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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. Image R. 25(7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 27卷 57-57页

作者： Weizhi Xu Hui Yu Dianjie Lu Fenglong Song Da Wang Xiaochun Ye Songwei Pei Dongrui Fan Hongtao Xie Institute of Microelectronics Tsinghua University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Information Science and Engineering Shandong Normal University Jinan China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Institute of Information Engineering Chinese Academy of Sciences National Engineering Laboratory for Information Security Technologies Beijing China

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. 25 (7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 26卷 350-350页

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Laplacian normalization and random walk on heterogeneous networks for disease-gene prioritization

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Computational biology and chemistry 2015年 57卷 21-8页

作者： Zhi-Qin Zhao Guo-Sheng Han Zu-Guo Yu Jinyan Li Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China. Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia. Electronic address: yuzg1970@***. Advanced Analytics Institute & Centre for Health Technologies University of Technology Sydney Broadway NSW 2007 Australia. Electronic address: jinyan.li@uts.edu.au.

Random walk on heterogeneous networks is a recently emerging approach to effective disease gene prioritization. Laplacian normalization is a technique capable of normalizing the weight of edges in a network. We use this technique to normalize the gene matrix and the phenotype matrix before the construction of the heterogeneous network, and also use this idea to define the transition matrices of the heterogeneous network. Our method has remarkably better performance than the existing methods for recovering known gene-phenotype relationships. The Shannon information entropy of the distribution of the transition probabilities in our networks is found to be smaller than the networks constructed by the existing methods, implying that a higher number of top-ranked genes can be verified as disease genes. In fact, the most probable gene-phenotype relationships ranked within top 3 or top 5 in our gene lists can be confirmed by the OMIM database for many cases. Our algorithms have shown remarkably superior performance over the state-of-the-art algorithms for recovering gene-phenotype relationships. All Matlab codes can be available upon email request.

关键词： Disease genes and phenotypes Heterogeneous network Laplacian normalization Leave-one-out cross-validation Random walk with restart Shannon information entropy

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Informative gene selection using the Algebraic Connectivity Strength of Point and Scoring Criteria

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Chinese Science Bulletin 2013年第6期58卷 657-661页

作者： WANG Nian SU LiangLiang TANG Jun YE AiXia Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

This paper presents a novel method that integrates the Algebraic Connectivity Strength of Point(ACSP) and Scoring Criteria to identify genes associated with tumor ***,for each gene,the ACSP is used to identify reliable expression levels of the gene in all the *** informative genes are then selected using Scoring Criteria based on these reliable expression ***,the Support Vector Machine(SVM) classifier is used to classify the two datasets of gene expression *** results show that the informative genes selected by the proposed method have higher credibility than those selected by Scoring Criteria alone.

关键词：基因选择评分标准信息化强度连通代数基因表达谱支持向量机

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A high order composite scheme for the second order elliptic problem with nonlocal boundary and its fast algorithm

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Applied Mathematics and Computation 2014年 227卷 212-221页

作者： Cunyun Nie Shi Shu Haiyuan Yu Qianjiang An Department of Mathematics and Physics The Hunan Institution of Engineering Xiangtan City Hunan 411104 China Hunan Key Laboratory for Computation & Simulation in Science and Engineering Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Hunan 411105 China Department of Mathematics The Institute of Tongren Guizhou 554300 China

The elliptic problem with nonlocal boundary condition is widely applied in the field of science and engineering. Firstly, we construct a linear finite element scheme for the nonlocal boundary problem, and derive the optimal L 2 error estimate. Then, based on the quadratic finite element and the extrapolation linear finite element methods, we present a composite scheme, and prove that it is convergent order three. Furthermore, we design an upper triangular preconditioning algorithm for the linear finite element discrete system. Finally, numerical results not only validate that the new algorithm is efficient, but also show that the new scheme is convergent order three, furthermore order four on uniform grids.

关键词： The elliptic problem with nonlocal boundary condition The finite element method An upper triangular preconditioner Algebraic multigrid method

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Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions

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Physical Review E 2014年第3期89卷 032814-032814页

作者： Jin-Long Liu Zu-Guo Yu Vo Anh Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2−H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic

关键词： TOPOLOGICAL property FRACTAL analysis BROWNIAN motion CORRELATION (Statistics) RECURSIVE sequences (Mathematics) COMPUTER networks

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Many-Objective evolutionary algorithms for the characteristics of text in the email text categorization

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International Journal of Applied Mathematics and Statistics 2013年第14期44卷 357-364页

作者： Zou, Juan Zheng, Jinhua Deng, Cheng Hu, Weiping Information Engineering College of Xiangtan University Xiangtan Hunan China Key Laboratory of Intelligent Computing and Information Processing Xiangtan University Ministry of Education Xiangtan Hunan China

This paper use the characteristics of text in the email text categorization propose a method of feature word extraction based on many-objective evolutionary algorithms. This method fully considers the semantic characteristics between different feature words, by increasing the many-objective evolutionary algorithms to calculate the feature words, using the fuzzy theory to process the synonyms Compare the test results show that this method not only reduces the dimension of feature word, but also improves the classification accuracy and recall rate, thereby improves the overall performance of the classification system. And make the system reach a higher level of automation and strong portability. © 2013 by CESER Publications.

关键词： Extraction

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An improved generalized K-L transform and applications in image compression

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Journal of information and Computational Science 2013年第1期10卷 167-173页

作者： Shi, Yuexiang Tao, Zhiping Gong, Ping Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China School of Information Engineering Xiangtan University Xiangtan 411105 China

Though K-L transform is an optimum transform for image compression based on minimum mean-squared error, its matrix transform differentiates according to the images and the calculation is heavy and difficult. Some papers have proposed the transform based on the matrix K-L transform which was proved faster than K-L transform from tens to hundreds of times with the same level of peak signal-to-noise ratio. As the matrix K-L transform doesn't eliminate the inner correlations of transformed matrix row vectors and this thesis presents to reuse Matrix K-L Transform (MKLT) after the transformed matrix being transposed. As proved by experiments, this method works better at image compression and calculates faster than K-L transform tens to hundreds of times. © 2013 by Binary information Press.

关键词： Image compression

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Two-dimensional short-range microwave holography algorithm and convolutional gridding

Two-dimensional short-range microwave holography algorithm a...

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International Conference on Natural Computation (ICNC)

作者： Bao-qiang Lao Jun-yi Wang Jin-qing Wang Jie-lin Fu Tao An Hong-bing Qiu Key Laboratory of Cognitive Radio & Information Processing Ministry of Education Guilin University of Electronic Technology Guilin China school of Mathematics and Computing Science Xiangtan University Hunan China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781479951529

A new-style two-dimensional short-range microwave holography imaging technique is introduced to compensate the inadequateness of short-range millimeter-wave holography imaging. In this method, the scattered data collected includes not only back-scattered but also forward-scattered data, and the incident field obtained by simulation or measurement, can further improve the imaging quality and resolution. A simulation in FEKO about the algorithm is given to provide reference for practical applications. In this paper, a new technique has been proposed to reduce the alias by using convolution function gridding the microwave holographic data which are irregularly data. To choose a proper convolution function, the performance of alias rejection of different convolution functions has been analyzed, validate the spheroidal function is the most rejection alias convolution function. To evaluate the proposed technique, the convolution gridding used to interpolate the irregularly holographic data onto a rectangular gird is examined in detail, validate the convolution gridding can be reduced aliasing. The convolution grid algorithm will be used in the actual imaging system to process the irregular data.

关键词： Convolution Microwave imaging Holography Microwave communication

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Crank-Nicolson difference scheme for the coupled nonlinear Schrödinger equations with the Riesz space fractional derivative

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Journal of Computational Physics 2013年 242卷 670-681页

作者： Wang, Dongling Xiao, Aiguo Yang, Wei Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China

In this paper, the Crank-Nicolson (CN) difference scheme for the coupled nonlinear Schrödinger equations with the Riesz space fractional derivative is studied. The existence of this difference solution is proved by the Brouwer fixed point theorem. The stability and convergence of the CN scheme are discussed in the L2 norm. When the fractional order is two, all those results are in accord with the difference scheme developed for the classical non-fractional coupled nonlinear Schrödinger equations. Some numerical examples are also presented. © 2013 Elsevier Inc.

关键词： Nonlinear equations

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