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检索条件"机构=College of Control and Computer Engineering"

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Client Selection Based on Channel Capacity for Federated Learning Under Wireless Channels

Client Selection Based on Channel Capacity for Federated Lea...

引用

Asia-Pacific Conference on Communications

作者： Satoshi Yamazaki Takuma Furuki Dept. of Control and Computer Engineering National Institute of Technology Numazu College Numazu Japan Systems Innovation Faculty of Engineering Tokyo University Tokyo Japan

This paper proposes a user selection scheme for federated learning (FL) over wireless networks to reduce communication time based on channel capacity. In particular, the edge server calculates the Shannon channel capacity of each client for each round, and clients with a certain threshold capacity are randomly selected to participate in FL. We show that the convergence time of the proposed scheme outperformed that of the conventional scheme through computer simulation based on an image processing task under a wireless channel with pass-loss, shadowing, and Rician flat-fading. Moreover, the superiority of FL to centralized learning (CL) regarding total time is demonstrated theoretically and validated through computer simulation.

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Fault-Tolerant Multi-Robot Target Pursuit with Fault Detection and Isolation Based on Mobile Adaptive Networks 11

Fault-Tolerant Multi-Robot Target Pursuit with Fault Detecti...

引用

11th IEEE Annual International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2021

作者： You, Jia Li, Zhenhui Yang, Jianhua College of Information Science and Electronic Engineering Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781665425278

Multi-robot target pursuit is a typical problem in multi-robot systems and can be solved by mobile adaptive networks in distributed way. For the importance and difficulty in improving fault tolerance of multi-robot systems, many adaptations of mobile adaptive networks have emerged. This paper introduces fault detection and isolation to the standard (with the weighted average aggregation rule) and three existed adaptations (with the coordinate-wise median, geometric median, and centerpoint aggregation rules) of mobile adaptive networks, which uses the differences of the theoretical estimated values and the actual estimated values to predict normal neighbor set in mobile adaptive networks, and carries out target pursuit. Fault-tolerant multi-robot target pursuit algorithms with fault detection and isolation based on mobile adaptive networks are proposed to remove the interference of the faults in the networks to achieve better performance in target pursuit. Simulation experiments have been carried out with different numbers of faulty robots in the original algorithms and our improved algorithms. Our proposed algorithms are proved to perform better in convergence and accuracy than the original algorithms, especially when the number of faulty robots increases, and the improvement effects on target pursuit algorithms with different aggregation rules can be different. © 2021 IEEE.

关键词： Multipurpose robots

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Adaptive control Scheme for Clustering of Nodes Based on the Signs of Connections in Dynamical Signed Networks 19th

Adaptive Control Scheme for Clustering of Nodes Based on ...

引用

19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wang, Qi Wang, Yinhe Gao, Zilin Gao, Peitao Xiong, Jianbin Cen, Jian Gao, Ying School of Automation Guangdong Polytechnic Normal University Guangzhou510665 China School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Engineering Chongqing Three Gorges University Chongqing404020 China School of Electronics and Information Guangdong Polytechnic Normal University Guangzhou510665 China Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory Guangzhou510665 China School of Computer Science and Engineering South China University of Technology Guagnzhou510641 China

ISBN: (纸本)9783031651229

The concept of clustering has garnered significant attention within the field of complex networks. Numerous clustering algorithms have been documented in the extant academic literature. However, most of them consider static signed networks, which are not suitable for dynamical networks. For dynamical signed networks, there is a class of algorithms called cluster dynamics. Nevertheless, they regard the connection to be time-invariant, which is a constraint. In this paper, for a kind of dynamical signed networks with time-varying connections, we discuss the adaptive control scheme for clustering of nodes, such that the network evolves asymptotically into a classifiable network that contains several friends’ groups with clear sign boundaries. In other words, through the careful design of the controller for the nodes and the establishment of coupling relationships between the nodes and their connections, we ensure that the connection of the dynamical signed network can approximate asymptotically the connection of a given classifiable network, as measured by the concept of uniformly ultimately bounded (UUB). Finally, the simulation is used to illustrate the validity of the method proposed in this paper. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Adaptive control Classifiable networks Multi-clustering

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3D Point Cloud Semantic Segmentation Based on Diffusion Model

3D Point Cloud Semantic Segmentation Based on Diffusion Mode...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chang Liu Aimin Jiang Yibin Tang Yanping Zhu Qi Chen College of Information Science and Engineering Hohai University Changzhou China School of Microelectronics and Control Engineering Changzhou University Changzhou China School of Computer Science and Artificial Intelligence Changzhou University Changzhou China

Point cloud segmentation plays a crucial role in extracting unique attributes and separating various objects, thereby enabling semantic comprehension and analysis. In this paper, we introduce a novel point cloud segmentation approach based on Diffusion Probabilistic Network (DDPM). The proposed model treats points as particles undergoing diffusion towards a noise distribution, and a reverse diffusion process transforms this noise distribution into the desired shape. Leveraging a Markov diffusion model in the reverse process enables generating point clouds with more refined and specific topological structures. After the diffusion step, multi-scale sampled features are fused to enhance the discriminative representation of 3D shapes. Objective and subjective experimental results demonstrate that our segmentation method outperforms state-of-the-art techniques in terms of evaluation metrics.

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The Impact of Grid Harmonics on Commutation Failure

The Impact of Grid Harmonics on Commutation Failure

引用

China International Electrical and Energy Conference (CIEEC)

作者： Ming Li Xiaolin Shen Yucheng Wu Yiqi Liu State Grid Economic and Technology Research Institute Co. Ltd. Beijing China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Commutation failure is a common fault in Line Commutated Converter High Voltage Direct Current (LCC-HVDC) systems. LCC-HVDC relies on the AC power grid to provide reverse voltage to naturally turn off thyristors. Faults in the AC system on the inverter side can lead to commutation failures. In practical engineering applications, AC network harmonics also affect the commutation of thyristors. This paper further elucidates the impact of AC network harmonics on commutation failure and validates the effect of non-characteristic harmonics of different orders on LCC-HVDC commutation failure using the PSCAD/EMTDC simulation platform.

关键词： Thyristors Voltage High-voltage techniques Power system stability Harmonic analysis Stability analysis Power grids

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An Improved Unsupervised White Blood Cell Classification via Contrastive Learning 1

引用

6th International Conference on Data Mining and Big Data, DMBD 2021

作者： Zhong, Yuning Huang, Maoye Fan, Haoyi Hu, Rong Li, Zuoyong College of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Information Engineering Zhengzhou University Zhengzhou450001 China

ISBN: (数字)9789811674761

ISBN: (纸本)9789811674754

The classification and counting of white blood cells (WBCs, leukocytes) in blood smears are of great significance for clinicopathological diagnosis. Therefore, the classification of WBCs in the images is a basic task. Most of the existing WBCs classification methods are based on supervised learning, which highly depends on a large number of image labels. To cope with the challenge of image annotation, in this paper, we propose an unsupervised WBCs classification method, which combines the advantages of contrastive learning and a deep clustering algorithm. Specifically, the proposed method firstly employs contrastive learning to pre-train the feature encoder, which is able to improve the similarity of feature coding among the same kind of cell categories. Then, the classical clustering algorithm is used based on the pre-trained image features for unsupervised classification of WBCs. Finally, the high confidence clustering results are fed back to the pre-trained feature encoder, which can be used as the pseudo labels to form a closed loop. Experimental results on a dataset containing 574 leukocyte images demonstrate the effectiveness of the proposed method. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings 39

TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Yan, Dawei Li, Pengcheng Li, Yang Chen, Hao Chen, Qingguo Luo, Weihua Dong, Wei Yan, Qingsen Zhang, Haokui Shen, Chunhua School of Cybersecurity Northwestern Polytechnical University China AI Business Alibaba Group China College of Computer Science and Technology Zhejiang University China College of Information and Control Engineering Xi’an University of Architecture and Technology China School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)157735897X

Currently, inspired by the success of vision-language models (VLMs), an increasing number of researchers are focusing on improving VLMs and have achieved promising results. However, most existing methods concentrate on optimizing the connector and enhancing the language model component, while neglecting improvements to the vision encoder itself. In contrast, we propose Text Guided LLaVA (TG-LLaVA) in this paper, which optimizes VLMs by guiding the vision encoder with text, offering a new and orthogonal optimization direction. Specifically, inspired by the purpose-driven logic inherent in human behavior, we use learnable latent embeddings as a bridge to analyze textual instruction and add the analysis results to the vision encoder as guidance, refining it. Subsequently, another set of latent embeddings extracts additional detailed text-guided information from high-resolution local patches as auxiliary information. Finally, with the guidance of text, the vision encoder can extract text-related features, similar to how humans focus on the most relevant parts of an image when considering a question. This results in generating better answers. Experiments on various datasets validate the effectiveness of the proposed method. Remarkably, without the need for additional training data, our proposed method can bring more benefits to the baseline (LLaVA-1.5) compared with other concurrent methods. Furthermore, the proposed method consistently brings improvement in different settings. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Research on the Mechanism and Suppression Methods of Commutation Failure in High-Voltage Direct Current Transmission Systems

Research on the Mechanism and Suppression Methods of Commuta...

引用

China International Electrical and Energy Conference (CIEEC)

作者： Ming Li Xiaolin Shen Xuanlang Li Yiqi Liu State Grid Economic and Technology Research Institute Co. Ltd. Beijing China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

High-voltage Direct Current (HVDC) transmission technology has obvious advantages in power transmission, so it has been developed rapidly. Commutation failure is one of the most common faults in HV AC-DC hybrid transmission systems, which can cause DC lock and power oscillation. This paper takes commutation failure as the research object analyzes its causes and main influencing factors and puts forward corresponding suppression strategies, which are significant for the safe and stable operation of HVDC transmission systems.

关键词： Bridges Thyristors Harmonics suppression HVDC transmission High-voltage techniques Hybrid power systems Oscillators

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MPC-based Optimization Design for 3D Collision Avoidance of a Mobile Manipulator Based-on Obstacle Velocity Estimation

MPC-based Optimization Design for 3D Collision Avoidance of ...

引用

International Automatic control Conference

作者： Kai-Tai Song Chih-Hsuan Lin Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University 1001 Ta Hsueh Road Hsinchu Taiwan Taiwan R.O.C

ISBN: (数字)9798350354904

ISBN: (纸本)9798350354911

This paper presents an optimization design of 3D dynamic obstacle avoidance for a mobile manipulator based on model predictive control (MPC). The design enables a mobile manipulator to achieve optimized 3D collision avoidance motion with shorter avoidance path and faster avoidance time. A 3D LiDAR is installed onboard the robot to acquire environmental point cloud and estimate obstacle velocity. The MPC is designed to track an initial 3D path of the mobile manipulator and avoid any static and dynamic obstacles in real time. Experimental results show that the proposed method can simultaneously avoid static and dynamic obstacles in 3D space. Compared with baseline algorithms without velocity estimation, the proposed method reduces the avoidance path length by 8.27% and path execution time by 13.79%.

关键词： Solid modeling Three-dimensional displays Tracking Dynamics Estimation Real-time systems Collision avoidance Manipulator dynamics Optimization Predictive control

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K-Means-Based Mobile Adaptive Networks for Swarm Robotic Systems with Non-Cooperative Behaviors 6

K-Means-Based Mobile Adaptive Networks for Swarm Robotic Sys...

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6th International Conference on Computational Intelligence and Applications, ICCIA 2021

作者： You, Jia Li, Zhenhui Yang, Jianhua Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Zhejiang University College of Control Science and Engineering Hangzhou China Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9781665439336

Mobile adaptive networks enable distributed adaptation and learning over networks while maintaining the cooperative motion, and play an important role in multi-robot control. Non-cooperative behaviors are common in swarm robotic systems and can greatly affect the system performance through information transmission and fusion in mobile adaptive networks. Some adaptations of different aggregation rules have been emerged to improve fault tolerance in mobile adaptive networks. This paper proposes K-means-based mobile adaptive networks which use K-means clustering algorithm to detect the faulty neighbors with non-cooperative behaviors and carry out mobile adaptive networks depending on information of the normal neighbors. Simulations are carried out in four existed mobile adaptive networks with different aggregation rules and our K-means-based mobile adaptive networks with these four aggregation rules. Simulation results prove that our proposed algorithms have better fault tolerance than the original algorithms. © 2021 IEEE.

关键词： Adaptive control systems

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