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Brain-inspired Intelligent Robotics:Theoretical Analysis and systematic Application

Machine Intelligence Research 2023年第1期20卷 1-18页

作者： Hong Qiao Ya-Xiong Wu Shan-Lin Zhong Pei-Jie Yin Jia-Hao Chen The State Key Laboratory of Management and Control for Complex System Institute of AutomationChineseAcademyof SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Chinese Academy of Science Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China

Traditional joint-link robots have been widely used in production lines because of their high precision for single *** the development of the manufacturing and service industries,the requirement for the comprehensive performance of robotics is *** types of bio-inspired robotics have been investigated to realize human-like motion control and manipulation.A study route from inner mechanisms to external structures is proposed to imitate humans and animals *** this idea,a brain-inspired intelligent robotic system is constructed that contains visual cognition,decision-making,motion control,and musculoskeletal *** paper reviews cutting-edge research in brain-inspired visual cognition,decision-making,motion control,and musculoskeletal *** software systems and a corresponding hardware system are established,aiming at the verification and applications of next-generationbrain-inspired musculoskeletal robots.

关键词： Brain-inspired intelligent robot software and hardware decision making muscle control cognitive intelligence.

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Analysis of the SEIR mean-field model in dynamic networks under intervention

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Infectious Disease Modelling 2025年第3期10卷 850-874页

作者： Li, Jiangmin Jin, Zhen Tang, Ming Complex System Research Center Shanxi University Shanxi Taiyuan 030006 China Key Laboratory of Complex Systems and Data Science of Ministry of Education Shanxi University Shanxi Taiyuan 030006 China Shanxi Key Laboratory for Mathematical Technology in Complex Systems Shanxi University Shanxi Taiyuan 030006 China School of Physics and Electronic Science East China Normal University Shanghai 200241 China Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China

For emerging respiratory infectious diseases like COVID-19, non-pharmaceutical interventions such as isolation are crucial for controlling the spread. From the perspective of network transmission, non-pharmaceutical interventions like isolation alter the degree distribution and other topological structures of the network, thereby controlling the spread of the infectious disease. In this paper, we establish a SEIR mean-field propagation dynamics model for the synchronous evolution of dynamic networks caused by propagation and tracing isolation. We employ the reducing-dimension method to convert the mean-field model in networks into an equivalent and simpler low-dimension model, and then calculate the exact expression of the final size. In addition, we get the differential equations of the degree distribution over time in dynamic networks under tracing isolation and the relationships between the first and second moment of the dynamic network. While the degree of a node remains constant regardless of its state in many previous studies, this paper takes into account that the degree of each node changes over time whatever its state under the disease spread and intervention measures. © 2025 The Authors

关键词： Degree distribution Dynamic network The final size Tracing isolation

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Analysis of node importance of satellite network based on triangular motif 23

Analysis of node importance of satellite network based on tr...

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Proceedings of the 2023 International Conference on Communication Network and Machine Learning

作者： Zhongmin Pei Boren Hu Zhangkai Luo Jie Ding Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University China Department of Electronics and Optical Engineering Space Engineering University China

ISBN: (纸本)9798400716683

Motif provides a local high-order substructure angle for the analysis of network structure evolution, which is of great significance for the study of the interaction between satellite network structure and function. Taking the time scrambling null motif in steady state as a reference, the stability analysis of satellite network structure is carried out from the perspective of the local structure of the motif characteristics; define the temporal degree of satellite network, and propose a satellite network node importance analysis method based on the number of node-constructed triangle motifs, and compare the changes of motifs characteristics under the deliberate attack of temporal degree and based on triangle motifs. simulation experiments are conducted on 46-node GPS constellations containing satellites and ground stations, and it is found that the network with higher initial triangle concentration showed higher stability. In GPS satellite network where the number of node triangle motif is positively correlated with their temporal degree, the attack strategy based on the triangle motif accelerates the attenuation of the triangle subgraph, and the node importance analysis method of the satellite network has higher accuracy.

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer Modeling in Engineering & sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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Research on Active Vibration Control of the Plate Based on Modal Space Control 2nd

Research on Active Vibration Control of the Plate Based on M...

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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Lu, Hanjing Ma, Ziyao College of Engineering Peking University Beijing China Institute of Launch Dynamics Nanjing University of Science and Technology Nanjing China National Key Laboratory of Complex Multibody System Dynamics Nanjing China

ISBN: (纸本)9789819980475

In this study, we have devised an innovative strategy for active vibration control in plates by harnessing modal space control techniques. Our methodology encompasses the creation of a dynamic model to capture the plate's vibrational dynamics and subsequent simulation of its behavior. Building upon this, we have established a streamlined state-space representation, thereby simplifying the integration of control methodologies. To further optimize the control system's performance, we have meticulously optimized the placement of actuators and sensors. The culmination of our efforts is reflected in compelling numerical findings, underscoring the efficacy of our proposed active vibration control system. Notably, our system exhibits a remarkable ability to effectively curtail vibration displacement in the plate, reinforcing its potential impact in practical applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Vibration control

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Analysis and Optimization of Medium Frequency Noise in Vehicle Cabin Based on FE-SEA Hybrid Method 2nd

Analysis and Optimization of Medium Frequency Noise in Vehic...

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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Zhang, Dongye Gu, Junjie Zhang, Yanni Institute of Launch Dynamics Nanjing University of Science and Technology Jiangsu Province Nanjing210094 China National Key Laboratory of Complex Multibody System Dynamics Jiangsu Province Nanjing210094 China

ISBN: (纸本)9789819980475

This paper demonstrates the coupling relationship between Finite Element (FE) models and Statistical Energy Analysis (SEA) models based on wave theory and modal theory. A vehicle hybrid FE-SEA model is established by considering points, lines, surfaces, and loads. The VA One software is utilized to construct material and acoustic packages for the mixed model materials and acoustic media, and to perform vehicle cabin noise simulation analysis. This study investigates the effects of acoustic materials and damping materials on vehicle cabin noise under different working conditions, obtaining sound pressure level curves at the driver’s head under various conditions. By adding different structures of sound-absorbing materials to the model, the vibration and sound radiation performance of the cabin body panels are compared. Considering the comprehensive factors such as weight and driver’s comfort, an optimized design scheme for vehicle cabin noise reduction and vibration damping is proposed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Damping

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Facial expression recognition under occlusion conditions based on multi-feature cross-attention

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Journal of Intelligent and Fuzzy systems 2024年第4期46卷 9841-9856页

作者： Guo, Sheng Tan, Mian Cai, Shan Zhang, Zaijun Liang, Yihui Feng, Hongxi Zou, Xue Wang, Lin School of Data Science and Information Engineering Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Mathematics and Statistics Qiannan Normal University for Nationalities Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Aerospace Tianma Electromechanical Technology Co LTD Zunyi China

Although facial expression recognition (FER) has a wide range of applications, it may be difficult to achieve under local occlusion conditions which may result in the loss of valuable expression features. This issue has motivated the present study, as a part of which an effective multi-feature cross-attention network (MFCA-Net) is proposed. The MFCA-Net consists of a two-branch network comprising a multi-feature convolution module and a local cross-attention module. Thus, it enables decomposition of facial features into multiple sub-features by the multi-feature convolution module to reduce the impact of local occlusion on facial expression feature extraction. In the next step, the local cross-attention module distinguishes between occluded and unoccluded sub-features and focuses on the latter to facilitate FER. When the MFCA-Net performance is evaluated by applying it to three public large-scale datasets (RAF-DB, FERPlus, and AffectNet), the experimental results confirm its good robustness. Further validation is performed on a real FER dataset with local occlusion of the face. © 2024 – IOS Press.

关键词： Convolution

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Anti-bias Target Association Method Based on Laplacian Spectrum and Kuhn-Munkres Algorithm 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Bai, Xiaomeng Xu, Cheng Fu, Wenxing Guan, Xujun Zhang, Hang Fu, Wenxing Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China Unmanned System Research Institute Northwestern Polytechnical University Xi’an710072 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

In the problem of collaborative situational awareness, the single sensor inevitably has random errors, systematic errors, false alarms, and missed alarms. To improve the accuracy of target association in the above cases, this paper proposes an anti-bias target association method based on the Laplacian spectrum and Kuhn-Munkres (KM) algorithm. The main contributions of the paper include addressing the coupling problem between system error calibration and target association through two stages, focusing on the structural characteristics of the target formation in the first stage and the absolute position of the target itself in the second stage. The algorithm takes into account both factors and achieves accurate association under complex errors. The test results demonstrate that the proposed method effectively improves the accuracy of anti-bias target association. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： systematic errors

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Establishment of Coupling simulation Model of Diesel Engine Combustion Process and Mechanical system Dynamics 2nd

Establishment of Coupling Simulation Model of Diesel Engine ...

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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Fan, Jiangrui Zhang, Jianshu Yu, Hailong Institute of Launch Dynamics Nanjing University of Science and Technology Jiangsu Province Nanjing210094 China National Key Laboratory of Complex Multibody System Dynamics Jiangsu Province Nanjing210094 China

ISBN: (纸本)9789819980475

The diesel engine works by converting the thermal energy of fuel combustion into mechanical energy. Its actual working process is extremely complex, and the thermodynamic and dynamics processes are highly coupled. In the existing simulation model, the dynamic and thermodynamic processes are calculated separately. In this paper, the dynamic equation of diesel engine is introduced into the zero-dimensional model of classical diesel engine, and the thermal–mechanical coupling equation of diesel engine is established. The correctness of the thermal–mechanical coupling model is verified by comparing with the classical zero-dimensional combustion model. The thermal–mechanical coupling model established in this paper improves the accuracy and authenticity of diesel engine simulation analysis, and is of great significance to the thermodynamic and dynamics analysis of diesel engines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Diesel engines

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Attention-enhanced Relation Network for Few-shot Image Classification 23

Attention-enhanced Relation Network for Few-shot Image Class...

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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Li, Jinyang Tong, Jiahui Gao, Guangyu Xu, Wenbin School of Computer Science and Technology Beijing Institute of Technology China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Optical Radiation Laboratory Beijing Institute of Environmental Characteristics Beijing100854 China

ISBN: (纸本)9781450398572

Traditional deep learning models firmly rely on a large amount of labeled data during pre-training. Whereas it lacks generalization in the face of unfamiliar categories. Recently, few-shot learning is a hot topic in computer vision to classify unseen classes with limited labels. A representative approach is to extract features from the support and query sets, respectively, and compare similarities via metric learning. However, convolutional neural networks often focus only on a local region and ignore the global region, which severely reduces the accuracy of the matching. Specifically, in this paper, we pile lightweight attention-based blocks in the embedding module, which combines an adaptive kernel size 2D convolutional network with a cross-channel attention mechanism to encode multi-scale features and implicitly increase the receptive field. The SE-relation module chooses to construct learnable non-linear comparators to compare the relationship utilizing channel information. Finally, we show experimental results on standard few-shot testing benchmarks such as mini-ImageNet and tiered-ImageNet to demonstrate effectiveness. © 2023 ACM.

关键词： Image classification

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