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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Dong, Guanzhan Xu, Weipeng Gao, Kuidong College of Mechanical and Electronic Engineering Shandong University of Science and Technology Qingdao266590 China State Key Laboratory of Intelligent Coal Mining and Strata Control Shanghai China

ISBN: (纸本)9789819626243

Aiming at the mechanical continuous operation of bauxite mining process, firstly, an improved scheme of cutting bauxite with an 8-pole motor shearer is proposed, which is practical and feasible, and a 3D model is established in Solid Edge. Secondly, considering the higher meshing frequency of high-speed gear in the cutting part, the meshing characteristics under different loads were investigated by MASTA software, and the laws of contact stress, meshing dislocation and trans-mission error were obtained. Finally, the vibration displacement of one axis is obtained in view of the significant influence of individual order energy on the vibration of the shell under rated working conditions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bauxite deposits

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Seeking Secure Synchronous Tracking of Networked Agent Systems Subject to Antagonistic Interactions and Denial-of-Service Attacks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1309-1320页

作者： Li, Weihao Shi, Lei Shi, Mengji Yue, Jiangfeng Lin, Boxian Qin, Kaiyu University of Electronic Science and Technology of China School of Aeronautics and Astronautics Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China Henan University School of Artificial Intelligence Zhengzhou450046 China

Inspired by the group phenomenon of biological populations in nature, swarm intelligence has been derived and has further advanced the research of coordinated control of networked agent systems (NASs). With this in mind, this article delves into the problem of secure synchronous tracking control for high-order NASs subject to antagonistic interactions, particularly under the threat of denial-of-service (DoS) attacks. First, a novel distributed secure control scheme is crafted to address the complex dynamics of NASs that encompass both cooperative and antagonistic interactions among agents. This scheme is pivotal as it enables follower agents to synchronize their tracking with the leader agent, even amidst the disruptive influence of DoS attacks, transcending the conventional bipartite tracking consensus approach. Subsequently, a dynamic, time-varying closed-loop system is generated, which is intrinsically linked to the intermittent nature of DoS attacks, characterized by periods of dormancy and activity. Based on the infinite matrix product convergence analysis method, some essential algebraic conditions are formulated, which hinge on the parameters of DoS attacks, the underlying network structure, and the gain of the controller. These conditions are critical for guaranteeing the attainment of robust synchronous tracking. Finally, some numerical simulation examples are provided to verify the effectiveness of the proposed secure synchronous tracking control scheme for high-order NASs with signed networks. That is, all followers are able to achieve synchronous tracking of the leader when the corresponding topology, as well as control parameter conditions, are satisfied, and the opposite is not possible. © 2020 IEEE.

关键词： Swarm intelligence

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Dim-light image processing strategy rooted in improved dual-branch generative adversarial network

Dim-light image processing strategy rooted in improved dual-...

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2024 International Conference on Image Processing and Artificial Intelligence, ICIPAl 2024

作者： Li, keyi Wei, Zongshou Key Laboratory of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510681514

Images taken in dim lighting conditions usually suffer from drawbacks such as weak contrast along with unwanted interference. As a solution to this issue, this paper suggests a dim-light image processing strategy rooted in an improved dual-branch adversarial generative model. This method utilizes a generator network that combines a dim-light processing module and an image segmentation module, along with a patch discriminator network, trained using an adversarial loss function. The experiments demonstrate that the suggested approach for improving low-light image quality produces visually more captivating results when applied to real-world datasets. Moreover, it surpasses existing methods in terms of both preserving image structure and reducing noise. © 2024 SPIE.

关键词： Generative adversarial networks

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Swarm-Based Dynamic Coverage of Multi-ASV Systems in the Presence of Measurement Noises

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7237-7250页

作者： Liu, Lu Jiao, Shijian Han, Bing Li, Tieshan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China Shanghai Ship and Shipping Research Institute National Engineering Research Center of Ship & Shipping Control System Shanghai200135 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper is concerned with the dynamic coverage of multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles, limited communication distance, and measurement noises. A modular control method including planning, guidance, and control is proposed. At the planning level, a swarm-based dynamic coverage strategy is developed to achieve the coverage of a given domain. Both the collision avoidance and connectivity preservation issues are solved by using artificial potential fields. At the kinematic level, novel adaptive line-of-sight guidance laws are presented based on cascade extended state observers (CESOs), such that accurate guidance signals are given by compensating for time-varying sideslip angle and suppressing measurement noises. At the kinetic level, two CESOs are developed to estimate the internal model uncertainties and external environmental disturbance, and antidisturbance kinetic control laws are designed subsequently. The proposed CESOs overcome the noises sensitivity problem of classical observers, and thus facilitate the practical implementation under measurement noises. The input-to-state stability of the closed-loop system is confirmed by the Lyapunov theory and cascade stability theory. Simulation and hardware-in-the-loop experiment results are provided to demonstrate the effectiveness of the proposed swarm-based dynamic coverage method. © 1967-2012 IEEE.

关键词： Velocity measurement

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Broadcast Gossip Algorithm for Nash Equilibrium Seeking of Nonaggregative Games

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2444-2452页

作者： Wang, Dong Wu, Feiyue Xu, Xiaopeng Wen, Changyun Lian, Jie Zhou, Jun Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian116024 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore Xuzhou Heavy Machinery Company Ltd. Xuzhou221600 China

In this article, we focus on seeking the Nash equilibrium (NE) of nonaggregative games over a directed communication network. An asynchronous broadcast-based gossip algorithm is proposed, where each player broadcasts its own decision and estimates of other players' decisions to its out-neighbors. Then, the neighboring players update its respective decisions using its independent stepsize and estimates of other players' decisions by weighting its own and the received decision estimates from $(0,\,1)$. The almost surely convergence of the proposed algorithm with the diminishing stepsizes is presented by using a lemma and the property of the Kronecker product. Furthermore, the expected error bound between the NE and decisions for the proposed algorithm with constant stepsizes is presented with the increasing active probability of each player. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed algorithm and the convergence rate comparison. © 2020 IEEE.

关键词： Heuristic algorithms

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Ozone oxidation of 4H-SiC and flat-band voltage stability of SiC MOS capacitors

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Chinese Physics B 2022年第11期31卷 500-509页

作者： Zhi-Peng Yin Sheng-Sheng Wei Jiao Bai Wei-Wei Xie Zhao-Hui Liu Fu-Wen Qin De-Jun Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116024China State Key Laboratory of Materials Modification by Laser Ionand Electron Beams(Ministry of Education)Dalian University of TechnologyDalian 116024China

We investigate the effect of ozone(O_(3))oxidation of silicon carbide(SiC)on the flat-band voltage(Vfb)stability of SiC metal–oxide–semiconductor(MOS)*** SiC MOS capacitors are produced by O_(3)oxidation,and their Vfbstability under frequency variation,temperature variation,and bias temperature stress are *** ion mass spectroscopy(SIMS),atomic force microscopy(AFM),and x-ray photoelectron spectroscopy(XPS)indicate that O_(3)oxidation can adjust the element distribution near SiC/SiO_(2)interface,improve SiC/SiO_(2)interface morphology,and inhibit the formation of near-interface defects,*** addition,we elaborate the underlying mechanism through which O_(3)oxidation improves the Vfbstability of SiC MOS capacitors by using the measurement results and O_(3)oxidation kinetics.

关键词： SiC MOS capacitors ozone oxidation bias temperature instability Deal-Grove model

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Antisymmetry-breaking-coupling–enhanced sensing of quantum reservoirs

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Physical Review A 2024年第1期110卷 012613-012613页

作者： Ji-Bing Yuan Zhi-Min Tang Ya-Ju Song Shi-Qing Tang Zhao-Hui Peng Xin-Wen Wang Le-Man Kuang Key Laboratory of Opto-electronic Control and Detection Technology of University of Hunan Province and College of Physics and Electronic Engineering Hunan Provincial Key Laboratory of Intelligent Sensors and Advanced Sensor Materials and Department of Physics Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education and Department of Physics Synergetic Innovation Academy for Quantum Science and Technology

We investigate the use of a single generalized dephasing qubit for sensing a quantum reservoir, where the antisymmetry of the coupling between the qubit and its reservoir is broken. Our results indicate that, in addition to the decay factor encoding channel, the antisymmetry breaking coupling introduces another phase factor encoding channel. We propose an optimal measurement strategy for the generalized dephasing qubit, which enables the practical measurement precision to reach the theoretical ultimate precision quantified by the quantum signal-to-noise ratio (QSNR). As an application example, the generalized dephasing qubit is employed to estimate the s-wave scattering length of an atomic Bose-Einstein condensate. It is found that the QSNR contributed by the antisymmetry breaking coupling is at least two orders of magnitude higher than the QSNR contributed by the antisymmetry coupling at the millisecond timescale, and the optimal relative error can achieve a scaling ∝1/(χt) in long-term encoding, where χ represents the relative driving strength and t is the encoding time. Our work opens a way for supersensitive sensing of quantum reservoirs.

关键词： Open quantum systems & decoherence Quantum parameter estimation Bose-Einstein condensates

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A Range Alignment Method Using Deep Learning for MMW ISAR Imaging 1

A Range Alignment Method Using Deep Learning for MMW ISAR Im...

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1st International Conference on the Frontiers of electronic, Electrical and Information Engineering, ICFEEIE 2024

作者： Zhao, Chaofan Ma, Chunguang Chen, Xu Luo, Yong School of Electronic Science and Engineering University of Electronic Science Technology of China Sichuan Chengdu China School of Electronic Science and Engineering UESTC Chengdu Sichuan China State Key Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing China

ISBN: (纸本)9798331528300

Range alignment is an important step in the imaging process of inverse synthetic aperture radar (ISAR) radar. In this paper, a novel deep learning network model is proposed to effectively tackle the challenge of distance alignment in millimeter-wave (MMW) ISAR imaging. The proposed model leverages a multi-layer bidirectional long short-term memory (bi-LSTM) network architecture to learn intricate features among echoes, thus facilitating precise alignment along the range direction. Meanwhile transfer learning was used to enhance the adaptability of the model to multiple signal-to-noise ratios (SNR). Experiment results show that the aligned images generated by proposed model in this paper are closer to the reference images in low SNR environments compared to traditional methods. ©2024 IEEE.

关键词： Radar imaging

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification From Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20 000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Feature Layer Fusion of Linear Features and Empirical Mode Decomposition of Human EMG Signal

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Journal of electronic Science and technology 2022年第3期20卷 257-269页

作者： Jun-Yao Wang Yue-Hong Dai Xia-Xi Si the School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu611731China the Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu611731China

To explore the influence of the fusion of different features on recognition,this paper took the electromyography(EMG)signals of rectus femoris under different motions(walk,step,ramp,squat,and sitting)as samples,linear features(time-domain features(variance(VAR)and root mean square(RMS)),frequency-domain features(mean frequency(MF)and mean power frequency(MPF)),and nonlinear features(empirical mode decomposition(EMD))of the samples were *** feature fusion algorithms,the series splicing method and complex vector method,were designed,which were verified by a double hidden layer(BP)error back propagation neural *** show that with the increase of the types and complexity of feature fusions,the recognition rate of the EMG signal to actions is gradually *** the EMG signal is used in the series splicing method,the recognition rate of time-domain+frequency-domain+empirical mode decomposition(TD+FD+EMD)splicing is the highest,and the average recognition rate is 92.32%.And this rate is raised to 96.1%by using the complex vector method,and the variance of the BP system is also reduced.

关键词： Complex vector method electromyography(EMG)signal empirical mode decomposition feature layer fusion series splicing method

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