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Science China(Information Sciences) 2011年第11期54卷 2454-2458页

作者： LIU YanHeng 1,2,LIU XueLian 3 & WANG Jian 1,2 1 key laboratory of symbolic computation and knowledge engineering of ministry of education,Jilin University,Changchun 130012,China 2 College of Computer Science and Technology,Jilin University,Changchun 130012,China 3 College of Software,Jilin University,Changchun 130012,China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China College of Software Jilin University Changchun China

Functions and call relations are extracted into nodes and edges,respectively,by which a novel topological model is *** directional edges and the corresponding weight values express the call relations and tightness *** introducing two concepts of function fault-tolerant capability and software fault intensity and by designing a allocation rule on fault-tolerant capability,a cascading fault model is built to explore fault propagation *** on practical software networks show that a weak fault intensity,a small number of initial faults,and a strong fault-tolerant capability can slow down the spreading *** functions with more call relations and more closer tightness contribute more to the stability of the whole system.

关键词： software fault tolerant cascading faults fault-tolerant capability fault intensity

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A new feature selection method based on clustering

A new feature selection method based on clustering

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2011 8th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural computation, ICNC'11

作者： Liu, Huawen Mo, Yuchang Wang, Jiyi Zhao, Jianmin Department of Computer Science Zhejiang Normal University Jinhua 321004 China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China School of Computer Science and Engineering Southeast University Nanjing 211189 China

ISBN: (纸本)9781612841816

Feature selection is an effective technique to put the high dimension of data down, which is prevailing in many application domains, such as text categorization and bio-informatics, and can bring many advantages, such as improving efficiency and avoiding over-fitting, to learning algorithms. Currently, many efforts have been attempted in this field and various feature selection methods have been developed and proved to be very competitive. Unlike other selection methods, in this paper we propose a new method to select important features using a manner of feature clustering. The main character of our method is that it works like data clustering in an agglomerative way. In this method, each feature is considered as a data point clustered with between-cluster and within-cluster distances. As a result, the selected feature subset has minimal redundancy among its members and maximal relevance with the class labels. Our performance evaluations on seven benchmark datasets show that the classification performance achieved by our proposed method is better than other feature selection methods. © 2011 IEEE.

关键词： Feature Selection

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Blind identification of image copy-paste tampering based on logarithm polar coordinate transformation

Blind identification of image copy-paste tampering based on ...

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2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011

作者： Lv, A. Ying-Da Shen, B. Xuan-Jing Chen, C. Hai-Peng College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781601321916

To detect image copy-paste tampering, an improved blind identification was proposed in this study. Firstly, according to gray-level and gray-structure, every couple of doubtful blocks can be located. Secondly, for each located couple of doubtful blocks, use logarithm polar coordinate transformation to translate the rotation and scaling in Cartesian coordinate system into translation in logarithm polar coordinate system;and use phase correlation method to obtain rotation angle, scaling size and position offset;and then, the tampered regions would be located roughly. Finally, use geometry method to accurately calculate the rotation angle, scaling size and position offset between the copy-paste regions, and according to these values, the tampered region can be located accurately. Experimental results showed that our algorithm can detect the copy-paste tampering, even with rotation and scaling transformation, and it can resist some post-processing, such as blurring, adding noise, and so on.

关键词： Rotation

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A novel method for RNA secondary structure prediction

A novel method for RNA secondary structure prediction

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2011 7th International Conference on Natural computation, ICNC 2011

作者： Xing, Chong Ji, Zhaohua Wang, Gang Wang, Yao Shen, Wei Liang, Yanchun Key Laboratory for Symbol Computation and Knowledge Engineering of National Education MinistryCollege of Computer Science and TechnologyJilin University Changchun China College of Information Engineering Guanghua College of Changchun University Changchun China College of Communications Engineering Jilin University Changchun China

ISBN: (纸本)9781424499533

In this paper, we propose PSOfold, a particle swarm optimization for RNA secondary structure prediction. PSOfold is based on the recently published IPSO. We present two strategies to improve the performance of IPSO. Firstly, in order to boost the competence in searching an optimal solution, fuzzy logic control is used to adaptively adjust the parameters in PSO. Accordingly, three fuzzy logic controls are designed by which the inertia weight, learning factors and the number of ants are tuned respectively. Secondly, to further settle the stem permutation problem, we put forward a solution conversion strategy (SCS), which can transform discrete values of stems into an ordered stem combination, thereby supplying an enhanced solution to evaluation of objective function. An evaluation of the performance of PSOfold in terms of prediction accuracy is made via comparison with one dynamic programming algorithm mfold and four metaheuristics, IPSO, ACRNA, RnaPredict, SARNA-Predict and mfold for ten individual known structures. PSOfold is able to predict structures with higher prediction accuracy than the other metaheuristic based methods on certain sequences, and has comparable performance compared with mfold. © 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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A Chinese online document clustering algorithm based on hidden sentiment vector

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Journal of computational Information Systems 2011年第6期7卷 1974-1981页

作者： Yang, Hui Wang, Zhe Zhou, Xu Wang, Zuo Zhou, Tong College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbol Computation and Knowledge Engineering Ministry of Education China

The core idea of clustering algorithm is the division of data into groups of similar objects. Some clustering algorithms are proven good performance on document clustering, such as k-means and UPGMA etc. However, few document clustering algorithms pay attention to the hidden sentiment which is a very important feature of the documents. This paper presents an improved k-means algorithm (HSK-Means) based on hidden sentiment vector for Chinese document clustering. Chinese dependency grammar rules are used to extract document feature and evaluate hidden sentiment. A new method for selecting initial cluster centroids based on rank mechanism of similarity is also proposed to improve accuracy of clustering algorithm. The experimental results on real online document sets illustrate that the performance of HSK-Means algorithm is better than classic document clustering algorithms. Copyright © 2011 Binary Information Press.

关键词： Information retrieval

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MaxRPC algorithms based on bitwise operations

MaxRPC algorithms based on bitwise operations

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Lecture Notes in Computer Science

作者： Guo, Jinsong Li, Zhanshan Zhang, Liang Geng, Xuena Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9783642237850

Max Restricted Path Consistency (maxRPC) is a promising domain filtering consistency for binary constraints. In existing algorithms, the process of searching for PC-witnesses requires most constraint checks. And the computing speed of this process significantly affects the efficiency of the whole algorithm. In this paper, we propose a new method based on bitwise operations to speed up the computations of this process. Two algorithms maxRPCbit and maxRPCbi+rm utilizing this new method are proposed. Both algorithms and their light versions outperform the best ones among existing algorithms by a large margin. Significantly, our experiments, which compare the search algorithms applying light maxRPC with the one maintaining arc consistency, demonstrate that maxRPC is a much more promising filtering technique than what we thought. © 2011 Springer-Verlag.

关键词： Computers

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A Multi-Label Classification Algorithm Based on Label-Specific Features

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Wuhan University Journal of Natural Sciences 2011年第6期16卷 520-524页

作者： QU Huaqiao ZHANG Shichao LIU Huawen ZHAO Jianmin College of Mathematics Physics and Information Engineering Zhejiang Normal University Jinhua 321004 Zhejiang China Key Laboratory of Symbol Computation and KnowledgeEngineering of Ministry of Education Jilin University Changchun130012 Jilin China

Aiming at the problem of multi-label classification, a multi-label classification algorithm based on label-specific features is proposed in this paper. In this algorithm, we compute feature density on the positive and negative instances set of each class firstly and then select mk features of high density from the positive and negative instances set of each class, respectively; the intersec- tion is taken as the label-specific features of the corresponding class. Finally, multi-label data are classified on the basis of la- bel-specific features. The algorithm can show the label-specific features of each class. Experiments show that our proposed method, the MLSF algorithm, performs significantly better than the other state-of-the-art multi-label learning approaches.

关键词： multi-label classification label-specific features feature＇s value density

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A new model for topological relations between convex regions

A new model for topological relations between convex regions

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2011 8th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural computation, ICNC'11

作者： Ouyang, Jihong Ma, Ke Ma, Ling College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9781612841816

Topological relations between spatial objects have played important roles in spatial representing and reasoning. Various models for expressing topological relations have been put forward. The Region Connection Calculus (RCC) and 9-Intersection Method (9IM) are most well-known topological formalisms, but neither of them can characterize the characteristic of topological relations between convex regions. In this paper, we introduce a new model for representing topological relations between two convex plane regions, which characterized with the topological properties of details of region A and B. Applying our model to triangles, we obtain a complete classification of topological relations which called RCC32. By calculating the cost of transforming one relation into another, the closest topological relation graph of RCC32 is given. © 2011 IEEE.

关键词： computational geometry

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A kind of improving HMM model and using in the visual speech recognition

A kind of improving HMM model and using in the visual speech...

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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Zhang, Zeliang Li, Xiongfei Yang, Chengjia Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Beihua University Jilin China

ISBN: (纸本)9781424497638

Visual speech-lip reading, making the computer understands what do speakers want to express through observing the lip direction of them. The most simply method of lip reading in early stage is to compare between characters from the frozen pictures and templates being stored. It neglects the character is changing with time. This method is very simply, but it only can classify the simple elements not the words, so it couldn't render great serves to speech recognition. Afterwards the adoption of behavioral characteristics is becoming more widespread. Because of the superior of Hidden Markov model (HMM), it can be applied in speech recognition widely. In recent years, it is also used in the research of lip-reading recognition. The classical HMM model makes two hypotheses: hidden expropriation hypothesis: the state at t+1 is only conditioned by the state at t, not the state before;the expropriation hypothesis from hidden state to visible state: the visible state at t only conditioned by the hidden state at t, not the state before. Such kind of hypothesis is not very reasonable in some practical application (such as lip-reading). In some kind condition, the state at t is not only conditioned by t-1, but also t-2. Therefore this thesis revises the assumed condition classical HMM to derive a new HMM model and algorithm, and applying it into lip-reading recognition to increase the discrimination. © 2011 IEEE.

关键词： Hidden Markov models

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A study on improved hidden Markov models and applications to speech recognition

A study on improved hidden Markov models and applications to...

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International Conference on Computer Science and Service System (CSSS)

作者： Zeliang Zhang Xiongfei Li Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Beihang University Jilin China

Visual voice lip-reading, so the computer can understand what the speakers want to express direction by looking at their lips. Lip reading is the easiest way to compare the early characters and templates from the frozen image is stored. It ignores the very nature and time changes. This method is very simple, but it's just simple elements can be classified, then it may not show significant speech recognition services. Behavior was characterized by more and more common. Because of the hidden Markov model is superior (HMM), which can be widely used in speech recognition. In recent years, is also used to lip reading identification. Classical HMM model, so that the two assumptions: hidden assumptions collected: in t+1 the state can only be in this country is not in the state before t; from the hidden visible state hypothesis: only by regulating the t hide the visible state, rather than the previous state. This hypothesis is not very useful in some applications (such as lip reading) is reasonable. Under certain conditions, in the t state not only limits the t-1, but also t-2. Therefore, this study modified the assumptions of the classical HMM to derive a new HMM model and algorithms, and applied to the lip-reading recognition is increasing discrimination.

关键词： Hidden Markov models Mouth Speech recognition Cost accounting Training Viterbi algorithm Algorithm design and analysis

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