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

作者： Ma, Yuxuan Shen, Yuanjie Sun, Jinghu Zhang, Xiuyin Cui, Guolong Guo, Shisheng South China University of Technology School of Electronic and Information Engineering Guangzhou China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Quzhou China

ISBN: (纸本)9798331515669

Millimeter-wave (MMW) radar has been widely applied in road traffic target detection and tracking. However, targets and strong reflective surfaces such as static road guardrails can lead to multipath ghosts during the propagation of electromagnetic (EM) waves in these complex scenarios. The multipath phenomenon causes interference and many errors. To reduce the probability of false alarms for real target detection, we propose a method based on radar point clouds for multipath ghost recognition and suppression. This method utilizes a multipath propagation geometric model and reflection boundary information to obtain the Doppler velocity of multipath ghosts and implement velocity filtering. Furthermore, experimental results shows that our algorithm can efficiently recognize and suppress multipath ghosts in complex road scenarios with multiple targets, significantly reducing the false alarm rate of real target detection. © 2024 IEEE.

关键词： Guard rails

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Optimal Production Capacity Matching for Blockchain-Enabled Manufacturing Collaboration With the Iterative Double Auction Method

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 550-562页

作者： Ying Chen Feilong Lin Zhongyu Chen Changbing Tang Cailian Chen the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University the School of Computer Science and Technology Zhejiang Normal University IEEE the College of Physics and Electronic Information Engineering Zhejiang Normal University the Department of Automation Shanghai Jiao Tong University

The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other. In this article, a blockchain-enabled manufacturing collaboration framework is proposed, with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P) collaboration. First, a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain. Second, an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants. Third, a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information. It facilitates automation of the matching process while protecting users' privacy via blockchainbased smart contracts. Finally, simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4% compared to the Bayesian game-based approach, makes all participants profitable,and achieves 90% fairness of enterprises.

关键词： Blockchain iterative double auction manufacturing collaboration production capacity matching

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Event-Triggered Fixed-Time Adaptive Fuzzy Control for Nontriangular Nonlinear Systems With Unknown Control Directions

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2397-2409页

作者： Cui, Guozeng Xu, Hui Yu, Jinpeng Ma, Qian Jian, Muwei Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China Qingdao University School of Automation Qingdao266071 China Nanjing University of Science and Technology School of Automation Nanjing210094 China Shandong University of Finance and Economics School of Computer Science and Technology Jinan250014 China

This article focuses on the problem of fixed-time adaptive fuzzy control for a class of nontriangular nonlinear systems with unknown control directions under the event-triggered framework. To tackle the algebraic loop issue arising from the nontriangular structure, the property of the fuzzy logic system is employed. The command filter and the error compensation signals, which have the feature of fixed-time convergence, are constructed to eliminate the 'explosion of complexity' phenomenon and the effect of filtered error, respectively. By integrating the Nussbaum gain technique into the relative threshold-based event-triggered mechanism, a singularity-free fixed-time adaptive fuzzy control scheme is devised to ensure that the closed-loop system is practically fixed-time stable, and the tracking error converges to a small region near the origin in a fixed time. Finally, simulation examples are presented to demonstrate the effectiveness and superiority of the proposed fixed-time control algorithm. © 2020 IEEE.

关键词： Backstepping

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ACbot:an IIoT platform for industrial robots

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Frontiers of Computer science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

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Constructing Semantical Structure by Segmentation Integrated Video Embedding for Temporal Action Detection

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 5980-5992页

作者： Zhao, Zixuan Liu, Shuming Zhao, Chengze Zhao, Xu Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China King Abdullah University of Science and Technology Computer Science Program Thuwal23599 Saudi Arabia

Video embedding is the pivot in Temporal Action Detection (TAD). Once the video embedding can robustly capture the essence of actions and perceive activities in complex scenes, the TAD model can more accurately localize action boundaries. Currently, video embedding is typically based on rule-based pixel convolution or cube-based transformer, wherein structured semantic information is intertwined, leading to the submergence of crucial spatial semantic information, such as the intrinsic motion of key semantic objects and interactions among semantic objects. To address these limitations, it is imperative to explore alternative approaches. With the remarkable performance of general semantic segmentation models in visual representation, we introduce the general segmentation model SEEM into the video embedding paradigm, constructing a semantically structured representation from perceptual semantics to cognitive semantics. To more effectively utilize SEEM for structured video representation, we designed the Semantic Adapter (Sem-Adapter) as a bridge to connect the two models. Firstly, we design a Self-Motion Module (SMM) to pay attention to the self-motion of key semantic regions. Secondly, we propose a Mutual Relation Module (MRM) to construct the interactions between semantic regions. Extensive experiments on ActivityNet-1.3, THUMOS-14 and EPIC-Kitchens-100 reveal that our method significantly outperforms state-of-the-art methods under the same input modality, and our method improves the average mAP from 60.6% to 64.2% on THUMOS-14 with the same backbone. The code is available on https://***/shouxiaozixuan/semtad. © 1991-2012 IEEE.

关键词： Semantic Segmentation

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Transmit Beamforming for ISAC Based on Space-Time Coding in MU-MIMO Scenario

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IEEE Wireless Communications Letters 2025年第6期14卷 1678-1682页

作者： Huang, Penghui Luo, Kai Chen, Da Peng, Wei Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Sun Yat-sen University School of Electronics and Communication Engineering Shenzhen510275 China

Integrated sensing and communication (ISAC) system utilizes multi-antenna arrays to transmit integrated signals, enabling multi-target sensing and simultaneous communication with multiple communication users (CUs). This requires the transmit signal to have sufficient degrees of freedom (DoF) for sensing and a high communication rate for effective communication. However, the DoF of the transmit signal is limited by the quantity of uncorrelated communication symbol streams (CSSs) in the ISAC system. To address this limitation, we employ space-time coding (STC) to extend CSSs, which not only provides additional DoF for sensing but also offers diversity gain for communication. Moreover, we optimize the transmit beampattern while ensuring that the signal-to-interference-plus-noise ratio (SINR) for each CU remains above a specified threshold. Consequently, we formulate an optimization problem with rank constraints and derive a suboptimal solution. The simulation results demonstrate that the proposed method achieves a better beampattern and a higher communication rate compared to previous work. © 2025 IEEE. All rights reserved.

关键词： Beamforming

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GAN-IVDS: An Intrusion Detection System for Intelligent Connected Vehicles Based on Generative Adversarial Networks 8

GAN-IVDS: An Intrusion Detection System for Intelligent Conn...

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8th International Conference on Data science in Cyberspace, DSC 2023

作者： Chen, Xiansen Xiao, Kun Luo, Lei Li, Yun Chen, Lirong School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Guangdong Weichen Information Technology Co. Ltd Dongguan China

ISBN: (纸本)9798350331035

This paper proposes an anomaly detection algorithm based on Generative Adversarial Networks (GANs) for intrusion detection in Intelligent Connected Vehicles (ICVs). To address the imbalance between normal network traffic and attack traffic in vehicular networks, as well as the difficulty in collecting attack data, we train the neural network solely with normal traffic. We employ the Gini index to perform data dimensionality reduction, selecting 34 features with the highest purity of information and enhancing model training speed via normalization functions. Our algorithm combines the generative capabilities of GANs and the reconstructive power of autoencoders, detecting abnormal network data by learning the distribution of normal network data, thus eliminating the need to analyze packet payloads and safeguarding user privacy. We also develop a vehicular network traffic data collection scheme to collect network traffic data from ICVs. Experimental results indicate that our algorithm demonstrates high accuracy in detecting anomalous network traffic in ICVs, with an accuracy rate of 94.9%. © 2023 IEEE.

关键词： Anomaly Detection Algorithm Generative Adversarial Networks Intelligent Connected Vehicles Intrusion Detection Network Security

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Combustion characteristics of millimeter-sized aluminum particles in fluidized bed under various O_(2)/CO_(2)/H_(2)O atmospheres Author links open overlay panel

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Particuology 2024年第8期91卷 315-322页

作者： Jialing Zhou Rui Zhang Dong Liu Key Laboratory of Thermal Control of Electronic Equipment Ministry of Industry and Information TechnologyNanjing210094China Advanced Combustion Laboratory School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing210094China

Aluminum is an attractive alternative fuel,but it burns very inefficiently due to the formation of a dense Al_(2)O_(3)layer which prevents O_(2)from diffusion to the surface of Al *** previous experiments,the combustion of millimeter-sized Al(mAl)particles in the fluidized bed has achieved a substantial increase in the combustion efficiency,but further improvements are still *** this study,the effects of reaction atmosphere on the fluidized combustion of mAl particles were *** experiments with different O_(2)/H_(2)O/CO_(2)concentrations were *** experimental results indicate that the combustion efficiency of mAl particles in fluidized bed increases as the mole fraction of O_(2),H_(2)O or CO_(2)increases,and the highest combustion efficiency can reach 38.7%.After the analysis of the oxide film on the surface of aluminum particles,it was found that it is easier to generate the unstableθ-Al_(2)O_(3)under CO_(2)atmosphere,and it is easier to generate the unstableγ-Al_(2)O_(3)andθ-Al_(2)O_(3)under H_(2)O *** unstable Al_(2)O_(3)film is more likely to be abraded in the fluidized bed,which leads to the effective improvement of the combustion efficiency.

关键词： Al combustion Fluidized bed Atmosphere Combustion efficiency

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Coherence-protected operations in hybrid superconducting circuit-magnon system

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Chinese Physics B 2025年第3期34卷 251-257页

作者： Le-Tian Zhu Xing-Yu Zhu Zhu-Cheng Yue Tao Tu Chuan-Feng Li Key Laboratory of Quantum Information Chinese Academy of SciencesUniversity of Science and Technology of ChinaHefei 230026China School of Mechanical and Electronic Engineering Suzhou UniversitySuzhou 234000China Hefei National Laboratory University of Science and Technology of ChinaChinese Academy of SciencesHefei 230088China

Hybrid systems consisting of superconducting circuits and magnon systems are a promising platform for quantum ***,realizing high-fidelity magnon state preparation and manipulation remains an outstanding challenge due to the complexity of interactions and noise sources in hybrid ***,we propose a coherence-preserving magnon state manipulation *** engineering a superconducting-magnon coupling pulse and combining it with dynamical decoupling pulses,we design a composite pulse *** demonstrate the manipulation and preparation of non-classical states of magnons with a fidelity of up to 98%under realistic *** designs significantly improve the fidelity of manipulation and robustness to noise in hybrid systems compared to existing *** results pave the way for practical applications of quantum magnonics platforms.

关键词： circuit QED quantum information with hybrid systems entanglement production

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Detection and Navigation of Unmanned Vehicles in Wooded Environments Using Light Detection and Ranging Sensors

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Sensors and Materials 2023年第11期35卷 3637-3654页

作者： Zhang, Zhiwei Jhang, Jyun-Yu Lin, Cheng-Jian School of Electronic Information Engineering Hebei University of Technology Tianjin300401 China Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404 Taiwan Department of Computer Science & Information Engineering National Chin-Yi University of Technology Taichung411 Taiwan

With the advancement of automatic navigation, navigation control has become an indispensable core technology in the movement of unmanned vehicles. In particular, research on navigation control in outdoor wooded environments, which are more complex, less controlled, and more unpredictable than indoor environments, has received widespread attention. To realize the movement control and obstacle avoidance of unmanned vehicles in unknown environments, in this study, we use light detection and ranging (LiDAR) sensors to sense the surrounding environment. By plane meshing the point cloud reflected from LiDAR, we can instantly establish feasible regions. At the same time, using the artificial potential field algorithm, a stable obstacle avoidance and navigation path is planned for use in an unknown environment. In an actual woods navigation experiment to evaluate our proposed LiDAR detection method, we used an independently developed unmanned vehicle with Ackermann steering geometry. Experimental results indicate that the proposed method can effectively detect obstacles. The accuracy requirement is within 30 cm from the navigation target, and the experimental results show that the average navigation success rate of the proposed method is as high as 85%. The experimental results demonstrate that the system can stably and safely navigate in scenarios with different unknown environments. © MYU K.K.

关键词： Navigation

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