Pub Date : 2013-09-30DOI: 10.1142/S0219691313500355
J. Qiu, Zirui Xing, Li Li, Mohan Yang, Yi Li
This paper focuses on the problem of robust H∞ filtering for a class of nonlinear uncertain singular systems with time-varying delay. First of all, the dermition of robust H∞ filter is given. Considering the nonlinear disturbance link to uncertain singular systems with time-varying delay effects, we come up with the design idea of full order robust H∞ filter based on the Lyapunov stability theory. Under the condition that nonlinear uncertain functions satisfy Lipschitz condition, using Lyapunov stability theory and linear matrix inequality (LMI) methods, a sufficient condition of such nonlinear uncertain delayed filtering error singular systems which are asymptotically stable and satisfy the robust H∞ performance is obtained. Finally, two numerical examples are given to show the applicability of the proposed method.
{"title":"ROBUST H∞ filtering for a class of nonlinear uncertain singular systems with time-varying delay","authors":"J. Qiu, Zirui Xing, Li Li, Mohan Yang, Yi Li","doi":"10.1142/S0219691313500355","DOIUrl":"https://doi.org/10.1142/S0219691313500355","url":null,"abstract":"This paper focuses on the problem of robust H∞ filtering for a class of nonlinear uncertain singular systems with time-varying delay. First of all, the dermition of robust H∞ filter is given. Considering the nonlinear disturbance link to uncertain singular systems with time-varying delay effects, we come up with the design idea of full order robust H∞ filter based on the Lyapunov stability theory. Under the condition that nonlinear uncertain functions satisfy Lipschitz condition, using Lyapunov stability theory and linear matrix inequality (LMI) methods, a sufficient condition of such nonlinear uncertain delayed filtering error singular systems which are asymptotically stable and satisfy the robust H∞ performance is obtained. Finally, two numerical examples are given to show the applicability of the proposed method.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121142386","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 : 2012-11-26DOI: 10.1109/ICMLC.2012.6359484
C. Jettanasen, J. Klomjit, S. Bunjongjit, A. Ngaopitakkul, B. Suechoey, N. Suttisinthong, B. Seewirote
This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and back-propagation neural network (BPNN) for detecting and identifying internal winding fault of three-phase two-winding transformer. The maximum ratio obtained from division algorithm between coefficient from DWT of differential current and zero sequence for post-fault differential current waveforms is employed as an input for the training pattern in order to discriminate between internal fault and external short circuit. Various cases studies based on Thailand electricity transmission and distribution systems have been investigated so that the algorithm can be implemented. Results show that the proposed technique has good accuracy to detect fault and to identify its position in the considered system.
{"title":"Discriminati on between external short circuit and internal winding fault in power transformer using discrete wavelet transform and back-propagation neural network","authors":"C. Jettanasen, J. Klomjit, S. Bunjongjit, A. Ngaopitakkul, B. Suechoey, N. Suttisinthong, B. Seewirote","doi":"10.1109/ICMLC.2012.6359484","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359484","url":null,"abstract":"This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and back-propagation neural network (BPNN) for detecting and identifying internal winding fault of three-phase two-winding transformer. The maximum ratio obtained from division algorithm between coefficient from DWT of differential current and zero sequence for post-fault differential current waveforms is employed as an input for the training pattern in order to discriminate between internal fault and external short circuit. Various cases studies based on Thailand electricity transmission and distribution systems have been investigated so that the algorithm can be implemented. Results show that the proposed technique has good accuracy to detect fault and to identify its position in the considered system.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114320896","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 : 2012-11-26DOI: 10.1109/ICMLC.2012.6359532
Jian-Ru Zheng, Guo-Li Zhang, Hua Zuo
The inertia weight is an important parameter in the Particle Swarm Optimization algorithm, which controls the degree of influence of the contemporary speed to the next generation and plays a role of balancing global search and local search. In the iteration process, the inertia weight will decrease nonlinearly at the early stage and decrease linearly at the later stage. The improved algorithm will effectively prevent premature convergence of the algorithm. The simulation results show that the improved algorithm is superior to the particle swarm optimization algorithm of the linear decreasing weight.
{"title":"Hybrid linear and nonlinear weight Particle Swarm Optimization algorithm","authors":"Jian-Ru Zheng, Guo-Li Zhang, Hua Zuo","doi":"10.1109/ICMLC.2012.6359532","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359532","url":null,"abstract":"The inertia weight is an important parameter in the Particle Swarm Optimization algorithm, which controls the degree of influence of the contemporary speed to the next generation and plays a role of balancing global search and local search. In the iteration process, the inertia weight will decrease nonlinearly at the early stage and decrease linearly at the later stage. The improved algorithm will effectively prevent premature convergence of the algorithm. The simulation results show that the improved algorithm is superior to the particle swarm optimization algorithm of the linear decreasing weight.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127228883","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 : 2012-11-26DOI: 10.1109/ICMLC.2012.6359491
D. D. Wang, Hong Yan, Qiang Be
Transcriptional regulation is an important component in genetics, with transcriptional factors (TFs) and regulatory DNA regions involved in. In this paper, we observe cooperativity between two significant TFs Oct-1 and Sox-2 at their enhancer DNA binding sites in collective motions. Normal mode analysis (NMA) is carried out to simulate the motions of two POU/HMG/DNA complexes, with molecular dynamics (MD) results used as a comparison. We have discovered several types of cooperative interactions between the two TFs in these obtained motions.
{"title":"Transcriptional cooperativity in molecular dynamics based on normal mode analysis","authors":"D. D. Wang, Hong Yan, Qiang Be","doi":"10.1109/ICMLC.2012.6359491","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359491","url":null,"abstract":"Transcriptional regulation is an important component in genetics, with transcriptional factors (TFs) and regulatory DNA regions involved in. In this paper, we observe cooperativity between two significant TFs Oct-1 and Sox-2 at their enhancer DNA binding sites in collective motions. Normal mode analysis (NMA) is carried out to simulate the motions of two POU/HMG/DNA complexes, with molecular dynamics (MD) results used as a comparison. We have discovered several types of cooperative interactions between the two TFs in these obtained motions.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178665","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359498
Fan-Hui Kong
This paper presents some explorations and studies on image retrieval. Firstly, RGB color space is converted to HSV color space for feature extraction. Then, the texture features are obtained by using wavelet, which are combined with some color features based on wavelet transform. Finally, the multi-features generated by Gaussian Mixture Model (GMM) are employed to an image retrieval algorithm. The experimental results on an image database show the effectiveness and competitive performance of the GMM-based image retrieval algorithm.
{"title":"Image retrieval based on Gaussian Mixture Model","authors":"Fan-Hui Kong","doi":"10.1109/ICMLC.2012.6359498","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359498","url":null,"abstract":"This paper presents some explorations and studies on image retrieval. Firstly, RGB color space is converted to HSV color space for feature extraction. Then, the texture features are obtained by using wavelet, which are combined with some color features based on wavelet transform. Finally, the multi-features generated by Gaussian Mixture Model (GMM) are employed to an image retrieval algorithm. The experimental results on an image database show the effectiveness and competitive performance of the GMM-based image retrieval algorithm.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115229605","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359635
Young-Long Chen, Yu-Cheng Lin, Neng-Chung Wang
In Wireless sensor networks (WSNs), the energy of sensor node is finite, it's an important issue that how to reduce the energy consumption and extend the lifetime of entire network. In power-efficient gathering in sensor information systems (pEGASIS) topology architecture, the energy consumption of each sensor node is fewer and more average than low-energy adaptive clustering hierarchy (LEACH). Accordingly, we combine the PEGASIS topology architecture and intersection-based coverage algorithm (IBCA) to decrease the energy consumption. First of all, we find out the redundant sensor nodes to enter to the sleep mode by means of IBCA. Then, it builds the PEGASIS topology architecture by active sensor nodes which are not chosen to enter to sleep mode by IBCA. Through a series of simulations, the performances of our novel scheme outperform LEACH with PBCA in terms of energy consumption, number of alive nodes and sensing areas.
{"title":"An intersection-based coverage algorithm for PEGASIS architecture in Wireless sensor networks","authors":"Young-Long Chen, Yu-Cheng Lin, Neng-Chung Wang","doi":"10.1109/ICMLC.2012.6359635","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359635","url":null,"abstract":"In Wireless sensor networks (WSNs), the energy of sensor node is finite, it's an important issue that how to reduce the energy consumption and extend the lifetime of entire network. In power-efficient gathering in sensor information systems (pEGASIS) topology architecture, the energy consumption of each sensor node is fewer and more average than low-energy adaptive clustering hierarchy (LEACH). Accordingly, we combine the PEGASIS topology architecture and intersection-based coverage algorithm (IBCA) to decrease the energy consumption. First of all, we find out the redundant sensor nodes to enter to the sleep mode by means of IBCA. Then, it builds the PEGASIS topology architecture by active sensor nodes which are not chosen to enter to sleep mode by IBCA. Through a series of simulations, the performances of our novel scheme outperform LEACH with PBCA in terms of energy consumption, number of alive nodes and sensing areas.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115459133","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359585
Tianshi Yu, Zhong Ji, Peiguang Jing, Yuting Su
Feature dimensionality reduction is an important step for data processing, which is used to reduce data's dimensionalities in many areas. In this paper, we apply dimensionality reduction to image search reranking. As a supervised dimensionality reduction method, Linear Discriminant Analysis (LDA) performs well in classification applications, but is not the case for ranking tasks. Firstly, it does not take the relevance degrees into consideration, which is important for ranking problem. Secondly, owing to the supervised nature of LDA, a plenty of labeled samples are required, which are often costly and difficult to obtain. Therefore, based on LDA, we propose an improved method named Ranking Linear Discriminant Analysis (RLDA) by using the relevance degrees as labels. Meanwhile, both labeled and unlabeled samples are utilized so that it is a semi-supervised approach. Experiments are carried out to confirm the good performance of the proposed algorithm.
{"title":"Image search reranking with Ranking Linear Discriminant Analysis","authors":"Tianshi Yu, Zhong Ji, Peiguang Jing, Yuting Su","doi":"10.1109/ICMLC.2012.6359585","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359585","url":null,"abstract":"Feature dimensionality reduction is an important step for data processing, which is used to reduce data's dimensionalities in many areas. In this paper, we apply dimensionality reduction to image search reranking. As a supervised dimensionality reduction method, Linear Discriminant Analysis (LDA) performs well in classification applications, but is not the case for ranking tasks. Firstly, it does not take the relevance degrees into consideration, which is important for ranking problem. Secondly, owing to the supervised nature of LDA, a plenty of labeled samples are required, which are often costly and difficult to obtain. Therefore, based on LDA, we propose an improved method named Ranking Linear Discriminant Analysis (RLDA) by using the relevance degrees as labels. Meanwhile, both labeled and unlabeled samples are utilized so that it is a semi-supervised approach. Experiments are carried out to confirm the good performance of the proposed algorithm.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115459237","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359632
Chun-Yuan Lo, Kun-Ming Yu, Ouyang Wen, Chang-Hsing Lee
Traditional recommendation systems are mostly based on similarity discrimination which requires sufficient data and recommends high correlated items. It becomes very difficult to accurately recommend products when data are not enough. Thus, the research about Cold Start Problem becomes important which emphasizes in effective item recommendation when too little data are provided. In this work, we propose a novel method called Location-Time based Recommendation System (LTRS) to address the Cold Start Problem with location and time as the initial factors together with degree of membership from fuzzy theory to produce more effective and precise item recommendation. From experimental results, LTRS improves the effectiveness of item recommendation, not only in normal situations but also in Cold Start scenarios.
{"title":"Design a location-time based ethnic advertising recommendation system using degree of memberships","authors":"Chun-Yuan Lo, Kun-Ming Yu, Ouyang Wen, Chang-Hsing Lee","doi":"10.1109/ICMLC.2012.6359632","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359632","url":null,"abstract":"Traditional recommendation systems are mostly based on similarity discrimination which requires sufficient data and recommends high correlated items. It becomes very difficult to accurately recommend products when data are not enough. Thus, the research about Cold Start Problem becomes important which emphasizes in effective item recommendation when too little data are provided. In this work, we propose a novel method called Location-Time based Recommendation System (LTRS) to address the Cold Start Problem with location and time as the initial factors together with degree of membership from fuzzy theory to produce more effective and precise item recommendation. From experimental results, LTRS improves the effectiveness of item recommendation, not only in normal situations but also in Cold Start scenarios.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669434","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359660
Kazunori Wagatsuma, Y. Goto, Jingde Cheng
Formal analysis of cryptographic protocols is necessary to assure security before using it. In traditional approaches, analysts have to specify security goals or necessary conditions of the analysis firstly. However, it is difficult to specify all security goals or necessary conditions. A reasoning approach without the problem was proposed, but its concrete method is not established. In this paper, as the first step to elaborate the reasoning approach of cryptographic protocols, we analyzed Needham-Schroeder Shared-Key protocol by reasoning based on deontic relevant logic. By the case study, we show that the reasoning approach can find vulnerability of the cryptographic protocol as well as traditional approach, and can expect to find new vulnerability that has not been recognized. Then, we discuss about the concrete method for formal analysis of cryptographic protocols by the reasoning approach.
{"title":"Formal analysis of cryptographic protocols by reasoning based on deontic relevant logic: A case study in Needham-Schroeder Shared-Key protocol","authors":"Kazunori Wagatsuma, Y. Goto, Jingde Cheng","doi":"10.1109/ICMLC.2012.6359660","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359660","url":null,"abstract":"Formal analysis of cryptographic protocols is necessary to assure security before using it. In traditional approaches, analysts have to specify security goals or necessary conditions of the analysis firstly. However, it is difficult to specify all security goals or necessary conditions. A reasoning approach without the problem was proposed, but its concrete method is not established. In this paper, as the first step to elaborate the reasoning approach of cryptographic protocols, we analyzed Needham-Schroeder Shared-Key protocol by reasoning based on deontic relevant logic. By the case study, we show that the reasoning approach can find vulnerability of the cryptographic protocol as well as traditional approach, and can expect to find new vulnerability that has not been recognized. Then, we discuss about the concrete method for formal analysis of cryptographic protocols by the reasoning approach.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127443930","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 : 2012-07-15DOI: 10.1109/ICMLC.2012.6359609
Yung-Sheng Chen, Ming-Te Chao
The classical and potential thinning issues such as bias effect, boundary noise immunity, and even rotation invariant, are quite worthy of studying in image processing field. In this paper, based on the fundamental medial axis transformation (MAT) concept, we developed an approach including extraction of medial axis with symmetry information, clustering, linking, and post rule-based thinning to investigate the possibility of reducing the bias effect and increasing the boundary noise immunity. A rotation invariant rule-based thinning algorithm was adopted for experimental comparisons. The primary result confirms that the proposed approach is one of the feasible directions to overcome these issues.
{"title":"Skeletonization based on the medial-axis and symmetry information","authors":"Yung-Sheng Chen, Ming-Te Chao","doi":"10.1109/ICMLC.2012.6359609","DOIUrl":"https://doi.org/10.1109/ICMLC.2012.6359609","url":null,"abstract":"The classical and potential thinning issues such as bias effect, boundary noise immunity, and even rotation invariant, are quite worthy of studying in image processing field. In this paper, based on the fundamental medial axis transformation (MAT) concept, we developed an approach including extraction of medial axis with symmetry information, clustering, linking, and post rule-based thinning to investigate the possibility of reducing the bias effect and increasing the boundary noise immunity. A rotation invariant rule-based thinning algorithm was adopted for experimental comparisons. The primary result confirms that the proposed approach is one of the feasible directions to overcome these issues.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124839337","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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