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12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12

作者： Chen, Yinlin Bogen II, Paul Logasa Hsieh, Haowei Fox, Edward A. Cassel, Lillian N. Department of Computer Science Virginia Tech. Blacksburg VA United States Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge TN 37931 United States School of Library and Information Science University of Iowa Iowa City IA 52242 United States Department of Computing Sciences Villanova University Villanova PA 19085 United States

ISBN: (纸本)9781450311540

The Ensemble Portal harvests resources from multiple heterogeneous federated collections. Managing these dynamically increasing collections requires an automatic mechanism to categorize records in to corresponding topics. We propose an approach to use existing ACM DL metadata to build classifiers for harvested resources in the Ensemble project. We also present our experience with utilizing the Amazon Mechanical Turk platform to build ground truth training data sets from Ensemble collections. © 2012 ACM.

关键词： Digital libraries

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Box-particle intensity filter

Box-particle intensity filter

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9th IET data Fusion and Target Tracking Conference: Algorithms and Applications, DF and TT 2012

作者： Schikora, M. Gning, A. Mihaylova, L. Cremers, D. Koch, W. Streit, R. Fraunhofer FKIE Dept. Sensor Data and Information Fusion Wachtberg Germany University of Lancaster School of Computing and Communications United Kingdom University College London Department of Computer Science United Kingdom Technical University of Munich Department of Computer Science Germany Metron Inc. Reston VA United States

ISBN: (纸本)9781849196246

This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the box-iFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs.

关键词： Distributed computer systems

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Efficient approximation of the maximal preference scores by lightweight cubic views

Efficient approximation of the maximal preference scores by ...

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15th International Conference on Extending database Technology, EDBT 2012

作者： Chen, Yueguo Cui, Bin Du, Xiaoyong Tung, Anthony K. H. Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China Department of Computer Science Peking University Beijing China School of Information Renmin University of China Beijing China School of Computing National University of Singapore Singapore Singapore

ISBN: (纸本)9781450307901

Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in applications where users want to efficiently check whether many individual data sets contain tuples that are of interest to them. Although a BPQ can be naïvely answered by issuing a top-1 query and computing the score from the returned tuple, doing so might require to load a larger number of tuples externally. In this paper, we address the problem of efficient processing BPQs by using lightweight cubic (3-dimensional) views. With these in-memory views, the MPSs of BPQs can be efficiently estimated with an error bound guaranteed, by paying only a small number of I/Os. Extensive experimental results over real-life data sets show that our approximate solution can achieve the efficiency of up to three orders of magnitude compared to exact solutions, with certain accuracy guaranteed. © 2012 ACM.

关键词： best preference score materialized views preference query top-k query

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Cell oscillation resolution in mobility profile building

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International Journal of Computer science Issues 2012年第3 3-3期9卷 205-213页

作者： Shad, Shafqat Ali Chen, Enhong Laboratory of Semantic Computing and Data Mining Department of Computer Science and Technology University of Science and Technology of China Huangshan Road Hefei 230027 Anhui China

Mobility profile building became extensively examined area in Location based services (LBS) through extraction of significant locations. Mobility traces are recorded under three reference positioning systems that are Satellite based i.e. GPS, Network based i.e. GSM and Local positioning i.e. WLAN, RFID, IrDA. Satellite based and local positioning due to of high power consumption, additional resource installation, low accuracy and space limitation are less encouraging. So network based positioning i.e. GSM is only viable solution for mobility tracing through Cell global identity (CGI). CGI presents the Cell-ids to extract the significant locations from mobility history. However CGI faces cell oscillation problem, where user is assigned multiple Cell-Ids even at a stationary state for load balancing and GSM cells overlapping. In this paper we proposed two semi-supervised methodology for cell oscillation resolution i.e. semantic tagging and overlapped area clustering, the proposed methodologies are equally useful for the identification of significant places too. © 2012 International Journal of Computer science Issues.

关键词： Extraction

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Precise location acquisition of mobility data using cell-id

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International Journal of Computer science Issues 2012年第3 3-3期9卷 222-231页

Cellular network data has become a hot source of study for extraction of user-mobility and spatio-temporal trends. Location binding in mobility data can be done through different methods like GPS, service provider assisted faux-GPS and Cell Global Identity (CGI). Among these Cell Global Identity is most inexpensive method and readily available solution for mobility extraction;however exact spatial extraction is somehow a problem in it. This paper presents the spatial extraction technique of mobile phone user raw data which carries the information like location information, proximity location and activity of subjects. This work mainly focuses on the data pre-processing methodology and technique to interpret the low level mobility data into high level mobility information using the designed clustering methodology and publically available Cell-IDs databases. Work proposed the semi- supervised strategy to derive the missing locations thorough the usage of semantic tag information and removal of spatial outliers for precise mobility profile building. © 2012 International Journal of Computer science Issues.

关键词： Extraction

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Dark matter constraints from observations of 25 Milky Way satellite galaxies with the Fermi Large Area Telescope

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Physical Review D 2014年第4期89卷 042001-042001页

作者： M. Ackermann A. Albert B. Anderson L. Baldini J. Ballet G. Barbiellini D. Bastieri K. Bechtol R. Bellazzini E. Bissaldi E. D. Bloom E. Bonamente A. Bouvier T. J. Brandt J. Bregeon M. Brigida P. Bruel R. Buehler S. Buson G. A. Caliandro R. A. Cameron M. Caragiulo P. A. Caraveo C. Cecchi E. Charles A. Chekhtman J. Chiang S. Ciprini R. Claus J. Cohen-Tanugi J. Conrad F. D’Ammando A. de Angelis C. D. Dermer S. W. Digel E. do Couto e Silva P. S. Drell A. Drlica-Wagner R. Essig C. Favuzzi E. C. Ferrara A. Franckowiak Y. Fukazawa S. Funk P. Fusco F. Gargano D. Gasparrini N. Giglietto M. Giroletti G. Godfrey G. A. Gomez-Vargas I. A. Grenier S. Guiriec M. Gustafsson M. Hayashida E. Hays J. Hewitt R. E. Hughes T. Jogler T. Kamae J. Knödlseder D. Kocevski M. Kuss S. Larsson L. Latronico M. Llena Garde F. Longo F. Loparco M. N. Lovellette P. Lubrano G. Martinez M. Mayer M. N. Mazziotta P. F. Michelson W. Mitthumsiri T. Mizuno A. A. Moiseev M. E. Monzani A. Morselli I. V. Moskalenko S. Murgia R. Nemmen E. Nuss T. Ohsugi E. Orlando J. F. Ormes J. S. Perkins F. Piron G. Pivato T. A. Porter S. Rainò R. Rando M. Razzano S. Razzaque A. Reimer O. Reimer S. Ritz M. Sánchez-Conde N. Sehgal C. Sgrò E. J. Siskind P. Spinelli L. Strigari D. J. Suson H. Tajima H. Takahashi J. B. Thayer L. Tibaldo M. Tinivella D. F. Torres Y. Uchiyama T. L. Usher J. Vandenbroucke G. Vianello V. Vitale M. Werner B. L. Winer K. S. Wood M. Wood G. Zaharijas S. Zimmer Deutsches Elektronen Synchrotron DESY D-15738 Zeuthen Germany 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 Stockholm University AlbaNova SE-106 91 Stockholm Sweden The Oskar Klein Centre for Cosmoparticle Physics AlbaNova SE-106 91 Stockholm Sweden Università di Pisa and 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 e Astronomia “G. Galilei ” Università di Padova I-35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Pisa I-56127 Pisa Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste and Università di Trieste I-34127 Trieste 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 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 NASA Goddard Space Flight Center Greenbelt Maryland 20771 USA 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 INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Center for Earth Observing and Space Research College of Science George Mason University Fairfax Virginia 22030

The dwarf spheroidal satellite galaxies of the Milky Way are some of the most dark-matter-dominated objects known. Due to their proximity, high dark matter content, and lack of astrophysical backgrounds, dwarf spheroidal galaxies are widely considered to be among the most promising targets for the indirect detection of dark matter via γ rays. Here we report on γ-ray observations of 25 Milky Way dwarf spheroidal satellite galaxies based on 4 years of Fermi Large Area Telescope (LAT) data. None of the dwarf galaxies are significantly detected in γ rays, and we present γ-ray flux upper limits between 500 MeV and 500 GeV. We determine the dark matter content of 18 dwarf spheroidal galaxies from stellar kinematic data and combine LAT observations of 15 dwarf galaxies to constrain the dark matter annihilation cross section. We set some of the tightest constraints to date on the annihilation of dark matter particles with masses between 2 GeV and 10 TeV into prototypical standard model channels. We find these results to be robust against systematic uncertainties in the LAT instrument performance, diffuse γ-ray background modeling, and assumed dark matter density profile.

关键词： DWARF galaxies MILKY Way DARK matter (Astronomy) ANNIHILATION reactions TELESCOPES

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Corrigendum: “Provably-secure electronic cash based on certicateless partially-blind signatures”

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Electronic Commerce Research and Applications 2013年第1期12卷 60-60页

作者： Lei Zhang Futai Zhang Bo Qin Shubo Liu East China Normal University Software Engineering Institute Shanghai Key Laboratory of Trustworthy Computing Shanghai China Universitat Rovira i Virgili Department of Computer Engineering and Mathematics UNESCO Chair in Data Privacy Tarragona Catalonia Spain Nanjing Normal University School of Computer Science and Technology China Xi’an University of Technology School of Science Department of Maths China Wuhan University School of Computer Science Wuhan China

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On the performance of the Box Particle Filter for extended object tracking using laser data

On the performance of the Box Particle Filter for extended o...

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Workshop on Sensor data Fusion: Trends, Solutions, Applications (SDF)

作者： Nikolay Petrov Martin Ulmke Lyudmila Mihaylova Amadou Gning Marek Schikora Monika Wieneke Wolfgang Koch School of Computing and Communications Lancaster University UK Department of Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Department of Computer Science University College London UK

This paper considers the challenging task of realtime extended object tracking using cluttered measurements from laser range scanners. The performance of the recently proposed Box Particle Filter (Box PF) algorithm is evaluated utilising real measurements from laser range scanners obtained within a prototype security system replicating an airport corridor. The problem is expressed as the joint estimation of both state and parameters of an extended target. Circularly and elliptically shaped targets are considered. Promising results are presented.

关键词： Atmospheric measurements Particle measurements Vectors Target tracking Shape Uncertainty Time measurement

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Box-particle PHD filter for multi-target tracking

Box-particle PHD filter for multi-target tracking

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International Conference on Information Fusion

作者： Marek Schikora Amadou Gning Lyudmila Mihaylova Daniel Cremers Wolfgang Koch Department Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Department of Computer Science University College London UK School of Computing and Communications University of Lancaster UK Department Computer Science Technical University of Munich Germany

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable to deal with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small particle number makes this approach attractive for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes methods from the field of interval analysis. The theoretical derivation of the box-PHD filter is presented followed by a comparative analysis with a standard sequential Monte Carlo (SMC) version of the PHD filter. To measure the performance objectively three measures are used: inclusion, volume and the optimum subpattern assignment metric. Our studies suggest that the box-PHD filter reaches similar accuracy results, like a SMC-PHD filter but with much considerably less computational costs. Furthermore, we can show that in the presence of strongly biased measurement the box-PHD filter even outperforms the classical SMC-PHD filter.

关键词： Atmospheric measurements Particle measurements Time measurement Covariance matrix Target tracking Uncertainty Standards

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Practical privacy for value-added applications in vehicular ad hoc networks 5th

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5th International Conference on Internet and Distributed computing Systems, IDCS 2012

作者： Zhang, Lei Wu, Qianhong Qin, Bo Domingo-Ferrer, Josep Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China UNESCO Chair in Data Privacy Dept. of Comp. Eng. and Maths Universitat Rovira i Virgili TarragonaCatalonia Spain Key Lab. of Aerospace Information Security and Trusted Computing Ministry of Education Wuhan University School of Computer China Department of Maths School of Science Xi’an University of Technology China

ISBN: (纸本)9783642348822

Advances in mobile networking and information processing technologies have triggered vehicular ad hoc networks (VANETs) for traffic safety and value-added applications. Most efforts have been made to address the security concerns while little work has been done to investigate security and privacy for value-added applications in VANETs. To fill this gap, we propose a value-added application, specifically, a security and privacy preserving location-based service (LBS) scheme for VANETs. For each LBS transaction, the scheme provides authentication, integrity and non-repudiation for both the service provider and the user. A user can obtain the service in an anonymous way and hence user privacy is well protected. However, a tracing procedure can be invoked to find malicious users, thereby efficiently preventing users from abusing the anonymity provided by the system. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Location based services

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