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arXiv 2020年

作者： Oliveira, Micael J. T. Papior, Nick Pouillon, Yann Blum, Volker Artacho, Emilio Caliste, Damien Corsetti, Fabiano Gironcoli, Stefanode Elena, Alin M. Garca, Alberto Garca-Suarez, Vctor M. Genovese, Luigi Huhn, William P. Huhs, Georg Kokott, Sebastian Kucukbenli, Emine Larsen, Ask H. Lazzaro, Alo Lebedeva, Irina V. Li, Yingzhou Lopez-Duran, David Lopez-Tarifa, Pablo Luders, Martin Marques, Miguel A. L. Minar, Jan Mohr, Stephan Mosto, Arash A. O'Cais, Alan Payne, Mike C. Ruh, Thomas Smith, Daniel G. A. Soler, Jose M. Strubbe, David A. Tancogne-Dejean, Nicolas Tildesley, Dominic Torrent, Marc Wen-Zhe, Victor Max Planck Institute for the Structure and Dynamics of Matter HamburgD-22761 Germany DTU Computing Center Technical University of Denmark Lyngby2800 Denmark Departamento CITIMAC Universidad de Cantabria Santander Spain Simune Atomistics San Sebastian20018 Spain Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Department of Chemistry Duke University DurhamNC27708 United States CIC Nanogune BRTA DIPC San Sebastian20018 Spain Ikerbasque Basque Foundation for Science Bilbao48011 Spain Theory of Condensed Matter Cavendish Laboratory University of Cambridge CambridgeCB30HE United Kingdom Department of Physics IRIG Univ. Grenoble Alpes CEA GrenobleF-38000 France Departments of Materials and Physics Thomas Young Centre for Theory and Simulation of Materials Imperial College London LondonSW72AZ United Kingdom Synopsys Denmark Copenhagen2100 Denmark Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Scientific Computing Department Daresbury Laboratory WarringtonWA44AD United Kingdom Institut de Ciencia de Materials de Barcelona BellaterraE-08193 Spain Departamento de Fisica Universidad de Oviedo CINN Oviedo33007 Spain Barcelona Supercomputing Center Barcelona08034 Spain Fritz Haber Institut Berlin14195 Germany John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Nano-Bio Spectroscopy Group ETSF Departamento de Fisica de Materiales Universidad Del Pais Vasco San Sebastian20018 Spain Department of Chemistry University of Zurich ZurichCH-8057 Switzerland CIC Nanogune BRTA San Sebastian20018 Spain Department of Mathematics Duke University DurhamNC27708-0320 United States Centro de Fisica de Materiales Centro Mixto CSIC-UPV San Sebastian20018 Spain Institut fur Physik Martin-Luther-Universitat Halle-Wittenberg Halle Saale06120 Germany New Technologies Research Centre University of West Bohemia Plzen3

First-principles electronic structure calculations are now accessible to a very large community of users across many disciplines thanks to many successful software packages, some of which are described in this special issue. The traditional coding paradigm for such packages is monolithic, i.e., regardless of how modular its internal structure may be, the code is built independently from others, essentially from the compiler up, possibly with the exception of linear-algebra and message-passing libraries. This model has endured and been quite successful for decades. The successful evolution of the electronic structure methodology itself, however, has resulted in an increasing complexity and an ever longer list of features expected within all software packages, which implies a growing amount of replication between different packages, not only in the initial coding but, more importantly, every time a code needs to be re-engineered to adapt to the evolution of computer hardware architecture. The Electronic Structure Library (ESL) was initiated by CECAM (the European Centre for Atomic and Molecular Calculations) to catalyze a paradigm shift away from the monolithic model and promote modularization, with the ambition to extract common tasks from electronic structure codes and redesign them as open-source libraries available to everybody. Such libraries include, e.g., \heavy-duty"ones that have the potential for a high degree of parallelisation and adaptation to novel hardware within them, thereby separating the sophisticated computer science aspects of performance optimization and reengineering from the computational science done by, e.g., physicists and chemists when implementing new ideas. We envisage that this modular paradigm will improve overall coding eficiency and enable specialists (whether they be computer scientists or computational scientists) to use their skills more effectively, and will lead to a more dynamic evolution of software in the community as well as

关键词： Libraries

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Correction to: Multivariate statistical and trend analyses of surface water quality in the central Indian River Lagoon area, Florida

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Environmental Earth Sciences 2018年第5期77卷 1-1页

作者： Sayem Zaman Ming Ye Fan Zhang Mingming Zhu Department of Scientific Computing Florida State University Tallahassee USA Draper Aden Associates Richmond USA School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin China Department of Earth Ocean and Atmospheric Science Florida State University Tallahassee USA Key Laboratory of Tibetan Environmental Changes and Land Surface Processes Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China Center of Hydraulic Engineering Regulation and Management Jinzhou Waterwork Office Jinzhou China

Unfortunately, the online version of the original article has an error in authors’ names.

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A fully implicit method for lattice boltzmann equations

A fully implicit method for lattice boltzmann equations

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作者： Huang, Jizu Yang, Chao Cai, Xiao-Chuan Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Institute of Software Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Computer Science Beijing100190 China Department of Computer Science University of Colorado Boulder BoulderCO80309 United States

Existing approaches for solving the lattice Boltzmann equations with finite difference methods are explicit and semi-implicit;both have certain stability constraints on the time step size. In this work, a fully implicit second-order finite difference scheme is developed. We focus on a parallel, highly scalable, Newton-Krylov-RAS algorithm for the solution of a large sparse nonlinear system of equations arising at each time step. Here, RAS is a restricted additive Schwarz preconditioner based on a first-order spatial discretization. We show numerically that by using the fully implicit method the time step size is no longer constrained by the CFL condition, and the Newton-Krylov- RAS algorithm is scalable on a supercomputer with more than ten thousand processors. Moreover, to calculate the steady state solution we investigate an adaptive time stepping strategy. The total compute time required by the implicit method with adaptive time stepping is much smaller than that of an explicit method for several test cases. © 2015 Society for Industrial and Applied Mathematics.

关键词： Finite difference method

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Visual sentiment analysis for brand monitoring enhancement

Visual sentiment analysis for brand monitoring enhancement

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International Symposium on Image and Signal Processing and Analysis

作者： Theodoros Giannakopoulos Michalis Papakostas Stavros Perantonis Vangelis Karkaletsis Computational Intelligence Lab National Center for Scientific Research DEMOKRITOS Athens Greece Heracleia Human Centered Computing Laboratory University of Texas Arlington USA Software and Knowledge Engineering Lab National Center for Scientific Research DEMOKRITOS Athens Greece

Brand monitoring and reputation management are vital tasks in all modern business intelligence frameworks. However, recent related technologies rely mostly on the textual aspect of online content, in order to extract the underlying sentiment with respect to particular brands. In this work, we demonstrate the sentiment analysis method in the context of a brand monitoring framework, breaking the text-only barrier in the field. Towards this end, a wide range of visual features is extracted, some of which focus on the underlying semiotics and aesthetics of the images. In addition, we employ textual information embedded in the images under study, by adopting text mining techniques that focus on extracting sentiment. We evaluate the classification task for the particular binary task (negative vs positive sentiment) and propose a fusion approach that combines the two different modalities. Finally, the evaluation procedure has been carried out in the context of two different use cases, namely: (a) a general image sentiment classifier for brand and advertising images and (b) a brand-specific classification procedure, according to which the brand of the input images is known a-priori. Results have proven that the visual-based sentiment classification of brand and advertising information can outperform the respective text-based classification. In addition, fusing the two modalities leads to significant performance boosting.

关键词： Visualization Apertures Image edge detection Random access memory Ferroelectric films Nonvolatile memory

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Testing model transformation programs using metamorphic testing 26

Testing model transformation programs using metamorphic test...

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26th International Conference on software engineering and Knowledge engineering, SEKE 2014

作者： Jiang, Mingyue Chen, Tsong Yueh Kuo, Fei-Ching Zhou, Zhi Quan Ding, Zuohua Department of Computer Science and Software Engineering Swinburne University of Technology HawthornVIC Australia School of Computer Science and Software Engineering University of Wollongong WollongongNSW Australia Laboratory of Scientific Computing and Software Engineering Zhejiang Sci-Tech University Hangzhou Zhejiang China

Model transformations are crucial for the success of Model Driven engineering. Testing is a prevailing technique of verifying the correctness of model transformation programs. A major challenge in model transformation testing is the oracle problem, which refers to the difficulty or high cost in determining the correctness of the output models. Metamorphic Testing alleviates the oracle problem by making use of the relationships among the inputs and outputs of multiple executions of the target function. This paper investigates the effectiveness and feasibility of metamorphic testing in testing model transformation programs. Empirical results show that metamorphic testing is an effective testing method for model transformation programs. Copyright © 2014 by Knowledge Systems Institute Graduate School.

关键词： Metamorphic testing Model transformation software quality software testing Test oracle

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Toward a multi-tenant college sustained team seeking system

Toward a multi-tenant college sustained team seeking system

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World Congress on Information and Communication Technologies (WICT)

作者： Shuwei Yao Kun Ma Zhe Yang Ajith Abraham School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China Shandong Provincial Key Laboratory of Software Engineering Shandong University Jinan China IT4Innovations - Center of excellence VSB - Technical University of Ostrava Czech Republic Machine Intelligence Research Labs Scientific Network for Innovation and Research Excellence Auburn USA

College students often collaborate in some projects or contests with other students from different majors, but current team seeking system has some limitations on finding teammates. In this paper, we design a multi-tenant college sustained team seeking system, aiming at establishing a sustained team among college students who have similar interest. We present the architecture, core modules, and some emerging techniques to design such a system. The evaluation of query efficiency and page loading speed are present at last.

关键词： Databases Cache storage Loading Servers Rendering (computer graphics) Information and communication technology

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Message from the IWPAPS 2012 workshop chairs

Proceedings - 2012 IEEE International Conference on Cluster ...

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Proceedings - 2012 IEEE International Conference on Cluster computing Workshops, Cluster Workshops 2012 2012年 xiii页

作者： Zhang, Linbo Zhang, Yunquan State Key Laboratory of Scientific and Engineering Computing CAS China Institute of Software CAS China

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"At scale" author name matching with Hadoop/MapReduce

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Library Hi Tech News 2012年第4期29卷 6-12页

作者： Powell, James Collins, Linn Eberhardt, Ariane Izraelevitz, David Roman, Jorge Dufresne, Thomas Scott, Mark Blake, Miriam Grider, Gary Research Library Los Alamos National Laboratory Los Alamos NM United States International Research and Analysis Group Los Alamos National Laboratory Los Alamos NM United States Risk Analysis and Decision Support Los Alamos National Laboratory Los Alamos NM United States Scientific Software Engineering Los Alamos National Laboratory Los Alamos NM United States High Performance Computing Los Alamos National Laboratory Los Alamos NM United States

Purpose: The purpose of this paper is to describe a process for extracting and matching author names from large collections of bibliographic metadata using the Hadoop implementation of MapReduce. It considers the challenges and risks associated with name matching on such a large-scale and proposes simple matching heuristics for the reduce process. The resulting semantic graphs of authors link names to publications, and include additional features such as phonetic representations of author last names. The authors believe that this achieves an appropriate level of matching at scale, and enables further matching to be performed with graph analysis tools. Design/methodology/approach: A topically-focused collection of metadata records describing peer-reviewed papers was generated based upon a search. The matching records were harvested and stored in the Hadoop Distributed File System (HDFS) for processing by hadoop. A MapReduce job was written to perform coarse-grain author name matching, and multiple papers were matched with authors when the names were very similar or identical. Semantic graphs were generated so that the graphs could be analyzed to perform finer grained matching, for example by using other metadata such as subject headings. Findings: When performing author name matching at scale using MapReduce, the heuristics that determine whether names match should be limited to the rules that yield the most reliable results for matching. Bad rules will result in lots of errors, at scale. MapReduce can also be used to generate or extract other data that might help resolve similar names when stricter rules fail to do so. The authors also found that matching is more reliable within a well-defined topic domain. Originality/value: Libraries have some of the same big data challenges as are found in data-driven science. Big data tools such as hadoop can be used to explore large metadata collections, and these collections can be used as surrogates for other real world, big

关键词： Bibliographies Computer systems Information systems Libraries Metadata Research

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Automatic Digest Generation by Extracting Important Scenes from the Content of Presentations

Automatic Digest Generation by Extracting Important Scenes f...

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International Workshop on Database and Expert Systems Applications

作者： Hieu Hanh Le Thitiporn Lertrusdachakul Tetsutaro Watanabe Haruo Yokota Department of Computer Science Tokyo Institute of Technology Japan Department of Computer Science Graduate School of Information and Engineering Tokyo Institute of Technology Japan Application Lab Ricoh Company Ltd Application Laboratory Software R&D Group Ricoh Company Limited Japan Department of Computer Science Tokyo Institute of Technology Global Scientific Information and Computing Center Tokyo Institute of Technology

Recently, combining a video recording of a presentation along with the digital slides used in it has become popular in e-learning and presentation of archives. For users of the archives, it is useful to preview a digest of such content to grasp the atmosphere and/or an outline of the presentation. This paper proposes a method of automatic digest generation by extracting important scenes from the presentation content. The extracted scenes are chosen based on several factors such as frequency and specificity of words, scene duration and order. Finally, the effectiveness of the proposed methods are evaluated by comparing with testers' answer sets for actual lectures.

关键词： Data mining Speech Proposals Electronic learning Arrays Video recording software

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