A. Cancino, C, Nuñez, A & M. Merigó, J 2019, 'Influence of a seed capital program for supporting high growth firms in Chile', Contaduría y Administración, vol. 64, no. 1, pp. 65-65.
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<p>The main economic development agency in Chile, CORFO, implemented in 2001 a Seed Capital Program (SCP) to promote the development of high-growth firms. The SCP not only provides financial aid to entrepreneurs but also technical and administrative assistance through the support of incubators. Incubators may be universities incubators (UI) or private firms (NUI). The aim of this paper is to know the performance of beneficiaries according to the assistance of UI or NUI. A total of 238 new firms beneficiaries with the CORFO program were surveyed (84 supported by UI and 154 supported by NUI). Two logistic regression models were used, a first model to assess the probability that a new firm achieves positive sales, and a second model to assess the probability that the new firm reaches a high growth during the first five years from its inception. Overall, mixed results were found. SCP’s beneficiaries supported by either UI and NUI have the same probability of having positive sales when starting their operations. However, five years after started their operations, businesses supported by UI have higher probabilities of achieving high growth than businesses supported by NUI. The results highlight a positive interaction between private entrepreneurs, public agencies and university incubators.<strong></strong></p>
Abbasi, MH, Taki, M, Rajabi, A, Li, L & Zhang, J 2019, 'Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach', Applied Energy, vol. 239, pp. 1294-1307.
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© 2019 Elsevier Ltd As the number of electric vehicles (EVs) is steadily increasing, their aggregation can offer significant storage to improve the electric system operation in many aspects. To this end, a comprehensive stochastic optimization framework is proposed in this paper for the joint operation of a fleet of EVs with a wind power producer (WPP) in a three-settlement pool-based market. An aggregator procures enough energy for the EVs based on their daily driving patterns, and schedules the stored energy to counterbalance WPP fluctuations. Different sources of uncertainty including the market prices and WPP generation are modeled through proper scenarios, and the risk is hedged by adding a risk measure to the formulation. To obtain more accurate results, the battery degradation costs are also included in the problem formulation. A detailed case study is presented based on the Iberian electricity market data as well as the technical information of three different types of EVs. The proposed approach is benchmarked against the disjoint operation of EVs and WPP. Numerical simulations demonstrate that the proposed strategy can effectively benefit EV owners and WPP by reducing the energy costs and increasing the profits.
Abbasi, QH, Kiourti, A, Heidari, H, He, Y, Warkiani, M & Alomainy, A 2019, 'IEEE Access Special Section Editorial: Wearable and Implantable Devices and Systems', IEEE Access, vol. 7, pp. 139512-139517.
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© 2013 IEEE. Circuit techniques, sensors, antennas and communications systems are envisioned to help build new technologies over the next several years. Advances in the development and implementation of such technologies have already shown us their unique potential in realizing next-generation sensing systems. Applications include wearable consumer electronics, healthcare monitoring systems, and soft robotics, as well as wireless implants. There have been some interesting developments in the areas of circuits and systems, involving studies related to low-power electronics, wireless sensor networks, wearable circuit behaviour, security, real-time monitoring, connectivity of sensors, and Internet of Things (IoT). The direction for the current technology is electronics systems on large area electronics, integrated implantable systems and wearable sensors. So far, the research in the field has focused on materials, new processing techniques and one-off devices, such as diodes and transistors. However, current technology is not sufficient for future electronics to be useful in new applications; a great demand exists to scale up the research towards circuits and systems. Recent developments indicate that, in addition to fabrication technology, special attention should also be given to design, simulation and modeling of electronics, while keeping sensing system integration, power management, and sensors network under consideration.
Abdelkarim, A, Gaber, A, Youssef, A & Pradhan, B 2019, 'Flood Hazard Assessment of the Urban Area of Tabuk City, Kingdom of Saudi Arabia by Integrating Spatial-Based Hydrologic and Hydrodynamic Modeling', Sensors, vol. 19, no. 5, pp. 1024-1024.
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This study deals with the use of remote sensing (RS), geographic information systems (GISs), hydrologic modeling (water modeling system, WMS), and hydraulic modeling (Hydrologic Engineering Center River Analysis System, HEC-RAS) to evaluate the impact of flash flood hazards on the sustainable urban development of Tabuk City, Kingdom of Saudi Arabia (KSA). Determining the impact of flood hazards on the urban area and developing alternatives for protection and prevention measures were the main aims of this work. Tabuk City is exposed to frequent flash flooding due to its location along the outlets of five major wadis. These wadis frequently carry flash floods, seriously impacting the urban areas of the city. WMS and HEC-HMS models and RS data were used to determine the paths and morphological characteristics of the wadis, the hydrographic flow of different drainage basins, flow rates and volumes, and the expansion of agricultural and urban areas from 1998 to 2018. Finally, hydraulic modeling of the HEC-RAS program was applied to delineate the urban areas that could be inundated with floodwater. Ultimately, the most suitable remedial measures are proposed to protect the future sustainable urban development of Tabuk City from flood hazards. This approach is rarely used in the KSA. We propose a novel method that could help decision-makers and planners in determining inundated flood zones before planning future urban and agricultural development in the KSA.
Abdo, P, Huynh, BP, Irga, PJ & Torpy, FR 2019, 'Evaluation of air flow through an active green wall biofilter', Urban Forestry & Urban Greening, vol. 41, pp. 75-84.
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© 2019 Elsevier GmbH Green walls show promise as active bio-filters to improve indoor air quality by removing both gaseous and particulate air pollutants. The current work represents a detailed assessment of airflow through an active green wall module. Airflow distribution through the module, the effect of wetting the substrate, and the effect of introducing a cover to the module's open top face were investigated, with the aim to improve the module's design and achieve more appropriate and effective airflow. Four cases of both planted and unplanted modules under both dry and wet conditions are considered. This work's primary observation is that more air will pass through a typical green wall substrate, and hence become cleansed, when the substrate is saturated wet more than when it is dry. The increase was substantial at approximately 50% more with 14.9 ± 0.2 L/s total air flow rate passing through the wet planted module versus 10 ± 0.2 L/s when dry. Reducing the 15.5 ± 0.75% of airflow passing through the module's open top face was found to be essential to maximize the bio-filtration capacity. Adding a top cover to the module having six 10 mm holes for irrigation decreased the airflow through the top by 6 ± 0.75%, and directed it through the filter increasing the percentage of air flow passing through the front openings from 79 ± 4% to 85 ± 4%.
Abdollahi, A, Pradhan, B & Shukla, N 2019, 'Extraction of road features from UAV images using a novel level set segmentation approach', International Journal of Urban Sciences, vol. 23, no. 3, pp. 391-405.
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Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2019, 'Development of lag time and time of concentration for a tropical complex catchment under the influence of long-term land use/land cover (LULC) changes', Arabian Journal of Geosciences, vol. 12, no. 3.
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© 2019, Saudi Society for Geosciences. Lag time (t L ) and time of concentration (T c ) are essential time parameters used in hydrological flood-flow design methods for estimating peak discharge and flood hydrograph shape. They form the basis of a number of hydrological models used among the scientists. 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 water balance in the area. The most recent is that of December 2014 flood which lead to catastrophic loss of huge amount of properties worth millions of Malaysian ringgit. In view of this, the current research was conducted with the aim of developing (1) t L and T c based on 1984, 2002, and 2013 LULC conditions; (2) a relationship between t L and t L parameters; and (3) a relationship between t L and T c among different LULC conditions. Kelantan River basin was first delineated into four major catchments, viz., Galas, Pergau, Lebir, and Nenggiri, due to its large size (approximately 13,100 km 2 ). Soil map and LULC change maps corresponding to 1984, 2002, and 2013 were used for the calculation of CN values while NRCS lag equation was used for the estimation of t L and T c . The results showed that deforestation for logging activities and agricultural practices were the dominant LULC changes across the watershed. Low values of both t L and T c were obtained across the catchment which are typical for a tropical monsoon catchment characterized with high runoff and short peak discharge. Results of t L and T c in this study are not affected by LULC changes in the basin. Slope was observed to be highly correlated with t L . Correlation coefficient was used to determine the relationship between t L and t L factor, and hydraulic length and slope (L√S). The results showed high correlation in all the catchments from 1984 to 2013 except for Lebir catchment where a moder...
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2019, 'Long-term runoff dynamics assessment measured through land use/cover (LULC) changes in a tropical complex catchment', Environment Systems and Decisions, vol. 39, no. 1, pp. 16-33.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The estimation of excess rainfall is critically important in water resource management as it provides the basis for calculating flood peak discharge that results in surface runoff. Kelantan River basin in Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/cover (LULC) changes making the area consistently flood prone. The current study is therefore aimed to achieve the following goals: (1) to develop a curve number (CN) and runoff maps for 1984, 2002, and 2013 LULC conditions and (2) to determine runoff dynamics due to changes in LULC as well as to assess how the extent of LULC change will affect surface runoff generation. To achieve the aforementioned goals, land use maps corresponding to 1984, 2002, and 2014 LULC conditions were analyzed and prepared for the calculation of CN values using Soil Conservation Service (SCS-CN) method. CN and runoff maps corresponding to 1984, 2002, and 2013 LULC changes were successfully developed and the performance of the method was tested. The results indicated that forest was found to be the major land use type to have changed in all the LULC conditions across the watershed leading to intense runoff dynamics in the entire watershed. Higher runoff values were observed under 2013 LULC conditions across the watershed mainly due to intense deforestation relative to those of 1984 and 2002. The results of this study indicated that runoff generation is significantly affected by deforestation instead of changes in the rainfall pattern. The findings may be useful to water resource planners in controlling water loss for future planning.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2019, 'Prediction of spatial soil loss impacted by long-term land-use/land-cover change in a tropical watershed', Geoscience Frontiers, vol. 10, no. 2, pp. 389-403.
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© 2017 China University of Geosciences (Beijing) and Peking University. The devastating effect of soil erosion is one of the major sources of land degradation that affects human lives in many ways which occur mainly due to deforestation, poor agricultural practices, overgrazing, wildfire and urbanization. Soil erosion often leads to soil truncation, loss of fertility, slope instability, etc. which causes irreversible effects on the poorly renewable soil resource. In view of this, a study was conducted in Kelantan River basin to predict soil loss as influenced by long-term land use/land-cover (LULC) changes in the area. The study was conducted with the aim of predicting and assessing soil erosion as it is influenced by long-term LULC changes. The 13,100 km 2 watershed was delineated into four sub-catchments Galas, Pergau, Lebir and Nenggiri for precise result estimation and ease of execution. GIS-based Universal Soil Loss Equation (USLE) model was used to predict soil loss in this study. The model inputs used for the temporal and spatial calculation of soil erosion include rainfall erosivity factor, topographic factor, land cover and management factor as well as erodibility factor. The results showed that 67.54% of soil loss is located under low erosion potential (reversible soil loss) or 0-1 t ha -1 yr -1 soil loss in Galas, 59.17% in Pergau, 53.32% in Lebir and 56.76% in Nenggiri all under the 2013 LULC condition. Results from the correlation of soil erosion rates with LULC changes indicated that cleared land in all the four catchments and under all LULC conditions (1984-2013) appears to be the dominant with the highest erosion losses. Similarly, grassland and forest were also observed to regulate erosion rates in the area. This is because the vegetation cover provided by these LULC types protects the soil from direct impact of rain drops which invariably reduce soil loss to the barest minimum. Overall, it was concluded that the results have shown the significan...
Abidi, IH, Mendelson, N, Tran, TT, Tyagi, A, Zhuang, M, Weng, L, Özyilmaz, B, Aharonovich, I, Toth, M & Luo, Z 2019, 'Selective Defect Formation in Hexagonal Boron Nitride', Advanced Optical Materials, vol. 7, no. 13, pp. 1900397-1900397.
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© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Luminescent defects in hexagonal boron nitride (hBN) have emerged as promising single photon emitters (SPEs) due to their high brightness and robust operation at room temperature. The ability to create such emitters with well-defined optical properties is a cornerstone toward their integration into on-chip photonic architectures. Here, an effective approach is reported to fabricate hBN SPEs with desired emission properties in distinct spectral regions via the manipulation of boron diffusion through copper during atmospheric pressure chemical vapor deposition (CVD)—a process termed gettering. Using the gettering technique the resulting zero-phonon line is deterministically placed between the regions 550 and 600 nm or from 600 to 650 nm, paving the way for hBN SPEs with tailored emission properties. Additionally, rational control over the observed SPE density in the resulting films is demonstrated. The ability to control defect formation during hBN growth provides a cost effective means to improve the crystallinity of CVD hBN films, and lower defect density making it applicable to hBN growth for a wide-range of applications. The results are important to understand defect formation of quantum emitters in hBN and deploy them for scalable photonic technologies.
Abidi, S, Piccardi, M, Tsang, IW & Williams, M-A 2019, 'Well-M$^3$N: A Maximum-Margin Approach to Unsupervised Structured Prediction', IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 3, no. 6, pp. 427-439.
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Unsupervised structured prediction is of fundamental importance for the clustering and classification of unannotated structured data. To date, its most common approach still relies on the use of structural probabilistic models and the expectation-maximization (EM) algorithm. Conversely, structural maximum-margin approaches, despite their extensive success in supervised and semi-supervised classification, have not raised equivalent attention in the unsupervised case. For this reason, in this paper we propose a novel approach that extends the maximum-margin Markov networks (M3N) to an unsupervised training framework. The main contributions of our extension are new formulations for the feature map and loss function of M3N that decouple the labels from the measurements and support multiple ground-truth training. Experiments on two challenging segmentation datasets have achieved competitive accuracy and generalization compared to other unsupervised algorithms such as k-means, EM and unsupervised structural SVM, and comparable performance to a contemporary deep learning-based approach.
Abnisa, F, Anuar Sharuddin, SD, bin Zanil, MF, Wan Daud, WMA & Indra Mahlia, TM 2019, 'The Yield Prediction of Synthetic Fuel Production from Pyrolysis of Plastic Waste by Levenberg–Marquardt Approach in Feedforward Neural Networks Model', Polymers, vol. 11, no. 11, pp. 1853-1853.
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The conversion of plastic waste into fuel by pyrolysis has been recognized as a potential strategy for commercialization. The amount of plastic waste is basically different for each country which normally refers to non-recycled plastics data; consequently, the production target will also be different. This study attempted to build a model to predict fuel production from different non-recycled plastics data. The predictive model was developed via Levenberg-Marquardt approach in feed-forward neural networks model. The optimal number of hidden neurons was selected based on the lowest total of the mean square error. The proposed model was evaluated using the statistical analysis and graphical presentation for its accuracy and reliability. The results showed that the model was capable to predict product yields from pyrolysis of non-recycled plastics with high accuracy and the output values were strongly correlated with the values in literature.
Acosta, E, Smirnov, V, Szabo, PSB, Buckman, J & Bennett, NS 2019, 'Optimizing Thermoelectric Power Factor in p-Type Hydrogenated Nano-crystalline Silicon Thin Films by Varying Carrier Concentration', Journal of Electronic Materials, vol. 48, no. 4, pp. 2085-2094.
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© 2019, The Minerals, Metals & Materials Society. Most approaches to silicon-based thermoelectrics are focused on reducing the lattice thermal conductivity with minimal deterioration of the thermoelectric power factor. This study investigates the potential of p-type hydrogenated nano-crystalline silicon thin films (μc-Si:H), produced by plasma-enhanced chemical vapor deposition, for thermoelectric applications. We adopt this heterogeneous material structure, known to have a very low thermal conductivity (~ 1 W/m K), in order to obtain an optimized power factor through controlled variation of carrier concentration drawing on stepwise annealing. This approach achieves a best thermoelectric power factor of ~ 3 × 10 −4 W/mK 2 at a carrier concentration of ~ 4.5 × 10 19 cm 3 derived from a significant increase of electrical conductivity ~ × 8, alongside a less pronounced reduction of the Seebeck coefficient, while retaining a low thermal conductivity. These thin films have a good thermal and mechanical stability up to 500°C with appropriate adhesion at the film/substrate interface.
Acuna, P, Rojas, CA, Baidya, R, Aguilera, RP & Fletcher, JE 2019, 'On the Impact of Transients on Multistep Model Predictive Control for Medium-Voltage Drives', IEEE Transactions on Power Electronics, vol. 34, no. 9, pp. 8342-8355.
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© 1986-2012 IEEE. In medium-voltage drives, multistep model predictive control (MPC) can lower the total harmonic distortion of the stator currents and thereby reduce losses and improve efficiency. However, from the point of view of implementation, there is still uncertainty as to whether transients have a major adverse effect on achieving this improved steady-state performance. The time-varying nature of machine drives, initialization of the optimization process, and limited computational resources are identified as key factors. This paper analyzes the link between these key factors in detail, thus a suitable reformulation and selective initialization approach is designed to enable the deterministic use of multistep finite-control-set MPC irrespective of the drive system conditions. Guidelines to select the prediction horizon, weighting factor, and minimum switching frequency considering the control platform limitations are presented. The significant impacts of transients on the design and experimental validation, covering several drive conditions, are evaluated in a scaled-down three-level induction machine drive switching at 350 Hz. This paper is accompanied by a video demonstrating the real-Time implementation of multistep MPC.
Adak, C, Chaudhuri, BB, Lin, C-T & Blumenstein, M 2019, 'Intra-Variable Handwriting Inspection Reinforced with Idiosyncrasy Analysis', IEEE Transactions on Information Forensics and Security, 2020, vol. 15, pp. 3567-3579.
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In this paper, we work on intra-variable handwriting, where the writing
samples of an individual can vary significantly. Such within-writer variation
throws a challenge for automatic writer inspection, where the state-of-the-art
methods do not perform well. To deal with intra-variability, we analyze the
idiosyncrasy in individual handwriting. We identify/verify the writer from
highly idiosyncratic text-patches. Such patches are detected using a deep
recurrent reinforcement learning-based architecture. An idiosyncratic score is
assigned to every patch, which is predicted by employing deep regression
analysis. For writer identification, we propose a deep neural architecture,
which makes the final decision by the idiosyncratic score-induced weighted
average of patch-based decisions. For writer verification, we propose two
algorithms for patch-fed deep feature aggregation, which assist in
authentication using a triplet network. The experiments were performed on two
databases, where we obtained encouraging results.
Adanta, D, ., B, ., W, Quaranta, E & I. Mahlia, TM 2019, 'Investigation of the effect of gaps between the blades of open flume Pico hydro turbine runners', Journal of Mechanical Engineering and Sciences, vol. 13, no. 3, pp. 5493-5512.
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This study will analyze the impact of gap size in two different runners called runner A (five blades) and B (six blades) to provides recommendations in design and manufacture of open flume turbine runners so that maximize the conversion of kinetic and potential energy. There are three methods was used to investigate its: analytical method is used to design the turbine; experimental to determine the actual turbine performance; computational fluid dynamics (CFD) to study the physical phenomena and re-check the velocity triangle on the runner to validate the design and manufacturing process. Using the results obtained, gaps between the blades can alter the velocity vector on the outlet and unbalance the rotation of runner; this imbalance could cause cavitation. Then, the decreasing torque is assumed because water pressure in the draft tube is similar to atmospheric pressure. Two conditions must be satisfied to maximize the performance of the turbine: swirling flow is required after the water flows past the runner in order to minimize the radial velocity on the outlet so that the draft tube can function properly; the dimensions of the blade must be carefully selected to avoid the formation of gaps between the blades.
Adegbosin, AE, Plummer, D, Yau, M, Franklin, R, Cordier, R & Sun, J 2019, 'Larrikins? Wowsers? Hipsters? Snags? What does it mean to be a ‘real man’ in modern-day Australia?', Journal of Sociology, vol. 55, no. 3, pp. 551-570.
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Gender is constructed from social and cultural meanings that dynamically shift and vary. Previous work has assumed that the constructions of masculinity in Australia are like those in other Western societies, and typically focus on qualities such as physical strength, courage and sometimes military engagement. This study explores whether these assumptions hold, by conducting telephone interviews among 617 Queensland men, aged 18 years and above, across all geographical parts of Queensland. This survey was administered in 2013, as part of the Queensland Social Survey series. The study explores the diverse meanings associated with being a ‘real man’ given by the survey participants. Three main dimensions emerged from the thematic analysis: physicality; personality and character; social roles and relationships. The study confirmed that masculinities are dynamic and complex. Responses revealed a surprising emphasis on character and morality 44.5% (n = 684) as defining manhood, as against physical qualities 13.7% (n = 153).
Adegbosin, AE, Zhou, H, Wang, S, Stantic, B & Sun, J 2019, 'Systematic review and meta-analysis of the association between dimensions of inequality and a selection of indicators of Reproductive, Maternal, Newborn and Child Health (RMNCH)', Journal of Global Health, vol. 9, no. 1.
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Afshar, S, Hamilton, TJ, Tapson, J, van Schaik, A & Cohen, G 2019, 'Investigation of Event-Based Surfaces for High-Speed Detection, Unsupervised Feature Extraction, and Object Recognition', Frontiers in Neuroscience, vol. 12.
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Afzal, MK, Khan, WZ, Umer, T, Kim, B-S & Yu, S 2019, 'Editorial of cross-layer design issues, challenges and opportunities for future intelligent heterogeneous networks', Journal of Ambient Intelligence and Humanized Computing, vol. 10, no. 11, pp. 4207-4208.
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Agarwal, A, Dowsley, R, McKinney, ND, Wu, D, Lin, C-T, De Cock, M & Nascimento, ACA 2019, 'Protecting Privacy of Users in Brain-Computer Interface Applications', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 27, no. 8, pp. 1546-1555.
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Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data, a kind of data that is so rich with information that application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other intimate data. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. Hence, we propose cryptographic protocols based on secure multiparty computation (SMC) to perform linear regression over EEG signals from many users in a fully privacy-preserving (PP) fashion, i.e., such that each individual's EEG signals are not revealed to anyone else. To illustrate the potential of our secure framework, we show how it allows estimating the drowsiness of drivers from their EEG signals as would be possible in the unencrypted case, and at a very reasonable computational cost. Our solution is the first application of commodity-based SMC to EEG data, as well as the largest documented experiment of secret sharing-based SMC in general, namely, with 15 players involved in all the computations.
Ahmed II, JB & Pradhan, B 2019, 'Spatial assessment of termites interaction with groundwater potential conditioning parameters in Keffi, Nigeria', Journal of Hydrology, vol. 578, pp. 124012-124012.
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© 2019 Elsevier B.V. Termite mounds are traditionally presumed to be good indicators of groundwater in places they inhabit but this hypothesis is yet to be scientifically substantiated. To confirm this assertion, it is expected that termite mounds would have strong correlations with groundwater conditioning parameters (GCPs). In this study, termite mounds distribution covering an area of about 156 km2 were mapped and their structural characteristics documented with the aim of examining their relationships with twelve (12) chosen GCPs. Other specific objectives were to identify specific mound types with affinity to groundwater and to produce a groundwater potential map of the study area. To achieve this, 12 GCPs including geology, drainage density, lineament density, lineament intersection density, land use/land cover, topographic wetness index (TWI), normalized difference vegetation index (NDVI), slope, elevation, plan curvature, static water level and groundwater level fluctuation were extracted from relevant sources. Frequency ratio (FR) and Spearman's rank correlation were used to find relationships and direction of such relationships. The result revealed a consistent agreement between FR and Spearman's rank correlation that tall (≥1.8 m) and Cathedral designed mounds are good indicators of groundwater. Further, the groundwater potential map produced from the Random Forest (RF) model via Correlation-based Feature Selection (CFS) using best-first algorithm depicted an erratic nature of groundwater distribution in the study area. This was then classified using natural break into very-high, high, moderate, low and very low potential classes and area under curve (AUC) of the receiver operating characteristics (ROC) showed an 86.5% validity of the model. About 75% of mapped termite mounds fell within the very-high to moderate potential classes thereby suggesting that although tall and cathedral mounds in particular showed good correlations with a number of GCPs, hi...
Ahmed II, JB, Pradhan, B, Mansor, S, Yusoff, ZM & Ekpo, SA 2019, 'Aquifer Potential Assessment in Termites Manifested Locales Using Geo-Electrical and Surface Hydraulic Measurement Parameters', Sensors, vol. 19, no. 9, pp. 2107-2107.
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In some parts of tropical Africa, termite mound locations are traditionally used to site groundwater structures mainly in the form of hand-dug wells with high success rates. However, the scientific rationale behind the use of mounds as prospective sites for locating groundwater structures has not been thoroughly investigated. In this paper, locations and structural features of termite mounds were mapped with the aim of determining the aquifer potential beneath termite mounds and comparing the same with adjacent areas, 10 m away. Soil and species sampling, field surveys and laboratory analyses to obtain data on physical, hydraulic and geo-electrical parameters from termite mounds and adjacent control areas followed. The physical and hydraulic measurements demonstrated relatively higher infiltration rates and lower soil water content on mound soils compared with the surrounding areas. To assess the aquifer potential, vertical electrical soundings were conducted on 28 termite mounds sites and adjacent control areas. Three (3) important parameters were assessed to compute potential weights for each Vertical Electrical Sounding (VES) point: Depth to bedrock, aquifer layer resistivity and fresh/fractured bedrock resistivity. These weights were then compared between those of termite mound sites and those from control areas. The result revealed that about 43% of mound sites have greater aquifer potential compared to the surrounding areas, whereas 28.5% of mounds have equal and lower potentials compared with the surrounding areas. The study concludes that termite mounds locations are suitable spots for groundwater prospecting owing to the deeper regolith layer beneath them which suggests that termites either have the ability to locate places with a deeper weathering horizon or are themselves agents of biological weathering. Further studies to check how representative our study area is of other areas with similar termite activities are recommended.
Ahmed, AA & Pradhan, B 2019, 'Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system', Environmental Monitoring and Assessment, vol. 191, no. 3.
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This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.
Ahmed, MB, Hasan Johir, MA, Zhou, JL, Ngo, HH, Nghiem, LD, Richardson, C, Moni, MA & Bryant, MR 2019, 'Activated carbon preparation from biomass feedstock: Clean production and carbon dioxide adsorption', Journal of Cleaner Production, vol. 225, pp. 405-413.
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© 2019 Elsevier Ltd The current methods used for the production of activated carbon (AC) are often chemical and energy intensive and produce significant amount of chemical waste. Thus, clean production of AC is important to reduce its overall production cost and to limit the adverse effect on the environment. Therefore, the main aim of this study is to develop a clean method for AC production from woody biomass with low chemical consumption. Herein, this study reports a facile strategy for reducing chemical usages in the production of high-performance AC, by introducing a crucial pre-pyrolysis step before chemical activation of biomass. The ACs prepared were characterised using scanning electron microscopy, Fourier transform infrared spectroscopy, nitrogen and carbon dioxide gas adsorption measurements. All these characterisations indicated that produced ACs have similar physicochemical properties. The strategy reduced chemical use by 70% and produced high-performance ultra-microporous ACs with excellent carbon dioxide adsorption capacity (4.22–5.44 mmol m −2 ). The facile pre-pyrolysis method is recommended for further research as a cleaner activated carbon preparation method from biomass feedstock.
Ajibola, II, Mansor, S, Pradhan, B & Mohd. Shafri, HZ 2019, 'Fusion of UAV-based DEMs for vertical component accuracy improvement', Measurement, vol. 147, pp. 106795-106795.
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© 2019 Elsevier Ltd Most construction projects require data that comply with a certain standard of accuracy both in the horizontal and vertical components. This study aimed to develop a model for improving the quality of Digital Elevation Model (DEM) produced by UAV. UAV is the short form of Unmanned Aerial Vehicle, which is either fixed-wing or rotorcraft type. The study proposes a fusion approach that integrates a weighted averaging and additive median filtering algorithms to improve accuracy of the DEMs derived from fixed-wing UAVs. The low quality DEM was fused with high quality DEM produced by multi-rotor UAVs. Assessment of the DEM produced root mean square error of 1.14 cm and standard vertical accuracy of 2.24 cm at a 95% confidence level. This value represents a decrease in vertical standard error of 18.31 cm to 2.24 cm, which is an improvement of 88%. The result of the study indicates that the method is suitable for improving accuracy of DEM produced by UAVs.
Ajuyah, P, Hill, M, Ahadi, A, Lu, J, Hutvagner, G & Tran, N 2019, 'MicroRNA (miRNA)-to-miRNA Regulation of Programmed Cell Death 4 (PDCD4)', Molecular and Cellular Biology, vol. 39, no. 18, pp. 1-15.
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The regulation of tumor suppressor genes by microRNAs (miRNAs) is often demonstrated as a one-miRNA-to-one-target relationship. However, given the large number of miRNA sites within a 3′ untranslated region (UTR), most targets likely undergo miRNA cooperation or combinatorial action. Programmed cell death 4 (PDCD4), an important tumor suppressor, prevents neoplastic events and is commonly downregulated in cancer.
Akgun, B, Krunz, M & Koyluoglu, OO 2019, 'Vulnerabilities of Massive MIMO Systems to Pilot Contamination Attacks', IEEE Transactions on Information Forensics and Security, vol. 14, no. 5, pp. 1251-1263.
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© 2018 IEEE. We consider a single-cell massive multiple-input multiple-output (MIMO) system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination (PC) attacks. In our attack model, the attacker aims at minimizing the sum rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the achievable individual secrecy rates under PC attacks and provide an upper bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%.
Akhani, M, Kashani, AR, Mousavi, M & Gandomi, AH 2019, 'A hybrid computational intelligence approach to predict spectral acceleration', Measurement, vol. 138, pp. 578-589.
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Akther, N, Daer, S, Wei, Q, Janajreh, I & Hasan, SW 2019, 'Synthesis of polybenzimidazole (PBI) forward osmosis (FO) membrane and computational fluid dynamics (CFD) modeling of concentration gradient across membrane surface', Desalination, vol. 452, pp. 17-28.
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Akther, N, Lim, S, Tran, VH, Phuntsho, S, Yang, Y, Bae, T-H, Ghaffour, N & Shon, HK 2019, 'The effect of Schiff base network on the separation performance of thin film nanocomposite forward osmosis membranes', Separation and Purification Technology, vol. 217, pp. 284-293.
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© 2019 Elsevier B.V. In this study, Schiff base network-1 (SNW-1) nanoparticles, which are covalent organic frameworks (COFs), were used as fillers in the polyamide (PA) active layer to elevate the performance of thin-film nanocomposite (TFN) forward osmosis (FO) membranes. The TFN membranes were prepared by interfacial polymerization (IP) of m-phenylenediamine (MPD) and trimesoyl chloride (TMC), and the SNW-1 nanoparticles were dispersed in the MPD aqueous solution at various concentrations. The secondary amine groups of SNW-1 nanoparticles reacted with the acyl chloride groups of TMC during the IP reaction to form strong covalent/amide bonds, which facilitated better interface integration of SNW-1 nanoparticles in the PA layer. Additionally, the incorporation of amine-rich SNW-1 nanoparticles into the TFN membranes improved their surface hydrophilicity, and the porous structure of SNW-1 nanoparticles offered additional channels for transport of water molecules. The TFN0.005 membrane with a SNW-1 nanoparticle loading of 0.005 wt% demonstrated a higher water flux than that of pristine TFC membrane in both AL-FS (12.0 vs. 9.3 L m−2 h−1) and AL-DS (25.2 vs. 19.4 L m−2 h−1) orientations when they were tested with deionized water and 0.5 M NaCl as feed and draw solution, respectively.
Akther, N, Phuntsho, S, Chen, Y, Ghaffour, N & Shon, HK 2019, 'Recent advances in nanomaterial-modified polyamide thin-film composite membranes for forward osmosis processes', Journal of Membrane Science, vol. 584, pp. 20-45.
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Alaei, F, Alaei, A, Pal, U & Blumenstein, M 2019, 'A comparative study of different texture features for document image retrieval', Expert Systems with Applications, vol. 121, pp. 97-114.
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© 2018 Elsevier Ltd Due to the rapid increase of different digitised documents, there has been significant attention dedicated to document image retrieval over the past two decades. Finding discriminative and effective features is a fundamental task for providing a fast and more accurate retrieval system. Texture features are generally fast to compute and are suitable for large volume data. Thus, in this study, the effectiveness of texture features widely used in the literature of content-based image retrieval is investigated on document images. Twenty-six different texture feature extraction methods from four main categories of texture features, statistical, transform, model, and structural-based approaches, are considered in this research work to compare their performance on the problem of document image retrieval. Three document image datasets, MTDB, ITESOFT, and CLEF_IP with various content and page layouts are used to evaluate the twenty-six texture-based features on document image retrieval systems. The retrieval results are computed in terms of precision, recall and F-score, and a comparative analysis of the results is also provided. Feature dimensions and time complexity of the texture-based feature methods are further compared. Finally, some conclusions are drawn and suggestions are made about future research directions.
Alamdari, MM, Dang Khoa, NL, Wang, Y, Samali, B & Zhu, X 2019, 'A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge', Structural Health Monitoring, vol. 18, no. 1, pp. 35-48.
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A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated; damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold; first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation; second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification; and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities.
Al-Amin Hoque, M, Billah, MM & Pradhan, B 2019, 'Spatio-temporal and demographic distribution of lightning related casualties in northeastern part of Bangladesh', International Journal of Disaster Risk Reduction, vol. 38, pp. 101197-101197.
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© 2019 Lightning is one of the frequent catastrophic hazards to people and properties across the world. Bangladesh is one of the major lightning prone countries in the world. Information regarding the spatial, temporal and demographic distribution of lightning casualties is required to develop mitigation policies to minimize the impacts of lightning. This study aims to analyse the spatial, temporal and demographic distribution of lightning-related casualties in the northeastern part of Bangladesh from 2016 to 2018. The database of lightning casualties was developed from a variety of sources including government and private agencies. Records dating from 2016 to 2018 indicate that about 78 and 60 people have been killed and injured, respectively by lightning strikes. The highest number of lightning fatalities were reported in the districts of Kishoreganj (31%), Habiganj (18%) and Sunamganj (15%). The overall fatality rate is 1.76 per million people per year, and fatality density rate is 0.00388 per million people km−2 year−1. The majority of fatalities and injuries occurred within the early morning 0800 and early evening 1700 at local time. The number of fatalities was higher in April–May during the pre-monsoon season. The maximum number of people died by lightning during farming activities, followed by fishing, boating or bathing in water bodies. The findings of the study are highly beneficial to the administrator and policymakers to develop lightning mitigation plans, improve public awareness and lightning safety campaign to reduce the impacts of lightning hazards.
Alazigha, DP, Vinod, JS, Indraratna, B & Heitor, A 2019, 'Potential use of lignosulfonate for expansive soil stabilisation', Environmental Geotechnics, vol. 6, no. 7, pp. 480-488.
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This study involved the laboratory evaluation of the effectiveness of lignosulfonate (LS) admixture in improving engineering properties (i.e. swell potential, unconfined compressive strength, durability, compaction characteristics, permeability, consolidation characteristics and shrinkage behaviour) of a remoulded expansive soil. Standard geotechnical laboratory tests performed on untreated and LS-treated soil specimens compacted at optimum moisture content and maximum dry unit weight showed significant and consistent improvements in the engineering properties of the soil. The swell potential of the soil decreased by 23% while maintaining its ductility and pH value. The improved soil resistance to repeated freeze–thaw/wet–dry cycles was also observed in the LS-treated specimens. Likewise, the compressive strength, consolidation characteristics and shrinkage limit improved appreciably. However, the compaction characteristics and permeability of the treated soil remained relatively unchanged. With over 50 Mt of global annual production of LS, the successful use of LS as an alternative admixture for expansive soil stabilisation provides viable solutions to the sustainable use of the lignin by-products from paper manufacturing industry.
Alderighi, T, Malomo, L, Giorgi, D, Bickel, B, Cignoni, P & Pietroni, N 2019, 'Volume-aware design of composite molds.', ACM Trans. Graph., vol. 38, no. 4, pp. 110:1-110:1.
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© 2019 Association for Computing Machinery. We propose a novel technique for the automatic design of molds to cast highly complex shapes. The technique generates composite, two-piece molds. Each mold piece is made up of a hard plastic shell and a flexible silicone part. Thanks to the thin, soft, and smartly shaped silicone part, which is kept in place by a hard plastic shell, we can cast objects of unprecedented complexity. An innovative algorithm based on a volumetric analysis defines the layout of the internal cuts in the silicone mold part. Our approach can robustly handle thin protruding features and intertwined topologies that have caused previous methods to fail. We compare our results with state of the art techniques, and we demonstrate the casting of shapes with extremely complex geometry.
Alfaro-García, VG, Merigó, JM, Plata-Pérez, L, Alfaro-Calderón, GG & Gil-Lafuente, AM 2019, 'INDUCED AND LOGARITHMIC DISTANCES WITH MULTI-REGION AGGREGATION OPERATORS', Technological and Economic Development of Economy, vol. 0, no. 0, pp. 1-29.
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This paper introduces the induced ordered weighted logarithmic averaging IOWLAD and multiregion induced ordered weighted logarithmic averaging MR-IOWLAD operators. The distinctive characteristic of these operators lies in the notion of distance measures combined with the complex reordering mechanism of inducing variables and the properties of the logarithmic averaging operators. The main advantage of MR-IOWLAD operators is their design, which is specifically thought to aid in decision-making when a set of diverse regions with different properties must be considered. Moreover, the induced weighting vector and the distance measure mechanisms of the operator allow for the wider modeling of problems, including heterogeneous information and the complex attitudinal character of experts, when aiming for an ideal scenario. Along with analyzing the main properties of the IOWLAD operators, their families and specific cases, we also introduce some extensions, such as the induced generalized ordered weighted averaging IGOWLAD operator and Choquet integrals. We present the induced Choquet logarithmic distance averaging ICLD operator and the generalized induced Choquet logarithmic distance averaging IGCLD operator. Finally, an illustrative example is proposed, including real-world information retrieved from the United Nations World Statistics for global regions.
Alharbi, SK, Nghiem, LD, van de Merwe, JP, Leusch, FDL, Asif, MB, Hai, FI & Price, WE 2019, 'Degradation of diclofenac, trimethoprim, carbamazepine, and sulfamethoxazole by laccase from Trametes versicolor: Transformation products and toxicity of treated effluent', Biocatalysis and Biotransformation, vol. 37, no. 6, pp. 399-408.
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Ali, SM, Qamar, A, Kerdi, S, Phuntsho, S, Vrouwenvelder, JS, Ghaffour, N & Shon, HK 2019, 'Energy efficient 3D printed column type feed spacer for membrane filtration', Water Research, vol. 164, pp. 114961-114961.
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Modification of the feed spacer design significantly influences the energy consumption of membrane filtration processes. This study developed a novel column type feed spacer with the aim to reduce the specific energy consumption (SEC) of the membrane based water filtration system. The proposed spacer increases the clearance between the filament and the membrane (reducing the spacer filament diameter) while keeping the same flow channel thickness as compared to a standard non-woven symmetric spacer. Since the higher clearance reduces the flow unsteadiness, column type nodes were added in the spacer structure as additional vortex shading bodies. Fluid flow behaviour in the channel for this spacer was numerically simulated by 3D CFD studies and then compared with the standard spacer. The numerical results showed that the proposed spacer substantially reduced the pressure drop, shear stress at the constriction region and shortened the dead zone. Finally, these findings were confirmed experimentally by investigating the filtration performances using the 3D printed prototypes of these spacers in a lab-scale filtration module. It is observed that the column spacer reduced the pressure drop by three times and doubled the specific water flux. 2D OCT (Optical Coherence Tomography) scans of the membrane surface acquired after the filtration revealed much lower biomass accumulation using the proposed spacer. Consequently, the SEC for the column spacer was found about two folds lower than the standard spacer.
Alilou, H, Rahmati, O, Singh, VP, Choubin, B, Pradhan, B, Keesstra, S, Ghiasi, SS & Sadeghi, SH 2019, 'Evaluation of watershed health using Fuzzy-ANP approach considering geo-environmental and topo-hydrological criteria', Journal of Environmental Management, vol. 232, pp. 22-36.
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Assessment of watershed health and prioritization of sub-watersheds are needed to allocate natural resources and efficiently manage watersheds. Characterization of health and spatial prioritization of sub-watersheds in data scarce regions helps better comprehend real watershed conditions and design and implement management strategies. Previous studies on the assessment of health and prioritization of sub-watersheds in ungauged regions have not considered environmental factors and their inter-relationship. In this regard, fuzzy logic theory can be employed to improve the assessment of watershed health. The present study considered a combination of climate vulnerability (Climate Water Balance), relative erosion rate of surficial rocks, slope weighted K-factor, topographic indices, thirteen morphometric characteristics (linear, areal, and relief aspects), and potential non-point source pollution to assess watershed health, using a new framework which considers the complex linkage between human activities and natural resources. The new framework, focusing on watershed health score (WHS), was employed for the spatial prioritization of 31 sub-watersheds in the Khoy watershed, West Azerbaijan Province, Iran. In this framework, an analytical network process (ANP) and fuzzy theory were used to investigate the inter-relationships between the above mentioned geo-environmental factors and to classify and rank the health of each sub-watershed in four classes. Results demonstrated that only one sub-watershed (C15) fell into the class that was defined as 'a potentially critical zone'. This article provides a new framework and practical recommendations for watershed management agencies with a high level of assurance when there is a lack of reliable hydrometric gauge data.
Aliyu, A, El-Sayed, H, Abdullah, AH, Alam, I, Li, J & Prasad, M 2019, 'Video Streaming in Urban Vehicular Environments: Junction-Aware Multipath Approach', Electronics, vol. 8, no. 11, pp. 1239-1239.
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In multipath video streaming transmission, the selection of the best vehicle for video packet forwarding considering the junction area is a challenging task due to the several diversions in the junction area. The vehicles in the junction area change direction based on the different diversions, which lead to video packet drop. In the existing works, the explicit consideration of different positions in the junction areas has not been considered for forwarding vehicle selection. To address the aforementioned challenges, a Junction-Aware vehicle selection for Multipath Video Streaming (JA-MVS) scheme has been proposed. The JA-MVS scheme considers three different cases in the junction area including the vehicle after the junction, before the junction and inside the junction area, with an evaluation of the vehicle signal strength based on the signal to interference plus noise ratio (SINR), which is based on the multipath data forwarding concept using greedy-based geographic routing. The performance of the proposed scheme is evaluated based on the Packet Loss Ratio (PLR), Structural Similarity Index (SSIM) and End-to-End Delay (E2ED) metrics. The JA-MVS is compared against two baseline schemes, Junction-Based Multipath Source Routing (JMSR) and the Adaptive Multipath geographic routing for Video Transmission (AMVT), in urban Vehicular Ad-Hoc Networks (VANETs).
Alkalbani, AM, Hussain, W & Kim, JY 2019, 'A Centralised Cloud Services Repository (CCSR) Framework for Optimal Cloud Service Advertisement Discovery From Heterogenous Web Portals', IEEE Access, vol. 7, pp. 128213-128223.
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Almabrok, M, McLaughlan, R & Vessalas, K 2019, 'Investigation of the Influence of Light Crude Oil on the Performance of Cement Mortar', International Journal of Civil Engineering, vol. 6, no. 4, pp. 34-40.
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Almabrok, MH, McLaughlan, R, Vessalas, K & Thomas, P 2019, 'Effect of oil contaminated aggregates on cement hydration', American Journal of Engineering Research (AJER), vol. 8, no. 5, pp. 81-89.
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Canola oil, refined mineral oil, and crude oil additions up to 10% of the aggregate mass in
Portland cement mortars were found to decrease the 28-day compressive strength by 71%, 75% and 50%,
respectively, and retard setting times. There was a progressive impact upon cement hydration as the oil content
increased in mortars. Only in the case of vegetable oil and refined mineral oil could strength loss be attributed
in part to cement hydration inhibition, as evidenced by reduced total evolved heat. It is likely that
microstructural effects were also a key factor in strength loss for all mortars particularly for those containing
crude oil.
Al-Muhsen, NFO, Huang, Y & Hong, G 2019, 'Effects of direct injection timing associated with spark timing on a small spark ignition engine equipped with ethanol dual-injection', Fuel, vol. 239, pp. 852-861.
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© 2018 Elsevier Ltd Dual injection of ethanol fuel (DualEI) has been in development. DualEI has the potential in increasing the compression ratio and thermal efficiency of spark ignition engines by taking the advantages of ethanol fuel properties and the direct injection. This paper reports an experimental investigation of the effect of direct injection (DI) timing associated with spark timing on the performance of a small DualEI engine. Experiments were conducted with fixed port injection timing and varied DI timing before (early) and after (late) the intake valve closed at 3500 RPM and two load conditions. Results show that the engine performance is enhanced by early DI timing, although the variation of IMEP and indicated thermal efficiency with DI timing is not significant either with early DI timing or in most of the tested conditions with late DI timing. Only in the medium load condition when the DI timing is retarded from 80 to 60 CAD bTDC, the IMEP and thermal efficiency significantly reduced by about 16% due to the increased initial combustion duration, resulting in reduced flame speed and increased combustion instability. The results also show different effects of early and late DI timing associated with the spark timing on engine emissions. With late DI timing, the engine emissions of CO and NO increase with the advance of late DI timing and spark timing. With early DI timing, the engine emissions increase with the advance of spark timing. However, the variation of engine emissions with early DI timing is more complicated than that late.
Al-Najjar, HAH, Kalantar, B, Pradhan, B, Saeidi, V, Halin, AA, Ueda, N & Mansor, S 2019, 'Land Cover Classification from fused DSM and UAV Images Using Convolutional Neural Networks', Remote Sensing, vol. 11, no. 12, pp. 1461-1461.
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In recent years, remote sensing researchers have investigated the use of different modalities (or combinations of modalities) for classification tasks. Such modalities can be extracted via a diverse range of sensors and images. Currently, there are no (or only a few) studies that have been done to increase the land cover classification accuracy via unmanned aerial vehicle (UAV)–digital surface model (DSM) fused datasets. Therefore, this study looks at improving the accuracy of these datasets by exploiting convolutional neural networks (CNNs). In this work, we focus on the fusion of DSM and UAV images for land use/land cover mapping via classification into seven classes: bare land, buildings, dense vegetation/trees, grassland, paved roads, shadows, and water bodies. Specifically, we investigated the effectiveness of the two datasets with the aim of inspecting whether the fused DSM yields remarkable outcomes for land cover classification. The datasets were: (i) only orthomosaic image data (Red, Green and Blue channel data), and (ii) a fusion of the orthomosaic image and DSM data, where the final classification was performed using a CNN. CNN, as a classification method, is promising due to hierarchical learning structure, regulating and weight sharing with respect to training data, generalization, optimization and parameters reduction, automatic feature extraction and robust discrimination ability with high performance. The experimental results show that a CNN trained on the fused dataset obtains better results with Kappa index of ~0.98, an average accuracy of 0.97 and final overall accuracy of 0.98. Comparing accuracies between the CNN with DSM result and the CNN without DSM result for the overall accuracy, average accuracy and Kappa index revealed an improvement of 1.2%, 1.8% and 1.5%, respectively. Accordingly, adding the heights of features such as buildings and trees improved the differentiation between vegetation specifically where plants were dense.
Alshehri, MD & Hussain, FK 2019, 'A fuzzy security protocol for trust management in the internet of things (Fuzzy-IoT)', Computing, vol. 101, no. 7, pp. 791-818.
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© 2018, Springer-Verlag GmbH Austria, ein Teil von Springer Nature. Recently, the Internet of things (IoT) has received a lot of attention from both industry and academia. A reliable and secure IoT connection and communication is essential for the proper working of the IoT network as a whole. One of the ways to achieve robust security in an IoT network is to enable and build trusted communication among the things (nodes). In this area, the existing IoT literature faces many critical issues, such as the lack of intelligent cluster-based trust approaches for IoT networks and the detection of attacks on the IoT trust system from malicious nodes, such as bad service providers. The existing literature either does not address these issues or only addresses them partially. Our proposed solution can firstly detect on-off attacks using the proposed fuzzy-logic based approach, and it can detect contradictory behaviour attacks and other malicious nodes. Secondly, we develop a fuzzy logic-based approach to detect malicious nodes involved in bad service provisioning. Finally, to maintain the security of the IoT network, we develop a secure messaging system that enables secure communication between nodes. This messaging system uses hexadecimal values with a structure similar to serial communication. We carried out extensive experimentation under varying network sizes to validate the working of our proposed solution and also to test the efficiency of the proposed methods in relation to various types of malicious behavior. The experiment results demonstrate the effectiveness of our approach under various conditions.
Al‐Soeidat, M, Cheng, T, Lu, DD & Agelidis, VG 2019, 'Experimental study of static and dynamic behaviours of cracked PV panels', IET Renewable Power Generation, vol. 13, no. 16, pp. 3002-3008.
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Al-Soeidat, M, Lu, DD-C & Zhu, J 2019, 'An Analog BJT-Tuned Maximum Power Point Tracking Technique for PV Systems', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 4, pp. 637-641.
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IEEE In this paper, an analog, BJT-tuned voltage reference maximum power point tracking (MPPT) method for photovoltaic (PV) modules is proposed. Conventional fixed voltage reference method is the simplest method for tracking, but it does not obtain good MPPT efficiency because the maximum power point (MPP) voltage changes at different insolation levels. In reality, an approximately linear slope is formed when connecting the MPPs measured from the highest insolation level to the lowest. Utilizing this characteristic, a bipolar junction transistor (BJT), which has a similar electrical property, is used to implement a variable voltage reference that improves the accuracy of the MPP voltage when the insolation changes. The proposed circuit is simple, easy to implement and it can track the maximum power point very quickly without the need for a digital controller or PID controller. Hence, the circuit’s cost and complexity are reduced. Experimental results are given to verify the feasibility of the proposed MPPT method.
Altaee, A & Cipolina, A 2019, 'Modelling and optimization of modular system for power generation from a salinity gradient', Renewable Energy, vol. 141, pp. 139-147.
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Altaee, A, Braytee, A, Millar, GJ & Naji, O 2019, 'Energy efficiency of hollow fibre membrane module in the forward osmosis seawater desalination process', Journal of Membrane Science, vol. 587, pp. 117165-117165.
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Altaee, A, Zhou, J, Zaragoza, G & Sharif, AO 2019, 'Impact of membrane orientation on the energy efficiency of dual stage pressure retarded osmosis', Journal of Water Process Engineering, vol. 30, pp. 100621-100621.
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The performance of Dual Stage Pressure Retarded Osmosis (DSPRO) was analyzed using a developed computer model. DSPRO process was evaluated on Pressure Retarded Osmosis (PRO) and Forward Osmosis (FO) operating modes for different sodium chloride (NaCl) draw and feed concentrations. Simulation results revealed that the total power generation in the DSPRO process operating on the PRO mode was 2.5–5 times more than that operating on the FO mode. For DSPRO operating on the PRO mode, the higher power generation was in the case of 2 M NaCl-fresh and 32% the contribution of the second stage to the total power generation in the DSPRO. To the contrast, he total power generated in the DSPRO operating on the FO mode was in the following order 5M-0.6M > 5M-0.7M > 2M-0.01 > 2M-0.6 M. Interestingly, single stage process operating on the FO mode performed better than DSPRO process due to the severe concentration polarization effects. The results also showed that power density of the DSPRO reached a maximum amount at a hydraulic pressure less than the average osmotic pressure gradient, Δπ/2, due to the variation of optimum operating pressure of each stage. Moreover, results showed that the effective specific energy in the PRO process was lower than the maximum specific energy. However, the effective specific energy of the DSPRO was larger than that of the single stage PRO due to the rejuvenation of the salinity gradient, emphasizing the high potential of the DSPRO process for power generation.
Alterman, D, Stewart, MG & Netherton, MD 2019, 'Probabilistic assessment of airblast variability and fatality risk estimation for explosive blasts in confined building spaces', International Journal of Protective Structures, vol. 10, no. 3, pp. 306-329.
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Explosive blasts in confined building spaces, such as lobbies or foyers, can amplify blast loads. This article uses the computational fluid dynamics model ProsAir to estimate blast loads in a typical ground floor lobby of a commercial or government building. Monte-Carlo simulation is used to probabilistically model the effect that variability and uncertainty of charge mass and location, net equivalent quantity factor, temperature, atmospheric pressure and model errors have on airblast variability. The analysis then calculates the probability of casualties due to the effects of pressure and impulse, where human vulnerability due to the effects of pressure and impulse is a function of lung rupture, whole-body displacement or skull fracture (or the combination of the three). The terrorist threats considered are improvised explosive devices ranging in mass from 5 kg (backpack bomb) to 23 kg (suitcase bomb) detonated in various locations inside the building. As expected, blast pressure and fatality risks are dependent on the type of facade glazing (e.g. vulnerable glazing allows venting of the blast), improvised explosive device size and location. It was found that the mean fatality risk for a 23 kg terrorist improvised explosive device is 8.6%, but there is a 5% chance that fatality risks can exceed 20%. It was also found that a probabilistic analysis yielded lower mean fatality risks than a deterministic analysis. The effect of venting was also significant. Mean fatality risks increased by up to 10-fold if there was no venting (i.e. a bunker-like structure without windows), but reduced by about 30% for a fully vented structure (i.e. no windows). This probabilistic analysis allows decision-makers to be more aware of terrorism risks to building occupants, and how improved building design and security measures may ameliorate these risks.
Alturki, R & Gay, V 2019, 'The Development of an Arabic Weight-Loss App Akser Waznk: Qualitative Results', JMIR Formative Research, vol. 3, no. 1, pp. e11785-e11785.
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Al-Zubaydi, AYT & Hong, G 2019, 'Experimental study of a novel water-spraying configuration in indirect evaporative cooling', Applied Thermal Engineering, vol. 151, pp. 283-293.
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© 2019 Elsevier Ltd Indirect evaporative cooler (IEC) is a clean cooling device in development for air conditioning systems. It uses the water to partially replace the refrigerant and can be applied as a standalone cooling system or an energy recovery ventilation system. Driven by the concern about the sustainability, IEC has been required to reduce the power to operate and increase its capacity in order to reduce the energy consumption and increase the overall efficiency of the air condition system. The water distribution over the plate walls in the cooler is a key factor affecting the IEC performance and efficiency. This study investigates the effect of a novel suggested water spray configuration on the performance of a ventilation energy recovery IEC. Experiments were conducted to investigate three water spray modes: external spray, internal spray and mixed internal and external sprays. The results show that the mixed mode performs best and internal spraying mode performs better than the external spraying mode does in terms of the wet-bulb efficiency, cooling capacity and the COP of IEC. The mixed mode improves the performance further by increasing wettability.
Amirbagheri, K, Núñez-Carballosa, A, Guitart-Tarrés, L & Merigó, JM 2019, 'Research on green supply chain: a bibliometric analysis', Clean Technologies and Environmental Policy, vol. 21, no. 1, pp. 3-22.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Abstract: Recently, the emergent concept of green supply chain has received increasing attention. Although popular among scholars, many literature reviews have only examined GSC from a general point of view or focused on a specific issue related to GSC. This study presents a comprehensive analysis of the influence and productivity of research on GSC from 1995 to 2017 by reporting trends among authors, countries and institutions based on a bibliometric approach. To this end, the study analyzes around 1900 papers on GSC. This study uses the Web of Science Core Collection database to analyze the bibliometric data and the visualization of similarities viewer method to graphically map those data. The graphical analysis uses bibliographic coupling, co-citation, co-authorship and co-occurrence of keywords. Graphical abstract: [Figure not available: see fulltext.].
Amiri, M, Tofigh, F, Shariati, N, Lipman, J & Abolhasan, M 2019, 'Miniature tri‐wideband Sierpinski–Minkowski fractals metamaterial perfect absorber', IET Microwaves, Antennas & Propagation, vol. 13, no. 7, pp. 991-996.
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© The Institution of Engineering and Technology 2019. With rapidly growing adoption of wireless technologies, requirements for the design of a miniature wideband multiresonators are increasing. In this study, a compact fractal-based metamaterial structure with lumped resistors is described. The structure of the authors proposed absorber is a combination of Sierpinski curve and Minkowski fractal. The new combination provides larger capacitance and inductance in the system enabling perfect absorption at lower frequencies. The final structure with dimensions of 20 × 20 × 1.6 mm3 and an air gap of 12.5 mm provides three main resonances at frequencies of 2.1, 5.1, and 12.8 GHz with bandwidth (absorption ratio over 90%) of 840 MHz, 1.05 GHz, and 910 MHz, respectively.
Amjadipour, M, MacLeod, J, Lipton-Duffin, J, Tadich, A, Boeckl, JJ, Iacopi, F & Motta, N 2019, 'Electron effective attenuation length in epitaxial graphene on SiC', Nanotechnology, vol. 30, no. 2, pp. 025704-025704.
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The inelastic mean free path (IMFP) for carbon-based materials is notoriously challenging to model, and moving from bulk materials to 2D materials may exacerbate this problem, making the accurate measurements of IMFP in 2D carbon materials critical. The overlayer-film method is a common experimental method to estimate IMFP by measuring electron effective attenuation length (EAL). This estimation relies on an assumption that elastic scattering effects are negligible. We report here an experimental measurement of electron EAL in epitaxial graphene on SiC using photoelectron spectroscopy over an electron kinetic energy range of 50-1150 eV. We find a significant effect of the interface between the 2D carbon material and the substrate, indicating that the attenuation length in the so-called 'buffer layer' is smaller than for free-standing graphene. Our results also suggest that the existing models for estimating IMFPs may not adequately capture the physics of electron interactions in 2D materials.
An, L, Cheng, T & Lu, DD-C 2019, 'Single-Stage Boost-Integrated Full-Bridge Converter With Simultaneous MPPT, Wide DC Motor Speed Range, and Current Ripple Reduction', IEEE Transactions on Industrial Electronics, vol. 66, no. 9, pp. 6968-6978.
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IEEE This paper presents a new approach to controlling and optimizing single-stage boost-integrated full-bridge DC/DC converter for a stand-alone PV-battery powered DC motor system by combining pulse frequency modulation (PFM), pulse width modulation (PWM) and phase angle shift (PAS). Unlike most existing multiport DC/DC converters which aim at regulating the output voltage (first- or second-quadrant operation), the DC motor load requires both voltage and current reversals (four-quadrant operation). The converter is able to perform three tasks simultaneously, namely, maximum power point tracking (MPPT), battery charging/discharging and driving the DC motor at variable speeds including bi-directional and stall motions. To achieve these control objectives, the boost inductor and motor inductance operate in different modes such that pulse-frequency modulation (PFM) and pulse-width modulation (PWM) can be used to achieve MPPT and wide motor voltage range respectively. By properly adjusting the phase angle shift (PAS) of the duty cycles, the capacitor and battery RMS current value can be reduced while the operation of the converter remains unchanged, hence improving the conversion efficiency. Experimental results of a 26W laboratory prototype converter confirmed the proposed design and operation, and efficiency improvement by 2-6%.
Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 2019, 'Smart pothole detection system using vehicle-mounted sensors and machine learning', Journal of Civil Structural Health Monitoring, vol. 9, no. 1, pp. 91-102.
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Andrade-Valbuena, NA, Merigó-Lindahl, JM, Fernández, LV & Nicolas, C 2019, 'Mapping leading universities in strategy research: Three decades of collaborative networks', Cogent Business & Management, vol. 6, no. 1, pp. 1632569-1632569.
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© 2019, © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. This paper presents a longitudinal classification of the impact that universities have on strategy research from three decades of publications, between 1987 and 2016, by using bibliometric techniques and distance-based analysis of networks applied at the level of universities. Using the WoS database, this study proposes a general overview of three decades of strategic management research. Using these techniques we (i) categorize the last 30 years of academic production of research institutions in terms of strategy, evaluating their impact; (ii) analyze which universities are publishing the most in journals whose scope of publication covers strategic management; and (iii) map the network of collaboration structures among research organizations, determining its relationship and analyzing its evolution in those three decades. We found that the University of Pennsylvania was the most prominent institution throughout the years, showing the broadest network of citations according to our network analysis. There was also a remarkable presence of international universities from the UK, Canada, France and the Netherlands, however, the citation pattern among them is still low. We also observed evidence of inner knowledge flowing among different fields based on the deliberate multidisciplinary nature of research in strategy, as the strong coincidence with the ranking of the main journals in the marketing field when comparing the bibliometric studies of both fields. This analysis contributes to strategy research, first by delivering insights based on the impact of academic production and secondly through the evolution of collaborative network linkages in terms of strategy investigations undertaken to build collective knowledge.
Anis, Z, Wissem, G, Riheb, H, Biswajeet, P & Mohamed Essghaier, G 2019, 'Effects of clay properties in the landslides genesis in flysch massif: Case study of Aïn Draham, North Western Tunisia', Journal of African Earth Sciences, vol. 151, pp. 146-152.
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© 2018 Elsevier Ltd Heavy rainfall in Aïn Draham province in the North-Western of Tunisia lead to the formation of some landslides which could poses danger to lives and properties. The geological outcrops of the region mainly consist of Numidian flysch rocks. In this study, field based 15 undisturbed samples were taken, from 11 boreholes drilled in 4 landslide points, to understand the real behaviour of soils when landslides occur. For this purpose, the geotechnical characterization of all samples was carried out. The grain size distribution shows that the clay and silt fractions prevail. The clay fraction ranges between 4% and 64% with an average of 40.4%, the silt fraction ranging from 19% to 71% averaging 39.8% and the sand fraction was between 6% and 44% with an average of 19.8%. The Casagrande plasticity chart indicates that 33.3% of samples were in the high plasticity group (CH group) and 66.6% having a medium to low plasticity. The water content varies between 12% and 31%. The direct shear strength test shows that the cohesions values range from 41 KPa to 77 KPa and the internal friction angle values range widely from 12° to 27°. A statistical approach was taken to determine the most important factors responsible for the decrease of the cohesion and friction angle which are in charge of slope failure. For this, a correlation matrix of all soil properties was done. The coefficients of correlation show that the clay fraction is the most correlated parameter to the cohesion with an index of −0.872. Unfortunately, the internal friction angle is very low correlated to all geotechnical parameters. The clay fraction, as the most correlated to the cohesion, and the water content, which depends on rainfall (landslide triggering factor), were considered as two independent parameters for the establishment of a multiple linear and non-linear regression models of the cohesion. The multiple linear model showed that the cohesion decrease with the increase of water conten...
Ansari, M, Zhu, H, Shariati, N & Guo, YJ 2019, 'Compact Planar Beamforming Array With Endfire Radiating Elements for 5G Applications', IEEE Transactions on Antennas and Propagation, vol. 67, no. 11, pp. 6859-6869.
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In this paper, a compact 4×6 Butler matrix (BM) based on microstrip lines is designed and applied to a linear antenna array. The proposed design creates four beams in four different directions within the 27.5 and 28.5 GHz band. One of the advantages of this BM is a reduction in the size of the beamforming network (BFN). In order to attain this objective, the basic microstrip-based 4×4 BM is designed, and then modified to a 4×6 BM through a dual-substrate structure to avoid crossing lines using microstrip-to-slotline transitions. The BFN is cascaded with a six-element linear antenna array with endfire radiating elements. The array can be conveniently integrated into the BFN. The resulting design benefits from low-loss characteristics, ease of realization, and low fabrication cost. The array is fabricated and tested, and the experimental results are in good agreement with the simulated ones. The multi-beam antenna size is 5.6 λ × 4.6 λ including feed lines and feed network, while the new BM design is only 3.5λ0 × 1.4λ0 , which is almost half as large as the traditional one. The measured radiation patterns show that the beams cover roughly a spatial range of 90° with a peak active gain of 11 dBi.
Anshu, A, Berta, M, Jain, R & Tomamichel, M 2019, 'A minimax approach to one-shot entropy inequalities', Journal of Mathematical Physics, vol. 60, no. 12, pp. 122201-122201.
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One-shot information theory entertains a plethora of entropic quantities,
such as the smooth max-divergence, hypothesis testing divergence and
information spectrum divergence, that characterize various operational tasks
and are used to prove the asymptotic behavior of various tasks in quantum
information theory. Tight inequalities between these quantities are thus of
immediate interest. In this note we use a minimax approach (appearing
previously for example in the proofs of the quantum substate theorem), to
simplify the quantum problem to a commutative one, which allows us to derive
such inequalities. Our derivations are conceptually different from previous
arguments and in some cases lead to tighter relations. We hope that the
approach discussed here can lead to progress in open problems in quantum
Shannon theory, and exemplify this by applying it to a simple case of the joint
smoothing problem.
Arabameri, A, Chen, W, Blaschke, T, Tiefenbacher, JP, Pradhan, B & Tien Bui, D 2019, 'Gully Head-Cut Distribution Modeling Using Machine Learning Methods—A Case Study of N.W. Iran', Water, vol. 12, no. 1, pp. 16-16.
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To more effectively prevent and manage the scourge of gully erosion in arid and semi-arid regions, we present a novel-ensemble intelligence approach—bagging-based alternating decision-tree classifier (bagging-ADTree)—and use it to model a landscape’s susceptibility to gully erosion based on 18 gully-erosion conditioning factors. The model’s goodness-of-fit and prediction performance are compared to three other machine learning algorithms (single alternating decision tree, rotational-forest-based alternating decision tree (RF-ADTree), and benchmark logistic regression). To achieve this, a gully-erosion inventory was created for the study area, the Chah Mousi watershed, Iran by combining archival records containing reports of gully erosion, remotely sensed data from Google Earth, and geolocated sites of gully head-cuts gathered in a field survey. A total of 119 gully head-cuts were identified and mapped. To train the models’ analysis and prediction capabilities, 83 head-cuts (70% of the total) and the corresponding measures of the conditioning factors were input into each model. The results from the models were validated using the data pertaining to the remaining 36 gully locations (30%). Next, the frequency ratio is used to identify which conditioning-factor classes have the strongest correlation with gully erosion. Using random-forest modeling, the relative importance of each of the conditioning factors was determined. Based on the random-forest results, the top eight factors in this study area are distance-to-road, drainage density, distance-to-stream, LU/LC, annual precipitation, topographic wetness index, NDVI, and elevation. Finally, based on goodness-of-fit and AUROC of the success rate curve (SRC) and prediction rate curve (PRC), the results indicate that the bagging-ADTree ensemble model had the best performance, with SRC (0.964) and PRC (0.978). RF-ADTree (SRC = 0.952 and PRC = 0.971), ADTree (SRC = 0.926 and PRC = 0.965), and LR (SRC = 0.867 and ...
Arabameri, A, Pradhan, B & Lombardo, L 2019, 'Comparative assessment using boosted regression trees, binary logistic regression, frequency ratio and numerical risk factor for gully erosion susceptibility modelling', CATENA, vol. 183, pp. 104223-104223.
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© 2019 Elsevier B.V. The initiation and development of gullies as worldwide features in landscape have resulted in land degradation, soil erosion, desertification, flooding and groundwater level decrease, which in turn, cause severe destruction to infrastructure. Gully erosion susceptibility mapping is the first and most important step in managing these effects and achieving sustainable development. This paper attempts to generate a reliable map using four state-of-the-art models to investigate the Bayazeh Watershed in Iran. These models consists of boosted regression trees (BRT), binary logistic regression (BLR), numerical risk factor (NRF) and frequency ratio (FR), which are based on a geographic information system (GIS). The gully erosion inventory map accounts for 362 gully locations, which were randomly divided into two groups (70% for training and 30% for validation). Sixteen topographical, geological, hydrological and environmental gully-related conditioning factors were selected for modelling. The threshold-independent area under receiver operating characteristic (AUROC) and seed cell area index (SCAI) approaches were used for validation. According to the results of BLR and BRT, the conditioning parameters namely, NDVI and lithology, played a key role in gully occurrence. Validation results showed that the BRT model with AUROC = 0.834 (83.4%) had higher prediction accuracy than other models, followed by FR 0.823 (82.3%), NRF 0.746 (74.6%) and BLR 0.659 (65.9%). SCAI results indicated that the BRT, FR and BLR models had acceptable classification accuracy. The findings, in terms of model and predictor choice, can be used by decision-makers for hazard management and implementation of protective measures in gully erosion-prone areas.
Arabameri, A, Pradhan, B & Rezaei, K 2019, 'Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS', Journal of Environmental Management, vol. 232, pp. 928-942.
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Arabameri, A, Pradhan, B & Rezaei, K 2019, 'Spatial prediction of gully erosion using ALOS PALSAR data and ensemble bivariate and data mining models', Geosciences Journal, vol. 23, no. 4, pp. 669-686.
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© 2019, The Association of Korean Geoscience Societies and Springer. Remote sensing is recognized as a powerful and efficient tool that provides a comprehensive view of large areas that are difficult to access, and also reduces costs and shortens the timing of projects. The purpose of this study is to introduce effective parameters using remote sensing data and subsequently predict gully erosion using statistical models of Density Area (DA) and Information Value (IV), and data mining based Random Forest (RF) model and their ensemble. The aforementioned models were employed at the Tororud-Najarabad watershed in the northeastern part of Semnan province, Iran. For this purpose, at first using various resources, the map of the distribution of the gullies was prepared with the help of field visits and Google Earth images. In order to analyse the earth’s surface and extraction of topographic parameters, a digital elevation model derived from PALSAR (Phased Array type L-band Synthetic Aperture Radar) radar data with a resolution of 12.5 meters was used. Using literature review, expert opinion and multi-collinearity test, 15 environmental parameters were selected with a resolution of 12.5 meters for the modelling. Results of RF model indicate that parameters of NDVI (normalized difference vegetation index), elevation and land use respectively had the highest effect on the gully erosion. Several techniques such as area under curve (AUC), seed cell area index (SCAI), and Kappa coefficient were used for validation. Results of validation indicated that the combination of bivariate (IV and DA models) with the RF data-mining model has increased their performance. The prediction accuracy of AUC and Kappa values in DA, IV and RF are (0.745, 0.782, and 0.792) and (0.804, 0.852, and 0.860) and these values in ensemble models of DA-RF and IV-RF are (0.845, and 0.911) and (0.872, and 0.951) respectively. Results of SCAI show that ensemble models had a good performance, so that, with...
Arabameri, A, Pradhan, B, Rezaei, K & Conoscenti, C 2019, 'Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques', CATENA, vol. 180, pp. 282-297.
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© 2019 Elsevier B.V. This research introduces a scientific methodology for gully erosion susceptibility mapping (GESM)that employs geography information system (GIS)-based multi-criteria decision analysis. The model was tested in Semnan Province, Iran, which has an arid and semi-arid climate with high susceptibility to gully erosion. The technique for order of preference by similarity to ideal solution (TOPSIS)and the analytic hierarchy process (AHP)multi-criteria decision-making (MCDM)models were integrated. The important aspect of this research is that it did not require gully erosion inventory maps for GESM. Therefore, the proposed methodology could be useful in areas with missing or incomplete data. Fifteen variables reflecting topographic, hydrologic, geologic, environmental and soil characteristics were selected as proxies for gully erosion conditioning factors (GECFs). The experiment was conducted using 200 sample points that were selected randomly in the study area, and the weights of criteria (GECFs)were obtained using the AHP model. In the next step, the TOPSIS model was applied, and the weight of each alternative (sample points)was obtained. Kriging and inverse distance-weighted (IDW)methods were used for interpolation and GESM. Natural break method was used for classifying gully erosion susceptibility into five classes, from very low to very high. The area under the ROC curve (AUC)was used for validation. AHP results showed that distance to stream (0.14), slope degree (0.13)and distance to road (0.12)played major roles in controlling gully erosion in the study area. The values of points obtained by using the TOPSIS model ranged from 0.321 to 0.808. Verification results showed that kriging had higher prediction accuracy than IDW. The GESM results obtained by this methodology can be used by decision makers and managers to plan preventive measures and reduce damages due to gully erosion.
Arabameri, A, Pradhan, B, Rezaei, K, Sohrabi, M & Kalantari, Z 2019, 'GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms', Journal of Mountain Science, vol. 16, no. 3, pp. 595-618.
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© 2019, Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag GmbH Germany, part of Springer Nature. In this study, a novel approach of the landslide numerical risk factor (LNRF) bivariate model was used in ensemble with linear multivariate regression (LMR) and boosted regression tree (BRT) models, coupled with radar remote sensing data and geographic information system (GIS), for landslide susceptibility mapping (LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory (70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party (ILWP), Forestry, Rangeland and Watershed Organisation (FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve (AUC), frequency ratio (FR) and seed cell area index (SCAI). Normalised difference vegetation index, land use/ land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models (AUC = 0.912 (91.2%) and 0.907 (90.7%), respectively) had high predictive accuracy than the LNRF model alone (AUC = 0.855 (85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslid...
Arabameri, A, Yamani, M, Pradhan, B, Melesse, A, Shirani, K & Tien Bui, D 2019, 'Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility', Science of The Total Environment, vol. 688, pp. 903-916.
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Gully erosion is considered as a severe environmental problem in many areas of the world which causes huge damages to agricultural lands and infrastructures (i.e. roads, buildings, and bridges); however, gully erosion modeling and prediction with high accuracy are still difficult due to the complex interactions of various factors. The objective of this research was to develop and introduce three new ensemble models, which were based on Complex Proportional Assessment of Alternatives (COPRAS), Logistic Regression (LR), Boosted Regression Tree (BRT), Random Forest (RF), and Frequency Ratio (FR) for spatial prediction of gully erosion with a case study at the Najafabad watershed (Iran). For this purpose, a total of 290 head-cut of gullies and 17 conditioning factors were collected and used to establish a geospatial database. Subsequently, FR was used to determine the spatial relationship between the conditioning factors and the head-cut of gullies, whereas RF, BRT, and LR were used to quantify the relative importance of these factors. In the next step, three ensemble gully erosion models, named COPRAS-FR-RF, COPRAS-FR-BRT, and COPRAS-FR-LR were developed and verified. The Success Rate Curve (SRC), and the Prediction Rate Curve (PRC) and their areas under the curves (AUC) were used to check the performance of the three proposed models. The result showed that Soil group, geomorphology, and drainage density factors played the key role on the occurrence of the gully erosion. All the three models have very high degree-of-fit and the prediction performance, the COPRAS-FR-RF model (AUC-SRC = 0.974 and AUC-PRC = 0.929), the COPRAS-FR-BRT model (AUC-SRC = 0.973 and AUC-PRC = 0.928), and the COPRAS-FR-LR model (AUC-SRC = 0.972 and AUC-PRC = 0.926); therefore, it is concluded that they are efficient and new powerful tools which could be used for predicting gully erosion in prone-areas.
Arabameri, Cerda, Rodrigo-Comino, Pradhan, Sohrabi, Blaschke & Tien Bui 2019, 'Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)', Remote Sensing, vol. 11, no. 21, pp. 2577-2577.
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Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we tested the efficiency of the index of entropy (IoE), the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and their combination. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion. Firstly, a gully erosion inventory map (GEIM) with 206 gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data). Fifteen gully-related conditioning factors (GRCFs) including elevation, slope, aspect, plan curvature, stream power index, topographical wetness index, rainfall, soil type, drainage density, distance to river, distance to road, distance to fault, lithology, land use/land cover, and soil type, were used for modeling. The advanced land observing satellite (ALOS) digital elevation model with a spatial resolution of 30 m was used for the extraction of the above-mentioned topographic factors. The tolerance (TOL) and variance inflation factor (VIF) were also included for checking the multicollinearity among the GRCFs. Based on IoE, we concluded that soil type, lithology, and elevation were the most significant in terms of gully formation. Validation results using the area under the receiver operating characteristic curve (AUROC) showed that IoE (0.941) reached a higher prediction accuracy than VIKOR (0.857) and VIKOR-IoE (0.868). Based on our results, the combination of statistical (IoE) models along with remote sensing and GIS can convert the multi-criteria decision-making (MCDM) models into efficient and powerful tools for gully erosion prediction. We strongly suggest that decision-makers and managers shou...
Arabameri, Pradhan, Rezaei & Lee 2019, 'Assessment of Landslide Susceptibility Using Statistical- and Artificial Intelligence-based FR–RF Integrated Model and Multiresolution DEMs', Remote Sensing, vol. 11, no. 9, pp. 999-999.
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Landslide is one of the most important geomorphological hazards that cause significant ecological and economic losses and results in billions of dollars in financial losses and thousands of casualties per year. The occurrence of landslide in northern Iran (Alborz Mountain Belt) is often due to the geological and climatic conditions and tectonic and human activities. To reduce or control the damage caused by landslides, landslide susceptibility mapping (LSM) and landslide risk assessment are necessary. In this study, the efficiency and integration of frequency ratio (FR) and random forest (RF) in statistical- and artificial intelligence-based models and different digital elevation models (DEMs) with various spatial resolutions were assessed in the field of LSM. The experiment was performed in Sangtarashan watershed, Mazandran Province, Iran. The study area, which extends to 1,072.28 km2, is severely affected by landslides, which cause severe economic and ecological losses. An inventory of 129 landslides that occurred in the study area was prepared using various resources, such as historical landslide records, the interpretation of aerial photos and Google Earth images, and extensive field surveys. The inventory was split into training and test sets, which include 70 and 30% of the landslide locations, respectively. Subsequently, 15 topographic, hydrologic, geologic, and environmental landslide conditioning factors were selected as predictor variables of landslide occurrence on the basis of literature review, field works and multicollinearity analysis. Phased array type L-band synthetic aperture radar (PALSAR), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), and SRTM (Shuttle Radar Topography Mission) DEMs were used to extract topographic and hydrologic attributes. The RF model showed that land use/land cover (16.95), normalised difference vegetation index (16.44), distance to road (15.32) and elevation (13.6) were the most important...
Areerachakul, N, Sakulkhaemaruethai, S, Johir, MAH, Kandasamy, J & Vigneswaran, S 2019, 'Photocatalytic degradation of organic pollutants from wastewater using aluminium doped titanium dioxide', Journal of Water Process Engineering, vol. 27, pp. 177-184.
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Argha, A, Su, SW & Celler, BG 2019, 'Control allocation-based fault tolerant control', Automatica, vol. 103, pp. 408-417.
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Argha, A, Su, SW & Celler, BG 2019, 'Static output feedback fault tolerant control using control allocation scheme', International Journal of Robust and Nonlinear Control, vol. 29, no. 1, pp. 98-116.
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© 2018 John Wiley & Sons, Ltd. This paper describes two novel schemes for fault tolerant control using robust suboptimal static output feedback design methods. These schemes can also be employed as actuator redundancy management for overactuated uncertain linear systems. In contrast to many existing methods in the literature that assume the control input matrix (i) is not of full-rank such that it can be factorized into two matrices and (ii) it does not involve uncertainty, these schemes can be applied to systems whose control input matrix cannot be factorized and/or involve uncertainty. The so-called virtual control, in these schemes, is calculated using suboptimal H 2 -based static output feedback design schemes constructed to be robust against uncertainties emanating from inherent input matrix uncertainty and visibility of the control allocator to the controller. Then, using two proposed control allocation schemes (fixed and on-line), the obtained virtual control signal is redistributed among remaining (redundant or nonfaulty) set of actuators. As the proposed schemes are modular-based, they can be employed as real-time fault tolerant control schemes with no need to reconfigure the controller in the case of actuator faults or failures. The effectiveness of the proposed schemes is discussed and compared with numerical examples.
Argha, A, Su, SW, Savkin, A & Celler, B 2019, 'A framework for optimal actuator/sensor selection in a control system', International Journal of Control, vol. 92, no. 2, pp. 242-260.
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© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. When dealing with large-scale systems, manual selection of a subset of components (sensors/actuators), or equivalently identification of a favourable structure for the controller, that guarantees a certain closed-loop performance, is not very feasible. This paper is dedicated to the problem of concurrent optimal selection of actuators/sensors which can equivalently be considered as the structure identification for the controller. In the context of a multi-channel H 2 dynamic output feedback controller synthesis, we formulate and analyse a framework in which we incorporate two extra terms for penalising the number of actuators and sensors into the variational formulations of controller synthesis problems in order to induce a favourable controller structure. We then develop an explicit scheme as well as an iterative process for the purpose of dealing with the multi-objective problem of controller structure and control law co-design. It is also stressed that the immediate application of the proposed approach lies within the fault accommodation stage of a fault tolerant control scheme. By two numerical examples, we demonstrate the remarkable performance of the proposed approach.
Argha, A, Su, SW, Savkin, A & Celler, B 2019, 'Design of optimal sliding-mode control using partial eigenstructure assignment', International Journal of Control, vol. 92, no. 7, pp. 1511-1523.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group This paper describes a new framework for the design of a sliding surface for a given system while multi-channel (Formula presented.) performances of the closed-loop system are under control. In contrast to most of the current sliding surface design schemes, in this new method, the level of control effort required to maintain sliding is penalised. The proposed method for the design of optimal sliding mode control is implemented in two stages. In the first stage, a state feedback gain is derived using a linear matrix inequality (LMI)-based scheme that can assign a number of the closed-loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage by using one of the two different methods developed for this goal. The proposed theory is evaluated by using numerical examples including the problem of steady-state output tracking via a state-feedback SMC for flight control.
Argha, A, Su, SW, Zheng, WX & Celler, BG 2019, 'Sliding‐mode fault‐tolerant control using the control allocation scheme', International Journal of Robust and Nonlinear Control, vol. 29, no. 17, pp. 6256-6273.
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© 2019 John Wiley & Sons, Ltd. This paper is devoted to the design of a novel fault-tolerant control (FTC) using the combination of a robust sliding-mode control (SMC) strategy and a control allocation (CA) algorithm, referred to as a CA-based sliding-mode FTC (SMFTC). The proposed SMFTC can also be considered a modular-design control strategy. In this approach, first, a high-level SMC, designed without detailed knowledge of systems' actuators/effectors, commands a vector of virtual control signals to meet the overall control objectives. Then, a CA algorithm distributes the virtual control efforts among the healthy actuators/effectors using the real-time information obtained from a fault detection and reconstruction mechanism. As the underlying system is not assumed to have a rank-deficient input matrix, the control allocator module is visible to the SMC module resulting in an uncertainty. Hence, the virtual control, in this scheme, is designed to be robust against uncertainties emanating from the visibility of the control allocator to the controller and imperfections in the estimated effectiveness gain. The proposed CA-based SMFTC scheme is a unified FTC, which does not need to reconfigure the control system in the case of actuator fault or failure. Additionally, to cope with actuator saturation limits, a novel redistributed pseudoinverse-based CA mechanism is proposed. The effectiveness of the proposed schemes is discussed with a numerical example.
Argha, A, W. Su, S, Ye, L & G. Celler, B 2019, 'Optimal sparse output feedback for networked systems with parametric uncertainties', Numerical Algebra, Control & Optimization, vol. 9, no. 3, pp. 283-295.
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© 2019, American Institute of Mathematical Sciences. All rights reserved. This paper investigates the design of block row/column-sparse distributed static output H2 feedback control for interconnected systems with polytopic uncertainties. The proposed approach is applicable to the networked systems with publisher/subscriber communication topology. We added two additional terms into the optimisation index function to penalise the number of publishers and subscribers. To optimally select a subset of available publishers and/or subscribers in the network, we introduced both an explicit scheme and an iterative process to handle this problem. We demonstrated the effectiveness by using a numerical example. The example showed that the simultaneous identification of favourable networks topologies and design of controller strategy can be achieved by using the proposed method.
Argha, A, Wu, J, Su, SW & Celler, BG 2019, 'Blood Pressure Estimation From Beat-by-Beat Time-Domain Features of Oscillometric Waveforms Using Deep-Neural-Network Classification Models', IEEE Access, vol. 7, pp. 113427-113439.
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In general, existing machine learning based approaches, developed for systolic and diastolic blood pressure (SBP and DBP) estimation from oscillometric waveforms (OWs), employ features extracted from the OW envelope (OWE) alone and ignore important beat-by-beat (BBB) features which represent fundamental physical properties of the entire non-invasive blood pressure (NIBP) measurement system. Unlike the existing literature, this paper proposes a novel deep-learning based method for BP estimation trained with BBB time-domain features extracted from OWs. First, we extract six time-domain features from each beat of the OW, relative to the preceding beat. Second, using the extracted BBB features along with the corresponding cuff pressures, we form a feature vector for each OW beat and locate it in one of three different classes, namely pre-systolic (PS), between systolic and diastolic (BSD) and after diastolic (AD). We then devise a deep-belief network (DBN)-deep neural network (DNN) classification model as well as a novel artificial feature extraction method for estimating SBP and DBP from feature vectors extracted from OWs and their corresponding deflation curves. The proposed DBN-DNN classification approach can effectively learn the complex nonlinear relationship between the artificial feature vectors and target classes. The SBP and DBP points are then obtained by mapping the beats at which the network output sequence switches from PS phase to BSD phase and from BSD phase to AD phase, respectively, to the deflation curve. Adopting a 5-fold cross-validation scheme and using a data base of 350 NIBP recordings gave an average mean absolute error of 1.1±2.9 mmHg for SBP and 3.0±5.6 mmHg for DBP relative to reference values. We experimentally show that the proposed DBN-DNN-based classification algorithm trained with BBB time-domain features can outperform traditional deep-learning based methods for BP estimation trained with features extracted only from OWEs.
Arockia Baskaran, AGR, Nanda, P, Nepal, S & He, S 2019, 'Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks', Concurrency and Computation: Practice and Experience, vol. 31, no. 23.
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Arshad, B, Ogie, R, Barthelemy, J, Pradhan, B, Verstaevel, N & Perez, P 2019, 'Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review', Sensors, vol. 19, no. 22, pp. 5012-5012.
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Floods are amongst the most common and devastating of all natural hazards. The alarming number of flood-related deaths and financial losses suffered annually across the world call for improved response to flood risks. Interestingly, the last decade has presented great opportunities with a series of scholarly activities exploring how camera images and wireless sensor data from Internet-of-Things (IoT) networks can improve flood management. This paper presents a systematic review of the literature regarding IoT-based sensors and computer vision applications in flood monitoring and mapping. The paper contributes by highlighting the main computer vision techniques and IoT sensor approaches utilised in the literature for real-time flood monitoring, flood modelling, mapping and early warning systems including the estimation of water level. The paper further contributes by providing recommendations for future research. In particular, the study recommends ways in which computer vision and IoT sensor techniques can be harnessed to better monitor and manage coastal lagoons—an aspect that is under-explored in the literature.
Asadabadi, MR, Chang, E & Saberi, M 2019, 'Are MCDM methods useful? A critical review of Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP)', Cogent Engineering, vol. 6, no. 1.
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© 2019, © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Although Multi Criteria Decision Making (MCDM) methods have been applied in numerous case studies, many companies still avoid employing these methods in making their decisions and prefer to decide intuitively. There are studies claiming that MCDM methods provide better rankings for companies than intuitive approaches. This study argues that this claim may have low validity from a company’s perspective. For this purpose, it focuses on one of the MCDM methods referred to as the Analytic Hierarchy Process (AHP) and shows that AHP is very likely to provide a ranking of options that would not be acceptable by a rational person. The main reason that many companies do not rely on current MCDM methods can be due to the fact that managers intuitively notice ranking errors. Future studies should end the promotion of outdated approaches, pay closer attention to the deficiencies of the current MCDM processes, and develop more useful methods.
Ashok, B, Nanthagopal, K, Darla, S, Chyuan, OH, Ramesh, A, Jacob, A, Sahil, G, Thiyagarajan, S & Geo, VE 2019, 'Comparative assessment of hexanol and decanol as oxygenated additives with calophyllum inophyllum biodiesel', Energy, vol. 173, pp. 494-510.
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© 2019 Elsevier Ltd In this research work, the four ternary blends were prepared with 30% and 40% by volume of higher alcohol (decanol and hexanol) with biodiesel while maintain 50% of diesel concentration. All ternary blends of diesel-biodiesel-higher alcohols were used in single cylinder engine and the results were compared with binary blend of 50%–50% biodiesel, pure diesel and biodiesel. It was revealed that thermal efficiency of ternary blends was higher than biodiesel and in some cases it is closer to pure diesel. In contrary, specific fuel consumption is found to lower with increase in alcohol fractions in ternary blends. Moreover, hydrocarbon, smoke, carbon monoxide emissions from alcohol-infused fuel blends were observed to be lower than both biodiesel and pure diesel. Significant reduction in oxides of nitrogen (NOx) emissions was also observed by the addition of higher alcohols to the fuel blend when compared to biodiesel fuel. It is to be noted that decanol 40% addition with diesel and biodiesel blend has shown better results in emission characteristics. Furthermore, the heat release rate and in-cylinder pressure for biodiesel were significantly lower compared to pure diesel fuels. However, addition of 40% decanol with fuel blend improved the heat release rate and in-cylinder pressure.
Ashournejad, Q, Hosseini, A, Pradhan, B & Hosseini, SJ 2019, 'Hazard zoning for spatial planning using GIS-based landslide susceptibility assessment: a new hybrid integrated data-driven and knowledge-based model', Arabian Journal of Geosciences, vol. 12, no. 4.
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Ashtari, K, Nazari, H, Ko, H, Tebon, P, Akhshik, M, Akbari, M, Alhosseini, SN, Mozafari, M, Mehravi, B, Soleimani, M, Ardehali, R, Ebrahimi Warkiani, M, Ahadian, S & Khademhosseini, A 2019, 'Electrically conductive nanomaterials for cardiac tissue engineering', Advanced Drug Delivery Reviews, vol. 144, pp. 162-179.
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Patient deaths resulting from cardiovascular diseases are increasing across the globe, posing the greatest risk to patients in developed countries. Myocardial infarction, as a result of inadequate blood flow to the myocardium, results in irreversible loss of cardiomyocytes which can lead to heart failure. A sequela of myocardial infarction is scar formation that can alter the normal myocardial architecture and result in arrhythmias. Over the past decade, a myriad of tissue engineering approaches has been developed to fabricate engineered scaffolds for repairing cardiac tissue. This paper highlights the recent application of electrically conductive nanomaterials (carbon and gold-based nanomaterials, and electroactive polymers) to the development of scaffolds for cardiac tissue engineering. Moreover, this work summarizes the effects of these nanomaterials on cardiac cell behavior such as proliferation and migration, as well as cardiomyogenic differentiation in stem cells.
Asif, MB, Ansari, AJ, Chen, S-S, Nghiem, LD, Price, WE & Hai, FI 2019, 'Understanding the mechanisms of trace organic contaminant removal by high retention membrane bioreactors: a critical review', Environmental Science and Pollution Research, vol. 26, no. 33, pp. 34085-34100.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. High retention membrane bioreactors (HR-MBR) combine a high retention membrane separation process such as membrane distillation, forward osmosis, or nanofiltration with a conventional activated sludge (CAS) process. Depending on the physicochemical properties of the trace organic contaminants (TrOCs) as well as the selected high retention membrane process, HR-MBR can achieve effective removal (80–99%) of a broad spectrum of TrOCs. An in-depth assessment of the available literature on HR-MBR performance suggests that compared to CAS and conventional MBRs (using micro- or ultra-filtration membrane), aqueous phase removal of TrOCs in HR-MBR is significantly better. Conceptually, longer retention time may significantly improve TrOC biodegradation, but there are insufficient data in the literature to evaluate the extent of TrOC biodegradation improvement by HR-MBR. The accumulation of hardly biodegradable TrOCs within the bioreactor of an HR-MBR system may complicate further treatment and beneficial reuse of sludge. In addition to TrOCs, accumulation of salts gradually increases the salinity in bioreactor and can adversely affect microbial activities. Strategies to mitigate these limitations are discussed. A qualitative framework is proposed to predict the contribution of the different key mechanisms of TrOC removal (i.e., membrane retention, biodegradation, and sorption) in HR-MBR.
Askari, M, Yu, Y, Zhang, C, Samali, B & Gu, X 2019, 'Real-Time Tracking of Structural Stiffness Reduction with Unknown Inputs, Using Self-Adaptive Recursive Least-Square and Curvature-Change Techniques', International Journal of Structural Stability and Dynamics, vol. 19, no. 10, pp. 1950123-1950123.
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In this paper, a new computationally efficient algorithm is developed for online and real-time identification of time, location, and severity of abrupt changes in structural stiffness as well as the unknown inputs such as earthquake signal. The proposed algorithm consists of three stages and is based on self-adaptive recursive least-square (RLS) and curvature-change approaches. In stage 1 (intact structure), a simple compact RLS is hired to estimate the unknown parameters and input of the structure such as stiffness and earthquake. Once the damage has occurred, its time and location are identified in stage 2, using two robust damage indices which are based on the structural jerk response and the error between measured and estimated responses of structure from RLS. Finally, the damage severity as well as the unknown excitations are identified in the third stage (damaged structure), using a self-adaptive multiple-forgetting-factor RLS. The method is validated through numerical and experimental case studies including linear and nonlinear buildings, a truss structure, and a three-story steel frame with different excitations and damage scenarios. Results show that the proposed algorithm can effectively identify the time-varying structural stiffness as well as unknown excitations with high computational efficiency, even when the measured data is contaminated with different levels of noise. In addition, as no optimization method is used here, it can be applied to real-time applications with computational efficiency.
Atov, I, Chen, K-C & Yu, S 2019, 'Data Science and Artificial Intelligence for Communications', IEEE Communications Magazine, vol. 57, no. 5, pp. 56-56.
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Atov, I, Chen, K-C, Kamal, A & Yu, S 2019, 'Data Science and Artificial Intelligence for Communications', IEEE Communications Magazine, vol. 57, no. 11, pp. 82-83.
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Aung, Y, Khabbaz, H & Fatahi, B 2019, 'Mixed hardening hyper-viscoplasticity model for soils incorporating non-linear creep rate – H-creep model', International Journal of Plasticity, vol. 120, pp. 88-114.
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© 2019 Elsevier Ltd. This paper focuses on the deformation of soils considering the time-dependent stress-strain evolution. In this paper, a new mixed hardening hyper-viscoplasticity model is proposed for the derivation of the time-dependent constitutive behaviour of soils, with the intention to capture the variation in the shapes of the yield loci by pursuing non-associated flow rules and accounting for kinematic hardening effects. The distinctive departure from the existing viscoplasticity models is the application of thermodynamics, based upon the use of internal variables, to postulate free-energy and dissipation potential functions, from which the corresponding yield locus, isotropic and kinematic hardening laws, flow rules and the elasticity law are deduced in a systematic procedure. The kinematic hardening behaviour of the yield locus is considered using the shift stress, resulting from the additional plastic component of the free-energy function. A non-linear creep formulation is postulated to address the limitation of over-estimating long-term settlement and incorporated into the model for more reliable predictions. The major parameters required for the model are identified, along with the summary of descriptions on how the model parameters can readily be determined. Non-associated behaviour is found to be a natural consequence of this approach, whenever the division between dissipated and stored plastic work is not equal. This study aims to provide a theoretical background and a numerical implementation for those who are interested in the advancement of constitutive modelling of soil behaviour under the framework of hyperplasticity. Validity and versatility of the proposed constitutive model are evaluated against triaxial and oedometer test results available in literature.
Awwad, S, Tarvade, S, Piccardi, M & Gattas, DJ 2019, 'The use of privacy-protected computer vision to measure the quality of healthcare worker hand hygiene', International Journal for Quality in Health Care, vol. 31, no. 1, pp. 36-42.
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(i) To demonstrate the feasibility of automated, direct observation and collection of hand hygiene data, (ii) to develop computer visual methods capable of reporting compliance with moment 1 (the performance of hand hygiene before touching a patient) and (iii) to report the diagnostic accuracy of automated, direct observation of moment 1.Observation of simulated hand hygiene encounters between a healthcare worker and a patient.Computer laboratory in a university.Healthy volunteers.Sensitivity and specificity of automatic detection of the first moment of hand hygiene.We captured video and depth images using a Kinect camera and developed computer visual methods to automatically detect the use of alcohol-based hand rub (ABHR), rubbing together of hands and subsequent contact of the patient by the healthcare worker using depth imagery.We acquired images from 18 different simulated hand hygiene encounters where the healthcare worker complied with the first moment of hand hygiene, and 8 encounters where they did not. The diagnostic accuracy of determining that ABHR was dispensed and that the patient was touched was excellent (sensitivity 100%, specificity 100%). The diagnostic accuracy of determining that the hands were rubbed together after dispensing ABHR was good (sensitivity 83%, specificity 88%).We have demonstrated that it is possible to automate the direct observation of hand hygiene performance in a simulated clinical setting. We used cheap, widely available consumer technology and depth imagery which potentially increases clinical application and decreases privacy concerns.
Aydogdu, MO, Chou, J, Altun, E, Ekren, N, Cakmak, S, Eroglu, M, Osman, AA, Kutlu, O, Oner, ET, Avsar, G, Oktar, FN, Yilmaz, I & Gunduz, O 2019, 'Production of the biomimetic small diameter blood vessels for cardiovascular tissue engineering', International Journal of Polymeric Materials and Polymeric Biomaterials, vol. 68, no. 5, pp. 243-255.
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© 2018 Taylor & Francis A novel biomimetic vascular graft scaffolds were produced by electrospinning method with the most superior characteristics to be a proper biomimetic small diameter blood vessel using Polycaprolactone(PCL), Ethyl Cellulose(EC) and Collagen Type-1 were used to create the most convenient synergy of a natural and synthetic polymer to achieve similarity to native small diameter blood vessels. Scanning Electron Microscopy(SEM), Fourier Transform Infrared Spectroscopy(FTIR), Differential Scanning Calorimetry Analysis(DSC), tensile measurement tests, and in-vitro and in-vivo applications were performed. Results indicated significant properties such as having 39.33 nm minimum, 104.98 nm average fiber diameter, 3.2 MPa young modulus and 135% relative cell viability.
Aykin, I, Akgun, B & Krunz, M 2019, 'Multi-beam Transmissions for Blockage Resilience and Reliability in Millimeter-Wave Systems', IEEE Journal on Selected Areas in Communications, vol. 37, no. 12, pp. 2772-2785.
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Azadi, S, Aboulkheyr Es, H, Razavi Bazaz, S, Thiery, JP, Asadnia, M & Ebrahimi Warkiani, M 2019, 'Upregulation of PD-L1 expression in breast cancer cells through the formation of 3D multicellular cancer aggregates under different chemical and mechanical conditions', Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, vol. 1866, no. 12, pp. 118526-118526.
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Expression of programmed death-ligand 1 (PD-L1) in cancer cells plays an important role in cancer-immune cell interaction. The emerging evidence suggests regulation of PD-L1 expression by several tumor microenvironmental cues. However, the association of PD-L1 expression with chemical and mechanical features of the tumor microenvironment, specifically epidermal growth factor receptor (EGFR) signaling and matrix stiffness, remains elusive. Herein, we determine whether EGFR targeting and substrate stiffness affect the regulation of PD-L1 expression. Breast carcinoma cell lines, MCF7 and MDA-MB-231, were cultured under different conditions targeting EGFR and exposing cells to distinct substrate stiffness to evaluate PD-L1 expression. Furthermore, the ability to form aggregates in short-term culture of breast carcinoma cells and its effect on expression level of PD-L1 was probed. Our results indicated that PD-L1 expression was altered in response to both EGFR inhibition and substrate stiffness. Additionally, a positive association between the formation of multicellular aggregates and PD-L1 expression was observed. MDA-MB-231 cells expressed the highest PD-L1 level on a stiff substrate, while inhibition of EGFR reduced expression of PD-L1. The results suggested that both physical and chemical features of tumor microenvironment regulate PD-L1 expression through alteration of tumor aggregate formation potential. In line with these results, the in-silico study highlighted a positive correlation between PD-L1 expression, EGFR signaling, epithelial to mesenchymal transition related transcription factors (EMT-TFs) and stemness markers in metastatic breast cancer. These findings improve our understanding of regulation of PD-L1 expression by tumor microenvironment leading to evasion of tumor cells from the immune system.
Azadi, S, Tafazzoli‐Shadpour, M, Soleimani, M & Warkiani, ME 2019, 'Modulating cancer cell mechanics and actin cytoskeleton structure by chemical and mechanical stimulations', Journal of Biomedical Materials Research Part A, vol. 107, no. 8, pp. 1569-1581.
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To date, a myriad of strategies has been suggested for targeting the chemical signaling of cancer cells. Also, biomechanical features are gaining much more attention. These features can be used as biomarkers which influence cancer progression. Current approaches on cancer treatment are mainly focused on changing the biochemical signaling of cancer cells, whereas less attention was devoted to their biomechanical properties. Herein, we propose targeting of cancer cell mechanics through the microenvironmental mechanical and chemical cues. As such, we examined the role of substrate stiffness as well as the effect of epidermal growth factor receptor (EGFR) blockade in the cell mechanics. As a mechanical stimulus, stiff and soft polydimethylsiloxane substrates were utilized, while as a chemical stimulus, EGFR blockade was considered. Thus, breast cancer cell lines, MCF7 and MDA-MB-231, were cultured among chemical and mechanical groups. The local elasticity of cancer cells was assessed by atomic force microscopy nanoindentation method. Furthermore, we evaluated the effect of mentioned mechanical and chemical treatments on the morphology, actin cytoskeleton structures, and cancer cell migration abilities. The stiffness and migration ability of cancer cells increased by substrate stiffening while Cetuximab treatment demonstrated an elevation in the elastic modulus of cells followed by a reduction in the migration ability. These findings indicate that cancer cell mechanics is modulated not only by the mechanical cues but also by the chemical ones through EGFR signaling pathway. Overall, our results illustrate that manipulation of cell mechanics allows for the possible modulation of tumor cell migration. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 1569-1581, 2019.
Azar, APK, Askari, G, Crispini, L, Pour, AB, Zoheir, B & Pradhan, B 2019, 'Field and spaceborne imagery data for evaluation of the paleo-stress regime during formation of the Jurassic dike swarms in the Kalateh Alaeddin Mountain area, Shahrood, north Iran', Arabian Journal of Geosciences, vol. 12, no. 17.
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© 2019, Saudi Society for Geosciences. Dike swarms are commonly linked with extensional structures in diverse geodynamic environments. Mafic dyke swarms are typically used to reconstruct the paleo-stress fields of a given region. These dikes are considered paleo-stress indicators and excellent time marker (if related geochronological data are available) of the local and regional stress fields. In the Middle-Late Jurassic, swarms of mafic dikes emplaced into the Neoproterozoic schists and amphibolites in the Kalateh Alaeddin Mountain area in south Shahrood, north Iran. These dikes with different thicknesses show a general east–west strike direction, with mostly a steep dip angle. In this paper, we present structural data of these dike swarms for the sake of assessing the paleo-stress state and the magma pressure ratio at the time of their emplacement. Field and structural data are integrated with ASTER Global Digital Elevation Model (GDEM) and Centre National d’Etudes Spatiales (CNES)/SPOT imagery data, to extract important parameters of the investigated dikes and controlling fault/joint sets. Orientation of the principal paleo-stress axes, quantification of the stress ratio, and the associated magma pressure ratio (driving stress ratio) were calculated using the stereographic projection and Mohr’s circle reconstruction techniques. The results reveal that the maximum paleo-stress component (σ1) was sub-vertical and the intermediate (σ2) and minimum (σ3) paleo-stresses components were sub-horizontal in N264° E and N173° E trends, respectively. Due to the low value of the driving stress ratio (R = 0.05), these dikes developed perpendicular to the minimum principal stress (in E–W direction). The stress ratio value (ø = 0.66) indicates a moderately oblate stress ellipsoid. The orientation of the principal paleo-stress axes and the oblate ellipsoid are indicative of the dike emplacement during a N–S-directed tectonic extension, in agreement with the Jurassic subsidence...
AzariJafari, H, Taheri Amiri, MJ, Ashrafian, A, Rasekh, H, Barforooshi, MJ & Berenjian, J 2019, 'Ternary blended cement: An eco-friendly alternative to improve resistivity of high-performance self-consolidating concrete against elevated temperature', Journal of Cleaner Production, vol. 223, pp. 575-586.
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© 2019 Elsevier Ltd The unique fresh and hardened properties of high-performance self-consolidating concrete (HPSCC) led to an extensive application of this mixture in high-rise buildings. In this paper, the elevated temperature resistivity of 19 HPSCC mixtures incorporating binary and ternary blends of fly ash, silica fume, natural zeolite, and metakaolin was investigated. Changes in mass, compressive strength and ultrasonic pulse velocity (UPV) of the mixtures were measured at different temperatures (20, 300, 500, and 700 °C). A life cycle assessment (LCA) was also employed to explore the environmental performance of the mixtures. The test results revealed that in ambient temperature, ternary mixtures incorporating natural zeolite and fly ash or natural zeolite and metakaolin have lower compressive strength than that of the control mixture. The residual compressive strengths of fly ash-silica fume-incorporated mixture was similar to those in binary mixtures. The UPV test results revealed a larger than 50% reduction in transition velocity when the temperature was above 500 °C, and there is a strong association between the UPV and compressive strength test results of the mixtures at different temperatures, but the correlation decreased inversely proportional to the exposure temperature. Among the ternary mixtures, those mixtures that incorporate natural zeolite indicate the most significant mass loss after exposing to elevated temperature. The environmental results indicate that the substitution of pozzolanic materials with Portland cement may not always be beneficial. The ecosystem quality results of binary fly ash mixtures were larger than the control mixture due to the extensive transportation distance of import. In addition, metakaolin binary mixture exposes larger damage to the resources. Silica fume-incorporated mixtures had significant damage to human health. The ternary blended mixtures can be a remedy to obtain the optimized fire-resistant results and to...
Azeez, O, Pradhan, B, Shafri, H, Shukla, N, Lee, C-W & Rizeei, H 2019, 'Modeling of CO Emissions from Traffic Vehicles Using Artificial Neural Networks', Applied Sciences, vol. 9, no. 2, pp. 313-313.
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Traffic emissions are considered one of the leading causes of environmental impact in megacities and their dangerous effects on human health. This paper presents a hybrid model based on data mining and GIS models designed to predict vehicular Carbon Monoxide (CO) emitted from traffic on the New Klang Valley Expressway, Malaysia. The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. The other contribution is related to the case study, which represents the spatial and quantitative variations in the vehicular CO emissions between toll plaza areas and road networks. The proposed hybrid model consists of three steps: the first step is the implementation of the correlation-based Feature Selection model to select the best model’s predictors; the second step is the prediction of vehicular CO by using a multilayer perceptron neural network model; and the third step is the creation of micro scale prediction maps. The model was developed using six traffic CO predictors: number of vehicles, number of heavy vehicles, number of motorbikes, temperature, wind speed and a digital surface model. The network architecture and its hyperparameters were optimized through a grid search approach. The traffic CO concentrations were observed at 15-min intervals on weekends and weekdays, four times per day. The results showed that the developed model had achieved validation accuracy of 80.6 %. Overall, the developed models are found to be promising tools for vehicular CO simulations in highly congested areas.
Baba, A, Hashmi, R, Asadnia, M, Matekovits, L & Esselle, K 2019, 'A Stripline-Based Planar Wideband Feed for High-Gain Antennas with Partially Reflecting Superstructure', Micromachines, vol. 10, no. 5, pp. 308-308.
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This paper presents a new planar feeding structure for wideband resonant-cavity antennas (RCAs). The feeding structure consists of two stacked dielectric slabs with an air-gap in between. A U-shaped slot, etched in the top metal-cladding over the upper dielectric slab, is fed by a planar stripline printed on the back side of the dielectric slab. The lower dielectric slab backed by a ground plane, is used to reduce back radiation. To validate the wideband performance of the new structure, in an RCA configuration, it was integrated with a wideband all-dielectric single-layer partially reflecting superstructure (PRS) with a transverse permittivity gradient (TPG). The single-layer RCA fed by the U-slot feeding structure demonstrated a peak directivity of 18.5 dBi with a 3 dB directivity bandwidth of 32%. An RCA prototype was fabricated and experimental results are presented.
Baba, AA, Hashmi, RM, Esselle, KP, Ahmad, Z & Hesselbarth, J 2019, 'Millimeter-Wave Broadband Antennas With Low Profile Dielectric Covers', IEEE Access, vol. 7, pp. 186228-186235.
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Baba, AA, Hashmi, RM, Esselle, KP, Marin, JG & Hesselbarth, J 2019, 'Broadband Partially Reflecting Superstrate-Based Antenna for 60 GHz Applications', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4854-4859.
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© 1963-2012 IEEE. In this communication, a broadband low-profile partially reflecting superstrate (PRS)-based antenna is presented for 60 GHz applications. The PRS with an asymmetric pattern of circular metallic patches printed on one side of a thin dielectric slab improves the feed antenna gain from 6.5 to 18.5 dBi. A prototype antenna exhibits a peak gain of 18.8 dBi with a 3 dB gain bandwidth of 16.7%. Simulated and measured radiation patterns of the proposed antenna are highly directive toward broadside over a large operating bandwidth. The prototype antenna is well matched with a measured voltage standing wave ratio (VSWR) below 2 over a frequency range from 55.6 to 69.6 GHz, corresponding to a matching bandwidth of 22.4%. Fabrication limitations and assembly tolerances are also discussed. Overall, the prototype validates the high gain and wideband performance of the proposed antenna. The total area of the PRS is 5.2\lambda -{0}^{2} and the overall height of the antenna is only 0.66\lambda -{0} at the lowest operating frequency of 55.6 GHz.
Badakhshan, S, Ganjkhani, M, Safdarian, A & Li, L 2019, 'Day‐ahead power system scheduling considering water consumption in power plants', International Transactions on Electrical Energy Systems, vol. 29, no. 12.
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© 2019 John Wiley & Sons, Ltd. Power generation consumes a substantial amount of water in the power industry. In order to address the impact of water consumption restriction on the power generation, this paper proposes a security-constrained unit commitment (SCUC) formulation considering water consumption impact as an additional constraint. To this end, the water consumption in power plants is formulated. Consequently, the SCUC is extended to consider the consumed water volume as a restricting factor. A procedure is introduced to investigate the most appropriate point of power generation operation to save a vital amount of water by raising reasonable generation costs. The objective of the proposed model is to minimize the generation cost, while water consumption is considered as an additional constraint of the problem. The proposed method is then applied on the Institute of Electrical and Electronics Engineers (IEEE) 118-bus standard test system. It is shown that a dramatic amount of water volume can be saved in the industry by exploiting rationally higher costs in the power generation.
Bah, AO, Qin, P-Y, Ziolkowski, RW, Guo, YJ & Bird, TS 2019, 'A Wideband Low-Profile Tightly Coupled Antenna Array With a Very High Figure of Merit', IEEE Transactions on Antennas and Propagation, vol. 67, no. 4, pp. 2332-2343.
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© 1963-2012 IEEE. A wideband, low-profile, tightly coupled antenna array with a simple feed network is presented. The dipole and feed networks in each unit cell are printed on both sides of a single RT/Duroid 6010 substrate with a relative dielectric constant of 10.2. The feed network, composed of meandered impedance transformer and balun sections, is designed based on Klopfenstein tapered microstrip lines. The wide-angle impedance matching is empowered by a novel wideband metasurface superstrate. For the optimum design, scanning to 70° along the E-plane is obtained together with a very high array figure of merit P A = 2.84. The H-plane scan extends to 55°. The broadside impedance bandwidth is 5.5:1 (0.80-4.38) GHz with an active voltage standing-wave ratio value ≤2. The overall height of the array above the ground plane is 0.088λ L, where λ L is the wavelength at the lowest frequency of operation. A prototype was fabricated and tested to confirm the design concepts.
Baier-Fuentes, H, Merigó, JM, Amorós, JE & Gaviria-Marín, M 2019, 'International entrepreneurship: a bibliometric overview', International Entrepreneurship and Management Journal, vol. 15, no. 2, pp. 385-429.
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© 2018 Springer Science+Business Media, LLC, part of Springer Nature The aim of this paper is to provide an overview of the academic research on International Entrepreneurship (IE). To accomplish this, an exhaustive bibliometric analysis was carried out, involving a bibliometric performance analysis and a graphic mapping of the references in this field. Our analysis focuses on journals, papers, authors, institutions and countries. To perform the performance analysis, the work uses a series of bibliometric indicators such as h-index, productivity and citations. Furthermore, the VOS viewer to graphically map the bibliographic material is used. The graphical analysis uses co-citation, bibliographic coupling and co-occurrence of keywords. The results of both analyzes are consistent among them, and show that the USA is the most influential country in IE research as it houses the main authors and institutions in this research field. Moreover, is observed and expected the continued growth of the field globally. Our research plays an informative and complementary role as it presents most of the key aspects in International Entrepreneurship research.
Bajada, C & Shashnov, M 2019, 'The effects of economic development and the evolution of social institutions on the level of corruption: comparing the Asia-Pacific with other regional blocs', Asia Pacific Business Review, vol. 25, no. 4, pp. 470-500.
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© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. The variation in the level of economic development across countries has been proposed as an explanation for the disparity in the level of corruption that is observed. As a country evolves from one stage of economic development to another and its social institutions as a result become more refined and sophisticated, their capacity to tackle corruption and poor governance practices becomes increasingly better. Improvements in the overall quality of institutions, including better policing and justice systems, increase their capacity to detect and deter corruption. This evolution of institutional quality improves social and economic well-being of society, which in turn pressures regulators, legislators and politicians to continue in the fight against corruption. The objective of this paper is to examine how economic development mediated by improvements in the quality of social institutions impacts on the level of corruption. Lessons from worldwide trends, including the Asia-Pacific region, provide opportunities for countries to enact strategic measures that can accelerate the fight against corruption.
Bano, M, Zowghi, D, Ferrari, A, Spoletini, P & Donati, B 2019, 'Teaching requirements elicitation interviews: an empirical study of learning from mistakes.', Requir. Eng., vol. 24, pp. 259-289.
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Interviews are the most widely used elicitation technique in requirements engineering (RE). However, conducting a requirements elicitation interview is challenging. The mistakes made in design or conduct of the interviews can create problems in the later stages of requirements analysis. Empirical evidence about effective pedagogical approaches for training novices on conducting requirements elicitation interviews is scarce. In this paper, we present a novel pedagogical approach for training student analysts in the art of elicitation interviews. Our study is conducted in two parts: first, we perform an observational study of interviews performed by novices, and we present a classification of the most common mistakes made; second, we utilize this list of mistakes and monitor the students’ progress in three set of interviews to discover the individual areas for improvement. We conducted an empirical study involving role-playing and authentic assessment in two semesters on two different cohorts of students. In the first semester, we had 110 students, teamed up in 28 groups, to conduct three interviews with stakeholders. We qualitatively analysed the data to identify and classify the mistakes made from their first interview only. In the second semester, we had 138 students in 34 groups and we monitored and analysed their progress in all three interviews by utilizing the list of mistakes from the first study. First, we identified 34 unique mistakes classified into seven high-level themes, namely question formulation, question omission, interview order, communication skills, analyst behaviour, customer interaction, teamwork and planning. In the second study, we discovered that the students struggled mostly in the areas of question formulation, question omission and interview order and did not manage to improve their skills throughout the three interviews. Our study presents a novel and repeatable pedagogical design, and our findings extend the body of knowledge aimed at...
Bao, T, Damtie, MM, Yu, ZM, Liu, Y, Jin, J, Wu, K, Deng, CX, Wei, W, Wei, XL & Ni, B-J 2019, 'Green Synthesis of Fe3O4@Carbon Filter Media for Simultaneous Phosphate Recovery and Nitrogen Removal from Domestic Wastewater in Biological Aerated Filters', ACS Sustainable Chemistry & Engineering, vol. 7, no. 19, pp. 16698-16709.
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Copyright © 2019 American Chemical Society. Domestic wastewater depth processing and reclamation are essential in the alleviation of global water shortage. In this study, an innovative filter media (i.e., Fe3O4@Carbon filter media [FCM]) was synthesized and subsequently used in a biological aerated filter (BAF) for simultaneous phosphate recovery and nitrogen removal (SPN) from domestic wastewater. The performance of FCM was compared with the commercially available ceramsite (CAC). The results showed that the performance of FCMBAF was better than that of CACBAF; as far as SPN is concerned, the magnetic field of FCMBAF could accelerate the growth rate of biofilm. Moreover, the nitrospira and nirK gene copy numbers of FCMBAF were considerably higher than those of CACBAF. Interestingly, the interconnectivity and uniformity of pores were also suitable for the microdistribution of biofilm, where different aerobic and anaerobic zones of the FCM were formed. This facilitates the microinteraction between the key microorganisms and the filter media that successfully enhanced the nitrogen removal. The phosphate recovery was attained via hydroxyapatite (Ca10(PO4)6(OH)2) formation, which resulted from the reaction between phosphate (PO43-) and FCM. The average effluent concentrations of total organic carbon (TOC), total nitrogen (TN), ammonia nitrogen (NH4+-N), and PO43- were 8.12, 6.18, 0.997, and 0.073 mg/L of FCMBAF, respectively, which were lower than those from the national standard (CODcr ≤ 50 mg L-1, NH4+-N ≤ 5.0 mg L-1, TN ≤ 15 mg L-1, TP ≤ 0.5 mg L-1, GB 18918-2002, first standard). Thus, FCM demonstrated a promising potential for SPN and wastewater recycling of BAF in domestic wastewater treatment.
Baral, P, Rujikiatkamjorn, C, Indraratna, B, Leroueil, S & Yin, J-H 2019, 'Radial Consolidation Analysis Using Delayed Consolidation Approach', Journal of Geotechnical and Geoenvironmental Engineering, vol. 145, no. 10, pp. 04019063-04019063.
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© 2019 American Society of Civil Engineers. The paper offers an analytical solution for radial consolidation that captures isotaches with a strain-rate dependency of preconsolidation pressure. These relationships are obtained based on constant-rate-of-strain (CRS) and long-term consolidation (LTC) tests and then used in the radial consolidation model incorporating the field strain rate, which is generally much lower compared with the typical laboratory environment. In this study, the calculated settlement and associated excess pore-water pressure are obtained using the equivalent preconsolidation pressure from the reference isotache within the (σp′/σp0′)-(ϵv) domain. Moreover, the change in Cα/Cc ratio (i.e., secondary compression index/compression index) with decreasing strain rate is used to calculate the long-term settlement. This method is then validated using various case histories in Australia and Southeast Asia, where excess pore-water pressure is dissipated at a slower rate in relation to the observed settlement.
Barambu, NU, Bilad, MR, Wibisono, Y, Jaafar, J, Mahlia, TMI & Khan, AL 2019, 'Membrane Surface Patterning as a Fouling Mitigation Strategy in Liquid Filtration: A Review', Polymers, vol. 11, no. 10, pp. 1687-1687.
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Membrane fouling is seen as the main culprit that hinders the widespread of membrane application in liquid-based filtration. Therefore, fouling management is key for the successful implementation of membrane processes, and it is done across all magnitudes. For optimum operation, membrane developments and surface modifications have largely been reported, including membrane surface patterning. Membrane surface patterning involves structural modification of the membrane surface to induce secondary flow due to eddies, which mitigate foulant agglomeration and increase the effective surface area for improved permeance and antifouling properties. This paper reviews surface patterning approaches used for fouling mitigation in water and wastewater treatments. The focus is given on the pattern formation methods and their effect on overall process performances.
Barker, RA, Eager, D & Sharwood, LN 2019, 'Ensuring safety in public playgrounds is everybody's business', Medical Journal of Australia, vol. 210, no. 1, pp. 9-9.
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Basnet, S, He, Y, Dutkiewicz, E & Jayawickrama, BA 2019, 'Resource Allocation in Moving and Fixed General Authorized Access Users in Spectrum Access System', IEEE Access, vol. 7, pp. 107863-107873.
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© 2013 IEEE. Spectrum access system (SAS) is a spectrum sharing framework proposed to share the spectrum between the incumbent users and the citizen broadband radio service devices, i.e. Priority access users and general authorized access (GAA) users. In this paper, we propose an interfering angle based method for the joint resource (channel and transmit power) allocation problem to the mobile and fixed GAA users. With mobile GAA users, the set of GAA users that can hear each other will change at different time instants making the resource allocation problem more challenging. The resource allocation of fixed and mobile GAA users is done considering coexistence with priority users, as well as coexistence between mobile and fixed GAA users. For the conflict-free resource allocation to fixed and mobile GAA users, we propose to use the maximum allowed transmit power for the beams of fixed GAA users that lie within the interference range of mobile GAA users. The simulation results show improved capacity from our proposed method while satisfying a predetermined interference constraint.
Bauer, D, Patten, T & Vincze, M 2019, 'VeREFINE: Integrating Object Pose Verification with Physics-guided Iterative Refinement'.
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Accurate and robust object pose estimation for robotics applications requires
verification and refinement steps. In this work, we propose to integrate
hypotheses verification with object pose refinement guided by physics
simulation. This allows the physical plausibility of individual object pose
estimates and the stability of the estimated scene to be considered in a
unified optimization. The proposed method is able to adapt to scenes of
multiple objects and efficiently focuses on refining the most promising object
poses in multi-hypotheses scenarios. We call this integrated approach VeREFINE
and evaluate it on three datasets with varying scene complexity. The generality
of the approach is shown by using three state-of-the-art pose estimators and
three baseline refiners. Results show improvements over all baselines and on
all datasets. Furthermore, our approach is applied in real-world grasping
experiments and outperforms competing methods in terms of grasp success rate.
Code is publicly available at github.com/dornik/verefine.
Bautista, MG, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Dutkiewicz, E 2019, 'Compact Millimeter-Wave Bandpass Filters Using Quasi-Lumped Elements in 0.13-$\mu$ m (Bi)-CMOS Technology for 5G Wireless Systems', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 7, pp. 3064-3073.
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Behera, TM, Mohapatra, SK, Samal, UC, Khan, MS, Daneshmand, M & Gandomi, AH 2019, 'Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application', IEEE Internet of Things Journal, vol. 6, no. 3, pp. 5132-5139.
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© 2014 IEEE. Wireless sensor networks (WSNs) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head (CH) can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. This paper focuses on an efficient CH election scheme that rotates the CH position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy, and an optimum value of CHs to elect the next group of CHs for the network that suits for IoT applications, such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the low energy adaptive clustering hierarchy protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.
Beiranvand Pour, A, Park, Y, Crispini, L, Läufer, A, Kuk Hong, J, Park, T-YS, Zoheir, B, Pradhan, B, Muslim, AM, Hossain, MS & Rahmani, O 2019, 'Mapping Listvenite Occurrences in the Damage Zones of Northern Victoria Land, Antarctica Using ASTER Satellite Remote Sensing Data', Remote Sensing, vol. 11, no. 12, pp. 1408-1408.
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Listvenites normally form during hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represent a key indicator for the occurrence of ore mineralizations in orogenic systems. Hydrothermal/metasomatic alteration mineral assemblages are one of the significant indicators for ore mineralizations in the damage zones of major tectonic boundaries, which can be detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data were used to detect listvenite occurrences and alteration mineral assemblages in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL), Antarctica. Spectral information for detecting alteration mineral assemblages and listvenites were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineralogical assemblages containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were detected in the damage zones of the study area by implementing PCA/ICA fusion to visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate lithological groups were mapped and discriminated using PCA/ICA fusion to thermal infrared (TIR) bands of ASTER. Fraction images of prospective alteration minerals, including goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and possible zones encompassing listvenite occurrences were produced using LSU and CEM algorithms to ASTER VNIR+SWIR spectral bands. Several potential zones for listvenite occurrences were identified, typically in association with mafic metavolcanic rocks (Glasgow Volcanics) in the ...
Belete, GF, Voinov, A, Arto, I, Dhavala, K, Bulavskaya, T, Niamir, L, Moghayer, S & Filatova, T 2019, 'Exploring Low-Carbon Futures: A Web Service Approach to Linking Diverse Climate-Energy-Economy Models', Energies, vol. 12, no. 15, pp. 2880-2880.
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The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs. There is much expectation in climate-energy research that constructing new purposeful models out of existing models used as building blocks can meet particular needs of research and policy analysis. Integration of existing models, however, implies sophisticated coordination of inputs and outputs across different scales, definitions, data and software. This paper presents an online integration platform which links various independent models to enhance their scope and functionality. We illustrate the functionality of this web platform using several simulation models developed as standalone tools for analyzing energy, climate and economy dynamics. The models differ in levels of complexity, assumptions, modeling paradigms and programming languages, and operate at different temporal and spatial scales, from individual to global. To illustrate the integration process and the internal details of our integration framework we link an Integrated Assessment Model (GCAM), a Computable General Equilibrium model (EXIOMOD), and an Agent Based Model (BENCH). This toolkit is generic for similar integrated modeling studies. It still requires extensive pre-integration assessment to identify the ‘appropriate’ models and links between them. After that, using the web service approach we can streamline module coupling, enabling interoperability between different systems and providing open access to information for a wider community of users.
Belotti, Y, Tolomeo, S, Conneely, MJ, Huang, T, McKenna, SJ, Nabi, G & McGloin, D 2019, 'High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells', Scientific Reports, vol. 9, no. 1.
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AbstractWorldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, time-resolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.
Ben, X, Gong, C, Zhang, P, Jia, X, Wu, Q & Meng, W 2019, 'Coupled Patch Alignment for Matching Cross-View Gaits', IEEE Transactions on Image Processing, vol. 28, no. 6, pp. 3142-3157.
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Best, G, Cliff, OM, Patten, T, Mettu, RR & Fitch, R 2019, 'Dec-MCTS: Decentralized planning for multi-robot active perception', The International Journal of Robotics Research, vol. 38, no. 2-3, pp. 316-337.
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We propose a decentralized variant of Monte Carlo tree search (MCTS) that is suitable for a variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimize its own actions by maintaining a probability distribution over plans in the joint-action space. Robots periodically communicate a compressed form of their search trees, which are used to update the joint distribution using a distributed optimization approach inspired by variational methods. Our method admits any objective function defined over robot action sequences, assumes intermittent communication, is anytime, and is suitable for online replanning. Our algorithm features a new MCTS tree expansion policy that is designed for our planning scenario. We extend the theoretical analysis of standard MCTS to provide guarantees for convergence rates to the optimal payoff sequence. We evaluate the performance of our method for generalized team orienteering and online active object recognition using real data, and show that it compares favorably to centralized MCTS even with severely degraded communication. These examples demonstrate the suitability of our algorithm for real-world active perception with multiple robots.
Beydoun, G, Abedin, B, Merigó, JM & Vera, M 2019, 'Twenty Years of Information Systems Frontiers.', Inf. Syst. Frontiers, vol. 21, no. 2, pp. 485-494.
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Information Systems Frontiers is a leading international journal that publishes research at the interface between information systems and information technology. The journal was launched in 1999. In 2019, the journal celebrates the 20th anniversary. Motivated by this event, this paper aims to review this first twenty years of publication record to uncover trends most influential on ISF. The analysis considers various metics including citation structure of the journal, most-cited papers, the most influential authors, institutions and countries, and citing articles. Importantly, the paper presents a thematic analysis of the publications that appeared in ISF in the past 20 years. The thematic analysis is evidenced by two sources of data: First, a bibliometric analysis highlighting core topics within the past 20 years is presented. Second, a semantic analysis of keywords introduced by the authors themselves is applied.
Bhowmick, S, Saha, SC, Qiao, M & Xu, F 2019, 'Transition to a chaotic flow in a V-shaped triangular cavity heated from below', International Journal of Heat and Mass Transfer, vol. 128, pp. 76-86.
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© 2018 Elsevier Ltd Natural convection in a V-shaped cavity heated from below and cooled from top is investigated owing to its extensive presence in industrial systems and in nature such as in a valley. Two dimensional numerical simulation is performed for natural convection in the cavity using a Finite Volume Method. A wide range of Rayleigh numbers of Ra = 100 to 108 for the aspect ratio of A = 0.5 and the Prandtl number of Pr = 0.71 is considered. A set of supercritical bifurcations in a transition to a chaotic flow are described, which include a Pitchfork bifurcation from symmetric to asymmetric state and a Hopf bifurcation from steady to unsteady state. It is found that the Pitchfork bifurcation occurs between Ra = 7.5 × 103 and 7.6 × 103 and the Hopf bifurcation occurs between Ra = 1.5 × 107 and 1.6 × 107. Additionally, a further bifurcation from periodic to chaotic state occurs between Ra = 5 × 107 and 6 × 107. The power spectral density, the phase space trajectory and the largest Lyapunov exponent of unsteady flows in the transition to a chaotic state have been described. Further, heat transfer in the cavity is calculated and the corresponding dependence on the Rayleigh number is discussed and quantified.
Biglari, S, Le, TYL, Tan, RP, Wise, SG, Zambon, A, Codolo, G, De Bernard, M, Warkiani, M, Schindeler, A, Naficy, S, Valtchev, P, Khademhosseini, A & Dehghani, F 2019, 'Simulating Inflammation in a Wound Microenvironment Using a Dermal Wound‐on‐a‐Chip Model', Advanced Healthcare Materials, vol. 8, no. 1, pp. 1801307-1801307.
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Considerable progress has been made in the field of microfluidics to develop complex systems for modeling human skin and dermal wound healing processes. While microfluidic models have attempted to integrate multiple cell types and/or 3D culture systems, to date they have lacked some elements needed to fully represent dermal wound healing. This paper describes a cost-effective, multicellular microfluidic system that mimics the paracrine component of early inflammation close to normal wound healing. Collagen and Matrigel are tested as materials for coating and adhesion of dermal fibroblasts and human umbilical vein endothelial cells (HUVECs). The wound-on-chip model consists of three interconnecting channels and is able to simulate wound inflammation by adding tumor necrosis factor alpha (TNF-α) or by triculturing with macrophages. Both the approaches significantly increase IL-1β, IL-6, IL-8 in the supernatant (p < 0.05), and increases in cytokine levels are attenuated by cotreatment with an anti-inflammatory agent, Dexamethasone. Incorporation of M1 and M2 macrophages cocultured with fibroblasts and HUVECs leads to a stimulation of cytokine production as well as vascular structure formation, particularly with M2 macrophages. In summary, this wound-on-chip system can be used to model the paracrine component of the early inflammatory phase of wound healing and has the potential for the screening of anti-inflammatory compounds.
BINSAWAD, M, SOHAIB, O & HAWRYSZKIEWYCZ, I 2019, 'FACTORS IMPACTING TECHNOLOGY BUSINESS INCUBATOR PERFORMANCE', International Journal of Innovation Management, vol. 23, no. 01, pp. 1950007-1950007.
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Technology business incubators support economic growth by developing innovative technologies. However, assessing the performance of technology business incubators in Saudi Arabia has not been well recognised. This study provides a conceptual framework for assessing technology business incubators based on knowledge sharing practices and sharing, diffusion of innovation and individual creativity. Partial least squares structural equation modelling, such as (PLS-SEM) path modelling was used to test the model. The results provide empirical insights about the performance of technology business incubators. The findings show knowledge donation and collection has positive effects on technology business incubator. The importance–performance map analysis shows additional findings and conclusions for managerial actions.
Blamires, SJ, Cerexhe, G, White, TE, Herberstein, ME & Kasumovic, MM 2019, 'Spider silk colour covaries with thermal properties but not protein structure', Journal of The Royal Society Interface, vol. 16, no. 156, pp. 20190199-20190199.
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Understanding how and why animal secretions vary in property has important biomimetic implications as desirable properties might covary. Spider major ampullate (MA) silk, for instance, is a secretion earmarked for biomimetic applications, but many of its properties vary among and between species across environments. Here, we tested the hypothesis that MA silk colour, protein structure and thermal properties covary when protein uptake is manipulated in the spider
Trichonephila plumipes
. We collected silk from adult female spiders maintained on a protein-fed or protein-deprived diet. Based on spectrophotometric quantifications, we classified half the silks as ‘bee visible’ and the other half ‘bee invisible’. Wide angle X-ray diffraction and differential scanning calorimetry were then used to assess the silk's protein structure and thermal properties, respectively. We found that although protein structures and thermal properties varied across our treatments only the thermal properties covaried with colour. This ultimately suggests that protein structure alone is not responsible for MA silk thermal properties, nor does it affect silk colours. We speculate that similar ecological factors act on silk colour and thermal properties, which should be uncovered to inform biomimetic programmes.
Blanco-Mesa, F, León-Castro, E & Merigó, JM 2019, 'A bibliometric analysis of aggregation operators', Applied Soft Computing, vol. 81, pp. 105488-105488.
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© 2019 Elsevier B.V. Aggregation operators consist of mathematical functions that enable the combining and processing of different types of information. The aim of this work is to present the main contributions in this field by a bibliometric review approach. The paper employs an extensive range of bibliometric indicators using the Web of Science (WoS) Core Collection and Scopus datasets. The work considers leading journals, articles, authors, institutions countries and patterns. This paper highlights that Xu is the most productive author and Yager is the most influential author in the field. Likewise, China is leading the field with many new researchers who have entered the field in recent years. This discipline has been strengthening to create a unique theory and will continue to expand with many new theoretical developments and applications.
Blanco‐Mesa, F, León‐Castro, E, Merigó, JM & Herrera‐Viedma, E 2019, 'Variances with Bonferroni means and ordered weighted averages', International Journal of Intelligent Systems, vol. 34, no. 11, pp. 3020-3045.
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© 2019 Wiley Periodicals, Inc. The variance is a statistical measure frequently used for analysis of dispersion in the data. This paper presents new types of variances that use Bonferroni means and ordered weighted averages in the aggregation process of the variance. The main advantage of this approach is that we can underestimate or overestimate the variance according to the attitudinal character of the decision-maker. The work considers several particular cases including the minimum and the maximum variance and presents some numerical examples. The article also develops some extensions and generalizations by using induced aggregation operators and generalized and quasi-arithmetic means. These approaches provide a more general framework that can consider a lot of other particular cases and a complex attitudinal character that could be affected by a wide range of variables. The study ends with an application of the new approach in a business decision-making problem regarding strategic analysis in enterprise risk management.
Blanco-Mesa, F, León-Castro, E, Merigó, JM & Xu, Z 2019, 'Bonferroni means with induced ordered weighted average operators', International Journal of Intelligent Systems, vol. 34, no. 1, pp. 3-23.
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© 2018 Wiley Periodicals, Inc. The induced ordered weighted average is an averaging aggregation operator that provides a parameterized family of aggregation operators between the minimum and the maximum. This paper presents some new generalizations by using Bonferroni means (BM) forming induced BM. The main advantage of this approach is the possibility of reordering the results according to complex ranking processes based on order-inducing variables. The work also presents some additional extensions by using the weighted ordered weighted average, immediate weights, and hybrid averages. Some further generalizations with generalized and quasi-arithmetic means are also developed to consider a wide range of particular cases including quadratic and geometric aggregations. The article also considers the applicability of the new approach in-group decision-making developing an application in sales forecasting.
Bliuc, D, Tran, T, Geel, T, Adachi, JD, Berger, C, den Bergh, J, Eisman, JA, Geusens, P, Goltzman, D, Hanley, DA, Josse, R, Kaiser, S, Kovacs, CS, Langsetmo, L, Prior, JC, Nguyen, TV & Center, JR 2019, 'Reduced Bone Loss Is Associated With Reduced Mortality Risk in Subjects Exposed to Nitrogen Bisphosphonates: A Mediation Analysis', Journal of Bone and Mineral Research, vol. 34, no. 11, pp. 2001-2011.
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Bliuc, D, Tran, T, van Geel, T, Adachi, JD, Berger, C, van den Bergh, J, Eisman, JA, Geusens, P, Goltzman, D, Hanley, DA, Josse, RG, Kaiser, S, Kovacs, CS, Langsetmo, L, Prior, JC, Nguyen, TV & Center, JR 2019, 'Mortality risk reduction differs according to bisphosphonate class: a 15-year observational study', Osteoporosis International, vol. 30, no. 4, pp. 817-828.
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In this prospective cohort of 6120 participants aged 50+, nitrogen-bisphosphonates but not non-nitrogen bisphosphonates were associated with a significant 34% mortality risk reduction compared to non-treated propensity score matched controls. These findings open new avenues for research into mechanistic pathways. INTRODUCTION:Emerging evidence suggests that bisphosphonates (BP), first-line treatment of osteoporosis, are associated with reduced risks for all-cause mortality. This study aimed to determine the association between different BP types and mortality risk in participants with or without a fracture. METHODS:A prospective cohort study of users of different BPs matched to non-users by propensity score (age, gender, co-morbidities, fragility fracture status) and time to starting the BP medication from the population-based Canadian Multicentre Osteoporosis Study from nine Canadian centres followed from 1995 to 2013. Mortality risk for bisphosphonate users vs matched non-users was assessed using pairwise multivariable Cox proportional hazards models. RESULTS:There were 2048 women and 308 men on BP and 1970 women and 1794 men who did not receive medication for osteoporosis. The relationship between BP and mortality risk was explored in three separate 1:1 propensity score-matched cohorts of BP users and no treatment (etidronate, n = 599, alendronate, n = 498, and risedronate n = 213). Nitrogen BP (n-BP) (alendronate and risedronate) was associated with lower mortality risks [pairwise HR, 0.66 (95% CI, 0.48-0.91)] while the less potent non-n-BP, etidronate, was not [pairwise HR: 0.89 (95% CI, 0.66-1.20)]. A direct comparison between n-BP and etidronate (n = 340 pairs) also suggested a better survival for n-BP [paired HR, 0.47 (95%CI, (95% CI, 031-0.70)] for n-BP vs. etidronate]. CONCLUSION:Compared to no treatment, nitrogen but not non-nitrogen bisphosphonates appear to be associated with better survival.
Bobba, SS & Agrawal, A 2019, 'Author Correction: Ultra-broad Mid-IR Supercontinuum Generation in Single, Bi and Tri Layer Graphene Nano-Plasmonic waveguides pumping at Low Input Peak Powers', Scientific Reports, vol. 9, no. 1.
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A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
Braytee, A, Liu, W, Anaissi, A & Kennedy, PJ 2019, 'Correlated Multi-label Classification with Incomplete Label Space and Class Imbalance', ACM Transactions on Intelligent Systems and Technology, vol. 10, no. 5, pp. 1-26.
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Multi-label classification is defined as the problem of identifying the multiple labels or categories of new observations based on labeled training data. Multi-labeled data has several challenges, including class imbalance, label correlation, incomplete multi-label matrices, and noisy and irrelevant features. In this article, we propose an integrated multi-label classification approach with incomplete label space and class imbalance (ML-CIB) for simultaneously training the multi-label classification model and addressing the aforementioned challenges. The model learns a new label matrix and captures new label correlations, because it is difficult to find a complete label vector for each instance in real-world data. We also propose a label regularization to handle the imbalanced multi-labeled issue in the new label, and
l
1
regularization norm is incorporated in the objective function to select the relevant sparse features. A multi-label feature selection (ML-CIB-FS) method is presented as a variant of the proposed ML-CIB to show the efficacy of the proposed method in selecting the relevant features. ML-CIB is formulated as a constrained objective function. We use the accelerated proximal gradient method to solve the proposed optimisation problem. Last, extensive experiments are conducted on 19 regular-scale and large-scale imbalanced multi-labeled datasets. The promising results show that our method significantly outperforms the state-of-the-art.
Bródka, P, Musial, K & Jankowski, J 2019, 'Interacting spreading processes in multilayer networks', IEEE Access, volume 8, 2020, vol. 8, pp. 10316-10341.
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The world of network science is fascinating and filled with complex phenomena
that we aspire to understand. One of them is the dynamics of spreading
processes over complex networked structures. Building the knowledge-base in the
field where we can face more than one spreading process propagating over a
network that has more than one layer is a challenging task, as the complexity
comes both from the environment in which the spread happens and from
characteristics and interplay of spreads' propagation. As this
cross-disciplinary field bringing together computer science, network science,
biology and physics has rapidly grown over the last decade, there is a need to
comprehensively review the current state-of-the-art and offer to the research
community a roadmap that helps to organise the future research in this area.
Thus, this survey is a first attempt to present the current landscape of the
multi-processes spread over multilayer networks and to suggest the potential
ways forward.
Brown, P, Tan, A-C, El-Esawi, MA, Liehr, T, Blanck, O, Gladue, DP, Almeida, GMF, Cernava, T, Sorzano, CO, Yeung, AWK, Engel, MS, Chandrasekaran, AR, Muth, T, Staege, MS, Daulatabad, SV, Widera, D, Zhang, J, Meule, A, Honjo, K, Pourret, O, Yin, C-C, Zhang, Z, Cascella, M, Flegel, WA, Goodyear, CS, van Raaij, MJ, Bukowy-Bieryllo, Z, Campana, LG, Kurniawan, NA, Lalaouna, D, Hüttner, FJ, Ammerman, BA, Ehret, F, Cobine, PA, Tan, E-C, Han, H, Xia, W, McCrum, C, Dings, RPM, Marinello, F, Nilsson, H, Nixon, B, Voskarides, K, Yang, L, Costa, VD, Bengtsson-Palme, J, Bradshaw, W, Grimm, DG, Kumar, N, Martis, E, Prieto, D, Sabnis, SC, Amer, SEDR, Liew, AWC, Perco, P, Rahimi, F, Riva, G, Zhang, C, Devkota, HP, Ogami, K, Basharat, Z, Fierz, W, Siebers, R, Tan, K-H, Boehme, KA, Brenneisen, P, Brown, JAL, Dalrymple, BP, Harvey, DJ, Ng, G, Werten, S, Bleackley, M, Dai, Z, Dhariwal, R, Gelfer, Y, Hartmann, MD, Miotla, P, Tamaian, R, Govender, P, Gurney-Champion, OJ, Kauppila, JH, Zhang, X, Echeverría, N, Subhash, S, Sallmon, H, Tofani, M, Bae, T, Bosch, O, Cuív, PO, Danchin, A, Diouf, B, Eerola, T, Evangelou, E, Filipp, FV, Klump, H, Kurgan, L, Smith, SS, Terrier, O, Tuttle, N, Ascher, DB, Janga, SC, Schulte, LN, Becker, D, Browngardt, C, Bush, SJ, Gaullier, G, Ide, K, Meseko, C, Werner, GDA, Zaucha, J, Al-Farha, AA, Greenwald, NF, Popoola, SI, Rahman, MS, Xu, J, Yang, SY, Hiroi, N, Alper, OM, Baker, CI, Bitzer, M, Chacko, G, Debrabant, B, Dixon, R, Forano, E, Gilliham, M, Kelly, S, Klempnauer, K-H, Lidbury, BA, Lin, MZ, Lynch, I, Ma, W, Maibach, EW, Mather, DE, Nandakumar, KS, Ohgami, RS, Parchi, P, Tressoldi, P, Xue, Y, Armitage, C, Barraud, P, Chatzitheochari, S, Coelho, LP, Diao, J, Doxey, AC, Gobet, A, Hu, P, Kaiser, S, Mitchell, KM, Salama, MF, Shabalin, IG, Song, H, Stevanovic, D, Yadollahpour, A, Zeng, E, Zinke, K, Alimba, CG, Beyene, TJ, Cao, Z, Chan, SS, Gatchell, M, Kleppe, A, Piotrowski, M, Torga, G, Woldesemayat, AA, Cosacak, MI, Haston, S, Ross, SA, Williams, R, Wong, A, Abramowitz, MK, Effiong, A, Lee, S, Abid, MB, Agarabi, C, Alaux, C, Albrecht, DR, Atkins, GJ, Beck, CR, Bonvin, AMJJ, Bourke, E, Brand, T, Braun, RJ, Bull, JA, Cardoso, P, Carter, D, Delahay, RM, Ducommun, B, Duijf, PHG, Epp, T, Eskelinen, E-L, Fallah, M, Farber, DB, Fernandez-Triana, J, Feyerabend, F, Florio, T, Friebe, M, Furuta, S, Gabrielsen, M, Gruber, J, Grybos, M, Han, Q & et al. 2019, 'Large expert-curated database for benchmarking document similarity detection in biomedical literature search', Database, vol. 2019, pp. 1-66.
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Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
Bryce, T, Far, H & Gardner, A 2019, 'Barriers to career advancement for female engineers in Australia’s civil construction industry and recommended solutions', Australian Journal of Civil Engineering, vol. 17, no. 1, pp. 1-10.
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This study explores the challenges that have emerged from the outdated and inflexible workplace culture of the civil construction industry, and how it is affecting female engineers and women in other functional site roles. The study primarily explores issues such as the strong culture of long work hours, the perception of staff who pursue work-life balance, and the perception of part time and flexible working options within the industry. The study was conducted over three phases where members of the industry answered questionnaires on the workplace issues listed above. The first phase aimed to document a female perspective on the construction workplace culture while the second phase focused on the perceptions of the same respondents regarding the industry’s attitude to work-life balance and whether any of the aspects of workplace culture has discouraged them from staying in the industry. The final phase included men and women in management and employer roles to determine their views on part time and flexible working options within the industry. The results of the study are presented and discussed before recommendations are offered for contractor organisations, their employers and staff. The recommendations have been addressed in a way that a gradual culture change can be accepted and acted on throughout the entire workplace.
Bui, HH, Ha, NH, Nguyen, TND, Nguyen, AT, Pham, TTH, Kandasamy, J & Nguyen, TV 2019, 'Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam', Ecohydrology & Hydrobiology, vol. 19, no. 2, pp. 210-223.
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Bui, Moayedi, Kalantar, Osouli, Gör, Pradhan, Nguyen & Rashid 2019, 'Harris Hawks Optimization: A Novel Swarm Intelligence Technique for Spatial Assessment of Landslide Susceptibility', Sensors, vol. 19, no. 16, pp. 3590-3590.
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In this research, the novel metaheuristic algorithm Harris hawks optimization (HHO) is applied to landslide susceptibility analysis in Western Iran. To this end, the HHO is synthesized with an artificial neural network (ANN) to optimize its performance. A spatial database comprising 208 historical landslides, as well as 14 landslide conditioning factors—elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), topographic wetness index (TWI), and rainfall—is prepared to develop the ANN and HHO–ANN predictive tools. Mean square error and mean absolute error criteria are defined to measure the performance error of the models, and area under the receiving operating characteristic curve (AUROC) is used to evaluate the accuracy of the generated susceptibility maps. The findings showed that the HHO algorithm effectively improved the performance of ANN in both recognizing (AUROCANN = 0.731 and AUROCHHO–ANN = 0.777) and predicting (AUROCANN = 0.720 and AUROCHHO–ANN = 0.773) the landslide pattern.
Buscemi, F, Sutter, D & Tomamichel, M 2019, 'An information-theoretic treatment of quantum dichotomies', Quantum, vol. 3, p. 209.
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Given two pairs of quantum states, we want to decide if there exists a
quantum channel that transforms one pair into the other. The theory of quantum
statistical comparison and quantum relative majorization provides necessary and
sufficient conditions for such a transformation to exist, but such conditions
are typically difficult to check in practice. Here, by building upon work by
Matsumoto, we relax the problem by allowing for small errors in one of the
transformations. In this way, a simple sufficient condition can be formulated
in terms of one-shot relative entropies of the two pairs. In the asymptotic
setting where we consider sequences of state pairs, under some mild convergence
conditions, this implies that the quantum relative entropy is the only relevant
quantity deciding when a pairwise state transformation is possible. More
precisely, if the relative entropy of the initial state pair is strictly larger
compared to the relative entropy of the target state pair, then a
transformation with exponentially vanishing error is possible. On the other
hand, if the relative entropy of the target state is strictly larger, then any
such transformation will have an error converging exponentially to one. As an
immediate consequence, we show that the rate at which pairs of states can be
transformed into each other is given by the ratio of their relative entropies.
We discuss applications to the resource theories of athermality and coherence.
Buys, NJ, Selander, J & Sun, J 2019, 'Employee experience of workplace supervisor contact and support during long-term sickness absence', Disability and Rehabilitation, vol. 41, no. 7, pp. 808-814.
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Bykerk, L, Quin, P & Liu, D 2019, 'A Method for Selecting the Next Best Angle-of-Approach for Touch-Based Identification of Beam Members in Truss Structures', IEEE Sensors Journal, vol. 19, no. 10, pp. 3939-3949.
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© 2001-2012 IEEE. A robot designed to climb truss structures such as power transmission towers is expected to have an adequate tactile sensing in the grippers to identify a structural beam member and its properties. Depending on how a gripper grasps a structural member, defined as the Angle-of-Approach (AoA), the extracted tactile data can result in erroneous identifications due to the similarities in beam cross-sectional shapes and sizes. In these cases, further grasps at favorable Angles-of-Approach (AoAs) are required to correctly identify the beam member and its properties. This paper presents an information-based method which uses tactile data to determine the next best AoA for the identification of beam members in truss structures. The method is used in conjunction with a state estimate of beam shape, dimension, and AoA calculated by a Random Forest classifier. The method is verified through simulation by using the data collected using a soft gripper retrofitted with simple tactile sensors. The results show that this method can correctly identify a structural beam member and its properties with a small number of grasps (typically fewer than 4). This method can be applied to other adaptive robotic gripper designs fitted with suitable tactile sensors, regardless of the number of sensors used and their layout.
Byrne, J, Boutros, R, Catchpoole, D, Collins, K, Cross, S, Downie, P, Drinkwater, C, Fletcher, J, Gottardo, N, Hunter, S, Kirby, M, Ludlow, L, Macnish, M, Maybury, M, Moore, A, Morrin, H, Purdy, S, Revesz, T, Saffery, R, Strong, R, Trahair, T, Wood, A & Byrne, J 2019, 'The Australian and New Zealand Children's Haematology/Oncology Group Biobanking Network', Biopreservation and Biobanking, vol. 17, no. 2, pp. 95-97.
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Cagno, E, Moschetta, D & Trianni, A 2019, 'Only non-energy benefits from the adoption of energy efficiency measures? A novel framework', Journal of Cleaner Production, vol. 212, pp. 1319-1333.
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© 2018 Elsevier Ltd Industrial energy efficiency has been widely recognized as a major contributor to the reduction of greenhouse gases emissions and improvement of industrial competitiveness. Nevertheless, a broad set of studies have pointed out the existence of barriers limiting the adoption of promising Energy Efficiency Measures (EEMs). Recently, scholars have shown the relevance of the so-called “non-energy benefits” (NEBs) coming from the adoption of EEMs for overcoming those barriers. Still, the existence of such benefits has been pointed out from specific studies and manuals for practitioners, but an overall framework describing them in terms of savings and benefits, as well as technical and management implications, is missing yet. Moreover, a considerable part of the scholars and of the practitioners just focuses on the identification and definition of the positive benefits deriving from these measures after they have been completely adopted, thus neglecting to describe the full set of both positive and negative effects occurring also during the implementation phase. Thus, starting from a literature review of scientific as well as practitioners’ studies, we have proposed a novel framework and characterization of the relevant items to be considered by an industrial decision-maker when deciding whether to adopt an EEM considering both the implementation and service phases. Hence, by taking this perspective, we have tested and validated the framework and the characterization in a two-step process: firstly, considering a set of EEMs well diffused and adopted in industry; secondly, investigating benefits and losses in ad-hoc selected manufacturing companies. Finally, considerations and implications are drawn from the preliminary validation and suggestion for further research are proposed, for both industrial decision-making as well as policy-making purposes.
Cagno, E, Neri, A, Howard, M, Brenna, G & Trianni, A 2019, 'Industrial sustainability performance measurement systems: A novel framework', Journal of Cleaner Production, vol. 230, pp. 1354-1375.
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© 2019 Elsevier Ltd Improved sustainability of industrial activities and measurement of its performance are becoming prime topics of discussion among policy-makers and industrial decision-makers. The current literature proposes a number of performance measurement systems and related indicators, but mainly lacks a real capability to address all sustainability pillars and their intersections, as well as scalability to firms of different sizes, availability of internal resources, and maturity over sustainability issues, suggesting that further research is needed in this area. Building on the literature, our work develops a new framework for the evaluation of industrial sustainability performance, proposing three different Industrial Sustainability Performance Measurement Systems (ISPMSs), with a decreasing number of indicators suitable in different contexts of application. In the framework, selection mechanisms have been conceived and used to reduce the number of indicators considered, while still guaranteeing complete and adequate coverage of all sustainability pillars, as well as their intersections. The framework has been tested through semi-structured case studies in heterogeneous Northern Italian manufacturing firms. The preliminary results are sound as the different ISPMSs proved to be complete, useful, and easy to use. The proposed ISPMSs provide industrial decision-makers with a scalable framework applicable in different contexts, allowing benchmarking and development of specific implementation strategies for increased sustainability, and provide policy-makers with a framework to develop a more effective regulatory policy, better understanding how sustainability performance can be addressed in an integrated manner across industrial firms.
Cai, Z, Yang, Y, Tang, X, Li, Z, Lu, D & Liu, Y 2019, 'Ultralow Phase-Noise Differential Oscillator Using Quarter Stepped-Impedance Resonator', IEEE Microwave and Wireless Components Letters, vol. 29, no. 12, pp. 806-809.
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© 2019 IEEE. In this letter, an ultralow phase-noise differential oscillator is proposed using a balanced feedback filter based on quarter stepped-impedance resonators (QSIRs). Phase-noise performance of the designed oscillators can be significantly improved by taking advantage of high peak group delay, improved stopband suppression, and differential configuration of the proposed feedback filter. To verify the hypothesis and compare the phase-noise performance among single-ended and differential oscillators, both the prototypes are designed, fabricated, and measured. The measured results show that the designed single-ended and differential oscillators are operating at 1.953 GHz. The differential oscillator shows not only a good balanced output power of 8.29 dBm with a measured high suppression of 40.07 dB on the second harmonic but also a superior low phase-noise performance of −130.19 dBc/Hz at a frequency offset of 100 kHz. To the best of our knowledge, this is the best phase-noise performance among the state-of-the-art works designed on planar hybrid integrated circuits at a similar frequency range.
Cancino, CA, Amirbagheri, K, Merigó, JM & Dessouky, Y 2019, 'A bibliometric analysis of supply chain analytical techniques published in Computers & Industrial Engineering', Computers & Industrial Engineering, vol. 137, pp. 106015-106015.
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© 2019 Elsevier Ltd Computers & Industrial Engineering (CAIE) is a leading international journal that publishes manuscripts in the field of supply chain. Due to the recent advances of different analytical techniques applied in order to address supply chain related problems, the aim of this work is to study CAIE publications with a focus on the supply chain using a bibliometric approach that can identify the leading trends in this area by analysing the most significant papers, keywords, authors, institutions and countries. The work also develops a graphical mapping of the bibliographic material by using the visualization of similarities (VOS) viewer software. With this software, the study analyses bibliographic coupling, co-occurrence of author keywords and how the journal is connected with other journals through co-citation analysis. The results indicate that Computers and Industrial Engineering has the fourth highest publications in this area among leading journals that publish in Supply Chain, and China and Iran are the leading publishing countries while Taiwan and Singapore have the highest publications per capita. Finally, supply chain optimization modelling received the highest number of publications in the study.
Canning, J 2019, 'Optical hoovering on plasmonic rinks', MRS Communications, vol. 9, no. 3, pp. 1072-1078.
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© The Author(s) 2019. Excitation of surface waves on conducting materials provides a near resistance-free interface capable of a material glissade either by plasmon forces or by optical beam tractors. Analogous to an ice hockey rink, as proof-of-principle plasmon-assisted optical traction, or hoovering, of water drops on a gold surface is demonstrated. Changes in the contact angle provide a novel, low-cost nanoscale method of quantifying observable and potentially tunable changes. Variability in thresholds and movement, including jumps, is observed and can be explained by the presence of significant roughness, measured by scanning electron microscopy, with water tension. The demonstration opens a path to directly integrate various optical and plasmonic traction technologies. Implications of the phenomena and ways of improving transport and potential applications spanning configurable microfluidics, antennas, tunable lenses, diagnostics, sensing, and active Kerr and other devices are discussed.
Cao, C, Huang, Y, Yang, Y, Wang, L, Wang, Z & Tan, T 2019, 'Feedback Convolutional Neural Network for Visual Localization and Segmentation', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 7, pp. 1627-1640.
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Cao, L 2019, 'Data Science: Profession and Education', IEEE Intelligent Systems, vol. 34, no. 5, pp. 35-44.
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Cao, X, Qiu, B & Xu, G 2019, 'BorderShift: toward optimal MeanShift vector for cluster boundary detection in high-dimensional data', Pattern Analysis and Applications, vol. 22, no. 3, pp. 1015-1027.
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© 2018 Springer-Verlag London Ltd., part of Springer Nature We present a cluster boundary detection scheme that exploits MeanShift and Parzen window in high-dimensional space. To reduce the noises interference in Parzen window density estimation process, the kNN window is introduced to replace the sliding window with fixed size firstly. Then, we take the density of sample as the weight of its drift vector to further improve the stability of MeanShift vector which can be utilized to separate boundary points from core points, noise points, isolated points according to the vector models in multi-density data sets. Under such circumstance, our proposed BorderShift algorithm doesn’t need multi-iteration to get the optimal detection result. Instead, the developed Shift value of each data point helps to obtain it in a liner way. Experimental results on both synthetic and real data sets demonstrate that the F-measure evaluation of BorderShift is higher than that of other algorithms.
Cao, X, Qiu, B, Li, X, Shi, Z, Xu, G & Xu, J 2019, 'Multidimensional Balance-Based Cluster Boundary Detection for High-Dimensional Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 6, pp. 1867-1880.
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IEEE The balance of neighborhood space around a central point is an important concept in cluster analysis. It can be used to effectively detect cluster boundary objects. The existing neighborhood analysis methods focus on the distribution of data, i.e., analyzing the characteristic of the neighborhood space from a single perspective, and could not obtain rich data characteristics. In this paper, we analyze the high-dimensional neighborhood space from multiple perspectives. By simulating each dimension of a data point's k nearest neighbors space (kNNs) as a lever, we apply the lever principle to compute the balance fulcrum of each dimension after proving its inevitability and uniqueness. Then, we model the distance between the projected coordinate of the data point and the balance fulcrum on each dimension and construct the DHBlan coefficient to measure the balance of the neighborhood space. Based on this theoretical model, we propose a simple yet effective cluster boundary detection algorithm called Lever. Experiments on both low- and high-dimensional data sets validate the effectiveness and efficiency of our proposed algorithm.
Cao, Y, Cao, Y, Wen, S, Huang, T & Zeng, Z 2019, 'Passivity analysis of delayed reaction–diffusion memristor-based neural networks', Neural Networks, vol. 109, pp. 159-167.
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Cao, Y, Wang, S, Guo, Z, Huang, T & Wen, S 2019, 'Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control', Neural Networks, vol. 119, pp. 178-189.
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© 2019 Elsevier Ltd In this paper, we investigate the synchronization problem on delayed memristive neural networks (MNNs) with leakage delay and parameters mismatch via event-triggered control. We divide MNNs with parameters mismatch into two categories for discussion. One is state-dependent and can achieve synchronization by designing a suitable controller. A novel Lyapunov functional is constructed to analyze the synchronization problem. Moreover, the triggering conditions are independent from the delay boundaries and can be static or dynamic. Another category of parameters mismatch is structure-dependent and can only achieve quasi-synchronization by appropriate controller. By using matrix measure method and generalized Halanay inequality, a quasi-synchronization criterion is established. The controllers in this paper are discrete state-dependent and can be updated under the event-based triggering condition, which is more simpler than the previous results. In the end of our paper, two illustrative examples are given to support our results.
Cao, Z, Chuang, C-H, King, J-K & Lin, C-T 2019, 'Multi-channel EEG recordings during a sustained-attention driving task', Scientific Data, vol. 6, no. 1.
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AbstractWe describe driver behaviour and brain dynamics acquired from a 90-minute sustained-attention task in an immersive driving simulator. The data included 62 sessions of 32-channel electroencephalography (EEG) data for 27 subjects driving on a four-lane highway who were instructed to keep the car cruising in the centre of the lane. Lane-departure events were randomly induced to cause the car to drift from the original cruising lane towards the left or right lane. A complete trial included events with deviation onset, response onset, and response offset. The next trial, in which the subject was instructed to drive back to the original cruising lane, began 5–10 seconds after finishing the previous trial. We believe that this dataset will lead to the development of novel neural processing methodology that can be used to index brain cortical dynamics and detect driving fatigue and drowsiness. This publicly available dataset will be beneficial to the neuroscience and brain-computer interface communities.
Cao, Z, Lin, C-T, Ding, W, Chen, M-H, Li, C-T & Su, T-P 2019, 'Identifying Ketamine Responses in Treatment-Resistant Depression Using a Wearable Forehead EEG', IEEE Transactions on Biomedical Engineering, vol. 66, no. 6, pp. 1668-1679.
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IEEE This study explores the responses to ketamine in patients with treatment-resistant depression (TRD) using a wearable forehead electroencephalography (EEG) device. We recruited 55 outpatients with TRD who were randomized into three approximately equal- sized groups (A: 0.5 mg/kg ketamine; B: 0.2 mg/kg ketamine; and C: normal saline) under double-blind conditions. The ketamine responses were measured by EEG signals and Hamilton Depression Rating Scale (HDRS) scores. At baseline, responders showed a significantly weaker EEG theta power than did non- responders (p < 0.05). Responders exhibited a higher EEG alpha power but lower EEG alpha asymmetry and theta cordance at post-treatment than at baseline (p < 0.05). Furthermore, our baseline EEG predictor classified responders and non-responders with 81.3 $\pm$ 9.5% accuracy, 82.1 $\pm$ 8.6% sensitivity and 91.9 $\pm$ 7.4% specificity. In conclusion, the rapid antidepressant effects of mixed doses of ketamine are associated with prefrontal EEG power, asymmetry and cordance at baseline and early post-treatment changes. The prefrontal EEG patterns at baseline may account for recognizing ketamine effects in advance. Our randomized, double- blind, placebo-controlled study provides information regarding clinical impacts on the potential targets underlying baseline identification and early changes from the effects of ketamine in patients with TRD.
Castel, A, François, R, Santisi d’Avila, MP & Jenkins, D 2019, 'New service limit state criteria for reinforced concrete in chloride environments', Corrosion Reviews, vol. 37, no. 1, pp. 21-29.
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Abstract
In chloride environments, reinforcement stress limits, intended to control flexural cracking, are one of the most important requirements for service limit state (SLS) design. However, concrete damage at the steel-concrete interface between bending cracks, so called cover-controlled cracking, is always correlated to areas of severe steel reinforcement corrosion. Based on the assumption that cover-controlled cracking should be limited, a model has been developed to provide alternative reinforcement stress limits in marine exposure conditions such as concrete in sea water, including permanently submerged, spray zone and tidal/splash zone, as well as coastal constructions located within 1 km of the shoreline. In this paper, the new reinforcement stress limitation is compared to the Australian Standards AS3600 concrete building code and AS5100.5 concrete bridge code provisions. Analysis shows that the new model is very sensitive to the reinforcement percentage of the cross-section. As a result, the existing AS3600 and AS5100.5 code provisions are more conservative than the new limitation for lightly to normally reinforced concrete cross-section. In this case, crack width control governs the SLS design. However, for normally to heavily reinforced concrete cross-section, the new model provides more conservative results suggesting that cover-controlled cracking governs the SLS design.
Castillo, EHC, Thomas, N, Al-Ketan, O, Rowshan, R, Abu Al-Rub, RK, Nghiem, LD, Vigneswaran, S, Arafat, HA & Naidu, G 2019, '3D printed spacers for organic fouling mitigation in membrane distillation', Journal of Membrane Science, vol. 581, pp. 331-343.
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Catchpoole, DR, Parry-Jones, A & Kozlakidis, Z 2019, 'ISBER's Global Outlook: A Summary of Recent International Activities', Biopreservation and Biobanking, vol. 17, no. 1, pp. 91-92.
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Cavillon, M, Lancry, M, Poumellec, B, Wang, Y, Canning, J, Cook, K, Hawkins, T, Dragic, P & Ballato, J 2019, 'Overview of high temperature fibre Bragg gratings and potential improvement using highly doped aluminosilicate glass optical fibres', Journal of Physics: Photonics, vol. 1, no. 4, pp. 042001-042001.
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Abstract
In this paper, various types of high temperature fibre Bragg gratings (FBGs) are reviewed, including recent results and advancements in the field. The main motivation of this review is to highlight the potential of fabricating thermally stable refractive index contrasts using femtosecond (fs) near-infrared radiation in fibres fabricated with non-conventional techniques, such as the molten core method. As a demonstration of this, an yttrium aluminosilicate (YAS) core and pure silica cladding glass optical fibre is fabricated and investigated after being irradiated by an fs laser within the Type II regime. The familiar formation of nanogratings inside both core and cladding regions are identified and studied using birefringence measurements and scanning electron microscopy. The thermal stability of the Type II modifications is then investigated through isochronal annealing experiments (up to T = 1100 °C; time steps, Δt = 30 min). For the YAS core composition, the measured birefringence does not decrease when tested up to 1000 °C, while for the SiO2 cladding under the same conditions, its value decreased by ∼30%. These results suggest that inscription of such ‘Type II fs-IR’ modifications in YAS fibres could be employed to make FBGs with high thermal stability. This opens the door toward the fabrication of a new range of ‘FBG host fibres’ suitable for ultra-high temperature operation.
Chacon, A, Guatelli, S, Rutherford, H, Bolst, D, Mohammadi, A, Ahmed, A, Nitta, M, Nishikido, F, Iwao, Y, Tashima, H, Yoshida, E, Akamatsu, G, Takyu, S, Kitagawa, A, Hofmann, T, Pinto, M, Franklin, DR, Parodi, K, Yamaya, T, Rosenfeld, A & Safavi-Naeini, M 2019, 'Comparative study of alternative Geant4 hadronic ion inelastic physics models for prediction of positron-emitting radionuclide production in carbon and oxygen ion therapy', Physics in Medicine & Biology, vol. 64, no. 15, pp. 155014-155014.
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Chacon, A, Safavi-Naeini, M, Bolst, D, Guatelli, S, Franklin, DR, Iwao, Y, Akamatsu, G, Tashima, H, Yoshida, E, Nishikido, F, Kitagawa, A, Mohammadi, A, Gregoire, M-C, Yamaya, T & Rosenfeld, AB 2019, 'Monte Carlo investigation of the characteristics of radioactive beams for heavy ion therapy', Scientific Reports, vol. 9, no. 1.
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AbstractThis work presents a simulation study evaluating relative biological effectiveness at 10% survival fraction (RBE10) of several different positron-emitting radionuclides in heavy ion treatment systems, and comparing these to the RBE10s of their non-radioactive counterparts. RBE10 is evaluated as a function of depth for three positron-emitting radioactive ion beams (10C, 11C and 15O) and two stable ion beams (12C and 16O) using the modified microdosimetric kinetic model (MKM) in a heterogeneous skull phantom subject to a rectangular 50 mm × 50 mm × 60 mm spread out Bragg peak. We demonstrate that the RBE10 of the positron-emitting radioactive beams is almost identical to the corresponding stable isotopes. The potential improvement in PET quality assurance image quality which is obtained when using radioactive beams is evaluated by comparing the signal to background ratios of positron annihilations at different intra- and post-irradiation time points. Finally, the incidental dose to the patient resulting from the use of radioactive beams is also quantified and shown to be negligible.
Chacon, D, Braytee, A, Huang, Y, Thoms, J, Subramanian, S, Sauerland, MC, Bohlander, SK, Braess, J, Wörmann, BJ, Berdel, WE, Hiddemann, W, Gabrys, B, Metzeler, KH, Herold, T, Pimanda, J & Beck, D 2019, 'Prospective Identification of Acute Myeloid Leukemia Patients Who Benefit from Gene-Expression Based Risk Stratification', Blood, vol. 134, no. Supplement_1, pp. 1397-1397.
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Background: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy and risk stratification based on genetic and clinical variables is standard practice. However, current models incorporating these factors accurately predict clinical outcomes for only 64-80% of patients and fail to provide clear treatment guidelines for patients with intermediate genetic risk. A plethora of prognostic gene expression signatures (PGES) have been proposed to improve outcome predictions but none of these have entered routine clinical practice and their role remains uncertain.
Methods: To clarify clinical utility, we performed a systematic evaluation of eight highly-cited PGES i.e. Marcucci-7, Ng-17, Li-24, Herold-29, Eppert-LSCR-48, Metzeler-86, Eppert-HSCR-105, and Bullinger-133. We investigated their constituent genes, methodological frameworks and prognostic performance in four cohorts of non-FAB M3 AML patients (n= 1175). All patients received intensive anthracycline and cytarabine based chemotherapy and were part of studies conducted in the United States of America (TCGA), the Netherlands (HOVON) and Germany (AMLCG).
Results: There was a minimal overlap of individual genes and component pathways between different PGES and their performance was inconsistent when applied across different patient cohorts. Concerningly, different PGES often assigned the same patient into opposing adverse- or favorable- risk groups (Figure 1A: Rand index analysis; RI=1 if all patients were assigned to equal risk groups and RI =0 if all patients were assigned to different risk groups). Differences in the underlying methodological framework of different PGES and the molecular heterogeneity between AMLs contributed to these low-fidelity risk assignments. However, all PGES consistently assigned a significant subset of patients into the same adverse- or favorable-risk groups (40%-70%; Figure 1B: Principal component analysis...
Chang, L, Ni, J, Zhu, Y, Pang, B, Graham, P, Zhang, H & Li, Y 2019, 'Liquid biopsy in ovarian cancer: recent advances in circulating extracellular vesicle detection for early diagnosis and monitoring progression', Theranostics, vol. 9, no. 14, pp. 4130-4140.
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Chapple, A, Nguyen, LN, Hai, FI, Dosseto, A, Rashid, MH-O, Oh, S, Price, WE & Nghiem, LD 2019, 'Impact of inorganic salts on degradation of bisphenol A and diclofenac by crude extracellular enzyme from Pleurotus ostreatus', Biocatalysis and Biotransformation, vol. 37, no. 1, pp. 10-17.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group This study investigated the influence of inorganic salts on enzymatic activity and the removal of trace organic contaminants (TrOCs) by crude laccase from the white-rot fungus Pleurotus ostreatus. A systematic analysis of 15 cations and anions from common inorganic salts was presented. Laccase activity was not inhibited by monovalent cations (i.e. Na + , NH 4 + , K + ), while the presence of divalent and trivalent cations showed variable impact – from negligible to complete inhibition – of both laccase activity and its TrOC removal performance. Of interest was the observation of discrepancy between residual laccase activity and TrOC removal in the presence of some ions. Mg 2+ had negligible impact on residual laccase activity but significant impact on TrOC removal. Conversely, F − showed greater impact on residual laccase activity than on TrOC removal. This observation indicated different impacts of the interfering ions on the interaction between laccase and TrOCs as compared to that between laccase and the reagent used to measure its activity, implicating that residual laccase activity may not always be an accurate indicator of TrOC removal. The degree of impact of halides was in the order of F − > I − > Br − > Cl − . Particularly, the tolerance of the tested laccase to Cl − has important implications for a range of industrial applications.
Cheah, R, Billa, L, Chan, A, Teo, FY, Pradhan, B & Alamri, AM 2019, 'Geospatial Modelling of Watershed Peak Flood Discharge in Selangor, Malaysia', Water, vol. 11, no. 12, pp. 2490-2490.
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Conservative peak flood discharge estimation methods such as the rational method do not take into account the soil infiltration of the precipitation, thus leading to inaccurate estimations of peak discharges during storm events. The accuracy of estimated peak flood discharge is crucial in designing a drainage system that has the capacity to channel runoffs during a storm event, especially cloudbursts and in the analysis of flood prevention and mitigation. The aim of this study was to model the peak flood discharges of each sub-watershed in Selangor using a geographic information system (GIS). The geospatial modelling integrated the watershed terrain model, the developed Soil Conservation Service Curve Cumber (SCS-CN) and precipitation to develop an equation for estimation of peak flood discharge. Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) was used again to simulate the rainfall-runoff based on the Clark-unit hydrograph to validate the modelled estimation of peak flood discharge. The estimated peak flood discharge showed a coefficient of determination, r2 of 0.9445, when compared with the runoff simulation of the Clark-unit hydrograph. Both the results of the geospatial modelling and the developed equation suggest that the peak flood discharge of a sub-watershed during a storm event has a positive relationship with the watershed area, precipitation and Curve Number (CN), which takes into account the soil bulk density and land-use of the studied area, Selangor in Malaysia. The findings of the study present a comparable and holistic approach to the estimation of peak flood discharge in a watershed which can be in the absence of a hydrodynamic simulation model.
Chen, B, Huang, J & Ji, JC 2019, 'Control of flexible single-link manipulators having Duffing oscillator dynamics', Mechanical Systems and Signal Processing, vol. 121, pp. 44-57.
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Chen, B, Yu, S, Yu, Y & Guo, R 2019, 'Nonlinear active noise control system based on correlated EMD and Chebyshev filter', Mechanical Systems and Signal Processing, vol. 130, pp. 74-86.
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© 2019 Elsevier Ltd Investigations into active noise control (ANC)have been widely conducted with the aim of effective control of low-frequency noise. This paper proposes a novel nonlinear ANC system to control non-stationary noise produced by rotating machinery under nonlinear primary path. A real-time correlated empirical mode decomposition (CEMD)is first presented to decompose non-stationary noise into intrinsic mode functions (IMFs), some of which are chosen by the correlation analysis between IMFs and primary noise. Subsequently, the second-order Chebyshev nonlinear filter is applied to expand selected IMFs that are controlled individually by the filtered-x LMS. The convergence of proposed nonlinear ANC system is also investigated. Simulation results demonstrate that proposed method outperforms the filtered-x LMS, filtered-s LMS and Volterra filtered-x LMS algorithms with respect to noise reduction and convergence rate.
Chen, C, Guo, W & Ngo, HH 2019, 'Pesticides in stormwater runoff—A mini review', Frontiers of Environmental Science & Engineering, vol. 13, no. 5.
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© 2019, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature. Recently, scientific interest has grown in harvesting and treating stormwater for potable water use, in order to combat the serious global water scarcity issue. In this context, pesticides have been identified as the key knowledge gap as far as reusing stormwater is concerned. This paper reviewed the presence of pesticides in stormwater runoff in both rural and urban areas. Specifically, the sources of pesticide contamination and possible pathways were investigated in this review. Influential factors affecting pesticides in stormwater runoff were critically identified as: 1) characteristics of precipitation, 2) properties of pesticide, 3) patterns of pesticides use, and 4) properties of application surface. The available pesticide mitigation strategies including best management practice (BMP), low impact development (LID), green infrastructure (GI) and sponge city (SC) were also included in this paper. In the future, large-scale multi-catchment studies that directly evaluate pesticide concentrations in both urban and rural stormwater runoff will be of great importance for the development of effective pesticides treatment approaches and stormwater harvesting strategies.[Figure not available: see fulltext.].
Chen, C, liu, Z & Jin, D 2019, 'Bypassing the limit in volumetric imaging of mesoscale specimens', Advanced Photonics, vol. 1, no. 02, pp. 1-1.
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Chen, D, Luo, Q, Meng, M, Li, Q & Sun, G 2019, 'Low velocity impact behavior of interlayer hybrid composite laminates with carbon/glass/basalt fibres', Composites Part B: Engineering, vol. 176, pp. 107191-107191.
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Chen, F, Duarte, C & Fu, W-T 2019, 'Special Issue on Highlights of ACM Intelligent User Interface (IUI) 2017', ACM Transactions on Interactive Intelligent Systems, vol. 9, no. 2-3, pp. 1-3.
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Chen, F, Hua, W, Huang, W, Zhu, J & Tong, M 2019, 'Open-circuit Fault-tolerant Strategies for a Five-phase Flux-switching Permanent Magnet Motor Based on Model Predictive Torque Control Method', Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, vol. 39, no. 2, pp. 337-346.
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To improve the fault-tolerant performance of five-phase flux-switching permanent magnet (FSPM) motor under open-circuit fault, the model predictive torque control (MPTC) was investigated. For the comprehensive control of the fundamental and harmonic subspaces, the torque, the amplitude of the stator flux linkage and the current in the harmonic subspace were employed as the control targets. Moreover, a pre-selective method, which was inspired by the switching table in the direct torque control, was developed to reduce the number of active switching states as well as the computational burden. By combining the sector where the stator flux linkage is located with the variations of the torque and the stator flux linkage magnitude, the specific voltage vectors instead of all vectors were determined as the vector candidates. As a result, the number of traversals was effectively reduced, and the computational burden was significantly alleviated. Consequently, the effectiveness of the proposed MPTC methods had been validated by simulations and experiments.
Chen, F, Lu, S, Hu, X, He, Q, Feng, C, Xu, Q, Chen, N, Ngo, HH & Guo, H 2019, 'Multi-dimensional habitat vegetation restoration mode for lake riparian zone, Taihu, China', Ecological Engineering, vol. 134, pp. 56-64.
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© 2019 Elsevier B.V. The riparian zones that were surround bodies of fresh water have been extensively degraded by human influence. Their restoration strength and management are an issue of urgent. Particularly, the knowledge based for the restoration of riparian zone has expanded in recent years. However, progress on a global scale has been limited, because little is known about its complex and diverse functions and structures. A national ecological restoration project of Taihu Lake (China)provided a case study for classifying and restoring the riparian zone. In this work, we quantified the classification of riparian zone, vegetation-zone in the ecotones and a recommended suite of introduced riparian vegetation communities. Taking the structures of the ecotones, soil conditions, vegetation configurations, and anthropogenic disturbances into account, six types of vegetation-zone were used to classify riparian zone, which are as follow: reefs, islands, dokdo–island, island–shore, dike–shore, and shoreland. Then a multi-dimensional habitat vegetation restoration mode for each type based on six vegetation-zones were also recommended. The water ecological quality was developed to a healthy state under this implement. Therefore, results suggest that profound division of habitat-vegetation is important in the modern ecological engineering theories for riparian zone. In order to provide a key parameter for Taihu Lake and other worldwide lakes with similar characteristics, an eco-restoration model and a reconstruction scheme for the vegetation community have been presented. In a conclusion, these recommendations could largely assist further development for lake management.
Chen, G, Jin, Z, Liu, Y, Hu, Y, Zhang, J & Qing, X 2019, 'Programmable Topology Derivation and Analysis of Integrated Three-Port DC-DC Converters with Reduced Switches for Low-Cost Applications', IEEE Transactions on Industrial Electronics, vol. 66, no. 9, pp. 1-1.
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IEEE Thanks to the favorable advantage of low cost, integrated three-port dc-dc converters with reduced switches have attracted extensive attention. In order to provide more new topologies, this paper aims to propose a programmable topology derivation method, which effectively simplifies the cumbersome process of the conventional combination method. Instead of the manual connection and examination, the proposed alternative can quickly and rigorously derive multiple viable integrated three-port dc-dc topologies from a great number of possible connections with the aid of computer program. Besides, generalized analysis is also accomplished, with which performance characteristics of all derived converters are simultaneously obtained and then a comprehensive comparison can be easily conducted to select a preferred one for the practical application. Finally, an example specific application with one input and two outputs is given, with topology selection, design and experimental results demonstrated in detail.
Chen, H, Li, A, Cui, C, Ma, F, Cui, D, Zhao, H, Wang, Q, Ni, B & Yang, J 2019, 'AHL-mediated quorum sensing regulates the variations of microbial community and sludge properties of aerobic granular sludge under low organic loading', Environment International, vol. 130, pp. 104946-104946.
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CHEN, J, SU, S & WANG, X 2019, 'Towards Privacy-Preserving Location Sharing over Mobile Online Social Networks', IEICE Transactions on Information and Systems, vol. E102.D, no. 1, pp. 133-146.
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Chen, J, Tian, Z, Cui, X, Yin, L & Wang, X 2019, 'Trust architecture and reputation evaluation for internet of things', Journal of Ambient Intelligence and Humanized Computing, vol. 10, no. 8, pp. 3099-3107.
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Chen, S, Chen, S, Wang, Z, Liang, J, Wu, Y & Yuan, X 2019, 'D-Map+', ACM Transactions on Intelligent Systems and Technology, vol. 10, no. 1, pp. 1-26.
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Information diffusion analysis is important in social media. In this work, we present a coherent ego-centric and event-centric model to investigate diffusion patterns and user behaviors. Applying the model, we propose Diffusion Map+ (D-Maps+), a novel visualization method to support exploration and analysis of user behaviors and diffusion patterns through a map metaphor. For ego-centric analysis, users who participated in reposting (i.e., resending a message initially posted by others) one central user’s posts (i.e., a series of original tweets) are collected. Event-centric analysis focuses on multiple central users discussing a specific event, with all the people participating and reposting messages about it. Social media users are mapped to a hexagonal grid based on their behavior similarities and in the chronological order of repostings. With the additional interactions and linkings, D-Map+ is capable of providing visual profiling of influential users, describing their social behaviors and analyzing the evolution of significant events in social media. A comprehensive visual analysis system is developed to support interactive exploration with D-Map+. We evaluate our work with real-world social media data and find interesting patterns among users and events. We also perform evaluations including user studies and expert feedback to certify the capabilities of our method.
Chen, S, Wang, Y, Lin, C-T, Ding, W & Cao, Z 2019, 'Semi-supervised feature learning for improving writer identification', Information Sciences, vol. 482, pp. 156-170.
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© 2019 Elsevier Inc. Data augmentation is typically used by supervised feature learning approaches for offline writer identification, but such approaches require a mass of additional training data and potentially lead to overfitting errors. In this study, a semi-supervised feature learning pipeline is proposed to improve the performance of writer identification by training with extra unlabeled data and the original labeled data simultaneously. Specifically, we propose a weighted label smoothing regularization (WLSR) method for data augmentation, which assigns a weighted uniform label distribution to the extra unlabeled data. The WLSR method regularizes the convolutional neural network (CNN) baseline to allow more discriminative features to be learned to represent the properties of different writing styles. The experimental results on well-known benchmark datasets (ICDAR2013 and CVL) showed that our proposed semi-supervised feature learning approach significantly improves the baseline measurement and perform competitively with existing writer identification approaches. Our findings provide new insights into offline writer identification.
Chen, S-L, Karmokar, DK, Li, Z, Qin, P-Y, Ziolkowski, RW & Guo, YJ 2019, 'Circular-Polarized Substrate-Integrated-Waveguide Leaky-Wave Antenna With Wide-Angle and Consistent-Gain Continuous Beam Scanning', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4418-4428.
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© 2019 IEEE. Circularly polarized (CP) antennas are in high demand for use in future wireless communications. To advance the development of CP substrate-integrated-waveguide (SIW) leaky-wave antennas (LWAs) with the intent to meet this demand, a novel benzene-ring-shaped slot-loaded LWA with partially reflecting wall (PRW) vias is investigated and verified to realize wide-angle continuous beam scanning with consistent gain. The dispersion features of slot-loaded SIW LWAs with PRW vias are theoretically explored using an equivalent circuit model. The CP radiation feature is investigated numerically utilizing the E- A nd H-field distributions of an initial design and its equivalent magnetic currents. The results of these studies are used to demonstrate that improved CP performance over a wide-angle scan range can be attained with a change from a standard slot shape to a benzene-ring-shaped slot. The resulting benzene-ring-shaped slot-loaded CP SIW LWA was optimized, fabricated, and measured. The measured results verify that a CP beam was continuously scanned through a wide angle from backward to forward directions with a consistent gain. The prototype exhibits a continuous 97.1° CP beam scan with a gain variation between 8 and 11.3 dBic when the source frequency is swept from 9.35 to 11.75 GHz.
Chen, S-L, Karmokar, DK, Li, Z, Qin, P-Y, Ziolkowski, RW & Guo, YJ 2019, 'Continuous Beam Scanning at a Fixed Frequency With a Composite Right-/Left-Handed Leaky-Wave Antenna Operating Over a Wide Frequency Band', IEEE Transactions on Antennas and Propagation, vol. 67, no. 12, pp. 7272-7284.
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© 1963-2012 IEEE. Fixed-frequency beam scanning leaky-wave antennas (LWAs) that can scan their main beam over a specific frequency band are highly desired for future wireless communication systems. A composite right-/left-handed (CRLH) LWA is developed in this article that facilitates fixed-frequency continuous beam scanning over a wide operational frequency band. A variation of a simple single-layer nonreconfigurable frequency-based continuous beam scanning CRLH LWA is considered first. Its dispersion properties are approximately investigated using an equivalent circuit model. It is reported how two groups of varactor diodes can be incorporated into its basic circuit model to electronically control its dispersion behavior. An optimized reconfigurable CRLH LWA with practical dc biasing lines is then realized from this nonreconfigurable design. Fixed-frequency continuous beam scanning, from backward to forward directions through broadside, is reported over a wide operational frequency band. Simulations predict that the antenna can operate from 4.75 to 5.25 GHz with the main beam being continuously scannable at each frequency point. A prototype was fabricated, assembled, and tested. The measured results confirm its simulated performance characteristics.
Chen, W, Pradhan, B, Li, S, Shahabi, H, Rizeei, HM, Hou, E & Wang, S 2019, 'Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis', Natural Resources Research, vol. 28, no. 4, pp. 1239-1258.
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© 2019, International Association for Mathematical Geosciences. Groundwater is a vital water source in the rural and urban areas of developing and developed nations. In this study, a novel hybrid integration approach of Fisher’s linear discriminant function (FLDA) with rotation forest (RFLDA) and bagging (BFLDA) ensembles was used for groundwater potential assessment at the Ningtiaota area in Shaanxi, China. A spatial database with 66 groundwater spring locations and 14 groundwater spring contributing factors was prepared; these factors were elevation, aspect, slope, plan and profile curvatures, sediment transport index, stream power index, topographic wetness index, distance to roads and streams, land use, lithology, soil and normalized difference vegetation index. The classifier attribute evaluation method based on the FLDA model was implemented to test the predictive competence of the mentioned contributing factors. The area under curve, confidence interval at 95%, standard error, Friedman test and Wilcoxon signed-rank test were used to compare and validate the success and prediction competence of the three applied models. According to the achieved results, the BFLDA model showed the most prediction competence, followed by the RFLDA and FLDA models, respectively. The resulting groundwater spring potential maps can be used for groundwater development plans and land use planning.
Chen, W, Yan, X, Zhao, Z, Hong, H, Bui, DT & Pradhan, B 2019, 'Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)', Bulletin of Engineering Geology and the Environment, vol. 78, no. 1, pp. 247-266.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. The main goal of this study is to assess and compare three advanced machine learning techniques, namely, kernel logistic regression (KLR), naïve Bayes (NB), and radial basis function network (RBFNetwork) models for landslide susceptibility modeling in Long County, China. First, a total of 171 landslide locations were identified within the study area using historical reports, aerial photographs, and extensive field surveys. All the landslides were randomly separated into two parts with a ratio of 70/30 for training and validation purposes. Second, 12 landslide conditioning factors were prepared for landslide susceptibility modeling, including slope aspect, slope angle, plan curvature, profile curvature, elevation, distance to faults, distance to rivers, distance to roads, lithology, NDVI (normalized difference vegetation index), land use, and rainfall. Third, the correlations between the conditioning factors and the occurrence of landslides were analyzed using normalized frequency ratios. A multicollinearity analysis of the landslide conditioning factors was carried out using tolerances and variance inflation factor (VIF) methods. Feature selection was performed using the chi-squared statistic with a 10-fold cross-validation technique to assess the predictive capabilities of the landslide conditioning factors. Then, the landslide conditioning factors with null predictive ability were excluded in order to optimize the landslide models. Finally, the trained KLR, NB, and RBFNetwork models were used to construct landslide susceptibility maps. The receiver operating characteristics (ROC) curve, the area under the curve (AUC), and several statistical measures, such as accuracy (ACC), F-measure, mean absolute error (MAE), and root mean squared error (RMSE), were used for the assessment, validation, and comparison of the resulting models in order to choose the best model in this study. The validation results s...
Chen, W, Zhang, Y, Wang, D & Wu, C 2019, 'Investigation on damage development of AP1000 nuclear power plant in strong ground motions with numerical simulation', Nuclear Engineering and Technology, vol. 51, no. 6, pp. 1669-1680.
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© 2019 Seismic safety is considered to be one of the key design objectives of AP1000 nuclear power plant (NPP) in strong earthquakes. Dynamic behavior, damage development and aggravation effect are studied in this study for the three main components of AP1000 NPP, namely reinforced concrete shield building (RCSB), steel vessel containment (SVC) and reinforced concrete auxiliary building (RCAB). Characteristics including nonlinear concrete tension and compressive constitutions with plastic damage are employed to establish the numerical model, which is further validated by existing studies. The author investigates three earthquakes and eight input levels with the maximum magnitude of 2.4 g and the results show that the concrete material of both RCSB and RCAB have suffered serious damage in intense earthquakes. Considering RCAB in the whole NPP, significant damage aggravation effect can be detected, which is mainly concentrated at the upper intersection between RCSB and RCAB. SVC and reinforcing bar demonstrate excellent seismic performance with no obvious damage.
Chen, W-H, Cheng, C-L, Show, P-L & Ong, HC 2019, 'Torrefaction performance prediction approached by torrefaction severity factor', Fuel, vol. 251, pp. 126-135.
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Chen, W-H, Lee, K & Ong, H 2019, 'Biofuel and Bioenergy Technology', Energies, vol. 12, no. 2, pp. 290-290.
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Biomass is considered as a renewable resource because of its short life cycle, and biomass-derived biofuels are potential substitutes to fossil fuels [...]
Chen, W-H, Lin, Y-Y, Liu, H-C, Chen, T-C, Hung, C-H, Chen, C-H & Ong, HC 2019, 'A comprehensive analysis of food waste derived liquefaction bio-oil properties for industrial application', Applied Energy, vol. 237, pp. 283-291.
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© 2019 Elsevier Ltd Hydrothermal liquefaction is a promising technology to convert wet biomass into bio-oil with high calorific value and without drying process. To evaluate the potential application of liquefaction bio-oil in industry, the present study aims to provide a comprehensive analysis on the properties of liquefaction bio-oil derived from food waste. The food waste is pretreated with K2CO3 at 100 °C for 1 h, followed by liquefaction in a semi-pilot reactor at 320 °C for 30 min. The higher heating value of produced bio-oil is 34.79 MJ kg−1, accounting for 53% increase when compared to the feedstock (22.74 MJ kg−1). The ignition and burnout temperatures of the bio-oil are lower than other liquefaction bio-oils, reflecting its higher reactivity and combustibility. Meanwhile, the bio-oil has a higher oxidation onset temperature than pyrolysis bio-oils, showing its higher thermal stability. The independent parallel reaction model in association with the particle swarm optimization indicates that the pyrolysis kinetics of the bio-oil can be approximated by four groups. The component analysis further reveals two important groups of fatty acids and amides in the bio-oil, stemming from the conversion of carbohydrate and protein in the food waste. The comprehensive analysis shows that the liquefaction bio-oil from food waste, characterized by higher energy density and better combustibility, is a potential substitute to the fossil fuels.
Chen, X, Chamoli, U, Lapkin, S, Castillo, JV & Diwan, AD 2019, 'Complication rates of different discectomy techniques for the treatment of lumbar disc herniation: a network meta-analysis', European Spine Journal, vol. 28, no. 11, pp. 2588-2601.
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PURPOSE:The aim of this network meta-analysis (NMA) was to compare the complication rates of discectomy/microdiscectomy, percutaneous laser disc decompression (PLDD), percutaneous endoscopic lumbar discectomy (PELD), microendoscopic discectomy (MED), and tubular discectomy for symptomatic lumbar disc herniation (LDH). METHODS:We searched three online databases for randomized controlled trials (RCTs). Overall complication rates, complication rates per general and modified Clavien-Dindo classification schemes, and reoperation rates were considered as primary outcomes. Odds ratio with 95% confidence intervals for direct comparisons and 95% credible intervals for NMA results were reported. Surface under cumulative ranking curve (SUCRA) was used to estimate ranks for each discectomy technique based on the complication rates. RESULTS:In total, 18 RCTs with 2273 patients were included in this study. Our results showed that there was no significant difference in any of the pairwise comparisons. PELD (SUCRA: 0.856) ranked the lowest for overall complication rates. Discectomy/microdiscectomy (SUCRA: 0.599) and PELD (SUCRA: 0.939) ranked the lowest for intraoperative and post-operative complication rates, respectively. Concerning modified Clavien-Dindo classification scheme, PELD (SUCRA: 0.803), MED (SUCRA: 0.730), and PLDD (SUCRA: 0.605) ranked the lowest for the occurrence of type I, II, and III complications, respectively. Tubular discectomy (SUCRA: 0.699) ranked the lowest for reoperation rates. CONCLUSIONS:The results of this NMA suggest that discectomy/microdiscectomy and PELD are the safest procedures for LDH with minimal intraoperative and post-operative complications, respectively. PELD, MED, and PLDD are the safest procedures for LDH in terms of minimal rates for complications necessitating conservative, pharmacological, and surgical treatment, respectively. These slides can be retrieved under Electronic Supplementary Material.
Chen, X, Kong, X, Xu, M, Sandrasegaran, K & Zheng, J 2019, 'Road Vehicle Detection and Classification Using Magnetic Field Measurement', IEEE Access, vol. 7, pp. 52622-52633.
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Chen, X, Lai, C-Y, Fang, F, Zhao, H-P, Dai, X & Ni, B-J 2019, 'Model-based evaluation of selenate and nitrate reduction in hydrogen-based membrane biofilm reactor', Chemical Engineering Science, vol. 195, pp. 262-270.
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© 2018 Elsevier Ltd A biofilm model was developed to describe the simultaneous NO3− and SeO42− reduction in a H2-based membrane biofilm reactor (MBfR). Model calibration and validation was conducted using the experimental data of a reported H2-based MBfR. With a good level of identifiability, the SeO42− affinity constant and the SeO32− affinity constant were estimated at 9.80 ± 0.51 g Se m−3 and 1.83 ± 0.38 g Se m−3, respectively. The model was then applied to evaluate the effects of key operating conditions on the single-stage H2-based MBfR and the role of reactor configuration through comparing two-stage to single-stage MBfR systems. The results showed that (i) high SeO42− or low NO3− concentration in the influent favored the growth of selenate-reducing bacteria (SeRB) and therefore benefited the Se removal, (ii) the influent dissolved oxygen slightly inhibited the Se removal through enhancing the aerobic microbial respiration on H2, (iii) the H2 supply should be controlled at a proper level to avoid SeRB suppression and H2 wastage, (iv) thin biofilm should be avoided to ensure a protected niche for SeRB and therefore a promising Se removal, and (v) the two-stage MBfR configuration offered relatively higher efficiency in removing Se and NO3− simultaneously under the same loading condition.
Chen, X, Ni, B & Sin, G 2019, 'Nitrous oxide production in autotrophic nitrogen removal granular sludge: A modeling study', Biotechnology and Bioengineering, vol. 116, no. 6, pp. 1280-1291.
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The sustainability of autotrophic granular system performing partial nitritation and anaerobic ammonium oxidation (anammox) for complete nitrogen removal is impaired by the production of nitrous oxide (N2 O). A systematic analysis of the pathways and affecting parameters is, therefore, required for developing N 2 O mitigation strategies. To this end, a mathematical model capable of describing different N 2 O production pathways was defined in this study by synthesizing relevant mechanisms of ammonium-oxidizing bacteria (AOB), nitrite-oxidizing bacteria, heterotrophic bacteria (HB), and anammox bacteria. With the model validity reliably tested and verified using two independent sets of experimental data from two different autotrophic nitrogen removal biofilm/granular systems, the defined model was applied to reveal the underlying mechanisms of N 2 O production in the granular structure as well as the impacts of operating conditions on N 2 O production. The results show that: (a) in the aerobic zone close to the granule surface where AOB contribute to N 2 O production through both the AOB denitrification pathway and the NH 2 OH pathway, the co-occurring HB consume N 2 O produced by AOB but indirectly enhance the N 2 O production by providing NO from NO 2 - reduction for the NH 2 OH pathway, (b) the inner anoxic zone of granules with the dominance of anammox bacteria acts as a sink for NO 2 - diffusing from the outer aerobic zone and, therefore, reduces N 2 O production from the AOB denitrification pathway, (c) operating parameters including bulk DO, influent NH 4 + , and granule size affect the N 2 O production in the granules mainly by regulating the NH 2 OH pathway of AOB, accounting for 34-58% of N 2 O turnover, and (d) the competition between the NH 2 OH pathway and heterotrophic denitrification for nitric oxide leads to the positive role of HB in reducing N 2 O production in the autotrophic nitrogen removal granules, which could be further enhanced in the pres...
Chen, X, Ni, W, Chen, T, Collings, IB, Wang, X, Liu, RP & Giannakis, GB 2019, 'Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining', IEEE Transactions on Mobile Computing, vol. 18, no. 12, pp. 2899-2912.
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IEEE Network Function Virtualization (NFV) can cost-efficiently provide network services by running different virtual network functions (VNFs) at different virtual machines (VMs) in a correct order. This can result in strong couplings between the decisions of the VMs on the placement and operations of VNFs. This paper presents a new fully decentralized online approach for optimal placement and operations of VNFs. Building on a new stochastic dual gradient method, our approach decouples the real-time decisions of VMs, asymptotically minimizes the time-average cost of NFV, and stabilizes the backlogs of network services with a cost-backlog tradeoff of [1], for any 0. Our approach can be relaxed into multiple timescales to have VNFs (re)placed at a larger timescale and hence alleviate service interruptions. While proved to preserve the asymptotic optimality, the larger timescale can slow down the optimal placement of VNFs. A learn-and-adapt strategy is further designed to speed the placement up with an improved tradeoff. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 23% and reduce the queue length (or delay) by 74%, as compared to existing benchmarks.
Chen, X, Ni, W, Collings, IB, Wang, X & Xu, S 2019, 'Automated Function Placement and Online Optimization of Network Functions Virtualization', IEEE Transactions on Communications, vol. 67, no. 2, pp. 1225-1237.
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Chen, X, Sin, G & Ni, B-J 2019, 'Impact of granule size distribution on nitrous oxide production in autotrophic nitrogen removal granular reactor', Science of The Total Environment, vol. 689, pp. 700-708.
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This work applied an approach with reactor compartmentation and artificial diffusion to study the impact of granule size distribution on the autotrophic granular reactor performing partial nitritation and anaerobic ammonium oxidation with focus on the nitrous oxide (N2O) production. The results show that the microbial community and the associated N2O production rates in the granular structure are significantly influenced by the granule size distribution. Heterotrophic bacteria growing on microbial decay products tend to be retained and contribute to N2O consumption in relatively small granules. Ammonium-oxidizing bacteria are mainly responsible for N2O production via two pathways in granules of different sizes. Under the conditions studied, such heterogeneity in the granular structure disappears when the number of granule size classes considered reaches >4, where heterotrophic bacteria are completely outcompeted in the granules. In general, larger granules account for a higher portion of the net N2O production, while the trend regarding the volumetric contribution of each granule size class changes with a varied number of granule size classes, due to the different contributions of relevant N2O production pathways (with the heterotrophic denitrification pathway being the most decisive). Overall, with the increasing extent of granule size distribution, the nitrogen removal efficiency decreases slightly but consistently, whereas the N2O production factor increases until the number of granule size classes reaches 4 or above. Practical implications of this work include: i) granules should be controlled as well-distributed as possible in order to obtain high nitrogen removal while minimizing N2O production; ii) granule size distribution should be considered carefully and specifically when modelling N2O production/emission from the autotrophic nitrogen removal granular reactor.
Chen, X, Yang, L, Sun, J, Dai, X & Ni, B-J 2019, 'Modelling of simultaneous nitrogen and thiocyanate removal through coupling thiocyanate-based denitrification with anaerobic ammonium oxidation', Environmental Pollution, vol. 253, pp. 974-980.
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Thiocyanate (SCN-)-based autotrophic denitrification (AD) has recently been demonstrated as a promising technology that could be integrated with anaerobic ammonium oxidation (Anammox) to achieve simultaneous removal of nitrogen and SCN-. However, there is still a lack of a complete SCN--based AD model, and the potential microbial competition/synergy between AD bacteria and Anammox bacteria under different operating conditions remains unknown, which significantly hinders the possible application of coupling SCN--based AD with Anammox. To this end, a complete SCN--based AD model was firstly developed and reliably calibrated/validated using experimental datasets. The obtained SCN--based AD model was then integrated with the well-established Anammox model and satisfactorily verified with experimental data from a system coupling AD with Anammox. The integrated model was lastly applied to investigate the impacts of influent NH4+-N/NO2--N ratio and SCN- concentration on the steady-state microbial composition as well as the removal of nitrogen and SCN-. The results showed that the NH4+-N/NO2--N ratio in the presence of a certain SCN- level should be controlled at a proper value so that the maximum synergy between AD bacteria and Anammox bacteria could be achieved while their competition for NO2- would be minimized. For the simultaneous maximum removal (>95%) of nitrogen and SCN-, there existed a negative relationship between the influent SCN- concentration and the optimal NH4+-N/NO2--N ratio needed.
Chen, Y, Alanezi, AA, Zhou, J, Altaee, A & Shaheed, MH 2019, 'Optimization of module pressure retarded osmosis membrane for maximum energy extraction', Journal of Water Process Engineering, vol. 32, pp. 100935-100935.
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© 2019 Elsevier Ltd A full-scale Pressure Retarded Osmosis process (PRO) is optimized in non-ideal operating conditions using Grey Wolf Optimization (GWO) algorithms. Optimization process included the classical parameters that previous studies recommended such as operating pressure, and feed and draw fractions in the mixture solution. The study has revealed that the recommended operating pressure ΔP=Δπ/2 and the ratio of feed or draw solution to the total mixture solution, ̴ 0.5, in a laboratory scale unit or in an ideal PRO process are not valid in a non-ideal full-scale PRO module. The optimization suggested that the optimum operating pressure is less than the previously recommended value of ΔP=Δπ/2. The optimization of hydraulic pressure resulted in 4.4% increase of the energy output in the PRO process. Conversely, optimization of feed fraction in the mixture has resulted in 28%–70% higher energy yield in a single-module PRO process and 9%–54% higher energy yield in a four-modules PRO process. The net energy generated in the optimized PRO process is higher than that in the unoptimized (normal) PRO process. The findings of this study reveal the significance of incorporating machine-learning algorithms in the optimization of PRO process and identifying the preferable operating conditions.
Chen, Y, Ju, LA, Zhou, F, Liao, J, Xue, L, Su, QP, Jin, D, Yuan, Y, Lu, H, Jackson, SP & Zhu, C 2019, 'An integrin αIIbβ3 intermediate affinity state mediates biomechanical platelet aggregation', Nature Materials, vol. 18, no. 7, pp. 760-769.
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Integrins are membrane receptors that mediate cell adhesion and mechanosensing. The structure-function relationship of integrins remains incompletely understood, despite the extensive studies carried out because of its importance to basic cell biology and translational medicine. Using a fluorescence dual biomembrane force probe, microfluidics and cone-and-plate rheometry, we applied precisely controlled mechanical stimulations to platelets and identified an intermediate state of integrin αIIbβ3 that is characterized by an ectodomain conformation, ligand affinity and bond lifetimes that are all intermediate between the well-known inactive and active states. This intermediate state is induced by ligand engagement of glycoprotein (GP) Ibα via a mechanosignalling pathway and potentiates the outside-in mechanosignalling of αIIbβ3 for further transition to the active state during integrin mechanical affinity maturation. Our work reveals distinct αIIbβ3 state transitions in response to biomechanical and biochemical stimuli, and identifies a role for the αIIbβ3 intermediate state in promoting biomechanical platelet aggregation.
Chen, Y, Su, QP & Yu, L 2019, 'Studying Autophagic Lysosome Reformation in Cells and by an In Vitro Reconstitution System', vol. 1880, pp. 163-172.
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Autophagic lysosome reformation (ALR) is the terminal step of autophagy. ALR functions to recycle lysosomal membranes and maintain lysosome homeostasis. Maintaining a functional lysosome pool is critical for generating autolysosomes, in which cellular components are degraded and turned over during autophagy. This unit describes methods to visualize ALR in cells. In addition, this unit provides detailed protocols to establish in vitro systems which can be used to reconstitute ALR as well as to reconstitute mitochondrial tubulation/network formation, another process that is driven by motor proteins.
Chen, Z, Duan, X, Wei, W, Wang, S & Ni, B-J 2019, 'Recent advances in transition metal-based electrocatalysts for alkaline hydrogen evolution', Journal of Materials Chemistry A, vol. 7, no. 25, pp. 14971-15005.
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Transition metal-based electrocatalysts for alkaline hydrogen evolution reaction.
Chen, Z, Li, J & You, X 2019, 'Learn to focus on objects for visual detection', Neurocomputing, vol. 348, pp. 27-39.
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© 2018 State-of-art visual detectors utilize object proposals as the reference of objects to achieve higher efficiency. However, the number of the proposal to ensure full coverage of potential objects is still large because the proposals are generated with thread and thrum, exposing proposal computation as a bottleneck. This paper presents a complementary technique that aims to work with any existing proposal generating system, amending the work-flow from “propose-assess” to “propose-adjust-assess”. Inspired by the biological processing, we propose to improve the quality of object proposals by analyzing visual contexts and gradually focusing proposals on targets. In particular, the proposed method can be employed with existing proposals generation algorithms based on both hand-crafted features and Convolutional Neural Network (CNN) features. For the former, we realize the focusing function by two learning-based transformation models, which are trained for identifying generic objects using image cues. For the latter, a Focus Proposal Net (FoPN) with cascaded layers, which can be directly injected into CNN models in an end-to-end manner, is developed as the implementation of focusing operation. Experiments on real-life image data sets demonstrate that the quality of the proposal is improved by the proposed technique. Besides, it can reduce the number of proposals to achieve high recall rate of the objects based on both hand-crafted features and CNN-features, and can boost the performance of state-of-art detectors.
Chen, Z, Liu, Y, Wei, W & Ni, B-J 2019, 'Recent advances in electrocatalysts for halogenated organic pollutant degradation', Environmental Science: Nano, vol. 6, no. 8, pp. 2332-2366.
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Advanced electrocatalysts for halogenated organic pollutant degradation.
Chen, Z, Ren, Z, Gao, H, Zheng, R, Jin, Y & Niu, C 2019, 'Flotation studies of fluorite and barite with sodium petroleum sulfonate and sodium hexametaphosphate', Journal of Materials Research and Technology, vol. 8, no. 1, pp. 1267-1273.
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© 2018 Brazilian Metallurgical, Materials and Mining Association. The development of new collectors to separate fluorite from barite is urgently needed in mineral processing. In this study, the flotation behavior of fluorite and barite was studied using sodium petroleum sulfonate (SPS) as a collector with sodium hexametaphosphate (SHMP) as a depressant. The performance of reagents on minerals was interpreted by infrared spectroscopic analysis and zeta potential measurement. The flotation results showed that SPS performed well in a wide pH region (7-11) even at a low temperature (5 °C), while the flotability of fluorite and barite were almost the same. At pH 11, the presence of SHMP obviously depressed fluorite rather than barite and SHMP exhibited good selective inhibition to fluorite. Fourier-transform infrared spectra and zeta potential results showed that: (1) SPS can adsorb on fluorite and barite surfaces and (2) SHMP had little effect on the adsorption of SPS on a barite surface, although it interfered with the adsorption of SPS on a fluorite surface through strong adsorption.
Cheng, C, Xiao, F & Cao, Z 2019, 'A New Distance for Intuitionistic Fuzzy Sets Based on Similarity Matrix', IEEE Access, vol. 7, pp. 70436-70446.
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Cheng, DL, Ngo, HH, Guo, WS, Chang, SW, Nguyen, DD & Kumar, SM 2019, 'Microalgae biomass from swine wastewater and its conversion to bioenergy', Bioresource Technology, vol. 275, pp. 109-122.
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Ever-increasing swine wastewater (SW) has become a serious environmental concern. High levels of nutrients and toxic contaminants in SW significantly impact on the ecosystem and public health. On the other hand, swine wastewater is considered as valuable water and nutrient source for microalgae cultivation. The potential for converting the nutrients from SW into valuable biomass and then generating bioenergy from it has drawn increasing attention. For this reason, this review comprehensively discussed the biomass production, SW treatment efficiencies, and bioenergy generation potentials through cultivating microalgae in SW. Microalgae species grow well in SW with large amounts of biomass being produced, despite the impact of various parameters (e.g., nutrients and toxicants levels, cultivation conditions, and bacteria in SW). Pollutants in SW can effectively be removed by harvesting microalgae from SW, and the harvested microalgae biomass elicits high potential for conversion to valuable bioenergy.
Cheng, E-J, Chou, K-P, Rajora, S, Jin, B-H, Tanveer, M, Lin, C-T, Young, K-Y, Lin, W-C & Prasad, M 2019, 'Deep Sparse Representation Classifier for facial recognition and detection system', Pattern Recognition Letters, vol. 125, pp. 71-77.
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Cheng, EJ, Young, K-Y & Lin, C-T 2019, 'Temporal EEG Imaging for Drowsy Driving Prediction', Applied Sciences, vol. 9, no. 23, pp. 5078-5078.
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As a major cause of vehicle accidents, the prevention of drowsy driving has received increasing public attention. Precisely identifying the drowsy state of drivers is difficult since it is an ambiguous event that does not occur at a single point in time. In this paper, we use an electroencephalography (EEG) image-based method to estimate the drowsiness state of drivers. The driver’s EEG measurement is transformed into an RGB image that contains the spatial knowledge of the EEG. Moreover, for considering the temporal behavior of the data, we generate these images using the EEG data over a sequence of time points. The generated EEG images are passed into a convolutional neural network (CNN) to perform the prediction task. In the experiment, the proposed method is compared with an EEG image generated from a single data time point, and the results indicate that the approach of combining EEG images in multiple time points is able to improve the performance for drowsiness prediction.
Cheng, H, Zhang, J, Wu, Q & An, P 2019, 'A Computational Model for Stereoscopic Visual Saliency Prediction', IEEE Transactions on Multimedia, vol. 21, no. 3, pp. 678-689.
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© 2018 IEEE. Depth information plays an important role in human vision as it provides additional cues that distinguish objects from their backgrounds. This paper explores depth information for analyzing stereoscopic saliency and presents a computational model that predicts stereoscopic visual saliency based on three aspects of human vision: 1) the pop-out effect; 2) comfort zones; and 3) background effects. Through an analysis of these three phenomena, we find that most of the stereoscopic saliency region can be explained. Our model comprises three modules, each describing one aspect of saliency distribution, and a control function that can be used to adjust the three models independently. The relationship between the three models is not mutually exclusive. One, two, or three phenomena may appear in one image. Therefore, to accurately determine which phenomena the image conforms to, we have devised a selection strategy that chooses the appropriate combination of models based on the content of the image. Our approach is implemented within a framework based on the multifeature analysis. The framework considers surrounding regions, color/depth contrast, and points of interest. The selection strategy can improve the performance of the framework. A series of experiments on two recent eye-tracking datasets shows that our proposed method outperforms several state-of-the-art saliency models.
Cheng, H-C & Hsieh, M-H 2019, 'Matrix Poincaré, Φ-Sobolev inequalities, and quantum ensembles', Journal of Mathematical Physics, vol. 60, no. 3, pp. 032201-032201.
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© 2019 Author(s). Sobolev-type inequalities have been extensively studied in the frameworks of real-valued functions and non-commutative Lp spaces, and have proven useful in bounding the time evolution of classical/quantum Markov processes, among many other applications. In this paper, we consider yet another fundamental setting - matrix-valued functions - and prove new Sobolev-type inequalities for them. Our technical contributions are two-fold: (i) we establish a series of matrix Poincaré inequalities for separably convex functions and general functions with Gaussian unitary ensembles inputs; and (ii) we derive Φ-Sobolev inequalities for matrix-valued functions defined on Boolean hypercubes and for those with Gaussian distributions. Our results recover the corresponding classical inequalities (i.e., real-valued functions) when the matrix has one dimension. Finally, as an application of our technical outcomes, we derive the upper bounds for a fundamental entropic quantity - the Holevo quantity - in quantum information science since classical-quantum channels are a special instance of matrix-valued functions. This is obtained through the equivalence between the constants in the strong data processing inequality and the Φ-Sobolev inequality.
Cheng, L, Song, W, Rao, Q, Zhou, J & Zhao, Z 2019, 'Bioaccumulation and toxicity of methoxychlor on Chinese mitten crab (Eriocheir sinensis)', Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, vol. 221, pp. 89-95.
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Cheng, Q, Shi, Z, Nguyen, DN & Dutkiewicz, E 2019, 'Sensing OFDM Signal: A Deep Learning Approach', IEEE Transactions on Communications, vol. 67, no. 11, pp. 7785-7798.
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Cheng, R, Omidvar, MN, Gandomi, AH, Sendhoff, B, Menzel, S & Yao, X 2019, 'Solving Incremental Optimization Problems via Cooperative Coevolution', IEEE Transactions on Evolutionary Computation, vol. 23, no. 5, pp. 762-775.
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© 1997-2012 IEEE. Engineering designs can involve multiple stages, where at each stage, the design models are incrementally modified and optimized. In contrast to traditional dynamic optimization problems, where the changes are caused by some objective factors, the changes in such incremental optimization problems (IOPs) are usually caused by the modifications made by the decision makers during the design process. While existing work in the literature is mainly focused on traditional dynamic optimization, little research has been dedicated to solving such IOPs. In this paper, we study how to adopt cooperative coevolution to efficiently solve a specific type of IOPs, namely, those with increasing decision variables. First, we present a benchmark function generator on the basis of some basic formulations of IOPs with increasing decision variables and exploitable modular structure. Then, we propose a contribution-based cooperative coevolutionary framework coupled with an incremental grouping method for dealing with them. On one hand, the benchmark function generator is capable of generating various benchmark functions with various characteristics. On the other hand, the proposed framework is promising in solving such problems in terms of both optimization accuracy and computational efficiency. In addition, the proposed method is further assessed using a real-world application, i.e., the design optimization of a stepped cantilever beam.
Cheng, S, Dong, H, Yu, L, Zhang, D & Ji, J 2019, 'Consensus of Second-order Multi-agent Systems with Directed Networks Using Relative Position Measurements Only', International Journal of Control, Automation and Systems, vol. 17, no. 1, pp. 85-93.
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Cheng, T, Al‐Soeidat, M, Lu, DD & Agelidis, VG 2019, 'Experimental study of PV strings affected by cracks', The Journal of Engineering, vol. 2019, no. 18, pp. 5124-5128.
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Crack is one critical factor that degrades the performance of photovoltaic (PV) panels. To gain a better understanding of the impacts of cracks appeared on PVs and also to mitigate it, its failure mechanism, detrimental effects, criticality, and potential risks on independent PV panels are firstly reviewed in this study. An experimental study which investigates the degree of series connected and parallel connected PV strings which are affected by cracked cells are presented. A comparison of impacts of the partially shaded PV panel string and cracked cells happened to the PV panel string is given to evaluate their criticality levels. The experimental results show that the series connected PV panel string is strongly affected once the cell is seriously cracked, as the current generation capability is clamped. Partial shading, however, shows better performance. In addition, though the overall power the parallel connected PV string is reduced, it is less affected by the cracked cells compared to the series connected one. Lastly, a bypass diode is added to a series connected PV panel string with cracked cells, and the experimental results show that it can be an effective way to minimise the negative impacts of cracks.
Cheng, X, Jiang, Z, Wei, D, Wu, H & Jiang, L 2019, 'Adhesion, friction and wear analysis of a chromium oxide scale on a ferritic stainless steel', Wear, vol. 426-427, pp. 1212-1221.
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Cheng, Z, Chang, X, Zhu, L, Kanjirathinkal, RC & Kankanhalli, M 2019, 'MMALFM', ACM Transactions on Information Systems, vol. 37, no. 2, pp. 1-28.
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Personalized rating prediction is an important research problem in recommender systems. Although the latent factor model (e.g., matrix factorization) achieves good accuracy in rating prediction, it suffers from many problems including cold-start, non-transparency, and suboptimal results for individual user-item pairs. In this article, we exploit textual reviews and item images together with ratings to tackle these limitations. Specifically, we first apply a proposed multi-modal aspect-aware topic model (MATM) on text reviews and item images to model users’ preferences and items’ features from different
aspects
, and also estimate the
aspect importance
of a user toward an item. Then, the aspect importance is integrated into a novel aspect-aware latent factor model (ALFM), which learns user’s and item’s latent factors based on ratings. In particular, ALFM introduces a weight matrix to associate those latent factors with the same set of aspects in MATM, such that the latent factors could be used to estimate aspect ratings. Finally, the overall rating is computed via a linear combination of the aspect ratings, which are weighted by the corresponding aspect importance. To this end, our model could alleviate the data sparsity problem and gain good interpretability for recommendation. Besides, every aspect rating is weighted by its aspect importance, which is dependent on the targeted user’s preferences and the targeted item’s features. Therefore, it is expected that the proposed method can model a user’s preferences on an item more accurately for each user-item pair. Comprehensive experimental studies have been conducted on the Yelp 2017 Challenge dataset and Amazon product datasets. Results show that (1) our method achieves significant improvement compared to strong baseline methods, especially for users with only few ratings; (2) item visual feat...
Cheng, Z, Xiong, G, Liu, Y, Zhang, T, Tian, J & Guo, YJ 2019, 'High‐efficiency Doherty power amplifier with wide OPBO range for base station systems', IET Microwaves, Antennas & Propagation, vol. 13, no. 7, pp. 926-929.
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Chepurin, D, Chamoli, U, Sheldrick, K, Lapkin, S, Scott, D, Kuan, J & Diwan, AD 2019, 'Bony stress in the lumbar spine is associated with intervertebral disc degeneration and low back pain: a retrospective case–control MRI study of patients under 25 years of age', European Spine Journal, vol. 28, no. 11, pp. 2470-2477.
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PURPOSE:Abnormal stress in the lumbar vertebra, also known as bony stress, can be a precursor to degenerative changes which may manifest as low back pain (LBP). However, the prevalence of bony stress in the lumbar spine and its relationship with degenerative changes and LBP is unclear. The purpose of this study was to evaluate the prevalence of bony stress in the lumbar spine and its relationship with intervertebral disc (IVD) degeneration, facet osteoarthritis and LBP in patients under 25 years of age. METHODS:A retrospective case-control study of 130 patients under 25 years of age was conducted from a population of 493 patients who had lumbar MRI across three imaging centres over three years. A cohort of 55 consecutive patients with bony stress was identified. A control group of consecutive patients (n = 75) without bony stress was also selected from the population. RESULTS:Bony stress was prevalent in 11% (95% CI [8.4-14.5%]) of patients and was not diagnosed in 36% (95% CI [22-55%]) of these cases. Patients with bony stress had over twofold (OR 2.3, 95% CI [1.1-4.8]) and fivefold (OR 5.3, 95% CI [2.11-13.3]) higher likelihood of having IVD degeneration and LBP, respectively, when compared with the control group. Bony stress was not found to be associated with facet osteoarthritis. CONCLUSION:Bony stress in the lumbar spine was prevalent in 11% of patients under 25 years of age. It was commonly undiagnosed in radiology reports (not reported in 36% of the cases). Being significantly associated and with an increased likelihood of IVD degeneration and LBP, we posit that bony stress is likely a symptomatic and clinically meaningful diagnostic entity in the assessment of LBP. These slides can be retrieved under Electronic Supplementary Material.
Chi, C, Buys, N, Li, C, Sun, J & Yin, C 2019, 'Effects of prebiotics on sepsis, necrotizing enterocolitis, mortality, feeding intolerance, time to full enteral feeding, length of hospital stay, and stool frequency in preterm infants: a meta-analysis', European Journal of Clinical Nutrition, vol. 73, no. 5, pp. 657-670.
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Chih, Y-K, Chen, W-H, Ong, HC & Show, PL 2019, 'Product Characteristics of Torrefied Wood Sawdust in Normal and Vacuum Environments', Energies, vol. 12, no. 20, pp. 3844-3844.
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To investigate the efficacy of torrefaction in a vacuum environment, wood sawdust was torrefied at various temperatures (200–300 °C) in different atmospheres (nitrogen and vacuum) with different residence times (30 and 60 min). It was found that the amount of biochar reduced at the same rate—regardless of atmosphere type—throughout the torrefaction process. In terms of energy density, the vacuum system produced biochar with better higher heating value (HHV, MJ/kg) than the nitrogen system below 250 °C. This was the case because the moisture and the high volatility compounds such as aldehydes diffused more easily in a vacuum. Over 250 °C, however, a greater amount of low volatility compounds evaded from the vacuum system, resulting in lower higher heating value in the biochar. Despite the mixed results with the solid products, the vacuum system increased the higher heating value of its liquid products more significantly than did the nitrogen system regardless of torrefaction temperature. It was found that 23% of the total energy output came from the liquid products in the vacuum system; the corresponding ratio was 19% in the nitrogen system. With liquid products contributing to a larger share of the total energy output, the vacuum system outperformed the nitrogen system in terms of energy density.
Chiu, SK, Orive, SL, Moon, MJ, Saw, J, Ellis, S, Kile, BT, Huang, Y, Chacon, D, Pimanda, JE, Beck, D, Hamilton, JR, Tremblay, CS & Curtis, DJ 2019, 'Shared roles for Scl and Lyl1 in murine platelet production and function', Blood, vol. 134, no. 10, pp. 826-835.
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Abstract
The stem cell leukemia (Scl or Tal1) protein forms part of a multimeric transcription factor complex required for normal megakaryopoiesis. However, unlike other members of this complex such as Gata1, Fli1, and Runx1, mutations of Scl have not been observed as a cause of inherited thrombocytopenia. We postulated that functional redundancy with its closely related family member, lymphoblastic leukemia 1 (Lyl1) might explain this observation. To determine whether Lyl1 can substitute for Scl in megakaryopoiesis, we examined the platelet phenotype of mice lacking 1 or both factors in megakaryocytes. Conditional Scl knockout (KO) mice crossed with transgenic mice expressing Cre recombinase under the control of the mouse platelet factor 4 (Pf4) promoter generated megakaryocytes with markedly reduced but not absent Scl. These Pf4Sclc-KO mice had mild thrombocytopenia and subtle defects in platelet aggregation. However, Pf4Sclc-KO mice generated on an Lyl1-null background (double knockout [DKO] mice) had severe macrothrombocytopenia, abnormal megakaryocyte morphology, defective pro-platelet formation, and markedly impaired platelet aggregation. DKO megakaryocytes, but not single-knockout megakaryocytes, had reduced expression of Gata1, Fli1, Nfe2, and many other genes that cause inherited thrombocytopenia. These gene expression changes were significantly associated with shared Scl and Lyl1 E-box binding sites that were also enriched for Gata1, Ets, and Runx1 motifs. Thus, Scl and Lyl1 share functional roles in platelet production by regulating expression of partner proteins including Gata1. We propose that this functional redundancy provides one explanation for the absence of Scl and Lyl1 mutations in inherited thrombocytopenia.
Choi, J, Dorji, P, Shon, HK & Hong, S 2019, 'Applications of capacitive deionization: Desalination, softening, selective removal, and energy efficiency', Desalination, vol. 449, pp. 118-130.
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© 2018 Elsevier B.V. Capacitive deionization (CDI) has attracted a great attention as a promising desalination technology, and studies on CDI have increased significantly in the last ten years. However, there have been no guidelines for developing strategies involving CDI technology for specific applications. Therefore, our work presents a critical review of the recent advances in CDI to meet the technical requirements of various applicable areas, with an emphasis on hybrid systems. This paper first summarizes the major developments made on novel electrode materials for CDI for brackish water desalination. Then, CDI and reverse osmosis (RO) integrated systems are critically reviewed for both ultrapure water production and wastewater treatment. Additionally, the applicability of CDI on various industrial processes is discussed, covering two distinct topics: (1) water softening and (2) selective removal of valuable heavy metals and nutrients (nitrate/phosphate). Lastly, recent improvements on the energy efficiency of CDI processes are delineated, specifically focusing on energy recovery and hybridization with energy producing technology, such as reverse electrodialysis (RED) and microbial fuel cells (MFC). This review paper is expected to share the practical experience of CDI applications as well as to provide guidelines for electrode material development for each specific application.
Choi, J, Dorji, P, Shon, HK & Hong, S 2019, 'Corrigendum to “Applications of capacitive deionization: Desalination, softening, selective removal, and energy efficiency” [Desalination 449 (2019) 118–130]', Desalination, vol. 468, pp. 114096-114096.
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Choi, Y, Naidu, G, Lee, S & Vigneswaran, S 2019, 'Effect of inorganic and organic compounds on the performance of fractional-submerged membrane distillation-crystallizer', Journal of Membrane Science, vol. 582, pp. 9-19.
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© 2019 Elsevier B.V. A novel approach - fractional-submerged membrane distillation crystallizer (F-SMDC) was evaluated for treating brine. F-SMDC is based on creating concentration gradient (CG) and temperature gradient (TG) in a reactor containing submerged hollow-fiber membrane. This enables water and salt recovery to occur simultaneously in a single reactor. The influence of inorganic and organic compounds present in brine solutions on the development and stability of CG/TG in F-SMDC was evaluated in detail in this study. The results of the study showed that properties of inorganic compounds - molecular weight and electronegativity played a significant role in influencing CG/TG in F-SMDC. A high CG ratio (between 1.51 and 1.83 after crystallization) was observed when using feed solutions with inorganic compounds such as KCl, MgSO4, and Na2SO4. However, only low CG ratio (between 0.94 and 1.46) was achieved in the case of feed solutions containing lower molecular weight compounds, NH4Cl and NaCl. The high CG ratio with KCl resulted in the occurrence of salt crystallization at a faster rate (from VCF 2.4 onwards) compared to the predicted theoretical salt saturation point of VCF 3.0. On the other hands, Na2SO4 showed lower flux decline (12.56% flux decline) compared to MgSO4 (55.93% flux decline) This was attributed to lower cation electronegativity of Na+. The presence of CG in F-SMDC by concentrated inorganic compounds also enhanced organic compounds to gravitate downwards to the bottom of the reactor, potentially mitigating organic deposition on the membrane.
Choi, Y, Naidu, G, Nghiem, LD, Lee, S & Vigneswaran, S 2019, 'Membrane distillation crystallization for brine mining and zero liquid discharge: opportunities, challenges, and recent progress', Environmental Science: Water Research & Technology, vol. 5, no. 7, pp. 1202-1221.
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This review outlines all the work done on the membrane distillation crystallization process.
Choi, Y, Ryu, S, Naidu, G, Lee, S & Vigneswaran, S 2019, 'Integrated submerged membrane distillation-adsorption system for rubidium recovery', Separation and Purification Technology, vol. 218, pp. 146-155.
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Seawater reverse osmosis (SWRO) brine management is essential for desalination. Improving brine recovery rate with resource recovery can enhance the overall desalination process. In this study, an integrated submerged membrane distillation (S-MD) with adsorption (granular potassium copper hexacyanoferrate (KCuFC)) was evaluated for improving water recovery from brine while extracting valuable Rb. The thermal S-MD process (55 °C) with a continuous supply of Rb-rich SWRO brine enabled Rb to be concentrated (99% rejection) while producing fresh water. Concentrated Rb in thermal condition enhanced Rb extraction by granular KCuFC. An optimum dose (0.24 g/L) KCuFC was identified based on 98% Rb mass adsorption (9.78 mg as Rb). The integrated submerged MD-adsorption system was able to achieve more than 85% water recovery and Rb extraction in continuous feed supply (in two cycles). Ca in SWRO brine resulted in CaSO4 deposition onto the membrane and surface of KCuFC, reducing recovery rate and Rb adsorption. MD water recovery significantly improved upon Ca removal while achieving a total of 6.65 mg of Rb extraction. In comparing the performance of different KCuFC forms (granular, particle and powder), the particle form of KCuFC exhibited 10–47% higher capacity in terms of total adsorbed Rb mass and adsorption rate.
Chong, CT, Mong, GR, Ng, J-H, Chong, WWF, Ani, FN, Lam, SS & Ong, HC 2019, 'Pyrolysis characteristics and kinetic studies of horse manure using thermogravimetric analysis', Energy Conversion and Management, vol. 180, pp. 1260-1267.
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Chu Van, T, Zare, A, Jafari, M, Bodisco, TA, Surawski, N, Verma, P, Suara, K, Ristovski, Z, Rainey, T, Stevanovic, S & Brown, RJ 2019, 'Effect of cold start on engine performance and emissions from diesel engines using IMO-Compliant distillate fuels', Environmental Pollution, vol. 255, no. Pt 2, pp. 113260-113260.
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Emissions from ships at berth are small compared to the total ship emissions; however, they are one of the main contributors to pollutants in the air of densely-populated areas, consequently heavily affecting public health. This is due to auxiliary marine engines being used to generate electric power and steam for heating and providing services. The present study has been conducted on an engine representative of a marine auxiliary, which was a heavy duty, six-cylinder, turbocharged and after-cooled engine with a high pressure common rail injection system. Engine performance and emission characterisations during cold start are the focus of this paper, since cold start is significantly influential. Three tested fuels were used, including the reference diesel and two IMO (International Maritime Organization) compliant spiked fuels. The research engine was operated at a constant speed and 25% load condition after 12 h cooled soak. Results show that during cold start, significant heat generated from combustion is used to heat the engine block, coolant and lubricant. During the first minute, compared to the second minute, emissions of particle number (PN), carbon monoxide (CO), particulate matter (PM), and nitrogen oxides (NOx) were approximately 10, 4, 2 and 1.5 times higher, respectively. The engine control unit (ECU) plays a vital role in reducing engine emissions by changing the engine injection strategy based on the engine coolant temperature. IMO-compliant fuels, which were higher viscosity fuels associated with high sulphur content, resulted in an engine emission increase during cold start. It should be taken into account that auxiliary marine diesel engines, working at partial load conditions during cold start, contribute considerably to emissions in coastal areas. It demonstrates a need to implement practical measures, such as engine pre-heating, to obtain both environmental and public health advantages in coastal areas.
Chu, L, Shi, J & Braun, R 2019, 'The equivalent Young's modulus prediction for vacancy defected graphene under shear stress', Physica E: Low-dimensional Systems and Nanostructures, vol. 110, pp. 115-122.
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© 2019 Elsevier B.V. The uncertain and unavoidable vacancy defects in graphene have the inevitable influence in the extraordinary intrinsic in-plane strength. In this paper, the equivalent Young's modulus is derived from the strain energy as an important factor to evaluate the stiffness of the entire graphene based on the mechanical molecular theory. The location of vacancy defects in graphene is discussed in the regular deterministic and uncertain patterns. In terms of the boundary condition, shear stress is loaded in armchair and zigzag edges, respectively. The results show that the center concentrated vacancy defects evidently deteriorate the elastic stiffness under shear stress. The influences of periodic and regular vacancy defects are sensitive to the boundary condition. By the Monte Carlo based finite element method, vacancy defects are dispersed randomly and propagated. The results of the equivalent Young's modulus are compared with the original values in pristine graphene. The interval and mean values of Young's modulus, total strain and energy density are also provided and discussed. Compared with the results of graphene with vacancy defects under uniaxial tension, the enhancement effects of vacancy defects are less evident in the graphene under shear stress.
Chu, VW, Wong, RK, Chen, F, Ho, I & Lee, J 2019, 'Enhancing portfolio return based on sentiment-of-topic', Data & Knowledge Engineering, vol. 123, pp. 101601-101601.
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Chu, Y, Fu, X, Luo, Y, Canning, J, Tian, Y, Cook, K, Zhang, J & Peng, G-D 2019, 'Silica optical fiber drawn from 3D printed preforms', Optics Letters, vol. 44, no. 21, pp. 5358-5358.
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Silica optical fiber was drawn from a three-dimensional printed preform. Both single mode and multimode fibers are reported. The results demonstrate additive manufacturing of glass optical fibers and its potential to disrupt traditional optical fiber fabrication. It opens up fiber designs for novel applications hitherto not possible.
Condina, MR, Dilmetz, BA, Razavi Bazaz, S, Meneses, J, Ebrahimi Warkiani, M & Hoffmann, P 2019, 'Rapid separation and identification of beer spoilage bacteria by inertial microfluidics and MALDI-TOF mass spectrometry', Lab on a Chip, vol. 19, no. 11, pp. 1961-1970.
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Microfluidics and MALDI-TOF MS is a rapid, high-throughput, and accurate method for the identification of beer spoilage bacteria.
Crowther, CA, Ashwood, P, Andersen, CC, Middleton, PF, Tran, T, Doyle, LW, Robinson, JS, Harding, JE, Crowther, C, Ashwood, P, Andersen, C, Middleton, P, Tran, T, Ball, V, Holst, C, Robinson, K, Zhang, S, Robinson, J, Khong, Y, McPhee, A, Groom, K, Alsweiler, J, Eaglen, D, Harding, J, Hauch, H, Vallely, A, Angus, S, Chenia, F, Drew, A, Gavranich, J, Green, A, Jack, S, Mahomed, K, Sebastian, R, Turner, L, Baldwin, M, Dennis, A, Fisher, E, Gee, K, Gee, M, Strong, D, Boord, D, Edge, N, Marsh, M, Staehr, C, Chaplin, J, Gardener, G, Gray, P, Hurrion, E, Jardine, L, Kan, J, Lynn, L, Poulsen, L, Tremellen, A, Codner, T, Cubis, W, Downward, S, Dunn, C, Furey, J, Hansen, D, Lampropoulos, B, Masson, E, Peek, M, Sellar, S, Butterley, K, Chadwick, M, Davis, C, DePaoli, T, Green, L, Matzolic, T, Woodhead, G, Biggs, V, Henry, A, Lainchbury, A, Nesbitt-Hawes, E, Oei, JL, Rodrigues, C, Shand, A, Sutton, L, Welsh, A, Bowen, J, Hayes-Cameron, L, Howard, G, Jacobs, C, Milligan, J, Morris, J, Rickard, K, Sedgley, J, White-Matthews, K, Blandthorn, J, Brownfoot, F, Burnett, A, Callanan, K, Davis, N, Deluca, C, Doyle, L, Duff, J, Howard, K, Hutchinson, E, Kelly, E, Kornman, L, Kuschel, C, Maxwell, D, McDonald, M, Poth, M, Co, J, Davis, G, Fonsesca, B, Khouri, J, Roberts, L, Rowe, C, Boniface, C, Boynton, C, Davies, C, Dickinson, C, Edmonds, L, Ireland, S, Koh, G, Kumar, P, Lawrence, A, Lock, R, Watson, D, Bahtia, V, Cash, S, Gagliardi, D, Gooding, M, Gowling, K, Grivell, R, Haslam, R, Headley, B, Johnson, M, Kobayashi, N, Kochar, A, Nikpoor, P, Simmonds, L, Siwicki, K, Stark, M & Trenowden, S 2019, 'Maternal intramuscular dexamethasone versus betamethasone before preterm birth (ASTEROID): a multicentre, double-blind, randomised controlled trial', The Lancet Child & Adolescent Health, vol. 3, no. 11, pp. 769-780.
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Cui, H, Xu, F, Saha, SC & Liu, Q 2019, 'Transient free convection heat transfer in a section-triangular prismatic enclosure with different aspect ratios', International Journal of Thermal Sciences, vol. 139, pp. 282-291.
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© 2019 Elsevier Masson SAS Free convection studies in a section-triangular prismatic enclosure with different aspect ratios (depth-width ratios, A) is conducted using three-dimensional numerical modeling approach. The Rayleigh number (Ra) covers a broad range from 10 0 to 10 7 . Transient free convection is characterized under top cooled and bottom heated boundary conditions. The flow structure of transverse rolls and longitudinal rolls is described. The critical Rayleigh numbers for the transition of the flow from driven by the baroclinic to Rayleigh-Bénard instability and from a steady to an unsteady state have been obtained for different aspect ratios. Free convection in the section-triangular prismatic enclosure could be divided into three regimes, which are presented in a Ra-A space. The quantitative relationship between heat transfer and the aspect ratio as well as the Rayleigh number has been obtained numerically.
Cui, L, Qu, Y, Nosouhi, MR, Yu, S, Niu, J-W & Xie, G 2019, 'Improving Data Utility Through Game Theory in Personalized Differential Privacy', Journal of Computer Science and Technology, vol. 34, no. 2, pp. 272-286.
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© 2019, Springer Science+Business Media, LLC & Science Press, China. Due to dramatically increasing information published in social networks, privacy issues have given rise to public concerns. Although the presence of differential privacy provides privacy protection with theoretical foundations, the trade-off between privacy and data utility still demands further improvement. However, most existing studies do not consider the quantitative impact of the adversary when measuring data utility. In this paper, we firstly propose a personalized differential privacy method based on social distance. Then, we analyze the maximum data utility when users and adversaries are blind to the strategy sets of each other. We formalize all the payoff functions in the differential privacy sense, which is followed by the establishment of a static Bayesian game. The trade-off is calculated by deriving the Bayesian Nash equilibrium with a modified reinforcement learning algorithm. The proposed method achieves fast convergence by reducing the cardinality from n to 2. In addition, the in-place trade-off can maximize the user’s data utility if the action sets of the user and the adversary are public while the strategy sets are unrevealed. Our extensive experiments on the real-world dataset prove the proposed model is effective and feasible.
Cui, P-F, Zhang, JA, Lu, W-J, Guo, YJ & Zhu, H 2019, 'Statistical Sparse Channel Modeling for Measured and Simulated Wireless Temporal Channels', IEEE Transactions on Wireless Communications, vol. 18, no. 12, pp. 5868-5881.
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© 2002-2012 IEEE. Time-domain wireless channels are generally modeled by Tapped Delay Line (TDL) model and its variants. These models are not effective for channel representation and estimation when the number of multipath taps is large. Compressive sensing (CS) provides a powerful tool for sparse channel modeling and estimation. Most of the research has been focusing on sparse channel estimation, while sparse channel modeling (SCM) is rarely considered for centimetre-wave channels. In this paper, we investigate statistical sparse channel modeling, using both measured and simulated channels over a frequency range of 6 to 8.5 GHz. We first introduce the triple equilibrium principle to explore the trade-off between sparsity, modeling accuracy, and algorithm complexity in SCM, and provide a methodology for characterizing the sparsity of time-domain channels using single-measurement-vector compressive sensing algorithms. Using mainly the selected wavelet dictionary and various CS reconstruction (aka recovery) algorithms, we then present comprehensive statistical sparse channel models, including channel sparsity, magnitude decaying profile, sparse coefficient distribution and atomic index distribution. Connections between the parameters of conventional TDL and sparse channel models are mathematically established. We also propose three methods for generating simulated channels from the developed sparse channel models, which validates their effectiveness.
Cui, Q, Gong, Z, Ni, W, Hou, Y, Chen, X, Tao, X & Zhang, P 2019, 'Stochastic Online Learning for Mobile Edge Computing: Learning from Changes', IEEE Communications Magazine, vol. 57, no. 3, pp. 63-69.
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© 1979-2012 IEEE. ML has been increasingly adopted in wireless communications, with popular techniques, such as supervised, unsupervised, and reinforcement learning, applied to traffic classification, channel encoding/ decoding, and cognitive radio. This article discusses a different class of ML technique, stochastic online learning, and its promising applications to MEC. Based on stochastic gradient descent, stochastic online learning learns from the changes of dynamic systems (i.e., the gradient of the Lagrange multipliers) rather than training data, decouples tasks between time slots and edge devices, and asymptotically minimizes the time-averaged operational cost of MEC in a fully distributed fashion with the increase of the learning time. By taking the widely adopted big data analytic framework MapReduce as an example, numerical studies show that the network throughput can increase by eight times through adopting stochastic online learning as compared to existing offline implementations.
Cui, Q, Wang, Y, Chen, K-C, Ni, W, Lin, I-C, Tao, X & Zhang, P 2019, 'Big Data Analytics and Network Calculus Enabling Intelligent Management of Autonomous Vehicles in a Smart City', IEEE Internet of Things Journal, vol. 6, no. 2, pp. 2021-2034.
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Cui, Y, Poon, J, Miro, JV, Yamazaki, K, Sugimoto, K & Matsubara, T 2019, 'Environment-adaptive interaction primitives through visual context for human–robot motor skill learning', Autonomous Robots, vol. 43, no. 5, pp. 1225-1240.
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© 2018, The Author(s). In situations where robots need to closely co-operate with human partners, consideration of the task combined with partner observation maintains robustness when partner behavior is erratic or ambiguous. This paper documents our approach to capture human–robot interactive skills by combining their demonstrative data with additional environmental parameters automatically derived from observation of task context without the need for heuristic assignment, as an extension to overcome shortcomings of the interaction primitives framework. These parameters reduce the partner observation period required before suitable robot motion can commence, while also enabling success in cases where partner observation alone was inadequate for planning actions suited to the task. Validation in a collaborative object covering exercise with a humanoid robot demonstrate the robustness of our environment-adaptive interaction primitives, when augmented with parameters directly drawn from visual data of the task scene.
Dackermann, U, Smith, WA, Alamdari, MM, Li, J & Randall, RB 2019, 'Cepstrum-based damage identification in structures with progressive damage', Structural Health Monitoring, vol. 18, no. 1, pp. 87-102.
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This article aims at developing a new framework to identify and assess progressive structural damage. The method relies solely on output measurements to establish the frequency response functions of a structure using cepstrum-based operational modal analysis. Two different damage indicative features are constructed using the established frequency response functions. The first damage feature takes the residual frequency response function, defined as the difference in frequency response function between evolving states of the structure, and then reduces its dimension using principle component analysis; while in the second damage indicator, a new feature based on the area under the residual frequency response function curve is proposed. The rationale behind this feature lies in the fact that damage often affects a number of modes of the system, that is, it affects the frequency response function over a wide range of frequencies; as a result, this quantity has higher sensitivity to any structural change by combining all contributions from different frequencies. The obtained feature vectors serve as inputs to a novel multi-stage neural network ensemble designed to assess the severity of damage in the structure. The proposed method is validated using extensive experimental data from a laboratory four-girder timber bridge structure subjected to gradually progressing damage at various locations with different severities. In total, 13 different states of the structure are considered, and it is demonstrated that the new damage feature outperforms the conventional principle component analysis–based feature. The contribution of the work is threefold: first, the application of cepstrum-based operational modal analysis in structural health monitoring is further validated, which has potential for real-life applications where only limited knowledge of the input is available; second, a new damage feature is proposed and its superior performance is demonstrated; and final...
Dadzie, J, Runeson, G & Ding, G 2019, 'Assessing determinants of sustainable upgrade of existing buildings', Journal of Engineering, Design and Technology, vol. 18, no. 1, pp. 270-292.
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Purpose
Estimates show that close to 90% of the buildings we will need in 2050 are already built and occupied. The increase in the existing building stock has affected energy consumption thereby negatively impacting the environment. The purpose of this paper is to assess determinants of sustainable upgrade of existing buildings through the adoption and application of sustainable technologies. The study also ranks sustainable technologies adopted by the professionals who participated in the survey with an in-built case study.
Design/methodology/approach
As part of the overall methodology, a detailed literature review on the nature and characteristics of sustainable upgrade and the sustainable technologies adopted was undertaken. A survey questionnaire with an in-built case study was designed to examine all the sustainable technologies adopted to improve energy consumption in Australia. The survey was administered to sustainability consultants, architects, quantity surveyors, facility managers and engineers in Australia.
Findings
The results show a total of 24 technologies which are mostly adopted to improve energy consumption in existing buildings. A factor analysis shows the main components as: lighting and automation, heating, ventilation and air conditioning (HAVC) systems and equipment, envelope, renewable energy and passive technologies.
Originality/value
The findings bridge the gap in the literature on the adoption and application of sustainable technologies to upgrade existing buildings. The technologies can be adopted to reduce the excessive energy consumption patterns in existing bui...
Damanik, Ong, Mofijur, Tong, Silitonga, Shamsuddin, Sebayang, Mahlia, Wang & Jang 2019, 'The Performance and Exhaust Emissions of a Diesel Engine Fuelled with Calophyllum inophyllum—Palm Biodiesel', Processes, vol. 7, no. 9, pp. 597-597.
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Nowadays, increased interest among the scientific community to explore the Calophyllum inophyllum as alternative fuels for diesel engines is observed. This research is about using mixed Calophyllum inophyllum-palm oil biodiesel production and evaluation that biodiesel in a diesel engine. The Calophyllum inophyllum–palm oil methyl ester (CPME) is processed using the following procedure: (1) the crude Calophyllum inophyllum and palm oils are mixed at the same ratio of 50:50 volume %, (2) degumming, (3) acid-catalysed esterification, (4) purification, and (5) alkaline-catalysed transesterification. The results are indeed encouraging which satisfy the international standards, CPME shows the high heating value (37.9 MJ/kg) but lower kinematic viscosity (4.50 mm2/s) due to change the fatty acid methyl ester (FAME) composition compared to Calophyllum inophyllum methyl ester (CIME). The average results show that the blended fuels have higher Brake Specific Fuel Consumption (BSFC) and NOx emissions, lower Brake Thermal Efficiency (BTE), along with CO and HC emissions than diesel fuel over the entire range of speeds. Among the blends, CPME5 offered better performance compared to other fuels. It can be recommended that the CPME blend has great potential as an alternative fuel because of its excellent characteristics, better performance, and less harmful emission than CIME blends.
Damtie, MM, Woo, YC, Kim, B, Hailemariam, RH, Park, K-D, Shon, HK, Park, C & Choi, J-S 2019, 'Removal of fluoride in membrane-based water and wastewater treatment technologies: Performance review', Journal of Environmental Management, vol. 251, pp. 109524-109524.
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The presence of excess fluoride in aqueous media above local environmental standards (e.g., the U.S. Environmental Protection Agency (EPA) standard of 4 mg/L) affects the health of aquatic life. Excess fluoride in drinking water above the maximum contaminant level (e.g., the World Health Organization (WHO) standard of 1.5 mg/L) also affects the skeletal and nervous systems of humans. Fluoride removal from aqueous solutions is difficult using conventional electrochemical, precipitation, and adsorption methods owing to its ionic size and reactivity. Thus, new technologies have been introduced to reduce the fluoride concentration in industrial wastewater effluents and various drinking water sources. Membrane technology is one of the newer technologies found to be very effective in significantly reducing fluoride to desired standards levels; however, it has received less attention than other technologies because it is perceived as a costly process. This study critically reviewed the performance of various membrane process and compared it with effluent and zero liquid discharge (ZLD) standards. The performance review has been conducted with the consideration of the theoretical background, rejection mechanisms, technical viability, and parameters affecting flux and rejection performance. This review includes membrane systems investigated for the defluoridation process but operated under pressure (i.e., reverse osmosis [RO] and nanofiltration [NF]), temperature gradients (i.e., membrane distillation [MD]), electrical potential gradients (i.e., electrodialysis [ED] and Donnan dialysis [DD]), and concentration differences (i.e., forward osmosis [FO]). Moreover, the study also addressed the advantages, limitations, & applicable conditions of each membrane based defluoridation process.
Damtie, MM, Woo, YC, Kim, B, Park, K-D, Hailemariam, RH, Shon, HK & Choi, J-S 2019, 'Analysis of mass transfer behavior in membrane distillation: Mathematical modeling under various conditions', Chemosphere, vol. 236, pp. 124289-124289.
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Dang, C, Zhang, J, Kwong, C-P & Li, L 2019, 'Demand Side Load Management for Big Industrial Energy Users Under Blockchain-Based Peer-to-Peer Electricity Market', IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6426-6435.
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Daniel, J, Naderpour, M & Lin, C-T 2019, 'A Fuzzy Multilayer Assessment Method for EFQM', IEEE Transactions on Fuzzy Systems, vol. 27, no. 6, pp. 1252-1262.
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© 1993-2012 IEEE. Although the European Foundation for Quality Management (EFQM) is one of the best-known business excellence frameworks, its inherent self-assessment approaches have several limitations. A critical review of self-assessment models reveals that most models are ambiguous and limited to precise data. In addition, the impact of expert knowledge on scoring is overly subjective, and most methodologies assume the relationships between variables are linear. This paper presents a new fuzzy multilayer assessment method that relies on fuzzy inference systems to accommodate imprecise data and varying assessor experiences to overcome uncertainty and complexity in the EFQM model. The method was implemented, tested, and verified under real conditions at a regional electricity company. The case was assessed by internal company experts and external assessors from an EFQM business excellence organization and the model was implemented using MATLAB software. When comparing the classical model with the new model, assessors and experts favored outputs from the new model.
Dano, U, Balogun, A-L, Matori, A-N, Wan Yusouf, K, Abubakar, I, Said Mohamed, M, Aina, Y & Pradhan, B 2019, 'Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia', Water, vol. 11, no. 3, pp. 615-615.
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Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control.
Daqamseh, S, Al-Fugara, A, Pradhan, B, Al-Oraiqat, A & Habib, M 2019, 'MODIS Derived Sea Surface Salinity, Temperature, and Chlorophyll-a Data for Potential Fish Zone Mapping: West Red Sea Coastal Areas, Saudi Arabia', Sensors, vol. 19, no. 9, pp. 2069-2069.
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In this study, a multi-linear regression model for potential fishing zone (PFZ) mapping along the Saudi Arabian Red Sea coasts of Yanbu’ al Bahr and Jeddah was developed, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived parameters, such as sea surface salinity (SSS), sea surface temperature (SST), and chlorophyll-a (Chl-a). MODIS data was also used to validate the model. The model expanded on previous models by taking seasonal variances in PFZs into account, examining the impact of the summer, winter, monsoon, and inter-monsoon season on the selected oceanographic parameters in order to gain a deeper understanding of fish aggregation patterns. MODIS images were used to effectively extract SSS, SST, and Chl-a data for PFZ mapping. MODIS data were then used to perform multiple linear regression analysis in order to generate SSS, SST, and Chl-a estimates, with the estimates validated against in-situ data obtained from field visits completed at the time of the satellite passes. The proposed model demonstrates high potential for use in the Red Sea region, with a high level of congruence found between mapped PFZ areas and fish catch data (R2 = 0.91). Based on the results of this research, it is suggested that the proposed PFZ model is used to support fisheries in determining high potential fishing zones, allowing large areas of the Red Sea to be utilized over a short period. The proposed PFZ model can contribute significantly to the understanding of seasonal fishing activity and support the efficient, effective, and responsible use of resources within the fishing industry.
Darabi, H, Choubin, B, Rahmati, O, Torabi Haghighi, A, Pradhan, B & Kløve, B 2019, 'Urban flood risk mapping using the GARP and QUEST models: A comparative study of machine learning techniques', Journal of Hydrology, vol. 569, pp. 142-154.
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© 2018 Elsevier B.V. Flood risk mapping and modeling is important to prevent urban flood damage. In this study, a flood risk map was produced with limited hydrological and hydraulic data using two state-of-the-art machine learning models: Genetic Algorithm Rule-Set Production (GARP) and Quick Unbiased Efficient Statistical Tree (QUEST). The flood conditioning factors used in modeling were: precipitation, slope, curve number, distance to river, distance to channel, depth to groundwater, land use, and elevation. Based on available reports and field surveys for Sari city (Iran), 113 points were identified as flooded areas (with each flooded zone assigned a value of 1). Different conditioning factors, including urban density, quality of buildings, age of buildings, population density, and socio-economic conditions, were taken into account to analyze flood vulnerability. In addition, the weight of these conditioning factors was determined based on expert knowledge and Fuzzy Analytical Network Process (FANP). An urban flood risk map was then produced using flood hazard and flood vulnerability maps. The area under the receiver-operator characteristic curve (AUC-ROC) and Kappa statistic were applied to evaluate model performance. The results demonstrated that the GARP model (AUC-ROC = 93.5%, Kappa = 0.86) had higher performance accuracy than the QUEST model (AUC-ROC = 89.2%, Kappa = 0.79). The results also indicated that distance to channel, land use, and elevation played major roles in flood hazard determination, whereas population density, quality of buildings, and urban density were the most important factors in terms of vulnerability. These findings demonstrate that machine learning models can help in flood risk mapping, especially in areas where detailed hydraulic and hydrological data are not available.
Dash, SK, Saikia, R & Nimbalkar, S 2019, 'Contact Pressure Distribution on Subgrade Soil Underlying Geocell Reinforced Foundation Beds', Frontiers in Built Environment, vol. 5.
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© Copyright © 2019 Dash, Saikia and Nimbalkar. High contact stresses generated in the foundation soil, owing to increased load, causes distress, instability, and large settlements. Present days, geocell reinforcement is being widely used for the performance improvement of foundation beds. Pressure distribution on subgrade soil in geocell reinforced foundation beds is studied through model tests and numerical analysis. The test data indicates that with provision of geocell reinforcement the contact pressure on the subgrade soil reduces significantly. Consequently, the subgrade soil tends to remain intact until large loadings on the foundation leading to significant performance improvement. Through numerical analysis it is observed that the geocells in the region under the footing were subjected to compression and beyond were in tension. This indicates that the geocell reinforcement right under the footing directly sustains the footing loading through mobilization of its compressive stiffness and bending rigidity. Whereas, the end portions of the geocell reinforcement, contribute to the performance improvement in a secondary manner through mobilization of anchorage derived from soil passive resistance and friction.
De Carvalho Gomes, S, Zhou, JL, Li, W & Long, G 2019, 'Progress in manufacture and properties of construction materials incorporating water treatment sludge: A review', Resources, Conservation and Recycling, vol. 145, pp. 148-159.
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© 2019 Elsevier B.V. Water treatment sludge (WTS) management is a growing global problem for water treatment plants (WTPs) and governments. Considering the scarcity of raw materials in many parts of the planet and unique properties of WTS, extensive research has been conducted on the application of WTS in the production of construction materials such as roof tiles, bricks, lightweight aggregates, cement, concrete and geopolymers. This paper critically reviews the progress in the application of WTS in construction materials, by synthesizing results from recent studies. Research findings have revealed that incorporation of ≤10% alum-based sludge in ceramic bricks is satisfactory with a small reduction of mechanical performance. Using the iron-based sludge, the bricks presented better mechanical strength than the reference clay-bricks. Concerning WTS application in concrete, 5% replacement of cement or sand by WTS was considered as the ideal value for the application in a variety of structural and non-structural concrete without adverse effect on concrete mechanical performance. Furthermore, this paper discusses sludge-amended concrete in terms of durability, potential leaching of toxic elements and cost, and suggests topics for future research on the sustainable management of WTS.
de Moura, PK, Cavalli, CB & da Rocha, CG 2019, 'Interface design for in-home displays', Sustainable Production and Consumption, vol. 18, pp. 130-144.
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© 2018 Institution of Chemical Engineers In-home displays can support behavioral changes by providing users with real time information (or feedback) on their energy consumption. Previous studies have shown that the design of such devices plays an important role in effectively communicating such information to users and that preferences are culturally-depend. This paper examines information elements best suited to the Brazilian context for children, adults, and elderly. It explores the preference, ranking, and understanding in addition to the ideal in-home display for each user profile. Lastly, display prototypes suited to each user profile are also proposed based on the results of seven focus groups totaling fifty participants. Real-time consumption was one of the most important information whereas penalty was the least. All participants preferred historical comparison to normative comparison. Numerical formats were better understood than ambient formats for real-time consumption. In addition, children and adults preferred and designed ambient formats whereas elderly preferred numerical information in monetary unit. Elderly would like to keep the display simple whereas adults and children need more interactive designs. These findings contribute to more effective in-home display design particularly for the Brazilian context, where smart meter and in home-displays are not extensively adopted.
Dekhtyar, A, Huffman Hayes, J, Hadar, I, Combs, E, Ferrari, A, Gregory, S, Horkoff, J, Levy, M, Nayebi, M, Paech, B, Payne, J, Primrose, M, Spoletini, P, Clarke, S, Brophy, C, Amyot, D, Maalej, W, Ruhe, G, Cleland-Huang, J & Zowghi, D 2019, 'Requirements Engineering (RE) for Social Good: RE Cares [Requirements]', IEEE Software, vol. 36, no. 1, pp. 86-94.
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© 1984-2012 IEEE. As researchers and teachers and practitioners, we software types excel at multitasking. This, in part, led us to ask the question: Can one attend a software engineering conference and do something good for society? We found the answer to be a resounding yes. In this article, we present our first experience of running RE Cares, a conference collocated event. This event included a workshop, conference sessions, and a hackathon for developing an application to support emergency field activity for Mutual Aid Alberta, a nonprofit organization coordinating natural disaster responses in the Canadian province.
Deng, L, Ngo, H-H, Guo, W & Zhang, H 2019, 'Pre-coagulation coupled with sponge-membrane filtration for organic matter removal and membrane fouling control during drinking water treatment', Water Research, vol. 157, pp. 155-166.
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A new hybrid system was developed in this study for the treatment of drinking water consisting of pre-coagulation using polyaluminium chloride (PACl) and membrane filtration (MF) with sponge cubes acting as biomass carriers (P-SMF). When compared to a conventional MF (CMF) and a MF after coagulation by utilizing PACl (P-MF), better removal of nutrients, UV254 and dissolved organic carbon (DOC) (>65%) was obtained from the P-SMF. The accumulation of biopolymers (including polysaccharides and proteins), humic substances, hydrophilic organics, and other small molecular weight (MW) organic matter in the CMF led to the most severe membrane fouling coupled with the highest pore blocking and cake resistance. Pre-coagulation was ineffective in eliminating small MW and hydrophilic organic matter. Conversely, the larger MW organics (i.e. biopolymers and humic substances), small MW organics and hydrophilic organic compounds could be removed in significantly larger quantities in the P-SMF by PACl coagulation. This was achieved via adsorption and the biodegradation by attached biomass on these sponges and by the suspended sludge. Further analyses of the microbial community indicated that the combined addition of PACl and sponges generated a high enrichment of Zoolgloea, Amaricoccus and Reyranella leading to the reduction of biopolymers, and Flexibacter and Sphingobium were linked to the degradation of humic substances. Moreover, some members of Alphaproteobacteria in the P-SMF may be responsible for the removal of low MW organics. These results suggest that the pre-coagulation process coupled with adding sponge in the MF system is a promising technology for mitigating membrane fouling.
Deng, S, Ji, J, Yin, S & Wen, G 2019, 'Multistability in the Centrifugal Governor System Under a Time-Delay Control Strategy', Journal of Computational and Nonlinear Dynamics, vol. 14, no. 11.
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Abstract
The centrifugal governor system plays an indispensable role in maintaining the near-constant speed of engines. Although different arrangements have been developed, the governor systems are still applied in many machines for its simple mechanical structure. Therefore, the large-amplitude vibrations of the governor system which can lead to the function failure of the system should be attenuated to guarantee reliable operation. This paper adopts a time-delay control strategy to suppress the undesirable large-amplitude motions in the centrifugal governor system, which can be regarded as the practical application of the delayed feedback controller in this system. The stability region of the trivial equilibrium of the controlled system is determined by investigating the characteristic equation and generic Hopf bifurcations. It is found that the dynamic behavior of multistability can be induced by the Bautin bifurcation, arising on the stability boundary of the trivial equilibrium with a constant delay. More specifically, a coexistence of two desirable stable motions, i.e., an equilibrium or a small-amplitude periodic motion, can be observed in the controlled centrifugal governor system without changing the physical parameters. This is a new feature of the motion control in the centrifugal governor systems, which has not yet been reported in the existing studies. Finally, the results of theoretical analyses are verified by numerical simulations.
Deng, W-Y, Lendasse, A, Ong, Y-S, Tsang, IW-H, Chen, L & Zheng, Q-H 2019, 'Domain Adaption via Feature Selection on Explicit Feature Map', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 4, pp. 1180-1190.
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In most domain adaption approaches, all features are used for domain adaption. However, often, not every feature is beneficial for domain adaption. In such cases, incorrectly involving all features might cause the performance to degrade. In other words, to make the model trained on the source domain work well on the target domain, it is desirable to find invariant features for domain adaption rather than using all features. However, invariant features across domains may lie in a higher order space, instead of in the original feature space. Moreover, the discriminative ability of some invariant features such as shared background information is weak, and needs to be further filtered. Therefore, in this paper, we propose a novel domain adaption algorithm based on an explicit feature map and feature selection. The data are first represented by a kernel-induced explicit feature map, such that high-order invariant features can be revealed. Then, by minimizing the marginal distribution difference, conditional distribution difference, and the model error, the invariant discriminative features are effectively selected. This problem is NP-hard to be solved, and we propose to relax it and solve it by a cutting plane algorithm. Experimental results on six real-world benchmarks have demonstrated the effectiveness and efficiency of the proposed algorithm, which outperforms many state-of-the-art domain adaption approaches.
Derakhshani, M, Abbaszadeh, H, Movassaghpour, AA, Mehdizadeh, A, Ebrahimi-Warkiani, M & Yousefi, M 2019, 'Strategies for elevating hematopoietic stem cells expansion and engraftment capacity', Life Sciences, vol. 232, pp. 116598-116598.
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Hematopoietic stem cells (HSCs) are a rare cell population in adult bone marrow, mobilized peripheral blood, and umbilical cord blood possessing self-renewal and differentiation capability into a full spectrum of blood cells. Bone marrow HSC transplantation has been considered as an ideal option for certain disorders treatment including hematologic diseases, leukemia, immunodeficiency, bone marrow failure syndrome, genetic defects such as thalassemia, sickle cell anemia, autoimmune disease, and certain solid cancers. Ex vivo proliferation of these cells prior to transplantation has been proposed as a potential solution against limited number of stem cells. In such culture process, MSCs have also been shown to exhibit high capacity for secretion of soluble mediators contributing to the principle biological and therapeutic activities of HSCs. In addition, endothelial cells have been introduced to bridge the blood and sub tissues in the bone marrow, as well as, HSCs regeneration induction and survival. Cell culture in the laboratory environment requires cell growth strict control to protect against contamination, symmetrical cell division and optimal conditions for maximum yield. In this regard, microfluidic systems provide culture and analysis capabilities in micro volume scales. Moreover, two-dimensional cultures cannot fully demonstrate extracellular matrix found in different tissues and organs as an abstract representation of three dimensional cell structure. Microfluidic systems can also strongly describe the effects of physical factors such as temperature and pressure on cell behavior.
Deuse, J, Schmitt, J, Bönig, J & Beitinger, G 2019, 'Dynamische Röntgenprüfung in der Elektronikproduktion', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 114, no. 5, pp. 264-267.
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Kurzfassung
In diesem Beitrag wird ein Konzept zur dynamischen Röntgenprüfung in der Elektronikproduktion vorgestellt, das durch die Auswertung von Prozessdaten mithilfe von Data-Mining-Verfahren die Prognose der finalen Produktqualität im laufenden Prozess erlaubt. Dies ermöglicht die Reduzierung von Röntgenprüfumfängen durch die Entwicklung dynamischer Prüfpläne.
Devereux, L, Watson, PH, Mes-Masson, A-M, Luna-Crespo, F, Thomas, G, Pitman, H, Speirs, V, Hall, AG, Bollinger, N, Posada, M, Lochmüller, H, Thorne, H, Eng, CB, Riegman, PHJ, Ng, W & Parry-Jones, A 2019, 'A Review of International Biobanks and Networks: Success Factors and Key Benchmarks—A 10-Year Retrospective Review', Biopreservation and Biobanking, vol. 17, no. 6, pp. 512-519.
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Dhingra, S, Madda, RB, Gandomi, AH, Patan, R & Daneshmand, M 2019, 'Internet of Things Mobile–Air Pollution Monitoring System (IoT-Mobair)', IEEE Internet of Things Journal, vol. 6, no. 3, pp. 5577-5584.
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© 2014 IEEE. Internet of Things (IoT) is a worldwide system of 'smart devices' that can sense and connect with their surroundings and interact with users and other systems. Global air pollution is one of the major concerns of our era. Existing monitoring systems have inferior precision, low sensitivity, and require laboratory analysis. Therefore, improved monitoring systems are needed. To overcome the problems of existing systems, we propose a three-phase air pollution monitoring system. An IoT kit was prepared using gas sensors, Arduino integrated development environment (IDE), and a Wi-Fi module. This kit can be physically placed in various cities to monitoring air pollution. The gas sensors gather data from air and forward the data to the Arduino IDE. The Arduino IDE transmits the data to the cloud via the Wi-Fi module. We also developed an Android application termed IoT-Mobair, so that users can access relevant air quality data from the cloud. If a user is traveling to a destination, the pollution level of the entire route is predicted, and a warning is displayed if the pollution level is too high. The proposed system is analogous to Google traffic or the navigation application of Google Maps. Furthermore, air quality data can be used to predict future air quality index (AQI) levels.
Dietrich, A, Bürk, M, Steiger, ES, Antoniuk, L, Tran, TT, Nguyen, M, Aharonovich, I, Jelezko, F & Kubanek, A 2019, 'Reply to “Comment on ‘Observation of Fourier transform limited lines in hexagonal boron nitride’”', Physical Review B, vol. 100, no. 4.
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© 2019 American Physical Society. In this Reply, we answer to the comments by Langbein [Phys. Rev. B 100, 047401 (2019)10.1103/PhysRevB.100.047401]. We disagree with the argument that our measured spectral shapes and the extracted linewidths are caused by temporal blinking. We give detailed information on our evaluation process to exclude blinking events. Beyond the question raised in the Comment, we analyze the influence of spectral diffusion. Although spectral diffusion is an ongoing limitation for defect centers in hexagonal boron nitride, we prove that it is not influencing our extracted linewidths.
Dikshit, A, Sarkar, R, Pradhan, B, Acharya, S & Dorji, K 2019, 'Estimating Rainfall Thresholds for Landslide Occurrence in the Bhutan Himalayas', Water, vol. 11, no. 8, pp. 1616-1616.
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Consistently over the years, particularly during monsoon seasons, landslides and related geohazards in Bhutan are causing enormous damage to human lives, property, and road networks. The determination of thresholds for rainfall triggered landslides is one of the most effective methods to develop an early warning system. Such thresholds are determined using a variety of rainfall parameters and have been successfully calculated for various regions of the world at different scales. Such thresholds can be used to forecast landslide events which could help in issuing an alert to civic authorities. A comprehensive study on the determination of rainfall thresholds characterizing landslide events for Bhutan is lacking. This paper focuses on defining event rainfall–duration thresholds for Chukha Dzongkhag, situated in south-west Bhutan. The study area is chosen due to the increase in frequency of landslides during monsoon along Phuentsholing-Thimphu highway, which passes through it and this highway is a major trade route of the country with the rest of the world. The present threshold method revolves around the use of a power law equation to determine event rainfall–duration thresholds. The thresholds have been established using available rainfall and landslide data for 2004–2014. The calculated threshold relationship is fitted to the lower boundary of the rainfall conditions leading to landslides and plotted in logarithmic coordinates. The results show that a rainfall event of 24 h with a cumulated rainfall of 53 mm can cause landslides. Later on, the outcome of antecedent rainfall varying from 3–30 days was also analysed to understand its effect on landslide incidences based on cumulative event rainfall. It is also observed that a minimum 10-day antecedent rainfall of 88 mm and a 20-day antecedent rainfall of 142 mm is required for landslide occurrence in the area. The thresholds presented can be improved with the availability of hourly rainfall data and the add...
Dikshit, A, Satyam, N & Pradhan, B 2019, 'Estimation of Rainfall-Induced Landslides Using the TRIGRS Model', Earth Systems and Environment, vol. 3, no. 3, pp. 575-584.
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© 2019, King Abdulaziz University and Springer Nature Switzerland AG. Rainfall-induced landslides have become the biggest threat in the Indian Himalayas and their increasing frequency has led to serious calamities. Several models have been built using various rainfall characteristics to determine the minimum rainfall amount for landslide occurrences. The utilisation of such models depends on the quality of available landslide and rainfall data. However, these models do not consider the effect of local soil, geology, hydrology and topography, which varies spatially. This study is to analyse the triggering process for shallow landslides using physical-based models for the Indian Himalayan region. This research focuses on the utilisation and dependability of physical models in the Kalimpong area of Darjeeling Himalayas, India. The approach utilised the transient rainfall infiltration and grid-based regional slope-stability (TRIGRS) model, which is a widely used model in assessing the variations in pore water pressure and determining the change in the factor of safety. TRIGRS uses an infinite slope model to calculate the change in the factor of safety for every pixel. Moreover, TRIGRS is used to compare historical rainfall scenarios with available landslide database. This study selected the rainfall event from 30th June to 1st July 2015 as input for calibration because the amount of rainfall in this period was higher than the monthly average and caused 18 landslides. TRIGRS depicted variations in the factor of safety with duration before, during and after the heavy rainfall event in 2015. This study further analysed the landslide event and evaluated the predictive capability using receiver operating characteristics. The model was able to successfully predict 71.65% of stable pixels after the landslide event, however, the availability of more datasets such as hourly rainfall, accurate time of landslide event would further improve the results. The results from this stu...
Ding, A, Lin, D, Zhao, Y, Ngo, HH, Guo, W, Bai, L, Luo, X, Li, G, Ren, N & Liang, H 2019, 'Effect of metabolic uncoupler, 2,4‑dinitrophenol (DNP) on sludge properties and fouling potential in ultrafiltration membrane process', Science of The Total Environment, vol. 650, no. Pt 2, pp. 1882-1888.
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Energy uncoupling technology was applied to the membrane process to control the problem of bio-fouling. Different dosages of uncoupler (2,4‑dinitrophenol, DNP) were added to the activated sludge, and a short-term ultrafiltration test was systematically investigated for analyzing membrane fouling potential and underlying mechanisms. Ultrafiltration membrane was used and made of polyether-sulfone with a molecular weight cut off (MWCO) of 150 kDa. Results indicated that low DNP concentration (15-30 mg/g VSS) aggravated membrane fouling because more soluble microbial products were released and then rejected by the membrane, which significantly increased cake layer resistance compared with the control. Conversely, a high dosage of DNP (45 mg/g VSS) retarded membrane fouling owing to the high inhibition of extracellular polymeric substances (proteins and polysaccharides) of the sludge, which effectively prevented the formation of cake layer on the membrane surface. Furthermore, analyses of fouling model revealed that a high dosage of DNP delayed the fouling model from pore blocking transition to cake filtration, whereas this transition process was accelerated in the low dosage scenario.
Ding, G & Ying, X 2019, 'Embodied and operating energy assessment of existing buildings – Demolish or rebuild', Energy, vol. 182, pp. 623-631.
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© 2019 Addressing climate change and energy efficiency of buildings challenge governments. Research studies to improve the efficiency of new buildings are many, but the potential of existing buildings to alleviate environmental problems is yet to be recognised. The economic development in China triggered the rapid growth of population and urbanisation. The government has experienced severe environmental problems due, among other things, to an increasing demand for housing. The demand for housing and environmental degradation have compelled the government to demolish historic houses for the construction of more efficient residential buildings. Nevertheless, the consumption of natural resources is essential considerations for redevelopment. The research has selected a south China town to conduct multiple case studies to analyse and compare the energy efficiency of historic and modern dwellings. The research reveals that modern building overall outperforms the historic houses in energy consumption for heating but consumes much higher energy for cooling over a 12-month period. However, the historic houses outperform the modern building in the embodied energy and carbon analysis. If these historic houses are to be replaced with energy efficient buildings, it will take approximately 18–41 years to recover the embodied energy invested in the materials for the new buildings.
Ding, G, Zhang, S, Khan, S, Tang, Z, Zhang, J & Porikli, F 2019, 'Feature Affinity-Based Pseudo Labeling for Semi-Supervised Person Re-Identification', IEEE Transactions on Multimedia, vol. 21, no. 11, pp. 2891-2902.
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© 1999-2012 IEEE. Vision-based person re-identification aims to match a person's identity across multiple images, which is a fundamental task in multimedia content analysis and retrieval. Deep neural networks have recently manifested great potential in this task. However, a major bottleneck of existing supervised deep networks is their reliance on a large amount of annotated training data. Manual labeling for person identities in large-scale surveillance camera systems is quite challenging and incurs significant costs. Some recent studies adopt generative model outputs as training data augmentation. To more effectively use these synthetic data for an improved feature learning and re-identification performance, this paper proposes a novel feature affinity-based pseudo labeling method with two possible label encodings. To the best of our knowledge, this is the first study that employs pseudo-labeling by measuring the affinity of unlabeled samples with the underlying clusters of labeled data samples using the intermediate feature representations from deep networks. We propose training the network with the joint supervision of cross-entropy loss together with a center regularization term, which not only ensures discriminative feature representation learning but also simultaneously predicts pseudo-labels for unlabeled data. We show that both label encodings can be learned in a unified manner and help improve the overall performance. Our extensive experiments on three person re-identification datasets: Market-1501, DukeMTMC-reID, and CUHK03, demonstrate significant performance boost over the state-of-the-art person re-identification approaches.
Ding, H, Ji, J & Chen, L-Q 2019, 'Nonlinear vibration isolation for fluid-conveying pipes using quasi-zero stiffness characteristics', Mechanical Systems and Signal Processing, vol. 121, pp. 675-688.
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© 2018 Fluid-conveying pipes are always subjected to various excitations to cause unwanted vibrations. A quasi-zero stiffness system consisting of three linear springs is adopted as the nonlinear isolator to attenuate the transverse vibrations of fluid-conveying pipes induced by foundation excitations. A dynamic model of nonlinear forced vibration of the fluid-conveying pipe coupled with two nonlinear isolators is established for the nonlinear continuous system and validated by using two methods, Galerkin method and the finite difference method. The influence of the quasi-zero stiffness isolators on the vibration characteristics and vibration transmission of the pipe is investigated by analyzing the natural frequency, vibration mode, and nonlinear vibration response. The effects of flow speed of the fluid and the system parameters of the isolator are studied to evaluate the isolation performance. It is found that the quasi-zero stiffness isolator and fluid flow can shift several natural frequencies of vibration of the pipeline to the low-frequency region. When the linear stiffness of the vibration isolation is zero in the vertical direction, the first two modes of the bending vibration of the fluid-conveying pipe tend to become rigid mode. While achieving high-efficiency vibration isolation in the high-frequency region, the vibration in the low-frequency region is complicated. The flow speed of the fluid can deteriorate the performance of vibration isolation.
Ding, W, Jin, W, Cao, S, Zhou, X, Wang, C, Jiang, Q, Huang, H, Tu, R, Han, S-F & Wang, Q 2019, 'Ozone disinfection of chlorine-resistant bacteria in drinking water', Water Research, vol. 160, pp. 339-349.
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The wide application of chlorine disinfectant for drinking water treatment has led to the appearance of chlorine-resistant bacteria, which pose a severe threat to public health. This study was performed to explore the physiological-biochemical characteristics and environmental influence (pH, temperature, and turbidity) of seven strains of chlorine-resistant bacteria isolated from drinking water. Ozone disinfection was used to investigate the inactivation effect of bacteria and spores. The DNA concentration and cell surface structure variations of typical chlorine-resistant spores (Bacillus cereus spores) were also analysed by real-time qPCR, flow cytometry, and scanning electron microscopy to determine their inactivation mechanisms. The ozone resistance of bacteria (Aeromonas jandaei < Vogesella perlucida < Pelomonas < Bacillus cereus < Aeromonas sobria) was lower than that of spores (Bacillus alvei < Lysinibacillus fusiformis < Bacillus cereus) at an ozone concentration of 1.5 mg/L. More than 99.9% of Bacillus cereus spores were inactivated by increasing ozone concentration and treatment duration. Moreover, the DNA content of Bacillus cereus spores decreased sharply, but approximately 1/4 of the target genes remained. The spore structure exhibited shrinkage and folding after ozone treatment. Both cell structures and gene fragments were damaged by ozone disinfection. These results showed that ozone disinfection is a promising method for inactivating chlorine-resistant bacteria and spores in drinking water.
Ding, W, Lin, C-T & Cao, Z 2019, 'Deep Neuro-Cognitive Co-Evolution for Fuzzy Attribute Reduction by Quantum Leaping PSO With Nearest-Neighbor Memeplexes', IEEE Transactions on Cybernetics, vol. 49, no. 7, pp. 2744-2757.
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Attribute reduction with many patterns and indicators has been regarded as an important approach for large-scale data mining and machine learning tasks. However, it is extremely difficult for researchers to inadequately extract knowledge and insights from multiple overlapping and interdependent fuzzy datasets from the current changing and interconnected big data sources. This paper proposes a deep neuro-cognitive co-evolution for fuzzy attribute reduction (DNCFAR) that contains a combination of quantum leaping particle swarm optimization with nearest-neighbor memeplexes. A key element of DNCFAR resides in its deep neuro-cognitive cooperative co-evolution structure, which is explicitly permitted to identify interdependent variables and adaptively decompose them in the same neuro-subpopulation, with minimizing the complexity and nonseparability of interdependent variables among different fuzzy attribute subsets. Next DNCFAR formalizes to the different types of quantum leaping particles with nearest-neighbor memeplexes to share their respective solutions and deeply cooperate to evolve the assigned fuzzy attribute subsets. The experimental results demonstrate that DNCFAR can achieve competitive performance in terms of average computational efficiency and classification accuracy while reinforcing noise tolerance. Furthermore, it can be well applied to clearly identify different longitudinal surfaces of infant cerebrum regions, which indicates its great potential for brain disorder prediction based on fMRI.
Ding, W, Lin, C-T & Cao, Z 2019, 'Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 7, pp. 2013-2027.
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The unprecedented increase in data volume has become a severe challenge for conventional patterns of data mining and learning systems tasked with handling big data. The recently introduced Spark platform is a new processing method for big data analysis and related learning systems, which has attracted increasing attention from both the scientific community and industry. In this paper, we propose a shared nearest-neighbor quantum game-based attribute reduction (SNNQGAR) algorithm that incorporates the hierarchical coevolutionary Spark model. We first present a shared coevolutionary nearest-neighbor hierarchy with self-evolving compensation that considers the features of nearest-neighborhood attribute subsets and calculates the similarity between attribute subsets according to the shared neighbor information of attribute sample points. We then present a novel attribute weight tensor model to generate ranking vectors of attributes and apply them to balance the relative contributions of different neighborhood attribute subsets. To optimize the model, we propose an embedded quantum equilibrium game paradigm (QEGP) to ensure that noisy attributes do not degrade the big data reduction results. A combination of the hierarchical coevolutionary Spark model and an improved MapReduce framework is then constructed that it can better parallelize the SNNQGAR to efficiently determine the preferred reduction solutions of the distributed attribute subsets. The experimental comparisons demonstrate the superior performance of the SNNQGAR, which outperforms most of the state-of-the-art attribute reduction algorithms. Moreover, the results indicate that the SNNQGAR can be successfully applied to segment overlapping and interdependent fuzzy cerebral tissues, and it exhibits a stable and consistent segmentation performance for neonatal cerebral cortical surfaces.
Ding, X, Wei, D, Guo, W, Wang, B, Meng, Z, Feng, R, Du, B & Wei, Q 2019, 'Biological denitrification in an anoxic sequencing batch biofilm reactor: Performance evaluation, nitrous oxide emission and microbial community', Bioresource Technology, vol. 285, pp. 121359-121359.
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Do, T-TN, Chuang, C-H, Hsiao, S-J, Lin, C-T & Wang, Y-K 2019, 'Neural Comodulation of Independent Brain Processes Related to Multitasking', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 27, no. 6, pp. 1160-1169.
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Distracted driving is regarded as an integrated task requiring different regions of the brain to receive sensory data, coordinate information, make decisions, and synchronize movements. In this paper, we applied an independent modulator analysis (IMA) method to temporally independent electroencephalography (EEG) components to understand how the human executive control system coordinates different brain regions to simultaneously perform multiple tasks with distractions presented in different modalities. The behavioral results showed that the reaction time (RT) in response to traffic events increased while multitasking. Moreover, the RT was longer when the distractor was presented in an auditory form versus a visual form. The IMA results showed that there were performance-related IMs coordinating different brain regions during distracted driving. The component spectral fluctuations affected by the modulators were distinct between the single- and dual-task conditions. Specifically, more modulatory weight was projected to the occipital region to address the additional distracting stimulus in both visual and auditory modality in the dual-task conditions. A comparison of modulatory weights between auditory and visual distractors showed that more modulatory weight was projected to the frontal region during the processing of the auditory distractor. This paper provides valuable insights into the temporal dynamics of attentional modulation during multitasking as well as an understanding of the underlying brain mechanisms that mediate the synchronization across brain regions and govern the allocation of attention in distracted driving.
Doborjeh, M, Kasabov, N, Doborjeh, Z, Enayatollahi, R, Tu, E & Gandomi, AH 2019, 'Personalised modelling with spiking neural networks integrating temporal and static information', Neural Networks, vol. 119, pp. 162-177.
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This paper proposes a new personalised prognostic/diagnostic system that supports classification, prediction and pattern recognition when both static and dynamic/spatiotemporal features are presented in a dataset. The system is based on a proposed clustering method (named d2WKNN) for optimal selection of neighbouring samples to an individual with respect to the integration of both static (vector-based) and temporal individual data. The most relevant samples to an individual are selected to train a Personalised Spiking Neural Network (PSNN) that learns from sets of streaming data to capture the space and time association patterns. The generated time-dependant patterns resulted in a higher accuracy of classification/prediction (80% to 93%) when compared with global modelling and conventional methods. In addition, the PSNN models can support interpretability by creating personalised profiling of an individual. This contributes to a better understanding of the interactions between features. Therefore, an end-user can comprehend what interactions in the model have led to a certain decision (outcome). The proposed PSNN model is an analytical tool, applicable to several real-life health applications, where different data domains describe a person's health condition. The system was applied to two case studies: (1) classification of spatiotemporal neuroimaging data for the investigation of individual response to treatment and (2) prediction of risk of stroke with respect to temporal environmental data. For both datasets, besides the temporal data, static health data were also available. The hyper-parameters of the proposed system, including the PSNN models and the d2WKNN clustering parameters, are optimised for each individual.
Dong, B, Xia, Z, Sun, J, Dai, X, Chen, X & Ni, B-J 2019, 'The inhibitory impacts of nano-graphene oxide on methane production from waste activated sludge in anaerobic digestion', Science of The Total Environment, vol. 646, pp. 1376-1384.
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Dong, M, Wen, S, Zeng, Z, Yan, Z & Huang, T 2019, 'Sparse fully convolutional network for face labeling', Neurocomputing, vol. 331, pp. 465-472.
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© 2018 Elsevier B.V. This paper proposes a sparse fully convolutional network (FCN) for face labeling. FCN has demonstrated strong capabilities in learning representations for semantic segmentation. However, it often suffers from heavy redundancy in parameters and connections. To ease this problem, group Lasso regularization and intra-group Lasso regularization are utilized to sparsify the convolutional layers of the FCN. Based on this framework, parameters that correspond to the same output channel are grouped into one group, and these parameters are simultaneously zeroed out during training. For the parameters in groups that are not zeroed out, intra-group Lasso provides further regularization. The essence of the regularization framework lies in its ability to offer better feature selection and higher sparsity. Moreover, a fully connected conditional random fields (CRF) model is used to refine the output of the sparse FCN. The proposed approach is evaluated on the LFW face dataset with the state-of-the-art performance. Compared with a non-regularized FCN, the sparse FCN reduces the number of parameters by 91.55% while increasing the segmentation performance by 11% relative error reduction.
Dong, W, Li, W, Long, G, Tao, Z, Li, J & Wang, K 2019, 'Electrical resistivity and mechanical properties of cementitious composite incorporating conductive rubber fibres', Smart Materials and Structures, vol. 28, no. 8, pp. 085013-085013.
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© 2019 IOP Publishing Ltd. Conductive cementitious composites with excellent conductivity and piezoresistivity can be potentially used for pavement deicing, concrete corrosion evaluations or structural health monitoring. Inspired by the practice of recycling rubber wastes for concrete manufacturing, the conductive rubbers are first added as enhanced fillers to improve the electrical conductivity of cementitious composite in this study. Based on the experimental investigations on electrical resistivity, mechanical properties and microstructure, the results show that cementitious composites containing conductive rubber fibres exhibit relatively low resistivity with nearly one order of magnitude to approximately 1 × 104 Ω cm. On the other hand, cementitious composites with aluminium/silver filled rubber (AR) exhibit better conductivity than the counterparts with carbon black filled rubber (CR). For CR reinforced composites (CRC) and AR reinforced composite (ARC) with more than 40 rubber fibres (0.64 vol%), the higher the rubber fibre content, the better is the conductivity but the slightly lower the compressive strength. The cementitious composites reinforced by 100 conductive rubber fibres (1.6 vol%) not only display excellent conductivity but also provides acceptable mechanical properties, with up to 30.6% increase in ultimate strain but only 17.3% reduction in compressive strength. Furthermore, cementitious composites with rubber fibres demonstrate better damping capacity by enlarging stress-strain hysteresis loops compared to the counterpart without rubber. Such promising conductivity and damping properties provide the cementitious composites with great potentials for being used as cementitious composite sensors and smart composites to self-monitor the structural health or traffic load of various transportation infrastructures, such as bridges, highways and pavements.
Dong, W, Li, W, Lu, N, Qu, F, Vessalas, K & Sheng, D 2019, 'Piezoresistive behaviours of cement-based sensor with carbon black subjected to various temperature and water content', Composites Part B: Engineering, vol. 178, pp. 107488-107488.
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Dong, W, Li, W, Shen, L & Sheng, D 2019, 'Piezoresistive behaviours of carbon black cement-based sensors with layer-distributed conductive rubber fibres', Materials & Design, vol. 182, pp. 108012-108012.
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Dong, X & Yang, Y 2019, 'Network Pruning via Transformable Architecture Search', Advances in Neural Information Processing Systems, vol. 32.
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Network pruning reduces the computation costs of an over-parameterized
network without performance damage. Prevailing pruning algorithms pre-define
the width and depth of the pruned networks, and then transfer parameters from
the unpruned network to pruned networks. To break the structure limitation of
the pruned networks, we propose to apply neural architecture search to search
directly for a network with flexible channel and layer sizes. The number of the
channels/layers is learned by minimizing the loss of the pruned networks. The
feature map of the pruned network is an aggregation of K feature map fragments
(generated by K networks of different sizes), which are sampled based on the
probability distribution.The loss can be back-propagated not only to the
network weights, but also to the parameterized distribution to explicitly tune
the size of the channels/layers. Specifically, we apply channel-wise
interpolation to keep the feature map with different channel sizes aligned in
the aggregation procedure. The maximum probability for the size in each
distribution serves as the width and depth of the pruned network, whose
parameters are learned by knowledge transfer, e.g., knowledge distillation,
from the original networks. Experiments on CIFAR-10, CIFAR-100 and ImageNet
demonstrate the effectiveness of our new perspective of network pruning
compared to traditional network pruning algorithms. Various searching and
knowledge transfer approaches are conducted to show the effectiveness of the
two components. Code is at: https://github.com/D-X-Y/NAS-Projects.
Dong, X, Qiu, P, Lu, J, Cao, L & Xu, T 2019, 'Mining Top-${k}$ Useful Negative Sequential Patterns via Learning', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 9, pp. 2764-2778.
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As an important tool for behavior informatics, negative sequential patterns (NSPs) (such as missing a medical treatment) are sometimes much more informative than positive sequential patterns (PSPs) (e.g., attending a medical treatment) in many applications. However, NSP mining is at an early stage and faces many challenging problems, including 1) how to mine an expected number of NSPs; 2) how to select useful NSPs; and 3) how to reduce high time consumption. To solve the first problem, we propose an algorithm Topk-NSP to mine the k most frequent negative patterns. In Topk-NSP, we first mine the top- k PSPs using the existing methods, and then we use an idea which is similar to top- k PSPs mining to mine the top- k NSPs from these PSPs. To solve the remaining two problems, we propose three optimization strategies for Topk-NSP. The first optimization strategy is that, in order to consider the influence of PSPs when selecting useful top- k NSPs, we introduce two weights, wP and wN , to express the user preference degree for NSPs and PSPs, respectively, and select useful NSPs by a weighted support wsup. The second optimization strategy is to merge wsup and an interestingness metric to select more useful NSPs. The third optimization strategy is to introduce a pruning strategy to reduce the high computational costs of Topk-NSP. Finally, we propose an optimization algorithm Topk-NSP+. To the best of our knowledge, Topk-NSP+ is the first algorithm that can mine the top- k useful NSPs. The experimental results on four synthetic and two real-life data sets show that the Topk-NSP+ is very efficient in mining the top- k NSPs in the sense of computational cost and scalability.
Dong, X, Yan, Y, Tan, M, Yang, Y & Tsang, IW 2019, 'Late Fusion via Subspace Search With Consistency Preservation', IEEE Transactions on Image Processing, vol. 28, no. 1, pp. 518-528.
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In many real-world applications, data can be represented by multiple ways or multi-view features to describe various characteristics of data. In this sense, the prediction performance can be significantly improved by taking advantages of these features together. Late fusion, which combines the predictions of multiple features, is a commonly used approach to make the final decision for a test instance. However, it is ubiquitous that different features dispute the prediction on the same data with each other, leading to performance degeneration. In this paper, we propose an efficient and effective matrix factorization-based approach to fuse predictions from multiple sources. This approach leverages a hard constraint on the matrix rank to preserve the consistency of predictions by various features, and we thus named it as Hard-rank Constraint Matrix Factorization-based fusion (HCMF). HCMF can avoid the performance degeneration caused by the controversy of multiple features. Extensive experiments demonstrate the efficacy of HCMF for outlier detection and the performance improvement, which outperforms the state-of-the-art late fusion algorithms on many data sets.
Dong, Y, Lu, Z, Liu, Y, Zhang, Q & Wu, D 2019, 'China’s corridors-in-the-sky design and space-time congestion identification and the influence of air routes’ traffic flow', Journal of Geographical Sciences, vol. 29, no. 12, pp. 1999-2014.
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© 2019, Science Press. With rapid development of air transportation, the airspace structure of the future will need to be flexible and dynamic to accommodate the increase in traffic demand. The corridors-in-the-sky has become a new technology to support the full exploitation and utilization of airspace resources. This paper proposes a method of designing corridor, identifying congestion state, and analyzing the influence of air routes’ traffic flow. From this, we have reached a number of conclusions. (1) The congestion periods present the multi-peak “wavy” scattered distributions and the peaks back-end agglomeration characteristics in the whole day. (2) The congestion segments present the structural characteristics of unbalanced coverage and concentrated distribution to the crossing points. The corridors with high congestion level present as an italic “N-shaped” frame, which presents incomplete penetration of short segments. (3) For the temporal and spatial interaction, there are two types of congestion segments, and there are some common congestion periods in different congestion segments of multiple corridors. The high-density air route plays a relatively decisive role in corridor congestion, and the influence of two directions is unbalanced. This research can provide a basis for the dynamic evaluation of China’s airspace resources and corridors construction in the future.
Dorji, P, Kim, DI, Jiang, J, Choi, J, Phuntsho, S, Hong, S & Shon, HK 2019, 'Bromide and iodide selectivity in membrane capacitive deionisation, and its potential application to reduce the formation of disinfection by-products in water treatment', Chemosphere, vol. 234, pp. 536-544.
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Dorji, U, Tenzin, UM, Dorji, P, Wangchuk, U, Tshering, G, Dorji, C, Shon, H, Nyarko, KB & Phuntsho, S 2019, 'Wastewater management in urban Bhutan: Assessing the current practices and challenges', Process Safety and Environmental Protection, vol. 132, pp. 82-93.
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© 2019 Institution of Chemical Engineers This study reviews the current wastewater management practices and their challenges in urban Bhutan. The study data was collected from the local authorities of 35 classified towns, and the field survey was conducted for the two representative towns of Thimphu City and Khuruthang town. The study observed that only eight of the 35 classified towns (22.8%) have public sewerage systems, with an average coverage of 19.7% of Bhutan's total urban population, or 7.4% of Bhutan's entire population. The imported modular wastewater treatment technology was significantly more expensive than alternative options; however, approximately six towns have already adopted this technology, due to a lack of space for a much cheaper waste stabilisation ponds. Currently, over 80% of Bhutan's urban population depends on the on-site sanitation system for their domestic wastewater disposal; however, over 40% of these properties lacked a soak-pit system for the safe disposal of septic tank effluent. Therefore, this study indicates that urban settlements in Bhutan are potentially subjected to overflow of significant amount of hazardous septic tank effluents directly into the environment posing significant risk to public and the environment. A critical urban plot space analysis indicates that the current system of on-site sanitation is inadequate and unsuitable for the current urban settings. Since it is impractical for the government to provide public sewerage system to all the towns, a low-cost public sewerage system, or an alternative and improved on-site treatment system, needs to be explored and promoted to achieve long-term environmental objectives.
Dou, W, Tang, W, Li, S, Yu, S & Raymond Choo, K-K 2019, 'A heuristic line piloting method to disclose malicious taxicab driver’s privacy over GPS big data', Information Sciences, vol. 483, pp. 247-261.
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Dou, Y, Li, Y, Zhu, J, Wang, L, Li, A & Zhang, C 2019, 'High-frequency effects analysis of windings in magnetic properties tester with nanocrystalline core', International Journal of Applied Electromagnetics and Mechanics, vol. 61, pp. S81-S88.
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Du, G, Xu, W, Zhu, J & Huang, N 2019, 'Rotor Stress Analysis for High-Speed Permanent Magnet Machines Considering Assembly Gap and Temperature Gradient', IEEE Transactions on Energy Conversion, vol. 34, no. 4, pp. 2276-2285.
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© 1986-2012 IEEE. For predesigned high speed permanent magnet machines (HSPMMs), the accurate evaluation of rotor strength is extremely important to ensure the reliability of the rotor at high speeds. This paper mainly addresses a comprehensive study on the rotor stress of one predesigned HSPMM with predetermined dimensions, by considering the effect of the assembly gaps between the segmented PMs and between the PMs and the pole filler, and temperature gradient in the rotor. First, the influence of the assembly gaps for different rotor structures, different PM segments, different pole fillers, different material properties on the rotor stress are summarized by Ansys Workbench. Then, the full investigation on the rotor stress distribution is performed under the influence of the rotor temperature gradient, which is obtained by Ansys-Cfx. And then, by considering the non-isothermal distribution of rotor temperature, the 3D temperature-stress coupling analysis is performed to obtain the optimal sleeve thickness. After fabricating the prototype, continuous operation test is carried out, which validates the effectiveness of aforementioned theoretical analysis.
Du, J, Jing, H, Castro-Lacouture, D & Sugumaran, V 2019, 'Multi-agent simulation for managing design changes in prefabricated construction projects', Engineering, Construction and Architectural Management, vol. 27, no. 1, pp. 270-295.
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Purpose
The purpose of this paper is to develop a multi-agent-based model for quantitatively measuring how the design change management strategies improve project performance.
Design/methodology/approach
Based on questionnaires and interviews, this paper investigates the coordination mechanism of risks due to design changes in prefabricated construction (PC) projects. Combined with all the variables related with design change risks, a multi-agent-based simulation model is proposed to evaluate the design change management effect.
Findings
The coordination mechanism between design change factors, design change events, risk consequence and management strategy in PC projects is described and then the simulation-based design change management mechanism in PC projects is used to assess the effect of management strategies under dynamic scenarios.
Originality/value
PC projects have rapidly increased in recent years due to the advantages of fast construction, high quality and labor savings. Different from traditional on-site construction, the impact and risk from design changes are likely to be greater due to the prefabricated project being multi-stage, highly interactive and complex. The simulations presented in this paper make it possible to test different design change management strategies in order to study their effectiveness and support managerial decision making.
Du, W & Su, QP 2019, 'Single-molecule in vitro reconstitution assay for kinesin-1-driven membrane dynamics', Biophysical Reviews, vol. 11, no. 3, pp. 319-325.
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Intracellular membrane dynamics, especially the nano-tube formation, plays important roles in vesicle transportation and organelle biogenesis. Regarding the regulation mechanisms, it is well known that during the nano-tube formation, motor proteins act as the driven force moving along the cytoskeleton, lipid composition and its associated proteins serve as the linkers and key mediators, and the vesicle sizes play as one of the important regulators. In this review, we summarized the in vitro reconstitution assay method, which has been applied to reconstitute the nano-tube dynamics during autophagic lysosomal regeneration (ALR) and the morphology dynamics during mitochondria network formation (MNF) in a mimic and pure in vitro system. Combined with the single-molecule microscopy, the advantage of the in vitro reconstitution system is to study the key questions at a single-molecule or single-vesicle level with precisely tuned parameters and conditions, such as the motor mutation, ion concentration, lipid component, ATP/GTP concentration, and even in vitro protein knockout, which cannot easily be achieved by in vivo or intracellular studies.
Du, X, Nie, F, Wang, W, Yang, Y & Zhou, X 2019, 'Exploiting Combination Effect for Unsupervised Feature Selection by <inline-formula> <tex-math notation='LaTeX'>$\ell_{2,0}$ </tex-math> </inline-formula> Norm', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 1, pp. 201-214.
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In learning applications, exploring the cluster structures of the high dimensional data is an important task. It requires projecting or visualizing the cluster structures into a low dimensional space. The challenges are: 1) how to perform the projection or visualization with less information loss and 2) how to preserve the interpretability of the original data. Recent methods address these challenges simultaneously by unsupervised feature selection. They learn the cluster indicators based on the k nearest neighbor similarity graph, then select the features highly correlated with these indicators. Under this direction, many techniques, such as local discriminative analysis, nonnegative spectral analysis, nonnegative matrix factorization, etc., have been successfully introduced to make the selection more accurate. In this paper, we focus on enhancing the unsupervised feature selection in another perspective, namely, making the selection exploit the combination effect of the features. Given the expected feature amount, previous works operate on the whole features then select those of high coefficients one by one as the output. Our proposed method, instead, operates on a group of features initially then update the selection when a better group appears. Compared to the previous methods, the proposed method exploits the combination effect of the features by l2,0 norm. It improves the selection accuracy where the cluster structures are strongly related to a group of features. We conduct the experiments on six open access data sets from different domains. The experimental results show that our proposed method is more accurate than the recent methods which do not specially consider the combination effect of the features.
Du, Z, Ge, L, Ng, AH, Zhu, Q, Zhang, Q, Kuang, J & Dong, Y 2019, 'Long‐term subsidence in Mexico City from 2004 to 2018 revealed by five synthetic aperture radar sensors', Land Degradation & Development, vol. 30, no. 15, pp. 1785-1801.
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© 2019 John Wiley & Sons, Ltd. Anthropogenic land subsidence is an example of changes to the natural environment due to human activities and is one of the key factors in causing land degradation at a range of scales. Previous studies assessing land subsidence in the Valley of Mexico either focused on regional scale or short (noncontinuous) temporal scale. In this study, long-term land subsidence (~15 years) is mapped in Mexico City (Mexico) using two interferometric synthetic aperture radar (InSAR) methods, namely, GEOS (Geoscience and Earth Observing Systems Group)-Advance Time-series Analysis and GEOS-Small Baseline Subset. An inverse distance weighted-based integration module and maximum likelihood regression-based M estimator are introduced to further enhance these two methods. The land subsidence was continuously mapped using ENVISAT (2004–2007), ALOS-1 (2007–2011), COSMO-SkyMed (2011–2014), ALOS-2 (2014–2018), and SENTINEL-1 (2015–2017) data sets. A comparison between InSAR time-series and GPS measurement shows that the subsidence rates are consistent over 2004–2018. The subsidence map over 15 years was generated finding a maximum subsidence over 4.5 m. By comparing our InSAR results with a land use map, we find that the subsidence centre in Mexico City is mostly located in the residential regions with the consumption of groundwater contributing considerably to the local subsidence rate. A total volume of 1.20 × 108 m3 of the land in Ciudad Nezahualcoyotl subsided/degraded. A continuing subsidence process limits the potential land use causing serious land degradation. Our results may be used to assist disaster reduction plans.
Duan, H, Ye, L, Wang, Q, Zheng, M, Lu, X, Wang, Z & Yuan, Z 2019, 'Nitrite oxidizing bacteria (NOB) contained in influent deteriorate mainstream NOB suppression by sidestream inactivation', Water Research, vol. 162, pp. 331-338.
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Duan, L, Sun, C-A, Zhang, Y, Ni, W & Chen, J 2019, 'A Comprehensive Security Framework for Publish/Subscribe-Based IoT Services Communication', IEEE Access, vol. 7, pp. 25989-26001.
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Duan, N, Xu, W, Li, Y, Wang, S & Zhu, J 2019, 'A Temperature and Stress Dependent Hysteresis Model with Experiment Validation', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 34, no. 13, pp. 2686-2692.
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The design and performance analysis of the electrical equipment usually involve the coupling of electrical, magnetic, thermal, mechanical and other physical fields. With the development of numerical calculation technology of electromagnetic field and the improvement of computer performance, the electromagnetic field numerical simulation software has been widely used to analyze the coupling problem of electromagnetic field, thermal field and mechanical field. The magnetic properties of magnetic material under work conditions will be influenced by some non-magnetic factors, such as temperature and stress. However, these characteristics are difficult to be simulated by the traditional hysteresis models. In this paper, based on the microscopic magnetization mechanisms of magnetic materials, a hysteresis elemental operator, which contains two easy axes and two hard axes, has been presented. Besides, with the help of the energy minimum principle, the octagonal law which can determine the orientation of the magnetization has been introduced. By taking into account the differences between the laboratory conditions and the practical engineering manufacturing and operation, the temperature-depended saturation magnetization, temperature-depended anisotropy, and stress-depended distribution function are introduced to the hysteresis elemental operator. With the employment of the Gaussian-Gaussian distribution function and the interaction field, a temperature and stress dependent hysteresis model is proposed to simulate the magnetic properties under different temperature and stress conditions. Finally, by comparing the simulation results with the experimental measurement results, the effectiveness and viability of this proposed hysteresis model have been confirmed.
Duan, N, Xu, W, Wang, S & Zhu, J 2019, 'Quasi-3-D Cylindrical Coordinate XFEM Model of HTS Cable', IEEE Transactions on Magnetics, vol. 55, no. 6, pp. 1-4.
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© 1965-2012 IEEE. This paper presents a quasi-3-D cylindrical coordinate high-Temperature superconducting (HTS) cable model 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. The improved extended finite-element method (XFEM) is proposed to solve the field problem in close-jointed thin layers. The numerical simulation results are reported compared with the experimental test results for the case of an HTS cable with three layers.
Duong, HC, Ansari, AJ, Nghiem, LD, Cao, HT, Vu, TD & Nguyen, TP 2019, 'Membrane Processes for the Regeneration of Liquid Desiccant Solution for Air Conditioning', Current Pollution Reports, vol. 5, no. 4, pp. 308-318.
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Duong, HC, Pham, TM, Luong, ST, Nguyen, KV, Nguyen, DT, Ansari, AJ & Nghiem, LD 2019, 'A novel application of membrane distillation to facilitate nickel recovery from electroplating wastewater', Environmental Science and Pollution Research, vol. 26, no. 23, pp. 23407-23415.
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Duong, NMH, Glushkov, E, Chernev, A, Navikas, V, Comtet, J, Nguyen, MAP, Toth, M, Radenovic, A, Tran, TT & Aharonovich, I 2019, 'Facile Production of Hexagonal Boron Nitride Nanoparticles by Cryogenic Exfoliation', Nano Letters, vol. 19, no. 8, pp. 5417-5422.
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Fluorescent nanoparticles with optically robust luminescence are imperative to applications in imaging and labeling. Here we demonstrate that hexagonal boron nitride (hBN) nanoparticles can be reliably produced using a scalable cryogenic exfoliation technique with sizes below 10 nm. The particles exhibit bright fluorescence generated by color centers that act as atomic-size quantum emitters. We analyze their optical properties, including emission wavelength, photon-statistics, and photodynamics, and show that they are suitable for far-field super-resolution fluorescence nanoscopy. Our results provide a foundation for exploration of hBN nanoparticles as candidates for bioimaging, labeling, as well as biomarkers that are suitable for quantum sensing.
Dura-Bernal, S, Suter, BA, Gleeson, P, Cantarelli, M, Quintana, A, Rodriguez, F, Kedziora, DJ, Chadderdon, GL, Kerr, CC, Neymotin, SA, McDougal, RA, Hines, M, Shepherd, GMG & Lytton, WW 2019, 'NetPyNE, a tool for data-driven multiscale modeling of brain circuits', eLife, vol. 8.
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Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena.
Eager, D & Hayati, H 2019, 'Additional Injury Prevention Criteria for Impact Attenuation Surfacing Within Children's Playgrounds', ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg, vol. 5, no. 1.
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More than four decades have passed since the introduction of safety standards for impact attenuation surfaces (IAS) used in playgrounds. Falls in children's playground are a major source of injuries and IAS is one of the best methods of preventing severe head injuries. However, the ability of IAS in prevention of other types of injuries, such as upper limb fractures, is unclear. Accordingly, in this paper, ten synthetic playground surfaces were tested to examine their performance beyond the collected head injury criterion (HIC) and maximum G-force (Gmax) outputs recommended by ASTM F1292. The aim of this work was to investigate any limitations with current safety criteria and proposing additional criteria to filter hazardous IAS that technically comply with the current 1000 HIC and 200 Gmax thresholds. The proposed new criterion is called the impulse force criterion (If). If combines two important injury predictor characteristics, namely: HIC duration that is time duration of the most severe impact; and the change in momentum that addresses the IAS properties associated with bounce. Additionally, the maximum jerk (Jmax), the bounce, and the IAS absorbed work are presented. HIC, Gmax, If, and Jmax followed similar trends regarding material thickness and drop height. Moreover, the bounce and work done by the IAS on the falling missile at increasing drop heights was similar for all surfaces apart from one viscoelastic foam sample. The results presented in this paper demonstrate the limitations of current safety criteria and should, therefore, assist future research to reduce long-bone injuries in playgrounds.
Eder, K, Otter, LM, Yang, L, Jacob, DE & Cairney, JM 2019, 'Overcoming Challenges Associated with the Analysis of Nacre by Atom Probe Tomography', Geostandards and Geoanalytical Research, vol. 43, no. 3, pp. 385-395.
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Eeshwarasinghe, D, Loganathan, P & Vigneswaran, S 2019, 'Simultaneous removal of polycyclic aromatic hydrocarbons and heavy metals from water using granular activated carbon', Chemosphere, vol. 223, pp. 616-627.
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Polycyclic aromatic hydrocarbons (PAHs) and heavy metals are dangerous pollutants that commonly co-occur in water. An adsorption study conducted on the simultaneous removal of PAHs (acenaphthylene, phenanthrene) and heavy metals (Cd, Cu, Zn) by granular activated carbon (GAC) showed that, when these pollutants are present together, their adsorption was less than when they were present individually. The adsorptive removal percentage of PAHs (initial concentration 1 mg/L) was much higher than that of heavy metals (initial concentration (20 mg/L). The reduction in adsorption of PAHs by heavy metals followed the heavy metals' adsorption capacity and reduction in the negative zeta potential of GAC order (Cu > Zn > Cd). In contrast, PAHs had little effect on the zeta potential of GAC. The Langmuir adsorption capacities of acenaphthylene (0.31-2.63 mg/g) and phenanthrene (0.74-7.36 mg/g) on GAC decreased with increased metals' concentration with the reduction following the order of the metals' adsorption capacity. The kinetic adsorption data fitted to Weber and Morris plots, indicating intra-particle diffusion of both PAHs and heavy metals into the mesopores and micropores in GAC with the diffusion rates. This depended on the type of PAH and metal and whether the pollutants were present alone or together.
Eickelmann, M, Wiegand, M, Deuse, J & Bernerstätter, R 2019, 'Bewertungsmodell zur Analyse der Datenreife', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 114, no. 1-2, pp. 29-33.
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Kurzfassung
Die digitale Transformation der Unternehmensprozesse führt zu einem stetigen Anstieg verfügbarer Daten. Zur effizienten Nutzung des in den Daten verborgenen Wissens streben Unternehmen den Einsatz maschineller Lernverfahren an. Die Datenqualität hat eine herausragende Bedeutung für die Anwendbarkeit maschineller Lernverfahren sowie die resultierende Güte der Ergebnisse. Dieser Beitrag präsentiert ein Modell zur Bewertung der Datenreife, das die Evaluierung der Erfolgs-chancen industrieller Datenanalyseprojekte ermöglicht und Hinweise auf erforderliche Schritte zur Verbesserung der Datenreife gibt.
Ejeian, F, Azadi, S, Razmjou, A, Orooji, Y, Kottapalli, A, Ebrahimi Warkiani, M & Asadnia, M 2019, 'Design and applications of MEMS flow sensors: A review', Sensors and Actuators A: Physical, vol. 295, pp. 483-502.
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© 2019 Elsevier B.V. There is an indispensable need for fluid flow rate and direction sensors in various medical, industrial and environmental applications. Besides the critical demands on sensing range of flow parameters (such as rate, velocity, direction and temperature), the properties of different target gases or liquids to be sensed pose challenges to the development of reliable, inexpensive and low powered sensors. This paper presents an overview of the work done on design and development of Microelectromechanical system (MEMS)-based flow sensors in recent years. In spite of using some similar principles, diverse production methods, analysis strategies, and different sensing materials, MEMS flow sensors can be broadly categorized into three main types, namely thermal sensors, piezoresistive sensors and piezoelectric sensors. Additionally, some key challenges and future prospects for the use of the MEMS flow sensors are discussed briefly.
Ekanayake, D, Aryal, R, Hasan Johir, MA, Loganathan, P, Bush, C, Kandasamy, J & Vigneswaran, S 2019, 'Interrelationship among the pollutants in stormwater in an urban catchment and first flush identification using UV spectroscopy', Chemosphere, vol. 233, pp. 245-251.
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Assessing urban stormwater quality by investigation and characterisation of pollutants is a prerequisite for its effective management, for reuse and safe discharge. The stochastic nature of rainfall, dry weather periods, topology, human activities and climatic conditions generate and wash-off pollutants differently from event to event. This study investigated the major physico-chemical pollutants in stormwater runoff collected from an urban catchment over a period of two years. The aim of this study was to explore the use of UV spectroscopy to identify the first flush. In this study, the variation of pollutants during the passage of a rain event and the relationships among the measured pollutants was analysed to help broaden the application of UV spectroscopy beyond the detection of organic matter. Correlation analysis and principal component analysis (PCA) were performed to identify the possible relationship among measured pollutants. Although correlation analysis revealed some relationships between pollutants, in general they were not strong enough and was not helpful. PCA biplots suggested a few groups and revealed that the two components model could explain nearly 72% of the variability between pollutants. Pollutants in the group that included dissolved organic carbon (DOC) behaved in a similar manner. UV spectroscopy was applied to identify the first flush by comparing the recorded spectrum of consecutive samples that were collected in an event. Analysis of the spectra was able to isolate the point when first flush ends for DOC and pollutants that behave similar to it.
Entezari, A, Roohani, I, Li, G, Dunstan, CR, Rognon, P, Li, Q, Jiang, X & Zreiqat, H 2019, 'Architectural Design of 3D Printed Scaffolds Controls the Volume and Functionality of Newly Formed Bone', Advanced Healthcare Materials, vol. 8, no. 1, pp. 1801353-1801353.
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Entezari, A, Zhang, Z, Sue, A, Sun, G, Huo, X, Chang, C-C, Zhou, S, Swain, MV & Li, Q 2019, 'Nondestructive characterization of bone tissue scaffolds for clinical scenarios', Journal of the Mechanical Behavior of Biomedical Materials, vol. 89, pp. 150-161.
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Eskandari, M & Li, L 2019, 'Microgrid operation improvement by adaptive virtual impedance', IET Renewable Power Generation, vol. 13, no. 2, pp. 296-307.
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© The Institution of Engineering and Technology 2018.. Microgrids (MGs) are regarded as the best solution for optimal integration of the renewable energy sources into power systems. However, novel control strategies should be developed because of the distinct inherent feature of MG components in comparison to conventional power systems. Although the droop-based control method is adopted in the MG to share power among distributed generation units, its dependency to grid parameters makes its implementation not as convenient as that in conventional power systems. Virtual impedance has been proposed as the complementary part of droop control in MGs. In this study, adaptive virtual impedance is designed considering its effects on the system performance in the MG including: (i) decoupling active and reactive power control by making the grid X/R ratio high, (ii) maximum transferable power through the feeder, (iii) stability concern and (iv) precise reactive power sharing in different operating modes as well as smooth transition from connected mode to islanded mode (IM). To this end, a novel method is proposed to determine the reactive power reference of distributed generation (DG) units according to their contribution in reactive power sharing in IM. In addition, simulation in MATLAB/Simulink environment is conducted to assess the performance of the control system.
Eskandari, M, Li, L, Moradi, MH & Siano, P 2019, 'A nodal approach based state-space model of droop-based autonomous networked microgrids', Sustainable Energy, Grids and Networks, vol. 18, pp. 100216-100216.
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© 2019 Elsevier Ltd As the requirement of expensive and unreliable high band-width communication infrastructure is obviated, decentralized droop-like control method has been considered for power sharing implementation in autonomous microgrids (MGs). To this end, the power network is regarded as a communication link and voltage variables (magnitude and frequency) as control signals. This, however, reduces the stability margin of islanded MGs due to the interaction of droop controllers through the power network. Lack of inertia of droop-controlled power converters and low X/R ratio of interconnecting power lines intensify this interaction which may lead to the instability of Networked MGs (NMG). On the other hand, the existing parallel-based small signal model of MGs is inadequate to represent this interaction, as the adopted common-based reference frame (RF) is not applicable in islanded NMGs. This issue is investigated in this work in details and, inspired from power flow equations, a local RF is proposed to improve the small-signal model accuracy. Droop controllers are also correlated through the power flow equations to properly model their interaction through the power network. Moreover, the state-space model is developed in a fully decentralized approach which does not rely on any converter for any specific role. Eigenvalue analysis and simulation in MATLAB\SIMULINK platforms are executed to evaluate the effectiveness and accuracy of the proposed model.
Eskandari, M, Li, L, Moradi, MH, Siano, P & Blaabjerg, F 2019, 'Active Power Sharing and Frequency Restoration in an Autonomous Networked Microgrid', IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 4706-4717.
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Esmaili, N, Norman, BA & Rajgopal, J 2019, 'Exact analysis of (R,s,S) inventory control systems with lost sales and zero lead time', Naval Research Logistics (NRL), vol. 66, no. 2, pp. 123-132.
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© 2019 Wiley Periodicals, Inc. We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead-time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed-form solutions for the limiting distribution of the on-hand inventory level at the end of a review period, given the reorder level (s) and order-up-to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady-state equations for the corresponding Markov model. Point-of-use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items.
Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2019, 'Correction: Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models', PLOS ONE, vol. 14, no. 4, pp. e0214973-e0214973.
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Esselle, K 2019, 'Call for IEEE AP-S Distinguished Lecturer Nominations', IEEE Antennas and Propagation Magazine, vol. 61, no. 3, pp. C2-C2.
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Esselle, KP 2019, 'Distinguished Lecturer Program Update [Distinguished Lecturers]', IEEE Antennas and Propagation Magazine, vol. 61, no. 4, pp. 120-120.
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Esselle, KP 2019, 'Nominating a Distinguished Lecturer and Requesting a Lecture [Distinguished Lecturers]', IEEE Antennas and Propagation Magazine, vol. 61, no. 3, pp. 124-125.
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Etchebarne, MS, Cancino, CA & Merigó, JM 2019, 'Evolution of the business and management research in Chile', International Journal of Technology, Policy and Management, vol. 19, no. 2, pp. 108-108.
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Copyright © 2019 Inderscience Enterprises Ltd. Different aspects have enhanced the development of scientific research in business and management in Chile. The aim of this paper is to analyse the characterisation of this scientific evolution. The method used is a Bibliometric analysis. Our sample examines any paper published between 1991 and 2015 in the Web of Science (WoS) database in the area of business and management. The main results show that the publications have had a significant increase. Scientific productivity increase may be related, among other factors: to the efforts of the Chilean universities that reward and incentivise publications in WoS; the participation of academics in competitive grants (Fondecyt); and international accreditations that demand more productive universities in terms of research. The results of the study could be interesting for universities from developing countries wishing to generate policies to increase the productivity in the areas of business and management.
Fahmi, Rahman, Ong, Jan, Kusumo, Sebayang, Husin, Silitonga, Mahlia & Rahman 2019, 'Production Process and Optimization of Solid Bioethanol from Empty Fruit Bunches of Palm Oil Using Response Surface Methodology', Processes, vol. 7, no. 10, pp. 715-715.
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This study aimed to observe the potential of solid bioethanol as an alternative fuel with high caloric value. The solid bioethanol was produced from liquid bioethanol, which was obtained from the synthesis of oil palm empty fruit bunches (PEFBs) through the delignification process by using organosolv pretreatment and enzymatic hydrolysis. Enzymatic hydrolysis was conducted using enzyme (60 FPUg−1 of cellulose) at a variety of temperatures (35 °C, 70 °C, and 90 °C) and reaction times (2, 6, 12, 18, and 24 h) in order to obtain a high sugar yield. The highest sugars were yielded at the temperature of 90 °C for 48 h (152.51 mg/L). Furthermore, fermentation was conducted using Saccharomyces cerevisiae. The bioethanol yield after fermentation was 62.29 mg/L. Bioethanol was extracted by distillation process to obtain solid bioethanol. The solid bioethanol was produced by using stearic acid as the additive. In order to get high-quality solid bioethanol, the calorific value was optimized using the response surface methodology (RSM) model. This model provided the factor variables of bioethanol concentration (vol %), stearic acid (g), and bioethanol (mL) with a minus result error. The highest calorific value was obtained with 7 g stearic acid and 5 mL bioethanol (43.17 MJ/kg). Burning time was tested to observe the quality of the solid bioethanol. The highest calorific value resulted in the longest burning time. The solid bioethanol has a potential as solid fuel due to the significantly higher calorific value compared to the liquid bioethanol.
Fahmideh, M & Beydoun, G 2019, 'Big data analytics architecture design - An application in manufacturing systems.', Comput. Ind. Eng., vol. 128, pp. 948-963.
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© 2018 Elsevier Ltd Context: The rapid prevalence and potential impact of big data analytics platforms have sparked an interest amongst different practitioners and academia. Manufacturing organisations are particularly well suited to benefit from data analytics platforms in their entire product lifecycle management for intelligent information processing, performing manufacturing activities, and creating value chains. This needs a systematic re-architecting approach incorportaitng careful and thorough evaluation of goals for for integrating manufacturing legacy information systems with data analytics platforms. Furthermore, ameliorating the uncertainty of the impact the new big data architecture on system quality goals is needed to avoid cost blowout in implementation and testing phases. Objective: We propose an approach for goal-obstacle analysis and selecting suitable big data solution architectures that satisfy quality goal preferences and constraints of stakeholders at the presence of the decision outcome uncertainty. The approach will highlight situations that may impede the goals. They will be assessed and resolved to generate complete requirements of an architectural solution. Method: The approach employs goal-oriented modelling to identify obstacles causing quality goal failure and their corresponding resolution tactics. It combines fuzzy logic to explore uncertainties in solution architectures and to find an optimal set of architectural decisions for the big data enablement process of manufacturing systems. Result: The approach brings two innovations to the state of the art of big data analytics platform adoption in manufacturing systems: (i) A goal-oriented modelling for exploring goals and obstacles in integrating manufacturing systems with data analytics platforms at the requirement level and (ii) An analysis of the architectural decisions under uncertainty. The efficacy of the approach is illustrated with a scenario of reengineering a hyper-connected ...
Fahmideh, M, Beydoun, G & Low, G 2019, 'Experiential probabilistic assessment of cloud services.', Inf. Sci., vol. 502, pp. 510-524.
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© 2019 Elsevier Inc. Substantial difficulties in adopting cloud services are often encountered during upgrades of existing software systems. A reliable early stage analysis can facilitate an informed decision process of moving systems to cloud platforms. It can also mitigate risks against system quality goals. Towards this, we propose an interactive goal reasoning approach which is supported by a probabilistic layer for the precise analysis of cloud migration risks to improve the reliability of risk control. The approach is illustrated using a commercial scenario of integrating a digital document processing system to Microsoft Azure cloud platform.
Fahmideh, M, Daneshgar, F, Rabhi, FA & Beydoun, G 2019, 'A generic cloud migration process model.', Eur. J. Inf. Syst., vol. 28, no. 3, pp. 233-255.
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© 2018, © 2018 Operational Research Society. The cloud computing literature provides various ways to utilise cloud services, each with a different viewpoint and focus and mostly using heterogeneous technical-centric terms. This hinders efficient and consistent knowledge flow across the community. Little, if any, research has aimed on developing an integrated process model which captures core domain concepts and ties them together to provide an overarching view of migrating legacy systems to cloud platforms that is customisable for a given context. We adopt design science research guidelines in which we use a metamodeling approach to develop a generic process model and then evaluate and refine the model through three case studies and domain expert reviews. This research benefits academics and practitioners alike by underpinning a substrate for constructing, standardising, maintaining, and sharing bespoke cloud migration models that can be applied to given cloud adoption scenarios.
Fan, X, Li, C, Yuan, X, Dong, X & Liang, J 2019, 'An interactive visual analytics approach for network anomaly detection through smart labeling', Journal of Visualization, vol. 22, no. 5, pp. 955-971.
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© 2019, The Visualization Society of Japan. Abstract: Network anomaly detection is an important means for safeguarding network security. On account of the difficulties encountered in traditional automatic detection methods such as lack of labeled data, expensive retraining costs for new data and non-explanation, we propose a novel smart labeling method, which combines active learning and visual interaction, to detect network anomalies through the iterative labeling process of the users. The algorithms and the visual interfaces are tightly integrated. The network behavior patterns are first learned by using the self-organizing incremental neural network. Then, the model uses a Fuzzy c-means-based algorithm to do classification on the basis of user feedback. After that, the visual interfaces are updated to present the improved results of the model, which can help users to choose meaningful candidates, judge anomalies and understand the model results. The experiments show that compared to labeling without our visualizations, our method can achieve a high accuracy rate of anomaly detection with fewer labeled samples. Graphic abstract: [Figure not available: see fulltext.].
Fan, Y, Lin, X, Liang, W, Tan, G & Nanda, P 2019, 'A secure privacy preserving deduplication scheme for cloud computing', Future Generation Computer Systems, vol. 101, pp. 127-135.
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Data deduplication is a key technique to improve storage efficiency in cloud computing. By pointing redundant files to a single copy, cloud service providers greatly reduce their storage space as well as data transfer costs. Despite of the fact that the traditional deduplication approach has been adopted widely, it comes with a high risk of losing data confidentiality because of the data storage models in cloud computing. To deal with this issue in cloud storage, we first propose a TEE (trusted execution environment) based secure deduplication scheme. In our scheme, each cloud user is assigned a privilege set; the deduplication can be performed if and only if the cloud users have the correct privilege. Moreover, our scheme augments the convergent encryption with users’ privileges and relies on TEE to provide secure key management, which improves the ability of such cryptosystem to resist chosen plaintext attacks and chosen ciphertext attacks. A security analysis indicates that our scheme is secure enough to support data deduplication and to protect the confidentiality of sensitive data. Furthermore, we implement a prototype of our scheme and evaluate the performance of our prototype, experiments show that the overhead of our scheme is practical in realistic environments.
Fang, G, Lu, H, Law, A, Gallego-Ortega, D, Jin, D & Lin, G 2019, 'Gradient-sized control of tumor spheroids on a single chip', Lab on a Chip, vol. 19, no. 24, pp. 4093-4103.
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Gradient-sized spheroids can be simultaneously generated on a single chip using a liquid-dome method assisted by the surface tension. The facile method can be used for investigation of the size-dependent behaviors of spheroids in biomedical research.
Fang, J, Wu, C, Li, J, Liu, Q, Wu, C, Sun, G & Li, Q 2019, 'Phase field fracture in elasto-plastic solids: Variational formulation for multi-surface plasticity and effects of plastic yield surfaces and hardening', International Journal of Mechanical Sciences, vol. 156, pp. 382-396.
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The phase field modelling has been extended from brittle fracture to ductile fracture by incorporating plasticity. However, the effects of plastic yield functions and hardening on the fracture behaviour have not been examined systematically to date. The phase field fracture coupled with multi-surface plasticity is formulated in the variational framework for the unified yield criterion, which is able to facilitate the study on different yield surfaces. First, the homogeneous solutions of fracture in elasto-plastic solids are derived analytically for 1D and 2D cases. The results show that a greater hardening modulus would lead to an ascending branch of the stress versus strain curve; and the yield function may significantly affect the stress state and phase field damage. Second, the finite element (FE) technique is implemented for modelling the phase field fracture in elasto-plastic solids, in which the stress update and consistent tangent modular matrix are derived for the unified yield criterion. Finally, three numerical examples are presented to explore the effects of the yield function and material hardening. It is found that the yield function and material hardening could significantly affect the crack propagation and the final fracture pattern. In particular, the Tresca yield function tends to create a straight crack path orthogonal to the first principal stress, while the other yield functions show no sizeable difference in their crack paths.
Fang, J, Wu, C, Liu, Q, Sun, G & Li, Q 2019, 'Implicit Integration of the Unified Yield Criterion in the Principal Stress Space', Journal of Engineering Mechanics, vol. 145, no. 7, pp. 04019041-04019041.
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© 2019 American Society of Civil Engineers. An implicit numerical integration algorithm is presented for the unified yield criterion, which could encompass most other yield criteria. The modification matrix, which is used to convert the continuum tangent modular matrix into the consistent tangent modular matrix, is derived for the return to planes, lines, and the apex of the unified yield criterion with multisurface plasticity with discontinuities. The stress update and consistent tangent modular matrix are first derived in closed form in the principal stress space, and then they are transformed back into the general stress space by coordinate transformation. Three numerical examples are used to demonstrate the effectiveness of the presented algorithm. The correctness of the developed algorithm is validated by the analytical solution and ABAQUS solution with the built-in Mohr-Coulomb model. The developed algorithm is also demonstrated to be least twice more efficient than the ABAQUS built-in algorithm. The presented algorithm for the unified yield criterion can facilitate the understanding of the effect the intermediate principal stress. With the increase in b, the force versus deflection curve at the midspan increases for the beam under three-point bending, and the critical radius of the elastoplastic interface decreases (i.e., the plastic zone becomes small) for the circular tunnel under hydrostatic pressure.
Fang, J, Wu, C, Rabczuk, T, Wu, C, Ma, C, Sun, G & Li, Q 2019, 'Phase field fracture in elasto-plastic solids: Abaqus implementation and case studies', Theoretical and Applied Fracture Mechanics, vol. 103, pp. 102252-102252.
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© 2019 Elsevier Ltd Phase field modelling for fracture has been extended from elastic solids to elasto-plastic solids. In this study, we present the implementation procedures of a staggered scheme for phase field fracture of elasto-plastic solids in commercial finite element software Abaqus using subroutines UEL and UMAT. The UMAT is written for the constitutive behaviour of elasto-plastic solids, while the UEL is written for the phase field fracture. The phase field and displacement field are solved separately using the Newton-Raphson iteration method. In each iteration, one field is computed by freezing the other field at the last loading increment. A number of benchmark examples are tested from one single element up to 3D problems. The correctness of the staggered scheme is verified analytically in terms of the stress-strain curve and the evolution of the phase field in the one single element example. In the 2D and 3D problems, the fracture behaviour of elasto-plastic solids can be reproduced in terms of reaction force curve and crack propagation, which exhibit good agreement with the experimental observations and numerical results in literature. Not only can the proposed implementation help attract more academic researchers, but also engineering practitioners to take the advantages of phase field modelling for fracture in elasto-plastic solids. The Abaqus subroutine codes can be downloaded online from Mendeley data repository linked to this work (The link is provided in Supplementary material).
Fang, XS, Sheng, QZ, Wang, X, Chu, D & Ngu, AHH 2019, 'SmartVote: a full-fledged graph-based model for multi-valued truth discovery', World Wide Web, vol. 22, no. 4, pp. 1855-1885.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. In the era of Big Data, truth discovery has emerged as a fundamental research topic, which estimates data veracity by determining the reliability of multiple, often conflicting data sources. Although considerable research efforts have been conducted on this topic, most current approaches assume only one true value for each object. In reality, objects with multiple true values widely exist and the existing approaches that cope with multi-valued objects still lack accuracy. In this paper, we propose a full-fledged graph-based model, SmartVote, which models two types of source relations with additional quantification to precisely estimate source reliability for effective multi-valued truth discovery. Two graphs are constructed and further used to derive different aspects of source reliability (i.e., positive precision and negative precision) via random walk computations. Our model incorporates four important implications, including two types of source relations, object popularity, loose mutual exclusion, and long-tail phenomenon on source coverage, to pursue better accuracy in truth discovery. Empirical studies on two large real-world datasets demonstrate the effectiveness of our approach.
Fang, Y, Huang, X, Qin, L, Zhang, Y, Zhang, W, Cheng, R & Lin, X 2019, 'A Survey of Community Search Over Big Graphs.', CoRR, vol. abs/1904.12539, no. 1, pp. 353-392.
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© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. With the rapid development of information technologies, various big graphs are prevalent in many real applications (e.g., social media and knowledge bases). An important component of these graphs is the network community. Essentially, a community is a group of vertices which are densely connected internally. Community retrieval can be used in many real applications, such as event organization, friend recommendation, and so on. Consequently, how to efficiently find high-quality communities from big graphs is an important research topic in the era of big data. Recently, a large group of research works, called community search, have been proposed. They aim to provide efficient solutions for searching high-quality communities from large networks in real time. Nevertheless, these works focus on different types of graphs and formulate communities in different manners, and thus, it is desirable to have a comprehensive review of these works. In this survey, we conduct a thorough review of existing community search works. Moreover, we analyze and compare the quality of communities under their models, and the performance of different solutions. Furthermore, we point out new research directions. This survey does not only help researchers to have better understanding of existing community search solutions, but also provides practitioners a better judgment on choosing the proper solutions.
Fanos, AM & Pradhan, B 2019, 'A Novel Hybrid Machine Learning-Based Model for Rockfall Source Identification in Presence of Other Landslide Types Using LiDAR and GIS', Earth Systems and Environment, vol. 3, no. 3, pp. 491-506.
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© 2019, King Abdulaziz University and Springer Nature Switzerland AG. Abstract: Rockfall is a common phenomenon in mountainous and hilly areas worldwide, including Malaysia. Rockfall source identification is a challenging task in rockfall hazard assessment. The difficulty rise when the area of interest has other landslide types with nearly similar controlling factors. Therefore, this research presented and assessed a hybrid model for rockfall source identification based on the stacking ensemble model of random forest (RF), artificial neural network, Naive Bayes (NB), and logistic regression in addition to Gaussian mixture model (GMM) using high-resolution airborne laser scanning data (LiDAR). GMM was adopted to automatically compute the thresholds of slope angle for various landslide types. Chi square was utilised to rank and select the conditioning factors for each landslide type. The best fit ensemble model (RF–NB) was then used to produce probability maps, which were used to conduct rockfall source identification in combination with the reclassified slope raster based on the thresholds obtained by the GMM. Next, landslide potential area was structured to reduce the sensitivity and the noise of the model to the variations in different conditioning factors for improving its computation performance. The accuracy assessment of the developed model indicates that the model can efficiently identify probable rockfall sources with receiver operating characteristic curve accuracies of 0.945 and 0.923 on validation and training datasets, respectively. In general, the proposed hybrid model is an effective model for rockfall source identification in the presence of other landslide types with a reasonable generalisation performance. Graphic Abstract: [Figure not available: see fulltext.].
Fanos, AM & Pradhan, B 2019, 'A novel rockfall hazard assessment using laser scanning data and 3D modelling in GIS', CATENA, vol. 172, pp. 435-450.
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Fanos, AM & Pradhan, B 2019, 'A Spatial Ensemble Model for Rockfall Source Identification From High Resolution LiDAR Data and GIS', IEEE Access, vol. 7, pp. 74570-74585.
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Fanos, AM, Pradhan, B, Mansor, S, Yusoff, ZM, Abdullah, AFB & Jung, H-S 2019, 'Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data', Korean Journal of Remote Sensing, vol. 35, no. 1, pp. 93-115.
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The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.
Far, C & Far, H 2019, 'Improving energy efficiency of existing residential buildings using effective thermal retrofit of building envelope', Indoor and Built Environment, vol. 28, no. 6, pp. 744-760.
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Upgrading the energy efficiency of existing buildings is a well-known issue around the globe. Given the very low renewal rate of the building stock, thermal retrofit of the existing buildings seems to be a good solution to improve the environmental performance of the building sector. Several studies have acknowledged the lack of knowledge, experience and best-practice examples as barriers in thermal retrofit of existing buildings. Therefore, this study has focused on developing recommendations on the most effective and feasible retrofitting techniques for existing buildings and performing financial analysis of initial investment vs. return based on the quantitative results of the energy modelling. Thermal comfort modelling software FirstRate5 has been used to simulate the annual heating and cooling energy consumption of nine benchmark buildings through a range of retrofitting techniques. Dwellings of varying construction materials including weatherboard, cavity brick and brick veneer have been simulated to improve accuracy. Examining seven different thermal retrofitting options in this study, it has become apparent that there is significant heating and cooling energy reduction, with payback period of less than three years, by implementing two options of the examined retrofitting cases to existing residential dwellings.
Far, H 2019, 'Advanced computation methods for soil-structure interaction analysis of structures resting on soft soils', International Journal of Geotechnical Engineering, vol. 13, no. 4, pp. 352-359.
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Adopting the most accurate and realistic modelling technique and computation method for treatment of dynamic soil-structure interaction effects in seismic analysis and design of structures resting on soft soil deposits is one of the most discussed and challenging issues in the field of seismic design and re-qualification of different structures. In this study, a comprehensive critical review has been carried out on available and well-known modelling techniques and computation methods for dynamic soil-structure interaction analysis. Discussing and comparing the advantages and disadvantages of employing each method, in this study, the most precise and reliable modelling technique as well as computation method have been identified and proposed to be employed in studying dynamic soil-structure interaction analysis of structures resting on soft soil deposits.
Far, H & Far, C 2019, 'Timber Portal Frames vs Timber Truss-Based Systems for Residential Buildings', Advances in Civil Engineering, vol. 2019, pp. 1-7.
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A large number of structures have been built during or after the construction of a house or residential-zoned building, which are not built at the same time and/or integrally with the structural integrity of the residential dwelling. These include carports, pergolas, sheds, and barns. The typical method of constructing these structures is a general timber truss and column system. The aim of this study is to look at the feasibility and economic incentive that may be gained from using a timber portal frame system, similar to the steel or timber portal frames used for larger industrial constructions, over the traditional timber truss and column arrangement. In this study, designs for three cases of timber truss and timber portals were carried out using industry appropriate methods and standards. Using the design information and data gathered through talks with industry professionals, both methods of construction were compared on cost and overall time duration. From the comparison of the truss and portal designs, the use of timber portal frames over timber truss systems proved to have advantage in relation to overall cost and man power involved. This could certainly affect the current attitude towards the construction of small residential buildings in the future.
Farzadkhoo, M, Keshavarzi, A, Hamidifar, H & Ball, J 2019, 'Flow and longitudinal dispersion in channel with partly rigid floodplain vegetation', Proceedings of the Institution of Civil Engineers - Water Management, vol. 172, no. 5, pp. 229-240.
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The influence of rigid vegetation on the longitudinal dispersion coefficient in a compound open channel was examined using an image processing technique. To simulate floodplain vegetation, cylinders of 5 mm diameter were attached to the floodplain surface. Potassium permanganate solution was used as a conservative tracer. Instantaneous velocity components were measured using particle image velocimetry. The results showed that, compared with non-vegetated conditions, floodplain vegetation decreased the depth-averaged longitudinal velocity and maximum tracer concentration by up to 83% and 12·5%, respectively. It was also found that the magnitude of the longitudinal dispersion coefficient, K, increased with the relative flow depth, Dr (the ratio of the floodplain to main channel flow depth). Furthermore, the value of K increased by up to 39·3% for vegetated tests compared with non-vegetated tests. Moreover, the results were compared with several previous empirical equations and the most appropriate equation for prediction of K in compound channels with partly vegetated floodplain was found to be that proposed by Fischer in 1975.
Fatahi, B 2019, 'Editorial', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 172, no. 1, pp. 1-2.
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Fatimah, I, Sahroni, I, Fadillah, G, Musawwa, MM, Mahlia, TMI & Muraza, O 2019, 'Glycerol to Solketal for Fuel Additive: Recent Progress in Heterogeneous Catalysts', Energies, vol. 12, no. 15, pp. 2872-2872.
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Biodiesel has been successfully commercialized in numerous countries. Glycerol, as a byproduct in biodiesel production plant, has been explored recently for fuel additive production. One of the most prospective fuel additives is solketal, which is produced from glycerol and acetone via an acetalization reaction. This manuscript reviewed recent progress on heterogeneous catalysts used in the exploratory stage of glycerol conversion to solketal. The effects of acidity strength, hydrophobicity, confinement effect, and others are discussed to find the most critical parameters to design better catalysts for solketal production. Among the heterogeneous catalysts, resins, hierarchical zeolites, mesoporous silica materials, and clays have been explored as effective catalysts for acetalization of glycerol. Challenges with each popular catalytic material are elaborated. Future works on glycerol to solketal will be improved by considering the stability of the catalysts in the presence of water as a byproduct. The presence of water and salt in the feed is certainly destructive to the activity and the stability of the catalysts.
Fattah, IMR, Yip, HL, Jiang, Z, Yuen, ACY, Yang, W, Medwell, PR, Kook, S, Yeoh, GH & Chan, QN 2019, 'Effects of flame-plane wall impingement on diesel combustion and soot processes', Fuel, vol. 255, pp. 115726-115726.
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© 2019 Elsevier Ltd This work aims to assess the effects of flame-wall impingement on the combustion and soot processes of diesel flames. For this work, experimental measurements were performed in a constant-volume combustion chamber (CVCC) at ambient conditions that are representative of compression-ignition engines. The characteristics of impinging and free flames were compared at two identical ambient and injector conditions (20.8 kg/m3 ambient density, 6 MPa ambient pressure, 1000 K bulk temperature, 15 and 10 vol% ambient O2 concentration, and 100 MPa injection pressure). To simulate flame-wall impingement, a flat plane steel wall, normal to the injector axis, was initially placed at 53 mm from nozzle, but was varied from 53 to 35 mm during the experiments. Under the test conditions of this work, it was found that wall impingement resulted in lower soot temperature and soot content, in addition to a loss of momentum for the wall jet. The results also revealed that decreasing impingement distance from the nozzle resulted in reduced soot temperature and soot level for the wall jet. The reduced soot content observed for the wall jet appeared to be mainly driven by enhanced mixing. Flame transparency modeling was also performed to assess the uncertainties of two-color measurements for flame-plane wall impingement. The analysis indicated that the derived soot temperature and concentration values would be affected by the actual temperature profiles, rendering the technique useful to reveal trends, but not reliable for absolute soot concentration measurements.
Feng, J, Liu, L, Wu, D, Li, G, Beer, M & Gao, W 2019, 'Dynamic reliability analysis using the extended support vector regression (X-SVR)', Mechanical Systems and Signal Processing, vol. 126, pp. 368-391.
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© 2019 Elsevier Ltd For engineering applications, the dynamic system responses can be significantly affected by uncertainties in the system parameters including material and geometric properties as well as by uncertainties in the excitations. The reliability of dynamic systems is widely evaluated based on the first-passage theory. To improve the computational efficiency, surrogate models are widely used to approximate the relationship between the system inputs and outputs. In this paper, a new machine learning based metamodel, namely the extended support vector regression (X-SVR), is proposed for the reliability analysis of dynamic systems via utilizing the first-passage theory. Furthermore, the capability of X-SVR is enhanced by a new kernel function developed from the vectorized Gegenbauer polynomial, especially for solving complex engineering problems. Through the proposed approach, the relationship between the extremum of the dynamic responses and the input uncertain parameters is approximated by training the X-SVR model such that the probability of failure can be efficiently predicted without using other computational tools for numerical analysis, such as the finite element analysis (FEM). The feasibility and performance of the proposed surrogate model in dynamic reliability analysis is investigated by comparing it with the conventional ε-insensitive support vector regression (ε-SVR) with Gaussian kernel and Monte Carlo simulation (MSC). Four numerical examples are adopted to evidently demonstrate the practicability and efficiency of the proposed X-SVR method.
Feng, S, Shen, S, Huang, L, Champion, AC, Yu, S, Wu, C & Zhang, Y 2019, 'Three-dimensional robot localization using cameras in wireless multimedia sensor networks', Journal of Network and Computer Applications, vol. 146, pp. 102425-102425.
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© 2019 Elsevier Ltd We consider three-dimensional (3D) localization in wireless multimedia sensor networks (WMSNs) and seek optimal localization accuracy in order to ensure real-time data fusion of mobile robots in WMSNs. To this end, we propose a real-time 3D localization algorithm realized by a distributed architecture with various smart devices to overcome network instability and the bottleneck channel at the coordinator. We then employ the recursive least squares (RLS) algorithm to fuse the 2D image coordinates from multiple views synchronously in WMSNs and determine the mobile robot's 3D location in an indoor environment. To minimize wireless data transmission, we also develop a distributed architecture that combines various smart devices by defining the data content transmitted from multiple wireless visual sensors. Moreover, we analyze the factors influencing the network instability of various smart devices, and factors influencing the localization performance of mobile robots in a multiple-view system. Experimental results show the proposed algorithm can achieve reliable, efficient, and real-time 3D localization in indoor WMSNs.
Feng, X, Bai, X, Ni, J, Wasinger, VC, Beretov, J, Zhu, Y, Graham, P & Li, Y 2019, 'CHTOP in Chemoresistant Epithelial Ovarian Cancer: A Novel and Potential Therapeutic Target', Frontiers in Oncology, vol. 9.
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Feng, Y, Gao, W, Wu, D & Tin-Loi, F 2019, 'Machine learning aided stochastic elastoplastic analysis', Computer Methods in Applied Mechanics and Engineering, vol. 357, pp. 112576-112576.
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© 2019 Elsevier B.V. The stochastic elastoplastic analysis is investigated for structures under plane stress/strain conditions. A novel uncertain nonlinear analysis framework, namely the machine leaning aided stochastic elastoplastic analysis (MLA-SEPA), is presented herein via finite element method (FEM). The proposed MLA-SEPA is a favourable alternative to determine structural reliability when full-scale testing is not achievable, thus leading to significant eliminations of manpower and computational efforts spent in practical engineering applications. Within the MLA-SEPA framework, an extended support vector regression (X-SVR) approach is introduced and then incorporated for the subsequent uncertainty quantification. By successfully establishing the governing relationship between the uncertain system parameters and any concerned structural output, a comprehensive probabilistic profile including means, standard deviations, probability density functions (PDFs), and cumulative distribution functions (CDFs) of the structural output can be effectively established through a sampling scheme. Consequently, the nonlinear performance of the structure against both serviceability and strength limit states can be effectively investigated with the consideration of various system uncertainties. Three numerical examples are thoroughly investigated to illustrate the accuracy, applicability and effectiveness of the proposed MLA-SEPA approach.
Feng, Y, Zhao, Y, Jiang, B, Zhao, H, Wang, Q & Liu, S 2019, 'Discrepant gene functional potential and cross-feedings of anammox bacteria Ca. Jettenia caeni and Ca. Brocadia sinica in response to acetate', Water Research, vol. 165, pp. 114974-114974.
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Although the enhancement of anammox performance for wastewater treatment due to the addition of small amount of acetate has been reported, discrepant metabolic responses of different anammox species have not been experimentally evaluated. Based on metagenomics and metatranscriptomic data, we investigated the competitiveness between two typical anammox species, Candidatus Jettenia caeni (J. caeni) and Candidatus Brocadia sinica (B. sinica), in anammox consortia under mixotrophic condition, where complex metabolic interactions among anammox bacteria and heterotrophs also changed with acetate addition. Contrary to J. caeni, the dissimilatory nitrate reduction to ammonium pathway of B. sinica was markedly stimulated for improving nitrogen removal. More acetate metabolic pathways and up-regulated AMP-acs expression for acetyl-CoA synthesis in B. sinica contributed to its superiority in acetate utilization. Interestingly, cross-feedings, including the nitrogen cycle, amino acid cross-feeding and B-vitamin metabolic exchange between B. sinica and other heterotrophs seemed to be enhanced with acetate addition, contributing to a reduction in metabolic energy cost to the whole community. Our work not only clarified the mechanism underlying discrepant responses of different anammox species to acetate, but also suggests a possible strategy for obtaining higher nitrogen removal rates in wastewater treatment under low C/N ratio.
Figlioli, G, Bogliolo, M, Catucci, I, Caleca, L, Lasheras, SV, Pujol, R, Kiiski, JI, Muranen, TA, Barnes, DR, Dennis, J, Michailidou, K, Bolla, MK, Leslie, G, Aalfs, CM, Balleine, R, Baxter, R, Braye, S, Carpenter, J, Dahlstrom, J, Forbes, J, Lee, CS, Marsh, D, Morey, A, Pathmanathan, N, Scott, R, Simpson, P, Spigelman, A, Wilcken, N, Yip, D, Zeps, N, Adank, MA, Adlard, J, Agata, S, Cadoo, K, Agnarsson, BA, Ahearn, T, Aittomäki, K, Ambrosone, CB, Andrews, L, Anton-Culver, H, Antonenkova, NN, Arndt, V, Arnold, N, Aronson, KJ, Arun, BK, Asseryanis, E, Auber, B, Auvinen, P, Azzollini, J, Balmaña, J, Barkardottir, RB, Barrowdale, D, Barwell, J, Beane Freeman, LE, Beauparlant, CJ, Beckmann, MW, Behrens, S, Benitez, J, Berger, R, Bermisheva, M, Blanco, AM, Blomqvist, C, Bogdanova, NV, Bojesen, A, Bojesen, SE, Bonanni, B, Borg, A, Brady, AF, Brauch, H, Brenner, H, Brüning, T, Burwinkel, B, Buys, SS, Caldés, T, Caliebe, A, Caligo, MA, Campa, D, Campbell, IG, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Claes, KBM, Clarke, CL, Collavoli, A, Conner, TA, Cox, DG, Cybulski, C, Czene, K, Daly, MB, de la Hoya, M, Devilee, P, Diez, O, Ding, YC, Dite, GS, Ditsch, N, Domchek, SM, Dorfling, CM, dos-Santos-Silva, I, Durda, K, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Ellberg, C, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Flyger, H, Foulkes, WD, Friebel, TM, Friedman, E, Gabrielson, M, Gaddam, P, Gago-Dominguez, M, Gao, C, Gapstur, SM, Garber, J, García-Closas, M, García-Sáenz, JA, Gaudet, MM, Gayther, SA, Belotti, M, Bertrand, O, Birot, A-M, Buecher, B, Caputo, S, Dupré, A, Fourme, E, Gauthier-Villars, M, Golmard, L, Le Mentec, M, Moncoutier, V, de Pauw, A, Saule, C, Boutry-Kryza, N, Calender, A, Giraud, S, Léone, M, Bressac-de-Paillerets, B, Caron, O, Guillaud-Bataille, M, Bignon, Y-J, Uhrhammer, N, Bonadona, V, Lasset, C, Berthet, P, Castera, L, Vaur, D, Bourdon, V, Noguès, C, Noguchi, T, Popovici, C, Remenieras, A, Sobol, H, Coupier, I, Pujol, P, Adenis, C, Dumont, A, Révillion, F, Muller, D, Barouk-Simonet, E, Bonnet, F, Bubien, V, Longy, M, Sevenet, N, Gladieff, L, Guimbaud, R, Feillel, V, Toulas, C, Dreyfus, H, Leroux, CD, Peysselon, M, Rebischung, C, Legrand, C, Baurand, A, Bertolone, G, Coron, F, Faivre, L, Jacquot, C, Lizard, S, Kientz, C, Lebrun, M, Prieur, F, Fert-Ferrer, S, Mari, V, Vénat-Bouvet, L, Bézieau, S & et al. 2019, 'The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer', npj Breast Cancer, vol. 5, no. 1.
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AbstractBreast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM d...
Fis, AM & Cetindamar, D 2019, 'Unlocking the Relationship between Corporate Entrepreneurship and Firm Performance', Entrepreneurship Research Journal, vol. 0, no. 0.
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AbstractThis paper explores the relationship between corporate entrepreneurship and performance by developing a comprehensive theoretical model based on Schumpeterian understanding of entrepreneurship supported with the Theory of Planned Behavior from social psychology. The model shows how organizational culture (value) triggers a chain effect through its influence on entrepreneurial orientation (attitude) and managerial support (intentions) that ultimately generate impact on corporate entrepreneurship (behavior). We test our model in an emerging economy context and present our results with implications to theory and practice.
Fleming, C, Gunawan, C, Golzan, M, Torpy, F, Irga, P & Mcgrath, K 2019, 'Investigating the effects of air pollutant nanoparticles on the onset or progression of Alzheimer's disease', IBRO Reports, vol. 6, pp. S329-S330.
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Fraietta, A, Bown, O, Ferguson, S, Gillespie, S & Bray, L 2019, 'Rapid Composition for Networked Devices: HappyBrackets', Computer Music Journal, vol. 43, no. 2-3, pp. 89-108.
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Abstract
This article introduces an open-source Java-based programming environment for creative coding of agglomerative systems using Internet-of-Things (IoT) technologies. Our software originally focused on digital signal processing of audio—including synthesis, sampling, granular sample playback, and a suite of basic effects—but composers now use it to interface with sensors and peripherals through general-purpose input/output and external networked systems. This article examines and addresses the strategies required to integrate novel embedded musical interfaces and creative coding paradigms through an IoT infrastructure. These include: the use of advanced tooling features of a professional integrated development environment as a composition or performance interface rather than just as a compiler; techniques to create media works using features such as autodetection of sensors; seamless and serverless communication among devices on the network; and uploading, updating, and running of new compositions to the device without interruption.
Furthermore, we examined the difficulties many novice programmers experience when learning to write code, and we developed strategies to address these difficulties without restricting the potential available in the coding environment. We also examined and developed methods to monitor and debug devices over the network, allowing artists and programmers to set and retrieve current variable values to or from these devices during the performance and composition stages. Finally, we describe three types of art work that demonstrate how the software, called HappyBrackets, is being used in live-coding and dance performances, in interactive sound installations, and as an advanced composition and performance tool for multimedia works.
Franzò, S, Frattini, F, Cagno, E & Trianni, A 2019, 'A multi-stakeholder analysis of the economic efficiency of industrial energy efficiency policies: Empirical evidence from ten years of the Italian White Certificate Scheme', Applied Energy, vol. 240, pp. 424-435.
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© 2019 There is growing interest worldwide in more effective policies to promote industrial energy efficiency and mitigate climate change. The White Certificates Scheme is a market-based mechanism aimed at stimulating the adoption of Energy Efficiency Measures. The Italian White Certificates scheme - one of the most long-standing and articulated - is a successful example of industrial energy efficiency policies, considered an interesting and remarkable case by other countries, especially due to its robustness in terms of the volume of certificates traded. Despite the considerable interest in White Certificates, an in-depth analysis of the economic efficiency of the mechanism from the perspective of different stakeholders is still lacking. To address this gap, this study develops a cost-benefit evaluation framework and a multi-stakeholder economic efficiency analysis of the Italian White Certificates scheme focusing on the Italian State, utilities, players in the energy efficiency value chain, and energy users. Our findings (also corroborated with sensitivity analyses) show that the White Certificates Scheme has led to several positive impacts for almost all stakeholders involved, with the exception of energy utilities that have suffered a major economic loss mainly due to a reduction of energy sold to end users. Such loss is likely to promote a deep change in the role of utilities in the energy market in terms of the services they offer and their business models. Our findings, in addition to providing useful directions for future research, offer interesting insights and implications for policymakers who may take inspiration from the pros and cons of the Italian White Certificates scheme when promoting energy efficiency through incentive mechanisms.
Fu, C, Liu, X-Y, Yang, J, Yang, LT, Yu, S & Zhu, T 2019, 'Wormhole: The Hidden Virus Propagation Power of the Search Engine in Social Networks', IEEE Transactions on Dependable and Secure Computing, vol. 16, no. 4, pp. 693-710.
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© 2004-2012 IEEE. Today search engines are tightly coupled with social networks, and present users with a double-edged sword: They are able to acquire information interesting to users but are also capable of spreading viruses introduced by hackers. It is challenging to characterize how a search engine spreads viruses, since the search engine serves as a virtual virus pool and creates propagation paths over the underlying network structure. In this paper, we quantitatively analyze virus propagation effects and the stability of the virus propagation process in the presence of a search engine. First, although social networks have a community structure that impedes virus propagation, we find that a search engine generates a propagation wormhole. Second, we propose an epidemic feedback model and quantitatively analyze propagation effects based on a model employing four metrics: infection density, the propagation wormhole effect, the epidemic threshold, and the basic reproduction number. Third, we verify our analyses on four real-world data sets and two simulated data sets. Moreover, we prove that the proposed model has the property of partial stability. Evaluation results show that, compared the cases without a search engine, virus propagation with the search engine has a higher infection density, shorter network diameter, greater propagation velocity, lower epidemic threshold, and larger basic reproduction number.
Fu, J, Liu, Q, Liufu, K, Deng, Y, Fang, J & Li, Q 2019, 'Design of bionic-bamboo thin-walled structures for energy absorption', Thin-Walled Structures, vol. 135, pp. 400-413.
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© 2018 Elsevier Ltd Bio-inspired engineering design has drawn considerable attention in the recent years for its great structural and mechanical features. This study aimed to explore the energy absorption characteristics of a novel bionic-bamboo tube (BBT) structure subjected to axial crushing. The tubes with six different cross-sectional configurations were devised with inspiration of bamboo microstructure. The effects of rib shape and rib number were analyzed by using the finite element code LS-DYNA. The numerical results indicated that the BBT structures with the rib shape of “X” and the rib number of six exhibited the best crashworthiness. To further improve the energy absorption capabilities of these BBT structures, the multiobjective optimization was employed with respect to design variables of configurational structure, such as the rib angle of the “X” shaped cross-section, center distance and rib thickness. The response surface method (RSM) and multiobjective particle swarm optimization (MOPSO) algorithm were adopted to maximize specific energy absorption (SEA) while minimizing peak crushing force (PCF). The optimization results demonstrated that compared to the baseline design, the SEA value of the optimized BBT structure was further increased by 6.84% without sacrificing in peak crushing force.
Fujioka, T, Hoang, AT, Ueyama, T & Nghiem, LD 2019, 'Integrity of reverse osmosis membrane for removing bacteria: new insight into bacterial passage', Environmental Science: Water Research & Technology, vol. 5, no. 2, pp. 239-245.
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Fluorescent microspheres (surrogates for bacteria) allowed identification of the fact that even an intact O-ring seal can allow for some bacterial passage through the reverse osmosis membrane element.
Fujioka, T, Kodamatani, H, Nghiem, LD & Shintani, T 2019, 'Transport of N-Nitrosamines through a Reverse Osmosis Membrane: Role of Molecular Size and Nitrogen Atoms', Environmental Science & Technology Letters, vol. 6, no. 1, pp. 44-48.
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© 2018 American Chemical Society. Reliable and adequate removal of small and uncharged trace organic chemicals, particularly N-nitrosodimethylamine (NDMA) that is carcinogenic and known to occur in treated effluent, is essential for implementing direct potable water use. This study provides new insights to explain the low rejection of NDMA and other N-nitrosamines by reverse osmosis (RO) membranes by examining the role of molecular size and polarity in their molecular structure. The results show that molecular weight is not a suitable molecular property for evaluating the rejection of small uncharged chemicals. In this study, NDMA and two other uncharged chemicals have similar molecular weights (i.e., 72-74 g/mol), but their rejection by the ESPA2 RO membrane varied considerably from 30 to 88%. Instead, a minimum projection area was identified as a more suitable molecular property, indicating that size exclusion plays a primary role in their rejection. It was also determined that chemicals with more nitrogen atoms in their chemical structure consistently showed rejections lower than those of their similarly sized counterparts. The results suggest that chemicals bearing more nitrogen atoms (e.g., NDMA) have higher affinity to amide or amine functional group of a polyamide RO membrane possibly through hydrogen bonding interactions.
Gabela, J, Kealy, A, Li, S, Hedley, M, Moran, W, Ni, W & Williams, S 2019, 'The Effect of Linear Approximation and Gaussian Noise Assumption in Multi-Sensor Positioning Through Experimental Evaluation', IEEE Sensors Journal, vol. 19, no. 22, pp. 10719-10727.
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© 2001-2012 IEEE. Assumptions of Gaussianity in describing the errors of ranging data and linearization of the measurement models are well-accepted techniques for wireless tracking multi-sensor fusion. The main contribution of this paper is the empirical study on the effect of these assumptions on positioning accuracy. A local positioning system (LPS) was set up and raw data were collected using both the global satellite navigation system (GNSS) and the LPS. These data were fused to estimate position using both an extended Kalman filter (EKF) and a particle filter (PF). For these data, it was shown that the PF had an improvement in accuracy over the EKF of 67 cm (72%) with achieved accuracy of 26 cm. This improvement was attributed to the PF handling the non-linear system dynamics, rather than a linear approximation as in the EKF. Furthermore, when the PF used the fitted three-component Gaussian mixture model as the better approximation of the actual LPS ranging error distribution, rather than a Gaussian approximation, a further 3 cm (13%) reduction in positioning error was observed. Overall, the average accuracy of 23 cm was achieved for the proposed multi-sensor positioning system when the assumptions of Gaussianity are not made and the non-linear measurement model is not linearized.
Gamble, LD, Purgato, S, Murray, J, Xiao, L, Yu, DMT, Hanssen, KM, Giorgi, FM, Carter, DR, Gifford, AJ, Valli, E, Milazzo, G, Kamili, A, Mayoh, C, Liu, B, Eden, G, Sarraf, S, Allan, S, Di Giacomo, S, Flemming, CL, Russell, AJ, Cheung, BB, Oberthuer, A, London, WB, Fischer, M, Trahair, TN, Fletcher, JI, Marshall, GM, Ziegler, DS, Hogarty, MD, Burns, MR, Perini, G, Norris, MD & Haber, M 2019, 'Inhibition of polyamine synthesis and uptake reduces tumor progression and prolongs survival in mouse models of neuroblastoma', Science Translational Medicine, vol. 11, no. 477.
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MYCN regulates polyamines in neuroblastoma, and combined inhibition of polyamine synthesis and transport has therapeutic effects in mouse models.
Gan, YY, Ong, HC, Ling, TC, Chen, W-H & Chong, CT 2019, 'Torrefaction of de-oiled Jatropha seed kernel biomass for solid fuel production', Energy, vol. 170, pp. 367-374.
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Gandomi, AH, Daneshmand, M, Jha, R, Kaur, D, Ning, H, Robinson, C & Schilling, H 2019, 'Guest Editorial Nature-Inspired Approaches for IoT and Big Data', IEEE Internet of Things Journal, vol. 6, no. 6, pp. 9213-9216.
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Gandomi, AH, Deb, K, Averill, RC, Rahnamayan, S & Omidvar, MN 2019, 'Using semi-independent variables to enhance optimization search', Expert Systems with Applications, vol. 120, pp. 279-297.
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Gao, C, Ji, J, Yan, F & Liu, H 2019, 'Oscillation induced by Hopf bifurcation in the p53–Mdm2 feedback module', IET Systems Biology, vol. 13, no. 5, pp. 251-259.
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This study develops an integrated model of the p53-Mdm2 interaction composed of five basic components and time delay in the DNA damage response based on the existing research work. Some critical factors, including time delay, system parameters, and their interactions in the p53-Mdm2 system are investigated to examine their effects on the oscillatory behaviour induced by Hopf bifurcation. It is shown that the positive feedback formed between p53 and the activity of Mdm2 in the cytoplasm can cause a slight decrease in the amplitude of the p53 oscillation. The length of the time delay plays an important role in determining the amplitude and period of the oscillation and can significantly extend the parameter range for the system to demonstrate oscillatory behaviour. The numerical simulation results are found to be in good agreement with the published experimental observation. It is expected that the results of this research would be helpful to better understand the biological functions of p53 pathway and provide some clues in the treatment of cancer.
Gao, H, Liu, Z, Yang, Y, Wu, C & Geng, J 2019, 'Blast-resistant performance of aluminum foam-protected reinforced concrete slabs', Baozha Yu Chongji/Explosion and Shock Waves, vol. 39, no. 2.
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n order to study the blast-resistant protective effect of the aluminum foam slab as porous energy absorbing material on the engineering structure, using an outdoor explosion test, the dynamic response and failure modes of reinforced concrete (RC) slabs with different aluminum foam protective layers under blast loading were studied, and the finite element model was established by using the LS-DYNA software. Through comparison with the test, the feasibility of the model was verified. The dynamic responses of RC slabs with or without aluminum foam protective layers were compared and analyzed, and the effects of aluminum foam density gradient distribution and longitudinal reinforcement ratio were analyzed. The results show that the finite element model can accurately describe the dynamic response of RC slabs with aluminum foam protective layers. Aluminum foam protective layers can effectively reduce the deflection of reinforced concrete slabs and reduce the damage of specimens. The aluminum foam density increases from bottom to top, which has the best blast-resistant performance on RC slabs. Moreover, increasing the reinforcement ratio can improve the blast-resistant performance of aluminum foam-protected RC slabs.
Gao, J, Gao, L, Luo, Z & Li, P 2019, 'Isogeometric topology optimization for continuum structures using density distribution function', International Journal for Numerical Methods in Engineering, vol. 119, no. 10, pp. 991-1017.
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© 2019 John Wiley & Sons, Ltd. This paper will propose a more effective and efficient topology optimization method based on isogeometric analysis, termed as isogeometric topology optimization (ITO), for continuum structures using an enhanced density distribution function (DDF). The construction of the DDF involves two steps. (1) Smoothness: the Shepard function is firstly utilized to improve the overall smoothness of nodal densities. Each nodal density is assigned to a control point of the geometry. (2) Continuity: the high-order NURBS basis functions are linearly combined with the smoothed nodal densities to construct the DDF for the design domain. The nonnegativity, partition of unity, and restricted bounds [0, 1] of both the Shepard function and NURBS basis functions can guarantee the physical meaning of material densities in the design. A topology optimization formulation to minimize the structural mean compliance is developed based on the DDF and isogeometric analysis to solve structural responses. An integration of the geometry parameterization and numerical analysis can offer the unique benefits for the optimization. Several 2D and 3D numerical examples are performed to demonstrate the effectiveness and efficiency of the proposed ITO method, and the optimized 3D designs are prototyped using the Selective Laser Sintering technique.
Gao, J, Luo, Z, Li, H & Gao, L 2019, 'Topology optimization for multiscale design of porous composites with multi-domain microstructures', Computer Methods in Applied Mechanics and Engineering, vol. 344, pp. 451-476.
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Gao, J, Luo, Z, Li, H, Li, P & Gao, L 2019, 'Dynamic multiscale topology optimization for multi-regional micro-structured cellular composites', Composite Structures, vol. 211, pp. 401-417.
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In this paper, a new dynamic multiscale topology optimization method for cellular composites with multi-regional material microstructures is proposed to improve the structural performance. Firstly, a free-material distribution optimization method (FMDO) is developed to generate the overall configuration for the discrete element densities distributed within a multi-regional pattern. The macrostructure is divided into several sub regions, and each of them consists of a number of elements but with the same densities. Secondly, a dynamic topology optimization formulation is developed to perform the concurrent design of the macrostructure and material microstructures, subject to the multi-regional distributed element densities. A parametric level set method is employed to optimize the topologies of the macrostructure and material microstructures, with the effective macroscopic properties evaluated by the homogenization. In the numerical implementation, the quasi-static Ritz vector (QSRV) method is incorporated into the finite element analysis so as to reduce the computational cost in numerical analysis, and some kinematical connectors are introduced to make sure the connectivity between adjacent material microstructures. Finally, 2D and 3D numerical examples are tested to demonstrate the effectiveness of the proposed dynamic multiscale topology optimization method for the material-structural composites.
Gao, J, Luo, Z, Xia, L & Gao, L 2019, 'Concurrent topology optimization of multiscale composite structures in Matlab', Structural and Multidisciplinary Optimization, vol. 60, no. 6, pp. 2621-2651.
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Gao, J, Xue, H, Gao, L & Luo, Z 2019, 'Topology optimization for auxetic metamaterials based on isogeometric analysis', Computer Methods in Applied Mechanics and Engineering, vol. 352, pp. 211-236.
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© 2019 Elsevier B.V. In this paper, an effective and efficient topology optimization method, termed as Isogeometric Topology Optimization (ITO), is proposed for systematic design of both 2D and 3D auxetic metamaterials based on isogeometric analysis (IGA). Firstly, a density distribution function (DDF)with the desired smoothness and continuity, to represent the topological changes of structures, is constructed using the Shepard function and non-uniform rational B-splines (NURBS)basis functions. Secondly, an energy-based homogenization method (EBHM)to evaluate material effective properties is numerically implemented by IGA, with the imposing of the periodic boundary formulation on material microstructure. Thirdly, a topology optimization formulation for 2D and 3D auxetic metamaterials is developed based on the DDF, where the objective function is defined as a combination of the homogenized elastic tensor and the IGA is applied to solve the structural responses. A relaxed optimality criteria (OC)method is used to update the design variables, due to the non-monotonic property of the problem. Finally, several numerical examples are used to demonstrate the effectiveness and efficiency of the proposed method. A series of auxetic microstructures with different deformation mechanisms (e.g. the re-entrant and chiral)can be obtained. The auxetic behavior of material microstructures are numerically validated using ANSYS, and the optimized designs are prototyped using the Selective Laser Sintering (SLS)technique.
Gao, P, Wang, X, Huang, Z & Yu, H 2019, '11B NMR Chemical Shift Predictions via Density Functional Theory and Gauge-Including Atomic Orbital Approach: Applications to Structural Elucidations of Boron-Containing Molecules', ACS Omega, vol. 4, no. 7, pp. 12385-12392.
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Gao, X, Du, J, Zhang, T & Guo, YJ 2019, 'High-<italic>T<sub>c</sub> </italic> Superconducting Fourth-Harmonic Mixer Using a Dual-Band Terahertz On-Chip Antenna of High Coupling Efficiency', IEEE Transactions on Terahertz Science and Technology, vol. 9, no. 1, pp. 55-62.
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© 2019 IEEE. This paper presents a dual-band on-chip antenna-coupled high-T c superconducting (HTS) Josephson-junction subterahertz (THz) fourth-harmonic mixer. The antenna utilizes a couple of different structured twin slots to enable the resonant radiations at two frequencies, and integrates a well-designed coplanar waveguide network for achieving good radiation coupling and signal isolation characteristics. The electromagnetic simulations show that coupling efficiencies as high as -4 and -3.5 dB are achieved for the 160- and 640-GHz operating frequency bands, respectively. Based on this dual-band antenna, a 640-GHz HTS fourth-harmonic mixer is developed and characterized in a range of operating temperatures. The mixer exhibits a measured conversion gain of around -18 dB at 20 K and -22 dB at 40 K, respectively. The achieved intermediate frequency bandwidth is larger than 23 GHz. These are the best results reported for HTS harmonic mixers at comparable sub-THz frequency bands to date.
Gao, X, Xu, G, Li, S, Wu, Y, Dancigs, E & Du, J 2019, 'Particle Filter-Based Prediction for Anomaly Detection in Automatic Surveillance', IEEE Access, vol. 7, pp. 107550-107559.
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Gao, Y, Xu, Y, Wu, C & Fang, J 2019, 'Topology Optimization of Metal and Carbon Fiber Reinforced Plastic (CFRP) Structures under Loading Uncertainties', SAE Technical Paper Series, vol. 2019-April, no. April.
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© 2019 SAE International. All Rights Reserved. Carbon fiber reinforced plastic (CFRP) composite materials have gained particular interests due to their high specific modulus, high strength, lightweight and perfect corrosion resistance. However, in reality, CFRP composite materials cannot be used alone in some critical places such as positions of joints with hinges, locks. Therefore, metal reinforcements are usually necessary in local positions to prevent structure damage. Besides, if uncertainties present, obtained optimal structures may experience in failures as the optimization usually pushes solutions to the boundaries of constraints and has no room for tolerance and uncertainties, so robust optimization should be considered to accommodate the uncertainties in practice. This paper proposes a mixed topology method to optimize metal and carbon fiber reinforced plastic composite materials simultaneously under nondeterministic load with random magnitude and direction. A joint cost function is employed to contain both the mean and standard deviations of compliance in the robust optimization. The sensitivities of the cost function are derived with respect to the design variables in a nondeterministic context. The discrete material and thickness optimization (DMTO) technique is applied to undertake robust topology optimization for CFRP composites and metal material while the casting constraint to prevent intermediate void was introduced. In this study, two examples are presented to demonstrate the effectiveness of the proposed methods. The robust topology optimization results exhibit that the composite structures with proper distribution of materials and orientations are of more stable performance when the load fluctuates.
Garcia, JA 2019, 'A Virtual Reality Game-Like Tool for Assessing the Risk of Falling in the Elderly.', Stud Health Technol Inform, vol. 266, pp. 63-69.
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In recent years, the use of interactive game technology has gained much interest in the research community as a means to measure indicators associated with the risk of falling in the elderly. Input devices used for gaming offer an inexpensive but yet reliable alternative to the costly apparatuses used in clinics and medical centers. In this paper, we explore the feasibility of using virtual reality technology as a tool to assess the risk of falling in the senior community in a more immersive, intuitive and descriptive manner. Our VR-based tool captures stepping performance parameters in order to fulfill the requirements of a well-established clinical test for fall risk assessment. The use of virtual reality allows for an immersive experience where elderly users can fully concentrate on the motor and cognitive functions being assessed rather than the technology being used.
Garcia, MV, Luckett, T, Johnson, M, Hutchinson, A, Lal, S & Phillips, JL 2019, 'The roles of dispositional coping style and social support in helping people with respiratory disease cope with a breathlessness crisis', Journal of Advanced Nursing, vol. 75, no. 9, pp. 1953-1965.
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AIM:To explore the role of coping moderators in self-management of breathlessness crises by people with advanced respiratory disease. DESIGN:A secondary analysis of semi-structured interview data. METHODS:Interviews with patients who had advanced respiratory disease, chronic breathlessness and at least one experience where they considered presenting to Emergency but self-managed instead (a "near miss"). Participants were recruited from New South Wales, Queensland, Victoria, South Australia or Tasmania. Eligible caregivers were those who contributed to Emergency-related decision-making. Interviews were coded inductively and then deductively against the coping moderators social support and dispositional coping style, defined by the Transactional Model of Stress and Coping. RESULTS:Interviews were conducted between October 2015 - April 2016 with 20 patients and three caregivers. Social networks offered emotional and practical support but also had potential for conflict with patients' 'hardy' coping style. Patient hardiness (characterized by a sense of 'commitment' and 'challenge') promoted a proactive approach to self-management but made some patients less willing to accept support. Information-seeking tendencies varied between patients and were sometimes shared with caregivers. An optimistic coping style appeared to be less equivocally beneficial. CONCLUSION:This study shows that social support and coping style may influence how people self-manage through their breathlessness crises and identified ways coping moderators can facilitate or hinder effective self-management. IMPACT:This study confers insights into how social-support and coping style can be supported and optimized to facilitate breathlessness self-management. Acknowledging coping moderator interactions is beneficial for developing resources and strategies that recognise patient mastery.
Gardner, A & Willey, K 2019, 'The role of peer review in identity development for engineering education researchers', European Journal of Engineering Education, vol. 44, no. 3, pp. 347-359.
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Gargiulo, G, Bifulco, P, Cesarelli, M, McEwan, A, Nikpour, A, Jin, C, Gunawardana, U, Sreenivasan, N, Wabnitz, A & Hamilton, T 2019, 'Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented', Sensors, vol. 19, no. 4, pp. 772-772.
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The Open-electroencephalography (EEG) framework is a popular platform to enable EEG measurements and general purposes Brain Computer Interface experimentations. However, the current platform is limited by the number of available channels and electrode compatibility. In this paper we present a fully configurable platform with up to 32 EEG channels and compatibility with virtually any kind of passive electrodes including textile, rubber and contactless electrodes. Together with the full hardware details, results and performance on a single volunteer participant (limited to alpha wave elicitation), we present the brain computer interface (BCI)2000 EEG source driver together with source code as well as the compiled (.exe). In addition, all the necessary device firmware, gerbers and bill of materials for the full reproducibility of the presented hardware is included. Furthermore, the end user can vary the dry-electrode reference circuitry, circuit bandwidth as well as sample rate to adapt the device to other generalized biopotential measurements. Although, not implemented in the tested prototype, the Biomedical Analogue to Digital Converter BIOADC naturally supports SPI communication for an additional 32 channels including the gain controller. In the appendix we describe the necessary modification to the presented hardware to enable this function.
Gautam, S, Lu, Y, Xiao, W, Lu, DD & Golsorkhi, MS 2019, 'Dual‐loop control of transfer delay based PLL for fast dynamics in single‐phase AC power systems', IET Power Electronics, vol. 12, no. 13, pp. 3571-3581.
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© The Institution of Engineering and Technology 2019. Phase-locked loop (PLL) is commonly utilised for AC power systems to detect phase and frequency. With the increasing use of small-scale distributed power generation, the technique becomes widely available for grid interconnection of renewable power source into single-phase AC distribution network. Through comprehensive analysis and design, this study proposed a new approach that includes dual independent control loops to enhance the transfer delay-based PLL capability in terms of speed and accuracy. The effectiveness and advantages of the proposed PLL structure are demonstrated by numerical simulation and verified by experimental test.
Gaviria-Marin, M, Merigó, JM & Baier-Fuentes, H 2019, 'Knowledge management: A global examination based on bibliometric analysis', Technological Forecasting and Social Change, vol. 140, pp. 194-220.
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© 2018 Knowledge management (KM) is a field of research that has gained wide acceptance in the scientific community and management literature. This article presents a bibliometric overview of the academic research on KM in the business and management areas. Various bibliometric methods are used to perform this overview, including performance analysis and science mapping of the KM field. The performance analysis uses a series of bibliometric indicators, such as the h-index, productivity and citations. In addition, the VOSviewer software is used to map the bibliographic material. Science mapping uses co-citations and the concurrency of keywords. References were obtained from the Web of Science database. We identified and classified the most relevant research in the field according to journals, articles, authors, institutions and countries. The results show that research in this field has increased significantly in the last ten years and that the USA is the most influential country in all aspects in this field. It is important to consider, however, that science continues to advance in this and in all fields and that data rapidly change over time. Therefore, this paper fulfills an informational role that shows that most of the fundamental research of KM is in business and management areas.
Gay, VC, Garcia, JA & Leong, TW 2019, 'Using Asynchronous Exergames to Encourage an Active Ageing Lifestyle: Solitaire Fitness Study Protocol.', Stud Health Technol Inform, vol. 266, pp. 70-75.
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A healthy and active lifestyle can significantly improve the well-being and quality of life; however, some elderly people struggle to stay motivated and engaged with any form of exercise. The project Elaine (Elderly, AI and New Experiences) addresses this problem by seeking to improve the quality of life of the elderly through exergames. Currently, the project explores a novel approach in the field of health informatics called asynchronous exergaming. This approach, a new trend in games in the health domain, allows the elderly to workout at their own pace, and in their own time, with their physical activity linked asynchronously to a game. This paper presents the study protocol for Solitaire Fitness, a new asynchronous exergame developed by the team. The game aims at increasing the motivation of the elderly to engage in physical exercise whilst helping to maintain their cognitive abilities. It also describes the protocol for the trial. The result of this research has the potential to benefit elderly that need nudging to be motivated to exercise, health care providers treating people with sedentary lifestyles and researchers investigating ways to encourage the elderly to exercise.
Geekiyanage, NM, Balanant, MA, Sauret, E, Saha, S, Flower, R, Lim, CT & Gu, Y 2019, 'A coarse-grained red blood cell membrane model to study stomatocyte-discocyte-echinocyte morphologies', PLOS ONE, vol. 14, no. 4, pp. e0215447-e0215447.
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An improved red blood cell (RBC) membrane model is developed based on the bilayer coupling model (BCM) to accurately predict the complete sequence of stomatocyte-discocyte-echinocyte (SDE) transformation of a RBC. The coarse-grained (CG)-RBC membrane model is proposed to predict the minimum energy configuration of the RBC from the competition between lipid-bilayer bending resistance and cytoskeletal shear resistance under given reference constraints. In addition to the conventional membrane surface area, cell volume and bilayer-leaflet-area-difference constraints, a new constraint: total-membrane-curvature is proposed in the model to better predict RBC shapes in agreement with experimental observations. A quantitative evaluation of several cellular measurements including length, thickness and shape factor, is performed for the first time, between CG-RBC model predicted and three-dimensional (3D) confocal microscopy imaging generated RBC shapes at equivalent reference constraints. The validated CG-RBC membrane model is then employed to investigate the effect of reduced cell volume and elastic length scale on SDE transformation, to evaluate the RBC deformability during SDE transformation, and to identify the most probable RBC cytoskeletal reference state. The CG-RBC membrane model can predict the SDE shape behaviour under diverse shape-transforming scenarios, in-vitro RBC storage, microvascular circulation and flow through microfluidic devices.
Geng, J, Ziolkowski, RW, Wang, K, Zhao, X, Zhou, H, Chenhu, G, Liang, X & Jin, R 2019, 'Dual CP Polarization Diversity and Space Diversity Antennas Enabled by a Compact T-Shaped Feed Structure', IEEE Access, vol. 7, pp. 96284-96296.
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© 2013 IEEE. A compact T-shaped feed structure (TFS) is reported that enables the realization of two types of diversity antennas: a polarization diversity antenna (PDA) and a spatial diversity antenna (SDA). Both systems have a high potential for mobile wireless communication applications. The TFS includes four ports and two independent coaxial channels with effective isolation between them all. The PDA is a dual CP omnidirectional antenna. Its optimized prototype achieves measured impedance bandwidths of 16.4% and 15.28% in its LHCP and RHCP states, respectively, and realized gains in both between 4.8 and 6.46 dBic. The inner thin coaxial cable (ITCC) of the TFS directly drives its LHCP subsystem, facilitating its improved omnidirectional performance. This ITCC is also used to directly feed the SDA's low-profile directional planar equiangular spiral antenna and its side port drives its omnidirectional RHCP antenna. Good hemispherical coverage is realized with a measured common impedance bandwidth larger than 14.35% with more than 40-dB isolation between its two ports. The corresponding measured realized gain of the SDA is between 4 and 7.8 dBic. The measured results for both optimized prototypes confirm their simulated performance characteristics.
Geng, L, Lu, Z, He, L, Zhang, J, Li, X & Guo, X 2019, 'Smart charging management system for electric vehicles in coupled transportation and power distribution systems', Energy, vol. 189, pp. 116275-116275.
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© 2019 Elsevier Ltd With the increasing popularity of electric vehicles, the connections between urban transportation and power distribution systems gradually change from independent to tightly coupled. To promote the coordinated operation of the two kind of systems, this paper proposes a smart charging management system considering the elastic response of electric vehicle users to electricity charging price. In this system, a multi-class user traffic equilibrium assignment model with elastic charging demand is formulated to capture link flow distributions of vehicles across the urban transportation network and estimate charging demand of each fast charging station. An alternating current optimal power flow model for power distribution network is also established to calculate optimal charging capacity of each fast charging station and scheduling plan of generators. Combining the above two models, a distributed coordination pricing method is designed based on alternating direction multiplier method, which can obtain a proper electricity charging price signal to better manage electric vehicles. A case study is performed to show the effectiveness of the proposed model and the distributed coordination pricing method.
Gentil, CL, Vidal-Calleja, T & Huang, S 2019, 'IN2LAAMA: INertial Lidar Localisation Autocalibration And MApping', IEEE Transactions on Robotics, vol. 37, no. 1, pp. 275-290.
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In this paper, we present INertial Lidar Localisation Autocalibration And
MApping (IN2LAAMA): an offline probabilistic framework for localisation,
mapping, and extrinsic calibration based on a 3D-lidar and a 6-DoF-IMU. Most of
today's lidars collect geometric information about the surrounding environment
by sweeping lasers across their field of view. Consequently, 3D-points in one
lidar scan are acquired at different timestamps. If the sensor trajectory is
not accurately known, the scans are affected by the phenomenon known as motion
distortion. The proposed method leverages preintegration with a continuous
representation of the inertial measurements to characterise the system's motion
at any point in time. It enables precise correction of the motion distortion
without relying on any explicit motion model. The system's pose, velocity,
biases, and time-shift are estimated via a full batch optimisation that
includes automatically generated loop-closure constraints. The autocalibration
and the registration of lidar data rely on planar and edge features matched
across pairs of scans. The performance of the framework is validated through
simulated and real-data experiments.
Gentile, C, Kesteven, S, Wu, J, Bursill, C, Davies, MJ & Figtree, G 2019, 'Abstract 138: A Novel Cellular and Genetic Approach to Investigate the Cardioprotective Role Played by Endothelial Nitric Oxide Synthase in Myocardial Infarction', Circulation Research, vol. 125, no. Suppl_1.
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The loss of regenerative properties in adult cardiomyocytes (CMs) is directly linked to their inability to proliferate. Following an extensive ischaemic event in an aged heart, fibrotic scar formation is the only repair process and eventually heart failure develops. However, molecular and cellular cues in the neonatal heart support that cardiac regeneration is possible in presence of proliferating CMs. Based on previous studies demonstrating that endothelial nitric oxide synthase (eNOS) regulates proliferation in both endothelial cells (ECs) and CMs, we hypothesized that eNOS signaling could play a cardioprotective role. To test our hypothesis, we injected different combinations of co-cultured ECs and CMs in the LV muscle wall of MI mice (permanent LAD ligation). First, injected cells were isolated from either WT or KO eNOS neonatal mice and then co-cultured to form 3D vascularized cardiac spheroids (VCSs), which were eventually transplanted in adult MI mice on the day of the procedure. Control infarcted animals received media-only (vehicle). Other mice received a suspension of co-cultured VCSs in media as follows:
i
) WT CMs and ECs;
ii
) WT CMs and KO ECs;
iii
) KO CMs and WT ECs. Following 28 days, injection of WT cells increased the ejection fraction (EF%) by 20% compared with control animals (61%±4% and 41%±11%, respectively). When eNOS was absent in either CMs or ECs, the EF% was 40%±5% and 46%±2%, respectively, suggesting that the eNOS-mediated protection is dependent on its presence in both cells. Histological analyses confirmed the presence of WT VCSs in MI mice, contributing to a thicker wall thickness compared to vehicle MI mice. No VCSs were observed in the LV wall when KO cells were injected. Therefore, our results strongly suggest that eNOS may play a major role via both an auto...
Gerami, A, Alzahid, Y, Mostaghimi, P, Kashaninejad, N, Kazemifar, F, Amirian, T, Mosavat, N, Ebrahimi Warkiani, M & Armstrong, RT 2019, 'Microfluidics for Porous Systems: Fabrication, Microscopy and Applications', Transport in Porous Media, vol. 130, no. 1, pp. 277-304.
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© 2018, Springer Nature B.V. No matter how sophisticated the structures are and on what length scale the pore sizes are, fluid displacement in porous media can be visualized, captured, mimicked and optimized using microfluidics. Visualizing transport processes is fundamental to our understanding of complex hydrogeological systems, petroleum production, medical science applications and other engineering applications. Microfluidics is an ideal tool for visual observation of flow at high temporal and spatial resolution. Experiments are typically fast, as sample volume is substantially low with the use of miniaturized devices. This review first discusses the fabrication techniques for generating microfluidics devices, experimental setups and new advances in microfluidic fabrication using three-dimensional printing, geomaterials and biomaterials. We then address multiphase transport in subsurface porous media, with an emphasis on hydrology and petroleum engineering applications in the past few decades. We also cover the application of microfluidics to study membrane systems in biomedical science and particle sorting. Lastly, we explore how synergies across different disciplines can lead to innovations in this field. A number of problems that have been resolved, topics that are under investigation and cutting-edge applications that are emerging are highlighted.
Ghadi, MJ, Ghavidel, S, Rajabi, A, Azizivahed, A, Li, L & Zhang, J 2019, 'A review on economic and technical operation of active distribution systems', Renewable and Sustainable Energy Reviews, vol. 104, pp. 38-53.
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© 2019 Elsevier Ltd Along with the advent of restructuring in power systems, considerable integration of renewable energy resources has motivated the transition of traditional distribution networks (DNs) toward new active ones. In the meanwhile, rapid technology advances have provided great potentials for future bulk utilization of generation units as well as the energy storage (ES) systems in the distribution section. This paper aims to present a comprehensive review of recent advancements in the operation of active distribution systems (ADSs) from the viewpoint of operational time-hierarchy. To be more specific, this time-hierarchy consists of two stages, and at the first stage of this time-hierarchy, four major economic factors, by which the operation of traditional passive DNs is evolved to new active DNs, are described. Then the second stage of the time-hierarchy refers to technical management and power quality correction of ADSs in terms of static, dynamic and transient periods. In the end, some required modeling and control developments for the optimal operation of ADSs are discussed. As opposed to previous review papers, potential applications of devices in the ADS are investigated considering their operational time-intervals. Since some of the compensating devices, storage units and generating sources may have different applications regarding the time scale of their utilization, this paper considers real scenario system operations in which components of the network are firstly scheduled for the specified period ahead; then their deviations of operating status from reference points are modified during three time-intervals covering static, dynamic and transient periods.
Ghadi, MJ, Rajabi, A, Ghavidel, S, Azizivahed, A, Li, L & Zhang, J 2019, 'From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors', Applied Energy, vol. 253, pp. 113543-113543.
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© 2019 Elsevier Ltd Restructuring of power systems along with the integration of renewable energy resources in electricity networks have transformed traditional distribution networks (DNs) into new active distribution systems (ADSs). In addition, rapid advancement of technology has enabled the bulk utilization of power generation units and energy storage (ES) systems in distribution networks. The next step in this trend is to decentralize ADSs to microgrids (MGs). This paper aims to present a review on the recent advancements in the development of ADSs and MGs. In this respect, the regulatory requirements and economic concepts, by which the traditional passive DNs are evolved into ADSs, are categorized and illustrated first. Then, the state-of-the-art of ADS formation is detailed based on the novel standpoint of grid operation factors which are involved in deregulated electricity markets at the distribution level. After presenting highlighted projects of MGs across the world, a similar review approach has been adopted to explain the formation of MGs which play a vital role in the decentralization of ADSs. This survey can provide both policy makers and distribution system planners with new perspectives to establish or participate in day-ahead wholesale markets.
Ghaffari Jadidi, M, Valls Miro, J & Dissanayake, G 2019, 'Sampling-based incremental information gathering with applications to robotic exploration and environmental monitoring', The International Journal of Robotics Research, vol. 38, no. 6, pp. 658-685.
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We propose a sampling-based motion-planning algorithm equipped with an information-theoretic convergence criterion for incremental informative motion planning. The proposed approach allows dense map representations and incorporates the full state uncertainty into the planning process. The problem is formulated as a constrained maximization problem. Our approach is built on rapidly exploring information-gathering algorithms and benefits from the advantages of sampling-based optimal motion-planning algorithms. We propose two information functions and their variants for fast and online computations. We prove an information-theoretic convergence for an entire exploration and information-gathering mission based on the least upper bound of the average map entropy. A natural automatic stopping criterion for information-driven motion control results from the convergence analysis. We demonstrate the performance of the proposed algorithms using three scenarios: comparison of the proposed information functions and sensor configuration selection, robotic exploration in unknown environments, and a wireless signal strength monitoring task in a lake from a publicly available dataset collected using an autonomous surface vehicle.
Ghantous, GB & Gill, AQ 2019, 'An Agile-DevOps Reference Architecture for Teaching Enterprise Agile', International Journal of Learning, Teaching and Educational Research, vol. 18, no. 7, pp. 128-144.
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DevOps emerged as an important extension to support the Agile development for frequent and continuous software delivery. The adoption of Agile-DevOps for large scale enterprise agility depends on the most important human capability such as people competency and experience. Hence, academic education and professional training is key to the successful adoption of Agile-DevOps approach. Thus, education and training providers need to teach Agile-DevOps. However, the challenge is: how to establish and simulate an effective Agile-DevOps technology environment for teaching Enterprise Agile? This paper introduces the integrated Adaptive Enterprise Project Management (AEPM) and DevOps Reference Architecture (DRA) approach for adopting and teaching the Agile-DevOps with the help of a teaching case study from the University of Technology - Sydney (UTS), Australia. These learnings can be utilised by educators to develop and teach practice-oriented Agile-DevOps for software engineering courses. Furthermore, the experience and observations can be employed by researchers and practitioners aiming to integrate Agile-DevOps at the large enterprise scale.
Ghasemi, M, Akbari, E, Rahimnejad, A, Razavi, SE, Ghavidel, S & Li, L 2019, 'Phasor particle swarm optimization: a simple and efficient variant of PSO', Soft Computing, vol. 23, no. 19, pp. 9701-9718.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Particle swarm optimizer is a well-known efficient population and control parameter-based algorithm for global optimization of different problems. This paper focuses on a new and primary sample for PSO, which is named phasor particle swarm optimization (PPSO) and is based on modeling the particle control parameters with a phase angle (θ), inspired from phasor theory in the mathematics. This phase angle (θ) converts PSO algorithm to a self-adaptive, trigonometric, balanced, and nonparametric meta-heuristic algorithm. The performance of PPSO is tested on real-parameter optimization problems including unimodal and multimodal standard test functions and traditional benchmark functions. The optimization results show good and efficient performance of PPSO algorithm in real-parameter global optimization, especially for high-dimensional optimization problems compared with other improved PSO algorithms taken from the literature. The phasor model can be used to expand different types of PSO and other algorithms. The source codes of the PPSO algorithms are publicly available at https://github.com/ebrahimakbary/PPSO.
Ghasemi, M, Akbari, E, Zand, M, Hadipour, M, Ghavidel, S & Li, L 2019, 'An Efficient Modified HPSO-TVAC-Based Dynamic Economic Dispatch of Generating Units', Electric Power Components and Systems, vol. 47, no. 19-20, pp. 1826-1840.
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© 2020, © 2020 Taylor & Francis Group, LLC. This paper proposes a novel particle swarm optimization (PSO) algorithm with population reduction, which is called modified new self-organizing hierarchical PSO with jumping time-varying acceleration coefficients (MNHPSO-JTVAC). The proposed method is used for solving well-known benchmark functions, as well as non-convex and non-smooth dynamic economic dispatch (DED) problems for a 24 h time interval in two different test systems. Operational constraints including the prohibited operating zones (POZs), the transmission losses, the ramp-rate limits and the valve-point effects are considered in solving the DED problem. The obtained numerical results show that the MNHPSO-JTVAC algorithm is very suitable and competitive compared to other algorithms and have the capacity to obtain better optimal solutions in solving the non-convex and non-smooth DED problems compared to the other variants of PSO and the state of the art optimization algorithms proposed in recent literature. The source codes of the HPSO-TVAC algorithms and supplementary data for this paper are publicly available at https://github.com/ebrahimakbary/MNHPSO-JTVAC.
Ghasemi, M, Rasekh, H, Berenjian, J & AzariJafari, H 2019, 'Dealing with workability loss challenge in SCC mixtures incorporating natural pozzolans: A study of natural zeolite and pumice', Construction and Building Materials, vol. 222, pp. 424-436.
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Ghavidel, S, Rajabi, A, Ghadi, MJ, Azizivahed, A, Li, L & Zhang, J 2019, 'Risk‐constrained demand response and wind energy systems integration to handle stochastic nature and wind power outage', IET Energy Systems Integration, vol. 1, no. 2, pp. 114-120.
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Ghodousi, Alesheikh, Saeidian, Pradhan & Lee 2019, 'Evaluating Citizen Satisfaction and Prioritizing Their Needs Based on Citizens’ Complaint Data', Sustainability, vol. 11, no. 17, pp. 4595-4595.
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Citizen Relationship Management (CiRM) is one of the important matters in citizen-centric e-government. In fact, the most important purpose of e-government is to satisfy citizens. The ‘137 system’ is one of the most important ones based on the citizen-centric that is a municipality phone based request/response system. The aim of this research is a data-mining of a ‘137 system’ (citizens’ complaint system) of the first district of Bojnourd municipality in Iran, to prioritize the urban needs and to estimate citizens’ satisfaction. To reach this, the K-means and Bees Algorithms (BA) were used. Each of these two algorithms was executed using two different methods. In the first method, prioritization and estimation of satisfaction were done separately, whereas in the second method, prioritization and estimation of satisfaction were done simultaneously. To compare the clustering results in the two methods, an index was presented quantitatively. The results showed the superiority of the second method. The index of the second method for the first needs in K-means was 0.299 more than the first method and it was the same in two methods in BA. Also, the results of the BA clustering were better at it because of the S (silhouette) and CH (Calinski-Harabasz) indexes. Considering the final prioritization done by the two algorithms in two methods, the primary needs included asphalt, so specific schemes should be considered.
Ghorbani, F, Abbaszadeh, H, Mehdizadeh, A, Ebrahimi-Warkiani, M, Rashidi, M-R & Yousefi, M 2019, 'Biosensors and nanobiosensors for rapid detection of autoimmune diseases: a review', Microchimica Acta, vol. 186, no. 12.
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This review (with 77 refs.) describes the progress that has been made in biosensors for the detection of autoimmune diseases, mainly via detection of autoantibodies. In addition, specific proteins, cytokines and ions have also been introduced as promising diagnostic biomarkers. Following an introduction into the various kinds of autoimmune diseases, we first discuss the state of the art in respective electrochemical biosensors and nanobiosensors (with subsections on amperometric, impedimetric, voltammetric and photoelectrochemical methods). The next large chapter covers optical methods (with subsections on electrochemiluminescence, fluorescence and surface plasmon resonance). We then make a critical comparison between commercially available kits used for detection of autoimmune diseases with the established biosensors. Several Tables are also presented that give an overview on the wealth of methods and nanomaterials. Finally, in the conclusion part, we summarize the current status, addresse present issues, and give an outlook on potential future opportunities. Graphical abstractSchematic representation of various developed optical and electrochemical biosensors and nanobiosensors for rapid detection of autoimmune diseases nanobiosensors for rapid detection of autoimmune diseases which could significantly prevent irreversable tissue damages and increse the quality of life in these patients.
Ghorbani, S, Eyni, H, Khosrowpour, Z, Salari Asl, L, Shabani, R, Nazari, H, Mehdizadeh, M, Ebrahimi Warkiani, M & Amjadi, F 2019, 'Spermatogenesis induction of spermatogonial stem cells using nanofibrous poly( l ‐lactic acid)/multi‐walled carbon nanotube scaffolds and naringenin', Polymers for Advanced Technologies, vol. 30, no. 12, pp. 3011-3025.
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© 2019 John Wiley & Sons, Ltd. Spermatogenesis is a process in which animals generate spermatozoa from spermatogonial stem cells (SSCs). Successful in vitro differentiation of SSCs towards spermatids holds a significant promise for regeneration of impaired spermatogenesis. The present study aims to evaluate the efficiency of a 3D culture containing naringenin on proliferation and differentiation potentials of mouse SSCs. In this study, multi-walled carbon nanotubes (MWCNTs) were incorporated into poly(l-lactic acid) (PLLA) fibers via electrospinning technique. The fibrous PLLA/MWCNTs were studied by Fourier-transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), water contact angle measurements, electrical conductivity, and mechanical properties. Next, the SSCs were seeded into the PLLA/MWCNTs scaffolds and exhibited preferable survival and differentiation efficiency to subsequent cell lines. To shed more light on this matter, the immunocytochemistry, reverse-transcription polymerase chain reaction (RT-PCR), and qRT-PCR results showed that the aforementioned cells on the 3D fabrics overexpressed the C-kit and SYCP3 proteins. In addition, the reactive oxygen species (ROS) measurement data demonstrated that naringenin, an effective antioxidant, plays an important role in in vitro spermatogenesis. Taken together, the results of this study revealed the synergistic effects of 3D scaffolds and naringenin for efficient spermatogenesis in laboratories.
Gill, AQ & Chew, E 2019, 'Configuration information system architecture: Insights from applied action design research.', Inf. Manag., vol. 56, no. 4, pp. 507-525.
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© 2018 Elsevier B.V. One of the critical information systems that enables service resilience is the service configuration information system (CiS). The fundamental challenge for organisations is the effective designing and implementation of the CiS architecture. This paper addresses this important research problem and reports insights from a completed applied action design research (ADR) project in an Australian financial services organisation. This paper aims to provide guidance to researchers and practitioners contemplating ADR, rooted in the organisational context, for practice-oriented academia-industry collaborative research. This research also contributes in terms of the CiS reference architecture design knowledge and demonstrates the applicability of the ADR method.
Giri, P, Kharkovsky, S, Zhu, X, Clark, SM & Samali, B 2019, 'Debonding detection in a carbon fibre reinforced concrete structure using guided waves', Smart Materials and Structures, vol. 28, no. 4, pp. 045020-045020.
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Guided waves are traditionally used in different non-destructive testing applications because of their cost-effectiveness and piezoelectric patches that are easy to incorporate into the structure as transducers. The non-destructive evaluation of interfacial defects such as debonding in a composite structure is critical for safety and long-term use. A new guided wave technique to detect a variety of debondings in carbon fibre reinforced concrete structure has been developed and experimental testing has been carried out to verify the proposed approach. Five composite specimens with different debondings have been prepared. The received guided wave in the specimen with a perfect bonding is taken as a reference. This signal is compared with the received signal under different debonding conditions. The debonding is quantified using three damage indices: correlation coefficient, change in peak-to-peak and root mean square deviation. The results demonstrated that these indices could be a good indicator of the debond conditions as they correlated linearly with the extent of the debonding. The proposed method is effective in detecting interfacial defects in an existing structure without special preparation.
Giri, P, Kharkovsky, S, Zhu, X, Clark, SM, Taheri, S & Samali, B 2019, 'Characterization of carbon fiber reinforced polymer strengthened concrete and gap detection with a piezoelectric-based sensory technique', Structural Health Monitoring, vol. 18, no. 1, pp. 172-179.
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In this article, a piezoelectric-based sensory technique is proposed for detection of the gap between surfaces of a carbon fiber reinforced polymer plate and a concrete specimen and characterization of shrinkage of early-age concrete. The proposed technique uses the propagation properties of the guided waves in the carbon fiber reinforced polymer plate excited and received by piezoelectric transducers attached to an external surface of the carbon fiber reinforced polymer–strengthened concrete specimen. Measurements are conducted with fresh and hardened early-age concrete specimens and two carbon fiber reinforced polymer plates at different gaps. A piezoelectric actuator is excited using a sine burst signal, and the generated wave is received by a sensor after propagation along the specimen. The received signal at different gap values is used to detect a gap. To quantify the gap, damage indices, including correlation coefficient, peak-to-peak amplitude of resultant signal, and root-mean-square deviation, are used. The shrinkage of concrete is detected and predicted by comparing the damage indices at different gaps with the indices at different stages of early-age concrete. The proposed technique is relatively simple method using small transducers. It is one-sided, non-destructive, and cost-effective solution for gap detection and concrete characterization.
Goh, BHH, Ong, HC, Cheah, MY, Chen, W-H, Yu, KL & Mahlia, TMI 2019, 'Sustainability of direct biodiesel synthesis from microalgae biomass: A critical review', Renewable and Sustainable Energy Reviews, vol. 107, pp. 59-74.
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© 2019 Elsevier Ltd Microalgae has been identified as a potential feedstock for biodiesel production since its cultivation requires less cropland compared to conventional oil crops and the high growth rate of microalgae. Research on microalgae oils often are focused on microalgae oil extraction and biomass harvesting techniques. However, energy intensive and costly lipid extraction methods are the major obstacles hampering microalgae biodiesel commercialisation. Direct biodiesel synthesis avoids such problems as it combines lipid extraction techniques and transesterification into a single step. In this review, the potential of direct biodiesel synthesis from microalgae biomass was comprehensively analysed. The various species of microalgae commonly used as biodiesel feedstock was critically assessed, particularly on high lipid content species. The production of microalgae biodiesel via direct conversion from biomass was systematically discussed, covering major enhancements such as heterogeneous catalysts, the use of ultrasonic and microwave- techniques and supercritical alcohols that focus on the overall improvement of biodiesel production. In addition, this review illustrates the cultivation conditions for biomass growth and lipid productivity improvement, the available harvesting and lipid extraction technologies, as well as the key challenges and future prospect of microalgae biodiesel production. This review serves as a basis for future research on direct biodiesel synthesis from modified microalgae biomass to improve profitability of microalgae biodiesel.
Goldsmith, R, Willey, K & Boud, D 2019, 'Investigating invisible writing practices in the engineering curriculum using practice architectures', European Journal of Engineering Education, vol. 44, no. 1-2, pp. 71-84.
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Writing practices are seen to be essential for professional engineers, yet many engineering students and academics struggle with written communication, despite years of interventions to improve student writing. Much has been written about the importance of getting engineering students to write, but there has been a little investigation of engineering academics’ perceptions of writing practices in the curriculum, and the extent to which these practices are visible to their students and to the academics. This paper draws on research from an ongoing study into the invisibility of writing practices in the engineering curriculum using a practice architectures lens. The paper uses examples from the sites of practice of two participants in the study to argue that prevailing practices in engineering education constrain more than enable the development and practice of writing in the engineering curriculum.
Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2019, 'Estimating chlorophyll content at leaf scale in viroid-inoculated oil palm seedlings (Elaeis guineensis Jacq.) using reflectance spectra (400 nm–1050 nm)', International Journal of Remote Sensing, vol. 40, no. 19, pp. 7647-7662.
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Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2019, 'Selection of a Spectral Index for Detection of Orange Spotting Disease in Oil Palm (Elaeis guineensis Jacq.) Using Red Edge and Neural Network Techniques', Journal of the Indian Society of Remote Sensing, vol. 47, no. 4, pp. 639-646.
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© 2019, Indian Society of Remote Sensing. Spectral screening can play an important role in successful detection of viroid-infected oil palm seedlings from nursery stage prior to transplanting into the field. Coconut cadang–cadang viroid (CCCVd) is the main causal agent of orange spotting (OS) disease. OS disease is an emerging disease in Malaysian plantation. In this study, a glasshouse experiment was conducted with fifteen CCCVd-inoculated and five healthy oil palm seedlings in the growing season of 2015. Spectral screening was performed using a hyperspectral spectroradiometer, Analytic Spectral Device HandHeld 2 (325–1075 nm). The red edge, a steep gradient in reflectance between red and near-infrared bands (680–780 nm), was used for selection of red edge bands. A maximum point (i.e., 700 nm) and minimum point (i.e., 768 nm) of red edge were selected from healthy and inoculated spectra. Shifts of red edge inflection point from healthy to inoculated spectra were also studied. Four well-known spectral indices, namely simple ratio, red edge normalized difference vegetation index, two-band enhanced vegetation index 2 (EVI2), and chlorophyll index red edge, were evaluated using selected red edge bands. The multilayer perceptron neural network model was used to establish a nonlinear relationship between selected spectral bands and each spectral index. EVI2 was selected as a best spectral index which resulted in zero errors at the training, testing, and validation datasets. The highest coefficient of correlation (r = 1) was recorded between spectral bands (input values) and EVI2 (target values).
Golsorkhi, MS, Shafiee, Q, Lu, DD-C & Guerrero, JM 2019, 'Distributed Control of Low-Voltage Resistive AC Microgrids', IEEE Transactions on Energy Conversion, vol. 34, no. 2, pp. 573-584.
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IEEE This paper proposes a distributed control strategy for coordination of distributed energy resources (DERs) in low-voltage resistive microgrids. The proposed framework consists of two level structure; primary and secondary control. Unlike the existing distributed control solutions, the proposed method is based upon the practical assumption of resistive network impedance. The primary control level consists of a V-I droop mechanism, where GPS timing is used to synchronize the control agents. A consensus-based distributed secondary control method is introduced to improve the voltage regulation and load sharing accuracy of the V-I droop method. In the proposed approach, the d-axis component of the voltage is altered so as to regulate the average microgrid voltage to the rated value while guarantying proper sharing of active power among the DERs. Additionally, the q-axis component of voltage is adjusted to perform proper current and, accordingly reactive power sharing. The proposed control methodology accounts for the distribution line impedances. It features a plug-and-play environment; prior system knowledge is not required, and an arbitrary DER can enter the microgrid without any need for additional synchronization. An AC microgrid is prototyped to experimentally demonstrate the efficacy of the proposed method.
Gong, B, Wang, S, Sloan, SW, Sheng, D & Tang, C 2019, 'Modelling Rock Failure with a Novel Continuous to Discontinuous Method', Rock Mechanics and Rock Engineering, vol. 52, no. 9, pp. 3183-3195.
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© 2019, Springer-Verlag GmbH Austria, part of Springer Nature. The original discontinuous deformation and displacement (DDD) method is greatly refined using the statistical damage theory and contact mechanics. Next, a novel coupled method is proposed to model the continuous to discontinuous failure process of rocks. By hybridizing the finite element method (FEM) and discontinuous deformation analysis (DDA) method, the proposed method inherits the advantages of both and is able to provide a complete and unified description of rock deformation, crack initiation and propagation, and rock body translation, rotation and interaction. Moreover, to improve the deformation results and refine the stress distribution within the model blocks, finite elements are introduced into the blocks. The ability of an intact block to fracture is included as well, i.e., the deformable blocks that contain several finite elements may split into smaller blocks if the strength criteria are satisfied continuously. The boundaries of damaged elements represent newly formed joints, and sliding and opening may occur along these joints, i.e., mechanical interaction is allowed between adjacent blocks. The correctness and validity of the proposed method are verified through a series of benchmark tests. The simulated results are consistent with the analytical solutions, previous studies and experimental observations. Overall, the coupled method is an effective and reliable approach for modelling the entire rock failure process with satisfactory accuracy and shows considerable potential in geotechnical engineering.
Gong, C, Tao, D, Chang, X & Yang, J 2019, 'Ensemble Teaching for Hybrid Label Propagation', IEEE Transactions on Cybernetics, vol. 49, no. 2, pp. 388-402.
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IEEE Label propagation aims to iteratively diffuse the label information from labeled examples to unlabeled examples over a similarity graph. Current label propagation algorithms cannot consistently yield satisfactory performance due to two reasons: one is the instability of single propagation method in dealing with various practical data, and the other one is the improper propagation sequence ignoring the labeling difficulties of different examples. To remedy above defects, this paper proposes a novel propagation algorithm called hybrid diffusion under ensemble teaching (HyDEnT). Specifically, HyDEnT integrates multiple propagation methods as base ''learners'' to fully exploit their individual wisdom, which helps HyDEnT to be stable and obtain consistent encouraging results. More importantly, HyDEnT conducts propagation under the guidance of an ensemble of ''teachers''. That is to say, in every propagation round the simplest curriculum examples are wisely designated by a teaching algorithm, so that their labels can be reliably and accurately decided by the learners. To optimally choose these simplest examples, every teacher in the ensemble should comprehensively consider the examples' difficulties from its own viewpoint, as well as the common knowledge shared by all the teachers. This is accomplished by a designed optimization problem, which can be efficiently solved via the block coordinate descent method. Thanks to the efforts of the teachers, all the unlabeled examples are logically propagated from simple to difficult, leading to better propagation quality of HyDEnT than the existing methods. Experiments on six popular datasets reveal that HyDEnT achieves the highest classification accuracy when compared with six state-of-the-art propagation methodologies such as harmonic functions, Fick's law assisted propagation, linear neighborhood propagation, semisupervised ensemble learning, bipartite graph-based consensus maximization, and teaching-to-learn and learnin...
Gong, S, Gao, L, Xu, J, Guo, Y, Hoang, DT & Niyato, D 2019, 'Exploiting Backscatter-Aided Relay Communications With Hybrid Access Model in Device-to-Device Networks', IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 835-848.
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© 2015 IEEE. The backscatter and active RF radios can complement each other and bring potential performance gain. In this paper, we envision a dual-mode radio structure that allows each device to make smart decisions on mode switch between backscatter communications (i.e., the passive mode) or RF communications (i.e., the active mode), according to the channel and energy conditions. The flexibility in mode switching also makes it more complicated for transmission control and network optimization. To exploit the radio diversity gain, we consider a wireless powered device-to-device network of hybrid radios and propose a sum throughput maximization by jointly optimizing energy beamforming and transmission scheduling in two radio modes. We further exploit the user cooperation gain by allowing the passive radios to relay for the active radios. As such, the sum throughput maximization is reformulated into a non-convex. We first present a sub-optimal algorithm based on successive convex approximation, which optimizes the relays' reflection coefficients by iteratively solving semi-definite programs. We also devise a set of heuristic algorithms with reduced computational complexity, which are shown to significantly improve the sum throughput and amenable for practical implementation.
Gong, S, Guo, Z, Wen, S & Huang, T 2019, 'Synchronization control for memristive high-order competitive neural networks with time-varying delay', Neurocomputing, vol. 363, pp. 295-305.
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Gong, S, Hoang, DT, Niyato, D, El Shafie, A, De Domenico, A, Strinati, EC & Hoydis, J 2019, 'Introduction to the special section on deep reinforcement learning for future wireless communication networks', IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 1019-1023.
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Gonzales, RR, Park, MJ, Bae, T-H, Yang, Y, Abdel-Wahab, A, Phuntsho, S & Shon, HK 2019, 'Melamine-based covalent organic framework-incorporated thin film nanocomposite membrane for enhanced osmotic power generation', Desalination, vol. 459, pp. 10-19.
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Gonzalez Marin, J, Baba, AA, Lopez Cuenca, D, Hesselbarth, J, Hashmi, RM & Esselle, KP 2019, 'High-Gain Low-Profile Chip-Fed Resonant Cavity Antennas for Millimeter-Wave Bands', IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 11, pp. 2394-2398.
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Gowripalan, N, Cao, J, Sirivivatnanon, V & South, W 2019, 'Accelerated autoclave test for determining alkali silica reaction of concrete', Concrete in Australia, vol. Volume 45, no. No 2, pp. 37-40.
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Alkali silica reaction (ASR) in concrete is a deleterious reaction which occurs due to the reaction between alkalis in the pore solution and reactive forms of silica found in some aggregates. ASR results in expansion and cracking which reduce the mechanical properties of the concrete. An ultra-accelerated autoclave test method has been used to test concrete prisms with and without alkali boosting. In this method, expansion and deterioration caused by ASR in concrete was investigated using an autoclave to simulate long-term deterioration. Test parameters such as temperature, pressure, duration of autoclaving and alkali boosting were investigated. Results obtained within a short period, clearly show large expansions and deterioration levels for concrete made with reactive aggregates.
Gowripalan, N, Nguyen, T, Yang, Y, Li, J & Sirivivatnanon, V 2019, 'Evaluation of elastic modulus reduction due to ASR', Concrete in Australia, vol. 45, no. 2, pp. 47-52.
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Evaluation of reduction in modulus of elasticity of concrete undergoing alkali silica reaction is carried out using an artificial neural network
Gracia, L, Solanes, JE, Muñoz-Benavent, P, Miro, JV, Perez-Vidal, C & Tornero, J 2019, 'Human-robot collaboration for surface treatment tasks', Interaction Studies, vol. 20, no. 1, pp. 148-184.
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Abstract
This paper presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks
such as polishing, grinding, finishing, deburring, etc. The proposed scheme is based on task priority and non-conventional sliding
mode control. Furthermore, the proposal includes two force sensors attached to the manipulator end-effector and tool: one sensor
is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool.
The applicability and feasibility of the proposed collaborative solution for robotic surface treatment are substantiated by
experimental results using a redundant 7R manipulator: the Sawyer collaborative robot.
Gravina da Rocha, C, El Ghoz, HBC & Jr Guadanhim, S 2019, 'A model for implementing product modularity in buildings design', Engineering, Construction and Architectural Management, vol. 27, no. 3, pp. 680-699.
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Purpose
The purpose of this paper is to examine the fundamental underpinnings of product modularity and how these can be adapted to construction and its specificities (e.g. one-off products delivered by temporary supply chains) to create a model to design modular buildings.
Design/methodology/approach
This research adopts a design science research approach. Explanation I (substantive theory devising based on the analysis of an artefact ‒ a low-income housing project) is used, followed by Solution Incubation (a model to implement product modularity in buildings design).
Findings
The model allows product modularity to be implemented at distinct levels (i.e. building, systems and components) at a single stage (building design), different from manufacturing where each level is considered at a distinct stage. This is in line with the project investigated: modularity was considered for house layouts, roof types and gable formats.
Practical implications
The model provides a hands-on tool for practitioners to design modular buildings. The low-income project is also extensively detailed: three-dimensional models, floor plans and conceptual diagrams (outlining how fundamental underpinnings were applied at each level) are presented. There is a lack of comprehensive accounts such as the one presented here to demonstrate the application of product modularity in real-world projects.
Originality/value
This paper identifies and adapts the fundamental underpinnings of product modularity to construction, and it...
Gu, Q, Qi, S, Yue, Y, Shen, J, Zhang, B, Sun, W, Qian, W, Islam, MS, Saha, SC & Wu, J 2019, 'Structural and functional alterations of the tracheobronchial tree after left upper pulmonary lobectomy for lung cancer', BioMedical Engineering OnLine, vol. 18, no. 1.
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Abstract
Background
Pulmonary lobectomy has been a well-established curative treatment method for localized lung cancer. After left upper pulmonary lobectomy, the upward displacement of remaining lower lobe causes the distortion or kink of bronchus, which is associated with intractable cough and breathless. However, the quantitative study on structural and functional alterations of the tracheobronchial tree after lobectomy has not been reported. We sought to investigate these alterations using CT imaging analysis and computational fluid dynamics (CFD) method.
Methods
Both preoperative and postoperative CT images of 18 patients who underwent left upper pulmonary lobectomy are collected. After the tracheobronchial tree models are extracted, the angles between trachea and bronchi, the surface area and volume of the tree, and the cross-sectional area of left lower lobar bronchus are investigated. CFD method is further used to describe the airflow characteristics by the wall pressure, airflow velocity, lobar flow rate, etc.
Results
It is found that the angle between the trachea and the right main bronchus increases after operation, but the angle with the left main bronchus decreases. No significant alteration is observed for the surface area or volume of the tree between pre-operation and post-operation. After left upper pulmonary lobectomy, the cross-sectional area of left lower lobar bronchus is reduced for most of the patients (15/18) by 15–75%, especially for 4 patients by more than 50%. The wall pressure, airflow velocity and pressure drop significantly increase after the operation. The flow rate to the r...
Gu, S, Zeng, W, Jia, Y & Yan, Z 2019, 'Intelligent Tennis Robot Based on a Deep Neural Network', Applied Sciences, vol. 9, no. 18, pp. 3746-3746.
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In this paper, an improved you only look once (YOLOv3) algorithm is proposed to make the detection effect better and improve the performance of a tennis ball detection robot. The depth-separable convolution network is combined with the original YOLOv3 and the residual block is added to extract the features of the object. The feature map output by the residual block is merged with the target detection layer through the shortcut layer to improve the network structure of YOLOv3. Both the original model and the improved model are trained by the same tennis ball data set. The results show that the recall is improved from 67.70% to 75.41% and the precision is 88.33%, which outperforms the original 77.18%. The recognition speed of the model is increased by half and the weight is reduced by half after training. All these features provide a great convenience for the application of the deep neural network in embedded devices. Our goal is that the robot is capable of picking up more tennis balls as soon as possible. Inspired by the maximum clique problem (MCP), the pointer network (Ptr-Net) and backtracking algorithm (BA) are utilized to make the robot find the place with the highest concentration of tennis balls. According to the training results, when the number of tennis balls is less than 45, the accuracy of determining the concentration of tennis balls can be as high as 80%.
Gu, X, Yu, Y, Li, Y, Li, J, Askari, M & Samali, B 2019, 'Experimental study of semi-active magnetorheological elastomer base isolation system using optimal neuro fuzzy logic control', Mechanical Systems and Signal Processing, vol. 119, pp. 380-398.
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In this paper, a “smart” base isolation strategy is proposed in this study utilising a semi-active magnetorheological elastomer (MRE) isolator whose stiffness can be controlled in real-time and reversible fashion. By modulating the applied current, the horizontal stiffness of the MRE isolator can be controlled and thus the control action can be generated for the isolated structure. To overcome the inherent nonlinearity and hysteresis of the MRE isolator, radial basis function neural network based fuzzy logic control (RBF-NFLC) was developed due to its inherent robustness and capability in coping with uncertainties. The NFLC was optimised by a non-dominated sorting genetic algorithm type II (NSGA-II) for better suited fuzzy control rules as well as most appropriate parameters for the membership functions. To evaluate the effectiveness of the proposed smart base isolation system, four scenarios are tested under various historical earthquake excitations, i.e. bare building with no isolation, passive isolated structure, MRE isolated structure with Bang-Bang control, MRE isolated structure with proposed NFLC. A three-storey shear building model was adopted as the testing bed. Through the testing results, limited performance of passive isolation system was revealed. In contrast, the adaptability of the proposed isolation strategy was demonstrated and it is proven that the smart MRE base isolation system is able to provide satisfactory protection for both structural and non-structural elements of the system over a wide range of hazard dynamic loadings.
Guan, J, Feng, Y, Turrini, A & Ying, M 2019, 'Model Checking Applied to Quantum Physics.', CoRR, vol. abs/1902.03218.
Guan, Z, Zhang, Y, Zhu, L, Wu, L & Yu, S 2019, 'EFFECT: an efficient flexible privacy-preserving data aggregation scheme with authentication in smart grid', Science China Information Sciences, vol. 62, no. 3.
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© 2019, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature. Smart grid is considered as a promising approach to solve the problems of carbon emission and energy crisis. In smart grid, the power consumption data are collected to optimize the energy utilization. However, security issues in communications still present practical concerns. To cope with these challenges, we propose EFFECT, an efficient flexible privacy-preserving aggregation scheme with authentication in smart grid. Specifically, in the proposed scheme, we achieve both data source authentication and data aggregation in high efficiency. Besides, in order to adapt to the dynamic smart grid system, the threshold for aggregation is adjusted according to the energy consumption information of each particular residential area and the time period, which can support fault-tolerance while ensuring individual data privacy during aggregation. Detailed security analysis shows that our scheme can satisfy the desired security requirements of smart grid. In addition, we compare our scheme with existing schemes to demonstrate the effectiveness of our proposed scheme in terms of low computational complexity and communication overhead.
Guertler, M, Sick, N & Kriz, A 2019, 'A Discipline-Spanning Overview of Action Research and Its Implications for Technology and Innovation Management', Technology Innovation Management Review, vol. 9, no. 4, pp. 48-65.
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The iterative and learning character of action research is particularly beneficial for exploring complex socio-technical problems in technology and innovation management (TIM). In this respect, action research allows both rigorous and relevant research due to parallel solving of real-world problems, capability building, and gaining scientific insights. However, the use of action research within TIM research is surprisingly limited. Action research also is not a homogeneous research methodology since each research discipline, such as education and organizational science, has its own action research streams, which are often only loosely linked. A systematic overview of those action research traditions and specific best practices is still missing, which complicates a systematic transfer and use of action research in TIM. This article addresses this essential gap by building a cross-disciplinary overview of action research streams based on a bibliometric analysis using Scopus. The analysis includes relevant disciplines with action research traditions, their development over time, and the most influential journals, authors, institutions, and countries. Along with this discipline-spanning analysis, the article investigates particular TIM benefits and challenges of action research. The two key contributions of this article are: 1) a discipline-spanning overview of action research and its evolution and 2) an analysis of its implications for TIM research. These contributions build the basis for strengthening the use of action research in TIM. In the medium-term, action research has the capacity to link academia and industry more closely and, in doing so, assists important endeavours of translating more of our research outcomes into practice.
Guo, B, Ouyang, Y, Guo, T, Cao, L & Yu, Z 2019, 'Enhancing Mobile App User Understanding and Marketing With Heterogeneous Crowdsourced Data: A Review', IEEE Access, vol. 7, pp. 68557-68571.
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The mobile app market has been surging in recent years. It has some key differentiating characteristics which make it different from traditional markets. To enhance mobile app development and marketing, it is important to study the key research challenges such as app user profiling, usage pattern understanding, popularity prediction, requirement and feedback mining, and so on. This paper reviews CrowdApp, a research field that leverages heterogeneous crowdsourced data for mobile app user understanding and marketing. We first characterize the opportunities of the CrowdApp, and then present the key research challenges and state-of-the-art techniques to deal with these challenges. We further discuss the open issues and future trends of the CrowdApp. Finally, an evolvable app ecosystem architecture based on heterogeneous crowdsourced data is presented.
Guo, D, Lui, GYL, Lai, SL, Wilmott, JS, Tikoo, S, Jackett, LA, Quek, C, Brown, DL, Sharp, DM, Kwan, RYQ, Chacon, D, Wong, JH, Beck, D, Geldermalsen, M, Holst, J, Thompson, JF, Mann, GJ, Scolyer, RA, Stow, JL, Weninger, W, Haass, NK & Beaumont, KA 2019, 'RAB27A promotes melanoma cell invasion and metastasisviaregulation of pro‐invasive exosomes', International Journal of Cancer, vol. 144, no. 12, pp. 3070-3085.
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Despite recent advances in targeted and immune-based therapies, advanced stage melanoma remains a clinical challenge with a poor prognosis. Understanding the genes and cellular processes that drive progression and metastasis is critical for identifying new therapeutic strategies. Here, we found that the GTPase RAB27A was overexpressed in a subset of melanomas, which correlated with poor patient survival. Loss of RAB27A expression in melanoma cell lines inhibited 3D spheroid invasion and cell motility in vitro, and spontaneous metastasis in vivo. The reduced invasion phenotype was rescued by RAB27A-replete exosomes, but not RAB27A-knockdown exosomes, indicating that RAB27A is responsible for the generation of pro-invasive exosomes. Furthermore, while RAB27A loss did not alter the number of exosomes secreted, it did change exosome size and altered the composition and abundance of exosomal proteins, some of which are known to regulate cancer cell movement. Our data suggest that RAB27A promotes the biogenesis of a distinct pro-invasive exosome population. These findings support RAB27A as a key cancer regulator, as well as a potential prognostic marker and therapeutic target in melanoma.
Guo, G, Sun, Y, Fu, Q, Ma, Y, Zhou, Y, Xiong, Z & Liu, Y 2019, 'Sol-gel synthesis of ternary conducting polymer hydrogel for application in all-solid-state flexible supercapacitor', International Journal of Hydrogen Energy, vol. 44, no. 12, pp. 6103-6115.
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Guo, G-C & Ying, M 2019, 'Preface to special topic on quantum computing', National Science Review, vol. 6, no. 1, pp. 20-20.
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Guo, H, Hu, J, Li, J, Gao, M-T, Wang, Q, Guo, W & Ngo, HH 2019, 'Systematic insight into the short-term and long-term effects of magnetic microparticles and nanoparticles on critical flux in membrane bioreactors', Journal of Membrane Science, vol. 582, pp. 284-288.
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© 2019 This study aims to systematically investigate the short-term and long-term effects of magnetic microparticles (MPs) and nanoparticles (NPs) on critical flux in membrane bioreactors (MBRs). Comparison among six MBRs was carried out with different activated sludge samples. Results showed that the short-term adsorption and flocculation contributed only minimally, however, the long-term magnetic induced bio-effect improved the critical flux by conditioning sludge properties. Additional molecular weight distribution of soluble microbial product (SMP) indicated that long-term magnetic induced bio-effect declined the content of macromolecules (>500 kDa and 300–500 kDa), but promoted the content of small molecules (<100 kDa), consequently reduced the free energy of SMP gelling foulants, and further promoted the higher critical flux. Moreover, the magnetic MPs presented the better performance than NPs. This study illustrated that sufficient pre-acclimatization of magnetic activated sludge is significantly necessary to improve the critical flux in MBRs.
Guo, H, Wang, F, Li, L, Zhang, L & Luo, J 2019, 'A Minimum Loss Routing Algorithm Based on Real-Time Transaction in Energy Internet', IEEE Transactions on Industrial Informatics, vol. 15, no. 12, pp. 6446-6456.
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Guo, K & Guo, Y 2019, 'Key Parameter Design and Analysis of Flux Reversal Linear Rotary Permanent Magnet Actuator', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-5.
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© 2002-2011 IEEE. Flux reversal linear rotary permanent magnet actuator (FR-LRPMA) is a two-degree-of-freedom actuator with two ferromagnetic (Fe) poles and two permanent magnet (PM) poles mounted on the surface of each stator pole. The flux linkage waveform of the actuator is more sinusoidal than that of the traditional topology, which are analyzed by the ideal linear model of one stator section of the proposed actuator. In order to reduce the amplitudes of the cogging torque and detent force, a key space gap parameter of the FR-LRPMA between the Fe pole and PM pole is studied in the circumferential and axial directions. The expressions of cogging torque and detent force are derived by the magnetomotive force analytical method, which are used to obtain the optimal space gap parameter value. The electromagnetic characteristics of the actuator are analyzed by the finite-element method. The amplitudes of cogging torque and detent force are reduced and the back electromotive force waveform is more sinusoidal than that of the original topology, which are verified by the experiment.
Guo, K, Chai, R, Candra, H, Guo, Y, Song, R, Nguyen, H & Su, S 2019, 'A Hybrid Fuzzy Cognitive Map/Support Vector Machine Approach for EEG-Based Emotion Classification Using Compressed Sensing', International Journal of Fuzzy Systems, vol. 21, no. 1, pp. 263-273.
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© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Due to the high dimensional, non-stationary and non-linear properties of electroencephalogram (EEG), a significant portion of research on EEG analysis remains unknown. In this paper, a novel approach to EEG-based human emotion study is presented using Big Data methods with a hybrid classifier. An EEG dataset is firstly compressed using compressed sensing, then, wavelet transform features are extracted, and a hybrid Support Vector Machine (SVM) and Fuzzy Cognitive Map classifier is designed. The compressed data is only one-fourth of the original size, and the hybrid classifier has the average accuracy by 73.32%. Comparing to a single SVM classifier, the average accuracy is improved by 3.23%. These outcomes show that psychological signal can be compressed without the sparsity identity. The stable and high accuracy classification system demonstrates that EEG signal can detect human emotion, and the findings further prove the existence of the inter-relationship between various regions of the brain.
Guo, L, Zhu, H & Abbosh, A 2019, 'Phase Reconfigurable Microwave Power Divider', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 1, pp. 21-25.
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© 2004-2012 IEEE. A reconfigurable power divider (PD) that can operate either in an in-phase mode or out-of-phase mode is presented. To that end, the novel concept of using tunable phase shifter, which is a reflection-type loaded coupled lines, to emulate an effective variable length transmission line (TL) is utilized. The proposed PD uses a quarter-wavelength TL, a 100 Ω isolation resistor and two tunable phase shifters. The presented theoretical analysis shows that by properly selecting the parameters of the phase shifter, it can be used to approximate the performance of variable length TL. To validate the design, a prototype of dimensions 50 mm × 25 mm is built, using Rogers RO3010 substrate, and tested. The results indicate that the device can operate as an in-phase and out-of-phase by using suitable biasing voltages. Across the band 0.9-1.1 GHz, the device has more than 12 dB return loss at all the ports and more than 15 dB isolation between the two output ports with less than 5° phase deviation for both of the in-phase and out-of-phase states.
Guo, Q, Zhang, Y, Celler, BG & Su, SW 2019, 'Neural Adaptive Backstepping Control of a Robotic Manipulator With Prescribed Performance Constraint', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3572-3583.
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IEEE This paper presents an adaptive neural network (NN) control of a two-degree-of-freedom manipulator driven by an electrohydraulic actuator. To restrict the system output in a prescribed performance constraint, a weighted performance function is designed to guarantee the dynamic and steady tracking errors of joint angle in a required accuracy. Then, a radial-basis-function NN is constructed to train the unknown model dynamics of a manipulator by traditional backstepping control (TBC) and obtain the preliminary estimated model, which can replace the preknown dynamics in the backstepping iteration. Furthermore, an adaptive estimation law is adopted to self-tune every trained-node weight, and the estimated model is online optimized to enhance the robustness of the NN controller. The effectiveness of the proposed control is verified by comparative simulation and experimental results with Proportional-integral-derivative and TBC methods.
Guo, T, Pan, S, Zhu, X & Zhang, C 2019, 'CFOND: Consensus Factorization for Co-Clustering Networked Data', IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 4, pp. 706-719.
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IEEE Networked data are common in domains where instances are characterized by both feature values and inter-dependency relationships. Finding cluster structures for networked instances and discovering representative features for each cluster represent a special co-clustering task usefully for many real-world applications, such as automatic categorization of scientific publications and finding representative key-words for each cluster. To date, although co-clustering has been commonly used for finding clusters for both instances and features, all existing methods are focused on instance-feature values, without leveraging valuable topology relationships between instances to help boost co-clustering performance. In this paper, we propose CFOND, a consensus factorization based framework for co-clustering networked data. We argue that feature values and linkages provide useful information from different perspectives, yet they are not always consistent and therefore need to be carefully aligned for best clustering results. In the paper, we advocate a consensus factorization principle, which simultaneously factorizes information from three aspects: network topology structures, instance-feature content relationships, and feature-feature correlations. The consensus factorization ensures that the final cluster structures are consistent across information from the three aspects with minimum errors. CFOND enjoys sound theoretical basis and proved convergence, and its performance is validated on real-world networks.
Guo, W, Lei, Z, Wang, J & Wei, D 2019, 'Special issue on challenges in biological wastewater treatment and resource recovery', Bioresource Technology Reports, vol. 7, pp. 100243-100243.
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Guo, Z, Gong, S, Wen, S & Huang, T 2019, 'Event-Based Synchronization Control for Memristive Neural Networks With Time-Varying Delay', IEEE Transactions on Cybernetics, vol. 49, no. 9, pp. 3268-3277.
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Guo, Z, Yang, C, Maritz, MF, Wu, H, Wilson, P, Warkiani, ME, Chien, C, Kempson, I, Aref, AR & Thierry, B 2019, 'Validation of a Vasculogenesis Microfluidic Model for Radiobiological Studies of the Human Microvasculature', Advanced Materials Technologies, vol. 4, no. 4, pp. 1800726-1800726.
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© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim The therapeutic ratio of radiotherapy is limited by acute or chronic side effects with often severe consequences to patients. The microvasculature is a central player involved in both tumor responses and healthy tissue/organ radiological injuries. However, current preclinical vascular models based on 2D culture offer only limited radiobiological insight due to their failure in recapitulating the 3D nature experienced by endothelial cells within the human microvasculature. To address this issue, the use of a 3D microvasculature-on-a-chip microfluidic technology is demonstrated in radiobiological studies. Within this vasculogenesis model a perfusable network that structurally mimics the human microvasculature is formed and the biological response to ionizing radiation including cellular apoptosis, vessel tight adherens junction breakage, DNA double strand break, and repair is systematically investigated. In comparison to cells grown in a 2D environment, human umbilical vein endothelial cells in the 3D microvasculature-on-a-chip displays significant differences in biological responses, especially at high X-ray dose. This data confirms the feasibility of using microvascular-on-a-chip models for radiobiological studies. Such vasculogenesis models have strong potential to yield more accurate prediction of healthy tissue responses to ionizing radiation as well as to guide the development of risk-reducing strategies to prevent radiation-induced acute and long-term side-effects.
Gupta, D, Pratama, M, Ma, Z, Li, J & Prasad, M 2019, 'Financial time series forecasting using twin support vector regression', PLOS ONE, vol. 14, no. 3, pp. e0211402-e0211402.
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Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper proposes twin support vector regression for financial time series prediction to deal with noisy data and nonstationary information. Various interesting financial time series datasets across a wide range of industries, such as information technology, the stock market, the banking sector, and the oil and petroleum sector, are used for numerical experiments. Further, to test the accuracy of the prediction of the time series, the root mean squared error and the standard deviation are computed, which clearly indicate the usefulness and applicability of the proposed method. The twin support vector regression is computationally faster than other standard support vector regression on the given 44 datasets.
Gurjar, DS, Nguyen, HH & Tuan, HD 2019, 'Wireless Information and Power Transfer for IoT Applications in Overlay Cognitive Radio Networks', IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3257-3270.
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IEEE This paper proposes and investigates an overlay spectrum sharing system in conjunction with the simultaneous wireless information and power transfer (SWIPT) to enable communications for the Internet of Things (IoT) applications. Considered is a cooperative cognitive radio network, where two IoT devices (IoDs) exchange their information and also provide relay assistance to a pair of primary users (PUs). Different from most existing works, in this paper, both IoDs can harvest energy from the radio-frequency (RF) signals received from the PUs. By utilizing the harvested energy, they provide relay cooperation to PUs and realize their own communications. For harvesting energy, a time-switching (TS) based approach is adopted at both IoDs. With the proposed scheme, one round of bidirectional information exchange for both primary and IoT systems is performed in four phases, i.e., one energy harvesting (EH) phase and three information processing (IP) phases. Both IoDs rely on the decode-and-forward operation to facilitate relaying, whereas the PUs employ selection combining (SC) technique. For investigating the performance of the considered network, this paper first provides exact expressions of user outage probability (OP) for the primary and IoT systems under Nakagami-m fading. Then, by utilizing the expressions of user OP, the system throughput and energy efficiency are quantified together with the average end-to-end transmission time. Numerical and simulation results are provided to give useful insights into the system behavior and to highlight the impact of various system/channel parameters.
Ha, Q & Phung, MD 2019, 'IoT‐enabled dependable control for solar energy harvesting in smart buildings', IET Smart Cities, vol. 1, no. 2, pp. 61-70.
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Ha, QP, Yen, L & Balaguer, C 2019, 'Robotic autonomous systems for earthmoving in military applications', Automation in Construction, vol. 107, pp. 102934-102934.
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© 2019 Elsevier B.V. Along with increasing innovations in frontier engineering sciences, the advancement in Robotic Autonomous Systems (RAS) has brought about a new horizon in earthmoving processes for construction. In the military domain, there is also an increasing interest in utilising RAS technologies. In particular, ground-based forces are frequently called upon to conduct earthmoving tasks as part of military operations, tasks which could be partially or fully aided by the employment of RAS technologies. There have been rapid developments in military construction automation using high-mobility ground-based platforms, human-machine and machine-machine interfaces, teleoperation and control systems, data transmission systems, machine perception and manipulation capabilities, as well as advances in networked robotics and cyberphysical systems. Given these developments it is timely to undertake a comprehensive overview on the topic of interest to the research community and the authority. This paper presents an overview of the RAS development for platform-centric earthworks together with an analysis of the technical feasibility, maturity, key technical challenges, and future directions for the application of RAS technologies to earthmoving tasks of interest to the army.
Habib, M, Alfugara, A & Pradhan, B 2019, 'A LOW-COST SPATIAL TOOL FOR TRANSFORMING FEATURE POSITIONS OF CAD-BASED TOPOGRAPHIC MAPPING', Geodesy and cartography, vol. 45, no. 4, pp. 161-168.
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In fact, Computer Aided Design (CAD) offers powerful design tools to produce digital large scale topographic mapping that is considered the backbone for construction projects, urban planning and landscape architecture. Nowadays local agencies in small communities and developing countries are facing some difficulties in map to map transformation and handling discrepancies between the physical reality and represented spatial data due to the need for implementing high cost systems such as GIS and the experienced staff required. Therefore, the require for providing a low-cost tool based on the most common CAD system is very important to guarantee a quality and positional accuracy of features. The main aim of this study is to describe a mathematical relationship to fulfil the coordinate conversion between two different grid references applying two-dimensional conformal polynomial models built on control points and a least squares fitting algorithm. In addition, the automation of this model was performed in the Microsoft Visual Studio environment to calculate polynomial coefficients and convert the positional property of entities in AutoCAD by developing spatial CAD tool. To evaluate the proposed approach the extracted coordinates of check points from the interpolation surface are compared with the known ones.
Hadzhiev, Y, Qureshi, HK, Wheatley, L, Cooper, L, Jasiulewicz, A, Van Nguyen, H, Wragg, JW, Poovathumkadavil, D, Conic, S, Bajan, S, Sik, A, Hutvàgner, G, Tora, L, Gambus, A, Fossey, JS & Müller, F 2019, 'A cell cycle-coordinated Polymerase II transcription compartment encompasses gene expression before global genome activation', Nature Communications, vol. 10, no. 1.
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AbstractMost metazoan embryos commence development with rapid, transcriptionally silent cell divisions, with genome activation delayed until the mid-blastula transition (MBT). However, a set of genes escapes global repression and gets activated before MBT. Here we describe the formation and the spatio-temporal dynamics of a pair of distinct transcription compartments, which encompasses the earliest gene expression in zebrafish. 4D imaging of pri-miR430 and zinc-finger-gene activities by a novel, native transcription imaging approach reveals transcriptional sharing of nuclear compartments, which are regulated by homologous chromosome organisation. These compartments carry the majority of nascent-RNAs and active Polymerase II, are chromatin-depleted and represent the main sites of detectable transcription before MBT. Transcription occurs during the S-phase of increasingly permissive cleavage cycles. It is proposed, that the transcription compartment is part of the regulatory architecture of embryonic nuclei and offers a transcriptionally competent environment to facilitate early escape from repression before global genome activation.
Hafiz, MA, Hawari, AH & Altaee, A 2019, 'A hybrid forward osmosis/reverse osmosis process for the supply of fertilizing solution from treated wastewater', Journal of Water Process Engineering, vol. 32, pp. 100975-100975.
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This work investigates the application of a hybrid system that combines forward osmosis (FO) and reverse osmosis (RO) processes for the supply of a fertilizing solution that could be used directly for irrigation purposes. In the FO process the feed solution is treated sewage effluent (TSE) and two different types of draw solutions were investigated. The impact of the feed solution and the draw solution flowrates and the membrane orientation on the membrane flux were investigated in the forward osmosis process. RO was used for the regeneration of the draw solution. In the forward osmosis process it was found that the highest membrane flux was 13.2 LMH. The FO process had high rejection rates for total phosphorus and ammonium which were 99% and 97%, respectively. RO achieved 99% total salts rejection rate. Seawater RO (SW30HR) and brackish water RO (BW30LE) membranes were used for the regeneration of the draw solution. The specific power consumption for the regeneration of the draw solution was 2.58 kWh/m3 and 2.18 kWh/m3 for SW30HR and BW30LE membranes, respectively. The final product water had high quality in terms of total dissolved solids concentration but the concentration of phosphorus was slightly higher than recommended due to adding 0.1M of diammonium phosphate in the draw solution.
Haider, N, Ali, A, Suarez-Rodriguez, C & Dutkiewicz, E 2019, 'Optimal Mode Selection for Full-Duplex Enabled D2D Cognitive Networks.', IEEE Access, vol. 7, pp. 57298-57311.
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Hakdaoui, S, Emran, A, Pradhan, B, Lee, C-W & Nguemhe Fils, SC 2019, 'A Collaborative Change Detection Approach on Multi-Sensor Spatial Imagery for Desert Wetland Monitoring after a Flash Flood in Southern Morocco', Remote Sensing, vol. 11, no. 9, pp. 1042-1042.
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This study aims to present a technique that combines multi-sensor spatial data to monitor wetland areas after a flash-flood event in a Saharan arid region. To extract the most efficient information, seven satellite images (radar and optical) taken before and after the event were used. To achieve the objectives, this study used Sentinel-1 data to discriminate water body and soil roughness, and optical data to monitor the soil moisture after the event. The proposed method combines two approaches: one based on spectral processing, and the other based on categorical processing. The first step was to extract four spectral indices and utilize change vector analysis on multispectral diachronic images from three MSI Sentinel-2 images and two Landsat-8 OLI images acquired before and after the event. The second step was performed using pattern classification techniques, namely, linear classifiers based on support vector machines (SVM) with Gaussian kernels. The results of these two approaches were fused to generate a collaborative wetland change map. The application of co-registration and supervised classification based on textural and intensity information from Radar Sentinel-1 images taken before and after the event completes this work. The results obtained demonstrate the importance of the complementarity of multi-sensor images and a multi-approach methodology to better monitor changes to a wetland area after a flash-flood disaster.
Hamzehei, A, Wong, RK, Koutra, D & Chen, F 2019, 'Collaborative topic regression for predicting topic-based social influence', Machine Learning, vol. 108, no. 10, pp. 1831-1850.
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Han, B, Tsang, IW, Chen, L, Zhou, JT & Yu, CP 2019, 'Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3774-3787.
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Crowdsourcing has become the most appealing way to provide a plethora of labels at a low cost. Nevertheless, labels from amateur workers are often noisy, which inevitably degenerates the robustness of subsequent learning models. To improve the label quality for subsequent use, majority voting (MV) is widely leveraged to aggregate crowdsourced labels due to its simplicity and scalability. However, when crowdsourced labels are "heavily" noisy (e.g., 40% of noisy labels), MV may not work well because of the fact "garbage (heavily noisy labels) in, garbage (full aggregated labels) out." This issue inspires us to think: if the ultimate target is to learn a robust model using noisy labels, why not provide partial aggregated labels and ensure that these labels are reliable enough for learning models? To solve this challenge by improving MV, we propose a coarse-to-fine label filtration model called double filter machine (DFM), which consists of a (majority) voting filter and a sparse filter serially. Specifically, the DFM refines crowdsourced labels from coarse filtering to fine filtering. In the stage of coarse filtering, the DFM aggregates crowdsourced labels by voting filter, which yields (quality-acceptable) full aggregated labels. In the stage of fine filtering, DFM further digs out a set of high-quality labels from full aggregated labels by sparse filter, since this filter can identify high-quality labels by the methodology of support selection. Based on the insight of compressed sensing, DFM recovers a ground-truth signal from heavily noisy data under a restricted isometry property. To sum up, the primary benefits of DFM are to keep the scalability by voting filter, while improve the robustness by sparse filter. We also derive theoretical guarantees for the convergence and recovery of DFM and reveal its complexity. We conduct comprehensive experiments on both the UCI simulated and the AMT crowdsourced datasets. Empirical results show that partial aggregated labels...
Han, B, Yao, Q, Pan, Y, Tsang, IW, Xiao, X, Yang, Q & Sugiyama, M 2019, 'Millionaire: a hint-guided approach for crowdsourcing', Machine Learning, vol. 108, no. 5, pp. 831-858.
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© 2018, The Author(s). Modern machine learning is migrating to the era of complex models, which requires a plethora of well-annotated data. While crowdsourcing is a promising tool to achieve this goal, existing crowdsourcing approaches barely acquire a sufficient amount of high-quality labels. In this paper, motivated by the “Guess-with-Hints” answer strategy from the Millionaire game show, we introduce the hint-guided approach into crowdsourcing to deal with this challenge. Our approach encourages workers to get help from hints when they are unsure of questions. Specifically, we propose a hybrid-stage setting, consisting of the main stage and the hint stage. When workers face any uncertain question on the main stage, they are allowed to enter the hint stage and look up hints before making any answer. A unique payment mechanism that meets two important design principles for crowdsourcing is developed. Besides, the proposed mechanism further encourages high-quality workers less using hints, which helps identify and assigns larger possible payment to them. Experiments are performed on Amazon Mechanical Turk, which show that our approach ensures a sufficient number of high-quality labels with low expenditure and detects high-quality workers.
Han, C, Li, W, Shu, C, Guo, H, Liu, H, Dou, S & Wang, J 2019, 'Catalytic Activity Boosting of Nickel Sulfide toward Oxygen Evolution Reaction via Confined Overdoping Engineering', ACS Applied Energy Materials, vol. 2, no. 8, pp. 5363-5372.
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Han, L, Han, XF, Ou, XP & Guo, Y 2019, 'Operating performances analysis of brushless doubly-fed machine using magnetic equivalent circuit', Dianji yu Kongzhi Xuebao/Electric Machines and Control, vol. 23, no. 1, pp. 27-34.
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There are few effective tools to quickly and correctly analyze the operating performances of Brushless Doubly-Fed Machine (BDFM) due to its special structure and complex magnetic field modulation mechanism. Based on the basic concept of Magnetic Equivalent Circuit (MEC), this paper described the method for establishing the MEC model of BDFM with cage rotor, considering the effects of special structure of BDFM, core saturation and rotor revolution. Furthermore, a dynamic MEC model of a prototype with cage rotor was built up and solved by the mesh method. And then, the operating performances of the prototype under different operating conditions were obtained and analyzed. Finally, the results of dynamic MEC model were compared with those of Finite Element Analysis (FEA) and experiment data. The results show that the dynamic MEC model can correctly predict the operating performances of BDFM with cage rotor and is much faster than FEA. This work can broaden the research thought for analyzing the operating performances of BDFM of cage rotor.
Han, L, Zhou, M, Han, S, Jia, W, Sun, C & Fu, C 2019, 'Targeting malware discrimination based on reversed association task', Concurrency and Computation: Practice and Experience, vol. 31, no. 23.
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©2018 John Wiley & Sons, Ltd. Regarding the current situation that the recognition rate of malware is decreasing, the article points out that the reason for this dilemma is that more and more targeting malware have emerged, which share little or no common feature with traditional malware. The premise of malware recognition judging whether a software is malicious or benign is actually a decision problem. We propose that malware discrimination should resort to the corresponding task or purpose. We first present a formal definition of a task and then provide further classifications of malicious tasks. Based on the decidable theory, we prove that task performed by any software is recursive and determinable. By establishing a mapping from software to task, we prove that software is many-to-one reducible to corresponding tasks. Thus, we demonstrate that software, including malware, is also recursive and can be determined by the corresponding tasks. Finally, we present the discrimination process of our method. Nine real malwares are presented, which were firstly discriminated by our method but at that time could not be identified by Kaspersky, McAfee, Symantec Norton, or Kingsoft Antivirus.
Han, L, Zhou, M, Jia, W, Dalil, Z & Xu, X 2019, 'Intrusion detection model of wireless sensor networks based on game theory and an autoregressive model', Information Sciences, vol. 476, pp. 491-504.
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© 2018 Elsevier Inc. An effective security strategy for Wireless Sensor Networks (WSNs) is imperative to counteract security threats. Meanwhile, energy consumption directly affects the network lifetime of a wireless sensor. Thus, an attempt to exploit a low-consumption Intrusion Detection System (IDS) to detect malicious attacks makes a lot of sense. Existing Intrusion Detection Systems can only detect specific attacks and their network lifetime is short due to their high energy consumption. For the purpose of reducing energy consumption and ensuring high efficiency, this paper proposes an intrusion detection model based on game theory and an autoregressive model. The paper not only improves the autoregressive theory model into a non-cooperative, complete-information, static game model, but also predicts attack pattern reliably. The proposed approach improves on previous approaches in two main ways: (1) it takes energy consumption of the intrusion detection process into account, and (2) it obtains the optimal defense strategy that balances the system's detection efficiency and energy consumption by analyzing the model's mixed Nash equilibrium solution. In the simulation experiment, the running time of the process is regarded as the main indicator of energy consumption of the system. The simulation results show that our proposed IDS not only effectively predicts the attack time and the next targeted cluster based on the game theory, but also reduces energy consumption.
Han, M, Bao, Y, Sun, Z, Wen, S, Xia, L, Zhao, J, Du, J & Yan, Z 2019, 'Automatic Segmentation of Human Placenta Images With U-Net', IEEE Access, vol. 7, pp. 180083-180092.
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© 2013 IEEE. Placenta is closely related to the health of the fetus. Abnormal placental function will affect the normal development of the fetus, and in severe cases, even endanger the life of the fetus. Therefore, accurate and quantitative evaluation of placenta has important clinical significance. It is a common method to segment human placenta with semantic segmentation. However, manual segmentation relies too much on the professional knowledge and clinical experience of the staff, and it will also consume a lot of time. Therefore, based on u-net, we propose an automatic segmentation method of human placenta, which reduces manual intervention and greatly speeds up the segmentation, making large-scale segmentation possible. The human placenta data set we used was labeled by experts, which was obtained from prenatal examinations of 11 pregnant women, about 1,110 images. It was a comprehensive and clinically significant data set. By training the network with such data set, the robustness of the model will be better. After testing on the data set, the segmentation effect is basically consistent with the manual segmentation effect.
Han, R, Khan, MH, Angeloski, A, Casillas, G, Yoon, CW, Sun, X & Huang, Z 2019, 'Hexagonal Boron Nitride Nanosheets Grown via Chemical Vapor Deposition for Silver Protection', ACS Applied Nano Materials, vol. 2, no. 5, pp. 2830-2835.
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Han, S-F, Jin, W, Abomohra, AE-F, Zhou, X, Tu, R, Chen, C, Chen, H, Gao, S-H & Wang, Q 2019, 'Enhancement of Lipid Production of Scenedesmus obliquus Cultivated in Municipal Wastewater by Plant Growth Regulator Treatment', Waste and Biomass Valorization, vol. 10, no. 9, pp. 2479-2485.
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© 2018 Springer Science+Business Media B.V., part of Springer Nature Effects of four different plant growth regulators including indole-3-acetic acid (IAA), 1-triacontanol (TRIA), 2,4-dichlorophenoxyacetic acid (2,4-D) and 6-benzylaminopurine (6-BA) on biomass and lipid productivity of microalga Scenedesmus obliquus cultured in municipal wastewater were primarily studied. The results showed that the lipid productivity of S. obliquus was significantly increased by 30.5 and 23.6% after the treatment by IAA and TRIA, respectively. According to the GC analysis of the lipids, the addition of IAA and TRIA could increase the content of monounsaturated fatty acid in S. obliquus, and thus improving the grade of biodiesel. After the addition of IAA and TRIA, the nitrogen content of S. obliquus significantly decreased, while bacterial diversity in wastewater increased, which could enhance the stability of microbial system in the wastewater medium. Meanwhile, significant increase were also found in the abundances of β-Proteobacteria and α-Proteobacteria.
Han, S-F, Jin, W, Yang, Q, El-Fatah Abomohra, A, Zhou, X, Tu, R, Chen, C, Xie, G-J & Wang, Q 2019, 'Application of pulse electric field pretreatment for enhancing lipid extraction from Chlorella pyrenoidosa grown in wastewater', Renewable Energy, vol. 133, pp. 233-239.
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Han, Z, Wu, M, Zhu, Q & Yang, J 2019, 'Three-dimensional wave-domain acoustic contrast control using a circular loudspeaker array', The Journal of the Acoustical Society of America, vol. 145, no. 6, pp. EL488-EL493.
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This paper proposes a three-dimensional wave-domain acoustic contrast control method to reproduce a multizone sound field using a circular loudspeaker array. In this method, sound field analysis is based on spherical harmonic decomposition, and the loudspeaker weights are obtained by maximizing the acoustic energy contrast between the predefined bright zone and dark zone. Simulation results show that the proposed method provides good multizone separation performance over a large spatial region and requires lower-order spherical harmonics, resulting in a much lower number of microphones required to measure the acoustic transfer functions.
Hao, P, Zhang, G, Martinez, L & Lu, J 2019, 'Regularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation', IEEE Transactions on Cybernetics, vol. 49, no. 1, pp. 83-96.
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IEEE Traditional recommender systems suffer from the data sparsity problem. However, user knowledge acquired in one domain can be transferred and exploited in several other relevant domains. In this context, cross-domain recommender systems have been proposed to create a new and effective recommendation paradigm in which to exploit rich data from auxiliary domains to assist recommendations in a target domain. Before knowledge transfer takes place, building reliable and concrete domain correlation is the key ensuring that only relevant knowledge will be transferred. Social tags are used to explicitly link different domains, especially when neither users nor items overlap. However, existing models only exploit a subset of tags that are shared by heterogeneous domains. In this paper, we propose a complete tag-induced cross-domain recommendation (CTagCDR) model, which infers interdomain and intradomain correlations from tagging history and applies the learned structural constraints to regularize joint matrix factorization. Compared to similar models, CTagCDR is able to fully explore knowledge encoded in both shared and domain-specific tags. We demonstrate the performance of our proposed model on three public datasets and compare it with five state-of-the-art single and cross-domain recommendation approaches. The results show that CTagCDR works well in both rating prediction and item recommendation tasks, and can effectively improve recommendation performance.
Hao, Q, Liu, Y, Chen, T, Guo, Q, Wei, W & Ni, B-J 2019, 'Bi2O3@Carbon Nanocomposites for Solar-Driven Photocatalytic Degradation of Chlorophenols', ACS Applied Nano Materials, vol. 2, no. 4, pp. 2308-2316.
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Chlorophenols are corrosive and toxic in a water environment, which have caused increasing concerns and encourage the development of solar-driven techniques with highly efficient photocatalysts for green remediation. Coupling photocatalysis with the surface plasmon resonance (SPR) effect is a practical solution for boosting the utilization of solar light in the IR region while improving the overall performance of the photocatalysts. However, a facile and green strategy to synthesize metallic non-noble bismuth (Bi0)-based photocatalysts is still lacking. Herein, we report smart Bi/Bi2O3/C composites with high performance for the photocatalytic degradation of 2,4-dichlorophenol. Advanced characterizations such as X-ray diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy are applied to analyze the morphology and structure of the prepared materials. The photodegradation rate of the hybrid is significantly enhanced compared with the sole counterparts, which are 1.60-fold of Bi2O3 and 2.47-fold of g-C3N4. The synthesized Bi/C-2 exhibits excellent stability without a decline in activity after four cycles. The SPR effect of Bi is identified to account for the strengthened photoreactivity. Moreover, the relatively high utilization efficiency of solar energy and the rapid separation rate of photogenerated electron and hole pairs helped to enhance the photocatalytic performance synergistically
Hao, S, Shi, C, Niu, Z & Cao, L 2019, 'Modeling positive and negative feedback for improving document retrieval', Expert Systems with Applications, vol. 120, pp. 253-261.
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© 2018 Elsevier Ltd Pseudo-relevance feedback (PRF) has evident potential for enriching the representation of short queries. Traditional PRF methods treat top-ranked documents as feedback, since they are assumed to be relevant to the query. However, some of these feedback documents may actually distract from the query topic for a range of reasons and accordingly downgrade PRF system performance. Such documents constitute negative examples (negative feedback) but could also be valuable in retrieval. In this paper, a novel framework of query language model construction is proposed in order to improve retrieval performance by integrating both positive and negative feedback. First, an improvement-based method is proposed to automatically identify the types of feedback documents (i.e. positive or negative) according to whether the document enhances the retrieval's effectiveness. Subsequently, based on the learned positive and negative examples, the positive feedback models and the negative feedback models are estimated using an Expectation-Maximization algorithm with the assumptions: the positive term distribution is affected by the context term distribution and the negative term distribution is affected by both the positive term distribution and the context term distribution (such that the positive feedback model upgrades the rankings of relevant documents and the negative feedback model prunes the irrelevant documents from a query). Finally, a content-based representativeness criterion is proposed in order to obtain the representative negative feedback documents. Experiments conducted on the TREC collections demonstrate that our proposed approach results in better retrieval accuracy and robustness than baseline methods.
Harper, R, Hincks, I, Ferrie, C, Flammia, ST & Wallman, JJ 2019, 'Statistical analysis of randomized benchmarking', Physical Review A, vol. 99, no. 5.
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© 2019 American Physical Society. Randomized benchmarking and variants thereof, which we collectively call RB+, are widely used to characterize the performance of quantum computers because they are simple, scalable, and robust to state-preparation and measurement errors. However, experimental implementations of RB+ allocate resources suboptimally and make ad-hoc assumptions that undermine the reliability of the data analysis. In this paper, we propose a simple modification of RB+ which rigorously eliminates a nuisance parameter and simplifies the experimental design. We then show that, with this modification and specific experimental choices, RB+ efficiently provides estimates of error rates with multiplicative precision. Finally, we provide a simplified rigorous method for obtaining credible regions for parameters of interest and a heuristic approximation for these intervals that performs well in currently relevant regimes.
Hassan, W, Lu, DD & Xiao, W 2019, 'Analysis and experimental verification of a single‐switch high‐voltage gain ZCS DC–DC converter', IET Power Electronics, vol. 12, no. 8, pp. 2146-2153.
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Hassan, W, Lu, DD-C & Xiao, W 2019, 'Single-Switch High Step-Up DC–DC Converter With Low and Steady Switch Voltage Stress', IEEE Transactions on Industrial Electronics, vol. 66, no. 12, pp. 9326-9338.
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© 1982-2012 IEEE. In this paper, a new high voltage gain step-up dc-dc converter is proposed for interfacing renewable power generation. The configuration optimally integrates both the coupled-inductor and switched-capacitor techniques to achieve an ultra-high step-up gain of voltage conversion with low voltage stress and high efficiency. It consists of a voltage boost unit, a passive clamp circuit, and a symmetrical voltage multiplier network. The structure becomes modular and extendable without adding any extra winding for ultra-high step-up voltage gain. The proposed topology not only reduces the voltage stress on the main switch but also maintains it steady for the entire duty cycle range. Furthermore, the reverse recovery issue of the diodes is alleviated through the leakage inductance of the coupled inductor. The operation principle and steady-state analysis are presented in detail. Experimental evaluation validates the claimed advantages and demonstrates a well-distributed efficiency curve and the peak of 96.70%.
Hayat, T, Afzal, MU, Lalbakhsh, A & Esselle, KP 2019, '3-D-Printed Phase-Rectifying Transparent Superstrate for Resonant-Cavity Antenna', IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 7, pp. 1400-1404.
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© 2019 IEEE. A three-dimensional (3-D)-printed nonplanar highly transmitting superstrate is presented to improve the directive radiation characteristics of a resonant-cavity antenna (RCA). Classical RCAs are reported with nonuniform aperture-field distribution that compromises their far-field directivity. The concept of near-field phase correction has been used here to design a phase-rectifying transparent superstrate (PRTS), which was fabricated using the 3-D printing technology. The PRTS is printed using easily accessible polylactic acid filament. It has a significantly lower cost and weight compared to its recently published counterparts, while its performance is comparable. The 3-D printing technology yielded the prototype in less than 4 h, which is considerably less compared to the traditional machining methods. Measurements of the prototype indicated close correspondence between the predicted and the measured results. Significant increase in the antenna performance has been achieved, due to the rectification of the aperture phase distribution. Notable aspects encompass 7.3 dB increase in the antenna peak directivity (from 13-20.3 dBi), significant sidelobe level suppression, and an improvement of aperture efficiency by 36.1%, with a PRTS that costs less than 2.5 USD.
Hayat, T, Afzal, MU, Lalbakhsh, A & Esselle, KP 2019, 'Additively Manufactured Perforated Superstrate to Improve Directive Radiation Characteristics of Electromagnetic Source', IEEE Access, vol. 7, pp. 153445-153452.
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© 2013 IEEE. Additively manufactured perforated superstrate (AMPS) is presented to realize directive radio frequency (RF) front-end antennas. The superstrate comprises spatially distributed dielectric unit-cell elements with square perforations, which creates a pre-defined transmission phase delay pattern in the propagating electric field. The proposed square perforation has superior transmission phase characteristics compared to traditionally machined circular perforations and full-wave simulations based parametric analysis has been performed to highlight this supremacy. The AMPS is used with a classical electromagnetic-bandgap resonator antenna (ERA) to improve its directive radiation characteristics. A prototype is developed using the most common, low-cost and easily accessible Acrylonitrile Butadiene Styrene (ABS) filament. The prototype was rapidly fabricated in less than five hours and weighs 139.3 g., which corresponds to the material cost of only 2.1 USD. The AMPS has remarkably improved the radiation performance of ERA by increasing its far-field directivity from 12.67 dB to 21.12 dB and reducing side-lobe level from-7.3 dB to-17.2 dB.
Hayati, H, Eager, D & Walker, P 2019, 'The effects of surface compliance on greyhound galloping dynamics', Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, vol. 233, no. 4, pp. 1033-1043.
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Greyhounds are the fastest breed of dog and can reach a speed up to 68 km/h. These racing animals sustain unique injuries seldom seen in other breeds of dog. The highest rate of life-threatening injuries in these dogs is hock fracture, mostly of the right hind-leg. One of the main injury contributing factors in this sport is the track surface. There are some studies into the ideal track surface composition for greyhound racing but almost no study has investigated the body–surface interaction. Accordingly, the purpose of this work is to study the effect of surface compliance on the galloping dynamics of greyhounds during the hind-leg single-support phase which is a critical phase in hock injuries. Thus, a three degrees-of-freedom model for the greyhound body and substrate surface is designed using spring-loaded inverted pendulum method. The results showed that forces acting on the hind-leg were substantially affected when the surface compliance altered from the relatively hard (natural grass) to a relatively soft surface (synthetic rubber). The main contribution of this work is designing a mathematical model to predict the dynamics of the hock and the hind-leg as the most vulnerable body parts in greyhounds. Furthermore, this model can be used to optimise the greyhound track surface composition and therefore improve the safety and welfare within the greyhound racing industry.
Hayati, H, Mahdavi, F & Eager, D 2019, 'Analysis of Agile Canine Gait Characteristics Using Accelerometry', Sensors, vol. 19, no. 20, pp. 4379-4379.
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The high rate of severe injuries associated with racing greyhounds poses a significant problem for both animal welfare and the racing industry. Using accelerometry to develop a better understanding of the complex gait of these agile canines may help to eliminate injury contributing factors. This study used a single Inertial Measurement Unit (IMU) equipped with a tri-axial accelerometer to characterise the galloping of thirty-one greyhounds on five different race tracks. The dorsal-ventral and anterior-posterior accelerations were analysed in both the time and frequency domains. The fast Fourier transform (FFT) and Morlet wavelet transform were applied to signals. The time-domain signals were synced with the corresponding high frame rate videos of the race. It was observed that the acceleration peaks in the dorsal-ventral accelerations correspond to the hind-leg strikes which were noted to be fifteen times the greyhound’s weight. The FFT analysis showed that the stride frequencies in all tracks were around 3.5 Hz. The Morlet wavelet analysis also showed a reduction in both the frequency and magnitude of signals, which suggests a speed reduction throughout the race. Also, by detecting abrupt changes along the track, the wavelet analysis highlighted potentially hazardous locations on the track. In conclusion, the methods applied in this research contribute to animal safety and welfare by eliminating the factors leading to injuries through optimising the track design and surface type.
He, L, Lu, Z, Pan, L, Zhao, H, Li, X & Zhang, J 2019, 'Optimal Economic and Emission Dispatch of a Microgrid with a Combined Heat and Power System', Energies, vol. 12, no. 4, pp. 604-604.
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With the rapid development of the new concept of energy internet, electric power systems often need to be investigated together with thermal energy systems. Additionally, to reduce pollution from gas emissions, it is very important to study the economic and emission dispatch of integrated electrical and heating systems. Hence, this paper proposes a multi-objective optimization dispatch model for a microgrid (MG) with a combined heat and power (CHP) system. This CHP-based MG system consists of a CHP unit, a wind turbine, a PV system, a fuel cell, an electric boiler, an electric storage, and a heat storage. It can exchange electricity with the distribution network and exchange heat with the district heating network. Minimum economic cost and minimum environmental cost are considered as the two objectives for the operation of this CHP-based MG system. To solve the two objective optimization problem, the multi-objective bacterial colony chemotaxis algorithm is utilized to obtain the Pareto optimal solution set, and the optimal solution is chosen by the Technique for Order of Preference by Similarity to Ideal Solution method. Finally, numerical case studies demonstrate the effectiveness of proposed model and method for the optimal economic and emission dispatch of the CHP-based MG system.
He, L-X, Wu, C & Li, J 2019, 'Post-earthquake evaluation of damage and residual performance of UHPSFRC piers based on nonlinear model updating', Journal of Sound and Vibration, vol. 448, pp. 53-72.
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© 2019 Elsevier Ltd This paper presents an innovative approach for damage and residual performance evaluation of ultra-high performance steel fiber reinforced concrete (UHPSFRC) piers after earthquakes utilizing low-level vibration tests. A nonlinear fiber section element model is constructed in OpenSees to simulate the hysteretic behavior of a UHPSFRC bridge pier. Experimental data from a UHPSFRC column is utilized to verify the accuracy of the nonlinear numerical model. Based on the nonlinear fiber section element model, a new technique of nonlinear finite element model updating involving two updating stages is developed. This new method is designed to incorporate the maximum and minimum strains of section fibers as the updating parameters. By forming the objective function from the modal information, the damage parameters related to the nonlinear material model can be updated by solving the constrained optimization problem. To validate the efficiency of this updating approach, it has been applied to a numerically simulated UHPSFRC pier. With using the updated nonlinear finite element model, the residual axial loading capacity and post-seismic performance of the UHPSFRC pier are examined. The numerical results indicate that the updated nonlinear finite element model can be used not only to assess the current damage state of the UHPSFRC pier but also to predict its future performance after an earthquake. Finally, the noise effect on the proposed method is also investigated. The results reveal that the post-earthquake evaluation approach for UHPSFRC piers based on this study's updating algorithm is robust to noise.
He, M, Xu, W, Zhu, J, Ning, L, Du, G & Ye, C 2019, 'A Novel Hybrid Excited Doubly Salient Machine With Asymmetric Stator Poles', IEEE Transactions on Industry Applications, vol. 55, no. 5, pp. 4723-4732.
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He, T, Wu, M, Lu, DD-C, Aguilera, RP, Zhang, J & Zhu, J 2019, 'Designed Dynamic Reference With Model Predictive Control for Bidirectional EV Chargers', IEEE Access, vol. 7, pp. 129362-129375.
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He, T, Zhu, J, Lu, DD-C & Zheng, L 2019, 'Modified Model Predictive Control for Bidirectional Four-Quadrant EV Chargers With Extended Set of Voltage Vectors', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 274-281.
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© 2013 IEEE. This paper presents a modified model predictive control (MMPC) for bidirectional power flow control between the electric vehicle (EV) chargers and the main grid. In contrast to the conventional finite control set MPC which selects an optimal switching state from eight possible voltage vectors, the proposed MMPC is based on the application of an optimal voltage vector chosen from an extended set of 20 modulated voltage vectors with a fixed duty ratio. To reduce the computational burden introduced by the increased number of voltage sets, a preselection algorithm is developed for the MMPC method. Six voltage vectors are preselected from the 20 sectors. Due to the increased number of the voltage space vectors, the grid currents and active and reactive power performance can be improved by using the proposed MMPC scheme. Both the conventional and proposed methods are compared through experimental test results of a two-level three-phase off-board EV charger.
He, W, Sun, C, Wunsch, DC & Xu, RYD 2019, 'Guest Editorial Special Issue on Intelligent Control Through Neural Learning and Optimization for Human–Machine Hybrid Systems', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3530-3533.
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He, X, Lyu, C, Hsieh, M-H & Wang, X 2019, 'Quantum transfer component analysis for domain adaptation'.
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Domain adaptation, a crucial sub-field of transfer learning, aims to utilize
known knowledge of one data set to accomplish tasks on another data set. In
this paper, we perform one of the most representative domain adaptation
algorithms, transfer component analysis (TCA), on quantum devices. Two
different quantum implementations of this transfer learning algorithm; namely,
the linear-algebra-based quantum TCA algorithm and the variational quantum TCA
algorithm, are presented. The algorithmic complexity of the
linear-algebra-based quantum TCA algorithm is $O(\mathrm{poly}(\log (n_{s} +
n_{t})))$, where $n_{s}$ and $n_{t}$ are input sample size. Compared with the
corresponding classical algorithm, the linear-algebra-based quantum TCA can be
performed on a universal quantum computer with exponential speedup in the
number of given samples. Finally, the variational quantum TCA algorithm based
on a quantum-classical hybrid procedure, that can be implemented on the near
term quantum devices, is proposed.
He, X, Wu, W & Wang, S 2019, 'A constitutive model for granular materials with evolving contact structure and contact forces—Part I: framework', Granular Matter, vol. 21, no. 2.
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He, X, Wu, W & Wang, S 2019, 'A constitutive model for granular materials with evolving contact structure and contact forces—part II: constitutive equations', Granular Matter, vol. 21, no. 2.
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© 2019, The Author(s). This and the companion paper present a constitutive model for granular materials with evolving contact structure and contact forces, where the contact structure and contact forces are characterised by some statistics of grain-scale entities such as contact normals and contact forces. And these statistics are actually the “fabric” or “force” terms in the “stress–force–fabric” (SFF) equation. The stress–strain response is obtained by inserting the predicted “fabric” or “force” terms from evolution equations into the SFF equation. In the model, the critical state is characterised by two fitting equations and three critical state parameters. A semi-mechanistic analysis is conducted about the change of the contact number and the obtained results are combined with observed phenomena in DEM virtual experiments to give the constitutive equations for the “fabric” terms. The change of fabric anisotropy is related to the strain rate, current fabric anisotropy and also contact forces. The change of coordination number is induced by two terms related to volumetric and shear deformations, and also an additional term related to the change of fabric anisotropy. The constitutive equations regarding the “force” terms are also proposed. All the “fabric” or “force” terms are modelled to tend toward their critial state value, which agrees with Li and Dafalias’s (J Eng Mech 138(3):263–275, 2012. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000324) basic philosophy in their evolution equation for the fabric tensor. These equations along with the SFF equation form a constitutive model.
Heathcote, K, Wullschleger, M & Sun, J 2019, 'The effectiveness of multi-dimensional resilience rehabilitation programs after traumatic physical injuries: a systematic review and meta-analysis', Disability and Rehabilitation, vol. 41, no. 24, pp. 2865-2880.
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Heitor, A & Ngo, T 2019, 'Editorial', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 172, no. 4, pp. 211-212.
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Henke, T & Deuse, J 2019, 'Arbeitsfortschrittssynchrone Materialbereitstellung in der Großgerätemontage', ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 114, no. 5, pp. 243-246.
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Since the assembly of large-scale products is strongly influenced by the customer, the products have an unique character. Contract manufacturing is characterized by a low level of standardization and a high share of non-value adding activities with negative effects on throughput times and on-time delivery. In the research project SySMaG the IPS (Dortmund) therefore developed a planning framework to standardize the material supply in large scale assembly and to reduce non-value adding activities.
Hesamian, MH, Jia, W, He, X & Kennedy, P 2019, 'Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges', Journal of Digital Imaging, vol. 32, no. 4, pp. 582-596.
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Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.
Hirzallah, M, Krunz, M & Xiao, Y 2019, 'Harmonious Cross-Technology Coexistence With Heterogeneous Traffic in Unlicensed Bands: Analysis and Approximations', IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 3, pp. 690-701.
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IEEE The dramatic growth in demand for mobile data has prompted mobile network operators (MNOs) to explore spectrum sharing in unlicensed bands. MNOs have been allowed recently to operate their LTE services over the 5 GHz Unlicensed National Information Infrastructure (U-NII) bands, currently occupied by Wi-Fi. The unlicensed LTE operation has been standardized by 3GPP under the name Licensed Assisted Access (LAA). Unlicensed 5G New radio (NR) operation over the U-NII bands, a.k.a., NR-Unlicensed (NR-U), is also being explored. To support applications with diverse quality of service requirements, LAA, NR-U, and Wi-Fi technologies offer multiple priority classes with different contention parameters for accessing an unlicensed channel. How these different classes affect the interplay between coexisting MNOs and Wi-Fi systems is still a relatively under-explored topic. In this paper, we develop a simple yet efficient framework for fair coexistence between LTE MNOs and Wi-Fi systems, each with multiple priority classes. We derive approximate closed-form solutions for the probability of successful transmission (PST), average contention delay, and average throughput under different LAA and Wi-Fi priority classes. LTE and Wi-Fi operators can fit these solutions to offline and/or online measurements, and use them to further optimize their system throughput and latency. Our results reveal that PSTs computed with our approximate models are within 5% of these obtained via simulation under dense network deployments and high traffic loads.
Hoang, DT, Nguyen, DN, Alsheikh, MA, Gong, S, Dutkiewicz, E, Niyato, D & Han, Z 2019, ''Borrowing Arrows with Thatched Boats': The Art of Defeating Reactive Jammers in IoT Networks', IEEE Wireless Communications Magazine, vol. 27, no. 3, pp. 79-87.
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In this article, we introduce a novel deception strategy which is inspired by
the 'Borrowing Arrows with Thatched Boats', one of the most famous military
tactics in the history, in order to defeat reactive jamming attacks for
low-power IoT networks. Our proposed strategy allows resource-constrained IoT
devices to be able to defeat powerful reactive jammers by leveraging their own
jamming signals. More specifically, by stimulating the jammer to attack the
channel through transmitting fake transmissions, the IoT system can not only
undermine the jammer's power, but also harvest energy or utilize jamming
signals as a communication means to transmit data through using RF energy
harvesting and ambient backscatter techniques, respectively. Furthermore, we
develop a low-cost deep reinforcement learning framework that enables the
hardware-constrained IoT device to quickly obtain an optimal defense policy
without requiring any information about the jammer in advance. Simulation
results reveal that our proposed framework can not only be very effective in
defeating reactive jamming attacks, but also leverage jammer's power to enhance
system performance for the IoT network.
Hodges, J, Attia, T, Arukgoda, J, Kang, C, Cowden, M, Doan, L, Ranasinghe, R, Abdelatty, K, Dissanayake, G & Furukawa, T 2019, 'Multistage bayesian autonomy for high-precision operation in a large field', Journal of Field Robotics, vol. 36, no. 1, pp. 183-203.
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© 2018 Wiley Periodicals, Inc. This paper presents a generalized multistage bayesian framework to enable an autonomous robot to complete high-precision operations on a static target in a large field. The proposed framework consists of two multistage approaches, capable of dealing with the complexity of high-precision operation in a large field to detect and localize the target. In the multistage localization, locations of the robot and the target are estimated sequentially when the target is far away from the robot, whereas these locations are estimated simultaneously when the target is close. A level of confidence (LOC) for each detection criterion of a sensor and the associated probability of detection (POD) of the sensor are defined to make the target detectable with different LOCs at varying distances. Differential entropies of the robot and target are used as a precision metric for evaluating the performance of the proposed approach. The proposed multistage observation and localization approaches were applied to scenarios using an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV). Results with the UGV in simulated environments and then real environments show the effectiveness of the proposed approaches to real-world problems. A successful demonstration using the UAV is also presented.
Hoque, M, Tasfia, S, Ahmed, N & Pradhan, B 2019, 'Assessing Spatial Flood Vulnerability at Kalapara Upazila in Bangladesh Using an Analytic Hierarchy Process', Sensors, vol. 19, no. 6, pp. 1302-1302.
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Floods are common natural disasters worldwide, frequently causing loss of lives and huge economic and environmental damages. A spatial vulnerability mapping approach incorporating multi-criteria at the local scale is essential for deriving detailed vulnerability information for supporting flood mitigation strategies. This study developed a spatial multi-criteria-integrated approach of flood vulnerability mapping by using geospatial techniques at the local scale. The developed approach was applied on Kalapara Upazila in Bangladesh. This study incorporated 16 relevant criteria under three vulnerability components: physical vulnerability, social vulnerability and coping capacity. Criteria were converted into spatial layers, weighted and standardised to support the analytic hierarchy process. Individual vulnerability component maps were created using a weighted overlay technique, and then final vulnerability maps were produced from them. The spatial extents and levels of vulnerability were successfully identified from the produced maps. Results showed that the areas located within the eastern and south-western portions of the study area are highly vulnerable to floods due to low elevation, closeness to the active channel and more social components than other parts. However, with the integrated coping capacity, western and south-western parts are highly vulnerable because the eastern part demonstrated particularly high coping capacity compared with other parts. The approach provided was validated by qualitative judgement acquired from the field. The findings suggested the capability of this approach to assess the spatial vulnerability of flood effects in flood-affected areas for developing effective mitigation plans and strategies.
Hoque, MA-A, Ahmed, N, Pradhan, B & Roy, S 2019, 'Assessment of coastal vulnerability to multi-hazardous events using geospatial techniques along the eastern coast of Bangladesh', Ocean & Coastal Management, vol. 181, pp. 104898-104898.
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© 2019 Elsevier Ltd The eastern coastal region of Bangladesh, which has a 377 km-long coastline, is highly vulnerable to multi-hazardous events, such as tropical cyclones, coastal floods, coastal erosion and salinity intrusion. The vulnerability of this coastal region is likely to increase under the future climate change context. This research aims to develop a coastal vulnerability index (CVI) of multi-hazardous events for the eastern coastal region of Bangladesh. Eight parameters, mostly focused on physical vulnerability, were considered in this study. Various thematic layers were prepared for each parameter using spatial techniques, and all parameters were assigned a vulnerability ranking. Finally, a CVI was developed and the related values were categorised into five distinct classes (i.e., very high, high, moderate, low, and very low). Results indicate that approximately 121 km (32%) of the coastline of the study area is in high-to very high-vulnerability zones. Low elevations, gentle slopes, high storm surge impacts, sandy coastlines, high shoreline erosion rates and high sea-level changes are the most important factors of high to very-high vulnerability zones. The moderately vulnerable area covers approximately 119 km (32%) of the coastline. Meanwhile, 78 (21%) and 59 (16%) km of the coastlines are in low-to very low-vulnerability zones, respectively. These coastlines are characterised by steep slopes with high elevations, low tide range and storm surge heights as well as less erosion. The CVI results were validated by qualitative observations acquired from the field. The findings of this study can be applied by policymakers and administrators to develop effective mitigation plans and minimise the likely impacts of coastal multi-hazards.
Hoque, MA-A, Pradhan, B, Ahmed, N & Roy, S 2019, 'Tropical cyclone risk assessment using geospatial techniques for the eastern coastal region of Bangladesh', Science of The Total Environment, vol. 692, pp. 10-22.
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Tropical cyclones frequently affect millions of people, damaging properties, livelihoods and environments in the coastal region of Bangladesh. The intensity and extent of tropical cyclones and their impacts are likely to increase in the future due to climate change. The eastern coastal region of Bangladesh is one of the most cyclone-affected coastal regions. A comprehensive spatial assessment is therefore essential to produce a risk map by identifying the areas under high cyclone risks to support mitigation strategies. This study aims to develop a comprehensive tropical cyclone risk map using geospatial techniques and to quantify the degree of risk in the eastern coastal region of Bangladesh. In total, 14 spatial criteria under three risk components, namely, vulnerability and exposure, hazard, and mitigation capacity, were assessed. A spatial layer was created for each criterion, and weighting was conducted following the Analytical Hierarchy Process. The individual risk component maps were generated from their indices, and subsequently, the overall risk map was produced by integrating the indices through a weighted overlay approach. Results demonstrate that the very-high risk zone covered 9% of the study area, whereas the high-risk zone covered 27%. Specifically, the south-western (Sandwip and Sonagazi), western (Patiya, Kutubdia, Maheshkhali, Chakaria, Cox's Bazar and Chittagong Sadar) and south-western (Teknaf) regions of the study site are likely to be under a high risk of tropical cyclone impacts. Low and very-low hazard zones constitute 11% and 28% of the study area, respectively, and most of these areas are located inland. The results of this study can be used by the concerned authorities to develop and apply effective cyclone impact mitigation plans and strategies.
Hossain, MA, Pota, HR, Hossain, MJ & Blaabjerg, F 2019, 'Evolution of microgrids with converter-interfaced generations: Challenges and opportunities', International Journal of Electrical Power & Energy Systems, vol. 109, pp. 160-186.
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© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids.
Hossain, N & Mahlia, TMI 2019, 'Progress in physicochemical parameters of microalgae cultivation for biofuel production', Critical Reviews in Biotechnology, vol. 39, no. 6, pp. 835-859.
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Microalgae have been exploited for biofuel generation in the current era due to its enormous energy content, fast cellular growth rate, inexpensive culture approaches, accumulation of inorganic compounds, and CO2 sequestration. Currently, research is ongoing towards the advancement of the microalgae cultivation parameters to enhance the biomass yield. The main objective of this study was to delineate the progress of physicochemical parameters for microalgae cultivation such as gaseous transfer, mixing, light demand, temperature, pH, nutrients and the culture period. This review demonstrates the latest research trends on mass transfer coefficient of different microalgae culturing reactors, gas velocity optimization, light intensity, retention time, and radiance effects on microalgae cellular growth, temperature impact on chlorophyll production, and nutrient dosage ratios for cellulosic metabolism to avoid nutrient deprivation. Besides that, cultivation approaches for microalgae associated with mathematical modeling for different parameters, mechanisms of microalgal growth rate and doubling time have been elaborately described. Along with that, this review also documents potential lipid-carbohydrate-protein enriched microalgae candidates for biofuel, biomass productivity, and different cultivation conditions including open-pond cultivation, closed-loop cultivation, and photobioreactors. Various photobioreactor types, the microalgae strain, productivity, advantages, and limitations were tabulated. In line with microalgae cultivation, this study also outlines in detail numerous biofuels from microalgae.
Hossain, N, Mahlia, TMI & Saidur, R 2019, 'Latest development in microalgae-biofuel production with nano-additives', Biotechnology for Biofuels, vol. 12, no. 1.
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Background:Microalgae have been experimented as a potential feedstock for biofuel generation in current era owing to its' rich energy content, inflated growth rate, inexpensive culture approaches, the notable capacity of CO2 fixation, and O2 addition to the environment. Currently, research is ongoing towards the advancement of microalgal-biofuel technologies. The nano-additive application has been appeared as a prominent innovation to meet this phenomenon. Main text:The main objective of this study was to delineate the synergistic impact of microalgal biofuel integrated with nano-additive applications. Numerous nano-additives such as nano-fibres, nano-particles, nano-tubes, nano-sheets, nano-droplets, and other nano-structures' applications have been reviewed in this study to facilitate microalgae growth to biofuel utilization. The present paper was intended to comprehensively review the nano-particles preparing techniques for microalgae cultivation and harvesting, biofuel extraction, and application of microalgae-biofuel nano-particles blends. Prospects of solid nano-additives and nano-fluid applications in the future on microalgae production, microalgae biomass conversion to biofuels as well as enhancement of biofuel combustion for revolutionary advancement in biofuel technology have been demonstrated elaborately by this review. This study also highlighted the potential biofuels from microalgae, numerous technologies, and conversion processes. Along with that, the study recounted suitability of potential microalgae candidates with an integrated design generating value-added co-products besides biofuel production. Conclusions:Nano-additive applications at different stages from microalgae culture to end-product utilization presented strong possibility in mercantile approach as well as positive impact on the environment along with valuable co-products generation into the near future.
Hossain, N, Mahlia, TMI, Zaini, J & Saidur, R 2019, 'Techno‐economics and Sensitivity Analysis of Microalgae as Commercial Feedstock for Bioethanol Production', Environmental Progress & Sustainable Energy, vol. 38, no. 5, pp. 13157-13157.
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© 2019 American Institute of Chemical Engineers The foremost purpose of this techno-economic analysis (TEA) modeling was to predict a harmonized figure of comprehensive cost analysis for commercial bioethanol generation from microalgae species in Brunei Darussalam based on the conventional market scenario. This model was simulated to set out economic feasibility and probabilistic assumption for large-scale implementations of a tropical microalgae species, Chlorella vulgaris, for a bioethanol plant located in the coastal area of Brunei Darussalam. Two types of cultivation systems such as closed system (photobioreactor—PBR) and open pond approaches were anticipated for a total approximate biomass of 220 t year−1 on 6 ha coastal areas. The biomass productivity was 56 t ha−1 for PBR and 28 t ha−1 for pond annually. The plant output was 58.90 m3 ha−1 for PBR and 24.9 m3 ha−1 for pond annually. The total bioethanol output of the plant was 57,087.58 gal year−1 along with the value added by-products (crude bio-liquid and slurry cake). The total production cost of this project was US$2.22 million for bioethanol from microalgae and total bioethanol selling price was US$2.87 million along with the by-product sale price of US$1.6 million. A sensitivity analysis was conducted to forecast the uncertainty of this conclusive modeling. Different data sets through sensitivity analysis also presented positive impacts of economical and environmental views. This TEA model is expected to be initialized to determine an alternative energy and also minimize environmental pollution. With this current modeling, microalgal-bioethanol utilization mandated with gasoline as well as microalgae cultivation, biofuel production integrated with existing complementary industries, are strongly recommended for future applications. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019.
Hossain, N, Razali, AN, Mahlia, TMI, Chowdhury, T, Chowdhury, H, Ong, HC, Shamsuddin, AH & Silitonga, AS 2019, 'Experimental Investigation, Techno-Economic Analysis and Environmental Impact of Bioethanol Production from Banana Stem', Energies, vol. 12, no. 20, pp. 3947-3947.
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Banana stem is being considered as the second largest waste biomass in Malaysia. Therefore, the environmental challenge of managing this huge amount of biomass as well as converting the feedstock into value-added products has spurred the demand for diversified applications to be implemented as a realistic approach. In this study, banana stem waste was experimented for bioethanol generation via hydrolysis and fermentation methods with the presence of Saccharomyces cerevisiae (yeast) subsequently. Along with the experimental analysis, a realistic pilot scale application of electricity generation from the bioethanol has been designed by HOMER software to demonstrate techno-economic and environmental impact. During sulfuric acid and enzymatic hydrolysis, the highest glucose yield was 5.614 and 40.61 g/L, respectively. During fermentation, the maximum and minimum glucose yield was 62.23 g/L at 12 h and 0.69 g/L at 72 h, respectively. Subsequently, 99.8% pure bioethanol was recovered by a distillation process. Plant modeling simulated operating costs 65,980 US$/y, net production cost 869347 US$ and electricity cost 0.392 US$/kWh. The CO2 emission from bioethanol was 97,161 kg/y and SO2 emission was 513 kg/y which is much lower than diesel emission. The overall bioethanol production from banana stem and application of electricity generation presented the approach economically favorable and environmentally benign.
Hossain, N, Zaini, J & Indra Mahlia, TM 2019, 'Life cycle assessment, energy balance and sensitivity analysis of bioethanol production from microalgae in a tropical country', Renewable and Sustainable Energy Reviews, vol. 115, pp. 109371-109371.
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© 2019 Elsevier Ltd Overuse of petroleum and ongoing carbon-di-oxide (CO2) rise in the air of Brunei Darussalam has been emerged as a major environmental concern in this country. To resolve this issue, a comprehensive life cycle assessment (LCA) of alternative biofuel, bioethanol production from microalgae was demanded for realistic implementation. Therefore, LCA of bioethanol production from microalgae in terms of CO2 emission and energy balance was investigated based on the scenario of industrial-scale in Brunei Darussalam. This study demonstrated that 220 tons microalgae biomass was cultivated on 6 ha offshore lands for commercial bioethanol generation. The annual outcome of this commercial bioethanol plant has revealed net CO2 balance 218.86 ton. From the energy perspective, this study manifested itself as favourable with net energy ratio, 0.45 and net energy balance, −2749.6 GJ y−1. Apart from CO2 balance and energy generation aspect, the project demanded low water and land footprints. For photobioreactor cultivation, water and land footprints were 2 m3 GJ−1 and 2 m2 GJ−1, respectively as well as for open pond approach, they were 87 m3 GJ−1 and 13 m2 GJ−1, respectively. The project also presented microalgae growth supplements (phosphorus and nitrogen) accumulation possibilities from wastewater of manure and industries which is another positive aspect for benign environment. Overall, the commercial plant presented low CO2 emission, low land and water demand for microalgae cultivation, alternative eco-friendly and cheaper nutrients sources, quite high energy generation with main product and by-products. Thus, this study projected positive impact on energy and environmental aspects of microalgae-to-bioethanol conversion.
Hossain, SI, Gandhi, NS, Hughes, ZE, Gu, YT & Saha, SC 2019, 'Molecular insights on the interference of simplified lung surfactant models by gold nanoparticle pollutants', Biochimica et Biophysica Acta (BBA) - Biomembranes, vol. 1861, no. 8, pp. 1458-1467.
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Inhaled nanoparticles (NPs) are experienced by the first biological barrier inside the alveolus known as lung surfactant (LS), a surface tension reducing agent, consisting of phospholipids and proteins in the form of the monolayer at the air-water interface. The monolayer surface tension is continuously regulated by the alveolus compression and expansion and protects the alveoli from collapsing. Inhaled NPs can reach deep into the lungs and interfere with the biophysical properties of the lung components. The interaction mechanisms of bare gold nanoparticles (AuNPs) with the LS monolayer and the consequences of the interactions on lung function are not well understood. Coarse-grained molecular dynamics simulations were carried out to elucidate the interactions of AuNPs with simplified LS monolayers at the nanoscale. It was observed that the interactions of AuNPs and LS components deform the monolayer structure, change the biophysical properties of LS and create pores in the monolayer, which all interfere with the normal lungs function. The results also indicate that AuNP concentrations >0.1 mol% (of AuNPs/lipids) hinder the lowering of the LS surface tension, a prerequisite of the normal breathing process. Overall, these findings could help to identify the possible consequences of airborne NPs inhalation and their contribution to the potential development of various lung diseases.
Hossain, SM, Park, MJ, Park, HJ, Tijing, L, Kim, J-H & Shon, HK 2019, 'Preparation and characterization of TiO2 generated from synthetic wastewater using TiCl4 based coagulation/flocculation aided with Ca(OH)2', Journal of Environmental Management, vol. 250, pp. 109521-109521.
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This study focused on the preparation of undoped and Ca-doped titania from flocculation generated sludge. Initially, TiCl4 was utilised to perform coagulation and flocculation in synthetic wastewater and an optimised dose of coagulant was determined by evaluating the turbidity, dissolved organic carbon (DOC) and zeta potential of the treated water. Later, using Ca(OH)2 as a coagulant aid, the effects on effluent pH, turbidity and DOC removal were investigated. Both Ca-doped and undoped anatase TiO2 were prepared from the flocculated sludge for morphological and photocatalytic evaluation. During the standalone use of TiCl4, maximum turbidity and DOC removal were found at 11.63 and 14.54 mg Ti/L, respectively. At the corresponding coagulant dose, rapid deprotonation of water caused the pH of the effluent to reach below 3.77 mg Ti/L. Whereas, when using Ca(OH)2 as a coagulant aid, a neutral pH (7.26) was attained at a simultaneous dosing of 32.40 mg Ca/L and 14.54 mg Ti/L. When aided with Ca(OH)2, the turbidity removal was further increased by 54.28% and the DOC removal was somewhat similar to the standalone use of TiCl4. TiO2 was prepared by incinerating the collected sludge at 600 °C for 2 h. Both XRD and SEM analysis were conducted to observe the morphology of the prepared titania. The XRD pattern of the TiO2 showed only an anatase phase along with the presence of a high atomic proportion of Ca (4.14%). Consequently, a high amount of Ca atoms inhibited the level of TiO2 phase and no obvious presence of CaO was observed. The prepared Ca-doped TiO2 at the optimised dose of Ca(OH)2 was found to be inferior to the undoped TiO2 during the photodegradation of acetaldehyde. However, a reduced dose of Ca(OH)2 (<15 mg Ca/L) exhibited a substantial increase in photoactivity under UV irradiance.
Hosseini, SM & Al-Jumaily, A 2019, 'Analytical solution for forced vibration of piezoelectrically actuated Timoshenko beam', Journal of Intelligent Material Systems and Structures, vol. 30, no. 8, pp. 1276-1284.
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Forced vibrations of a Timoshenko beam covered with a piezoelectric actuator on its top surface were investigated in this article. As the proposed beam model complied with Timoshenko beam theory, the effects of both rotary inertia and shear deformation were considered. Hamilton principle in conjunction with the Galerkin procedure were applied to derive the governing equation of motion resulting in a second-order ordinary differential equation in time. A sinusoidal electric voltage was applied to the piezoelectric actuator, and a spatially distributed harmonic mechanical force was exerted to the beam. The response of the system to the force stimulation gave an analytical relation between natural frequency and amplitude of the vibration. Using the obtained analytical relation, the effects of different factors and material properties including the modulus of elasticity of the piezoelectric layer and the piezoelectric coefficient on the vibrational response of the beam were examined. The results indicated that the piezoelectric layer as an actuator provided an effective tool for active control of vibration. Increasing the piezoelectric coefficient as well as the electric voltage applied on the piezoelectric actuator increased the amplitude of vibration, while the amplitude decreased by increasing the modulus of elasticity of the piezoelectric actuator. The results were also verified by finite element analysis.
Hou, Z, Tang, J-F, Ferrie, C, Xiang, G-Y, Li, C-F & Guo, G-C 2019, 'Experimental realization of self-guided quantum process tomography', Phys. Rev. A, vol. 101, no. 2, p. 022317.
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Characterization of quantum processes is a preliminary step necessary in the
development of quantum technology. The conventional method uses standard
quantum process tomography, which requires $d^2$ input states and $d^4$ quantum
measurements for a $d$-dimensional Hilbert space. These experimental
requirements are compounded by the complexity of processing the collected data,
which can take several orders of magnitude longer than the experiment itself.
In this paper we propose an alternative self-guided algorithm for quantum
process tomography, tuned for the task of finding an unknown unitary process.
Our algorithm is a fully automated and adaptive process characterization
technique. The advantages of our algorithm are: inherent robustness to both
statistical and technical noise; requires less space and time since there is no
post-processing of the data; requires only a single input state and
measurement; and, provides on-the-fly diagnostic information while the
experiment is running. Numerical results show our algorithm achieves the same
$1/n$ scaling as standard quantum process tomography when $n$ uses of the
unknown process are used. We also present experimental results wherein the
algorithm, and its advantages, are realized for the task of finding an element
of $SU(2)$.
Howard, D, Macsween, K, Edwards, GC, Desservettaz, M, Guérette, E-A, Paton-Walsh, C, Surawski, NC, Sullivan, AL, Weston, C, Volkova, L, Powell, J, Keywood, MD, Reisen, F & (Mick) Meyer, CP 2019, 'Investigation of mercury emissions from burning of Australian eucalypt forest surface fuels using a combustion wind tunnel and field observations', Atmospheric Environment, vol. 202, pp. 17-27.
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Hu, C, Liu, X & Lu, J 2019, 'Robust trading strategies for a waste-to-energy combined heat and power plant in a day-ahead electricity market', IFAC-PapersOnLine, vol. 52, no. 13, pp. 1108-1113.
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© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Waste-to-energy (WtE) technologies have been used all over the world as they can solve the dilemma of waste management, energy demand, and global warming. Many modern WtE plants are built and operated in a combined heat and power (CHP) mode due to the high overall energy efficiency. This paper studies robust trading strategies for a WtE CHP plant which sells electricity in a day-ahead electricity market and exports heat to a district heating network. Owing to the requirements of the day-ahead electricity market, plant operators must determine the trading strategy one day before real delivery of electricity. However, many key problem parameters including electricity price, heat demand, and the amount of waste delivered to the plant are uncertain at the day-ahead stage. To derive robust electricity trading strategies for the WtE CHP plant under different types of uncertainty, a two-stage robust optimization model is developed and a solution procedure based on the column-and-constraint generation method is designed. A case study is also performed to illustrate the effectiveness of the robust model and the solution procedure.
Hu, J, Li, Y & Zhu, J 2019, 'Multi‐objective model predictive control of doubly‐fed induction generators for wind energy conversion', IET Generation, Transmission & Distribution, vol. 13, no. 1, pp. 21-29.
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© The Institution of Engineering and Technology 2018. As large-scale integration of wind systems into the power grid is on the rise, advanced control techniques for wind power generators are highly desired. This paper proposes a simple but effective control technique for doubly fed induction generators (DFIGs) based on the multi-objective model predictive control (MOMPC) scheme. The future behaviors of the DFIGs are predicted by using the system model and the possible converter switching states. The most appropriate vector is then determined by a cost function. By properly modifying the cost function with active and reactive powers as the control objectives, fast grid synchronisation, smooth grid connection, flexible power regulation and maximum power point tracking (MPPT) can be achieved, respectively. In order to reduce the switching frequency for switching loss reduction, a nonlinear constraint is integrated into the cost function. The controller is simple without using any Proportion Integration (PI) regulators, current loops, and switching tables. A numerical simulation of a 2MW system based on MATLAB/Simulink is built to verify the effectiveness of the proposed method. The results show that the proposed method can achieve quicker transient response, better steady-state performance, and lower switching frequency compared to the conventional switching table based direct power control (DPC).
Hu, J, Li, Z, Zhu, J & Guerrero, JM 2019, 'Voltage Stabilization: A Critical Step Toward High Photovoltaic Penetration', IEEE Industrial Electronics Magazine, vol. 13, no. 2, pp. 17-30.
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© 2007-2011 IEEE. The increasing photovoltaic (PV) power sources connected to low-voltage (LV) distribution networks generate a new grid environment featuring various types of power generations near consumers and bidirectional active and reactive power flows. However, the large-scale deployment of PVs is hindered by the power quality problems, particularly voltage deviation. To overcome this obstacle, proper mitigation techniques should be developed to eliminate the negative impacts of high-PV penetration in LV networks. This article provides an in-depth review of recently developed technologies that prevent voltage deviation in LV grids with PVs. Following an investigation of the voltage fluctuation phenomena along the distribution feeder due to variable PV output and power demand, the mathematical relationship between power flow and voltage level is revealed. The solutions that mitigate the voltage variation are then investigated and classified. Their effectiveness, advantages, and disadvantages are illustrated. Finally, the current trend in grid integration of PVs and other distributed generators (DGs) under future grid framework is discussed.
Hu, J, Liang, B & Qiu, X 2019, 'High-efficiency collimation of airborne sound through a single deep-subwavelength aperture in an ultra-thin planar plate', Applied Physics Express, vol. 12, no. 2, pp. 027002-027002.
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Hu, L, Chen, Q, Cao, L, Jian, S, Zhao, H & Cao, J 2019, 'Evolving Coauthorship Modeling and Prediction via Time-Aware Paired Choice Analysis', IEEE Access, vol. 7, pp. 98639-98651.
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Coauthorship prediction is challenging yet important for academic collaboration and novel research topics discovery. The challenges lie in the dynamics of social or organizational relationships, changing preferences of suitable collaborators, and the evolution of research interests or topics. However, most current approaches and systems developed so far are mainly based on past coauthorships from a static viewpoint and do not capture the above evolving characteristics in coauthoring. Accordingly, this paper proposes a time-aware approach to capture the evolving coauthorships from online academic databases in terms of capturing the dynamics of social relationships and research interests. In particular, in order to understand the underlying factors influencing researchers to make choices of coauthors, we incorporate choice modeling based on utility theory. More specifically, our model conducts a series of pairwise choices over a poset induced by a utility function so as to learn the preference over all candidate coauthors. To complete the model inference, a gradient-based algorithm is devised to efficiently learn the model parameters for large-scale data. Finally, extensive experiments conducted on a real-world dataset show that our approach consistently outperforms other state-of-the-art methods.
Hu, M, Liu, Y, Sugumaran, V, Liu, B & Du, J 2019, 'Automated structural defects diagnosis in underground transportation tunnels using semantic technologies', Automation in Construction, vol. 107, pp. 102929-102929.
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Hu, S, Xu, M, Zhang, H, Xiao, C & Gui, C 2019, 'Affective Content-aware Adaptation Scheme on QoE Optimization of Adaptive Streaming over HTTP', ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 15, no. 3s, pp. 1-18.
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The article presents a novel affective content-aware adaptation scheme (ACAA) to optimize Quality of Experience (QoE) for dynamic adaptive video streaming over HTTP (DASH). Most of the existing DASH adaptation schemes conduct video bit-rate adaptation based on an estimation of available network resources, which ignore user preference on affective content (AC) embedded in video data streaming over the network. Since the personal demands to AC is very different among all viewers, to satisfy individual affective demand is critical to improve the QoE in commercial video services. However, the results of video affective analysis cannot be applied into a current adaptive streaming scheme directly. Correlating the AC distributions in user's viewing history to each being streamed segment, the affective relevancy can be inferred as an affective metric for the AC related segment. Further, we have proposed an ACAA scheme to optimize QoE for user desired affective content while taking into account both network status and affective relevancy. We have implemented the ACAA scheme over a realistic trace-based evaluation and compared its performance in terms of network performance, QoE with that of Probe and Adaptation (PANDA), buffer-based adaptation (BBA), and Model Predictive Control (MPC). Experimental results show that ACAA can preserve available buffer time for future being delivered affective content preferred by viewer's individual preference to achieve better QoE in affective contents than those normal contents while remain the overall QoE to be satisfactory.
Hu, X, Zheng, W, Zhu, Q, Gu, L, Du, Y, Han, Z, Zhang, X, Carter, DR, Cheung, BB, Qiu, A & Jiang, C 2019, 'Increase in DNA Damage by MYCN Knockdown Through Regulating Nucleosome Organization and Chromatin State in Neuroblastoma', Frontiers in Genetics, vol. 10, no. JUL.
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© 2019 Hu, Zheng, Zhu, Gu, Du, Han, Zhang, Carter, Cheung, Qiu and Jiang. As a transcription factor, MYCN regulates myriad target genes including the histone chaperone FACT. Moreover, FACT and MYCN expression form a forward feedback loop in neuroblastoma. It is unclear whether MYCN is involved in chromatin remodeling in neuroblastoma through regulation of its target genes. We showed here that MYCN knockdown resulted in loss of the nucleosome-free regions through nucleosome assembly in the promoters of genes functionally enriched for DNA repair. The active mark H3K9ac was removed or replaced by the repressive mark H3K27me3 in the promoters of double-strand break repair-related genes upon MYCN knockdown. Such chromatin state alterations occurred only in MYCN-bound promoters. Consistently, MYCN knockdown resulted in a marked increase in DNA damage in the treatment with hydroxyurea. In contrast, nucleosome reorganization and histone modification changes in the enhancers largely included target genes with tumorigenesis-related functions such as cell proliferation, cell migration, and cell-cell adhesion. The chromatin state significantly changed in both MYCN-bound and MYCN-unbound enhancers upon MYCN knockdown. Furthermore, MYCN knockdown independently regulated chromatin remodeling in the promoters and the enhancers. These findings reveal the novel epigenetic regulatory role of MYCN in chromatin remodeling and provide an alternative potential epigenetic strategy for MYCN-driven neuroblastoma treatment.
Hu, Y, Manzoor, A, Ekparinya, P, Liyanage, M, Thilakarathna, K, Jourjon, G & Seneviratne, A 2019, 'A Delay-Tolerant Payment Scheme Based on the Ethereum Blockchain', IEEE Access, vol. 7, pp. 33159-33172.
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Huang, J, Fei, Z, Wang, T, Wang, X, Liu, F, Zhou, H, Zhang, JA & Wei, G 2019, 'V2X-communication assisted interference minimization for automotive radars', China Communications, vol. 16, no. 10, pp. 100-111.
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With the development of automated driving vehicles, more and more vehicles will be fitted with more than one automotive radars, and the radar mutual interference will become very significant. Vehicle to everything (V2X) communication is a potential way for coordinating automotive radars and reduce the mutual interference. In this paper, we analyze the positional relation of the two radars that interfere with each other, and evaluate the mutual interference for different types of automotive radars based on Poisson point process (PPP). We also propose a centralized framework and the corresponding algorithm, which relies on V2X communication systems to allocate the spectrum resources for automotive radars to minimize the interference. The minimum spectrum resources required for zero-interference are analyzed for different cases. Simulation results validate the analysis and show that the proposed framework can achieve near-zero-interference with the minimum spectrum resources.
Huang, K, Chuang, C, Wang, Y, Hsieh, C, King, J & Lin, C 2019, 'The effects of different fatigue levels on brain–behavior relationships in driving', Brain and Behavior, vol. 9, no. 12.
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BACKGROUND:In the past decade, fatigue has been regarded as one of the main factors impairing task performance and increasing behavioral lapses during driving, even leading to fatal car crashes. Although previous studies have explored the impact of acute fatigue through electroencephalography (EEG) signals, it is still unclear how different fatigue levels affect brain-behavior relationships. METHODS:A longitudinal study was performed to investigate the brain dynamics and behavioral changes in individuals under different fatigue levels by a sustained attention task. This study used questionnaires in combination with actigraphy, a noninvasive means of monitoring human physiological activity cycles, to conduct longitudinal assessment and tracking of the objective and subjective fatigue levels of recruited participants. In this study, degrees of effectiveness score (fatigue rating) are divided into three levels (normal, reduced, and high risk) by the SAFTE fatigue model. RESULTS:Results showed that those objective and subjective indicators were negatively correlated to behavioral performance. In addition, increased response times were accompanied by increased alpha and theta power in most brain regions, especially the posterior regions. In particular, the theta and alpha power dramatically increased in the high-fatigue (high-risk) group. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change. CONCLUSION:Our results help to explain the inconsistent findings among existing studies, which considered the effects of only acute fatigue on driving performance while ignoring different levels of resident fatigue, and potentially lead to practical and precise biomathematical models to better predict the performance of human operators.
Huang, L, Liu, Z, Wu, C & Liang, J 2019, 'The scattering of plane P, SV waves by twin lining tunnels with imperfect interfaces embedded in an elastic half-space', Tunnelling and Underground Space Technology, vol. 85, pp. 319-330.
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© 2018 Elsevier Ltd A viscous-slip interface model is employed to simulate the contact between the tunnels lining and the surrounding rock, and the scattering of P, SV waves by twin shallowly buried lining tunnels is investigated with the indirect boundary integral equation method (IBIEM). The amplification effect of the dynamic stress concentration of the lining and the surface displacement near the tunnels is examined. It is evident that the slipping-stiffness coefficient and viscosity coefficient at the lining-surrounding rock interface have a significant influence on the dynamic stress distribution and the nearby surface displacement response of the lining tunnel, while the influence characteristics strongly depend on the incident wave type, frequency and angle. Under the incidence of low frequency wave, as a whole, with the increase of the sliding stiffness, the hoop stress increases gradually for plane P and SV waves; while in the resonance frequency (the incident wave frequency is consistent with the natural frequency of the soil column above the tunnels), specially for high-frequency band, the dynamic stress concentration effect is more significant for smaller sliding stiffness. With the increase of viscosity coefficient, the dynamic stress concentration factor inside the lining gradually decreases. Also, the tunnels with viscous-slip interfaces have a more significant amplification effect on the nearby surface displacement amplitude. Moreover, the hoop stress of the twin tunnels may be obviously larger than that of single tunnel in most cases. The dynamic analysis of the underground structure under the actual strong dynamic loading should consider the influence of the slip effect between the lining and surrounding rock interface.
Huang, L, Zhang, G, Yu, S, Fu, A & Yearwood, J 2019, 'SeShare: Secure cloud data sharing based on blockchain and public auditing', Concurrency and Computation: Practice and Experience, vol. 31, no. 22, pp. 1-15.
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© 2017 John Wiley & Sons, Ltd. In a data sharing group, each user can upload, modify, and access group files and a user is required to generate a new signature for the modified file after modification. There is a situation that two or more users modify the same file at almost the same time, which should be avoided as it gives rise to a signature conflict. However, the existing schemes do not take it into consideration. In this paper, we proposed a new mechanism SeShare for data storing based on blockchain to realize signature uniqueness, which solves the problem of generating signatures for the same file meanwhile by different group users. Specifically, we record every signature of a file in a blockchain in chronological order, and only one user is allowed to add new signature at the end of the blockchain when modification conflicts occur. On the other hand, to provide a secure data sharing service, SeShare introduces an efficient public auditing scheme for file integrity verification when a group user leaves the group. We also prove the security of the proposed scheme and evaluate the performance at the end of this paper. Our experimental results demonstrate the efficiency of public auditing for user leaving.
Huang, L, Zhang, J, Zuo, Y & Wu, Q 2019, 'Pyramid-Structured Depth MAP Super-Resolution Based on Deep Dense-Residual Network', IEEE Signal Processing Letters, vol. 26, no. 12, pp. 1723-1727.
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© 1994-2012 IEEE. Although deep convolutional neural networks (DCNN) show significant improvement for single depth map (SD) super-resolution (SR) over the traditional counterparts, most SDSR DCNNs do not reuse the hierarchical features for depth map SR resulting in blurred high-resolution (HR) depth maps. They always stack convolutional layers to make network deeper and wider. In addition, most SDSR networks generate HR depth maps at a single level, which is not suitable for large up-sampling factors. To solve these problems, we present pyramid-structured depth map super-resolution based on deep dense-residual network. Specially, our networks are made up of dense residual blocks that use densely connected layers and residual learning to model the mapping between high-frequency residuals and low-resolution (LR) depth map. Furthermore, based on the pyramid structure, our network can progressively generate depth maps of various levels by taking advantages of features from different levels. The proposed network adopts a deep supervision scheme to reduce the difficulty of model training and further improve the performance. The proposed method is evaluated on Middlebury datasets which shows improved performance compared with 6 state-of-the-art methods.
Huang, L, Zhe, T, Wu, J, Wu, Q, Pei, C & Chen, D 2019, 'Robust Inter-Vehicle Distance Estimation Method Based on Monocular Vision', IEEE Access, vol. 7, pp. 46059-46070.
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© 2013 IEEE. Advanced driver assistance systems (ADAS) based on monocular vision are rapidly becoming a popular research subject. In ADAS, inter-vehicle distance estimation from an in-car camera based on monocular vision is critical. At present, related methods based on a monocular vision for measuring the absolute distance of vehicles ahead experience accuracy problems in terms of the ranging result, which is low, and the deviation of the ranging result between different types of vehicles, which is large and easily affected by a change in the attitude angle. To improve the robustness of a distance estimation system, an improved method for estimating the distance of a monocular vision vehicle based on the detection and segmentation of the target vehicle is proposed in this paper to address the vehicle attitude angle problem. The angle regression model (ARN) is used to obtain the attitude angle information of the target vehicle. The dimension estimation network determines the actual dimensions of the target vehicle. Then, a 2D base vector geometric model is designed in accordance with the image analytic geometric principle to accurately recover the back area of the target vehicle. Lastly, area-distance modeling based on the principle of camera projection is performed to estimate distance. The experimental results on the real-world computer vision benchmark, KITTI, indicate that our approach achieves superior performance compared with other existing published methods for different types of vehicles (including front and sideway vehicles).
Huang, Q-S, Wei, W, Sun, J, Mao, S & Ni, B-J 2019, 'Hexagonal K2W4O13 Nanowires for the Adsorption of Methylene Blue', ACS Applied Nano Materials, vol. 2, no. 6, pp. 3802-3812.
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© 2019 American Chemical Society. In this study, novel hexagonal K2W4O13 (h-K2W4O13) nanowires were strategically synthesized via a facial hydrothermal method, which exhibited excellent adsorption capacities for wastewater treatment. The inorganic agent K2SO4 was used as a structure-directing agent to scaffold the tunnel structure of h-K2W4O13 and form the one-dimensional structure. Through increasing the relative molar ratio of K2SO4 to Na2WO4 precursor, the pure-phase h-WO3 nanorods and h-K2W4O13 nanowires were obtained, attributing to the competitive electrostatic adsorption between K+ ions and Na+ ions on h-WO3 nuclei. With a smaller hydrated radius in the solution (dK+ = 3.31 Å, dNa+= 3.58 Å), K+ exhibited superior affinity compared to Na+ with the negatively charged h-WO3 nuclei because of a larger charge density, resulting in the formation of h-K2W4O13. Adsorption experimental results showed that 89.4% of methylene blue was removed by h-K2W4O13 in the first 5 min (99% in 1 h) and the maximum uptake capacity reached 204.08 mg g-1. In addition, the novel h-K2W4O13 exhibited acid or alkali resistance and good reusability, revealed by the stable adsorption capacity in a wide pH range of 3.0-11.0 and five-run recycle tests. The large specific area, high proportion of effective pore volume, and abundant hydroxyl groups of the synthesized h-K2W4O13 resulted in excellent adsorption performance for methylene blue.
Huang, Q-S, Wu, W, Wei, W & Ni, B-J 2019, 'Polyethylenimine modified potassium tungsten oxide adsorbent for highly efficient Ag+ removal and valuable Ag0 recovery', Science of The Total Environment, vol. 692, pp. 1048-1056.
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Huang, S 2019, 'A review of optimisation strategies used in simultaneous localisation and mapping', Journal of Control and Decision, vol. 6, no. 1, pp. 61-74.
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© 2018, © 2018 Northeastern University, China. This paper provides a brief review of the different optimisation strategies used in mobile robot simultaneous localisation and mapping (SLAM) problem. The focus is on the optimisation-based SLAM back end. The strategies are classified based on their purposes such as reducing the computational complexity, improving the convergence and improving the robustness. It is clearly pointed out that some approximations are made in some of the methods and there is always a trade-off between the computational complexity and the accuracy of the solution. The local submap joining is a strategy that has been used to address both the computational complexity and the convergence and is a flexible tool to be used in the SLAM back end. Although more research is needed to further improve the SLAM back end, nowadays there are quite a few relatively mature SLAM back end algorithms that can be used by SLAM researchers and users.
Huang, S, Kang, Z, Tsang, IW & Xu, Z 2019, 'Auto-weighted multi-view clustering via kernelized graph learning', Pattern Recognition, vol. 88, pp. 174-184.
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Huang, W, Hua, W, Chen, F, Qi, J & Zhu, J 2019, 'Performance Improvement of Model Predictive Current Control of Fault-Tolerant Five-Phase Flux-Switching Permanent Magnet Motor Drive', IEEE Transactions on Industry Applications, vol. 55, no. 6, pp. 6001-6010.
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© 1972-2012 IEEE. To improve the fault-tolerant performance of a five-phase flux-switching permanent magnet (FSPM) motor drive under open-circuit fault (OCF) condition, a model predictive current control (MPCC) with pre-selective method and duty ratio control (DRC) technology is proposed and investigated in this paper. First, on the principle of minimizing harmonic voltages in x-y subspace, two zero switching states and the switching state, which generates a larger voltage vector in α-β subspace are pre-selected. Second, voltage vector references in α-β subspace and x-y subspace are predicted to further select active voltage vector candidates. Consequently, the number of current predictions has been significantly reduced, resulting in the alleviation of the computational complexity and the increase of sampling frequency. Third, the DRC approach is applied in conjunction with the pre-selection-based MPCC to improve the steady-state performance. Finally, the effectiveness of the proposed MPCC method for the OCF tolerant five-phase FSPM motor drive is validated by comparative experiments.
Huang, W, Kim, S, Billinghurst, M & Alem, L 2019, 'Sharing hand gesture and sketch cues in remote collaboration', Journal of Visual Communication and Image Representation, vol. 58, pp. 428-438.
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© 2018 Elsevier Inc. Many systems have been developed to support remote guidance, where a local worker manipulates objects under guidance of a remote expert helper. These systems typically use speech and visual cues between the local worker and the remote helper, where the visual cues could be pointers, hand gestures, or sketches. However, the effects of combining visual cues together in remote collaboration has not been fully explored. We conducted a user study comparing remote collaboration with an interface that combined hand gestures and sketching (the HandsInTouch interface) to one that only used hand gestures, when solving two tasks; Lego assembly and repairing a laptop. In the user study, we found that (1) adding sketch cues improved the task completion time, only with the repairing task as this had complex object manipulation but (2) using gesture and sketching together created a higher task load for the user.
Huang, W-Y, Ngo, H-H, Lin, C, Vu, C-T, Kaewlaoyoong, A, Boonsong, T, Tran, H-T, Bui, X-T, Vo, T-D-H & Chen, J-R 2019, 'Aerobic co-composting degradation of highly PCDD/F-contaminated field soil. A study of bacterial community', Science of The Total Environment, vol. 660, pp. 595-602.
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This study investigated bacterial communities during aerobic food waste co-composting degradation of highly PCDD/F-contaminated field soil. The total initial toxic equivalent quantity (TEQ) of the soil was 16,004 ng-TEQ kg-1 dry weight. After 42-day composting and bioactivity-enhanced monitored natural attenuation (MNA), the final compost product's TEQ reduced to 1916 ng-TEQ kg-1 dry weight (approximately 75% degradation) with a degradation rate of 136.33 ng-TEQ kg-1 day-1. Variations in bacterial communities and PCDD/F degraders were identified by next-generation sequencing (NGS). Thermophilic conditions of the co-composting process resulted in fewer observed bacteria and PCDD/F concentrations. Numerous organic compound degraders were identified by NGS, supporting the conclusion that PCDD/Fs were degraded during food waste co-composting. Bacterial communities of the composting process were defined by four phyla (Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes). At the genus level, Bacillus (Firmicutes) emerged as the most dominant phylotype. Further studies on specific roles of these bacterial strains are needed, especially for the thermophiles which contributed to the high degradation rate of the co-co-composting treatment's first 14 days.
Huang, X, An, P, Cao, F, Liu, D & Wu, Q 2019, 'Light-field compression using a pair of steps and depth estimation', Optics Express, vol. 27, no. 3, pp. 3557-3557.
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Huang, X, Zhang, JA, Liu, RP, Guo, YJ & Hanzo, L 2019, 'Airplane-Aided Integrated Networking for 6G Wireless: Will It Work?', IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 84-91.
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As demand for wireless connectivity increases, communication technology is moving toward integrating terrestrial networks with space networks. Creating this integrated space and terrestrial network (ISTN) is critically important for industries such as logistics, mining, agriculture, fisheries, and defense. However, a number of significant technological challenges must be overcome for ISTN through low-cost airborne platforms and high-data-rate backbone links.
Huang, Y, Fu, J, Liu, A, Rao, R, Wu, D & Shen, J 2019, 'Model Test and Optimal Design of the Joint in a Sunflower Arch Bridge', Journal of Bridge Engineering, vol. 24, no. 2, pp. 04018121-04018121.
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© 2018 American Society of Civil Engineers. The sunflower arch bridge is a new type of reinforced concrete arch bridge that has been developed recently. Because of the complex constructional details, the stress distribution at the joint between the main arch and spandrel arch is very complicated. To explore the mechanical behavior of this new type of arch bridge, particularly the stress state at the joint of the arch, a 1:5-scaled model of a segment for a sunflower arch bridge was tested. The displacements and stresses at key locations of the tested model were recorded. The experimental results showed that the displacements of the main arch and spandrel arch under dead loads were notably small, which indicated that the global stiffness of the arch was sufficiently large. Moreover, the maximum tensile stress at the end of the spandrel arch subjected to dead loads was larger than the tensile strength of the concrete; therefore, the concrete in these regions is vulnerable to cracking. To avoid cracks at the end of the spandrel arch, an optimized design scheme was proposed for the joint using a steel I-beam to replace the concrete at the end of the spandrel arch. Design parameters were also suggested through a comprehensive parametric investigation based on finite-element analysis (FEA).
Huang, Y, Ng, ECY, Yam, Y-S, Lee, CKC, Surawski, NC, Mok, W-C, Organ, B, Zhou, JL & Chan, EFC 2019, 'Impact of potential engine malfunctions on fuel consumption and gaseous emissions of a Euro VI diesel truck', Energy Conversion and Management, vol. 184, pp. 521-529.
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Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Yam, Y-S & Chan, EFC 2019, 'Characterisation of diesel vehicle emissions and determination of remote sensing cutpoints for diesel high-emitters', Environmental Pollution, vol. 252, no. Part A, pp. 31-38.
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Diesel vehicles are a major source of air pollutants in cities and have caused significant health risks to the public globally. This study used both on-road remote sensing and transient chassis dynamometer to characterise emissions of diesel light goods vehicles. A large sample size of 183 diesel vans were tested on a transient chassis dynamometer to evaluate the emission levels of in-service diesel vehicles and to determine a set of remote sensing cutpoints for diesel high-emitters. The results showed that 79% and 19% of the Euro 4 and Euro 5 diesel vehicles failed the transient cycle test, respectively. Most of the high-emitters failed the NO limits, while no vehicle failed the HC limits and only a few vehicles failed the CO limits. Vehicles that failed NO limits occurred in both old and new vehicles. NO/CO2 ratios of 57.30 and 22.85 ppm/% were chosen as the remote sensing cutpoints for Euro 4 and Euro 5 high-emitters, respectively. The cutpoints could capture a Euro 4 and Euro 5 high-emitter at a probability of 27% and 57% with one snapshot remote sensing measurement, while only producing 1% of false high-emitter detections. The probability of high-emitting events was generally evenly distributed over the test cycle, indicating that no particular driving condition produced a higher probability of high-emitting events. Analysis on the effect of cutpoints on real-driving diesel fleet was carried out using a three-year remote sensing program. Results showed that 36% of Euro 4 and 47% of Euro 5 remote sensing measurements would be detected as high-emitting using the proposed cutpoints.
Huang, Y, Porter, A, Zhang, Y & Barrangou, R 2019, 'Author Correction: Collaborative networks in gene editing', Nature Biotechnology, vol. 37, no. 12, pp. 1522-1522.
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Huang, Y, Porter, A, Zhang, Y & Barrangou, R 2019, 'Collaborative networks in gene editing', Nature Biotechnology, vol. 37, no. 10, pp. 1107-1109.
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Huang, Y, Porter, AL, Zhang, Y, Lian, X & Guo, Y 2019, 'An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)', Technological Forecasting and Social Change, vol. 146, pp. 831-843.
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The increasingly uncertain dynamics of technological change pose special challenges to traditional technology forecasting tools, which facilitates future-oriented technology analysis (FTA) tools to support the policy processes in the fields of science, technology & innovation (ST&I) and the management of technology (MOT), rather than merely forecasting incremental advances via analyses of continuous trends. Dye-sensitized solar cells are a promising third-generation photovoltaic technology that can add functionality and lower costs to enhance the value proposition of solar power generation in the early years of the 21st century. Through a series of technological forecasting studies analyzing the R&D patterns and trends in Dye-sensitized solar cells technology over the past several years, we have come to realize that validating previous forecasts is useful for improving ST&I policy processes. Yet, rarely do we revisit forecasts or projections to ascertain how well they fared. Moreover, few studies pay much attention to assessing FTA techniques. In this paper, we compare recent technology activities with previous forecasts to reveal the influencing factors that led to differences between past predictions and actual performance. Beyond our main aim of checking accuracy, in this paper we also wish to gain some sense of how valid those studies were and whether they proved useful to others in some ways.
Huang, Y, Surawski, NC, Organ, B, Zhou, JL, Tang, OHH & Chan, EFC 2019, 'Fuel consumption and emissions performance under real driving: Comparison between hybrid and conventional vehicles', Science of The Total Environment, vol. 659, pp. 275-282.
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Hybrid electric vehicles (HEVs) are perceived to be more energy efficient and less polluting than conventional internal combustion engine (ICE) vehicles. However, increasing evidence has shown that real-driving emissions (RDE) could be much higher than laboratory type approval limits and the advantages of HEVs over their conventional ICE counterparts under real-driving conditions have not been studied extensively. Therefore, this study was conducted to evaluate the real-driving fuel consumption and pollutant emissions performance of HEVs against their conventional ICE counterparts. Two pairs of hybrid and conventional gasoline vehicles of the same model were tested simultaneously in a novel convoy mode using two portable emission measurement systems (PEMSs), thus eliminating the effect of vehicle configurations, driving behaviour, road conditions and ambient environment on the performance comparison. The results showed that although real-driving fuel consumption for both hybrid and conventional vehicles were 44%-100% and 30%-82% higher than their laboratory results respectively, HEVs saved 23%-49% fuel relative to their conventional ICE counterparts. Pollutant emissions of all the tested vehicles were lower than the regulation limits. However, HEVs showed no reduction in HC emissions and consistently higher CO emissions compared to the conventional ICE vehicles. This could be caused by the frequent stops and restarts of the HEV engines, as well as the lowered exhaust gas temperature and reduced effectiveness of the oxidation catalyst. The findings therefore show that while achieving the fuel reduction target, hybridisation did not bring the expected benefits to urban air quality.
Huang, Y, Xu, J, Wu, Q, Zheng, Z, Zhang, Z & Zhang, J 2019, 'Multi-Pseudo Regularized Label for Generated Data in Person Re-Identification', IEEE Transactions on Image Processing, vol. 28, no. 3, pp. 1391-1403.
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Sufficient training data normally is required to train deeply learned models. However, due to the expensive manual process for labelling large number of images (i.e., annotation), the amount of available training data (i.e., real data) is always limited. To produce more data for training a deep network, Generative Adversarial Network (GAN) can be used to generate artificial sample data (i.e., generated data). However, the generated data usually does not have annotation labels. To solve this problem, in this paper, we propose a virtual label called Multi-pseudo Regularized Label (MpRL) and assign it to the generated data. With MpRL, the generated data will be used as the supplementary of real training data to train a deep neural network in a semi-supervised learning fashion. To build the corresponding relationship between the real data and generated data, MpRL assigns each generated data a proper virtual label which reflects the likelihood of the affiliation of the generated data to predefined training classes in the real data domain. Unlike the traditional label which usually is a single integral number, the virtual label proposed in this work is a set of weight-based values each individual of which is a number in (0,1] called multi-pseudo label and reflects the degree of relation between each generated data to every pre-defined class of real data. A comprehensive evaluation is carried out by adopting two state-of-the-art convolutional neural networks (CNNs) in our experiments to verify the effectiveness of MpRL. Experiments demonstrate that by assigning MpRL to generated data, we can further improve the person re-ID performance on five re-ID datasets, i.e., Market-1501, DukeMTMC-reID, CUHK03, VIPeR, and CUHK01. The proposed method obtains +6.29%, +6.30%, +5.58%, +5.84%, and +3.48% improvements in rank-1 accuracy over a strong CNN baseline on the five datasets respectively, and outperforms state-of-the-art methods.
Huang, Y, Zhong, Y, Wu, Q, Dutkiewicz, E & Jiang, T 2019, 'Cost-Effective Foliage Penetration Human Detection Under Severe Weather Conditions Based on Auto-Encoder/Decoder Neural Network', IEEE Internet of Things Journal, vol. 6, no. 4, pp. 6190-6200.
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IEEE Military surveillance events and rescue activities are vital missions for the Internet-of-things. To this end, foliage penetration for human detection plays an important role. However, although the feasibility of that mission has been validated, we observe that it still cannot performs promisingly under severe weather conditions such as rainy, foggy, and snowy days. Therefore, in this paper, experiments are conducted under severe weather conditions based on a proposed deep learning approach. We present an Auto-Encoder/Decoder (Auto-ED) deep neural network that can learn the deep representation and conduct classification task concurrently. Since the property of cost-effective, the device-free sensing (DFS) techniques are used to address human detection in our case. As we pursue the signal-based mission, two components are involved in the proposed Auto-ED approach. First, an encoder is utilized that encode signal-based inputs into higher dimensional tensors by fractionally-strided convolution operations. Then, a decoder is leveraged with convolution operations to extract deep representations and learn the classifier simultaneously. To verify the effectiveness of the proposed approach, we compare it with several machine learning approaches under different weather conditions. Also, a simulation experiment is conducted by adding Additive White Gaussian Noise (AWGN) to the original target signals with different Signal to Noise Ratios (SNRs). Experimental results demonstrate that the proposed approach can best tackle the challenge of human detection under severe weather conditions in the high-clutter foliage environment, which indicates its potential application values in the near future.
Huang, YQ, Fu, JY, Liu, AR, Pi, YL, Wu, D & Gao, W 2019, 'Effect of concrete creep on dynamic stability behavior of slender concrete-filled steel tubular column', Composites Part B: Engineering, vol. 157, pp. 173-181.
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© 2018 Elsevier Ltd An analytical procedure for dynamic stability of CFST column accounting for the creep of concrete core is proposed. The long-term effect of creep of concrete core is formulated based on the creep model by the ACI 209 committee and the age-adjusted effective modulus method (AEMM). The equations of boundary frequencies accounting for the effects of concrete creep are derived by the Bolotin's theory and solved as a quadratic eigenvalue problem. The effectiveness of the proposed method and the characteristics of time-varying distribution of instability regions are numerically surveyed. It is shown that the CFST column becomes dynamically unstable even when the sum of the sustained static load and the amplitude of the dynamic excitation is much lower than the static instability load. It is also found that due to the time effects of concrete creep under the sustained static load, the same excitation, that cannot induce dynamic instability in the early stage of sustained loading, can induce the dynamic instability in a few days later. The critical amplitude and frequency of the dynamic excitation can decrease by 6% and 3% in 5 days, and 11% and 6% in 100 days.
Hung, S-H, Hietala, K, Zhu, S, Ying, M, Hicks, M & Wu, X 2019, 'Quantitative robustness analysis of quantum programs.', Proc. ACM Program. Lang., vol. 3, no. POPL, pp. 31:1-31:1.
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Quantum computation is a topic of significant recent interest, with practical advances coming from both research and industry. A major challenge in quantum programming is dealing with errors (quantum noise) during execution. Because quantum resources (e.g., qubits) are scarce, classical error correction techniques applied at the level of the architecture are currently cost-prohibitive. But while this reality means that quantum programs are almost certain to have errors, there as yet exists no principled means to reason about erroneous behavior. This paper attempts to fill this gap by developing a semantics for erroneous quantum while-programs, as well as a logic for reasoning about them. This logic permits proving a property we have identified, called є-robustness, which characterizes possible “distance” between an ideal program and an erroneous one. We have proved the logic sound, and showed its utility on several case studies, notably: (1) analyzing the robustness of noisy versions of the quantum Bernoulli factory (QBF) and quantum walk (QW); (2) demonstrating the (in)effectiveness of different error correction schemes on single-qubit errors; and (3) analyzing the robustness of a fault-tolerant version of QBF.
Hussain, W & Sohaib, O 2019, 'Analysing Cloud QoS Prediction Approaches and Its Control Parameters: Considering Overall Accuracy and Freshness of a Dataset.', IEEE Access, vol. 7, pp. 82649-82671.
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Huynh, NV, Hoang, DT, Nguyen, DN & Dutkiewicz, E 2019, 'Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 37, no. 6, pp. 1455-1470.
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Effective network slicing requires an infrastructure/network provider to deal
with the uncertain demand and real-time dynamics of network resource requests.
Another challenge is the combinatorial optimization of numerous resources,
e.g., radio, computing, and storage. This article develops an optimal and fast
real-time resource slicing framework that maximizes the long-term return of the
network provider while taking into account the uncertainty of resource demand
from tenants. Specifically, we first propose a novel system model which enables
the network provider to effectively slice various types of resources to
different classes of users under separate virtual slices. We then capture the
real-time arrival of slice requests by a semi-Markov decision process. To
obtain the optimal resource allocation policy under the dynamics of slicing
requests, e.g., uncertain service time and resource demands, a Q-learning
algorithm is often adopted in the literature. However, such an algorithm is
notorious for its slow convergence, especially for problems with large
state/action spaces. This makes Q-learning practically inapplicable to our case
in which multiple resources are simultaneously optimized. To tackle it, we
propose a novel network slicing approach with an advanced deep learning
architecture, called deep dueling that attains the optimal average reward much
faster than the conventional Q-learning algorithm. This property is especially
desirable to cope with real-time resource requests and the dynamic demands of
users. Extensive simulations show that the proposed framework yields up to 40%
higher long-term average return while being few thousand times faster, compared
with state of the art network slicing approaches.
Huynh, NV, Nguyen, DN, Hoang, DT & Dutkiewicz, E 2019, ''Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 37, no. 11, pp. 2603-2620.
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With conventional anti-jamming solutions like frequency hopping or spread
spectrum, legitimate transceivers often tend to 'escape' or 'hide' themselves
from jammers. These reactive anti-jamming approaches are constrained by the
lack of timely knowledge of jamming attacks. Bringing together the latest
advances in neural network architectures and ambient backscattering
communications, this work allows wireless nodes to effectively 'face' the
jammer by first learning its jamming strategy, then adapting the rate or
transmitting information right on the jamming signal. Specifically, to deal
with unknown jamming attacks, existing work often relies on reinforcement
learning algorithms, e.g., Q-learning. However, the Q-learning algorithm is
notorious for its slow convergence to the optimal policy, especially when the
system state and action spaces are large. This makes the Q-learning algorithm
pragmatically inapplicable. To overcome this problem, we design a novel deep
reinforcement learning algorithm using the recent dueling neural network
architecture. Our proposed algorithm allows the transmitter to effectively
learn about the jammer and attain the optimal countermeasures thousand times
faster than that of the conventional Q-learning algorithm. Through extensive
simulation results, we show that our design (using ambient backscattering and
the deep dueling neural network architecture) can improve the average
throughput by up to 426% and reduce the packet loss by 24%. By augmenting the
ambient backscattering capability on devices and using our algorithm, it is
interesting to observe that the (successful) transmission rate increases with
the jamming power. Our proposed solution can find its applications in both
civil (e.g., ultra-reliable and low-latency communications or URLLC) and
military scenarios (to combat both inadvertent and deliberate jamming).
Iacopi, F & McIntosh, M 2019, 'Opportunities and perspectives for green chemistry in semiconductor technologies', Green Chemistry, vol. 21, no. 12, pp. 3250-3255.
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Semiconductor technologies offer a plethora of technological challenges and opportunities for a more extensive implementation of green chemistry principles.
Ibrar, I, Naji, O, Sharif, A, Malekizadeh, A, Alhawari, A, Alanezi, AA & Altaee, A 2019, 'A Review of Fouling Mechanisms, Control Strategies and Real-Time Fouling Monitoring Techniques in Forward Osmosis', Water, vol. 11, no. 4, pp. 695-695.
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Forward osmosis has gained tremendous attention in the field of desalination and wastewater treatment. However, membrane fouling is an inevitable issue. Membrane fouling leads to flux decline, can cause operational problems and can result in negative consequences that can damage the membrane. Hereby, we attempt to review the different types of fouling in forward osmosis, cleaning and control strategies for fouling mitigation, and the impact of membrane hydrophilicity, charge and morphology on fouling. The fundamentals of biofouling, organic, colloidal and inorganic fouling are discussed with a focus on recent studies. We also review some of the in-situ real-time online fouling monitoring technologies for real-time fouling monitoring that can be applicable to future research on forward osmosis fouling studies. A brief discussion on critical flux and the coupled effects of fouling and concentration polarization is also provided.
Im, S-J, Shon, HK, Kim, IS & Jang, A 2019, 'The effects of naturally occurring operation factors on the removal mechanism of major algae metabolized materials in forward osmosis process', Journal of Cleaner Production, vol. 239, pp. 118009-118009.
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© 2019 Elsevier Ltd This research investigated the removal mechanism of algae metabolized materials (geosmin, 2-methylisoborneol (2-MIB), and microcystin-leucine arginine (MC-LR)) according to the naturally occurring operation factors such as temperature (10, 20 and 30 °C), transmembrane temperature (20 °C: 10 vs. 30, 30 vs. 10 °C) difference and valance of reverse salt flux (RSF) in forward osmosis membrane. Algae metabolized materials had high removal efficiency (94–99%) at all experimental conditions. According to the temperature difference, the absorption percentage of geosmin and 2-MIB on the FO membrane was 76, 75% and 75, 55%, respectively. However, adsorption percentage of toxin (MC-LR) materials were observed to be 11 and 85%, respectively. Temperature-dependent parameters such as water and solute viscosity & diffusivity, membrane intrinsic properties, have effects on the removal mechanism and rate. Consequently, the results from this research provide meaningful information on not only the removal of algae metabolized materials like micropollutants but also the water treatment process with consideration of the temperature conditions (temperature difference).
Imdad, U, Asif, M, Ahmad, MT, Sohaib, O, Hanif, MK & Chaudary, MH 2019, 'Three Dimensional Point Cloud Compression and Decompression Using Polynomials of Degree One.', Symmetry, vol. 11, no. 2, pp. 209-209.
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Indraratna, B, Babar Sajjad, M, Ngo, T, Gomes Correia, A & Kelly, R 2019, 'Improved performance of ballasted tracks at transition zones: A review of experimental and modelling approaches', Transportation Geotechnics, vol. 21, pp. 100260-100260.
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© 2019 Elsevier Ltd Track transitions such as bridge approaches, road crossings and shifts from slab track to ballasted track are common locations where track degradation accelerates due to dynamic and high impact forces; as a consequence there is higher differential settlement. These types of discontinuities cause an abrupt change in the structural response of the track due mainly to variations in stiffness and track damping. Track transition zones are prone to an accelerated deterioration of track material and geometry that leads to increased maintenance costs. Track deterioration also leads to vehicle degradation due to enhanced acceleration, low frequency oscillation, and high frequency vibrations. While ballast deterioration is a major factor affecting the stability and longevity of rail tracks, the cost of tackling transition related problems that detract from passenger comfort is also high. A good transition zone lessens the impact of dynamic load of moving trains by minimising the abrupt variations in track stiffness and ensuring a smooth and gradual change from a less stiff (ballasted track) to a stiff (slab track) structure. This paper presents a critical review of various problems associated with transition zones and the measures adopted to mitigate them; it also includes critical review of research work carried out using large-scale laboratory testing, mathematical and computational modelling and field measurements on track transition zones.
Indraratna, B, Qi, Y, Heitor, A & Vinod, JS 2019, 'The influence of rubber crumbs on the critical state behavior of waste mixtures', E3S Web of Conferences, vol. 92, pp. 06004-06004.
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The practical application of waste materials such as steel furnace slag (SFS) and coal wash (CW) is becoming more prevalent in many geotechnical projects. It was found that the inclusion of rubber crumbs (RCs) from recycled tyres into mixtures of SFS and CW not only solves the problem of large stockpiles of waste tyres, it also can provide an energy-absorbing medium that will reduce track degradation. In order to investigate the influence of RC on the geotechnical properties of the granular waste matrix (SFS+CW+RC), a series of monotonic consolidated drained triaxial tests were conducted on waste mixtures. The test results reveal that the inclusion of RC significantly affects the geotechnical properties of the waste mixtures, especially their critical state behaviour. Specifically, the waste matrix can achieve a critical state with a low RC content (<20%), whereas those mixtures with higher RC contents (20-40%) cannot attain a critical state within the ultimate strain capacity that can be applied to specimens using the traditional triaxial equipment. Therefore, for the waste matrix with higher RC contents extrapolation of the measured volumetric strains had to be adopted to obtain the appropriate critical state parameters. Moreover, the influence of energy absorbing property by adding RC on the critical state behaviour has also been captured through an empirical equation.
Indraratna, B, Qi, Y, Ngo, TN, Rujikiatkamjorn, C, Neville, T, Ferreira, FB & Shahkolahi, A 2019, 'Use of Geogrids and Recycled Rubber in Railroad Infrastructure for Enhanced Performance', Geosciences, vol. 9, no. 1, pp. 30-30.
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Railway tracks are conventionally built on compacted ballast and structural fill layers placed above the natural (subgrade) foundation. However, during train operations, track deteriorations occur progressively due to ballast degradation. The associated track deformation is usually accompanied by a reduction in both load bearing capacity and drainage, apart from imposing frequent track maintenance. Suitable ground improvement techniques involving plastic inclusions (e.g., geogrids) and energy absorbing materials (e.g., rubber products) to enhance the stability and longevity of tracks have become increasingly popular. This paper presents the outcomes from innovative research and development measures into the use of plastic and rubber elements in rail tracks undertaken at the University of Wollongong, Australia, over the past twenty years. The results obtained from laboratory tests, mathematical modelling and numerical modelling reveal that track performance can be improved significantly by using geogrid and energy absorbing rubber products (e.g., rubber crumbs, waste tire-cell and rubber mats). Test results show that the addition of rubber materials can efficiently improve the energy absorption of the structural layer and also reduce ballast breakage. Furthermore, by incorporating the work input parameters, the energy absorbing property of the newly developed synthetic capping layer is captured by correct modelling of dilatancy. In addition, the laboratory behavior of tire cells and geogrids has been validated by numerical modelling (i.e., Finite Element Modelling-FEM, Discrete Element—DEM), and a coupled DEM-FEM modelling approach is also introduced to simulate ballast deformation.
Indraratna, B, Rujikiatkamjorn, C, Baral, P & Ameratunga, J 2019, 'Performance of marine clay stabilised with vacuum pressure: Based on Queensland experience', Journal of Rock Mechanics and Geotechnical Engineering, vol. 11, no. 3, pp. 598-611.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences Stabilising soft marine clay and estuarine soils via vacuum preloading has become very popular in Australasia over the past decades because it is a cost-effective and time-efficient approach. In recent times, new land on areas outside but adjacent to existing port amenities, the Fisherman Islands at the Port of Brisbane (POB), was reclaimed to cater for an increase in trade activities. A vacuum preloading method combined with surcharge to stabilise the deep layers of soil was used to enhance the application of prefabricated vertical drains (PVDs). This paper describes the performance of this combined surcharge fill and vacuum system under the embankment and also compares it with a surcharge loading system to demonstrate the benefits of vacuum pressure ove