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arXiv 2017年

作者： Ouyang, Bin Xiong, Shiyun Yang, Zhi Jing, Yuhang Wang, Yongjie National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou JiangSu215123 China College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan ShanXi030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan ShanXi030024 China Department of Astronautical Science and Mechanics Harbin Institute of Technology Harbin Heilongjiang150001 China Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical Engineering and Computer Engineering University of Michigan Ann ArborMI48109 United States

Due to the distinguished properties offered by different structural phases of monolayer MoS2, phase engineering design are urgently required for achieving switchable structural phase. Strain engineering is widely accepted as a clean and flexible method, however, can not be achieved in engineering monolayer MoS2 phase transition because the critical biaxial strain required (~15%) is much larger than measured elastic limit (~11%). In this study, employing density functional theoretical calculations, it has been found out that with the forming of heterostructure between MoS2 with buckled 2D materials such as silicence, germanene and stanene, only a small strain can trigger the phase transition. As being suggested by the constructed phase stability diagram, biaxial deformation as low as 3% in MoS2/silicene and MoS2/stanene sandwich structure, would be sufficient to induce the structural phase transition in MoS2 lattice. This strain falls well within experimental elastic limit, thus would be feasible to realize in experiment. The origin of such behavior can be understood as strain induced interlayer covalent bond formation, which finally make MoS2 lattice more sensitive to external strain. This theoretical work provides one realistic route for achieving flexible phase stabilities in experimental design. Copyright © 2017, The Authors. All rights reserved.

关键词： Molybdenum compounds

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26th Annual computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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The status of KAGRA underground cryogenic gravitational wave telescope

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Journal of Physics: Conference Series 2019年第1期1342卷

作者： T. Akutsu M. Ando A. Araya N. Aritomi H. Asada Y. Aso S. Atsuta K. Awai M. A. Barton K. Cannon K. Craig W. Creus K. Doi K. Eda Y. Enomoto R. Flaminio Y. Fujii M.-K. Fujimoto T. Furuhata S. Haino K. Hasegawa K. Hashino K. Hayama S. Hirobayashi E. Hirose A. H. Hsieh Y. Inoue K. Ioka Y. Itoh T. Kaji T. Kajita M. Kakizaki M. Kamiizumi S. Kambara N. Kanda S. Kanemura M. Kaneyama G. Kang J. Kasuya Y. Kataoka N. Kawai S. Kawamura C. Kim H. Kim J. Kim Y. Kim N. Kimura T. Kinugawa S. Kirii Y. Kitaoka Y. Kojima K. Kokeyama K. Komori K. Kotake R. Kumar H. Lee Y. Liu N. Luca E. Majorana S. Mano M. Marchio T. Matsui F. Matsushima Y. Michimura O. Miyakawa T. Miyamoto A. Miyamoto K. Miyo S. Miyoki W. Morii S. Morisaki Y. Moriwaki T. Morozumi M. Musha S. Nagano K. Nagano K. Nakamura T. Nakamura H. Nakano M. Nakano K. Nakao T. Narikawa L.Nguyen Quynh W.-T. Ni T. Ochi J. Oh S. Oh M. Ohashi N. Ohishi M. Ohkawa K. Okutomi K. Oohara F. E.Peña Alleano I. Pinto N. Sago M. Saijo Y. Saito K. Sakai Y. Sakai Y. Sasaki M. Sasaki S. Sato T. Sato Y. Sekiguchi N. Seto M. Shibata T. Shimoda H. Shinkai A. Shoda K. Somiya E. Son A. Suemasa T. Suzuki H. Tagoshi H. Takahashi R. Takahashi A. Takamori H. Takeda H. Tanaka K. Tanaka T. Tanaka D. Tatsumi T. Tomaru T. Tomura F. Travasso K. Tsubono S. Tsuchida N. Uchikata T. Uchiyama T. Uehara S. Ueki K. Ueno T. Ushiba M. H. P. M. van Putten H. Vocca S. Wada T. Wakamatsu T. Yamada S. Yamamoto T. Yamamoto K. Yamamoto A. Yamamoto J. Yokoyama T. Yokozawa T. H. Yoon H. Yuzurihara S. Zeidler Z.-H. Zhu KAGRA Collaboration National Astronomical Observatory of Japan Mitaka Tokyo 181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo 113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo 113-0032 Japan Department of Advanced Physics Hirosaki University Hirosaki Aomori 036-8561 Japan National Astronomical Observatory of Japan Hida Gifu 506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo 152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu 506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo 113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba 277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Department of Physics University of Toyama Toyama Toyama 930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama 930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto 606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka 558-8585 Japan Department of Physics Osaka University Toyonaka Osaka 560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Korea Astronomy and Space Science Institute (KASI) Yuseong Daejeon 34055 Korea National Institute for Mathematical Sciences Daejeon 34047 Korea Department of Computer Simulation Inje University Gimhae Gyeongsangnam 50834 Korea Department of Physics and Astronomy Seoul National University Seoul 151-742 Korea High Energy Accelerator Research Organization Tsukuba Ibaraki 305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima 903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka 814-0180 Japan Department of Advanced Materials Science University of Tokyo Kashiwa Chiba 277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma 00185 Italy Department of Ma

KAGRA is a 3-km interferometric gravitational wave telescope located in the Kamioka mine in Japan. It is the first km-class gravitational wave telescope constructed underground to reduce seismic noise, and the first km-class telescope to use cryogenic cooling of test masses to reduce thermal noise. The construction of the infrastructure to house the interferometer in the tunnel, and the initial phase operation of the interferometer with a simple 3-km Michelson configuration have been completed. The first cryogenic operation is expected in 2018, and the observing runs with a full interferometer are expected in 2020s. The basic interferometer configuration and the current status of KAGRA are described.

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Synchronization of Lienard-type oscillators in uniform electrical networks

Synchronization of Lienard-type oscillators in uniform elect...

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American control Conference

作者： Mohit Sinha Florian Dorfler Brian B. Johnson Sairaj V. Dhople Department of Electrical and Computer Engineering at the University of Minnesota (UMN) Minneapolis United States of America Automatic Control Laboratory at ETH Zurich Switzerland Power Systems Engineering Center at the National Renewable Energy Laboratory (NREL) Golden CO United States of America

ISBN: (纸本)9781467386838

This paper presents a condition for global asymptotic synchronization of Lienard-type nonlinear oscillators in uniform LTI electrical networks with series R-L circuits modeling interconnections. By uniform electrical networks, we mean that the per-unit-length impedances are identical for the interconnecting lines. We derive conditions for global asymptotic synchronization for a particular feedback architecture where the derivative of the oscillator output current supplements the innate current feedback induced by simply interconnecting the oscillator to the network. Our proof leverages a coordinate transformation to a set of differential coordinates that emphasizes signal differences and the particular form of feedback permits the formulation of a quadratic Lyapunov function for this class of networks. This approach is particularly interesting since synchronization conditions are difficult to obtain by means of quadratic Lyapunov functions when only current feedback is used and for networks composed of series R-L circuits. Our synchronization condition depends on the algebraic connectivity of the underlying network, and reiterates the conventional wisdom from Lyapunov- and passivity-based arguments that strong coupling is required to ensure synchronization.

关键词： Oscillators Synchronization Integrated circuit interconnections Integrated circuit modeling Lyapunov methods Limit-cycles Mathematical model Oscillators integrated circuit interconnections integrated circuit modelling Lyapunov methods Liapunov function Electric circuits Power grids Mathematical Model current feedback

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Driving fatigue prediction with pre-event electroencephalography (EEG) via a recurrent fuzzy neural network

Driving fatigue prediction with pre-event electroencephalogr...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Yu-Ting Liu Shang-Lin Wu Kuang-Pen Chou Yang-Yin Lin Jie Lu Guangquan Zhang Wen-Chieh Lin Chin-Teng Lin Brain Research Center Institute of Electrical Control Engineering Institute of Computer Science and Engineering Electronic Systems Research Division National Chung-Shan Institute of Science and Technology (NCSIST) Taoyuan Taiwan FacuIty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9781509006274

We propose an electroencephalography (EEG) prediction system based on a recurrent fuzzy neural network (RFNN) architecture to assess drivers' fatigue degrees during a virtual-reality (VR) dynamic driving environment. Prediction of fatigue degrees is a crucial and arduous biomedical issue for driving safety, which has attracted growing attention of the research community in the recent past. Meanwhile, combined with the benefits of measuring EEG signals facilitates, many EEG-based brain-computer interfaces (BCIs) have been developed for use in real-time mental assessment. In the literature, EEG signals are severely blended with stochastic noise; therefore, the performance of BCIs is constrained by low resolution in recognition tasks. For this rationale, independent component analysis (ICA) is usually used to find a source mapping from original data that has been blended with unrelated artificial noise. However, the mechanism of ICA cannot be used in real-time BCI design. To overcome this bottleneck, the proposed system in this paper utilizes a recurrent self-evolving fuzzy neural work (RSEFNN) to increase memory capability for adaptive noise cancellation when assessing drivers' mental states during a car driving task. The experimental results without the use of ICA procedure indicate that the proposed RSEFNN model remains superior performance compared with the state-of-the-arts models.

关键词： Electroencephalography Fatigue Real-time systems Vehicles Fuzzy neural networks Signal processing algorithms Integrated circuits

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A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

A motor imagery based brain-computer interface system via sw...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Shang-Lin Wu Yu-Ting Liu Kuang-Pen Chou Yang-Yin Lin Jie Lu Guangquan Zhang Chun-Hsiang Chuang Wen-Chieh Lin Chin-Teng Lin Brain Research Center Institute of Electrical Control Engineering Institute of Computer Science and Engineering Electronic Systems Research Division National Chung-Shan Institute of Science and Technology (NCSIST) Taoyuan Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9781509006274

A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications.

关键词： Electroencephalography Feature extraction Wireless sensor networks Wireless communication Electrodes Particle swarm optimization Microcontrollers

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Online policy iterations for optimal control of input-saturated systems

Online policy iterations for optimal control of input-satura...

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American control Conference

作者： Simone Baldi Giorgio Valmorbida Antonis Papachristodoulou Elias B. Kosmatopoulos Delft Center for Systems and Control Delft University of Technology 2628CD The Netherlands Department of Engineering Science Control Group University of Oxford Parks Road OX1 3PJ U.K. Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece

ISBN: (纸本)9781467386838

This work proposes an online policy iteration procedure for the synthesis of sub-optimal control laws for uncertain Linear Time Invariant (LTI) Asymptotically Null-controllable with Bounded Inputs (ANCBI) systems. The proposed policy iteration method relies on: a policy evaluation step with a piecewise quadratic Lyapunov function in both the state and the deadzone functions of the input signals;a policy improvement step which guarantees at the same time close to optimality (exploitation) and persistence of excitation (exploration). The proposed approach guarantees convergence of the trajectory to a neighborhood around the origin. Besides, the trajectories can be made arbitrarily close to the optimal one provided that the rate at which the the value function and the control policy are updated is fast enough. The solution to the inequalities required to hold at each policy evaluation step can be efficiently implemented with semidefinite programming (SDP) solvers. A numerical example illustrates the results.

关键词： Optimal control Linear systems Convergence Asymptotic stability Lyapunov methods Estimation Trajectory trajectory Optimal control Lyapunov methods asymptotic stability region Linear system Converge iterative methods control strategy Policies

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Robust Decentralized control of Interconnected Nonlinear Systems Subject to Uncertainties and Disturbances via Generalized Extended State Observers 34

Robust Decentralized Control of Interconnected Nonlinear Sys...

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第三十四届中国控制会议

作者： ZHANG Chuanlin YANG ning HE Shuaipeng JIA Ruting Shanghai Engineering Research Center of Intelligent Management and Control for Power Process College of Automation EngineeringShanghai University of Electric Power Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Electrical and Computer Engineering Department California State University

ISBN: (纸本)9789881563897

This paper studies the problem of robust decentralized control for a class of large-scale interconnected systems subject to uncertainties and disturbances via a generalized active disturbance rejection control method. First, a novel extended state observer(ESO) is constructed separately for each subsystem with less dependence of the precise system information and structure. Second, an explicit formula of the decentralized active disturbance rejection control(DADRC) law is presented by utilizing the output feedback domination approach. It is shown that by a delicate analysis procedure, the closed-loop system can be rendered semi-globally asymptotically stable only using decentralized output feedback anti-disturbance controller. Numerical simulations show the efficiency of the proposed method.

关键词： output feedback control global stabilization disturbance rejection control extended state observer

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Counterattack detection in broadcast soccer videos using camera motion estimation

Counterattack detection in broadcast soccer videos using cam...

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2015 International Symposium on Artificial Intelligence and Signal Processing, AISP 2015

作者： Sigari, Mohamad-Hoseyn Soltanian-Zadeh, Hamid Kiani, Vahid Pourreza, Amid-Reza Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Machine Vision Research Laboratory Computer Engineering Department Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781479988174

This paper presents a new method for counterattack detection using estimated camera motion and evaluates some classification methods to detect this event. To this end, video is partitioned to shots and view type of each shot is recognized first. Then, relative pan of the camera during far-view and medium-view shots is estimated. After weighting of pan value of each frame according to the type of shots, the video is partitioned to motion segments. Then, motion segments are refined to achieve better results. Finally, the features extracted from consecutive motion segments are investigated for counterattack detection. We propose two methods for counterattack detection: (1) rule-based (heuristic rules) and (2) SVM-based. Experiments show that the SVM classifier with linear or RBF kernel results in the best results. © 2015 IEEE.

关键词： Motion estimation

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TOWARD PERCEPTUAL DEEP LEARNING–BASED ABNORMAL BEHAVIOR PATTERN ANALYSIS FOR PATIENTS WITH ALZHEIMER’S DISEASE

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Alzheimer's & Dementia 2018年第7期14卷 P548-P548页

作者： Jeonghwan Gwak Jong-In Song Kiseon Kim Moongu Jeon Cheolbin Park Hyunsu Jeong Kyu Yeong Choi Jung Eun Park Jung Sup Lee Byeong Chae Kim Kun Ho Lee Biomedical Research Institute & Department of Radiology Seoul National University Hospital Seoul Republic of South Korea School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju Republic of South Korea Department of Premedics Chosun University Gwangju Republic of South Korea BK21-plus Research Team for Bioactive Control Technology Chosun University Gwangju Republic of South Korea Department of Life Science Chosun University Gwangju Republic of South Korea Department of Biomedical Science Chosun University Gwangju Republic of South Korea National Research Center for Dementia Chosun University Gwangju Republic of South Korea Department of Neurology Chonnam National University Medical School Gwangju Republic of South Korea

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