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作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Chen, Jingrun Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

ISBN: (纸本)9783642051722

Automatic image segmentation remains a challenging problem in the fields of computer vision, image analysis and understanding. A lot of algorithms and technologies have been proposed and developed for image segmentation, among which the N-cut has been a promising method and active research area due to better quality. But the N-cut can't process medium and large image dataset online due to incredible memory and time complexity. Moreover, the N-cut algorithm can't utilize texture information since its basic unit of clustering algorithm is pixel. To overcome the drawback and improve the description power, the paper proposes a block-based N-cut algorithm for image segmentation, whose basic unit of clustering is image block instead of individual pixel. Block-based algorithm not only decreases the time and storage complexity, but also improves the discrimination power of visual feature vector. The experiments demonstrate that proposed algorithm outperform the original N-cut algorithm in efficiency. Experiments show that the proposed block-based N-cut algorithm is more suitable for online processing large-scale data. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Image segmentation

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A New Framework for IPv6 Crossing GPRS Network

A New Framework for IPv6 Crossing GPRS Network

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The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Shujing Li Siguo Chen Jian Wang Yanheng Liu College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012 China

ISBN: (纸本)9781424472352

In order to realize that IPv6 (Internet Protocol version 6) clients are able to visit remote IPv6 servers through GPRS (General Packet Radio Service), we proposed a new and feasible framework. After discussing the limitations of those existing methods which aren't suitable for GPRS network, we then detailedly demonstrated the proposed framework, and also gave the implementations based on NetFilter framework, Libnet as well as Libipq. Simulation results show that the isolated IPv6 areas can be efficiently connected by GPRS network through the presented framework.

关键词： IPv4 IPv6 GPRS Wireless Access tunnel

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A diversity-guided heuristic-based genetic algorithm for triangulation of Bayesian networks

A diversity-guided heuristic-based genetic algorithm for tri...

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作者： Dong, Xuchu Yu, Haihong Ouyang, Dantong Ye, Yuxin Zhang, Yonggang Department of Computer Science and Technology Jilin University Changchun Jilin 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin 130012 China

ISBN: (纸本)9788988678251

For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population diversity to identify stagnation and convergence as well as to guide the search procedure. Experiments on representative benchmarks show that DHGA posses better performance and robustness than other swarm intelligence methods.

关键词： Bayesian networks

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Research on Indoor Wireless Localization System for Radioactive Sources Based on ZigBee

Research on Indoor Wireless Localization System for Radioact...

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International Conference on Computing Control and Industrial engineering (CCIE)

作者： Ruixue Li Zhiyi Fang Baocong Hao Fengjie Yang College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Qiming Information Technology Company Limited Changchun China

ISBN: (纸本)9781424467501

This paper made a good many research on the related theory about indoor localization technology, and pointed out the key techniques for the proposed remote wireless monitoring system solution for radioactive sources. Because of the specificity of system monitoring objects-radioactive sources, ZigBee technology was adopted to implement the monitoring system, by studying the typical indoor localization technology. Functional requirements and difficulties in implementation, during the indoor localization of radioactive sources, were analyzed from three points of view. After the detailed planning of the ZigBee network nodes, the indoor wireless localization system for radioactive sources was designed. Four major functional modules, including system management, serial communication, data processing, and data storage, were devised to realize the host computer. Testing environment was constructed to test the localization system. Test results show that the indoor wireless localization system can meet users' requirements, controlling the localization error in the range of 3m.

关键词： ZigBee Remote monitoring Control systems System testing Wireless sensor networks Indoor environments Radio control Educational technology Paper technology Global Positioning System

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Genetic algorithm with affinity propagation

Genetic algorithm with affinity propagation

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2010 IEEE International Conference on Information and Automation, ICIA 2010

作者： Wu, Chunguo Gao, Hao Yu, Lianjiang Liang, Yanchun Xiang, Rongwu College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry Jilin University Changchun 130012 China School of Basic Courses Shenyang Pharmaceutical University Shenyang 110016 China

ISBN: (纸本)9781424457021

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems, e.g., aerodynamic design optimization, qualitative model learning in bioinformatics. To address this problem, we present a combination between genetic algorithms and clustering methods. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy. ©2010 IEEE.

关键词： Genetic algorithms

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Dynamic game based intrusion response model

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Journal of computational Information Systems 2010年第7期6卷 2199-2211页

作者： Zhu, Jianqi Liu, Yanheng Yang, Xu Sun, Xin College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Computation and Knowledge Engineering China

The severity and number of intrusions on computer networks are rapidly increasing, which requires advances not only in detection algorithm, but also in automatic response techniques. In this paper, a new approach to automatic response called DGII_IDR is presented that employs a game-theoretic response strategy against adversaries. It transforms the incomplete information dynamic game into a complete but imperfect information game by Harsanyi transformation. The optimal response is chosen by the use of perfect Bayesian equilibrium to revise the posterior belief of player's type continuously. Moreover, DGII_IDR solved the conflict between the rational assumption and irrational behavior of attacker/defender by restricting their strategies in game theory. We also show how our game theoretical framework can be applied to configure the intrusion detection strategies in realistic scenarios via a case study and demonstrate the effectiveness of DGII_IDR. Copyright © 2010 Binary Information Press.

关键词： Game theory

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An ontology-based schema matching on deep web

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Journal of computational Information Systems 2010年第4期6卷 1077-1084页

作者： Zhang, Aiqi Zuo, Wanli Wang, Ying Ji, Wenyan Peng, Tao Key Laboratory of Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130012 China

A large number of techniques have been implemented mostly based on abundance of data statistics and they usually do not harness the semantic relationships between attributes. This paper proposes a novel ontology-based schema matching approach. First, a core domain ontology has been built through analyzing pages from numerous domains. Then a two-step schema-matching process is presented to identify the correct matches between schema attributes and ontology information from the semantic perspective and this process can handle not only simple matches but also complex matches. Within the matching process, the ontology is real-time updated to make the subsequent matching processes easier. Finally, 100 interfaces about four different domains in the UIUC dataset are used for evaluating our approach and the experimental results show that it can improve the accuracy and the efficiency of schema matching among multiple interfaces. Copyright © 2010 Binary Information Press.

关键词： Ontology

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Multiple attribute mappings for domain ontology generation in deep web

Multiple attribute mappings for domain ontology generation i...

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International Conference on Environmental Science and Information Application Technology, ESIAT

作者： Kerui Chen Fan Zhang Wanli Zuo Fengling He College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Computation and Knowledge Engineering Ministry of Education China College of Information Engineering University of Zhengzhou Zhengzhou China Key Laboratory of Computation a Knowledge Engineering Ministry of Education China

Due to the structuring and semi-structuring of the most data contained in deep web, it's considerably much easier to extract and construct the ontology. The constructed ontology has multiple appliances, such as the data integration, data extraction assistance and so on. During the process of constructing ontology, the matching of attribute is a significantly important step, the quality of whose result will directly affect ontology's quality. The method proposed in this paper works well on identifying and solving the cases of simple matching and complex matching. Experiment results approve that the ontology constructed under the instruction of this method is perfect, as well as effective.

关键词： Books Automobiles Accuracy

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A hybrid algorithm of minimum spanning tree and nearest neighbor for classifying human cancers

A hybrid algorithm of minimum spanning tree and nearest neig...

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2010 3rd International Conference on Advanced Computer Theory and engineering, ICACTE 2010

作者： Zhou, Chunbao Wan, Liming Liang, Yanchun College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Research Institute on General Development and Evaluation of Equipment EAAF of PLA Beijing 100076 China

ISBN: (纸本)9781424465408

Classification and prediction of different cancers based on gene expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. The k nearest neighbor algorithm (k-NN) is one easy and efficient machine learning method for cancer classification and the parameter k is crucial. In this paper, we integrate minimum spanning tree (MST) and k nearest neighbor algorithm (k-NN) for cancer classification. The MST is designed for the selection of parameter k and the nearest neighbors for k-NN. Firstly we build a minimum spanning tree (MST) based on Euclidean distance between each two samples for gene expression data only including one unknown class sample. Secondly for unknown class sample in the gene expression data, we find the connected samples and then apply majority vote principle. Thirdly if there are tied votes then we expend the connected samples with the nearest neighbors for unknown class sample until all the samples are expended or the class for unknown sample is obtained. This hybrid algorithm is referred to as MSTNN. The hybrid algorithm MSTNN is compared with kNN and other 3 existing classification algorithms on CNS dataset, Colon dataset and Lung dataset, 3 binary class gene expression datasets and 3 multi-class gene expression datasets: Leukemial, Leukemia2, and Leukemia3 *** human cancers. The MSTNN algorithm improves 5.65% better than k-NN on average LOOCV accuracy and 13.80% better than kNN on testing datasets classification average accuracy, and achieves the best performance in all the 5 algorithms. The results demonstrate that the proposed MSTNN algorithm is feasible to classify human cancers. © 2010 IEEE.

关键词： Classification (of information)

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An adaptive multi-heuristic ant colony system for finding optimal elimination orderings in Bayesian networks

An adaptive multi-heuristic ant colony system for finding op...

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International Conference on Electrical engineering Computing Science and Automatic Control

作者： Dong, Xuchu Zhang, Yonggang Cai, Dianbo Yu, Haihong Ye, Yuxin Department of Computer Science and Technology Jilin University China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education China Network Monitor Maintenance Centre of Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424473120

To find an optimal elimination ordering for Bayesian networks, a multi-heuristic-based ant colony system named MHC-HS-ACS is proposed. MHC-HS-ACS uses a set of heuristics to guide the ants to search solutions. The heuristic set can evolve with the searching procedure in an adaptive way. MHC-HS-ACS also utilizes a heuristic-based local search to accelerate its convergence. computational experiments show that MHC-HS-ACS can find very high quality solutions. © 2010 IEEE.

关键词： Bayesian networks

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