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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Yu, Yao Li, Qirui Zhang, Qieshi Hu, Wenjian Liu, Shumei Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China

ISBN: (纸本)9781728162676

Blockchain has unique advantages in data privacy protection and data integrity. We can solve many security problems, such as the single point of failure and data sharing in the current centralized system through blockchain approach. Existing studies have demonstrated that the application of blockchain in the medical system could improve the patient's medical experience. However, we found that the blockchain-based medical systems didn't consider the problems of long insurance claim cycle and complicated procedures. There are also very few healthcare systems that provide targeted sharing protocols for medical data and personal health data. In this paper, we propose a multi-role healthcare data sharing system framework based on blockchain. In this system, we reduce the storage cost through the collaborative storage of blockchain and IPFS. Then we design a smart contract on insurance to help patients achieve automatic insurance claim. In addition, we design two different sharing protocols to realize the fine management of personal data. The system analysis shows that our proposed blockchain-based multi-role healthcare data sharing system can effectively address the actual needs of users and has perfect performance in data storage, privacy protection, insurance claims and personal data management. © 2021 IEEE.

关键词： Blockchain

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Compactness and Separateness Driven Fuzzy Clustering Validity Index Called TLW 18th

Compactness and Separateness Driven Fuzzy Clustering Validit...

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18th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2023

作者： Tang, Yiming Wang, Xiang Li, Bing Hu, Xianghui Xie, Wenjun Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Anhui Hefei230601 China Engineering Research Center of Safety Critical Industry Measure and Control Technology Ministry of Education Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9789819996391

The design of validity index of fuzzy clustering has always been a historical problem in fuzzy clustering field. When the distribution of cluster centers is very close, it is difficult for the existing fuzzy clustering validity indexes to obtain a reasonable cluster number, and the separation mechanism of these indexes is too simple. In order to solve the above problems, we propose a novel fuzzy clustering validity index called TLW (Tang-Li-Wang) index. Firstly, compactness is expressed as the ratio of the membership weighted distance value to the sample variance of the dataset. Secondly, the sum of the maximum distance between cluster centers and the mean distance is used in separateness, and the sample variance of cluster centers is introduced, and the two are multiplied to describe the separateness. Thirdly, on the basis of considering compactness and separateness, the introduction of cluster number can alleviate the phenomenon that the index value may change monotonically with the increase of cluster number. Finally, the classical FCM (Fuzzy C-Mean) algorithm is used to conduct experiments on indexes. Comparative experiments and analyses were carried out on 17 typical datasets and 12 clustering validity indexes. From the experimental results of normal simple datasets and high-dimensional difficult datasets, the proposed index shows some advantages. All in all, these results verify that the proposed TLW index has better accuracy and stronger stability. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy clustering

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space

Safe Reinforcement Learning for Social Motor Coordination in...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Fan Yang Yuening Huang Chao Zhai Hehong Zhang China University of Geosciences Wuhan Campus School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing Houston Texas United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints.

关键词： Autism Filters Reinforcement learning Games Variable speed drives Motors Trajectory Safety Mirrors Motion control

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Dimensional synthesis and static/dynamic analysis of a robot in automobile hubs polishing

Dimensional synthesis and static/dynamic analysis of a robot...

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IEEE International Conference on Mechatronics and Automation

作者： Long Chen Manru Xi Yue Ma Bin Li Qi Liu Changrui Li Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

Focusing on the polishing operation of automobile hubs, this paper proposed a polishing robot by combining a 1T2R parallel mechanism (PM) and an X-Y worktable. The dimensional synthesis and static/dynamic performance analysis of the 1T2R PM are also presented with the key points as follows. Firstly, the inverse displacement model and velocity model of the PM are built to formulate the motion/force transmissibility indices on the basis of the generalized Jacobian matrix. Secondly, the dimensional synthesis problem is formulated to determine the optimized normalized dimensional parameters by maximizing the global force/motion transmissibility of the PM subject to geometric constraints without mechanical interference. Finally, the finite element (FE) model of the 1T2R PM is built with the aid of the SAMCEF, and the static stiffness and lower-order natural frequencies of the PM are evaluated. The research results of this paper provide dimensions and mechanical structures for developing the physical prototype of the automobile hub polishing robot.

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A Control Method of Robotic Arm Based on Improved Deep Deterministic Policy Gradient

A Control Method of Robotic Arm Based on Improved Deep Deter...

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IEEE International Conference on Mechatronics and Automation

作者： Yanpeng Shao Haibo Zhou Shuaishuai Zhao Xiaoyan Fan Jiayi Jiang National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China

With the continuous development of Machine Learning, Reinforcement Learning has achieved excellent results in many fields. An improved Deep Deterministic Policy Gradient (DDPG) algorithm is proposed in this paper to optimize Reinforcement Learning control performance, because of the issue of sparse rewards during training in continuous action spaces such as robotic arms, leading to slow convergence and low success rates. The algorithm merges the DDPG algorithm with the Hindsight Experience Relay (HER) algorithm, enabling the agent to learn from the failed experience when learning. Moreover, a double experience replay buffer is introduced, comprising a primary buffer and a secondary buffer containing high-reward experiences, which enhances the sampling probability of high-quality samples. At long last, a PyBullet simulation environment was utilized to execute a simulation experiment. The robotic arm using the improved DDPG algorithm achieved a success rate of nearly 100% in about 220 epochs of training, and the algorithm convergence speed was greatly improved. The trained robotic arm can reach any target point in the workspace. The efficacy of the improved DDPG algorithm is demonstrated by the outcomes, providing a valuable reference for further exploration into the intelligent control of robotic arms for object grasping.

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Gait Planning and Simulation of 3-RRP Legged Mobile Robot

Gait Planning and Simulation of 3-RRP Legged Mobile Robot

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IEEE International Conference on Mechatronics and Automation

作者： Jinyuan Wang Bin Li Yue Ma Xinjie Wang Pai Peng Wei Peng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

In order to meet the requirements of keeping the body posture level with the ground during the movement of the quadruped robots, this paper designs a quadruped robot with three joints and three degrees of freedom in each leg, which is a 3-RRP kinematic chain. The legs and body of the quadruped robot are virtually modeled by SolidWorks. Combining the forward and inverse kinematics analysis, the reasonable and ideal foot trajectory and body motion trajectory are planned in Matlab. The gait stability is based on the ZMP stability criterion and is quantified by the stability margin. According to the structural characteristics of the quadruped robot in this paper, the body posture adjustment strategy is proposed. Finally, the simulation is carried out under the two gait plannings of straight driving and turning using ADAMS. The simulation results show that the quadruped robot has a reasonable walking gait on the flat road surface with little impact on the body. The minimum stability margin of the strategy with body adjustment is improved compared with the strategy without body adjustment.

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Control Strategy of Permanent Magnet Synchronous Motor and Brushed DC Servo Motor Based on ADRC

Control Strategy of Permanent Magnet Synchronous Motor and B...

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IEEE International Conference on Mechatronics and Automation

作者： Liang Liu Haikui Liu Guangyin Nie Yang Gao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

Adaptive disturbance rejection control (ADRC) is a rapidly evolving and promising control method that has been widely applied in various industrial fields and may yield better results than traditional method. In order to promote the controller performance, ADRC technology was employed to construct a three-loop structure for the controllers of permanent magnet synchronous motor (PMSM) and brushed DC Servo Motor (BDSM). Firstly, the mathematical models of the both kinds of motors were presented and combined with the ADRC, respectively. Secondly, the simulation models based on ADRC were constructed in MATLAB/SIMULINK, respectively. Finally, comparative experiments were carried out by ADRC and Proportional-Integral (PI) methods. The simulation results showed that ADRC outperforms PI control in terms of response speed, overshoot reduction, and anti-interference capability, which verified the proposed method can exhibit superior dynamic properties in the induction motor control.

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Research on Robot Optimal Working Space Based on Spiral Theory

Research on Robot Optimal Working Space Based on Spiral Theo...

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2022 International Symposium on Robotics, Artificial Intelligence, and Information Engineering, RAIIE 2022

作者： Li, Yu-Fei Ge, Wei-Min Zhang, Zhi-Li Zhao, Xiang-Bin College of Mechanical Engineering TianJin University of Technology TianJin province TianJin300074 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China Intelligent Manufacturing College Tianjin Sino-German University of Applied Science Tianjin300350 China

ISBN: (纸本)9781510660137

Because industrial robots have uneven positioning accuracy in the overall working space, they have greatly limited their applications in the fields of high-precision production and *** this status quo, this article focuses on analyzing the optimal working space of industrial robots, and screening and limiting the optimal working scope of the selected industrial robots to ensure that the robot end is at a relatively high position with high positioning *** article selects the collaborative robot AUBO E3 for modeling, analysis and simulation. Calculate the robot based on the Jacques matrix and the number of conditions under the spiral theory, quantitatively depict the exercise performance of the *** excellent working space is visually simulated, and finally uses the API laser tracker to measure the end error of the robot. As a result, the accuracy of the end point in the optimal working space is higher than the endpoint accuracy of the overall work space. © 2022 SPIE.

关键词： Industrial robots

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An optimal design and fuzzy control method for a new flapping-wing robot

An optimal design and fuzzy control method for a new flappin...

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Electrical Engineering and Control Science (IC2ECS), International Conference on

作者： Chunxiao Zhang Yansen Zhao Ting Zhang Qi Liu Bin Li Yue Ma Mengze Suo Changrui Li Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

Bionic flapping-wing robot has the advantages of good maneuverability, low noise and strong stealth performance. It is widely used in military intelligence collection, field rescue and investigation. In this paper, an optimal design method of bionic flapping-wing robot non-phase difference driving mechanism is proposed. By setting the constraints of flapping angle amplitude, fuselage height and slider stroke, the scale parameters of the mechanism are optimized by using the minimum transmission angle; on this basis, the effectiveness of fuzzy PD control in improving the tracking accuracy of the drive system is verified by means of ADAMS and MATLAB / Simulink electromechanical coupling simulation. This research has practical value for designing new flapping-wing robot and improving its control quality.

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