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New method for structural reliability analysis by combining curve fitting with Monte Carlo simulation

jilin Daxue Xuebao (Gongxueban)/Journal of jilin University (engineering and Technology Edition) 2010年第SUPPL.1期40卷 293-296页

作者： Meng, Guang-Wei Cai, Bin Li, Feng Dong, Xin State Key Laboratory of Automobile Dynamic Simulation Jilin University Changchun 130022 China College of Mechanical Science and Engineering Jilin University Changchun 130022 China School of Civil Engineering Jilin Institute of Architecture and Civil Engineering Changchun 130118 China

To overcome shortcomings of large amount of computational efforts and long computation time existing in Monte Carlo simulation for system reliability analysis, an improved method was proposed in the light of curve fitting. Reliability problem was reformed by depending on an optimal parameter, and the failure probability was treated as a function of this parameter by exploiting the regularity of it and fitting the reliability function by Levenberg-Marquardt method. A ten-bar truss structure numerical example was given to prove the feasibility of proposed method. Result indicates that the proposed method has high computational accuracy with less computational efforts and computation time, providing an effective way to analyze reliability of large complex structures.

关键词： Curve fitting

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A mutual information and information entropy pair based feature selection method in text classification

A mutual information and information entropy pair based feat...

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International Conference on computer Application and System Modeling (ICCASM)

作者： Zhili Pei Yuxin Zhou Lisha Liu Lihua Wang Yinan Lu Ying Kong Mathematics School & Institute Jilin University Changchun China Tonghua China College of Mechanical Engineering Inner Mongolia University of Nationalities Tongliao China College of Computer Science and Technology Jilin University Changchun China College of Basic Medical Dalian Medical University Dalian China

ISBN: (纸本)9781424472352

Text classification is an important research field of data mining topics. This article brings a mutual information and information entropy pair based feature selection method (MIIEP_FS) based on the theory of information entropy and information entropy pair concept. This method measure the classification effect using feature by mutual information method and show the difference extent between the features being selected and the ones selected by information entropy. The experimental results show that the MIIEP_FS method proposed is more effective than MI and CHI methods. Macro F1 degrees of different kinds of machine learning algorithms: Naive Bayes and KNN method are higher by MIIEP_FS method, sometimes even more than the ones of support vector machines.

关键词： feature selection information entropy text classification

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Research on Chinese-Japanese Sign Language Translation System

Research on Chinese-Japanese Sign Language Translation Syste...

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Japan-China Joint Workshop on Frontier of computer science and Technology (FCST)

作者： Zhen Liu Xiaomei Zhang Jien Kato College of Computer Science and Technology Jilin University China Graduate School of Engineering Nagasaki Institute of Applied Science Nagasaki Japan Special Education College Changchun University China Graduate School of Information Science University of Nagoya Japan

Sign Language is a main way for deaf to express their thought and emotions, obtain information and participate in social activities. All sign languages of the world are not very similar each other. With the increasing of economic and cultural exchanges between China and Japan, more and more deaf from the two countries need to learn partner's sign language. At the same time, the translation of Chinese-Japanese sign languages has the important means right now. In this paper, the features of the two sign languages, Chinese sign language and Japanese sign language, are studied and compared. And, a scheme of Chinese-Japanese sign language translation system is proposed.

关键词： Handicapped aids Dictionaries Fingers Lips Vocabulary Speech Shape

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Method for universal combat platform simulator based on domain component model

Method for universal combat platform simulator based on doma...

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International Conference on Information science and engineering (ICISE)

作者： Shufen Liu Weifeng Xu JinHong Zhao Jun Peng Xiaodi Zhang Department of Computer Science and Technology Jilin University Changchun China System Engineering Research Institute China State Shipbuilding Corporation Beijing China Linjiang City People's Procuratorate Baishan China

A method for universal combat platform simulator development based on domain model and component technology is proposed. On the high abstraction level, domain model can be used to obtain demand model in the special domains, based on which different business objects should be mapped to different components. Basic Framework describes the combat platform commonness and provides its variety extensions in which corresponding components can be integrated into the simulator. In this way, all kinds of combat platform simulators can be developed. This method is capable to capture domain commonness and control variability successfully. For this reason, the reusability and interoperability of a military simulation software are both greatly improved.

关键词： Business Computational modeling Object oriented modeling Data models Software Data processing Human computer interaction

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Application of immune genetic algorithm in mobile robot

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Harbin Gongye Daxue Xuebao/Journal of Harbin institute of Technology 2010年第SUPPL. 2期42卷 157-159页

作者： Tan, Jing-Wei-Jia Wang, Hui Qi, Hong Zhang, Hong Department of Computer Science and Technology Jilin University Changchun 130012 China Department of Electrical Engineering Changchun Institute of Technology Changchun 130012 China

To improve the control precision of position and speed of mobile robot, a new way of optimized PID controller parameters based on Immune Genetic Algorithm (IGA) is proposed. The performance index for the integral of time weighted absolute error is used as the minimum objective function during parameter choice and IGA has the ability of global searching, self-adjustment and memory, which realize the auto-adapted of PID controller. The experiment result shows that the algorithm based on IGA is an effective algorithm.

关键词： Mobile robots

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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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International Conference on Advanced computer Theory and engineering, ICACTE

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

ISBN: (纸本)9781424465392

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 k-NN 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: Leukemia1, Leukemia2, and Leukemia3 involving human cancers. The MSTNN algorithm improves 5.65% better than k-NN on average LOOCV accuracy and 13.80% better than k-NN 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.

关键词： Classification algorithms Artificial neural networks Niobium Lungs Colon Support vector machines Cancer

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Occupant detection approach for smart airbag application

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jilin Daxue Xuebao (Gongxueban)/Journal of jilin University (engineering and Technology Edition) 2010年第SUPPL.1期40卷 195-198页

作者： Zhao, Yong-Hua Xu, Tao Li, Zhi-Hui Guo, Wei Xie, Kong-Feng College of Mechanical Science and Engineering Jilin University Changchun 130022 China Center of Computer Teaching and Research Jilin University Changchun 130012 China College of Transportation Jilin University Changchun 130022 China Institute of Chemical Defence Beijing 102205 China

A method on occupant detection under a single video camera was presented, which used a window classifier to explore occupant header in the image. The window classifier was constructed by histograms of oriented gradients and support vector machine classifier, and it was trained by occupant header and non-occupant header. To get multiscale detection results, non-maximum suppression was used to get the maxim point in the space of position and scale, which is occupant header region. In experiment, 200 occupant header samples and 200 non-occupant header samples under occupant different pose condition were trained to get the classifier mode between occupant header and non occupant header, and occupant videos including different occupant poses were tested by the proposed method. The results show the method can satisfy the need of occupant detect in smart airbag application.

关键词： Graphic methods

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Detecting conflict policy rules with concept lattice

Detecting conflict policy rules with concept lattice

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5th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2009

作者： Suyun, Jiao Yanheng, Liu Xin, Qi Yaoqiang, Zhu Juan, Wang Institute of Computer Science and Engineering Changchun University of Technology Changchun China College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)9781424436934

Concept lattice was creatively used in policy based network management in this study. It takes much time for a conflict detection routine to search every rule in a policy rule set with conventional algorithms to see if conflict occurs before a new rule is added to the rule set. A novel conflict detection algorithm was proposed based on concept lattice to address this problem. The algorithm greatly increases efficiency of conflict detection. Performance analysis and simulation show that the proposed algorithm is effective. ©2009 IEEE.

关键词： Information analysis

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A cooperative framework for effective ontology matching

A cooperative framework for effective ontology matching

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2009 International Conference on Information engineering and computer science, ICIECS 2009

作者： Yang, Feng Liu, Lei College of Computer Science and Technology Jilin University Changchun China College of Information JiLin Teacher's Institute of Engineering and Technology Changchun China

ISBN: (纸本)9781424449941

Ontology matching is critical to semantic interaction and knowledge sharing. The purpose of ontology matching is to reuse the ontologies and integrate them in different fields. It is the basement of the other semantic web application, such as, semantic web-based service, ontology alignment. Nowadays most ontology mapping approaches integrate multiple individual matchers to explore both linguistic and structure similarity of different ontologies. Thus how to effectively aggregating different similarities is pervasive in ontology mapping. However, the achievements of similarities aggregation are very limited. Addressing this issue, the work presented in this paper puts forward an ontology matching approach, which uses as a backbone a multi-similarity matching technique and explores both linguistic and structure similarity. In the process of similarities aggregation, the method based on statistical learning is used. Our approach takes the different similarities into one whole, as a similarity vector. All of them form the similarity space, by this way, matching discovery can be converted into binary classification. SVM (Support Vector Machine) is used to carry on this task. For making full use of the message of ontology, our implementation and experimental results are given to demonstrate the effectiveness of the matching approach. ©2009 IEEE.

关键词： Ontology

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Ontology matching approach based on multi-strategy combined

Ontology matching approach based on multi-strategy combined

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2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009

作者： Yang, Feng Gao, Yanhua Liu, Lei College of Computer Science and Technology Jilin University Changchun China College of Information JiLin Teacher's Institute of Engineering and Technology Changchun China

ISBN: (纸本)9780769538730

The purpose of ontology matching is to reuse the ontologies and integrate them in different fields, so as to implement the more bigger pool of information and knowledge to the new communication and application. The achievements of (semi-)automatic ontology matching are very limited. There are many works to do in about this field. Under the background, an ontology matching approach, SGOM, is put forward. It combines several strategies and has element-level matching, as well as structure-level matching. It carries on the ontology matching by using the semantic information. Our implementation and experimental results are given to demonstrate the effectiveness of the matching approach. © 2009 IEEE.

关键词： Ontology

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