Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580523
V. Nguyen, Nguyen Thi Ly Sa
Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.
{"title":"Evaluating technologies based rough set theory","authors":"V. Nguyen, Nguyen Thi Ly Sa","doi":"10.1109/ICMLC.2010.5580523","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580523","url":null,"abstract":"Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121352536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580480
Ruihua Li, Zheng Hua Zhu, Chen Li, Min-Hui Jiang
In this paper, we study the development and status of the current trusted measurement, and analyze the threats of process running in today's structure of the computer system. From the view of Turing, we abstract the key elements of process behavior, propose a trusted measurement for the process behavior running, in which trusted measurement formulas based on the process behavior itself and computing environment that the process running on are given. Finally, a frame to realize the model function is presented.
{"title":"Trusted measurement model of runtime process behavior based on turing","authors":"Ruihua Li, Zheng Hua Zhu, Chen Li, Min-Hui Jiang","doi":"10.1109/ICMLC.2010.5580480","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580480","url":null,"abstract":"In this paper, we study the development and status of the current trusted measurement, and analyze the threats of process running in today's structure of the computer system. From the view of Turing, we abstract the key elements of process behavior, propose a trusted measurement for the process behavior running, in which trusted measurement formulas based on the process behavior itself and computing environment that the process running on are given. Finally, a frame to realize the model function is presented.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127268893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580573
Xiao-hua Xu, Ping He, Ling Chen
Nonlinear multi-classification has been a popular task in machine learning recently. In this paper, we propose a nonlinear multi-classification algorithm named Supervised Spectral Space Classifier (S3C), S3C integrates the discriminative information into the spectral graph mapping and transforms the input data into the low-dimensional supervised spectral space. S3C not only enables researchers to examine the mapped data in its supervised spectral space, but also can be directly applied to multi-classification problems. Experimental results on synthetic and real-world datasets demonstrate that S3C outperforms the state-of-the-art nonlinear classifiers SVM.
{"title":"Learning spectral graph mapping for classification","authors":"Xiao-hua Xu, Ping He, Ling Chen","doi":"10.1109/ICMLC.2010.5580573","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580573","url":null,"abstract":"Nonlinear multi-classification has been a popular task in machine learning recently. In this paper, we propose a nonlinear multi-classification algorithm named Supervised Spectral Space Classifier (S3C), S3C integrates the discriminative information into the spectral graph mapping and transforms the input data into the low-dimensional supervised spectral space. S3C not only enables researchers to examine the mapped data in its supervised spectral space, but also can be directly applied to multi-classification problems. Experimental results on synthetic and real-world datasets demonstrate that S3C outperforms the state-of-the-art nonlinear classifiers SVM.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"12 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124837061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580548
Y. Su, Yanmin Nie, Xi-xian Niu
Financial risk of a certain enterprise usually is categorized into a determination grade under the traditional evaluation method. The traditional classification can lead to part information loss, then result in mistake decisions of users. According to the characteristics of financial risk, a multi-level fuzzy model of comprehensive evaluation is put forward in this paper. The evaluation result can indicate the degree that the enterprise risk should belong to; help users to take advantage the enterprise risk information completely. To verify the accurate of new classification model, financial risk evaluation is carried out based on the data set of Shanghai Dianli. The result of simulated experiment shows that the fuzzy evaluation method ran well and can provide more useful information.
{"title":"Enterprise financial risk evaluation research based on fuzzy mathematics","authors":"Y. Su, Yanmin Nie, Xi-xian Niu","doi":"10.1109/ICMLC.2010.5580548","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580548","url":null,"abstract":"Financial risk of a certain enterprise usually is categorized into a determination grade under the traditional evaluation method. The traditional classification can lead to part information loss, then result in mistake decisions of users. According to the characteristics of financial risk, a multi-level fuzzy model of comprehensive evaluation is put forward in this paper. The evaluation result can indicate the degree that the enterprise risk should belong to; help users to take advantage the enterprise risk information completely. To verify the accurate of new classification model, financial risk evaluation is carried out based on the data set of Shanghai Dianli. The result of simulated experiment shows that the fuzzy evaluation method ran well and can provide more useful information.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"14 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124911645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580749
Chuntao Zhang, Jiao Guo, Qianli Ma, Hong Peng, Xiao-Dong Zhang
In order to obtain the effective input vector for the prediction of multivariate time series, method of joint entropy determine the dimension(JEDD) is proposed in the reconstructed phase space. For multivariate chaotic time series, Firstly, determine the delay time of each variate with mutual information method, and then propose the algorithm that determines the embedding dimension of phase space by the joint entropy. The algorithm could choose the reconstructed components based on the maximum entropy principle, continuously expand phase space to make the amount of the information of reconstructed components as much as the system, which could eliminate the redundancy of phase space. The numerical experiments show that the neutral network prediction in the reconstructed phase space by JEDD is much better than univariate time series prediction and existing multiple variable predictions.
{"title":"Phase space reconstruction and prediction of multivariate chaotic time series","authors":"Chuntao Zhang, Jiao Guo, Qianli Ma, Hong Peng, Xiao-Dong Zhang","doi":"10.1109/ICMLC.2010.5580749","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580749","url":null,"abstract":"In order to obtain the effective input vector for the prediction of multivariate time series, method of joint entropy determine the dimension(JEDD) is proposed in the reconstructed phase space. For multivariate chaotic time series, Firstly, determine the delay time of each variate with mutual information method, and then propose the algorithm that determines the embedding dimension of phase space by the joint entropy. The algorithm could choose the reconstructed components based on the maximum entropy principle, continuously expand phase space to make the amount of the information of reconstructed components as much as the system, which could eliminate the redundancy of phase space. The numerical experiments show that the neutral network prediction in the reconstructed phase space by JEDD is much better than univariate time series prediction and existing multiple variable predictions.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124921213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580868
Cheng-Liang Lai, Sung-Ting Tsai
Surveillance system is widely applied in various fields in recent years. The demand for monitoring quality is not only to capture the object image, but also to present sharp and recognizable image. Thus, PTZ camera, which has pan and zoom functions, has become the best equipment. How to zoom in object and move camera lens so that the object is placed at the center of image becomes the major issue. This paper proposes the method of using the widest camera viewing angle as the moving range, and employing the spatial adjustment method of camera to establish the relative position of the camera and space. However, once the targeted object is unclear, the zoom in function of the PTZ camera is used; if the targeted object is not within the center of the image, the targeted object will move out of the image frame during the zoom-in process. Hence, by using the fuzzy nerves to simulate nonlinear horizontal movement and vertical rotation of PTZ camera, the image can be moved to the center of the image. In this paper, PTZ camera can zoom in image of the targeted object and move camera lens so that the object is at the frame center. Without additional adjustment, the camera lens can be moved exactly to the target position.
{"title":"Application of using fuzzy-neural network on PTZ camera","authors":"Cheng-Liang Lai, Sung-Ting Tsai","doi":"10.1109/ICMLC.2010.5580868","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580868","url":null,"abstract":"Surveillance system is widely applied in various fields in recent years. The demand for monitoring quality is not only to capture the object image, but also to present sharp and recognizable image. Thus, PTZ camera, which has pan and zoom functions, has become the best equipment. How to zoom in object and move camera lens so that the object is placed at the center of image becomes the major issue. This paper proposes the method of using the widest camera viewing angle as the moving range, and employing the spatial adjustment method of camera to establish the relative position of the camera and space. However, once the targeted object is unclear, the zoom in function of the PTZ camera is used; if the targeted object is not within the center of the image, the targeted object will move out of the image frame during the zoom-in process. Hence, by using the fuzzy nerves to simulate nonlinear horizontal movement and vertical rotation of PTZ camera, the image can be moved to the center of the image. In this paper, PTZ camera can zoom in image of the targeted object and move camera lens so that the object is at the frame center. Without additional adjustment, the camera lens can be moved exactly to the target position.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125068485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580870
Jin-Ling Pang, Zhen-Ning Yang
With deregulation and globalization, and the impact of these developments on economies worldwide, it has become necessary for China to consider an approach that would further attune its economic engine toward sustained growth. This paper aims to establish a theory framework to evaluate the performance of the small and medium-sized enterprises (SMEs) in Chinese Science Parks. The authors have developed the scale through reading the literature, interviewing in companies. According to the data mining that has been proceeded after the questionnaire inquiry, we get 6 aspects of the factor of the SMEs' performance: product innovation performance, R&D performance, firms' development performance, technology leading-edge performance, R&D funding performance, and performance of policy access. Finally, this paper concluded by examining the relation between the factors of enterprises' size, characteristic & industry and the performance of SMEs in Science Parks.
{"title":"Notice of RetractionEvaluation on the performance of SMEs: Taking the SMEs in Chinese Science Parks as example","authors":"Jin-Ling Pang, Zhen-Ning Yang","doi":"10.1109/ICMLC.2010.5580870","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580870","url":null,"abstract":"With deregulation and globalization, and the impact of these developments on economies worldwide, it has become necessary for China to consider an approach that would further attune its economic engine toward sustained growth. This paper aims to establish a theory framework to evaluate the performance of the small and medium-sized enterprises (SMEs) in Chinese Science Parks. The authors have developed the scale through reading the literature, interviewing in companies. According to the data mining that has been proceeded after the questionnaire inquiry, we get 6 aspects of the factor of the SMEs' performance: product innovation performance, R&D performance, firms' development performance, technology leading-edge performance, R&D funding performance, and performance of policy access. Finally, this paper concluded by examining the relation between the factors of enterprises' size, characteristic & industry and the performance of SMEs in Science Parks.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125878328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5581000
R. Ben, D. Gong, Kevin Meng
Systems engineering is an interdisciplinary engineering management approach that evolves and verifies an integrated set of system solutions to satisfy mission objectives in many areas. But literatures less focused the approach to confirm a strategic consistency and quality on enterprise strategy for engineering background managers. Hence, we explore strategy formulation process from organization hierarchy view through systems engineering methods while emergent strategy is being developed. The whole practice experiences would be extended for shared at knowledge management platform in their organization. Finally, we use an example illustrate strategic quality with a stage-gate analyzer through the above method and focus process reengineering on the ongoing NPD process. We believe that a strong linkage would be well constructed between strategy-makers and executors to improve their great foresight toward a business goal.
{"title":"A knowledge-based systems engineering approach for confirming emergent strategy-making quality","authors":"R. Ben, D. Gong, Kevin Meng","doi":"10.1109/ICMLC.2010.5581000","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5581000","url":null,"abstract":"Systems engineering is an interdisciplinary engineering management approach that evolves and verifies an integrated set of system solutions to satisfy mission objectives in many areas. But literatures less focused the approach to confirm a strategic consistency and quality on enterprise strategy for engineering background managers. Hence, we explore strategy formulation process from organization hierarchy view through systems engineering methods while emergent strategy is being developed. The whole practice experiences would be extended for shared at knowledge management platform in their organization. Finally, we use an example illustrate strategic quality with a stage-gate analyzer through the above method and focus process reengineering on the ongoing NPD process. We believe that a strong linkage would be well constructed between strategy-makers and executors to improve their great foresight toward a business goal.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580597
Jinfang Han, Hui Tian, Z. Meng
In this paper, the sufficient conditions of the robust stability for a class of discrete-time dynamic interval systems with multiple time-delays are obtained using the Lyapunov stability theory and some properties of spectral radius. Using the decomposition of matrix, a kind of equivalent description of the discrete-time dynamic interval systems is presented. Numerical examples have been given to illustrate the effectiveness of the proposed results. Some previously known results are generalized.
{"title":"Critria for robust stability of discrete-time dynamic interval systems with multiple time-delays","authors":"Jinfang Han, Hui Tian, Z. Meng","doi":"10.1109/ICMLC.2010.5580597","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580597","url":null,"abstract":"In this paper, the sufficient conditions of the robust stability for a class of discrete-time dynamic interval systems with multiple time-delays are obtained using the Lyapunov stability theory and some properties of spectral radius. Using the decomposition of matrix, a kind of equivalent description of the discrete-time dynamic interval systems is presented. Numerical examples have been given to illustrate the effectiveness of the proposed results. Some previously known results are generalized.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125398794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-07-11DOI: 10.1109/ICMLC.2010.5580945
Zhenghua Pan
In this paper, the negative relation in fuzzy information is distinguished contradictory negative relation and opposite negative relation, and a character of fuzzy information is discovered that if two opposite concepts are fuzzy concepts, there must exist a “medium” fuzzy concept between them, vice versa. Therefore, we proposed that negative relation in fuzzy information include contradictory negative relation, opposite negative relation and medium negative relation, and that formalization definition of them. Based on this cognition, we defined a new fuzzy set FScom with contradictory negation, opposite negation and medium negation, and discussed characteristics of FScom, operations and their properties in FScom.
{"title":"Fuzzy set with three kinds of negations in fuzzy knowledge processing","authors":"Zhenghua Pan","doi":"10.1109/ICMLC.2010.5580945","DOIUrl":"https://doi.org/10.1109/ICMLC.2010.5580945","url":null,"abstract":"In this paper, the negative relation in fuzzy information is distinguished contradictory negative relation and opposite negative relation, and a character of fuzzy information is discovered that if two opposite concepts are fuzzy concepts, there must exist a “medium” fuzzy concept between them, vice versa. Therefore, we proposed that negative relation in fuzzy information include contradictory negative relation, opposite negative relation and medium negative relation, and that formalization definition of them. Based on this cognition, we defined a new fuzzy set FScom with contradictory negation, opposite negation and medium negation, and discussed characteristics of FScom, operations and their properties in FScom.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116568942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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