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31st International Symposium on computational Geometry, SoCG 2015

作者： Agarwal, Pankaj K. Mølhave, Thomas Revsbæk, Morten Safa, Issam Wang, Yusu Yang, Jungwoo Department of Computer Science Duke University United States Scalable Algorithmics SCALGO United States MADALGO Center for Massive Data Algorithmics Aarhus University Denmark Computational Lithography Group Intel Corporation United States Department of Computer Science and Engineering Ohio State University United States

ISBN: (纸本)9783939897835

We study the problem of maintaining the contour tree T of a terrain σ, represented as a triangulated xy-monotone surface, as the heights of its vertices vary continuously with time. We characterize the combinatorial changes in T and how they relate to topological changes in. We present a kinetic data structure (KDS) for maintaining T efficiently. It maintains certificates that fail, i.e., an event occurs, only when the heights of two adjacent vertices become equal or two saddle vertices appear on the same contour. Assuming that the heights of two vertices of κ become equal only O(1) times and these instances can be computed in O(1) time, the KDS processes O(κ + n) events, where n is the number of vertices in σ and κ;is the number of events at which the combinatorial structure of T changes, and processes each event in O(log n) time. The KDS can be extended to maintain an augmented contour tree and a join/split tree.

关键词： Trees (mathematics)

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Precision Medicine:What Challenges Are We Facing?

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Genomics, Proteomics & Bioinformatics 2016年第5期14卷 253-261页

作者： Yu Xue Eric-Wubbo Lameijer Kai Ye Kunlin Zhang Suhua Chang Xiaoyue Wang Jianmin Wu Ge Gao Fangqing Zhao Jian Li Chunsheng Han Shuhua Xu Jingfa Xiao Xuerui Yang Xiaomin Ying Xuegong Zhang Wei-Hua Chen Yun Liu Zhang Zhang Kun Huang Jun Yu MOE Key Lahoratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Brain ScienceHuazhong University of Science and TechnologyWuhan 430074China School of Electronic and Information Engineering.Xi'an Jiaotong University.Xi'an 710049 China CAS Key Laboratory of Mental Health Institute of PsychologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of'Medical Molecular Biology Institute of Basic Medical SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijing 100005China MOE Beijing Key Laboratory of Carcinogenesis and Translatiooal ResearchCenter for Cancer BioinformaticsPeking University Cancer Hospital&InstituteBeijing 100142China Center for Bioinformatics State Key Laboratory of Protein and Plant Gene ResearchSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Institutes of Life Science.Chinese Academy of Sciences Beijing 100101China MOE Key Lahoratory of Developnlental Genes and Human Disease Institute of Life SciencesSoutheast UniversityNanjing 210096China State Key Laboratory of Stem Cell and Reproductive Biology Institute of Zoology Chinese Academy of SciencesBeijing 100101China Max Planck Independent Research Group on Population Genomics CAS-MPG Partner Institute for Computational Biology(PICB)Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China CAS Ker Laboratory of Genome Sciences and Information Chinese Academy of Sciences.Beijing 100101China MOE Key Laboratory of Bioinformatics School of Life Sciences Center for Synthetic and Systems BiologyTsinghua UniversityBeijing 100084China Computational Omics Lahoratory Center of Computational BiologyBeijing Institute of Basic Medical SciencesBeijing 100850China Bioinformatics Division TNLIST and MOE Key Laboratory for Bioinformatics Department of AutomationTsinghua UniversityBeijing 100084China Department of Bioinformatics and Systems Biology College of LifeScience and Technol

Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several n... 详细信息

关键词： PMI Precision Medicine data We

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Sustainable computational science: The Rescience initiative

arXiv

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arXiv 2017年

作者： Rougier, Nicolas P. Hinsen, Konrad Alexandre, Frédéric Arildsen, Thomas Barba, Lorena Benureau, Fabien C.Y. Titus Brown, C. de Buyl, Pierre Caglayan, Ozan Davison, Andrew P. Delsuc, Marc André Detorakis, Georgios Diem, Alexandra K. Drix, Damien Enel, Pierre Girard, Benoît Guest, Olivia Hall, Matt G. Henriques, Rafael Neto Hinaut, Xavier Jaron, Kamil S. Khamassi, Mehdi Klein, Almar Manninen, Tiina Marchesi, Pietro McGlinn, Dan Metzner, Christoph Petchey, Owen L. Plesser, Hans Ekkehard Poisot, Timothée Ram, Karthik Ram, Yoav Roesch, Etienne Rossant, Cyrille Rostami, Vahid Shifman, Aaron Stimberg, Marcel Stachelek, Joseph Stollmeier, Frank Vaggi, Federico Viejo, Guillaume Vitay, Julien Vostinar, Anya Yurchak, Roman Zito, Tiziano INRIA Bordeaux Sud-Ouest Talence France Institut des Maladies Neurodégénératives Université de Bordeaux CNRS UMR 5293 Bordeaux France LaBRI Université de Bordeaux Bordeaux INP CNRS UMR 5800 Talence France Centre de Biophysique Moléculaire CNRS UPR4301 Orléans France Synchrotron SOLEIL Division Expériences Gif sur Yvette France Department of Electronic Systems Technical Faculty of IT and Design Aalborg University Denmark Department of Mechanical and Aerospace Engineering George Washington University WashingtonDC United States Department of Population Health and Reproduction University of California Davis DavisCA United States Instituut voor Theoretische Fysica KU Leuven Belgium Le Mans France Unité de Neurosciences Information et Complexité CNRS FRE 3693 Gif sur Yvette France Institut de Génétique et de Biologie Moléculaire et Cellulaire INSERM U964 CNRS UMR 7104 Université de Strasbourg Illkirch France Department of Cognitive Sciences University of California Irvine United States Computational Engineering and Design Faculty of Engineering and the Environment University of Southampton United Kingdom Department of Computer Science Humboldt-Universität zu Berlin Friedman Brain Institute Icahn School of Medicine Mount SinaiNY United States Institut des Systèmes Intelligent et de Robotique Sorbonne Universités UPMC Univ Paris 06 CNRS Paris France Experimental Psychology University College London United Kingdom UCL Great Ormond St Institute of Child Health University College London London United Kingdom MRC Cognition and Brain Sciences Unit Cambridge United Kingdom Department of Ecology and Evolution University of Lausanne Lausanne Switzerland Independent scholar Enschede Netherlands BioMediTech Institute and Faculty of Biomedical Sciences and Engineering Tampere University of Technology Tampere Finland Swammerdam Institute for Life Sciences Center for Neuroscience Faculty of Science University of Amsterdam Amsterdam Netherlands Depart

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. Rescience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. Rescience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests. Copyright © 2017, The Authors. All rights reserved.

关键词： Open source software

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From categorical to numerical: Multiple transitive distance learning and embedding

From categorical to numerical: Multiple transitive distance ...

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SIAM International Conference on data Mining 2015, SDM 2015

作者： Zhang, Kai Wang, Qiaojun Chen, Zhengzhang Marsic, Ivan Kumar, Vipin Jiang, Guofei Zhang, Jie School of Computer Science Southwest Petroleum University Chengdu Sichuan Province610500 China Institute of Data Science and Technology Alibaba Group SeattleWA98101 United States Department of Electrical and Computer Engineering Rutger-s the State University of New Jersey NJ08854 United States NEC Laboratories America Inc. PrincetonNJ08540 United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States Center for Computational Systems Biology Fudan University Shanghai200433 China

ISBN: (纸本)9781510811522

Categorical data are ubiquitous in real-world databases. However, due to the lack of an intrinsic proximity measure, many powerful algorithms for numerical data analysis may not work well on their categorical counterparts, making it a bottleneck in practical applications. In this paper, we propose a novel method to transform categorical data to numerical representations, so that abundant numerical learning methods can be exploited in categorical data mining. Our key idea is to learn a pairwise dissimilarity among categorical symbol-s, henceforth a continuous embedding, which can then be used for subsequent numerical treatment. There are two important criteria for learning the dissimilarities. First, it should capture the important "transitivity" which has shown to be particularly useful in measuring the proximity relation in categorical data. Second, the pairwise sample geometry arising from the learned symbol distances should be maximally consistent with prior knowledge (e.g., class labels) to obtain a good generalization performance. We achieve them through multiple transitive distance learning and embedding. Encouraging results are observed on a number of benchmark classification tasks against state-of-the-art. Copyright © SIAM.

关键词： Distance education

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Dense matter with eXTP

arXiv

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arXiv 2018年

作者： Watts, Anna L. Yu, Wenfei Poutanen, Juri Zhang, Shu Bhattacharyya, Sudip Bogdanov, Slavko Ji, Long Patruno, Alessandro Riley, Thomas E. Bakala, Pavel Baykal, Altan Bernardini, Federico Bombaci, Ignazio Brown, Edward Cavecchi, Yuri Chakrabarty, Deepto Chenevez, Jérôme Degenaar, Nathalie Santo, Melania Del Salvo, Tiziana Di Doroshenko, Victor Falanga, Maurizio Ferdman, Robert D. Feroci, Marco Gambino, Angelo F. Ge, MingYu Greif, Svenja K. Guillot, Sebastien Gungor, Can Hartmann, Dieter H. Hebeler, Kai Heger, Alexander Homan, Jeroen Iaria, Rosario in’t Zand, Jean Kargaltsev, Oleg Kurkela, Aleksi Lai, Xiaoyu Li, Ang Li, XiangDong Li, Zhaosheng Linares, Manuel Lu, FangJun Mahmoodifar, Simin Méndez, Mariano Miller, M. Coleman Morsink, Sharon Nättilä, Joonas Possenti, Andrea Prescod-Weinstein, Chanda Qu, JinLu Riggio, Alessandro Salmi, Tuomo Sanna, Andrea Santangelo, Andrea Schatz, Hendrik Schwenk, Achim Song, LiMing Šrámková, Eva Stappers, Benjamin Stiele, Holger Strohmayer, Tod Tews, Ingo Tolos, Laura Török, Gabriel Tsang, David Urbanec, Martin Vacchi, Andrea Xu, RenXin Xu, Ypeng Zane, Silvia Zhang, Guobao Zhang, ShuangNan Zhang, Wenda Zheng, ShiJie Zhou, Xia Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Shanghai Astronomical Observatory Shanghai200030 China Tuorla Observatory Department of Physics and Astronomy University of Turku Väisäläntie 20 PiikkiöFIN-21500 Finland Nordita KTH Royal Institute of Technology Stockholm University Roslagstullsbacken 23 StockholmSE-10691 Sweden Institute of High Energy Physics CAS Beijing100049 China Tata Institute of Fundamental Research Mumbai400005 India Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Institut für Astronomie und Astrophysik Tübingen Universität Tübingen Sand 1 TübingenD-72076 Germany Leiden Observatory Leiden University PO Box 9513 Leiden2300 RA Netherlands Research Center for Computational Physics and Data Processing Silesian University in Opava Bezrucovo nam. 13 OpavaCZ-74601 Czech Republic Physics Department Middle East Technical University Ankara06531 Turkey INAF Osservatorio Astronomico di Roma Via Frascati 33 Monteporzio CatoneI-00078 Italy New York University Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates Dipartimento di Fisica Enrico Fermi University of Pisa PisaI-56127 Italy INFN Italian National Institute for Nuclear Physics Pisa Section Pisa56127 Italy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Mathematical Sciences and STAG Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom MIT Kavli Institute for Astrophysics and Space Research CambridgeMA02139 United States DTU Space Technical University of Denmark Elektrovej 327-328 Kgs Lyngby2800 Denmark INAF/IASF Palermo via Ugo La Malfa 153 PalermoI-90146 Italy Universita degli Studi di Palermo Dipartimento di Fisica e Chimica via Archira 36 Palermo90123 Italy

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter;neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of science, the eXTP mission is expected to be launched in the mid 2020s. Copyright © 2018, The Authors. All rights reserved.

关键词： Pulsars

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Investigation on the influence of atomic potentials on the above threshold ionization

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Chinese Physics B 2014年第5期23卷 238-243页

作者：田原野李苏宇魏珊珊郭福明曾思良陈基根杨玉军 Institute of Atomic and Molecular Physics Jilin University Data Center for High Energy Density Physics Institute of Applied Physics and Computational Mathematics Science and Technology Computation Physics Laboratory Institute of Applied Physics and Computational Mathematics Department of Physics and Materials Engineering Taizhou University

We systematically investigate the influence of atomic potentials on the above-threshold ionization （ATI） spectra in one-dimensional （1D） cases and compare them with the three-dimensional （3D） case by numerically solving the time-dependent Schrrdinger equation. It is found that the direct ionization plateau and the rescattering plateau of the ATI spectrum in the 3D case can be well reproduced by the 1D ATI spectra calculated from the supersolid-core potential and the soft-core potential, respectively. By analyzing the factors that affect the yield of the ATI spectrum, we propose a modified-potential with which we can reproduce the overall 3D ATI spectrum. In addition, the influence of the incident laser intensities and frequencies on the ATI spectra calculated from the proposed modified potential is studied.

关键词： above threshold ionization model potential angular distribution of photoelectron

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Supernovae 2016bdu and 2005gl, and their link with SN 2009ip-like transients: another piece of the puzzle

arXiv

引用

arXiv 2017年

作者： Pastorello, A. Kochanek, C.S. Fraser, M. Dong, S. Elias-Rosa, N. Benetti, S. Cappellaro, E. Tomasella, L. Drake, A.J. Hermanen, J. Reynolds, T. Shappee, B.J. Smartt, S.J. Chambers, K.C. Huber, M.E. Smith, K. Stanek, K.Z. Filippenko, A.V. Christensen, E.J. Denneau, L. Djorgovski, S.G. Flewelling, H. Gall, C. Gal-Yam, A. Geier, S. Heinze, A. Holoien, T.W.-S. Isern, J. Kangas, T. Kankare, E. Koff, R.A. Llapasset, J.-M. Lowe, T.B. Lundqvist, P. Magnier, E.A. Mattila, S. Morales-Garoffolo, A. Mutel, R. Nicolas, J. Ochner, P. Ofek, E.O. Prosperi, E. Rest, A. Sano, Y. Stalder, B. Stritzinger, M.D. Taddia, F. Terreran, G. Tonry, J.L. Wainscoat, R.J. Waters, C. Weiland, H. Willman, M. Young, D.R. Zheng, W. INAF-Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Department of Astronomy Ohio State University 140 West 18th Avenue ColumbusOH43210 United States Ohio State University 191 W. Woodruff Ave. ColumbusOH43210 United States School of Physics O’Brien Centre for Science North University College Dublin Belfield Dublin 4 Ireland Institute of Astronomy University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Royal Society – Science Foundation Ireland University Research Fellow Kavli Institute for Astronomy and Astrophysics Peking University Yi He Yuan Road 5 Hai Dian District Beijing100871 China Astronomy Department California Institute of Technology PasadenaCA91125 United States Tuorla Observatory Department of Physics and Astronomy University of Turku Väisäläntie 20 PiikkiöFI-21500 Finland Nordic Optical Telescope Apartado 474 Santa Cruz de La PalmaE-38700 Spain Carnegie Observatories 813 Santa Barbara Street PasadenaCA91101 United States Hubble Fellow and Carnegie-Princeton Fellow Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast BelfastBT7 1NN United Kingdom Institute for Astronomy University of Hawaii 2680 Woodlawn Drive HonoluluHI96822 United States Department of Astronomy University of California BerkeleyCA94720-3411 United States Lunar and Planetary Lab Department of Planetary Sciences University of Arizona TucsonAZ85721 United States Dark Cosmology Centre Niels Bohr Institute University of Copenhagen Juliane Maries Vej 30 Copenhagen2100 Denmark Department of Physics and Astronomy Aarhus University Ny Munkegade 120 Aarhus CDK-8000 Denmark Department of Particle Physics and Astrophysics Faculty of Physics Weizmann Institute of Science Rehovot76100 Israel Cuesta de San José s/n Breña Baja La PalmaE-38712 Spain Instituto de Astrofísica de Canarias Vía Láctea s/n La Laguna TenerifeE-38200 Spain US Department of Energy Computatio

Supernova (SN) 2016bdu is an unusual transient resembling SN 2009ip. SN 2009ip-like events are characterized by a long-lasting phase of erratic variability which ends with two luminous outbursts a few weeks apart. The second outburst is significantly more luminous (about 3 mag) than the first. In the case of SN 2016bdu, the first outburst (Event A) reached an absolute magnitude Mr ≈ −15.3 mag, while the second one (Event B) occurred over one month later and reached Mr ≈ −18 mag. By inspecting archival data, a faint source at the position of SN 2016bdu is detectable several times in the past few years. We interpret these detections as signatures of a phase of erratic variability, similar to that experienced by SN 2009ip between 2008 and mid-2012, and resembling the currently observed variability of the luminous blue variable SN 2000ch in NGC 3432. Spectroscopic monitoring of SN 2016bdu during the second peak initially shows features typical of a SN IIn. One month after the Event B maximum, the spectra develop broad Balmer lines with P Cygni profiles and broad metal features. At these late phases, the spectra resemble those of a typical Type II SN. All members of this SN 2009ip-like group are remarkably similar to the Type IIn SN 2005gl. For this object, the claim of a terminal SN explosion is supported by the disappearance of the progenitor star. The similarity with SN 2005gl suggests that all members of this family may finally explode as genuine SNe, although the unequivocal detection of nucleosynthesised elements in their nebular spectra is still missing. Copyright © 2017, The Authors. All rights reserved.

关键词： Supernovae

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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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Probing dynamic interference in high-order harmonic generation from long-range molecular ion:Bohmian trajectory investigation

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Chinese Physics B 2014年第5期23卷 233-237页

作者：王俊王兵兵郭福明李苏宇丁大军陈基根曾思良杨玉军 Institute of Atomic and Molecular Physics Jilin University Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of Sciences Department of Physics and Materials Engineering Taizhou University Science and Technology Computation Physics Laboratory Institute of Applied Physics and Computational Mathematics Data Center for High Energy Density Physics Institute of Applied Physics and Computational Mathematics

Using Bohmlan trajectory （151） method, we investigate the dynamic interference in nlgn-orcter narmonlc generauon from diatomic molecular ions. It is demonstrated that the main characteristics of the molecular harmonic spectrum can be well reproduced by only two BTs which are located at the two ions. This haiapens because these two localized trajectories can receive and store the whole collision information coming from all of the other re-collision trajectories. Therefore, the amplitudes and frequencies of these two trajectories represent the intensity and frequency distribution of the harmonic generation. Moreover, the interference between these two trajectories shows a dip in the harmonic spectrum, which reveals the molecular structure information.

关键词： Bohmian trajectory molecular high-order harmonic generation dynamic interference

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A visualization for the dynamic behaviors of the mixture of water mass for northwestern pacific near Japan

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International Journal of Modeling, Simulation, and Scientific Computing 2015年第2期6卷 213-214页

作者： Kun Zhao Satoshi Nakada Naohisa Sakamoto Koji Koyamada Chandrajit Bajaj Yoichi Ishikawa Toshiyuki Awaji Teiji In Sei-Ichi Saitoh Graduate School of Engineering Kyoto University KyotoKyoto Prefecture606-8501Japan Institute for the Promotion of Excellence in Higher Education Kyoto University KyotoKyoto Prefecture606-8501Japan Department of Computer Science The Institute for Computational Engineering and Sciences University of Texas at Austin AustinTexas78712USA Department of Geophysics Division of Earth and Planetary Sciences Kyoto University KyotoKyoto Prefecture606-8501Japan Data Research Center for Marine-Earth Sciences Japan Agency for Marine-Earth Science and Technology Yokosuka Kanakawa Prefecture237-0061Japan Japan Marine Science Foundation Tokyo Tokyo Metropolis110-0008Japan Laboratory of Marine Bioresource and Environment Sensing Faculty of Fisheries Sciences Hokkaido University SapporoHokkaido Prefecture060-0808Japan

(1)This article,published on 20 June 2013,had the following title:A VASUALIZATION FOR THE DYNAMIC BEHAVIORS OF THE MIXTURE OF WATER MASS FOR NORTHWESTERN PACIFIC NEAR JAPAN Here“VASUALIZATION”should be“VISUALIZATIO... 详细信息

关键词： northwestern dynamic NORTH

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