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2011 International Conference on Mechanical engineering, Materials and Energy, ICMEME 2011

作者： Wang, Hongyan Shan, Xiaobiao Xie, Tao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China College of Computer and Control Engineering Qiqihar University Qiqihar 161006 China

ISBN: (纸本)9783037853405

The impedance matching and the optimization of power from a circular piezoelectric energy harvester with a central-attached mass are studied. A finite element model is constructed to analyze the electrical equivalent impedance of the circular piezoelectric energy harvester. Furthermore, the complex conjugate matching load is used to extract the maximum output power of the energy harvester. The power output from complex conjugate matching load is compared with the power output from the resistive matching load and a constant resistance, separately. The results suggest that the complex conjugate matching can result in a significant increase of the output power for all frequencies. The effective bandwidth of the piezoelectric energy harvester is extended significantly. © (2012) Trans Tech Publications, Switzerland.

关键词： Finite element method

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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PHD filter for multi-target tracking by variational Bayesian approximation

PHD filter for multi-target tracking by variational Bayesian...

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IEEE Annual Conference on Decision and control

作者： Wenling Li Yingmin Jia Junping Du Jun Zhang Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781467357159

In this paper, we address the problem of multitarget tracking with unknown measurement noise variance parameters by the probability hypothesis density (PHD) filter. Based on the concept of conjugate prior distributions for noise statistics, the inverse-Gamma distributions are employed to describe the dynamics of the noise variance parameters and a novel implementation to the PHD recursion is developed by representing the predicted and the posterior intensities as mixtures of Gaussian-inverse-Gamma terms. As the target state and the noise variance parameters are coupled in the likelihood functions, the variational Bayesian approximation approach is applied so that the posterior is derived in the same form as the prior and the resulting algorithm is recursive. A numerical example is provided to illustrate the effectiveness of the proposed filter.

关键词： Nickel

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State estimation for jump Markov linear systems with uncompensated biases

State estimation for jump Markov linear systems with uncompe...

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American control Conference

作者： Wenling Li Yingmin Jia Junping Du Jun Zhang Deyuan Meng Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China. Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479901777

This paper studies the problem of state estimation for jump Markov linear systems with uncompensated biases. By describing the state and the measurement biases as additive random variables, a suboptimal filter has been developed by applying the basic interacting multiple model (IMM) approach. To derive a precise representation of the biases contributions to the state estimation, three auxiliary matrices are introduced with respect to the correlation between the state estimation errors and the biases, which helps to derive mode-conditioned estimates in the framework of the IMM. A numerical example involving tracking a maneuvering target is provided to compare the performance of the proposed filter with that of the augmented state filter.

关键词： Jump Markov linear system Interacting multiple model Uncompensated bias State estimation Bias uncompensated maneuvering target Linear system interacting boson model Markov jump IMM

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Finite-time consensus control for multiple manipulators with unmodeled dynamics

Finite-time consensus control for multiple manipulators with...

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American control Conference

作者： Bin Zhang Yingmin Jia Junping Du Jun Zhang Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479901777

This paper is devoted to the finite-time control problem for multiple manipulators, where unmodeled dynamics is taken into consideration. An effective coordinated control strategy is introduced, under which distributed protocols with continuous feedbacks are proposed. By applying the homogeneous theory for stability analysis, it is proven that the multi-robot system can be globally finite-time stabilized through our protocols. Numerical simulations on four manipulators with two degrees of freedom are presented to validate the effectiveness of the control strategy.

关键词： unmodeled dynamics control strategy Manipulators two degrees of freedom multi-robot systems Stability analysis distributed protocol

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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Online semantic mapping of urban environments

Online semantic mapping of urban environments

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International Conference on Spatial Cognition, SC 2012

作者： Mitsou, Nikos De Nijs, Roderick Lenz, David Frimberger, Johannes Wollherr, Dirk Kühnlenz, Kolja Tzafestas, Costas Technische Universität München Munich D-80290 Germany School of Electrical and Computer Engineering Division of Signals Control and Robotics National Technical University of Athens Greece

ISBN: (纸本)9783642327315

In this paper we present an integrated approach for efficient online 3D semantic map building of urban environments and the subsequent extraction of qualitative spatial relationships between the different objects in the scene. We split this process into three stages, where we combine a state of the art image segmentation and classification algorithm with an online clustering algorithm to obtain a coherent representation of the environment. Finally, a graph representation is extracted which can then be used for spatial reasoning and human robot interaction. We present first results from data collected by a mobile robot which operates in city areas. © 2012 Springer-Verlag.

关键词： Clustering algorithms

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Potential Function Based Multi-Agent Formation control in 3D Space

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IFAC Proceedings Volumes 2012年第22期45卷 682-689页

作者： Marko Bunic Stjepan Bogdan University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering LARICS–Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia

This paper presents the extension of the previously proposed method for multi-agent formation control based on potential function. The method derived for 2D space is extended to 3D. It has been shown that the control algorithm keeps all the properties of the original scheme in case of multi-agent formation moving in 3D. An adaptation mechanism that assures avoidance of unwanted stable equilibria, used in 2D, is implemented in the same form for 3D formations. The obtained simulation results demonstrate stable behavior of the system for various sets of parameters - the desired 3D formation is reached in finite time and maintained during trajectory execution.

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Mechanical properties of boron nitride nanocones

Mechanical properties of boron nitride nanocones

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作者： Tian, Y. Wei, R. Eichhorn, V. Fatikow, S. Shirinzadeh, B. Zhang, D. School of Mechanical Engineering Tianjin University Tianjin 300072 China Division of Microrobotics and Control Engineering University of Oldenburg 26111 Oldenburg Germany Robotics and Mechatronics Research Laboratory Department of Mechanical and Aerospace Engineering Monash University Clayton VIC 3800 Australia

Using classic molecular dynamics simulation, the mechanical properties of boron nitride nanocones (BNNCs) have been systematically investigated. The influences of the apex angle, cone height on tensile, and compressive behavior of BNNCs under axial strains are analyzed. The failure strains and strain energy per atom of BNNCs decrease with the increasing cone height, whereas the failure forces almost remain constant for BNNCs under axial tensile strains. For the buckling analyses of BNNCs, the critical strain and critical axial force reduce significantly with the increase of the apex angle. The increasing cone height can also significantly decrease the critical strain of BNNCs and only slightly affects the critical force of BNNCs. The cone height has little influence on the resulting buckling patterns;however, the apex angle has a significant effect on the buckling patterns of the BNNCs. From the computational analyses, it is noted that there exist three deformation patterns, i.e., fourfold rotational symmetric, threefold rotational symmetric, and reflection symmetric modes for the BNNC with an apex angle of 83.6° and the former pattern will gradually transform to the latter pattern during the postbuckling stage. On the contrary, there is only one reflection symmetric fin-like buckling pattern for the BNNC with an apex angle of 39.8°. © 2012 American Institute of Physics.

关键词： Boron nitride

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Robustness and Generalization of Model-Free Learning for Robot Kinematic control using a Nested-Hierarchical Multi-Agent Topology

Robustness and Generalization of Model-Free Learning for Rob...

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IEEE RAS & EMBS International Conference on Biomedical robotics and Biomechatronics

作者： John N. Karigiannis Costas S. Tzafestas Faculty of Electrical and Computer Engineering Division of Signals Control and Robotics National Technical University of Athens (NTUA)

ISBN: (纸本)9781457711992

This paper focuses on evaluating the robustness and knowledge generalization properties of a model-free learning mechanism, applied for the kinematic control of robot manipulation chains based on a nested-hierarchical multi-agent architecture. In the proposed topology, the agents correspond to independent degrees-of-freedom (DOF) of the system, managing to gain experience over the task that they collaboratively perform by continuously exploring and exploiting their state-to-action mapping space. Each agent forms a local (partial) view of the global system state and task progress, through a recursive learning process. By organizing the agents in a nested topology, the goal is to facilitate modular scaling to more complex kine-matic topologies, with loose control coupling among the agents. Reinforcement learning is applied within each agent, to evolve a local state-to-action mapping in a continuous domain, thus leading to a system that exhibits developmental properties. This work addresses problem settings in the domain of kinematic control of dexterous-redundant robot manipulation systems. The numerical experiments performed consider the case of a single-linkage open kinematic chain, presenting kinematic redundancies given the desired task-goal. The focal issue in these experiments is to assess the capacity of the proposed multi-agent system to progressively and autonomously acquire cooperative sensorimotor skills through a self-learning process, that is, without the use of any explicit model-based planning strategy. In this paper, generalization and robustness properties of the overall multi-agent system are explored. Furthermore, the proposed framework is evaluated in constrained motion tasks, both in static and non-static environments. The computational cost of the proposed multi-agent architecture is also assessed.

关键词： Multi-agent systems Generalization kinematics Agents Robot Robustness topology Learning processes

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