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Symposium on Theory of modeling and simulation - DEVS Integrative M and S Symposium, DEVS 2015, Part of the 2015 Spring simulation Multi-Conference, SpringSim 2015

作者： Fard, Mostafa D. Sarjoughian, Hessam S. School of Electrical and Computer Engineering University of Tehran Tehran Iran Arizona Center for Integrative Modeling and Simulation School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States

ISBN: (纸本)9781510810600

An integrated visual modeling and simulation tool called Component-based System modeling and simulation (CoSMoS) is extended to support behavioral specification of parallel atomic DEVS model. An approach based on Statecharts and Graphical modeling Framework has been developed and implemented for specifying behaviors of atomic models. One or more Statecharts can be developed for any atomic model and stored in a relational database. The behavioral modeling complements atomic and coupled DEVS structural modeling where families of models with semi-automated code generated for the DEVS-Suite simulator are systematically stored and retrieve. The behavioral modeling enriches visual development of models that have DEVS-compliant specifications with modular, component-based visual representations. The visual representation of hierarchal coupled models are automatically generated or restored. An example model is employed to show the degree of details supported both in visual representation and database representation. Current and future works are briefly described. © 2015 Society for modeling & simulation International (SCS).

关键词： Specifications

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Development of a Comprehensive Framework for Video-Based Safety Assessment

Development of a Comprehensive Framework for Video-Based Saf...

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IEEE International Conference on Intelligent Transportation Systems

作者： Kun Xie Chenge Li Kaan Ozbay Gregory Dobler Hong Yang An-Ti Chiang Masoud Ghandehari Department of Civil and Urban Engineering Center for Urban Science and Progress (CUSP) New York University Brooklyn 11201 USA Department of Electrical and Computer Engineering Center for Urban Science and Progress (CUSP) New York University Brooklyn 11201 USA Department of Physics Center for Urban Science and Progress (CUSP) New York University Brooklyn 11201 USA Department of Modeling Simulation and Visualization Engineering Old Dominion University Norfolk Virginia 23529 USA

ISBN: (纸本)9781509018901

In most of the traffic safety studies, both the identification of high-risk locations and the assessment of safety improvement solutions are done through the use of historical crash data. This study proposes an alternative approach that makes use of traffic conflicts extracted from traffic video recordings for safety assessment. State-of-the-art computer vision techniques are used to extract vehicle trajectories automatically from 70 hours of traffic video data at two intersections. More specifically, a modified implementation of the Kanade-Lucas-Tomasi (KLT) feature tracker is used to extract the feature points and track those feature points frame by frame. The spectral embedding and the Dirichlet process Gaussian mixture model (DPGMM) are employed to cluster feature points that belong to the same object. The combination of each vehicle's individual trajectory with all the others' trajectories is then screened to identify all the possible vehicle pairs involved in conflict risk. Traffic conflict risks are identified after the time to collision (TTC) is computed for each vehicle pair. Hourly number of conflicts are found to follow a negative binomial distribution similar to number of crashes. A strong correlation is observed between the traffic conflicts and actual crashes, and thus the validity of using conflict data extracted from videos for safety assessment can be confirmed. The proposed approach has potential transferability and can be implemented by transportation agencies in other cities.

关键词： Vehicles Safety Trajectory Vehicle crash testing Feature extraction Electronic mail computer vision

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Graphic and haptic simulation for transvaginal cholecystectomy training in NOTES

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Journal of Biomedical Informatics 2016年 60卷 410-421页

作者： Pan, Jun J. Ahn, Woojin Dargar, Saurabh Halic, Tansel Li, Bai C. Sankaranarayanan, Ganesh Roberts, Kurt Schwaitzberg, Steven De, Suvranu State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Center for Modeling Simulation and Imaging in Medicine Rensselaer Polytechnic Institute Troy United States Computer Science Department University of Central Arkansas Conway United States Gastrointestinal Surgery Yale School of Medicine Yale University New Heaven United States Department of Surgery Cambridge Health Alliance Harvard Medical School Boston United States

Background: Natural Orifice Transluminal Endoscopic Surgery (NOTES) provides an emerging surgical technique which usually needs a long learning curve for surgeons. Virtual reality (VR) medical simulators with vision and haptic feedback can usually offer an efficient and cost-effective alternative without risk to the traditional training approaches. Under this motivation, we developed the first virtual reality simulator for transvaginal cholecystectomy in NOTES (VTEST™). Methods: This VR-based surgical simulator aims to simulate the hybrid NOTES of cholecystectomy. We use a 6DOF haptic device and a tracking sensor to construct the core hardware component of simulator. For software, an innovative approach based on the inner-spheres is presented to deform the organs in real time. To handle the frequent collision between soft tissue and surgical instruments, an adaptive collision detection method based on GPU is designed and implemented. To give a realistic visual performance of gallbladder fat tissue removal by cautery hook, a multi-layer hexahedral model is presented to simulate the electric dissection of fat tissue. Results: From the experimental results, trainees can operate in real time with high degree of stability and fidelity. A preliminary study was also performed to evaluate the realism and the usefulness of this hybrid NOTES simulator. Conclusions: This prototyped simulation system has been verified by surgeons through a pilot study. Some items of its visual performance and the utility were rated fairly high by the participants during testing. It exhibits the potential to improve the surgical skills of trainee and effectively shorten their learning curve. © 2016 Elsevier Inc.

关键词： Virtual reality

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Autonomous migration of virtual machine based on OpenStack

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International Journal of Hybrid Information Technology 2016年第8期9卷 65-84页

作者： Zhou, Li Yu, Zhuoer Zhang, Jilin Wan, Jian Wu, Yusen School of Computer and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China College of Electrical Engineering Zhejiang University Hangzhou310058 China School of Information and Electronic engineering Zhejiang University of Science & Technology Hangzhou310023 China Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis HangzhouZhejiang China

For the problem of compute nodes load unbalance leads to the overload node impact VM performance and the underload node waste electrical energy. Dynamic VM consolidation is an efficient approach for improving the utilization of servers and reducing energy costs. In this paper, we introduce dynamic consolidation into OpenStack and implement AMVM based on OpenStack. AMVM collect and analyze all performance data of VM and compute node in OpenStack. Then AMVM automatically schedules VM live migrate to the most appropriate node according to the real-time load of all compute nodes. Then we use hybrid-copy instead of pre-copy in AMVM to improve the efficiency of VM live migration. Finally, we analyze the performance of hybrid-copy, hybrid-copy can reduce page faults compared with post-copy and reduce total data transferred compared with pre-copy. © 2016 SERSC.

关键词： Virtual machine

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Erratum to: A novel revenue optimization model to address the operation and maintenance cost of a data center

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Journal of Cloud Computing 2016年第1期5卷 1-1页

作者： Snehanshu Saha Jyotirmoy Sarkar Avantika Dwivedi Nandita Dwivedi Anand M. Narasimhamurthy Ranjan Roy Shrisha Rao Center for Applied Mathematical Modeling and Simulation (CAMMS) & Department of Computer Science and Engineering PESIT-BSC Bangalore India GE Healthcare Bangalore India BITS Pilani Hyderabad India State Resource Centre Chattisgarh India IIIT Bangalore Bangalore India

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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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A clustering method for identifying regions of interest in turbulent combustion tensor fields

Mathematics and Visualization

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Mathematics and Visualization 2015年 40卷 323-338页

作者： Maries, Adrian Luciani, Timothy Pisciuneri, P.H. Nik, Mehdi B. Yilmaz, S. Levent Givi, Peyman Marai, G. Elisabeta Learning Research and Development Center University of Pittsburgh PittsburghPA15260 United States Department of Computer Science Brown University ProvidenceRI02912 United States Center for Simulation and Modeling University of Pittsburgh PittsburghPA15260 United States Department of Mechanical Engineering and Materials Science University of Pittsburgh PittsburghPA15260 United States Mathworks NatickMA01760 United States Department of Computer Science University of Illinois at Chicago ChicagoIL60647 United States

Production of electricity and propulsion systems involve turbulent combustion. Computational modeling of turbulent combustion can improve the efficiency of these processes. However, large tensor datasets are the result of such simulations;these datasets are difficult to visualize and analyze. In this work we present an unsupervised statistical approach for the segmentation, visualization and potentially the tracking of regions of interest in large tensor data. The approach employs a machine learning clustering algorithm to locate and identify areas of interest based on specified parameters such as strain tensor value. Evaluation on two combustion datasets shows this approach can assist in the visual analysis of the combustion tensor field. © Springer International Publishing Switzerland 2015.

关键词： Combustion

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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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Improvement of a virtual pivot for minimally invasive surgery simulators using haptic augmentation

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8678卷 70-79页

作者： Obeid, Mohammad F. Chemlal, Salim Rechowicz, Krzysztof J. Heo, Eun-Sil Kelly, Robert E. McKenzie, Frederic D. Dept. of Modeling Simulation and Visualization Engineering Old Dominion University Norfolk United States Dept. of Electrical and Computer Engineering Old Dominion University Norfolk United States Virginia Modeling Analysis and Simulation Center Old Dominion University Norfolk United States Pediatric Surgery Children’s Hospital of The King’s Daughters and Eastern Virginia Medical School Norfolk United States

With rapid development of minimally invasive surgery, proficiency with intricate skills is becoming a greater concern. Consequently, the use of out-of-operating room training has increased significantly through employing high-fidelity and anatomically-correct graphics and haptic interfaces in virtual reality simulations. The effort in developing surgical simulators for generic minimally invasive procedures is still, however, suboptimal for many haptic implementations. A main aspect of such simulations is the pivoting behavior of the surgical tool realized using the haptic device. This paper investigates the limitation of a fullyvirtual implementation of the pivot and the ability to augment haptic interfaces to achieve a natural representation of forces. The design and implementation of two surgical tool pivoting techniques are introduced. Furthermore, a phantom is constructed from synthesized components to be used to measure and reproduce realistic mechanical properties of the anatomical model and pivot behavior. © Springer International Publishing Switzerland 2014.

关键词： Augmented reality

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Scalable replay with partial-order dependencies for message-logging fault tolerance

Scalable replay with partial-order dependencies for message-...

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IEEE International Conference on Cluster Computing

作者： Jonathan Lifflander Esteban Meneses Harshitha Menon Phil Miller Sriram Krishnamoorthy Laxmikant V. Kalé Department of Computer Science University of Illinois Urbana-Champaign Center for Simulation and Modeling University of Pittsburgh Department of Computer Science University of Illinois at Urbana-Champaign Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory

Deterministic replay of a parallel application is commonly used for discovering bugs or to recover from a hard fault with message-logging fault tolerance. For message passing programs, a major source of overhead during forward execution is recording the order in which messages are sent and received. During replay, this ordering must be used to deterministically reproduce the execution. Previous work in replay algorithms often makes minimal assumptions about the programming model and application to maintain generality. However, in many applications, only a partial order must be recorded due to determinism intrinsic in the program, ordering constraints imposed by the execution model, and events that are commutative (their relative execution order during replay does not need to be reproduced exactly). In this paper, we present a novel algebraic framework for reasoning about the minimum dependencies required to represent the partial order for different orderings and interleavings. By exploiting this framework, we improve on an existing scalable message-logging fault tolerance scheme that uses a total order. The improved scheme scales to 131,072 cores on an IBM BlueGene/P with up to 2× lower overhead.

关键词： Fault tolerance Fault tolerant systems Programming Debugging Program processors Electronic mail Benchmark testing

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