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

作者： Jing Zhou Gregor V. Bochmann Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Electrical Engineering and Computer Science University of Ottawa Ontario Canada

ISBN: (纸本)9781479913725

Sharing the Semantic Web data in proprietary datasets in which data is encoded in RDF triples in a decentralized environment calls for efficient support from distributed computing technologies. The highly dynamic ad-hoc settings that would be pervasive for Semantic Web data sharing among personal users in the future, however, pose even more demanding challenges for the enabling technologies. We extend previous work on a hybrid P2P architecture for an ad-hoc Semantic Web data sharing system which better models the data sharing scenario by allowing data to be maintained by its own providers and exhibits satisfactory scalability owing to the adoption of a two-level distributed index and hashing techniques. Additionally, we propose efficient distributed processing of SPARQL queries in such a context and explore optimization techniques that build upon distributed query processing for database systems and relational algebra optimization. We anticipate that our work will become an indispensable, complementary approach to making the Semantic Web a reality by delivering efficient data sharing and reusing in an ad-hoc environment.

关键词： Peer-to-peer computing Resource description framework Indexes Query processing Distributed databases Optimization

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Two-level default theories

Two-level default theories

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2013 International Conference on Artificial Intelligence, ICAI 2013

作者： Zang, Liangjun Cao, Cungen Sui, Yuefei Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Hai Dian Distinct Beijing 100190 China University of Chinese Academy of Sciences No.19 Yu Quan Road Shi Jing Shan Distinct Beijing 100049 China

ISBN: (纸本)1601322488

Default Logic employs assumption-based default rules to draw plausible consequences in face of incomplete information. In ontology representation, there are two kinds of relations between concepts: subsumption relation and default subsumption relation. Subsumption relation is transitive, whereas default subsumption relation is transitive by default. Both default transitivity of default subsumption and default inheritance of default property should be represented as defaults about defaults, i.e. two-level defaults. None of existing default logics can represent two-level defaults. In this paper, we propose two-level default theories which augment default theories with two-level defaults. A two-level default theory can be divided into two levels and its extensions can be generated by two steps. We prove that normal two-level default theories cannot reduce to normal default theories. Specifically, there is a normal two-level default theory such that there exists no normal default theory such that they share the same set of extensions.

关键词： Formal logic

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pNovo+: De Novo Peptide Sequencing and Assembly Using Complementary HCD and ETD Tandem Mass Spectra

pNovo+: De Novo Peptide Sequencing and Assembly Using Comple...

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第八届中国蛋白质组学大会

作者： Hao Chi Haifeng Chen Kun He Long Wu Bing Yang Rui-Xiang Sun Jianyun Liu Wen-Feng Zeng Chun-Qing Song Si-Min He Meng-Qiu Dong Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China National Institute of Biological SciencesBeijingBeijing 102206China Laboratory of Intelligent Recognition and Image ProcessingBeijing Key Laboratory of Digital MediaBeihang UniversityBeijing100191China

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Superconvergence and asymptotic expansion for semidiscrete bilinear finite volume element approximation of the parabolic problem

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Computers & Mathematics with Applications 2013年第1期66卷 91-104页

作者： Cunyun Nie Shi Shu Haiyuan Yu Yuyue Yang Department of Mathematics and Physics Hunan Institution of Engineering Hunan 411104 China Hunan Key Laboratory for Computation & Simulation in Science and Engineering Xiangtan University Hunan 411105 China Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Hunan 411105 China

We first derive the asymptotic expansion of the bilinear finite volume element for the linear parabolic problem by employing the energy-embedded method on uniform grids, and then obtain a high accuracy combination pointwise formula of the derivatives for the finite volume element approximation based on the above asymptotic expansion. Furthermore, we prove that the approximate derivatives have the convergence rate of order two. Numerical experiments confirm the theoretical results.

关键词： Linear parabolic problem Bilinear finite volume element Error asymptotic expansion Superconvergence

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The improved upper solution bounds of the continuous coupled algebraic Riccati matrix equation

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International Journal of Control, Automation and Systems 2013年第4期11卷 852-858页

作者： Juan Zhang Jianzhou Liu Department of Mathematics and Computational Science Xiangtan University Xiangtan Hunan P. R. China Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Hunan China Hunan Key Laboratory for Computation & Simulation in Science & Engineering Xiangtan University Hunan China

In this paper, combining some special eigenvalue inequalities of matrix’s product and sum with the equivalent form of the continuous coupled algebraic Riccati equation (CCARE), we construct linear inequalities. Then, in terms of the properties of M-matrix and its inverse matrix, through solving the derived linear inequalities, we offer new upper matrix bounds for the solution of the CCARE, which improve some of the recent results. Finally, we present a corresponding numerical example to show the effectiveness of the given results.

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INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE ALIGNMENT

INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE AL...

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IEEE International Conference on Image processing

作者： Deming Zhai Hong Chang Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China 150001 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China 100080

ISBN: (纸本)9781479923427

Canonical correlation analysis (CCA) based methods achieve great success for pose alignment. However, CCA has limitations as a linear and global algorithm. Although some variants have been proposed to overcome the limitations, neither of them achieves locality and nonlinearity at the same time. In this paper, we propose a novel algorithm called Instance-Specific Canonical Correlation Analysis (ISCCA), which approximates the nonlinear data by computing the instance specific projections along the smooth curve of the manifold. Based on the framework of least squares regression, CCA is extended to the instance-specific case which obtains a set of locally-linear smooth but globally-nonlinear transformations. The optimization problem is proved to be convex and could be solved efficiently by alternating optimization. And the globally optimal solutions could be achieved with theoretical guarantee. Experimental results for pose alignment demonstrate the effectiveness of our proposed method.

关键词： proposed alignment transofrmations Alignment Posing optimal solution multivariate analysis nonlinearity Manifolds Convexity

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Moving vehicle detection and tracking in traffic images based on horizontal edges

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第11期11卷 6477-6483页

作者： Zhu, Hongjin Fan, Honghui Guo, Shuqiang School of Computer Engineering Jiangsu University of Technology Changzhou 213001 Jiangsu China Key Laboratory of Cloud Computing Intelligent Information Processing of Changzhou City China School of Information Engineering Northeast Dianli University Jilin 132012 Jilin China

This paper presents a moving vehicle detection and tracking system, which comprising of Horizontal Edges method and Local Auto Correlation. Horizontal Edges characteristic can be strengthened and the influence of weather condition is reduced by using Local Auto Correlation, so the detection rate of extracting and tracking moving vehicles with horizontal edge can be raised. Local Auto Correlation images are generated for vehicle detection and based on Horizontal Edges method. The distance of the gravity center of Horizontal Edges is used to track vehicles in traffic video. We verify the system using a variety of weather (in fog, car shadow existence, morning and evening) traffic video. Experimental results have shown that the high detection rate of moving vehicles be obtained by using the proposed method. © 2013 Universitas Ahmad Dahlan.

关键词： Tracking (position)

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Spectral Distance Distributions for Non-rigid Objects

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Computer Aided Drafting,Design and Manufacturing 2013年第2期23卷 17-24页

作者： CAO Wei-guo Li Hai-yang LI Shi-rui LIU Yu-jie LI Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China School of Computer Science and Communication Engineering China University of Petroleum Qingdao 266555 China.

Non-rigid shape deformation without tearing or stretching is called isometry. There are many difficulties to research non-rigid shape in Euclidean space. Therefore, non-rigid shapes are firstly embedded into a none-Euclidean space. Spectral space is chosen in this paper. Then three descriptors are proposed based on three spectral distances. The existence of zero-eigenvalue has negative effects on computation of spectral distance, Therefore the spectral distance should be computed from the first non-zcro-eigenvalue. Experiments show that spectral distance distributions are very effective to describe the non-rigid shapes.

关键词： non-rigid shape analysis pattern recognization isometry Laplace-Beltrami operator spectrum

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CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MULTI-ANGULAR HYPERSPECTRAL MEASUREMENTS

CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MUL...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jinling Zhao Lin Yuan Linsheng Huang Dongyan Zhang Jingcheng Zhang Xiaohe Gu Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9781479911127

This study aims at characterizing wheat canopies caused by powdery mildew (Blumeria graminis f. sp. tritici) with multi-angular hyperspectral data. The filling stage (23 May, 2012) was chosen to achieve such a goal, considering that the disease can show distinctive symptoms during the months of May and June. A total of 37 sample plots were selected including 32 normal canopies and 5 diseased canopies with varied severity. To minimizing the soil background influences, multi-angular hyperspectral data were acquired at different view angles (0°, 45° and 90°). The results showed that the proportion of wheat vegetation and soil changed greatly and the hyperspectral reflectance values correspondingly changed. Consequently, the reflectance at different viewing angles showed great differences, but the curves had the same change trends. The results showed that, to accurately identify the spectral differences caused by powdery mildew, the optimal angle or a combination of several angles must be firstly found from multi-angular hyperspectral measurements.

关键词： Hyperspectral remote sensing Multi-angular spectral measurement Powdery mildew Sensitive wave bands Winter wheat powdery mildew winter wheat hyperspectral remote sensing multiangular Angle Wheat look angles (electronics) Canopies Winter

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Fusion of multi-spectral image and panchromatic image based on support vector regression

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Journal of Beijing Institute of Technology 2012年第2期21卷 269-277页

作者：胡根生梁栋 Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi- spectral image and the panchromatic image are fused based on regions at different levels. Our experi- ments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image.

关键词： image processing image fusion support vector regression super-resolution

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