a number of alternative driving cycles and their weighted combination. Different driver styles are also evaluated. Studying the relationship between the fuel economy and driveability, where driveability is addressed using fuel-economical gear shift strategies. Our simulation suggests the hybrid concept presented can deliver fuel economy gains of between 5 and 10%, as compared to the conventional powertrain.
Ayachit, A, Siwakoti, YP, Galigekere, VPN, Kazimierczuk, MK & Blaabjerg, F 2018, 'Steady-State and Small-Signal Analysis of A-Source Converter', IEEE Transactions on Power Electronics, vol. 33, no. 8, pp. 7118-7131.
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© 1986-2012 IEEE. This paper presents a detailed steady-state analysis and ac small-signal modeling of the power stage of pulse-width modulated A-source converter. The voltage and current waveforms along with their corresponding expressions describing the converter operation are presented in detail. The input-to-output and input-to-capacitor dc voltage transfer functions are determined. The minimum inductance required to ensure continuous conduction mode is derived. The expressions for the semiconductor devices stresses are also presented. The dc, averaged equivalent circuit is derived using the circuit averaging technique. A complete derivation of the small-signal model including the converter parasitic resistances are presented followed by the power stage transfer functions relevant to the capacitor voltage loop, such as: 1) duty cycle-to-capacitor voltage; and 2) input-to-capacitor voltage. In addition, the expressions for the network input impedance and output impedance are derived. Finally, experimental validations of the derived small-signal models are performed, both in frequency and time domain for a laboratory prototype of an A-source converter. The theoretical predictions were in good agreement with the experimental results over a wide range of frequencies.
Aykin, I, Krunz, M & Xiao, Y 2018, 'Adaptive frequency-hopping schemes for CR-based multi-link satellite networks', International Journal of Satellite Communications and Networking, vol. 36, no. 4, pp. 315-331.
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Copyright © 2018 John Wiley & Sons, Ltd. In this paper, we study two dynamic frequency hopping (DFH)–based interference mitigation approaches for satellite communications. These techniques exploit the sensing capabilities of a cognitive radio to predict future interference on the upcoming frequency hops. We consider a topology where multiple low Earth orbit satellites transmit packets to a common geostationary equatorial orbit satellite. The FH sequence of each low Earth orbit–geostationary equatorial orbit link is adjusted according to the outcome of out-of-band proactive sensing scheme, performed by a cognitive radio module in the geostationary equatorial orbit satellite. On the basis of sensing results, new frequency assignments are made for the upcoming slots, taking into account the transmit powers, achievable rates, and overhead of modifying the FH sequences. In addition, we ensure that all satellite links are assigned channels such that their minimum signal-to-interference-plus-noise ratio requirements are met, if such an assignment is possible. We formulate two multi-objective optimization problems: DFH-Power and DFH-Rate. Discrete-time Markov chain analysis is used to predict future channel conditions, where the number of states are inferred using k-means clustering, and the state transition probabilities are computed using maximum likelihood estimation. Finally, simulation results are presented to evaluate the effects of different system parameters on the performance of the proposed designs.
Azeez, O, Pradhan, B & Shafri, H 2018, 'Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS', Sustainability, vol. 10, no. 10, pp. 3434-3434.
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Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.
Aziz, N, Rasekh, H, Mirzaghorbanali, A, Yang, G, Khaleghparast, S & Nemcik, J 2018, 'An Experimental Study on the Shear Performance of Fully Encapsulated Cable Bolts in Single Shear Test', Rock Mechanics and Rock Engineering, vol. 51, no. 7, pp. 2207-2221.
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© 2018, Springer-Verlag GmbH Austria, part of Springer Nature. A set of single shear tests on fully encapsulated cable bolts was carried out using a newly developed and integrated Megabolt single shear apparatus. The instrument is designed to determine the pure shear strength of cable bolts where there is no contact between the host body faces during the shearing process. Eight different types of cable bolt were encapsulated in 40 MPa concrete cylinders, using Stratabinder HS grout. Prior to encapsulation, cable bolts were pretensioned at the desired value using a manual pretensioner. Effects of surface profile, pretension value and debonding on shear strength of cable bolts were investigated. It was found that the shear strength of spiral/indented cable bolts was lower than that of plain cable bolts. Increasing the pretension load decreased the peak shear load of cable bolts. In general, no debonding was observed for spiral/indented cable bolts during shear testing; however, all tested plain cable bolts were debonded.
Azizivahed, A, Barani, M, Razavi, S, Ghavidel, S, Li, L & Zhang, J 2018, 'Energy storage management strategy in distribution networks utilised by photovoltaic resources', IET Generation, Transmission & Distribution, vol. 12, no. 21, pp. 5627-5638.
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Azuma, K, Sun, J, Choo, Y, Rokhlenko, Y, Dwyer, JH, Schweitzer, B, Hayakawa, T, Osuji, CO & Gopalan, P 2018, 'Self-Assembly of an Ultrahigh-χ Block Copolymer with Versatile Etch Selectivity', Macromolecules, vol. 51, no. 16, pp. 6460-6467.
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Ba, X, Guo, Y, Zhu, J & Zhang, C 2018, 'An Equivalent Circuit Model for Predicting the Core Loss in a Claw-Pole Permanent Magnet Motor With Soft Magnetic Composite Core', IEEE Transactions on Magnetics, vol. 54, no. 11, pp. 1-6.
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© 1965-2012 IEEE. Soft magnetic composite (SMC) materials and SMC electromagnetic devices have attracted strong research interest in the past decades. However, SMC devices have large core loss that needs to be put into consideration even at the design stage. Effective and accurate prediction of the core loss becomes crucial for the design and optimization of high-performance motors with these materials. Equivalent circuit model is a widely used method for machine analysis, due to the advantages in the fast calculation with a clear physical mechanism. This paper presents an equivalent circuit model to predict the core loss of a claw-pole permanent magnet motor with SMC stator core. All the parameters including the equivalent core-loss resistance in the equivalent circuit model are identified based on the finite-element method to achieve high accuracy, and the effectiveness of the parameters identification methods is experimentally verified. The proposed equivalent circuit model can predict the core loss and motor's performance efficiently both under no-load and loading conditions.
Baba, AA, Hashmi, RH, Esselle, KP & Weily, AR 2018, 'Improving radiation performance of extremely truncated RCAs through near‐field analysis', IET Microwaves, Antennas & Propagation, vol. 12, no. 12, pp. 1954-1959.
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Baba, AA, Hashmi, RM, Esselle, KP & Weily, AR 2018, 'Compact High-Gain Antenna With Simple All-Dielectric Partially Reflecting Surface', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 4343-4348.
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Babaee, M & Castel, A 2018, 'Chloride diffusivity, chloride threshold, and corrosion initiation in reinforced alkali-activated mortars: Role of calcium, alkali, and silicate content', Cement and Concrete Research, vol. 111, pp. 56-71.
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Babaee, M & Castel, A 2018, 'Water vapor sorption isotherms, pore structure, and moisture transport characteristics of alkali-activated and Portland cement-based binders', Cement and Concrete Research, vol. 113, pp. 99-120.
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Babaee, M, Khan, MSH & Castel, A 2018, 'Passivity of embedded reinforcement in carbonated low-calcium fly ash-based geopolymer concrete', Cement and Concrete Composites, vol. 85, pp. 32-43.
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Babar, A, Bunker, D & Qumer Gill, A 2018, 'Investigating the Relationship between Business Analysts’ Competency and IS Requirements Elicitation: A Thematic-analysis Approach', Communications of the Association for Information Systems, vol. 42, no. 1, pp. 334-362.
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Babbush, R, Berry, DW, Sanders, YR, Kivlichan, ID, Scherer, A, Wei, AY, Love, PJ & Aspuru-Guzik, A 2018, 'Exponentially more precise quantum simulation of fermions in the configuration interaction representation', Quantum Science and Technology, vol. 3, no. 1, pp. 015006-015006.
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Bach, Q-V, Le, VT, Yoon, YS, Bui, XT, Chung, W, Chang, SW, Ngo, HH, Guo, W & Nguyen, DD 2018, 'A new hybrid sewage treatment system combining a rolled pipe system and membrane bioreactor to improve the biological nitrogen removal efficiency: A pilot study', Journal of Cleaner Production, vol. 178, pp. 937-946.
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© 2018 Elsevier Ltd A new hybrid pilot plant configuration based on a modularized rolled pipe system (RPS) combined with a submerged flat sheet membrane bioreactor (MBR) was investigated to enhance the sewage treatment and membrane performance. The system was operated under actual conditions for more than four months, that is, at a constant flow rate of 30 m³/d and with two internal recycling ratios. The results indicate that the hybrid system produces an excellent effluent quality and considerably mitigated membrane fouling. The average concentrations of SS, COD, TN, NH4+-N, NO3−-N, and PO43--P remained below 2.81, 8.29, 8.77, 0.15, 8.17, and 1.49 mg/L, respectively. It was estimated that the periodic chemical cleaning of the membrane could be extended to approximately six months. The MBR and RPS can virtually complete nitrification and denitrification, respectively. The highest average denitrification rate of the RPS is 116.95 mg NO3-N/(g MLVSS d), with a hydraulic retention time of 1.05 h. Therefore, the RPS–MBR hybrid system has potential to improve the sewage treatability. The emerging RPS technique can obtain high rates of denitrification coupled with a compact design, ease of installation, and small footprint.
Bah, AO, Qin, P-Y, Ziolkowski, RW, Cheng, Q & Guo, YJ 2018, 'Realization of an Ultra-thin Metasurface to Facilitate Wide Bandwidth, Wide Angle Beam Scanning', Scientific Reports, vol. 8, no. 1.
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AbstractA wide bandwidth, ultra-thin, metasurface is reported that facilitates wide angle beam scanning. Each unit cell of the metasurface contains a multi-resonant, strongly-coupled unequal arm Jerusalem cross element. This element consists of two bent-arm, orthogonal, capacitively loaded strips. The wide bandwidth of the metasurface is achieved by taking advantage of the strong coupling within and between its multi-resonant elements. A prototype of the proposed metasurface has been fabricated and measured. The design concept has been validated by the measured results. The proposed metasurface is able to alleviate the well-known problem of impedance mismatch caused by mutual coupling when the main beam of an array is scanned. In order to validate the wideband and wide scanning ability of the proposed metasurface, it is integrated with a wideband antenna array as a wide angle impedance matching element. The metasurface-array combination facilitates wide angle scanning over a 6:1 impedance bandwidth without the need for bulky dielectrics or multi-layered structures.
Bai, F, Vidal-Calleja, T & Huang, S 2018, 'Robust Incremental SLAM Under Constrained Optimization Formulation', IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1207-1214.
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Bai, L, Wang, J, Ma, X & Lu, H 2018, 'Air Pollution Forecasts: An Overview', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 780-780.
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Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.
Baidya, R, Aguilera, RP, Acuna, P, Vazquez, S & Mouton, HDT 2018, 'Multistep Model Predictive Control for Cascaded H-Bridge Inverters: Formulation and Analysis', IEEE Transactions on Power Electronics, vol. 33, no. 1, pp. 876-886.
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© 1986-2012 IEEE. In this paper, a suitable long prediction horizon (multistep) model predictive control (MPC) formulation for cascaded H-bridge inverters is proposed. The MPC is formulated to include the full steady-state system information in terms of output current and output voltage references. Generally, basic single-step predictive controllers only track the current references. As a distinctive feature, the proposed MPC also tracks the control input references, which in this case is designed to minimize the common-mode voltage (CMV). This allows the controller to address both output current and CMV targets in a single optimization. To reduce the computational effort introduced by a long prediction horizon implementation, the proposed MPC formulation is transformed into an equivalent optimization problem that can be solved by a fast sphere decoding algorithm. Moreover, the benefits of including the control input references in the proposed formulation are analyzed based on this equivalent optimization problem. This analysis is key to understand how the proposed MPC formulation can handle both control targets. Experimental results show that the proposal provides an improved steady-state performance in terms of current distortion, inverter voltages symmetry, and CMV.
Baier-Fuentes, H, Cascón-Katchadourian, J, Sánchez, ÁM, Herrera-Viedma, E & Merigó, J 2018, 'A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence', International Journal of Interactive Multimedia and Artificial Intelligence, vol. 5, no. 3, pp. 9-9.
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Bajada, C & Shashnov, M 2018, 'The Effects of Regulatory Change on Taxpayer Compliance Behaviour in the Building and Construction Industry', Journal of Australian Taxation, vol. 20, no. 1.
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Using the results from a comprehensive telephone survey of home builders during 2007-8 and 2014-15, we provide an analysis of the behaviour, characteristics and perceptions of cash economy activity in the building and construction sector in Australia. In 2012-13, the ATO introduced the Taxable Payment Reporting System which yielded an additional compliance dividend. By comparing responses of builders before and after the introduction of this reporting system, we evaluate the impact of this regulatory change on grassroots activity in the cash economy. Although this regulatory change has impacted on certain cash economy activities, more targeted strategies are still required.
I.
Bajan, S, Johnston, M & Hutvagner, G 2018, 'Destabilisation of Argonaute 2 generates a truncated protein: halfAgo2', Matters.
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The Argonaute 2 (Ago2) protein is an essential effector protein in miRNA-mediated
mechanisms that regulate gene expression. Ago2 directly binds to the miRNA, forming
the RISC. RISC function is critical to controlling key biological processes and when
dysregulated can result in disease pathogenesis. Understanding Ago2 protein stability
and turnover will further our understanding in how RISC function is regulated. In human
cells, we discovered a previously unidentified ~55 kDa protein that is a truncated
form of Ago2, that is formed from proteolytic cleavage of the full length Ago2 protein.
Further experiments are needed to determine (i) the detailed mechanism that forms
halfAgo2 (ii) the cellular or environmental triggers or stresses that initiate halfAgo2
production and (iii) if halfAgo2 has a potentially new role in gene regulation.
Balathanigaimani, MS, Haider, MB, Jha, D, Kumar, R, Lee, SJ, Shim, WG, Shon, HK, Kim, SC & Moon, H 2018, 'Nanostructured Biomass Based Carbon Materials from Beer Lees for Hydrogen Storage', Journal of Nanoscience and Nanotechnology, vol. 18, no. 3, pp. 2196-2199.
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The present work describes the preparation of carbon materials from beer lees and their hydrogen adsorption abilities. Activated carbons (ACs) from beer lees were prepared through chemical activation using potassium hydroxide as an activating agent. The low temperature nitrogen adsorption isotherm studies on prepared ACs were conducted at 77 K to determine their physical properties and adsorption energy distribution. The beer lees based carbons have energetically heterogeneous surfaces and high surface area ranging from 1927–2408 m2/g. ACs prepared in this study show the gravimetric hydrogen adsorption capacity of 2.43–2.92 wt% depending on their physical properties
Bano, M, Zowghi, D & Rimini, FD 2018, 'User Involvement in Software Development: The Good, the Bad, and the Ugly.', IEEE Softw., vol. 35, pp. 8-11.
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Bano, M, Zowghi, D, Kearney, M, Schuck, S & Aubusson, P 2018, 'Mobile learning for science and mathematics school education: A systematic review of empirical evidence.', Comput. Educ., vol. 121, pp. 30-58.
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The ubiquity, flexibility, ease of access and diverse capabilities of mobile technologies make them valuable and a necessity in current times. However, they are under-utilized assets in mathematics and science school education. This article analyses the high quality empirical evidence on mobile learning in secondary school science and mathematics education. Our study employed a Systematic Literature Review (SLR) using well-accepted and robust guidelines. The SLR resulted in the detailed analysis of 49 studies (60 papers) published during 2003–2016. Content and thematic analyses were used to ascertain pedagogical approaches, methodological designs, foci, and intended and achieved outcomes of the studies. The apps and technologies used in these studies were further classified for domain, type and context of use. The review has highlighted gaps in existing literature on the topic and has provided insights that have implications for future research.
Baral, P, Rujikiatkamjorn, C, Indraratna, B & Kelly, R 2018, 'Radial consolidation characteristics of soft undisturbed clay based on large specimens', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1037-1045.
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Bargi, A, Xu, RYD & Piccardi, M 2018, 'AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 3953-3968.
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Barker, RA, Eager, D & Sharwood, LN 2018, 'Ensuring safety in public playgrounds is everybody's business.', Med J Aust, vol. 210, no. 1, pp. 9-11.
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When an injury occurs in a children’s playground, who is responsible? Media headlines1,2 have highlighted risks associated with a recently opened playground in north-western Sydney. The playground’s giant tube slide was closed following a spate of injuries to both adult and child patrons. With injuries described as “horrific”, the media questioned “how the 30 m long, 14 m tall slide passed safety rules”.1 While playground injuries are fairly common,3 there are specific multilevel responsibilities required to balance the importance of play and physical activity with mitigation of injury risk. In this article, we review the role of standards in industry governance and injury prevention.
Basack, S & Nimbalkar, S 2018, 'Measured and Predicted Response of Pile Groups in Soft Clay Subjected to Cyclic Lateral Loading', International Journal of Geomechanics, vol. 18, no. 7, pp. 04018073-04018073.
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© 2018 American Society of Civil Engineers. Major offshore and onshore structures, including transport corridors and high-rise buildings, resting on soft compressible clays are often supported by pile foundations. Apart from the usual vertical loading from the superstructures, these piles are usually subjected to large cyclic loads arising from the actions of waves, ship impacts, or moving vehicles. Under such circumstances, vertical and lateral modes of cyclic loading are predominant and affect overall stability. Such repetitive loading on piles leads to reversal of axial stresses in the adjacent soft clay, initiating progressive degradation in soil strength and stiffness that deteriorates the pile capacity with unacceptable displacements. Although several studies have been carried out to investigate the response of a single pile, a detailed investigation on a pile group in soft soil subjected to cyclic lateral loading, which is of immense practical interest to field engineers, had yet to be conducted. In this paper, extensive laboratory model tests with steel-pipe-pile groups in soft cohesive soil were conducted followed by the development of a numerical model that was based on a two-dimensional (2D) dynamic finite-element (FE) approach. The degradation of both axial and lateral capacities of the pile group and the pattern of the degradation with variations in the cyclic-loading parameters were studied. Comparisons of the experimental data with the computed results validated the numerical analysis. The study indicates that both the axial and lateral pile capacities and displacements were significantly influenced by the cyclic-loading parameters (number of cycles, frequency, and amplitude). Relevant design recommendations are presented.
Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2018, 'Closure to “Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation” by Sudip Basack, Buddhima Indraratna, Cholachat Rujikiatkamjorn, and Firman Siahaan', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 5, pp. 07018008-07018008.
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Basack, S, Siahaan, F, Indraratna, B & Rujikiatkamjorn, C 2018, 'Stone Column–Stabilized Soft-Soil Performance Influenced by Clogging and Lateral Deformation: Laboratory and Numerical Evaluation', International Journal of Geomechanics, vol. 18, no. 6, pp. 04018058-04018058.
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Bazaz, SR, Mehrizi, AA, Ghorbani, S, Vasilescu, S, Asadnia, M & Warkiani, ME 2018, 'A hybrid micromixer with planar mixing units', RSC Advances, vol. 8, no. 58, pp. 33103-33120.
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Taguchi-optimized “hybrid micromixer” has been proposed which can be utilized in a wide range of chemical and biological applications.
Beck, D, Thoms, JAI, Palu, C, Herold, T, Shah, A, Olivier, J, Boelen, L, Huang, Y, Chacon, D, Brown, A, Babic, M, Hahn, C, Perugini, M, Zhou, X, Huntly, BJ, Schwarzer, A, Klusmann, J-H, Berdel, WE, Wörmann, B, Büchner, T, Hiddemann, W, Bohlander, SK, To, LB, Scott, HS, Lewis, ID, D'Andrea, RJ, Wong, JWH & Pimanda, JE 2018, 'A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients', Leukemia, vol. 32, no. 2, pp. 263-272.
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Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.
Beiranvand Pour, A, Park, T-Y, Park, Y, Hong, J, Zoheir, B, Pradhan, B, Ayoobi, I & Hashim, M 2018, 'Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland', Remote Sensing, vol. 10, no. 8, pp. 1186-1186.
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Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc deposits. In this research, multi-sensor remote sensing satellite data (e.g., Landsat-8, Phased Array L-band Synthetic Aperture Radar (PALSAR) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) were used for exploring zinc in the trough sequences and shelf-platform carbonate of the Franklinian Basin. A series of robust image processing algorithms was implemented for detecting spatial distribution of pixels/sub-pixels related to key alteration mineral assemblages and structural features that may represent potential undiscovered Zn–Pb deposits. Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) was applied to some selected Landsat-8 mineral indices for mapping gossan, clay-rich zones and dolomitization. Major lineaments, intersections, curvilinear structures and sedimentary formations were traced by the application of Feature-oriented Principal Components Selection (FPCS) to cross-polarized backscatter PALSAR ratio images. Mixture Tuned Matched Filtering (MTMF) algorithm was applied to ASTER VNIR/SWIR bands for sub-pixel detection and classification of hematite, goethite, jarosite, alunite, gypsum, chalcedony, kaolinite, muscovite, chlorite, epidote, calcite and dolomite in the prospective targets. Using the remote sensing data and approaches, several high potential zones characterized by distinct alteration mineral assemblages and structural fabrics were identified that could represent undiscovered Zn–Pb sulfide deposits in the study area. This research establishes a straightforward/cost-effective multi-sensor satellite-based remote sensing approach for reconnaissance stages of mineral exploration in hardly accessible parts of the High Arctic...
Belhaj, D, Athmouni, K, Ahmed, MB, Aoiadni, N, El Feki, A, Zhou, JL & Ayadi, H 2018, 'Polysaccharides from Phormidium versicolor (NCC466) protecting HepG2 human hepatocellular carcinoma cells and rat liver tissues from cadmium toxicity: Evidence from in vitro and in vivo tests', International Journal of Biological Macromolecules, vol. 113, pp. 813-820.
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Bellezoni, RA, Sharma, D, Villela, AA & Pereira Junior, AO 2018, 'Water-energy-food nexus of sugarcane ethanol production in the state of Goiás, Brazil: An analysis with regional input-output matrix', Biomass and Bioenergy, vol. 115, pp. 108-119.
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© 2018 Elsevier Ltd Concerns about impacts of biomass growth for biofuel production emphasize the importance of planning energy crops expansion considering land, water, food and biodiversity. Brazil is the second largest ethanol producer worldwide and sugarcane is cultivated in many regions, including the Brazilian Cerrado (a Savannah-type biome). This paper analyses the impacts of first-generation sugarcane expansion in the Paranaíba basin (Goiás State), focusing on how future demand for ethanol could affect local resources availability. The study area is a sugarcane expansion frontier in Brazil, thus, the Cerrado biome should be focus of research considering competition for land and water uses. An economic-ecologic Input-Output (IO) framework was applied to develop a water-energy-food (WEF) nexus analysis. The Goiás’ IO table was expanded to assess water, energy and land uses, GHG emissions and employment levels through six different ethanol supply scenarios. Results show that if sugarcane expansion projected to 2030 considers the Goiás’ extended IO structure for the year 2008, it should cause little impact on land and water availability in the state, due to both the ample availability of suitable pasturelands for sugarcane expansion as well as water in most of the Paranaíba basin. The WEF nexus analysis is a valuable tool on guiding the sustainable management of natural resources considering water, energy, land use and GHG emissions as goals to the same policy. In particular, the hybrid extended IO-WEF nexus framework is useful to design effective biofuel policies, collectively addressing impacts on environmental, social and economic spheres, in a local or broader context.
Berry, DW, Kieferová, M, Scherer, A, Sanders, YR, Low, GH, Wiebe, N, Gidney, C & Babbush, R 2018, 'Improved techniques for preparing eigenstates of fermionic Hamiltonians', npj Quantum Information, vol. 4, no. 1.
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AbstractModeling low energy eigenstates of fermionic systems can provide insight into chemical reactions and material properties and is one of the most anticipated applications of quantum computing. We present three techniques for reducing the cost of preparing fermionic Hamiltonian eigenstates using phase estimation. First, we report a polylogarithmic-depth quantum algorithm for antisymmetrizing the initial states required for simulation of fermions in first quantization. This is an exponential improvement over the previous state-of-the-art. Next, we show how to reduce the overhead due to repeated state preparation in phase estimation when the goal is to prepare the ground state to high precision and one has knowledge of an upper bound on the ground state energy that is less than the excited state energy (often the case in quantum chemistry). Finally, we explain how one can perform the time evolution necessary for the phase estimation based preparation of Hamiltonian eigenstates with exactly zero error by using the recently introduced qubitization procedure.
Best, G, Faigl, J & Fitch, R 2018, 'Online planning for multi-robot active perception with self-organising maps', Autonomous Robots, vol. 42, no. 4, pp. 715-738.
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© 2017, Springer Science+Business Media, LLC, part of Springer Nature. We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has a runtime complexity that is polynomial in the number of nodes to be observed and the magnitude of the relative weighting of rewards. We show empirically the runtime is sublinear in the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Exploration objectives for online tasks where the environment is only partially known in advance are modelled by introducing goal regions in unexplored space. Online replanning is performed efficiently by adapting previous solutions as new information becomes available. Simulations were performed using a 3D point-cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for online active perception tasks with continuous sets of candidate viewpoints and long planning horizons.
Beydoun, G, Dascalu, S, Dominey-Howes, D & Sheehan, A 2018, 'Disaster Management and Information Systems: Insights to Emerging Challenges.', Inf. Syst. Frontiers, vol. 20, no. 4, pp. 649-652.
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BEZDEK, J, KELLER, J, PAL, N, LIN, C-T & GARIBALDI, J 2018, 'Editorial Celebrating 25 Years of the IEEE Transactions on Fuzzy Systems', IEEE Transactions on Fuzzy Systems, vol. 26, no. 1, pp. 1-5.
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Bhoi, SK, Puthal, D, Khilar, PM, Rodrigues, JJPC, Panda, SK & Yang, LT 2018, 'Adaptive routing protocol for urban vehicular networks to support sellers and buyers on wheels', Computer Networks, vol. 142, pp. 168-178.
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© 2018 Marketing on wheels is an emerging area of research, where users can buy or sell items using inter vehicular communication and web is not required. For quicker delivery of items, the communication between the vehicles should be faster. In this paper, a routing protocol is proposed for urban vehicular ad hoc network (VANET) to send the messages from the buyer to the seller or vice versa in a minimum time to get faster service. Currently, many routing protocols are proposed for urban environment, which are based on the methods of shortest path, high density, minimum packet forwarding delay, and intermediate junction selection. However, these protocols lack knowledge about the communication gaps generated between the junctions before forwarding the data. In this method, the RSU at the junction calculates a path value for each path to choose the next path. The parameters used for path value calculation are number of network fragments between the junctions, delay to send the data from to other junction, and destination closeness. Then, the path which has a less path value is chosen as the next path. Results show that proposed protocol performs better than the existing city based routing protocols in terms of delay, number of network fragments or gaps encountered, path length, total service time, and packet delivery ratio. At last, the proposed routing protocol is validated by conducting an experiment in a small VANET platform designed in an indoor laboratory environment (https://www.youtube.com/watch?v=H3UmgI5AAH0).
Bhowmick, S, Xu, F, Zhang, X & Saha, SC 2018, 'Natural convection and heat transfer in a valley shaped cavity filled with initially stratified water', International Journal of Thermal Sciences, vol. 128, pp. 59-69.
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Bian, X, Jin, W, Gu, Q, Zhou, X, Xi, Y, Tu, R, Han, S-F, Xie, G-J, Gao, S-H & Wang, Q 2018, 'Subcritical n-hexane/isopropanol extraction of lipid from wet microalgal pastes of Scenedesmus obliquus', World Journal of Microbiology and Biotechnology, vol. 34, no. 3, pp. 39-39.
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Subcritical co-solvents of n-hexane/isopropanol were primarily utilized to extract lipid from wet microalgal pastes of Scenedesmus obliquus. The effects of key operational parameters were investigated, and the optimal parameters were obtained: solvent ratio of n-hexane to isopropanol was 3:2 (V:V), phase ratio of co-solvents to microalgal biomass was 35:1 (mL:g), reactor stirring speed was 900 rpm, extraction time was 60 min. Additional pretreatment with acid, ultrasonic and microwave as well as enhanced subcritical pressure/heating treatments were also applied to further study their effects on lipid extraction. The results showed that the lipid recovery rate with acid pretreatment was 8.6 and 6.2% higher than ultrasonic and microwave pretreatment; the optimum enhanced subcritical condition was 55 °C with atmospheric pressure. Under optimal operating conditions, the lipid and FAME yield were 13.5 and 7.2%, which was 82.6 and 135.1% higher than the traditional method. The results indicated that the subcritical n-hexane/isopropanol extraction process had promising application potential.
Bickel, B, Cignoni, P, Malomo, L & Pietroni, N 2018, 'State of the Art on Stylized Fabrication.', Comput. Graph. Forum, vol. 37, pp. 325-342.
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Blanco-Mesa, F, Gil-Lafuente, AM & Merigo, JM 2018, 'Dynamics of stakeholder relations with multi-person aggregation', Kybernetes, vol. 47, no. 9, pp. 1801-1820.
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Purpose
The purpose of this paper is to develop a novel method to analyse dynamic interactions of stakeholders to explain how a set of agents can act by considering the power/influence positions.
Design/methodology/approach
A novel mathematical application uses the importance of characteristics algorithm in combination with composition max-min to compare, group and order information according to the importance of its characteristics. The mathematical application is focused on a strategic analysis, evaluating stakeholder dynamics through power relationships.
Findings
The results show a comparison of the relationships among each of the stakeholders to obtain the relative intensity and importance of relationships between them, given by the fuzzy matrix FRInM and the fuzzy matrix FRIM, respectively. This application provides a useful tool for a dynamic analysis of stakeholders in a complex environment, where the best approach to performing a strategic analysis process is sought.
Research limitations/implications
The main implication of the proposed approach is taking into account the importance of information to establish the boundaries and relationships of each characteristic according to its intensity. However, limitations are due to the nature of this research, based on theoretical assumptions regarding stakeholders and the use of a hypothetical example to show the operation of algorithms.
Originality/value
The primary advantage of this proposition is that it takes into account the importance o...
BLANCO-MESA, F, GIL-LAFUENTE, AM & MERIGÓ, JM 2018, 'NEW AGGREGATION OPERATORS FOR DECISION-MAKING UNDER UNCERTAINTY: AN APPLICATIONS IN SELECTION OF ENTREPRENEURIAL OPPORTUNITIES', Technological and Economic Development of Economy, vol. 24, no. 2, pp. 335-357.
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The main aim of this paper is to study how economic environment and logic reasoning guidance the decision-making process to start-up a new business by potential entrepreneurs. The study proposes a new method using the family of selection indices with OWA operator, which allows aggregating information according to the level of importance and their level of objectivity and subjectivity in the same formulation within the decision-making process. To develop case study, we have taken into account some industries of the sports sector and some critical environmental factors that influence the competitiveness and entrepreneurship in Colombia to start a new business. The results show in an orderly way all information aggregated, which can help potential investors and entrepreneurs to make a decision based on their preferences. Finally, the applicability of this method in real case can be given in aggregation different sources of information to help at dealing decision-making processes.
Blanco-Mesa, F, Gil-Lafuente, AM & Merigó, JM 2018, 'Subjective stakeholder dynamics relationships treatment: a methodological approach using fuzzy decision-making', Computational and Mathematical Organization Theory, vol. 24, no. 4, pp. 441-472.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Since the stakeholder theory was proposed to explain the interaction among its agents, extensive approaches have been developed. However, the literature continues to suggest the development of new methodologies that allow an analysis of the dynamics and uncertainty of the relationships between each agent. In this sense, this research proposes a novel methodology for the treatment of subjective stakeholder dynamics using fuzzy decision-making. The study proposes a mathematical methodological perspective for the treatment of subjective relationships among stakeholders, which allows a predictive simulation tool to be developed for attitude and personal preferences to analyze the links among all stakeholders. A mathematical application is developed to help the decision-making process in uncertainty concerning the ordering-according-to-their-importance and linking-of-relation algorithms, which are based on notions of relation, gathering and ordering. A numerical example is proposed to understand the method’s usefulness and feasibility. The results approximate how stakeholder ambiguity and fuzziness can be managed considering the decision-maker’s preference subjectivity. In addition, these results highlight the different relationships among each stakeholder, their intensity levels, the incidence linkage loops and the incidence relative on stakeholder behaviors. The main implication of this proposition is to deal with the subjective preferences provide by decision-maker to better interpret environmental and subjective factors. Furthermore, this study contributes to the strategic planning and decision-making processes for operative units within uncertain environment in the short term.
Blanco-Mesa, F, León-Castro, E & Merigó, JM 2018, 'Bonferroni induced heavy operators in ERM decision-making: A case on large companies in Colombia', Applied Soft Computing, vol. 72, pp. 371-391.
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© 2018 Elsevier B.V. Averaging aggregation operators analyse a set of data providing a summary of the results. This study focuses on the Bonferroni mean and the induced and heavy aggregation operators. The aim of the work is to present new aggregation operators that combine these concepts forming the Bonferroni induced heavy ordered weighted average and several particular formulations. This approach represents Bonferroni means with order inducing variables and with weighting vectors that can be higher than one. The paper also develops some extensions by using distance measures forming the Bonferroni induced heavy ordered weighted average distance and several particular cases. The study ends with an application in a large companies risk management problem in Colombia. The main advantage of this approach is that it provides a more general framework for analysing the data in scenarios where the numerical values may have some complexities that should be assessed with complex attitudinal characters.
Bluff, A, Johnston, A & Clarkson, D 2018, 'Interaction, Narrative and Animation in Live Theatre', IEEE Computer Graphics and Applications, vol. 38, no. 2, pp. 8-14.
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Boo, C, Wang, Y, Zucker, I, Choo, Y, Osuji, CO & Elimelech, M 2018, 'High Performance Nanofiltration Membrane for Effective Removal of Perfluoroalkyl Substances at High Water Recovery', Environmental Science & Technology, vol. 52, no. 13, pp. 7279-7288.
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Boroon, MP, Ayani, M-B & Bazaz, SR 2018, 'Estimation of the optimum number and location of nanoparticle injections and the specific loss power for ideal hyperthermia', Journal of Thermal Biology, vol. 72, pp. 127-136.
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Bowden, R & Veitch, D 2018, 'Finding the Right Tree: Topology Inference Despite Spatial Dependences', IEEE Transactions on Information Theory, vol. 64, no. 6, pp. 4594-4609.
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© 1963-2012 IEEE. Network tomographic techniques have almost exclusively been built on a strong assumption of mutual independence of link processes. We introduce model classes for link loss processes with non-Trivial spatial dependencies, for which the tree topology is nonetheless identifiable from leaf measurements using multicast probing. We show that these classes are large in a well-defined sense, and we provide an algorithm, SLTD, capable of returning the correct topology with certainty in the limit of infinite data.
Bown, O & Ferguson, S 2018, 'Creative Media + the Internet of Things = Media Multiplicities', Leonardo, vol. 51, no. 1, pp. 53-54.
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This paper proposes the term “media multiplicities” to describe contemporary media artworks that create multiples of “internet of things” devices. It discusses the properties that distinguish media multiplicities from other forms of media artwork, provides parameters for categorizing media multiplicities, and discusses aesthetic and creative factors in the production of media multiplicities.
Bown, O & Ferguson, S 2018, 'Understanding media multiplicities', Entertainment Computing, vol. 25, pp. 62-70.
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Internet of Things (IoT) technologies enable new forms of media artworks. ‘Media multiplicities’ are defined here as creative media experiences made up of multiples of interacting and coordinated devices. In this paper, we review the state of the art of multiplicitous media artworks and provide a systematic analysis of the novel affordances and different forms such artworks can take, specifically that they are spatial, scalable, scatterable and sensing. We consider the analysis of media multiplicities from the point of view of both user experience and creative production. We offer three primary axes through which a categorisation of multiplicitous media forms can be framed: substrate versus object; composed versus self-organised, and homogeneous versus heterogeneous. We also analyse how the number of elements in the multiplicities (from tens to tens of thousands and beyond) affects the qualities of the experience.
Bracci, M, Tarini, M, Pietroni, N, Livesu, M & Cignoni, P 2018, 'HexaLab.net: an online viewer for hexahedral meshes.', CoRR, vol. abs/1806.06639, pp. 24-36.
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We introduce HexaLab: a WebGL application for real time visualization, exploration and assessment of hexahedral meshes. HexaLab can be used by simply opening www.hexalab.net. Our visualization tool targets both users and scholars. Practitioners who employ hexmeshes for Finite Element Analysis, can readily check mesh quality and assess its usability for simulation. Researchers involved in mesh generation may use HexaLab to perform a detailed analysis of the mesh structure, isolating weak points and testing new solutions to improve on the state of the art and generate high quality images. To this end, we support a wide variety of visualization and volume inspection tools. Our system offers also immediate access to a repository containing all the publicly available meshes produced with the most recent techniques for hexmesh generation. We believe HexaLab, providing a common tool for visualizing, assessing and distributing results, will push forward the recent strive for replicability in our scientific community
Brennan, MJ, Karimi, M, Muggleton, JM, Almeida, FCL, Kroll de Lima, F, Ayala, PC, Obata, D, Paschoalini, AT & Kessissoglou, N 2018, 'On the effects of soil properties on leak noise propagation in plastic water distribution pipes', Journal of Sound and Vibration, vol. 427, pp. 120-133.
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Burdon, S, Mooney, G & Kang, K 2018, 'Where Everybody Knows Your Name: Lessons in Innovation from the High-Tech Sector', Journal of Innovation and Business Best Practice, vol. 2018, no. 2018, pp. 1-16.
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This paper examines the major priorities and prevailing values of firms highly regarded for
innovation success within the Australian high-tech sector. In conjunction with the
Information Industry Association of Australia (AIIA),
a survey was undertaken regarding
member perceptions of peer enterprises most admired
for innovation origination and
delivery. 244 responses from 102 organisations were received, analysed and compared.
Direct follow-up with selected enterprises then more closely examined factors deemed key
to sustaining a cycle of innovation leadership. Findings suggest that firms most esteemed by
peers also prioritise the realisation of innovation
over simply making money - yet both high
growth and cash flows are still habitually generated
.Results also show that having a strong
reputation for innovation is a competitive advantage in its own right as they attract
invitation to cross-enterprise ecosystems and beneficial partner alliances. Interestingly
however, topics linked to outsider/peer perceptions
of rival enterprises seem to collect
comparatively limited precedence within innovation
debates. What our study shows is that
balancing an internal reality of innovation with the external perception for innovation can
lead firms to significant improvements in overall commercial performance.
Cagno, E, Neri, A & Trianni, A 2018, 'Broadening to sustainability the perspective of industrial decision-makers on the energy efficiency measures adoption: some empirical evidence', Energy Efficiency, vol. 11, no. 5, pp. 1193-1210.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. The industry should take further efforts towards increased energy efficiency, that is a major contributor to improve industrial sustainability performance, by implementing energy efficiency measures (EEMs). However, the rate of adoption of these measures is still quite low. Hitherto, EEMs and barriers to their adoption have been evaluated almost exclusively from the viewpoint of energy efficiency decision-makers, not accounting for the broader sustainability perspective. This work aims at understanding whether an industrial sustainability perspective can better address issues related to EEMs adoption, analyzing the question through different viewpoints and insights offered by industrial decision-makers of different industrial sustainability areas within a firm. By doing this, we aim at offering a contribution in the understanding of the low rate of adoption of EEMs. As case studies, we investigated 12 firms from Northern Italy. In comparison to previous literature, results show that an industrial sustainability perspective can better explain the real decision-making process of adopting an EEM. Indeed, people knowledgeable about different industrial sustainability areas may perceive different barriers about the same EEM. EEMs may be negatively affected by reasons related to other areas of industrial sustainability, while positive reciprocal impacts may exist among areas of industrial sustainability; thus, EEMs may have effects on areas other than energy efficiency, and these effects may be perceived only by such areas. The study concludes with some remarks for policy and industrial decision-makers and advice for further research.
Cai, C, Hu, S, Chen, X, Ni, B-J, Pu, J & Yuan, Z 2018, 'Effect of methane partial pressure on the performance of a membrane biofilm reactor coupling methane-dependent denitrification and anammox', Science of The Total Environment, vol. 639, pp. 278-285.
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Complete nitrogen removal has recently been demonstrated by integrating anaerobic ammonium oxidation (anammox) and denitrifying anaerobic methane oxidation (DAMO) processes. In this work, the effect of methane partial pressure on the performance of a membrane biofilm reactor (MBfR) consisting of DAMO and anammox microorganisms was evaluated. The activities of DAMO archaea and DAMO bacteria in the biofilm increased significantly with increased methane partial pressure, from 367 ± 9 and 58 ± 22 mg-N L-1d-1 to 580 ± 12 and 222 ± 22 mg-N L-1d-1, respectively, while the activity of anammox bacteria only increased slightly, when the methane partial pressure was elevated from 0.24 to 1.39 atm in the short-term batch tests. The results were supported by a long-term (seven weeks) continuous test, when the methane partial pressure was dropped from 1.39 to 0.78 atm. The methane utilization efficiency was always above 96% during both short-term and long-term tests. Taken together, nitrogen removal rate (especially the nitrate reduction rate by DAMO archaea) and methane utilization efficiency could be maintained at high levels in a broad range of methane partial pressure (0.24-1.39 atm in this study). In addition, a previously established DAMO/anammox biofilm model was used to analyze the experimental data. The observed impacts of methane partial pressure on biofilm activity were well explained by the modeling results. These results suggest that methane partial pressure can potentially be used as a manipulated variable to control reaction rates, ultimately to maintain high nitrogen removal efficiency, according to nitrogen loading rate.
Cai, Q, Turner, BD, Sheng, D & Sloan, S 2018, 'Application of kinetic models to the design of a calcite permeable reactive barrier (PRB) for fluoride remediation', Water Research, vol. 130, pp. 300-311.
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Cancino, CA, Merigo, JM, Torres, JP & Diaz, D 2018, 'A bibliometric analysis of venture capital research', Journal of Economics, Finance and Administrative Science, vol. 23, no. 45, pp. 182-195.
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PurposeThe purpose of this study is to present the evolution of academic research in venture capital (VC) research between 1990 and 2014.Design/methodology/approachThe study analyzes the most influential journals in VC research by analyzing papers, which were published on the Web of Science database.FindingsResults show a steady increasing rate of VC research during the past 25 years. The paper reports the 40 academic journals that permanently publish articles about VC research.Originality/valueThe main contribution of this work is to develop a general overview of the leading journals in VC research, which leads to the development of a future research agenda for bibliometric analysis, such as the review of the most productive and influential authors, universities and countries in VC research.
Canning, J 2018, 'Water photonics, non-linearity, and anomalously large electro-optic coefficients in poled silica fibers', MRS Communications, vol. 8, no. 1, pp. 29-34.
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Cannon, DL, Sriram, KB, Liew, AW-C & Sun, J 2018, 'Resilience Factors Important in Health-Related Quality of Life of Subjects With COPD', Respiratory Care, vol. 63, no. 10, pp. 1281-1292.
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Cao, Y, Cao, Y, Wen, S, Huang, T & Zeng, Z 2018, 'Passivity analysis of coupled neural networks with reaction–diffusion terms and mixed delays', Journal of the Franklin Institute, vol. 355, no. 17, pp. 8915-8933.
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Cao, Y, Romero, J, Olson, JP, Degroote, M, Johnson, PD, Kieferová, M, Kivlichan, ID, Menke, T, Peropadre, B, Sawaya, NPD, Sim, S, Veis, L & Aspuru-Guzik, A 2018, 'Quantum Chemistry in the Age of Quantum Computing', Chemical Reviews, vol. 119, no. 19.
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Practical challenges in simulating quantum systems on classical computers
have been widely recognized in the quantum physics and quantum chemistry
communities over the past century. Although many approximation methods have
been introduced, the complexity of quantum mechanics remains hard to appease.
The advent of quantum computation brings new pathways to navigate this
challenging complexity landscape. By manipulating quantum states of matter and
taking advantage of their unique features such as superposition and
entanglement, quantum computers promise to efficiently deliver accurate results
for many important problems in quantum chemistry such as the electronic
structure of molecules. In the past two decades significant advances have been
made in developing algorithms and physical hardware for quantum computing,
heralding a revolution in simulation of quantum systems. This article is an
overview of the algorithms and results that are relevant for quantum chemistry.
The intended audience is both quantum chemists who seek to learn more about
quantum computing, and quantum computing researchers who would like to explore
applications in quantum chemistry.
Cao, Z & Lin, C-T 2018, 'Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 1032-1035.
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© 2017 IEEE. In recent years, the concept of entropy has been widely used to measure the dynamic complexity of signals. Since the state of complexity of human beings is significantly affected by their health state, developing accurate complexity evaluation algorithms is a crucial and urgent area of study. This paper proposes using inherent fuzzy entropy (Inherent FuzzyEn) and its multiscale version, which employs empirical mode decomposition and fuzzy membership function (exponential function) to address the dynamic complexity in electroencephalogram (EEG) data. In the literature, the reliability of entropy-based complexity evaluations has been limited by superimposed trends in signals and a lack of multiple time scales. Our proposed method represents the first attempt to use the Inherent FuzzyEn algorithm to increase the reliability of complexity evaluation in realistic EEG applications. We recorded the EEG signals of several subjects under resting condition, and the EEG complexity was evaluated using approximate entropy, sample entropy, FuzzyEn, and Inherent FuzzyEn, respectively. The results indicate that Inherent FuzzyEn is superior to other competing models regardless of the use of fuzzy or nonfuzzy structures, and has the most stable complexity and smallest root mean square deviation.
Cao, Z, Lai, K-L, Lin, C-T, Chuang, C-H, Chou, C-C & Wang, S-J 2018, 'Exploring resting-state EEG complexity before migraine attacks', Cephalalgia, vol. 38, no. 7, pp. 1296-1306.
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Objective Entropy-based approaches to understanding the temporal dynamics of complexity have revealed novel insights into various brain activities. Herein, electroencephalogram complexity before migraine attacks was examined using an inherent fuzzy entropy approach, allowing the development of an electroencephalogram-based classification model to recognize the difference between interictal and preictal phases. Methods Forty patients with migraine without aura and 40 age-matched normal control subjects were recruited, and the resting-state electroencephalogram signals of their prefrontal and occipital areas were prospectively collected. The migraine phases were defined based on the headache diary, and the preictal phase was defined as within 72 hours before a migraine attack. Results The electroencephalogram complexity of patients in the preictal phase, which resembled that of normal control subjects, was significantly higher than that of patients in the interictal phase in the prefrontal area (FDR-adjusted p < 0.05) but not in the occipital area. The measurement of test-retest reliability (n = 8) using the intra-class correlation coefficient was good with r1 = 0.73 ( p = 0.01). Furthermore, the classification model, support vector machine, showed the highest accuracy (76 ± 4%) for classifying interictal and preictal phases using the prefrontal electroencephalogram complexity. Conclusion Entropy-based analytical methods identified enhancement or “normalization” of frontal electroencephalogram complexity during the preictal phase compared with the interictal phase. This classification model, using this complexity feature, may have the potential to provide a preictal alert to migraine without aura patients.
CARLES, M-F, PATRICIA, H, ANTONIO, S & JOSÉ M., M 2018, 'The Forgotten Effects: An Application in the Social Economy of Companies of the Balearic Islands', ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, vol. 52, no. 3/2018, pp. 147-160.
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© 2018, Bucharest University of Economic Studies. All rights reserved. Few studies have analyzed how to improve the results and productivity of companies with very peculiar characteristics, such as social economy entities. This paper determines the principal worth-creating activities for this type of companies that dedicate their activities to the service sector of the Balearic Islands. In order to carry out this work, incidence matrixes and recovery of forgotten effects have been used. Both direct cause and second generation causes that arise in the majority of the socio-economic cases have been identified. In fact, determining the second generation effects, or forgotten effects, is one of the main contributions of this study as it shows that those causes that are usually not foreseen, at least in the first instance, affect notably in the generation of social economy companies value to the service sector of the Balearic Islands.
Castro, J, Lu, J, Zhang, G, Dong, Y & Martinez, L 2018, 'Opinion Dynamics-Based Group Recommender Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 12, pp. 2394-2406.
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With the accessibility to information, users often face the problem of selecting one item (a product or a service) from a huge search space. This problem is known as information overload. Recommender systems (RSs) personalize content to a user's interests to help them select the right item in information overload scenarios. Group RSs (GRSs) recommend items to a group of users. In GRSs, a recommendation is usually computed by a simple aggregation method for individual information. However, the aggregations are rigid and overlook certain group features, such as the relationships between the group members' preferences. In this paper, it is proposed a GRS based on opinion dynamics that considers these relationships using a smart weights matrix to drive the process. In some groups, opinions do not agree, hence the weights matrix is modified to reach a consensus value. The impact of ensuring agreed recommendations is evaluated through a set of experiments. Additionally, a sensitivity analysis studies its behavior. Compared to existing group recommendation models and frameworks, the proposal based on opinion dynamics would have the following advantages: 1) flexible aggregation method; 2) member relationships; and 3) agreed recommendations.
Cetindamar, D 2018, 'Designed by law: Purpose, accountability, and transparency at benefit corporations', Cogent Business & Management, vol. 5, no. 1, pp. 1423787-1423787.
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The article explores the realization of major goals of the Benefit
Corporation (BC) law, which is a corporation form designed for social enterprises in the United States in 2010. BCs have a dual mission of generating both profit and social value and hence they might have the potential to transform society. This paper attempts to observe the first movers established as BCs during the period of 2010–2012. By adopting the institutional theory approach, the study examines the realization of the BC law’s three major goals: purpose, accountability, and transparency.
The paper utilizes the regulatory legitimacy concept to measure the discrepancy between design and implementation of law. The observations point out some of the challenges of establishing new innovative organizations through an institutional intervention of a law. Conclusions consist of implications of the study as well as suggestions
for further studies.
Chaei, MG, Akbarnezhad, A, Castel, A, Lloyd, R, Keyte, L & Foster, S 2018, 'Precision of cement hydration heat models in capturing the effects of SCMs and retarders', Magazine of Concrete Research, vol. 70, no. 23, pp. 1217-1231.
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A major input to numerical simulation models used to predict the risk of early-age thermal cracking in concrete is the hydration heat estimation. The precision of hydration heat estimation models has been extensively verified for different cement compositions in previous studies. However, little has been done to investigate the accuracy of such models for concrete mixes containing supplementary cementitious materials and retarders. This paper presents the results of a series of isothermal calorimetry tests conducted first to investigate the effects of Class F fly ash, ground-granulated blast-furnace slag (GGBFS) and three commonly used retarders (namely, retarder N, sucrose and citrate) on the heat of hydration profile of Australian general-purpose cement under different curing temperatures of 10, 23 and 30°C, and second to evaluate the precision of the two most commonly used hydration heat models in capturing the effects of fly ash, GGBFS, retarders and curing temperature on the hydration profile. The results reveal the possibility of considerable errors in estimating the hydration heat of concrete mixes containing supplementary cementitious materials and retarders under different curing temperatures, highlighting the need for re-calibration of the existing models for locally used materials to avoid misleading errors in numerical simulation of early-age thermal cracking.
Chang, X, Yan, Y & Nie, L 2018, 'Guest Editorial: Semantic Concept Discovery in MM Data', Multimedia Tools and Applications, vol. 77, no. 3, pp. 2945-2946.
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Chauhan, J, Seneviratne, S, Hu, Y, Misra, A, Seneviratne, A & Lee, Y 2018, 'Breathing-Based Authentication on Resource-Constrained IoT Devices using Recurrent Neural Networks', Computer, vol. 51, no. 5, pp. 60-67.
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Chekli, L, Pathak, N, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Shon, HK 2018, 'Combining high performance fertiliser with surfactants to reduce the reverse solute flux in the fertiliser drawn forward osmosis process', Journal of Environmental Management, vol. 226, pp. 217-225.
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Solutions to mitigate the reverse diffusion of solutes are critical to the successful commercialisation of the fertiliser drawn forward osmosis process. In this study, we proposed to combine a high performance fertiliser (i.e., ammonium sulfate or SOA) with surfactants as additives as an approach to reduce the reverse diffusion of ammonium ions. Results showed that combining SOA with both anionic and non-ionic surfactants can help in reducing the reverse salt diffusion by up to 67%. We hypothesised that, hydrophobic interactions between the surfactant tails and the membrane surface likely constricted membrane pores resulting in increased rejection of ions with large hydrated radii such as SO42-. By electroneutrality, the rejection of the counter ions (i.e., NH4+) also therefore subsequently improved. Anionic surfactant was found to further decrease the reverse salt diffusion due to electrostatic repulsions between the surfactant negatively-charged heads and SO42-. However, when the feed solution contains cations with small hydrated radii (e.g., Na+); it was found that NH4+ ions can be substituted in the DS to maintain its electroneutrality and thus the diffusion of NH4+ to the feed solution was increased.
Chen, C, Guo, WS, Ngo, HH, Chang, SW, Nguyen, DD, Zhang, J, Liang, S, Guo, JB & Zhang, XB 2018, 'Effects of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor for municipal wastewater treatment', Bioresource Technology, vol. 247, pp. 340-346.
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This study aimed to evaluate the impact of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor (SAAMB-AnGMBR) in municipal wastewater treatment. The results showed that organic removal efficiencies were above 94% at all C/N conditions. Nutrient removal was over 91% at C/N ratio of 100/5 but was negatively affected when decreasing C/N ratio to 100/10. At lower C/N ratio (100/10), more noticeable membrane fouling was caused by aggravated cake formation and pore clogging, and accumulation of extracellular polymeric substances (EPS) in the mixed liquor and sludge cake as a result of deteriorated granular quality. Foulant analysis suggested significant difference existed in the foulant organic compositions under different C/N ratios, and humic substances were dominant when the fastest fouling rate was observed. The performance of the hybrid system was found to recover when gradually increasing C/N ratio from 100/10 to 100/5.
Chen, C, Wang, F, Wen, S, Su, QP, Wu, MCL, Liu, Y, Wang, B, Li, D, Shan, X, Kianinia, M, Aharonovich, I, Toth, M, Jackson, SP, Xi, P & Jin, D 2018, 'Multi-photon near-infrared emission saturation nanoscopy using upconversion nanoparticles', Nature Communications, vol. 9, no. 1.
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AbstractMultiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 μm thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking.
Chen, H, McGowan, EM, Ren, N, Lal, S, Nassif, N, Shad-Kaneez, F, Qu, X & Lin, Y 2018, 'Nattokinase: A Promising Alternative in Prevention and Treatment of Cardiovascular Diseases', Biomarker Insights, vol. 13, pp. 117727191878513-117727191878513.
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Cardiovascular disease (CVD) is the leading cause of death in the world and our approach to the control and management of CVD mortality is limited. Nattokinase (NK), the most active ingredient of natto, possesses a variety of favourable cardiovascular effects and the consumption of Natto has been linked to a reduction in CVD mortality. Recent research has demonstrated that NK has potent fibrinolytic activity, antihypertensive, anti-atherosclerotic, and lipid-lowering, antiplatelet, and neuroprotective effects. This review covers the major pharmacologic effects of NK with a focus on its clinical relevance to CVD. It outlines the advantages of NK and the outstanding issues pertaining to NK pharmacokinetics. Available evidence suggests that NK is a unique natural compound that possesses several key cardiovascular beneficial effects for patients with CVD and is therefore an ideal drug candidate for the prevention and treatment of CVD. Nattokinase is a promising alternative in the management of CVD.
Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to “Estimation of Passive Earth Pressure against Rigid Retaining Wall Considering Arching Effect in Cohesive-Frictional Backfill under Translation Mode” by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7, pp. 07018012-07018012.
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Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to 'Estimation of passive earth pressure against rigid retaining wall considering arching effect in cohesive- frictional backfill under translation mode' by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7.
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Chen, S, Wang, Z, Liang, J & Yuan, X 2018, 'Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal data', Journal of Visual Languages & Computing, vol. 48, pp. 187-198.
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Chen, S, Yu, H & Fang, J 2018, 'A novel multi-cell tubal structure with circular corners for crashworthiness', Thin-Walled Structures, vol. 122, pp. 329-343.
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© 2017 Elsevier Ltd Multi-cell structures have proven to own excellent energy absorbing capability and lightweight effect in the automotive and aerospace industries. The cross-sectional configuration of the multi-cell structure has a significant effect on crashworthiness. Unlike existing multi-cell tubes, a new type of five-cell profile with four circular elements at the corners (C5C) was proposed in this study. To investigate the crashworthiness of the new C5C tube, finite element (FE) models were first established by using the nonlinear finite element code LS-DYNA and validated with experimental results. Following that, the comparison of the C5C tube and other multi-cell tubes with the same mass was conducted to quantify the relative merits of the C5C tube. Then, a detailed study was performed to analyze the effect of the corner-cell size and wall thickness. Finally, the optimization design was carried out to seek the optimal structure. The results showed that the new multi-cell structure can absorb much more crash energy than other four types of tubes. Moreover, the energy absorption of this new multi-cell tube C5C was affected by the corner-cell size and wall thickness significantly. A proper corner-cell size and slightly thicker internal ribs were recommended. In addition, the multi-objective particle swarm optimization (MOPSO) algorithm and radial basis function (RBF) surrogate model can optimize the structure effectively. The outcomes of the present study will facilitate the design of multi-cell structures with better crashworthiness.
Chen, S-L, Qin, P-Y, Lin, W & Guo, YJ 2018, 'Pattern-Reconfigurable Antenna With Five Switchable Beams in Elevation Plane', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 3, pp. 454-457.
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© 2017 IEEE. Pattern-reconfigurable antennas with multiple switchable beams, especially with both boresight and endfire directions, are highly desired for wireless communications. In this letter, a novel pattern-reconfigurable antenna is proposed that provides an efficient solution. By reconfiguring parasitic striplines placed around a radiating dipole and reflecting metal pieces under the dipole using p-i-n diodes, the antenna main beam can be switched to five directions in the elevation plane, approximately from-90(left endfire),-45 , 0 (boresight),+45 to +90(right endfire). The proposed antenna operates at 2.45 GHz with dimensions of about 0.57λ× 0.45\lambda×, 0.28λ. An antenna prototype is fabricated and measured. For all five directional beams, the measured S-{11}| values are below 13 dB, and the measured realized gains range from 5.2 to 6.5 dBi. They agree reasonably well with the simulated ones.
Chen, W, Peng, J, Hong, H, Shahabi, H, Pradhan, B, Liu, J, Zhu, A-X, Pei, X & Duan, Z 2018, 'Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China', Science of The Total Environment, vol. 626, pp. 1121-1135.
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© 2018 Elsevier B.V. The preparation of a landslide susceptibility map is considered to be the first step for landslide hazard mitigation and risk assessment. However, these maps are accepted as end products that can be used for land use planning. The main goal of this study is to assess and compare four advanced machine learning techniques, namely the Bayes’ net (BN), radical basis function (RBF) classifier, logistic model tree (LMT), and random forest (RF) models, for landslide susceptibility modelling in Chongren County, China. A total of 222 landslide locations were identified in the study area using historical reports, interpretation of aerial photographs, and extensive field surveys. The landslide inventory data was randomly split into two groups with a ratio of 70/30 for training and validation purposes. Fifteen landslide conditioning factors were prepared for landslide susceptibility modelling. The spatial correlation between landslides and conditioning factors was analyzed using the information gain (IG) method. The BN, RBF classifier, LMT, and RF models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) and statistical measures, including sensitivity, specificity, and accuracy, were employed to validate and compare the predictive capabilities of the models. Out of the tested models, the RF model had the highest sensitivity, specificity, and accuracy values of 0.787, 0.716, and 0.752, respectively, for the training dataset. Overall, the RF model produced an optimized balance for the training and validation datasets in terms of AUC values and statistical measures. The results of this study also demonstrate the benefit of selecting optimal machine learning techniques with proper conditioning selection methods for landslide susceptibility modelling.
Chen, W, Simpson, JM, March, LM, Blyth, FM, Bliuc, D, Tran, T, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Comorbidities Only Account for a Small Proportion of Excess Mortality After Fracture: A Record Linkage Study of Individual Fracture Types', Journal of Bone and Mineral Research, vol. 33, no. 5, pp. 795-802.
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Nonhip, nonvertebral (NHNV) fractures constitute the majority of osteoporotic fractures, but few studies have examined the association between these fractures, comorbidity, and mortality. Our objective was to examine the relationship between individual nonhip, nonvertebral fractures, comorbidities, and mortality. The prospective population-based cohort of 267,043 subjects (45 and Up Study, Australia) had baseline questionnaires linked to hospital administrative and all-cause mortality data from 2006 to 2013. Associations between fracture and mortality were examined using multivariate, time-dependent Cox models, adjusted for age, prior fracture, body mass index, smoking, and comorbidities (cardiovascular disease, diabetes, stroke, thrombosis, and cancer), and survival function curves. Population attributable fraction was calculated for each level of risk exposure. During 1,490,651 person-years, women and men experienced 7571 and 4571 fractures and 7064 deaths and 11,078 deaths, respectively. In addition to hip and vertebral fractures, pelvis, humerus, clavicle, rib, proximal tibia/fibula, elbow and distal forearm fractures in both sexes, and ankle fractures in men were associated with increased multivariable-adjusted mortality hazard ratios ranging from 1.3 to 3.4. Comorbidity independently added to mortality such that a woman with a humeral fracture and 1 comorbidity had a similarly reduced 5-year survival as that of a woman with a hip fracture and no comorbidities. Population mortality attributable to any fracture without comorbidity was 9.2% in women and 5.3% in men. All proximal nonhip, nonvertebral fractures in women and men were associated with increased mortality risk. Coexistent comorbidities independently further increased mortality. Population attributable risk for mortality for fractures was similar to cardiovascular disease and diabetes, highlighting their importance and potential benefit for early intervention and treatment. © 2018 American Society fo...
Chen, X, Li, Y, Li, J & Gu, X 2018, 'A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices', Smart Materials and Structures, vol. 27, no. 1, pp. 015005-015005.
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Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov's direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.
Chen, X, Yuan, G, Wang, W, Nie, F, Chang, X & Huang, JZ 2018, 'Local Adaptive Projection Framework for Feature Selection of Labeled and Unlabeled Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6362-6373.
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Chen, X, Yuan, Z & Ni, B-J 2018, 'Nitrite accumulation inside sludge flocs significantly influencing nitrous oxide production by ammonium-oxidizing bacteria', Water Research, vol. 143, pp. 99-108.
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Chen, Y, Dong, Y, Sun, Y & Liang, J 2018, 'A Multi-comparable visual analytic approach for complex hierarchical data', Journal of Visual Languages & Computing, vol. 47, pp. 19-30.
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© 2018 Elsevier Ltd Maximum residue limit (MRL) standard which specifies the highest level of every pesticide residue in different agricultural products plays a critical role in food safety. However, such standards which related to the characteristics of pesticides and the classification of agricultural products which organized into a hierarchical structure are complex and vary widely across different regions or countries. So it is a big challenge to compare multi-regional MRL standard data comprehensively. In this paper, we present a multi-comparable visual analytic approach for complex hierarchical data and a visual analytics system (McVA) to support multiple comparison and evaluation of MRL standard. With a cooperative multi-view visual design, our proposed approach links the hierarchies of MRL datasets and provides the capacity for comparison at different levels and dimensions. We also introduce a metric model for evaluating the completeness and strictness of MRL standards quantitatively. The case study of real problems and the positive feedback from domain experts demonstrate the effectiveness of this approach.
Chen, Y, Su, QP, Sun, Y & Yu, L 2018, 'Visualizing Autophagic Lysosome Reformation in Cells Using In Vitro Reconstitution Systems', Current Protocols in Cell Biology, vol. 78, no. 1, pp. 11.24.1-11.24.15.
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Autophagy is a lysosome-based degradation pathway. Autophagic lysosome reformation (ALR) is a lysosomal membrane recycling process that marks the terminal step of autophagy. During ALR, LAMP1-positive tubules, named reformation tubules, are extruded from autolysosomes, and nascent lysosomes are generated from these tubules. By combining proteomic analysis of purified autolysosomes and RNA interference screening of identified candidates, we systematically elucidated the ALR pathway at the molecular level. Based on the key components clathrin, PtdIns(4,5)P2 , and the motor protein KIF5B, among others, we reconstituted this process in vitro. This unit describes a detailed method for visualizing ALR in cells during the autophagy process. This unit also present a protocol for reconstituting the ALR tubular protrusion and elongation process in vitro and three methods for preparing materials for in vitro reconstitution: (1) autolysosome purification from cultured cells, (2) liposome preparation, and (3) KIF5B purification and quality testing. © 2018 by John Wiley & Sons, Inc.
Chen, Y, Wu, Y, Wang, D, Li, H, Wang, Q, Liu, Y, Peng, L, Yang, Q, Li, X, Zeng, G & Chen, Y 2018, 'Understanding the mechanisms of how poly aluminium chloride inhibits short-chain fatty acids production from anaerobic fermentation of waste activated sludge', Chemical Engineering Journal, vol. 334, pp. 1351-1360.
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© 2017 Elsevier B.V. Poly aluminum chloride (PAC) is accumulated in waste activated sludge at high levels. However, details of how PAC affects short-chain fatty acids (SCFA) production from anaerobic sludge fermentation has not been documented. This work therefore aims to fill this knowledge gap by analyzing the impact of PAC on the aggregate of sludge flocs, disruption of extracellular polymeric substances (EPS), and the bio-processes of hydrolysis, acidogenesis, and methanogenesis. The relationship between SCFA production and different aluminum species (i.e., Ala, Alb, and Alc) was also identified by controlling different OH/Al ratio and pH in different fermentation systems. Experimental results showed that with the increase of PAC addition from 0 to 40 mg Al per gram of total suspended solids, SCFA yield decreased from 212.2 to 138.4 mg COD/g volatile suspended solids. Mechanism exploration revealed that PAC benefited the aggregates of sludge flocs and caused more loosely- and tightly-bound extracellular polymeric substances remained in sludge cells. Besides, it was found that the hydrolysis, acidiogenesis, and methanogenesis processes were all inhibited by PAC. Although three types of Al species, i.e., Ala (Al monomers, dimer, and trimer), Alb (Al13(AlO4Al12(OH)24(H2O)7 + 12), and Alc (Al polymer molecular weight normally larger than 3000 Da), were co-existed in fermentation systems, their impacts on SCFA production were different. No correlation was found between SCFA and Ala, whereas SCFA production decreased with the contents of Alb and Alc. Compared with Alb, Alc was the major contributor to the decreased SCFA production (R2 = 0.5132 vs R2 = 0.98). This is the first report revealing the underlying mechanism of how PAC affects SCFA production and identifying the contribution of different Al species to SCFA inhibition.
Chen, Z, Ren, Z, Gao, H, Qian, Y & Zheng, R 2018, 'Effect of modified starch on separation of fluorite from barite using sodium oleate', Physicochemical Problems of Mineral Processing, vol. 54, no. 2, pp. 228-237.
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In this study, a modified starch was utilized to selectively separate barite from fluorite. The results of flotation tests showed that highly selective separation of fluorite from barite was obtained when 250 mg/dm3 of modified starch and 13.16×10-5 mol/dm3 sodium oleate was used in neutral solutions. FTIR spectra results showed that the modified starch can adsorb on the fluorite and barite surfaces. Zeta potential analyses indicated that the modified starch had little effect on adsorption of sodium oleate on the fluorite surface, although it interfered with the adsorption of sodium oleate on the barite surface. Contact angle measurements results corresponded well with the flotation results.
Chen, Z, Wang, D, Sun, M, Hao Ngo, H, Guo, W, Wu, G, Jia, W, Shi, L, Wu, Q, Guo, F & Hu, H-Y 2018, 'Sustainability evaluation and implication of a large scale membrane bioreactor plant', Bioresource Technology, vol. 269, pp. 246-254.
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Membrane bioreactor (MBR) technology is receiving increasing attention in wastewater treatment and reuse. This study presents an integral sustainability evaluation of a full scale MBR plant. The plant is capable of achieving prominent technical performance in terms of high compliance rate, low variation in effluent quality and high removal efficiency during long term operation. It is also more responsive to the new local standard with rigorous limits. However, electricity consumption is found to be the dominant process resulting in elevated life cycle environmental impacts and costs, accounting for 51.6% of the costs. As such, it is suggested to optimize energy use in MBR unit and implement sludge treatment and management. The prolonged membrane life span could also contribute largely to reduced life cycle environmental concerns and expenses. This study is of great theoretical significance and applicable value in guaranteeing the performance and sustainability of large scale MBR schemes.
Chen, Z, Yu, T, Ngo, HH, Lu, Y, Li, G, Wu, Q, Li, K, Bai, Y, Liu, S & Hu, H-Y 2018, 'Assimilable organic carbon (AOC) variation in reclaimed water: Insight on biological stability evaluation and control for sustainable water reuse', Bioresource Technology, vol. 254, pp. 290-299.
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This review highlights the importance of conducting biological stability evaluation due to water reuse progression. Specifically, assimilable organic carbon (AOC) has been identified as a practical indicator for microbial occurrence and regrowth which ultimately influence biological stability. Newly modified AOC bioassays aimed for reclaimed water are introduced. Since elevated AOC levels are often detected after tertiary treatment, the review emphasizes that actions can be taken to either limit AOC levels prior to disinfection or conduct post-treatment (e.g. biological filtration) as a supplement to chemical oxidation based approaches (e.g. ozonation and chlorine disinfection). During subsequent distribution and storage, microbial community and possible microbial regrowth caused by complex interactions are discussed. It is suggested that microbial surveillance, AOC threshold values, real-time field applications and surrogate parameters could provide additional information. This review can be used to formulate regulatory plans and strategies, and to aid in deriving relevant control, management and operational guidance.
Chenari, RJ, Fatahi, B, Ghorbani, A & Alamoti, MN 2018, 'Evaluation of strength properties of cement stabilized sand mixed with EPS beads and fly ash', Geomechanics and Engineering, vol. 14, no. 6, pp. 533-544.
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The importance of using materials cost effectively to enhance the strength and reduce the cost, and weight of earth fill materials in geotechnical engineering led researchers to seek for modifying the soil properties by adding proper additives. Lightweight fill materials made of soil, binder, water, and Expanded polystyrene (EPS) beads are increasingly being used in geotechnical practices. This paper primarily investigates the behavior of sandy soil, modified by EPS particles. Besides, the mechanical properties of blending sand, EPS and the binder material such as fly ash and cement were examined in different mixing ratios using a number of various laboratory studies including the Modified Standard Proctor (MSP) test, the Unconfined Compressive Strength (UCS) test, the California Bearing Ratio (CBR) test and the Direct Shear test (DST). According to the results, an increase of 0.1% of EPS results in a reduction of the density of the mixture for 10%, as well as making the mixture more ductile rather than brittle. Moreover, the compressive strength, CBR value and shear strength parameters of the mixture decreases by an increase of the EPS beads, a trend on the contrary to the increase of cement and fly ash content.
Cheng, D, Gong, Y, Chang, X, Shi, W, Hauptmann, A & Zheng, N 2018, 'Deep feature learning via structured graph Laplacian embedding for person re-identification', Pattern Recognition, vol. 82, pp. 94-104.
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Cheng, D, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD, Zhou, J & Ni, B 2018, 'Anaerobic membrane bioreactors for antibiotic wastewater treatment: Performance and membrane fouling issues', Bioresource Technology, vol. 267, pp. 714-724.
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Antibiotic wastewater has become a major concern due to the toxicity and recalcitrance of antibiotics. Anaerobic membrane bioreactors (AnMBRs) are considered alternative technology for treating antibiotic wastewater because of their advantages over the conventional anaerobic processes and aerobic MBRs. However, membrane fouling remains the most challenging issue in the AnMBRs' operation and this limits their application. This review critically discusses: (i) antibiotics removal and antibiotic resistance genes (ARGs) in different types of AnMBRs and the impact of antibiotics on membrane fouling and (ii) the integrated AnMBRs systems for fouling control and removal of antibiotics. The presence of antibiotics in AnMBRs could aggravate membrane fouling by influencing fouling-related factors (i.e., sludge particle size, extracellular polymeric substances (EPS), soluble microbial products (SMP), and fouling-related microbial communities). Conclusively, integrated AnMBR systems can be a practical technology for antibiotic wastewater treatment.
Cheng, DL, Ngo, HH, Guo, WS, Chang, SW, Nguyen, DD, Kumar, SM, Du, B, Wei, Q & Wei, D 2018, 'Problematic effects of antibiotics on anaerobic treatment of swine wastewater', Bioresource Technology, vol. 263, pp. 642-653.
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Swine wastewaters with high levels of organic pollutants and antibiotics have become serious environmental concerns. Anaerobic technology is a feasible option for swine wastewater treatment due to its advantage in low costs and bioenergy production. However, antibiotics in swine wastewater have problematic effects on micro-organisms, and the stability and performance of anaerobic processes. Thus, this paper critically reviews impacts of antibiotics on pH, COD removal efficiencies, biogas and methane productions as well as the accumulation of volatile fatty acids (VFAs) in the anaerobic processes. Meanwhile, impacts on the structure of bacteria and methanogens in anaerobic processes are also discussed comprehensively. Furthermore, to better understand the effect of antibiotics on anaerobic processes, detailed information about antimicrobial mechanisms of antibiotics and microbial functions in anaerobic processes is also summarized. Future research on deeper knowledge of the effect of antibiotics on anaerobic processes are suggested to reduce their adverse environmental impacts.
Cheng, DL, Ngo, HH, Guo, WS, Liu, YW, Zhou, JL, Chang, SW, Nguyen, DD, Bui, XT & Zhang, XB 2018, 'Bioprocessing for elimination antibiotics and hormones from swine wastewater', Science of The Total Environment, vol. 621, pp. 1664-1682.
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Antibiotics and hormones in swine wastewater have become a critical concern worldwide due to the severe threats to human health and the eco-environment. Removal of most detectable antibiotics and hormones, such as sulfonamides (SAs), SMs, tetracyclines (TCs), macrolides, and estrogenic hormones from swine wastewater utilizing various biological processes were summarized and compared. In biological processes, biosorption and biodegradation are the two major removal mechanisms for antibiotics and hormones. The residuals in treated effluents and sludge of conventional activated sludge and anaerobic digestion processes can still pose risks to the surrounding environment, and the anaerobic processes' removal efficiencies were inferior to those of aerobic processes. In contrast, membrane bioreactors (MBRs), constructed wetlands (CWs) and modified processes performed better because of their higher biodegradation of toxicants. Process modification on activated sludge, anaerobic digestion and conventional MBRs could also enhance the performance (e.g. removing up to 98% SMs, 88.9% TCs, and 99.6% hormones from wastewater). The hybrid process combining MBRs with biological or physical technology also led to better removal efficiency. As such, modified conventional biological processes, advanced biological technologies and MBR hybrid systems are considered as a promising technology for removing toxicants from swine wastewater.
Cheng, H-C, Hanson, EP, Datta, N & Hsieh, M-H 2018, 'Non-Asymptotic Classical Data Compression with Quantum Side Information'.
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In this paper, we analyze classical data compression with quantum side
information (also known as the classical-quantum Slepian-Wolf protocol) in the
so-called large and moderate deviation regimes. In the non-asymptotic setting,
the protocol involves compressing classical sequences of finite length $n$ and
decoding them with the assistance of quantum side information. In the large
deviation regime, the compression rate is fixed, and we obtain bounds on the
error exponent function, which characterizes the minimal probability of error
as a function of the rate. Devetak and Winter showed that the asymptotic data
compression limit for this protocol is given by a conditional entropy. For any
protocol with a rate below this quantity, the probability of error converges to
one asymptotically and its speed of convergence is given by the strong converse
exponent function. We obtain finite blocklength bounds on this function, and
determine exactly its asymptotic value. In the moderate deviation regime for
the compression rate, the latter is no longer considered to be fixed. It is
allowed to depend on the blocklength $n$, but assumed to decay slowly to the
asymptotic data compression limit. Starting from a rate above this limit, we
determine the speed of convergence of the error probability to zero and show
that it is given in terms of the conditional information variance. Our results
complement earlier results obtained by Tomamichel and Hayashi, in which they
analyzed the so-called small deviation regime of this protocol.
Cheng, L, Acuna, P, Aguilera, RP, Jiang, J, Wei, S, Fletcher, JE & Lu, DDC 2018, 'Model Predictive Control for DC–DC Boost Converters With Reduced-Prediction Horizon and Constant Switching Frequency', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 9064-9075.
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IEEE The implementation of multi-step direct model predictive control (MPC) for DC-DC boost converters overcomes the well-known issue of non-minimum phase behaviour. However, it can lead to a high computational burden depending on the prediction horizon length. In this work, a simple and computationally efficient MPC method for DC-DC boost converters is proposed. The key novelty of the presented control strategy lies in the way dynamic references are handled. The control strategy is capable of providing suitable references for the inductor current and the output voltage, without requiring additional control loops. Moreover, this reference design allows the predictive controller to be implemented with a single-step prediction horizon. Thus, a significant reduction in the required real-time calculations executed in the control hardware is achieved. To obtain constant switching frequency, the power switch commutation instants within a sampling period are considered as control inputs. Therefore, the predictive controller is formulated as a continuous control set MPC (CCS-MPC). Additionally, the proposed formulation is able to deal with different operation modes of the converter without changing the controller structure. Finally, an observer is used to dynamically modify the reference to provide robustness to system parameter uncertainties. Simulation and experimental results show an accurate tracking of dynamic inductor current and output voltage references, while respecting the restrictions on maximum inductor current levels of the converter.
Cheng, P, Chen, Z, Zhang, JA, Li, Y & Vucetic, B 2018, 'A Unified Precoding Scheme for Generalized Spatial Modulation', IEEE Transactions on Communications, vol. 66, no. 6, pp. 2502-2514.
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© 1972-2012 IEEE. Generalized spatial modulation (GSM) activates Nt (1 ≤ nt < Nt) available transmit antennas, and information is conveyed through nt modulated symbols as well as the index of the nt activated antennas. GSM strikes an attractive tradeoff between spectrum efficiency and energy efficiency. Linear precoding that exploits channel state information at the transmitter enhances the system error performance. For GSM with nt=1 (the traditional SM), the existing precoding methods suffer from high computational complexity. On the other hand, GSM precoding for nt ≥ 2 is not thoroughly investigated in the open literature. In this paper, we develop a unified precoding design for GSM systems, which universally works for all nt values. Based on the maximum minimum Euclidean distance criterion, we find that the precoding design can be formulated as a large-scale nonconvex quadratically constrained quadratic program problem. Then, we transform this challenging problem into a sequence of unconstrained subproblems by leveraging augmented Lagrangian and dual ascent techniques. These subproblems can be solved in an iterative manner efficiently. Numerical results show that the proposed method can substantially improve the system error performance relative to the GSM without precoding and features extremely fast convergence rate with a very low computational complexity.
Cheng, T, Lu, DD-C & Qin, L 2018, 'Non-Isolated Single-Inductor DC/DC Converter With Fully Reconfigurable Structure for Renewable Energy Applications.', IEEE Trans. Circuits Syst. II Express Briefs, vol. 65-II, no. 3, pp. 351-355.
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© 2017 IEEE. A novel non-isolated three-port converter (NITPC) is introduced in this brief. The purpose of this topology is to integrate a regenerative load such as DC bus and motor with dynamic braking, instead of the widely reported consuming load, with a photovoltaic (PV)-battery system. Conventional methods require either a separate DC-DC converter to process the reversible power flow or employing an isolated three-port converter (TPC), which allows bi-directional power flow between any two ports. However, these methods require many switches, which increases the converter size and control complexity. This brief hence presents a compact but fully functional design by combining and integrating basic converters to form a simplified single-inductor converter structure while keeping a minimum amount of switches. The resultant converter is fully reconfigurable that all possible power flow combinations among the sources and load are achieved through different switching patterns, while preserving the single power processing feature of TPC. This brief presents a design example of the proposed NITPC for a PV-battery powered DC microgrid. Detailed circuitry analysis, operation principles of both DC grid-connected and islanded modes, and experimental results of different modes in steady state and mode transitions are presented.
Cheng, X-W, Jiang, Z-Y, Monaghan, BJ, Longbottom, RJ, Wei, D-B, Hee, AC & Jiang, L-Z 2018, 'Degradation of ferritic stainless steels at 1200 °C in air', Materials and Corrosion, vol. 69, no. 1, pp. 63-75.
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Cheng, Z, Zhang, X, Shen, S, Yu, S, Ren, J & Lin, R 2018, 'T-Trail: Link Failure Monitoring in Software-Defined Optical Networks', Journal of Optical Communications and Networking, vol. 10, no. 4, pp. 344-344.
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Chi, L, Li, B, Zhu, X, Pan, S & Chen, L 2018, 'Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts', IEEE Transactions on Cybernetics, vol. 48, no. 5, pp. 1591-1604.
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Many applications involve processing networked streaming data in a timely manner. Graph stream classification aims to learn a classification model from a stream of graphs with only one-pass of data, requiring real-time processing in training and prediction. This is a nontrivial task, as many existing methods require multipass of the graph stream to extract subgraph structures as features for graph classification which does not simultaneously satisfy "one-pass" and "real-time" requirements. In this paper, we propose an adaptive real-time graph stream classification method to address this challenge. We partition the unbounded graph stream data into consecutive graph chunks, each consisting of a fixed number of graphs and delivering a corresponding chunk-level classifier. We employ a random hashing function to compress the original node set of graphs in each chunk for fast feature detection when training chunk-level classifiers. Furthermore, a differential hashing strategy is applied to map unlimited increasing features (i.e., cliques) into a fixed-size feature space which is then used as a feature vector for stochastic learning. Finally, the chunk-level classifiers are weighted in an ensemble learning model for graph classification. The proposed method substantially speeds up the graph feature extraction and avoids unbounded graph feature growth. Moreover, it effectively offsets concept drifts in graph stream classification. Experiments on real-world and synthetic graph streams demonstrate that our method significantly outperforms existing methods in both classification accuracy and learning efficiency.
Chia, SR, Chew, KW, Show, PL, Yap, YJ, Ong, HC, Ling, TC & Chang, J-S 2018, 'Analysis of Economic and Environmental Aspects of Microalgae Biorefinery for Biofuels Production: A Review', Biotechnology Journal, vol. 13, no. 6, pp. 1700618-1700618.
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Chia, SR, Ong, HC, Chew, KW, Show, PL, Phang, S-M, Ling, TC, Nagarajan, D, Lee, D-J & Chang, J-S 2018, 'Sustainable approaches for algae utilisation in bioenergy production', Renewable Energy, vol. 129, pp. 838-852.
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Chia, SR, Show, PL, Phang, S-M, Ling, TC & Ong, HC 2018, 'Sustainable approach in phlorotannin recovery from macroalgae', Journal of Bioscience and Bioengineering, vol. 126, no. 2, pp. 220-225.
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Chikara, RK, Chang, EC, Lu, Y-C, Lin, D-S, Lin, C-T & Ko, L-W 2018, 'Monetary Reward and Punishment to Response Inhibition Modulate Activation and Synchronization Within the Inhibitory Brain Network', Frontiers in Human Neuroscience, vol. 12.
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© 2018 Chikara, Chang, Lu, Lin, Lin and Ko. A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback) to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback), and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG) and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks.
Chitambar, E, Fortescue, B & Hsieh, M-H 2018, 'The Conditional Common Information in Classical and Quantum Secret Key Distillation', IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 7381-7394.
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© 2018 IEEE. In this paper, we consider two extensions of the Gács-Körner common information to three variables, the conditional common information (cCI) and the coarse-grained conditional common information (ccCI). Both quantities are shown to be useful technical tools in the study of classical and quantum resource transformations. In particular, the ccCI is shown to have an operational interpretation as the optimal rate of secret key extraction from an eavesdropped classical source pXYZ when Alice (X) and Bob (Y) are unable to communicate but share common randomness with the eavesdropper Eve (Z). Moving to the quantum setting, we consider two different ways of generating a tripartite quantum state from classical correlations pXYZ : 1) coherent encodings ∑xyz√pxyz|xyz〉 and 2) incoherent encodings ∑xyzpxyz|xyz〉〈xyz|. We study how well can Alice and Bob extract secret key from these quantum sources using quantum operations compared with the extraction of key from the underlying classical sources pXYZ using classical operations. While the power of quantum mechanics increases Alice and Bob's ability to generate shared randomness, it also equips Eve with a greater arsenal of eavesdropping attacks. Therefore, it is not obvious who gains the greatest advantage for distilling secret key when replacing a classical source with a quantum one. We first demonstrate that the classical key rate of pXYZ is equivalent to the quantum key rate for an incoherent quantum encoding of the distribution. For coherent encodings, we next show that the classical and quantum rates are generally incomparable, and in fact, their difference can be arbitrarily large in either direction. Finally, we introduce a "zoo" of entangled tripartite states all characterized by the conditional common information of their encoded probability distributions. Remarkably, for these states almost all entanglement measures, such as Alice and Bob's entanglement cost, squashed entanglement, and relative entropy of...
Chiu, SK, Saw, J, Huang, Y, Sonderegger, SE, Wong, NC, Powell, DR, Beck, D, Pimanda, JE, Tremblay, CS & Curtis, DJ 2018, 'A novel role for Lyl1 in primitive erythropoiesis', Development, vol. 145, no. 19.
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Stem Cell Leukemia (Scl or Tal1) and Lymphoblastic Leukemia 1 (Lyl1) are highly related members of the basic helix-loop-helix (bHLH) family of transcription factors that are co- expressed in the erythroid lineage. Previous studies suggest that Scl is essential for primitive erythropoiesis. However, analysis of single-cell RNA-sequencing data of early embryos showed that primitive erythroid cells express both Scl and Lyl1. Therefore, to determine whether Lyl1 can function in primitive erythropoiesis, we crossed conditional Scl knockout mice with mice expressing a Cre recombinase under the control of the Epo receptor, active in erythroid progenitors. Embryos with 20% expression of Scl from E9.5 survived to adulthood. However, mice with reduced expression of Scl and absence of Lyl1 (double knockout; DKO) died at E10.5 due to progressive loss of erythropoiesis. Gene expression profiling of DKO yolk sacs revealed loss of Gata1 and many of the known target genes of the SCL-GATA1 complex. ChIP-seq analyses showed that LYL1 exclusively bound a small subset of SCL targets including GATA1. Together, these data show for the first time that Lyl1 can maintain primitive erythropoiesis.
Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of Mental Health Screening on Promoting Immediate Online Help-Seeking: Randomized Trial Comparing Normative Versus Humor-Driven Feedback', JMIR Mental Health, vol. 5, no. 2, pp. e26-e26.
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Background
Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking.
Objective
The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking.
Methods
An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource.
Results
A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link across all meas...
Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of mental health screening on promoting immediate online help-seeking: Randomized trial comparing normative versus humor-driven feedback', Journal of Medical Internet Research, vol. 20, no. 4.
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Background: Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. Objective: The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. Methods: An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. Results: A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link across all measures. A larger proportion of participants from the Wellbeing measure (170/274, 62.0%) clicked on the links than the Resilience (47/179, 26.3%) or Symptoms (26/75, 34.7%) measures (? =60.35, P<.001). There were no significant demographic factors associated with help-seeking for the Resilience or Wellbeing measures. Participants with a previous episode of poor mental health were less likely...
Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Effect of chemical and physical factors on the crystallization of calcium sulfate in seawater reverse osmosis brine', Desalination, vol. 426, pp. 78-87.
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© 2017 Elsevier B.V. A major challenge of seawater reverse osmosis (SWRO) desalination process corresponds to the management of concentrated brine waste because discharging the brine back into the sea influences the marine ecosystem and incurs additional costs to plants. A membrane distillation crystallizer (MDC) can further produce clean water and simultaneously recover valuable resources from the concentrated brine; this is more environmentally and economically optimal. SWRO brine contains salts, which contribute to scaling development during the MDC operation. Hence, the main goals of this study was to observe the crystallization tendency of calcium sulfate (CaSO4) under high salinity and, to examine other inorganic and organic compounds and operational conditions that affect the CaSO4 crystallization. The crystallization tendency of CaSO4 in SWRO brine was examined with respect to different temperatures; changes in pH values; and in the presence of co-existing ions, chemical agents, and organic matters as well as physical factors. The results showed that the size and quantity of crystals formed increased at higher temperatures. Furthermore, an increase in the pH values increased the crystal size. At higher pH, the complexion of NaCl along with CaSO4 was created. Moreover, stirring enhanced CaSO4 crystal formation due to the kinetic mechanism.
Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Fractional-submerged membrane distillation crystallizer (F-SMDC) for treatment of high salinity solution', Desalination, vol. 440, pp. 59-67.
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© 2018 Elsevier B.V. Membrane distillation with crystallization (MDC) is an attractive process for high saline seawater reverse osmosis (SWRO) brine treatment. MDC produces additional fresh water while simultaneously recovering valuable resources. This study developed a novel approach of fractional-submerged MDC (F-SMDC) process, in which MD and crystallizer are integrated in a feed tank with a submerged membrane. F-SMDC principle is based on the presence of temperature/concentration gradient (TG/CG) in the feed reactor. The operational conditions at the top portion of the feed reactor (higher temperature and lower feed concentration) was well suited for MD operation, while the bottom portion of the reactor (lower temperature and higher concentration) was favourable for crystal growth. F-SMDC performance with direct contact MD to treat brine and produce sodium sulfate (Na2SO4) crystals using TG/CG showed positive results. The TG/CG approach in F-SMDC enabled to achieve higher water recovery for brine treatment with a volume concentration factor (VCF) of over 3.5 compared to VCF of 2.9 with a conventional S-MDC set-up. Further, the high feed concentration and low temperature at the reactor bottom in F-SMDC enabled the formation of Na2SO4crystals with narrow crystal size distribution.
Chotipant, S, Hussain, FK & Hussain, OK 2018, 'SERNOTATE: An automated approach for business service description annotation for efficient service retrieval and composition', Concurrency and Computation: Practice and Experience, vol. 30, no. 1, pp. e4189-e4189.
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Copyright © 2017 John Wiley & Sons, Ltd. Business service advertisements are today published online to convey essential information about services to customers. However, current Web search engines are unable to search and combine online service advertisements. Semantic service annotation is important for its ability to enable machines to understand the meaning of services and support in effective service retrieval and service composition. Existing research in the area of semantic service annotation has focused on the annotation of Web services in a semi-automated approach. It cannot be applied to business service information as it is not in the form of Web Services Description Language but in free text format. Moreover, semi-automated approaches are inappropriate for annotating a large amount of online service information which changes dynamically and they are therefore not suitable for the timely dissemination of service information to customers. To solve these issues, we propose SERNOTATE, which is an automated approach for business service description annotation for efficient service retrieval and composition. We propose new semantic-based linking approaches, namely, Extended Case-based Reasoning, vector-based, and classification-based, that automatically annotate business services to relevant service concepts. Each approach assists in the single-label and multi-label annotation of service terms to concept terms to provide a better representation of services. The experimental results test and validate the applicability of the proposed approaches to the automatic annotation of business service descriptions to service concepts on a real-world dataset.
Chou, K-P, Prasad, M, Wu, D, Sharma, N, Li, D-L, Lin, Y-F, Blumenstein, M, Lin, W-C & Lin, C-T 2018, 'Robust Feature-Based Automated Multi-View Human Action Recognition System', IEEE Access, vol. 6, pp. 15283-15296.
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Chu Van, T, Ristovski, Z, Surawski, N, Bodisco, TA, Rahman, SMA, Alroe, J, Miljevic, B, Hossain, FM, Suara, K, Rainey, T & Brown, RJ 2018, 'Effect of sulphur and vanadium spiked fuels on particle characteristics and engine performance of auxiliary diesel engines', Environmental Pollution, vol. 243, no. Pt B, pp. 1943-1951.
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Particle emission characteristics and engine performance were investigated from an auxiliary, heavy duty, six-cylinder, turbocharged and after-cooled diesel engine with a common rail injection system using spiked fuels with different combinations of sulphur (S) and vanadium (V) spiking. The effect of fuel S content on both particle number (PN) and mass (PM) was clearly observed in this study. Higher PN and PM were observed for fuels with higher S contents at all engine load conditions. This study also found a correlation between fuel S content and nucleation mode particle number concentration which have more harmful impact on human health than larger particles. The highest PN and PM were observed at partial load conditions. In addition, S in fuel resulted in higher viscosity of spiked fuels, which led to lower engine blow-by. Fuel V content was observed in this study, evidencing that it had no clear effect on engine performance and emissions. Increased engine load also resulted in higher engine blow-by. The lower peak of in-cylinder pressure observed at both pre-mixed and diffusion combustion phases with the spiked fuels may be associated with the lower energy content in the fuel blends compared to diesel fuel.
Chu, S, Gao, L, Xiao, M, Luo, Z & Li, H 2018, 'Stress-based multi-material topology optimization of compliant mechanisms', International Journal for Numerical Methods in Engineering, vol. 113, no. 7, pp. 1021-1044.
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In this paper, a level‐set‐based method is presented to deal with the multi‐material topology optimization of compliant mechanisms with stress constraints. A novel stress‐based multi‐material topology optimization model of compliant mechanisms is proposed. In this model, the multi‐material level set topology description model and the separable stress interpolation scheme are adopted. The weighted sum method is used to deal with the multi‐objective optimization of the output displacement and compliance of compliant mechanisms. The penalty of stresses is also considered in the objective function to control the local stress level in different materials. To solve the optimization problem, the parametric level set method is employed, and the sensitivity analysis is conducted. Application of the method is demonstrated by 2 numerical examples. Results show that the multi‐material structures without undesirable de facto hinges can be obtained. The output displacement and compliance of the compliant mechanisms are optimized, and stress constraints in different materials are simultaneously satisfied.
Chu, S, Gao, L, Xiao, M, Luo, Z, Li, H & Gui, X 2018, 'A new method based on adaptive volume constraint and stress penalty for stress-constrained topology optimization', Structural and Multidisciplinary Optimization, vol. 57, no. 3, pp. 1163-1185.
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© 2017 Springer-Verlag GmbH Germany This paper focuses on the stress-constrained topology optimization of minimizing the structural volume and compliance. A new method based on adaptive volume constraint and stress penalty is proposed. According to this method, the stress-constrained volume and compliance minimization topology optimization problem is transformed into two simple and related problems: a stress-penalty-based compliance minimization problem and a volume-decision problem. In the former problem, stress penalty is conducted and used to control the local stress level of the structure. To solve this problem, the parametric level set method with the compactly supported radial basis functions is adopted. Meanwhile, an adaptive adjusting scheme of the stress penalty factor is used to improve the control of the local stress level. To solve the volume-decision problem, a combination scheme of the interval search and local search is proposed. Numerical examples are used to test the proposed method. Results show the lightweight design, which meets the stress constraint and whose compliance is simultaneously optimized, can be obtained by the proposed method.
Chuah, C, Wang, J, Tavakoli, J & Tang, Y 2018, 'Novel Bacterial Cellulose-Poly (Acrylic Acid) Hybrid Hydrogels with Controllable Antimicrobial Ability as Dressings for Chronic Wounds', Polymers, vol. 10, no. 12, pp. 1323-1323.
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This investigation examines the combination of poly (acrylic acid) (PAA) and bacterial cellulose (BC) nanofibers to synthesize hydrogel hybrid composites used for wound dressing application. Amoxicillin (AM) was also grafted onto the composites for drug release. Fourier transform infrared analysis and scanning electron microscopy conducted revealed the structure and porosity of the composite being developed, as well as the successful fabrication of BC-PAA composites. The results of mechanical testing and hygroscopicity revealed that the composite shows higher stability than hydrogels which are currently used worldwide, albeit with a slight reduction in swelling capabilities. However, the composite was revealed to be responsive to a rise in pH values with an increase in composite swelling and drug release. These results together with their morphological characteristics suggest that BC-PAA hydrogel hybrid composite is a promising candidate for wound dressing application.
Chuah, S, Li, W, Chen, SJ, Sanjayan, JG & Duan, WH 2018, 'Investigation on dispersion of graphene oxide in cement composite using different surfactant treatments', Construction and Building Materials, vol. 161, pp. 519-527.
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© 2017 Elsevier Ltd Graphene oxide (GO) is a novel class of two-dimensional nanoscale sheet material due to its excellent dispersibility in water, high aspect ratio and good intrinsic strengths. In order to obtain a well-distributed GO-reinforced cement composites, the dispersion of GO in water, alkali and several ionic species are investigated with the aid of UV–vis spectroscopy. High alkalinity and calcium ions are key factors inducing the agglomeration of GO in cement system. Dispersion of GO in simulated pore solution is the culmination of the alkali and salt experiments. Agglomeration of GO occurred when GO contacted with the simulated pore solution, highlighting the necessity to protect GO against such aggressive media. The test on surfactant compatibility was then carried out to ensure GO was effectively dispersed in polycarboxylate, air-entrainment and Gum Arabic admixtures within the pore solution. Polycarboxylate-based superplasticisers gave the most promising results to disperse GO in cement alkaline environment. Flexural experiments was performed to highlight the importance of fabrication protocol on the mechanical properties of GO-cement composites. The result shows that the amount of 0.03% GO by weight of cement can increase the flexural strength of GO-cement composite up to 67%.
Chuang, C-H, Cao, Z, King, J-T, Wu, B-S, Wang, Y-K & Lin, C-T 2018, 'Brain Electrodynamic and Hemodynamic Signatures Against Fatigue During Driving', Frontiers in Neuroscience, vol. 12, pp. 1-12.
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Fatigue is likely to be gradually cumulated in a prolonged and attention-demanding task that may adversely affect task performance. To address the brain dynamics during a driving task, this study recruited 16 subjects to participate in an event-related lane-departure driving experiment. Each subject was instructed to maintain attention and task performance throughout an hour-long driving experiment. The subjects' brain electrodynamics and hemodynamics were simultaneously recorded via 32-channel electroencephalography (EEG) and 8-source/16-detector functional near-infrared spectroscopy (fNIRS). The behavior performance demonstrated that all subjects were able to promptly respond to lane-deviation events, even if the sign of fatigue arose in the brain, which suggests that the subjects were fighting fatigue during the driving experiment. The EEG event-related analysis showed strengthening alpha suppression in the occipital cortex, a common brain region of fatigue. Furthermore, we noted increasing oxygenated hemoglobin (HbO) of the brain to fight driving fatigue in the frontal cortex, primary motor cortex, parieto-occipital cortex and supplementary motor area. In conclusion, the increasing neural activity and cortical activations were aimed at maintaining driving performance when fatigue emerged. The electrodynamic and hemodynamic signatures of fatigue fighting contribute to our understanding of the brain dynamics of driving fatigue and address driving safety issues through the maintenance of attention and behavioral performance.
Chubb, CT, Tomamichel, M & Korzekwa, K 2018, 'Moderate deviation analysis of majorisation-based resource interconversion', Phys. Rev. A, vol. 99, no. 3, p. 032332.
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We consider the problem of interconverting a finite amount of resources
within all theories whose single-shot transformation rules are based on a
majorisation relation, e.g. the resource theories of entanglement and coherence
(for pure state transformations), as well as thermodynamics (for
energy-incoherent transformations). When only finite resources are available we
expect to see a non-trivial trade-off between the rate $r_n$ at which $n$
copies of a resource state $\rho$ can be transformed into $nr_n$ copies of
another resource state $\sigma$, and the error level $\varepsilon_n$ of the
interconversion process, as a function of $n$. In this work we derive the
optimal trade-off in the so-called moderate deviation regime, where the rate of
interconversion $r_n$ approaches its optimum in the asymptotic limit of
unbounded resources ($n\to\infty$), while the error $\epsilon_n$ vanishes in
the same limit. We find that the moderate deviation analysis exhibits a
resonance behaviour which implies that certain pairs of resource states can be
interconverted at the asymptotically optimal rate with negligible error, even
in the finite $n$ regime.
Chung, Y, Jin, W, Lee, B, Canning, J, Nakamura, K & Yuan, L 2018, 'Guest Editorial JLT Special Issue on OFS-25', Journal of Lightwave Technology, vol. 36, no. 4, pp. 841-843.
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Clarke, C, Liu, D, Wang, F, Liu, Y, Chen, C, Ton-That, C, Xu, X & Jin, D 2018, 'Large-scale dewetting assembly of gold nanoparticles for plasmonic enhanced upconversion nanoparticles', Nanoscale, vol. 10, no. 14, pp. 6270-6276.
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The integrated methods of core shell upconversion nanoparticle synthesis, thermal annealing and gold dewetting produce gold-decorated upconversion nanoparticles with enhanced emission.
Clement, S, Chen, W, Deng, W & Goldys, EM 2018, 'X-ray radiation-induced and targeted photodynamic therapy with folic acid-conjugated biodegradable nanoconstructs', International Journal of Nanomedicine, vol. Volume 13, pp. 3553-3570.
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Clemon, LM & Zohdi, TI 2018, 'On the tolerable limits of granulated recycled material additives to maintain structural integrity', Construction and Building Materials, vol. 167, pp. 846-852.
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© 2018 Elsevier Ltd Production and maker spaces are increasingly generating mixed plastic material waste of varying quality from 3-D printers. Industrial interest is growing in embedding granulated recycled particulate material additives into a virgin binding matrix. Examples include the introduction of granulated mixed recycled materials into 3-D printer material, concrete, and pavement. The stress load-sharing between the particulate additive and the binding matrix is an important factor in design and development of these composite materials. With mixed material additives, a designer is interested in the variation of such predicted load-sharing. However, experimental development is costly and time-consuming, thus analytical and semi-analytical estimates are desired for accelerated development. In this work, we expand on previous analytically correlated phase-averaged micro- and macrostructural loading to include variational effects present in mixed recycled material. In addition, model trade-offs are provided to aid designers in quickly selecting application specific mixtures. This framework identifies the stress contributions, and their variation, to reduce product development time and costs, which could greatly accelerate material recycling and reuse for improved infrastructure materials, low-cost 3-D printer filament, and reduced waste towards a more circular economy.
Cliff, O, Prokopenko, M & Fitch, R 2018, 'Minimising the Kullback–Leibler Divergence for Model Selection in Distributed Nonlinear Systems', Entropy, vol. 20, no. 2, pp. 51-51.
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The Kullback–Leibler (KL) divergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables; however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL divergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems.
Cliff, OM, Saunders, DL & Fitch, R 2018, 'Robotic ecology: Tracking small dynamic animals with an autonomous aerial vehicle', Science Robotics, vol. 3, no. 23.
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Estimation algorithms for wildlife tracking with an autonomous aerial robot are supported by field validation with wild swift parrots.
Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'Author Correction: The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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The original version of the published Article contained an error in the spelling of the third Author’s name. “John Halamaka” has been changed to “John Halamka”. This has been corrected in the HTML and PDF version of the Article.
Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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AbstractCurrent generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks.
Combes, J, Ferrie, C, Leifer, MS & Pusey, MF 2018, 'Why protective measurement does not establish the reality of the quantum state', Quantum Studies: Mathematics and Foundations, vol. 5, no. 2, pp. 189-211.
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Cong, C, Tao, J & Qiu, X 2018, 'A Multi-Tone Sound Absorber Based on an Array of Shunted Loudspeakers', Applied Sciences, vol. 8, no. 12, pp. 2484-2484.
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It has been demonstrated that a single shunted loudspeaker can be used as an effective low frequency sound absorber in a duct, but many shunted loudspeakers have to be used in practice for noise reduction or reverberation control in rooms, thus it is necessary to understand the performance of an array of shunted loudspeakers. In this paper, a model for the parallel shunted loudspeaker array for multi-tone sound absorption is proposed based on a modal solution, and then the acoustic properties of a shunted loudspeaker array under normal incidence are investigated using both the modal solution and the finite element method. It was found that each shunted loudspeaker can work almost independently where each unit resonates. Based on the interaction analysis, multi-tone absorbers in low frequency can be achieved by designing multiple shunted loudspeakers with different shunt circuits respectively. The simulation and experimental results show that the normal incidence sound absorption coefficient of the designed absorber has four absorption peaks with values of 0.42, 0.58, 0.80, and 0.84 around 100 Hz, 200 Hz, 300 Hz, and 400 Hz respectively.
Cong, C, Tao, J & Qiu, X 2018, 'Thin multi-tone sound absorbers based on analog circuit shunt loudspeakers', Noise Control Engineering Journal, vol. 66, no. 6, pp. 496-504.
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Cook, AJ, Ng, B, Gargiulo, GD, Hindmarsh, D, Pitney, M, Lehmann, T & Hamilton, TJ 2018, 'Instantaneous VO2 from a wearable device', Medical Engineering & Physics, vol. 52, pp. 41-48.
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© 2018 IPEM We present a method for calculating instantaneous oxygen uptake (VO2) through the use of a non-invasive and non-obtrusive (i.e. without a face mask) wearable device, together with its clinical evaluation against a standard technique based upon expired gas calorimetry. This method can be integrated with existing wearable devices, we implemented it in the “Device for Reliable Energy Expenditure Monitoring” (DREEM). The DREEM comprises a single lead electrocardiogram (ECG) device combined with a tri-axial accelerometer and is worn around the waist. Our clinical evaluation tests the developed method against a gold standard for VO2, expired gas calorimetry, using an ethically approved protocol comprising active exercise and sedentary periods. The study was performed on 42 participants from a wide sample population including healthy people, athletes and an at-risk health group including persons affected by obesity. We developed an algorithm combining heart rate (HR) and the integral of absolute acceleration (IAA), with results showing a correlation of r = 0.93 for instantaneous VO2, and r = 0.97 for 3 min mean VO2, this is a considerably improved estimation of VO2 in comparison to methods utilising HR and IAA independently.
Corsetti, S, Rabl, T, McGloin, D & Nabi, G 2018, 'Raman spectroscopy for accurately characterizing biomolecular changes in androgen-independent prostate cancer cells', Journal of Biophotonics, vol. 11, no. 3, pp. e201700166-e201700166.
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© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer-related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone-resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid-specific signals were identified, especially loss of arginine band. Androgen-resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L-arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).
Cu Thi, P, Ball, J & Dao, N 2018, 'Uncertainty Estimation Using the Glue and Bayesian Approaches in Flood Estimation: A case Study—Ba River, Vietnam', Water, vol. 10, no. 11, pp. 1641-1641.
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In the last few decades tremendous progress has been made in the use of catchment models for the analysis and understanding of hydrologic systems. A common application involves the use of these models to predict flows at catchment outputs. However, the outputs predicted by these models are often deterministic because they focused only on the most probable forecast without an explicit estimate of the associated uncertainty. This paper uses Bayesian and Generalized Likelihood Uncertainty Estimation (GLUE) approaches to estimate uncertainty in catchment modelling parameter values and uncertainty in design flow estimates. Testing of join probability of both these estimates has been conducted for a monsoon catchment in Vietnam. The paper focuses on computational efficiency and the differences in results, regardless of the philosophies and mathematical rigor of both methods. It was found that the application of GLUE and Bayesian techniques resulted in parameter values that were statistically different. The design flood quantiles estimated by the GLUE method were less scattered than those resulting from the Bayesian approach when using a closer threshold value (1 standard deviation departed from the mean). More studies are required to evaluate the impact of threshold in GLUE on design flood estimation.
Cui, H, Wang, X, Zhou, J, Gong, G, Eberl, S, Yin, Y, Wang, L, Feng, D & Fulham, M 2018, 'A topo-graph model for indistinct target boundary definition from anatomical images', Computer Methods and Programs in Biomedicine, vol. 159, pp. 211-222.
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BACKGROUND AND OBJECTIVE:It can be challenging to delineate the target object in anatomical imaging when the object boundaries are difficult to discern due to the low contrast or overlapping intensity distributions from adjacent tissues. METHODS:We propose a topo-graph model to address this issue. The first step is to extract a topographic representation that reflects multiple levels of topographic information in an input image. We then define two types of node connections - nesting branches (NBs) and geodesic edges (GEs). NBs connect nodes corresponding to initial topographic regions and GEs link the nodes at a detailed level. The weights for NBs are defined to measure the similarity of regional appearance, and weights for GEs are defined with geodesic and local constraints. NBs contribute to the separation of topographic regions and the GEs assist the delineation of uncertain boundaries. Final segmentation is achieved by calculating the relevance of the unlabeled nodes to the labels by the optimization of a graph-based energy function. We test our model on 47 low contrast CT studies of patients with non-small cell lung cancer (NSCLC), 10 contrast-enhanced CT liver cases and 50 breast and abdominal ultrasound images. The validation criteria are the Dice's similarity coefficient and the Hausdorff distance. RESULTS:Student's t-test show that our model outperformed the graph models with pixel-only, pixel and regional, neighboring and radial connections (p-values <0.05). CONCLUSIONS:Our findings show that the topographic representation and topo-graph model provides improved delineation and separation of objects from adjacent tissues compared to the tested models.
Cui, L, Hu, H, Yu, S, Yan, Q, Ming, Z, Wen, Z & Lu, N 2018, 'DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks', Journal of Network and Computer Applications, vol. 103, pp. 119-130.
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Cui, L, Yue, L, Wen, D & Qin, L 2018, 'K-Connected Cores Computation in Large Dual Networks.', Data Sci. Eng., vol. 3, no. 4, pp. 293-306.
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© 2018, The Author(s). Computing k- cores is a fundamental and important graph problem, which can be applied in many areas, such as community detection, network visualization, and network topology analysis. Due to the complex relationship between different entities, dual graph widely exists in the applications. A dual graph contains a physical graph and a conceptual graph, both of which have the same vertex set. Given that there exist no previous studies on the k- core in dual graphs, we formulate a k-connected core (k- CCO) model in dual graphs. A k- CCO is a k- core in the conceptual graph, and also connected in the physical graph. Given a dual graph and an integer k, we propose a polynomial time algorithm for computing all k- CCOs. We also propose three algorithms for computing all maximum-connected cores (MCCO), which are the existing k- CCOs such that a (k+ 1) -CCO does not exist. We further study a subgraph search problem, which is computing a k- CCO that contains a set of query vertices. We propose an index-based approach to efficiently answer the query for any given parameter k. We conduct extensive experiments on six real-world datasets and four synthetic datasets. The experimental results demonstrate the effectiveness and efficiency of our proposed algorithms.
Cui, Q, Gu, Y, Ni, W, Zhang, X, Tao, X, Zhang, P & Liu, RP 2018, 'Preserving Reliability of Heterogeneous Ultra-Dense Distributed Networks in Unlicensed Spectrum', IEEE Communications Magazine, vol. 56, no. 6, pp. 72-78.
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© 1979-2012 IEEE. This article investigates the prominent dilemma between capacity and reliability in heterogeneous ultra-dense distributed networks, and advocates a new measure of effective capacity to quantify the maximum sustainable data rate of a link while preserving the quality of service of the link in such networks. Recent breakthroughs are brought forth in developing the theory of the effective capacity in heterogeneous ultra-dense distributed networks. Potential applications of the effective capacity are demonstrated on the admission control, power control, and resource allocation of such networks, with substantial gains revealed over existing technologies. This new measure is of particular interest to ultra-dense deployment of the emerging 5G wireless networks in the unlicensed spectrum, leveraging the capacity gain brought by the use of the unlicensed band and the stringent reliability sustained by 5G in future heterogeneous network environments.
Cui, Z, Wang, J, Zhang, H, Ngo, HH, Jia, H, Guo, W, Gao, F, Yang, G & Kang, D 2018, 'Investigation of backwashing effectiveness in membrane bioreactor (MBR) based on different membrane fouling stages', Bioresource Technology, vol. 269, pp. 355-362.
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In this study the effect of different fouling stages of hollow fiber membranes on effective backwashing length in MBR has been investigated. Computational fluid dynamics (CFD) is imported to simulate backwashing process. A multi-physics coupling model for free porous media flow, convective mass transfer and diluted species transport was established. The laser bijection sensors (LBS) were imported to monitor the backwashing solution position inside fiber lumen. Simulation results indicated that membrane fouling degree could change the velocity of backwash solution inside fiber lumen and make a further effect on effective backwash length. The signal variations of LBS are in accordance with the simulation results. The backwashing process can only play an active role when the filtration pressure is below the critical TMP. It can be concluded that backwash duration in industrial applications need to be set based on changes in TMP.
D’Urso, G, Smith, SL, Mettu, R, Oksanen, T & Fitch, R 2018, 'Multi-vehicle refill scheduling with queueing', Computers and Electronics in Agriculture, vol. 144, pp. 44-57.
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We consider the problem of refill scheduling for a team of vehicles or robots that must contend for access to a single physical location for refilling. The objective is to minimise time spent in travelling to/from the refill station, and also time lost to queuing (waiting for access). In this paper, we present principled results for this problem in the context of agricultural operations. We first establish that the problem is NP-hard and prove that the maximum number of vehicles that can usefully work together is bounded. We then focus on the design of practical algorithms and present two solutions. The first is an exact algorithm based on dynamic programming that is suitable for small problem instances. The second is an approximate anytime algorithm based on the branch and bound approach that is suitable for large problem instances with many robots. We present simulated results of our algorithms for three classes of agricultural work that cover a range of operations: spot spraying, broadcast spraying and slurry application. We show that the algorithm is reasonably robust to inaccurate prediction of resource utilisation rate, which is difficult to estimate in cases such as spot application of herbicide for weed control, and validate its performance in simulation using realistic scenarios with up to 30 robots.
da Rocha, CG & Kemmer, S 2018, 'Integrating product and process design in construction', Construction Management and Economics, vol. 36, no. 9, pp. 535-543.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Product modularity namely the notion that products can be decomposed into parts (or modules) has been widely applied in manufacturing but not in construction, precluding this industry to also benefit from it. The narrow definition of a module, which is often simplistically equated to a sub-assembly produced off-site, and the lack of integration between product and process design, which is typical in construction, are argued to be two root causes of such problem. This paper starts by discussing the operational implications of misaligned decisions in these two domains in an empirical study addressing a high-rise apartments building project. Seven guidelines are then devised using a Design Science Research (DSR) approach for integrating product (product modularity and modules) and process (work structure and work packages) design. The results indicate that product modularity can be applied for improving operations regardless of the construction method(s) used. Yet, a revised understanding of modules (as a material, a component, a non-volumetric or a volumetric sub-assembly) is needed in addition to a coordinated product and process design, particularly for traditional construction.
da Rocha, CG & Miron, LIG 2018, 'The House Factory: A Simulation Game for Understanding Mass Customization in House Building', Journal of Professional Issues in Engineering Education and Practice, vol. 144, no. 1, pp. 05017007-05017007.
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Dadzie, J, Runeson, G & Ding, G 2018, 'Determinants of sustainable upgrade for energy efficiency – the case of existing buildings in Australia', Energy Procedia, vol. 153, pp. 284-289.
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© 2018 The Authors. Published by Elsevier Ltd. The impact of existing buildings on the environment is on the rise; thus to achieve environmental sustainability requires sustainable upgrade (SU) of existing built facilities. Over the years, SU has focused on technologies with little attention given to the nature and conditions of existing buildings. The purpose of this paper is to identify existing building characteristics that impact SU. A detailed literature review on the nature and characteristics of existing buildings, as well as energy and environmental performance was undertaken. A survey questionnaire with all the determinants of existing buildings was administered to sustainability and construction professionals in Australia. The results show that size of building, age of building, U-value of wall, U-value of ceiling, area of external wall, thickness of insulation materials, occupancy, size of window opening, life span of sustainable technologies, and the type of building impact sustainable upgrade of existing buildings for energy efficiency.
Dadzie, J, Runeson, G, Ding, G & Bondinuba, F 2018, 'Barriers to Adoption of Sustainable Technologies for Energy-Efficient Building Upgrade—Semi-Structured Interviews', Buildings, vol. 8, no. 4, pp. 57-57.
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© 2018 by the authors. Globally, only 2% of existing building stock is built yearly; the remaining 98% already exist. Energy consumption and indoor thermal comfort of the existing building stock are not encouraging. This is due to many challenges associated with existing buildings; the challenges range from cracks, leakages, poor insulation, heat losses and high rate of unsustainable technologies. This paper investigates possible barriers facing the adoption and application of sustainable technologies (STs) for sustainable or energy-efficient upgrade of existing buildings. New STs are manufactured on a regular basis to meet improved energy efficiency standards, yet there are minimal actions/attempts to adopt and apply improved technologies in existing buildings for energy efficiency. Indeed, there are limited studies focused on the use of qualitative approaches to identify barriers to adoption and use of STs. Thus, a semi-structured interview approach was adopted and applied using sustainability/energy efficiency professionals, building services engineers, project managers, architects, and facility managers in Australia. The results indicate that barriers to the adoption and application of sustainable technologies are perceived benefits in demolish-and-build, age of building, cost of STs, perceived poor payback time, unreliable energy-savings projections, existing design, hidden and overall cost of renovation, and cost of STs.
Dai, S, Tymchenko, M, Xu, Z-Q, Tran, TT, Yang, Y, Ma, Q, Watanabe, K, Taniguchi, T, Jarillo-Herrero, P, Aharonovich, I, Basov, DN, Tao, TH & Alù, A 2018, 'Internal Nanostructure Diagnosis with Hyperbolic Phonon Polaritons in Hexagonal Boron Nitride', Nano Letters, vol. 18, no. 8, pp. 5205-5210.
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Imaging materials and inner structures with resolution below the diffraction limit has become of fundamental importance in recent years for a wide variety of applications. We report subdiffractive internal structure diagnosis of hexagonal boron nitride by exciting and imaging hyperbolic phonon polaritons. On the basis of their unique propagation properties, we are able to accurately locate defects in the crystal interior with nanometer resolution. The precise location, size, and geometry of the concealed defects are reconstructed by analyzing the polariton wavelength, reflection coefficient, and their dispersion. We have also studied the evolution of polariton reflection, transmission, and scattering as a function of defect size and photon frequency. The nondestructive high-precision polaritonic structure diagnosis technique introduced here can be also applied to other hyperbolic or waveguide systems and may be deployed in the next-generation biomedical imaging, sensing, and fine structure analysis.
Damanik, N, Ong, HC, Tong, CW, Mahlia, TMI & Silitonga, AS 2018, 'A review on the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends', Environmental Science and Pollution Research, vol. 25, no. 16, pp. 15307-15325.
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Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.
Das, A, Suwanwiwat, H, Ferrer, MA, Pal, U & Blumenstein, M 2018, 'Thai Automatic signature verification System Employing Textural Features', IET Biometrics, vol. 7, no. 6, pp. 615-627.
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© The Institution of Engineering and Technology 2018. This study focuses on a comprehensive study of Automatic Signature Verification (ASV) for off-line Thai signatures; an investigation was carried out to characterise the challenges in Thai ASV and to baseline the performance of Thai ASV employing baseline features, being Local Binary Pattern, Local Directional Pattern, Local Binary and Directional Patterns combined (LBDP), and the baseline shape/feature-based hidden Markov model. As there was no publicly available Thai signature database found in the literature, the authors have developed and proposed a database considering real-world signatures from Thailand. The authors have also identified their latent challenges and characterised Thai signature-based ASV. The database consists of 5,400 signatures from 100 signers. Thai signatures could be bi-script in nature, considering the fact that a single signature can contain only Thai or Roman characters or contain both Roman and Thai, which poses an interesting challenge for script-independent SV. Therefore, along with the baseline experiments, the investigation on the influence and nature of bi-script ASV was also conducted. From the equal error rates and Bhattacharyya distance, the score achieved in the experiments indicate that the Thai SV scenario is a script-independent problem. The open research area on this subject of research has also been addressed.
De Medeiros, JF, Da Rocha, CG & Ribeiro, JLD 2018, 'Design for sustainable behavior (DfSB): Analysis of existing frameworks of behavior change strategies, experts' assessment and proposal for a decision support diagram', Journal of Cleaner Production, vol. 188, pp. 402-415.
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Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary Effectiveness of a Smartphone App to Reduce Depressive Symptoms in the Workplace: Feasibility and Acceptability Study', JMIR mHealth and uHealth, vol. 6, no. 12, pp. e11661-e11661.
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BACKGROUND:The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app-based intervention designed to reduce depressive symptoms and increase well-being in these populations. OBJECTIVE:This paper presents the development and pilot testing of the app's usability, acceptability, feasibility, and preliminary effectiveness. METHODS:The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. RESULTS:The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=-2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. CONCLUSIONS:Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted with caution. The next stage of evaluation will be a randomized controlled trial. If found to be efficacious, the a...
Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary effectiveness of a smartphone app to reduce depressive symptoms in the workplace: Feasibility and acceptability study', Journal of Medical Internet Research, vol. 20, no. 12.
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© Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, Samuel Harvey. Background: The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app–based intervention designed to reduce depressive symptoms and increase well-being in these populations. Objective: This paper presents the development and pilot testing of the app’s usability, acceptability, feasibility, and preliminary effectiveness. Methods: The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. Results: The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=−2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. Conclusions: Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted with caut...
Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'A smartphone application for treating depressive symptoms: study protocol for a randomised controlled trial', BMC Psychiatry, vol. 18, no. 1, pp. 1-9.
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Depression is a commonly occurring disorder linked to diminished role functioning and quality of life. The development of treatments that overcome barriers to accessing treatment remains an important area of clinical research as most people delay or do not receive treatment at an appropriate time. The workplace is an ideal setting to roll-out an intervention, particularly given the substantial psychological benefits associated with remaining in the workforce. Mobile health (mhealth) interventions utilising smartphone applications (apps) offer novel solutions to disseminating evidence based programs, however few apps have undergone rigorous testing. The present study aims to evaluate the effectiveness of a smartphone app designed to treat depressive symptoms in workers.
Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'Smartphone application for preventing depression: study protocol for a workplace randomised controlled trial', BMJ Open, vol. 8, no. 7, pp. e020510-e020510.
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IntroductionDepression is the leading cause of life years lost due to disability. Appropriate prevention has the potential to reduce the incidence of new cases of depression, however, traditional prevention approaches face significant scalability issues. Prevention programmes delivered by via smartphone applications provide a potential solution. The workplace is an ideal setting to roll out this form of intervention, particularly among industries that are unlikely to access traditional health initiatives and whose workplace characteristics create accessibility and portability issues. The study aims to evaluate the effectiveness of a smartphone application designed to prevent depression and improve well-being. The effectiveness of the app as a universal, selective and indicated prevention tool will also be evaluated.Methods and analysisA multicentre randomised controlled trial, to determine the effectiveness of the intervention compared with an active mood monitoring control in reducing depressive symptoms (primary outcome) and the prevalence of depression at 3 months, with secondary outcomes assessing well-being and work performance. Employees from a range of industries will be invited to participate. Participants with likely current depression at baseline will be excluded. Following baseline assessment, participants, blinded to their allocation, will be randomised to receive one of two versions of the application: headgear (a 30-day mental health intervention) or a control application (mood monitoring for 30 days). Both versions of the app contain a risk calculator to provide a measure of future risk. Analyses will be conducted within an intention-to-treat framework using mixed modelling, with additional analyses conducted to compare the moderating effect of baseline risk level and depression symptom severity on the intervention’s effectiveness.
Deng, L, Ngo, H-H, Guo, W, Wang, J & Zhang, H 2018, 'Evaluation of a new sponge addition-microbial fuel cell system for removing nutrient from low C/N ratio wastewater', Chemical Engineering Journal, vol. 338, pp. 166-175.
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© 2018 This study developed a new microbial fuel cell (MFC) system (Sponge-MFC), which consisted of a cathodic chamber with an added sponge and two anodic chambers, for low carbon/nitrogen (C/N) wastewater treatment. When operating in the closed-circuit state, the Sponge-MFC(C) demonstrated its superior electrochemical performance compared to the closed-circuit MFC. This superiority took the form of higher coulombic efficiencies, voltage outputs, current densities and power densities. Adding a sponge could reduce the cathode's charge transfer resistance and solution resistance, and improve its capacitance, thus increasing cathodic reaction rate and power outputs. Simultaneous nitrification denitrification (SND) and bioelectrochemical denitrification processes on the cathode coupled with the sponge's SND process were responsible for efficient removal of nitrogen from the Sponge-MFC(C). Fluorescent in situ hybridization (FISH) analysis revealed that nitrifying bacteria and highly diversified denitrifying bacteria were distributed at the cathode's outer layer and inner layer, respectively. Higher phosphorus removal efficiencies (82.06 ± 1.21%) in the Sponge-MFC(C) than that in the MFC(C) (53.97 ± 2.32%) could be ascribed to biological phosphorus removal and precipitation of phosphate salts on the cathode. These results suggested the Sponge-MFC(C) could accomplish better electrochemical behaviors and nutrient removal due to sponge addition when treating wastewater with low C/N ratio.
Deng, W, Chen, W, Clement, S, Guller, A, Zhao, Z, Engel, A & Goldys, EM 2018, 'Controlled gene and drug release from a liposomal delivery platform triggered by X-ray radiation', Nature Communications, vol. 9, no. 1.
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AbstractLiposomes have been well established as an effective drug delivery system, due to simplicity of their preparation and unique characteristics. However conventional liposomes are unsuitable for the on-demand content release, which limits their therapeutic utility. Here we report X-ray-triggerable liposomes incorporating gold nanoparticles and photosensitizer verteporfin. The 6 MeV X-ray radiation induces verteporfin to produce singlet oxygen, which destabilises the liposomal membrane and causes the release of cargos from the liposomal cavity. This triggering strategy is demonstrated by the efficiency of gene silencing in vitro and increased effectiveness of chemotherapy in vivo. Our work indicates the feasibility of a combinatorial treatment and possible synergistic effects in the course of standard radiotherapy combined with chemotherapy delivered via X-ray-triggered liposomes. Importantly, our X-ray-mediated liposome release strategy offers prospects for deep tissue photodynamic therapy, by removing its depth limitation.
Deng, Z, Chen, J, Zhang, T, Cao, L & Wang, S 2018, 'Generalized Hidden-Mapping Minimax Probability Machine for the training and reliability learning of several classical intelligent models', Information Sciences, vol. 436-437, pp. 302-319.
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© 2018 Elsevier Inc. Minimax Probability Machine (MPM) is a binary classifier that optimizes the upper bound of the misclassification probability. This upper bound of the misclassification probability can be used as an explicit indicator to characterize the reliability of the classification model and thus makes the classification model more transparent. However, the existing related work is constrained to linear models or the corresponding nonlinear models by applying the kernel trick. To relax such constraints, we propose the Generalized Hidden-Mapping Minimax Probability Machine (GHM-MPM). GHM-MPM is a generalized MPM. It is capable of training many classical intelligent models, such as feedforward neural networks, fuzzy logic systems, and linear and kernelized linear models for classification tasks, and realizing the reliability learning of these models simultaneously. Since the GHM-MPM, similarly to the classical MPM, was originally developed only for binary classification, it is further extended to multi-class classification by using the obtained reliability indices of the binary classifiers of two arbitrary classes. The experimental results show that GHM-MPM makes the trained models more transparent and reliable than those trained by classical methods.
Deng, Z, He, T, Ding, W & Cao, Z 2018, 'A Multimodel Fusion Engine for Filtering Webpages', IEEE Access, vol. 6, pp. 66062-66071.
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OAPA Fusing multiple existing models for filtering webpages can mitigate the shortcomings of individual filtering models. To provide an engine for such fusion, we propose a multimodel fusion engine for filtering webpages (MMFEFWP) for the extraction of target webpages. This engine can handle large datasets of webpages crawled from websites and supports five individual filtering models and the fusion of any two of them. There are two possible fusion methods: one is to simultaneously satisfy the conditions of both individual models, and the other is to satisfy the conditions of one of the two individual models. We present the functions, architecture, and software design of the proposed engine. We use recall ratio (RR) and precision ratio (PR) as the evaluation indices of the filtering models and propose rules describing how PR and RR change when individual models are fused. We use 200,000 webpages collected by crawling the popular online shopping website "www.jd.com" as the experimental dataset to verify these rules. The experimental results show that two-model fusion can improve either PR or RR. Thus, the proposed engine has good practical value for engineering applications.
Deveci, Ö & Shannon, AG 2018, 'The quaternion-Pell sequence', Communications in Algebra, vol. 46, no. 12, pp. 5403-5409.
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© 2018, © 2018 Taylor & Francis. In this paper, we define the quaternion-Pell sequence and derive the generating matrix of the sequence. Then we produce the semigroups using the multiplicative orders of the generating matrix of the quaternion-Pell sequence when read modulo α. We also study the quaternion-Pell sequence modulo α and then we give the relationship among the periods of the quaternion-Pell sequence modulo α and the orders of the semigroups obtained. In addition, we extend the quaternion-Pell sequence to groups. Finally, we obtain the periods of the quaternion-Pell sequences in dihedral groups D 2m as applications of the results obtained.
Dian, R, Xu, W, Zhu, J, Hu, D & Liu, Y 2018, 'An Improved Speed Sensorless Control Strategy for Linear Induction Machines Based on Extended State Observer for Linear Metro Drives', IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp. 9198-9210.
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© 2018 IEEE. This paper proposes an improved systematic approach for sensorless speed estimation and controller design of a linear induction machine (LIM) for linear metro drives. A novel speed estimation method based on the extended state observer is developed to improve the dynamic speed estimation response. In contrast to the conventional proportional-integral speed adaptive mechanism based only on the LIM electromagnetic model, this new speed estimation method incorporates both the electromagnetic and mechanical models such that it can estimate the LIM speed and load resistance at the same time. A new speed controller incorporating the disturbance observer based control algorithm is developed to strengthen the speed tracking ability and suppress the disturbance of load variation. Having fewer parameters, it brings great convenience to the drive system parameter setting and tuning. The performance of the proposed method is numerically simulated and experimentally verified.
Dickson-Deane, C, Bradshaw, AC & Asino, TI 2018, 'Recognizing the Inseparability of Culture, Learning, and Technology', TechTrends, vol. 62, no. 4, pp. 310-311.
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Dietrich, A, Bürk, M, Steiger, ES, Antoniuk, L, Tran, TT, Nguyen, M, Aharonovich, I, Jelezko, F & Kubanek, A 2018, 'Observation of Fourier transform limited lines in hexagonal boron nitride', Physical Review B, vol. 98, no. 8.
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© 2018 American Physical Society. Single defect centers in layered hexagonal boron nitride are promising candidates as single-photon sources for quantum optics and nanophotonics applications. However, spectral instability hinders many applications. Here, we perform resonant excitation measurements and observe Fourier transform limited linewidths down to ≈50 MHz. We investigated the optical properties of more than 600 single-photon emitters (SPEs) in hBN. The SPEs exhibit narrow zero-phonon lines distributed over a spectral range from 580 to 800 nm and with dipolelike emission with a high polarization contrast. Finally, the emitters withstand transfer to a foreign photonic platform, namely, a silver mirror, which makes them compatible with photonic devices such as optical resonators and paves the way to quantum photonics applications.
Ding, C, Sun, H-H, Ziolkowski, RW & Jay Guo, Y 2018, 'A Dual Layered Loop Array Antenna for Base Stations With Enhanced Cross-Polarization Discrimination', IEEE Transactions on Antennas and Propagation, vol. 66, no. 12, pp. 6975-6985.
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Ding, KC, Xiaoyu, Y, Xin, R & Qi, K 2018, 'Design analysis of high-rise buildings in the view of wind environment——A case study of four seasons green block in Hangzhou Qianjiang new city', Xi'an Jianzhu Keji Daxue Xuebao/Journal of Xi'an University of Architecture & Technology, vol. 50, no. 6, pp. 884-900.
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Due to the trend of high-rise and densification of urban buildings, high-rise buildings have a significant impact on the wind environment in their plots, and further affect the comfort of outdoor pedestrians to improve the wind environment around high-rise buildings, which is an urgent problem to be solved. First of all, in this paper, six high-rise buildings in Qianjiang New Town, Hangzhou City, were measured and the location of the building group towards the outdoor wind environment was selected and the points were determined. Then, by constantly changing the orientation of the building blocks, eight typical layouts were obtained. Finally, the CFD fluid dynamics simulation software phoenics was used to analyze the distribution of the wind speed ratio at the height (1.5 m). It is found that the change of the building orientation can achieve the optimization of the surrounding wind environment of the high-rise buildings. This paper, by exploring the relationship between wind environment and building orientation, provides a reference for the design of high-rise building groups in the region.
Ding, W, Lin, C-T & Prasad, M 2018, 'Hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection and its application in neonatal cerebral cortex MRI', Expert Systems with Applications, vol. 101, pp. 243-257.
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© 2018 Elsevier Ltd A wide variety of feature selection methods have been developed as promising solutions to find the classification pattern inside increasing applications. But the exploring efficient, flexible and robust feature selection method to handle the rising big data is still an exciting challenge. This paper presents a novel hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection algorithm (CTFGES). It aims to select out the high-quality feature subsets, which can enrich the research of feature selection and classification in the heterogeneous big data. Firstly, we construct a flexible hierarchical co-evolutionary clustering tree model to speed up the process of feature selection, which can effectively extract the features from the parent and children branches of four-layer co-evolutionary clustering tree. Secondly, we design a mixed co-evolutionary game equilibrium scheme with adaptive dynamics to guide parent and children branch subtrees to approach the optimal equilibrium regions, and enable their feature sets to converge stably to the Nash equilibrium. So both noisy heterogeneous features and non-identified redundant ones can be further eliminated. Finally, the extensive experiments on various big datasets are conducted to demonstrate the more excellent performance of CTFGES, in terms of accuracy, efficiency and robustness, compared with the representative feature selection algorithms. In addition, the proposed CTFGES algorithm has been successfully applied into the feature segmentation of large-scale neonatal cerebral cortex MRI with varying noise ratios and intensity non-uniformity levels. The results indicate that it can be adaptive to derive from the cortical folding surfaces and achieves the satisfying consistency with medical experts, which will be potential significance for successfully assessing the impact of aberrant brain growth on the neurodevelopment of neonatal cerebrum.
Ding, W, Lin, C-T, Chen, S, Zhang, X & Hu, B 2018, 'Multiagent-consensus-MapReduce-based attribute reduction using co-evolutionary quantum PSO for big data applications', Neurocomputing, vol. 272, pp. 136-153.
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© 2017 Elsevier B.V. The attribute reduction for big data applications has become an urgent challenge in pattern recognition, machine learning and data mining. In this paper, we introduce the multi-agent consensus MapReduce optimization model and co-evolutionary quantum PSO with self-adaptive memeplexes for designing the attribute reduction method, and propose a multiagent-consensus-MapReduce-based attribute reduction algorithm (MCMAR). Firstly, the co-evolutionary quantum PSO with self-adaptive memeplexes is designed for grouping particles into different memeplexes, which aims to explore the search space and locate the global best region during the attribute reduction of big datasets. Secondly, the four layers neighborhood radius framework with compensatory scheme is constructed to partition big attribute sets by exploiting the interdependency among multiple-relevant-attribute sets. Thirdly, a novel multi-agent consensus MapReduce optimization model is adopted to perform the multiple-relevance-attribute reduction, in which five kinds of agents are used to conduct the ensemble co-evolutionary optimization. So the uniform reduction framework of different agents' co-evolutionary game under the bounded rationality is further refined. Fourthly, the approximation MapReduce parallelism mechanism is permitted to formalize to the multi-agent co-evolutionary consensus structure, interaction and adaptation, which enhances different agents to share their solutions. Finally, extensive experimental studies substantiate the effectiveness and accuracy of MCMAR on some well-known benchmark datasets. Moreover, successful applications in big medical datasets are expected to dramatically scaling up MCMAR for complex infant brain MRI in terms of efficiency and feasibility.
Ding, W, Lin, C-T, Prasad, M, Cao, Z & Wang, J 2018, 'A Layered-Coevolution-Based Attribute-Boosted Reduction Using Adaptive Quantum-Behavior PSO and Its Consistent Segmentation for Neonates Brain Tissue', IEEE Transactions on Fuzzy Systems, vol. 26, no. 3, pp. 1177-1191.
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IEEE The main challenge of attribute reduction in large data applications is to develop a new algorithm to deal with large, noisy, and uncertain large data linking multiple relevant data sources, structured or unstructured. This paper proposes a new and efficient layered-coevolution-based attribute-boosted reduction algorithm (LCQ-ABR*) using adaptive quantum behavior particle swarm optimization (PSO). First, the quantum rotation angle of an evolutionary particle is updated by a dynamic change of self-adapting step size. Second, a self-adaptive partitioning strategy is employed to group particles into different memeplexes, and the quantum-behavior mechanism with the particles & #x0027; states depicted by the wave function cooperates to achieve superior performance in their respective memeplexes. Third, a new layered co-evolutionary model with multi-agent interaction is constructed to decompose a complex attribute set, and it can self-adapt the attribute sizes among different layers and produce the reasonable decompositions by exploiting any interdependency among multiple relevant attribute subsets. Fourth, the decomposed attribute subsets are evolved to compute the positive region and discernibility matrix by using their best quantum particles, and the global optimal reduction set is induced successfully. Finally, extensive comparative experiments are provided to illustrate that LCQ-ABR* has better feasibility and effectiveness of attribute reduction on large-scale and uncertain dataset problems with complex noise, compared with representative algorithms. Moreover, LCQ-ABR* can be successfully applied in the consistent segmentation for neonatal brain 3D-MRI, and the consistent segmentation results further demonstrate its stronger applicability.
Ding, Z, Dong, Y, Kou, G, Palomares, I & Yu, S 2018, 'Consensus formation in opinion dynamics with online and offline interactions at complex networks', International Journal of Modern Physics C, vol. 29, no. 07, pp. 1850046-1850046.
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Nowadays, with the development of information communication technology and Internet, more and more people receive information and exchange their opinions with others via online environments (e.g. Twitter, Facebook, Weibo, and WeChat). According to eMarketer Report [Worldwide Internet and Mobile Users: eMarketer’s Updated Estimates and Forecast for 2015–2020 (eMarketer Report). Published October 11, 2016, https://www.emarketer.com/Report/Worldwide-Internet-Mobile-Users-eMarketers-Updated-Estimates-Forecast-20152020/2001897 ).], by the end of 2016, more than 3.2 billion individuals worldwide will use the Internet regularly, accounting for nearly 45% of the world population. By contrast, the other half of the global population still obtain information and regularly exchange their opinions in a more traditional way (e.g. face to face). Generally, the speed at which information spreads and opinions are exchanged and updated in an online environment is much faster than in an offline environment. This paper focuses on jointly investigating the challenge of consensus formation in opinion dynamics with online and offline interactions. Without loss of generality, we assume the speed at which information spreads and opinions are exchanged and updated in an online environment is [Formula: see text] times as fast as in an offline environment. We demonstrate that the update speed ratio in mixed online and offline environments (i.e. [Formula: see text]) strongly impacts the consensus formation at complex networks: a large update speed ratio of online and offline environments (i.e. [Formula: see text]) makes it difficult for all agents to reach consensus in opinion dynamics. Furthermore, these effects are often further intensified as the number of online participating agents increases.
Do, MH, Ngo, HH, Guo, WS, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Ni, BJ 2018, 'Challenges in the application of microbial fuel cells to wastewater treatment and energy production: A mini review', Science of The Total Environment, vol. 639, pp. 910-920.
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Wastewater is now considered to be a vital reusable source of water reuse and saving energy. However, current wastewater has multiple limitations such as high energy costs, large quantities of residuals being generated and lacking in potential resources. Recently, great attention has been paid to microbial fuel cells (MFCs) due to their mild operating conditions where a variety of biodegradable substrates can serve as fuel. MFCs can be used in wastewater treatment facilities to break down organic matter, and they have also been analysed for application as a biosensor such as a sensor for biological oxygen which demands monitoring. MFCs represent an innovation technology solution that is simple and rapid. Despite the advantages of this technology, there are still practical barriers to consider including low electricity production, current instability, high internal resistance and costly materials used. Thus, many problems must be overcome and doing this requires a more detailed analysis of energy production, consumption, and application. Currently, real-world applications of MFCs are limited due to their low power density level of only several thousand mW/m2. Efforts are being made to improve the performance and reduce the construction and operating costs of MFCs. This paper explores several aspects of MFCs such as anode, cathode and membrane, and in an effort to overcome the practical challenges of this system.
Dong, F, Lu, J, Zhang, G & Li, K 2018, 'Active Fuzzy Weighting Ensemble for Dealing with Concept Drift', International Journal of Computational Intelligence Systems, vol. 11, no. 1, pp. 438-438.
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© 2018, the Authors. The concept drift problem is a pervasive phenomenon in real-world data stream applications. It makes well-trained static learning models lose accuracy and become outdated as time goes by. The existence of different types of concept drift makes it more difficult for learning algorithms to track. This paper proposes a novel adaptive ensemble algorithm, the Active Fuzzy Weighting Ensemble, to handle data streams involving concept drift. During the processing of data instances in the data streams, our algorithm first identifies whether or not a drift occurs. Once a drift is confirmed, it uses data instances accumulated by the drift detection method to create a new base classifier. Then, it applies fuzzy instance weighting and a dynamic voting strategy to organize all the existing base classifiers to construct an ensemble learning model. Experimental evaluations on seven datasets show that our proposed algorithm can shorten the recovery time of accuracy drop when concept drift occurs, adapt to different types of concept drift, and obtain better performance with less computation costs than the other adaptive ensembles.
Dong, F, Zhang, G, Lu, J & Li, K 2018, 'Fuzzy competence model drift detection for data-driven decision support systems', Knowledge-Based Systems, vol. 143, pp. 284-294.
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© 2017 Elsevier B.V. This paper focuses on concept drift in business intelligence and data-driven decision support systems (DSSs). The assumption of a fixed distribution in the data renders conventional static DSSs inaccurate and unable to make correct decisions when concept drift occurs. However, it is important to know when, how, and where concept drift occurs so a DSS can adjust its decision processing knowledge to adapt to an ever-changing environment at the appropriate time. This paper presents a data distribution-based concept drift detection method called fuzzy competence model drift detection (FCM-DD). By introducing fuzzy sets theory and replacing crisp boundaries with fuzzy ones, we have improved the competence model to provide a better, more refined empirical distribution of the data stream. FCM-DD requires no prior knowledge of the underlying distribution and provides statistical guarantee of the reliability of the detected drift, based on the theory of bootstrapping. A series of experiments show that our proposed FCM-DD method can detect drift more accurately, has good sensitivity, and is robust.
Dong, X, Gong, Y & Cao, L 2018, 'F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage', Pattern Recognition, vol. 84, pp. 13-27.
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© 2018 Elsevier Ltd Mining negative sequential patterns (NSP) is an important tool for nonoccurring behavior analysis, and it is much more challenging than mining positive sequential patterns (PSPs) due to the high computational complexity and huge search space when obtaining the support of negative sequential candidates (NSCs). Very few NSP mining algorithms are available and most of them are very inefficient since they obtain the support of NSC by scanning the database repeatedly. Instead, the state-of-the-art NSP mining algorithm e-NSP only uses the PSP's information stored in an array structure to ‘calculate' the support of NSC by equations, without database re-scanning. This makes e-NSP highly efficient, particularly on sparse datasets. However, when datasets become dense, the key process to obtain the support of NSC in e-NSP becomes very time-consuming and needs to be improved. In this paper, we propose a novel and efficient data structure, a bitmap, to obtain the support of NSC. We correspondingly propose a fast NSP mining algorithm, f-NSP, which uses a bitmap to store the PSP's information and then obtain the support of NSC only by bitwise operations, which is much faster than the hash method in e-NSP. Experimental results on real-world and synthetic datasets show that f-NSP is not only tens to hundreds of times faster than e-NSP, but also saves more than ten-fold the storage spaces of e-NSP, particularly on dense datasets with a large number of elements in a sequence or a small number of itemsets. Further, we find that f-NSP consumes more storage space than e-NSP when PSP's support is less than a support threshold sdsup, a value obtained through our theoretical analysis of storage space. Accordingly, we propose a self-adaptive storage strategy and a corresponding algorithm f-NSP+to overcome this deficiency. f-NSP+can automatically choose a bitmap or an array structure to store PSP information according to PSP support. Experimental results show that f-NSP...
Dong, Y, Fatahi, B, Khabbaz, H & Zhang, H 2018, 'Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1154-1170.
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The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly in problems concerning in situ testing, pile installation and so forth, explaining why cavity expansion simulation using DEM has been adopted in this study. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric st...
Dorji, P, Choi, J, Kim, DI, Phuntsho, S, Hong, S & Shon, HK 2018, 'Membrane capacitive deionisation as an alternative to the 2nd pass for seawater reverse osmosis desalination plant for bromide removal', Desalination, vol. 433, pp. 113-119.
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© 2018 Elsevier B.V. Most Australian surface and ground waters have relatively high concentration of bromide between 400 and 8000 μg/L and even higher concentration in seawater between 60,000–78,000 μg/L. Although bromide is not regulated, even at low concentrations of 50–100 μg/L, it can lead to the formation of several types of harmful disinfection by-products (DBPs) during the disinfection process. One of the major concerns with brominated DBPs is the formation of bromate (BrO3−), a serious carcinogen that is formed when water containing a high concentration of bromide is disinfected. As a result, bromate is highly regulated in Australian water standards with the maximum concentration of 20 μg/L in the drinking water. Since seawater reverse osmosis (SWRO) desalination plays an important role in augmenting fresh water supplies in Australia, SWRO plants in Australia usually adopt 2nd pass brackish water reverse osmosis (BWRO) for effective bromide removal, which is not only energy-intensive to operate but also has higher capital cost. In this study, we evaluated the feasibility of membrane capacitive deionisation (MCDI) as one of the alternatives to the 2nd pass BWRO for effective bromide removal in a more energy efficient way.
Dorneburg, C, Fischer, M, Barth, TFE, Mueller-Klieser, W, Hero, B, Gecht, J, Carter, DR, de Preter, K, Mayer, B, Christner, L, Speleman, F, Marshall, GM, Debatin, K-M & Beltinger, C 2018, 'LDHA in Neuroblastoma Is Associated with Poor Outcome and Its Depletion Decreases Neuroblastoma Growth Independent of Aerobic Glycolysis', Clinical Cancer Research, vol. 24, no. 22, pp. 5772-5783.
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Abstract
Purpose: To investigate whether lactate dehydrogenase A (LDHA), an important component of the LDH tetramer crucial for aerobic glycolysis, is associated with patient outcome and constitutes a therapeutic target in neuroblastoma (NB).
Experimental Design: Expression of LDHA mRNA and protein was determined in 709 and 110 NB patient samples, respectively, and correlated with survival and risk factors. LDHA and LDHB were depleted in human NB cell lines by CRISPR/Cas9 and shRNA, respectively, and aerobic glycolysis, clonogenicity, and tumorigenicity were determined. Expression of LDHA in relation to MYCN was measured in NB cell lines and in the TH-MYCN NB mouse model.
Results: Expression of LDHA, both on the mRNA and the protein level, was significantly and independently associated with decreased patient survival. Predominant cytoplasmic localization of LDHA protein was associated with poor outcome. Amplification and expression of MYCN did not correlate with expression of LDHA in NB cell lines or TH-MYCN mice, respectively. Knockout of LDHA inhibited clonogenicity, tumorigenicity, and tumor growth without abolishing LDH activity or significantly decreasing aerobic glycolysis. Concomitant depletion of LDHA and the isoform LDHB ablated clonogenicity while not abrogating LDH activity or decreasing aerobic glycolysis. The isoform LDHC was not expressed.
Conclusions: High expression of LDHA is independently associated with outcome of NB, and NB cells can be inhibited by depletion of LDHA or LDHB. This inhibition appears to be unrelated to LDH activity and aerobic glycolysis. Thus, investigations of inhibitory mechanisms beyond attenuation of aerobic glycolysis are warranted, both in NB and normal cells. Clin Cancer Res; 24(22); 5772–83. ©2018 AACR.
Douglas, A, Torpy, F, Surawski, N & Irga, P 2018, 'Mapping Urban Aerosolized Fungi: Predicting Spatial and Temporal Indoor Concentrations', Human Ecology Review, vol. 24, no. 2, pp. 81-103.
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Du, X, Yin, H, Huang, Z, Yang, Y & Zhou, X 2018, 'Exploiting detected visual objects for frame-level video filtering', World Wide Web, vol. 21, no. 5, pp. 1259-1284.
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© 2017 Springer Science+Business Media, LLC Videos are generated at an unprecedented speed on the web. To improve the efficiency of access, developing new ways to filter the videos becomes a popular research topic. One on-going direction is using visual objects to perform frame-level video filtering. Under this direction, existing works create the unique object table and the occurrence table to maintain the connections between videos and objects. However, the creation process is not scalable and dynamic because it heavily depends on human labeling. To improve this, we propose to use detected visual objects to create these two tables for frame-level video filtering. Our study begins with investigating the existing object detection techniques. After that, we find object detection lacks the identification and connection abilities to accomplish the creation process alone. To supply these abilities, we further investigate three candidates, namely, recognizing-based, matching-based and tracking-based methods, to work with the object detection. Through analyzing the mechanism and evaluating the accuracy, we find that they are imperfect for identifying or connecting the visual objects. Accordingly, we propose a novel hybrid method that combines the matching-based and tracking-based methods to overcome the limitations. Our experiments show that the proposed method achieves higher accuracy and efficiency than the candidate methods. The subsequent analysis shows that the proposed method can efficiently support the frame-level video filtering using visual objects.
DU, Y 2018, 'Topology Optimization of Multiple Materials Compliant Mechanisms Based on Sequence Interpolation Model and Multigrid Method', Journal of Mechanical Engineering, vol. 54, no. 13, pp. 47-47.
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Multi-material flexible mechanism topology optimization based on Solid isotropic material with penalization (SIMP) is to decompose the original problem into several sub-problems for layer optimization, which increases the number of design variables exponentially. The method utilizes the traditional finite element discretization. In order to obtain a clear topology, the number of meshes is inevitably huge. These two factors cause the computational efficiency of the method to be low. Therefore, based on the power function polynomial, the sequence interpolation model is proposed, and the multi-material layout iteration is used to make the different materials gather in the design domain to a plurality of predefined material points. It can be completed under a single optimization framework without decomposing into sub-problems. Topology optimization of materials without increasing the number of design variables. Aiming at the maximum geometric gain of the mechanism, a multi-material flexible mechanism topology optimization model is established. In the process of solving the governing equations by using finite element method, the multi-grid method is introduced. The meshing granularity progressively moves the displacement field of the coarse mesh horizontally as the initial field quantity on the fine mesh, avoiding directly using the fine mesh to design the domain. The high computational cost problem caused by the overall dispersion improves the calculation efficiency. The improved optimization criterion method is used to solve the model, and the multi-material flexible mechanism with optimal sequence layout is obtained. The effectiveness of the proposed method is verified by a typical example and the corresponding results of SIMP-based methods.
Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'A Grover-search Based Quantum Learning Scheme for Classification', New J. Phys., vol. 23, p. 023020.
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The hybrid quantum-classical learning scheme provides a prominent way to
achieve quantum advantages on near-term quantum devices. A concrete example
towards this goal is the quantum neural network (QNN), which has been developed
to accomplish various supervised learning tasks such as classification and
regression. However, there are two central issues that remain obscure when QNN
is exploited to accomplish classification tasks. First, a quantum classifier
that can well balance the computational cost such as the number of measurements
and the learning performance is unexplored. Second, it is unclear whether
quantum classifiers can be applied to solve certain problems that outperform
their classical counterparts. Here we devise a Grover-search based quantum
learning scheme (GBLS) to address the above two issues. Notably, most existing
QNN-based quantum classifiers can be seamlessly embedded into the proposed
scheme. The key insight behind our proposal is reformulating the classification
tasks as the search problem. Numerical simulations exhibit that GBLS can
achieve comparable performance with other quantum classifiers under various
noise settings, while the required number of measurements is dramatically
reduced. We further demonstrate a potential quantum advantage of GBLS over
classical classifiers in the measure of query complexity. Our work provides
guidance to develop advanced quantum classifiers on near-term quantum devices
and opens up an avenue to explore potential quantum advantages in various
classification tasks.
Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'The Expressive Power of Parameterized Quantum Circuits', Phys. Rev. Research, vol. 2, no. 3, p. 033125.
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Parameterized quantum circuits (PQCs) have been broadly used as a hybrid
quantum-classical machine learning scheme to accomplish generative tasks.
However, whether PQCs have better expressive power than classical generative
neural networks, such as restricted or deep Boltzmann machines, remains an open
issue. In this paper, we prove that PQCs with a simple structure already
outperform any classical neural network for generative tasks, unless the
polynomial hierarchy collapses. Our proof builds on known results from tensor
networks and quantum circuits (in particular, instantaneous quantum polynomial
circuits). In addition, PQCs equipped with ancillary qubits for post-selection
have even stronger expressive power than those without post-selection. We
employ them as an application for Bayesian learning, since it is possible to
learn prior probabilities rather than assuming they are known. We expect that
it will find many more applications in semi-supervised learning where prior
distributions are normally assumed to be unknown. Lastly, we conduct several
numerical experiments using the Rigetti Forest platform to demonstrate the
performance of the proposed Bayesian quantum circuit.
Duan, H, Wang, Q, Erler, DV, Ye, L & Yuan, Z 2018, 'Effects of free nitrous acid treatment conditions on the nitrite pathway performance in mainstream wastewater treatment', Science of The Total Environment, vol. 644, pp. 360-370.
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Inline sludge treatment using free nitrous acid (FNA) was recently shown to be effective in establishing the nitrite pathway in a biological nitrogen removal system. However, the effects of FNA treatment conditions on the nitrite pathway performance remained to be investigated. In this study, three different FNA treatment frequencies (daily sludge treatment ratios of 0.22, 0.31 and 0.38, respectively), two FNA concentrations (1.35 mgN/L and 4.23 mgN/L, respectively) and two influent feeding regimes (one- and two-step feeding) were investigated in four laboratory-scale sequencing batch reactors. The nitrite accumulation ratio was positively correlated to the FNA treatment frequency. However, when a high treatment frequency was used e.g., daily sludge treatment ratio of 0.38, a significant reduction in ammonia oxidizing bacteria (AOB) activity occurred, leading to poor ammonium oxidation. AOB were able to acclimatise to FNA concentrations up to of 4.23 mgN/L, whereas nitrite oxidizing bacteria (NOB) were limited by an FNA concentration of 1.35 mgN/L over the duration of the study (up to 120 days). This difference in sensitivity to FNA could be used to further enhance nitrite accumulation, with 90% accumulation achieved at an FNA concentration of 4.23 mgN/L and a daily sludge treatment ratio of 0.31 in this study. However, this high level of nitrite accumulation led to increased N2O emission, with emission factors of up to 3.9% observed. The N2O emission was mitigated (reduced to 1.3%) by applying two-step feeding resulting in a nitrite accumulation ratio of 45.1%. Economic analysis showed that choosing the optimal FNA treatment conditions depends on a combination of the wastewater characteristics, the nitrogen discharge standards, and the operational costs. This study provides important information for the optimisation and practical application of FNA-based sludge treatment technology for achieving the mainstream stable nitrite pathway.
Duan, N, Xu, W, Feng, H, Wang, S, Guo, Z, Li, Y, Wang, S & Zhu, J 2018, 'A Scalar Hysteresis Model of Ferromagnetic Materials Based on the Elemental Operators', IEEE Transactions on Magnetics, vol. 54, no. 11, pp. 1-4.
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© 1965-2012 IEEE. This paper introduces an elemental operator with biaxial anisotropy to simulate the scalar hysteresis phenomenon of the ferromagnetic materials. The equilibrium position of the magnetization for the elemental operator can be determined by energy minimization. To directly describe the magnetic properties of each operator, an improved analytical expression is deduced by the partial approximate substitutions. Moreover, this approach utilizes the concept of distribution function density in order to consider the interaction field and the coercive force of the elemental operators. To verify the presented model, the magnetic hysteresis of two different magnetic materials under alternating excitations is measured by the magnetic property measurement system and calculated by this elemental operator method, respectively. The comparisons suggest that this elemental operator is effective and can be a useful tool to simulate the scalar magnetic properties of ferromagnetic materials.
Duan, N, Xu, W, Li, Y, Wang, S & Zhu, J 2018, 'Rotational magnetic hysteresis of soft magnetic composite materials based on the elemental operator method', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 33, no. 10, pp. 2268-2273.
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The paper introduces a vector elemental operator with biaxial anisotropy based on the underlying magnetization mechanisms of the magnetic material. Detailed analysis of the magnetic properties of one elemental operator under rotational magnetization has been presented thereafter. With the help of the proposed vector elemental operator, the rotational magnetic hysteresis of soft magnetic composite material is simulated. The simulation results are compared with the experimental results obtained by the 3-D magnetic property measurement system. The good agreement shows the validity and practicability of the elemental operator method in the modelling of the rotational magnetic hysteresis.
Duan, N, Xu, W, Wang, S & Zhu, J 2018, 'Current Distribution Calculation of Superconducting Layer in HTS Cable Considering Magnetic Hysteresis by Using XFEM', IEEE Transactions on Magnetics, vol. 54, no. 3, pp. 1-4.
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© 2017 IEEE. This paper presents a coupled field-circuit analysis method for the high-temperature superconducting (HTS) cable considering magnetic hysteresis by using the improved extended finite-element method (XFEM). The quasi-3-D cylindrical coordinate HTS cable model is first proposed based on the shell element theory. The quasi-3-D meshing elements are used instead of the traditional 3-D meshing elements to overcome the difficulties in meshing. A new Preisach type hysteresis model of HTS tapes is first combined with the improved XFEM to determine the magnetic hysteresis inductance. A magnetic field-circuit coupled program for current analysis of superconducting layers is coded. The numerical simulation results of this field-circuit coupled method are reported compared with the experimental test results for the case of an HTS cable with two layers.
Duong, HC, Álvarez, IRC, Nguyen, TV & Nghiem, LD 2018, 'Membrane distillation to regenerate different liquid desiccant solutions for air conditioning', Desalination, vol. 443, pp. 137-142.
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© 2018 The capacity of membrane distillation (MD) to regenerate three commonly used liquid desiccant solutions (i.e. CaCl2, LiCl, and a mixture of CaCl2/LiCl) for liquid desiccant air-conditioners (LDAC) was evaluated. The results demonstrate considerable impact of the concentration polarisation effect on the process water flux during MD regeneration of these three desiccant solutions. For each of these liquid desiccant solutions, the experimentally measured water flux of the MD process was about half of the calculated value using the process mass transfer coefficient (Km) obtained during the process characterisation without taking into account the concentration polarisation effect. The observed deviation between the experimentally measured and calculated process water flux indicates the need to include the concentration polarisation effect in the model for calculating water flux. Although Ca2+ concentration in the CaCl2 and CaCl2/LiCl liquid desiccant solutions exceeded the solubility limit for CaCO3, membrane scaling was not observed. Nevertheless, there was evidence that membrane fouling might occur during extended MD regeneration of liquid desiccant solutions containing CaCl2.
Duong, HC, Ansari, AJ, Nghiem, LD, Pham, TM & Pham, TD 2018, 'Low Carbon Desalination by Innovative Membrane Materials and Processes', Current Pollution Reports, vol. 4, no. 4, pp. 251-264.
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Duong, HC, Chuai, D, Woo, YC, Shon, HK, Nghiem, LD & Sencadas, V 2018, 'A novel electrospun, hydrophobic, and elastomeric styrene-butadiene-styrene membrane for membrane distillation applications', Journal of Membrane Science, vol. 549, pp. 420-427.
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© 2017 In this study, a novel hydrophobic, microporous membrane was fabricated from styrene-butadiene-styrene (SBS) polymer using electrospinning and evaluated for membrane distillation applications. Compared to a commercially available polytetrafluoroethylene (PTFE) membrane, the SBS membrane had larger membrane pore size and fiber diameter and comparable membrane porosity. The fabricated SBS showed slightly lower water flux than the PTFE membrane because it was two times thicker. However, the SBS membrane had better salt rejection and most importantly could be fabricated via a simple process. The SBS membrane was also more hydrophobic than the reference PTFE membrane. In particular, as temperature of the reference water liquid increased to 60 °C, the SBS membrane remained hydrophobic with a contact angle of 100° whereas the PTFE became hydrophilic with a contact angle of less than 90°. The hydrophobic membrane surface prevented the intrusion of liquid into the membrane pores, thus improving the salt rejection of the SBS membrane. In addition, the SBS membrane had superior mechanical strength over the PTFE membrane. Using the SBS membrane, stable water flux was achieved throughout an extended MD operation period of 120 h to produce excellent quality distillate (over 99.7% salt rejection) from seawater.
Duong, NMH, Xu, Z-Q, Kianinia, M, Su, R, Liu, Z, Kim, S, Bradac, C, Li, L-J, Solntsev, A, Liu, J & Aharonovich, I 2018, 'Enhanced Emission from WSe2 Monolayers Coupled to Circular Bragg Gratings', ACS Photonics, vol. 5, pp. 3950-3955.
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Two-dimensional transition-metal dichalcogenides (TMDC) are of great interest
for on-chip nanophotonics due to their unique optoelectronic properties. Here,
we propose and realize coupling of tungsten diselenide (WSe2) monolayers to
circular Bragg grating structures to achieve enhanced emission. The interaction
between WSe2 and the resonant mode of the structure results in Purcell-enhanced
emission, while the symmetric geometrical structure improves the directionality
of the out-coupling stream of emitted photons. Furthermore, this hybrid
structure produces a record high contrast of the spin valley readout (> 40%)
revealed by the polarization resolved photoluminescence (PL) measurements. Our
results are promising for on-chip integration of TMDC monolayers with optical
resonators for nanophotonic circuits.
Durán Santomil, P, Otero González, L, Martorell Cunill, O & Merigó Lindahl, JM 2018, 'Backtesting an equity risk model under Solvency II', Journal of Business Research, vol. 89, pp. 216-222.
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© 2018 Elsevier Inc. Backtesting is a technique for validating internal models under Solvency II, which allows for evaluating the discrepancies between the results provided by a model and real observations. This paper aims to establish various backtesting tests and to show their applications to equity risk in Solvency II. Normal and empirical models with a rolling window are used to determine VaR at the 99.5% confidence level over a one-year time horizon. The proposed methodology performs the backtesting of annualized returns arising from the accumulation of daily returns. The results show that even if a model is conservative when tested out of a sample, it may be inadequate when evaluated in a sample, thereby highlighting the problems inherent in the out-of-sample backtesting proposed by the regulator.
Dyson, LE & Frawley, JK 2018, 'A Student-Generated Video Careers Project', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 32-51.
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This article describes how in recent years, the multimedia recording capabilities of mobile devices have been used increasingly to create a more active, learner-centred educational experience. Despite the proven value of student-generated multimedia projects, there are still gaps in our understanding of how students learn during them. This article reports on a project in which first-year information technology students interviewed IT professionals in their workplace and video-recorded the interview to enable sharing with their peers. In order to understand the statistically significant increases found in students' learning, student diaries and reflections were analyzed qualitatively. Factors found to contribute to learning included: the iterative nature of student activities; the multiple, evolving representations of knowledge as students proceeded through the project; the importance of the workplace context in engaging students and enhancing learning; the affordance of mobile technology for capturing and sharing this context; and the collaborative and metacognitive processes fostered by the project.
Eager, D 2018, 'Playground Equipment Falls', Journal of Paediatrics and Child Health, vol. 54, no. 6, pp. 705-705.
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Ebrahimi, M, ShafieiBavani, E, Wong, R & Chen, F 2018, 'Twitter user geolocation by filtering of highly mentioned users', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 879-889.
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Eeshwarasinghe, D, Loganathan, P, Kalaruban, M, Sounthararajah, DP, Kandasamy, J & Vigneswaran, S 2018, 'Removing polycyclic aromatic hydrocarbons from water using granular activated carbon: kinetic and equilibrium adsorption studies', Environmental Science and Pollution Research, vol. 25, no. 14, pp. 13511-13524.
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El-Sayed, H, Sankar, S, Daraghmi, Y-A, Tiwari, P, Rattagan, E, Mohanty, M, Puthal, D & Prasad, M 2018, 'Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier', Sensors, vol. 18, no. 6, pp. 1696-1696.
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Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks (VANETs), which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs). The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS) improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM) kernels with a radial basis function (RBF). The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.
El-Sayed, H, Sankar, S, Prasad, M, Puthal, D, Gupta, A, Mohanty, M & Lin, C-T 2018, 'Edge of Things: The Big Picture on the Integration of Edge, IoT and the Cloud in a Distributed Computing Environment', IEEE Access, vol. 6, pp. 1706-1717.
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© 2013 IEEE. A centralized infrastructure system carries out existing data analytics and decision-making processes from our current highly virtualized platform of wireless networks and the Internet of Things (IoT) applications. There is a high possibility that these existing methods will encounter more challenges and issues in relation to network dynamics, resulting in a high overhead in the network response time, leading to latency and traffic. In order to avoid these problems in the network and achieve an optimum level of resource utilization, a new paradigm called edge computing (EC) is proposed to pave the way for the evolution of new age applications and services. With the integration of EC, the processing capabilities are pushed to the edge of network de vices such as smart phones, sensor nodes, wearables, and on-board units, where data analytics and knowledge generation are performed which removes the necessity for a centralized system. Many IoT applications, such as smart cities, the smart grid, smart traffic lights, and smart vehicles, are rapidly upgrading their applications with EC, significantly improving response time as well as conserving network resources. Irrespective of the fact that EC shifts the workload from a centralized cloud to the edge, the analogy between EC and the cloud pertaining to factors such as resource management and computation optimization are still open to research studies. Hence, this paper aims to validate the efficiency and resourcefulness of EC. We extensively survey the edge systems and present a comparative study of cloud computing systems. After analyzing the different network properties in the system, the results show that EC systems perform better than cloud computing systems. Finally, the research challenges in implementing an EC system and future research directions are discussed.
Engemann, KJ, Merigó, JM, Terceño, A & Yager, RR 2018, 'Foreword', International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 26, no. Suppl. 1, pp. v-vii.
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Erfani, SS & Abedin, B 2018, 'Impacts of the use of social network sites on users' psychological well-being: A systematic review', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 900-912.
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As Social Network Sites (SNSs) are increasingly becoming part of people's everyday lives, the implications of their use need to be investigated and understood. We conducted a systematic literature review to lay the groundwork for understanding the relationship between SNS use and users' psychological well‐being and for devising strategies for taking advantage of this relationship. The review included articles published between 2003 and 2016, extracted from major academic databases. Findings revealed that the use of SNSs is both positively and negatively related to users' psychological well‐being. We discuss the factors that moderate this relationship and their implications on users' psychological well‐being. Many of the studies we reviewed lacked a sound theoretical justification for their findings and most involved young and healthy students, leaving other cohorts of SNS users neglected. The paper concludes with the presentation of a platform for future investigation.
Eskandari, M, Li, L & Moradi, MH 2018, 'Decentralized Optimal Servo Control System for Implementing Instantaneous Reactive Power Sharing in Microgrids', IEEE Transactions on Sustainable Energy, vol. 9, no. 2, pp. 525-537.
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Eskandari, M, Li, L & Moradi, MH 2018, 'Improving power sharing in islanded networked microgrids using fuzzy-based consensus control', Sustainable Energy, Grids and Networks, vol. 16, pp. 259-269.
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© 2018 Elsevier Ltd The rising world-wide trend toward developing clean energy resources has caused dispersed installation of renewable energy resources (RESs) in distribution grids. Microgrid (MG) concept is proposed as a key factor in optimal and secure integration of, mostly converter-based, RESs into power systems. One of the major challenges related to MG control is ineffectiveness of droop control in accurate power sharing which is affected by the feeder impedance. In this paper, a fuzzy-based consensus control protocol is developed to address this issue in multi-bus MGs (MBMGs). Consensus signals are inserted into the conventional droop controller as complementary part to overcome the drawback of the droop control in power sharing in MBMGs. Dynamic fuzzy coefficients of consensus signals are designed to model X/R ratio of the grid impedance in the control system. In addition, a novel small signal model of MBMG is developed, by considering the conventional droop control, MBMG power network and power lines impedance to design and assess performance of the control system. Consensus control is also incorporated into the proposed control system of MBMG to analyze the stability. Simulation results are presented to assess effectiveness of the control strategy in MATLAB\Simulink.
Esmaili, N, Norman, BA & Rajgopal, J 2018, 'Shelf-space optimization models in decentralized automated dispensing cabinets', Operations Research for Health Care, vol. 19, pp. 92-106.
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We propose a mixed integer programming (MIP) model to help clinicians store medications and medical supplies optimally in space-constrained, decentralized Automated Dispensing Cabinets (ADCs) located on hospital patient floors. We also propose a second MIP model that addresses human errors associated with the selection of pharmaceuticals from floor storage, and not only selects the best set of medications for storage but also determines their optimal layout within the cabinet. To improve the computational performance of these MIP models, we investigate several valid inequalities and relaxations that allow us to solve large, real-world instances in reasonable times. These models are applicable to very general ADCs and are illustrated using real-world data from ADCs at hospitals. Our results indicate that using these models can significantly reduce the time spent by clinical staff on routine logistical functions, while making efficient use of limited space and decreasing risks associated with errors in the selection of medication.
Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2018, 'Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models', PLOS ONE, vol. 13, no. 11, pp. e0206274-e0206274.
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Fahmideh, M & Beydoun, G 2018, 'Reusing empirical knowledge during cloud computing adoption.', J. Syst. Softw., vol. 138, pp. 124-157.
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Fan, X, He, X, Xiang, C, Puthal, D, Gong, L, Nanda, P & Fang, G 2018, 'Towards System Implementation and Data Analysis for Crowdsensing Based Outdoor RSS Maps', IEEE Access, vol. 6, pp. 47535-47545.
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With the explosive usage of smart mobile devices, sustainable access to wireless networks (e.g., WiFi) has become a pervasive demand. Most mobile users expect seamless network connection with low cost. Indeed,
this can be achieved by using an accurate received signal strength (RSS) map of wireless access points. While existing methods are either costly or unscalable, the recently emerged mobile crowdsensing (MCS)
paradigm is a promising technique for building RSS maps. MCS applications leverage pervasive mobile devices to collaboratively collect data. However, the heterogeneity of devices and the mobility of users
could cause inherent noises and blank spots in collected dataset. In this paper, we study (1) how to tame the sensing noises from heterogenous mobile devices, and (2) how to construct accurate and complete RSS
maps with random mobility of crowdsensing participants. First, we build a mobile crowdsensing system called iMap to collect RSS measurements with heterogeneous mobile devices. Second, through observing
experimental results, we build statistical models of sensing noises and derive different parameters for each kind of mobile device. Third, we present the signal transmission model with measurement error model, and we propose a novel signal recovery scheme to construct accurate and complete RSS maps. The evaluation results show that the proposed method can achieve 90% and 95% recovery rate in geographic coordinate
system and polar coordinate system, respectively.
Fan, X, Zhao, J, Ren, F, Wang, Y, Feng, Y, Ding, L, Zhao, L, Shang, Y, Li, J, Ni, J, Jia, B, Liu, Y & Chang, Z 2018, 'Dimerization of p15RS mediated by a leucine zipper–like motif is critical for its inhibitory role on Wnt signaling', Journal of Biological Chemistry, vol. 293, no. 20, pp. 7618-7628.
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© 2018 Fan et al. We previously demonstrated that p15RS, a newly discovered tumor suppressor, inhibits Wnt/-catenin signaling by interrupting the formation of -cateninTCF4 complex. However, it remains unclear how p15RS helps exert such an inhibitory effect on Wnt signaling based on its molecular structure. In this study, we reported that dimerization of p15RS is required for its inhibition on the transcription regulation of Wnt-targeted genes. We found that p15RS forms a dimer through a highly conserved leucine zipper–like motif in the coiled-coil terminus domain. In particular, residues Leu-248 and Leu-255 were identified as being responsible for p15RS dimerization, as mutation of these two leucines into prolines disrupted the homodimer formation of p15RS and weakened its suppression of Wnt signaling. Functional studies further confirmed that mutations of p15RS at these residues results in diminishment of its inhibition on cell proliferation and tumor formation. We therefore concluded that dimerization of p15RS governed by the leucine zipper–like motif is critical for its inhibition of Wnt/-catenin signaling and tumorigenesis.
Fang, J, Sun, G, Qiu, N, Pang, T, Li, S & Li, Q 2018, 'On hierarchical honeycombs under out-of-plane crushing', International Journal of Solids and Structures, vol. 135, pp. 1-13.
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© 2017 Hierarchy has been introduced to honeycomb structures in pursuing ultralight materials with outstanding mechanical properties. Nevertheless, the hierarchical honeycombs under the out-of-plane loads have not been well studied experimentally and analytically for energy absorption to date. This study aimed to apply a special structural hierarchy to the honeycomb by replacing the sides of hexagons with smaller hexagons. The quasi-static test of the hierarchical honeycomb specimen was first conducted experimentally to investigate the crushing behaviours; and then the corresponding finite element (FE) analyses were performed. Finally, the analytical solutions to the mean crushing force and plateau stress were derived based on the simplified super folding element (SSFE) method. It was shown that the experimental data and numerical results agreed well in terms of crushing force versus displacement relation and energy absorption characteristics; and the analytical results were validated by the experimental test. Importantly, the hierarchy could improve the energy absorption; and the increase in the order and number of replacement hexagons could excavate the advantage even further. Specifically, the second order honeycomb characterized by five smaller replacement hexagons at each order can yield a plateau stress 2.63 and 4.16 times higher than the regular honeycomb and the aluminium foam, respectively. While it might lead to global bending, structural hierarchy provides new architectural configurations for developing novel ultralight materials with exceptional energy absorption capacity under out-of-plane loads.
Fanos, AM & Pradhan, B 2018, 'Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review', Earth Systems and Environment, vol. 2, no. 2, pp. 163-182.
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Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.
Fanos, AM, Pradhan, B, Mansor, S, Yusoff, ZM & Abdullah, AFB 2018, 'A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data', Landslides, vol. 15, no. 9, pp. 1833-1850.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.
Farrok, O, Islam, MR, Guo, Y, Zhu, J & Xu, W 2018, 'A Novel Design Procedure for Designing Linear Generators', IEEE Transactions on Industrial Electronics, vol. 65, no. 2, pp. 1846-1854.
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IEEE A number of research works have been carried out based on the optimization of linear generators for harvesting oceanic wave energy, but no significant method of shape optimization for determination of the optimal shape of linear generator has been found. Moreover, inclusion of some parameters, such as shape of linear generator & #x0027;s translator and stator, has been considered out of the scope of the conventional, adaptive or knowledge based genetic algorithm. This paper proposes a novel method through which any type of linear generator & #x0027;s shape can be optimized graphically. A mathematical model of the proposed method including human intervened genetic algorithm is presented. The proposed method has been applied to a direct-drive system based linear generator where the maximization of electrical power output and minimization of steel core volume have been considered as the optimization objectives. The optimization parameters have been further optimized graphically within functional volumetric and electromagnetic constraints to achieve improved design solutions. The proposed method has included comprehensive geometric dimensions, magnetic and electrical parameters. Finally, the shape of steel cores of the translator and special m-shaped stator of the linear generator is determined and simulated using the copper wire. This optimized shape of the linear generator is capable of satisfying the multi-objectives of maximal electrical power generation and reduction of its size. The ANSYS/Ansoft software has been used to create the platform for analyses of the whole system.
Farrok, O, Islam, MR, Islam Sheikh, MR, Guo, Y, Zhu, J & Lei, G 2018, 'Oceanic Wave Energy Conversion by a Novel Permanent Magnet Linear Generator Capable of Preventing Demagnetization', IEEE Transactions on Industry Applications, vol. 54, no. 6, pp. 6005-6014.
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© 1972-2012 IEEE. In the conventional permanent magnet linear generators (PMLGs) used for oceanic wave energy conversion system, demagnetization could cause everlasting degradation in electrical power generation. This paper presents a new design that can be applied to various PMLGs to avoid demagnetization. To check the effectiveness of the proposed technique, a PMLG is considered, which allows both the fixed and variable length of airgaps for analysis. The finite element analysis is used by using the software package ANSYS/Ansoft to simulate the testing PMLG for two conditions: with and without using the proposed technique. Different parameters and characteristics of the PMLG under both conditions are presented in detail. Both the simulation and test results show that the proposed design is able to avoid the demagnetization problem successfully.
Farrok, O, Islam, MR, Sheikh, MRI, Guo, Y & Zhu, JG 2018, 'A Split Translator Secondary Stator Permanent Magnet Linear Generator for Oceanic Wave Energy Conversion', IEEE Transactions on Industrial Electronics, vol. 65, no. 9, pp. 7600-7608.
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IEEE Almost all flux switching permanent magnet linear generators (FSPMLGs) and Vernier hybrid machines contain a heavy solid translator due to their design limitations for electricity generation from the oceanic waves. This paper presents the new design of a FSPMLG in which the translator weight is reduced and an additional static steel core is inserted inside the translator cavity to improve the magnetic flux linkage of the main stator. The generated voltage, current, power, efficiency, core loss, force ripples and cogging force minimization of the proposed FSPMLG are presented. From the dynamic model of the oceanic wave, it is shown that the translator with lower mass could generate electricity more effectively. The special stator and translator sets have been optimized by using the genetic algorithm before they are used in the proposed FSPMLG. To analyze the performance and verify the feasibility of the new design of FSPMLG, the finite element analysis is performed by using the commercial software package ANSYS/Ansoft.
Fatahi, B, Van Nguyen, Q, Xu, R & Sun, W-J 2018, 'Three-Dimensional Response of Neighboring Buildings Sitting on Pile Foundations to Seismic Pounding', International Journal of Geomechanics, vol. 18, no. 4, pp. 04018007-04018007.
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© 2018 American Society of Civil Engineers. Seismic pounding occurs when the separation gap between buildings and structures is not wide enough, particularly during major earthquake events; this can cause them to collide, causing local damage or, in extreme cases, collapse. This study investigated the impact that this separation gap has on the seismic response of midrise buildings supported on piles while considering seismic soil-pile-structure interaction (SSPSI). To achieve this aim, three 15-story reinforced concrete buildings sitting on pile foundations and with five different separation gaps under excitations from the 1994 Northridge and 1995 Kobe earthquakes were numerically simulated. This study used three-dimensional numerical modeling to simultaneously capture the effects of seismic pounding and SSPSI. Because the considered structure, pile foundation, and soil deposit are three-dimensional in nature, the adopted three-dimensional numerical modeling can provide a more realistic simulation to capture the seismic behavior of the system. The nonlinear behavior of structural elements was included, and the dynamic soil properties were obtained from field data and backbone curves. A contact pair interface with small-sliding surface-to-surface formulation between buildings was used to capture possible seismic pounding, and contact interfaces with a finite-sliding formulation were used to simulate the interaction between the piles and the soil. The results, including lateral building deflections, interstory drifts, structural shear forces, foundation rocking, lateral pile deflections, and the distributions of bending moments and shear forces of the piles, are presented and discussed. The findings of this study will give engineers a better insight into the possible effects of seismic pounding on the seismic performance of buildings, and the response of endbearing piles in soft soils.
Fattah, IMR, Ming, C, Chan, QN, Wehrfritz, A, Pham, PX, Yang, W, Kook, S, Medwell, PR, Yeoh, GH, Hawkes, ER & Masri, AR 2018, 'Spray and Combustion Investigation of Post Injections under Low-Temperature Combustion Conditions with Biodiesel', Energy & Fuels, vol. 32, no. 8, pp. 8727-8742.
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Faunce, TA, Prest, J, Su, D, Hearne, SJ & Iacopi, F 2018, 'On-grid batteries for large-scale energy storage: Challenges and opportunities for policy and technology', MRS Energy & Sustainability, vol. 5, no. 1.
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ABSTRACT
Feng, J, Wu, D, Gao, W & Li, G 2018, 'Hybrid uncertain natural frequency analysis for structures with random and interval fields', Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 365-389.
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© 2017 Elsevier B.V. This paper presents a robust non-deterministic free vibration analysis for engineering structures involving hybrid, yet spatially dependent, uncertain system parameters. Distinguished from the conventional hybrid uncertain eigenvalue problem, the concept of interval field is enclosed with random field model such that, both the stochastic and non-stochastic representations of the spatial dependency of the uncertainties are simultaneously incorporated within a unified non-deterministic free vibration analysis. In order to determine the probabilistic characteristics (i.e., means and standard deviations) of the extremities of structural natural frequencies, an extended unified interval stochastic sampling (X-UISS) method is implemented for the purpose of effective hybrid uncertain free vibration analysis. By meticulously blending sharpness-promised interval eigenvalue analysis with stochastic sampling techniques, the stochastic profiles (i.e., probability density functions (PDFs) and the cumulative distribution functions (CDFs)) of the extreme bounds of the structural natural frequencies can be rigorously established by utilizing the adequate statistical inference methods. The applicability and effectiveness of the proposed computational framework are evidently demonstrated through the numerical investigations on various practically motivated engineering structures.
Feng, X, Chang, L, Lin, X, Qin, L, Zhang, W & Yuan, L 2018, 'Distributed computing connected components with linear communication cost.', Distributed Parallel Databases, vol. 36, no. 3, pp. 555-592.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The paper studies three fundamental problems in graph analytics, computing connected components (CCs), biconnected components (BCCs), and 2-edge-connected components (ECCs) of a graph. With the recent advent of big data, developing efficient distributed algorithms for computing CCs, BCCs and ECCs of a big graph has received increasing interests. As with the existing research efforts, we focus on the Pregel programming model, while the techniques may be extended to other programming models including MapReduce and Spark. The state-of-the-art techniques for computing CCs and BCCs in Pregel incur O(m× # supersteps) total costs for both data communication and computation, where m is the number of edges in a graph and #supersteps is the number of supersteps. Since the network communication speed is usually much slower than the computation speed, communication costs are the dominant costs of the total running time in the existing techniques. In this paper, we propose a new paradigm based on graph decomposition to compute CCs and BCCs with O(m) total communication cost. The total computation costs of our techniques are also smaller than that of the existing techniques in practice, though theoretically almost the same. Moreover, we also study distributed computing ECCs. We are the first to study this problem and an approach with O(m) total communication cost is proposed. Comprehensive empirical studies demonstrate that our approaches can outperform the existing techniques by one order of magnitude regarding the total running time.
Feng, X, Wan, W, Xu, RYD, Chen, H, Li, P & Sánchez, JA 2018, 'A perceptual quality metric for 3D triangle meshes based on spatial pooling', Frontiers of Computer Science, vol. 12, no. 4, pp. 798-812.
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Feng, X, Wan, W, Xu, RYD, Perry, S, Zhu, S & Liu, Z 2018, 'A new mesh visual quality metric using saliency weighting-based pooling strategy', Graphical Models, vol. 99, pp. 1-12.
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© 2018 Elsevier Inc. Several metrics have been proposed to assess the visual quality of 3D triangular meshes during the last decade. In this paper, we propose a mesh visual quality metric by integrating mesh saliency into mesh visual quality assessment. We use the Tensor-based Perceptual Distance Measure metric to estimate the local distortions for the mesh, and pool local distortions into a quality score using a saliency weighting-based pooling strategy. Three well-known mesh saliency detection methods are used to demonstrate the superiority and effectiveness of our metric. Experimental results show that our metric with any of three saliency maps performs better than state-of-the-art metrics on the LIRIS/EPFL general-purpose database. We generate a synthetic saliency map by assembling salient regions from individual saliency maps. Experimental results reveal that the synthetic saliency map achieves better performance than individual saliency maps, and the performance gain is closely correlated with the similarity between the individual saliency maps.
Feng, X, Wan, W, Yi Da Xu, R, Perry, S, Li, P & Zhu, S 2018, 'A novel spatial pooling method for 3D mesh quality assessment based on percentile weighting strategy', Computers & Graphics, vol. 74, pp. 12-22.
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Feng, Y, Zhou, H, Zhang, Y, Perkins, A, Wang, Y & Sun, J 2018, 'Comparison in executive function in Chinese preterm and full-term infants at eight months', Frontiers of Medicine, vol. 12, no. 2, pp. 164-173.
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Fernandez, E, Hossain, MJ & Nizami, MSH 2018, 'Game-theoretic approach to demand-side energy management for a smart neighbourhood in Sydney incorporating renewable resources', Applied Energy, vol. 232, pp. 245-257.
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Fernández-Barrera, J, Bernabé-Rubio, M, Casares-Arias, J, Rangel, L, Fernández-Martín, L, Correas, I & Alonso, MA 2018, 'The actin-MRTF-SRF transcriptional circuit controls tubulin acetylation via α-TAT1 gene expression', The Journal of Cell Biology, vol. 217, no. 3, pp. 929-944.
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The role of formins in microtubules is not well understood. In this study, we have investigated the mechanism by which INF2, a formin mutated in degenerative renal and neurological hereditary disorders, controls microtubule acetylation. We found that silencing of INF2 in epithelial RPE-1 cells produced a dramatic drop in tubulin acetylation, increased the G-actin/F-actin ratio, and impaired myocardin-related transcription factor (MRTF)/serum response factor (SRF)–dependent transcription, which is known to be repressed by increased levels of G-actin. The effect on tubulin acetylation was caused by the almost complete absence of α-tubulin acetyltransferase 1 (α-TAT1) messenger RNA (mRNA). Activation of the MRTF-SRF transcriptional complex restored α-TAT1 mRNA levels and tubulin acetylation. Several functional MRTF-SRF–responsive elements were consistently identified in the α-TAT1 gene. The effect of INF2 silencing on microtubule acetylation was also observed in epithelial ECV304 cells, but not in Jurkat T cells. Therefore, the actin-MRTF-SRF circuit controls α-TAT1 transcription. INF2 regulates the circuit, and hence microtubule acetylation, in cell types where it has a prominent role in actin polymerization.
Fitch, R, Isler, V, Tokekar, P & Scaramuzza, D 2018, 'Guest editorial: Special issue on active perception', Autonomous Robots, vol. 42, no. 2, pp. 175-176.
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Fonseca, A, Kerick, S, King, J-T, Lin, C-T & Jung, T-P 2018, 'Brain Network Changes in Fatigued Drivers: A Longitudinal Study in a Real-World Environment Based on the Effective Connectivity Analysis and Actigraphy Data', Frontiers in Human Neuroscience, vol. 12.
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The analysis of neurophysiological changes during driving can clarify the mechanisms of fatigue, considered an important cause of vehicle accidents. The fluctuations in alertness can be investigated as changes in the brain network connections, reflected in the direction and magnitude of the information transferred. Those changes are induced not only by the time on task but also by the quality of sleep. In an unprecedented 5-month longitudinal study, daily sampling actigraphy and EEG data were collected during a sustained-attention driving task within a near-real-world environment. Using a performance index associated with the subjects' reaction times and a predictive score related to the sleep quality, we identify fatigue levels in drivers and investigate the shifts in their effective connectivity in different frequency bands, through the analysis of the dynamical coupling between brain areas. Study results support the hypothesis that combining EEG, behavioral and actigraphy data can reveal new features of the decline in alertness. In addition, the use of directed measures such as the Convergent Cross Mapping can contribute to the development of fatigue countermeasure devices.
Forouzesh, M, Shen, Y, Yari, K, Siwakoti, YP & Blaabjerg, F 2018, 'High-Efficiency High Step-Up DC–DC Converter With Dual Coupled Inductors for Grid-Connected Photovoltaic Systems', IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 5967-5982.
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© 1986-2012 IEEE. This paper introduces a non-isolated high step-up DC-DC converter with dual coupled inductors suitable for distributed generation applications. By implementing an input parallel connection, the proposed DC-DC structure inherits shared input current with low ripple, which also requires small capacitive filter at its input. Moreover, this topology can reach high voltage gain by using dual coupled inductors in series connection at the output stage. The proposed converter uses active clamp circuits with a shared clamp capacitor for the main switches. In addition to the active clamp circuit, the leakage energy is recycled to the output by using an integrated regenerative snubber. Indeed, these circuits allow soft-switching conditions, i.e., zero voltage switching and zero current switching for active and passive switching devices, respectively. The mentioned features along with a common ground connection of the input and output make the proposed topology a proper candidate for transformer-less grid-connected photovoltaic systems. The operating performance, analysis and mathematical derivations of the proposed DC-DC converter have been demonstrated in the paper. Moreover, the main features of the proposed converter have been verified through experimental results of a 1-kW laboratory prototype.
Fortunato, L, Pathak, N, Ur Rehman, Z, Shon, H & Leiknes, T 2018, 'Real-time monitoring of membrane fouling development during early stages of activated sludge membrane bioreactor operation', Process Safety and Environmental Protection, vol. 120, pp. 313-320.
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© 2018 Institution of Chemical Engineers Non-invasive analysis and a final destructive analysis were employed to study the fouling formation during the initial days of AS-MBR operation. The fouling layer development was quantified in-situ non-invasively with Optical Coherence Tomography (OCT). The increase in biomass thickness was related to the transmembrane pressure (TMP) and to the increase in concentration of soluble microbial products (SMP) in the reactor The OCT non-destructive analysis allowed normalizing the final autopsy values for the amount of biomass deposited on the membrane. After 8 days of operation, the cake layer presented a biomass activity of 400 pg/mm3 of intra-ATP and EPS concentration of 9.8 mg/ mm3. The microbial community analysis of sludge and biofouling on the membrane surface revealed the abundance of Proteobacteria.
Frawley, JK & Dyson, LE 2018, 'Literacies and Learning in Motion', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 52-72.
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Mobile and participatory cultures have led to widespread change in the way we communicate; emphasizing user generated content and digital multimedia. In this environment, informal learning may occur through digital and networked activities, with literacy no longer limited to alphabetic and character-based texts. This article explores adult learners' new literacies within the context of a digital mobile storytelling project. A qualitative approach is used to explore the artifacts and practices of nine adult participants who comprise the study. Participants created a range of fiction, non-fiction, poetry and diary-style content in a variety of modes and media. Outcomes from content analysis, interview and survey methods depict mobile digital literacies as characteristically situated, experiential and multimodal. The mobile and participatory nature of this project was catalytic to participants' imaginative re-interpretation of the world around them as sources for meaning making and transformation. This paper contributes a case example of mobile learning with adults in a community setting.
Fu, A, Li, S, Yu, S, Zhang, Y & Sun, Y 2018, 'Privacy-preserving composite modular exponentiation outsourcing with optimal checkability in single untrusted cloud server', Journal of Network and Computer Applications, vol. 118, pp. 102-112.
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© 2018 Elsevier Ltd Outsourcing computing allows users with resource-constrained devices to outsource their complex computation workloads to cloud servers, which is more economical for cloud customers. However, since users lose direct control of the computation task, possible threats need to be addressed, such as data privacy and the correctness of results. Modular exponentiation is one of the most basic and time-consuming operations but widely applied in the field of cryptography. In this paper, we propose two new and efficient algorithms for secure outsourcing of single and multiple composite modular exponentiations. Unlike the algorithms based on two untrusted servers, we outsource modular exponentiation operation to only a single server, eliminating the possible collusion attack with two servers. Moreover, we put forward a new mathematical division method, which hides the base and exponent of the outsourced data, without exposing sensitive information to the cloud server. In addition, compared with other state-of-the-art algorithms, our scheme shows a remarkable improvement in checkability, enabling the user to detect any misbehavior with the optimal probability close to 1. Finally, we use our proposed algorithms as a subroutine to realize Shamir's Identity-Based Signature Scheme and Identity-Based Multi-Signatures Scheme.
Fu, A, Li, Y, Yu, S, Yu, Y & Zhang, G 2018, 'DIPOR: An IDA-based dynamic proof of retrievability scheme for cloud storage systems', Journal of Network and Computer Applications, vol. 104, pp. 97-106.
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Fu, A, Zhu, Y, Yang, G, Yu, S & Yu, Y 2018, 'Secure outsourcing algorithms of modular exponentiations with optimal checkability based on a single untrusted cloud server', Cluster Computing, vol. 21, no. 4, pp. 1933-1947.
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Fu, Q, Ranji-Burachaloo, H, Liu, M, McKenzie, TG, Tan, S, Reyhani, A, Nothling, MD, Dunstan, DE & Qiao, GG 2018, 'Controlled RAFT polymerization facilitated by a nanostructured enzyme mimic', Polymer Chemistry, vol. 9, no. 35, pp. 4448-4454.
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A nanostructured MOF composite was utilized as an enzyme mimic for the generation of hydroxyl radicals from hydrogen peroxide, which can subsequently initiate RAFT polymerizations in aqueous or organic media.
Fujioka, T, Hoang, A, Okuda, T, Takeuchi, H, Tanaka, H & Nghiem, L 2018, 'Water Reclamation Using a Ceramic Nanofiltration Membrane and Surface Flushing with Ozonated Water', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 799-799.
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A new membrane fouling control technique using ozonated water flushing was evaluated for direct nanofiltration (NF) of secondary wastewater effluent using a ceramic NF membrane. Experiments were conducted at a permeate flux of 44 L/m²h to evaluate the ozonated water flushing technique for fouling mitigation. Surface flushing with clean water did not effectively remove foulants from the NF membrane. In contrast, surface flushing with ozonated water (4 mg/L dissolved ozone) could effectively remove most foulants to restore the membrane permeability. This surface flushing technique using ozonated water was able to limit the progression of fouling to 35% in transmembrane pressure increase over five filtration cycles. Results from this study also heighten the need for further development of ceramic NF membrane to ensure adequate removal of pharmaceuticals and personal care products (PPCPs) for water recycling applications. The ceramic NF membrane used in this study showed approximately 40% TOC rejection, and the rejection of PPCPs was generally low and highly variable. It is expected that the fouling mitigation technique developed here is even more important for ceramic NF membranes with smaller pore size and thus better PPCP rejection.
Fujioka, T, Kodamatani, H, Takeuchi, H, Tanaka, H & Nghiem, LD 2018, 'Online monitoring of N-nitrosodimethylamine for the removal assurance of 1,4-dioxane and other trace organic compounds by reverse osmosis', Environmental Science: Water Research & Technology, vol. 4, no. 12, pp. 2021-2028.
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Online monitoring of N-nitrosodimethylamine (NDMA) during reverse osmosis (RO) treatment was effective in ensuring the removal of trace organic chemicals, particularly 1,4-dioxane.
Fujioka, T, Nguyen, K, Hoang, A, Ueyama, T, Yasui, H, Terashima, M & Nghiem, L 2018, 'Biofouling Mitigation by Chloramination during Forward Osmosis Filtration of Wastewater', International Journal of Environmental Research and Public Health, vol. 15, no. 10, pp. 2124-2124.
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Pre-concentration is essential for energy and resource recovery from municipal wastewater. The potential of forward osmosis (FO) membranes to pre-concentrate wastewater for subsequent biogas production has been demonstrated, although biofouling has also emerged as a prominent challenge. This study, using a cellulose triacetate FO membrane, shows that chloramination of wastewater in the feed solution at 3–8 mg/L residual monochloramine significantly reduces membrane biofouling. During a 96-h pre-concentration, flux in the chloraminated FO system decreased by only 6% and this flux decline is mostly attributed to the increase in salinity (or osmotic pressure) of the feed due to pre-concentration. In contrast, flux in the non-chloraminated FO system dropped by 35% under the same experimental conditions. When the feed was chloraminated, the number of bacterial particles deposited on the membrane surface was significantly lower compared to a non-chloraminated wastewater feed. This study demonstrated, for the first time, the potential of chloramination to inhibit bacteria growth and consequently biofouling during pre-concentration of wastewater using a FO membrane.
Fujioka, T, O'Rourke, BE, Michishio, K, Kobayashi, Y, Oshima, N, Kodamatani, H, Shintani, T & Nghiem, LD 2018, 'Transport of small and neutral solutes through reverse osmosis membranes: Role of skin layer conformation of the polyamide film', Journal of Membrane Science, vol. 554, pp. 301-308.
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© 2018 Elsevier B.V. The polyamide skin layer of reverse osmosis (RO) membranes was characterised using advanced and complementary analytical techniques to investigate the mechanisms underlying the permeation of contaminants of emerging concern in potable water reuse – N-nitrosodimethylamine (NDMA) and N-nitrosomethylethylamine (NMEA). This study used five RO membrane samples with similar membrane properties. The five RO membrane samples spanned over a large range of water permeance (0.9–5.8 L/m2 h bar) as well as permeation of NDMA (9–66%) and NMEA (3–29%). Despite these differences among the five RO membranes, characterisations of the skin layer using positron annihilation lifetime spectroscopy, atomic force microscopy and field emission scanning electron microscopy revealed almost no variation in their free-volume hole-radius (0.270–0.275 nm), effective surface area (198–212%) and thickness (30–35 nm) of the skin layer. The results suggest that there could be other RO skin layer properties, such as the interconnectivity of the protuberances within the polyamide skin layer additional to the free-volume hole-size and thickness of the skin layer, which can also govern water and solute permeation.
Galvao, JR, Biffe Di Renzo, A, Esber Schaphauser, P, Dutra, G, Dreyer, UJ, Kalinowski, A, Canning, J, Zamarreno, CR, Cardozo da Silva, JC & Martelli, C 2018, 'Optical Fiber Bragg Grating Instrumentation Applied to Horse Gait Detection', IEEE Sensors Journal, vol. 18, no. 14, pp. 5778-5785.
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© 2001-2012 IEEE. This paper presents two in vivo instrumentation techniques to study the different types of gait of horses performing athletics using fiber Bragg gratings (FBG). These techniques can be used as an auxiliary tool in the early diagnosis of injuries related to the horse's locomotor system, mainly in the distal portion of the digit, one of the most common causes of retirement when they are athletes. Therefore, the first technique presented consists of the fixation of FBGs without encapsulation, directly on the dorsal wall of the hoof in each of the limbs. In the second technique presented, the FBG sensor is encapsulated in a prototype developed using a composite material reinforced with carbon fiber in a horseshoe shape. The second technique is associated with digital image processing (DIP) for better visualization of the deformation and compression forces that act upon the limbs. The first method showed sensitivity to detection of the digit compression against the ground, being able to identify walking patterns. The second technique, with the encapsulated sensor elements, also allows the capture of characteristic signals of gait, such as step walk, trot, and gallop under training conditions. Both, FBG sensor interrogation and DIP, analysis techniques have proven good performance and promising results for the clinical and biomechanical study and medical evaluations of horses even during dynamic training and competitions.
Gan, YY, Ong, HC, Ling, TC, Zulkifli, NWM, Wang, C-T & Yang, Y-C 2018, 'Thermal conductivity optimization and entropy generation analysis of titanium dioxide nanofluid in evacuated tube solar collector', Applied Thermal Engineering, vol. 145, pp. 155-164.
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Gan, YY, Ong, HC, Show, PL, Ling, TC, Chen, W-H, Yu, KL & Abdullah, R 2018, 'Torrefaction of microalgal biochar as potential coal fuel and application as bio-adsorbent', Energy Conversion and Management, vol. 165, pp. 152-162.
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Gandomi, AH & Alavi, AH 2018, 'Metaheuristics in Reliability and Risk Analysis', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 4, no. 3, pp. 02018001-02018001.
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Gandomi, AH & Goldman, BW 2018, 'Parameter-less population pyramid for large-scale tower optimization', Expert Systems with Applications, vol. 96, pp. 175-184.
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Gandomi, AH & Kashani, AR 2018, 'Automating pseudo-static analysis of concrete cantilever retaining wall using evolutionary algorithms', Measurement, vol. 115, pp. 104-124.
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Gandomi, AH & Kashani, AR 2018, 'Construction Cost Minimization of Shallow Foundation Using Recent Swarm Intelligence Techniques', IEEE Transactions on Industrial Informatics, vol. 14, no. 3, pp. 1099-1106.
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Gandomi, AH & Kashani, AR 2018, 'Probabilistic evolutionary bound constraint handling for particle swarm optimization', Operational Research, vol. 18, no. 3, pp. 801-823.
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Gao, H, Li, Y, Wang, S, Zhu, J, Yang, Q, Zhang, C & Li, J 2018, 'Losses analysis of soft magnetic ring core under sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) excitations', AIP Advances, vol. 8, no. 5, pp. 056638-056638.
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Gao, J, Li, H, Luo, Z, Gao, L & Li, P 2018, 'Topology optimization of micro-structured materials featured with the specific mechanical properties', International Journal of Computational Methods, vol. 15, no. 8.
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Micro-structured materials consisting of an array of microstructures are
engineered to provide the specific material properties. This present work
investigates the design of cellular materials under the framework of level set,
so as to optimize the topologies and shapes of these porous material
microstructures. Firstly, the energy-based homogenization method (EBHM) is
applied to evaluate the material effective properties based on the topology of
the material cell, where the effective elasticity property is evaluated by the
average stress and strain theorems. Secondly, a parametric level set method
(PLSM) is employed to optimize the microstructural topology until the specific
mechanical properties can be achieved, including the maximum bulk modulus, the
maximum shear modulus and their combinations, as well as the negative Poisson's
ratio (NPR). The complicated topological shape optimization of the material
microstructure has been equivalent to evolve the sizes of the expansion
coefficients in the interpolation of the level set function. Finally, several
numerical examples are fully discussed to demonstrate the effectiveness of the
developed method. A series of new and interesting material cells with the
specific mechanical properties can be found.
Gao, K, Gao, W, Wu, B, Wu, D & Song, C 2018, 'Nonlinear primary resonance of functionally graded porous cylindrical shells using the method of multiple scales', Thin-Walled Structures, vol. 125, pp. 281-293.
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© 2017 Elsevier Ltd An analytical method is proposed for the nonlinear primary resonance analysis of cylindrical shells made of functionally graded (FG) porous materials subjected to a uniformly distributed harmonic load including the damping effect. The Young's modulus, shear modulus and density of porous materials are assumed to vary through the thickness direction based on the assumption of a common mechanical feature of the open-cell foam. Three types of FG porous distributions, namely symmetric porosity distribution, non-symmetric porosity stiff or soft distribution and uniform porosity distribution are considered in this paper. Theoretical formulations are derived based on Donnell shell theory (DST) and accounting for von-Kármán strain-displacement relation and damping effect. The first mode of deflection function that satisfies the boundary conditions is introduced into this nonlinear governing partial differential equation and then a Galerkin-based procedure is utilized to obtain a Duffing-type nonlinear ordinary differential equation with a cubic nonlinear term. Finally, the governing equation is solved analytically by conducting the method of multiple scales (MMS) which results in frequency-response curves of FG porous cylindrical shells in the presence of damping effect. The detailed parametric studies on porosity distribution, porosity coefficient, damping ratio, amplitude and frequency of the external harmonic excitation, aspect ratio and thickness ratio, shown that the distribution type of FG porous cylindrical shells significantly affects primary resonance behavior and the response presents a hardening-type nonlinearity, which provides a useful help for the design and optimize of FG porous shell-type devices working under external harmonic excitation.
Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic buckling of the imperfect orthotropic E-FGM circular cylindrical shells subjected to the longitudinal constant velocity', International Journal of Mechanical Sciences, vol. 138-139, pp. 199-209.
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In this study, an analytical approach on the nonlinear dynamic buckling of the orthotropic circular cylindrical shells made of exponential law functionally graded material (E-FGM) subjected to the longitudinal constant velocity is investigated with the incorporation of mercurial damping effect. The material properties are assumed to vary gradually in the thickness direction according to an exponential distribution function of the volume fraction of constituent materials. Theoretical formulations are derived based on improved Donnell shell theory (DST) and accounting for von-Kármán strain–displacement relation, initial imperfection and damping effect. By applying Galerkin method and Airy's stress function, the obtained nonlinear differential equations are solved numerically by the fourth-order Runge–Kutta method. The nonlinear dynamic stability of the orthotropic FG cylindrical shell is assessed based on Budiansky–Roth criterion. Additionally, a parametric study is conducted to demonstrate the effects of various velocities, initial imperfections, damping ratios, inhomogeneous parameters on nonlinear dynamic buckling behavior of an imperfect orthotropic FG cylindrical shell. Comparing results with those in other publications validates the proposed method.
Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic stability of the orthotropic functionally graded cylindrical shell surrounded by Winkler-Pasternak elastic foundation subjected to a linearly increasing load', Journal of Sound and Vibration, vol. 415, pp. 147-168.
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This paper focuses on the dynamic stability behaviors of the functionally graded (FG) orthotropic circular cylindrical shell surrounded by the two-parameter (Winkler-Pasternak) elastic foundation subjected to a linearly increasing load with the consideration of damping effect. The material properties are assumed to vary gradually in the thickness direction based on an exponential distribution function of the volume fraction of constituent materials. Equations of motion are derived from Hamilton's principle and the nonlinear compatibility equation is considered by the means of modified Donnell shell theory including large deflection. Then the nonlinear dynamic buckling equation is solved by a hybrid analytical-numerical method (combined Galerkin method and fourth-order Runge-Kutta method). The nonlinear dynamic stability of the FG orthotropic cylindrical shell is assessed based on Budiansky-Roth criterion. Additionally, effects of different parameters such as various inhomogeneous parameters, loading speeds, damping ratios and aspect ratios and thickness ratios of the structure on dynamic buckling are discussed in details. Finally, the proposed method is validated with published literature.
Gao, L, Chen, J, Liu, Y, Yamauchi, Y, Huang, Z & Kong, X 2018, 'Revealing the chemistry of an anode-passivating electrolyte salt for high rate and stable sodium metal batteries', Journal of Materials Chemistry A, vol. 6, no. 25, pp. 12012-12017.
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A compact and conductive solid-electrolyte interphase formed by NaDFOB enables high performance of sodium metal batteries.
Gao, W, Wu, D, Gao, K, Chen, X & Tin-Loi, F 2018, 'Structural reliability analysis with imprecise random and interval fields', Applied Mathematical Modelling, vol. 55, pp. 49-67.
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This paper investigates the issue of reliability assessment for engineering structures involving mixture of stochastic and non-stochastic uncertain parameters through the Finite Element Method (FEM). Non-deterministic system inputs modelled by both imprecise random and interval fields have been incorporated, so the applicability of the structural reliability analysis scheme can be further promoted to satisfy the intricate demand of modern engineering application. The concept of robust structural reliability profile for systems involving hybrid uncertainties is discussed, and then a new computational scheme, namely the unified interval stochastic reliability sampling (UISRS) approach, is proposed for assessing the safety of engineering structures. The proposed method provides a robust semi-sampling scheme for assessing the safety of engineering structures involving multiple imprecise random fields with various distribution types and interval fields simultaneously. Various aspects of structural reliability analysis with multiple imprecise random and interval fields are explored, and some theoretically instructive remarks are also reported herein.
Gao, W, Zhang, Q, Lu, Z, Wu, D & Du, X 2018, 'Modelling and application of fuzzy adaptive minimum spanning tree in tourism agglomeration area division', Knowledge-Based Systems, vol. 143, pp. 317-326.
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© 2017 Elsevier B.V. Tourism agglomeration area division plays an increasingly important role in government's policy making on planning and development of tourism industry nowadays. With the development of ICT technologies, tourism “big data” such as geographic data, tourist attractions evaluation data, tourist service data and related traffic information, becomes available to access, which provides great opportunities to develop intelligent tourism decision support systems (TDSS) for related government policy making. To effectively divide tourism agglomeration areas to support tourism-planning decision, by use of the “big data” resources, a fuzzy adaptive minimum spanning tree (F-AMST) model, which integrates adaptive minimum spanning tree (AMST) method and fuzzy level evaluation method, is proposed in this study. The F-AMST model consists of three parts: F-MST generation, F-MST splitting, and clustering solution evaluation and adjustment. The proposed model is then applied to cluster 142 A-level scenic spots in mountain areas of Hebei province, China, and the optimal tourism clustering solution with seven tourism agglomeration areas is finally obtained. The result is then analysed from the following aspects: the spatial agglomeration degree of each tourism agglomeration area is analysed by use of the fuzzy dense degree based on F-AMST model; the spatial distribution type of scenic spot nodes within each agglomeration area is analysed by using the nearest neighbour index R with consideration of spatial distance factors; the scenic spot node level system of each agglomeration area is analysed by use of the node level perfection index Z considering the scenic spot node level factor; the influences of the two factors, the spatial distance and the scenic spot node level, to the agglomeration degree are then analysed by use of the correlation between R and fuzzy dense degree and that between Z and fuzzy dense degree respectively. The findings are carefully described ...
Gao, X, Zhang, T, Du, J & Guo, YJ 2018, 'Design, modelling and simulation of a monolithic high-T c superconducting terahertz mixer', Superconductor Science and Technology, vol. 31, no. 11, pp. 115010-115010.
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Gardner, A & Willey, K 2018, 'Academic identity reconstruction: the transition of engineering academics to engineering education researchers', Studies in Higher Education, vol. 43, no. 2, pp. 234-250.
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The field of research (FoR) that an academic participates in is both a manifestation of, and a contributor to the development of their identity. When an academic changes that FoR the question then arises as to how they reconcile this change with their identity. This paper uses the identity-trajectory framework to analyse the discourse of 19 engineering academics in relation to their educational research. The findings reveal insights into the identity changes experienced in the transition from typical engineering academic to engineering education researcher. Participants’ responses illustrate how various aspects of their research activities contribute to the development of the networking and intellectual strands of their academic identity as engineering education researchers, and the effect of their university environment on this development. Conference participation was found to be an important contributor to progression of the intellectual and networking strands of identity-trajectory for researchers at all stages of development, although for different reasons.
Gatsios, E, García-Rincón, J, Rayner, JL, McLaughlan, RG & Davis, GB 2018, 'LNAPL transmissivity as a remediation metric in complex sites under water table fluctuations', Journal of Environmental Management, vol. 215, pp. 40-48.
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Water table fluctuations affect the recoverability of light non-aqueous phase liquid (LNAPL) petroleum hydrocarbons. LNAPL transmissivity (Tn) is being applied as an improved metric for LNAPL recoverability. In this paper, the applicability of Tn as a lagging and leading metric in unconsolidated aquifers under variable water table conditions was investigated. Tn values obtained through baildown testing and recovery data-based methods (skimming) were compared in three areas of a heterogeneous gasoline contaminated site in Western Australia. High-resolution characterisation methods were applied to account for differences in the stratigraphic profile and LNAPL distribution. The results showed a range of Tn from 0 m2/day to 2.13 m2/day, exhibiting a strong spatial and temporal variability. Additionally, observations indicated that Tn reductions may be more affected by the potentiometric surface elevation (Zaw) than by the application of mass recovery technologies. These observations reflected limitations of Tn as a lagging metric and a Remedial Endpoint. On the other hand, the consistency and accuracy of Tn as a leading metric was affected by the subsurface conditions. For instance, the area with a larger vertical LNAPL distribution and higher LNAPL saturations found Tn to be less sensitive to changes in Zaw than the other two areas during the skimming trials. Tn values from baildown and skimming tests were generally in a close agreement (less than a factor of 2 difference), although higher discrepancies (by a factor up to 7.3) were found, probably linked to a preferential migration pathway and Zaw. Under stable Zaw, Tn was found to be a relatively reliable metric. However, variable water table conditions affected Tn and caution should be exercised in such scenarios. Consequently, remediation practitioners, researchers and regulators should account for the nexus between Tn, LNAPL distribution, geological setting and temporal effects for a more efficient and sustainab...
Gaviria-Marin, M, Merigo, JM & Popa, S 2018, 'Twenty years of theJournal of Knowledge Management: a bibliometric analysis', Journal of Knowledge Management, vol. 22, no. 8, pp. 1655-1687.
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PurposeIn 2017, theJournal of Knowledge Management(JKM) celebrates its 20th anniversary. This study aims to show an updated analysis of their publications to provide a general overview of the journal, focusing on a bibliometric analysis of its publications between 1997 and 2016.Design/methodology/approachThe methodology involves two procedures: a performance analysis and a science mapping analysis of JKM. The performance analysis uses a series of bibliometric indicators such ash-index, productivity and citations. This analysis considers different dimensions, including papers, authors, universities and countries. VOSviewer software is used to carry out the mapping of science of JKM, which, based on the concurrence of key words and co-citation points of view, seeks to graphically analyze the structure of the references of this journal.FindingsThere is a positive evolution in the number of publications (although with certain oscillations), which shows a growing interest in publishing in JKM. The USA and the UK lead the publications in this journal, although at a regional level, Europe is the most productive. The low participation of emerging economies in JKM is also observed.Practical implicationsThe paper will identify the leading trends in the journal in terms of papers, authors, institutions, countries, journals and keywords. This study is useful for obtaining a quick snapshot of what is happening in the journal.Originality/valueFrom the historical ...
Gentile, C, Kesteven, S, Wu, J, Bursill, C, Davies, M, Feneley, M & Figtree, G 2018, 'Endothelial nitric oxide synthase plays a protective role against myocardial infarction', Free Radical Biology and Medicine, vol. 128, pp. S26-S26.
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George, L, Lehmann, T & Hamilton, TJ 2018, 'A reconfigurable dual-output buck-boost switched-capacitor converter using adaptive gain and discrete frequency scaling control', Microelectronics Journal, vol. 73, pp. 59-74.
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Ghabrial, A, Franklin, D & Zaidi, H 2018, 'A Monte Carlo simulation study of the impact of novel scintillation crystals on performance characteristics of PET scanners', Physica Medica, vol. 50, pp. 37-45.
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The purpose of this study is to validate a Monte Carlo simulation model for the clinical Siemens Biograph mCT PET scanner using the GATE simulation toolkit, and to evaluate the performance of six different scintillation materials in this model using the National Electrical Manufactures Association (NEMA) NU 2-2007 protocol.A model of the Biograph mCT PET detection system and its geometry was developed. NEMA NU 2-2007 phantoms were also modelled. The accuracy of the developed scanner model was validated through a comparison of the simulation results from GATE, SimSET and PeneloPET toolkits, and experimental data obtained using the NEMA NU 2-2007 protocols. The evaluated performance metrics included count rate performance, spatial resolution, sensitivity, and scatter fraction (SF). Thereafter, the mCT PET scanner was simulated with six different candidate high-performance scintillation materials, including LSO, LaBr3, CeBr3, LuAP, GLuGAG and LFS-3, and its performance evaluated according to the NEMA NU 2-2007 specifications.The Monte Carlo simulation model demonstrates good agreement with the experimental data and results from other simulation packages. For instance, the scatter fraction calculated using GATE simulation is 34.35% while the experimentally measured value is 33.2%, 38.48% for the SimSET, and 34.8% for the PeneloPET toolkit. The best-performing scintillation materials were found to be LuAP, LSO and LFS-3, while GLuGAG offers acceptable performance if cost is the dominant concern.The main performance characteristics of the Biograph mCT PET scanner can be simulated accurately using GATE with a good agreement with other Monte Carlo simulation packages and experimental measurements. Newly developed scintillators show promise and offer alternative options for the design of novel generation PET scanners.
Ghaffari Jadidi, M, Valls Miro, J & Dissanayake, G 2018, 'Gaussian processes autonomous mapping and exploration for range-sensing mobile robots', Autonomous Robots, vol. 42, no. 2, pp. 273-290.
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© 2017, Springer Science+Business Media, LLC. Most of the existing robotic exploration schemes use occupancy grid representations and geometric targets known as frontiers. The occupancy grid representation relies on the assumption of independence between grid cells and ignores structural correlations present in the environment. We develop a Gaussian processes (GPs) occupancy mapping technique that is computationally tractable for online map building due to its incremental formulation and provides a continuous model of uncertainty over the map spatial coordinates. The standard way to represent geometric frontiers extracted from occupancy maps is to assign binary values to each grid cell. We extend this notion to novel probabilistic frontier maps computed efficiently using the gradient of the GP occupancy map. We also propose a mutual information-based greedy exploration technique built on that representation that takes into account all possible future observations. A major advantage of high-dimensional map inference is the fact that such techniques require fewer observations, leading to a faster map entropy reduction during exploration for map building scenarios. Evaluations using the publicly available datasets show the effectiveness of the proposed framework for robotic mapping and exploration tasks.
Ghanbarikarekani, M, Qu, X, Zeibots, M & Qi, W 2018, 'Minimizing the Average Delay at Intersections via Presignals and Speed Control', Journal of Advanced Transportation, vol. 2018, pp. 1-8.
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Urban intersections have been well recognized as bottlenecks of urban transport systems. It is thus important to propose and implement strategies for increasing the efficiency of public and private transportation systems as a whole. In order to achieve this goal, an additional signal could be set up near the intersection to give priority to buses through stopping vehicles in advance of the main intersection as a presignal. It has been increasingly popular in urban cities. While presignals indeed reduce the average delay per traveler, they cause extra stops of private vehicles, which might compromise the overall efficiency, safety, and sustainability. This paper aims to propose a model to improve presignals by reducing the vehicles’ number of stops behind the presignals. By applying the method, vehicles would be able to adjust their speed based on traffic conditions as well as buses’ speed and approach. Numerical analyses have been conducted to determine the conditions required for implementing this method.
Gharehbaghi, S, Gandomi, AH, Achakpour, S & Omidvar, MN 2018, 'A hybrid computational approach for seismic energy demand prediction', Expert Systems with Applications, vol. 110, pp. 335-351.
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Ghasemi, K, Pradhan, B & Jena, R 2018, 'Spatial Identification of Key Alteration Minerals Using ASTER and Landsat 8 Data in a Heavily Vegetated Tropical Area', Journal of the Indian Society of Remote Sensing, vol. 46, no. 7, pp. 1061-1073.
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© 2018, Indian Society of Remote Sensing. The Central Gold Belt (CGB) of Malaysia is a major host to gold deposits. Penjom, Raub, Selising and Buffalo reef are major gold mines in CGB. The study area, Selinsing gold mine, is located at the northwest of Pahang province on the lineament known as the Raub Bentong Suture. Presence of dense vegetation and cloud cover in tropical regions are main obstacles in alteration mapping using satellite imageries. In this study, Landsat 8 and ASTER level 1B images were used to map clay minerals and quartz rich zones at Selinsing gold mine and surrounding areas. Direct principal component analysis (DPCA), matched filtering (MF) and band ratio were the effective methods used in this study. High concentration of clay minerals was detected using band ratio 6/7, DPC2 and MF and ratio 14/12 was carried out to highlight quartz rich zones. The results of image processing methods were verified by in situ inspection and X-ray diffraction analyses. The results show that, in spite of limited bedrock exposure, the known gold prospects and potential areas of mineralization can be recognized by the methods employed in this study.
Ghasemi, M, Ghavidel, S, Aghaei, J, Akbari, E & Li, L 2018, 'CFA optimizer: A new and powerful algorithm inspired by Franklin's and Coulomb's laws theory for solving the economic load dispatch problems', International Transactions on Electrical Energy Systems, vol. 28, no. 5, pp. e2536-e2536.
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Copyright © 2018 John Wiley & Sons, Ltd. This paper presents a new efficient algorithm inspired by Franklin's and Coulomb's laws theory that is referred to as CFA algorithm, for finding the global solutions of optimal economic load dispatch problems in power systems. CFA is based on the impact of electrically charged particles on each other due to electrical attraction and repulsion forces. The effectiveness of the CFA in different terms is tested on basic benchmark problems. Then, the quality of the CFA to achieve accurate results in different aspects is examined and proven on economic load dispatch problems including 4 different size cases, 6, 10, 15, and 110-unit test systems. Finally, the results are compared with other inspired algorithms as well as results reported in the literature. The simulation results provide evidence for the well-organized and efficient performance of the CFA algorithm in solving great diversity of nonlinear optimization problems.
Ghavidel, S, Azizivahed, A & Li, L 2018, 'A hybrid Jaya algorithm for reliability–redundancy allocation problems', Engineering Optimization, vol. 50, no. 4, pp. 698-715.
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This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching–learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability–redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series–parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30–100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.
Gheisari, S, Catchpoole, D, Charlton, A, Melegh, Z, Gradhand, E & Kennedy, P 2018, 'Computer Aided Classification of Neuroblastoma Histological Images Using Scale Invariant Feature Transform with Feature Encoding', Diagnostics, vol. 8, no. 3, pp. 56-56.
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Neuroblastoma is the most common extracranial solid malignancy in early childhood. Optimal management of neuroblastoma depends on many factors, including histopathological classification. Although histopathology study is considered the gold standard for classification of neuroblastoma histological images, computers can help to extract many more features some of which may not be recognizable by human eyes. This paper, proposes a combination of Scale Invariant Feature Transform with feature encoding algorithm to extract highly discriminative features. Then, distinctive image features are classified by Support Vector Machine classifier into five clinically relevant classes. The advantage of our model is extracting features which are more robust to scale variation compared to the Patched Completed Local Binary Pattern and Completed Local Binary Pattern methods. We gathered a database of 1043 histologic images of neuroblastic tumours classified into five subtypes. Our approach identified features that outperformed the state-of-the-art on both our neuroblastoma dataset and a benchmark breast cancer dataset. Our method shows promise for classification of neuroblastoma histological images.
Gheisari, S, Catchpoole, DR, Charlton, A & Kennedy, PJ 2018, 'Convolutional Deep Belief Network with Feature Encoding for Classification of Neuroblastoma Histological Images', Journal of Pathology Informatics, vol. 9, no. 1, pp. 17-17.
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Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification.We apply a combination of convolutional deep belief network (CDBN) with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier.We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors.The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods.The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.
Ghorbani, S, Eyni, H, Bazaz, SR, Nazari, H, Asl, LS, Zaferani, H, Kiani, V, Mehrizi, AA & Soleimani, M 2018, 'Hydrogels Based on Cellulose and its Derivatives: Applications, Synthesis, and Characteristics', Polymer Science, Series A, vol. 60, no. 6, pp. 707-722.
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Ghorbani, S, Eyni, H, Tiraihi, T, Salari Asl, L, Soleimani, M, Atashi, A, Pour Beiranvand, S & Ebrahimi Warkiani, M 2018, 'Combined effects of 3D bone marrow stem cell-seeded wet-electrospun poly lactic acid scaffolds on full-thickness skin wound healing', International Journal of Polymeric Materials and Polymeric Biomaterials, vol. 67, no. 15, pp. 905-912.
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© 2017 Taylor & Francis. Tissue engineering has emerged as an alternative treatment to traditional grafts for skin wound healing. Three-dimensional nanofibers have been used extensively for this purpose due to their excellent biomedical-related properties. In this study, high porous 3D poly lactic acid nanofibrous scaffolds (PLA-S) were prepared by wet-electrospinning technique and seeded with rat bone-marrow stem cells (BMSCs) to characterize the biocompatibility and therapeutic efficacy of these fibers on the treating full-thickness dermal wounds. The results of in vitro andin vivo studies indicate that the 3D fibrous PLA-S can be a potential wound dressing for wound repair, particularly when seeded with BMSCs. GRAPHICAL ABSTRACT.
Giarmatzi, C & Costa, F 2018, 'Witnessing quantum memory in non-Markovian processes', Quantum, vol. 5, p. 440.
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We present a method to detect quantum memory in a non-Markovian process. We
call a process Markovian when the environment does not provide a memory that
retains correlations across different system-environment interactions. We
define two types of non-Markovian processes, depending on the required memory
being classical or quantum. We formalise this distinction using the process
matrix formalism, through which a process is represented as a multipartite
state. Within this formalism, a test for entanglement in a state can be mapped
to a test for quantum memory in the corresponding process. This allows us to
apply separability criteria and entanglement witnesses to the detection of
quantum memory. We demonstrate the method in a simple model where both system
and environment are single interacting qubits and map the parameters that lead
to quantum memory. As with entanglement witnesses, our method of witnessing
quantum memory provides a versatile experimental tool for open quantum systems.
Gill, AQ, Henderson-Sellers, B & Niazi, M 2018, 'Scaling for agility: A reference model for hybrid traditional-agile software development methodologies', Information Systems Frontiers, vol. 20, no. 2, pp. 315-341.
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The adoption of agility at a large scale often requires the integration of agile and non-agile development elements for architecting a hybrid adaptive methodology. The challenge is ”which elements or components (agile or non-agile) are relevant to develop the context-aware hybrid adaptive methodology reference architecture?” This paper addresses this important challenge and develops a hybrid adaptive methodology reference architecture model using a qualitative constructive empirical research approach. In this way, we have uncovered the agility, abstraction, business value, business policy, rules, legal, context and facility elements or components that have not been explicitly modelled or discussed in International Standards (IS) such as the ISO/IEC 24744 metamodel. It is anticipated that a context-aware hybrid adaptive methodology can be architected by using the proposed context-aware hybrid adaptive methodology reference architecture elements for a particular situation when using a situational method engineering approach.
Glynn, PD, Voinov, AA, Shapiro, CD & White, PA 2018, 'Response to Comment by Walker et al. on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments”', Earth's Future, vol. 6, no. 5, pp. 762-769.
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Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2018, 'A review of neural networks in plant disease detection using hyperspectral data', Information Processing in Agriculture, vol. 5, no. 3, pp. 354-371.
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© 2018 China Agricultural University This paper reviews advanced Neural Network (NN) techniques available to process hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a review on NN mechanism, types, models, and classifiers that use different algorithms to process hyperspectral data. Then we highlight the current state of imaging and non-imaging hyperspectral data for early disease detection. The hybridization of NN-hyperspectral approach has emerged as a powerful tool for disease detection and diagnosis. Spectral Disease Index (SDI) is the ratio of different spectral bands of pure disease spectra. Subsequently, we introduce NN techniques for rapid development of SDI. We also highlight current challenges and future trends of hyperspectral data.
Golkarian, A, Naghibi, SA, Kalantar, B & Pradhan, B 2018, 'Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS', Environmental Monitoring and Assessment, vol. 190, no. 3.
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Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.
Gong, B, Wang, S, Sloan, SW, Sheng, D & Tang, C 2018, 'Modelling Coastal Cliff Recession Based on the GIM–DDD Method', Rock Mechanics and Rock Engineering, vol. 51, no. 4, pp. 1077-1095.
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Gong, C, Li, Z, Chang, X & Luo, Y 2018, 'Learning-Based Multimedia Analyses and Applications', Advances in Multimedia, vol. 2018, pp. 1-2.
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Gong, L, Heitor, A & Indraratna, B 2018, 'An approach to measure infill matric suction of irregular infilled rock joints under constant normal stiffness shearing', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 4, pp. 653-660.
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Gong, Y, Zhao, D & Wang, Q 2018, 'An overview of field-scale studies on remediation of soil contaminated with heavy metals and metalloids: Technical progress over the last decade', Water Research, vol. 147, pp. 440-460.
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Soil contamination by heavy metals and metalloids has been a major concern to human health and environmental quality. While many remediation technologies have been tested at the bench scale, there have been only limited reports at the field scale. This paper aimed to provide a comprehensive overview on the field applications of various soil remediation technologies performed over the last decade or so. Under the general categories of physical, chemical, and biological approaches, ten remediation techniques were critically reviewed. The technical feasibility and economic effectiveness were evaluated, and the pros and cons were appraised. In addition, attention was placed to the environmental impacts of the remediation practices and long-term stability of the contaminants, which should be taken into account in the establishment of remediation goals and environmental criteria. Moreover, key knowledge gaps and practical challenges are identified.
Gonzales, R, Park, M, Tijing, L, Han, D, Phuntsho, S & Shon, H 2018, 'Modification of Nanofiber Support Layer for Thin Film Composite forward Osmosis Membranes via Layer-by-Layer Polyelectrolyte Deposition', Membranes, vol. 8, no. 3, pp. 70-70.
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Electrospun nanofiber-supported thin film composite membranes are among the most promising membranes for seawater desalination via forward osmosis. In this study, a high-performance electrospun polyvinylidenefluoride (PVDF) nanofiber-supported thin film composite (TFC) membrane was successfully fabricated after molecular layer-by-layer polyelectrolyte deposition. Negatively-charged electrospun polyacrylic acid (PAA) nanofibers were deposited on electrospun PVDF nanofibers to form a support layer consisted of PVDF and PAA nanofibers. This resulted to a more hydrophilic support compared to the plain PVDF nanofiber support. The PVDF-PAA nanofiber support then underwent a layer-by-layer deposition of polyethylenimine (PEI) and PAA to form a polyelectrolyte layer on the nanofiber surface prior to interfacial polymerization, which forms the selective polyamide layer of TFC membranes. The resultant PVDF-LbL TFC membrane exhibited enhanced hydrophilicity and porosity, without sacrificing mechanical strength. As a result, it showed high pure water permeability and low structural parameter values of 4.12 L m−2 h−1 bar−1 and 221 µm, respectively, significantly better compared to commercial FO membrane. Layer-by-layer deposition of polyelectrolyte is therefore a useful and practical modification method for fabrication of high performance nanofiber-supported TFC membrane.
Gonzalez Cruz, C, Naderpour, M & Ramezani, F 2018, 'Water resource selection and optimisation for shale gas developments in Australia: A combinatorial approach', Computers & Industrial Engineering, vol. 124, pp. 1-11.
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Goodswen, SJ, Kennedy, PJ & Ellis, JT 2018, 'A Gene-Based Positive Selection Detection Approach to Identify Vaccine Candidates Using Toxoplasma gondii as a Test Case Protozoan Pathogen', Frontiers in Genetics, vol. 9.
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Over the last two decades, various in silico approaches have been developed and refined that attempt to identify protein and/or peptide vaccines candidates from informative signals encoded in protein sequences of a target pathogen. As to date, no signal has been identified that clearly indicates a protein will effectively contribute to a protective immune response in a host. The premise for this study is that proteins under positive selection from the immune system are more likely suitable vaccine candidates than proteins exposed to other selection pressures. Furthermore, our expectation is that protein sequence regions encoding major histocompatibility complexes (MHC) binding peptides will contain consecutive positive selection sites. Using freely available data and bioinformatic tools, we present a high-throughput approach through a pipeline that predicts positive selection sites, protein subcellular locations, and sequence locations of medium to high T-Cell MHC class I binding peptides. Positive selection sites are estimated from a sequence alignment by comparing rates of synonymous (dS) and non-synonymous (dN) substitutions among protein coding sequences of orthologous genes in a phylogeny. The main pipeline output is a list of protein vaccine candidates predicted to be naturally exposed to the immune system and containing sites under positive selection. Candidates are ranked with respect to the number of consecutive sites located on protein sequence regions encoding MHCI-binding peptides. Results are constrained by the reliability of prediction programs and quality of input data. Protein sequences from Toxoplasma gondii ME49 strain (TGME49) were used as a case study. Surface antigen (SAG), dense granules (GRA), microneme (MIC), and rhoptry (ROP) proteins are considered worthy T. gondii candidates. Given 8263 TGME49 protein sequences processed anonymously, the top 10 predicted candidates were all worthy candidates. In particular, the top ten included ROP5 and...
Goswami, K, Giarmatzi, C, Kewming, M, Costa, F, Branciard, C, Romero, J & White, AG 2018, 'Indefinite Causal Order in a Quantum Switch', Phys. Rev. Lett., vol. 121, p. 090503.
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In quantum mechanics events can happen in no definite causal order: in
practice this can be verified by measuring a causal witness, in the same way
that an entanglement witness verifies entanglement. Indefinite causal order can
be observed in a quantum switch, where two operations act in a quantum
superposition of the two possible orders. Here we realise a photonic quantum
switch, where polarisation coherently controls the order of two operations,
$\hat{A}$ and $\hat{B}$, on the transverse spatial mode of the photons. Our
setup avoids the limitations of earlier implementations: the operations cannot
be distinguished by spatial or temporal position. We show that our quantum
switch has no definite causal order, by constructing a causal witness and
measuring its value to be 18 standard deviations beyond the definite-order
bound.
Gour, G, Jennings, D, Buscemi, F, Duan, R & Marvian, I 2018, 'Quantum majorization and a complete set of entropic conditions for quantum thermodynamics', Nature Communications, vol. 9, no. 1.
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AbstractWhat does it mean for one quantum process to be more disordered than another? Interestingly, this apparently abstract question arises naturally in a wide range of areas such as information theory, thermodynamics, quantum reference frames, and the resource theory of asymmetry. Here we use a quantum-mechanical generalization of majorization to develop a framework for answering this question, in terms of single-shot entropies, or equivalently, in terms of semi-definite programs. We also investigate some of the applications of this framework, and remarkably find that, in the context of quantum thermodynamics it provides the first complete set of necessary and sufficient conditions for arbitrary quantum state transformations under thermodynamic processes, which rigorously accounts for quantum-mechanical properties, such as coherence. Our framework of generalized thermal processes extends thermal operations, and is based on natural physical principles, namely, energy conservation, the existence of equilibrium states, and the requirement that quantum coherence be accounted for thermodynamically.
Govindan, K, Cheng, TCE, Mishra, N & Shukla, N 2018, 'Big data analytics and application for logistics and supply chain management', Transportation Research Part E: Logistics and Transportation Review, vol. 114, pp. 343-349.
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Gracia, L, Perez-Vidal, C & Valls-Miro, J 2018, 'Advanced Mathematical Methods for Collaborative Robotics', Mathematical Problems in Engineering, vol. 2018, pp. 1-3.
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Gracia, L, Solanes, JE, Muñoz-Benavent, P, Esparza, A, Valls Miro, J & Tornero, J 2018, 'Cooperative transport tasks with robots using adaptive non-conventional sliding mode control', Control Engineering Practice, vol. 78, pp. 35-55.
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© 2018 Elsevier Ltd This work presents a hybrid position/force control of robots aimed at handling applications using multi-task and sliding mode ideas. The proposed robot control is based on a novel adaptive non-conventional sliding mode control used to robustly satisfy a set of inequality constraints defined to accomplish the cooperative transport task. In particular, these constraints are used to guarantee the reference parameters imposed by the task (e.g., keeping the load at a desired orientation) and to guide the robot using the human operator's forces detected by a force sensor located at the robot tool. Another feature of the proposal is the multi-layered nature of the strategy, where a set of four tasks are defined with different priorities. The effectiveness of the proposed adaptive non-conventional sliding mode control is illustrated by simulation results. Furthermore, the applicability and feasibility of the proposed robot control for transport tasks are substantiated by experimental results using a redundant 7R manipulator.
Gracia, L, Solanes, JE, Muñoz-Benavent, P, Valls Miro, J, Perez-Vidal, C & Tornero, J 2018, 'Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback', Mechatronics, vol. 52, pp. 102-118.
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© 2018 Elsevier Ltd This work presents a hybrid position-force control of robots in order to apply surface treatments such as polishing, grinding, finishing, deburring, etc. The robot force control is designed using sliding mode concepts to benefit from robustness. In particular, the sliding mode force task is defined using equality constraints to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. In order to deal with sudden changes in material stiffness, which are ultimately transferred to the polishing tool and can produce instability and compromise polishing performance, several adaptive switching gain laws are considered and compared. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. Hence, deviations from the reference trajectory are allowed if such deviations are required to satisfy the constraints mentioned above. Finally, a third-level task is also considered for the case of redundant robots in order to use the remaining degrees of freedom to keep the manipulator close to the home configuration with safety in mind. The main advantages of the method are increased robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Rethink Robotics Sawyer collaborative robot.
Graham, C, Smith, W, Moncur, W & van den Hoven, E 2018, 'Introduction: Mortality in Design', Design Issues, vol. 34, no. 1, pp. 3-14.
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Gray, S, Voinov, A, Paolisso, M, Jordan, R, BenDor, T, Bommel, P, Glynn, P, Hedelin, B, Hubacek, K, Introne, J, Kolagani, N, Laursen, B, Prell, C, Schmitt Olabisi, L, Singer, A, Sterling, E & Zellner, M 2018, 'Purpose, processes, partnerships, and products: four Ps to advance participatory socio‐environmental modeling', Ecological Applications, vol. 28, no. 1, pp. 46-61.
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Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.
Gu, Y, Cui, Q, Chen, Y, Ni, W, Tao, X & Zhang, P 2018, 'Effective Capacity Analysis in Ultra-Dense Wireless Networks With Random Interference', IEEE Access, vol. 6, pp. 19499-19508.
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© 2013 IEEE. Ultra-dense networks (UDNs) provide a promising paradigm to cope with exponentially increasing mobile traffic. However, a little work has to date considered unsaturated traffic with Quality-of-Service (QoS) requirements. This paper presents a new cross-layer analytical model to capture the unsaturated traffic of a UDN in the presence of QoS requirements. The effiective capacity (EC) of the UDN is derived, taking into account small-scale channel fading and possible interference. Key properties of the EC are revealed. The amount of traffic impacts EC of the UDN due to the sophisticated interactions among small base stations operating in the same frequency. The maximization of total EC is formulated as a non-cooperative game in this paper. The best-response function is derived, iteratively searching the Nash equilibrium point. System simulation results indicate that our proposed model is accurate. The simulations also show the maximum allowed arrival rate with the QoS guarantee, compared with the full interference model.
Gu, Y, Gu, M, Long, Y, Xu, G, Yang, Z, Zhou, J & Qu, W 2018, 'An enhanced short text categorization model with deep abundant representation', World Wide Web, vol. 21, no. 6, pp. 1705-1719.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Short text categorization is a crucial issue to many applications, e.g., Information Retrieval, Question-Answering System, MRI Database Construction and so forth. Many researches focus on data sparsity and ambiguity issues in short text categorization. To tackle these issues, we propose a novel short text categorization strategy based on abundant representation, which utilizes Bi-directional Recurrent Neural Network(Bi-RNN) with Long Short-Term Memory(LSTM) and topic model to catch more contextual and semantic information. Bi-RNN enriches contextual information, and topic model discovers more latent semantic information for abundant text representation of short text. Experimental results demonstrate that the proposed model is comparable to state-of-the-art neural network models and method proposed is effective.
Gunawardane, K & Kularatna, N 2018, 'Supercapacitor‐assisted low dropout regulator technique: a new design approach to achieve high‐efficiency linear DC–DC converters', IET Power Electronics, vol. 11, no. 2, pp. 229-238.
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Guntuku, SC, Zhou, JT, Roy, S, Lin, W & Tsang, IW 2018, '‘Who Likes What and, Why?’ Insights into Modeling Users’ Personality Based on Image ‘Likes’', IEEE Transactions on Affective Computing, vol. 9, no. 1, pp. 130-143.
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The increased proliferation of data production technologies (e.g., cameras) and consumption avenues (e.g., social media) has led to images and videos being utilized by users to convey innate preferences and tastes. This has opened up the possibility of using multimedia as a source for user-modeling. This work attempts to model personality traits (based on the Five Factor Theory) of users using a collection of images they tag as ‘favorite’ (or like) on Flickr. First, a set of semantic features are proposed to be used for representing different concepts in images which influence users to like them. The addition of the proposed features led to improvement over state-of-the-art by 12 percent. Second, a novel machine learning approach is developed to model users’ personality based on the
image features (resulting in upto 15 percent improvement). Third, efficacy of the semantic features and the modeling approach is shown in recommending images based on personality modeling. Using the modeling approach, recommendations are made regarding the factors that might influence users with different personality traits to like an image.
Guo, J, Ren, W, Ren, Y & Zhu, T 2018, 'A Watermark-Based in-Situ Access Control Model for Image Big Data', Future Internet, vol. 10, no. 8, pp. 69-69.
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When large images are used for big data analysis, they impose new challenges in protecting image privacy. For example, a geographic image may consist of several sensitive areas or layers. When it is uploaded into servers, the image will be accessed by diverse subjects. Traditional access control methods regulate access privileges to a single image, and their access control strategies are stored in servers, which imposes two shortcomings: (1) fine-grained access control is not guaranteed for areas/layers in a single image that need to maintain secret for different roles; and (2) access control policies that are stored in servers suffers from multiple attacks (e.g., transferring attacks). In this paper, we propose a novel watermark-based access control model in which access control policies are associated with objects being accessed (called an in-situ model). The proposed model integrates access control policies as watermarks within images, without relying on the availability of servers or connecting networks. The access control for images is still maintained even though images are redistributed again to further subjects. Therefore, access control policies can be delivered together with the big data of images. Moreover, we propose a hierarchical key-role-area model for fine-grained encryption, especially for large size images such as geographic maps. The extensive analysis justifies the security and performance of the proposed model
Guo, J, Tan, Z-H, Cho, SH & Zhang, G 2018, 'Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet', Wireless Personal Communications, vol. 102, no. 3, pp. 2093-2098.
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Guo, J, Yang, T, Yuan, J & Zhang, JA 2018, 'A Novel Linear Physical-Layer Network Coding Scheme for Y-Channel Without Transmitter CSI', IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp. 10049-10053.
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© 1967-2012 IEEE. We propose a novel linear physical-layer network coding (NC) scheme for a fading Y-channel without channel state information at transmitters. In this three-user scheme, each user intends to realize a full data exchange with the other two users via a relay. Instead of directly decoding the users' messages from the received signal, the relay determines NC generator matrices and reconstructs linear NC codewords from its received signals to facilitate the information exchange. We present an explicit solution for NC generator matrices that minimize the NC error probability at high SNRs. We also present and prove an approximation of the NC error probability of the proposed scheme at high SNRs. Numerical results show that the proposed scheme outperforms existing ones, and its performance can be well characterized by the approximation.
Guo, J, Yuan, J & Zhang, J 2018, 'An Achievable Throughput Scaling Law of Wireless Device-to-Device Caching Networks With Distributed MIMO and Hierarchical Cooperations', IEEE Transactions on Wireless Communications, vol. 17, no. 1, pp. 492-505.
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© 2002-2012 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 neighbors 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 neighbors. 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. Furthermore, we derive an explicit expression of the optimal throughput as a function of system parameters, such as pathloss factor under a target outage probability. Analytical and numerical results demonstrate that our proposed scheme outperforms existing ones when the local cache size is limited.
Guo, Q, Zhang, Y, Celler, BG & Su, SW 2018, 'State-Constrained Control of Single-Rod Electrohydraulic Actuator With Parametric Uncertainty and Load Disturbance', IEEE Transactions on Control Systems Technology, vol. 26, no. 6, pp. 2242-2249.
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IEEE The suppression of disturbances under parametric uncertainties is one of the most common control problems in electrohydraulic systems, as both disturbances and uncertainties often significantly degrade the tracking performance and bias the load pressure of the electrohydraulic actuator (EHA). This brief presents a state-constrained control of single-rod EHA to restrict the position tracking error to a prescribed accuracy and guarantee the load pressure in the maximal power boundary. Furthermore, a dynamic surface is designed to avoid the explosion of complexity due to the repeatedly calculated differentiations of the virtual control variables in the backstepping iteration. Integrating with a disturbance observer and the parametric estimation law, this state-constrained controller guarantees the asymptotic convergence of system state error under parametric uncertainties and large load disturbances. The effectiveness of the proposed controller has been demonstrated by a comparative experiment on the motion control of the two-degree-of-freedom robotic arm.
Guo, Y, Xie, H, Zhang, J, Wang, W, Ngo, HH, Guo, W, Kang, Y & Zhang, B 2018, 'Improving nutrient removal performance of surface flow constructed wetlands in winter using hardy submerged plant-benthic fauna systems', RSC Advances, vol. 8, no. 73, pp. 42179-42188.
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A novel hardy submerged plant-benthic fauna systems to enhance the performance of surface flow constructed wetlands in winter.
Guo, YJ, Qin, P-Y, Chen, S-L, Lin, W & Ziolkowski, RW 2018, 'Advances in Reconfigurable Antenna Systems Facilitated by Innovative Technologies', IEEE Access, vol. 6, pp. 5780-5794.
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© 2013 IEEE. Future fifth generation (5G) wireless platforms will require reconfigurable antenna systems to meet their performance requirements in compact, light-weight, and cost-effective packages. Recent advances in reconfigurable radiating and receiving structures have been enabled by a variety of innovative technology solutions. Examples of reconfigurable partially reflective surface antennas, reconfigurable filtennas, reconfigurable Huygens dipole antennas, and reconfigurable feeding network-enabled antennas are presented and discussed. They represent novel classes of frequency, pattern, polarization, and beam-direction reconfigurable systems realized by the innovative combinations of radiating structures and circuit components.
Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie International Edition, vol. 57, no. 28, pp. 8493-8497.
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Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie, vol. 130, no. 28, pp. 8629-8633.
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H. Almabrok, M, G. McLaughlan, R & Vessalas, K 2018, 'EFFECT OF SYNTHETIC DRILL CUTTINGS ON MORTAR PROPERTIES', Malaysian Journal of Civil Engineering, vol. 30, no. 3, pp. 405-414.
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Drill cuttings from oil exploration are recognised as a major environmental concern. Current cost-effective treatment technologies often involve sending treated products to landfill without any potential end-use thereby rendering these solutions unsustainable. There is potential for using drill cuttings comprising of oily, saline and clayey waste materials as fine aggregate replacements in structural concretes requiring characteristic compressive strength from 20-32 MPa. Research into the hydration process as well as evaluating the fresh and hardened properties of mortars incorporating synthetic drill cuttings were undertaken. Replacement of sand by synthetic drill cuttings (up to 25% by weight) produced mortar with accelerated hydration as well as reduced flow and density. In addition, the 28-day compressive strength of mortar incorporating synthetic drill cuttings decreased by up to 50%. Satisfactory strength for all sand replacement levels evaluated in mortars was still attainable for reuse of these synthetic of drill cuttings as fine aggregate replacements in structural concretes.
Ha, Q, Royel, S & Balaguer, C 2018, 'Low-energy structures embedded with smart dampers', Energy and Buildings, vol. 177, pp. 375-384.
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Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation. Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and sup- pressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excitations validate the proposed technique for low-energy structures with smart devices. The closed-loop performance and comparison in terms of energy signals indicate that the pro- posed method allows not only to reduce induced vibrations and input energy, but also its spectrum can be adjusted to prevent natural modes of the structure under external excitations.
Halliday, BJ, Fukuzawa, R, Markie, DM, Grundy, RG, Ludgate, JL, Black, MA, Skeen, JE, Weeks, RJ, Catchpoole, DR, Roberts, AGK, Reeve, AE & Morison, IM 2018, 'Germline mutations and somatic inactivation of TRIM28 in Wilms tumour', PLOS Genetics, vol. 14, no. 6, pp. e1007399-e1007399.
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Han, B, Pan, Y & Tsang, IW 2018, 'Robust Plackett–Luce model for k-ary crowdsourced preferences', Machine Learning, vol. 107, no. 4, pp. 675-702.
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© 2017, The Author(s). The aggregation of k-ary preferences is an emerging ranking problem, which plays an important role in several aspects of our daily life, such as ordinal peer grading and online product recommendation. At the same time, crowdsourcing has become a trendy way to provide a plethora of k-ary preferences for this ranking problem, due to convenient platforms and low costs. However, k-ary preferences from crowdsourced workers are often noisy, which inevitably degenerates the performance of traditional aggregation models. To address this challenge, in this paper, we present a RObust PlAckett–Luce (ROPAL) model. Specifically, to ensure the robustness, ROPAL integrates the Plackett–Luce model with a denoising vector. Based on the Kendall-tau distance, this vector corrects k-ary crowdsourced preferences with a certain probability. In addition, we propose an online Bayesian inference to make ROPAL scalable to large-scale preferences. We conduct comprehensive experiments on simulated and real-world datasets. Empirical results on “massive synthetic” and “real-world” datasets show that ROPAL with online Bayesian inference achieves substantial improvements in robustness and noisy worker detection over current approaches.
Han, B, Tsang, IW, Chen, L, Yu, CP & Fung, S-F 2018, 'Progressive Stochastic Learning for Noisy Labels', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 10, pp. 5136-5148.
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Large-scale learning problems require a plethora of labels that can be efficiently collected from crowdsourcing services at low cost. However, labels annotated by crowdsourced workers are often noisy, which inevitably degrades the performance of large-scale optimizations including the prevalent stochastic gradient descent (SGD). Specifically, these noisy labels adversely affect updates of the primal variable in conventional SGD. To solve this challenge, we propose a robust SGD mechanism called progressive stochastic learning (POSTAL), which naturally integrates the learning regime of curriculum learning (CL) with the update process of vanilla SGD. Our inspiration comes from the progressive learning process of CL, namely learning from "easy" tasks to "complex" tasks. Through the robust learning process of CL, POSTAL aims to yield robust updates of the primal variable on an ordered label sequence, namely, from "reliable" labels to "noisy" labels. To realize POSTAL mechanism, we design a cluster of "screening losses," which sorts all labels from the reliable region to the noisy region. To sum up, POSTAL using screening losses ensures robust updates of the primal variable on reliable labels first, then on noisy labels incrementally until convergence. In theory, we derive the convergence rate of POSTAL realized by screening losses. Meanwhile, we provide the robustness analysis of representative screening losses. Experimental results on UCI1 simulated and Amazon Mechanical Turk crowdsourcing data sets show that the POSTAL using screening losses is more effective and robust than several existing baselines.1UCI is the abbreviation of University of California Irvine.
Han, C, Ding, Q, Zhang, L, Li, W, Wang, J, Gu, Q, Sun, Q, Furukawa, Y, Dou, S, Cheng, Z & Li, Z 2018, 'First Observation of Low-Temperature Magnetic Transition in CuAgSe', The Journal of Physical Chemistry C, vol. 122, no. 33, pp. 19139-19145.
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Han, C, Tan, G, Varghese, T, Kanatzidis, MG & Zhang, Y 2018, 'High-Performance PbTe Thermoelectric Films by Scalable and Low-Cost Printing', ACS Energy Letters, vol. 3, no. 4, pp. 818-822.
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Han, F, Wei, D, Ngo, HH, Guo, W, Xu, W, Du, B & Wei, Q 2018, 'Performance, microbial community and fluorescent characteristic of microbial products in a solid-phase denitrification biofilm reactor for WWTP effluent treatment', Journal of Environmental Management, vol. 227, pp. 375-385.
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Microbial products, i.e. extracellular polymeric substance (EPS) and soluble microbial product (SMP), have a significant correlation with microbial activity of biologically based systems. In present study, the spectral characteristics of two kinds of microbial products were comprehensively evaluated in a solid-phase denitrification biofilm reactor for WWTP effluent treatment by using poly (butylene succinate) (PBS) as carbon source. After the achievement of PBS-biofilm, nitrate and total nitrogen removal efficiencies were high of 97.39 ± 1.24% and 96.38 ± 1.1%, respectively. The contents of protein and polysaccharide were changed different degrees in both LB-EPS and TB-EPS. Excitation-emission matrix (EEM) implied that protein-like substances played a significant role in the formation of PBS-biofilm. High-throughput sequencing result implied that the proportion of denitrifying bacteria, including Simplicispira, Dechloromonas, Diaphorobacter, Desulfovibrio, increased to 9.2%, 7.4%, 4.8% and 3.6% in PBS-biofilm system, respectively. According to EEM-PARAFAC, two components were identified from SMP samples, including protein-like substances for component 1 and humic-like and fulvic acid-like substances for component 2, respectively. Moreover, the fluorescent scores of two components expressed significant different trends to reaction time. Gas chromatography-mass spectrometer (GC-MS) implied that some new organic matters were produced in the effluent of SP-DBR due to biopolymer degradation and denitrification processes. The results could provide a new insight about the formation and stability of solid-phase denitrification PBS-biofilm via the point of microbial products.
Han, L, Liu, S, Han, S, Jia, W & Lei, J 2018, 'Owner based malware discrimination', Future Generation Computer Systems, vol. 80, pp. 496-504.
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© 2016 Elsevier B.V. A piece of malware code can be harmful in one's system but totally harmless in another's. In this paper, we point out that the detection of malicious code or software is actually a matter of discrimination which depends on the owners of the computer systems. We propose an owner based malicious software discrimination model, named as Unlimited Register Machine of Owners (URMO). First, we characterize and analyze the limitations of existing discrimination techniques in theory by using the discrimination model of Unlimited Register Machine (URM) and then move on to construct the URMO discrimination model by giving the two important elements of malicious behavior: an operation and the object of the operation. The relationship between an operation and the object of the operation is fundamental to solving the relativity of the discrimination problem about malice, which is also the advantage of the URMO model. Finally, by applying the model to discriminate real-world malware and comparing it with existing popular antivirus software, we demonstrate the effectiveness and superior performance of the URMO model.
Han, W, Zhang, H-P, Tavakoli, J, Campbell, J & Tang, Y 2018, 'Polydopamine as sizing on carbon fiber surfaces for enhancement of epoxy laminated composites', Composites Part A: Applied Science and Manufacturing, vol. 107, pp. 626-632.
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Han, Z, Wu, M, Zhu, Q & Yang, J 2018, 'Two-dimensional multizone sound field reproduction using a wave-domain method', The Journal of the Acoustical Society of America, vol. 144, no. 3, pp. EL185-EL190.
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This paper addresses a two-dimensional multizone sound field reproduction approach using a wave-domain method. The desired sound fields in the bright and dark zones are described as orthogonal expansions of basis functions over the regions. The loudspeaker weights are obtained by maximizing the contrast among multiple zones in the wave domain. Simulation results demonstrate that compared with the conventional acoustic contrast control approach, the proposed method improves the level of acoustic contrast and array gain over the entire control region and is less sensitive to the selection of the regularization parameter.
Handojoseno, AMA, Naik, GR, Gilat, M, Shine, JM, Nguyen, TN, Ly, QT, Lewis, SJG & Nguyen, HT 2018, 'Prediction of Freezing of Gait in Patients with Parkinson's Disease Using EEG Signals.', Stud Health Technol Inform, vol. 246, pp. 124-131.
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Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson's disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.
Hanh, LTM, Binh, NT & Tung, KT 2018, 'Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models', Journal of Telecommunications and Information Technology, vol. 4, no. 2017, pp. 90-100.
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Mutation testing – a fault-based technique for software testing – is a computationally expensive approach. One of the powerful methods to improve the performance of mutation without reducing effectiveness is to employ parallel processing, where mutants and tests are executed in parallel. This approach reduces the total time needed to accomplish the mutation analysis. This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. The experiments were carried out on eight different Simulink models. The results represented the efficiency of the proposed approaches in terms of execution time during the testing process.
Hannan, MA, Faisal, M, Ker, PJ, Mun, LH, Parvin, K, Mahlia, TMI & Blaabjerg, F 2018, 'A Review of Internet of Energy Based Building Energy Management Systems: Issues and Recommendations', IEEE Access, vol. 6, pp. 38997-39014.
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© 2013 IEEE. A building energy management system (BEMS) is a sophisticated method used for monitoring and controlling a building's energy requirements. A number of potential studies were conducted in nearly or net zero energy buildings (nZEBs) for the optimization of building energy consumption through efficient and sustainable ways. Moreover, policy makers are approving measures to improve building energy efficiency in order to foster sustainable energy usages. However, the intelligence of existing BEMSs or nZEBs is inadequate, because of the static set points for heating, cooling, and lighting, the complexity of large amounts of BEMS data, data loss, and network problems. To solve these issues, a BEMS or nZEB solution based on the Internet of energy (IoE) provides disruptive opportunities for revolutionizing sustainable building energy management. This paper presents a critical review of the potential of an IoE-based BEMS for enhancing the performance of future generation building energy utilization. The detailed studies of the IoE architecture, typical nZEB configuration, different generations of nZEB, and smart building energy systems for future BEMS are investigated. The operations, advantages, and limitations of the existing BEMSs or nZEBs are illustrated. A comprehensive review of the different types of IoE-based BEMS technologies, such as energy routers, storage systems and materials, renewable sources, and plug-and-play interfaces, is then presented. The rigorous review indicates that existing BEMSs require advanced controllers integrated with IoE-based technologies for sustainable building energy usage. The main objective of this review is to highlight several issues and challenges of the conventional controllers and IoE applications of BEMSs or nZEBs. Accordingly, the review provides several suggestions for the research and development of the advanced optimized controller and IoE of future BEMSs. All the highlighted insights and recommendations of this...
Hao, J, Chou, J, Kuroda, S, Otsuka, M, Kasugai, S & Lang, NP 2018, 'Injectable simvastatin gel for minimally invasive periosteal distraction: In vitro and in vivo studies in rat', Clinical Oral Implants Research, vol. 29, no. 2, pp. 227-234.
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To evaluate whether the subperiosteal injection of simvastatin (SIM) with a novel in situ gel-forming system, SrHA/Alg (strontium hydroxyapatite/alginate), can stimulate vertical bone augmentation in a rat calvarial model.The SrHA/Alg solution was synthesized and combined with different doses of SIM (0.01, 0.02, 0.1, and 0.2 mg) to form the following groups: (1) SrHA/Alg only, (2) SrHA/Alg/0.01, (3) SrHA/Alg/0.02, (4) SrHA/Alg/0.1, and (5) SrHA/Alg/0.2. The SIM release pattern was analyzed, and rat primary periosteum-derived cell (PDC) responses were investigated. Twenty male Wistar rats were enrolled in the calvarial subperiosteal injection experiment with each animal receiving a 200-μl single subperiosteal injection of SrHA/Alg with different amounts of SIM (0, 0.01, 0.02, and 0.1 mg) incorporated (n = 5). The 0.2 mg dose group was not tested in vivo due to the severe toxicity found in vitro. The new bone formation was assessed histologically and radiologically at 8 weeks.The slow release of SIM was confirmed, and PDC viability decreased in the SrHA/Alg/0.2 group. Alkaline phosphatase positive areas and mineralization areas were significantly greater in the SrHA/Alg/0.01 and SrHA/Alg/0.02 groups (p < .05). The mRNA expression level of Runx2 significantly increased in the SrHA/Alg/SIM-0.02 group by day 7 (p < .05) and significantly higher levels of VEGF were found in the SrHA/Alg/0.01 and SrHA/Alg/0.02 groups at different time points (p < .05). In vivo, no prominent clinical sign of inflammation was observed, and the most significant bone gain was shown in the SrHA/Alg/0.02 group (p < .05). The osteoclast formation within the newly formed bone area was reduced in the SrHA/Alg/0.1 group (p < .05).When combined with SrHA/Alg system, the 0.02 mg SIM seemed to be the optimal dose to stimulate subperiosteal bone formation without inducing inflammation. This combination may hold potential therapeutic benefits for clinical bone augmentation in a minimally invasive mann...
Hao, S, Shi, C, Niu, Z & Cao, L 2018, 'Concept coupling learning for improving concept lattice-based document retrieval', Engineering Applications of Artificial Intelligence, vol. 69, pp. 65-75.
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© 2017 Elsevier Ltd The semantic information in any document collection is critical for query understanding in information retrieval. Existing concept lattice-based retrieval systems mainly rely on the partial order relation of formal concepts to index documents. However, the methods used by these systems often ignore the explicit semantic information between the formal concepts extracted from the collection. In this paper, a concept coupling relationship analysis model is proposed to learn and aggregate the intra- and inter-concept coupling relationships. The intra-concept coupling relationship employs the common terms of formal concepts to describe the explicit semantics of formal concepts. The inter-concept coupling relationship adopts the partial order relation of formal concepts to capture the implicit dependency of formal concepts. Based on the concept coupling relationship analysis model, we propose a concept lattice-based retrieval framework. This framework represents user queries and documents in a concept space based on fuzzy formal concept analysis, utilizes a concept lattice as a semantic index to organize documents, and ranks documents with respect to the learned concept coupling relationships. Experiments are performed on the text collections acquired from the SMART information retrieval system. Compared with classic concept lattice-based retrieval methods, our proposed method achieves at least 9%, 8% and 15% improvement in terms of average MAP, IAP@11 and P@10 respectively on all the collections.
Hassan, M, Liu, D & Paul, G 2018, 'Collaboration of Multiple Autonomous Industrial Robots through Optimal Base Placements', Journal of Intelligent & Robotic Systems, vol. 90, no. 1-2, pp. 113-132.
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Multiple autonomous industrial robots can be of great use in manufacturing applications, particularly if the environment is unstructured and custom manufacturing is required. Autonomous robots that are equipped with manipulators can collaborate to carry out manufacturing tasks such as surface preparation by means of grit-blasting, surface coating or spray painting, all of which require complete surface coverage. However, as part of the collaboration process, appropriate base placements relative to the environment and the target object need to be determined by the robots. The problem of finding appropriate base placements is further complicated when the object under consideration is large and has a complex geometric shape, and thus the robots need to operate from a number of base placements in order to obtain complete coverage of the entire object. To address this problem, an approach for Optimization of Multiple Base Placements (OMBP) for each robot is proposed in this paper. The approach aims to optimize base placements for multi-robot collaboration by taking into account task-specific objectives such as makespan, fair workload division amongst the robots, and coverage percentage; and manipulator-related objectives such as torque and manipulability measure. In addition, the constraint of robots maintaining an appropriate distance between each other and relative to the environment is taken into account. Simulated and real-world experiments are carried out to demonstrate the effectiveness of the approach and to verify that the simulated results are accurate and reliable.
Hassanzadeh-Barforoushi, A, Law, AMK, Hejri, A, Asadnia, M, Ormandy, CJ, Gallego-Ortega, D & Ebrahimi Warkiani, M 2018, 'Static droplet array for culturing single live adherent cells in an isolated chemical microenvironment', Lab on a Chip, vol. 18, no. 15, pp. 2156-2166.
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Rapid and reliable capture and analysis of single cells in a chemically isolated static droplet array for fast-tracking single cell discoveries.
Hawari, AH, Al-Qahoumi, A, Ltaief, A, Zaidi, S & Altaee, A 2018, 'Dilution of seawater using dewatered construction water in a hybrid forward osmosis system', Journal of Cleaner Production, vol. 195, pp. 365-373.
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In this study, dewatered construction water was used for the first time as the feed solution in a combined pretreatment-forward osmosis process to dilute seawater (i.e. draw solution) for further desalination. It was found that at a feed solution and a draw solution flow rate of 2.2 L min−1 gave the optimum membrane flux with minimal fouling effects. The addition of a spacer in the membrane feed side was effective at low flow rates (0.8 and 1.5 L min−1). The feed solution was then pretreated using two methods: settling and multimedia filtration and used in the forward osmosis unit at a low flow rate of 0.8 L min−1 using a spacer at the feed side. Results revealed a significant increase in the forward osmosis membrane flux by 64.3% when multimedia filtration was carried out with a flux reduction of 7.7%. While the settling method achieved only 13.5% increase in the permeate flux and 12.5% flux reduction. The multimedia filtration process removed most of the particles that would cause fouling which resulted in an elevated and more consistent membrane flux. Results also showed that the water flux was 1.3 times higher when the membrane's active layer was facing the draw solution than when it was facing the feed solution. Cost analysis showed that forward osmosis treatment of dewatered construction water was 7.88 $.day−1 and it was slightly cheaper when the forward osmosis operates in the pressure retarded osmosis mode.
Haydar, H, Far, H & Saleh, A 2018, 'Portal steel trusses vs. portal steel frames for long-span industrial buildings', Steel Construction, vol. 11, no. 3, pp. 205-217.
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Portal frames and portal truss structures are two of the most cost effective and sustainable structural commodities for utilisation in the design and construction of long span industrial buildings. Although the application of both structure types as steel cladded structures is widely accepted, due to frame complexity and variation of frame types for use in single story buildings, that exceed spans greater than 30 meters, literature providing a comprehensive investigation on the concepts of portal trusses and portal frames is scarce. This study compares the behaviour of portal truss configuration with pitched portal frames for use in long span industrial buildings that exceed 30 meters with focus on weight, costs and time for construction. Furthermore, this study entails a numerical investigation that utilises SAP2000 computer program to model and structurally optimise the member properties for both portal frame and portal truss configurations. Based on the results obtained from the investigation, it has become apparent that the portal truss configurations are lighter and cheaper to fabricate and construct due to the smaller sections used in comparison to the pitched portal frame that require a shorter time for construction.
He, F, Jiang, F, Jiang, Y & Ling, SH 2018, 'New microscopic image sequence‐driven cell deformation model', The Journal of Engineering, vol. 2018, no. 16, pp. 1587-1589.
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He, L, Lu, Z, Zhang, J, Geng, L, Zhao, H & Li, X 2018, 'Low-carbon economic dispatch for electricity and natural gas systems considering carbon capture systems and power-to-gas', Applied Energy, vol. 224, pp. 357-370.
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He, Q, Wang, J & Lu, H 2018, 'A hybrid system for short-term wind speed forecasting', Applied Energy, vol. 226, pp. 756-771.
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© 2018 Elsevier Ltd Wind speed forecasting is important for high-efficiency utilization of wind energy. Correspondingly, numerous researchers have always focused on the development of reliable forecasting models of wind speed, which is often noisy, unstable and irregular. Current approaches could adapt to various wind speed data. However, many of these usually ignore the importance of the selection of the modeling sample, which often results in poor forecasting performance. In this study, a hybrid forecasting system is proposed that contains three modules: data preprocessing, data clustering, and forecasting modules. In this system, the decomposing technique is applied to reduce the influence of noise within the raw data series to obtain a more stable sequence that is conducive to extract traits from the original data. To extract the characteristic of similarity within wind speed data, a kernel-based fuzzy c-means clustering algorithm is used in data clustering module. In the forecasting module, a sample with a highly similar fluctuation pattern is selected as training dataset, and which could reduce the training requirement of model to improve the forecasting accuracy. The experimental results indicate that the developed system outperforms the discussed traditional forecasting models with respect to forecasting accuracy.
He, T, Cai, L, Meng, T, Chen, L, Deng, Z & Cao, Z 2018, 'Parallel Community Detection Based on Distance Dynamics for Large-Scale Network', IEEE Access, vol. 6, pp. 42775-42789.
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© 2013 IEEE. Data mining task is a challenge on finding a high-quality community structure from large-scale networks. The distance dynamics model was proved to be active on regular-size network community, but it is difficult to discover the community structure effectively from the large-scale network (0.1-1 billion edges), due to the limit of machine hardware and high time complexity. In this paper, we proposed a parallel community detection algorithm based on the distance dynamics model called P-Attractor, which is capable of handling the detection problem of large networks community. Our algorithm first developed a graph partitioning method to divide large network into lots of sub-networks, yet maintaining the complete neighbor structure of the original network. Then, the traditional distance dynamics model was improved by the dynamic interaction process to simulate the distance evolution of each sub-network. Finally, we discovered the real community structure by removing all external edges after evolution process. In our extensive experiments on multiple synthetic networks and real-world networks, the results showed the effectiveness and efficiency of P-Attractor, and the execution time on 4 threads and 32 threads are around 10 and 2 h, respectively. Our proposed algorithm is potential to discover community from a billion-scale network, such as Uk-2007.
He, T, Lu, DD-C, Li, L, Zhang, J, Zheng, L & Zhu, J 2018, 'Model-Predictive Sliding-Mode Control for Three-Phase AC/DC Converters', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 8982-8993.
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IEEE This paper presents a model predictive sliding mode control (MPSMC) strategy for a three-phase AC/DC converter to achieve better stability and dynamic performances. In the conventional model predictive control (MPC) method, a proportional integral (PI) controller is used to generate the active power reference to regulate the dc voltage. This traditional model predictive PI control (MPPIC) scheme produces a large overshoot/undershoot, a long settling time and a large steady-state error under disturbances. To overcome these deficiencies, a sliding mode controller is employed to replace PI controller in MPC. Since the sliding surface and the control law are designed based on the system model, the proposed MPSMC scheme can reduce the effects of the unknown disturbances. Compared with MPPIC, the simulation results obtained from MPSMC show that the dc voltage settling time can be minimized by 80% and the overshoot can be eliminated from 6.2% during the steady state progress. The active and reactive powers from MPSMC can be controlled to the desired values, respectively, with a smaller overshoot/undershoot and a faster response speed. Similar dynamic improvements can be achieved with MPSMC when the load voltage demand varies. Simulation results are validated through an experimental setup and experimental results are reported.
He, T, Zhu, J, Zhang, J & Zheng, L 2018, 'An optimal charging/discharging strategy for smart electrical car parks', Chinese Journal of Electrical Engineering, vol. 4, no. 2, pp. 28-35.
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This paper presents a smart electrical car park model where the power flows among electrical vehicles(EVs) as well as between EVs and the main grid. Based on this model, an optimal charging/discharging scheme is proposed. The fluctuation of hourly electricity rates is considered in this strategy to select a proper charging/discharging rate for each EV with less expenditure during each charging period. The proposed smart electrical car park is able to buy or sell electricity in the form of active and/or reactive power, i.e. kWh and/or kVARh, from or to the main grid to improve the power quality. According to the current state of charge of the EV's battery bank, customers and the grid demands, a control center makes the decisions and sends the instructions of specific charging/discharging mode to each charging station. The performance of the proposed charging/discharging algorithm is simulated in Matlab. A comparison between the proposed and the unregulated charging/discharging strategies has been implemented. The results demonstrate that the proposed scheme can achieve better economic profits for EV customers and increase the commercial benefits for the car park owner.
He, X, Liang, D & Bolton, MD 2018, 'Run-out of cut-slope landslides: mesh-free simulations', Géotechnique, vol. 68, no. 1, pp. 50-63.
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This study uses an incompressible smoothed-particle hydrodynamics (ISPH) model to investigate the run-out and deposit morphology of granular materials flowing down cut slopes. The primary aim is to study the influence of various factors on the run-out and to summarise a quantitative relationship for direct use in landslide hazard management. In the model, the granular materials are modelled as a rigid perfectly plastic material with a Coulomb yield surface. The coupled continuity equation and momentum equation are solved by a semi-implicit algorithm. The model is first validated and its results are carefully compared with various controlled experiments regarding granular flows. The model reproduces the flows and correctly predicts the deposition profiles under various conditions. Then, the computational results are used to study the run-out and mobility of landslides. For granular columns collapsing onto a flat surface, a normalised run-out and a new scaling relationship are proposed, which are supported by numerous measured and numerical results. A similar relationship for the run-out of granular rectangles on steep slopes has also been explored. It is found that the normalised run-out is mainly determined by the slope angle and the normalised drop height. Furthermore, three types of idealised cut-slope landslides are simulated to study the influence of the initial landslide shape on the run-out. It is found that the normalised run-out of these idealised cut-slope landslides is smaller than that of granular rectangles on slopes of the same angles and drop heights. The difference between the run-outs is found to be mainly determined by the proportion of the whole mass that initially lies above a predictable discontinuity plane.
He, X, Liang, D, Wu, W, Cai, G, Zhao, C & Wang, S 2018, 'Study of the interaction between dry granular flows and rigid barriers with an SPH model', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 11, pp. 1217-1234.
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He, Y, Dong, X, Kang, G, Fu, Y, Yan, C & Yang, Y 2018, 'Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks', IEEE Transactions on Cybernetics, vol. 50, no. 8, pp. 3594-3604.
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Deeper and wider Convolutional Neural Networks (CNNs) achieve superior
performance but bring expensive computation cost. Accelerating such
over-parameterized neural network has received increased attention. A typical
pruning algorithm is a three-stage pipeline, i.e., training, pruning, and
retraining. Prevailing approaches fix the pruned filters to zero during
retraining, and thus significantly reduce the optimization space. Besides, they
directly prune a large number of filters at first, which would cause
unrecoverable information loss. To solve these problems, we propose an
Asymptotic Soft Filter Pruning (ASFP) method to accelerate the inference
procedure of the deep neural networks. First, we update the pruned filters
during the retraining stage. As a result, the optimization space of the pruned
model would not be reduced but be the same as that of the original model. In
this way, the model has enough capacity to learn from the training data.
Second, we prune the network asymptotically. We prune few filters at first and
asymptotically prune more filters during the training procedure. With
asymptotic pruning, the information of the training set would be gradually
concentrated in the remaining filters, so the subsequent training and pruning
process would be stable. Experiments show the effectiveness of our ASFP on
image classification benchmarks. Notably, on ILSVRC-2012, our ASFP reduces more
than 40% FLOPs on ResNet-50 with only 0.14% top-5 accuracy degradation, which
is higher than the soft filter pruning (SFP) by 8%.
He, Y, Jayawickrama, BA, Dutkiewicz, E, Srikanteswara, S & Mueck, M 2018, 'Priority Access and General Authorized Access Interference Mitigation in the Spectrum Access System', IEEE Transactions on Vehicular Technology, vol. 67, no. 6, pp. 4969-4983.
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© 1967-2012 IEEE. To meet the capacity needs of next generation wireless communications, the U.S. Federal Communications Commission has recently introduced the spectrum access system. Spectrum is shared between three tiers - incumbents, priority access licensees (PAL), and general authorized access (GAA) licensees. When the incumbents are absent, PAL and GAA share the spectrum under the constraint that GAA ensure the interference to PAL is no more than $-$40 dBm with at least 99% confidence. We consider the scenario where locations are not shared between PAL and GAA. We propose a PAL-GAA cochannel interference mitigation technique that does not expose base station locations. Our approach relies on GAA sharing the distribution and maximum number of transmitters in a finite area. We show how PAL can derive the distribution of the aggregate interference using the probability density function and characteristic function, and notify GAA about the exclusion zones in space that will guarantee that the interference requirement is met. We also propose a numerical approximation using inverse fast Fourier and discrete Fourier transforms. Analytically calculated distribution aligns well with the numerical results. Additionally, we formulate an optimization problem for the optimal exclusion zone size. We analytically prove convexity of the problem. Our approach reduces the exclusion zone size by over 42%, which gives significantly more spectral opportunities to GAA in the spatial domain.
He, Y, Wan, Z, Liu, X, Zheng, X, Zeng, G & Zhang, J 2018, 'A CASCADED MULTILEVEL CONVERTER BASED ON SOC CLOSED LOOP TRACKING', Progress In Electromagnetics Research C, vol. 88, pp. 103-115.
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© 2018, Electromagnetics Academy. All rights reserved. This paper proposes a cascaded multilevel converter to reduce the number of IGBT switches for the purpose of improving system stability and decreasing switching losses. This converter can eliminate second-order ripple caused by energy exchange between grid and batteries, and thus extend battery life. This cascaded connection between the equivalent buck/boost circuit and the half-bridge inverter is also able to reduce the number of switch tubes. A control strategy based on state of charge (SOC) closed-loop tracking is designed to implement t0068e errorless follow-up control of average SOC values for electric vehicle batteries. The equivalent circuit under different working modes of the topology is analyzed, and the effectiveness of the control strategy is verified. Simulated and experimental results show that this converter can effectively achieve grid connection requirements and balance the battery units to meet practical needs.
He, Z, Zhang, S, Teng, J, Yao, Y & Sheng, D 2018, 'A coupled model for liquid water-vapor-heat migration in freezing soils', Cold Regions Science and Technology, vol. 148, pp. 22-28.
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Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'A local and scalable lattice renormalization method for ballistic quantum computation', npj Quantum Information, vol. 4, no. 1, pp. 1-8.
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AbstractA recent proposal has shown that it is possible to perform linear-optics quantum computation using a ballistic generation of the lattice. Yet, due to the probabilistic generation of its cluster state, it is not possible to use the fault-tolerant Raussendorf lattice, which requires a lower failure rate during the entanglement-generation process. Previous work in this area showed proof-of-principle linear-optics quantum computation, while this paper presents an approach to it which is more practical, satisfying several key constraints. We develop a classical measurement scheme that purifies a large faulty lattice to a smaller lattice with entanglement faults below threshold. A single application of this method can reduce the entanglement error rate to 7% for an input failure rate of 25%. Thus, we can show that it is possible to achieve fault tolerance for ballistic methods.
Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'Lattice surgery on the Raussendorf lattice', Quantum Science and Technology, vol. 3, no. 3, pp. 035011-035011.
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© 2018 IOP Publishing Ltd. Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.
Hill, M & Tran, N 2018, 'MicroRNAs Regulating MicroRNAs in Cancer', Trends in Cancer, vol. 4, no. 7, pp. 465-468.
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MicroRNAs (miRNA) are capable of self-regulation, termed miRNA to miRNA interaction. Very little is known about these interactions and their impact on the cellular milieu. We discuss known miRNA to miRNA interactions, potential mechanisms, and their role in cancer.
Hirzallah, M, Afifi, W & Krunz, M 2018, 'Provisioning QoS in Wi-Fi Systems With Asymmetric Full-Duplex Communications', IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 4, pp. 942-953.
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© 2015 IEEE. The traffic volume carried by wireless local area networks (WLANs) continues to increase at a rapid pace. Full-duplex communication is a key solution for satisfying the growing traffic demand, enhancing spectrum efficiency, and reducing latency for WLAN users. In this paper, we consider the application of asymmetric full-duplex (AFD) communications in WLANs, exemplified by a Wi-Fi system. Our system model relies on a full-duplex-enabled Wi-Fi access point to simultaneously transmit uplink and downlink to a pair of half-duplex Wi-Fi stations. Providing QoS guarantees in WLANs with AFD communication capabilities is challenging due to inter-node as well as residual self-interference. The heterogeneity of the QoS requirements between paired uplink and downlink stations further complicates the problem. To tackle these challenges, we introduce a framework called AFD-QoS, which incorporates AFD communications in WLANs and supports QoS. AFD-QoS consists of three components: 1) AFD-enabled uplink/downlink station-pair selection algorithm; 2) AFD-enabled block-acknowledgment session initiation/termination protocol; and 3) joint transmission rate/AFD communication mode adaptation scheme. Our adaptation scheme relies on intelligent and cognitive approaches to improve Wi-Fi networks awareness about channel dynamics as well as inter-node and self-interference. We introduce new intelligent MAC-layer procedures for supporting QoS services in AFD communications, and cast light on many challenges and their solutions. Our simulation results indicate that AFD-QoS outperforms classical half-duplex frameworks and achieves up to 90% of the optimal AFD performance.
Ho, L & Fatahi, B 2018, 'Analytical solution to axisymmetric consolidation of unsaturated soil stratum under equal strain condition incorporating smear effects', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 15, pp. 1890-1913.
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© 2018 John Wiley & Sons, Ltd. This paper proposes closed-form analytical solutions to the axisymmetric consolidation of an unsaturated soil stratum using the equal strain hypothesis. Following the 1-dimensional (1D) consolidation theory for unsaturated soil mechanics, polar governing equations describing the air and water flows are first presented on the basis of Fick's law and Darcy's law, respectively. The current study takes into account the peripheral smear caused by an installation of vertical drain. Separation of variables and Laplace transformation are mainly adopted in the analytical derivation to obtain final solutions. Then, the hydraulic conductivity ratio, the radius of influence zone and smear parameters influencing time-dependent excess pore pressures, and the average degree of consolidation are graphically interpreted. In this study, a comparison made between the proposed equal strain results and the existing free strain results suggests that both hypotheses would deliver similar predictions. Moreover, it is found that the smear zone resulting from vertical drain installations would hinder the consolidation rate considerably.
Ho, L, Fatahi, B & Khabbaz, H 2018, 'Analytical Solution to One-Dimensional Consolidation in Unsaturated Soil Deposit Incorporating Time-Dependent Diurnal Temperature Variation', International Journal of Geomechanics, vol. 18, no. 5, pp. 04018029-04018029.
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© 2018 American Society of Civil Engineers. Several experimental studies have demonstrated that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for unsaturated consolidation capturing the nonisothermal effect. This paper presents an analytical solution to the one-dimensional (1D) consolidation of unsaturated soil deposit in response to temperature variation. A set of governing equations of flow incorporating the nonisothermal condition were first obtained. Then, Fourier sine series and the Laplace transformation were used to derive solutions based on these governing equations. This study highlighted the effect of diurnal temperature variation on pore pressures and soil deformation at different depths while considering two conditions of interest: (1) no external applied load, and (2) application of step loading to the ground surface. In addition, the thermal diffusivity characterizing the consolidation behavior of unsaturated soils was also investigated and is discussed in this paper. It is predicted that a decrease in thermal diffusivity would attenuate the effects of diurnal temperature on the unsaturated consolidation.
Ho, N, Peng, H, Mayoh, C, Liu, PY, Atmadibrata, B, Marshall, GM, Li, J & Liu, T 2018, 'Delineation of the frequency and boundary of chromosomal copy number variations in paediatric neuroblastoma', Cell Cycle, vol. 17, no. 6, pp. 749-758.
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Hoang, DT, Niyato, D, Nguyen, DN, Dutkiewicz, E, Wang, P & Han, Z 2018, 'A Dynamic Edge Caching Framework for Mobile 5G Networks', IEEE Wireless Communications, vol. 25, no. 5, pp. 95-103.
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Mobile edge caching has emerged as a new paradigm to provide computing, networking resources, and storage for a variety of mobile applications. That helps achieve low latency, high reliability, and improve efficiency in handling a very large number of smart devices and emerging services (e.g., IoT, industry automation, virtual reality) in mobile 5G networks. Nonetheless, the development of mobile edge caching is challenged by the decentralized nature of edge nodes, their small coverage, limited computing, and storage resources. In this article, we first give an overview of mobile edge caching in 5G networks. After that, its key challenges and current approaches are discussed. We then propose a novel caching framework. Our framework allows an edge node to authorize the legitimate users and dynamically predicts and updates their content demands using the matrix factorization technique. Based on the prediction, the edge node can adopt advanced optimization methods to determine optimal content to store so as to maximize its revenue and minimize the average delay of its mobile users. Through numerical results, we demonstrate that our proposed framework provides not only an effective caching approach, but also an efficient economic solution for the mobile service provider.
Hoang, TM, Ngo, HQ, Duong, TQ, Tuan, HD & Marshall, A 2018, 'Cell-Free Massive MIMO Networks: Optimal Power Control Against Active Eavesdropping', IEEE Transactions on Communications, vol. 66, no. 10, pp. 4724-4737.
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© 1972-2012 IEEE. This paper studies the security aspect of a recently introduced 'cell-free massive MIMO' network under a pilot spoofing attack. First, a simple method to recognize the presence of this type of an active eavesdropping attack to a particular user is shown. In order to deal with this attack, we consider the problem of maximizing the achievable data rate of the attacked user or its achievable secrecy rate. The corresponding problems of minimizing the power consumption subject to security constraints are also considered in parallel. Path-following algorithms are developed to solve the posed optimization problems under different power allocation to access points (APs). Under equip-power allocation to APs, these optimization problems admit closed-form solutions. Numerical results show their efficiency.
Ho-Le, TP, Pham, HM, Center, JR, Eisman, JA, Nguyen, HT & Nguyen, TV 2018, 'Prediction of changes in bone mineral density in the elderly: contribution of “osteogenomic profile”', Archives of Osteoporosis, vol. 13, no. 1.
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The contribution of genetic variants to longitudinal bone loss has not been well documented. We constructed an "osteogenomic profile" based on 62 BMD-associated genetic variants and showed that the profile was significantly associated with bone loss, independently from baseline BMD and age. The osteogenomic profile can help predict bone loss in an individual.The rate of longitudinal bone loss (ΔBMD) is a risk factor for fracture. The variation in ΔBMD is partly determined by genetic factors. This study sought to define the association between an osteogenomic profile and ΔBMD.The osteogenomic profile was created from 62 BMD-associated SNPs from genome-wide association studies (GWAS) that were genotyped in 1384 elderly men and women aged 60+ years. Weighted genetic risk scores (GRS) were constructed for each individual by summing the products of the number of risk alleles and the sex-specific regression coefficients [associated with BMD from GWAS]. ΔBMD, expressed as annual percent change-in-BMD, was determined by linear regression analysis for each individual who had had at least two femoral neck BMD measurements.The mean ΔBMD was - 0.65% (SD 1.64%) for women and - 0.57% (SD 1.40%) for men, and this difference was not statistically significant (P = 0.32). In women, each unit increase in GRS was associated with 0.21% (SE 0.10) higher ΔBMD at the femoral neck (P = 0.036), and this association was independent of baseline BMD and age. In logistic regression analysis, each unit increase of GRS was associated with 41% odds (95%CI: 1.07-1.87) of rapid bone loss (ΔBMD ≤ - 1.2%/year; mean of rapid loss group = - 2.2%/year). There was no statistically significant association between ΔBMD and GRS in men.We conclude that the osteogenomic profile constructed from BMD-associated genetic variants is modestly associated with long-term changes in femoral neck BMD in women, but not in men.
Hong, H, Liu, J, Bui, DT, Pradhan, B, Acharya, TD, Pham, BT, Zhu, A-X, Chen, W & Ahmad, BB 2018, 'Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)', CATENA, vol. 163, pp. 399-413.
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© 2018 Elsevier B.V. Landslides are a manifestation of slope instability causing different kinds of damage affecting life and property. Therefore, high-performance-based landslide prediction models are useful to government institutions for developing strategies for landslide hazard prevention and mitigation. Development of data mining based algorithms shows that high-performance models can be obtained using ensemble frameworks. The primary objective of this study is to investigate and compare the use of current state-of-the-art ensemble techniques, such as AdaBoost, Bagging, and Rotation Forest, for landslide susceptibility assessment with the base classifier of J48 Decision Tree (JDT). The Guangchang district (Jiangxi province, China) was selected as the case study. Firstly, a landslide inventory map with 237 landslide locations was constructed; the landslide locations were then randomly divided into a ratio of 70/30 for the training and validating models. Secondly, fifteen landslide conditioning factors were prepared, such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), plan curvature, profile curvature, lithology, distance to faults, distance to rivers, distance to roads, land use, normalized difference vegetation index (NDVI), and rainfall. Relief-F with the 10-fold cross-validation method was applied to quantify the predictive ability of the conditioning factors and for feature selection. Using the JDT and its three ensemble techniques, a total of four landslide susceptibility models were constructed. Finally, the overall performance of the resulting models was assessed and compared using area under the receiver operating characteristic (ROC) curve (AUC) and statistical indexes. The result showed that all landslide models have high performance (AUC > 0.8). However, the JDT with the Rotation Forest model presents the highest prediction capability (AUC = 0.855), followed by the JDT with the...
Hong, H, Pradhan, B, Sameen, MI, Kalantar, B, Zhu, A & Chen, W 2018, 'Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach', Landslides, vol. 15, no. 4, pp. 753-772.
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© 2017, Springer-Verlag GmbH Germany. Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors.
Ho-Pham, LT, Chau, PMN, Do, AT, Nguyen, HC & Nguyen, TV 2018, 'Type 2 diabetes is associated with higher trabecular bone density but lower cortical bone density: the Vietnam Osteoporosis Study', Osteoporosis International, vol. 29, no. 9, pp. 2059-2067.
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It is not clear why type 2 diabetes (T2D) has an increased risk of fracture despite higher areal bone mineral density. This study showed that compared with controls, T2D patients had higher trabecular bone density but lower cortical bone density, resulting in a lower bone strength. INTRODUCTION:To define the association between type 2 diabetes and bone architecture and measures of bone strength. METHODS:The study was part of the Vietnam Osteoporosis Study, in which 1115 women and 614 men aged ≥ 30 were randomly recruited from Ho Chi Minh City. HbA1c levels were measured with analyzers ADAMS™ A1c HA-8160 (Arkray, Kyoto, Japan). The diagnosis of T2D was made if HbA1c was ≥ 6.5%. Trabecular and cortical volumetric bone density (vBMD) was measured in the forearm and leg by a pQCT XCT2000 (Stratec, Germany). Polar stress strain index (pSSI) was derived from the pQCT measurements. Difference in bone parameters between T2D and non-diabetic individuals was assessed by the number of standard deviations (effect size [ES]) by the propensity score analysis. RESULTS:The prevalence of T2D was ~ 8%. The results of propensity score matching for age, sex, and body mass index in 137 pairs of diabetic and non-diabetic individuals showed that T2D patients had significantly higher distal radius trabecular vBMD (ES 0.26; 95% CI, 0.02 to 0.50), but lower cortical vBMD (ES - 0.22; - 0.46 to 0.00) and reduced pSSI (ES - 0.23; - 0.47 to - 0.02) compared with non-diabetic individuals. Multiple linear regression analysis based on the entire sample confirmed the results of the propensity score analysis. CONCLUSION:Compared with non-diabetic individuals, patients with T2D have greater trabecular but lower cortical vBMD which leads to lower bone strength.
Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Assessing tropical cyclone risks using geospatial techniques', Applied Geography, vol. 98, pp. 22-33.
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Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques', International Journal of Digital Earth, vol. 11, no. 3, pp. 246-263.
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Hossain, MA, Pota, HR, Hossain, MJ & Haruni, AMO 2018, 'Active power management in a low-voltage islanded microgrid', International Journal of Electrical Power & Energy Systems, vol. 98, pp. 36-47.
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Hossain, MJ, Rafi, FHM, Town, G & Lu, J 2018, 'Multifunctional Three-Phase Four-Leg PV-SVSI With Dynamic Capacity Distribution Method', IEEE Transactions on Industrial Informatics, vol. 14, no. 6, pp. 2507-2520.
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Hou, Z, Wang, Y, Sui, Y, Gu, J, Zhao, T & Zhou, X 2018, 'Managing high-performance computing applications as an on-demand service on federated clouds', Computers & Electrical Engineering, vol. 67, pp. 579-595.
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© 2018 Elsevier Ltd There are several challenges (e.g., imbalance between supply and demand of hardware resources and software licenses, and usability) under modern High-Performance Computing (HPC) environment. As a means of providing an on-demand service for end users, we propose a Software-as-a-Service (SaaS) approach for managing commercial HPC applications as a Web-based service deployed on top of federated clouds. Some inter-trusted private or public clouds are federated to create a unified service platform with a large amount of hardware resources. In addition, an on-demand, pay-per-use model for Web-service-enabled HPC applications is proposed. Further, we provide an economic analysis of the proposed approach from the perspective of end users, cloud service providers, and Independent Software Vendors (ISVs). We conduct a simulation using two HPC application services on three federated clouds. A combined Quality of Service (QoS) and economic evaluation demonstrates a better effect of the proposed approach comparing with existing HPC platforms.
Hou, ZJ, Yang, Y, Chiu, L, Zhu, X & Xue, Q 2018, 'Wideband Millimeter-Wave On-Chip Quadrature Coupler With Improved In-Band Flatness in 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu$ </tex-math> </inline-formula>m SiGe Technology', IEEE Electron Device Letters, vol. 39, no. 5, pp. 652-655.
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© 1980-2012 IEEE. This letter proposes a compact and broadband quadrature coupler with a center frequency of 55 GHz, which consists of a 90° broadside coupled-line to support the differential signal propagation and two T-type L-C networks to support the common signal propagation. To analyze the proposed coupler, an equivalent circuit model is provided for estimation of the distributed and lumped component values. The measured results of the proposed on-chip quadrature coupler show that the return loss and isolation are greater than 20 dB with a bandwidth of 105%, while the insertion loss is about -0.85 dB. The magnitude imbalances are less than 1 dB within the bandwidth of 56% and the phase differences are with ±1° errors within the bandwidth of 96.9%. The chip size, excluding the test pads, is only 0.31 × 0.22 mm2.
Hou, ZJ, Yang, Y, Chiu, L, Zhu, X, Dutkiewicz, E, Vardaxoglou, JC & Xue, Q 2018, 'A W-Band Balanced Power Amplifier Using Broadside Coupled Strip-Line Coupler in SiGe BiCMOS 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu\text{m}$ </tex-math> </inline-formula> Technology', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 7, pp. 2139-2150.
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IEEE Load-variation insensitivity, for impedance matching between power amplifiers (PAs) and transmitting antennas, contributes to challenging the design of millimeter-wave wireless systems. In this paper, a W-band two-way balanced PA based on a compact quadrature coupler with a broadside coupled strip-line (BCSL) as the core is presented to enhance the load-variation insensitivity and stability. The proposed coupler is truly broadband with low amplitude and phase imbalance. The proposed $W$-band balanced PA achieves higher power-added efficiency (PAE) and unsaturated output power Psat over wide frequency bandwidth. The W-band balanced PA is implemented in a 0.13- & #x03BC;m SiGe BiCMOS process and achieves a measured Psat of 16.3 dBm and a peak PAE of 14.1 & #x0025; at 100 GHz (with 1.6-V power supply). The measured Psat with 1-dB bandwidth is from 91 to 102 GHz. The measured results present the feasibility of the compact quadrature coupler. The total chip surface area (with pads) is 0.64 mm & #x00B2;, where the size of the proposed quadrature coupler area is only 0.04 mm & #x00B2;.
Hou, ZJ, Yang, Y, Zhu, X, Li, YC, Dutkiewicz, E & Xue, Q 2018, 'A Compact and Low-Loss Bandpass Filter Using Self-Coupled Folded-Line Resonator With Capacitive Feeding Technique', IEEE Electron Device Letters, vol. 39, no. 10, pp. 1-1.
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IEEE This letter proposes a compact and low-loss on-chip bandpass filter (BPF) design in (Bi)-CMOS technology. The proposed BPF consists of a self-coupled folded-line resonator (SCFLR) and a pair of metal-insulator-metal (MIM) capacitors. The proposed resonator has a property of flexible self-resonant-frequency (SRF) to form a transmission zero (TZ), which is analyzed in details by a simplified LC equivalent circuit. Moreover, the parametric studies of the feeding capacitance for the proposed BPF design have been performed to demonstrate the tenability of the resonant frequency. For verification, the proposed BPF is fabricated in a standard 0.13-μm (Bi)-CMOS technology. The measured results show that the proposed BPF has a notch with 25.4 dB suppression at 65 GHz and an insertion loss of 1.66 dB in the passband. The chip size of the device, excluding the test pads, is only 0.009mm2 (0.11 × 0.086mm2).
How, HG, Masjuki, HH, Kalam, MA & Teoh, YH 2018, 'Influence of injection timing and split injection strategies on performance, emissions, and combustion characteristics of diesel engine fueled with biodiesel blended fuels', Fuel, vol. 213, pp. 106-114.
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Hu, C, Lu, J, Liu, X & Zhang, G 2018, 'Robust vehicle routing problem with hard time windows under demand and travel time uncertainty', Computers & Operations Research, vol. 94, pp. 139-153.
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Hu, D, Xu, W, Dian, R, Liu, Y & Zhu, J 2018, 'Loss Minimization Control of Linear Induction Motor Drive for Linear Metros', IEEE Transactions on Industrial Electronics, vol. 65, no. 9, pp. 6870-6880.
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© 1982-2012 IEEE. The linear induction motor (LIM) drive in linear metros suffers heavily from low efficiency due to its large air-gap length and the partial load conditions, where high loss appears in both the LIM and the inverter when a constant excitation current is generally required. Worse still, the end-effects, including both the transversal edge-effect and longitudinal end-effect, would lead to the decrease of magnetizing inductance and the increase of secondary resistance, resulting in extra loss and further deterioration of drive efficiency. To reduce the loss of the LIM drive, this paper proposes a novel loss model based loss minimization control (LMC) scheme for LIM drives. First, in the equivalent circuit and the mathematical model of LIM, four coefficients are introduced to evaluate the influence of the end-effects. Based on a thorough analysis of the LIM copper and core losses, together with the inverter conduction and switching losses, a novel integrated loss model of LIM drive is then developed, and an improved LMC scheme to obtain the optimal solution online is proposed to minimize the loss of the LIM drive. The proposed control method is successfully implemented in a 3-kW LIM drive prototype. The effectiveness of the proposed method is validated by the experimental results.
Hu, H, Liu, X, Zhao, J & Guo, Y 2018, 'Analysis and Minimization of Detent End Force in Linear Permanent Magnet Synchronous Machines', IEEE Transactions on Industrial Electronics, vol. 65, no. 3, pp. 2475-2486.
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© 1982-2012 IEEE. In this paper, the end forces caused by the longitude end effects in linear permanent magnet synchronous machines (LPMSMs) are analyzed and minimized. First, the left/right-end forces are calculated based on an analytical model and the Maxwell stress tensor, in which the optimal integration surfaces are investigated. Then, based on the spectrum analysis of the left/right-end forces, two different methods are adopted to minimize the fundamental and high-order harmonics, respectively. The optimal length of the primary iron is obtained from the phase difference of the fundamental and a two-step iteration instead of the trial-and-error with the finite element method. Furthermore, step-skewed auxiliary irons are added to the primary end to eliminate the high-order harmonics. Third, to reduce the secondary end effect when the primary moves to the secondary end, a compensation method of adding mirror permanent magnet is proposed and good results are obtained. Finally, an LPMSM prototype is manufactured and experiments are conducted. The experimental results verify the theoretical study.
Hu, J, Liang, B & Qiu, X-J 2018, 'Transparent and Ultra-lightweight Design for Ultra-Broadband Asymmetric Transmission of Airborne Sound', Chinese Physics Letters, vol. 35, no. 2, pp. 024301-024301.
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© 2018 Chinese Physical Society and IOP Publishing Ltd. Acoustic one-way manipulations have recently attracted significant attention due to the deep implications in many diverse fields such as biomedical imaging and treatment. However, the previous mechanisms of asymmetric manipulation of airborne sound need to use elaborate heavyweight structures and only work in certain frequency ranges. We propose a mechanism for designing an ultra-lightweight and optically transparent structure with asymmetric transmission property for normally incident plane waves. Instead of fabricating solids into complicated artificial structures with limited bandwidth and heavy weight, we simply use xenon to fill a spatial region of asymmetric shape which allows the incident plane wave to pass along one direction while reflecting the reversed wave regardless of frequency. We demonstrate both analytically and numerically its effectiveness of producing highly-asymmetric transmission within an ultra-broad band. Our design offers new possibility for the design of one-way devices and may have far-reaching impact on various scenarios such as noise control.
Hu, J, Zhang, Q, Lee, D-J & Ngo, HH 2018, 'Feasible use of microbial fuel cells for pollution treatment', Renewable Energy, vol. 129, pp. 824-829.
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© 2017 Elsevier Ltd. The microbial fuel cells (MFC) can directly transform chemical energy in feed substance to electricity by anodic aspiration pathways. This mini review provides an order-of-magnitude argument that MFC has much lower catalyst density at electrode surface and much higher diffusional resistance for substrates than the chemical fuel cell, the former should not be used as an energy generation unit; rather, it should be applied in low power density level applications such as biofilm wastewater treatment. The literature studies using MFC for pollution treatment are discussed.
Hu, K-Z, Tang, M-C, Li, M & Ziolkowski, RW 2018, 'Compact, Low-Profile, Bandwidth-Enhanced Substrate Integrated Waveguide Filtenna', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 8, pp. 1552-1556.
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© 2011 IEEE. In this letter, a compact, low-profile, bandwidth-enhanced, dual-cavity substrate integrated waveguide (SIW) filtenna is demonstrated. Two SIW cavities are stacked vertically on top of each other. A complementary split-ring resonator slot is etched in the top surface of the uppermost cavity, causing the top surface to act as a patch antenna. The operational impedance bandwidth is significantly enhanced by merging the three resonances that arise from this configuration. One is introduced by the patch, and the other two are inherently generated by the two cavities. A metallized coupling post is introduced from the ground plane through both cavities to the upper surface to excite the fundamental resonant mode of the patch, as well as to electromagnetically couple the two cavities. The optimized filtenna was fabricated by a standard printed circuit board technology and tested. It has a low profile λ 0 and a compact size 0.62λ 0×0.62λ0 at its center frequency, f0=2.95GHz. The measured results agree well with their simulated values. They demonstrate a 6.3% fractional bandwidth, a maximum realized gain of 6.73 dBi, a flat gain profile within its passband, and an excellent out-of-band selectivity.
Hu, L, Chen, Q, Zhao, H, Jian, S, Cao, L & Cao, J 2018, 'Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context', IEEE Intelligent Systems, vol. 33, no. 6, pp. 57-67.
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© 2018 IEEE. Classic recommender systems (RSs) often repeatedly recommend similar items to user historical profiles or recent purchases. For this, session-based RSs (SBRSs) are extensively studied in recent years. Current SBRSs often assume a rigid-order sequence, which does not fit in many real-world cases. In fact, the next-item recommendation depends on not only current session context but also historical sessions which are often neglected by current SBRSs. Accordingly, an SBRS over relaxed-order sequences with both intra- and inter-context is more pragmatic. Inspired by the successful experience in modern language modeling, we design an efficient neural architecture to model both intra- and inter-context for next item prediction.
Hu, Y, Lu, J & Qiu, X 2018, 'Direction of arrival estimation of multiple acoustic sources using a maximum likelihood method in the spherical harmonic domain', Applied Acoustics, vol. 135, pp. 85-90.
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Hu, Y, Wang, XC, Ngo, HH, Sun, Q & Yang, Y 2018, 'Anaerobic dynamic membrane bioreactor (AnDMBR) for wastewater treatment: A review', Bioresource Technology, vol. 247, pp. 1107-1118.
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© 2017 Elsevier Ltd Recently, an increasing level of attention has focused on the emerging technology of anaerobic dynamic membrane bioreactors (AnDMBRs), owing to its merits such as low membrane module cost, easy control of membrane fouling, low energy consumption and sludge production, as well as biogas production. As research on AnDMBRs is still in the nascent stage, an introduction of bioreactor configurations, dynamic membrane (DM) module, and DM layer formation and cleaning is firstly presented. The process performance of the AnDMBR for wastewater treatment is then reviewed with regard to pollutant removal, DM filterability, biogas production, and potential advantages over the conventional anaerobic membrane bioreactor (AnMBR). In addition, the important parameters affecting process performance are briefly discussed. Lastly, the challenges encountered and perspectives regarding the future development of the AnDMBR process to promote its practical applications are presented.
Hu, Y, Zheng, L, Yang, Y & Huang, Y 2018, 'Twitter100k: A Real-World Dataset for Weakly Supervised Cross-Media Retrieval', IEEE Transactions on Multimedia, vol. 20, no. 4, pp. 927-938.
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© 2017 IEEE. This paper contributes a new large-scale dataset for weakly supervised cross-media retrieval, named Twitter100k. Current datasets, such as Wikipedia, NUS Wide, and Flickr30k, have two major limitations. First, these datasets are lacking in content diversity, i.e., only some predefined classes are covered. Second, texts in these datasets are written in well-organized language, leading to inconsistency with realistic applications. To overcome these drawbacks, the proposed Twitter100k dataset is characterized by two aspects: it has 100 000 image-text pairs randomly crawled from Twitter, and thus, has no constraint in the image categories; and text in Twitter100k is written in informal language by the users. Since strongly supervised methods leverage the class labels that may be missing in practice, this paper focuses on weakly supervised learning for cross-media retrieval, in which only text-image pairs are exploited during training. We extensively benchmark the performance of four subspace learning methods and three variants of the correspondence AutoEncoder, along with various text features on Wikipedia, Flickr30k, and Twitter100k. As a minor contribution, we also design a deep neural network to learn cross-modal embeddings for Twitter100k. Inspired by the characteristic of Twitter100k, we propose a method to integrate optical character recognition into cross-media retrieval. The experiment results show that the proposed method improves the baseline performance.
Huang, H-L, Wang, X-L, Rohde, PP, Luo, Y-H, Zhao, Y-W, Liu, C, Li, L, Liu, N-L, Lu, C-Y & Pan, J-W 2018, 'Demonstration of topological data analysis on a quantum processor', Optica, vol. 5, no. 2, pp. 193-193.
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Huang, J, Duan, Q, Guo, S, Yan, Y & Yu, S 2018, 'Converged Network-Cloud Service Composition with End-to-End Performance Guarantee', IEEE Transactions on Cloud Computing, vol. 6, no. 2, pp. 545-557.
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Huang, L, Li, M, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Spectroscopic characteristics of dissolved organic matter from aquaculture wastewater and its interaction mechanism to chlorinated phenol compound', Journal of Molecular Liquids, vol. 263, pp. 422-427.
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© 2017 In present study, the characteristics of dissolved organic matter (DOM) from aquaculture wastewater and its interaction to 4-chlorophenol (4-CP) was evaluated via a spectroscopic approach. According to EEM-PARAFAC analysis, two components were derived from the interaction samples between DOM and 4-CP, including humic-like and fulvic-like substances for component 1 and protein-like substances for component 2, respectively. The fluorescence intensity scores of two PARAFAC-derived components decreased with increasing 4-CP concentration. Synchronous fluorescence coupled to two-dimensional correlation spectroscopy (2D-COS) implied that DOM fractions quenched different degrees and occurred in the order of fulvic-like and humic-like fractions > protein-like fraction. Moreover, the quenching mechanisms were mainly caused by static quenching process. It was also found from Fourier transform infrared spectroscopy that the main functional groups for interaction between 4-CP and DOM were O–H stretching and C[dbnd]O stretching vibration. The obtained results provided a spectroscopic approach for characterizing the interaction between organic pollutant and DOM from aquaculture wastewater.
Huang, L, Li, M, Si, G, Wei, J, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Assessment of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge: Extracellular polymeric substances contribution and soluble microbial products release', Journal of Colloid and Interface Science, vol. 527, pp. 87-94.
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© 2018 In the present study, the responses of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge were evaluated by using batch and spectroscopic approaches. Batch experimental data showed that extracellular polymeric substances (EPSs) contributed to Cu(II) removal from an aqueous solution, especially when treating low metal concentrations, whereas soluble microbial products (SMPs) were released under the metal stress during biosorption process. A three-dimensional excitation-emission matrix (3D-EEM) identified four main fluorescence peaks in the EPS, i.e., tryptophan protein-like, aromatic protein-like, humic-like and fulvic acid-like substances, and their fluorescence intensities decreased gradually in the presence of Cu(II) during the sorption process. Particularly, tryptophan protein-like substances quenched the Cu(II) binding to a much higher extent through a static quenching process with less than one class of binding sites. According to the synchronous fluorescence spectra, the whole fluorescence intensity of released SMP samples expressed an increased trend with different degrees along with contact time. Two-dimensional correlation spectroscopy (2D-COS) suggested that the fulvic-like fluorescence fraction might be more susceptible to metal exposure than other fractions. The result of molecular weight distribution demonstrated that the SMPs released from the biosorption process differed significantly according to contact time. The result obtained could provide new insights into the responses of microbial products from aerobic granular sludge with heavy metal treatment.
Huang, W, Alem, L, Tecchia, F & Duh, HB-L 2018, 'Augmented 3D hands: a gesture-based mixed reality system for distributed collaboration', Journal on Multimodal User Interfaces, vol. 12, no. 2, pp. 77-89.
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Huang, W, Li, J & Alem, L 2018, 'Towards Preventative Healthcare: A Review of Wearable and Mobile Applications.', Stud Health Technol Inform, vol. 251, pp. 11-14.
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Wearable and mobile devices are now commonly used in our daily activities, giving users instant access to various information. One the one hand, wearable and mobile technologies are developing at a fast rate and have been increasingly ubiquitous. On the other hand, the potential of their application in health is yet to be fully explored. This paper attempts to sketch an overview of wearable and mobile applications in the healthcare domain. We first review how various wearable and mobile applications are being used to monitor and manage health conditions. Then how connections between physiological factors and psychological factors can help with disease prevention is presented. Finally, challenges and future directions for further developments of these emerging technologies in health are discussed.
Huang, X, Zhang, J, Wu, Q, Fan, L & Yuan, C 2018, 'A Coarse-to-Fine Algorithm for Matching and Registration in 3D Cross-Source Point Clouds', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2965-2977.
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IEEE We propose an efficient method to deal with the matching and registration problem found in cross-source point clouds captured by different types of sensors. This task is especially challenging due to the presence of density variation, scale difference, a large proportion of noise and outliers, missing data and viewpoint variation. The proposed method has two stages: in the coarse matching stage, we use the ESF descriptor to select potential K regions from the candidate point clouds for the target. In the fine stage, we propose a scale embedded generative GMM registration method to refine the results from the coarse matching stage. Following the fine stage, both the best region and accurate camera pose relationships between the candidates and target are found. We conduct experiments in which we apply the method to two applications: one is 3D object detection and localization in street-view ourdoor (LiDAR/VSFM) cross-source point clouds, and the other is 3D scene matching and registration in indoor (KinectFusion/VSFM) cross-source point clouds. The experiment results show that the proposed method performs well when compared with the existing methods. It also shows that the proposed method is robust under various sensing techniques such as LiDAR, Kinect and RGB camera.
Huang, Y, Cao, L, Zhang, J, Pan, L & Liu, Y 2018, 'Exploring Feature Coupling and Model Coupling for Image Source Identification', IEEE Transactions on Information Forensics and Security, vol. 13, no. 12, pp. 3108-3121.
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© 2005-2012 IEEE. Recently, there has been great interest in feature-based image source identification. Previous statistical learning-based methods usually regarded the identification process as a classification problem. They assumed the dependence of features and the dependence of models. However, the two assumptions are usually problematic because of the genuine coupling of features and models. To address the issues, in this paper, we propose a novel image source identification scheme. For the feature coupling, a coupled feature representation is adopted to analyze the coupled interaction among features. The coupling relations among features and their powers are measured with Pearson's correlations and integrated in a Taylor-like expansion manner. Regarding model coupling, a new coupled probability representation is developed. The model coupling relationships are characterized with conditional probabilities induced by the confusion matrix and then combined with the law of total probability. The experiments carried out on the Dresden image collection confirm the effectiveness of the proposed scheme. Via mining the feature coupling and model coupling, the identification accuracy can be significantly improved.
Huang, Y, Ng, ECY, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Eco-driving technology for sustainable road transport: A review', Renewable and Sustainable Energy Reviews, vol. 93, pp. 596-609.
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© 2018 Elsevier Ltd Road transport consumes significant quantities of fossil fuel and accounts for a significant proportion of CO2 and pollutant emissions worldwide. The driver is a major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reviews the major factors, research methods and implementation of eco-driving technology. The major factors of eco-driving are acceleration/deceleration, driving speed, route choice and idling. Eco-driving training programs and in-vehicle feedback devices are commonly used to implement eco-driving skills. After training or using in-vehicle devices, immediate and significant reductions in fuel consumption and CO2 emissions have been observed with slightly increased travel time. However, the impacts of both methods attenuate over time due to the ingrained driving habits developed over the years. These findings imply the necessity of developing quantitative eco-driving patterns that could be integrated into vehicle hardware so as to generate more constant and uniform improvements, as well as developing more effective and lasting training programs and in-vehicle devices. Current eco-driving studies mainly focus on the fuel savings and CO2 reduction of individual vehicles, but ignore the pollutant emissions and the impacts at network levels. Finally, the challenges and future research directions of eco-driving technology are elaborated.
Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Emission measurement of diesel vehicles in Hong Kong through on-road remote sensing: Performance review and identification of high-emitters', Environmental Pollution, vol. 237, pp. 133-142.
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Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong', Atmospheric Environment, vol. 182, pp. 58-74.
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Huang, Y, Yam, YS, Lee, CKC, Organ, B, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Tackling nitric oxide emissions from dominant diesel vehicle models using on-road remote sensing technology', Environmental Pollution, vol. 243, no. Pt B, pp. 1177-1185.
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Remote sensing provides a rapid detection of vehicle emissions under real driving condition. Remote sensing studies showed that diesel nitrogen oxides emissions changed little or were even increasing in recent years despite the tightened emission standards. To more accurately and fairly evaluate the emission trends, it is hypothesized that analysis should be detailed for individual vehicle models as each model adopted different emissions control technologies and retrofitted the engine/vehicle at different time. Therefore, this study was aimed to investigate the recent nitric oxide (NO) emission trends of the dominant diesel vehicle models using a large remote sensing dataset collected in Hong Kong. The results showed that the diesel vehicle fleet was dominated by only seven models, accounting for 78% of the total remote sensing records. Although each model had different emission levels and trends, generally all the dominant models showed a steady decrease or stable level in the fuel based NO emission factors (g/kg fuel) over the period studied except for BaM1 and BdM2. A significant increase was observed for the BaM1 2.49 L and early 2.98 L models during 2005-2011, which we attribute to the change in the diesel fuel injection technology. However, the overall mean NO emission factor of all the vehicles was stable during 1991-2006 and then decreased steadily during 2006-2016, in which the emission trends of individual models were averaged out and thus masked. Nevertheless, the latest small, medium and heavy diesel vehicles achieved similar NO emission factors due to the converging of operation windows of the engine and emission control devices. The findings suggested that the increasingly stringent European emission standards were not very effective in reducing the NO emissions of some diesel vehicle models in the real world.
Huber, S, Koenig, R & Tomamichel, M 2018, 'Jointly constrained semidefinite bilinear programming with an application to Dobrushin curves', IEEE Trans Inf Theory, vol. 56, no. 5, pp. 2934-2950.
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We propose a branch-and-bound algorithm for minimizing a bilinear functional
of the form \[ f(X,Y) = \mathrm{tr}((X\otimes
Y)Q)+\mathrm{tr}(AX)+\mathrm{tr}(BY) , \] of pairs of Hermitian matrices
$(X,Y)$ restricted by joint semidefinite programming constraints. The
functional is parametrized by self-adjoint matrices $Q$, $A$ and $B$. This
problem generalizes that of a bilinear program, where $X$ and $Y$ belong to
polyhedra. The algorithm converges to a global optimum and yields upper and
lower bounds on its value in every step. Various problems in quantum
information theory can be expressed in this form. As an example application, we
compute Dobrushin curves of quantum channels, giving upper bounds on classical
coding with energy constraints.
Husin, H, Solo, BB, Ibrahim, IM, Chyuan, OH & Roslan, A 2018, 'Weight loss effect and potentiodynamic polarization response of 1-butyl-3-methylimidazolium chloride ionic liquid in highly acidic medium', Journal of Engineering Science and Technology, vol. 13, no. 4, pp. 1005-1015.
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Ionic liquids are increasingly being used as corrosion inhibitors when oil and gas industries started to give focus on sustainability and green impact in their operations. In this study, 1-butyl-3-methylimidazolium chloride ionic liquid in 2M HCl medium has been investigated on mild steel, stainless steel and aluminium bars by using weight loss technique and potentiodynamic polarization measurement. Results showed that 1-butyl-3-methylimidazolium chloride is able to reduce the weight loss of aluminium metal under acidic corrosive surrounding up to 11% compared to that of without the presence of 1-butyl-3-methylimidazolium chloride. Based on potentiodynamic polarization response, percentage of corrosion inhibition efficiency is found to be up to 99.3%. In summary, 1-butyl-3-methylimidazolium chloride is highly potential to act as an anti-corrosion agent, even in a very low concentration.
Hussain, W, Hussain, FK, Hussain, O, Bagia, R & Chang, E 2018, 'Risk-based framework for SLA violation abatement from the cloud service provider’s perspective', The Computer Journal, vol. 61, no. 9, pp. 1306-1322.
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The constant increase in the growth of the cloud market creates new challenges for cloud service providers. One such challenge is the need to avoid possible service level agreement (SLA) violations and their consequences through good SLA management. Researchers have proposed various frameworks and have made significant advances in managing SLAs from the perspective of both cloud users and providers. However, none of these approaches guides the service provider on the necessary steps to take for SLA violation abatement; that is, the prediction of possible SLA violations, the process to follow when the system identifies the threat of SLA violation, and the recommended action to take to avoid SLA violation. In this paper, we approach this process of SLA violation detection and abatement from a risk management perspective. We propose a Risk Management-based Framework for SLA violation abatement (RMF-SLA) following the formation of an SLA which comprises SLA monitoring, violation prediction and decision recommendation. Through experiments, we validate and demonstrate the suitability of the proposed framework for assisting cloud providers to minimize possible service violations and penalties.
Hussain, W, Hussain, FK, Saberi, M, Hussain, OK & Chang, E 2018, 'Comparing time series with machine learning-based prediction approaches for violation management in cloud SLAs', Future Generation Computer Systems, vol. 89, pp. 464-477.
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In cloud computing, service level agreements (SLAs) are legal agreements between a service provider and consumer that contain a list of obligations and commitments which need to be satisfied by both parties during the transaction. From a service provider’s perspective, a violation of such a commitment leads to penalties in terms of money and reputation and thus has to be effectively managed. In the literature, this problem has been studied under the domain of cloud service management. One aspect required to manage cloud services after the formation of SLAs is to predict the future Quality of Service (QoS) of cloud parameters to ascertain if they lead to violations. Various approaches in the literature perform this task using different prediction approaches however none of them study the accuracy of each. However, it is important to do this as the results of each prediction approach vary according to the pattern of the input data and selecting an incorrect choice of a prediction algorithm could lead to service violation and penalties. In this paper, we test and report the accuracy of time series and machine learning-based prediction approaches. In each category, we test many different techniques and rank them according to their order of accuracy in predicting future QoS. Our analysis helps the cloud service provider to choose an appropriate prediction approach (whether time series or machine learning based) and further to utilize the best method depending on input data patterns to obtain an accurate prediction result and better manage their SLAs to avoid violation penalties.
Hussaini, SKK, Indraratna, B & Vinod, JS 2018, 'A critical review of the performance of geosynthetic-reinforced railroad ballast', Geotechnical Engineering, vol. 49, no. 4, pp. 31-41.
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In the recent times, railway organizations across the world have resorted to the use of geosynthetics as a low-cost solution to stabilize ballast. In this view, extensive studies have been conducted worldwide to assess the performance of geosynthetic-reinforced ballast under various loading conditions. This paper evaluates the various benefits the rail industry could attain because of the geosynthetic reinforcement. A review of literature reveals that geogrid arrests the lateral spreading of ballast, reduces the extent of permanent vertical settlement and minimizes the particle breakage. The geogrid was also found to reduce the extent of volumetric compressions in ballast. The overall performance improvement due to geogrid was observed to be a function of the interface efficiency factor (φ). Moreover, studies also established the additional role of geogrids in reducing the differential track settlements and diminishing the stresses at the subgrade level. The geosynthetics were found to be more beneficial in case of tracks resting on soft subgrades. Furthermore, the benefits of geosynthetics in stabilizing ballast were found to be significantly higher when placed within the ballast. The optimum placement location of geosynthetics has been reported by several researchers to be about 200-250 mm below the sleeper soffit for a conventional ballast depth of 300-350 mm. A number of field investigations and track rehabilitation schemes also confirmed the role of geosynthetics/geogrids in stabilizing the tracks thereby helping in removing the stringent speed restrictions that were imposed earlier, and enhancing the time interval between maintenance operations.
Huynh, NV, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Wang, P 2018, 'Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning', IEEE Transactions on Communications, vol. 67, no. 8, pp. 5736-5752.
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Ambient backscatter has been introduced with a wide range of applications for
low power wireless communications. In this article, we propose an optimal and
low-complexity dynamic spectrum access framework for RF-powered ambient
backscatter system. In this system, the secondary transmitter not only harvests
energy from ambient signals (from incumbent users), but also backscatters these
signals to its receiver for data transmission. Under the dynamics of the
ambient signals, we first adopt the Markov decision process (MDP) framework to
obtain the optimal policy for the secondary transmitter, aiming to maximize the
system throughput. However, the MDP-based optimization requires complete
knowledge of environment parameters, e.g., the probability of a channel to be
idle and the probability of a successful packet transmission, that may not be
practical to obtain. To cope with such incomplete knowledge of the environment,
we develop a low-complexity online reinforcement learning algorithm that allows
the secondary transmitter to 'learn' from its decisions and then attain the
optimal policy. Simulation results show that the proposed learning algorithm
not only efficiently deals with the dynamics of the environment, but also
improves the average throughput up to 50% and reduces the blocking probability
and delay up to 80% compared with conventional methods.
Huynh, NV, Hoang, DT, Niyato, D, Wang, P & Kim, DI 2018, 'Optimal Time Scheduling for Wireless-Powered Backscatter Communication Networks', IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 820-823.
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This letter introduces a novel wireless-powered backscatter communication
system which allows sensors to utilize RF signals transmitted from a dedicated
RF energy source to transmit data. In the proposed system, when the RF energy
source transmits RF signals, the sensors are able to backscatter the RF signals
to transmit date to the gateway and/or harvest energy from the RF signals for
their operations. By integrating backscattering and energy harvesting
techniques, we can optimize the network throughput of the system. In
particular, we first formulate the time scheduling problem for the system, and
then propose an optimal solution using convex optimization to maximize the
overall network throughput. Numerical results show a significant throughput
gain achieved by our proposed design over two other baseline schemes.
Idrees, MO & Pradhan, B 2018, 'Geostructural stability assessment of cave using rock surface discontinuity extracted from terrestrial laser scanning point cloud', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 3, pp. 534-544.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The use of terrestrial laser scanning (TLS) in the caves has been growing drastically over the last decade. However, TLS application to cave stability assessment has not received much attention of researchers. This study attempted to utilize rock surface orientations obtained from TLS point cloud collected along cave passages to (1) investigate the influence of rock geostructure on cave passage development, and (2) assess cave stability by determining areas susceptible to different failure types. The TLS point cloud was divided into six parts (Entry hall, Chamber, Main hall, Shaft 1, Shaft 2 and Shaft 3), each representing different segments of the cave passages. Furthermore, the surface orientation information was extracted and grouped into surface discontinuity joint sets. The computed global mean and best–fit planes of the entire cave show that the outcrop dips 290° with a major north-south strike. But at individual level, the passages with dip angle between 26° and 80° are featured with dip direction of 75°–322°. Kinematic tests reveal the potential for various failure modes of rock slope. Our findings show that toppling is the dominant failure type accounting for high-risk rockfall in the cave, with probabilities of 75.26%, 43.07% and 24.82% in the Entry hall, Main hall and Shaft 2, respectively. Unlike Shaft 2 characterized by high risk of the three failure types (32.49%, 24.82% and 50%), the chamber and Shaft 3 passages are not suffering from slope failure. The results also show that the characteristics of rock geostructure considerably influence the development of the cave passages, and four sections of the cave are susceptible to different slope failure types, at varying degrees of risk.
Imani, MH, Ghadi, MJ, Ghavidel, S & Li, L 2018, 'Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs', Renewable and Sustainable Energy Reviews, vol. 94, pp. 486-499.
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© 2018 Elsevier Ltd During recent years, with the advent of restructuring in power systems as well as the increase of electricity demand and global fuel energy prices, challenges related to implementing demand response programs (DRPs) have gained remarkable attention of independent system operators (ISOs) and customers, aiming at the improvement of attributes of the load curve and reduction of energy consumption as well as benefiting customers. In this paper, different types of DRPs are modeled based on price elasticity of the demand and the concept of customer benefit. Besides, the impact of implementing DRPs on the operation of grid-connected microgrid (MG) is analyzed. Moreover, several scenarios are presented in order to model uncertainties interfering MG operations including failure of generation units and random outages of transmission lines and upstream line, error in load demand forecasting, uncertainty in production of renewable energies (wind and solar) based distributed generation units, and the possibility that customers do not respond to scheduled interruptions. Simulations are conducted for two principal categories of DRP including incentive-based programs and time-based programs on an 11-bus MG over a 24-h period and also a 14-bus MG over a period of 336 h (two weeks). Simulation results indicate the effects of DRPs on total operation costs, customer's benefit, and load curve as well as determining optimal use of energy resources in the MG operation. In this regard, prioritizing of DRPs on the MG operation is required.
Inan, DI, Beydoun, G & Opper, S 2018, 'Agent-Based Knowledge Analysis Framework in Disaster Management.', Inf. Syst. Frontiers, vol. 20, pp. 783-802.
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© 2017 Springer Science+Business Media, LLC Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.
Inan, DI, Beydoun, G & Pradhan, B 2018, 'Developing a decision support system for Disaster Management: Case study of an Indonesia volcano eruption', International Journal of Disaster Risk Reduction, vol. 31, pp. 711-721.
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Indraratna, B, Baral, P, Rujikiatkamjorn, C & Perera, D 2018, 'Class A and C predictions for Ballina trial embankment with vertical drains using standard test data from industry and large diameter test specimens', Computers and Geotechnics, vol. 93, pp. 232-246.
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Indraratna, B, Ferreira, FB, Qi, Y & Ngo, TN 2018, 'Application of geoinclusions for sustainable rail infrastructure under increased axle loads and higher speeds', Innovative Infrastructure Solutions, vol. 3, no. 1.
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© 2018, Springer Nature Switzerland AG. Given the ongoing demand for faster trains for carrying heavier loads, conventional ballasted railroads require considerable upgrading in order to cope with the increasing traffic-induced stresses. During train operations, ballast deteriorates due to progressive breakage and fouling caused by the infiltration of fine particles from the surface or mud-pumping from the underneath layers (e.g. sub-ballast, sub-grade), which decreases the load bearing capacity, impedes drainage and increases the deformation of ballasted tracks. Suitable ground improvement techniques involving geosynthetics and resilient rubber sheets are commonly employed to enhance the stability and longevity of rail tracks. This keynote paper focuses mainly on research projects undertaken at the University of Wollongong to improve track performance by emphasising the main research outcomes and their practical implications. Results from laboratory tests, computational modelling and field trials have shown that track behaviour can be significantly improved by the use of geosynthetics, energy-absorbing rubber mats, rubber crumbs and infilled-recycled tyres. Full-scale monitoring of instrumented track sections supported by rail industry (ARTC) has been performed, and the obtained field data for in situ stresses and deformations could verify the track performance, apart from validating the numerical simulations. The research outcomes provide promising approaches that can be incorporated into current track design practices to cater for high-speed freight trains carrying heavier loads.
Indraratna, B, Israr, J & Li, M 2018, 'Inception of geohydraulic failures in granular soils – an experimental and theoretical treatment', Géotechnique, vol. 68, no. 3, pp. 233-248.
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This paper outlines an experimental investigation into seepage-induced failures in soils subjected to static and cyclic loading. Internally stable, marginal and unstable soils are characterised by heave, composite heave–piping and suffusion that develops immediately upon instability. In this study, the stable specimens exhibited heave at larger hydraulic gradients than the unstable specimens failing by suffusion at relatively smaller hydraulic gradients. Under no external load (i.e. self-weight only), the relative density (Rd) and particle size distribution (PSD) in tandem controlled the internal stability of soils, although the effective stress magnitude (σ′vt) also had a role to play under both static and cyclic loading conditions. Instability in soils was governed by specific combinations of their geo-hydro-mechanical characteristics such as PSD, Rd, stress reduction factor, critical hydraulic gradients and associated effective stress levels. These factors are combined to model the development and inception of instability, and the paper offers visual guides as a practical tool for practitioners. Each soil has a unique critical envelope related to its PSD and Rd, and a critical path with its inclination that depends on the hydro-mechanical conditions. The current results of internal erosion tests conducted by the authors plus those adopted from published literature are used to verify the proposed model.
Indraratna, B, Qi, Y & Heitor, A 2018, 'Evaluating the Properties of Mixtures of Steel Furnace Slag, Coal Wash, and Rubber Crumbs Used as Subballast', Journal of Materials in Civil Engineering, vol. 30, no. 1, pp. 04017251-04017251.
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Indraratna, B, Sun, Q, Heitor, A & Grant, J 2018, 'Performance of Rubber Tire-Confined Capping Layer under Cyclic Loading for Railroad Conditions', Journal of Materials in Civil Engineering, vol. 30, no. 3, pp. 06017021-06017021.
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Ingkiriwang, YG & Far, H 2018, 'Numerical investigation of the design of single-span steel portal frames using the effective length and direct analysis methods', Steel Construction, vol. 11, no. 3, pp. 184-191.
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The era of globalisation enables the design, fabrication and erection of steel structures to take place in different locations far away from each other. Therefore, a widely acceptable steel design standard is required, and designers should be familiar with alternative specifications that may be considerably different from one another. This study deals with single span unbraced steel portal frames and makes a comparison between the design methodologies adopted by the Australian and American design provisions, in particular, the effective length method (ELM) and direct analysis method (DAM). A brief discussion on the main features of both standards is also presented. Furthermore, the results of the parametric study are portrayed, highlighting the differences between these two design standards regarding stress interaction.
Finally, of the two aforementioned methods, the most applicable optimisation method for the design and development of cost-effective industrial portal frame buildings is proposed with respect to the structure geometry.
Irga, PJ, Pettit, TJ & Torpy, FR 2018, 'The phytoremediation of indoor air pollution: a review on the technology development from the potted plant through to functional green wall biofilters', Reviews in Environmental Science and Bio/Technology, vol. 17, no. 2, pp. 395-415.
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Poor indoor air quality is a health problem of escalating magnitude, as communities become increasingly urbanised and people’s behaviours change, lending to lives spent almost exclusively in indoor environments. The accumulation of, and continued exposure to, indoor air pollution has been shown to result in detrimental health outcomes. Particulate matter penetrating into the building, volatile organic compounds (VOCs) outgassing from synthetic materials and carbon dioxide from human respiration are the main contributors to these indoor air quality concerns. Whilst a range of physiochemical methods have been developed to remove contaminants from indoor air, all methods have high maintenance costs. Despite many years of study and substantial market demand, a well evidenced procedure for indoor air bioremediation for all applications is yet to be developed. This review presents the main aspects of using horticultural biotechnological tools for improving indoor air quality, and explores the history of the technology, from the humble potted plant through to active botanical biofiltration. Regarding the procedure of air purification by potted plants, many researchers and decades of work have confirmed that the plants remove CO2 through photosynthesis, degrade VOCs through the metabolic action of rhizospheric microbes, and can sequester particulate matter through a range of physical mechanisms. These benefits notwithstanding, there are practical barriers reducing the value of potted plants as standalone air cleaning devices. Recent technological advancements have led to the development of active botanical biofilters, or functional green walls, which are becoming increasingly efficient and have the potential for the functional mitigation of indoor air pollutant concentrations.
Ishac, K & Suzuki, K 2018, 'LifeChair: A Conductive Fabric Sensor-Based Smart Cushion for Actively Shaping Sitting Posture', Sensors, vol. 18, no. 7, pp. 2261-2261.
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The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored in the past, but a full sensing solution for embedded real world use has not been proposed. We have designed our system with commercial use in mind, and as a result, it has a high focus on manufacturability, cost-effectiveness and adaptiveness. We demonstrate the performance of our fabric sensing system by installing it into the LifeChair and comparing its posture detection accuracy with our previous study that implemented a conventional flexible printed PCB-sensing system. In this study, it is shown that the LifeChair can detect all 11 postures across 20 participants with an improved average accuracy of 98.1%, and it demonstrates significantly lower variance when interfacing with different users. We also conduct a performance study with 10 participants to evaluate the effectiveness of the LifeChair device in improving upright posture and reducing slouching. Our performance study demonstrates that the LifeChair is effective in encouraging users to sit upright with an increase of 68.1% in time spent seated upright when vibrotactile feedback is activated.
Islam, M, Mithulananthan, N & Hossain, MJ 2018, 'Dynamic Voltage Support by TL-PV Systems to Mitigate Short-Term Voltage Instability in Residential DN', IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4360-4370.
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Islam, MR, Muttaqi, KM, Sutanto, D & Zhu, J 2018, 'Design and Implementation of Amorphous Magnetic Material Common Magnetic Bus for the Replacement of Common DC Bus', IEEE Transactions on Magnetics, vol. 54, no. 11, pp. 1-4.
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Islam, MS, Saha, SC, Gemci, T, Yang, IA, Sauret, E & Gu, YT 2018, 'Polydisperse Microparticle Transport and Deposition to the Terminal Bronchioles in a Heterogeneous Vasculature Tree', Scientific Reports, vol. 8, no. 1.
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AbstractThe atmospheric particles from different sources, and the therapeutic particles from various drug delivery devices, exhibit a complex size distribution, and the particles are mostly polydisperse. The limited available in vitro, and the wide range of in silico models have improved understanding of the relationship between monodisperse particle deposition and therapeutic aerosol transport. However, comprehensive polydisperse transport and deposition (TD) data for the terminal airways is still unavailable. Therefore, to benefit future drug therapeutics, the present numerical model illustrates detailed polydisperse particle TD in the terminal bronchioles for the first time. Euler-Lagrange approach and Rosin-Rammler diameter distribution is used for polydisperse particles. The numerical results show higher deposition efficiency (DE) in the right lung. Specifically, the larger the particle diameter (dp > 5 μm), the higher the DE at the bifurcation area of the upper airways is, whereas for the smaller particle (dp < 5 μm), the DE is higher at the bifurcation wall. The overall deposition pattern shows a different deposition hot spot for different diameter particle. These comprehensive lobe-specific polydisperse particle deposition studies will increase understanding of actual inhalation for particle TD, which could potentially increase the efficiency of pharmaceutical aerosol delivery at the targeted position of the terminal airways.
Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR & Jamalipour, A 2018, 'Analysis of Effective Capacity and Throughput of Polling-Based Device-To-Device Networks.', IEEE Trans. Veh. Technol., vol. 67, no. 9, pp. 8656-8666.
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© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model.
Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR, Dutkiewicz, E, Krunz, M & Jamalipour, A 2018, 'PCF-Based LTE Wi-Fi Aggregation for Coordinating and Offloading the Cellular Traffic to D2D Network.', IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12193-12203.
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© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1.
Israr, J & Indraratna, B 2018, 'Assessment of internal stability of filters under static and cyclic loading: An experimental and theoretical treatment', Australian Geomechanics Journal, vol. 53, no. 4, pp. 103-116.
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The occurrence of internal instability may significantly affect geo-mechanical characteristics of granular filters such as permeability and particle size distribution, consequently rendering them ineffective in retaining the protected base soils and thereby endangering the structural stability. This paper presents the results of 65 hydraulic tests performed on ten different granular soils compacted at varying relative densities between 0 and 100% and subjected to an upward hydraulic flow under both static and cyclic conditions. It was observed that the internal stability is a function of particle gradation and relative density in tandem, i.e. constriction size distribution, under static conditions. However, the agitation and pore pressure development under cyclic loading triggered excessively premature internal erosion in filters. Based on the analysis, new constriction-based criteria proposed for both static and cyclic conditions that showed remarkable accuracy in correctly assessing the potential of instability of filters compared to many existing criteria. Moreover, a new hydromechanical model is presented that could accurately capture the correct potential of instability of filters, thereby contributing toward increased confidence level for practical design of filters. Two practical design examples presented to demonstrate the implications of this research study in practice to conclude this paper.
Israr, J & Indraratna, B 2018, 'Closure to “Internal Stability of Granular Filters under Static and Cyclic Loading” by Jahanzaib Israr and Buddhima Indraratna', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 12, pp. 07018033-07018033.
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Israr, J & Indraratna, B 2018, 'Mechanical response and pore pressure generation in granular filters subjected to uniaxial cyclic loading', Canadian Geotechnical Journal, vol. 55, no. 12, pp. 1756-1768.
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This paper presents results from a series of piping tests carried out on a selected range of granular filters under static and cyclic loading conditions. The mechanical response of filters subjected to cyclic loading could be characterized in three distinct phases; namely, (I) pre-shakedown, (II) post-shakedown, and (III) post-critical (i.e., the occurrence of internal erosion). All the permanent geomechanical changes such, as erosion, permeability variations, and axial strain developments, took place during phases I and III, while the specimen response remained purely elastic during phase II. The post-critical occurrence of erosion incurred significant settlement that may not be tolerable for high-speed railway substructures. The analysis revealed that a cyclic load would induce excess pore-water pressure, which, in corroboration with steady seepage forces and agitation due to dynamic loading, could then cause internal erosion of fines from the specimens. The resulting excess pore pressure is a direct function of the axial strain due to cyclic densification, as well as the loading frequency and reduction in permeability. A model based on strain energy is proposed to quantify the excess pore-water pressure, and subsequently validated using current and existing test results from published studies.
Ivanyos, G, Qiao, Y & Subrahmanyam, KV 2018, 'Constructive non-commutative rank computation is in deterministic polynomial time', computational complexity, vol. 27, no. 4, pp. 561-593.
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Jafarzadeh, H, Akbari, P & Abedin, B 2018, 'A methodology for project portfolio selection under criteria prioritisation, uncertainty and projects interdependency – combination of fuzzy QFD and DEA', Expert Systems with Applications, vol. 110, pp. 237-249.
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Jakowiecki, J, Sztyler, A, Filipek, S, Li, P, Raman, K, Barathiraja, N, Ramakrishna, S, Eswara, JR, Altaee, A, Sharif, AO, Ajayan, PM & Renugopalakrishnan, V 2018, 'Aquaporin–graphene interface: relevance to point-of-care device for renal cell carcinoma and desalination', Interface Focus, vol. 8, no. 3, pp. 20170066-20170066.
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The aquaporin superfamily of hydrophobic integral membrane proteins constitutes water channels essential to the movement of water across the cell membrane, maintaining homeostatic equilibrium. During the passage of water between the extracellular and intracellular sides of the cell, aquaporins act as ultra-sensitive filters. Owing to their hydrophobic nature, aquaporins self-assemble in phospholipids. If a proper choice of lipids is made then the aquaporin biomimetic membrane can be used in the design of an artificial kidney. In combination with graphene, the aquaporin biomimetic membrane finds practical application in desalination and water recycling using mostly
Escherichia coli
AqpZ. Recently, human aquaporin 1 has emerged as an important biomarker in renal cell carcinoma. At present, the ultra-sensitive sensing of renal cell carcinoma is cumbersome. Hence, we discuss the use of epitopes from monoclonal antibodies as a probe for a point-of-care device for sensing renal cell carcinoma. This device works by immobilizing the antibody on the surface of a single-layer graphene, that is, as a microfluidic device for sensing renal cell carcinoma.
Jamil, S, Jeong, S & Vigneswaran, S 2018, 'Application of forward osmosis membrane in nanofiltration mode to treat reverse osmosis concentrate from wastewater reclamation plants', Water Science and Technology, vol. 77, no. 8, pp. 1990-1997.
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Abstract
Reverse osmosis concentrate (ROC) from wastewater reclamation plants have high concentrations of organic and inorganic compounds, which have to be removed before its disposal. Forward osmosis (FO) and nanofiltration (NF) membranes were tested to treat the ROC for possible water reuse. This research investigated the combined and individual influence of organic and inorganic matter on the fouling of NF and FO membranes. The results revealed that the NF membrane removed most of the organic compounds and some inorganics. The study further highlighted that the FO membrane at NF mode removed the majority of the inorganic compounds and some organics from the ROC. A pretreatment of granulated activated carbon (GAC) adsorption removed 90% of the organic compounds from ROC. In addition, GAC adsorption and acid pretreatment of ROC improved the net water permeate flux by 17% when an FO membrane was used in the NF system. Acid treatment (by bringing the pH down to 5) helped to remove inorganic ions. Therefore, the resultant permeate can be recycled back to the RO water reclamation plant to improve its efficiency.
Jan, MA, Nanda, P, He, X & Liu, RP 2018, 'A Sybil attack detection scheme for a forest wildfire monitoring application', Future Generation Computer Systems, vol. 80, pp. 613-626.
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Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter, etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user’s specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to a wildfire. Our proposed approach has better network lifetime due to efficient sleep–awake scheduling, higher detection rate and low false-negative rate.
Jan, MA, Tan, Z, He, X & Ni, W 2018, 'Moving towards highly reliable and effective sensor networks', Ad-Hoc and Sensor Wireless Networks, vol. 40, no. 3-4, pp. 163-168.
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Wireless Sensor Networks (WSNs) have been the preferred choice for the
design and deployment of next generation monitoring and control systems
[1]. In these networks, the sensor nodes forward their sensed data towards a
centralized base station. The neighboring nodes frequently sense correlated
data and forward towards the base station, using disjoints multiple paths [2].
As a result, the area around the base station becomes congested with all the
traffic converging towards it. Apart from packet lost due to congestion, a
significant number of packets are lost due to interference, packet collision,
node failure and transmission errors [3]. For a successful monitoring of the
deployed environment, the critical data collected by the sensor nodes need to
be reliably and effectively delivered to the base station. Given the error-prone
nature of the wireless links, ensuring reliable transmission of data from
resource-constrained sensor nodes towards the base station continues to be
one of the major challenges in the field of WSNs [4]. Retransmission and
redundancy are classified as the two main approaches to achieve data transmission reliability in WSNs. However, retransmission and redundancy techniques perform better when using hop-by-hop transmission approach as
compared to end-to-end transmission. Using hop-by-hop approach introduces
in-node processing overhead and incurs high overall latency in reporting data
to the base station. As a result, hybrid approaches need to be adopted to ensure highly reliable and effective data transmission towards the base stations in WSNs.
The specific objective of this special issue is to collect high quality research
articles with solid background in both theoretical and practical aspects of reliability and effectiveness for WSNs. This special issue focuses on various
topics pertaining to reliable and effective communication such as, fault-tolerance, energy-efficiency, topology control, load-balancing, propagation pathloss, co-channe...
Jayabarathi, T, Raghunathan, T & Gandomi, AH 2018, 'The Bat Algorithm, Variants and Some Practical Engineering Applications: A Review', vol. 744, pp. 313-330.
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© Springer International Publishing AG 2018. The bat algorithm (BA), a metaheuristic algorithm developed by Xin-She Yang in 2010, has since been modified, and applied to numerous practical optimization problems in engineering. This chapter is a survey of the BA, its variants, some sample real-world optimization applications, and directions for future research.
Jayawickrama, BA, He, Y, Dutkiewicz, E & Mueck, MD 2018, 'Scalable Spectrum Access System for Massive Machine Type Communication', IEEE Network, vol. 32, no. 3, pp. 154-160.
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Jhang, J-Y, Lin, C-J, Lin, C-T & Young, K-Y 2018, 'Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization', International Journal of Control, Automation and Systems, vol. 16, no. 5, pp. 2446-2457.
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© 2018, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature. This paper presents an effective navigation control method for mobile robots in an unknown environment. The proposed behavior manager (BM) switches between two behavioral control patterns, wall-following behavior (WFB) and toward-goal behavior (TGB), based on the relationship between the mobile robot and the unknown environment. An interval type-2 fuzzy neural controller with a dynamic-group particle swarm optimization (DGPSO) algorithm is proposed to provide WFB control and obstacle avoidance for mobile robots. In the WFB learning process, the input signal of a controller is the distance between the wall and the sonar sensors, and its output signal is the speed of two wheels of a mobile robot. A fitness function, which operates on the total distance traveled by the mobile robot, distance from the side wall, angle to the side wall, and moving speed, evaluates the WFB performance of the mobile robot. In addition, an escape mechanism is proposed to avoid a dead cycle. Experimental results reveal that the proposed DGPSO is superior to other methods in WFB and navigation control.
Ji, K, Chen, Z, Sun, R, Ma, K, Yuan, Z & Xu, G 2018, 'GIST: A generative model with individual and subgroup-based topics for group recommendation', Expert Systems with Applications, vol. 94, pp. 81-93.
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© 2017 Elsevier Ltd In this paper, a Topic-based probabilistic model named GIST is proposed to infer group activities, and make group recommendations. Compared with existing individual-based aggregation methods, it not only considers individual members’ interest, but also consider some subgroups’ interest. Intuition might seem that when a group of users want to take part in an activity, not every group member is decisive, instead, more likely the subgroups of members having close relationships lead to the final activity decision. That motivates our study on jointly considering individual members’ choices and subgroups’ choices for group recommendations. Based on this, our model uses two kinds of unshared topics to model individual members’ interest and subgroups’ interest separately, and then make final recommendations according to the choices from the two aspects with a weight-based scheme. Moreover, the link information in the graph topology of the groups can be used to optimize the weights of our model. The experimental results on real-life data show that the recommendation accuracy is significantly improved by GIST comparing with the state-of-the-art methods.
Ji, L-Y, Qin, P-Y & Guo, YJ 2018, 'Wideband Fabry-Perot Cavity Antenna With a Shaped Ground Plane', IEEE Access, vol. 6, pp. 2291-2297.
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© 2013 IEEE. This paper proposes a novel approach to broaden the 3-dB gain bandwidth of Fabry-Perot cavity (FPC) antennas by utilizing a shaped ground plane. The shaped ground plane is flat in the middle to accommodate the source antenna, and then angled up in the shape of trapezoids. Compared with an FPC antenna with a traditional flat ground plane, the 3-dB gain bandwidth of the one with a shaped ground plane is improved from 11% to 20.2% with the maximum realized gain and the 10-dB impedance bandwidth almost unchanged. To validate the feasibility of the proposed approach, an FPC antenna prototype has been designed, fabricated, and measured. It consists of a U-slot rectangular microstrip patch antenna as the source, a Rogers RT6006 superstrate as the partially reflective surface, and the proposed shaped ground plane. Measured results on input reflection coefficients and radiation patterns agree well with simulated ones. Therefore, this new approach can be an effective way to enhance the gain bandwidth without increasing the cavity profile or using multi-layer superstrate structures.
Ji, S, Yu, CP, Fung, S-F, Pan, S & Long, G 2018, 'Supervised Learning for Suicidal Ideation Detection in Online User Content', Complexity, vol. 2018, pp. 1-10.
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Early detection and treatment are regarded as the most effective ways to prevent suicidal ideation and potential suicide attempts—two critical risk factors resulting in successful suicides. Online communication channels are becoming a new way for people to express their suicidal tendencies. This paper presents an approach to understand suicidal ideation through online user-generated content with the goal of early detection via supervised learning. Analysing users’ language preferences and topic descriptions reveals rich knowledge that can be used as an early warning system for detecting suicidal tendencies. Suicidal individuals express strong negative feelings, anxiety, and hopelessness. Suicidal thoughts may involve family and friends. And topics they discuss cover both personal and social issues. To detect suicidal ideation, we extract several informative sets of features, including statistical, syntactic, linguistic, word embedding, and topic features, and we compare six classifiers, including four traditional supervised classifiers and two neural network models. An experimental study demonstrates the feasibility and practicability of the approach and provides benchmarks for the suicidal ideation detection on the active online platforms: Reddit SuicideWatch and Twitter.
Jia, H, Liu, W, Wang, J, Ngo, H-H, Guo, W & Zhang, H 2018, 'Optimization of sensing performance in an integrated dual sensors system combining microbial fuel cells and upflow anaerobic sludge bed reactor', Chemosphere, vol. 210, pp. 931-940.
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Jian, S, Cao, L, Lu, K & Gao, H 2018, 'Unsupervised Coupled Metric Similarity for Non-IID Categorical Data', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 9, pp. 1810-1823.
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© 1989-2012 IEEE. Appropriate similarity measures always play a critical role in data analytics, learning, and processing. Measuring the intrinsic similarity of categorical data for unsupervised learning has not been substantially addressed, and even less effort has been made for the similarity analysis of categorical data that is not independent and identically distributed (non-IID). In this work, a Coupled Metric Similarity (CMS) is defined for unsupervised learning which flexibly captures the value-to-attribute-to-object heterogeneous coupling relationships. CMS learns the similarities in terms of intrinsic heterogeneous intra-and inter-attribute couplings and attribute-to-object couplings in categorical data. The CMS validity is guaranteed by satisfying metric properties and conditions, and CMS can flexibly adapt to IID to non-IID data. CMS is incorporated into spectral clustering and k-modes clustering and compared with relevant state-of-the-art similarity measures that are not necessarily metrics. The experimental results and theoretical analysis show the CMS effectiveness of capturing independent and coupled data characteristics, which significantly outperforms other similarity measures on most datasets.
Jiang, J, Wen, S, Yu, S, Xiang, Y & Zhou, W 2018, 'Rumor Source Identification in Social Networks with Time-Varying Topology', IEEE Transactions on Dependable and Secure Computing, vol. 15, no. 1, pp. 166-179.
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© 2004-2012 IEEE. Identifying rumor sources in social networks plays a critical role in limiting the damage caused by them through the timely quarantine of the sources. However, the temporal variation in the topology of social networks and the ongoing dynamic processes challenge our traditional source identification techniques that are considered in static networks. In this paper, we borrow an idea from criminology and propose a novel method to overcome the challenges. First, we reduce the time-varying networks to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual in traditional techniques, we adopt a reverse dissemination strategy to specify a set of suspects of the real rumor source. This process addresses the scalability issue of source identification problems, and therefore dramatically promotes the efficiency of rumor source identification. Third, to determine the real source from the suspects, we employ a novel microscopic rumor spreading model to calculate the maximum likelihood (ML) for each suspect. The one who can provide the largest ML estimate is considered as the real source. The evaluations are carried out on real social networks with time-varying topology. The experiment results show that our method can reduce 60 - 90 percent of the source seeking area in various time-varying social networks. The results further indicate that our method can accurately identify the real source, or an individual who is very close to the real source. To the best of our knowledge, the proposed method is the first that can be used to identify rumor sources in time-varying social networks.
Jiang, Q, Ngo, HH, Nghiem, LD, Hai, FI, Price, WE, Zhang, J, Liang, S, Deng, L & Guo, W 2018, 'Effect of hydraulic retention time on the performance of a hybrid moving bed biofilm reactor-membrane bioreactor system for micropollutants removal from municipal wastewater', Bioresource Technology, vol. 247, pp. 1228-1232.
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This study evaluated micropollutants removal and membrane fouling behaviour of a hybrid moving bed biofilm reactor-membrane bioreactor (MBBR-MBR) system at four different hydraulic retention times (HRTs) (24, 18, 12 and 6h). The results revealed that HRT of 18h was the optimal condition regarding the removal of most selected micropollutants. As the primary removal mechanism in the hybrid system was biodegradation, the attached growth pattern was desirable for enriching slow growing bacteria and developing a diversity of biocoenosis. Thus, the efficient removal of micropollutants was obtained. In terms of membrane fouling propensity analysis, a longer HRT (e.g. HRTs of 24 and 18h) could significantly mitigate membrane fouling when compared with the shortest HRT of 6h. Hence, enhanced system performance could be achieved when the MBBR-MBR system was operated at HRT of 18h.
Jing, D, Huang, Y, Liu, X, Sia, KCS, Zhang, JC, Tai, X, Wang, M, Toscan, CE, McCalmont, H, Evans, K, Mayoh, C, Poulos, RC, Span, M, Mi, J, Zhang, C, Wong, JWH, Beck, D, Pimanda, JE & Lock, RB 2018, 'Lymphocyte-Specific Chromatin Accessibility Pre-determines Glucocorticoid Resistance in Acute Lymphoblastic Leukemia', Cancer Cell, vol. 34, no. 6, pp. 906-921.e8.
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Jing, N, Jiang, T, Du, J & Sugumaran, V 2018, 'Personalized recommendation based on customer preference mining and sentiment assessment from a Chinese e-commerce website', Electronic Commerce Research, vol. 18, no. 1, pp. 159-179.
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Jonasson, OJ & Kandasamy, J 2018, 'Decentralised water reuse in Sydney, Australia: drivers for implementation and energy consumption', Journal of Environmental Engineering and Science, vol. 13, no. 1, pp. 2-7.
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Water recycling and reuse is becoming increasingly common throughout the world. The objective of this study was to compare five decentralised water recycling and reuse systems in Sydney, Australia, in terms of the drivers for their implementation and their ongoing energy consumption, allowing comparison to conventional water sources. The security of supply was found to be the main driver for four out of the five schemes. For the fifth scheme, the driver was to obtain a high environmental rating for the building it is located in. The analysis shows that water reuse can provide water at the same or less energy consumption compared to water supplied through the mains network. However, where the water recycling ethos of ‘fit for purpose’ is not considered, this can often lead to a significant overall increase in power consumption. This study highlights the need for regulatory bodies to consider a wider range of impacts when preparing guidelines and incentive schemes for water reuse. When the focus is too narrow, there is a risk that unintentional negative impacts such as increased power consumption and potential carbon dioxide emissions are the outcomes.
Jordaan, J, Punzet, S, Melnikov, A, Sanches, A, Oberst, S, Marburg, S & Powell, DA 2018, 'Measuring monopole and dipole polarizability of acoustic meta-atoms', Applied Physics Letters, vol. 113, no. 22, pp. 224102-224102.
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© 2018 Author(s). We present a method to extract monopole and dipole polarizability from experimental measurements of two-dimensional acoustic meta-atoms. In contrast to extraction from numerical results, this enables all second-order effects and uncertainties in material properties to be accounted for. We apply the technique to 3D-printed labyrinthine meta-atoms of a variety of geometries. We show that the polarizability of structures with a shorter acoustic path length agrees well with numerical results. However, those with longer path lengths suffer strong additional damping, which we attribute to the strong viscous and thermal losses in narrow channels.
Jordan, R, Gray, S, Zellner, M, Glynn, PD, Voinov, A, Hedelin, B, Sterling, EJ, Leong, K, Olabisi, LS, Hubacek, K, Bommel, P, BenDor, TK, Jetter, AJ, Laursen, B, Singer, A, Giabbanelli, PJ, Kolagani, N, Carrera, LB, Jenni, K & Prell, C 2018, 'Twelve Questions for the Participatory Modeling Community', Earth's Future, vol. 6, no. 8, pp. 1046-1057.
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©2018. The Authors. Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio-Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.
Joshi, S, Sharma, M, Kumar, S & Pant, MK 2018, 'Co-Creation Among Small Scale Tourism Firm', International Journal of Strategic Information Technology and Applications, vol. 9, no. 4, pp. 1-14.
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ICT enabled tourism brings planners and actors into a common platform. Uttarakhand falls under the L4 (above average) category as per an e-readiness report and subsequently within the span of 5 years, it has climbed to level L3 after the infusion of web-based technologies. Tourism Firm's innovation is primarily based on following criteria: coexistence with existing competitors, cross-value chain income generating activities (IGA) along tourism, new products/processes developed in the past 2 years. An intensive literature review has been done, out of which three critical success factors were identified: (a) Internet usage; (b) firm's innovation and competitiveness; (c) income generating activities (IGA) by the firm. Together, these critical success factors (CSFs) express high cumulative variance. The study identifies co-innovation strategies among supply chain actors at the micro and small levels, which is based on cross-functional linkage between allied industries, and on internet use and IGAs. Validation has been done using an explorative study.
Ju, M, Ding, C, Zhang, D & Guo, YJ 2018, 'Gamma-Correction-Based Visibility Restoration for Single Hazy Images', IEEE Signal Processing Letters, vol. 25, no. 7, pp. 1084-1088.
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© 1994-2012 IEEE. In this letter, a concise gamma-correction-based dehazing model (GDM) is proposed. This GDM explicitly describes the inner relationship between the gamma correction (GC) and the traditional scattering model. Combined with the existing priori constraints, GDM is further approximated into a one-dimensional (1-D) function to seek the only unknown constant that is used for haze removal. Using the determined constant, the scene albedo can be recovered, eliminating the haze from single hazy images. The proposed GDM is able to suppress the halo/blocking artifacts in the recovered results due to the scene albedo, which is less sensitive to the determined constant. Simulation results on different types of benchmark images verify that the proposed technique outperforms state-of-the-art methods in terms of both recovery, quality, and real-time performance.
Jumaah, HJ, Mansor, S, Pradhan, B & Adam, SN 2018, 'UAV-based PM2.5 monitoring for small-scale urban areas', International Journal of Geoinformatics, vol. 14, no. 4, pp. 61-69.
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Air quality data such as Particulate Matter PM2.5 collection near the ground is difficult, particularly in small complex regions. This study aims to introduce a PM2.5 prediction algorithm based on measurements from Unmanned Arial Vehicle (UAV)-based sensing system and validate the model at a specified low altitude. Observations were applied around 1.6 km2 area in University Putra Malaysia. This study uses an empirical method via applying amassed records of PM2.5 and meteorological parameters to produce a predictive Geographically Weighted Regression (GWR) model. An accuracy value is computed from the probability value given by the regression analysis model. To validate this approach, we have utilized training and testing data. To evaluate and validate the suggested model, we applied the model to the training set. The obtained result indicated that there is a good statistical correlation, and demonstrated that the characteristics obtained by analysis are able to predict the concentration of PM2.5.
Kabir, MI, Subhani, M, Shrestha, R & Samali, B 2018, 'Experimental and theoretical analysis of severely damaged concrete beams strengthened with CFRP', Construction and Building Materials, vol. 178, pp. 161-174.
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© 2018 Elsevier Ltd In recent years, carbon fibre reinforced polymer (CFRP) has gained its popularity for repairing reinforced concrete structures. At the same time, numerous research have been conducted on the use of different admixtures in the concrete to enhance its various physical properties. This study investigates the repairing techniques of three concrete beams which contain fly ash, waste rubber and polypropylene fibre in the concrete mix. The control beams were loaded up to its ultimate strength (severely damaged) and then repaired using CFRP, externally bonded to the beam soffit and anchored with complete CFRP wraps. The repaired beams were tested under four-point bending set-up to investigate its failure modes and improvement in strength, stiffness and ductility. In terms of strength and stiffness, two of the repaired beams (with fly ash and waste rubber) exceeded the capacity of the control beams, whereas the beam with polypropylene fibre gained around half of the strength and stiffness compared to its control counterpart. While the ductility of the repaired beams was found to be less than the control ones, the repaired beams exhibit pseudo ductile behaviour. In addition, an analytical study is conducted considering the effect of transverse CFRP anchorage wraps on the flexural capacity of repaired beams using shear friction model which can predict the strength of repaired beam to great accuracy.
Kaiwartya, O, Abdullah, AH, Cao, Y, Lloret, J, Kumar, S, Shah, RR, Prasad, M & Prakash, S 2018, 'Virtualization in Wireless Sensor Networks: Fault Tolerant Embedding for Internet of Things', IEEE Internet of Things Journal, vol. 5, no. 2, pp. 571-580.
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IEEE Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for IoT. Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering fault tolerance and communication delay as two conflicting objectives. An adapted non-dominated sorting based genetic algorithm (A-NSGA) is developed to solve the optimization problem. The major components of A-NSGA include chromosome representation, fault tolerance and delay computation, crossover and mutation, and non-dominance based sorting. Analytical and simulation based comparative performance evaluation has been carried out. From the analysis of results, it is evident that the framework effectively optimizes fault tolerance for virtualization in WSNs.
Kalantar, B, Pradhan, B, Naghibi, SA, Motevalli, A & Mansor, S 2018, 'Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 49-69.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selection effects on the LSM. Thus, this study assesses the training landslides random selection effects on support vector machine (SVM) accuracy, logistic regression (LR) and artificial neural networks (ANN) models for LSM in a catchment at the Dodangeh watershed, Mazandaran province, Iran. A 160 landslide locations inventory was collected by Geological Survey of Iran for this investigation. Different methods were implemented to define the landslide locations, such as inventory reports, satellite images and field survey. Moreover, 14 landslide conditioning factors were considered in the analysis of landslide susceptibility. These factors include curvature, plan curvature, profile curvature, altitude, slope angle, slope aspect, distance to faults, distance to stream, topographic wetness index, stream power index, terrain roughness index, sediment transport index, lithology and land use. The results show that the random landslide training data selection affected the parameter estimations of the SVM, LR and ANN algorithms. The results also show that the training samples selection had an effect on the accuracy of the susceptibility model because landslide conditioning factors vary according to the geographic locations in the study area. The LR model was found to be less sensitive than the SVM and ANN models to the training samples selection. Validation results showed that SVM and LR models outperformed the ANN model for all scenarios. The average overall accuracy of LR, SVM and ANN models are 81.42%, 79.82% and 70.2%, respectively.
Kalaruban, M, Loganathan, P, Kandasamy, J & Vigneswaran, S 2018, 'Submerged membrane adsorption hybrid system using four adsorbents to remove nitrate from water', Environmental Science and Pollution Research, vol. 25, no. 21, pp. 20328-20335.
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Nitrate contamination of ground and surface waters causes environmental pollution and human health problems in many parts of the world. This study tests the nitrate removal efficiencies of two ion exchange resins (Dowex 21K XLT and iron-modified Dowex 21K XLT (Dowex-Fe)) and two chemically modified bio-adsorbents (amine-grafted corn cob (AG corn cob) and amine-grafted coconut copra (AG coconut copra)) using a dynamic adsorption treatment system. A submerged membrane (microfiltration) adsorption hybrid system (SMAHS) was used for the continuous removal of nitrate with a minimal amount of adsorbents. The efficiency of membrane filtration flux and replacement rate of adsorbent were studied to determine suitable operating conditions to maintain the effluent nitrate concentration below the WHO drinking standard limit of 11.3 mg N/L. The volume of water treated and the amount of nitrate adsorbed per gramme of adsorbent for all four flux tested were in the order Dowex-Fe > Dowex > AG coconut copra > AG corn cob. The volumes of water treated (L/g adsorbent) were 0.91 and 1.85, and the amount of nitrate removed (mg N/g adsorbent) were 9.8 and 22.2 for AG corn cob and Dowex-Fe, respectively, at a flux of 15 L/(m2/h).
Kalaruban, M, Loganathan, P, Shim, W, Kandasamy, J & Vigneswaran, S 2018, 'Mathematical Modelling of Nitrate Removal from Water Using a Submerged Membrane Adsorption Hybrid System with Four Adsorbents', Applied Sciences, vol. 8, no. 2, pp. 194-194.
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© 2018 by the authors. Excessive concentrations of nitrate in ground water are known to cause human health hazards. A submerged membrane adsorption hybrid system that includes a microfilter membrane and four different adsorbents (Dowex 21K XLT ion exchange resin (Dowex), Fe-coated Dowex, amine-grafted (AG) corn cob and AG coconut copra) operated at four different fluxes was used to continuously remove nitrate. The experimental data obtained in this study was simulated mathematically with a homogeneous surface diffusion model that incorporated membrane packing density and membrane correlation coefficient, and applied the concept of continuous flow stirred tank reactor. The model fit with experimental data was good. The surface diffusion coefficient was constant for all adsorbents and for all fluxes. The mass transfer coefficient increased with flux for all adsorbents and generally increased with the adsorption capacity of the adsorbents.
Kalhori, H, Alamdari, MM & Ye, L 2018, 'Automated algorithm for impact force identification using cosine similarity searching', Measurement, vol. 122, pp. 648-657.
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Kalhori, H, Makki Alamdari, M, Zhu, X & Samali, B 2018, 'Nothing-on-Road Axle Detection Strategies in Bridge-Weigh-in-Motion for a Cable-Stayed Bridge: Case Study', Journal of Bridge Engineering, vol. 23, no. 8, pp. 05018006-05018006.
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Kamal, MS, Trivdedi, MC, Alam, JB, Dey, N, Ashour, AS, Shi, F & Tavares, JMRS 2018, 'Big DNA datasets analysis under push down automata', Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1555-1565.
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Kamal, S, Dey, N, Nimmy, SF, Ripon, SH, Ali, NY, Ashour, AS, Karaa, WBA, Nguyen, GN & Shi, F 2018, 'Evolutionary framework for coding area selection from cancer data', Neural Computing and Applications, vol. 29, no. 4, pp. 1015-1037.
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Kamyabniya, A, Lotfi, MM, Naderpour, M & Yih, Y 2018, 'Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach', Information Systems Frontiers, vol. 20, no. 4, pp. 759-782.
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© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.
Kang, G, Li, J & Tao, D 2018, 'Shakeout: A New Approach to Regularized Deep Neural Network Training', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1245-1258.
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Kang, Y, Zhang, J, Li, B, Zhang, Y, Sun, H, Hao Ngo, H, Guo, W, Xie, H, Hu, Z & Zhao, C 2018, 'Improvement of bioavailable carbon source and microbial structure toward enhanced nitrate removal by Tubifex tubifex', Chemical Engineering Journal, vol. 353, pp. 699-707.
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Kani, K, Malgras, V, Jiang, B, Hossain, MSA, Alshehri, SM, Ahamad, T, Salunkhe, RR, Huang, Z & Yamauchi, Y 2018, 'Periodically Arranged Arrays of Dendritic Pt Nanospheres Using Cage-Type Mesoporous Silica as a Hard Template', Chemistry - An Asian Journal, vol. 13, no. 1, pp. 106-110.
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Dendritic Pt nanospheres of 20 nm diameter are synthesized by using a highly concentrated surfactant assembly within the large-sized cage-type mesopores of mesoporous silica (LP-FDU-12). After diluting the surfactant solution with ethanol, the lower viscosity leads to an improved penetration inside the mesopores. After Pt deposition followed by template removal, the arrangement of the Pt nanospheres is a replication from that of the mesopores in the original LP-FDU-12 template. Although it is well known that ordered LLCs can form on flat substrates, the confined space inside the mesopores hinders surfactant self-organization. Therefore, the Pt nanospheres possess a dendritic porous structure over the entire area. The distortion observed in some nanospheres is attributed to the close proximity existing between neighboring cage-type mesopores. This new type of nanoporous metal with a hierarchical architecture holds potential to enhance substance diffusivity/accessibility for further improvement of catalytic activity.
Kapeleris, J, Kulasinghe, A, Warkiani, ME, Vela, I, Kenny, L, O'Byrne, K & Punyadeera, C 2018, 'The Prognostic Role of Circulating Tumor Cells (CTCs) in Lung Cancer', Frontiers in Oncology, vol. 8, no. AUG.
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© 2018 Kapeleris, Kulasinghe, Warkiani, Vela, Kenny, O'Byrne and Punyadeera. Lung cancer affects over 1. 8 million people worldwide and is the leading cause of cancer related mortality globally. Currently, diagnosis of lung cancer involves a combination of imaging and invasive biopsies to confirm histopathology. Non-invasive diagnostic techniques under investigation include "liquid biopsies" through a simple blood draw to develop predictive and prognostic biomarkers. A better understanding of circulating tumor cell (CTC) dissemination mechanisms offers promising potential for the development of techniques to assist in the diagnosis of lung cancer. Enumeration and characterization of CTCs has the potential to act as a prognostic biomarker and to identify novel drug targets for a precision medicine approach to lung cancer care. This review will focus on the current status of CTCs and their potential diagnostic and prognostic utility in this setting.
Karamanakos, P, Geyer, T & Aguilera, RP 2018, 'Long-Horizon Direct Model Predictive Control: Modified Sphere Decoding for Transient Operation', IEEE Transactions on Industry Applications, vol. 54, no. 6, pp. 6060-6070.
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© 1972-2012 IEEE. In this paper, we present modifications to the sphere decoder initially introduced in the work of Geyer and Quevedo and modified in the work of Karamanakos et al. that significantly reduce the computation times during transients. The relative position of the unconstrained solution of the integer quadratic program underlying model predictive control (MPC) with respect to the convex hull of the (truncated) lattice of integer points is examined. If it is found that the unconstrained solution does not lie within the convex hull - a phenomenon that is observed mostly during transients - then a projection is performed onto the convex hull. By doing so, a new sphere that guarantees feasibility and includes a significant smaller number of candidate solutions is computed. This reduces the computation time by up to three orders of magnitude when solving the optimization problem at hand. Nonetheless, the reduction of the computational burden comes at a cost of (mild) suboptimal results. The effectiveness of the proposed algorithm is tested with a variable speed drive system consisting of a three-level neutral point clamped voltage source inverter and a medium-voltage induction machine. Based on the presented results, the sphere decoding algorithm with the proposed refinements maintains the very fast transient responses inherent to direct MPC. Moreover, it is observed that the occasional implementation of suboptimal solutions does not lead to a deterioration of the system performance.
Karimi, F & Matous, P 2018, 'Mapping diversity and inclusion in student societies: A social network perspective', Computers in Human Behavior, vol. 88, pp. 184-194.
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Karmokar, DK, Guo, YJ, Qin, P-Y, Chen, S-L & Bird, TS 2018, 'Substrate Integrated Waveguide-Based Periodic Backward-to-Forward Scanning Leaky-Wave Antenna With Low Cross-Polarization', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 3846-3856.
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© 1963-2012 IEEE. For many leaky-wave antennas (LWAs), it is challenging to realize beam scanning through broadside. A problem is the presence of an open stopband (OSB), which restricts radiation in the broadside direction. In this paper, a novel substrate integrated waveguide (SIW)-based LWA is described to overcome the OSB problem and provide beam scanning continuously from the backward to the forward direction from a conventional periodic LWA. It is demonstrated that the n =-1 spatial harmonic can be excited efficiently from an SIW LWA and enables broadside radiation. However, it was found in our initial design that when the beam scans through the broadside, the cross-polarization level increases significantly compared to the beam close to the backfire direction. A technique is developed to reduce the cross-polarization level. As a result, a new antenna configuration is created. The antenna design has been realized and measured to validate the concept. The measured beam scanning range of the prototype is from -74° to +45° (119° of beam scanning) when the frequency sweeps from 7.625 to 11 GHz, and the measured cross-polarization level is 20.8 dB low at the main beam direction for the broadside beam.
Kashif, M, Hossain, MJ, Zhuo, F & Gautam, S 2018, 'Design and implementation of a three-level active power filter for harmonic and reactive power compensation', Electric Power Systems Research, vol. 165, pp. 144-156.
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Katalo, R, Okuda, T, Nghiem, LD & Fujioka, T 2018, 'Moringa oleifera coagulation as pretreatment prior to microfiltration for membrane fouling mitigation', Environmental Science: Water Research & Technology, vol. 4, no. 10, pp. 1604-1611.
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Coagulation pretreatment using Moringa oleifera in the microfiltration of river water achieved membrane fouling mitigation and filtered water quality improvement.
Ke, G, Li, W, Li, R, Li, Y & Wang, G 2018, 'Mitigation Effect of Waste Glass Powders on Alkali–Silica Reaction (ASR) Expansion in Cementitious Composite', International Journal of Concrete Structures and Materials, vol. 12, no. 1.
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© 2018, The Author(s). The effects of different contents and particle sizes of waste glass powder on alkali–silica reaction (ASR) expansion of cementitious composite bar were investigated in this study. Waste glass powder with particle size less than 300 μm exhibits an excellent mitigation effect on ASR expansion. With larger content and smaller particle size, the mitigation effect of waste glass powder on ASR expansion gradually increases. The mitigation effect of waste glass powder with particle size ranging from 38 to 53 μm and 20% by weight of cement seems relatively better than that of fly ash. When the waste glass powder content reaches 30%, the mitigation effect is still effective and almost the same as that of fly ash. However, the waste glass powder with particle size larger than 300 μm presents negative mitigation effect on ASR expansion when the replacement rate is larger than 30%. On the other hand, the waste glass powder and calcium hydroxide (CH) further react, and produce more calcium–silicate–hydrate gels, which apparently reduce the amount of CH. Moreover, the increasing content of waste glass powder results in a lower pH value in the pore solution of cementitious composite.
Kelly, SL, Martin-Hughes, R, Stuart, RM, Yap, XF, Kedziora, DJ, Grantham, KL, Hussain, SA, Reporter, I, Shattock, AJ, Grobicki, L, Haghparast-Bidgoli, H, Skordis-Worrall, J, Baranczuk, Z, Keiser, O, Estill, J, Petravic, J, Gray, RT, Benedikt, CJ, Fraser, N, Gorgens, M, Wilson, D, Kerr, CC & Wilson, DP 2018, 'The global Optima HIV allocative efficiency model: targeting resources in efforts to end AIDS', The Lancet HIV, vol. 5, no. 4, pp. e190-e198.
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Kendrick, L, Musial, K & Gabrys, B 2018, 'Change point detection in social networks—Critical review with experiments', Computer Science Review, vol. 29, pp. 1-13.
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© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes.
Keshari, A, Mishra, N, Shukla, N, McGuire, S & Khorana, S 2018, 'Multiple order-up-to policy for mitigating bullwhip effect in supply chain network', Annals of Operations Research, vol. 269, no. 1-2, pp. 361-386.
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© 2017 Springer Science+Business Media New YorkThis paper proposes a multiple order-up-to policy based inventory replenishment scheme to mitigate the bullwhip effect in a multi-stage supply chain scenario, where various transportation modes are available between the supply chain (SC) participants. The proposed policy is similar to the fixed order-up-to policy approach where replenishment decision ¿how much to order¿ is made periodically on the basis of the pre-decided order-up-to inventory level. In the proposed policy, optimal multiple order-up-to levels are assigned to each SC participants, which provides decision making reference point for deciding the transportation related order quantity. Subsequently, a mathematical model is established to define optimal multiple order-up-to levels for each SC participants that aims to maximize overall profit from the SC network. In parallel, the model ensures the control over supply chain pipeline inventory, high satisfaction of customer demand and enables timely utilization of available transportation modes. Findings from the various numerical datasets including stochastic customer demand and lead times validate that¿the proposed optimal multiple order-up-to policy based inventory replenishment scheme can be a viable alternative for mitigating the bullwhip effect and well-coordinated SC. Moreover, determining the multiple order-up-to levels is a NP hard combinatorial optimization problem. It is found that the implementation of new emerging optimization algorithm named bacterial foraging algorithm (BFA) has presented superior optimization performances. The robustness and applicability of the BFA algorithm are further validated statistically by employing the percentage heuristic gap and two-way ANOVA analysis.
Keshavarzi, A, Shrestha, CK, Melville, B, Khabbaz, H, Ranjbar-Zahedani, M & Ball, J 2018, 'Estimation of maximum scour depths at upstream of front and rear piers for two in-line circular columns', Environmental Fluid Mechanics, vol. 18, no. 2, pp. 537-550.
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Previous investigations indicate that scour around bridge piers is one of the most important factors for the failure of waterway bridges. Hence, it is essential to determine the accurate scour depth around the bridge piers. Most of the previous studies were based on scour around a single pier; however, in practice, new bridges are usually wide and then piers comprise two circular piers aligned in the flow direction that together support the loading of the structure. In this study, the effect on maximum scour depth of the spacing between two piers aligned in the flow direction was investigated experimentally under clear water scour conditions. The results show that the maximum scour depth at upstream of the front pier occurs when the spacing between the two piers is 2.5 times the diameter of the pier. Two semi empirical equations have been developed to predict the maximum scour depth at upstream of both front and rear piers as a function of the spacing between the piers, in terms of a pier-spacing factor. If the new equations for the pier-spacing factor are used with some of the existing equations for scour at a single pier, the predicted scouring depths are in good agreement with observed results. The S/M equation exhibited the best performance among the various equations tested and was recommended for use in prediction of the equilibrium scour depth. The findings of this study can be used to facilitate the positioning of piers when scouring is a design concern.
Keshavarzi, A, Shrestha, CK, Zahedani, MR, Ball, J & Khabbaz, H 2018, 'Experimental study of flow structure around two in-line bridge piers', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 6, pp. 311-327.
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Previous investigations indicate that local scouring is one of the most common causes of waterway bridge failure. The scour mechanism around bridge piers is complicated by the interaction of flow and structure. To explore the local scouring process, it is therefore essential to study the flow–structure interaction around bridge piers. Most previous studies have been based on this interaction around a single pier; however, in practice, many bridges are wide and comprise a number of piers aligned in the flow direction that together support the loading. In this study, a particle image velocimetry technique was used to investigate two-dimensional flow–structure interaction around two in-line bridge piers with different spacings. Various influencing flow characteristics including turbulence intensity, turbulent kinetic energy and Reynolds stresses were calculated in different vertical planes around the bridge piers. Results indicated that the flow characteristics around two in-line bridge piers are very different than for a single pier and the spacing between two in-line piers significantly influences the flow characteristics, particularly in the rear of the piers. Furthermore, for spacing in the range of 2 ≤ L/D ≤ 3, stronger turbulence structures occurred behind pier 1 and, as a result, a higher scour depth can be expected around pier 1.
Khalesi, S, Irwin, C & Sun, J 2018, 'Lifestyle and self-management determinants of hypertension control in a sample of Australian adults', Expert Review of Cardiovascular Therapy, vol. 16, no. 3, pp. 229-236.
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Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'A market-oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage', Wind Energy, vol. 21, no. 4, pp. 242-254.
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Copyright © 2018 John Wiley & Sons, Ltd. In this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid-tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time-varying market-price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market-price data, depict the proficiency of the proposed methodology over standard linear programming methods.
Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting', Applied Energy, vol. 211, pp. 764-773.
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© 2017 Elsevier Ltd This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity. The obtained results depict the effectiveness of the strategy to help power system operators in ensuring economically optimal energy dispatch. Moreover, the results can aid power system planners in the selection of optimal BESS capacity for given power ratings in order to maximize their operational profits.
Khalid, M, AlMuhaini, M, Aguilera, RP & Savkin, AV 2018, 'Method for planning a wind–solar–battery hybrid power plant with optimal generation‐demand matching', IET Renewable Power Generation, vol. 12, no. 15, pp. 1800-1806.
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© 2018 The Institution of Engineering and Technology. This study aims to propose a methodology for a hybrid wind-solar power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar-wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of wind and solar with optimal ratio will lead to clear benefits for hybrid wind-solar power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into electricity grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. This research targets at battery storage technology and proposes a generic methodology for optimal capacity calculations for the proposed hybrid wind-solar power system.
Khan, AA, Abolhasan, M & Ni, W 2018, 'An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs', IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 4501-4513.
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© 1967-2012 IEEE. Discovering and maintaining efficient routes for data dissemination in vehicular ad hoc networks (VANETs) has proven to be a very challenging problem. Clustering is one of the control protocols used to provide efficient and stable routes for data dissemination. However, the rapid changes in network topology in VANETs creates frequent cluster reformation, which can seriously affect route stability. We propose a novel evolutionary game theoretic (EGT) framework to automate the clustering of nodes and nominations of cluster heads, to achieve cluster stability in VANETs. The equilibrium point is proven analytically and the stability is also tested using Lyapunov function. The performance of the proposed evolutionary game is empirically investigated with different cost functions using static and mobile scenarios. The simulation results demonstrate the effectiveness and robustness of our proposed EGT approach for different populations and speeds, thus reducing the overhead of frequent cluster reformation in VANETs.
Khan, F, ur Rehman, A, Usman, M, Tan, Z & Puthal, D 2018, 'Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait', Mobile Networks and Applications, vol. 23, no. 3, pp. 479-488.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the traditional wireless network applications. On the other hand, licensed spectrum bands are almost completely allocated to the licensed users also known as Primary users (PUs). This dilemma became a blackhole for the upcoming innovative wireless network applications. To mitigate this problem, the cognitive radio (CR) concept emerges as a promising solution for reducing the spectrum scarcity issue. The CR network is a low cost solution for efficient utilization of the spectrum by allowing secondary users (SUs) to exploit the unoccupied licensed spectrum. In this paper, we model the PU’s utilization activity by a two-state Discrete-Time-Markov Chain (DTMC) (i.e., Free and busy states), for identifying the temporarily unoccupied spectrum bands,. Furthermore, we propose a Cognitive Radio Sense-and-Wait assisted HARQ scheme, which enables the Cluster Head (CH) to perform sensing operation for the sake of determining the PU’s activity. Once the channel is found in free state, the CH advertise control signals to the member nodes for data transmission relying on Stop-and-Wait Hybrid- Automatic Repeat-Request (SW-HARQ). By contrast, when the channel is occupied by the PU, the CH waits and start sensing again. Additionally, the proposed CRSW assisted HARQ scheme is analytical modeled, based on which the closed-form expressions are derived both for average block delay and throughput. Finally, the correctness of the closed-form expressions are confirmed by the simulation results. It is also clear from the performance results that the level of PU utilization and the reliability of the PU channel have great influence on the delay and throughput of CRSW assisted HARQ model.
Khan, H, Razmjou, A, Ebrahimi Warkiani, M, Kottapalli, A & Asadnia, M 2018, 'Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring', Sensors, vol. 18, no. 2, pp. 418-418.
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Khan, HA, Khan, MSH, Castel, A & Sunarho, J 2018, 'Deterioration of alkali-activated mortars exposed to natural aggressive sewer environment', Construction and Building Materials, vol. 186, pp. 577-597.
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Khan, MA, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Liang, H 2018, 'Can membrane bioreactor be a smart option for water treatment?', Bioresource Technology Reports, vol. 4, pp. 80-87.
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The gradual increase of organic and inorganic micropollutants in natural and drinking watercourses has posed a greater challenge for current water treatment technologies. Currently established water treatment processes such as activated sludge, microfiltration, reverse osmosis, adsorption, carbon nanotube etc. have a limited range of application, low energy recovery, and cost-intensive operation. Membrane bioreactor has already been utilized as a useful option to remove soluble organics, nutrients, and micropollutants from wastewater. Although currently established Membrane Bioreactors have few limitations, recent developments on this technology have improved its energy efficiency and reduced the operating and maintenance cost. Implementing these research findings in full-scale operation can make this process a favorable option in industrial wastewater treatment.
Khan, MA, Ngo, HH, Guo, W, Liu, Y, Zhang, X, Guo, J, Chang, SW, Nguyen, DD & Wang, J 2018, 'Biohydrogen production from anaerobic digestion and its potential as renewable energy', Renewable Energy, vol. 129, pp. 754-768.
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© 2017. The current demand-supply scenario for fossil fuels requires an alternative energy source with cleaner combustion products whilst production of hydrogen from anaerobic digestion involves the utilization of waste materials and zero emission of greenhouse gasses. However, large scale industrial application has yet not been implemented due to numerous challenges in its production, storage, and transportation. This review study demonstrates that production of hydrogen from anaerobic digestion is potentially a worthy alternative regarding energy density, environmental impact, and cost. Moreover, dependence on fossil fuel systems in the future could be minimized when biohydrogen production is feasible from renewable energy sources.
Khan, MA, Umer, T, Khan, SU, Yu, S & Rachedi, A 2018, 'IEEE Access Special Section Editorial: Green Cloud and Fog Computing: Energy Efficiency and Sustainability Aware Infrastructures, Protocols, and Applications', IEEE Access, vol. 6, pp. 12280-12283.
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Khan, MSH & Castel, A 2018, 'Effect of MgO and Na2SiO3 on the carbonation resistance of alkali activated slag concrete', Magazine of Concrete Research, vol. 70, no. 13, pp. 685-692.
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This paper investigates the effect of magnesium oxide (MgO) on the carbonation resistance of alkali-activated slag–fly ash blend containing 75% ground granulated blast furnace slag (GGBS) and 25% low-calcium fly ash. Two types of GGBS were used with different magnesium oxide content. Phenolphthalein indicator and pH profiles showed that the GGBS with higher levels of magnesium oxide offered no significant improvement in resistance against natural and 1% accelerated carbonation. X-ray diffraction confirmed no hydrotalcite formation, although the magnesium oxide content was 9·1%. A very small amount of free magnesium ions (Mg2+) was available in the pore solution, which was deemed insufficient to form hydrotalcite. Lack of its formation was the major reason for the lower carbonation resistance. Excessive silicate in the system reduces the calcium oxide/silicon dioxide ratio, which leads to the incorporation of magnesium ions in the calcium silicate hydrate structure. Hydrotalcite was observed when the activator concentration was reduced. The results suggest that in addition to magnesium and aluminium ion (Al3+) availability, silicate concentration also plays a strong role in deciding the hydrotalcite formation in alkali-activated GGBS concrete.
Khokle, R, Esselle, K & Bokor, D 2018, 'Design, Modeling, and Evaluation of the Eddy Current Sensor Deeply Implanted in the Human Body', Sensors, vol. 18, no. 11, pp. 3888-3888.
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Joint replacement surgeries have enabled motion for millions of people suffering from arthritis or grave injuries. However, over 10% of these surgeries are revision surgeries. We have first analyzed the data from the worldwide orthopedic registers and concluded that the micromotion of orthopedic implants is the major reason for revisions. Then, we propose the use of inductive eddy current sensors for in vivo micromotion detection of the order of tens of μ m. To design and evaluate its characteristics, we have developed efficient strategies for the accurate numerical simulation of eddy current sensors implanted in the human body. We present the response of the eddy current sensor as a function of its frequency and position based on the robust curve fit analysis. Sensitivity and Sensitivity Range parameters are defined for the present context and are evaluated. The proposed sensors are fabricated and tested in the bovine leg.
Khosrokhani, M, Khairunniza-Bejo, S & Pradhan, B 2018, 'Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques', Geocarto International, vol. 33, no. 3, pp. 260-276.
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Khuat, TT & Le, MH 2018, 'A Novel Hybrid ABC-PSO Algorithm for Effort Estimation of Software Projects Using Agile Methodologies', Journal of Intelligent Systems, vol. 27, no. 3, pp. 489-506.
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Abstract
In modern software development processes, software effort estimation plays a crucial role. The success or failure of projects depends greatly on the accuracy of effort estimation and schedule results. Many studies focused on proposing novel models to enhance the accuracy of predicted results; however, the question of accurate estimation of effort has been a challenging issue with regards to researchers and practitioners, especially when it comes to projects using agile methodologies. This study aims at introducing a novel formula based on team velocity and story point factors. The parameters of this formula are then optimized by employing swarm optimization algorithms. We also propose an improved algorithm combining the advantages of the artificial bee colony and particle swarm optimization algorithms. The experimental results indicated that our approaches outperformed methods in other studies in terms of the accuracy of predicted results.
Kieu, LM, Ou, Y & Cai, C 2018, 'Large-scale transit market segmentation with spatial-behavioural features', Transportation Research Part C: Emerging Technologies, vol. 90, pp. 97-113.
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© 2018 Elsevier Ltd Transit market segmentation enables transit providers to comprehend the commonalities and heterogeneities among different groups of passengers, so that they can cater for individual transit riders’ mobility needs. The problem has recently been attracting a great interest with the proliferation of automated data collection systems such as Smart Card Automated Fare Collection (AFC), which allow researchers to observe individual travel behaviours over a long time period. However, there is a need for an integrated market segmentation method that incorporating both spatial and behavioural features of individual transit passengers. This algorithm also needs to be efficient for large-scale implementation. This paper proposes a new algorithm named Spatial Affinity Propagation (SAP) based on the classical Affinity Propagation algorithm (AP) to enable large-scale spatial transit market segmentation with spatial-behavioural features. SAP segments transit passengers using spatial geodetic coordinates, where passengers from the same segment are located within immediate walking distance; and using behavioural features mined from AFC data. The comparison with AP and popular algorithms in literature shows that SAP provides nearly as good clustering performance as AP while being 52% more efficient in computation time. This efficient framework would enable transit operators to leverage the availability of AFC data to understand the commonalities and heterogeneities among different groups of passengers.
Kim, DI, Gwak, G, Dorji, P, He, D, Phuntsho, S, Hong, S & Shon, H 2018, 'Palladium Recovery through Membrane Capacitive Deionization from Metal Plating Wastewater', ACS Sustainable Chemistry & Engineering, vol. 6, no. 2, pp. 1692-1701.
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© 2017 American Chemical Society. The potential application of membrane capacitive deionization (MCDI) for recovery of palladium (Pd) ions from catalyst solution wastewater generated from the plating industry was investigated in this study. Several major issues were explored in this work to verify the suitability of MCDI for Pd recovery from a practical perspective: adsorption and desorption efficiencies, desorption mechanisms into high concentration of Pd concentrate, and its sustainability in long-term operation. The lab-scale MCDI operation achieved satisfactory and highly competitive Pd removal (99.07-99.94% removal with 1.42-1.52 of Pd selectivity over ammonium ions) showing that Pd can be effectively collected from plating industry wastewater. A high concentration of Pd concentrate (64.77 and 919.44 mg/L of Pd from the 10 and 100 mg/L Pd containing catalyst solution, respectively) was obtained through successive five operation cycles of adsorption/desorption phases. However, it is significant to note that the desorption efficiency was inversely proportional to the concentration of Pd concentrate which is likely due to the Pd ions discharged from carbon electrode toward Pd solution against the enhanced concentration gradient. The long-term operation results suggest that scaling could reduce the MCDI efficiency during Pd recovery (0.17% decrease in Pd removal for every cycle on average) and hence may require an adequate electrode cleaning regime.
Kim, H, Wrann, CD, Jedrychowski, M, Vidoni, S, Kitase, Y, Nagano, K, Zhou, C, Chou, J, Parkman, V-JA, Novick, SJ, Strutzenberg, TS, Pascal, BD, Le, PT, Brooks, DJ, Roche, AM, Gerber, KK, Mattheis, L, Chen, W, Tu, H, Bouxsein, ML, Griffin, PR, Baron, R, Rosen, CJ, Bonewald, LF & Spiegelman, BM 2018, 'Irisin Mediates Effects on Bone and Fat via αV Integrin Receptors', Cell, vol. 175, no. 7, pp. 1756-1768.e17.
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Irisin is secreted by muscle, increases with exercise, and mediates certain favorable effects of physical activity. In particular, irisin has been shown to have beneficial effects in adipose tissues, brain, and bone. However, the skeletal response to exercise is less clear, and the receptor for irisin has not been identified. Here we show that irisin binds to proteins of the αV class of integrins, and biophysical studies identify interacting surfaces between irisin and αV/β5 integrin. Chemical inhibition of the αV integrins blocks signaling and function by irisin in osteocytes and fat cells. Irisin increases both osteocytic survival and production of sclerostin, a local modulator of bone remodeling. Genetic ablation of FNDC5 (or irisin) completely blocks osteocytic osteolysis induced by ovariectomy, preventing bone loss and supporting an important role of irisin in skeletal remodeling. Identification of the irisin receptor should greatly facilitate our understanding of irisin's function in exercise and human health.
Kim, J 2018, 'Robot Navigation and SLAM', Robots and Human: Special Issue on Robot Navigation and SLAM Technology, vol. 15.
Kim, JE, Phuntsho, S, Ali, SM, Choi, JY & Shon, HK 2018, 'Forward osmosis membrane modular configurations for osmotic dilution of seawater by forward osmosis and reverse osmosis hybrid system', Water Research, vol. 128, pp. 183-192.
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This study evaluates various options for full-scale modular configuration of forward osmosis (FO) process for osmotic dilution of seawater using wastewater for simultaneous desalination and water reuse through FO-reverse osmosis (RO) hybrid system. Empirical relationship obtained from one FO membrane element operation was used to simulate the operational performances of different FO module configurations. The main limiting criteria for module operation is to always maintain the feed pressure higher than the draw pressure throughout the housing module for safe operation without affecting membrane integrity. Experimental studies under the conditions tested in this study show that a single membrane housing cannot accommodate more than four elements as the draw pressure exceeds the feed pressure. This then indicates that a single stage housing with eight elements is not likely to be practical for safe FO operation. Hence, six different FO modular configurations were proposed and simulated. A two-stage FO configuration with multiple housings (in parallel) in the second stage using same or larger spacer thickness reduces draw pressure build-up as the draw flow rates are reduced to half in the second stage thereby allowing more than four elements in the second stage housing. The loss of feed pressure (pressure drop) and osmotic driving force in the second stage are compensated by operating under the pressure assisted osmosis (PAO) mode, which helps enhance permeate flux and maintains positive pressure differences between the feed and draw chamber. The PAO energy penalty is compensated by enhanced permeate throughput, reduced membrane area, and plant footprint. The contribution of FO/PAO to total energy consumption was not significant compared to post RO desalination (90%) indicating that the proposed two-stage FO modular configuration is one way of making the FO full-scale operation practical for FO-RO hybrid system.
Kim, JE, Phuntsho, S, Chekli, L, Choi, JY & Shon, HK 2018, 'Environmental and economic assessment of hybrid FO-RO/NF system with selected inorganic draw solutes for the treatment of mine impaired water', Desalination, vol. 429, pp. 96-104.
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© 2017 Elsevier B.V. A hybrid forward osmosis (FO) and reverse osmosis (RO)/nanofiltration (NF) system in a closed-loop operation with selected draw solutes was evaluated to treat coal mine impaired water. This study provides an insight of selecting the most suitable draw solution (DS) by conducting environmental and economic life cycle assessment (LCA). Baseline environmental LCA showed that the dominant components to energy use and global warming are the DS recovery processes (i.e. RO or NF processes) and FO membrane materials, respectively. When considering the DS replenishment in FO, the contribution of chemical use to the overall global warming impact was significant for all hybrid systems. Furthermore, from an environmental perspective, the FO-NF hybrid system with Na 2 SO 4 shows the lowest energy consumption and global warming with additional considerations of final product water quality and FO brine disposal. From an economic perspective, the FO-NF with Na 2 SO 4 showed the lowest total operating cost due to its lower DS loss and relatively low solute cost. In a closed-loop system, FO-NF with NaCl and Na 2 SO 4 had the lowest total water cost at optimum NF recovery rates of 90 and 95%, respectively. FO-NF with Na 2 SO 4 had the lowest environmental and economic impacts. Overall, draw solute performances and cost in FO and recovery rate in RO/NF play a crucial role in determining the total water cost and environmental impact of FO hybrid systems in a closed-loop operation.
Kim, S, Piao, G, Han, DS, Shon, HK & Park, H 2018, 'Solar desalination coupled with water remediation and molecular hydrogen production: a novel solar water-energy nexus', Energy & Environmental Science, vol. 11, no. 2, pp. 344-353.
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A novel solar water-energy nexus technology is presented that combines the solar desalination of saline water and desalination-driven wastewater remediation coupled with the production of H2.
Kim, T, Sotirova, E, Shannon, A, Atanassova, V, Atanassov, K & Jang, L-C 2018, 'Interval Valued Intuitionistic Fuzzy Evaluations for Analysis of a Student’s Knowledge in University e-Learning Courses', INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, vol. 18, no. 3, pp. 190-195.
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© The Korean Institute of Intelligent Systems. In the paper a method is proposed for evaluation of the students' knowledge obtained in the university e-learning courses and an evaluation of the whole student class. For the assessment of the student's solution of the respective assessment units the theory of intuitionistic fuzzy sets is used, while for the class evaluation, interval valued intuitionistic fuzzy sets is used. The obtained intuitionistic fuzzy estimations reflect the degree of each student's good or poor performances, for each assessment unit. The interval valued intuitionistic fuzzy evaluations are based on the separate student's evaluations. We also consider a degree of uncertainty that represents such cases wherein the student is currently unable to solve the problem. The method presented here provides the possibility for the algorithmization of the process of forming the student's evaluations.
Kok, VC, Zhang, H-W, Lin, C-T, Huang, S-C & Wu, M-F 2018, 'Positive association between hypertension and urinary bladder cancer: epidemiologic evidence involving 79,236 propensity score-matched individuals', Upsala Journal of Medical Sciences, vol. 123, no. 2, pp. 109-115.
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INTRODUCTION:We hypothesized that hypertensive patients harbor a higher risk of urinary bladder (UB) cancer. MATERIAL AND METHODS:We performed a population-based cohort study on adults using a National Health Insurance Research Database (NHIRD) dataset. Hypertension and comparison non-hypertensive (COMP) groups comprising 39,618 patients each were propensity score-matched by age, sex, index date, and medical comorbidities. The outcome was incident UB cancer validated using procedure codes. We constructed multivariable Cox models to derive adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Cumulative incidence was compared using a log-rank test. RESULTS:During a total follow-up duration of 380,525 and 372,020 person-years in the hypertension and COMP groups, 248 and 186 patients developed UB cancer, respectively, representing a 32% increase in the risk (aHR, 1.32; 95% CI, 1.09-1.60). Hypertensive women harbored a significantly increased risk of UB cancer (aHR, 1.55; 95% CI, 1.12-2.13) compared with non-hypertensive women, whereas men with hypertension had a statistically non-significant increased risk (aHR, 1.22; 95% CI, 0.96-1.55). The sensitivity analysis demonstrated that the increased risk was sustained throughout different follow-up durations for the entire cohort; a statistical increase in the risk was also noted among hypertensive men. CONCLUSION:This nationwide population-based propensity score-matched cohort study supports a positive association between hypertension and subsequent UB cancer development.
Kong, F, Sun, X, Guo, YJ, Leung, VCM, Zhu, Q & Zhu, H 2018, 'Queue-Aware Power Consumption Minimization in Two-Tier Heterogeneous Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 9, pp. 8875-8889.
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© 1967-2012 IEEE. In this paper, we study the network average power consumption minimization problem in a two-tier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signal-to-interference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the average traffic intensity of each tier is characterized by a set of fixed-point equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network average power consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network average power consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network average power consumption and the network SIR coverage in the considered scenario.
Kong, S, Lee, JH & Li, S 2018, 'A new distributed algorithm for efficient generalized arc-consistency propagation', Autonomous Agents and Multi-Agent Systems, vol. 32, no. 5, pp. 569-601.
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© 2018, The Author(s). Generalized arc-consistency propagation is predominantly used in constraint solvers to efficiently prune the search space when solving constraint satisfaction problems. Although many practical applications can be modelled as distributed constraint satisfaction problems, no distributed arc-consistency algorithms so far have considered the privacy of individual agents. In this paper, we propose a new distributed arc-consistency algorithm, called DisAC3.1, which leaks less private information of agents than existing distributed arc-consistency algorithms. In particular, DisAC3.1 uses a novel termination determination mechanism, which allows the agents to share domains, constraints and communication addresses only with relevant agents. We further extend DisAC3.1 to DisGAC3.1, which is the first distributed algorithm that enforces generalized arc-consistency on k-ary (k≥ 2) constraint satisfaction problems. Theoretical analyses show that our algorithms are efficient in both time and space. Experiments also demonstrate that DisAC3.1 outperforms the state-of-the-art distributed arc-consistency algorithm and that DisGAC3.1 ’s performance scales linearly in the number of agents.
Kook, S, Lee, C, Nguyen, TT, Lee, J, Shon, HK & Kim, IS 2018, 'Serially connected forward osmosis membrane elements of pressure-assisted forward osmosis-reverse osmosis hybrid system: Process performance and economic analysis', Desalination, vol. 448, pp. 1-12.
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Korzekwa, K, Chubb, CT & Tomamichel, M 2018, 'Avoiding irreversibility: engineering resonant conversions of quantum resources', Phys. Rev. Lett., vol. 122, no. 11, p. 110403.
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We identify and explore the intriguing property of resource resonance arising
within resource theories of entanglement, coherence and thermodynamics. While
the theories considered are reversible asymptotically, the same is generally
not true in realistic scenarios where the available resources are bounded. The
finite-size effects responsible for this irreversibility could potentially
prohibit small quantum information processors or thermal machines from
achieving their full potential. Nevertheless, we show here that by carefully
engineering the resource interconversion process any such losses can be greatly
suppressed. Our results are predicted by higher order expansions of the
trade-off between the rate of resource interconversion and the achieved
fidelity, and are verified by exact numerical optimizations of appropriate
approximate majorization conditions.
Kulasinghe, A, Schmidt, H, Perry, C, Whitfield, B, Kenny, L, Nelson, C, Warkiani, ME & Punyadeera, C 2018, 'A Collective Route to Head and Neck Cancer Metastasis', Scientific Reports, vol. 8, no. 1.
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AbstractDistant metastasis (DM) from head and neck cancers (HNC) portends a poor patient prognosis. Despite its important biological role, little is known about the cells which seed these DM. Circulating tumour cells (CTCs) represent a transient cancer cell population, which circulate in HNC patients’ peripheral blood and seed at distant sites. Capture and analysis of CTCs offers insights into tumour metastasis and can facilitate treatment strategies. Whilst the data on singular CTCs have shown clinical significance, the role of CTC clusters in metastasis remains limited. In this pilot study, we assessed 60 treatment naïve HNC patients for CTCs with disease ranging from early to advanced stages, for CTC clusters utilizing spiral CTC enrichment technology. Single CTCs were isolated in 18/60–30% (Ranging from Stage I-IV), CTC clusters in 15/60–25% (exclusively Stage IV) with 3/15–20% of CTC clusters also containing leukocytes. The presence of CTC clusters associated with the development of distant metastatic disease(P = 0.0313). This study demonstrates that CTC clusters are found in locally advanced patients, and this may be an important prognostic marker. In vivo and in vitro studies are warranted to determine the role of these CTC clusters, in particular, whether leukocyte involvement in CTC clusters has clinical relevance.
Kulasinghe, A, Wu, H, Punyadeera, C & Warkiani, M 2018, 'The Use of Microfluidic Technology for Cancer Applications and Liquid Biopsy', Micromachines, vol. 9, no. 8, pp. 397-397.
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There is growing awareness for the need of early diagnostic tools to aid in point-of-care testing in cancer. Tumor biopsy remains the conventional means in which to sample a tumor and often presents with challenges and associated risks. Therefore, alternative sources of tumor biomarkers is needed. Liquid biopsy has gained attention due to its non-invasive sampling of tumor tissue and ability to serially assess disease via a simple blood draw over the course of treatment. Among the leading technologies developing liquid biopsy solutions, microfluidics has recently come to the fore. Microfluidic platforms offer cellular separation and analysis platforms that allow for high throughout, high sensitivity and specificity, low sample volumes and reagent costs and precise liquid controlling capabilities. These characteristics make microfluidic technology a promising tool in separating and analyzing circulating tumor biomarkers for diagnosis, prognosis and monitoring. In this review, the characteristics of three kinds of circulating tumor markers will be described in the context of cancer, circulating tumor cells (CTCs), exosomes, and circulating tumor DNA (ctDNA). The review will focus on how the introduction of microfluidic technologies has improved the separation and analysis of these circulating tumor markers.
Kurugodu, HV, Bordoloi, S, Hong, Y, Garg, A, Garg, A, Sreedeep, S & Gandomi, AH 2018, 'Genetic programming for soil-fiber composite assessment', Advances in Engineering Software, vol. 122, pp. 50-61.
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Kusakunniran, W, Wu, Q, Ritthipravat, P & Zhang, J 2018, 'Hard exudates segmentation based on learned initial seeds and iterative graph cut', Computer Methods and Programs in Biomedicine, vol. 158, pp. 173-183.
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Lacava, M, Camargo, A, Garcia, LF, Benamú, MA, Santana, M, Fang, J, Wang, X & Blamires, SJ 2018, 'Web building and silk properties functionally covary among species of wolf spider', Journal of Evolutionary Biology, vol. 31, no. 7, pp. 968-978.
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Laengle, S, Modak, NM, Merigó, JM & De La Sotta, C 2018, 'Thirty years of the International Journal of Computer Integrated Manufacturing: a bibliometric analysis', International Journal of Computer Integrated Manufacturing, vol. 31, no. 12, pp. 1247-1268.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The International Journal of Computer Integrated Manufacturing was established in 1988 with the idea of advancing research in computer integrated manufacturing (CIM) technologies and promoting the application of those technologies within industry. The journal was created to facilitate the exchange of new knowledge between industry and academia derived from both research and practical application. To celebrate the 30-year journey of the journal, this study develops a bibliometric analysis of all the publications of the journal to 2017. Information was collected using the Web of Science Core Collection database. The present study has been conducted to highlight the significant contributions of the journal in terms of impact, topics, authors, universities and countries. Finally, visualisation of similarities (VOS) viewer software was used to present graphical representations of the bibliographic coupling, co-citation, citation, co-authorship and co-occurrence of keywords.
Laengle, S, Modak, NM, Merigo, JM & Zurita, G 2018, 'Twenty-Five Years of Group Decision and Negotiation: A Bibliometric Overview', Group Decision and Negotiation, vol. 27, no. 4, pp. 505-542.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Twenty-five years ago, in 1992, a journal named Group Decision and Negotiation was established in association with the Institute for Operations Research and the Management Sciences with the vision of promoting theoretical and empirical research, real-world applications and case studies on group decision and negotiation processes. To celebrate its 25 years of continuous and outstanding contributions, this study aims to develop a bibliometric analysis of the publications of the journal between 1992 and 2016. The Web of Science Core Collection database is used to identify the leading trends of the journal in terms of impacts, topics, authors, universities and countries. Moreover, it utilizes the visualization of similarities viewer software to analyze the bibliographic couplings, co-citations, citations, co-authorships and co-occurrences of keywords.
Lai, W, Ni, W, Wang, H & Liu, RP 2018, 'Analysis of Average Packet Loss Rate in Multi-Hop Broadcast for VANETs', IEEE Communications Letters, vol. 22, no. 1, pp. 157-160.
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© 2017 IEEE. Multi-hop relay can effectively improve the average packet loss rate (PLR) of vehicular ad hoc networks within a particular zone of interest. Challenges arise from analyzing the average PLR affected by distributed relay selections, which depend on the mobility of vehicles, the wireless channel conditions, and media access control (MAC). In this letter, we propose an average PLR analysis model taking into account the above three factors. However, the closed-form expression for the average PLR is intractable mainly due to the multiple integral of the joint distance distribution integrating with the channel conditions and vehicle mobility. An explicit expression for the upper bound of the average PLR is obtained by using Taylor series expansion, Holder's inequality, and the relay probability relaxation, which can facilitate the selection of the parameters at the physical and MAC layers for a better PLR. Simulation results validate our analyses.
Lake, C & Sheng, D 2018, 'Note of appreciation / Note de reconnaissance', Canadian Geotechnical Journal, vol. 55, no. 12, pp. v-vii.
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Lal, S, Caseley, EA, Hall, RM & Tipper, JL 2018, 'Biological Impact of Silicon Nitride for Orthopaedic Applications: Role of Particle Size, Surface Composition and Donor Variation', Scientific Reports, vol. 8, no. 1, pp. 9109-9109.
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AbstractThe adverse biological impact of orthopaedic wear debris currently limits the long-term safety of human joint replacement devices. We investigated the role of particle size, surface composition and donor variation in influencing the biological impact of silicon nitride as a bioceramic for orthopaedic applications. Silicon nitride particles were compared to the other commonly used orthopaedic biomaterials (e.g. cobalt-chromium and Ti-6Al-4V alloys). A novel biological evaluation platform was developed to simultaneously evaluate cytotoxicity, inflammatory cytokine release, oxidative stress, and genotoxicity potential of particles using peripheral blood mononuclear cells (PBMNCs) from individual human donors. Irrespective of the particle size, silicon nitride did not cause any adverse responses whereas cobalt-chromium wear particles caused donor-dependent cytotoxicity, TNF-α cytokine release, oxidative stress, and DNA damage in PBMNCs after 24 h. Despite being similar in size and morphology, silicon dioxide nanoparticles caused the release of significantly higher levels of TNF-α compared to silicon nitride nanoparticles, suggesting that surface composition influences the inflammatory response in PBMNCs. Ti-6Al-4V wear particles also released significantly elevated levels of TNF-α cytokine in one of the donors. This study demonstrated that silicon nitride is an attractive orthopaedic biomaterial due to its minimal biological impact on human PBMNCs.
Laloo, AE, Wei, J, Wang, D, Narayanasamy, S, Vanwonterghem, I, Waite, D, Steen, J, Kaysen, A, Heintz-Buschart, A, Wang, Q, Schulz, B, Nouwens, A, Wilmes, P, Hugenholtz, P, Yuan, Z & Bond, PL 2018, 'Mechanisms of Persistence of the Ammonia-Oxidizing Bacteria Nitrosomonas to the Biocide Free Nitrous Acid', Environmental Science & Technology, vol. 52, no. 9, pp. 5386-5397.
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Free nitrous acid (FNA) exerts a broad range of antimicrobial effects on bacteria, although susceptibility varies considerably among microorganisms. Among nitrifiers found in activated sludge of wastewater treatment processes (WWTPs), nitrite-oxidizing bacteria (NOB) are more susceptible to FNA compared to ammonia-oxidizing bacteria (AOB). This selective inhibition of NOB over AOB in WWTPs bypasses nitrate production and improves the efficiency and costs of the nitrogen removal process in both the activated sludge and anaerobic ammonium oxidation (Anammox) system. However, the molecular mechanisms governing this atypical tolerance of AOB to FNA have yet to be understood. Herein we investigate the varying effects of the antimicrobial FNA on activated sludge containing AOB and NOB using an integrated metagenomics and label-free quantitative sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) metaproteomic approach. The Nitrosomonas genus of AOB, on exposure to FNA, maintains internal homeostasis by upregulating a number of known oxidative stress enzymes, such as pteridine reductase and dihydrolipoyl dehydrogenase. Denitrifying enzymes were upregulated on exposure to FNA, suggesting the detoxification of nitrite to nitric oxide. Interestingly, proteins involved in stress response mechanisms, such as DNA and protein repair enzymes, phage prevention proteins, and iron transport proteins, were upregulated on exposure to FNA. In addition enzymes involved in energy generation were also upregulated on exposure to FNA. The total proteins specifically derived from the NOB genus Nitrobacter was low and, as such, did not allow for the elucidation of the response mechanism to FNA exposure. These findings give us an understanding of the adaptive mechanisms of tolerance within the AOB Nitrosomonas to the biocidal agent FNA.
Lamqadem, A, Saber, H & Pradhan, B 2018, 'Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques', Remote Sensing, vol. 10, no. 12, pp. 1862-1862.
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Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI–albedo, TCG–TCB and TCW–TCB combinations. Results showed a higher correlation between TCW and TCB (r = −0.812) than with that of the NDVI–albedo (r = −0.50). On the basis of this analysis, a desertification degree index was developed using the TCW–TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands.
Lan, C, Peng, H, McGowan, EM, Hutvagner, G & Li, J 2018, 'An isomiR expression panel based novel breast cancer classification approach using improved mutual information', BMC Medical Genomics, vol. 11, no. S6, pp. 118-118.
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BACKGROUND:Gene expression-based profiling has been used to identify biomarkers for different breast cancer subtypes. However, this technique has many limitations. IsomiRs are isoforms of miRNAs that have critical roles in many biological processes and have been successfully used to distinguish various cancer types. Biomarker isomiRs for identifying different breast cancer subtypes has not been investigated. For the first time, we aim to show that isomiRs are better performing biomarkers and use them to explain molecular differences between breast cancer subtypes. RESULTS:In this study, a novel method is proposed to identify specific isomiRs that faithfully classify breast cancer subtypes. First, as a null hypothesis method we removed the lowly expressed isomiRs from small sequencing data generated from diverse breast cancers types. Second, we developed an improved mutual information-based feature selection method to calculate the weight of each isomiR expression. The weight of isomiR measures the importance of a given isomiR in classifying breast cancer subtypes. The improved mutual information enables to apply the dataset in which the feature is continuous data and label is discrete data; whereby, the traditional mutual information cannot be applied in this dataset. Finally, the support vector machine (SVM) classifier is applied to find isomiR biomarkers for subtyping. CONCLUSIONS:Here we demonstrate that isomiRs can be used as biomarkers in the identification of different breast cancer subtypes, and in addition, they may provide new insights into the diverse molecular mechanisms of breast cancers. We have also shown that the classification of different subtypes of breast cancer based on isomiRs expression is more effective than using published gene expression profiling. The proposed method provides a better performance outcome than Fisher method and Hellinger method for discovering biomarkers to distinguish different breast cancer subtypes. This novel techniqu...
Lanese, I & Devitt, S 2018, 'Preface for the special issue of the 8th Conference on Reversible Computation (RC 2016)', Science of Computer Programming, vol. 151, pp. 1-1.
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Laranjo, L, Dunn, AG, Tong, HL, Kocaballi, AB, Chen, J, Bashir, R, Surian, D, Gallego, B, Magrabi, F, Lau, AYS & Coiera, E 2018, 'Conversational agents in healthcare: a systematic review', Journal of the American Medical Informatics Association, vol. 25, no. 9, pp. 1248-1258.
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Abstract
Objective
Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes.
Methods
We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen’s kappa measured inter-coder agreement.
Results
The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies.
Conclusions
The use of conversational agents with unconstrained natural lan...
LASHKARIPOUR, ALI, MEHRIZI, AA, GOHARIMANESH, M, RASOULI, M & BAZAZ, SR 2018, 'SIZE-CONTROLLED DROPLET GENERATION IN A MICROFLUIDIC DEVICE FOR RARE DNA AMPLIFICATION BY OPTIMIZING ITS EFFECTIVE PARAMETERS', Journal of Mechanics in Medicine and Biology, vol. 18, no. 01, pp. 1850002-1850002.
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Versatility and portability of microfluidic devices play a dominant role in their widespread use by researchers. Droplet-based microfluidic devices have been extensively used due to their precise control over sample volume, and ease of manipulating and addressing each droplet on demand. Droplet-based polymerase chain reaction (PCR) devices are particularly desirable in single DNA amplification. If the droplets are small enough to contain only one DNA molecule, single molecule amplification becomes possible, which can be advantageous in several cases such as early cancer detection. In this work, flow-focusing microfluidic droplet generation’s parameters are numerically investigated and optimized for generating the smallest droplet possible, while considering fabrication limits. Taguchi design of experiment method is used to study the effects of key parameters in droplet generation. By exploiting this approach, a droplet with a radius of 111[Formula: see text]nm is generated using a 3[Formula: see text][Formula: see text]m orifice. Since the governing physics of the droplet generation process is not totally understood yet, by means of analysis of variance (ANOVA) analysis, a generalized linear model (GLM) is proposed to predict the droplet radius, given the values of eight major parameters affecting the droplet size. The proposed model shows a correlation of 95.3% and 64.95% for droplets of radius greater than and lower than 5[Formula: see text][Formula: see text]m, respectively. Finally, the source of this variation of behavior in different size scales is identified.
Le, X, Chen, S, Yan, Z & Xi, J 2018, 'A Neurodynamic Approach to Distributed Optimization With Globally Coupled Constraints', IEEE Transactions on Cybernetics, vol. 48, no. 11, pp. 3149-3158.
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IEEE In this paper, a distributed neurodynamic approach is proposed for constrained convex optimization. The objective function is a sum of local convex subproblems, whereas the constraints of these subproblems are coupled. Each local objective function is minimized individually with the proposed neurodynamic optimization approach. Through information exchange between connected neighbors only, all nodes can reach consensus on the Lagrange multipliers of all global equality and inequality constraints, and the decision variables converge to the global optimum in a distributed manner. Simulation results of two power system cases are discussed to substantiate the effectiveness and characteristics of the proposed approach.
Lee, D, van Dorp Schuitman, J, Qiu, X & Burnett, I 2018, 'Development of a clarity parameter using a time-varying loudness model', The Journal of the Acoustical Society of America, vol. 143, no. 6, pp. 3455-3459.
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Lee, J-H, Sameen, MI, Pradhan, B & Park, H-J 2018, 'Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods', Geomorphology, vol. 303, pp. 284-298.
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Lee, M & McCambridge, A 2018, 'Clinimetrics: Amyotrophic Lateral Sclerosis Functional Rating Scale-revised (ALSFRS-R)', Journal of Physiotherapy, vol. 64, no. 4, pp. 269-270.
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Lee, S, Kim, Y, Park, J, Shon, HK & Hong, S 2018, 'Treatment of medical radioactive liquid waste using Forward Osmosis (FO) membrane process', Journal of Membrane Science, vol. 556, pp. 238-247.
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© 2018 Elsevier B.V. The use of forward osmosis (FO) for concentrating radioactive liquid waste from radiation therapy rooms in hospitals was systematically investigated in this study. The removal of natural and radioactive iodine using FO was first investigated with varying pHs and draw solutions (DSs) to identify the optimal conditions for FO concentration. Results showed that FO had a successful rejection rate for both natural and radioactive iodine (125I) of up to 99.3%. This high rejection rate was achieved at a high pH, mainly due to electric repulsion between iodine and membrane. Higher iodine removal by FO was also attained with a DS that exhibits a reverse salt flux (RSF) adequate to hinder iodine transport. Following this, actual radioactive medical liquid waste was collected and concentrated using FO under these optimal conditions. The radionuclides in the medical waste (131I) were removed effectively, but the water recovery rate was limited due to severe membrane fouling. To enhance the recovery rate, hydraulic washing was applied, but this had only limited success due to combined organic-inorganic fouling of the FO membrane. Finally, the effect of FO concentration on the reduction of septic tank volume was simulated as a function of recovery rate. To our knowledge, this study is the first attempt to explore the potential of FO technology for treating radioactive waste, and thus could be expanded to the dewatering of the radioactive liquid wastes from a variety of sources, such as nuclear power plants.
Lees, T, Chalmers, T, Burton, D, Zilberg, E, Penzel, T, Lal, S & Lal, S 2018, 'Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers', Physiological Measurement, vol. 39, no. 10, pp. 105012-105012.
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OBJECTIVE:In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers. APPROACH:Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20). MAIN RESULTS:Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores. SIGNIFICANCE:Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.
Lees, T, Shad-Kaneez, F, Simpson, AM, Nassif, NT, Lin, Y & Lal, S 2018, 'Heart Rate Variability as a Biomarker for Predicting Stroke, Post-stroke Complications and Functionality', Biomarker Insights, vol. 13, pp. 117727191878693-117727191878693.
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Background: Heart rate variability (HRV) is a non-invasive measure of the function of the autonomic nervous system, and its dynamic nature may provide a means through which stroke and its associated complications may be predicted, monitored, and managed. Objective: The objective of this review is to identify and provide a critique on the most recent uses of HRV in stroke diagnosis/management and highlight areas that warrant further research. Methods: The MEDLINE, CINAHL, and OVID MEDLINE databases were canvassed using a systematic search strategy, for articles investigating the use of HRV in stroke diagnosis and management. Initial paper selections were based on title alone, and final paper inclusion was informed by a full-text critical appraisal. Results: The systematic search returned 98 records, of which 51 were unique. Following screening, 22 records were included in the final systematic review. The included papers provided some information regarding predicting incident stroke, which largely seems to be best predicted by time- and frequency-domain HRV parameters. Furthermore, post-stroke complications and functionality are similarly predicted by time- and frequency-domain parameters, as well as non-linear parameters in some instances. Conclusions: Current research provides good evidence that HRV parameters may have utility as a biomarker for stroke and for post-stroke complications and/or functionality. Future research would benefit from the integration of non-linear, and novel parameters, the hybridisation of HRV parameters, and the expansion of the utilisation of predictive regression and hazard modelling.
Lei, B, Li, W, Tang, Z, Tam, VWY & Sun, Z 2018, 'Durability of recycled aggregate concrete under coupling mechanical loading and freeze-thaw cycle in salt-solution', Construction and Building Materials, vol. 163, pp. 840-849.
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© 2017 Elsevier Ltd In this study, a novel coupling testing protocol with separated repetitive loading and freezing-thaw cycles in salt-solution is designed to simulate coupling mechanical loading and complex environmental effects on durability and deterioration of recycled aggregate concrete (RAC). The Micromechanical properties and porosity of RAC were also characterized by scanning electron microscopy (SEM) and microhardness. The results show that the number and width of cracks of RAC and NAC under freeze-thaw cycles obviously increased with the increase of alternating times of repetitive load and the compressive stress level. The compressive strength losses for both RAC and NAC increase with the increase of compressive stress level and alternative times of repetitive load. However, the compressive strength of natural aggregate concrete (NAC) became lower than that of RAC after freeze-thaw cycles. It was found that the freeze-thaw resistance of RAC seems even better than that of NAC under the same freeze-thaw attacks and cyclic mechanical loading. It indicates that after freeze-thaw cycles in salt-solution, the durability of RAC is better than that of NAC. On the other hand, the microhardness and SEM characterization results indicate that the interface transition zone (ITZ) was a weak part in both RAC and NAC, and the ITZ in NAC obviously deteriorated faster than that of RAC.
Lei, G, Wang, T, Zhu, J & Guo, Y 2018, 'Robust multiobjective and multidisciplinary design optimization of electrical drive systems', CES Transactions on Electrical Machines and Systems, vol. 2, no. 4, pp. 409-416.
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Lenka, RK, Rath, AK, Tan, Z, Sharma, S, Puthal, D, Simha, NVR, Prasad, M, Raja, R & Tripathi, SS 2018, 'Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors', IEEE Access, vol. 6, pp. 30162-30173.
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© 2013 IEEE. Wireless sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete the IoT Infrastructure. These deployed wireless sensors are with limited energy and processing capabilities. The IoT infrastructure becomes a key factor to building cyber-physical-social networking infrastructure, where all these sensing devices transmit data toward the cloud data center. Data routing toward cloud data center using such low power sensor is still a challenging task. In order to prolong the lifetime of the IoT sensing infrastructure and building scalable cyber infrastructure, there is the requirement of sensing optimization and energy efficient data routing. Toward addressing these issues of IoT sensing, this paper proposes a novel rendezvous data routing protocol for low-power sensors. The proposed method divides the sensing area into a number of clusters to lessen the energy consumption with data accumulation and aggregation. As a result, there will be less amount of data stream to the network. Another major reason to select cluster-based data routing is to reduce the control overhead. Finally, the simulation of the proposed method is done in the Castalia simulator to observe the performance. It has been concluded that the proposed method is energy efficient and it prolongs the networks lifetime for scalable IoT infrastructure.
León-Castro, E, Avilés-Ochoa, E & Merigó, JM 2018, 'Induced Heavy Moving Averages', International Journal of Intelligent Systems, vol. 33, no. 9, pp. 1823-1839.
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León-Castro, E, Avilés-Ochoa, E, Merigó, JM & Gil-Lafuente, AM 2018, 'Heavy Moving Averages and Their Application in Econometric Forecasting', Cybernetics and Systems, vol. 49, no. 1, pp. 26-43.
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Leong, KY, Razali, I, Ku Ahmad, KZ, Ong, HC, Ghazali, MJ & Abdul Rahman, MR 2018, 'Thermal conductivity of an ethylene glycol/water-based nanofluid with copper-titanium dioxide nanoparticles: An experimental approach', International Communications in Heat and Mass Transfer, vol. 90, pp. 23-28.
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Leyendekkers, JV & Shannon, AG 2018, 'An indicator characteristic for twin prime formation independent of integer size', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 1, pp. 10-15.
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Leyendekkers, JV & Shannon, AG 2018, 'Prime sequences', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 3, pp. 77-83.
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Leyendekkers, JV & Shannon, AG 2018, 'The structure of prime sums', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 4, pp. 86-91.
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Li, G, Chen, H, Peng, S, Li, X, Wang, C, Yu, S & Yin, P 2018, 'A Collaborative Data Collection Scheme Based on Optimal Clustering for Wireless Sensor Networks', Sensors, vol. 18, no. 8, pp. 2487-2487.
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In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.
Li, H, Liu, D, Dai, Y, Luan, TH & Yu, S 2018, 'Personalized Search Over Encrypted Data With Efficient and Secure Updates in Mobile Clouds', IEEE Transactions on Emerging Topics in Computing, vol. 6, no. 1, pp. 97-109.
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Li, H, Luo, Z, Gao, L & Qin, Q 2018, 'Topology optimization for concurrent design of structures with multi-patch microstructures by level sets', Computer Methods in Applied Mechanics and Engineering, vol. 331, pp. 536-561.
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© 2017 Elsevier B.V. This paper focuses on the novel concurrent design for cellular structures consisting of multiple patches of material microstructures using a level set-based topological shape optimization method. The macro structure is featured with the configuration of a cluster of non-uniformly distributed patches, while each patch hosts a number of identical material microstructures. At macro scale, a discrete element density based approach is presented to generate an overall structural layout involving different groups of discrete element densities. At micro scale, each macro element is regarded as an individual microstructure with a discrete intermediate density. Hence, all the macro elements with the same discrete densities (volume fractions) are represented by a unique microstructure. The representative microstructures corresponding to different density groups are topologically optimized by incorporating the numerical homogenization approach into a parametric level set method. The multiscale concurrent designs are integrated into a uniform optimization procedure, so as to optimize both topologies for the macrostructure and its microstructures, as well as locations of the microstructures in the design space. Numerical examples demonstrate that the proposed method can substantially improve the structural performance with an affordable computation and manufacturing cost.
Li, H, Luo, Z, Gao, L & Walker, P 2018, 'Topology optimization for functionally graded cellular composites with metamaterials by level sets', Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 340-364.
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The application of auxetic composites in practice often relies on a compromise between properties as auxetics are mostly too porous (not dense enough or not stiff enough) to bear structural loads. Hence, the focus of this paper is topological design optimization of new functionally graded cellular composites with auxetics using a level set method. Firstly, a new hierarchical multi-scale formulation is developed to account for both the auxetic behavior of the microstructure and the stiffness of the macrostructure. The composite, comprising multiple layers of periodic microstructures, is tailored to have functionally graded properties for stiffness and auxetic behaviors, subject to volumetric gradient constraints. Secondly, the microstructures underpinning composite layers are topologically designed under the consideration of boundary and loading conditions of the macrostructure. Finally, a level set method is applied to evolve the shape and topology of the microstructure for each layer, with the numerical homogenization method to evaluate the effective properties of the microstructures. Several numerical examples are used to demonstrate the effectiveness of the proposed method. It can be seen that such composites systematically gear together the features of the functionally graded materials, cellular composites, and metamaterials towards a new kind of man-made composites.
Li, H, Luo, Z, Gao, L & Wu, J 2018, 'An improved parametric level set method for structural frequency response optimization problems', Advances in Engineering Software, vol. 126, pp. 75-89.
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© 2018 Elsevier Ltd In conventional parametric level set methods, the compactly supported radial basis functions (CSRBF) are used to approximate the level set function due to their unique properties, such as the sparsity of the interpolation matrix. The CSRBFs only consider the contributions of knots within a narrow sub-region, which sacrifices accuracy for efficiency in the interpolation. However, the accuracy loss in the CSRBF-based method may prolong the iteration and gradually lead the topology optimization towards a worse local optimum or even an unfeasible design, especially when the allowable material usage in the design domain is relatively low. This will significantly affect the performance of the optimization method. This paper proposes an improved parametric level set method (iPLSM), which is more efficient and effective in topology optimization designs. In this method, the Gaussian radial basis function with global support is used to parameterize the level set surface, to ensure a high numerical accuracy due to the consideration of all interpolation knots in the global domain. Then, a discrete wavelet transform scheme is incorporated into the parametric form to compress the full interpolation matrix and save the computational cost. The proposed method is applied to both the global and local frequency response optimization problems under wide excitation frequency ranges, to validate its efficiency and effectiveness.
Li, H, Öchsner, A, Yarlagadda, PKDV, Xiao, Y, Furushima, T, Wei, D, Jiang, Z & Manabe, K-I 2018, 'A new constitutive analysis of hexagonal close-packed metal in equal channel angular pressing by crystal plasticity finite element method', Continuum Mechanics and Thermodynamics, vol. 30, no. 1, pp. 69-82.
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© 2017, Springer-Verlag GmbH Germany. Most of hexagonal close-packed (HCP) metals are lightweight metals. With the increasing application of light metal products, the production of light metal is increasingly attracting the attentions of researchers worldwide. To obtain a better understanding of the deformation mechanism of HCP metals (especially for Mg and its alloys), a new constitutive analysis was carried out based on previous research. In this study, combining the theories of strain gradient and continuum mechanics, the equal channel angular pressing process is analyzed and a HCP crystal plasticity constitutive model is developed especially for Mg and its alloys. The influence of elevated temperature on the deformation mechanism of the Mg alloy (slip and twin) is novelly introduced into a crystal plasticity constitutive model. The solution for the new developed constitutive model is established on the basis of the Lagrangian iterations and Newton Raphson simplification.
Li, H, Wang, J, Lu, H & Guo, Z 2018, 'Research and application of a combined model based on variable weight for short term wind speed forecasting', Renewable Energy, vol. 116, pp. 669-684.
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Li, J & Wu, C 2018, 'Damage evaluation of ultra-high performance concrete columns after blast loads', International Journal of Protective Structures, vol. 9, no. 1, pp. 44-64.
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As emerging advanced construction material, ultra-high performance concretes have seen increasing field applications over the past two decades to take advantages of their ultra-high mechanical strength and durability; yet the systematic study on its dynamic behaviour under impact and blast loads is not commonly seen. This article presents an experimental and numerical study on the static and dynamic behaviour of an existing ultra-high performance concrete material. Experimental study on its flexural behaviour under static loads is conducted and an inverse study is carried out to derive its uniaxial tensile constitutive law. The derived relationship is used in the material model in hydro-code LS-DYNA together with dynamic material properties to study ultra-high performance concrete columns under blast loads. The residual loading capacity of the column is studied and pressure–impulse diagrams for assessing the ultra-high performance concrete column damage under blast loads are proposed. Parametric study on effects of ultra-high performance concrete strength, column height, cross-section size and reinforcement ratio is performed and analytical equations are proposed for generating pressure–impulse diagrams for generic ultra-high performance concrete columns.
Li, J, Luo, H, Zhang, S, Yu, S & Wolf, T 2018, 'Traffic Engineering in Information-Centric Networking: Opportunities, Solutions and Challenges', IEEE Communications Magazine, vol. 56, no. 11, pp. 124-130.
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Li, J, Nakai, K, Zheng, Y, Sato, K & Wong, L 2018, 'Introduction to Selected Papers from GIW2018', Journal of Bioinformatics and Computational Biology, vol. 16, no. 06, pp. 1802005-1802005.
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Li, J, Wei, J, Ngo, HH, Guo, W, Liu, H, Du, B, Wei, Q & Wei, D 2018, 'Characterization of soluble microbial products in a partial nitrification sequencing batch biofilm reactor treating high ammonia nitrogen wastewater', Bioresource Technology, vol. 249, pp. 241-246.
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In present study, the characterization of soluble microbial products (SMP) was evaluated in a partial nitrification sequencing batch biofilm reactor (SBBR). During the stable operation of SBBR, the NH4+-N removal efficiency and nitrite accumulation ratio were 96.70±0.41% and 93.77±1.04%, respectively. According to excitation-emission matrix (EEM), the intensities of protein-like substances were reduced under anoxic and aerobic phases, whereas humic-like substances had little change during the whole cycle. Parallel factor analysis (PARAFAC) further indentified two components and their fluorescence intensity scores were both reduced. Synchronous fluorescence spectra revealed that the fluorescence intensity of protein-like fraction decreased with reaction time. Two-dimensional correlation spectroscopy (2D-COS) further demonstrated that protein-like fraction might decrease earlier than the other fractions. The information obtained in present study is of fundamental significance for understanding the key components in SMP and their changes in partial nitrification system by using a spectral approach.
Li, J, Wu, C & Liu, Z-X 2018, 'Comparative evaluation of steel wire mesh, steel fibre and high performance polyethylene fibre reinforced concrete slabs in blast tests', Thin-Walled Structures, vol. 126, pp. 117-126.
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© 2017 Elsevier Ltd. Concrete is the most widely used construction material in the modern construction practice. Due to its relatively low tensile resistance, concrete tends to experience tensile failure and cracking under external loads. To enhance the tensile performance and ductility of concrete material, possible solutions including fibre reinforcement and steel mesh reinforcement are investigated in the present study. Steel fibre, ultra-high molecular weight polyethylene (UHMWPE) fibre and steel wire meshes were mixed with varying volume fraction in the concrete matrix. Static material tests including uniaxial compression and flexural bending tests showed that the steel fibre addition yielded better strength enhancement while UHMWPE fibre provided better material ductility. Concrete samples with hybrid steel fibre-steel mesh reinforcement showed high strength and ductility. Field blast tests are designed to study the behaviour of reinforced concrete slabs under close-in detonations. Different damage profiles are observed from the blast tests. The advantages and disadvantages of using different reinforcing materials are discussed. From the results, the advantages of replacing steel fibre with UHMWPE fibre or steel wire mesh were demonstrated.
Li, J, Wu, C, Hao, H, Liu, Z & Yang, Y 2018, 'Basalt scale-reinforced aluminium foam under static and dynamic loads', Composite Structures, vol. 203, pp. 599-613.
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© 2018 Elsevier Ltd In this paper, mechanical performance and deformation behaviour of basalt scale-reinforced closed-cell aluminium foams are investigated. Quasi-static uniaxial compressive tests on the constitutive alloy material reveal that after basalt scale reinforcement, the alloy elasticity modulus and yield strength show noticeable enhancement. Quasi-static compression tests on the foam material show that while basalt scale-reinforced aluminium foam has higher plastic crush stress and plateau stress, the densification strain is lower than non-reinforced foam. A method based on energy absorption efficiency is adopted to accurately measure the densification strain for both foam materials. In the subsequent split-Hopkinson pressure bar tests, dynamic compressive behaviour of basalt scale-reinforced aluminium foams with relative densities ranged from 14% to 33% is studied experimentally under strain rate ranging from 480/s to 1720/s. Clear material rate sensitivity is noted from the dynamic tests. The results indicate that the plateau stress of aluminium foam increases with relative density and strain rate. In addition, with the increase in strain rates, an increase in the energy absorption capacity is observed and this characteristic is beneficial when the foam material is used to absorb impact energy. A mesoscopic model based on the X-ray CT for the aluminium foam material is developed. The simulations and the test data agreed well for the quasi-static loading case. However, it is noted that the mesoscale model without consideration of the base material rate sensitivity and the entrapped gas underestimated the strength enhancement under dynamic loading scenario.
Li, J, Ye, W, Wei, D, Ngo, HH, Guo, W, Qiao, Y, Xu, W, Du, B & Wei, Q 2018, 'System performance and microbial community succession in a partial nitrification biofilm reactor in response to salinity stress', Bioresource Technology, vol. 270, pp. 512-518.
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The system performance and microbial community succession in a partial nitrification biofilm reactor in response to salinity stress was conducted. It was found that the NH4+-N removal efficiency decreased from 98.4% to 42.0% after salinity stress increased to 20 g/L. Specific oxygen uptake rates suggested that AOB activity was more sensitive to the stress of salinity than that of NOB. Protein and polysaccharides contents showed an increasing tendency in both LB-EPS and TB-EPS after the salinity exposure. Moreover, EEM results indicated that protein-like substances were the main component in LB-EPS and TB-EPS as self-protection in response to salinity stress. Additionally, humic acid-like substances were identified as the main component in the effluent organic matter (EfOM) of partial nitrification biofilm, whereas fulvic acid-like substances were detected at 20 g/L salinity stress. Microbial community analysis found that Nitrosomonas as representative species of AOB were significantly inhibited under high salinity condition.
Li, JJ, Akey, A, Dunstan, CR, Vielreicher, M, Friedrich, O, Bell, DC & Zreiqat, H 2018, 'Effects of Material–Tissue Interactions on Bone Regeneration Outcomes Using Baghdadite Implants in a Large Animal Model', Advanced Healthcare Materials, vol. 7, no. 15, pp. 1800218-1800218.
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Li, JJ, Ebied, M, Xu, J & Zreiqat, H 2018, 'Current Approaches to Bone Tissue Engineering: The Interface between Biology and Engineering', Advanced Healthcare Materials, vol. 7, no. 6, pp. 1701061-1701061.
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Li, K, Gao, W, Wu, D, Song, C & Chen, T 2018, 'Spectral stochastic isogeometric analysis of linear elasticity', Computer Methods in Applied Mechanics and Engineering, vol. 332, pp. 157-190.
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© 2017 Elsevier B.V. The stochastic isogeometric analysis of linear elasticity problem is investigated in this study. The spectral stochastic analysis is introduced into isogeometric analysis (IGA), and a novel, yet robust, stochastic analysis framework, namely the spectral stochastic isogeometric analysis (SSIGA), is freshly proposed. Unlike traditional numerical solutions of the Karhunen–Loève (K-L) expansion, the non-uniform rational B-spline (NURBS) and T-spline basis functions are employed within the proposed framework of SSIGA, so the random fields acting on a continuous physical medium with complex geometry can be handled in an appropriate, physically feasible and efficient fashion. The polynomials chaos expansion (PCE) is implemented to represent the stochastic structural response (e.g., displacement, strain and stress), such that all corresponding statistical characteristics (e.g., mean and standard deviation) can be robustly acquired. Furthermore, by utilizing the nonparametric statistical analysis, both probability density functions (PDFs) and cumulative distribution functions (CDFs) of concerned structural displacements and stresses can be effectively established. Within the framework of IGA, by meticulously implementing the concept of the higher-order k-refinement, the proposed SSIGA provides a more legitimate and efficient stochastic computational approach for modern engineering structures which are complicated by both spatially dependent uncertainties and complex geometries.
Li, K, Ni, W, Duan, L, Abolhasan, M & Niu, J 2018, 'Wireless Power Transfer and Data Collection in Wireless Sensor Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 3, pp. 2686-2697.
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© 1967-2012 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, whereas the other nodes 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 EHMDP, aimin g to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semidecentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.
Li, K, Wu, D & Gao, W 2018, 'Spectral stochastic isogeometric analysis for static response of FGM plate with material uncertainty', Thin-Walled Structures, vol. 132, pp. 504-521.
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© 2018 Elsevier Ltd In this study, the nondeterministic structural responses of functionally graded material (FGM) plates under static loads with uncertain material property is investigated. The considered spatially dependent uncertainties are modelled as random fields with Gaussian distribution. A novel spectral stochastic isogeometric analysis (SSIGA) framework is proposed for such uncertainty quantification through the first-order shear deformation theory. Within the SSIGA framework, the non-uniform rational B-spline (NURBS) is adopted for both the geometry modelling of the random fields of the uncertain material properties and random field discretization through the Karhunen-Loève (K-L) expansion. Such new feature provides an effective and practically applicable random field modelling technique, especially for uncertain parameters over complex physical domains. The polynomial chaos expansion (PCE) is employed for estimating the statistical characteristics (e.g., mean and standard deviation) of any concerned structural responses (e.g., displacement and stress). By further implementing various statistical inference techniques, the probability density functions (PDF) and cumulative distribution functions (CDF) of structural responses can be established to determine both serviceability and strength limits of FGM plate. Two numerical examples are thoroughly investigated to illustrate the applicability, effectiveness and efficiency of the proposed computational approach.
Li, K, Wu, D, Chen, X, Cheng, J, Liu, Z, Gao, W & Liu, M 2018, 'Isogeometric Analysis of functionally graded porous plates reinforced by graphene platelets', Composite Structures, vol. 204, pp. 114-130.
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© 2018 Elsevier Ltd This paper investigates the static linear elasticity, natural frequency, and buckling behaviour of functionally graded porous plates reinforced by graphene platelets (GPLs). Both first- and third-order shear deformation plate theories are incorporated within the Isogeometric Analysis (IGA) framework. The pores and the GPLs within the plates are distributed in the metal matrix either uniformly or non-uniformly according to different patterns. The graded distributions of porosity and nanocomposite are achieved by material parameters varying across the thickness direction of plate. The Halpin-Tsai micromechanics model is implemented to establish the relationship between porosity coefficient and Young's modulus, as well as to obtain the mass density of the nanocomposite. The variation of Poisson's ratio is determined by the mechanical properties of closed-cell cellular solids under Gaussian Random Field scheme. A comprehensive parametric study is accomplished to investigate the effects of weight fraction, distribution pattern, geometry, and size of the GPLs reinforcement on the static linear elasticity, natural frequency, and buckling behaviour of the nanocomposite plates with diverse metal matrices and porosity coefficients. The outcome of numerical investigation shows that the inclusion of the GPLs can effectively improve the stiffness of functionally graded porous plate.
Li, L, Deng, N, Ren, W, Kou, B, Zhou, W & Yu, S 2018, 'Multi-Service Resource Allocation in Future Network With Wireless Virtualization', IEEE Access, vol. 6, pp. 53854-53868.
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Li, L, Liu, J, Sun, Y, Xu, G, Yuan, J & Zhong, L 2018, 'Unsupervised keyword extraction from microblog posts via hashtags', Journal of Web Engineering, vol. 17, no. 1-2, pp. 93-120.
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Nowadays, huge amounts of texts are being generated for social networking purposes on Web. Keyword extraction from such texts like microblog posts benefits many applications such as advertising, search, and content filtering. Unlike traditional web pages, a microblog post usually has some special social feature like a hashtag that is topical in nature and generated by users. Extracting keywords related to hashtags can reflect the intents of users and thus provides us better understanding on post content. In this paper, we propose a novel unsupervised keyword extraction approach for microblog posts by treating hashtags as topical indicators. Our approach consists of two hashtag enhanced algorithms. One is a topic model algorithm that infers topic distributions biased to hashtags on a collection of microblog posts. The words are ranked by their average topic probabilities. Our topic model algorithm can not only find the topics of a collection, but also extract hashtag-related keywords. The other is a random walk based algorithm. It first builds a word-post weighted graph by taking into account posts themselves. Then, a hashtag biased random walk is applied on this graph, which guides the algorithm to extract keywords according to hashtag topics. Last, the final ranking score of a word is determined by the stationary probability after a number of iterations. We evaluate our proposed approach on a collection of real Chinese microblog posts. Experiments show that our approach is more effective in terms of precision than traditional approaches considering no hashtag. The result achieved by the combination of two algorithms performs even better than each individual algorithm.
Li, L, Liu, Z & Zhang, J 2018, 'Unsupervised image co-segmentation via guidance of simple images', Neurocomputing, vol. 275, pp. 1650-1661.
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© 2017 Elsevier B.V. This paper proposes a novel image co-segmentation method, which aims to segment the common objects in a group of images. The proposed method takes advantages of the reliability of simple images and successfully improves the performance. The images are first ranked by the complexities based on their saliency maps. Then, the simple images, in which objects are common and easy to be segmented, are selected and processed to obtain their segmentation results, these segmentation results are taken as the samples of the targeted objects. Finally, the remaining complicated images are segmented with the guidance of the samples. The experiments on the iCoseg dataset demonstrate the outperformance and robustness of the proposed method.
Li, L, Nimbalkar, S & Zhong, R 2018, 'Finite element model of ballasted railway with infinite boundaries considering effects of moving train loads and Rayleigh waves', Soil Dynamics and Earthquake Engineering, vol. 114, pp. 147-153.
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© 2018 Elsevier Ltd This paper proposes a three-dimensional model incorporating finite element (FE) meshes with infinite element (IE) boundaries for ballasted railways. Moving train loads are simulated with sliding motions of moving elements which have hard contact feature at the interface with supporting rails. Dynamic responses of ballasted railway under different train speeds are investigated in time domain and frequency domain to identify the predominant frequency and critical speed. Rayleigh wave (R-Wave) propagation is simulated using the combined FE-IE model to determine the velocity of R-Wave in the layered embankment model and its relationship with the critical speed of the ballasted railway. The proposed model is successfully validated against the results of Euler-Bernoulli Elastic Beam (E-BEB) model.
Li, L, Zhang, S, Yu, X & Zhang, L 2018, 'PMSC: PatchMatch-Based Superpixel Cut for Accurate Stereo Matching', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 3, pp. 679-692.
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Li, M, Liu, Y & Guo, YJ 2018, 'Shaped Power Pattern Synthesis of a Linear Dipole Array by Element Rotation and Phase Optimization Using Dynamic Differential Evolution', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 4, pp. 697-701.
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Li, M, Yang, Y, Xu, KD, Zhu, X & Wong, SW 2018, 'Microwave On-Chip Bandpass Filter Based on Hybrid Coupling Technique', IEEE Transactions on Electron Devices, vol. 65, no. 12, pp. 5453-5459.
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Li, P, Yang, X, Greenshaw, AJ, Li, S, Luo, J, Han, H, Liu, J, Zhong, Z, Guo, Z, Xiong, H, Yao, S, Chen, Y, Sun, J & Li, Z 2018, 'The effects of cognitive behavioral therapy on resting-state functional brain network in drug-naive patients with obsessive-compulsive disorder', Brain and Behavior, vol. 8, no. 5, pp. e00963-e00963.
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Li, Q, Wu, D, Chen, X, Liu, L, Yu, Y & Gao, W 2018, 'Nonlinear vibration and dynamic buckling analyses of sandwich functionally graded porous plate with graphene platelet reinforcement resting on Winkler–Pasternak elastic foundation', International Journal of Mechanical Sciences, vol. 148, pp. 596-610.
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© 2018 Elsevier Ltd The nonlinear vibration and the dynamic buckling of a graphene platelet reinforced sandwich functionally graded porous (GPL-SFGP) plate are thoroughly investigated in this paper. The investigated GPL-SFGP plate consists of two metal face layers and a functionally graded porous core with graphene platelet reinforcement. The effects of the Winkler–Pasternak elastic foundation, thermal environment and damping are incorporated. The open-cell metal foam model is implemented to model the mechanical properties of the porous core. Axial compressive stress is applied on the GPL-SFGP plate by exerting various compressive loading speeds at one edge of the plate. Grounded on the classical plate theory, both motion and geometric compatibility equations of the plate are deduced by introducing the Von Kármán strain-displacement relationship and stress function. Both the Galerkin and the fourth-order Runge–Kutta methods are implemented to solve the governing equation of the dynamic system. Meticulously designed numerical experiments are conducted to identify the critical influential factors of the dynamic stability of the GPL-SFGP plate. The influences of loading speed, damping ratio, temperature variation, initial imperfection, elastic foundation parameters, porosity, GPL weight fraction and the dimensions of the GPL on the overall dynamic stability of the GPL-SFGP plate are evidently demonstrated.
Li, S, Han, K, Ansari, N, Bao, Q, Hu, D, Liu, J, Yu, S & Zhu, Z 2018, 'Improving SDN Scalability With Protocol-Oblivious Source Routing: A System-Level Study', IEEE Transactions on Network and Service Management, vol. 15, no. 1, pp. 275-288.
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Li, S, Ni, W, Sung, CK & Hedley, M 2018, 'Recent advances on cooperative wireless localization and their application in inhomogeneous propagation environments', Computer Networks, vol. 142, pp. 253-271.
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© 2018 Elsevier B.V. In this survey, we review recent advances on cooperative localization techniques and identify critical challenges in realistic cooperative localization systems. Particularly, we focus on the inhomogeneity of radio propagation environments, which has substantial impact on the accuracy of positioning systems that assume a homogeneous propagation model. Popular cooperative localization algorithms based on maximum-likelihood estimation, convex relaxation and optimization, and message passing are surveyed, with more emphasis placed on Received Signal Strength (RSS) based approaches due to their potential application in low cost devices. It is shown that most existing algorithms are based on the assumption of a propagation environment with a priori known spatially invariant propagation models. The extension of existing algorithms to capture the inhomogeneity of propagation environments are studied.
Li, S, Ren, W, Zhu, T & Choo, K-KR 2018, 'Lico: A Lightweight Access Control Model for Inter-Networking Linkages', IEEE Access, vol. 6, pp. 51748-51755.
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© 2013 IEEE. Processes in operating systems are assigned different privileges to access different resources. A process may invoke other processes whose privileges are different; thus, its privileges are expanded (or escalated) due to such improper 'inheritance.' Inter-networking can also occur between processes, either transitively or iteratively. This complicates the monitoring of inappropriate privilege assignment/escalation, which can result in information leakage. Such information leakage occurs due to privilege transitivity and inheritance and can be defined as a general access control problem for inter-networking linkages. This is also a topic that is generally less studied in existing access control models. Specifically, in this paper, we propose a lightweight directed graph-based model, LiCo, which is designed to facilitate the authorization of privileges among inter-networking processes. To the best of our knowledge, this is the first general access control model for inter-invoking processes and general inter-networking linkages.
Li, T, Zhou, H, Luo, H & Yu, S 2018, 'SERvICE: A Software Defined Framework for Integrated Space-Terrestrial Satellite Communication', IEEE Transactions on Mobile Computing, vol. 17, no. 3, pp. 703-716.
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Li, W, Han, C, Xia, Q, Zhang, K, Chou, S, Kang, Y, Wang, J, Liu, HK & Dou, SX 2018, 'Remarkable Enhancement in Sodium‐Ion Kinetics of NaFe 2 (CN) 6 by Chemical Bonding with Graphene', Small Methods, vol. 2, no. 4, pp. 1700346-1700346.
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Li, W, Long, R, Chen, H, Yang, T, Geng, J & Yang, M 2018, 'Effects of personal carbon trading on the decision to adopt battery electric vehicles: Analysis based on a choice experiment in Jiangsu, China', Applied Energy, vol. 209, pp. 478-488.
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© 2017 Elsevier Ltd. The implementation of personal carbon trading (PCT) to influence transport choices has recently been suggested as a method to reduce private carbon emissions. In this study, we conducted a choice experiment in Jiangsu, China, to evaluate if PCT influences individual decisions to adopt battery electric vehicles (BEVs). The results showed that PCT can effectively change the decision to adopt and encourage the adoption of BEVs. PCT was shown to be more effective than free parking as well as eliminating road tolls, vehicle and vessel tax, and purchase tax, but less effective than government subsidies. In addition, we found that improving some BEV performance attributes was preferred to policy incentives, including PCT. These results improve our understanding of the effectiveness of PCT and the individual decision to adopt BEVs. Our findings could facilitate the practical implementation of PCT and provide suitable guidelines for developing BEV promotion strategies.
Li, W, Luo, Z, Wu, C & Duan, WH 2018, 'Impact performances of steel tube-confined recycled aggregate concrete (STCRAC) after exposure to elevated temperatures', Cement and Concrete Composites, vol. 86, pp. 87-97.
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Li, W, Ni, W, Liu, D, Liu, R & Luo, S 2018, 'Unified Ciphertext-Policy Weighted Attribute-Based Encryption for Sharing Data in Cloud Computing', Applied Sciences, vol. 8, no. 12, pp. 2519-2519.
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With the rapid development of cloud computing, it is playing an increasingly important role in data sharing. Meanwhile, attribute-based encryption (ABE) has been an effective way to share data securely in cloud computing. In real circumstances, there is often a mutual access sub-policy in different providers’ access policies, and the significance of each attribute is usual diverse. In this paper, a secure and efficient data-sharing scheme in cloud computing, which is called unified ciphertext-policy weighted attribute-based encryption (UCP-WABE), is proposed. The weighted attribute authority assigns weights to attributes depending on their importance. The mutual information extractor extracts the mutual access sub-policy and generates the mutual information. Thus, UCP-WABE lowers the total encryption time cost of multiple providers. We prove that UCP-WABE is selectively secure on the basis of the security of ciphertext-policy weighted attribute-based encryption (CP-WABE). Additionally, the results of the implementation shows that UCP-WABE is efficient in terms of time.
Li, W, Yang, M & Sandu, S 2018, 'Electric vehicles in China: A review of current policies', Energy & Environment, vol. 29, no. 8, pp. 1512-1524.
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Prompted by the urgency of reducing greenhouse gas emissions in the transport sector, the Chinese government has set ambitious targets for the uptake of electric vehicles. To achieve these targets is however a challenging task, due to various barriers in the uptake of electric vehicles, at both micro- and macro-levels. A range of monetary and non-monetary incentives has been implemented, or being considered for implementation, to overcome these barriers. This paper reviews these incentives with a view to assess the extent to which they are likely to remove the barriers in the uptake of electric vehicles. The review suggests that the primary focus of these incentives is to remove the micro-level barriers, such as high upfront costs, poor technical performance, and insufficient charging infrastructure. Limited attention has been paid to the macro-level barriers (for example, fragmented authority and local protectionism), despite ample evidence suggesting that these barriers could significantly impede the uptake of electric vehicles. Further, these incentives have tended to rely on regulation-based measures to remove the barriers. Only in the recent years, there appears to be a gradual shift towards market-based measures. This shift could improve the effectiveness of electric vehicle policies. The effectiveness of these policies could be enhanced if one recognizes the underlying macro-level barriers that are likely to protract or distort the implementation of market-based measures. This paper also provides some recommendations to remove these macro-level barriers.
Li, X, Mei, Q, Yan, X, Dong, B, Dai, X, Yu, L, Wang, Y, Ding, G, Yu, F & Zhou, J 2018, 'Molecular characteristics of the refractory organic matter in the anaerobic and aerobic digestates of sewage sludge', RSC Advances, vol. 8, no. 58, pp. 33138-33148.
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The chemical characteristics of the refractory organic matter in anaerobic and aerobic digestates are hardly known although they are significant for further improving the degradation of organic matter during sludge digestion.
Li, X, Nie, L, Xu, H & Wang, X 2018, 'Collaborative Fall Detection Using Smart Phone and Kinect', Mobile Networks and Applications, vol. 23, no. 4, pp. 775-788.
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Li, X, Wang, L, Liu, Y, Li, W, Dong, B & Duan, WH 2018, 'Dispersion of graphene oxide agglomerates in cement paste and its effects on electrical resistivity and flexural strength', Cement and Concrete Composites, vol. 92, pp. 145-154.
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Li, XP, Ji, G, Eder, K, Yang, LM, Addad, A, Vleugels, J, Van Humbeeck, J, Cairney, JM & Kruth, JP 2018, 'Additive manufacturing of a novel alpha titanium alloy from commercially pure titanium with minor addition of Mo2C', Materialia, vol. 4, pp. 227-236.
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Li, Y & Ying, M 2018, 'Algorithmic analysis of termination problems for quantum programs.', Proc. ACM Program. Lang., vol. 2, pp. 35:1-35:1.
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Li, Y, Li, W, Deng, D, Wang, K & Duan, WH 2018, 'Reinforcement effects of polyvinyl alcohol and polypropylene fibers on flexural behaviors of sulfoaluminate cement matrices', Cement and Concrete Composites, vol. 88, pp. 139-149.
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© 2018 Elsevier Ltd The fracture behavior of unoiled/uncoated polyvinyl alcohol (PVA) fiber reinforced sulphoaluminate cement (SAC) matrices was experimentally investigated and compared with those of polypropylene (PP) fiber reinforced SAC and PVA fiber reinforced Portland cement (PC) matrices in this study. In the experimental investigation, three-point bending tests were carried out for notched fiber reinforced cement beams. Special attentions were paid on their deflection-hardening and multiple crack patterns. The different flexural behaviors between the plain SAC and PC matrices were evaluated using the double-K fracture model. The results indicate that the PVA fiber reinforced SAC matrices exhibited better flexural behaviors when compared with the PVA fiber reinforced PC matrix having comparable matrix strength. The bond strength between SAC matrix and PVA fiber are relatively better than that between the counterpart PC matrix and PVA fiber, while the bond strength between SAC matrix and PVA fiber is obviously stronger than that between the SAC and PP fibers.
Li, Y, Ren, W, Zhu, T, Ren, Y, Qin, Y & Jie, W 2018, 'RIMS: A Real-time and Intelligent Monitoring System for live-broadcasting platforms', Future Generation Computer Systems, vol. 87, pp. 259-266.
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Personal live shows on Internet streaming platforms currently are blooming as one of the most popular applications on mobile phones and especially attracting millions of young generation users. The content supervision on live streaming platforms, in which there are thousands or hundreds of show rooms for performing and chatting synchronously, is a major concern with the development of this new service. Traditional image captures and real-time content analysis experience huge difficulties such as processing delay, data overwhelming, and matching overhead. In this paper, we propose a comprehensive method to monitor real-time live stream and to identify illegal or unchartered live misbehaviors intelligently based on various proposed aspects instead of image analysis only. The proposed system called RIMS makes use of several novel indicators on show room status rather than analyzing images solely to support real-time requirements. Three detecting techniques are adopted: self-adaptive threshold-based abnormal traffic detection, sensitive Danmaku comment perception, and frame difference analysis. RIMS can detect dramatically increasing of user number in a show room, filter sensitive words in Danmaku, and capture segmentation of video scenes by frame difference analysis. We deploy our system to monitor a typical live- broadcasting platform called panda.tv, and overall accuracy of detection via three indicators reaches 90.1%. The application of RIMS can change current supervison methods on live platforms that they totally rely on real-time manual review or after the event check. The key techniques in RIMS can also be widely employed in many other mobile applications in edge computing such as video surveillance in Internet of Things and mobile short video sharing.
Li, Y, Zhu, L & Zhu, J 2018, 'Core Loss Calculation Based on Finite-Element Method With Jiles–Atherton Dynamic Hysteresis Model', IEEE Transactions on Magnetics, vol. 54, no. 3, pp. 1-5.
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© 2018 IEEE. For accurate computation of core losses, the Jiles-Atherton ( J - A ) dynamic hysteresis model accounting for hysteresis, eddy current and excess losses is incorporated into the finite-element method (FEM). The J - A dynamic hysteresis model is constructed by combining the traditional J - A hysteresis model with the models of instantaneous eddy current and excess losses. The J - A model parameters and dynamic loss coefficients are determined by fitting the models to the measurement data of a single sheet tester (SST 500) and Epstein frame tester. To find the robust best fit, the particle swarm optimization algorithm is employed. By using the proposed J - A dynamic hysteresis model and FEM, the magnetic characteristics of a magnetic core is simulated and the core loss distribution within the core obtained. The calculated and measured results are compared to show the accuracy and effectiveness of the proposed model.
Li, Z, Nie, F, Chang, X, Nie, L, Zhang, H & Yang, Y 2018, 'Rank-Constrained Spectral Clustering With Flexible Embedding', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6073-6082.
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Spectral clustering (SC) has been proven to be effective in various applications. However, the learning scheme of SC is suboptimal in that it learns the cluster indicator from a fixed graph structure, which usually requires a rounding procedure to further partition the data. Also, the obtained cluster number cannot reflect the ground truth number of connected components in the graph. To alleviate these drawbacks, we propose a rank-constrained SC with flexible embedding framework. Specifically, an adaptive probabilistic neighborhood learning process is employed to recover the block-diagonal affinity matrix of an ideal graph. Meanwhile, a flexible embedding scheme is learned to unravel the intrinsic cluster structure in low-dimensional subspace, where the irrelevant information and noise in high-dimensional data have been effectively suppressed. The proposed method is superior to previous SC methods in that: 1) the block-diagonal affinity matrix learned simultaneously with the adaptive graph construction process, more explicitly induces the cluster membership without further discretization; 2) the number of clusters is guaranteed to converge to the ground truth via a rank constraint on the Laplacian matrix; and 3) the mismatch between the embedded feature and the projected feature allows more freedom for finding the proper cluster structure in the low-dimensional subspace as well as learning the corresponding projection matrix. Experimental results on both synthetic and real-world data sets demonstrate the promising performance of the proposed algorithm.
Li, Z, Nie, F, Chang, X, Yang, Y, Zhang, C & Sebe, N 2018, 'Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6323-6332.
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Spectral clustering (SC) has been widely applied to various computer vision tasks, where the key is to construct a robust affinity matrix for data partitioning. With the increase in visual features, conventional SC methods are facing two challenges: 1) how to effectively generate an affinity matrix based on multiple features? and 2) how to deal with high-dimensional visual features which could be redundant? To address these issues mentioned earlier, we present a new approach to: 1) learn a robust affinity matrix using multiple features, allowing us to simultaneously determine optimal weights for each feature; and 2) decide a set of optimal projection matrixes, one for each feature, that decide the lower dimensional space, as well as the optimal affinity weight of each data pair in the lower dimensional space. There are two major advantages of our new approach over the existing clustering techniques. First, our approach assigns affinity weights for data points on a per-data-pair basis. The learning procedure avoids the explicit specification of the size of the neighborhood in the affinity matrix, and the bandwidth parameter required to compute the Gaussian kernel, both of which are sensitive and yet difficult to determine beforehand. Second, the affinity weights are based on the distances in a lower dimensional space, while the low-dimensional space is inferred according to the optimized affinity weights. Both variables are jointly optimized so as to leverage mutual benefits. The experimental results outperform the compared alternatives, which indicate that the proposed method is effective in simultaneously learning the affinity graph and feature fusion, resulting in better clustering results.
Lian, D, Zheng, K, Ge, Y, Cao, L, Chen, E & Xie, X 2018, 'GeoMF++', ACM Transactions on Information Systems, vol. 36, no. 3, pp. 1-29.
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Location recommendation is an important means to help people discover attractive locations. However, extreme sparsity of user-location matrices leads to a severe challenge, so it is necessary to take implicit feedback characteristics of user mobility data into account and leverage the location’s spatial information. To this end, based on previously developed GeoMF, we propose a scalable and flexible framework, dubbed GeoMF++, for joint geographical modeling and implicit feedback-based matrix factorization. We then develop an efficient optimization algorithm for parameter learning, which scales linearly with data size and the total number of neighbor grids of all locations. GeoMF++ can be well explained from two perspectives. First, it subsumes two-dimensional kernel density estimation so that it captures spatial clustering phenomenon in user mobility data; Second, it is strongly connected with widely used neighbor additive models, graph Laplacian regularized models, and collective matrix factorization. Finally, we extensively evaluate GeoMF++ on two large-scale LBSN datasets. The experimental results show that GeoMF++ consistently outperforms the state-of-the-art and other competing baselines on both datasets in terms of NDCG and Recall. Besides, the efficiency studies show that GeoMF++ is much more scalable with the increase of data size and the dimension of latent space.
Liang, X & Wu, C 2018, 'Investigation on Thermal Conductivity of Steel Fiber Reinforced Concrete Using Mesoscale Modeling', International Journal of Thermophysics, vol. 39, no. 12.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. A mesoscale model was developed to investigate the effect of steel fiber on the thermal conductivity of steel fiber-reinforced concrete (SFRC). Delaunay triangulation was employed to generate the unstructured mesh for SFRC materials. The model was validated using the existing experimental data. Then, it was used to study how model thickness affected simulation outcomes of thermal conductivity of models with different fiber lengths, by which an appropriate thickness was determined for the later analyses. The validated and optimized model was applied to the study of relationships between thermal conductivity and factors such as fiber content, fiber aspect ratio and different parts of an SFRC block by conducting steady-state heat analyses with the finite element analysis software ANSYS. The simulation results reveal that adding steel fiber increases thermal conductivity considerably, while fiber aspect ratio only has an insignificant effect. Besides, the presence of steel fibers has an obvious impact on the distribution of temperature and heat flux vector of the SFRC blocks.
Liang, X & Wu, C 2018, 'Meso-scale modelling of steel fibre reinforced concrete with high strength', Construction and Building Materials, vol. 165, pp. 187-198.
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© 2018 Based on Delaunay triangulation, a 3D meso-scale model is successfully developed and verified. This approach modelling fibre and concrete separately and linking them with slide line contact has the capability to truly reflect the interfacial behaviour of fibre and mortar, and thus achieve high fidelity of numerical simulations. However, meso-scale modelling usually means tremendous complexity and long computational time. This paper proposes a model to achieve relatively high computation efficiency, as well as accuracy. Besides, the model has the potential to deal with small specimens cut from steel fibre reinforced concrete (SFRC) blocks.
Liang, X, Wu, C, Su, Y, Chen, Z & Li, Z 2018, 'Development of ultra-high performance concrete with high fire resistance', Construction and Building Materials, vol. 179, pp. 400-412.
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Liao, H, Xu, Z, Herrera, F & Merigó, JM 2018, 'Editorial Message: Special Issue on Hesitant Fuzzy Linguistic Decision Making: Algorithms, Theory and Applications', International Journal of Fuzzy Systems, vol. 20, no. 7, pp. 2083-2083.
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Liberal, I, Ederra, I & Ziolkowski, RW 2018, 'Quantum antenna arrays: The role of quantum interference on direction-de