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Parallel intelligent education with ChatGPT

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 12-18页

作者： jiacun wang Ying TANG Ryan HARE Fei-Yue wang Department of Computer Science and Software Engineering Monmouth UniversityNew Jersey 07764USA Department of Electrical and Computer Engineering Rowan UniversityNew Jersey 08028USA Institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning *** especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing to its considerable potential to supplement regular class *** address the strengths and weaknesses of learning with ***,we discuss the challenges and solutions of the proposed parallel intelligent education with ChatGPT.

关键词： education GPT intelligent

Probabilistic Automata-Based Method for Enhancing Performance of Deep Reinforcement Learning Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2327-2339页

作者： Min Yang Guanjun Liu Ziyuan Zhou jiacun wang the Department of Computer Science Tongji University IEEE the Computer Science and Software Engineering Department Monmouth University West Long Branch

Deep reinforcement learning(DRL) has demonstrated significant potential in industrial manufacturing domains such as workshop scheduling and energy system ***, due to the model's inherent uncertainty, rigorous validation is requisite for its application in real-world tasks. Specific tests may reveal inadequacies in the performance of pre-trained DRL models, while the “black-box” nature of DRL poses a challenge for testing model behavior. We propose a novel performance improvement framework based on probabilistic automata,which aims to proactively identify and correct critical vulnerabilities of DRL systems, so that the performance of DRL models in real tasks can be improved with minimal model ***, a probabilistic automaton is constructed from the historical trajectory of the DRL system by abstracting the state to generate probabilistic decision-making units(PDMUs), and a reverse breadth-first search(BFS) method is used to identify the key PDMU-action pairs that have the greatest impact on adverse outcomes. This process relies only on the state-action sequence and final result of each trajectory. Then, under the key PDMU, we search for the new action that has the greatest impact on favorable results. Finally, the key PDMU, undesirable action and new action are encapsulated as monitors to guide the DRL system to obtain more favorable results through real-time monitoring and correction mechanisms. Evaluations in two standard reinforcement learning environments and three actual job scheduling scenarios confirmed the effectiveness of the method, providing certain guarantees for the deployment of DRL models in real-world applications.

关键词： Deep reinforcement learning (DRL) performance improvement framework probabilistic automata real-time monitoring the key probabilistic decision-making units (PDMU)-action pair

Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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Computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi jiacun wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

A Transfer Learning Framework for Deep Multi-Agent Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2346-2348页

作者： Yi Liu Xiang Wu Yuming Bo jiacun wang Lifeng Ma the School of Automation Nanjing University of Science and Technology the Department of Computer Science and Software Engineering Monmouth University

Dear Editor,This letter presents a new transfer learning framework for the deep multi-agent reinforcement learning(DMARL) to reduce the convergence difficulty and training time when applying DMARL to a new scenario [1...

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A Simulation Engine for Stochastic Timed Petri Nets and Application to Emergency Healthcare Systems

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 969-980页

作者： Jiani Zhou jiacun wang Jun wang Monmouth University New Jersey 07764-1898 USA the School of Automation Nanjing University of Science and TechnologyNanjing 210094China

In many service delivery systems,the quantity of available resources is often a decisive factor of service *** can be personnel,offices,devices,supplies,and so on,depending on the nature of the services a system *** service computing has been an active research topic for decades,general approaches that assess the impact of resource provisioning on service quality matrices in a rigorous way remain to be *** nets have been a popular formalism for modeling systems exhibiting behaviors of competition and concurrency for almost a half *** timed Petri nets(STPN),an extension to regular Petri nets,are a powerful tool for system performance ***,we did not find any single existing STPN software tool that supports all timed transition firing policies and server types,not to mention resource provisioning and requirement *** paper presents a generic and resource oriented STPN simulation engine that provides all critical features necessary for the analysis of service delivery system quality *** *** power of the simulation system is illustrated by an application to emergency health care systems.

关键词： Emergency department healthcare resource requirements simulation sojourn time stochastic timed Petri nets(STPNs) workflows

Deep Learning Based Hand Gesture Recognition and UAV Flight Controls

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International Journal of Automation and computing 2020年第1期17卷 17-29页

作者： Bin Hu jiacun wang Monmouth University West Long Branch

Dynamic hand gesture recognition is a desired alternative means for human-computer *** paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehicles(UAV).A data representation model that represents a dynamic gesture sequence by converting the 4-D spatiotemporal data to 2-D matrix and a 1-D array is *** train the system to recognize designed gestures,skeleton data collected from a Leap Motion Controller are converted to two different data *** many as 9124 samples of the training dataset,1938 samples of the testing dataset are created to train and test the proposed three deep learning neural networks,which are a 2-layer fully connected neural network,a 5-layer fully connected neural network and an 8-layer convolutional neural *** static testing results show that the 2-layer fully connected neural network achieves an average accuracy of 96.7%on scaled datasets and 12.3%on non-scaled *** 5-layer fully connected neural network achieves an average accuracy of 98.0%on scaled datasets and 89.1%on non-scaled *** 8-layer convolutional neural network achieves an average accuracy of 89.6%on scaled datasets and 96.9%on non-scaled *** on a drone-kit simulator and a real drone shows that this system is feasible for drone flight controls.

关键词： Deep learning neural networks hand gesture recognition Leap Motion Controllers drones

Dynamic Hand Gesture Recognition Based on Short-Term Sampling Neural Networks

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 110-120页

作者： Wenjin Zhang jiacun wang Fangping Lan the Department of Computer Science and Software Engineering Monmouth UniversityNew Jersey 07740 USA

Hand gestures are a natural way for human-robot *** based dynamic hand gesture recognition has become a hot research topic due to its various *** paper presents a novel deep learning network for hand gesture *** network integrates several well-proved modules together to learn both short-term and long-term features from video inputs and meanwhile avoid intensive *** learn short-term features,each video input is segmented into a fixed number of frame groups.A frame is randomly selected from each group and represented as an RGB image as well as an optical flow *** two entities are fused and fed into a convolutional neural network(Conv Net)for feature *** Conv Nets for all groups share *** learn longterm features,outputs from all Conv Nets are fed into a long short-term memory(LSTM)network,by which a final classification result is *** new model has been tested with two popular hand gesture datasets,namely the Jester dataset and Nvidia *** with other models,our model produced very competitive *** robustness of the new model has also been proved with an augmented dataset with enhanced diversity of hand gestures.

关键词： Convolutional neural network(ConvNet) hand gesture recognition long short-term memory(LSTM)network short-term sampling transfer learning

钢筋-砂浆面层交叉条带加固带填充墙框架抗震性能试验研究

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建筑结构 2024年第7期54卷 30-37页

作者：蒋济同高之皓隋正昂周献祥王家存中国海洋大学工程学院青岛266100 中国人民解放军军事科学院国防工程研究院北京100036

为研究钢筋-砂浆面层交叉条带加固带填充墙框架结构的抗震性能并建立受剪承载力计算公式,设计制作了8榀低矮填充墙框架结构、3榀高窄填充墙框架结构、1榀未设钢筋-砂浆面层交叉条带加固的对照试件,进行了抗震性能试验。结果表明:钢筋-... 详细信息

为研究钢筋-砂浆面层交叉条带加固带填充墙框架结构的抗震性能并建立受剪承载力计算公式,设计制作了8榀低矮填充墙框架结构、3榀高窄填充墙框架结构、1榀未设钢筋-砂浆面层交叉条带加固的对照试件,进行了抗震性能试验。结果表明:钢筋-砂浆面层交叉条带加固带填充墙框架的受剪承载力受混凝土强度、框架柱截面尺寸以及交叉条带配筋量影响较大,加固后受剪承载力最高可提升40%;加固后试件的耗能能力和延性均有一定程度的提升;在填充墙上增设的钢筋-砂浆面层交叉条带可视为协助框架结构受力的拉压杆体系。对试验数据进行拟合得到加固后试件受剪承载力计算公式,结果表明:框架、填充墙和交叉条带之间有承载力协同效果,填充墙框架结构的公式计算值和试验值吻合较好。

关键词：钢筋-砂浆面层交叉条带带填充墙框架受剪承载力抗震性能

A Cooperative Location Management Scheme for Mobile Ad Hoc Networks

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International Journal of Communications, Network and System Sciences 2009年第8期2卷 732-741页

作者： Demin LI jiacun wang Liping ZHANG Hao LI Jie ZHOU 不详

A mobile ad hoc network (MANET) is a kind of wireless ad hoc network. It is a self-configuring network of mobile routers connected by wireless links. Since MANETs do not have a fixed infrastructure, it is a chal-lenge to design a location management scheme that is both scalable and cost-efficient. In this paper, we propose a cooperative location management scheme, called CooLMS, for MANETs. CooLMS combines the strength of grid based location management and pointer forwarding strategy to achieve high scalability and low signaling cost. An indepth formal analysis of the location management cost of CooLMS is presented. In particular, the total location management cost of mobile nodes moving at variable velocity is estimated using the Gauss_Markov mobility model for the correlation of mobility velocities. Simulation results show CooLMS performs better than other schemes under certain circumstances.

关键词： Ad hoc Network Grid Home Region Location Management Forwarding Pointer Cost Estimation