Analysis of contemporary information security systems (ISS) and especially the case of intrusion detection systems (IDS) shows us few character negative features and drawbacks. Original methods and combined anomaly and signature IDS applications are presented in the paper. Human-centered methods INCONSISTENCY, FUNNEL, CALEIDOSCOPE and CROSSWORD interact on a competitive principle and are controlled by a synthetic metamethod SMM. A research is going on for the possibilities of including other machine learning and data mining methods under the general control of SMM. Their applications aim at computational discovery and knowledge acquisition. It is reinforced by identification and resolution of contradictions, self-learning and other methods for analysis of different types of models from the ISS domain. The complexity of application results is considered. The data analysis in the field frequently needs an act of creation especially if it is applied in a knowledge-poor environment. It is shown that even in this case the creative processes are based on applications of clear and well-formalized methods.
{"title":"Novel intrusion prevention and detection methods","authors":"V. Jotsov","doi":"10.1109/IS.2008.4670526","DOIUrl":"https://doi.org/10.1109/IS.2008.4670526","url":null,"abstract":"Analysis of contemporary information security systems (ISS) and especially the case of intrusion detection systems (IDS) shows us few character negative features and drawbacks. Original methods and combined anomaly and signature IDS applications are presented in the paper. Human-centered methods INCONSISTENCY, FUNNEL, CALEIDOSCOPE and CROSSWORD interact on a competitive principle and are controlled by a synthetic metamethod SMM. A research is going on for the possibilities of including other machine learning and data mining methods under the general control of SMM. Their applications aim at computational discovery and knowledge acquisition. It is reinforced by identification and resolution of contradictions, self-learning and other methods for analysis of different types of models from the ISS domain. The complexity of application results is considered. The data analysis in the field frequently needs an act of creation especially if it is applied in a knowledge-poor environment. It is shown that even in this case the creative processes are based on applications of clear and well-formalized methods.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122212987","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}
Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.
{"title":"Volterra model predictive control of a lyophilization plant","authors":"Yancho V. Todorov, Tsvetan D. Tsvetkov","doi":"10.1109/IS.2008.4670467","DOIUrl":"https://doi.org/10.1109/IS.2008.4670467","url":null,"abstract":"Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130370794","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}
Many statistical algorithms have been proposed for software quality prediction of fault-prone and non fault-prone program modules. The main goal of these algorithms is the improvement of software development processes. In this paper, we introduce a new software prediction algorithm. Our approach is purely Bayesian and is based on finite Dirichlet mixture models. The implementation of the Bayesian approach is done through the use of the Gibbs sampler. Experimental results are presented using simulated data, and a real application for software modules classification is also included.
{"title":"A Bayesian approach for software quality prediction","authors":"N. Bouguila, J. Wang, A. Ben Hamza","doi":"10.1109/IS.2008.4670508","DOIUrl":"https://doi.org/10.1109/IS.2008.4670508","url":null,"abstract":"Many statistical algorithms have been proposed for software quality prediction of fault-prone and non fault-prone program modules. The main goal of these algorithms is the improvement of software development processes. In this paper, we introduce a new software prediction algorithm. Our approach is purely Bayesian and is based on finite Dirichlet mixture models. The implementation of the Bayesian approach is done through the use of the Gibbs sampler. Experimental results are presented using simulated data, and a real application for software modules classification is also included.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130691966","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}
Collaboration among enterprises in a dynamic environment makes the actors to concentrate on their respective core competences and allow provision and sharing of expertise, resources, and skills for taking advantages and better respond to business opportunities. The coming together of such organizations, usually enhanced by computer network, is referred to as virtual enterprise (VE) or task group. This partnership is only possible if the systems in the various associated organizations can process the data in one another. A major challenge in the enterprise collaborative system that has attracted many research efforts in the recent past is semantic interoperability. This collaborative-based market place requires among others common conceptualization and meaningful data exchange. Effective collaboration among VE members is a major key to the accomplishment of this noble objective. For this interoperability to be effective, we propose in this paper an ontology-based middleware framework ldquoOntology Gatewayrdquo used by players in such situation to exchange information needed to carry out the process. The middleware not only assists in the formation of VE by interested members, but also facilitates semantic interpretability among task groups.
{"title":"Ontology based semantic interoperability facilitator among task group","authors":"M. Pasha, Mukaila Rahman, H. Ahmad","doi":"10.1109/IS.2008.4670476","DOIUrl":"https://doi.org/10.1109/IS.2008.4670476","url":null,"abstract":"Collaboration among enterprises in a dynamic environment makes the actors to concentrate on their respective core competences and allow provision and sharing of expertise, resources, and skills for taking advantages and better respond to business opportunities. The coming together of such organizations, usually enhanced by computer network, is referred to as virtual enterprise (VE) or task group. This partnership is only possible if the systems in the various associated organizations can process the data in one another. A major challenge in the enterprise collaborative system that has attracted many research efforts in the recent past is semantic interoperability. This collaborative-based market place requires among others common conceptualization and meaningful data exchange. Effective collaboration among VE members is a major key to the accomplishment of this noble objective. For this interoperability to be effective, we propose in this paper an ontology-based middleware framework ldquoOntology Gatewayrdquo used by players in such situation to exchange information needed to carry out the process. The middleware not only assists in the formation of VE by interested members, but also facilitates semantic interpretability among task groups.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131215068","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}
A new complete procedure for the selection of pruning threshold in MIMO (multiple input multiple output) feedforward artificial neural networks (FANN) is presented. It is based on the evaluation of a local sensitivity index calculated with respect of any single output of the network. Special emphasis is given to a particular class of neural networks with multiple heterogeneous outputs. It will be shown how to take into account of the non-homogeneous nature of the outputs by deriving an ldquoimportance indexrdquo from the nonlinear correlation of data. An example of the proposed method will be shown by the development of a neural architecture devoted to a specific multi-output inversion system.
{"title":"A pruning method for multiple heterogeneous output neural networks","authors":"F. Grasso, A. Luchetta, S. Manetti","doi":"10.1109/IS.2008.4670442","DOIUrl":"https://doi.org/10.1109/IS.2008.4670442","url":null,"abstract":"A new complete procedure for the selection of pruning threshold in MIMO (multiple input multiple output) feedforward artificial neural networks (FANN) is presented. It is based on the evaluation of a local sensitivity index calculated with respect of any single output of the network. Special emphasis is given to a particular class of neural networks with multiple heterogeneous outputs. It will be shown how to take into account of the non-homogeneous nature of the outputs by deriving an ldquoimportance indexrdquo from the nonlinear correlation of data. An example of the proposed method will be shown by the development of a neural architecture devoted to a specific multi-output inversion system.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128157385","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}
The paper intends to present a modeling philosophy, that allows a global view of a generic manufacturing enterprise behavior, combining managerial and control approaches. The main objective of the assessment is to design a system architecture for manufacturing that will be able to develop an intelligent comportment displaying characteristics like environment adaptability, problem solving and learning from experience. The foundations of this approach are mainly knowledge management and control engineering techniques, as well as agent-based architectures.
{"title":"Towards a new generation of intelligent manufacturing systems","authors":"I. Dumitrache, S. Caramihai","doi":"10.1109/IS.2008.4670422","DOIUrl":"https://doi.org/10.1109/IS.2008.4670422","url":null,"abstract":"The paper intends to present a modeling philosophy, that allows a global view of a generic manufacturing enterprise behavior, combining managerial and control approaches. The main objective of the assessment is to design a system architecture for manufacturing that will be able to develop an intelligent comportment displaying characteristics like environment adaptability, problem solving and learning from experience. The foundations of this approach are mainly knowledge management and control engineering techniques, as well as agent-based architectures.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133431425","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}
P. Papazoglou, Dimitrios Alexios Karras, R. C. Papademetriou
Channel allocation in wireless communication systems is one of the fundamental issues. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. On the other hand, the ant colony optimization approach has been proposed for solving optimization problems but this approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. In this paper, a comprehensive heuristic approach for solving the channel allocation problem based on intelligent techniques such as multi-agents and ant colony optimization is proposed. Moreover, important implementation issues such as thread execution sequence are also presented. Finally, the simulation results show the performance improvement of the proposed ant colony optimization algorithm as well as the multi-agent modeling approach.
{"title":"On the implementation of ant colony optimization scheme for improved channel allocation in wireless communications","authors":"P. Papazoglou, Dimitrios Alexios Karras, R. C. Papademetriou","doi":"10.1109/IS.2008.4670437","DOIUrl":"https://doi.org/10.1109/IS.2008.4670437","url":null,"abstract":"Channel allocation in wireless communication systems is one of the fundamental issues. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. On the other hand, the ant colony optimization approach has been proposed for solving optimization problems but this approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. In this paper, a comprehensive heuristic approach for solving the channel allocation problem based on intelligent techniques such as multi-agents and ant colony optimization is proposed. Moreover, important implementation issues such as thread execution sequence are also presented. Finally, the simulation results show the performance improvement of the proposed ant colony optimization algorithm as well as the multi-agent modeling approach.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131779647","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}
Fuzzy linear regression model with crisp input, fuzzy output is investigated. A least absolute deviation approach, by introducing and applying a new metric on the space of fuzzy numbers, is developed. In addition, a new capability index is proposed to evaluate the proposed model.
{"title":"Fuzzy least absolutes regression","authors":"S. M. Taheri, M. Kelkinnama","doi":"10.1109/IS.2008.4670509","DOIUrl":"https://doi.org/10.1109/IS.2008.4670509","url":null,"abstract":"Fuzzy linear regression model with crisp input, fuzzy output is investigated. A least absolute deviation approach, by introducing and applying a new metric on the space of fuzzy numbers, is developed. In addition, a new capability index is proposed to evaluate the proposed model.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128559729","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}
A. Fetais, D. Al-Abdulla, A. Alatawnah, S. Alkhulaifi, T. El-Fouly
The rapid improvement in latest technologies motivates individuals to progress in their societies. Fast and worthy can be significant titles for the demands of this modern life. And because of technology improvements, there arenpsilat any excuses for slow processing of jobs and duties. Everyone at any position wants things to be done in the shortest time. Therefore, attempts to apply instant, fast and convenient processing methods became a common aim. Taking an example of administrative services illustrates the need of such attempts. In order to get an authenticated application or document, this consumes a lot of effort in reviewing many employees and getting many administratorspsila approvals. Also, it might need transactions from one place to place, not to mention that a person may need more than one application. In fact, it becomes a common situation to hear complaints from applicants, which leads to thinking of an effective solution. Saving time, minimizing customerpsilas transactions, and digitizing life are all core targets in such condition. Moreover, these targets are the significant requirements for modern life evolution, and this work is considered as the first step for approaching this goal.
{"title":"Digital government service machine DGSM","authors":"A. Fetais, D. Al-Abdulla, A. Alatawnah, S. Alkhulaifi, T. El-Fouly","doi":"10.1109/IS.2008.4670524","DOIUrl":"https://doi.org/10.1109/IS.2008.4670524","url":null,"abstract":"The rapid improvement in latest technologies motivates individuals to progress in their societies. Fast and worthy can be significant titles for the demands of this modern life. And because of technology improvements, there arenpsilat any excuses for slow processing of jobs and duties. Everyone at any position wants things to be done in the shortest time. Therefore, attempts to apply instant, fast and convenient processing methods became a common aim. Taking an example of administrative services illustrates the need of such attempts. In order to get an authenticated application or document, this consumes a lot of effort in reviewing many employees and getting many administratorspsila approvals. Also, it might need transactions from one place to place, not to mention that a person may need more than one application. In fact, it becomes a common situation to hear complaints from applicants, which leads to thinking of an effective solution. Saving time, minimizing customerpsilas transactions, and digitizing life are all core targets in such condition. Moreover, these targets are the significant requirements for modern life evolution, and this work is considered as the first step for approaching this goal.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128194219","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}
Recognition of specific functionally-important DNA sequence fragments is considered one of the most important problems in bioinformatics. One type of such fragments are promoters, i.e., short regulatory DNA sequences located upstream of a gene. Detection of promoters in DNA sequences is important for successful gene prediction. In this paper, a machine learning method, called support vector machine (SVM), is used for classification of DNA sequences and promoter recognition. For optimal classification, 11 rules for mapping of DNA sequences into binary SVM feature space are analyzed. Classification is performed using a power series kernel function. Kernel parameters are optimized using a modification of the Nelder-Mead (downhill simplex) optimization method. The results of classification for drosophila and human sequence datasets are presented.
{"title":"Analysis of binary feature mapping rules for promoter recognition in imbalanced DNA sequence datasets using Support Vector Machine","authors":"Robertas Damaševičius","doi":"10.1109/IS.2008.4670503","DOIUrl":"https://doi.org/10.1109/IS.2008.4670503","url":null,"abstract":"Recognition of specific functionally-important DNA sequence fragments is considered one of the most important problems in bioinformatics. One type of such fragments are promoters, i.e., short regulatory DNA sequences located upstream of a gene. Detection of promoters in DNA sequences is important for successful gene prediction. In this paper, a machine learning method, called support vector machine (SVM), is used for classification of DNA sequences and promoter recognition. For optimal classification, 11 rules for mapping of DNA sequences into binary SVM feature space are analyzed. Classification is performed using a power series kernel function. Kernel parameters are optimized using a modification of the Nelder-Mead (downhill simplex) optimization method. The results of classification for drosophila and human sequence datasets are presented.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121929513","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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