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Optimize diagnosability and sensor placement in discrete event system

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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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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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 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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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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A Loss Assessment Design Method Based on SOA for Insurance Informationization

A Loss Assessment Design Method Based on SOA for Insurance I...

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Niya Li Jian Zhang Wei Lv Chengye Jin Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China Jilin University Changchun Jilin CN College of Computer Science and Technology Jilin University China LeJin Electronics Company Limited Jilin China

The loss assessment is an important operation of claim process in insurance industry. On the growing tide of making the insurance information system the in-depth support to optimizing operation and serving insurant, a methodological framework for the loss assessment is given based on SOA technology, Under the framework, the operation process design, the client design, the service design and the database design are given. These design results have been validated by an actual application system.

关键词： Insurance Databases Companies Information systems Service oriented architecture Design methodology

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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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Verilog combinational equivalence checking based on smt constraint solver

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ICIC Express Letters, Part B: Applications 2011年第5期2卷 1087-1092页

作者： Zeng, Hailin Ouyang, Dantong Zhang, Yuehua Zhang, Liming Zhang, Guiling School of Computer Science and Technology Jilin University No. 2699 Qanjin Street Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University No. 2699 Qanjin Street Changchun 130012 China Software College Jilin University No. 2699 Qanjin Street Changchun 130012 China

Most previous works on combinational equivalence checking use BDDs and other Boolean level representations to formulate and solve the problem, and therefore, not utilizing the word-level information inherently presents in the design. To overcome this limitation, word level proof techniques like Satis ability Module Theory (SMT) were proposed. The SMT can efficiently handle the designs containing word-level arithmetic operators and bit-level Boolean logic. In this paper, we present a technique checking the equivalence of two combinational circuits based on SMT constraint solver. The experimental results indicate that our method can utilize word-level information to speed up the process of verification and result in a decrease in memory usage. © 2011 ISSN 2185-2766.

关键词： Formal verification

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A verifiable multi-secret sharing scheme

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Dongbei Daxue Xuebao/Journal of Northeastern University 2011年第SUPPL.1期32卷 120-123页

作者： Wang, Yan-Xi Liu, Yan-Heng Wang, Jian Dong, Tian-Zhe College 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 130012 China

Analyzing two improved YCH schemes and a multi-secret sharing scheme based on homogeneous linear recursion, we propose and implement a new verifiable multi-secret sharing model based on Shamir secret sharing. The time complexity of this model in the phase of secrets recovery is O(k×t2), which is superior to other two improved YCH models (O(t3) (t>k) O(k3) (t≤k), O(k×(n+k)2)), and the time of secrets synthesis in the actual simulation is less than that of the other three models. Further, we compare the advantages and disadvantages of the four models on the time complexity, verifiability and open values. When n>k, the open values the new model needs are fewer than those of the other two improved YCH models. The experimental results show that the new model is better than the other three models on the time of secrets recovery.

关键词： Information theory

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A fuzzy adaptive multi-population parallel genetic algorithm for spam filtering

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Journal of Convergence Information Technology 2011年第2期6卷 172-182页

作者： Zhao, Zheng-dong Wang, Gang Zhao, Wei Chen, Hui-ling Zhao, Wei Li, Lu-lu Network Information Center Changchun University of Science and Technology Changchun 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 Department of Information Engineering Jilin Police College China Branch Institute of information technology Changchun Vocational Institute of Technology Changchun China

Nowadays, e-mail is one of the most inexpensive and expeditious means of communication. However, a principal problem of any internet user is the increasing number of spam, and therefore an efficient spam filtering method is imperative. Feature selection is one of the most important factors, which can influence the classification accuracy rate. To improve the performance of spam prediction, this paper proposes a new fuzzy adaptive multi-population parallel genetic algorithm (FAMGA) for feature selection. To maintain the diversity of population, a few studies of multi-swarm strategy are reported, whereas the dynamic parameter setting has not been considered further. The proposed method is based on multiple subpopulations and each subpopulation runs in independent memory space. For the purpose of controlling the subpopulations adaptively, we put forward two regulation strategies, namely population adjustment and subpopulation adjustment. In subpopulation adjustment, a controller is designed to adjust the crossover rate for each subpopulation, and in population adjustment, a controller is designed to adjust the size of each subpopulation. Three publicly available benchmark corpora for spam filtering, the PU1, Ling-Spam and Spam Assassin, are used in our experiments. The results of experiments show that the proposed method improves the performance of spam filtering, and is significantly better than other feature selection methods. Thus, it is proved that the multi-population regulation strategy can find the optimal feature subset, and prevent premature convergence of the population.

关键词： Data mining

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