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第10届全国计算机支持的协同工作学术会议暨中国计算机学会协同计算专委年度工作会议

作者： Guangping Xu Huan Li Xing Guo Sheng Lin Qunfang Mao Hua Zhang Tianjin Key Lab. of Intelligence Computing and New Software Technology Tianjin University of TechnologyTianjinChina 300384

In cloud storage,various erasure coding techniques,particularly regenerating codes,not only need to ensure the multi-node fault tolerance,but also need to reduce bandwidth consumption during storage repair to cope with frequent failures of storage *** paper studies the optimization of replicated erasure codes in cloud storage by using a variant of balls-inbins *** network bandwidth is much valuable,such replicated coding scheme supplies the efficient fault repair by cooperation of parts of storage *** that a set of balls of n different colored are thrown into m distinguishable bins such that ball number of each color is the same and the number of balls in each bins is the *** that here the same color balls are also *** can we ensure the number of balls with distinct colors is at least c in any k bins(k ≤ m)with the minimum number of balls? Considering that balls correspond to coded packets and bins correspond to storage nodes,we present that the optimal colored bins in bins is equivalent to the optimization design of fractional repetition codes in cloud storage *** optimal repetition code can be described by a biregualr graph and then this problem deduced to the Zarankiewicz *** can optimize the storage capacity of an FR code with the required k fault-tolerance from the Ks,t-free structure of a biregular ***,constructions of the optimized codes by 2-desings are analyzed to tolerate the desired k fault-tolerance with c = n-1.

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newBalance: Efficient data space management and algorithmic optimization for cloud storage

NewBalance: Efficient data space management and algorithmic ...

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第10届全国计算机支持的协同工作学术会议暨中国计算机学会协同计算专委年度工作会议

作者： Guangping Xu Sheng Lin Xing Guo Kai Shi Hua Zhang Tianjin Key Lab. of Intelligence Computing and New Software Technology Tianjin University of TechnologyTianjinChina 300384

Fragmentation usually occurs when data space of original storage nodes has to be reallocated to new added storage nodes during the scale-out evolution of the large-scale storage *** greatly influences the performance of the large-scale storage *** this paper,we present an efficient space management framework,called newBalance,to reduce fragmentation with the minimum data movement while keeping the storage system load *** space management framework has two phases including the collection phase and the allocation *** the collection phase,we propose a novel algorithm,called the greedy bi-direction collector,which collects enough space for the new storage *** the allocation phase,we formally represent it as one variant of the bin packing problem and then utilize some bin packing heuristics including the first fitting and the best fitting to allocate collected intervals to new added storage *** experimental results show that the amount of intervals can be reduced by 20%~55%and our algorithmic optimization improves the data lookup performance by at least 10%and the scale-out performance by 2×~3×.

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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Novel synthesis method for image of materials texture

Novel synthesis method for image of materials texture

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2014 International Conference on Manufacturing technology and Electronics Applications, ICMTEA 2014

作者： Peng, Hong-Tao Zhang, De-Gan Song, Xiao-Dong Wang, Xiang Department of Computer CNPC Managers Training Institute Beijing China Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Ministry of Education China

ISBN: (纸本)9783038353287

Most patch-based texture synthesis algorithms using Markov Random Field for composite materials only considers color similarity between the corresponding pixels. The traditional algorithms are lack of adaptability, so the size of patches needs to be defined artificially in advance as the result of blurring of image texture features for composite materials. In order to improve above problems, a new patch-based sampling algorithm for synthesizing textures from an input sample image texture of composite materials is presented in this paper. By using patches of the sample texture as building blocks for image texture synthesis of composite materials, this algorithm makes high-quality texture synthesis for a wide variety of textures ranging regular to stochastic. The method is effective by our experimental results. © (2014) Trans Tech Publications, Switzerland.

关键词： Image texture

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A consistent pixel-wise blur measure for partially blurred images

A consistent pixel-wise blur measure for partially blurred i...

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作者： Fang, Xianyong Shen, Feng Guo, Yanwen Jacquemin, Christian Zhou, Jian Huang, Shanchun Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei230601 China State Key Lab. for Novel Software Technology Nanjing University Nanjing210023 China AMI LIMSI-CNRS Orsay91403 France

ISBN: (纸本)9781479957514

Despite numerous efforts on blur measurement of partially blurred images, there still lacks an effective blur measure that is both pixel-wise and locally sharp consistent. The paper proposes a novel method with two contributions to overcome this limitation: 1) A new pixel-based blur metric, Multi-resolution Singular Value (MSV), which leverages the average singular value of high frequency bands to measure the blur of each pixel, and 2) a locally continuous strategy, maximum-likelihood estimation (MLE) based refinement, that ensures local continuity by imposing the local sharp consistency on pixel blur in a local correcting process. Experimental results show that our method is effective to smoothly measure the partially blurred images without local discontinuity. © 2014 IEEE.

关键词： Pixels

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A GA-based approach for SQL-injection detection

A GA-based approach for SQL-injection detection

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2013 International Conference on Information Engineering, ICIE 2013

作者： Chen, Jianmin Yang, Lin Zhang, Honghao Liu, Yan College of Computer Science Beijing University of Technology Beijing China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China National Computer Virus Emergency Response Center Tianjin China

ISBN: (纸本)9781845648558

In order to deal with serious security threats of SQL injection to Web applications, this paper proposes a novel SQL-injection detection method based on genetic algorithm (GA). A unified description for characteristics of SQL-injection was issued by regular expression, and an optimized SQL-injection sequence motherboard was got through GA. We detected harmful levels of SQL-injection attacks using template matching and achieved optimized correction scheme of the algorithm by a large amount of data. © 2014 WIT Press.

关键词： Genetic algorithms

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A Novel Terms Semantic Query Model Based on Wikipedia

A Novel Terms Semantic Query Model Based on Wikipedia

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2014 11th Web Information System and Application Conference(第十一届全国web信息系统及其应用学术会议)

作者： Dexin Zhao Pengjie Liu Liangliang Qin Yukun Li Tianjin Key Lab of Intelligent Computing & Novel Software Technology Tianjin University of Technology Tianjin 300384China

ISBN: (纸本)9781479957286

Search engines have become the main way for people to get expected information, most of them are based on keyword ***, keyword search is based on computing the similarity of letters of the keywords, instead of semantic meaning, therefore the searching results often include irrelevant information to user *** paper aims to find a way on improving keyword search *** Wikipedia,which is the largest online encyclopedia, this paper explores the relations of terms through computing the semantic relatedness between words, and presents an algorithm called WLA in the light of link structure and text message in *** is more, we design a terms query platform through which users will be able to get all the meanings about the *** making a comparison with lexical database WordNet, it has demonstrated the feasibility on our methods.

关键词： Wikipedia text information link structure semantic computing

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Social sensing enhanced time estimation for bus service

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Concurrency and Computation: Practice and Experience 2015年第15期27卷

作者： Jin Liu Juan Li Xiaohui Cui Xiaoguang Niu Xiaoping Sun Jing Zhou State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEA s and road condition attributions PRCA s. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEA s of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： social sensing in-time bus service bus route arrival time estimation

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Joint Multiple Dictionary Learning for Tensor Sparse Coding

Joint Multiple Dictionary Learning for Tensor Sparse Coding

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International Joint Conference on Neural Networks

作者： Yifan Fu Junbin Gao Yanfeng Sun Xia Hong School of Computing and Mathematics Charles Sturt University Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology Beijing University of Technology School of Systems Engineering University of Reading

ISBN: (纸本)9781479914821

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form - a tensor - by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

关键词： Tensile stress Dictionaries Joints Vectors Correlation Databases Encoding

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