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arXiv 2021年

作者： Cai, Yaoming Zhang, Zijia Liu, Yan Ghamisi, Pedram Li, Kun Liu, Xiaobo Cai, Zhihua School of Computer Science China University of Geosciences Wuhan430074 China Helmholtz Institute Freiberg for Resource Technology Freiberg09599 Germany Vienna1030 Austria College of Electronic Science and Technology National University of Defense Technology Changsha410073 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering has evolved from shallow models to deep and achieved promising results in many benchmark datasets. However, their poor scalability, robustness, and generalization ability, mainly resulting from their offline clustering scenarios, greatly limit their application to large-scale hyperspectral data. To circumvent these problems, we present a scalable deep online clustering model, named Spectral-Spatial Contrastive Clustering (SSCC), based on self-supervised learning. Specifically, we exploit a symmetric twin neural network comprised of a projection head with a dimensionality of the cluster number to conduct dual contrastive learning from a spectral-spatial augmentation pool. We define the objective function by implicitly encouraging withincluster similarity and reducing between-cluster redundancy. The resulting approach is trained in an end-to-end fashion by batch-wise optimization, making it robust in large-scale data and resulting in good generalization ability for unseen data. Extensive experiments on three hyperspectral image benchmarks demonstrate the effectiveness of our approach and show that we advance the state-of-the-art approaches by large margins. Copyright © 2021, The Authors. All rights reserved.

关键词： Spectroscopy

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Initial Study on Implementation of Smoothing Filters for the Purpose of Bioimpedance Spectroscopy Parameters Classification

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IFAC-PapersOnLine 2022年第4期55卷 393-398页

作者： Aleksandra Kawala-Sterniuk Amir F. Al-Bakri Mariusz Pelc Katarzyna Cichoń Wojciech Chlewicki Stepan Ozana Radek Martinek Jakub Możaryn Volodymyr Khoma Halyna Kenyo Edward Jacek Gorzelańczyk Michał Podpora Jarosław Zygarlicki Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45-758 Opole Poland Department of Biomedical Engineering College of Engineering University of Babylon 51001 Babylon Iraq University of Greenwich School of Computing and Mathematical Sciences SE10 9LS London UK West Pomeranian University of Technology in Szczecin Faculty of Electrical Engineering 70-313 Szczecin Poland Faculty of Mechatronics Warsaw University of Technology 02-525 Warsaw Poland Lviv Polytechnic National University Institute of Computer Technologies Automation and Metrology Lviv Ukraine Institute of Philosophy Kazimierz Wielki University 85-092 Bydgoszcz Poland Faculty of Mathematics and Computer Science Adam Mickiewicz University in Poznań 61-614 Poznań Poland

Bioimpedance is a commonly used method for various conditions monitoring. In this paper, the authors carried out some research where they implemented various smoothing filters to enable identification of the bioimpedance spectroscopy parameters. The proposed filtering methods may also be used for application on embedded systems, which have smaller computing power but have become recently very popular. The obtained results with the implementation of smoothing filters were promising, however, some of the obtained results were unsatisfactory. This work also contains a brief introduction to bioimpedance spectroscopy and smoothing filters.

关键词： Bioimpedance Spectroscopy smoothing-filtering Savitzky-Golay Filter Median Filtering Moving-Average Filters

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Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

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Chinese Journal of Aeronautics 2019年第12期32卷 2679-2693页

作者： Yang XU Delin LUO Dongyu LI Yancheng YOU Haibin DUAN School of Aerospace Engineering Xiamen UniversityXiamen 361005China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Department of Electrical&Computer Engineering National University of SingaporeSingapore 117583Singapore

This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.

关键词： Affine formation control Collision avoidance Lyapunov stability Target enclosing Two-layer strategy

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MODELING AND FUZZY control OF PERMANENT MAGNET SYNCHRONOUS MOTORS

MODELING AND FUZZY CONTROL OF PERMANENT MAGNET SYNCHRONOUS M...

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The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)

作者： D.-K. Jukić T. Varga T. Benšić V. J. Štil M. Barukčić Automation and Control Institute TU Wien Vienna Austria Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Osijek Croatia

This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic controller operation is tested using Real-Time (Model-in-the-Loop) simulations.

关键词： fuzzy control finite element analysis genetic algorithms neural nets permanent magnet motors machine control synchronous motors nonlinear control systems PI control electric machine analysis computing

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Formation control for Mobile Robot using Fuzzy - PI controller

Formation Control for Mobile Robot using Fuzzy - PI Controll...

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International Conference on Advanced Robotics and Intelligent Systems (ARIS)

作者： Min-Fan Ricky Lee H.P.M Willybrordus Sukamto Sharfiden Hassen Asep Nugroho National Taiwan University of Science and Technology Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan College of Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (数字)9781728198231

ISBN: (纸本)9781728198248

Protecting soldiers in the long march of platoon formation is crucial mission in the military operation. Autonomous ground mobile robots can be deployed to carry out such kind of the mission. The primary task is maintaining robot position automatically based on the movement of soldier in a platoon formation. The GPS is employed to determine the soldier current pose. This information is used as an input to create a dynamic convex hull around a platoon. The Proportional-Integral (PI) controller is applied to control each robot so it can move in a desired trajectory. The fuzzy logic control (FLC) is involved to tune the gain of PI controller to optimize the performance. Three protective robots and nine soldiers are used to evaluate the algorithm in simulation. The proposed algorithm will provide a platoon soldiers with optimal protection encirclement and enhance their safety. The simulation results show good performance using the proposed controller.

关键词： Robot kinematics Mobile robots Wheels Task analysis Fuzzy logic Kinematics

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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A New LMI-Based controller Design Method for Uncertain Differential Repetitive Processes 1

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20th Polish control Conference, PCC 2020

作者： Maniarski, Robert Paszke, Wojciech Rogers, Eric Institute of Control and Computation Engineering University of Zielona Góra Szafrana 2 Zielona Góra65-516 Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Szafrana 2 Zielona Góra65-516 Poland School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

ISBN: (数字)9783030509361

ISBN: (纸本)9783030509354

The paper develops new results on stability analysis and control law design for differential linear repetitive processes. These results are based on new dilated LMI characterizations for stability along the pass where auxiliary slack variables with full structure are employed. This provides additional flexibility to the solution. The results are also easily extended to processes with norm-bounded uncertainties. It is also shown that the generalized Kalman-Yakubovich-Popov lemma can be used to obtain stability and controller design procedures in which performance specifications are imposed over finite frequency ranges. Sufficient conditions for the existence of a robust controller in this setting are established. Finally, a simulation example is given to illustrate the merits of the new design. © 2020, Springer Nature Switzerland AG.

关键词： Linear matrix inequalities

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An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

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Signal Transduction and Targeted Therapy 2021年第5期6卷 1585-1600页

作者： Yiyue Ge Tingzhong Tian Suling Huang Fangping Wan Jingxin Li Shuya Li Xiaoting Wang Hui Yang Lixiang Hong Nian Wu Enming Yuan Yunan Luo Lili Cheng Chengliang Hu Yipin Lei Hantao Shu Xiaolong Feng Ziyuan Jiang Yunfu Wu Ying Chi Xiling Guo Lunbiao Cui Liang Xiao Zeng Li Chunhao Yang Zehong Miao Ligong Chen Haitao Li Hainian Zeng Dan Zhao Fengcai Zhu Xiaokun Shen Jianyang Zeng Institute for Interdisciplinary Information Sciences Tsinghua UniversityBeijingChina NHC Key laboratory of Emeric Pathogenic Microbiology Jiangsu Provincial Center for Diseases Control and PreventionNanjingJiangsu ProvinceChina Shanghai Institute of Materia Medica Chinese Academy of SciencesShanghaiChina Silexon Al Technology Co. Ltd.NanjingJiangsu ProvinceChina Department of Computer Science University of Illinois at Urbana-ChampaignIllinoisILUSA School of Pharmaceutical Sciences Tsinghua UniversityBeijingChina School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanHubei ProvinceChina Institute of Pathology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina Department of Automation Tsinghua UniversityBeijingChina Inner Mongolia Alashan League Organization Establishment Committee Office Electronic Support Center AlashanInner MongoliaChina Convalife(Shanghai)Co. Ltd.ShanghaiChina Advanced Innovation Center for Human Brain Protection Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Beijing Advanced Innovation Center for Structural Biology Tsinghua-Peking Joint Center for Life SciencesDepartment of Basic Medical SciencesSchool of MedicineTsinghua UniversityBeijingChina Center for Global Health Nanjing Medical UniversityNanjingJiangsu ProvinceChina

The global spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)requires an urgent need to find effective therapeutics for the treatment of coronavirus disease 2019(COVID-19).In this study,we developed an integrative drug repositioning framework,which fully takes advantage of machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph,literature and transcriptome data to discover the potential drug candidates against *** in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1(PARP1)inhibitor,CVL218,currently in Phase I clinical trial,may be repurposed to treat *** in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic *** addition,we showed that CVL218 can interact with the nucleocapsid(N)protein of SARS-CoV-2 and is able to suppress the LPS-induced production of several inflammatory cytokines that are highly relevant to the prevention of immunopathology induced by SARS-CoV-2 infection.

关键词： prevention respiratory acute

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Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

arXiv

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arXiv 2022年

作者： Li, Yang Wei, Xinhao Li, Yuanzheng Dong, Zhaoyang Shahidehpour, Mohammad The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States The ECE Department The King Abdulaziz University Saudi Arabia

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. Copyright © 2022, The Authors. All rights reserved.

关键词： Smart power grids

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Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

arXiv

引用

arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

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