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

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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Author Correction: The use of microfluidic spinning fiber as an ophthalmology suture showing the good anastomotic strength control

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Scientific reports 2018年第1期8卷 13293页

作者： DoYeun Park In Sung Yong Kyong Jin Cho Jie Cheng Youngmee Jung Soo Hyun Kim Sang-Hoon Lee KU-KIST Graduate School of Converging Science and Technology Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. Department of Bio and Brain Engineering KAIST Daejeon 34141 Republic of Korea. Department of Ophthalmology College of Medicine Dankook University 119 Danaeo-ro Dongnam-gu Cheonan-si Chungcheongnam-do 31116 Republic of Korea. MOE Key Laboratory of Spectrochemical Analysis & Instrumentation Collaborative Innovation Center of Chemistry for Energy Materials Key Laboratory for Chemical Biology of Fujian Province State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering Xiamen University Xiamen 361005 China. Biomaterials Research Center Korea Institute of Science and Technology 5 Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Republic of Korea. KU-KIST Graduate School of Converging Science and Technology Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. soohkim@kist.re.kr. Biomaterials Research Center Korea Institute of Science and Technology 5 Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Republic of Korea. soohkim@kist.re.kr. School of Biomedical Engineering College of Health Science Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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Optimal DNA structure of reverse-hairpin beacons for label-free and positive surface enhanced Raman scattering assays: retraction

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Optical materials Express 2017年第9期7卷 3136-3136页

作者： Jisun Ki Jinyoung Kim Seeungmin Han Eunji Jang Taeksu Lee Jung-Sub Wi Tae Geol Lee Woonsung Na Daesub Song Seungjoo Haam Department of Chemical and Biomolecular Engineering Yonsei University Yonsei-ro 50 Seoul 120-749 South Korea Department of Radiology College of Medicine Yonsei University Seoul 120-752 South Korea Nano-Mechanical Systems Research Center Korea Institute of Machinery and Materials Daejeon 305-343 South Korea Center for Nano-Bio Measurement World Class Laboratory Korea Research Institute of Standards and Science Daejeon 34113 South Korea Department of Pharmacy College of Pharmacy Korea University Sejong South Korea

The referenced article [Opt. Mater. Express 7 , 2352 (2017)] has been retracted.

关键词： Fluorescence Surface enhanced Raman scattering

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Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

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Chinese Journal of chemical engineering 2015年第12期23卷 1945-1950页

作者：李晨黄彪钱锋 Key Laboratory of Advanced Control and Optimization Ministry of EducationEast China University of Science and Technology Department of Chemical and Materials Engineering University of Alberta

control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

关键词： control performance monitoring Kernel density estimation Hellinger distance Nonlinear system

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Magnetoelectricity: Unleashing the Full Potential of Magnetoelectric Coupling in Film Heterostructures (Adv. Mater. 10/2017)

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Advanced materials 2017年第10期29卷

作者： Haribabu Palneedi Deepam Maurya Gi‐Yeop Kim Venkateswarlu Annapureddy Myoung‐Sub Noh Chong‐Yun Kang Jong‐Woo Kim Jong‐Jin Choi Si‐Young Choi Sung‐Yoon Chung Suk‐Joong L. Kang Shashank Priya Jungho Ryu Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 South Korea Functional Ceramics Group Korea Institute of Materials Science (KIMS) Changwon 51508 South Korea Bio‐Inspired Materials and Devices Laboratory (BMDL) Center for Energy Harvesting Materials and Systems (CEHMS) Virginia Tech Blacksburg VA 24061 USA Materials Modeling and Characterization Department Korea Institute of Materials Science (KIMS) Changwon 51508 South Korea Center for Electronic Materials Korea Institute of Science and Technology (KIST) Seoul 02792 South Korea KU‐KIST Graduate School of Converging Science and Technology Korea University Seoul 02841 South Korea Graduate School of EEWS Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 South Korea Korea Institute of Ceramic Engineering and Technology (KICET) Jinju 52851 South Korea

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Robust fault detection and diagnosis for multiple-model systems with uncertainties 9

Robust fault detection and diagnosis for multiple-model syst...

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9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015

作者： Zhao, Shunyi Huang, Biao Luan, Xiaoli Yin, Yanyan Liu, Fei Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

In this paper, a robust fault detection and diagnosis (FDD) method is proposed for multiple-model systems with modeling uncertainties. A compensation step is introduced to modify the mixed states and their variances obtained through the interacting multiple model (IMM) approximation and to solve the uncertainty problem. The degree of compensation is governed by a modification parameter determined by the orthogonality principle, which means that the estimation error calculated in the sub-filter using the true system models should be orthogonal to the residual error vector. To avoid over compensation in the unmatched models, a minimization procedure is used to derive the overall modification parameter. When the modification parameter is equal to one, the proposed method reduces to the IMM algorithm. An experiment is conducted through the ball and tube system to demonstrate the effectiveness of the proposed method. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Fault detection

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Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Hellinger distance based probability distribution approach t...

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作者： Li, Chen Huang, Biao Qian, Feng Key Laboratory of Advanced Control and Optimization Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities (e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method. © 2015 The chemical Industry and engineering Society of China, and chemical Industry Press. All rights reserved.

关键词： Probability distributions

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Recursive State Estimation for Stochastic Hybrid systems with Unknown Transition Probabilities

Recursive State Estimation for Stochastic Hybrid Systems wit...

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第26届中国过程控制会议（CPCC2015）

作者： Shunyi Zhao Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Department of Chemical and Materials Engineering University of Alberta

This paper considers the recursive state estimation problem for a class of Markov jump linear systems(JMLSs) with unknown transition probabilities(TPs). Compared with other existing recursive estimators, the underlying real but unknown TPs to be addressed in our method are allowed to be time-variant. The expectation and covariances of residual error calculated in the interacting multiple model(IMM) algorithm are computed to demonstrate that Kalman filter running under true systems can still perform satisfactorily in the presence of wrong TPs and the various mode probabilities reflect the influences of uncertain TPs. A compensation operator which heuristically modifies the posterior probabilities by adjusting a compensation parameter is then developed. A moving target tracking example of the proposed method is presented to demonstrate the effectiveness.

关键词： Recursive state estimation JMLSs unknown TPs time-variant systems IMM

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Dynamic thermal management for aerospace technology: A review and outlook 53

Dynamic thermal management for aerospace technology: A revie...

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53rd AIAA Aerospace Sciences Meeting, 2015

作者： Doty, J. Yerkes, K. Byrd, L. Murthy, J. Alleyne, A. Wolff, M. Heister, S. Fisher, T.S. Department of Materials Science University of Dayton DaytonOH United States Power and Control Division Air Force Research Laboratory Aerospace Systems Directorate WPAFB OH United States Department of Mechanical Engineering University of Texas AustinTX United States Department of Mechanical Science and Engineering University of Illinois Urbana-ChampaignIL United States Department of Mechanical and Materials Engineering Wright State University DaytonOH United States School of Aeronautics and Astronautics Purdue University West LafayetteIN United States School of Mechanical Engineering and Birck Nanotechnology Center Purdue University West LafayetteIN United States

ISBN: (数字)9781624103438

ISBN: (纸本)9781624103438

Thermal energy is composed, by definition, of randomized carriers and is often an unwanted by-product of human-engineered functions such as propulsion, communications, and directed forms of other types of energy. This inherent randomness greatly impedes the ‘orderly’ management and control of heat, particularly when compared to electrical energy (e.g., power distribution lines) and optical energy (e.g., fiber optics). The thermal conductivities of common solids, for example, span only a few orders of magnitude, whereas electrical conductivities vary by ten or more orders. Further, chemical and electrical energy can be stored and released with relative ease, while thermal storage materials and systems are typically bulky and inefficient. Motivated by critical aerospace needs to develop transformative thermal management strategies-particularly for high-flux, episodic heat loads within the tightly weight-and volume-constrained environment of aerospace vehicles-this paper provide an overview of prospective strategies and technologies that can address these challenges by exploiting the transient nature of the required cooling while also providing insights into the commensurate uncertainty quantification and control methods that will be essential to their eventual transition to practical applications. © 2015, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Temperature control

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