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Journal of Software 2011年第11 SPEC. ISSUE期6卷 2239-2246页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Key Laboratory of Symbol Computation and Knowledge Engineering of 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

Automatic image annotation is a promising solution to narrow the semantic gap between low-level content and high-level semantic concept, which has been an active research area in the fields of image retrieval, pattern recognition, and machine learning. However, even the most dedicated annotation algorithms are often unsatisfactory. Image annotation refinement has attracted much more attention recently. In this paper, a novel refinement algorithm using dynamic voting based on mutual information is proposed. Unlike the traditional refinement algorithm, the proposed algorithm adopts dynamic weighted voting to measure the dependence between the candidate annotations, which not only permits that the annotations with higher probabilities deny the annotations with lower probabilities, but also permits that the annotations with lower probabilities deny the annotations with higher probabilities. The proposed refinement algorithm adopts progressive method instead of iterative, which can significantly decrease the time cost of refining annotations. In order to further improve efficiency without sacrificing precision, we propose the block-based normalized cut algorithm to segment image. Experiments conducted on standard Washington Ground Truth Image database demonstrate the effectiveness and efficiency of our proposed approach for refining image annotations. © 2011 ACADEMY PUBLISHER.

关键词： Image annotation

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基于划分的集合相似连接

基于划分的集合相似连接

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第29届中国数据库学术会议

作者： Rong Chuitian 荣垂田 Xu Tianren 徐天任 Du Xiaoyong 杜小勇 Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China) Ministry o 教育部数据工程与知识工程重点实验室(中国人民大学) 北京 100872 中国人民大学信息学院北京 100872 School of Information Renmin University of China Beijing 100872 Key Laboratory of Education Inform 中国人民大学信息学院北京 100872 民族教育信息化教育部重点实验室(云南师范大学) 昆明 650500

集合相似连接(set similarity join)是指在给定的数据集中，按照基于集合间覆盖关系的相似度计算方法来衡量数据之间的相似度、并找出所有相似度不小于给定阈值的数据对的操作。集合相似连接作为一种新的基本操作在很多领域中有重要应... 详细信息

集合相似连接(set similarity join)是指在给定的数据集中，按照基于集合间覆盖关系的相似度计算方法来衡量数据之间的相似度、并找出所有相似度不小于给定阈值的数据对的操作。集合相似连接作为一种新的基本操作在很多领域中有重要应用。随着社会网络、移动应用以及在线服务的发展，使得数据收集的效率和规模得到了很大的提高，同时给相似连接操作带来新的挑战。根据集合相似的必要条件，提出了相似集合之间的差异度。利用差异度和鸽巢原理，提出了一种新颖的基于数据划分的集合相似连接计算方法，该方法对集合进行自适应的均衡划分，并利用基于划分块的过滤方法来提高过滤的效率。为了进一步提高过滤的效果和相似连接的效率，利用划分块的位置信息提出了增强的过滤方法。针对提出的方法，在不同的环境下进行了实验，实验结果表明，该方法与已有的方法相比可以有效地提高相似连接的效率。

关键词：数据库集合相似连接均衡划分法阈值

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Damaged solar cell detection based on gray-intensity wave transformation

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Procedia engineering 2011年 15卷 3808-3813页

作者： Xuanjing Shen Wei Wei Jianwu Long Qingji Qian Colledge of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012China Colledge of Physics Jilin University Changchun 130025 China

An automatic system to detect cracks of solar cells on satellite solar panel through camera has been proposed in this study. And a novel binarization method based on gray intensity wave transformation is also introduced to decrease the impact of non-uniform illumination on cell image. It adaptively classifies the pixel depending on local peak and trough on the gray intensity surface. After the cell image binareized, a strategy called “adjacency searching” is adopted to remove the gate lines. Then the ellipse fitting based on least squares is conducted on the contours of crack segments to get their angles, which are used to connect these segments into the whole crack. The experiment on 5000 cells in one panel had shown that the precision of our system has reached 98.5%, and its false alarm rate is less than 9%, which could meet the application requirements.

关键词： Satellite Solar cell Binarization Crack detection

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Operon Prediction by Markov Clustering

Operon Prediction by Markov Clustering

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2011·国际基因组学大会

作者： Wei Du Zhongbo Cao Yan Wang Enrico Blanzieri Chen Zhang Yanchun Liang College of Mathematics Jilin University Changchun 130012 China Department of Information and Communication Technology University of Trento Povo 38050 Italy College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

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Optimize diagnosability and sensor placement in discrete event system

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Journal of Convergence Information Technology 2011年第7期6卷 219-224页

作者： Jian, Zhao Dantong, Ouyang Xiaoyu, Wang Liming, Zhang College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Changchun University Changchun China

Diagnosability indicates that whether the fault can be detected in finite time, which is an important property in model based diagnosis. As diagnosis depends on the sensor placement and the modeling, it is hard to make a choice whether to place more sensors for testing or to compute more diagnosis pathways in practical application. In this paper, a method is proposed to resolve this by defining key point. The key points take priority on testing among the existing sensors. In these key points, the observation can be optimized and be diagnosis tested efficiently. Experimental result indicates that this method achieves efficient faults distinction and identification, and reduces the cost of sensors and the computational complexity of diagnostic in the case of normal behavior.

关键词： Discrete event simulation

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Eliminating repeated constraint checks in MaxRPC algorithms

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ICIC Express Letters, Part B: Applications 2011年第5期2卷 1189-1194页

作者： Guo, Jinsong Li, Zhanshan Zhang, Liang Geng, Xuena Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education Jilin University No. 2699 Qianjin Street Changchun 130012 China College of Computer Science and Technology Jilin University No. 2699 Qianjin Street Changchun 130012 China

Filtering techniques are used in Constraint Satisfaction Problems to remove all the local inconsistencies during a processing step or prune the search tree efficiently during search. Local consistencies are used as preprocessing filtering techniques. MaxRPC which can remove more values than arc consistency is not used as widely as arc consistency for its relatively expensive time cost. We discover that, in the algorithms enforcing maxRPC, there are repeated constraint checks which can affect the efficiency of the algorithm negatively. In this paper, we propose a method making use of a data structure of AC4 and the relation "stronger" between local consistencies to eliminate the repeated constraint checks. Since the repeated constraint checks can be eliminated and the time cost of enforcing maxRPC can be reduced, the applicable occasions of maxRPC should be reconsidered. © 2011 ISSN 2185-2766.

关键词： Constraint satisfaction problems

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A Heuristic Genetic Process Mining Algorithm

A Heuristic Genetic Process Mining Algorithm

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International Conference on Computational Intelligence and Security

作者： Jiafei Li Jihong OuYang Mingyong Feng Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN Industry Applications Department Cattsoft Technology Company Limited Beijing China

The current GPM algorithm needs many iterations to get good process models with high fitness which makes the GPM algorithm usually time-consuming and sometimes the result can not be accepted. To mine higher quality model in shorter time, a heuristic solution by adding log-replay based crossover operator and direct/indirect dependency relation based mutation operator is put forward. Experiment results on 25 benchmark logs show encouraging results.

关键词： data mining Genetics Heuristic algorithms Computational modeling Process control Industries Measurement

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An adaptive fuzzy ant colony optimization for feature selection

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Journal of Computational Information Systems 2011年第4期7卷 1206-1213页

作者： Liu, Yuanning Wang, Gang Chen, Huiling Zhao, Zhengdong Zhu, Xiaodong Liu, Zhen College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Network Center Changchun University of Science and Technology Changchun 130022 China Graduate School of Engineering Nagasaki Institute of Applied Science Japan

Standard pattern classifiers perform on all data features. Whereas, some of the features are redundant or irrelevant, which reduce prediction accuracy, and increase running time of classifier. The purpose of this study is to search optimal feature subset, in order to increase the classification performance. The feature selection problem differs from traditional optimization problem on the problem size, namely the searching space or the problem dimension. Thus it is easy to converge at a local optimum by means of the ant colony optimization (ACO) based method with static parameter settings, but the adaptive parameter control strategy can balance between exploration and exploitation in the search space to intelligently improve solutions and avoid premature convergence. Only little research has been reported to adjust parameters of ACO adaptively. This paper proposes a novel adaptive fuzzy ant colony optimization (AFACO) based method for feature selection. We design two fuzzy controllers to adjust parameters of ACO, namely pheromone evaporation rate and the number of ants. The performance of the proposed method is compared with that of the Standard ACO based, Standard particle swarm optimization (PSO) based and genetic algorithm (GA) based methods on 10 benchmark data sets, taken from UCI machine learning and StatLog databases. The experimental results show that the proposed method outperforms the other methods in prediction accuracy, and is efficient and effective for feature selection problem. Copyright © 2011 Binary Information Press.

关键词： Ant colony optimization

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A novel framework for gene selection

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International Journal of Advancements in Computing Technology 2011年第3期3卷 184-191页

作者： Zhao, Wei Wang, Gang Wang, Hong-bin Chen, Hui-ling Dong, Hao Zhao, Zheng-dong Network Information Center Changchun University of Science and Technology Changchun 130022 China College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Microarray data are highly redundant and noisy, and most genes are believed to be uninformative with respect to studied classes, as only a fraction of genes may present distinct profiles for different classes of samples. This paper proposed a novel hybrid framework (NHF) for the classification of high dimensional microarray data, which combined information gain(IG), F-score, genetic algorithm(GA), particle swarm optimization(PSO) and support vector machines(SVM). In order to identify a subset of informative genes embedded out of a large dataset which is contaminated with high dimensional noise, the proposed method is divided into three stages. In the first stage, IG is used to construct a ranking list of features, and only 10% features of the ranking list are provided for the second stage. In the second stage, PSO performs the feature selection task combining SVM. F-score is considered as a part of the objective function of PSO. The feature subsets are filtered according to the ranking list from the first stage, and then the results of it are supplied to the initialization of GA. Both the SVM parameter optimization and the feature selection are dynamically executed by PSO. In the third stage, GA initializes the individual of population from the results of the second stage, and an optimal result of feature selection is gained using GA integrating SVM. Both the SVM parameter optimization and the feature selection are dynamically performed by GA. The performance of the proposed method was compared with that of the PSO based, GA based, Ant colony optimization (ACO) based and simulated annealing (SA) based methods on five benchmark data sets, leukemia, colon, breast cancer, lung carcinoma and brain cancer. The numerical results and statistical analysis show that the proposed approach is capable of selecting a subset of predictive genes from a large noisy data set, and can capture the correlated structure in the data. In addition, NHF performs significantly better than th

关键词： Feature Selection

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Strong Security Enabled Certificateless Aggregate Signatures Applicable to Mobile Computation

Strong Security Enabled Certificateless Aggregate Signatures...

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International Conference on Intelligent Networking and Collaborative Systems (INCOS)

作者： Hu Xiong Qianhong Wu Zhong Chen Key Laboratory of Network and Software Security Assurance of the Ministry of Education Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Department of Computer Engineering and Mathematics UNESCO Chair in Data Pr Universitat Rovira i Virgili Tarragona Spain Key Laboratory of AeroSpace Information Security and Trusted Computing Ministry of Education School of Computer Wuhan University of China China

An aggregate signature scheme allows a public algorithm to aggregate n signatures of n distinct messages from n signers into a single signature. By validating the single resulting signature, one can be convinced that the messages have been endorsed by all the signers. Certificateless aggregate signatures allow the signers to authenticate messages without suffering from the complex certificate management in the traditional public key cryptography or the key escrow problem in identity-based cryptography. In this paper, we present a new efficient certificate less aggregate signature scheme. Compared with up-to-date certificate less aggregate signatures, our scheme is equipped with a number of attracting features: (1) it is shown to be secure under the standard computational Diffie-Hellman assumption in the random oracle model, (2) the security is proven in the strongest security model so far, (3) the signers do not need to be synchronized, and (4) its performance is comparable to the most efficient up-to-date schemes. These features are desirable in a mobile networking and computing environment where the storage/computation capacity of the end devices are limited, and due to the wireless connection and distributed feature, the computing devices are easy to be attacked and hard to be synchronized.

关键词： Aggregates Games Generators Synchronization Public key cryptography

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