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Articles 331 - 360 of 14367

Full-Text Articles in Social and Behavioral Sciences

Bayesian Inference Of Spatio-Temporal Changes Of Arctic Sea Ice, Bohai Zhang, Noel A. Cressie Jan 2020

Bayesian Inference Of Spatio-Temporal Changes Of Arctic Sea Ice, Bohai Zhang, Noel A. Cressie

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 International Society for Bayesian Analysis. Arctic sea ice extent has drawn increasing interest and alarm from geoscientists, owing to its rapid decline. In this article, we propose a Bayesian spatio-temporal hierarchical statistical model for binary Arctic sea ice data over two decades, where a latent dynamic spatio-temporal Gaussian process is used to model the data-dependence through a logit link function. Our ultimate goal is to perform inference on the dynamic spatial behavior of Arctic sea ice over a period of two decades. Physically motivated covariates are assessed using autologistic diagnostics. Our Bayesian spatio-temporal model shows how parameter uncertainty …

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An Improved Lstm Model For Behavior Recognition Of Intelligent Vehicles, Haipeng Xiao, Miguel Sotelo, Yulin Ma, Bo Cao, Yuncheng Zhou, Youchun Xu, Rendong Wang, Zhixiong Li Jan 2020

An Improved Lstm Model For Behavior Recognition Of Intelligent Vehicles, Haipeng Xiao, Miguel Sotelo, Yulin Ma, Bo Cao, Yuncheng Zhou, Youchun Xu, Rendong Wang, Zhixiong Li

Faculty of Engineering and Information Sciences - Papers: Part B

© 2013 IEEE. Long Short-Term Memory (LSTM) neural network has been widely used in many applications, but its application in classification of vehicle movement patterns is still limited. In this paper, LSTM is applied to the vehicle behavior recognition problem to identify the left turn, right turn and straight behavior of the vehicle at the intersection. On the basis of the traditional LSTM classification model, this paper transversely merges the input features and then inputs into a LSTM cell to get an improved model. The improved model can make full use of the input information and reduce unnecessary calculations, and …

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Recent Advances And Development In Optimal Design And Control Of Ground Source Heat Pump Systems, Zhenjun Ma, Lei Xia, Xuemei Gong, Georgios Kokogiannakis, Shugang Wang, Xinlei Zhou Jan 2020

Recent Advances And Development In Optimal Design And Control Of Ground Source Heat Pump Systems, Zhenjun Ma, Lei Xia, Xuemei Gong, Georgios Kokogiannakis, Shugang Wang, Xinlei Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd Ground source heat pump (GSHP) systems have attracted wide attention in developing energy-efficient buildings. Considering the high upfront cost of GSHP systems, appropriate design and control optimization are essential to enhancing their energy efficiency and reducing the payback period. Since there are many variables influencing the performance of GSHP systems, the commonly used rule-based approaches cannot ensure that the system is designed and operated in an optimal manner. This paper presents an overview of recent advances and development in optimal design and control of GSHP systems, aiming to provide some concluding remarks and recommendations for future …

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Hime: Mining And Ensembling Heterogeneous Information For Protein Interaction Predictions, Huaming Chen, Yaochu Jin, Lei Wang, Chi-Hung Chi, Jun Shen Jan 2020

Hime: Mining And Ensembling Heterogeneous Information For Protein Interaction Predictions, Huaming Chen, Yaochu Jin, Lei Wang, Chi-Hung Chi, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

esearch on protein-protein interactions (PPIs) data paves the way towards understanding the mechanisms of infectious diseases, however improving the prediction performance of PPIs of inter-species remains a challenge. Since one single type of sequence data such as amino acid composition may be deficient for high-quality prediction of protein interactions, we have investigated a broader range of heterogeneous information of sequences data. This paper proposes a novel framework for PPIs prediction based on Heterogeneous Information Mining and Ensembling (HIME) process to effectively learn from the interaction data. In particular, the proposed approach introduces an ensemble process together with substantial features that …

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Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun Jan 2020

Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun

Faculty of Engineering and Information Sciences - Papers: Part B

Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early …

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Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha Jan 2020

Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha

Faculty of Engineering and Information Sciences - Papers: Part B

Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account …

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Effect Of Attenuation Mismatches In Time Of Flight Pet Reconstruction, Elise Emond, Alexandre Bousse, Maria Machado, Joanna C. Porter, Ashley M. Groves, Brian F. Hutton, Kris Thielemans Jan 2020

Effect Of Attenuation Mismatches In Time Of Flight Pet Reconstruction, Elise Emond, Alexandre Bousse, Maria Machado, Joanna C. Porter, Ashley M. Groves, Brian F. Hutton, Kris Thielemans

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Institute of Physics and Engineering in Medicine. While the pursuit of better time resolution in positron emission tomography (PET) is rapidly evolving, little work has been performed on time of flight (TOF) image quality at high time resolution in the presence of modelling inconsistencies. This works focuses on the effect of using the wrong attenuation map in the system model, causing perturbations in the reconstructed radioactivity image. Previous work has usually considered the effects to be local to the area where there is attenuation mismatch, and has shown that the quantification errors in this area tend to reduce …

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Electron Scattering Cross Sections From Nitrobenzene In The Energy Range 0.4-1000 Ev: The Role Of Dipole Interactions In Measurements And Calculations, L Álvarez, F Costa, A Lozano, J Oller, Antonio Munoz, F Blanco, P Limão-Vieira, R White, M Brunger, G García Jan 2020

Electron Scattering Cross Sections From Nitrobenzene In The Energy Range 0.4-1000 Ev: The Role Of Dipole Interactions In Measurements And Calculations, L Álvarez, F Costa, A Lozano, J Oller, Antonio Munoz, F Blanco, P Limão-Vieira, R White, M Brunger, G García

Faculty of Engineering and Information Sciences - Papers: Part B

Absolute total electron scattering cross sections (TCS) for nitrobenzene molecules with impact energies from 0.4 to 1000 eV have been measured by means of two different electron-transmission experimental arrangements. For the lower energies (0.4-250 eV) a magnetically confined electron beam system has been used, while for energies above 100 eV a linear beam transmission technique with high angular resolution allowed accurate measurements up to 1000 eV impact energy. In both cases random uncertainties were maintained below 5-8%. Systematic errors arising from the angular and energy resolution limits of each apparatus are analysed in detail and quantified with the help of …

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A Novel Approach In Crude Enzyme Laccase Production And Application In Emerging Contaminant Bioremediation, Luong Nguyen, Minh Vu, Md Johir, Nirenkumar Pathak, Jakub Zdarta, Teofil Jesionowski, Galilee Semblante, Faisal I. Hai, Hong Huynh Nguyen, Long D. Nghiem Jan 2020

A Novel Approach In Crude Enzyme Laccase Production And Application In Emerging Contaminant Bioremediation, Luong Nguyen, Minh Vu, Md Johir, Nirenkumar Pathak, Jakub Zdarta, Teofil Jesionowski, Galilee Semblante, Faisal I. Hai, Hong Huynh Nguyen, Long D. Nghiem

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 by the authors. Laccase enzyme from white-rot fungi is a potential biocatalyst for the oxidation of emerging contaminants (ECs), such as pesticides, pharmaceuticals and steroid hormones. This study aims to develop a three-step platform to treat ECs: (i) enzyme production, (ii) enzyme concentration and (iii) enzyme application. In the first step, solid culture and liquid culture were compared. The solid culture produced significantly more laccase than the liquid culture (447 vs. 74 μM/min after eight days), demonstrating that white rot fungi thrived on a solid medium. In the second step, the enzyme was concentrated 6.6 times using an …

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Microbial Electrochemical Systems For Hydrogen Peroxide Synthesis: Critical Review Of Process Optimization, Prospective Environmental Applications, And Challenges, Tae Chung, Mohamed Meshref, Faisal I. Hai, Abdullah Al-Mamun, Bipro Dhar Jan 2020

Microbial Electrochemical Systems For Hydrogen Peroxide Synthesis: Critical Review Of Process Optimization, Prospective Environmental Applications, And Challenges, Tae Chung, Mohamed Meshref, Faisal I. Hai, Abdullah Al-Mamun, Bipro Dhar

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd Hydrogen peroxide (H2O2) is an industrial chemical that has been widely adopted for various industrial applications, including water and wastewater treatment. Currently, the majority of H2O2 is being produced through the anthraquinone oxidation process, which is disadvantageous due to the requirement of toxic raw materials and high energy input. Recently, microbial electrochemical cells (MXCs), such as microbial fuel cells and microbial electrolysis cells, have demonstrated great potential for effective H2O2 production via cathodic oxygen-reduction reaction (ORR). Previous studies have specified key operational parameters for scaling-up of H2O2-producing MXCs, where improvements in production rate, conversion efficiency, product …

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A Critical Review On Advanced Oxidation Processes For The Removal Of Trace Organic Contaminants: A Voyage From Individual To Integrated Processes, Arbab Tufail, William E. Price, Faisal I. Hai Jan 2020

A Critical Review On Advanced Oxidation Processes For The Removal Of Trace Organic Contaminants: A Voyage From Individual To Integrated Processes, Arbab Tufail, William E. Price, Faisal I. Hai

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd Advanced oxidation processes (AOPs), such as photolysis, photocatalysis, ozonation, Fenton process, anodic oxidation, sonolysis, and wet air oxidation, have been investigated extensively for the removal of a wide range of trace organic contaminants (TrOCs). A standalone AOP may not achieve complete removal of a broad group of TrOCs. When combined, AOPs produce more hydroxyl radicals, thus performing better degradation of the TrOCs. A number of studies have reported significant improvement in TrOC degradation efficiency by using a combination of AOPs. This review briefly discusses the individual AOPs and their limitations towards the degradation of TrOCs containing …

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Lithium Recovery From Salt-Lake Brine: Impact Of Competing Cations, Pretreatment And Preconcentration, Biplob Pramanik, Muhammad Bilal Asif, Rajeev Roychand, Li Shu, Veeriah Jegatheesan, Muhammed Bhuiyan, Faisal I. Hai Jan 2020

Lithium Recovery From Salt-Lake Brine: Impact Of Competing Cations, Pretreatment And Preconcentration, Biplob Pramanik, Muhammad Bilal Asif, Rajeev Roychand, Li Shu, Veeriah Jegatheesan, Muhammed Bhuiyan, Faisal I. Hai

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd The global demand of lithium is rising steadily, and many industrially advanced countries may find it hard to secure an uninterrupted supply of lithium for meeting their manufacturing demands. Thus, innovative processes for lithium recovery from a wide range of natural reserves should be explored for meeting the future demands. In this study, a novel integrated approach was investigated by combining nanofiltration (NF), membrane distillation (MD) and precipitation processes for lithium recovery from salt-lake brines. Initially, the brine was filtered with an NF membrane for the separation of lithium ions (Li+) from competing ions such as …

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A Data-Driven Strategy To Forecast Next-Day Electricity Usage And Peak Electricity Demand Of A Building Portfolio Using Cluster Analysis, Cubist Regression Models And Particle Swarm Optimization, Kehua Li, Zhenjun Ma, Duane A. Robinson, Wenye Lin, Zhixiong Li Jan 2020

A Data-Driven Strategy To Forecast Next-Day Electricity Usage And Peak Electricity Demand Of A Building Portfolio Using Cluster Analysis, Cubist Regression Models And Particle Swarm Optimization, Kehua Li, Zhenjun Ma, Duane A. Robinson, Wenye Lin, Zhixiong Li

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd This study presents a new strategy using cluster analysis, Cubist regression models and Particle Swarm Optimization to forecast next-day total electricity usage and peak electricity demand of a building portfolio. Cluster analysis with a combined dissimilarity measure was first used to group daily electricity usage profiles of the building portfolio. The clustering result was then considered in the training of the Cubist-based forecasting models in order to improve the forecasting accuracy. A Particle Swarm Optimization algorithm was used to determine the optimal parameters in the cluster analysis to further improve the forecasting accuracy. The performance of …

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Tribochemistry And Lubrication Of Alkaline Glass Lubricants In Hot Steel Manufacturing, Thi D. Ta, Hoang B. Tran, Anh Kiet Tieu Jan 2020

Tribochemistry And Lubrication Of Alkaline Glass Lubricants In Hot Steel Manufacturing, Thi D. Ta, Hoang B. Tran, Anh Kiet Tieu

Faculty of Engineering and Information Sciences - Papers: Part B

Nowadays, the increasing demand to reduce energy consumption and improve process reliability requires an alternative lubricant with an effective tribological performance and environmentally friendly properties to replace traditional lubricants in hot steel manufacturing. The current work reviews recent comprehensive experimental and theoretical investigations in a new generation of alkaline-based glass lubricants, with phosphate, borate, and silicate being intensively researched. This class of lubricants showed an outstanding friction reduction, anti-wear, and anti-oxidation performance on coupled steel pairs over a wide range of temperatures (from 650 °C to 1000 °C). Each type had different tribochemical reactions within itself and with oxidized steel …

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Cbe Thermal Comfort Tool: Online Tool For Thermal Comfort Calculations And Visualizations, Federico Tartarini, Stefano Schiavon, Toby Cheung, Tyler Hoyt Jan 2020

Cbe Thermal Comfort Tool: Online Tool For Thermal Comfort Calculations And Visualizations, Federico Tartarini, Stefano Schiavon, Toby Cheung, Tyler Hoyt

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 The Authors The Center for the Built Environment (CBE) Thermal Comfort Tool is a free online tool for thermal comfort calculations and visualizations that complies with the ASHRAE 55–2017, ISO 7730:2005 and EN 16798–1:2019 Standards. It incorporates the major thermal comfort models, including the Predicted Mean Vote (PMV), Standard Effective Temperature (SET), adaptive models, local discomfort models, SolarCal, and dynamic predictive clothing insulation. Our tool also provides dynamic and interactive visualizations of thermal comfort zones. The CBE Thermal Comfort Tool has several practical applications and each year is used by more than 49,000 users worldwide, including engineers, architects, …

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Pricing Of Barrier Options On Underlying Assets With Jump-Diffusion Dynamics: A Mellin Transform Approach, Marianito R. Rodrigo Jan 2020

Pricing Of Barrier Options On Underlying Assets With Jump-Diffusion Dynamics: A Mellin Transform Approach, Marianito R. Rodrigo

Faculty of Engineering and Information Sciences - Papers: Part B

A barrier option is an exotic path-dependent option contract where the right to buy or sell is activated or extinguished when the underlying asset reaches a certain barrier price during the lifetime of the contract. In this article we use a Mellin transform approach to derive exact pricing formulas for barrier options with general payoffs and exponential barriers on underlying assets that have jump-diffusion dynamics. With the same approach we also price barrier options on underlying futures contracts.

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A Qualitative Study Of The Strategic Alignment Perspective Of Public-Sector Organisations In Saudi Arabia In The Digitalisation Age, Abdulaziz Alghazi, Tingru Cui, Jun Shen, Samuel Fosso Wamba, Mengxiang Li Jan 2020

A Qualitative Study Of The Strategic Alignment Perspective Of Public-Sector Organisations In Saudi Arabia In The Digitalisation Age, Abdulaziz Alghazi, Tingru Cui, Jun Shen, Samuel Fosso Wamba, Mengxiang Li

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

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An Edge Based Multi-Agent Auto Communication Method For Traffic Light Control, Qiang Wu, Jianqing Wu, Jun Shen, Binbin Yong, Qingguo Zhou Jan 2020

An Edge Based Multi-Agent Auto Communication Method For Traffic Light Control, Qiang Wu, Jianqing Wu, Jun Shen, Binbin Yong, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

With smart city infrastructures growing, the Internet of Things (IoT) has been widely used in the intelligent transportation systems (ITS). The traditional adaptive traffic signal control method based on reinforcement learning (RL) has expanded from one intersection to multiple intersections. In this paper, we propose a multi-agent auto communication (MAAC) algorithm, which is an innovative adaptive global traffic light control method based on multi-agent reinforcement learning (MARL) and an auto communication protocol in edge computing architecture. The MAAC algorithm combines multi-agent auto communication protocol with MARL, allowing an agent to communicate the learned strategies with others for achieving global optimization …

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Recent Progress In Electrical Generators For Oceanic Wave Energy Conversion, Abidur Rahman, Omar Farrok, Md Rabiul Islam, Wei Xu Jan 2020

Recent Progress In Electrical Generators For Oceanic Wave Energy Conversion, Abidur Rahman, Omar Farrok, Md Rabiul Islam, Wei Xu

Faculty of Engineering and Information Sciences - Papers: Part B

Oceanic wave energy extraction through electrical generator is one of the most interesting topics in the field of power engineering. Almost all the existing relevant review paper focus on electrical generator with the working principle of electromagnetic induction or piezoelectric or triboelectric effect. In this paper, all the existing types (based on principle of operation) of electrical generator used for wave power harvesting are discussed. This paper not only covers recent progress in electrical power generation by electro-magnetic induction, piezoelectric generator, and electrostatic induction, but also presents critical comparative review as well where suitable use and weakness of each type …

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Robust Extended H∞ Control Strategy Using Linear Matrix Inequality Approach For Islanded Microgrid, Maniza Armin, Mizanur Rahman, Md Mukidur Rahman, Subrata K. Sarker, Sajal Das, Md Rabiul Islam, Abbas Z. Kouzani, M. A Parvez Mahmud Jan 2020

Robust Extended H∞ Control Strategy Using Linear Matrix Inequality Approach For Islanded Microgrid, Maniza Armin, Mizanur Rahman, Md Mukidur Rahman, Subrata K. Sarker, Sajal Das, Md Rabiul Islam, Abbas Z. Kouzani, M. A Parvez Mahmud

Faculty of Engineering and Information Sciences - Papers: Part B

This paper presents the design of an extended parameterisations of H∞ controller for off grid operation of a microgrid. The microgrid consists of distributed generation units, filters and local loads. The filters are used to achieve accurate sinusoidal output voltage. However, loads which are connected to the microgrid are parametrically uncertain. Hence, it undergoes with unknown loads uncertainties. These unknown loads may create unknown loads harmonics, non-linearities which may reduce the voltage and current profile of the microgrid. As a result, the sudden rise and fall of voltage current profile damages the domestic and commercial loads. The proposed controller provides …

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A New Modulation Technique To Improve The Power Loss Division Performance Of The Multilevel Inverters, Md Razon Chowdhury, Md. Ashib Rahman, Md Rabiul Islam, A M. Mahfuz-Ur-Rahman Jan 2020

A New Modulation Technique To Improve The Power Loss Division Performance Of The Multilevel Inverters, Md Razon Chowdhury, Md. Ashib Rahman, Md Rabiul Islam, A M. Mahfuz-Ur-Rahman

Faculty of Engineering and Information Sciences - Papers: Part B

Multilevel inverters (MLIs) have offered significant contributions towards the implementation of energy conversion units used in industry and renewable energy applications. However, the switching devices in MLIs are associated with power loss division problems. The pulse width modulation (PWM) techniques greatly influence the peak, average, and ripple values of the device junction temperature. Thermal tension in the devices may be raised due to increased power loss caused by additional switching or uneven distribution of losses due to unbalanced gate pulses. Higher thermal stress accelerates the life degradation process of the power devices and eventually, leads to permanent damage of the …

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An Iot- Based Decision Support Tool For Improving The Performance Of Smart Grids Connected With Distributed Energy Sources And Electric Vehicles, Md Rabiul Islam, Haiyan Lu, M J. Hossain, Li Li Jan 2020

An Iot- Based Decision Support Tool For Improving The Performance Of Smart Grids Connected With Distributed Energy Sources And Electric Vehicles, Md Rabiul Islam, Haiyan Lu, M J. Hossain, Li Li

Faculty of Engineering and Information Sciences - Papers: Part B

vThe growing penetration of distributed energy sources (DES), such as photovoltaic (PV) solar power, battery energy systems and electric vehicles (EVs) into low voltage distribution networks is creating serious challenges for distribution network operators. Uncertain nature of these DES and EV charging is a key factor to cause unbalance, which degrade network performance in terms of energy loss, voltage unbalance, and voltage profile of the distribution network, etc. Some methods were proposed to mitigate such negative impact of these uncertain DES and EV charging from both centralized and decentralized approaches by controlling charging or discharging power of EVs. However, these …

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Role Of Optimization Algorithms Based Fuzzy Controller In Achieving Induction Motor Performance Enhancement, M Hannan, Jamal Ali, M J. Hossain, A Mohamed, Pin Ker, T Indra, M Mansor, Aini Hussain, Kashem M. Muttaqi, Z Dong Jan 2020

Role Of Optimization Algorithms Based Fuzzy Controller In Achieving Induction Motor Performance Enhancement, M Hannan, Jamal Ali, M J. Hossain, A Mohamed, Pin Ker, T Indra, M Mansor, Aini Hussain, Kashem M. Muttaqi, Z Dong

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020, The Author(s). Three-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time. To address these issues, optimisation algorithms for TIMs have received increasing interest among researchers and industrialists. Here, we present an advanced and efficient quantum-inspired lightning search algorithm (QLSA) to avoid exhaustive conventional heuristic procedures when obtaining MFs. The accuracy of the QLSA based …

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Concurrent Multiscale Simulations Of Rough Lubricated Contact Of Aluminum Single Crystal, Jie Zhang, Lihong Su, Zhongnan Wang Jan 2020

Concurrent Multiscale Simulations Of Rough Lubricated Contact Of Aluminum Single Crystal, Jie Zhang, Lihong Su, Zhongnan Wang

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In this paper, a concurrent multiscale simulation strategy coupling atomistic and continuum models was proposed to investigate the three-dimensional contact responses of aluminum single crystal under both dry and lubricated conditions. The Hertz contact is performed by using both the multiscale and full molecular dynamics (MD) simulations for validation. From the contact area, kinetic energy and stress continuity aspects, the multiscale model shows good accuracy. It can also save at least five times the computational time compared with the full MD simulations for the same domain size. Furthermore, the results of …

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3d Detectors On Hydrogenated Amorphous Silicon For Particle Tracking In High Radiation Environment, Mauro Menichelli, M Boscardin, M Crivellari, Jeremy A. Davis, S Dunand, L Fanò, Francesco Moscatelli, M Movileanu-Ionica, Marco Petasecca, M Piccini, A Rossi, A Scorzoni, G Verzellesi, N Wyrsch Jan 2020

3d Detectors On Hydrogenated Amorphous Silicon For Particle Tracking In High Radiation Environment, Mauro Menichelli, M Boscardin, M Crivellari, Jeremy A. Davis, S Dunand, L Fanò, Francesco Moscatelli, M Movileanu-Ionica, Marco Petasecca, M Piccini, A Rossi, A Scorzoni, G Verzellesi, N Wyrsch

Faculty of Engineering and Information Sciences - Papers: Part B

© Published under licence by IOP Publishing Ltd. The vertex detectors for the future hadronic colliders will operate under proton fluencies above 1016 p/cm2. Crystalline Silicon detector technology, up to now, has kept the pace of the increasing fluencies in the LHC era and it is still the prevalent vertex detector material for the present and for the immediate future. Looking ahead in time, an alternative solution for such a detector has to be found because for the future there is no guarantee that Crystalline Silicon will hold this challenge. For this reason the development of hydrogenated amorphous silicon vertex …

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Detecting Permafrost In Plateau And Mountainous Areas By Airborne Transient Electromagnetic Sensing, Benyu Su, Rongfu Rao, Zhixiong Li, Lei Song, Jianhua Yue Jan 2020

Detecting Permafrost In Plateau And Mountainous Areas By Airborne Transient Electromagnetic Sensing, Benyu Su, Rongfu Rao, Zhixiong Li, Lei Song, Jianhua Yue

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Transportation has become a key bottleneck which restricts economic development in Western China. However, during the construction of the western railway, the permafrost problem has plagued railway construction on the Qinghai–Tibet Plateau, and has not yet been resolved. Accurately identifying permafrost by geophysical method is the most effective means to solve this problem. However, the mountainous and plateau terrain in Western China impose huge challenges in collecting geophysical data. To address this issue, this paper proposes an airborne transient electromagnetic method to collect geophysical electromagnetic data to identify permafrost in the …

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New Insights Into The Corrosion Behaviour Of Medium Manganese Steel Exposed To A Nacl Solution Spray, Guanqiao Su, Xiuhua Gao, Mingshuai Huo, Haibo Xie, Linxiu Du, Jianzhong Xu, Zhengyi Jiang Jan 2020

New Insights Into The Corrosion Behaviour Of Medium Manganese Steel Exposed To A Nacl Solution Spray, Guanqiao Su, Xiuhua Gao, Mingshuai Huo, Haibo Xie, Linxiu Du, Jianzhong Xu, Zhengyi Jiang

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd A medium manganese steel with an appropriate concentration of chromium (0.8 wt.%) and other anti-corrosion elements (0.3Ni-0.3Cu-0.2Mo in wt.%) was studied with the aim of further characterizing the corrosion feature (via corrosion kinetics, XRD, SEM, EPMA and XPS) exposed to a NaCl solution spray. The results reveal that the increased Mn and Cr contents in medium manganese steel change the corrosion performance at different stages. The formation of the initial corrosion product β-FeO(OH) and high cationic fraction of Mn ions directly cause the high corrosion rate. The higher Cr content contributed to providing better protection when …

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Deep Learning Based Hep-2 Image Classification: A Comprehensive Review, Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou Jan 2020

Deep Learning Based Hep-2 Image Classification: A Comprehensive Review, Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Classification of HEp-2 cell patterns plays a significant role in the indirect immunofluorescence test for identifying autoimmune diseases in the human body. Many automatic HEp-2 cell classification methods have been proposed in recent years, amongst which deep learning based methods have shown impressive performance. This paper provides a comprehensive review of the existing deep learning based HEp-2 cell image classification methods. These methods perform HEp-2 image classification at two levels, namely, cell-level and specimen-level. Both levels are covered in this review. At each level, the methods are organized with a deep network usage based taxonomy. The core idea, …

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Reliability Analysis Of Tbm Disc Cutters Under Different Conditions, Bolong Liu, Haiqing Yang, Shivakumar Karekal Jan 2020

Reliability Analysis Of Tbm Disc Cutters Under Different Conditions, Bolong Liu, Haiqing Yang, Shivakumar Karekal

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Tongji University The reliability of disc cutters has a significant influence on the safety and working efficiency of tunnel boring machines (TBMs). To investigate the reliability of disc cutters under different geological and operational conditions, we conducted a series of novel rolling cutting tests on intact and jointed sandstone blocks using different dip angles and interlayers. Different normal forces and rotational speeds of the cutterhead were also applied during the experiment. A novel reliability estimation method, based on a logistic regression model, was then proposed, and the influence of dip angle, strata, normal force, and rotational speed on …

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Adaptive Bag-Of-Visual Word Modelling Using Stacked-Autoencoder And Particle Swarm Optimisation For The Unsupervised Categorisation Of Images, Abass Olaode, Golshah Naghdy Jan 2020

Adaptive Bag-Of-Visual Word Modelling Using Stacked-Autoencoder And Particle Swarm Optimisation For The Unsupervised Categorisation Of Images, Abass Olaode, Golshah Naghdy

Faculty of Engineering and Information Sciences - Papers: Part B

© The Institution of Engineering and Technology 2020 The bag-of-visual words (BOVWs) have been recognised as an effective mean of representing images for image classification. However, its reliance on a visual codebook developed using handcrafted image feature extraction algorithms and vector quantisation via k-means clustering often results in significant computational overhead, and poor classification accuracies. Therefore, this study presents an adaptive BOVW modelling, in which image feature extraction is achieved using deep feature learning and the amount of computation required for the development of visual codebook is minimised using a batch implementation of particle swarm optimisation. The proposed method is …

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