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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhang, Weiming Zhang, Xiaodong Xu, Cheng Zhou, Guchuan Zhang, Teng Wang, Yu Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robot School of Mechanical Engineering Shaanxi Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

ISBN: (纸本)9798350307320

The upper limb motion intention recognition method based on electroencephalography (EEG) and surface electromyography (sEMG) fusion has achieved significant results in fields such as prosthetic control. However, most existing fusion methods use manual means to select features, which cannot capture temporal and spatial features at different scales, and ignore the correlation features between the two types of signals. To address these issues, this article proposes a fusion recognition method for upper limb motion intention EEG and sEMG based on Multi-scale Convolution, Polarized Self-Attention, and Cross Intelligence Integration Module. This article extracts multidimensional temporal and spatial features of EEG and sEMG through multi-scale convolution, and introduce polarized self-attention mechanism to filter the extracted multi-scale features. Simultaneously using cross enhancement strategy to extract correlation features between EEG and sEMG. Finally, the features are input into the classification network for recognition. This method was validated on the Jeong database, and the results showed that compared with CNN-LSTM and EEGNet, the recognition accuracy of this method increased by 2.63% and 3.15%, respectively. © 2023 IEEE.

关键词： Electroencephalography

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Research on Comfort Perception and Evaluation of Immersive Experience Equipment in Cultural Tourism

Research on Comfort Perception and Evaluation of Immersive E...

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2024 International Conference on Culture-Oriented Science and Technology, CoST 2024

作者： Hu, Huibo Su, Zhibin Jiang, Yujian Qu, Lingxi Communication University of China School of Information and Communication Engineering Beijing China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (纸本)9798350380347

Virtual Reality Head-Mounted Display (HMD), also known as VR glasses, is a typical amusement device that provides an immersive viewing experience based on virtual reality technology in cultural tourism equipment. Various factors may cause users to experience different degrees of sensory discomfort when using VR head-mounted displays, posing potential safety risks during performances. This study focuses on typical VR glasses used in cultural tourism performances and evaluates user comfort as the primary indicator. Through subjective evaluation experiment design, it examines the impact of motion conditions, internal scene settings, and VR glasses configuration on users' comfort perception. The research aims to provide theoretical analysis and experimental data to reduce performance safety risks. © 2024 IEEE.

关键词： Virtual environments

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Fault Prediction Method of Stage Lifts Based on Digital Twin

Fault Prediction Method of Stage Lifts Based on Digital Twin

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2024 International Conference on Culture-Oriented Science and Technology, CoST 2024

作者： Wang, Huiqin Zhang, Chunxi Li, Zhen Xiao, Mengjiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China Communication University of China School of Information and Communication Engineering Beijing China

ISBN: (纸本)9798350380347

To improve the safety of stage lifts' operation and reduce the failure rate, a digital-twin assisted fault prediction method is proposed here. Signals such as vibration and temperature are collected from the virtual and physical models. A fault prediction model based on Graph Convolutional Networks (GCN) is constructed to identify the potential faults of stage lift. The experiment results illustrate the effectiveness of the proposed model. It would enhance the safety and stability of stage equipment, and provide reliable support for stage performances. © 2024 IEEE.

关键词： Prediction models

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Research on Named Entity Recognition for Oral History Text

Research on Named Entity Recognition for Oral History Text

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2024 International Conference on Culture-Oriented Science and Technology, CoST 2024

作者： Hu, Chaoyu Bai, Shilei Zhang, Mengfei Communication University of China School of Information and Communication Engineering Beijing China Beijing Key Laboratory of Modern Entertainment Technology Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing China

ISBN: (纸本)9798350380347

Oral history involves conveying experienced events through spoken narratives, typically preserved and later studied by converting spoken language into text. Named entity recognition (NER) is the recognition of meaningful named entities in text, such as person names, locations, organizations, etc. Conducting NER research on oral history text is significant as it not only facilitates the verification of named entities by researchers but also allows for the extraction of key information from texts through named entities. By collecting oral history corpus, we establish an oral history text dataset, manually annotating all texts with six entity labels and repeatedly verifying them manually. Utilizing the concept of machine reading comprehension (MRC), a semantic fusion module was added, integrating label information into text information using a cross-attention mechanism, and decoding the corresponding entity labels through span decoding. The final model performs well on the oral history text dataset and also showed good performance on general Chinese datasets. © 2024 IEEE.

关键词： Decoding

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SSD object detection algorithm based on knowledge map

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International Journal of Wireless and Mobile Computing 2024年第2期27卷 152-160页

作者： Huang, Li Wang, Xiaofeng Lu, Jianhua Hu, Wei Zhang, Changrong College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, issues such as dispersed knowledge points, overlapping content, a singular practice approach and ineffective evaluation have been identified. In response to these challenges, this paper proposes a multidisciplinary and comprehensive practical teaching methodology grounded in the knowledge graph framework. It delves into diverse paths for practical teaching and assessment, including aspects like teaching objectives, problem decomposition, resource integration, implementation methods and performance evaluation. The practical application of the SSD algorithm in researching service robot indoor object detection serves as an illustrative example. Employing the holistic practical teaching approach facilitated by the knowledge graph, this model guides students in acquiring object detection expertise, thereby enhancing their comprehensive development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Object detection

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ADAPTIVE BOUNDARY control VIBRATION SUPPRESSION OF FLEXIBLE MANIPULATOR BASED ON IMPROVED RBF NEURAL NETWORK

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2024年第2期86卷 3-18页

作者： Zheng, Qingchun Wei, Zhiyong Zhu, Peihao Ma, Wenpeng Deng, Jieyong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China China School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Jiangxi Technical College of Manufacturing Jiangxi Nanchang330095 China

With lighter weight, lower power consumption, and higher flexibility, flexible manipulators have been widely used in industrial fields. However, it is easy to produce elastic deformation, resulting in vibration. In this paper, an improved radial basis function (RBF) neural network (NN) for adaptive boundary control is proposed. The partial differential equation (PDE) model of the flexible manipulator is established, and the asymptotic stability of the system is proved by the first Lyapunov method. Finally, simulation results show that the proposed control method can eliminate the low-amplitude angular fluctuation and the high-amplitude angular velocity fluctuation. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Flexible manipulators

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Periodic and chaotic oscillations in mutual-coupled mid-infrared quantum cascade lasers

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Chinese Physics B 2022年第10期31卷 352-361页

作者： Zhi-Wei Jia Li Li Yi-Yan Guo An-Bang Wang Hong Han Jin-Chuan Zhang Pu Li Shen-Qiang Zhai Feng-Qi Liu Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Semiconductor Materials Science Beijing Key Laboratory of Low Dimensional Semiconductor Materials and DevicesInstitute of SemiconductorsChinese Academy of SciencesBeijing 100083China

Dynamic states in mutual-coupled mid-infrared quantum cascade lasers(QCLs) were numerically investigated in the parameter space of injection strength and detuning frequency based on the Lang-Kobayashi equations model. Three types of period-one states were found, with different periods of injection time delay τ_(inj), 2τ_(inj), and reciprocal of the detuning frequency. Besides, square-wave, quasi-period, pulse-burst and chaotic oscillations were also observed. It is concluded that external-cavity periodic dynamics and optical modes beating are the mainly periodic dynamics. The interaction of the two periodic dynamics and the high-frequency dynamics stimulated by strong injection induces the dynamic states *** work helps to understand the dynamic behaviors in QCLs and shows a new way to mid-infrared wide-band chaotic laser.

关键词： periodic oscillations chaotic oscillations mutual-coupled quantum cascade lasers

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High-spatial-resolution phase-chaos Brillouin optical correlation domain sensor: theoretical analysis and experimental demonstration

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Journal of Lightwave Technology 2025年第12期43卷 5957-5966页

作者： Niu, Lintao Wang, Yahui Tian, Yixiu Ma, Jinglian Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronic Engineering Taiyuan030024 China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032 China

The predicaments of micro-scale gain motivation and its high signal-to-noise ratio (SNR) extraction primarily restrict the practical measurement of a superior spatial resolution (SR) for stimulated Brillouin scattering sensors. A high-SNR phase-chaos laser Brillouin optical correlation domain analysis (PCL-BOCDA) is introduced to breakthrough the physical bottlenecks. The fundamental principle of gain excitation scale based on PCL linewidth is proposed, and a novel SR evolvement model is constructed. The significant impact of edge effects on SR measurement is thoroughly analyzed, and this approach is theoretically capable of achieving higher SR benefiting from the narrower gain range and feebler accumulation noise. Experiments with different linewidth PCLs are conducted and the results are confirmed to the simulated ones. Ultimately, an SR of 4.8 mm with a relative error of 4.3% is achieved over a 1.14 km sensing distance, representing a tenfold improvement over previous results. This advancement provides a competent approach for high-SR sensors and their application. © 1983-2012 IEEE.

关键词： Stimulated Brillouin scattering

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Modified multi-scale symbolic dynamic entropy and fuzzy broad learning-based fast fault diagnosis of railway point machines

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Transportation Safety and Environment 2023年第4期5卷 1-7页

作者： Junqi Liu Tao Wen Guo Xie Yuan Cao Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048ShaanxiChina School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation Control System Beijing Jiaotong UniversityBeijing 100044China

Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident *** realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy ***,the fuzzy BLS takes the above entropy features as input to complete model *** BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational *** results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.

关键词： railway point machine(RPM) fault diagnosis modified multi-scale symbolic dynamic entropy(MMSDE) fuzzy board learning system(BLS)

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