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Study of [Formula: see text] and [Formula: see text] production in [Formula: see text] collisions at [Formula: see text] and search for anomalous quartic gauge couplings with the ATLAS experiment

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The European physical journal. C, Particles and fields 2017年第9期77卷 646页

作者： M Aaboud G Aad B Abbott O Abdinov B Abeloos S H Abidi O S AbouZeid N L Abraham H Abramowicz H Abreu R Abreu Y Abulaiti B S Acharya S Adachi L Adamczyk J Adelman M Adersberger T Adye A A Affolder T Agatonovic-Jovin C Agheorghiesei J A Aguilar-Saavedra S P Ahlen F Ahmadov G Aielli S Akatsuka H Akerstedt T P A Åkesson E Akilli A V Akimov G L Alberghi J Albert P Albicocco M J Alconada Verzini S C Alderweireldt M Aleksa I N Aleksandrov C Alexa G Alexander T Alexopoulos M Alhroob B Ali M Aliev G Alimonti J Alison S P Alkire B M M Allbrooke B W Allen P P Allport A Aloisio A Alonso F Alonso C Alpigiani A A Alshehri M I Alstaty B Alvarez Gonzalez D Álvarez Piqueras M G Alviggi B T Amadio Y Amaral Coutinho C Amelung D Amidei S P Amor Dos Santos S Amoroso G Amundsen C Anastopoulos L S Ancu N Andari T Andeen C F Anders J K Anders K J Anderson A Andreazza V Andrei S Angelidakis I Angelozzi A Angerami A V Anisenkov N Anjos A Annovi C Antel M Antonelli A Antonov D J Antrim F Anulli M Aoki L Aperio Bella G Arabidze Y Arai J P Araque V Araujo Ferraz A T H Arce R E Ardell F A Arduh J-F Arguin S Argyropoulos M Arik A J Armbruster L J Armitage O Arnaez H Arnold M Arratia O Arslan A Artamonov G Artoni S Artz S Asai N Asbah A Ashkenazi L Asquith K Assamagan R Astalos M Atkinson N B Atlay K Augsten G Avolio B Axen M K Ayoub G Azuelos A E Baas M J Baca H Bachacou K Bachas M Backes M Backhaus P Bagnaia M Bahmani H Bahrasemani J T Baines M Bajic O K Baker E M Baldin P Balek F Balli W K Balunas E Banas A Bandyopadhyay Sw Banerjee A A E Bannoura L Barak E L Barberio D Barberis M Barbero T Barillari M-S Barisits J T Barkeloo T Barklow N Barlow S L Barnes B M Barnett R M Barnett Z Barnovska-Blenessy A Baroncelli G Barone A J Barr L Barranco Navarro F Barreiro J Barreiro Guimarães da Costa R Bartoldus A E Barton P Bartos A Basalaev A Bassalat R L Bates S J Batista J R Batley M Battaglia M Bauce F Bauer H S Bawa J B Beacham M D Beattie T Beau P H Beauchemin P Bechtle H P Beck H C Beck K Becker M Becker M Beckingham C Becot A J Beddall A Beddall Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco. CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France. Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan. LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France. Department of Physics University of Toronto Toronto ON Canada. Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA USA. Department of Physics and Astronomy University of Sussex Brighton UK. Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel. Department of Physics Technion: Israel Institute of Technology Haifa Israel. Center for High Energy Physics University of Oregon Eugene OR USA. Department of Physics Stockholm University Stockholm Sweden. The Oskar Klein Centre Stockholm Sweden. INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy. ICTP Trieste Italy. International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan. Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland. Department of Physics Northern Illinois University DeKalb IL USA. Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany. Particle Physics Department Rutherford Appleton Laboratory Didcot UK. Institute of Physics University of Belgrade Belgrade Serbia. Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania. Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal. Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain. Department of Physics Boston University Boston MA USA. Joint Institute for Nuclear Research JINR Dubna Dubna Russia. INFN Sezione di Roma Tor Vergata Rome Italy. Dipartimento di Fisica Università di Roma

This paper presents a study of and triboson production using events from proton-proton collisions at a centre-of-mass energy of recorded with the ATLAS detector at the LHC and corresponding to an integrated luminosity of 20.2 fb . The production cross-section is determined using a final state containing an electron, a muon, a photon, and neutrinos ( ). Upper limits on the production cross-section of the final state and the and final states containing an electron or a muon, two jets, a photon, and a neutrino ( or ) are also derived. The results are compared to the cross-sections predicted by the Standard Model at next-to-leading order in the strong-coupling constant. In addition, upper limits on the production cross-sections are derived in a fiducial region optimised for a search for new physics beyond the Standard Model. The results are interpreted in the context of anomalous quartic gauge couplings using an effective field theory. Confidence intervals at 95% confidence level are derived for the 14 coupling coefficients to which and production are sensitive.

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Facial expression recognition algorithm based on feature fusion adaptive weighted HLAC

Facial expression recognition algorithm based on feature fus...

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IEEE/SICE International Symposium on System Integration

作者： Rui Li Zhuguo Yu Min Hu Zhong Huang Fuji Ren Institute of Intelligent Machines(IIM) Chinese Academy of Sciences School of Computer and Information Affective Computing and Advanced Intelligent Machines AnHui Key Laboratory Hefei China Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

In this paper, a novel method of facial expression recognition based on adaptive weighted higher-order local autocorrelation coefficient (WHLAC) is presented. Firstly, The method gets whole face region and sub-regions of eyebrows, eyes, nose and mouth. Secondly, the global features of the face regions and local features of the sub-regions are extracted by HLAC, the weights of sub-regions are calculated by fisher linear discriminant (FLD), and then these two parts features are fused together by the weights. Finally, the fused features are classified by FLD. The experimental results show that the proposed method has higher recognition rate and lower computational cost than Gabor, WLBP, HLAC for facial expression recognition.

关键词： Feature extraction Face recognition Eyebrows Nose Mouth Educational institutions Correlation

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Feature fusion of HOG and WLD for facial expression recognition

Feature fusion of HOG and WLD for facial expression recognit...

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IEEE/SICE International Symposium on System Integration

作者： Xiaohua Wang Chao Jin Wei Liu Min Hu Liangfeng Xu Fuji Ren AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology China School of Computer and Information Hefei University of Technology China The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

A considerable amount of research work has been done for facial expression recognition using local or global feature extraction methods. Weber Local Descriptor (WLD), a simple and robust local image descriptor, is recently developed for local feature extraction. In facial expression recognition, the information contained in the local is important for the recognition result. The Histograms of Oriented Gradients (HOG) can well describe the local area information using gradient and orientation density distribution of the edge. In order to solve the lack of contour and shape information only by WLD features and to extract facial local features more efficiently, we propose a hybrid approach that combines the WLD with HOG features. We divide the images into blocks and weight each of them, then extract the two features and fuse them. At last, the weighted fused histograms are used to classify facial expressions by chi-square distance and the nearest neighbor method. The proposed method is applied on popular JAFFE and Cohn-Kanade facial expression databases and recognition rate is up to 93.97% and 95.86%. Compared with the Gabor Wavelet, LBP, and AAM and experimental results show that the proposed method achieves better performance for facial expression recognition.

关键词： Feature extraction Histograms Databases Face recognition Equations Active appearance model Data mining

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Metamaterial absorbers realized in an X-band rectangular waveguide

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Chinese Physics B 2012年第11期21卷 474-478页

作者：黄勇军文光俊李建钟靖平王平孙元华 O.Gordon 朱卫仁 Key Laboratory of Broadband Optical Fiber Transmission&Communication Networks School of Communication and Information EngineeringUniversity of Electronic Science and Technology of China Advanced Computing and Simulation Laboratory(AχL) Department of Electrical and Computer Systems EngineeringMonash University

In this paper, we demonstrate six types of metamaterial absorbers （MMAs） by measuring their absorptivities in an X-band （8 12 GHz） rectangular waveguide. Some of the MMAs have been demonstrated previously by using the free space measurement method, and the others are proposed firstly in this paper. The measured results show that all of the six MMAs exhibit high absorptivities above 98%, which have similar absorbing characteristics to those measured in the free space. The numerically obtained surface current densities for each MMA show that the absorbing mechanism is the same as that under the free space conditions. Such a demonstration method is superior to the conventional free space measurement method due to the small-scale test samples required, the simple measure device, and its low cost. Most importantly, the proposed method opens a way to enable MMAs to be used in microwave applications such as matched terminations.

关键词： metamaterial absorber electric resonator rectangular waveguide

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Laplacian coordinates-based motion transition for data-driven motion synthesis

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IET Image Processing 2012年第9期6卷 1331-1337页

作者： Yi, P. Zhang, Q. Wei, X. School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

As a fundamental technique in data-driven (or example-based) methods, motion blending has been employed to produce new motion clip from two or more clips or introduced as a medium to improve the final result of other method, for example, motion graphs. As methods of motion blending always require the system or users to classify the motion samples, it is difficult to accomplish motion blending automatically and to preserve local details, such as angular accelerations of joints of original motions. In this study, the authors developed a framework based on Laplacian coordinates to produce transitions between two motion clips, emphasising on preserving local details, without any need of motion classification. At first, multidimensional Laplacian coordinates are introduced to present local details of joints' angle. Then an error function is deduced to measure how much result motions differ from original ones in local details. By minimising such error function, new motions can then finally generated, which can preserve local details of input motion clips as much as possible. The following experiments show the effectiveness of the authors' framework. © The Institution of engineering and Technology 2012.

关键词： Laplace transforms

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An Iterative Two-Grid Method of A Finite Element PML Approximation for the Two Dimensional Maxwell Problem

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Advances in Applied Mathematics and Mechanics 2012年第2期4卷 175-189页

作者： Chunmei Liu Shi Shu Yunqing Huang Liuqiang Zhong Junxian Wang Hunan Key Laboratory for Computation&Simulation in Science and Engineering and Key Laboratory of Intelligent Computing&Information Processing of Ministry of Education Xiangtan UniversityHunan 411105China School of Mathematical Sciences South China Normal UniversityGuangzhou 510631China

In this paper,we propose an iterative two-grid method for the edge finite element discretizations(a saddle-point system)of Perfectly Matched Layer(PML)equations to the Maxwell scattering problem in two ***,we use a fine space to solve a discrete saddle-point system of H(grad)variational problems,denoted by auxiliary system ***,we use a coarse space to solve the original saddle-point ***,we use a fine space again to solve a discrete H(curl)-elliptic variational problems,denoted by auxiliary system ***,we develop a regularization diagonal block preconditioner for auxiliary system 1 and use H-X preconditioner for auxiliary system *** we essentially transform the original problem in a fine space to a corresponding(but much smaller)problem on a coarse space,due to the fact that the above two preconditioners are efficient and *** with some existing iterative methods for solving saddle-point systems,such as PMinres,numerical experiments show the competitive performance of our iterative two-grid method.

关键词： Maxwell scattering edge finite element PML iterative two-grid method

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Recent advances on apposition compound eye cameras

Recent advances on apposition compound eye cameras

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CLEO: Applications and Technology, CLEO_AT 2013

作者： Song, Y.M. Xie, Y. Malyarchuk, V. Xiao, J. Jung, I. Choi, K.-J. Liu, Z. Park, H. Lu, C. Kim, R.-H. Li, R. Crozier, K.B. Huang, Y. Rogers, J.A. Department of Materials Science and Engineering Beckman Institute for Advanced Science and Technology Frederick Seitz Materials Research Laboratory and University of Illinois at Urbana-Champaign Urbana IL 61801 United States Department of Mechanical Engineering University of Colorado at Boulder Boulder CO 80309 United States Department of Mechanical Engineering Kyung Hee University Yongin-si Gyeonggi-do 446-701 Korea Republic of Department of Chemistry University of Illinois at Urbana-Champaign Urbana IL 61801 United States Institute of High Performance Computing A star 1 Fusionopolis Way #16-16 Connexis 138632 Singapore School of Engineering and Applied Sciences Harvard University Cambridge MA 02138 United States Department of Civil Engineering and Soft Matter Research Center Zhejiang University Hangzhou 310058 China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian 116024 China Department of Mechanical Engineering Northwestern University Evanston IL 60208 United States

This work presents digital cameras that resemble, both structurally and functionally, apposition-type compound eyes of daylight insect. Hemispherical imagers with 180 artificial ommatidia yield 160 degree field of vie... 详细信息

ISBN: (纸本)9781557529725

关键词： Fiber optics

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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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CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing

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Protein & Cell 2012年第2期3卷 148-152页

作者： Guoguang Zhao Dechao Bu Changning Liu Jing Li Jian Yang Zhiyong Liu Yi Zhao Runsheng Chen Bioinformatics Research Group Key Laboratory of Intelligent Information ProcessingAdvanced Computing Research LaboratoryInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Bioinformatics Laboratory and National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China State Key Laboratory for Molecular Virology and Genetic Engineering National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 100176China Graduate School of the Chinese Academy of Sciences Beijing 100190China

Estimating taxonomic content constitutes a key problem in metagenomic sequencing data ***,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available ***,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data *** show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin *** comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat *** can be run on one multiprocessor node or a *** is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following ***,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.

关键词： CloudLCA metagenome analysis cloud computing

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CloudRank-D： benchmarking and ranking cloud computing systems for data processing applications

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Frontiers of Computer Science 2012年第4期6卷 347-362页

作者： Chunjie LUO Jianfeng ZHAN Zhen JIA Lei WANG Gang LU Lixin ZHANG Cheng-Zhong XU Ninghui SUN State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100019China Department of Electrical and Computer Engineering Wayne State UniversityDetroitM148202USA Shenzhenlnstitute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China

With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluating cloud performance on the whole system level. To the best of our knowledge, this paper proposes the first benchmark suite CloudRank-D to benchmark and rank cloud computing sys- tems that are shared for running big data applications. We an- alyze the limitations of previous metrics, e.g., floating point operations, for evaluating a cloud computing system, and propose two simple metrics： data processed per second and data processed per Joule as two complementary metrics for evaluating cloud computing systems. We detail the design of CloudRank-D that considers representative applications, di- versity of data characteristics, and dynamic behaviors of both applications and system software platforms. Through experi- ments, we demonstrate the advantages of our proposed met- tics. In several case studies, we evaluate two small-scale de- ployments of cloud computing systems using CloudRank-D.

关键词： data center systems clouds big data applica- tions benchmarks evaluation metrics

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