Research On Digital Twin Credibility Assessment Process And Index,
2023
Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China;
Research On Digital Twin Credibility Assessment Process And Index, Fan Yang, Ping Ma, Wei Li, Ming Yang
Journal of System Simulation
Abstract: With the application field expansion of digital twin technology, in order to meet the requirement of digital twin credibility and promote the digital twin credibility assessment, the credibility assessment process and indicators of digital twin are researched. The development process of digital twin is analyzed and the construction method of flexible multi-layer digital twin credibility assessment process model based on IDEF0 is proposed. Two index systems, process-stage-activity layers(P-S-A) and activity-element-feature layers(A-E-F),are proposed to solve the problems of defect backtracking and evaluation of complex objects. Several examples of index system are given.
Research On Real-Time Gesture Classification Algorithm Based On Imu And Semg Mixed Signals,
2023
1.School of Automation, Beijing Information Science and Technology University, Beijing 100192, China;
Research On Real-Time Gesture Classification Algorithm Based On Imu And Semg Mixed Signals, Tao Wang, Yingnian Wu, Rui Yang, Yueying Sun
Journal of System Simulation
Abstract: In order to improve the gesture classification accuracy of surface electromyography (sEMG), the mixed signal of attitude and sEMG is collected by inertial measurement unit (IMU) and EMG sensor, and a GRU-BiLSTM double-layer network real-time gesture classification algorithm is proposed. The first layer of gated recurrent unit (GRU) detects the mutation point of the initial mixed signal though energy combination operator feature and locates the starting point of the dynamic data. The second layer Bi-directional long short term memory (BiLSTM) classifies the motion state mixed signal into 10 gestures in two directions though energy kernel phase map feature. …
Machine Learning-Based Simulation Research Of On-Line Subway Pedestrian Flow Control,
2023
1.Tianjin University of Technology, Tianjin 300000, China;
Machine Learning-Based Simulation Research Of On-Line Subway Pedestrian Flow Control, Jiajie Shi, Peng Yang, Yannan Pi
Journal of System Simulation
Abstract: In recent years, a large number of digital experiments have been carried out in the field of space launch, such as digital design verification, digital joint training and simulation training, and rocket-ground joint simulation evaluation, all of which involve the space launch information visualization. Through virtual reality technology, system simulation technology, data visualization technology, etc., on the basis of multi-thread, multi-module architecture design idea, and message queue system interaction mode, the space launch visual simulation analysis technology platform with functions of data management, scenario management, calculation management, and script management is constructed. The application cases of visual simulation analysis …
Takeout Distribution Routes Optimization Considering Order Clustering Under Dynamic Demand,
2023
Transportation Engineering College, Dalian Maritime University, Dalian 116026, China;
Takeout Distribution Routes Optimization Considering Order Clustering Under Dynamic Demand, Houming Fan, Fushan Xian, Huaiqi Wang
Journal of System Simulation
Abstract: Takeout distribution optimization includes order allocation and route planning. Aiming at dynamic order and rider position change, with the goal of minimizing the overtime order proportion, average delivery time and average travel distance,a two-stage mathematical model is established based on the idea of pre-optimization and dynamic adjustment. In the pre-optimization stage, an improved variable neighborhood search algorithm is designed to obtain the initial distribution scheme. In the dynamic adjustment stage, a periodic optimization strategy is adopted to transform the problem into a virtual distribution center vehicle problem for solution. In each stage,different clustering methods are used to optimize the …
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment,
2023
Academy of Army Armored Force, Beijing 100072, China;
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Journal of System Simulation
Abstract: The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation …
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources,
2023
1.Graduate School, Space Engineering University, Beijing 101416, China;
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources, Naiyang Xue, Dan Ding, Yutong Jia, Zhiqiang Wang, Yuan Liu
Journal of System Simulation
Abstract: Joint scheduling of heterogeneous TT&C resources as research object, a deep Q network (DQN) algorithm based on reinforcement learning is proposed. The characteristics of the joint scheduling problem of heterogeneous TT&C resources being fully analyzied and mathematical language being used to describe the constraints affecting the solution, a resource joint scheduling model is established. From the perspective of applying reinforcement learning, two neural networks with the same structure and the action selection strategies based onεgreedy algorithm are respectively designed after Markov decision process description, and DQN solution framework is established. The simulation results show that DQN-based heterogeneous …
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit,
2023
College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit, Yafei Mei, Ying Liao, Kejie Gong, Xingyu Zheng
Journal of System Simulation
Abstract: For relative motion spacecraft, when the actuator fails and the external disturbance and system uncertainty occur simultaneously, a finite-time fault-tolerant control method is proposed on the basis of the robustness of sliding mode control. A single-rigid spacecraft integrated attitude-orbit model is established based on Lie Group SE(3), and the relative motion spacecraft error dynamic equation is derived in exponential coordinates. A class of non-singular fast terminal sliding surface is designed, and the equivalent adaptive method is adopted to design the controller to estimate and compensate the total disturbance. The proposed fault-tolerant control algorithm can be independent from fault diagnosis …
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network,
2023
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network, Hong Sun, Yuxiang Zhang, Yuelan Ling
Journal of System Simulation
Abstract: Since the first application of convolutional neural network to the field of super-resolution image reconstruction (super-resolution convolutional neural network, SRCNN), a large number of studies have proved that deep learning can improve the effect of image reconstruction. Aiming at the too many parameters in the image super-resolution network and the insufficient utilization of image features resulting in less available high-frequency information, a loss extraction feedback attention network (LEFAN) is proposed to reuse parameters in a circular way and increase the reuse of low-resolution image features to capture more high-frequency information. The loss caused in the reconstruction process is extracted …
Simulation Of Occluded Pedestrian Detection Based On Improved Yolo,
2023
Liangjiang International College, Chongqing University of Technology, Chongqing 401135, China;
Simulation Of Occluded Pedestrian Detection Based On Improved Yolo, Nan Xiang, Lu Wang, Chongliu Jia, Yuemou Jian, Xiaoxia Ma
Journal of System Simulation
Abstract: Aiming at the high missed detection rates and low accuracy of existing YOLO for occlusion and multi-scale pedestrian targets, an improved pedestrian detection algorithm is proposed. YOLO backbone is modified to enhance the capabilities of cross-scale feature extraction. To increase thepedestrian feature fusion capabilities of different scales, a spatial pyramid pooling module and two attention mechanisms are introduced at different positions in front of YOLO layers. Aiming at the detection performance degradation due to the extreme complexity of network module and to improve the model training efficiency, the network structure is pruned according to the actual …
Evacuation Dynamics Research Based On Evolutionary Game Theory,
2023
School of Civil Engineering and Transportation, Hebei University of Technology, Tianjin 300401, China;
Evacuation Dynamics Research Based On Evolutionary Game Theory, Qiaoru Li, Jinxiu Yan, Xiaoyong Tian, Kun Li, Xia Li
Journal of System Simulation
Abstract: In order to study the impact of individual cooperative behavior on the overall pedestrian evacuation efficiency, combined with cellular automata and social force model, the co-evolution of evacuation system dynamics and "cooperative behavior" is studied, and an evacuation dynamics research method based on evolutionary game theory is proposed. The cellular automata model is used as the basic simulation framework, and the social force model is used to represent the psychological repulsion among the practitioners. The evacuation individual strategy is updated through evolutionary game. The simulation results show that when the game gain coefficient exceeds a certain threshold, the …
Efficient Hmm Map Matching Method Using R-Tree And Trajectory Segmentation,
2023
1.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China;
Efficient Hmm Map Matching Method Using R-Tree And Trajectory Segmentation, Yanjiao Song, Jiayue Zhou, Longhao Wang, Jing Wu, Rui Li, Xiaoping Rui
Journal of System Simulation
Abstract: In view of the incapability of traditional methods to efficiently process massive trajectory data, an improved HMM (hidden-Markov model) map matching algorithm is proposed. Spatial index for road networks is established through R-tree spatial index. GPS trajectory data are segmented based on the position change rates of trajectory points. R-tree index is used to quickly determine the candidate road section that sub-trajectories belong to, and the key points of the sub-trajectories instead of the entire sub-trajectories are selected to judge which road the sub-trajectories should be matched with. The map matching of each sub-trajectory is carried out on …
Computation Offloading Strategy Based On Stackelberg Game And Drl,
2023
School of Software, South China Normal University, Foshan 528225, China;
Computation Offloading Strategy Based On Stackelberg Game And Drl, Xianwei Zhou, Qixu Gong, Songsen Yu
Journal of System Simulation
Abstract: To achieve the optimal computation offloading strategy for two kinds of MEC users in 5G hybrid private network, Stackelberg game is used to build the model of the competition for MEC server resources of two kinds of users, andthe strategies of complete information game and partially incomplete information game are researched respectively. It is proved that there is only one Nash equilibrium solution in the complete information scenario. In the incomplete information scenario, the environment is modeled as POMDP, and a two-stage deep reinforcement learning(TSDRL) is proposed to obtain the optimal computation offloading strategy. Simulation results show the proposed …
A Highly Efficient Broadband Multi-Functional
Metaplate,
2023
King Abdullah University of Science and Technology
A Highly Efficient Broadband Multi-Functional Metaplate, Azhar Javed Satti, Muhammad Ashar Naveed, Isma Javed, Nasir Mahmood, Muhammad Zubair, Muhammad Qasim Mehmood, Yehia Massoud
Department of Electrical and Computer Engineering: Faculty Publications
Due to the considerable potential of ultra-compact and highly integrated meta-optics, multi-functional metasurfaces have attracted great attention. The mergence of nanoimprinting and holography is one of the fascinating study areas for image display and information masking in meta-devices. However, existing methods rely on layering and enclosing, where many resonators combine various functions effectively at the expense of efficiency, design complication, and complex fabrication. To overcome these limitations, a novel technique for a tri-operational metasurface has been suggested by merging PB phase-based helicity-multiplexing and Malus's law of intensity modulation. To the best of our knowledge, this technique resolves the extreme-mapping issue …
Hangprinter For Large Scale Additive Manufacturing Using Fused Particle Fabrication With Recycled Plastic And Continuous Feeding,
2023
Western University
Hangprinter For Large Scale Additive Manufacturing Using Fused Particle Fabrication With Recycled Plastic And Continuous Feeding, Ravneet S. Rattan, Nathan Nauta, Alessia Romani, Joshua Pearce
Electrical and Computer Engineering Publications
The life cycle of plastic is a key source of carbon emissions. Yet, global plastics production has quadrupled in 40 years and only 9 % has been recycled. If these trends continue, carbon emissions from plastic wastes would reach 15 % of global carbon budgets by 2050. An approach to reducing plastic waste is to use distributed recycling for additive manufacturing (DRAM) where virgin plastic products are replaced by locally manufactured recycled plastic products that have no transportation-related carbon emissions. Unfortunately, the design of most 3-D printers forces an increase in the machine cost to expand for recycling plastic at …
Machine Learning Applications In Malware Classification: A Metaanalysis Literature Review,
2023
Dakota State University
Machine Learning Applications In Malware Classification: A Metaanalysis Literature Review, Tjada Nelson, Austin O'Brien, Cherie Noteboom
Research & Publications
With a text mining and bibliometrics approach, this study reviews the literature on the evolution of malware classification using machine learning. This work takes literature from 2008 to 2022 on the subject of using machine learning for malware classification to understand the impact of this technology on malware classification. Throughout this study, we seek to answer three main research questions: RQ1: Is the application of machine learning for malware classification growing? RQ2: What is the most common machine-learning application for malware classification? RQ3: What are the outcomes of the most common machine learning applications? The analysis of 2186 articles resulting …
Drone Detection Using Yolov5,
2023
Texas A & M University - Commerce
Drone Detection Using Yolov5, Burchan Aydin, Subroto Singha
Faculty Publications
The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). …
Towards Machine Learning-Based Fpga Backend Flow: Challenges And Opportunities,
2023
Zayed University
Towards Machine Learning-Based Fpga Backend Flow: Challenges And Opportunities, Imran Taj, Umer Farooq
All Works
Field-Programmable Gate Array (FPGA) is at the core of System on Chip (SoC) design across various Industry 5.0 digital systems—healthcare devices, farming equipment, autonomous vehicles and aerospace gear to name a few. Given that pre-silicon verification using Computer Aided Design (CAD) accounts for about 70% of the time and money spent on the design of modern digital systems, this paper summarizes the machine learning (ML)-oriented efforts in different FPGA CAD design steps. With the recent breakthrough of machine learning, FPGA CAD tasks—high-level synthesis (HLS), logic synthesis, placement and routing—are seeing a renewed interest in their respective decision-making steps. We focus …
Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques,
2023
Air Force Institute of Technology
Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton, Richard Dill, Michael R. Grimaila, Douglas Hodson
Faculty Publications
Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of …
Resource Management In Mobile Edge Computing For Compute-Intensive Application,
2023
CUNY Graduate Center
Resource Management In Mobile Edge Computing For Compute-Intensive Application, Xiaojie Zhang
Dissertations, Theses, and Capstone Projects
With current and future mobile applications (e.g., healthcare, connected vehicles, and smart grids) becoming increasingly compute-intensive for many mission-critical use cases, the energy and computing capacities of embedded mobile devices are proving to be insufficient to handle all in-device computation. To address the energy and computing shortages of mobile devices, mobile edge computing (MEC) has emerged as a major distributed computing paradigm. Compared to traditional cloud-based computing, MEC integrates network control, distributed computing, and storage to customizable, fast, reliable, and secure edge services that are closer to the user and data sites. However, the diversity of applications and a variety …
Stand-Up Comedy Visualized,
2023
CUNY Graduate Center
Stand-Up Comedy Visualized, Berna Yenidogan
Dissertations, Theses, and Capstone Projects
Stand-up comedy has become an increasingly popular form of comedy in the recent years and comedians reach audiences beyond the halls they are performing through streaming services, podcasts and social media. While comedic performances are typically judged by how 'funny' they are, which could be proxied by the frequency and intensity of laughs through the performance, comedians also explore untapped social issues and provoke conversation, especially in this age where interaction with artists goes beyond their act. It is easy to see commonalities in the topics addressed in comedians’ work such as relationships, race and politics.This project provides an interactive …
