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Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

International Journal of Digital Earth 2011年第4期4卷 305-329页

作者： Chaowei Yang Michael Goodchild Qunying Huang Doug Nebert Robert Raskin Yan Xu Myra Bambacus Daniel Fay Department of Geography and GeoInformation Science and Center for Intelligent Spatial Computing George Mason UniversityFairfax VA 22030-4444USA Department of Geography University of California5707 Ellison HallSanta Barbara CA 93106-4060USA Federal Geographic Data Committee 590 National CenterReston VA 20192USA NASA Jet Propulsion Laboratory 4800 Oak Grove Drive PasadenaCA 91109USA Microsoft Research Connections MicrosoftRedmondWAUSA NASA Goddard Space Flight Center Code 700GreenbeltMD 20771USA

The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal *** challenges require the readiness of a computing infrastructure that can:(1)better support discovery,access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public *** emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial *** discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud *** research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive *** paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC).

关键词： digital earth Cyber GIS geodynamics space-time high-performance computing geospatial cyberinfrastructure

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Search for gamma-ray spectral lines with the Fermi Large Area Telescope and dark matter implications

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Physical Review D 2013年第8期88卷 082002-082002页

作者： M. Ackermann M. Ajello A. Albert A. Allafort L. Baldini G. Barbiellini D. Bastieri K. Bechtol R. Bellazzini E. Bissaldi E. D. Bloom E. Bonamente E. Bottacini T. J. Brandt J. Bregeon M. Brigida P. Bruel R. Buehler S. Buson G. A. Caliandro R. A. Cameron P. A. Caraveo J. M. Casandjian C. Cecchi E. Charles R. C. G. Chaves A. Chekhtman J. Chiang S. Ciprini R. Claus J. Cohen-Tanugi J. Conrad S. Cutini F. D’Ammando A. de Angelis F. de Palma C. D. Dermer S. W. Digel L. Di Venere P. S. Drell A. Drlica-Wagner R. Essig C. Favuzzi S. J. Fegan E. C. Ferrara W. B. Focke A. Franckowiak Y. Fukazawa S. Funk P. Fusco F. Gargano D. Gasparrini S. Germani N. Giglietto F. Giordano M. Giroletti T. Glanzman G. Godfrey G. A. Gomez-Vargas I. A. Grenier S. Guiriec M. Gustafsson D. Hadasch M. Hayashida A. B. Hill D. Horan X. Hou R. E. Hughes Y. Inoue E. Izaguirre T. Jogler T. Kamae J. Knödlseder M. Kuss J. Lande S. Larsson L. Latronico F. Longo F. Loparco M. N. Lovellette P. Lubrano D. Malyshev M. Mayer M. N. Mazziotta J. E. McEnery P. F. Michelson W. Mitthumsiri T. Mizuno A. A. Moiseev M. E. Monzani A. Morselli I. V. Moskalenko S. Murgia T. Nakamori R. Nemmen E. Nuss T. Ohsugi A. Okumura N. Omodei M. Orienti E. Orlando J. F. Ormes D. Paneque J. S. Perkins M. Pesce-Rollins F. Piron G. Pivato S. Rainò R. Rando M. Razzano S. Razzaque A. Reimer O. Reimer R. W. Romani M. Sánchez-Conde A. Schulz C. Sgrò J. Siegal-Gaskins E. J. Siskind A. Snyder G. Spandre P. Spinelli D. J. Suson H. Tajima H. Takahashi J. G. Thayer J. B. Thayer L. Tibaldo M. Tinivella G. Tosti E. Troja Y. Uchiyama T. L. Usher J. Vandenbroucke V. Vasileiou G. Vianello V. Vitale B. L. Winer K. S. Wood M. Wood Z. Yang G. Zaharijas S. Zimmer Deutsches Elektronen Synchrotron DESY D-15738 Zeuthen Germany Space Sciences Laboratory 7 Gauss Way University of California Berkeley California 94720-7450 USA Department of Physics Center for Cosmology and AstroParticle Physics The Ohio State University Columbus Ohio 43210 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 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 Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik Leopold-Franzens-Universität Innsbruck A-6020 Innsbruck Austria Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Dipartimento di Fisica Università degli Studi di Perugia I-06123 Perugia Italy NASA Goddard Space Flight Center Greenbelt Maryland 20771 USA Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari 70126 Bari Italy Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 F-91128 Palaiseau France Institut de Ciències de l’Espai (IEEE-CSIC) Campus UAB 08193 Barcelona Spain INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Laboratoire AIM CEA-IRFU/CNRS/Université Paris Diderot Service d’Astrophysique CEA Saclay 91191 Gif sur Yvette France Center for Earth Observing and Space Research College of Science George Mason University Fairfax Virginia 22030 resid

Weakly interacting massive particles (WIMPs) are a theoretical class of particles that are excellent dark matter candidates. WIMP annihilation or decay may produce essentially monochromatic γ rays detectable by the Fermi Large Area Telescope (LAT) against the astrophysical γ-ray emission of the Galaxy. We have searched for spectral lines in the energy range 5–300 GeV using 3.7 years of data, reprocessed with updated instrument calibrations and an improved energy dispersion model compared to the previous Fermi-LAT Collaboration line searches. We searched in five regions selected to optimize sensitivity to different theoretically motivated dark matter density distributions. We did not find any globally significant lines in our a priori search regions and present 95% confidence limits for annihilation cross sections of self-conjugate WIMPs and decay lifetimes. Our most significant fit occurred at 133 GeV in our smallest search region and had a local significance of 3.3 standard deviations, which translates to a global significance of 1.5 standard deviations. We discuss potential systematic effects in this search, and examine the feature at 133 GeV in detail. We find that the use both of reprocessed data and of additional information in the energy dispersion model contributes to the reduction in significance of the linelike feature near 130 GeV relative to significances reported in other works. We also find that the feature is narrower than the LAT energy resolution at the level of 2 to 3 standard deviations, which somewhat disfavors the interpretation of the 133 GeV feature as a real WIMP signal.

关键词： GAMMA rays SPECTRAL lines

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On alpha-mean of Kullback-Leibler divergences for subspace selection

On alpha-mean of Kullback-Leibler divergences for subspace s...

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Chen, Si-Bao Wang, Hai-Xian Zhang, Xing-Yi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781612841816

Fisher's linear discriminant analysis (FLDA) is one of the most well-known linear subspace selection methods. However, FLDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. Recent results show that maximizing the geometric mean or harmonic mean of Kullback-Leibler (KL) divergences of class pairs can significantly reduce this problem. In this paper, to further reduce the class separation problem, the alpha-mean of divergences as a framework is proposed for subspace selection, with arithmetic mean, geometric mean and harmonic mean as special cases. We named it the maximization of the alpha-mean of all pairs of KL divergences (MAMD) criterion. A quasi-Newton method is applied to solve the optimization problem. Experiments on synthetic data and two datasets in UCI machine learning repository show the validity of MAMD. © 2011 IEEE.

关键词： Newton-Raphson method

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Hybrid feature-based teeth recognition system

Hybrid feature-based teeth recognition system

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Suprachaya Veeraprasit Suphakant Phimoltares Advanced Virtual and Intelligent Computing (AVIC) Research Center Department of Mathematics Faculty of Science Chulalongkom University Bangkok Thailand

Biometric technology is used in several security applications at present. The biometric information and classification have large impact in efficiency of the application. Teeth are chosen as a characteristic for biometric system in this research since teeth are difficult to be reshaped by intent surgery like well-known features such as face, palmprint and fingerprint. In this paper, appropriate features including machine learning model for teeth recognition are proposed. The features of our system can be classified into two categories: global and local features. Global features are composed of singular values and color histogram of teeth image whilst local features are obtained from normalized teeth width. For the experiments, our proposed features are applied into a system of the multilayer perceptrons network with Levenberg-Marquart backpropagation training algorithm. The performance of our system is better than other existing techniques in terms of accuracy and false acceptance.

关键词： Training Feature extraction Accuracy Artificial neural networks Image color analysis Histograms Backpropagation

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Facial expression recognition using graph-based features and artificial neural networks

Facial expression recognition using graph-based features and...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Chaiyasit Tanchotsrinon Suphakant Phimoltares Saranya Maneeroj Advanced Virtual and Intelligent Computing (AVIC) research center Department of Mathematics Faculty of Science Chulalongkom University Bangkok Thailand

Facial expression is significant for face-to-face communication since it is one of our body language that increases data information during the communication. In recent surveys, some of the existing methods extracting features from facial images as the regions of interest. Such regions cover eyes and nose, eyes with eyebrows, mouth, etc. Then global features are extracted from those regions afterwards. This feature extraction method can outperform if some irrelevant features are eliminated. Moreover, this causes lower time consumption in the process of normalization and recognition. In this paper, there are two main parts: locating the points in face region to form graph-based features and training the neural networks to recognize the emotion from the corresponding feature vector. For the first phase, fourteen points are manually located to create graph with edges connecting among such points. Subsequently, the Euclidean distances from those edges are calculated and defined as features for training in the next phase. The next phase is using Multilayer-perceptrons (MLPs), a kind of Artificial Neural Networks (ANN), with back-propagation learning algorithm to recognize six basic emotions. In order to evaluate the performance, the proposed systems are applied to Cohn-Kanade AU-Coded facial expression database and perform 95.24% accuracy which is higher than the existing method.

关键词： Artificial neural networks Feature extraction Face recognition Accuracy Eyebrows Face Emotion recognition

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Palmprint identification system using shape matching and K-Nearest neighbor algorithm

Palmprint identification system using shape matching and K-N...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Patprapa Tunkpien Suphakant Phimoltares Sasipa Panthuwadeethorn Advanced Virtual and Intelligent Computing (AVIC) Research Center Department of Mathematics Faculty of Science Chulalongkom University Bangkok Thailand

This paper presents a palmprint identification system based on principle lines. The system is divided into two main subsystems. The first part concerns with palmprint feature extraction using a cascade of consecutive filters to obtain the principle lines. To achieve our proposed system, recognition is provided as the second part to classify principle line image. Firstly, shape histogram is constructed from the extracted image by projections along vertical and horizontal axes. Then, the histogram of query image and the image in database are compared by using cosine similarity measure. Finally, K-Nearest Neighbor is employed to identify a person. The experimental results demonstrate the efficient system yielding high recognition accuracy.

关键词： Feature extraction Histograms Shape Support vector machine classification databases Accuracy Biometrics

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A Classification Framework of Service Composition Issues in BIRIS Scenario

A Classification Framework of Service Composition Issues in ...

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International Joint Conference on Service sciences (IJCSS)

作者： Dianhui Chu Zhongjie Wang Xiaofei Xu Research Center of Intelligent Computing for Enterprises and Services (ICES) School of Computer Science and Technology Harbin Institute of Technology Harbin China

Service composition (SC) is currently one of the most popular research topics in service computing domain. Given a specific functional and non-functional requirements on a specific service, a composition algorithm selects a set of service components from an existing repository and composes them together as a total solution to fulfill the requirement. There have been fruitful achievements, e.g., template-based composition, planning-based composition, automated/semi-automated/manual composition, etc. However, along with BIRIS becomes a dominate form of modern service systems, a series of new appearing features bring great challenges to traditional SC researches, e.g., (1) from one single requirement to temporally sequential requirements, (2) the available services from abundant to limited, (3) from orchestration-oriented composition solution to choreography-oriented ones, (4) from specified requirements to ambiguous and personalized ones, (5) from the objective of maximizing customer satisfaction to ensuring the benefits of customers and providers together, etc. This paper analyzes these challenges elaborately and presents a classification framework which includes 4 dimensions and 13 sub-dimensions. Several typical SC issues in BIRIS scenario are identified under the framework.

关键词： Web services Optimization Quality of service Customer satisfaction Manuals

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The Quantitative Evaluation on the Value-Oriented Priority of Service Elements

The Quantitative Evaluation on the Value-Oriented Priority o...

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International Joint Conference on Service sciences (IJCSS)

作者： Chao Ma Xiaofei Xu Zhongjie Wang Research Center of Intelligent Computing for Enterprises and Services (ICES) School of Computer Science and Technology Harbin Institute of Technology Harbin China

Value is considered as the ultimate goal of a good service, and whether and to what degree the expected value could be delivered to customers and providers depends on capacities and quality of various functional service elements in service system. Different elements have different contributions to the value production. Due to the limit of available service components to construct the service system, it is necessary to measure the priority of each service element in service models so that those elements with higher value-oriented priorities (VOP) should be implemented by concrete service components earlier and with higher capability during the service system development. This paper presents a quantitative evaluation method of VOP. Basic definition and measurement of service value are firstly introduced, and then VOP is put forward following three types of particular priorities called sensitivity points, tradeoff points and key points. Their characteristics and evaluation principles are presented in details, and the process of the quantitative evaluation method is put forward subsequently. To complement the above discussion, a case study from ocean transportation service is applied for demonstration.

关键词： Quality of service Sea measurements Sensitivity Reliability Receivers Transportation Oceans

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Special issue on the best papers of the Conference on intelligent data Understanding (CIDU 2010)

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Statistical Analysis and data Mining 2011年第4期4卷 355-357页

作者： Srivastava, Ashok N. Chawla, Nitesh V. Intelligent Systems Division Intelligent Data Understanding Group NASA Ames Research Center Moffett Field CA United States Department of Computer Science and Engineering Interdisciplinary Center for Network Science and Applications University of Notre Dame South Bend IN United States

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面向同时多线程的可扩展高速缓存动态划分方法

面向同时多线程的可扩展高速缓存动态划分方法

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2012全国高性能计算学术年会

作者： WU Jun-Min 吴俊敏 ZHU Xiao-Dong 朱小东 SUI Xiu-Feng 隋秀峰 JIN Ying-Qi 金瑛棋 ZHAO Xiao-Yu 赵小雨 School of Computer Science and Technology University of Science and Technology of China Hefei 230 中国科学技术大学计算机学院合肥230027 中国科学技术大学苏州研究院院苏州215123 National Research Center for Intelligent Computing Systems Institute of Computing Technology Beiji 中国科学院计算技术研究所国家智能计算研究中心北京100091

提出一种面向大规模同时多线程处理器可扩展高速缓存的动态划分方法.将文献所提的机制扩展到多体高速缓存中.线程的内存访问特征变化迅速，因此在运行时收集同时多线程的缺失率特征，依此特征在线程间划分高速缓存.实验结果显示，相对... 详细信息

提出一种面向大规模同时多线程处理器可扩展高速缓存的动态划分方法.将文献所提的机制扩展到多体高速缓存中.线程的内存访问特征变化迅速，因此在运行时收集同时多线程的缺失率特征，依此特征在线程间划分高速缓存.实验结果显示，相对于非划分的具有标准LRU替换策略的高速缓存，本文提出的划分方法能够IPC达18.94％.

关键词：多线程处理器高速缓存动态划分

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