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Articles 5191 - 5220 of 17340

Full-Text Articles in Engineering

Simulation Research On Optimization Of Agv Charging Strategy For Automated Terminal, Danlan Xie, Guo Di, Ji Yuan, Zhipeng Gao Oct 2020

Simulation Research On Optimization Of Agv Charging Strategy For Automated Terminal, Danlan Xie, Guo Di, Ji Yuan, Zhipeng Gao

Journal of System Simulation

Abstract: As the automated container terminal is the development trend of terminal, AGV (automated guided vehicle) becomes the most widely used horizontal transportation tool and it is important to make its reasonable charging strategy. Aiming at the shortcomings of the current AGV, a charging strategy of offline charging being primary and online charging being auxiliary is proposed. In order to solve the problem of location selection of online charging station, a quick method of selecting effective stations by using heat zone map is proposed. Through a large number of simulation experiments using this strategy, the fact that the number …

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Global Optimization Method Based On Consensus Particle Swarm Optimization, Zhanwen Lu, Xingong Cheng, Yongfeng Zhang Oct 2020

Global Optimization Method Based On Consensus Particle Swarm Optimization, Zhanwen Lu, Xingong Cheng, Yongfeng Zhang

Journal of System Simulation

Abstract: According to the characteristics of particle swarm optimization (PSO) and efficient global optimization algorithm (EGO), a global black box optimization algorithm based on consensus particle swarm optimization and local surrogate model (CPSO-LSM) is proposed. The algorithm fixes the period of the PSO algorithm to group the particles and stops after the particles reach a consensus. The high-quality sub-regions around each group of particles are used as the modeling area of the surrogate model, and the high-quality optimal solution or global optimal solution is obtained by comparing the optimal values of each region. It can not only avoid the complex …

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Natural Computing Method Based On Lle Dimension Reduction, Luyao Zhang, Weidong Ji, Cheng Hao Oct 2020

Natural Computing Method Based On Lle Dimension Reduction, Luyao Zhang, Weidong Ji, Cheng Hao

Journal of System Simulation

Abstract: In the natural computing method, the appearance of high-dimensional problem can make some existing optimization algorithms avoid falling into local optimum, but it makes the performance of the algorithm worse and the running time longer. On the basis of traditional natural calculation method, a natural calculation method based on LLE(Local Linear Embedding) algorithm is proposed, which analyzes the value of neighbor particle k and dimension d, and makes the algorithm get better optimization effect after dimension reduction. In the process, a small bias s is added to the data after dimension reduction to increase the diversity of …

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Research On Distribution Line Identification And Simulation Based On Sequence Impedance Method, Keyan Liu, Weijie Dong, Xueshun Ye, Muke Bai, Huaitian Zhang Oct 2020

Research On Distribution Line Identification And Simulation Based On Sequence Impedance Method, Keyan Liu, Weijie Dong, Xueshun Ye, Muke Bai, Huaitian Zhang

Journal of System Simulation

Abstract: The field fault test of distribution network cannot be repeated frequently, a line parameter identification and fault waveform reproduction method based on sequence impedance method is proposed to build the line sequence resistance model, and the π type equivalent lines are constructed. Based on the data of each node obtained in the field test process, the positive sequence impedance and zero sequence impedance parameters of π type equivalent circuits of all line sections are obtained by using the principle of symmetrical sequence components, and the digital model of the real lines in the field is established. The simulation results …

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Research On Fuzzy Flexible Job Shop Scheduling Problem Based On Hybrid Qpso, Junxuan Li, Wang Yan, Zhicheng Ji Oct 2020

Research On Fuzzy Flexible Job Shop Scheduling Problem Based On Hybrid Qpso, Junxuan Li, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: To solve the flexible job shop scheduling problem of uncertain processing time, triangular fuzzy numbers are used to characterize the relevant time parameters and a Hybrid Quantum Particle Swarm Optimization (HQPSO) is proposed. On the basis of making full use of the global search capability of Quantum Particle Swarm Optimization, the search efficiency is increased by designing a boundary repair strategy and a cooperative update strategy. Meanwhile, the cross-operator and path relinking technique are used to in the operation sequence mapped by the excellent particles, which makes up the disadvantages of the insufficient ability of deeply exploration of …

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Adaptive Control Method Of High Proportion Distributed Generation Connected To Distribution Network, Weijie Dong, Keyan Liu, Yilong Wang, Xiaozhong Li, Yang Hao Oct 2020

Adaptive Control Method Of High Proportion Distributed Generation Connected To Distribution Network, Weijie Dong, Keyan Liu, Yilong Wang, Xiaozhong Li, Yang Hao

Journal of System Simulation

Abstract: Focus on the instability of the reactive power output precision caused by the voltage drop and loss of DG lines being switched to grid and the low output frequency and voltage caused by power deficiency of DG islanding, an improved droop control strategy is proposed to ensure the running stability of Active Distribution Network during DG connecting to network. The DG model applies the feedback regulation of f-U droop output power and voltage drop compensator. The control system is applied to the quasi-synchronization grid-connected model, island mode and the modes switching process of an active distribution network's domain transient …

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Optimization Of Shore Bridge Driver Scheduling Strategy Considering Influence Of Illumination, Tiexin Wang, Haihong Yu, Danlan Xie, Yibin Wang Oct 2020

Optimization Of Shore Bridge Driver Scheduling Strategy Considering Influence Of Illumination, Tiexin Wang, Haihong Yu, Danlan Xie, Yibin Wang

Journal of System Simulation

Abstract: The luminous environment has an important effect on the efficiency of quay crane drivers' work. Aiming at the quay crane drivers' shift arrangement under the changing illumination intensity, the theoretical model of illumination influencing efficiency and the 3D simulation model of port operation are established. The influence of different lighting conditions on quay crane drivers' work is analyzed to find the optimal scheduling strategy. By comparing four different scheduling strategies, the optimal 6h interval scheduling is obtained, which increases the working efficiency by about 14% compared with the existing scheduling methods. It shows that when the total working …

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Cascading Failure Analysis Of Equipment Support Network Based On Sirv Virus Propagation Theory, Zhang Qiang, Junhai Cao, Tailiang Song, Haidong Du, Chuang Zhang Oct 2020

Cascading Failure Analysis Of Equipment Support Network Based On Sirv Virus Propagation Theory, Zhang Qiang, Junhai Cao, Tailiang Song, Haidong Du, Chuang Zhang

Journal of System Simulation

Abstract: According to the complexity phenomenon of equipment support network being attacked by the enemy, the similarity between network cascading process and virus propagation process is compared and analyzed. On the basis of the existing load capacity cascading failure model, the process of virus immune propagation is integrated, four different states of support nodes are defined, and the cascade transmission model of equipment support network is constructed, which can better reproduce the real situation of our support organization being attacked by the enemy and public opinion. The simulation and comparison shows that when the defense resources are limited and the …

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Research On Autonomous Berthing For Unmanned Ship Based On Berth Coordinates, Yupeng Jia, Yin Yong, Zhongxian Zhu Oct 2020

Research On Autonomous Berthing For Unmanned Ship Based On Berth Coordinates, Yupeng Jia, Yin Yong, Zhongxian Zhu

Journal of System Simulation

Abstract: Aiming at the problem that the neural network autonomous docking controllers can only complete the docking of a specific ports, but cannot extend to other ports without training data, a coordinate system (berth coordinates with the berth vertex as theorigin and the shoreline as the Y Axis) is proposed. The relative position is used to train the controller. In V.Dragon-5000 navigation simulator, the container ship “Yinhe” is selected. After docking training at Dalian port, the docking controller is successfully extended to Shenzhen Shekou port and Singapore Changi port without training data. The simulation verifies that the application …

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Modeling Research On Assessment System For Army Maintenance Work Capacity, Haidong Du, Junhai Cao, Fusheng Liu Oct 2020

Modeling Research On Assessment System For Army Maintenance Work Capacity, Haidong Du, Junhai Cao, Fusheng Liu

Journal of System Simulation

Abstract: A set of simulation model design scheme is proposed to meet the needs of maintenance simulation evaluation of combined army. After analyzing the principle of simulation evaluation of military maintenance capability, the requirements of the evaluation model is analyzed. The generation of maintenance tasks and the modeling scheme of maintenance support system are given; On the basis of the spare parts scheduling and the use process of support equipment, the maintenance support resource model is designed. The modeling basis for the evaluation of equipment maintenance capability of the combined army is provided, which supports the design and application case …

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Nature Computation Of Self-Adaptive Dynamic Control Strategy Of Population Grouping, Wanlu Ni, Weidong Ji, Xiaoqing Sun Oct 2020

Nature Computation Of Self-Adaptive Dynamic Control Strategy Of Population Grouping, Wanlu Ni, Weidong Ji, Xiaoqing Sun

Journal of System Simulation

Abstract: Multi-population optimization method can solve the optimization difficulty caused by the increase of data volume, but the existing population grouping is carried out by means of random grouping or artificial setting, which doesn't take particle trajectories into full consideration. In view of the problem a self-adaptive dynamic control strategy of population grouping is proposed, which uses Gaussian fitting function as the reference curve of population grouping and divides sub populations according to the function's monotone interval. For particles with the trend of crossing the upper boundary of sub populations, the contrarian strategy is adopted to maintain the population diversity …

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Research On Modeling And Process Parameters Optimization Of Glcn Fermentation Process, Wanli Yu, Wang Yan, Zhicheng Ji Oct 2020

Research On Modeling And Process Parameters Optimization Of Glcn Fermentation Process, Wanli Yu, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: In view of the high price and low detection accuracy of biosensors, which makes it difficult to obtain accurate and real-time biological parameters in the process of GlcN fermentation, the Least Square Support Vector Machine (LSSVM) model is established to predict the cell concentration, product concentration and substrate concentration. In order to improve the accuracy of the prediction model, the improved multiverse optimization algorithm based on Levy flight is utilized to optimize several parameters of the LSSVM model. On the basis of the model aiming at the maximum product concentration at the time of fermentation completion, the fermentation process …

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Chemical Cluster Cooperative Patrolling Strategy Based On Game Theory, Feiran Chen, Bin Chen, Zhengqiu Zhu, Xiaogang Qiu, Yiduo Wang, Zhao Yong Oct 2020

Chemical Cluster Cooperative Patrolling Strategy Based On Game Theory, Feiran Chen, Bin Chen, Zhengqiu Zhu, Xiaogang Qiu, Yiduo Wang, Zhao Yong

Journal of System Simulation

Abstract: Industrial production activities in the chemical cluster pose great threats to the surrounding atmospheric environment and human health. It is necessary for the management team to strictly supervise the chemical production processes and monitor the gas emissions to ensure the air quality. One of the effective means is to patrol chemical plants in the chemical cluster. The cooperative patrolling strategy of multiple patrol vehicles based on game theory is studied. A greedy deployment algorithm to determine the initial deployment of patrol vehicles is proposed. The static partition cooperation method is used to partition the chemical cluster into multiple small …

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Research On Network Attack And Defense Situation Based On Game Theory Model And Netlogo Simulation, Xiaohu Liu, Hengwei Zhang, Yuchen Zhang, Ma Zhuang, Wenlei Lü Oct 2020

Research On Network Attack And Defense Situation Based On Game Theory Model And Netlogo Simulation, Xiaohu Liu, Hengwei Zhang, Yuchen Zhang, Ma Zhuang, Wenlei Lü

Journal of System Simulation

Abstract: Aiming at the problem that the existing modeling methods lack of the analysis on the behavior and trend of attack and defense game, the characteristics of network attack and defense game from the perspective of confrontation are analyzed Based on the static game theory of non- cooperative incomplete information, the network attack and defense game model is established, and the revenue quantification, game equilibrium calculation and decision-making of strategic confrontation result are given. The multi-agent simulation model of network attack and defense game is constructed. The simulation experiments under different strategy combinations and different initial numbers of players are …

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Chaos Control Of Permanent Magnet Synchronous Motor Based On Finite Time Lasalle Invariant Set, Zhang Yun, Wang Cong, Hongli Zhang, Ma Ping Oct 2020

Chaos Control Of Permanent Magnet Synchronous Motor Based On Finite Time Lasalle Invariant Set, Zhang Yun, Wang Cong, Hongli Zhang, Ma Ping

Journal of System Simulation

Abstract: In order to effectively restrain the chaotic behavior of permanent magnet synchronous motor, an adaptive controller is designed based on finite time theory and LaSalle invariant set theorem. The chaotic dynamics characteristics of the permanent magnet synchronous motor system are analyzed, and the parameter fields of the system in different motion states are determined. It is proved theoretically that the controller can stabilize to the equilibrium point in finite time and can automatically track the equilibrium point of the system. Simulation results show that the control scheme is concise, faster and more stable. The research results are of great …

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Simulation On Spatial-Temporal Dynamic Change Of Ocean Environment In Marine Simulators, Qianfeng Jing, Helong Shen, Zhengli Gao, Yin Yong Oct 2020

Simulation On Spatial-Temporal Dynamic Change Of Ocean Environment In Marine Simulators, Qianfeng Jing, Helong Shen, Zhengli Gao, Yin Yong

Journal of System Simulation

Abstract: Marine structures are subject to environmental interference all the time, and the simulation of the ocean environment significantly affects the realism of the marine simulators. The ocean environmental fields are generated by the numerical wave model, and the real ocean databases are developed based on SQLite. The actual wind, current, and wave information are obtained from the databases to keep consistency with the actual sea. The environmental disturbances are modeled and both the spatiotemporal-varying features and the coupling effects are brought into the simulation. The real voyage cases are reproduced by the proposed simulation method. The measured data …

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Prediction Of N-Acetylglucosamine Content Based On Rf-Ga-Bp Neural Network, Wenfeng Yang, Wang Yan, Zhichen Ji Oct 2020

Prediction Of N-Acetylglucosamine Content Based On Rf-Ga-Bp Neural Network, Wenfeng Yang, Wang Yan, Zhichen Ji

Journal of System Simulation

Abstract: In order to solve the problem that the content of N-acetylglucosamine (GlcNAc) in the process of preparing glucocosamine (GlcN) by microbial fermentation is difficult to measure online, an improved prediction algorithm based on stochastic forest algorithm, genetic algorithm and neural network algorithm is proposed. The algorithm utilizes the feature of decreasing average impurity in random forest algorithm to analyze the relevance of the input characteristics. The initial weights and thresholds of the neural networks are optimized by the genetic algorithm. A prediction model based on the RF-GA-BP algorithm is established based on the data from the fermentation process of …

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A Photovoltaic Power Forecasting Method Based On Da-Rkelm Algorithm, Mingqi Wei, Tianrui Zhang, Xiuxiu Gao, Shumei Wang Oct 2020

A Photovoltaic Power Forecasting Method Based On Da-Rkelm Algorithm, Mingqi Wei, Tianrui Zhang, Xiuxiu Gao, Shumei Wang

Journal of System Simulation

Abstract: Aiming at the power grid safety problems caused by the fluctuation and randomness of photo-voltaic power generation, a method for predicting photo-voltaic power generation of a regular nuclear limit learning machine based on the optimization of a dragonfly algorithm was proposed. Through correlation analysis, the key factors affecting the photo-voltaic power generation are determined, and the photo-voltaic power prediction model is constructed. Dragonfly algorithm is used to obtain the optimal weight and threshold value of the network, and regularization function and kernel function are introduced based on the standard limit learning machine to avoid the over …

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Research On Simulation Optimization Of Intelligent Storage Robot Configuration Under Multiple Constraints, Guo Di, Danlan Xie, Ji Yuan Oct 2020

Research On Simulation Optimization Of Intelligent Storage Robot Configuration Under Multiple Constraints, Guo Di, Danlan Xie, Ji Yuan

Journal of System Simulation

Abstract: Aiming at the intelligent warehouse storage robot configuration, a discrete event simulation model based on queuing theory is constructed. Considering the influence of faults and the reliability and service intensity of the system, aiming at minimizing the total cost of distance cost, time cost, idle cost and purchase cost, a based on FlexSim simulation model is proposed. Discrete event simulation optimization method of the platform. By analyzing the system average team length, order average stay time and other indicators, the intuitionistic bottleneck of the system is combined with the actual operation data, and the configuration strategy of minimum system …

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Optimization And Simulation Of Offshore Edge Computing Network For E-Pilotage, Bin Lin, Chenchen Song, Yajing Zhang, Jianli Duan Oct 2020

Optimization And Simulation Of Offshore Edge Computing Network For E-Pilotage, Bin Lin, Chenchen Song, Yajing Zhang, Jianli Duan

Journal of System Simulation

Abstract: In order to improve the safety of the ship's piloting process, an INA-based offshore edge computing network (IOECN) architecture is proposed to provide navigation assistance information. The Layout Optimization Problem (LOP) of network element nodes in the network is mainly studied. The mathematical model is used to convert the LOP into an Integer Linear Programming (ILP) problem. On condition of the required network coverage and connectivity, aiming to minimize the network cost, being solved by Gurobi and simulated and demonstrated by Matlab, the network optimization on different scales is obtained and the correctness and scalability of …

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A User Study Of A Wearable System To Enhance Bystanders’ Facial Privacy, Alfredo J. Perez, Sherali Zeadally, Scott Griffith, Luis Y. Matos Garcia, Jaouad A. Mouloud Oct 2020

A User Study Of A Wearable System To Enhance Bystanders’ Facial Privacy, Alfredo J. Perez, Sherali Zeadally, Scott Griffith, Luis Y. Matos Garcia, Jaouad A. Mouloud

Information Science Faculty Publications

The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped with cameras which enable users to take pictures and record videos anytime they need to do so. In many such cases, bystanders’ privacy is not a concern, and as a result, audio and video of bystanders are often captured without their consent. We present results from a user study in which 21 participants were asked to use a wearable system called …

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A Novel Energy-Efficient Sensor Cloud Model Using Data Prediction And Forecasting Techniques, Kalyan Das, Satyabrata Das, Aurobindo Mohapatra Oct 2020

A Novel Energy-Efficient Sensor Cloud Model Using Data Prediction And Forecasting Techniques, Kalyan Das, Satyabrata Das, Aurobindo Mohapatra

Karbala International Journal of Modern Science

An energy-efficient sensor cloud model is proposed based on the combination of prediction and forecasting methods. The prediction using Artificial Neural Network (ANN) with single activation function and forecasting using Autoregressive Integrated Moving Average (ARIMA) models use to reduce the communication of data. The requests of the users generate in every second. These requests must be transferred to the wireless sensor network (WSN) through the cloud system in the traditional model, which consumes extra energy. In our approach, instead of one second, the sensors generally communicate with the cloud every 24 hours, and most of the requests reply using the …

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Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand Oct 2020

Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …

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Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan Oct 2020

Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan

Other Student Works

Cloud computing is the development of distributed and parallel computing that seeks to provide a new model of business computing by automating services and efficiently storing proprietary data. Cloud bursting is one of the cloud computing techniques that adopts the hybrid cloud model which seeks to expand the resources of a private cloud through the integration with a public cloud infrastructure. In this paper, the viability of cloud bursting is experimented and an attempt to integrate AWS EC2 onto an Openstack cloud environment using the Openstack OMNI driver is conducted.

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Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler Oct 2020

Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler

Engineering Technology Faculty Publications

Over the last two decades, Artificial Intelligence (AI) approaches have been applied to various applications of the smart grid, such as demand response, predictive maintenance, and load forecasting. However, AI is still considered to be a ‘‘black-box’’ due to its lack of explainability and transparency, especially for something like solar photovoltaic (PV) forecasts that involves many parameters. Explainable Artificial Intelligence (XAI) has become an emerging research field in the smart grid domain since it addresses this gap and helps understand why the AI system made a forecast decision. This article presents several use cases of solar PV energy forecasting using …

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Agent-Based Modelling Of Values: The Case Of Value Sensitive Design For Refugee Logistics, Christine Boshuijzen-Van Burken, Ross J. Gore, Frank Dignum, Lamber Royakkers, Phillip Wozny, F. Leron Shults Oct 2020

Agent-Based Modelling Of Values: The Case Of Value Sensitive Design For Refugee Logistics, Christine Boshuijzen-Van Burken, Ross J. Gore, Frank Dignum, Lamber Royakkers, Phillip Wozny, F. Leron Shults

VMASC Publications

We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz’s theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different ‘value scenarios’, stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform …

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A Centralised Multi-Objective Model Predictive Control For Biventricular Assist Devices, Vivian Koh Ci Ai Oct 2020

A Centralised Multi-Objective Model Predictive Control For Biventricular Assist Devices, Vivian Koh Ci Ai

Student Works (2020-2029)

Heart failure is defined as failure of heart to deliver adequate blood flow rate to support tissue perfusion. Heart failure can be treated by implantation of a left ventricular assist device (LVAD) for left heart failure patients, or a biventricular assist device (BiVAD) for bi-heart failure patients. Since left heart failure predominates right heart failure, all commercial ventricular assist devices are LVADs. Therefore, two LVADs are frequently used as BiVAD for bi-heart failure patients. Clinically, the constant speed (CS) control of BiVAD fails to adapt pump flow rate according to physiological changes, thus putting patients at risk of ventricular suction …

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Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau Oct 2020

Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In real-world urban logistics operations, changes to the routes and tasks occur in response to dynamic events. To ensure customers’ demands are met, planners need to make these changes quickly (sometimes instantaneously). This paper proposes the formulation of a dynamic vehicle routing problem with time windows and both known and stochastic customers as a route-based Markov Decision Process. We propose a solution approach that combines Deep Reinforcement Learning (specifically neural networks-based TemporalDifference learning with experience replay) to approximate the value function and a routing heuristic based on Simulated Annealing, called DRLSA. Our approach enables optimized re-routing decision to be generated …

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Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal Oct 2020

Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

In the blooming era of smart edge devices, surveillance cam- eras have been deployed in many locations. Surveillance cam- eras are most useful when they are spaced out to maximize coverage of an area. However, deciding where to place cam- eras is an NP-hard problem and researchers have proposed heuristic solutions. Existing work does not consider a signifi- cant restriction of computer vision: in order to track a moving object, the object must occupy enough pixels. The number of pixels depends on many factors (how far away is the object? What is the camera resolution? What is the focal length?). …

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Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu Oct 2020

Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu

Research Collection School Of Computing and Information Systems

Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating strategic intervention, and enabling adaptive online learning. Interactive online question pools provide students with interesting interactive questions to practice their knowledge in online education. However, little research has been done on student performance prediction in interactive online question pools. Existing work on student performance prediction targets at online learning platforms with predefined course curriculum and accurate knowledge labels like MOOC platforms, but they are not able to fully model knowledge evolution of students in interactive online …

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