检索结果-内蒙古大学图书馆

25th International Conference on Scientific and Statistical database Management, SSDBM 2013

作者： Burns, Randal Roncal, William Gray Kleissas, Dean Lillaney, Kunal Manavalan, Priya Perlman, Eric Berger, Daniel R. Bock, Davi D. Chung, Kwanghun Grosenick, Logan Kasthuri, Narayanan Weiler, Nicholas C. Deisseroth, Karl Kazhdan, Michael Lichtman, Jeff Reid, R. Clay Smith, Stephen J. Szalay, Alexander S. Vogelstein, Joshua T. Vogelstein, R. Jacob Department of Computer Science Institute for Data Intensive Engineering and Science Johns Hopkins University United States Applied Physics Laboratory Johns Hopkins University United States Department of Statistical Science and Mathematics Institute for Brain Science Duke University United States Janelia Farm Research Campus Howard Hughes Medical Institute United States Department of Molecular and Cellular Biology Harvard University United States Department of Computational Neuroscience Massachusetts Institute of Technology United States Allen Institute for Brain Science United States Department of Physics and Astronomy Institute for Data Intensive Engineering and Science Johns Hopkins University United States Department of Bioengineering Stanford University United States Department of Molecular and Cellular Physiology Stan- Ford University United States

ISBN: (纸本)9781450319218

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at ***. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effectiveness of spatial data organization. Copyright © 2013 ACM.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

A VASUALIZATION FOR THE DYNAMIC BEHAVIORS OF THE MIXTURE OF WATER MASS FOR NORTHWESTERN PACIFIC NEAR JAPAN

引用

International Journal of Modeling, Simulation, and Scientific Computing 2013年第S01期4卷 86-103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

Recent studies are focusing on the distribution of water mass because the mixture region of water mass is highly related to the rich fishing grounds[Yasuda I.,Watanabe Y.,***.3(3):172–181,1994].Due to the large data size and time-varying property,efficient exploration and visualization of the ocean data is always extremely *** extract the dynamic behaviors of the water mass and its mixture from a large-scale simulated ocean dataset,we developed an efficient visualization system by applying our volume compression method and our volume rendering *** system allows us to investigate the time-varying distributions of ocean physical properties,additionally from the user’s perspective and *** the experiments,we show the generality and expressiveness by applying our system for single-and multi-property visualizations to find some significant ocean water ***,we could obtain a clear visualization result to show the dynamic behaviors of the mixture of water mass for simulation data regarding a location in the northwestern Pacific near Japan.

关键词： Oceanography water mass visualization.

来源：评论

学校读者我要写书评

暂无评论

A tale of two systems: Flexibility of usage of Kraken and Nautilus at the National Institute for computational sciences

A tale of two systems: Flexibility of usage of Kraken and Na...

引用

1st Conference of the Extreme science and engineering Discovery Environment: Bridging from the eXtreme to the Campus and Beyond, XSEDE12

作者： Szczepański, Amy F. Huang, Jian Ahern, Sean Fahey, Mark R. Remote Data Analysis and Visualization Center Electrical Engineering and Computer Science University of Tennessee 1520 Middle Drive Knoxville TN 37996-2250 United States Remote Data Analysis and Visualization Center National Institute for Computational Sciences University of Tennessee PO Box 2008 Oak Ridge TN 37831-6173 United States National Institute for Computational Sciences Industrial and Information Engineering University of Tennessee PO Box 2008 Oak Ridge TN 37831-6173 United States

ISBN: (纸本)9781450316026

The National Institute for computational sciences (NICS) at the University of Tennessee currently operates two computational resources for the eXtreme science and engineering Discovery Environment (XSEDE), Kraken, a 112,896-core Cray XT5 for general purpose computation, and Nautilus, a 1,024-core SGI Altix UV 1000 for data analysis and visualization. We analyze a year's worth of accounting logs for Kraken and Nautilus to understand how users take advantage of these two systems and how analysis jobs differ from general HPC computation We find that researchers take advantage of the flexibility offered by these systems, running a wide variety of jobs at many scales and using the full range of core counts and available memory for their jobs. The jobs on Nautilus tend to use less walltime and more memory per core than the jobs run on Kraken. Additionally, researchers are more likely to run interactive jobs on Nautilus than on Kraken. Small jobs experience a good quality of service on both systems. This information can be used for the management and allocation of time on existing HPC and analysis systems as well as for planning for deploying future HPC and analysis systems. © 2012 ACM.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

A quantitative evaluation of techniques for detection of abnormal change events in blogs. 12

A quantitative evaluation of techniques for detection of abn...

引用

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

作者： Bogen II, Paul L. Furuta, Richard Shipman, Frank Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge TN United States Center for the Study of Digital Libraries Dept. of Computer Science and Engineering Texas A and M University College Station TX 77843 United States

ISBN: (纸本)9781450311540

While most digital collections have limited forms of change - primarily creation and deletion of additional resources - there exists a class of digital collections that undergoes additional kinds of change. These collections are made up of resources that are distributed across the Internet and brought together into a collection via hyperlinking. Resources in these collections can be expected to change as time goes on. Part of the difficulty in maintaining these collections is determining if a changed page is still a valid member of the collection. Others have tried to address this problem by measuring change and defining a maximum allowed threshold of change, however, these methods treat all change as a potential problem and treat web content as a static document despite its intrinsically dynamic nature. Instead, we approach the significance of change on the web as a normal part of a web document's life-cycle and determine the difference between what a maintainer expects a page to do and what it actually does. In this work we evaluate the different options for extractors and analyzers in order to determine the best options from a suite of techniques. The evaluation used a human-generated ground-truth set of blog changes. The results of this work showed a statistically significant improvement over a range of traditional threshold techniques when applied to our collection of tagged blog changes. © 2012 ACM.

关键词： Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Collaborative authoring of Walden's paths

Collaborative authoring of Walden's paths

引用

2nd International Conference on Theory and Practice of Digital Libraries, TPDL 2012

作者： Li, Yuanling Bogen II, Paul Logasa Pogue, Daniel Furuta, Richard Shipman, Frank Center for the Study of Digital Libraries Department of Computer Science and Engineering Texas A and M University College Station TX United States Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge United States User Experience and Interaction Design Team Production Enhancement Halliburton Energy Services Houston TX United States

ISBN: (纸本)9783642332890

This paper presents a prototype of an authoring tool to allow users to collaboratively build, annotate, manage, share and reuse collections of distributed resources from the World Wide Web. This extends on the Walden's Path project's work to help educators bring resources found on the World Wide Web into a linear contextualized structure. The introduction of collaborative authoring feature fosters collaborative learning activities through social interaction among participants, where participants can coauthor paths in groups. Besides, the prototype supports path sharing, branching and reusing;specifically, individual participant can contribute to the group with private collections of knowledge resources;paths completed by group can be shared among group members, such that participants can tailor, extend, reorder and/or replace nodes to have sub versions of shared paths for different information needs. © 2012 Springer-Verlag.

关键词： World Wide Web

来源：评论

学校读者我要写书评

暂无评论

Joint Analysis of BICEP2/Keck Array and Planck data

引用

Physical Review Letters 2015年第10期114卷 101301-101301页

作者： P. A. R. Ade N. Aghanim Z. Ahmed R. W. Aikin K. D. Alexander M. Arnaud J. Aumont C. Baccigalupi A. J. Banday D. Barkats R. B. Barreiro J. G. Bartlett N. Bartolo E. Battaner K. Benabed A. Benoît A. Benoit-Lévy S. J. Benton J.-P. Bernard M. Bersanelli P. Bielewicz C. A. Bischoff J. J. Bock A. Bonaldi L. Bonavera J. R. Bond J. Borrill F. R. Bouchet F. Boulanger J. A. Brevik M. Bucher I. Buder E. Bullock C. Burigana R. C. Butler V. Buza E. Calabrese J.-F. Cardoso A. Catalano A. Challinor R.-R. Chary H. C. Chiang P. R. Christensen L. P. L. Colombo C. Combet J. Connors F. Couchot A. Coulais B. P. Crill A. Curto F. Cuttaia L. Danese R. D. Davies R. J. Davis P. de Bernardis A. de Rosa G. de Zotti J. Delabrouille J.-M. Delouis F.-X. Désert C. Dickinson J. M. Diego H. Dole S. Donzelli O. Doré M. Douspis C. D. Dowell L. Duband A. Ducout J. Dunkley X. Dupac C. Dvorkin G. Efstathiou F. Elsner T. A. Enßlin H. K. Eriksen E. Falgarone J. P. Filippini F. Finelli S. Fliescher O. Forni M. Frailis A. A. Fraisse E. Franceschi A. Frejsel S. Galeotta S. Galli K. Ganga T. Ghosh M. Giard E. Gjerløw S. R. Golwala J. González-Nuevo K. M. Górski S. Gratton A. Gregorio A. Gruppuso J. E. Gudmundsson M. Halpern F. K. Hansen D. Hanson D. L. Harrison M. Hasselfield G. Helou S. Henrot-Versillé D. Herranz S. R. Hildebrandt G. C. Hilton E. Hivon M. Hobson W. A. Holmes W. Hovest V. V. Hristov K. M. Huffenberger H. Hui G. Hurier K. D. Irwin A. H. Jaffe T. R. Jaffe J. Jewell W. C. Jones M. Juvela A. Karakci K. S. Karkare J. P. Kaufman B. G. Keating S. Kefeli E. Keihänen S. A. Kernasovskiy R. Keskitalo T. S. Kisner R. Kneissl J. Knoche L. Knox J. M. Kovac N. Krachmalnicoff M. Kunz C. L. Kuo H. Kurki-Suonio G. Lagache A. Lähteenmäki J.-M. Lamarre A. Lasenby M. Lattanzi C. R. Lawrence E. M. Leitch R. Leonardi F. Levrier A. Lewis M. Liguori P. B. Lilje M. Linden-Vørnle M. López-Caniego P. M. Lubin M. Lueker J. F. Macías-Pérez B. Maffei D. Maino N. Mandolesi A. Mangilli M. Maris P. G. Martin E. Martínez-González S. Masi P. Mason S. Matarrese K. G. Megerian School of Physics and Astronomy Cardiff University Queens Buildings The Parade Cardiff CF24 3AA United Kingdom Institut d’Astrophysique Spatiale CNRS (UMR8617) Université Paris-Sud 11 Bâtiment 121 Orsay France Department of Physics Stanford University Stanford California 94305 USA California Institute of Technology Pasadena California USA Harvard-Smithsonian Center for Astrophysics 60 Garden Street MS 42 Cambridge Massachusetts 02138 USA Laboratoire AIM IRFU/Service d’Astrophysique–CEA/DSM–CNRS–Université Paris Diderot Bâtiment 709 CEA-Saclay F-91191 Gif-sur-Yvette Cedex France SISSA Astrophysics Sector via Bonomea 265 34136 Trieste Italy Université de Toulouse UPS-OMP IRAP F-31028 Toulouse cedex 4 France CNRS IRAP 9 Avenue colonel Roche BP 44346 F-31028 Toulouse cedex 4 France Joint ALMA Observatory Vitacura Santiago Chile Instituto de Física de Cantabria (CSIC-Universidad de Cantabria) Avenida de los Castros s/n Santander Spain APC AstroParticule et Cosmologie Université Paris Diderot CNRS/IN2P3 CEA/lrfu Observatoire de Paris Sorbonne Paris Cité 10 rue Alice Domon et Léonie Duquet 75205 Paris Cedex 13 France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena California USA Dipartimento di Fisica e Astronomia G. Galilei Università degli Studi di Padova via Marzolo 8 35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova via Marzolo 8 I-35131 Padova Italy University of Granada Departamento de Física Teórica y del Cosmos Facultad de Ciencias Granada Spain University of Granada Instituto Carlos I de Física Teórica y Computacional Granada Spain Institut d’Astrophysique de Paris CNRS (UMR7095) 98 bis Boulevard Arago F-75014 Paris France UPMC Université de Paris 06 UMR7095 98 bis Boulevard Arago F-75014 Paris France Institut Néel CNRS Université Joseph Fourier Grenoble I 25 rue des Martyrs Grenoble France Department of Physics and Astronomy University College London L

We report the results of a joint analysis of data from BICEP2/Keck Array and Planck. BICEP2 and Keck Array have observed the same approximately 400 deg2 patch of sky centered on RA 0 h, Dec. −57.5°. The combined maps reach a depth of 57 nK deg in Stokes Q and U in a band centered at 150 GHz. Planck has observed the full sky in polarization at seven frequencies from 30 to 353 GHz, but much less deeply in any given region (1.2 μK deg in Q and U at 143 GHz). We detect 150×353 cross-correlation in B modes at high significance. We fit the single- and cross-frequency power spectra at frequencies ≥150 GHz to a lensed-ΛCDM model that includes dust and a possible contribution from inflationary gravitational waves (as parametrized by the tensor-to-scalar ratio r), using a prior on the frequency spectral behavior of polarized dust emission from previous Planck analysis of other regions of the sky. We find strong evidence for dust and no statistically significant evidence for tensor modes. We probe various model variations and extensions, including adding a synchrotron component in combination with lower frequency data, and find that these make little difference to the r constraint. Finally, we present an alternative analysis which is similar to a map-based cleaning of the dust contribution, and show that this gives similar constraints. The final result is expressed as a likelihood curve for r, and yields an upper limit r0.05<0.12 at 95% confidence. Marginalizing over dust and r, lensing B modes are detected at 7.0σ significance.

关键词： STOKES equations FREQUENCIES of oscillating systems POWER spectra GRAVITATIONAL waves

来源：评论

学校读者我要写书评

暂无评论

T645 LOCALISED RESISTANCE SELECTIVELY ACTIVATES THE SEMISPINALIS CERVICIS MUSCLE IN PATIENTS WITH NECK PAIN

引用

European Journal of Pain Supplements 2011年第1期5卷 93-94页

作者： J. Schomacher D. Falla Health Science and Technology Aalborg University Aalborg Denmark Pain Clinic Center for Anesthesiology Emergency and Intensive Care Medicine University Hospital Göttingen Germany Department of Neurorehabilitation Engineering Bernstein Center for Computational Neuroscience University Medical Center Göttingen Georg-August University Göttingen Germany

来源：评论

学校读者我要写书评

暂无评论

T218 REDUCED SPECIFICITY OF SEMISPINALIS CERVICIS ACTIVITY IN WOMEN WITH PERSISTENT NECK PAIN

引用

European Journal of Pain Supplements 2011年第1期5卷 41-41页

作者： J. Schomacher D. Falla Center for Sensory-Motor Interaction (SMI) Department of Health Science and Technology Aalborg University Aalborg Denmark Pain Clinic Center for Anesthesiology Emergency and Intensive Care Medicine University Hospital Göttingen Department of Neurorehabilitation Engineering Bernstein Center for Computational Neuroscience University Medical Center Göttingen Georg-August University Göttingen Germany

来源：评论

学校读者我要写书评

暂无评论

JAWS: Job-aware workload scheduling for the exploration of turbulence simulations 10

JAWS: Job-aware workload scheduling for the exploration of t...

引用

Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis

作者： Wang, Xiaodan Perlman, Eric Burns, Randal Malik, Tanu Budavári, Tamas Meneveau, Charles Szalay, Alexander Dept. of Computer Science Johns Hopkins University United States Cyber Center Purdue University United States Dept. of Physics and Astronomy Johns Hopkins University United States Dept. of Mechanical Engineering Johns Hopkins University United States Institute for Data Intensive Engineering and Science Johns Hopkins University United States

ISBN: (纸本)9781424475575

We present JAWS, a job-aware, data-driven batch scheduler that improves query throughput for data-intensive scientific database clusters. As datasets reach petabyte-scale, workloads that scan through vast amounts of data to extract features are gaining importance in the sciences. However, acute performance bottlenecks result when multiple queries execute simultaneously and compete for I/O resources. Our solution, JAWS, divides queries into I/O-friendly sub-queries for scheduling. It then identifies overlapping data requirements within the workload and executes sub-queries in batches to maximize data sharing and reduce redundant I/O. JAWS extends our previous work [1] by supporting workflows in which queries exhibit data dependencies, exploiting workload knowledge to coordinate caching decisions, and combating starvation through adaptive and incremental trade-offs between query throughput and response time. Instrumenting JAWS in the Turbulence database Cluster [2] yields nearly three-fold improvement in query throughput when contention in the workload is high. © 2010 IEEE.

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

Resource management of enterprise cloud systems using layered queuing and historical performance models

Resource management of enterprise cloud systems using layere...

引用

IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： David A. Bacigalupo Jano van Hemert Asif Usmani Donna N. Dillenberger Gary B. Wills Stephen A. Jarvis School of Electronics and Computer Science University of Southampton UK Data-Intensive Research Group School of Informatics University of Edinburgh UK BRE Centre of Fire Safety Engineering School of Engineering University of Edinburgh UK IBM Thomas J. Watson Research Center Yorktown Heights NY USA High Performance Systems Group Department of Computer Science University of Warwick UK

ISBN: (纸本)9781424465330

The automatic allocation of enterprise workload to resources can be enhanced by being able to make `what-if' response time predictions, whilst different allocations are being considered. It is important to quantitatively compare the effectiveness of different prediction techniques for use in cloud infrastructures. To help make the comparison of relevance to a wide range of possible cloud environments it is useful to consider the following. 1.) urgent cloud customers such as the emergency services that can demand cloud resources at short notice (e.g. for our FireGrid emergency response software). 2.) dynamic enterprise systems, that must rapidly adapt to frequent changes in workload, system configuration and/or available cloud servers. 3.) The use of the predictions in a coordinated manner by both the cloud infrastructure and cloud customer management systems. 4.) A broad range of criteria for evaluating each technique. However, there have been no previous comparisons meeting these requirements. This paper, meeting the above requirements, quantitatively compares the layered queuing and (¿HYDRA¿) historical techniques - including our initial thoughts on how they could be combined. Supporting results and experiments include the following: i.) defining, investigating and hence providing guidelines on the use of a historical and layered queuing model; ii.) using these guidelines showing that both techniques can make low overhead and typically over 70% accurate predictions, for new server architectures for which only a small number of benchmarks have been run; and iii.) defining and investigating tuning a prediction-based cloud workload and resource management algorithm.

关键词： Resource management Clouds Delay Predictive models Computer science data engineering Emergency services Disaster management Guidelines Quality of service

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：