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2012 Third International Conference on Theoretical and Mathematical Foundations of computer Science(ICTMF 2012)

作者： Zining Cao Department of Computer Science and Technology Nanjing University of Aero.& Astro. Provincial Key Laboratory for Computer Information Processing Technology Soochow University

In this short paper,we show the equivalence between weak context bisimulation and strong bisimulation for the linear *** as a corollary,we get a complete proof system of weak context bisimulation over the linear HOcore.

关键词： Process Calculi,Bisimulation,Proof System,Higher Order pi Calculus

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A parallel ant colonies approach to de novo prediction of protein backbone in CASP8/9

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Science China(information Sciences) 2013年第10期56卷 226-238页

作者： LV Qiang WU HongJie WU JinZhen HUANG Xu LUO XiaoHu QIAN PeiDe School of Computer Science and Technology Soochow University Jiangsu Provincial Key Lab for Information Processing Technologies School of Electronic and Information Engineering Suzhou University of Science and Technology

Predicting the three-dimensional structure of proteins from amino acid sequences with only a few remote homologs,or de novo prediction,remains a major challenge in computational *** modeling of the protein backbone represents the initial phase of a protein structure prediction *** a parallel ant colony optimization based on sharing one pheromone matrix,this report proposes a parallel approach to predict the structure of a protein *** parallel approach combines various sources of energy functions and generates protein backbones with the lowest energies jointly determined by the various energy *** free modeling targets in CASP8/9 are used to evaluate the performance of the *** 13 targets in CASP8,two out of the predicted model1s selected by our approach are the best of the published CASP8 results,and seven out of the model1s are ranked in the top *** 29 targets in CASP9,20 out of the best models from our predictions are ranked in the top 10,and 11 out of the model1s are ranked in the top 10.

关键词： protein backbone prediction parallel ant colony optimization

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Application and Study on Sentiment-oriented Analysis on Social Semantic Network

Application and Study on Sentiment-oriented Analysis on Soci...

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2013 International Conference on Advanced computer Science and Electronics information(ICACSEI 2013)

作者： Dan Zhang Dongsheng Wang Haiping Huang College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Department of Computer and Information Science Korea University Seoul College of Computer & Information Science Nanjing University of Posts and Telecommunications Jiangsu Computer Information Processing Technology Key Laboratory Suzhou University

With the increasing growth of users and exponential propagation of messages, Social Network Services such as Twitter, Facebook can be used to analyze social trend, people's interests and personal-favor. Recently, the Social Network Analysis based on Semantic Web technology tends to be a hot study. In this paper, we propose a sentiment-oriented method that takes advantage of emotion ontology to reason out Twitter users' basic emotions and retrieve YAGO ontology to explain associative topics. We implement a prototype system that visualizes the analysis result, which is human- readable as well as machine-understandable.

关键词： Semantic Web technology, Twitter Mining, Social Network Analysis, emotion analysis, Social Semantic Network

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A new dynamic probabilistic Particle Swarm Optimization with dynamic random population topology

A new dynamic probabilistic Particle Swarm Optimization with...

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Congress on Evolutionary Computation

作者： Qingjian Ni Cen Cao Xushan Yin College of Software Engineering Southeast University Nanjing China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China School of Computer Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781479914869

Population topologies of Particle Swarm Optimization algorithm (PSO) have direct impacts on the information sharing amony particles during the evolution, and will influence the PSO algorithms' performance obviously. The canonical PSO algorithms usually use static population topologies, and the majority are the classic population topologies (such as fully connected topology and ring topology). In this paper, we present the strategies of dynamic random topology based on the random generation of population topologies. The basic idea is as follows: various random topologies are used at different stages of evolution in the population, and the solving performance of PSO algorithms is enhanced by improving the information exchange of population in different evolutionary stages. This provides a new way of thinking for the improvement of the PSO algorithm. Experimental results on a relatively new variant of dynamic probabilistic particle swarm optimization show that our strategies can achieve better performance compared with traditional static population topologies. Experimental data are analyzed and discussed in the paper, and the useful conclusions will provide a basis for further research.

关键词： Topology Sociology Statistics Heuristic algorithms Equations Mathematical model Particle swarm optimization

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Comparison of Particle Swarm Optimization algorithms in Wireless Sensor Network node localization

Comparison of Particle Swarm Optimization algorithms in Wire...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Cen Cao Qingjian Ni Xushan Yin School of Computer Science and Engineering Southeast University Nanjing China College of Software Engineering Southeast University Nanjing China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China

The node localization in Wireless Sensor Network (WSN) presently plays an important role in the field of applications. Particle Swarm Optimization (PSO) algorithm is a typical swarm intelligence method. Researchers propose many PSO variants and try to apply PSO algorithm to the related problems in WSN. This paper focuses on the WSN node localization using PSO algorithm. This paper conducts the experiment simulation, comparison and evaluation work in the node localization using PSO algorithm. The performance of different PSO variants with different population topologies is analyzed. Experiment simulations show that WSN node localization using PSO algorithm can get good performance in ring topology and square topology. In particular, the two newly proposed PSO variants (GDPSO and LDPSO) have good performance on this problem. This paper proposes some useful conclusions, which will provide a valuable reference to WSN engineering field.

关键词： Topology Wireless sensor networks Sociology Statistics Heuristic algorithms Particle swarm optimization Standards

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Detecting genuine communities from large-scale social networks: A pattern-based method

Detecting genuine communities from large-scale social networ...

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作者： Wu, Zhiang Cao, Jie Wu, Junjie Wang, Youquan Liu, Chunyang Jiangsu Provincial Key Laboratory of E-Business Nanjing University of Finance and Economics Nanjing210003 China College of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Department of Information Systems School of Economics and Management Beihang 100191 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China

Community detection is a long-standing yet very difficult task in social network analysis. It becomes more challenging as many online social networking sites are evolving into super-large scales. Numerous methods have been proposed for community detection from massive networks, but how to reconcile the partitioning efficiency and the community quality remains an open problem. In this paper, we attempt to address this challenge by introducing a COSine-pattern-based COMmunity extraction framework: COSCOM. The COSCOM adopts an extracting view of community detection. It first extracts the so-called asymptotically equivalent structures (AESs) from networks, from which the nodes are further partitioned into crisp communities using any of the existing methods. Specifically, we prove that an AES is a very tight group of nodes, and is actually a cosine pattern defined by the extended cosine similarity. A novel cosine-pattern mining algorithm based on the ordered anti-monotone of cosine similarity is thus proposed for the efficient extraction of AESs. Experiments on various real-world social networks demonstrate the advantage of the extracting view of community detection. In particular, COSCOM shows merits in detecting genuine communities by either internal or external validity. © The British computer Society 2013. All rights reserved.

关键词： Extraction

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Robust bilinear matrix recovery by Tensor Low-Rank Representation

Robust bilinear matrix recovery by Tensor Low-Rank Represent...

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International Joint Conference on Neural Networks (IJCNN)

作者： Zhao Zhang Shuicheng Yan Mingbo Zhao Fan-Zhang Li Provincial Key Laboratory for Computer Information Processing Technology Soochow University Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Electronic Engineering City University of Hong Kong Kowloon Hong Kong SAR

ISBN: (纸本)9781479914821

For low-rank recovery and error correction, Low-Rank Representation (LRR) row-reconstructs given data matrix X by seeking a low-rank representation, while Inductive Robust Principal Component Analysis (IRPCA) aims to calculate a low-rank projection to column-reconstruct X. But either column or row information of Xis lost by LRR and IRPCA. In addition, the matrix X itself is chosen as the dictionary by LRR, but (grossly) corrupted entries may greatly depress its performance. To solve these issues, we propose a simultaneous low-rank representation and dictionary learning framework termed Tensor LRR (TLRR) for robust bilinear recovery. TLRR reconstructs given matrix X along both row and column directions by computing a pair of low-rank matrices alternately from a nuclear norm minimization problem for constructing a low-rank tensor subspace. As a result, TLRR in the optimizations can be regarded as enhanced IRPCA with noises removed by low-rank representation, and can also be considered as enhanced LRR with a clean informative dictionary using a low-rank projection. The comparison with other criteria shows that TLRR exhibits certain advantages, for instance strong generalization power and robustness enhancement to the missing values. Simulations verified the validity of TLRR for recovery.

关键词： Dictionaries Robustness Noise Face Error correction Tensile stress Image reconstruction

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The system design of a node of P2P networks for intrusion detection

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Journal of Networks 2013年第8期8卷 1920-1927页

作者： Ding, Lei Yu, Fei Yang, Zhenghua Yue, Guangxue School of Information Science and Engineering Jishou University Jishou 416000 China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow 215006 China School of Mathematic and Computer Jiaxin University Jiaxin 314001 China

To improve the measuring accuracy of intrusion detection, a system design of a node for intrusion detection is proposed in this paper. First, the technology that applies the traditional intrusion detection method, such as anomaly detection and misuse detection, into P2P networks is presented. Next, to build the trust relationship among the nodes, and realize the cooperation mechanism of data detection, collection and response among the nodes of P2P networks, the corresponding solving plans, such as topological structure, trust model, information share and information fusion, are proposed in this paper. Then the concept of network telescope is presented to broaden the field of vision of malicious attacks and abnormal network packets in the propagation path. Finally, a system design of a node for intrusion detection using the honeypot technology is proposed in this paper. © 2013 ACADEMY PUBLISHER.

关键词： Intrusion detection

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Coverage Enhancement Strategy Based on Novel Perception and Co-evolution for Multimedia Sensor Networks

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电子学报(英文版) 2013年第1期22卷 135-140页

作者： XIAO Fu WANG Jing SUN Lijuan WANG Ruchuan GUO Jian College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing 210003 China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 China

Coverage enhancement is one of the hot research topics in wireless multimedia sensor net- works. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is proposed in multimedia sensor networks on the basis of the model whose pitch angle and deviation angle can be adjusted. Based on the proposed elliptical cone sensing model, we can derive the coverage area of the node and calculate the optimal pitch angle according the information of monitoring area and the nodes, and then the deviation angle is optimized based on co-evolution al- gorithm, which eliminate the overlapped and blind sensing area effectively. A set of simulations demonstrate the ef- fectiveness of our algorithm in coverage ratio.

关键词：无线多媒体传感器网络网络覆盖协同进化感知增强算法网络工程测量模型

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Survey of DCA for abnormal detection

Journal of Software

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Journal of Software 2013年第8期8卷 2087-2094页

作者： Ding, Lei Yu, Fei Yang, Zhenghua School of Information Science and Engineering Jishou University Jishou 416000 China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow 215006 China School of Information Science and Engineering Jishou University Jishou 416000 China

As a latest immune algorithm, dendritic cell algorithm (DCA) has been successfully applied into the abnormal detection. First, this paper reviewed the research progress of DCA from the following aspects: signal extraction technology, DCA signal processing technology, the decision method for load anomaly judgment, and the application research of DCA. Next, the corresponding solving thoughts for the main problems existing in the DCA were proposed in this paper. Finally, the future research trends of DCA were presented in this paper. © 2013 ACADEMY PUBLISHER.

关键词： Signal processing

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