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International Conference on Natural Computation

作者： Guo, Yu Tang Luo, Bin Department of Computer Science and Technology Hefei Normal University Hefei China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (纸本)9781424459612

In order to improve the accuracy of the image annotation, an automatic image annotation method based on mutual K-nearest neighbor graph(MKNN) is proposed. The peoposed algorithm describes the relationship between low-level features, annotation words and image by a mutual K-nearest neighbor graph. Semantic information is extracted by exploitingt the mutual relationship of two nodes in the mutual K-nearest neighbor graph. Inverse document frequency (IDF) is introduced to adjust the weights of edges between the image node and its annotation word's node, which overcomes the deviation caused by high-frequency words. Experimental results in Corel image dataset show that the proposed algorithm improves effectively the image annotation performance. ©2010 IEEE.

关键词： Image annotation

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Aggregation of interval numbers in group decision making

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ICIC Express Letters 2011年第4 A期5卷 1057-1062页

作者： Deng, Yong Wu, Jiyi Sun, Xiaohong Xu, Peida Zhang, Yajuan College of Computer and Information Sciences Southwest University Tiansheng Road Beibei District Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University No. 16 Xuelin Street Xiasha Higher Education Zone Hanzhou 310036 China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan University Xiangtan 411105 China College of Food Science and Technology Shanghai Ocean University Hu Cheng Loop-road Lingang New City Shanghai 201306 China School of Electronics and Information Technology Shanghai Jiao Tong University Dongchuan Rd. Shanghai 200240 China

A group of decision-makers may differ in their choice of alternatives while taking a decision. So, in any decision-making problem concerning decisions made by a group, the question arises how best we can aggregate individual choices into a general consensus choice. Due to the inherent uncertain property of the problems in the ambiguous decision domain, the decision makers may use interval numbers to represent their opinions in some situations. In this paper, a simple method is proposed to aggregate interval numbers. Some desirable properties of this method are also discussed. Finally, a numerical example is given to show the use of the proposed method. ICIC International © 2011.

关键词： Aggregates

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, lab.led data are very limited while unlab.led data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate lab.led data. To take advantage of unlab.led data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD. ©2010 IEEE.

关键词： Discriminant analysis

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An improved target immunization strategy

An improved target immunization strategy

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Zhang, Yanping Fang, Baoping Deng, Xiaochao He, Fugui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Key Laboratory of Physical Electronics of Anhui University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9780769542867

Strategies for network immunization have been drawing wide interest in the area of complex networks during the past decade. The target strategy, in which degree values are used to determine vaccinating priority, has been supposed to be the most effective strategy. In many networks where large numbers of nodes exists with same degree values, the target strategy will face a problem of deciding the priorities of nodes with equal degree. This paper discussed a refined method to evaluate priority using risk-value. With risk-values, an improved target immunization strategy is proposed. Simulations under SIS model using real network dataset have proved a better efficiency for the improved strategy. © 2010 IEEE.

关键词： Complex networks

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A more effective definition of evidential conflict combined with evidential distance

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Journal of Information and Computational Science 2011年第9期8卷 1729-1734页

作者： Chen, Yuxin Wu, Jiyi Cong, Jian Jie, Wenjing Deng, Yong School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 20024 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Hangzhou 310036 China College of Food Science and Technology Shanghai Ocean University 999 Hucheng Huan Road Shanghai 201306 China Key Subject Laboratory of National Defense for Radioactive Waste and Environment Security Southwest University of Science and Technology Mianyang 621010 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China College of Computer and Information Sciences Southwest University Chongqing 400715 China

Evidence theory is widely used in many application systems such as information fusion and decision making under uncertainty environment. However, the classical Dempster combination rule is not efficient to deal with highly conflicting evidences. One of the open issues is how to determine the conflict degree in conflict evidence management. In this paper, a new conflict coefficient is proposed to measure the conflict degree between bodies of evidence. It can overcome some drawbacks of the classical conflict coefficient. The numerical example shows the efficiency of our proposed method. Copyright © 2011 Binary Information Press.

关键词： Information fusion

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Optimal aggregation of interval numbers based on genetic algorithm in group decision

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Journal of Information and Computational Science 2011年第5期8卷 842-849页

作者： Kang, Bingyi Zhang, Yajuan Deng, Xinyang Wu, Jiyi Sun, Xiaohong Li, Ya Deng, Yong College of Computer and Information Sciences Southwest University Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Hangzhou 310036 China College of Food Science and Technology Shanghai Ocean University 999 Hucheng Huan Road Shanghai 201306 China Key Subject Laboratory of National Defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang 621010 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Electronics and Information Technology Shanghai Jiaotong University Shanghai 200240 China

A group of decision-makers may differ in their choice of alternatives while making a decision. As a result, how to aggregate opinions of different experts is still an open issue. Due to the uncertainty in the process of decision making, some mathematic tools such as fuzzy sets theory and evidence theory, are used to model uncertain information. In this paper, the experts' opinions are represented by interval numbers. A new optimal aggregation method to combine interval data is proposed based on genetic algorithm. The new method can deal with experts' opinions in an efficient manner. A numerical example on group decision making under uncertain environment is used to illustrate the efficiency of our proposed method. Copyright © 2011 Binary Information Press.

关键词： Genetic algorithms

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Application of AWE to scattering analysis of the double-negative medium

Application of AWE to scattering analysis of the double-nega...

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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

作者： Sun, Yu-Xin Chen, Ming-Sheng Wu, Xian-Liang Yang, Mei Wang, Hui Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China School of Information Science and Technology University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781424469062

The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band. ©2010 IEEE.

关键词： Method of moments

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SPEECH ENDPOINT DETECTION IN NOISY ENVIRONMENTS USING EMD AND TEAGER ENERGY OPERATOR

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Journal of Electronic Science and Technology 2010年第2期000卷 183-186页

作者： DE-XIANG ZHANG XIAO-PEI WU ZHAO Lü Key Lab.of Intelligent Computing and Signal Processing of Ministry of Education.Anhui University Hefei 230039China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Empirical mode decomposition endpoint detection noisy speech Teager energy operator

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A secure scheme for data statistics

A secure scheme for data statistics

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International Conference on E-Business and E-Government (ICEE)

作者： Huang, Hongsheng Zhong, Hong Shi, Runhua Key Laboratory of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei Anhui 230039 China School of Computer Science and Technology Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9780769539973

Secure Multi-party Computation (SMC) is a hot point concerning with information security and it is widely used in many fields, such as e-voting, e-auction and e-payment systems et al. This paper mainly discusses a special issue, data statistics, of SMC and its practical application background. Based on the oblivious transfer protocol and the homomorphic encryption scheme, a solution scheme is proposed. Furthermore, the security and the computational complexity of this scheme are as well analyzed. The results of analysis show that the proposed scheme is secure and efficient. © 2010 IEEE.

关键词： Cryptography

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Two protocols for computing the sub-polygon's areas divided by a line

Two protocols for computing the sub-polygon's areas divided ...

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International Conference on Advanced Computer Theory and Engineering

作者： Zhong, Hong Huang, Hongsheng Shi, Runhua Key Laboratory of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei Anhui 230039 China School of Computer Science and Technology Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9781424465408

Secure Multi-party Computation (SMC) plays an important role in information security under the circumstance of cooperation calculation, so SMC on privacy-preservation is of great interest. In this paper we discuss an issue which is a special SMC problem. Based on Scalar Product Protocol, Monte Carlo Method and Oblivious Transfer, we give two solutions to the problem about how to decide the areas. That is, a polygon is divided into two parts by a line: SI and S2. Furthermore, we analyze the security and computational complexity, as well as the comparison of these two protocols. The results of analysis show that the proposed protocols are secure and efficient. We believe the two protocols will be useful in other geometric and combinatorial problems. © 2010 IEEE.

关键词： Computational geometry

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