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Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng 2022 1.College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China;

Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng

Journal of System Simulation

Abstract: The project type manufacturing process is quite common in shipbuilding and construction industries. Aiming at the problem that the existing discrete manufacturing system modeling and simulation method for flow shop cannot effectively express and imitate this process, taking shipyard dock shop hoisting process as an example, we analyze its components structure, propose a working network-centric, information flow and work flow integrated simulation modelling method, and design a dedicated simulation algorithm with the task process interactive idea. A prototype simulation program is developed with Python language, and the effectiveness of the proposed modelling and simulation method is verified through …


Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang 2022 China North Vehicle Research Institute, Beijing 100072, China;

Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang

Journal of System Simulation

Abstract: In order to improve the utilization of the network resources of the FlexRay bus, the network is optimized for static segment scheduling. The FlexRay communication mechanism is analyzed, the message model is established and the calculation method of bandwidth loss is derived, while considering the protocol overhead and network idling, taking the number of static frames and the length of the static frame payload as design variables, the overall optimal packaging scheme is obtained by solving this multi-objective optimization problem. This solution is finally applied to the vehicle chassis integrated control system for simulation analysis and verification. The results …


Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye 2022 1.Business School, University of Shanghai for Science & Technology, Shanghai 200093, China;2.Henan Institute of Technology, Xinxiang 453000, China;

Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye

Journal of System Simulation

Abstract: Aiming at the joint optimization problem of energy-saving distributed manufacturing and preventive maintenance for semiconductor wafers, a two-stage green scheduling model considering both the manufacturing stage and the inspection and repair stage is established to minimize the makespan, the total carbon emissions and the total preventive maintenance cost. An improved hybrid multi-objective grey wolf optimization (IHMGWO)algorithm is proposed. The decoding schemes of factory allocation strategy, machine allocation strategy and synchronous scheduling maintenance strategy considering the flexibility of maintenance workers are designed in IHMGWO. By designing the initial population fusion strategy, predation behavior search strategy, and sub-population mutation strategy, the …


Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan 2022 1.Military Exercise and Training Center, Army Academy of Armored Forces, Beijing 100072, China;2.Unit 32128 of the Chinese PLA, Jinan 250024, China;

Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan

Journal of System Simulation

Abstract: Agents are difficult to be directly modeled and simulated due to the complexity of their own interaction and learning behaviors. Aiming at the common problems in the discrete simulation of the agent, the event transfer mechanism of the discrete event system specification (DEVS) atomic model is applied to express the interaction and learning of an agent. Through the interaction mode of the agent, the transfer control of multi-state external events, the port connection mode, as well as the introduction of reinforcement learning event transfer representation, a discrete simulation construction method of the agent based on the DEVS atomic model …


Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan 2022 1.School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China;3.Department of Information Management, University of International Business and Economics, Beijing 100029, China;

Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan

Journal of System Simulation

Abstract: The heterogeneous-fleet electric vehicle routing problem with partial linear recharging is studied for realistic logistics distribution scenarios using multiple electric vehicle fleets with different transport capacities, driving ranges and acquisition costs. A path-based mixed integer linear model is proposed. The model enumerates the paths visited by all vehicle types between any non-charging nodes, eliminates the infeasible paths through capacity constraints and time window constraints, and eliminates the dominated paths by the dominance criterion. Compared with the traditional charging station replica-based model, this model eliminates the need to set the number of charging station replicas. The results show that the …


Directional Pairwise Class Confusion Bias And Its Mitigation, Sudhashree Sayenju, Ramazan Aygun PhD, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang PhD, Bill Franks, Sereres Johnston PhD, George Lee, Dan Sullivan, Girish Modgil PhD 2022 Kennesaw State University

Directional Pairwise Class Confusion Bias And Its Mitigation, Sudhashree Sayenju, Ramazan Aygun Phd, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang Phd, Bill Franks, Sereres Johnston Phd, George Lee, Dan Sullivan, Girish Modgil Phd

Published and Grey Literature from PhD Candidates

Recent advances in Natural Language Processing have led to powerful and sophisticated models like BERT (Bidirectional Encoder Representations from Transformers) that have bias. These models are mostly trained on text corpora that deviate in important ways from the text encountered by a chatbot in a problem-specific context. While a lot of research in the past has focused on measuring and mitigating bias with respect to protected attributes (stereotyping like gender, race, ethnicity, etc.), there is lack of research in model bias with respect to classification labels. We investigate whether a classification model hugely favors one class with respect to another. …


Coordinated Delivery To Shopping Malls With Limited Docking Capacity, Ruidian SONG, Hoong Chuin LAU, Xue LUO, Lei ZHAO 2022 Tsinghua University

Coordinated Delivery To Shopping Malls With Limited Docking Capacity, Ruidian Song, Hoong Chuin Lau, Xue Luo, Lei Zhao

Research Collection School Of Computing and Information Systems

Shopping malls are densely located in major cities such as Singapore and Hong Kong. Tenants in these shopping malls generate a large number of freight orders to their contracted logistics service providers, who independently plan their own delivery schedules. These uncoordinated deliveries and limited docking capacity jointly cause congestion at the shopping malls. A delivery coordination platform centrally plans the vehicle routes for the logistics service providers and simultaneously schedules the dock time slots at the shopping malls for the delivery orders. Vehicle routing and dock scheduling decisions need to be made jointly against the backdrop of travel time and …


Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai LAN, Lei WANG, Qiyuan ZHANG, Yunshi LAN, Bing Tian DAI, Yan WANG, Dongxiang ZHANG, Ee-peng LIM 2022 Xihua University

Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

While Math Word Problem (MWP) solving has emerged as a popular field of study and made great progress in recent years, most existing methods are benchmarked solely on one or two datasets and implemented with different configurations. In this paper, we introduce the first open-source library for solving MWPs called MWPToolkit, which provides a unified, comprehensive, and extensible framework for the research purpose. Specifically, we deploy 17 deep learning-based MWP solvers and 6 MWP datasets in our toolkit. These MWP solvers are advanced models for MWP solving, covering the categories of Seq2seq, Seq2Tree, Graph2Tree, and Pre-trained Language Models. And these …


Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan MISRA, Nirmalya Roy 2022 Singapore Management University

Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan Misra, Nirmalya Roy

Research Collection School Of Computing and Information Systems

We tackle the problem of domain adaptation for inertial sensing-based human activity recognition (HAR) applications -i.e., in developing mechanisms that allow a classifier trained on sensor samples collected under a certain narrow context to continue to achieve high activity recognition accuracy even when applied to other contexts. This is a problem of high practical importance as the current requirement of labeled training data for adapting such classifiers to every new individual, device, or on-body location is a major roadblock to community-scale adoption of HAR-based applications. We particularly investigate the possibility of ensuring robust classifier operation, without requiring any new labeled …


Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin PU, Ying ZHANG, Li-Chen CHOU 2022 Wenzhou University of Technology

Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin Pu, Ying Zhang, Li-Chen Chou

Research Collection School Of Computing and Information Systems

This study applies the two-tier stochastic frontier model to estimate the distribution of housing transaction information in Hangzhou, Wenzhou, Ningbo, and Jinhua (four cities in Zhejiang Province, China) during the year 2018, to analyze the difference in the price information acquired by the buyers and sellers in the transaction, and the effect of information asymmetry on the transaction price. The empirical results show that in each city, during the housing transaction process, the supplier has more complete information about house prices than consumers, and can therefore implement price discrimination strategies in setting service prices. Due to the disadvantage in acquired …


Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng 2022 1.College of Computer Science, Guangdong University of Petrochemical Technology, Maoming 525000, China;

Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng

Journal of System Simulation

Abstract: To solve the difficulty in job scheduling in the complex and transient multi-user, multi-queue, and multi-data-center cloud computing environment, this paper proposed a job scheduling method based on deep reinforcement learning. A system model of cloud job scheduling and its mathematical model were built, and an optimization goal consisting of transmission time, waiting time, and execution time was obtained. A job scheduling algorithm based on deep reinforcement learning was designed, and its state space, action space, and reward function were given. A simulated cloud job scheduler was designed and developed, and simulated scheduling experiments were conducted on it. The …


Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang 2022 1.School of Computer Science, Chengdu Normal University, Chengdu 611130, China;2.Key Laboratory of Interior Layout Optimization and Security, Institutions of Higher Education of Sichuan Province, Chengdu Normal University, Chengdu 611130, China;

Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang

Journal of System Simulation

Abstract: Crowd evacuation in a multi-floor environment is a popular social concern, while the stagnation phenomenon easily occurs when simulating a multi-floor complex environment with the traditional social force model. Therefore, An improved social force model is proposed by a wavelet neural network, and a new multi-floor evacuation model is built. In the model, a pedestrian's direction of movement is obtained by the field model, which is used as the self-driving direction of the social force model. Meanwhile, the evaluation indexes of the exit congestion degree, path congestion degree, and average velocity in a multi-floor environment are given, and a …


Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao 2022 School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;

Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao

Journal of System Simulation

Abstract: To classify pixels of natural landform edges in remote sensing images, this paper proposes a multi-channel fusion model and a decoder-side module model both integrating an edge detection module. The edge detection module takes the Canny operator as the base to perform closed operations and mean filtering, as a result of which accurate image edges can be achieved. Based on DeepLabV3+, the semantic segmentation network is connected with an edge planning module in parallel at encoder and decoder sides respectively. The experimental results show that the two improved networks can achieve a better segmentation effect on a high-resolution natural …


Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su 2022 1.School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China;2.Guangxi Key Laboratory of Automatic Detection Technology and Instruments, Guilin 541004, China;

Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su

Journal of System Simulation

Abstract: The picket fence effect of fast Fourier transform (FFT) restricts the demodulation performance of the underwater acoustic(UWA) communication systemusing orthogonal frequency division multiplexing (OFDM). To solve this problem, we propose a demodulation algorithm based on ZoomFFT. Specifically, the received signal is processed by frequency shifting and downsampling forarefined spectrum, which improves the spectralresolution and weakens the picketfence effect.Meanwhile, the channel response is refined, and the channel equalization algorithm is constructed on the basis of the minimum mean square error (MMSE) principle to eliminate the channel influence. Simulations show that the performance of underwater acoustic OFDM demodulation algorithm based on …


Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, zhenhuan Ye 2022 1.College of Engineering, Zunyi Normal University, Zunyi 563006, China;

Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye

Journal of System Simulation

Abstract: An algorithm is proposed to greatly improves the face detection rate and ensures the accuracy by adjusting the size of input images, expanding the minimum face size, and reducing the scaling ratio between layers of the detection window. The detection efficiency of this algorithm is 18 times higher than that of the original MTCNN. By building a new CNN structure model for the detection of eyes and mouths, we can achieve network detection accuracy of 95.6%. The proposed network is cascaded with the original MTCNN to continue classifying and locating the eyes and mouth in the formerly …


Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li 2022 College of Computer Science & Technology, Xi'an University of Science and Technology, Xi'an 710054, China;

Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li

Journal of System Simulation

Abstract: It is an important pretreatment of a virtual orthodontic system to accurately segment teeth from a dental model. In the present methods, all patches are computed directly. To solve this problem, this paper proposes a segmentation line detection method based on target region constraint, which narrows down the detection range to the area around the actual segmentation line. In this method, the cutting plane and the cutting line are automatically formed according to the positions of seed points. The detection range is determined by the search for the position with the greatest negative curvature on the cutting line. The …


Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren 2022 1.Beihang University, Beijing, 100191, China;2.Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, 100191, China;

Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren

Journal of System Simulation

Abstract: To accommodate the dark and unstructured underwater working environment, the near-body pressure distribution characteristics of a bionic robot fish undulating in near wall region is studied. The feasibility of using artificial lateral line(ALL) to estimate the wall effect and flow field parameters is analyzed theoretically. A CFD(computational fluid dynamics) coupled solution model for near-body pressure simulation of a bionic robotic fish swimming near the wall is established and a near-body pressure data extraction and processing method is proposed. The effect of the wall clearance, inlet flow velocity and strouhal number (St) on the fish near-body pressure distribution …


Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu 2022 1.Beihang University, Beijing 100191, China;2.Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education, Beijing 100191, China;

Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu

Journal of System Simulation

Abstract: In order to resolve the nonlinear and ill-posed inverse problem of the image reconstruction of electrical capacitance tomography (ECT), an image reconstruction algorithm based on one-dimensional convolutional neural network (1D CNN) is presented. The nonlinear mapping relationship between the independent measurement value of ECT system and the gray value of reconstructed image is established by 1D CNN. Six typical flow regimes with random distribution are obtained by the finite element simulation software and a 1D CNN is successfully trained. Simulation and static experiments are carried out and the reconstructed images using linear back projection, Landweber iterative algorithm and 1D …


Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao 2022 1.State Grid Hebei Electric Power Co. Ltd. Training Center, Shijiazhuang, 050023, China;

Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao

Journal of System Simulation

Abstract: Social learning is defined as the process that consumers use online reviews to fetch more precise information about product quality.Consequently, consumers would be more likely to purchase the product if the product quality learned was higher than their expectation, reference point effect named.To understand the impact of this effect in social learning on a firm's product decisions, we built a multi-agent model to solve the problem through simulation. According to the results, the reference point effect has a negative influence on the firm. The firm has to higher the product quality and price and therefore loses some profits. …


Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei 2022 1.School of Business Administration, South China University of Technology, Guangzhou 510640, China;

Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei

Journal of System Simulation

Abstract: In order to find out the source of VOCs(volatile organic compounds) emission and diffusion to the target area, and prevent the target area from further pollution, this paper propose an analytical method of VOCs hazard causes in related areas based on object function Petri net. The net structure describes the relationship between the potential pollution sources and the target area, and the operation of the net system reflects the change of VOCs hazard degree in the target area, and the calculation of hazard degree is integrated into the operation of the Petri net system. Through the actual case study, …


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