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IEEE General Meeting Power& Energy Society

作者： Anthony M. Giacomoni Steven Y. Goldsmith S. Massoud Amin Bruce F. Wollenberg Electrical and Computer Engineering Department University of Minnesota Minneapolis MN USA Technological Leadership Institute University of Minnesota Minneapolis MN USA Advanced Information Systems Laboratory Sandia National Laboratories Albuquerque NM USA Technological Leadership Institute and the Electrical and Computer Engineering Department University of Minnesota Minneapolis MN USA

Autonomous microgrids are operated and coordinated by intelligent automatic controls without any reliance on human intervention. In this paper, a simulation framework utilizing sequential Monte Carlo simulations is developed to investigate the performance of autonomous microgrids that have the ability to interconnect to achieve adequate load service. Detailed models of the various microgrid components and interconnection policies implemented are provided. In order to minimize the exposure of each microgrid to vulnerabilities, it is also desired that the number of interconnections be minimal. Using the developed framework, various simulation scenarios are explored. Results show the impact of storage capacity, intermittent distributed energy resources (DERs), and the ability to interconnect occasionally with other microgrids on each microgrid's security and reliability as measured using standard risk indices.

关键词： Assembly Generators Load modeling Wind turbines Maintenance engineering Numerical models

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data Center Management and Cloud computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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SOLARE: Self-organizing latency-aware resource ensemble

SOLARE: Self-organizing latency-aware resource ensemble

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13th IEEE International Workshop on FTDCS 2011, the 8th International Conference on ATC 2011, the 8th International Conference on UIC 2011 and the 13th IEEE International Conference on HPCC 2011

作者： Eom, Heungsik Wolinsky, David Isaac Figueiredo, Renato J. Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville FL United States Department of Computer Science Yale University New Haven United States

ISBN: (纸本)9780769545387

This paper proposes and evaluates Self-Organizing Latency-Aware Resource Ensemble (SOLARE), a peer-to-peer self-organizing and self-managing cluster system based upon network coordinates and utility functions. In contrast to previous works, SOLARE is a fully decentralized clustering algorithm without any central units such as servers, super peers, cluster heads or landmarks. Furthermore, SOLARE allows for adaptability to dynamic network changes by monitoring the utility of a cluster and migrating nodes to other higher-utility clusters when the utility of an existing cluster is low. Quantitative, simulation-driven evaluations show that SOLARE is able to satisfy user demands expressed by utility functions that integrate system parameters in terms of intra cluster latencies and the number of cluster members. Also, we verify the ability of SOLARE to adapt to dynamic network changes through simulation based experiments that consider the number of nodes which migrate into another cluster and average utility value as nodes join SOLARE. © 2011 IEEE.

关键词： Clustering algorithms

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Poster abstracts

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Sleep and Biological Rhythms 2016年第1期5卷 A1-A189页

作者： J. Ferrie M. Shipley F. Cappuccio E. Brunner M. Miller M. Kumari M. Marmot A. Coenen J. L. Castillo F. Araya G. Bustamante L. Montecino C. Torres S. Oporto J. Gronli E. Fiske R. Murison B. Bjorvatn E. Sorensen R. Ursin C. M. Portas S. Rajaraman A. Gribok N. Wesensten T. Balkin J. Reifman N. Dursunoglu S. Ozkurt S. Baser O. Delen S. Sarikaya P. Sadler P. Mitchell D. Françon M. Decobert B. Herve A. Richard G. Griebel P. Avenet B. Scatton G. L. Fur D. Eckert A. Jordan A. Wellman S. Smith A. Malhotra D. White D. Bruck I. Thomas A. Kritikos W. Oertel K. Stiasny-Kolster D. Garcia-Borreguero W. Poewe B. Hoegl R. Kohnen E. Schollmayer J. Keffel C. Trenkwalder A. Valle S. Roizenblatt F. Fregni P. Boggio S. Tufik K. Ward L. Robertson L. Palmer P. Eastwood D. Hillman J. Lee S. Mukherjee V. de Padova G. Barbato G. Ficca I. Zilli P. Salzarulo M. Veldi T. Hion V. Vasar M. Kull L. Nowak J. Davis Y. Latzer O. Tzischinsky S. Crowley M. Carskadon M. Anca-Herschkovitsch D. Frey J. Ortega C. Wiseman C. Farley K. Wright A. Campbell A. Neill K. Spiegel R. Leproult E. Tasali N. Scherberg E. van Cauter A. T. Noradina N. A. Karim I. Norlinah A. A. Raymond R. Sahathevan B. Hamidon E. Werth R. Poryazova R. Khatami C. Bassetti R. G. Beran L. Ainley G. Holand J. Duncan H. Kinney B. Davis B. Hood S. Frey C. Schmidt M. Hofstetter P. Peigneux C. Cajochen W.-P. Hu J.-D. Li C. Zhang L. Boehmer J. Siegel Q.-Y. Zhou Y. Sagawa H. Kondo T. Takemura H. Kanayama Y. Kaneko M. Sato T. Kanbayashi Y. Hishikawa T. Shimizu A. Viola L. James L. Schlangen D.-J. Dijk R. Andretic Y.-C. Kim K.-A. Han F. Jones R. Greenspan L. Sanford L. Yang X. Tang K. Dieter E. Uta H. Sven M. Richard N. Oyane S. Pallesen F. Holsten Y. Inoue M. Fujita N. Emura K. Kuroda N. Uchimura A. Johnston J. Astbury G. Kennedy K. Hoedlmoser M. Schabus T. Pecherstorfer S. Moser G. Gruber P. Anderer W. Klimesch N. Naidoo M. Ferber A. Pack D. Neu O. Mairesse G. Hoffmann A. Dris L. Lambrecht P. Linkowski P. Verbanck O. Le Bon N. Matsuura M. Yamao N. Adachi R. Aritomi Y. Komada H. Tanaka S. Shirak University College London London UK University College London London USA Warwick Medical School London UK Warwick Medical School Coventry USA Radboud University Nijmegen Nijmegen Netherlands Department of Neurology University of Chile Santiago Chile Neurology Service Hospital del Salvador Santiago Chile Family Health Center Juan Pablo II Santiago Chile Department of Biomedicine Section on Physiology Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care University of Bergen Bergen Norway Norwegian Competence Center for Sleep Disorders Haukeland University Hospital Bergen Norway Department of Child and Adolescent Psychiatry Haukeland University Hospital Univeristy of Bergen Bergen Norway Department of Biomedicine University of Bergen Bergen Norway US Army Medical Research and Materiel Command Fort Detrick Frederick USA Walter Reed Army Institute of Research Silver Spring USA Department of Behavioral Biology Walter Reed Army Institute of Research Silver Spring USA Faculty Department of Pulmonology Pamukkale University Medical Denizli Turkey University of Ballarat Ballarat Australia Sanofi-Aventis Recherche et Developpement Paris France Brigham and Women’s Hospital Harvard Medical School Boston USA The University of Queensland Adelaide Australia School of Psychology University of Queensland Brisbane Australia The University of Queensland Brisbane Australia Victoria University Melbourne Australia Department of Psychology Victoria University Melbourne Australia School of Psychology Victoria University Melbourne Australia Philips-Universität Marburg Germany Philips-Universitaet-Marburg Marburg Germany Instituto de Investigaciones del Sueno Madrid Spain Universitätsklinik für Neurologie Innsbruck Austria Universitaetsklinik fuer Neurologie Innsbruck Austria IMEREM GmbH Nuernberg Germany Schwarz Pharma AG Monheim Germany

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Distributed dynamic load balancing for pipelined computations on heterogeneous systems

Distributed dynamic load balancing for pipelined computation...

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作者： Riakiotakis, Ioannis Ciorba, Florina M. Andronikos, Theodore Papakonstantinou, George Computing Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Center for Information Services and High Performance Computing Technische Universität Dresden Germany Department of Informatics Ionian University Corfu Greece

One of the most significant causes for performance degradation of scientific and engineering applications on high performance computing systems is the uneven distribution of the computational work to the resources of the system. This effect, which is known as load imbalance, is even more noticeable in the case of irregular applications and heterogeneous distributed systems. This motivated the parallel and distributed computing research community to focus on methods that provide good load balancing for scientific and engineering applications running on (heterogeneous) distributed systems. Efficient load balancing and scheduling methods are employed for scientific applications from various fields, such as mechanics, materials, physics, chemistry, biology, applied mathematics, etc. Such applications typically employ a large number of computational methods in order to simulate complex phenomena, on very large scales of time and magnitude. These simulations consist of routines that perform repetitive computations (in the form of DO/FOR loops) over very large data sets, which, if not properly implemented and executed, may suffer from poor performance. The number of repetitive computations in the simulation codes is not always constant. Moreover, the computational nature of these simulations may be in fact irregular, leading to the case when one computation takes (unpredictably) more time than others. For successful and timely results, large scale simulations require the use of large scale computing systems, which often are widely distributed and highly heterogeneous. Moreover, large scale computing systems are usually shared among multiple users, which causes the quality and quantity of the available resources to be highly unpredictable. There are numerous load balancing methods in the literature for different parallel architectures. The most recent of these methods typically follow the master-worker paradigm, where a single coordinator (master) is responsible for making

关键词： Parallel architectures

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Complex-ω approach versus complex-k approach in description of gain-assisted surface plasmon-polariton propagation along linear chains of metallic nanospheres

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Physical Review B 2011年第11期83卷 115451-115451页

作者： Indika B. Udagedara Ivan D. Rukhlenko Malin Premaratne Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton VIC 3800 Australia

Propagation characteristics of surface plasmon-polaritons (SPPs) in linear chains of metallic nanospheres (LCMNs) can be found from a dispersion equation, by assuming that either frequency or wave number of a SPP is real. In this paper, we present a comparative study of SPP modes corresponding to the two types of complex solutions for an infinitely long LCMN embedded in a gain medium. We show that even though gain predominantly affects the SPP dispersion obtained with real frequency, both solutions result in the same dispersion and attenuation of SPP modes, when Ohmic losses are almost compensated by gain. In this regime, an analytic expression for the propagation length of SPPs exists, and the SPPs’ dispersion is determined by a real equation. We also demonstrate that for a given amount of gain (below the amplification limit of ~1000 cm−1), transversely polarized SPPs attenuate slower than longitudinally polarized SPPs and are, therefore, preferable for the purpose of energy transfer in gain-supplied LCMNs. The transmission windows for SPP modes of different polarizations do not overlap each other, which facilitates realization of LCMN-based plasmonic filters. Our results may prove useful in design optimization of all-optical chips for power-efficient optical supercomputers.

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Propagation of surface plasmon-polaritons in linear chains of metallic nanoparticles embedded in a gain medium

Propagation of surface plasmon-polaritons in linear chains o...

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International Conference on Quantum Electronics (IQEC)

作者： Indika B. Udagedara Ivan D. Rukhlenko Malin Premaratne Advanced Computing and Simulation Laboratory (A-çL) Department of Electrical and Computer Systems Engineering Monash University VIC Australia

We analyze the two different types of complex solutions to the dispersion equation of surface plasmon-polaritons residing in a linear chain of metallic nanoparticles in the presence of gain in the host medium.

ISBN: (纸本)9780977565771

关键词： Dispersion Nanoparticles Equations Mathematical model Plasmons Optical polarization Optical surface waves

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SOLARE: Self-Organizing Latency-Aware Resource Ensemble

SOLARE: Self-Organizing Latency-Aware Resource Ensemble

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IEEE International Conference on High Performance computing and Communications (HPCC)

作者： Heungsik Eom David Isaac Wolinsky Renato J. Figueiredo Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville USA Department of Computer Science Yale University New Haven USA

关键词： Peer to peer computing Clustering algorithms Monitoring computer architecture Servers Performance evaluation Heuristic algorithms

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Degree of polarization of Mie scattered stationary partially coherent electromagnetic fields

Degree of polarization of Mie scattered stationary partially...

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International Conference on Quantum Electronics (IQEC)

作者： Madara L. Marasinghe Malin Premaratne David M. Paganin Advanced Computing and Simulation Laboratory (AL) Department of Electrical and Computer Systems Engineering Faculty of Engineering Monash University Clayton VIC Australia School of Physics Faculty of Science Monash University Clayton VIC Australia

The polarization of non-paraxial partially coherent light scattered from nanospheres cannot be described easily. We utilize the degree of polarization to quantify Mie scattered partially coherent light and demonstrate... 详细信息

ISBN: (纸本)9780977565771

关键词： Polarization Lattices Electromagnetic fields Optics Coherence Dielectrics

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Exploiting memristance for low-energy neuromorphic computing hardware

Exploiting memristance for low-energy neuromorphic computing...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Garrett S. Rose Robinson Pino Qing Wu Department of Electrical and Computer Engineering Polytechnic Institute of New York University Brooklyn NY USA Advanced Computing Architectures Information Directorate Air Force Research Laboratory Rome NY USA

As conventional CMOS technology approaches fundamental scaling limits novel nanotechnologies offer great promise for VLSI integration at nanometer scales. The memristor, or memory resistor, is a novel nanoelectronic device that holds great promise for continued scaling for emerging applications. Memristor behavior is very similar to that of the synapses necessary for realizing a neural network. In this research, we have considered circuits that leverage memristance in the realization of an artificial synapse that can be used to implement neuromorphic computing hardware. A novel charge sharing based neural network is described which consists of a hybrid of conventional CMOS technology and novel memristors. Simulation results are presented which demonstrate that dense CMOS-memristive neural networks can be implemented with energy consumption on the order of tens of femto-joules.

关键词： Memristors Integrated circuit modeling Transistors Mathematical model CMOS integrated circuits Artificial neural networks Threshold voltage

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