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Applications of nanogenerators for biomedical engineering and healthcare systems

InfoMat 2022年第2期4卷 53-109页

作者： Wanli Wang Jinbo Pang Jie Su Fujiang Li Qiang Li Xiaoxiong Wang Jingang Wang Bergoi Ibarlucea Xiaoyan Liu Yufen Li Weijia Zhou Kai Wang Qingfang Han Lei Liu Ruohan Zang Mark HRümmeli Yang Li Hong Liu Han Hu Gianaurelio Cuniberti College of Electrical Engineering Qingdao UniversityQingdaoChina Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinanChina College of Electronic Information Qingdao UniversityQingdaoChina Department of Pediatric Surgery The Affiliated Hospital of Qingdao UniversityQingdaoChina College of Physics Qingdao UniversityQingdaoChina Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresdenGermany Center for Advancing Electronics Dresden Technische Universität DresdenDresdenGermany College of Biological Science and Technology University of JinanJinanChina School of Chemistry and Chemical Engineering University of JinanShandongJinanChina College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhouChina Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhouChina Centre of Polymer and Carbon Materials Polish Academy of SciencesZabrzePoland Institute for Complex Materials IFW DresdenDresdenGermany Institute of Environmental Technology VŠB-Technical University of OstravaOstravaCzech Republic School of Information Science and Engineering University of JinanJinanChina Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinanChina State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong UniversityJinanChina College of Chemical Engineering China University of Petroleum(East China)QingdaoChina Dresden Center for Computational Materials Science Technische Universität DresdenDresdenGermany The Dresden Center for Intelligent Materials(DCIM) Technische Universität DresdenDresdenGermany

The dream of human beings for long living has stimulated the rapid development of biomedical and healthcare ***,conventional biomedical and healthcare devices have shortcomings such as short service life,large equipment size,and high potential safety ***,the power supply for conventional implantable device remains predominantly *** emerging nanogenerators,which harvest micro/nanomechanical energy and thermal energy from human beings and convert into electrical energy,provide an ideal solution for self-powering of biomedical *** combination of nanogenerators and biomedicine has been accelerating the development of self-powered biomedical *** article first introduces the operating principle of nanogenerators and then reviews the progress of nanogenerators in biomedical applications,including power supply,smart sensing,and effective ***,the microbial disinfection and biodegradation performances of nanogenerators have been ***,the protection devices have been discussed such as face mask with air filtering function together with real-time monitoring of human health from the respiration and heat ***,the nanogenerator devices have been categorized by the types of mechanical energy from human beings,such as the body movement,tissue and organ activities,energy from chemical reactions,and gravitational potential ***,the challenges and future opportunities in the applications of nanogenerators are delivered in the conclusive remarks.

关键词： biomedical engineering healthcare implantable devices nanogenerators self-powered devices sensors

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A RNNs-based algorithm for decentralized-partial-consensus constrained optimization

arXiv

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arXiv 2021年

作者： Xia, Zicong Liu, Yang Qiu, Jianlong Ruan, Qihua Cao, Jinde College of Mathematics and Information Science Zhejiang Normal University Jinhua321004 China School of Automation and Electrical Engineering Key Laboratory of Complex Systems Intelligent Computing in Universities of Shandong Linyi University Linyi276005 China School of Mathematics and Finance Putian University Putian351100 China Jiangsu Provincial Key Laboratory of Networked Collective Intelligence The School of Mathematics Southeast University Nanjing210096 China

This technical note proposes the decentralized-partial-consensus optimization with inequality constraints, and a continuous-time algorithm based on multiple interconnected recurrent neural networks (RNNs) is derived to solve the obtained optimization problems. First, the partial-consensus matrix originating from Laplacian matrix is constructed to tackle the partial-consensus constraints. In addition, using the nonsmooth analysis and Lyapunov-based technique, the convergence property about the designed algorithm is further guaranteed. Finally, the effectiveness of the obtained results is shown while several examples are presented. Copyright © 2021, The Authors. All rights reserved.

关键词： Matrix algebra

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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Science China(Information Sciences) 2018年第9期61卷 232-240页

This paper mainly analyzes the set stability of switched Boolean networks(SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop switching. First, the definitions of set stability are proposed for SBNs with such switching signals. Then, we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant set. Furthermore, the corresponding set stability conditions for SBNs are given in each case. In addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching signals. Finally, the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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Double Deep Q-learning for Anti-saturation Attack Problem of Warship Group

Double Deep Q-learning for Anti-saturation Attack Problem of...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wei Li Gang Xiong Hao Tao Yunjun Han Fang Wang Xisong Dong Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China China Ship Development and Design Center Wuhan China School of Control Science and Engineering (CSE) Shandong University Jinan China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China

Anti-saturation attack (ASA) strategy is vital for the survival of a warship group, and attracts the focus of many researchers. In this paper, the dynamics of ASA is formulated as a Markov Decision Process (MDP) with an enhanced states space since those characters are involved, such as the formation and detection and interception areas of warship group. A reinforcement learning method (Double Deep Q-leaning, DDQN) is developed to solve the problem and deal with the curse of dimensionality whereby the cost-to-go value is calculated by a marine engagement simulation system. A heuristic defense algorithm guided by field expert knowledge is designed for comparison. The experimental results show that the DDQN method performs better in anti-saturation attack scenarios.

关键词： Industries Heuristic algorithms Digital twin Conferences Knowledge based systems Reinforcement learning Markov processes

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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中国科学（信息科学） 2018年第9期61卷 226-234页

作者： Xiaohua LI Jianquan LU Jianlong QIU Xiangyong CHEN Xiaodi LI Fuad E.ALSAADI School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China School of Mathematics Southeast University Nanjing 210096 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics Southeast University Nanjing 210096 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China Department of Electrical and Computer Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia

This paper mainly analyzes the set stability of switched Boolean networks (SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop ***,the definitions of set stability are proposed for SBNs with such switching ***,we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant ***,the corresponding set stability conditions for SBNs are given in each *** addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching ***,the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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The Prediction of the Epidemic Trend of COVID-19 Using Neural Networks

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IFAC-PapersOnLine 2020年第5期53卷 857-862页

作者： Jing Yang Zhen Shen Xisong Dong Xiuqin Shang Wei Li Gang Xiong J. Yang is with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with College of Information Sciences & Technology Beijing University of Chemical Technology Beijing 100029 China. Z. Shen is with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with the Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao Shandong 266113 China. X. Dong X. Shang and W. Li are with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China. G. Xiong is with Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with the Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan Guangdong 523808 China.

In this paper, a BP neural network and an LSTM network are applied respectively to the prediction of Coronavirus Disease 2019 (COVID-19) in Wuhan, China and South Korea. The methods do not require specific theories of modelling and the predicted values can be obtained as long as the conventional parameters are set. The mean absolute percentage error (MAPE) of all the experiments are below 5% and the values of the determinable coefficient R are all larger than 0.9. The experiments show that the models can fit the actual values well and make relatively accurate predictions. As of March 29, 2020, the cumulative number of confirmed cases in Wuhan is expected to reach 50,068 using BP neural networks and 49,972 using LSTM network, respectively. As of April 13, 2020, the cumulative number of confirmed cases in South Korea is expected to reach 8,862 using BP neural networks and 8,716 using LSTM network, respectively. The models of neural networks are effective in predicting the trend of the COVID-19 epidemic, which is meaningful to prevent and control the epidemic.

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Outer synchronization in drive-response cyber-physical systems with time-varying delays via adaptive control

Outer synchronization in drive-response cyber-physical syste...

引用

Chinese Automation Congress

作者： Jianbao Zhang Deqian Fu Tongxing Li Xiao Chen Jianlong Qiu Ancai Zhang Xiangyong Chen School of Information Science and Engineering Linyi University Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi China

In this paper, a cyber-physical system under attack is modeled by a descriptor system with unknown inputs. By partitioning the descriptor system into several disjoint areas, we build a drive-response descriptor system and discuss the adaptive control problem in different situations based on Lyapunov stability theory. First, parameter update laws are presented to identify the unknown system parameters. Second, adaptive controllers are designed to deal with the problem of outer synchronization between the drive system and the response system. Third, it is proved that the effects of unknown inputs and time-varying delays are compensated by the adaptive controllers. Finally, several numerical simulations are carried out to illustrate the effectiveness of the update laws and adaptive controllers.

关键词： Adaptive control Outer synchronization Drive-response system Lyapunov stability theory Time-varying delay

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Finite-time Switching Synchronization of Four Real Chaotic systems with Combination Mode

Finite-time Switching Synchronization of Four Real Chaotic S...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Weiqi Qin Yanfeng Wang Tianze Li Ming Guo Xiangyong Chen Xinru Tong Affiliated Hospital of Shandong Medical College Linyi P. R. China School of Engineering Huzhou University Huzhou P. R. China School of Automation and Electrical Engineering Linyi University Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi P. R. China College of Mathematics and Systems Science Xinjiang University Urumqi P. R. China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

This paper mainly studies the problem of finite-time switching synchronization for four real chaotic systems with combination mode. Firstly, we analyze multi-switching synchronization behavior in signal switching transmission, and the definition of finite-time combination synchronization is given by choosing the preset switching rules. And then, a novel finite time controller is designed to realize fast synchronization, and the sufficient conditions are given. Finally, numerical examples verify the effectiveness of the proposed control scheme.

关键词： Synchronization Switching systems Chaotic communication Control system synthesis

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Design of AI + Curriculum for Primary and Secondary Schools in Qingdao

Design of AI + Curriculum for Primary and Secondary Schools ...

引用

2018 Chinese Automation Congress, CAC 2018

作者： Han, Xiao Hu, Fang Xiong, Gang Liu, Xiwei Gong, Xiaoyan Niu, Xiaojie Shi, Wanruo Wang, Xinzhu Qingdao Institute of Education Sciences Qingdao China Qingdao No.2 Middle School of Shandong Province Qingdao China Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Faculty of Education Beijing Normal University Institute of Educational Technology Beijing China

ISBN: (纸本)9781728113128

We are entering a new AI era, and the development of AI technology and popularization of AI education has become the national strategy of China. The primary and secondary school students are the builder of future society, and have strong curiosity and passion to learn new things;therefore, we should make a good preparation of AI education for them and cultivate their basic AI literacy and computational thinking to adapt to the future. In this paper, from the viewpoint of thinking mode and literacy and skill training, a curriculum including basic, project, and practical types is designed. Integrating with the iSTREAM educational system proposed by Chinese Academy of Sciences, exploratory works were shown with some case studies. The applications show that AI education is helpful to enrich the study of primary and secondary school students and to prompt comprehensive quality. © 2018 IEEE.

关键词： Curricula

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Finite-time tracking consensus control for a class of nonlinear 43

Finite-time tracking consensus control for a class of nonlin...

引用

43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

作者： systems, Multi-Agent Li, Zhenxing Chen, Xiangyong Wen, Yumei Qiu, Jianlong School of Automation and Electrical Engineering Key Laboratory of Complex Systems and Intelligent Computing Linyi University of Linyi Shandong276005 China China Shanshui Cement Group Limited Jinan250307 China

ISBN: (纸本)9781538611272

In this paper, we address the finite-time tracking consensus control problem for nonlinear multi-agent systems under no-cycle communication graph. Unlike most existing works of finite-time consensus, we focus on nonlinear multi-agent systems with lower triangular subsystems. Based on the local cooperative information among neighboring agents, we propose a tracking consensus protocol ensuring that all agents achieve consensus in a finite time. Finally, we give an example to illustrate the effectiveness of the proposed protocols. © 2017 IEEE.

关键词： Multi agent systems

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