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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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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Parallelized Race Detection Based on GPU Architecture

Parallelized Race Detection Based on GPU Architecture

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10th Annual Conference of Advanced Computer Architecture, ACA 2014

作者： Dai, Zhuofang Zhang, Zheng Wang, Haojun Li, Yi Zhang, Weihua Software School Fudan University Shanghai China Shanghai Key Laboratory of Data Science Fudan University Shanghai China Parallel Processing Institute Fudan University Shanghai 201203 China State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou 450001 China

ISBN: (纸本)9783662444900

In order to harness abundant hardware resources, parallel programming has become a necessity in multicore era. However, parallel programs are prone to concurrency bugs, especially data races. Even worse, current software tools always suffer from both large runtime overheads and poor scalability, while most of hardware supports for race detection are not available in parallel programming. Therefore, it has been a challenge that how to introduce a practical and fast race detection tools. Nowadays, GPUs with massive parallel computation resources have become one of the most popular hardware platforms. Hence, the prevalence of GPU architectures has opened an opportunity of accelerating data race detection. In this paper, we first have a deeply analysis on data race detection algorithms like happens-before and observe that these algorithms have very good computation and data parallelism. Based on the observation, we propose Grace, a software approach that leverages massive parallelism computation units of GPU architectures to accelerate data race detection. Grace deploys detection, the most computation intensive workload, on GPU to fully utilize the computation resource in GPU. Moreover, Grace leverages coarse-grained pipeline parallelism and data parallelism through exploiting the computation resource in multi-core CPUs to further improve performance. Experimental results show that Grace is fast and scalable. It achieves over 80x speedup compared to the sequential version even under a 128-thread configuration. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Graphics processing unit

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Reports of the AAAI 2014 conference workshops

Reports of the AAAI 2014 conference workshops

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作者： Albrecht, Stefano V. Barreto, André M. S. Braziunas, Darius Buckeridge, David L. Cuayáhuitl, Heriberto Dethlefs, Nina Endres, Markus Farahmand, Amir-Massoud Fox, Mark Frommberger, Lutz Ganzfried, Sam Guillet, Sébastien Gil, Yolanda Hunter, Lawrence E. Jhala, Arnav Kersting, Kristian Konidaris, George Lecue, Freddy McIlraith, Sheila Natarajan, Sriraam Noorian, Zeinab Poole, David Ronfard, Rémi Saffiotti, Alessandro Shaban-Nejad, Arash Srivastava, Biplav Tesauro, Gerald Uceda-Sosa, Rosario Van Den Broeck, Guy Van Otterlo, Martijn Wallace, Byron C. Weng, Paul Wiens, Jenna Zhang, Jie School of Informatics University of Edinburgh United Kingdom Department of Applied and Computational Mathematics Brazilian National Laboratory Brazil Big Data Group Kobo Inc. Brazil Department of Epidemiology and Biostatistics McGill University Canada School of Mathematical and Computer Sciences Heriot-Watt University in Edinburgh United Kingdom University of Augsburg Germany Carnegie Mellon University United States University of Toronto Canada Cognitive Systems Group University of Bremen Germany LIARA UQAC Chicoutimi Canada Information Sciences Institute University of Southern California Computer Science Department United States Center for Computational Pharmacology University of Colorado School of Medicine United States Department of Computational Media University of California Santa Cruz United States Computer Science Department Technical University of Dortmund Germany MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States IBM Research - Smarter Cities Technology Centre Dubline Ireland School of Informatics and Computing Indiana University United States Department of Computer Science University of Saskatchewan Canada University of British Columbia Canada INRIA University of Grenoble France Orebro University Sweden McGill Clinical and Health Informatics Group McGill University Canada IBM Research United States Cognitive Computing Department IBM Research Yorktown HeightsNY United States Computer Science Department Katholieke Universiteit Leuven Belgium Cognitive Artificial Intelligence Department Radboud University Nijmegen Netherlands University of Texas Austin United States Pierre and Marie Curie University Paris France University of Michigan United States School of Computer Engineering Nanyang Technological University Singapore

The AAAI-14 Workshop program was held Sunday and Monday, July 27-28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics;Artificial Intelligence Applied to Assistive Technologies and Smart Environments;Cognitive computing for Augmented Human Intelligence;Computer Poker and Imperfect Information;Discovery Informatics;Incentives and Trust in Electronic Communities;intelligent Cinematography and Editing;Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication;Modern Artificial Intelligence for Health Analytics;Multiagent Interaction Without Prior Coordination;Multidisciplinary Workshop on Advances in Preference Handling;Semantic Cities - Beyond Open data to Models, Standards, and Reasoning;Sequential Decision Making with big data;Statistical Relational AI;and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events. © 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Decision making

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Search for extended sources in the galactic plane using 6 years of Fermi-Large area telescope pass 8 data above 10 GeV

arXiv

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arXiv 2017年

作者： Ackermann, M. Ajello, M. Baldini, L. Ballet, J. Barbiellini, G. Bastieri, D. Bellazzini, R. Bissaldi, E. Bloom, E.D. Bonino, R. Bottacini, E. Brandt, T.J. Bregeon, J. Bruel, P. Buehler, R. Cameron, R.A. Caragiulo, M. Caraveo, P.A. Castro, D. Cavazzuti, E. Cecchi, C. Charles, E. Chekhtman, A. Cheung, C.C. Chiaro, G. Ciprini, S. Cohen, J.M. Costantin, D. Costanza, F. Cutini, S. D’Ammando, F. de Palma, F. Desiante, R. Digel, S.W. Di Lalla, N. Di Mauro, M. Di Venere, L. Favuzzi, C. Fegan, S.J. Ferrara, E.C. Franckowiak, A. Fukazawa, Y. Funk, S. Fusco, P. Gargano, F. Gasparrini, D. Giglietto, N. Giordano, F. Giroletti, M. Green, D. Grenier, I.A. Grondin, M.-H. Guillemot, L. Guiriec, S. Harding, A.K. Hays, E. Hewitt, J.W. Horan, D. Hou, X. Jóhannesson, G. Kamae, T. Kuss, M. la Mura, G. Larsson, S. Lemoine-Goumard, M. Li, J. Longo, F. Loparco, F. Lubrano, P. Magill, J.D. Maldera, S. Malyshev, D. Manfreda, A. Mazziotta, M.N. Michelson, P.F. Mitthumsiri, W. Mizuno, T. Monzani, M.E. Morselli, A. Moskalenko, I.V. Negro, M. Nuss, E. Ohsugi, T. Omodei, N. Orienti, M. Orlando, E. Ormes, J.F. Paliya, V.S. Paneque, D. Perkins, J.S. Persic, M. Pesce-Rollins, M. Petrosian, V. Piron, F. Porter, T.A. Principe, G. Rainò, S. Rando, R. Razzano, M. Razzaque, S. Reimer, A. Reimer, O. Reposeur, T. Sgrò, C. Simone, D. Siskind, E.J. Spada, F. Spandre, G. Spinelli, P. Suson, D.J. Tak, D. Thayer, J.B. Thompson, D.J. Torres, D.F. Tosti, G. Troja, E. Vianello, G. Wood, K.S. Wood, M. Deutsches Elektronen Synchrotron DESY ZeuthenD-15738 Germany Department of Physics and Astronomy Clemson University Kinard Lab of Physics ClemsonSC29634-0978 United States Università di Pisa Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy Laboratoire AIM CEA-IRFU CNRS Université Paris Diderot Service d’Astrophysique CEA Saclay Gif sur YvetteF-91191 France Istituto Nazionale di Fisica Nucleare Sezione di Trieste TriesteI-34127 Italy Dipartimento di Fisica Università di Trieste TriesteI-34127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy Dipartimento di Fisica e Astronomia "G. Galilei" Università di Padova PadovaI-35131 Italy Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari BariI-70126 Italy W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics SLAC National Accelerator Laboratory Stanford University StanfordCA94305 United States Istituto Nazionale di Fisica Nucleare Sezione di Torino TorinoI-10125 Italy Dipartimento di Fisica Università degli Studi di Torino TorinoI-10125 Italy NASA Goddard Space Flight Center GreenbeltMD20771 United States Laboratoire Univers et Particules de Montpellier Université Montpellier CNRS/IN2P3 MontpellierF-34095 France Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 PalaiseauF-91128 France Dipartimento di Fisica "M. Merlin" dell’Università e del Politecnico di Bari BariI-70126 Italy INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica Milano via E. Bassini 15 MilanoI-20133 Italy Science Data Center RomaI-00133 Italy Istituto Nazionale di Fisica Nucleare Sezione di Perugia PerugiaI-06123 Italy Dipartimento di Fisica Università degli Studi di Perugia PerugiaI-06123 Italy College of Science George Mason University Fairfax VA22030 United States Naval Research Laboratory Washi

The spatial extension of a γ-ray source is an essential ingredient to determine its spectral properties as well as its potential multi-wavelength counterpart. The capability to spatially resolve γ-ray sources is greatly improved by the newly delivered Fermi-Large Area Telescope (LAT) Pass 8 event-level analysis which provides a greater acceptance and an improved point spread function, two crucial factors for the detection of extended sources. Here, we present a complete search for extended sources located within 7◦ from the Galactic plane, using 6 years of Fermi-LAT data above 10 GeV. We find 46 extended sources and provide their morphological and spectral characteristics. This constitutes the first catalog of hard Fermi-LAT extended sources, named the Fermi Galactic Extended Source Catalog, which allows a thorough study of the properties of the Galactic plane in the sub-TeV domain. Copyright © 2017, The Authors. All rights reserved.

关键词： Gamma rays

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OBSERVATIONS OF M31 AND M33 WITH THE FERMI LARGE AREA TELESCOPE: A GALACTIC CENTER EXCESS IN ANDROMEDA?

arXiv

引用

arXiv 2017年

作者： Ackermann, M. Ajello, M. Albert, A. Baldini, L. Ballet, J. Barbiellini, G. Bastieri, D. Bellazzini, R. Bissaldi, E. Bloom, E.D. Bonino, R. Bottacini, E. Brandt, T.J. Bregeon, J. Bruel, P. Buehler, R. Cameron, R.A. Caputo, R. Caragiulo, M. Caraveo, P.A. Cavazzuti, E. Cecchi, C. Charles, E. Chekhtman, A. Chiaro, G. Ciprini, S. Costanza, F. Cutini, S. D’Ammando, F. de Palma, F. Desiante, R. Digel, S.W. Di Lalla, N. Di Mauro, M. Di Venere, L. Favuzzi, C. Funk, S. Fusco, P. Gargano, F. Giglietto, N. Giordano, F. Giroletti, M. Glanzman, T. Green, D. Grenier, I.A. Guillemot, L. Guiriec, S. Hayashi, K. Hou, X. Jóhannesson, G. Kamae, T. Knödlseder, J. Kong, A.K.H. Kuss, M. la Mura, G. Larsson, S. Latronico, L. Li, J. Longo, F. Loparco, F. Lubrano, P. Maldera, S. Malyshev, D. Manfreda, A. Martin, P. Mazziotta, M.N. Michelson, P.F. Mirabal, N. Mitthumsiri, W. Mizuno, T. Monzani, M.E. Morselli, A. Moskalenko, I.V. Negro, M. Nuss, E. Ohsugi, T. Omodei, N. Orlando, E. Ormes, J.F. Paneque, D. Persic, M. Pesce-Rollins, M. Piron, F. Porter, T.A. Principe, G. Rainò, S. Rando, R. Razzano, M. Reimer, O. Sánchez-Conde, M. Sgrò, C. Simone, D. Siskind, E.J. Spada, F. Spandre, G. Spinelli, P. Tanaka, K. Tibaldo, L. Torres, D.F. Troja, E. Uchiyama, Y. Wang, J.C. Wood, K.S. Wood, M. Zaharijas, G. Zhou, M. Deutsches Elektronen Synchrotron DESY ZeuthenD-15738 Germany Department of Physics and Astronomy Clemson University Kinard Lab of Physics ClemsonSC29634-0978 United States Los Alamos National Laboratory Los AlamosNM87545 United States Università di Pisa Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy Laboratoire AIM CEA-IRFU CNRS Université Paris Diderot Service d’Astrophysique CEA Saclay Gif sur YvetteF-91191 France Istituto Nazionale di Fisica Nucleare Sezione di Trieste TriesteI-34127 Italy Dipartimento di Fisica Università di Trieste TriesteI-34127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy Dipartimento di Fisica e Astronomia "G. Galilei" Università di Padova PadovaI-35131 Italy Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari BariI-70126 Italy W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics SLAC National Accelerator Laboratory Stanford University StanfordCA94305 United States Istituto Nazionale di Fisica Nucleare Sezione di Torino TorinoI-10125 Italy Dipartimento di Fisica Università degli Studi di Torino TorinoI-10125 Italy NASA Goddard Space Flight Center GreenbeltMD20771 United States Laboratoire Univers et Particules de Montpellier Université Montpellier CNRS/IN2P3 MontpellierF-34095 France Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 PalaiseauF-91128 France Santa Cruz Institute for Particle Physics Department of Physics Department of Astronomy and Astrophysics University of California at Santa Cruz Santa CruzCA95064 United States Dipartimento di Fisica "M. Merlin" dell’Università e del Politecnico di Bari BariI-70126 Italy INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica Milano via E. Bassini 15 MilanoI-20133 Italy Science Data Center RomaI-00133 Italy Istituto Nazionale di Fi

The Fermi Large Area Telescope (LAT) has opened the way for comparative studies of cosmic rays (CRs) and high-energy objects in the Milky Way (MW) and in other, external, star-forming galaxies. Using 2 yr of observations with the Fermi LAT, Local Group galaxy M31 was detected as a marginally extended gamma-ray source, while only an upper limit has been derived for the other nearby galaxy M33. We revisited the gamma-ray emission in the direction of M31 and M33 using more than 7 yr of LAT Pass 8 data in the energy range 0.1−100 GeV, presenting detailed morphological and spectral analyses. M33 remains undetected, and we computed an upper limit of 2.0×10−12 erg cm−2 s−1 on the 0.1−100 GeV energy flux (95% confidence level). This revised upper limit remains consistent with the observed correlation between gamma-ray luminosity and star-formation rate tracers and implies an average CR density in M33 that is at most half of that of the MW. M31 is detected with a significance of nearly 10σ. Its spectrum is consistent with a power law with photon index Γ = 2.4±0.1stat+syst and a 0.1−100 GeV energy flux of (5.6±0.6stat+syst)×10−12 erg cm−2 s−1. M31 is detected to be extended with a 4σ significance. The spatial distribution of the emission is consistent with a uniform-brightness disk with a radius of 0◦.4 and no offset from the center of the galaxy, but nonuniform intensity distributions cannot be excluded. The flux from M31 appears confined to the inner regions of the galaxy and does not fill the disk of the galaxy or extend far from it. The gamma-ray signal is not correlated with regions rich in gas or star-formation activity, which suggests that the emission is not interstellar in origin, unless the energetic particles radiating in gamma rays do not originate in recent star formation. Alternative and nonexclusive interpretations are that the emission results from a population of millisecond pulsars dispersed in the bulge and disk of M31 by disrupted globular clusters or from

关键词： Galaxies

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Improved factor analysis algorithm in factor spaces

Improved factor analysis algorithm in factor spaces

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2014 International Conference on Informatics, Networking and intelligent computing(INIC 2014)

作者： H.D.Wang Y.Shi P.Z.Wang H.T.Liu Key Research Lab on Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijingChina Research Center on Fictitious Economy & Data ScienceChinese Academy of SciencesBeijingChina School of Mathematical SciencesUniversity of Chinese Academy of Sciences Institute of Intelligent Engineering and Mathematics Liaoning Technical University

In order to further improve the velocity and the utilization of information contained in samples,an improved version of the Factor Analysis Algorithm(FAA) in factor spaces is presented in this *** primary algorithm is considered from the whole classes during the selection of the next classified factor,by which a smaller decision domain is generated than that generated by considering from each class,and the deletion of the decision domain is critical in decreasing calculation and increasing the velocity of the ***,based on inheriting the merits of the initial algorithm,the pushing way by each column is changed into that by each class during the selection of the next classified *** change not only decreases the calculation,but also improves the utilization of the sample *** testing results also indicate that the improvement is significant and the testing accuracy rate and velocity are both better than the primary algorithm.

关键词： Factor spaces factor analysis decision domain time complexity

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Clonepedia: Summarizing Code Clones by Common Syntactic Context for Software Maintenance

Clonepedia: Summarizing Code Clones by Common Syntactic Cont...

引用

International Conference on Software Maintenance (ICSM)

作者： Yun Lin Zhenchang Xing Xin Peng Yang Liu Jun Sun Wenyun Zhao Jinsong Dong Shanghai Key Laboratory of Data Science Fudan University Shanghai China School of Computer Engineering Nanyang Technological University Singapore Singapore University of Technology and Design Singapore School of Computing National University of Singapore Singapore

Code clones have to be made explicit and be managed in software maintenance. Researchers have developed many clone detection tools to detect and analyze code clones in software systems. These tools report code clones as similar code fragments in source files. However, clone-related maintenance tasks (e.g., refactorings) often involve a group of code clones appearing in larger syntactic context (e.g., code clones in sibling classes or code clones calling similar methods). Given a list of low-level code-fragment clones, developers have to manually summarize from bottom up low-level code clones that are relevant to the syntactic context of a maintenance task. In this paper, we present a clone summarization technique to summarize code clones with respect to their common syntactic context. The clone summarization allows developers to locate and maintain code clones in a top-down manner by type hierarchy and usage dependencies. We have implemented our approach in the Clonepedia tool and conducted a user study on JHotDraw with 16 developers. Our results show that Clonepedia users can better locate and refactor code clones, compared with developers using the Clone Detective tool.

关键词： Cloning Syntactics Abstracts Context Ontologies Production facilities Maintenance engineering

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Design of a high-performance full-system instrumentation

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Dongbei Daxue Xuebao/Journal of Northeastern University 2014年 35卷 129-134页

作者： Min, Qing-Hao Zhang, Zheng Wang, Hao-Jun Zhang, Wei-Hua Software School Fudan University Shanghai201203 China Shanghai Key Laboratory of Data Science Fudan University Shanghai201203 China Parallel Processing Institute Fudan University Shanghai201203 China State Key Laboratory of Mathematic Engineering and Advanced Computing PLA Information Engineering University Zhengzhou450001 China

Instrumentation is an important mechanism to collect run-time information of applications for further analysis like bottleneck analysis, hotspot analysis and even bug detection and revision. Currently there are lots of analyzers using instrumentation to collect their source data. However, most of these tools lack of full-system support and thus become inadequate for analyzing multi-core programs as they cannot provide full-system information like scheduling, system calls and inter-process communication, etc. Meanwhile, full-system instrumentation needs to collect OS and hardware information, resulting to performance degradation. In this paper, a high-performance full-system instrumentation method was designed for collecting full-system information as well as application information. The proposed method was implemented inside the QEMU full-system emulator, and 40 MIPS performance on average was achieved after optimization, which was appropriated for normal program analysis. ©, 2014, Northeastern University. All right reserved.

关键词： Full-system High-performance Instrumentation Multi-core

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Measurement of the high-energy gamma-ray emission from the Moon with the Fermi Large Area Telescope

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Physical Review D 2016年第8期93卷 082001-082001页

作者： M. Ackermann M. Ajello A. Albert W. B. Atwood L. Baldini G. Barbiellini D. Bastieri R. Bellazzini E. Bissaldi R. D. Blandford R. Bonino E. Bottacini J. Bregeon P. Bruel R. Buehler G. A. Caliandro R. A. Cameron M. Caragiulo P. A. Caraveo E. Cavazzuti C. Cecchi A. Chekhtman J. Chiang G. Chiaro S. Ciprini R. Claus J. Cohen-Tanugi F. Costanza A. Cuoco S. Cutini F. D’Ammando A. de Angelis F. de Palma R. Desiante S. W. Digel L. Di Venere P. S. Drell C. Favuzzi S. J. Fegan W. B. Focke A. Franckowiak S. Funk P. Fusco F. Gargano D. Gasparrini N. Giglietto F. Giordano M. Giroletti T. Glanzman G. Godfrey I. A. Grenier J. E. Grove S. Guiriec A. K. Harding J. W. Hewitt D. Horan X. Hou G. Iafrate G. Jóhannesson T. Kamae M. Kuss S. Larsson L. Latronico J. Li L. Li F. Longo F. Loparco M. N. Lovellette P. Lubrano J. Magill S. Maldera A. Manfreda M. Mayer M. N. Mazziotta P. F. Michelson W. Mitthumsiri T. Mizuno M. E. Monzani A. Morselli S. Murgia E. Nuss N. Omodei E. Orlando J. F. Ormes D. Paneque J. S. Perkins M. Pesce-Rollins V. Petrosian F. Piron G. Pivato S. Rainò R. Rando M. Razzano A. Reimer O. Reimer T. Reposeur C. Sgrò E. J. Siskind F. Spada G. Spandre P. Spinelli H. Takahashi J. B. Thayer D. J. Thompson L. Tibaldo D. F. Torres G. Tosti E. Troja G. Vianello B. L. Winer K. S. Wood M. Yassine F. Cerutti A. Ferrari P. R. Sala Deutsches Elektronen Synchrotron DESY D-15738 Zeuthen Germany Department of Physics and Astronomy Clemson University Kinard Lab of Physics Clemson South Carolina 29634-0978 USA 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 Università di Pisa and 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 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 Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Torino I-10125 Torino Italy Dipartimento di Fisica Generale “Amadeo Avogadro” Università degli Studi di Torino I-10125 Torino Italy Laboratoire Univers et Particules de Montpellier Université Montpellier CNRS/IN2P3 F-34095 Montpellier France Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 F-91128 Palaiseau Cedex France Consorzio Interuniversitario per la Fisica Spaziale (CIFS) I-10133 Torino Italy Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Agenzia Spaziale Italiana (ASI) Science Data Center I-00133 Roma Italy Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Dipartimento di Fisica Università degli Studi di Perugia I-06123 Perugia

We have measured the gamma-ray emission spectrum of the Moon using the data collected by the Large Area Telescope onboard the Fermi satellite during its first seven years of operation, in the energy range from 30 MeV up to a few GeV. We have also studied the time evolution of the flux, finding a correlation with the solar activity. We have developed a full Monte Carlo simulation describing the interactions of cosmic rays with the lunar surface. The results of the present analysis can be explained in the framework of this model, where the production of gamma rays is due to the interactions of cosmic-ray proton and helium nuclei with the surface of the Moon. Finally, we have used our simulation to derive the cosmic-ray proton and helium spectra near Earth from the Moon gamma-ray data.

关键词： Cosmic ray sources Cosmic rays & astroparticles Gamma ray astronomy Solar cycles

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Pivot probability induction for statistical machine translation with topic similarity

引用

Journal of Computational Information Systems 2013年第20期9卷 8351-8359页

作者： Huang, Yanzhou Shi, Xiaodong Su, Jinsong Chen, Yidong Huang, Guimin Fujian Key Lab. of the Brain-Like Intelligent Systems Xiamen University Xiamen 361005 China Department of Cognitive Science School of Information Science and Technology Xiamen University Xiamen 361005 China School of Software Xiamen University Xiamen 361005 China Research Center on Data Science and Social Computing Guilin University of Electronic Technology Guilin 541004 China

Previous works employ the pivot language approach to conduct statistical machine translation when encountering with limited amount of bilingual corpus. Conventional solutions based upon phrase-table combination overlook the semantic discrepancy between the source-pivot corpus and pivot-target corpus and consequently lead to probability estimation inaccuracy for the induced translation rules. In this paper, the latent topic structure of the document-level training data is learned automatically and each phrase translation rule is assigned to a topic distribution. Furthermore, the phrase probability induction is carried out on the basis of the topic similarity, allowing the translation system to consider the semantic relatedness among different rules. Using BLEU as a metric of translation accuracy, we find out our system is capable of achieving a absolute improvement in in-domain test compared with the baseline system. © 2013 Binary Information Press.

关键词： Semantics

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