D. K. Iakovidis, S. Tsevas, D. Maroulis, A. Polydorou
Capsule endoscopy is a non-invasive imaging technique commonly used for screening of the entire small intestine. It is performed by a wireless swallowable endoscopic capsule capable of transmitting thousands of video frames per examination. The visual inspection of the vast amount of images acquired during such an examination is a subjective and highly time consuming task even for experienced gastroenterologists. In this paper we propose a novel approach to the reduction of the number of the video frames to be inspected so as to enable faster inspection of the endoscopic video. It is based on symmetric non-negative matrix factorisation initialised by the fuzzy c-means algorithm and it is supported by non-negative Lagrangian relaxation to extract a subset of video frames containing the most representative scenes from a whole endoscopic examination. The experimental evaluation of the proposed approach was tested on annotated endoscopic videos with frames displaying ulcers, bleedings and normal tissues from various sites in the small intestine. The results demonstrate that the video summary produced consists of representative frames from all the abnormal findings and the normal tissues of the input video.
{"title":"Unsupervised summarisation of capsule endoscopy video","authors":"D. K. Iakovidis, S. Tsevas, D. Maroulis, A. Polydorou","doi":"10.1109/IS.2008.4670414","DOIUrl":"https://doi.org/10.1109/IS.2008.4670414","url":null,"abstract":"Capsule endoscopy is a non-invasive imaging technique commonly used for screening of the entire small intestine. It is performed by a wireless swallowable endoscopic capsule capable of transmitting thousands of video frames per examination. The visual inspection of the vast amount of images acquired during such an examination is a subjective and highly time consuming task even for experienced gastroenterologists. In this paper we propose a novel approach to the reduction of the number of the video frames to be inspected so as to enable faster inspection of the endoscopic video. It is based on symmetric non-negative matrix factorisation initialised by the fuzzy c-means algorithm and it is supported by non-negative Lagrangian relaxation to extract a subset of video frames containing the most representative scenes from a whole endoscopic examination. The experimental evaluation of the proposed approach was tested on annotated endoscopic videos with frames displaying ulcers, bleedings and normal tissues from various sites in the small intestine. The results demonstrate that the video summary produced consists of representative frames from all the abnormal findings and the normal tissues of the input video.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"59 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":"128799084","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}
Index structures for nearest neighbor search in high-dimensional metric space are mostly built by partitioning the data set based on distances to certain reference point(s). Using the constructed index, the search is limited to a smaller number of the partitions in a way to avoid exhaustive search. However, the approaches already described in the literature either ignore the property of the data distribution or produce non-disjoint partitions; this greatly aspects the search efficiency. In this paper, we propose a new index structure, which overcomes the above disadvantages. The proposed tree structure is constructed by recursively dividing the data set into a nested set of approximate equivalence classes. We also propose a new reference point selection method using principal component analysis (PCA). The conducted analysis and the reported test results demonstrate that the proposed index structure, empowered by the PCA-based reference selection strategy, gives an optimal partition of the data set and greatly improves the search efficiency compared to the VP-tree, which is one of the approaches well documented in the literature.
{"title":"Novel approach for nearest neighbor search in high dimensional space","authors":"Ming Zhang, R. Alhajj","doi":"10.1109/IS.2008.4670504","DOIUrl":"https://doi.org/10.1109/IS.2008.4670504","url":null,"abstract":"Index structures for nearest neighbor search in high-dimensional metric space are mostly built by partitioning the data set based on distances to certain reference point(s). Using the constructed index, the search is limited to a smaller number of the partitions in a way to avoid exhaustive search. However, the approaches already described in the literature either ignore the property of the data distribution or produce non-disjoint partitions; this greatly aspects the search efficiency. In this paper, we propose a new index structure, which overcomes the above disadvantages. The proposed tree structure is constructed by recursively dividing the data set into a nested set of approximate equivalence classes. We also propose a new reference point selection method using principal component analysis (PCA). The conducted analysis and the reported test results demonstrate that the proposed index structure, empowered by the PCA-based reference selection strategy, gives an optimal partition of the data set and greatly improves the search efficiency compared to the VP-tree, which is one of the approaches well documented in the literature.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"00 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":"121071639","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}
Model predictive control (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy model is suggested as a means to model the plant with nonlinearities depending on the operating region. The developed model is used as a predictive model for a parallel distributed model predictive control algorithm. In this paper, the parallel distributed neuro-fuzzy model predictive controller has been proposed to control a non-linear control system of a hydro turbine generator. The proposed technique has been tested and evaluated using this simulated industrial plant.
{"title":"Parallel distributed neuro-fuzzy model predictive controller applied to a hydro turbine generator","authors":"M. Petrov, A. Taneva, T. Puleva, S. Ahmed","doi":"10.1109/IS.2008.4670455","DOIUrl":"https://doi.org/10.1109/IS.2008.4670455","url":null,"abstract":"Model predictive control (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy model is suggested as a means to model the plant with nonlinearities depending on the operating region. The developed model is used as a predictive model for a parallel distributed model predictive control algorithm. In this paper, the parallel distributed neuro-fuzzy model predictive controller has been proposed to control a non-linear control system of a hydro turbine generator. The proposed technique has been tested and evaluated using this simulated industrial plant.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"75 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":"121103376","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}
In the design and performance evaluation of practical HF communication systems, it is essential to use procedures that assess the detrimental effect of interference from other users in a near real time mode. These procedures can extend system capability to estimate interference background, in the context of real time channel evaluation (RTCE) in order to advise operators on typical interference occupancy levels and to improve the quality and reliability of radio communication services through adaptation of communication parameters. In this study a Neural Network approach is proposed for the short-term forecasting of the likelihood of interference experienced by HF groundwave communication systems. In particular this paper describes the development of neural network models to indicate the degree of spectral congestion in frequency allocations in the lowest part of the HF spectrum (1.6 to 4 MHz) 1 hour in advance, as a function of the present congestion level, time of day, season, and field strength threshold. The modeled parameter, congestion, is defined as the relative number of narrow frequency channels (1 kHz wide) within a frequency allocation that have signals above a given threshold.
{"title":"Short-term forecasting of the likelihood of interference to groundwave users in the lowest part of the HF spectrum","authors":"H. Haralambous, H. Papadopoulos","doi":"10.1109/IS.2008.4670548","DOIUrl":"https://doi.org/10.1109/IS.2008.4670548","url":null,"abstract":"In the design and performance evaluation of practical HF communication systems, it is essential to use procedures that assess the detrimental effect of interference from other users in a near real time mode. These procedures can extend system capability to estimate interference background, in the context of real time channel evaluation (RTCE) in order to advise operators on typical interference occupancy levels and to improve the quality and reliability of radio communication services through adaptation of communication parameters. In this study a Neural Network approach is proposed for the short-term forecasting of the likelihood of interference experienced by HF groundwave communication systems. In particular this paper describes the development of neural network models to indicate the degree of spectral congestion in frequency allocations in the lowest part of the HF spectrum (1.6 to 4 MHz) 1 hour in advance, as a function of the present congestion level, time of day, season, and field strength threshold. The modeled parameter, congestion, is defined as the relative number of narrow frequency channels (1 kHz wide) within a frequency allocation that have signals above a given threshold.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"41 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":"116559268","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}
In this paper we present a kinematic description of a six-legged laboratory prototype robot and control algorithm for tracking a target from the robot using active camera. The hexapod hardware platform with fluidic muscle is described. We present an algorithm that provides automatic control of a tilt camera to follow a target and keep its image centered in the camera view. An error coordinate defined in the image plane and representing the target offset with respect to the center of the image is used for camera control. Simulation results are presented to illustrate the effectiveness of the proposed control law.
{"title":"Active target tracking from a six-legged robot","authors":"M. Milushev, P. Petrov, O. Boumbarov","doi":"10.1109/IS.2008.4670426","DOIUrl":"https://doi.org/10.1109/IS.2008.4670426","url":null,"abstract":"In this paper we present a kinematic description of a six-legged laboratory prototype robot and control algorithm for tracking a target from the robot using active camera. The hexapod hardware platform with fluidic muscle is described. We present an algorithm that provides automatic control of a tilt camera to follow a target and keep its image centered in the camera view. An error coordinate defined in the image plane and representing the target offset with respect to the center of the image is used for camera control. Simulation results are presented to illustrate the effectiveness of the proposed control law.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"26 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":"125157798","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 presents method, algorithm and software in MATLAB and Java for solving various optimization problems when the linear objective function is subject to fuzzy linear system of equations or fuzzy linear systems of inequalities as constraint.
{"title":"Software for optimization of linear objective function with fuzzy relational constraint","authors":"K. Peeva, Z. Zahariev, I. Atanasov","doi":"10.1109/IS.2008.4670459","DOIUrl":"https://doi.org/10.1109/IS.2008.4670459","url":null,"abstract":"The paper presents method, algorithm and software in MATLAB and Java for solving various optimization problems when the linear objective function is subject to fuzzy linear system of equations or fuzzy linear systems of inequalities as constraint.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"3 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":"131198985","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}
J. Sarraipa, J. Silva, R. Jardim-Gonçalves, A. Monteiro
Ontologies facilitate the computational understanding, communication and seamless interoperability between people and organizations. They allow key concepts and terms relevant to a given domain to be identified and defined in an open and unambiguous way. Therefore, ontologies facilitate the use and exchange of data, information, and knowledge among people and organizations, towards intelligent systems interoperability. Tasks on distributed and heterogeneous systems demand support from more than one ontology. Multiple ontologies need to be accessed by the same, but also different systems. The distributed nature of ontology development has led to dissimilar ontologies for the same or overlapping domains. Thus, various parties with different ontologies often do not understand each other. To solve these problems, it is necessary to use ontology mapping geared for interoperability. This paper proposes a methodology to support the development of a common reference ontology for a group of enterprises sharing a business domain. This methodology is based on the concept of Mediator Ontology (MO), which assists the semantic transformations among each enterprisepsilas ontology and the referential one. The MO enables each organization to keep its own terminology, glossary and ontological structures, providing seamless communication and interaction with the others. A use case is described and the proposed methodology demonstrated.
{"title":"MENTOR — A methodology for enterprise reference ontology development","authors":"J. Sarraipa, J. Silva, R. Jardim-Gonçalves, A. Monteiro","doi":"10.1109/IS.2008.4670436","DOIUrl":"https://doi.org/10.1109/IS.2008.4670436","url":null,"abstract":"Ontologies facilitate the computational understanding, communication and seamless interoperability between people and organizations. They allow key concepts and terms relevant to a given domain to be identified and defined in an open and unambiguous way. Therefore, ontologies facilitate the use and exchange of data, information, and knowledge among people and organizations, towards intelligent systems interoperability. Tasks on distributed and heterogeneous systems demand support from more than one ontology. Multiple ontologies need to be accessed by the same, but also different systems. The distributed nature of ontology development has led to dissimilar ontologies for the same or overlapping domains. Thus, various parties with different ontologies often do not understand each other. To solve these problems, it is necessary to use ontology mapping geared for interoperability. This paper proposes a methodology to support the development of a common reference ontology for a group of enterprises sharing a business domain. This methodology is based on the concept of Mediator Ontology (MO), which assists the semantic transformations among each enterprisepsilas ontology and the referential one. The MO enables each organization to keep its own terminology, glossary and ontological structures, providing seamless communication and interaction with the others. A use case is described and the proposed methodology demonstrated.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"24 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":"127823882","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 software tool for time series prediction by means of fuzzy inference systems is reported. This tool, named xftsp, implements a novel methodology for time series prediction based on methods for automatic fuzzy systems identification and supervised learning combined with statistical methods for nonparametric residual variance estimation. xftsp is designed as a tool integrated in the Xfuzzy development environment for fuzzy systems. Experiments carried out on a number of time series benchmarks show the advantages of xftsp in terms of both accuracy and computational requirements as compared against Least-Squared Support Vector Machines, an established technique in the field of time series prediction.
本文报道了一种利用模糊推理系统进行时间序列预测的新软件工具。这个名为xftsp的工具实现了一种新的时间序列预测方法，该方法基于自动模糊系统识别方法和监督学习方法，结合非参数残差估计的统计方法。xftsp是一个集成在Xfuzzy开发环境中的模糊系统开发工具。在许多时间序列基准上进行的实验表明，与时间序列预测领域的一种成熟技术——最小二乘支持向量机(Least-Squared Support Vector Machines)相比，xftsp在准确性和计算需求方面都具有优势。
{"title":"xftsp: A tool for time series prediction by means of fuzzy inference systems","authors":"F. Montesino, A. Lendasse, A. Barriga","doi":"10.1109/IS.2008.4670398","DOIUrl":"https://doi.org/10.1109/IS.2008.4670398","url":null,"abstract":"A new software tool for time series prediction by means of fuzzy inference systems is reported. This tool, named xftsp, implements a novel methodology for time series prediction based on methods for automatic fuzzy systems identification and supervised learning combined with statistical methods for nonparametric residual variance estimation. xftsp is designed as a tool integrated in the Xfuzzy development environment for fuzzy systems. Experiments carried out on a number of time series benchmarks show the advantages of xftsp in terms of both accuracy and computational requirements as compared against Least-Squared Support Vector Machines, an established technique in the field of time series prediction.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"6 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":"133635595","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}
Lattices play an important role in many areas of computer science and applied mathematics. The information, extracted from data in data analysis or operated with in intelligent systems, is usually represented by hierarchical structures, where relationships are described by lattices. To visualize the information, one needs to visualize lattices. We mention the existing methods of automated drawing of lattices and focus on the geometric method introduced by Wille et al. Diagrams drawn by the geometric method achieve a good level of readability and aesthetic criteria while satisfying common conventions and constraints, even for larger lattices. We discuss several questions regarding the method and show the diagram drawings produced by two software programs developed at Dept. Computer Science, Palacky University, Czech Republic.
{"title":"Drawing lattices with a geometric heuristic","authors":"Jan Outrata","doi":"10.1109/IS.2008.4670536","DOIUrl":"https://doi.org/10.1109/IS.2008.4670536","url":null,"abstract":"Lattices play an important role in many areas of computer science and applied mathematics. The information, extracted from data in data analysis or operated with in intelligent systems, is usually represented by hierarchical structures, where relationships are described by lattices. To visualize the information, one needs to visualize lattices. We mention the existing methods of automated drawing of lattices and focus on the geometric method introduced by Wille et al. Diagrams drawn by the geometric method achieve a good level of readability and aesthetic criteria while satisfying common conventions and constraints, even for larger lattices. We discuss several questions regarding the method and show the diagram drawings produced by two software programs developed at Dept. Computer Science, Palacky University, Czech Republic.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"21 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131892801","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 presents the algorithmization of multi-factor method used to estimate the teaching quality at universities. The evaluation methods and procedures suggested in the paper are intended to make expertspsila evaluations as objective as possible. The generalized nets methods used to describe the process of algorithmization.
{"title":"Generalized net model of the multifactor method of teaching quality estimation at universities","authors":"M. Hristova, E. Sotirova","doi":"10.1109/IS.2008.4670541","DOIUrl":"https://doi.org/10.1109/IS.2008.4670541","url":null,"abstract":"The paper presents the algorithmization of multi-factor method used to estimate the teaching quality at universities. The evaluation methods and procedures suggested in the paper are intended to make expertspsila evaluations as objective as possible. The generalized nets methods used to describe the process of algorithmization.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"10 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":"134397592","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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