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2014 International Conference on Communication Technology and Application(CTA2014)

作者： X.Y.Zhu L.Wang Department of Computer Science Hengyang Normal University College of Information Engineering Xiangtan University Key Laboratory of Intelligent Computing & Information Processing(Xiangtan University) Ministry of Education

ISBN: (纸本)9781845649302

In this paper, we propose a novel queue-based privacy-preserving data aggregation scheme for additive aggregation function. In the scheme, sensor nodes are divided into clusters in a distributed way first, and then, in each cluster, cluster members will form a queue and adopt a new queue-based privacy-preserving scheme to send data for aggregation upon the cluster head's request. We evaluate our scheme in terms of overheads, capacity of privacy-preservation, and data aggregation accuracy. The results show that our scheme is efficient and reasonable.

关键词： privacy preservation data aggregation wireless sensor network

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Recognition algorithm for plant leaves based on adaptive supervised locally linear embedding

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International Journal of Agricultural and Biological Engineering 2013年第3期6卷 52-57页

作者： Yan Qing Liang Dong Zhang Dongyan Wang Xiu Key Laboratory of Intelligent Computing&Signal Processing Ministry of EducationAnhui UniversityHefei 230039China Beijing Research Center for Information Technology in Agriculture Beijing 100097China

Locally linear embedding(LLE)algorithm has a distinct deficiency in practical *** requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented based on supervised LLE in this article.A similarity measure is formed by utilizing the Fisher projection distance,and then it is used as a threshold to select *** samples will produce different k adaptively according to the density of the data *** method is applied to classify plant *** experimental results show that the average classification rate of this new method is up to 92.4%,which is much better than the results from the traditional LLE and supervised LLE.

关键词： supervised locally linear embedding manifold learning Fisher projection adaptive neighbors leaf recognition Precision Agriculture

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Spectral clustering based on the edge betweenness dissimilarity matrix for community detection

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Journal of Information and Computational Science 2014年第11期11卷 3929-3939页

作者： Pei, Tingrui Cao, Yuxin Li, Zhetao Choi, Young-June College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

As an important global geometric quantity, edge betweennesses can reflect the impact of corresponding edges in the entire network, which have a very strong practical significance. However, edge betweenness ignores the relationship between the vertices which connected indirectly with the edge. This paper first puts forward a dissimilarity matrix based on a novel edge betweenness, and applies it to a spectral clustering algorithm and finally, in order to detect the community structure in complex networks with this improved algorithm, we use a correction step which is based on the gravitation force of the community. This algorithm has been tested on computer-generated networks and typical real world networks. Compared to GN, PBD, GK and DA, the proposed algorithm possesses an apparent advantage. ©2014 Binary Information Press

关键词： Complex networks

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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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Survey of community structure segmentation in complex networks

Journal of Software

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Journal of Software 2014年第1期9卷 89-93页

作者： Pei, Tingrui Zhang, Hongzhi Li, Zhetao Choi, Youngjune College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

Community structure analysis is a hot research spot in social networks and complex networks. In order to summarize recent research progress, this paper reviews the background, the motivation, the advantages and disadvantages of existing works related to community structure discovering. A comprehensive outline was obtained by analysis of different clustering algorithms. © 2014 ACADEMY PUBLISHER.

关键词： Complex networks

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Non-fragile Observer Design for Fractional-order One-sided Lipschitz Nonlinear Systems

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International Journal of Automation and computing 2013年第4期10卷 296-302页

作者： Yong-Hong Lan Wen-Jie Li Yan Zhou Yi-Ping Luo School of Information Engineering Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Institute of Intelligent Control Hunan Institute of Engineering

This paper is concerned with the problem of the full-order observer design for a class of fractional-order Lipschitz nonlinear systems. By introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach, the sufficient condition for asymptotic stability of the full-order observer error dynamic system is presented. The stability condition is obtained in terms of LMI, which is less conservative than the existing one. A numerical example demonstrates the validity of this approach.

关键词： Fractional-order nonlinear system observer design indirect Lyapunov approach linear matrix inequality （LMI）.

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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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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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Numerical methods for fractional variational problems depending on indefinite integrals

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Journal of Computational and Nonlinear Dynamics 2013年第2期8卷 021018页

作者： Wang, Dongling Xiao, Aiguo 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 fractional variational integrators for fractional variational problems depending on indefinite integrals in terms of the Caputo derivative are developed. The corresponding fractional discrete Euler-Lagrange equations are derived. Some fractional variational integrators are presented based on the Grünwald-Letnikov formula. The fractional variational errors are discussed. Some numerical examples are given to illustrate these results. Copyright © 2013 by ASME.

关键词： Numerical methods

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