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Victor: An Implicit Approach To Mitigate Misinformation Via Continuous Verification Reading, Kuan-Chieh LO, Shih-Chieh DAI, Aiping XIONG, Jing JIANG, Lun-Wei KU 2022 Academia Sinica

Victor: An Implicit Approach To Mitigate Misinformation Via Continuous Verification Reading, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

We design and evaluate VICTOR, an easy-to-apply module on top of a recommender system to mitigate misinformation. VICTOR takes an elegant, implicit approach to deliver fake-news verifications, such that readers of fake news can continuously access more verified news articles about fake-news events without explicit correction. We frame fake-news intervention within VICTOR as a graph-based question-answering (QA) task, with Q as a fake-news article and A as the corresponding verified articles. Specifically, VICTOR adopts reinforcement learning: it first considers fake-news readers’ preferences supported by underlying news recommender systems and then directs their reading sequence towards the verified news articles. To …


A Survey On Modern Deep Neural Network For Traffic Prediction: Trends, Methods And Challenges, David Alexander TEDJOPUMOMO, Zhifeng BAO, Baihua ZHENG, Farhana Murtaza CHOUDHURY, Kai QIN 2022 Royal Melbourne Institute of Technology

A Survey On Modern Deep Neural Network For Traffic Prediction: Trends, Methods And Challenges, David Alexander Tedjopumomo, Zhifeng Bao, Baihua Zheng, Farhana Murtaza Choudhury, Kai Qin

Research Collection School Of Computing and Information Systems

In this modern era, traffic congestion has become a major source of negative economic and environmental impact for urban areas worldwide. One of the most efficient ways to mitigate traffic congestion is through future traffic prediction. The field of traffic prediction has evolved greatly ever since its inception in the late 70s. Earlier studies mainly use classical statistical models such as ARIMA and its variants. Then, researchers started to focus on machine learning models due to their power and flexibility. As theoretical and technological advances emerge, we enter the era of deep neural network, which gained popularity due to its …


Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang 2022 School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710000, China;

Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang

Journal of System Simulation

Abstract: RRT (rapidly exploring random tree) algorithm is a sampling-based path planning algorithm, which can search a path in high-dimensional environment. The traditional RRT algorithm has the problems of low node utilization and large amount of calculation. To solve these problems, the fast RRT* (Quick RRT*) algorithm is improved by optimizing the strategy of reselection of parent node and pruning range, improving the sampling method and introducing adaptive step size, which makes the algorithm time-consuming and path length shorter. At the same time, the node connection screening strategy is added to eliminate the excessive turning angle in the path. …


Research On Real-Time Motion Matching Of Shadow Play Based On Kinect, Chuanqian Tang, Zhiqiang Liu, Yijun Su, Xiaojing Liu 2022 Department of Computer Technology and Application, Qinghai University, Xining 810016, China;

Research On Real-Time Motion Matching Of Shadow Play Based On Kinect, Chuanqian Tang, Zhiqiang Liu, Yijun Su, Xiaojing Liu

Journal of System Simulation

Abstract: In the inheritance of shadow play culture, due to the aging of the audience and the discontinuity of inheritance, the shadow play culture is gradually facing decline. Real-time matching of shadow play movements based on Kinect can inject new vitality into traditional shadow play culture. According to the characteristics of shadow play, a joint point shadow play model is constructed, and the static digitization of shadow play is realized. The human body depth image is obtained based on Kinect, and the human skeleton point coordinates are obtained through segmentation mask and machine learning to generate the human skeleton.Bone …


Collaborative Computing Support For Analysis Facilities Exploiting Software As Infrastructure Techniques, Maria Acosta Flechas, Garhan Attebury, Kenneth Bloom, Brian Bockelman, Lindsey Gray, Burt Holzman, Carl Lundstedt, Oksana Shadura, Nicholas Smith, John Thiltges 2022 Fermi National Accelerator Laboratory

Collaborative Computing Support For Analysis Facilities Exploiting Software As Infrastructure Techniques, Maria Acosta Flechas, Garhan Attebury, Kenneth Bloom, Brian Bockelman, Lindsey Gray, Burt Holzman, Carl Lundstedt, Oksana Shadura, Nicholas Smith, John Thiltges

Holland Computing Center: Faculty Publications

Prior to the public release of Kubernetes it was difficult to conduct joint development of elaborate analysis facilities due to the highly non-homogeneous nature of hardware and network topology across compute facilities. However, since the advent of systems like Kubernetes and OpenShift, which provide declarative interfaces for building fault-tolerant and self-healing deployments of networked software, it is possible for multiple institutes to collaborate more effectively since resource details are abstracted away through various forms of hardware and software virtualization. In this whitepaper we will outline the development of two analysis facilities: “Coffea-casa” at University of Nebraska Lincoln and the “Elastic …


Effectiveness Evaluation Of Surface Ship Air Defense And Antimissile Combat In Complex Electromagnetic Environment, Gaofeng Zhang, Liang Wu 2022 Unit 91336 of the Chinese PLA, Qinhuangdao 066326, China;

Effectiveness Evaluation Of Surface Ship Air Defense And Antimissile Combat In Complex Electromagnetic Environment, Gaofeng Zhang, Liang Wu

Journal of System Simulation

Abstract: In order to effectively evaluate the effectiveness of surface ship air defense and antimissile combat in complex electromagnetic environment, a surface ship air defense and antimissile combat effectiveness index system is established considering the influence of equipment, environment and human behavior, the evaluation process of surface ship air defense and antimissile combat effectiveness based on analytic hierarchy process(AHP) is proposed, and a hierarchical structure model of effectiveness evaluation is constructed including five levels of target layer, sub-efficiency layer, capability layer, constraint layer and plan layer. The application shows that the evaluation process and structure model can fully reflect the …


New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang 2022 1.State Key Laboratory of Complex Product Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China;2.Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center, Beijing 100854, China;3.Science and Technology on Special Simulation Laboratory, Beijing Simulation Center, Beijing 100854, China;4.Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education, Beihang University, Beijing 100191, China;

New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang

Journal of System Simulation

Abstract: Human society in the new development era and journey is facing the new situation. The operation paradigm, technology and ecosystem of industries related to the national economy and people's livelihood、national security are changing significantly towards the digital, networked, cloud-based and intelligent "Smart Internet of Things". The new embedded simulation technology, with the capabilities of online and continuous analysis, cognition, learning, decision-making, operation and optimization,is urgently needed for the development of "Smart Internet of Things". "Smart Internet of Things" is briefly introduced and the connotation, characteristics and application mode of the new embedded simulation technology are proposed and its architecture, …


Open Cloud Architecture Design For Complex Product Modeling And Simulation System, Guoqiang Shi, Zewei Liu, Tingyu Lin, Zhao Xu, Xingyi Yang, Liqin Guo, Zhengxuan Jia 2022 1.Beijing Simulation Center, Beijing 100854, China;2.State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China;

Open Cloud Architecture Design For Complex Product Modeling And Simulation System, Guoqiang Shi, Zewei Liu, Tingyu Lin, Zhao Xu, Xingyi Yang, Liqin Guo, Zhengxuan Jia

Journal of System Simulation

Abstract: Aiming at the problem that the complex product modeling and simulation system focuses on co-simulation of heterogeneous models and cannot realize the on-demand sharing and collaboration of simulation resources, this paper proposes an open cloud architecture for complex product modeling and simulation systems, realized on-demand sharing and collaboration of cross-organizational simulation software and hardware resources, thereby supporting complex product system-wide, full-lifecycle, anytime, anywhere, real-time, coherent, and transparently requesting accessing and obtaining simulation services. The object-process methodology (OPM) is used to model and deduce the simulation interoperability of the system and the on-demand sharing and collaborative process of simulation resources. …


Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang 2022 School of Information Engineering, Ningxia University, Yinchuan 750021, China;

Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang

Journal of System Simulation

Abstract: Aiming at the flexible job shop scheduling problem with AGV (automated guided vehicle), a dual resource integrated scheduling optimization model with the objective of minimizing makespan is established. In the process of population initialization, a heuristic initialization method is proposed to improve the quality of population initial solution and accelerate the convergence speed of the algorithm. A hybrid discrete particle swarm optimization algorithm that can effectively avoid premature maturation is proposed by combining the competitive learning mechanism and the random restart mechanism to address the disadvantages of discrete particle swarm algorithms that are prone to premature maturation. Simulation experiments …


Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu 2022 Management College, Xi′an University of Architecture & Technology, Xi′an 710055, China;

Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu

Journal of System Simulation

Abstract: The multi-resolution formal description based on discrete event system specification (DEVS) has the ability of hierarchical and structured description, but the description of the intelligent behavior inside the module is relatively lacking, while Agent-based modeling can describe the characteristics of individual perception, behavior, communication, cooperation, learning and evolution. Under the framework of multi-resolution modeling, DEVS and Agent model descriptions are combined to provide the description capabilities for events, behaviors, mechanisms, etc. Based on the description of multi-resolution DEVS models, a formal model description method with coupling closure is proposed, which includes the description of the multi-resolution entity-level atomic model …


Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu 2022 Key Laboratory for Advanced Process Control of Light Industry of Ministry of Education, Jiangnan University, Wuxi 214122, China;

Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu

Journal of System Simulation

Abstract: Aiming at the problems of complex modeling mechanism and low modeling accuracy in the prediction of electronic solid waste production, an intelligent modeling method combining fractional order multiple gray model and neural network compensation model is proposed. Particle swarm optimization is used to optimize the accumulative order and background parameters of the gray model to maximize the performance of the gray model. BP neural network is used to compensate the error of gray modeling and improve the prediction accuracy of solid waste production. The effectiveness of the proposed method is verified by Washington state electronic solid waste data. The …


Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang 2022 1.Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Wuxi 214122, China;

Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang

Journal of System Simulation

Abstract: A new shop rescheduling model driven by digital twin is proposed to solve the problems of disturbance cumulative rescheduling. A scheduling parameter updating method is proposed and a random probability distribution is used to describe the distribution of scheduling parameters to improve the accuracy of scheduling parameters. An implicit disturbance detection model is built based on Siamese Network using real-time data as input to realize the start time of rescheduling. The sample data for scheduling knowledge mining are extracted from the historical scheduling scenarios. Through the Pseudo-Siamese CNN, the mapping relationship between the Process state and machine state is …


Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing 2022 1.Engineering Department of Shanghai Polytechnic University, Shanghai 201209, China;

Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing

Journal of System Simulation

Abstract: Aiming at the problems of large measurement error, single image information, and poor real-time performance in binocular vision ranging, a binocular ranging method based on ORB (oriented fast and rotated brief) features is proposed. Median filtering is performed on the video frame, the ORB feature of the image is extracted, and the Hamming distance with the best matching effect is selected through experiments. The RANSAC (random sample consensus) model estimation is performed on the selected matching points, the mismatches are removed, the model relationship between parallax and true distance is analyzed, the optimal ranging model is constructed and verified …


Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang 2022 Tianjin University of Technology, Tianjin 300384, China;

Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang

Journal of System Simulation

Abstract: An intelligent agent technology architecture is adopted to the simulation model development of airport cargo business. Aiming at the optimization of airport cargo resources, a decision support system framework combining deep reinforcement learning (DRL) and airport cargo business simulation model is proposed. The simulated results are applied as the training data of the DRL network, and the DRL is used to optimize operation parameter of the simulation model. The mature system can be run online, which can provide optimized operation order in real time. In order to verify the effectiveness of the architecture, model development and experiments are conducted …


Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong 2022 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122;

Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong

Journal of System Simulation

Abstract: Since the data collected from industrial processes often contain a large number of unlabeled samples, while the number of labeled samples is small and the cost of manual labeling is high, an active learning method based on covariance matrix is proposed. This method uses labeled samples to establish a Gaussian process regression model, and constructs the covariance matrix between the unlabeled samples, using the value of the determinant of the covariance matrix as an evaluation indicator. While selecting informative unlabeled samples, the similarity between samples is measured to avoid redundant addition of samples, which finally improves model prediction accuracy …


Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi 2022 1.School of Automation, Northwestern Polytechnical University, Xi'an 710129, China;

Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi

Journal of System Simulation

Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …


An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li 2022 School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150000, China;

An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li

Journal of System Simulation

Abstract: The atom search algorithm (ASO) is a new optimization algorithm proposed by imitating the movement of atoms in the natural world. An improved atomic search algorithm (IASO) is proposed to address the problems of prematureness and slow convergence of ASO in solving complex functions. IASO adds the binding force generated by the historical optimal solution of individual atoms to correct the acceleration of ASO and enhance the global search capability. The two multiplier coefficients are adaptively updated to coordinate the algorithm's global search and local development capabilities. The Gaussian mutation strategy is used to re-update the atomic position and …


Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo 2022 1.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China;2.National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 611756, China;

Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo

Journal of System Simulation

Abstract: Based on the characteristics of a large number of transfer routes in rail transit network, an improved depth first search algorithm is proposed to get the effective travel time of transfer routes between stations. Based on passenger entry and exit timing obtained from the automatic fare collection (AFC) data, the connect relationship between passengers and trains in time and route is obtained from the arrival time and route selection behavior of passengers. Considering the difference of route choice behavior between departure passenger and transfer passenger, the two are distinguished from each other. The dynamically updated travel …


Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang 2022 School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China;

Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang

Journal of System Simulation

Abstract: Cell manufacturing is an important organizational form of modern production systems. In scheduling of cell manufacturing systems, machine failures or interruptions are very common in practice, meanwhile the waste due to energy consumption during machine idle time cannot be ignored. Hence the relevant research is with strong significance. This paper considers the problems of machine interruption and energy consumption in cell scheduling, and developed an integer programming model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A mixed optimization method is proposed based on improved wolf pack algorithm …


Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang 2022 1.School of Control Science and Engineering, Dalian University of Technology, Dalian 116023, China;

Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang

Journal of System Simulation

Abstract: A multi-modality modeling method for time series data based on fuzzy cognitive maps is proposed to address the problem that a single model is difficult to accurately reflect the multi-modal characteristics of time series.The bootstrap method is used to select multiple sub-sequences from the original time serieswhich contain the diverse modality in the original time series. The fuzzy cognitive map sub-models are constructed on each sub-sequencesrespectively. The formed sub-models are further merged by means of granular computing method and the merging performance with different weighting strategies is analyzed. The developed multi-modal model not only has prediction abilities at …


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