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28th Annual CHI Conference on Human Factors in computing Systems, CHI 2010

作者： Duh, Henry Been-Lirn Do, Ellen Yi-Luen Billinghurst, Mark Quek, Francis Chen, Vivian Hsueh-Hua National University of Singapore Department of Electrical and Computer Engineering 4 Engineering Drive 3 Singapore 117576 Singapore Georgia Institute of Technology College of Architecture School of Interactive Computing 245 Fourth Street Atlanta GA 30332-0155 United States University of Canterbury Human Interface Laboratory Old Maths Building New Zealand Virginnia Tech. Department of Computer Science Center for Human Computer Interaction Blacksburg VA 24061 United States Nanyang Technological University Wee Kim Wee School of Communication and Information 31 Nanyang Link Singapore 637718 Singapore

ISBN: (纸本)9781605589312

The elderly represent a valid group of users who can potentially benefit greatly from engaging with technology, such as healthcare systems or playing digital games. Yet, less attention has been given to the significance of senior citizens as technology users, as compared to the common younger population. In an effort to fill in the gap, this workshop aims to investigate the design of technology for senior citizens. To provide for more focused, thus more productive discussion, we will use elderly mobile phone games as a case in point here. The overarching objective is to understand what can help to make for better and more meaningful use of interactive applications and technology by the elderly, for instance, games on the mobile phone. © 2010 Copyright is held by the author/owner(s).

关键词： Cellular telephones

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Reports of the AAAI 2010 conference workshops

Reports of the AAAI 2010 conference workshops

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作者： Aha, David W. Boddy, Mark Bulitko, Vadim D'Avila Garcez, Artur S. Doshi, Prashant Edelkamp, Stefan Geib, Christopher Gmytrasiewicz, Piotr Goldman, Robert P. Halevy, Alon Hitzler, Pascal Isbell, Charles Josyula, Darsana Kaelbling, Leslie Pack Kersting, Kristian Kunda, Maithilee Lamb, Luis C. Marthi, Bhaskara McGreggor, Keith Mihalkova, Lilyana Nastase, Vivi Natarajan, Sriraam Provan, Gregory Raja, Anita Ram, Ashwin Riedl, Mark Russell, Stuart Sabharwal, Ashish Smaus, Jan-Georg Sukthankar, Gita Tuyls, Karl Van Der Meyden, Ron Adaptive Systems Section Naval Research Laboratory Washington DC United States Adventium Labs. Minneapolis MN United States Department of Computer Science University of Alberta Canada City University London United Kingdom University of Georgia United States University of Bremen Germany School of Informatics University of Edinburgh United Kingdom University of Illinois Chicago United States Smart Information Flow Technologies LLC Minneapolis MN United States Structured Data Group Google Research United States Department of Computer Science Wright State University Dayton OH United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer Science Bowie State University United States Department of Computer Science and Engineering Massachusetts Institute of Technology United States Statistical Relational Mining Group Fraunhofer IAIS Germany Department of Computer Science Federal University of Rio Grande Do sul Brazil Willow Garage Inc. CA United States Computer Science Department University of Maryland College Park United States Heidelberg Institute for Theoretical Studies Heidelberg Germany Department of Computer Science University of Wisconsin Madison United States University College Cork Ireland Cork Complex Systems Lab. Ireland Department of Software and Information Systems University of North Carolina Charlotte United States Department of Computer Science and Engineering University of California Berkeley United States Department of Computer Science Cornell University United States Institute for Computational Sustainability United States University of Freiburg Germany School of Electrical Engineering and Computer Science University of Central Florida United States Maastricht University Netherlands University of New South Wales NICTA Australia

The AAAI-10 workshop program was held on July 11-12, 2010, at the Westin Peachtree Plaza in Atlanta, Georgia. The workshop program included 13 workshops covering a wide range of topics in artificial intelligence. There were several presentations on particular formalisms for combining the levels of planning from the perspectives of classical planning, motion planning, POMDPs, search-based planning, and temporal logic-based constraints. Henry Lieberman from Massachusetts Institute of Technology Media laboratory presented work developing a platform for knowledge acquisition and usage from expert users, built upon experience with eliciting information from nonexperts in a collaborative manner. The objective of the AAAI Workshop on Goal-Directed Autonomy (GDA) was to encourage discussion and novel contributions on intelligent agents that can self-select their goals. Jeremy Baxter from QinetiQ focused on user interaction, while Nick Hawes described a goal-directed reasoning framework for controlling a mobile robot.

关键词： Motion planning

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Stretchable silicon electronics and their integration with rubber, plastic, paper, vinyl, leather and fabric substrates

Stretchable silicon electronics and their integration with r...

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作者： Kim, Dae-Hyeong Kim, Yun-Soung Liu, Zhuangjian Song, Jizhou Kim, Hoon-Sik Huang, Yonggang Y. Rogers, John A. Departments of Materials Science and Engineering Frederick Seitz Materials Research Laboratory Beckman Institute 1304 West Green Street Urbana IL 61801 United States Institute of High Performance Computing 1 Science Park Road #01-01 The Capricorn Singapore Science Park 11 117528 Singapore Department of Mechanical and Aerospace Engineering University of Miami Coral Gables FL 33146 United States Departments of Civil and Environmental Engineering and Mechanical Engineering Northwestern University Evanston IL 60208 United States Departments of Chemistry Mechanical Engineering Electrical and Computer Engineering University of Illinois at Urbana-Champaign 1304 West Green Street Urbana IL 61801 United States

ISBN: (纸本)9781617387555

Electronic systems that offer elastic mechanical responses to high strain deformations are of growing interest, due to their ability to enable new electrical, optical and biomedical devices and other applications whose requirements are impossible to satisfy with conventional wafer-based technologies or even with those that offer simple bendability. This paper describes materials and mechanical design strategies for classes of electronic circuits that offer extremely high flexibility and stretchability over large area, enabling them to accommodate even demanding deformation modes, such as twisting and linear stretching to 'rubber-band' levels of strain over 100%. The use of printed single crystalline silicon nanomaterials for the semiconductor provides performance in flexible and stretchable complementary metal-oxide-semiconductor (CMOS) integrated circuits approaching that of conventional devices with comparable feature sizes formed on silicon wafers. Comprehensive theoretical studies of the mechanics reveal the way in which the structural designs enable these extreme mechanical properties without fracturing the intrinsically brittle active materials or even inducing significant changes in their electrical properties. The results, as demonstrated through electrical measurements of arrays of transistors, CMOS inverters, ring oscillators and differential amplifiers, suggest a valuable route to high performance stretchable electronics that can be integrated with nearly arbitrary substrates. We show examples ranging from plastic and rubber, to vinyl, leather and paper, with capability for large area coverage. © 2010 Materials Research Society.

关键词： CMOS integrated circuits

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Impact of mobility on spectrum sensing in cognitive radio networks

Impact of mobility on spectrum sensing in cognitive radio ne...

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2009 ACM Workshop on Cognitive Radio Networks, CoRoNet'09, Co-located with the Mobile computing and Networking Conference, MobiCom'09

作者： Min, Alexander W. Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)9781605587387

In cognitive radio networks (CRNs), spectrum sensing is key to opportunistic spectrum access while preventing any unacceptable interference to primary users' communications. Although cognitive radios function as spectrum sensors and move around, most, if not all, of existing approaches assume stationary spectrum sensors, thus providing inaccurate sensing results. As part of our effort to solve/alleviate this problem, we consider the impact of sensor mobility on spectrum sensing performance in a joint optimization framework for sensor cooperation and sensing scheduling. We show that sensor mobility increases spatio-temporal diversity in received primary signal strengths, and thus, improves the sensing performance. This is intuitively plausible, but have not been tested previously. Based on this observation, we propose a sensing strategy that minimizes the sensing overhead by finding an optimal combination of the number of sensors to cooperate and the number of times spectrum sensing must be scheduled. This result provides a useful insight to understand the spectrum sensing and its coupling with sensor mobility. Copyright 2009 ACM.

关键词： Cognitive radio

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Constraining Dark Matter Models from a Combined Analysis of Milky Way Satellites with the Fermi Large Area Telescope

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Physical Review Letters 2011年第24期107卷 241302-241302页

作者： M. Ackermann M. Ajello A. Albert W. B. Atwood L. Baldini J. Ballet G. Barbiellini D. Bastieri K. Bechtol R. Bellazzini B. Berenji R. D. Blandford E. D. Bloom E. Bonamente A. W. Borgland J. Bregeon M. Brigida P. Bruel R. Buehler T. H. Burnett S. Buson G. A. Caliandro R. A. Cameron B. Cañadas P. A. Caraveo J. M. Casandjian C. Cecchi E. Charles A. Chekhtman J. Chiang S. Ciprini R. Claus J. Cohen-Tanugi J. Conrad S. Cutini A. de Angelis F. de Palma C. D. Dermer S. W. Digel E. do Couto e Silva P. S. Drell A. Drlica-Wagner L. Falletti C. Favuzzi S. J. Fegan E. C. Ferrara Y. Fukazawa S. Funk P. Fusco F. Gargano D. Gasparrini N. Gehrels S. Germani N. Giglietto F. Giordano M. Giroletti T. Glanzman G. Godfrey I. A. Grenier S. Guiriec M. Gustafsson D. Hadasch M. Hayashida E. Hays R. E. Hughes T. E. Jeltema G. Jóhannesson R. P. Johnson A. S. Johnson T. Kamae H. Katagiri J. Kataoka J. Knödlseder M. Kuss J. Lande L. Latronico A. M. Lionetto M. Llena Garde F. Longo F. Loparco B. Lott M. N. Lovellette P. Lubrano G. M. Madejski M. N. Mazziotta J. E. McEnery J. Mehault P. F. Michelson W. Mitthumsiri T. Mizuno C. Monte M. E. Monzani A. Morselli I. V. Moskalenko S. Murgia M. Naumann-Godo J. P. Norris E. Nuss T. Ohsugi A. Okumura N. Omodei E. Orlando J. F. Ormes M. Ozaki D. Paneque D. Parent M. Pesce-Rollins M. Pierbattista F. Piron G. Pivato T. A. Porter S. Profumo S. Rainò M. Razzano A. Reimer O. Reimer S. Ritz M. Roth H. F.-W. Sadrozinski C. Sbarra J. D. Scargle T. L. Schalk C. Sgrò E. J. Siskind G. Spandre P. Spinelli L. Strigari D. J. Suson H. Tajima H. Takahashi T. Tanaka J. G. Thayer J. B. Thayer D. J. Thompson L. Tibaldo M. Tinivella D. F. Torres E. Troja Y. Uchiyama J. Vandenbroucke V. Vasileiou G. Vianello V. Vitale A. P. Waite P. Wang B. L. Winer K. S. Wood M. Wood Z. Yang S. Zimmer M. Kaplinghat G. D. Martinez W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics and SLAC National Accelerator Laboratory Stanford University Stanford California 94305 USA Department of Physics Center for Cosmology and Astro-Particle Physics The Ohio State University Columbus Ohio 43210 USA Santa Cruz Institute for Particle Physics Department of Physics and Department of Astronomy and Astrophysics University of California at Santa Cruz Santa Cruz California 95064 USA Istituto Nazionale di Fisica Nucleare Sezione di Pisa I-56127 Pisa Italy Laboratoire AIM CEA-IRFU/CNRS/Université Paris Diderot Service d’Astrophysique CEA Saclay 91191 Gif sur Yvette France Istituto Nazionale di Fisica Nucleare Sezione di Trieste I-34127 Trieste Italy Dipartimento di Fisica Università di Trieste I-34127 Trieste Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova I-35131 Padova Italy Dipartimento di Fisica “G. Galilei ” Università di Padova I-35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Dipartimento di Fisica Università degli Studi di Perugia I-06123 Perugia Italy Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari 70126 Bari Italy Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 Palaiseau France Department of Physics University of Washington Seattle Washington 98195-1560 USA Institut de Ciències de l’Espai (IEEE-CSIC) Campus UAB 08193 Barcelona Spain Istituto Nazionale di Fisica Nucleare Sezione di Roma “Tor Vergata” I-00133 Roma Italy Dipartimento di Fisica Università di Roma “Tor Vergata” I-00133 Roma Italy INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Artep Inc. 2922 Excelsior Springs Court Ellicott City Maryland 21042 USA ASI Science Data Center I-00044 Frascati (Roma) Italy Laboratoire Univers et Particules de Montpell

Satellite galaxies of the Milky Way are among the most promising targets for dark matter searches in gamma rays. We present a search for dark matter consisting of weakly interacting massive particles, applying a joint likelihood analysis to 10 satellite galaxies with 24 months of data of the Fermi Large Area Telescope. No dark matter signal is detected. Including the uncertainty in the dark matter distribution, robust upper limits are placed on dark matter annihilation cross sections. The 95% confidence level upper limits range from about 10−26 cm3 s−1 at 5 GeV to about 5×10−23 cm3 s−1 at 1 TeV, depending on the dark matter annihilation final state. For the first time, using gamma rays, we are able to rule out models with the most generic cross section (∼3×10−26 cm3 s−1 for a purely s-wave cross section), without assuming additional boost factors.

关键词： Satellites

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Constraints on dark matter models from a Fermi LAT search for high-energy cosmic-ray electrons from the Sun

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Physical Review D 2011年第3期84卷 032007-032007页

作者： M. Ajello W. B. Atwood L. Baldini G. Barbiellini D. Bastieri R. Bellazzini B. Berenji R. D. Blandford E. D. Bloom E. Bonamente A. W. Borgland E. Bottacini A. Bouvier J. Bregeon M. Brigida P. Bruel R. Buehler S. Buson G. A. Caliandro R. A. Cameron P. A. Caraveo C. Cecchi E. Charles A. Chekhtman S. Ciprini R. Claus J. Cohen-Tanugi S. Cutini A. de Angelis F. de Palma C. D. Dermer S. W. Digel E. do Couto e Silva P. S. Drell C. Favuzzi S. J. Fegan W. B. Focke Y. Fukazawa P. Fusco F. Gargano N. Gehrels S. Germani N. Giglietto F. Giordano M. Giroletti T. Glanzman G. Godfrey I. A. Grenier S. Guiriec M. Gustafsson D. Hadasch G. Iafrate G. Jóhannesson A. S. Johnson T. Kamae H. Katagiri J. Kataoka M. Kuss L. Latronico A. M. Lionetto F. Longo F. Loparco M. N. Lovellette P. Lubrano M. N. Mazziotta J. E. McEnery P. F. Michelson T. Mizuno C. Monte M. E. Monzani A. Morselli I. V. Moskalenko S. Murgia M. Naumann-Godo J. P. Norris E. Nuss T. Ohsugi N. Omodei E. Orlando J. F. Ormes M. Ozaki D. Paneque J. H. Panetta M. Pesce-Rollins M. Pierbattista F. Piron S. Rainò R. Rando M. Razzano A. Reimer O. Reimer S. Ritz T. L. Schalk C. Sgrò J. Siegal-Gaskins E. J. Siskind P. D. Smith G. Spandre P. Spinelli D. J. Suson H. Takahashi T. Tanaka J. G. Thayer J. B. Thayer L. Tibaldo G. Tosti E. Troja T. L. Usher J. Vandenbroucke V. Vasileiou G. Vianello N. Vilchez A. P. Waite P. Wang B. L. Winer K. S. Wood Z. Yang S. Zimmer W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics and SLAC National Accelerator Laboratory Stanford University Stanford California 94305 USA Santa Cruz Institute for Particle Physics Department of Physics and Department of Astronomy and Astrophysics University of California at Santa Cruz Santa Cruz California 95064 USA Istituto Nazionale di Fisica Nucleare Sezione di Pisa I-56127 Pisa Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste I-34127 Trieste Italy Dipartimento di Fisica Università di Trieste I-34127 Trieste Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova I-35131 Padova Italy Dipartimento di Fisica “G. Galilei ” Università di Padova I-35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Dipartimento di Fisica Università degli Studi di Perugia I-06123 Perugia Italy Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari 70126 Bari Italy Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 Palaiseau France Institut de Ciències de l’Espai (IEEE-CSIC) Campus UAB 08193 Barcelona Spain INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Artep Inc. 2922 Excelsior Springs Court Ellicott City Maryland 21042 USA and resident at Naval Research Laboratory Washington D.C. 20375 USA ASI Science Data Center I-00044 Frascati (Roma) Italy Laboratoire Univers et Particules de Montpellier Université Montpellier 2 CNRS/IN2P3 Montpellier France Agenzia Spaziale Italiana (ASI) Science Data Center I-00044 Frascati (Roma) Italy Dipartimento di Fisica Università di Udine and Istituto Nazionale di Fisica Nucleare Sezione di Trieste Gruppo Collegato di Udine I-33100 Udine Italy Space Science Division Naval Research Laboratory Washington D.C. 20375-5352 USA Department of Physical Sciences Hiroshima

During its first year of data taking, the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope has collected a large sample of high-energy cosmic-ray electrons and positrons (CREs). We present the results of a directional analysis of the CRE events, in which we searched for a flux excess correlated with the direction of the Sun. Two different and complementary analysis approaches were implemented, and neither yielded evidence of a significant CRE flux excess from the Sun. We derive upper limits on the CRE flux from the Sun’s direction, and use these bounds to constrain two classes of dark matter models which predict a solar CRE flux: (1) models in which dark matter annihilates to CREs via a light intermediate state, and (2) inelastic dark matter models in which dark matter annihilates to CREs.

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An introduction to the echo state network and its applications in power system

An introduction to the echo state network and its applicatio...

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2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09

作者： Dai, Jing Venayagamoorthy, Ganesh K. Harley, Ronald G. Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA 30332 United States Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO 65409 United States

ISBN: (纸本)9781424450985

Echo State Network (ESN) is a new type of Recurrent Neural Network (RNN) proposed in recent years. The training process of ESN is easier and requires less computational effort than regular RNN which has the same size. Due to its high modeling capability of complex dynamic system, ESN has been used in various power system applications such as power system nonlinear load modeling and true harmonic current detection, wide area monitoring, intelligent control of an Active Power Filter (APF), overhead conductor thermal dynamics identification, wind speed or water inflow forecasting, etc. This paper introduces the basic concept and the offline and online training algorithms of the ESN in detail and reviews the state of the art of ESN applications in power systems. © 2009 IEEE.

关键词： Recurrent neural networks

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Predictive routing of contexts in an overlay network

Predictive routing of contexts in an overlay network

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IFIP/IEEE International Symposium on Integrated Network Management

作者： Hahnsang Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

While mobile nodes (MNs) undergo handovers across inter-wireless access networks, their contexts must be propagated for seamless re-establishment of on-going application sessions, including IP header compression, secure mobile IP, authentication, authorization, and accounting services, to name a few. Routing contexts via an overlay network either on-demand or based on prediction of an MNs' mobility, introduces a new challenging requirement of context management. This paper proposes a context router (CXR) that manages contexts in an overlay network. A CXR is responsible for (1) monitoring of MNs' cross-handover, (2) analysis of MNs' movement patterns, and (3) context routing ahead of each MN's arrival at an AP or a network. The predictive routing of contexts is performed based on statistical learning of (dis)similarities between the patterns obtained from vector distance measurements. The proposed CXR has been evaluated on a prototypical implementation based on an MN mobility model in an emulated access network. Our evaluation results show that the prediction mechanisms applied on the CXR outperform a Kalman-filter-based method with respect to both prediction accuracy and computation performance.

关键词： Routing Context-aware services Authentication Authorization Monitoring Pattern analysis Performance evaluation Statistical learning Distance measurement Prototypes

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On Dynamic Reconfiguration of a Large-Scale Battery System

On Dynamic Reconfiguration of a Large-Scale Battery System

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IEEE Symposium on real-time and Embedded Technology and Applications

作者： Hahnsang Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

Electric vehicles powered with large-scale battery packs are gaining popularity as gasoline price soars. Large-scale battery packs usually consist of an estimated 12,000 battery cells connected in series and parallel, which are susceptible to battery-cell failures. Unfortunately, current battery-management systems are unable to handle the inevitable battery-cell failures very well. To address this problem, we propose a dynamic reconfiguration framework that monitors, reconfigures, and controls large-scale battery packs online. The framework is built upon a syntactic bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. In particular, the semantic bypassing mechanism is dictated by constant-voltage-keeping and dynamic-voltage-allowing policies. The former policy is effective in preventing unavoidable voltage drops during the battery discharge, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements. Our experimental evaluation has shown the proposed framework to enable the battery packs to be 9 times as fault-tolerant as a legacy scheme.

关键词： Large-scale systems Vehicle dynamics Centralized control Control systems Voltage real time systems Battery management systems Application software Embedded computing Power engineering computing

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Scheduling of Battery Charge, Discharge, and Rest

Scheduling of Battery Charge, Discharge, and Rest

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real-time Systems Symposium (RTSS)

作者： Hahnsang Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

Electric vehicles operate inefficiently with a naive battery management system that charges or discharges battery cells in a pack based solely on application load demands. The battery pack's operation-time and lifetime can be extended significantly by effectively scheduling (the cyber part) battery charge, discharge, and rest activities, based on the battery characteristics (the physical part). We propose a set of policies for scheduling battery-cell activities, called the weighted-k round-robin (kRR) scheduling framework. This framework dynamically adapts battery-cell activities to load demands and the condition of individual cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage-imbalances. The framework comprises two key components. First, an adaptive filter estimates the upcoming load demand. Then, based on the estimated load demand, the kRR scheduler determines the number of parallel-connected cells to be discharged simultaneously. The scheduler also effectively partitions the cells in the pack, allowing the cells to be simultaneously charged and discharged in coordination with the battery reconfiguration system we developed earlier [17]. Besides the kRR scheduling framework, we characterize the discharge and recovery efficiency of a Lithium-ion battery cell. The kRR scheduling framework is shown to outperform three alternative scheduling mechanisms with respect to the operation-time by 7-56%, and improve the tolerance of voltage-imbalance by up to 50%.

关键词： real time systems Robustness Global warming Threshold voltage Processor scheduling Laboratories Battery powered vehicles Battery management systems Application software Adaptive filters

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