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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Ma, Yuanyuan Chen, Han Xu, Zhan Zhi, Ruxin Ma, Chunshuai Zheng, Yiyang Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Ministry of Information Industry Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China No.723 Research Institute China State Shipbuilding Corporation Yangzhou China Beijing Information Science and Technology University Beijing China Beijing Institute of Technology Beijing China

ISBN: (纸本)9798331515669

This study examines the secrecy outage performance of uplink transmission within a hybrid cooperative satellite-aerial-terrestrial network (SATN) that integrates radio-frequency (RF) and free-space optical (FSO) technologies. Specifically, in the proposed cooperative SATN, a terrestrial source (S) conveys its information to a satellite receiver (D) with the assistance of an aerial relay (R), while a group of eavesdropping aerial terminals (Eves) attempts to intercept the confidential data. RF and FSO transmission methods are employed over the S-R and R-D links, respectively, both subject to imperfect channel state information (CSI). By considering the randomness of R, D, and Eves, and utilizing a stochastic geometry framework, we investigate the secrecy outage performance of the considered SATN. A closed-form analytical expression for the end-to-end secrecy outage probability is derived. Finally, simulations are conducted to validate the accuracy of the analysis. © 2024 IEEE.

关键词： Stochastic systems

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STGSA:A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 226-238页

作者： Zebing Wei Hongxia Zhao Zhishuai Li Xiaojie Bu Yuanyuan Chen Xiqiao Zhang Yisheng Lv Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the Shandong Key Laboratory of Smart Transportation(Preparation) Shandong Jiao Tong UniversityShanghai 200240China the College of Science China University of PetroleumQingdao 266580China the Department of Transportation Engineering School of Transportation Science and TechnologyHarbin Institute of TechnologyHarbin 150090China IEEE

The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the *** existing frameworks typically utilize separate modules for spatial and temporal correlations ***,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some ***,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between *** overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies ***,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution *** each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting ***,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven ***,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global *** projects the embedding input repeatedly with multiple different ***,the predicted values are generated by stacking several multi-stream *** experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA

关键词： Deep learning graph neural network(GNN) multistream spatial-temporal feature extraction temporal graph traffic prediction

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Multi-Objective fuzzy flexible jobshop of dynamic scheduling optimization based on hybrid-nondominanted sorting algorithm

Multi-Objective fuzzy flexible jobshop of dynamic scheduling...

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IEEE International Conference on Networking, Sensing and control

作者： Wei Shen WeiMin Wu HaoYi Niu The State Key Laboratory of Industrial Control Technolog Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665472449

Multi-objective flexible job-shop scheduling problem is of great significance to improve the efficiency of the production system. However, most studies lack dynamic scheduling experiments. In this paper, a hybrid-nondominated sorting algorithm based on NSGA-II (Non-dominated Sorting Genetic Algorithm) is proposed to optimize problem considering the influence of transportation time window. Co-evolution PSO (Particles Swarm Optimization) based on Cauchy mutation and weight mapping crossover are used to generate new solutions to improve the ability of local search and global detection. The proposed method has better solution with convergence and distributivity. The chromosome is decoded by a dynamic fuzzy greedy interpolation method based on exact time. The algorithm is applied to famous benchmarks to verify the effectiveness of the proposed method in dynamic scene.

关键词： Production systems Interpolation Heuristic algorithms Transportation Dynamic scheduling Sensors Particle swarm optimization

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Magnetic Microrobots Fabricated by Photopolymerization and Assembly

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Cyborg and Bionic systems 2023年第1期4卷 41-46页

作者： Xiyue Liang Yue Zhao Dan Liu Yan Deng Tatsuo Arai Masaru Kojima Xiaoming Liu Key Laboratory of Biomimetic Robots and Systems Ministry of EducationState Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing Advanced Innovation Center for Intelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 182-8585Japan Department of Materials Engineering Science Osaka UniversityOsaka 560-8531Japan

Magnetic soft microrobots have great potential to access narrow spaces and conduct multiple tasks in the biomedical *** now,drug delivery,microsurgery,disease diagnosis,and dredging the blocked blood vessel have been realized by magnetic soft microrobots in vivo or in ***,as the tasks become more and more complex,more functional units have been embedded in the body of the developed magnetic *** magnetic soft microrobots with complex designed geometries,mechanisms,and magnetic orientation are now greatly challenging the fabrication of the magnetic *** this paper,we propose a new method combining photopolymerization and assembly for the fabrication of magnetic soft *** the micro-hand assembly system,magnetic modules with different shapes and materials are firstly arrayed with precise position and orientation ***,the developed photopolymerization system is employed to fix and link these modules with soft *** on the proposed fabrication method,3 kinds of soft magnetic microrobots were fabricated,and the fundamental locomotion was *** believe that the presented fabrication strategy could help accelerate the clinical application of magnetic microrobots.

关键词： Magnetic system precise

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A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services

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Energy and AI 2022年第3期9卷 148-171页

作者： Caizhi Zhang Yuqi Qiu Jiawei Chen Yuehua Li Zhitao Liu Yang Liu Jiujun Zhang Chan Siew Hwa College of Mechanical and Vehicle Engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing400044China College of Automation Chongqing UniversityKey Laboratory of Complex System Safety and ControlMinistry of EducationChongqing UniversityChongqing400044China School of Mechanical Engineering University of Science and Technology BeijingBeijing100083China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou310027China Institute for Sustainable Energy/College of Sciences Shanghai UniversityShanghai 200444China School of Mechanical and Aerospace Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore Sichuan Energy Internet Research Institute Tsinghua UniversityChengdu 610213Sichuan ProvinceChina

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight;hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell,battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.

关键词： Unmanned aerial vehicles(UAVs) Power supply system Fuel cell system Artificial intelligence(AI) Energy management systems

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Resilient observer-based event-triggered control for cyber-physical systems under asynchronous denial-of-service attacks

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Science China(Information Sciences) 2022年第4期65卷 182-196页

作者： Yifang ZHANG Zheng-Guang WU Zongze WU Deyuan MENG State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University School of Automation Guangdong University of Technology Seventh Research Division Beihang University (BUAA) School of Automation Science and Electrical Engineering Beihang University (BUAA)

We develop the resilient observer-based event-triggered control update strategy in this *** is utilized to achieve the input-to-state stability（ISS） of cyber-physical systems（CPSs） when there is an asynchronous denial-of-service（DoS） attack, which is launched by malicious adversaries both on measurement channel and control channel in a random attack strategy. To estimate the unmeasurable states while saving the limited networked bandwidth, an H∞observer-based event-triggered control scheme is first designed to guarantee the ISS of CPSs with economic communication. Moreover, the occurrence of Zeno behavior can be eliminated by providing the existence of a lower positive bound of any two inter-event times. Then, a recursive model of asynchronous DoS attacks is introduced. A resilient control update strategy is proposed and further analyzed to derive the stability criterion of CPSs. At last, a numerical simulation example is given to demonstrate the effectiveness of the introduced control update policy.

关键词： cyber-physical systems input-to-state stability asynchronous DoS attacks H ∞ observer event-triggered control

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ADMM-based Privacy-Preserving Peer-to-Peer Energy Trading Negotiation Mechanism

ADMM-based Privacy-Preserving Peer-to-Peer Energy Trading Ne...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Zhenwei Guo Jiajian Zhu Haoran Li Haibin Zheng Yujue Wang Research Center of Cyber Science and Technology Hangzhou Innovation Institute Beihang University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

The rapid development of demand response management and distributed energy has promoted the development of P2P energy trading mechanisms, making electricity market participants more active. However, how to prevent private information from being reached by malicious agents during P2P negotiation process is a challenging problem. This paper proposes a privacy protection decentralized optimization method for P2P energy trading based on consensus Alternating Direction Method of Multipliers (ADMM) and Partially Homomorphic Encryption (HE). Firstly, the general model of P2P electricity market and the P2P trading negotiation mechanism based on consensus ADMM are introduced. However, under this mechanism, malicious neighbor agents can collude to steal private information. In order to resist collusion attack, a two-party secure computation mechanism between each pair of agents is designed, and the energy amount and price are updated in a secure way without leaking any private information. The privacy-preserving mechanism can find a trade-off between the convergence efficiency and information security. Finally, the function of the privacy protection negotiation mechanism was simulated in terms of convergence performance, impact on social welfare and computational efficiency.

关键词： Privacy Simulation Optimization methods Electricity supply industry Convex functions Peer-to-peer computing Computational efficiency

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Object Pose Estimation Based on Improved YOLOX Algorithm 11

Object Pose Estimation Based on Improved YOLOX Algorithm

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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Zhou, Yanhong Liu, Shan Polytechnic Institute Zhejiang University Hangzhou310015 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

This paper proposes a deep learning method for object recognition and pose estimation only through a single RGB image. We extend the YOLOX algorithm, which has excellent performance in the field of 2D object detection, making it suitable for 6DoF pose estimation scenarios in a natural way. The model is designed to predict the position of key points in the image, which are used to establish the correspondence between the object model and the scene image. After that, the object pose can be obtained by PnP algorithm. In order to obtain labeled data for model training effectively, this paper designs a data augmentation method combining offline expansion and online augmentation, which can improve the generalization ability of the model. The results of experiments on the LINEMOD dataset demonstrate the effectiveness of our method, which is significantly competitive with other methods using similar implementation ideas. © 2022 IEEE.

关键词： Object recognition

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Framework and key Technologies for High-speed Railway Comprehensive Transport Hub 3

Framework and Key Technologies for High-speed Railway Compre...

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3rd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2023

作者： Xiong, Gang Zhang, Wei Liu, Xiaoming Yuan, Zhiming Zhu, Fenghua Zhang, Zundong Chinese Academy of Sciences State Key Laboratory for Multimodal Artificial Intelligence Systems Beijing China North China University of Technology School of Electrical and Control Engineering Beijing China China Academy of Railway Science Communication Signal Research Institute Beijing China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9798350318470

The surge in urban population density in China has underscored the vital role of high-speed rail and subway systems in urban transit. Comprehensive transportation hubs, notably high-speed rail passenger terminals, have emerged as linchpins for seamless multimodal transit both within and beyond urban centers. China's railway sector vigorously champions the innovative concept of "station-city integration"and has articulated a forward-looking "16-word policy"for modern railway stations: "Seamless integration, environmental friendliness, economic viability, and intelligent accessibility". The judicious allocation of resources and the augmentation of coordination and control capabilities within comprehensive transportation hubs are imperative for the harmonious evolution of urban transit. The implementation of intelligent control systems for transportation hubs has emerged as a pivotal area of research. This study delves into the framework and critical technologies for high-speed railway comprehensive transport hubs, encompassing various components and their intricate interplay, including transport modalities, infrastructure, travelers, environmental factors, and information systems, thus forming a prototypical cyber-physical-social system. Addressing the prevalent and pressing imperative for the advancement of "station-city integration"high-speed railway comprehensive transport hubs, this research endeavor aims to surmount bottleneck challenges and refine the oversight of passenger flows at high-speed rail terminals. The findings hold noteworthy theoretical import and portend promising practical applications. © 2023 IEEE.

关键词： Integration

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