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2023 4th International Conference on Computer engineering and Intelligent control, ICCEIC 2023

作者： Ren, Hui Han, Chunxiao Li, Shanshan Che, Yanqiu Wang, Ruofan Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education School of Information Technology Engineering Tianjin China

ISBN: (纸本)9798350308877

Electrical brain stimulation (EBS) has been established as a potent instrument for modulating brain activities. This paper presents a spatially distributed linear delayed feedback control (LDFC) approach for EBS, designed to suppress epileptiform activity within a Wilson-Cowan network model of the cortex. The EBS is administered distributively via a grid of stimulating electrodes positioned on the cortex, and we evaluate the efficacy of LDFC in suppressing epileptiform activity. In a large range of control parameter space (feedback gain and delay time), the overall pathological oscillations can be substantially reduced, although not entirely suppressed. © 2023 IEEE.

关键词： Feedback control

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A population randomization-based multi-objective genetic algorithm for gesture adaptation in human-robot interaction

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Science China(Information Sciences) 2021年第1期64卷 188-200页

作者： Luefeng CHEN Wanjuan SU Min LI Min WU Witold PEDRYCZ Kaoru HIROTA School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

In recent years, vision-based gesture adaptation has attracted great attention from many experts in the field of human-robot interaction, and many methods have been proposed and successfully applied, such as particle swarm optimization and genetic algorithm. However, the reduction of the error and energy consumption of a robot while paying attention to more subtle attitude changes is very important and *** view of these problems, we propose a population randomization-based multi-objective genetic *** gesture signal is processed with a slight change by imitating the biological evolution mechanisms. In the proposed algorithm, a random out-of-order matrix is added in the process of population evolution synthesis to prevent the premature grouping convergence of the new population. The weights of the objective function and the elite retention strategy are adopted, and the most adaptable individuals in each generation are inherited directly in the next generation without any recombination or mutation. To verify the effectiveness of the algorithm, preliminary application experiments are performed on the gesture adaptation of a robotic arm. The results are compared with the original signal, and the comparison shows that by using the proposed method, the energy consumption is reduced, and the end error is decreased to less than 3 mm while ensuring the tracking effect of the robotic arm. These obtained results meet the communication requirements for human-robot interactions such as handshakes. Moreover, the proposed method has better performance, uses less energy, and has a smaller tracking error than the particle swarm optimization, the single-objective genetic algorithm, and the traditional multi-objective genetic algorithm. A preliminary application experiment indicates that the robotic arm can adapt to human gestures in real time.

关键词： multi-objective genetic algorithm gesture adaptation human-robot interaction

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Simulation Device of Subway Short-Circuit Current Based on Luenberger Observer 11th

Simulation Device of Subway Short-Circuit Current Based on L...

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11th Frontier Academic Forum of Electrical engineering, FAFEE 2024

作者： Zou, Jiajin Chen, Peng Wang, Chunjie School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300382 China Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin300382 China

ISBN: (纸本)9789819788194

With the rapid development of urban subway system in recent years, the failure of subway traction network has become a research hotspot. In order to ensure the reliability of the subway power supply, better study the fault characteristics, provide close to the real subway short circuit current, study the action characteristics of the subway high voltage DC circuit breaker under the fault current, design a simulation device based on phase shift full bridge that can generate the subway short circuit current, by controlling the amplitude, frequency, initial phase angle of the input waveform, so that the corresponding waveform can be generated. And it is verified by experiments. The experimental results show that the output has the characteristics of good dynamic response and small error. Considering that the sensor is affected by the interference noise such as the environment, the Luenberger observer is added to optimize the device control algorithm reasonably. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Short circuit currents

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Coal and Gangue Recognition Based on Color Names and KSVM 41

Coal and Gangue Recognition Based on Color Names and KSVM

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第41届中国控制会议

作者： Xinliang Zhang Shengqiang Wei Jingtao Liu Yunji Zhao School of Electrical Engineering and Automation Henan Key Laboratory of Intelligent Detection and Control of Coal Mine EquipmentHenan Polytechnic University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Recognition of the gangue from the coal is an essential step in automatic coal *** solve the indistinguishability of coal and gangue in the low-dimensional color space,a kernel support vector machine(KSVM) model based on color names(CN) is proposed in this ***,the CN is used to map the original RGB image into a high-dimensional color *** provides eleven color channels for description of the *** use of the principal component analysis(PCA),two fundamental dimensional elements are selected to construct the principal color ***,through the combination with the gray component,an expanded color model with three channels is generated for the coal and gauge image with a higher contrast between the coal and gangue than the low-dimensional color ***,a screening mapping matrix is used to extract the contributing components of the gangue *** so-called Mask-CN color model is derived thereafter capable of determining the gangue candidate ***,six contributing features based on gray color histogram and gray-level co-occurrence matrix are selected and the SVM algorithm is adopted to realize the coal and gangue *** experimental results show that the proposed method has provided a satisfactory recognition accuracy up to 97.79%.It shows a strong robustness to diverse background conditions.

关键词： Coal and gangue recognition color names Mask-CN model KSVM

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Modeling and Simulation of Mixed Traffic Flow Considering Autonomous Vehicles and the Impact of Trucks 24

Modeling and Simulation of Mixed Traffic Flow Considering Au...

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4th Asia-Pacific Artificial Intelligence and Big Data Forum, AIBDF 2024

作者： Kuang, Xianyan Zhang, Zuliang Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control Jiangxi University of Science and Technology Jiangxi Ganzhou China School of Electrical Engineering and Automation Jiangxi University of Science and Technology Jiangxi Ganzhou China

ISBN: (纸本)9798400710865

Heavy trucks play a crucial role in shaping highway traffic dynamics. Their slower speed and unique acceleration and deceleration patterns can greatly influence the efficiency and stability of mixed traffic streams. This study explores a traffic scenario involving both heavy trucks and Connected and Autonomous Vehicles (CAVs), presenting an innovative model for mixed traffic flow and establishing specific lane-changing protocols for autonomous vehicles. Utilizing numerical simulations and comparative analyses, the research explores how heavy trucks affect traffic speed and lane-changing dynamics across different levels of CAV integration and varying traffic conditions. The findings of the study indicate that with lower rates of CAV penetration, increased traffic flow heightens the frequency of vehicle interactions, resulting in more pronounced variations in traffic speed. Conversely, when CAV penetration rates are elevated, there is a marked improvement in average traffic speed, alongside a significant reduction in speed fluctuations, particularly in high-density traffic situations. © 2024 Copyright held by the owner/author(s).

关键词： Automobiles

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RANSACs for 3D Rigid Registration:A Comparative Evaluation

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1861-1878页

作者： Jiaqi Yang Zhiqiang Huang Siwen Quan Zhiguo Cao Yanning Zhang the National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710072China the School of Electronic and Control Engineering Chang’an UniversityXi’an 710064China the School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China IEEE

Estimating an accurate six-degree-of-freedom(6-Do F)pose from correspondences with outliers remains a critical issue to 3D rigid *** sample consensus(RANSAC)and its variants are popular solutions to this *** there have been a number of RANSAC-fashion estimators,two issues remain ***,it is unclear which estimator is more appropriate to a particular ***,the impacts of different sampling strategies,hypothesis generation methods,hypothesis evaluation metrics,and stop criteria on the overall estimators remain *** work fills these gaps by first considering six existing RANSAC-fashion methods and then proposing eight variants for a comprehensive *** objective is to thoroughly compare estimators in the RANSAC family,and evaluate the effects of each key stage on the eventual 6-Do F pose estimation *** have been carried out on four standard datasets with different application scenarios,data modalities,and *** provide us with input correspondence sets with a variety of inlier ratios,spatial distributions,and *** on the experimental results,we summarize remarkable outcomes and valuable findings,so as to give practical instructions to real-world applications,and highlight current bottlenecks and potential solutions in this research realm.

关键词： 3D rigid registration performance evaluation point cloud pose estimation

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Coronary Artery Segmentation in X-ray Angiography Based on Deep Learning Approach

Coronary Artery Segmentation in X-ray Angiography Based on D...

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第43届中国控制会议

作者： Shanbin Li Yiting Fan School of Automation Science and Engineering South China University of Technology School of Energy and Control Engineering Changji University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Segmenting coronary arteries from X-ray coronary angiography(XCA) images allows observation of coronary artery morphology and stenosis, which is of great significance for computer-aided diagnosis and coronary artery disease ***, XCA images have low contrast and irregular lighting due to the limits of existing imaging techniques, making vascular segmentation challenging. Segmentation of coronary arteries using conventional U-shaped segmentation networks is challenging due to the problem of major differences in vascular morphology, size, and overlap. This paper proposes a network based on the U-shape structure for multiscale context information fusion with lightweight GhostNetV2 as the backbone feature extraction network to improve the model's feature extraction capabilities. Then a multi-scale context fusion module(MCF) is proposed to effectively capture the contextual information of blood vessels. Finally, we propose a feature re-extraction module(FRM)to achieve effective fine feature re-extraction in complex backgrounds. Experimental results show that the model we propose achieves more accurate coronary artery segmentation in complex backgrounds with fewer parameters, improves the segmentation of fine vessels at the end of coronary arteries, and performs well compared with other artery segmentation models. The F1 score,Intersection over Union(IOU), accuracy(ACC), and Sensitivity(Sen) of the model can reach 82.23%, 69.83%, 98.79%, 81.93%,respectively.

关键词： Coronary Arteries Segmentation Multi-scale Context Feature Fusion Encoder and Decoder Feature Fe-extraction Deep Learning

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2D Human Pose Estimation with Residual Upsampling and Spatial Feature Enhancement

2D Human Pose Estimation with Residual Upsampling and Spatia...

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第43届中国控制会议

作者： Shanbin Li Xishan Zheng School of Automation Science and Engineering South China University of Technology School of Energy and Control Engineering Changji University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Computer vision,which has been extensively used in intelligent monitoring,self-driving,medical assistance,sports analysis,and other fields,includes human pose estimation as a key *** pose estimation algorithms have been appearing nonstop in recent years,and as they get more complex and structured,it becomes harder to analyze and actually implement the *** network is surprisingly efficient for such a simple *** study makes several modifications based on SBL to further enhance its *** order to fuse rich features from the feature extraction stage to the upsampling phase,we first introduce the residual upsampling module(RUSM).This guarantees that more detailed,high-resolution information can be utilized to upsampling features,significantly increasing the accuracy of joint recognition in the human ***,we present the spatial feature enhancement module(SFEM),which utilizes the spatial attention mechanism with the residual *** is employed to boost spatial features of the upsampling phase and further increase the detection precision of the ***,we conduct numerous experiments on the LSP dataset,which amply illustrates the enhanced functionality of the extra modules and the better performance of our suggested network.

关键词： Human Pose Estimation Attention Mechanism Residual Upsampling Spatial Feature Enhancement

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Critical Node Identification of Cyber-Physical Power Systems Based on Improved Fuzzy Analytic Hierarchy Process 41

Critical Node Identification of Cyber-Physical Power Systems...

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第41届中国控制会议

作者： Jian Li Yiqiang Li Qingyu Su School of Automation Engineering Northeast Electric Power University Jilin Provincial Key Laboratory of Advanced Control Technology of Smart Energy

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Aiming at the present information security problems and the one-sidedness of vulnerability assessment indicators of cyber-physical power systems,an assessment model is proposed based on the improved fuzzy analytic hierarchy process to identify the critical nodes of the ***,an integrated model of the cyber-physical power system is established,and the cascading failure process after component failure of the power system is taken into ***,several assessment indicators considering two aspects of power flow character and structural safety are given.A three-scale method and the optimal transfer matrix are employed to improve the traditional analytic hierarchy process,and the fuzzy comprehensive evaluation is used to determine the final ***,the validity of the proposed method is verified on the model based on the IEEE 30-bus system.

关键词： cyber-physical power systems critical node identification improved fuzzy analytic hierarchy process cascading failure

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Research on Sign Language Gesture Division and Gesture Extraction in Complex Background

Research on Sign Language Gesture Division and Gesture Extra...

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2022 International Conference on Computer Vision, Application, and Algorithm, CVAA 2022

作者： Tian, Yifan Han, Fangfang Zhu, Minfeng Xu, Xiaoliang Li, Yadong School of Electrical Engineering and Automation China Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems China

ISBN: (纸本)9781510664036

Sign language plays an important role in information transmission and emotional communication between deaf-mute people and the outside world. With the development of artificial intelligence technology, the recognition, translation and generation of sign language based on digital image processing have attracted worldwide attention. In the field of sign language recognition, effective hand division and gesture extraction are the first and key steps, which directly affect the accuracy of sign language recognition. In this paper, a hand information extraction method based on depth image processing is proposed to solve the problem of sign language gesture extraction in complex background. For sign language speakers,hands are at the front of their bodies, so the depth images of sign language speakers can be collected by depth camera, and the complex background can be removed and hand information can be extracted by segmenting different color objects in the depth images. In this paper, the D435i camera of Inter is used to capture the depth image of the sign language speaker, and the HSV color space model based on the digital image is used for threshold processing of the fusion of hue components and brightness components to achieve the division of the hand position;through median filtering and mathematical morphology of digital image, division noise is removed and interference is reduced. Through skeleton extraction algorithm, the gesture gesture can be obtained. Experiments show that the proposed acquisition scheme and algorithm flow in this paper can effectively realize hand position division and gesture extraction in complex background conditions, and provide a good foundation for subsequent gesture recognition and expression. © 2023 SPIE.

关键词： Morphology

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