n this paper, an approach for intelligent integration of indoor visual tracking system for event detection and movement is proposed. This surveillance system is composed of a stationary camera and a pan tilt zoom (PTZ) camera, where the two cameras have been intrinsically and extrinsically calibrated. The stationary camera detects events such as fall and wandering using motion-based visual tracking. In this initial study, the PTZ camera tracks and follows the person who triggered the event using intelligent color-based particle filtering which is defined based on the expected dynamics of the scene. The purpose of tracking in view of the PTZ camera is to continuously keep the person in the full view of the camera which can further be processed for identifying details of the person. Preliminary experimental results for camera calibration, event detection, and human tracking are presented to demonstrate the performance of the proposed cooperative hybrid visual tracking system.
{"title":"Intelligent Cooperative Tracking in Multi-camera Systems","authors":"Yan Lu, S. Payandeh","doi":"10.1109/ISDA.2009.12","DOIUrl":"https://doi.org/10.1109/ISDA.2009.12","url":null,"abstract":"n this paper, an approach for intelligent integration of indoor visual tracking system for event detection and movement is proposed. This surveillance system is composed of a stationary camera and a pan tilt zoom (PTZ) camera, where the two cameras have been intrinsically and extrinsically calibrated. The stationary camera detects events such as fall and wandering using motion-based visual tracking. In this initial study, the PTZ camera tracks and follows the person who triggered the event using intelligent color-based particle filtering which is defined based on the expected dynamics of the scene. The purpose of tracking in view of the PTZ camera is to continuously keep the person in the full view of the camera which can further be processed for identifying details of the person. Preliminary experimental results for camera calibration, event detection, and human tracking are presented to demonstrate the performance of the proposed cooperative hybrid visual tracking system.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131091425","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}
Weifeng Lv, Leishi Xu, T. Zhu, Bowen Du, Dongdong Wu
Nowadays Float Car Data (FCD) is playing an important role in real-time traffic information systems. However, traffic signal control in urban road network will cause random delay on float cars, and this kind of delay will result in considerable fluctuation of travel time. Thus, the accuracy of FCD system is seriously affected. In this paper, float car refining models are proposed to calculate the stopped-time delay by means of low-sampling-rate FCD. And then, the classification of controlled delay and non-controlled delay is performed in order to remove traffic signal control's affection, and to obtain the data which can truly reflect the traffic flow characteristics. The contrast experiments indicate that the accuracy of the FCD system has achieved significant improvement after applying the new processing model.
{"title":"An FCD Information Processing Model under Traffic Signal Control","authors":"Weifeng Lv, Leishi Xu, T. Zhu, Bowen Du, Dongdong Wu","doi":"10.1109/ISDA.2009.13","DOIUrl":"https://doi.org/10.1109/ISDA.2009.13","url":null,"abstract":"Nowadays Float Car Data (FCD) is playing an important role in real-time traffic information systems. However, traffic signal control in urban road network will cause random delay on float cars, and this kind of delay will result in considerable fluctuation of travel time. Thus, the accuracy of FCD system is seriously affected. In this paper, float car refining models are proposed to calculate the stopped-time delay by means of low-sampling-rate FCD. And then, the classification of controlled delay and non-controlled delay is performed in order to remove traffic signal control's affection, and to obtain the data which can truly reflect the traffic flow characteristics. The contrast experiments indicate that the accuracy of the FCD system has achieved significant improvement after applying the new processing model.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133319341","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 concerns the autonomous thermal control system of Nano-satellite with a study of the combination of MEMS (Micro Electro Mechanical Systems)-based efficient cooling technique and the agent-oriented intelligent control strategies issue, especially with the issue of autonomy. The particular interest and complexity are the development of the thermal control system that has the intelligent autonomous control capability to maintain the Nano-satellite optimal performance. Based on the modeling and analysis the dynamic characteristics of efficient cooling system utilizing MEMSbased micro-channel heat sink and micro louver arrays by the means of lumped parameter method, the hierarchical structure of agent-oriented intelligent control method for Nano-satellite autonomous thermal system is investigated. With the domain expert knowledge and Fuzzy reasoning, the innovative agentoriented intelligent control strategies achieve an autonomous process to regulate several controlled variables according to the expectation of the system situations and variety tendency, the robustness of the thermal control system is accomplished as well.
{"title":"Agent-Oriented Intelligent Control Strategies for the Nano-satellite Autonomous Thermal System","authors":"Liu Jia, Li Yunze, W. Yuying, Wang Jun","doi":"10.1109/ISDA.2009.139","DOIUrl":"https://doi.org/10.1109/ISDA.2009.139","url":null,"abstract":"The paper concerns the autonomous thermal control system of Nano-satellite with a study of the combination of MEMS (Micro Electro Mechanical Systems)-based efficient cooling technique and the agent-oriented intelligent control strategies issue, especially with the issue of autonomy. The particular interest and complexity are the development of the thermal control system that has the intelligent autonomous control capability to maintain the Nano-satellite optimal performance. Based on the modeling and analysis the dynamic characteristics of efficient cooling system utilizing MEMSbased micro-channel heat sink and micro louver arrays by the means of lumped parameter method, the hierarchical structure of agent-oriented intelligent control method for Nano-satellite autonomous thermal system is investigated. With the domain expert knowledge and Fuzzy reasoning, the innovative agentoriented intelligent control strategies achieve an autonomous process to regulate several controlled variables according to the expectation of the system situations and variety tendency, the robustness of the thermal control system is accomplished as well.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133551004","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}
Machine learning methodologies such as artificial neural networks (ANN), fuzzy logic or genetic programming, as well as principal component analysis (PCA) and intelligent control have been recently introduced in medicine. ANNs imitate the structure and workings of the human brain by means of mathematical models able to adapt several parameters. ANNs learn the input/output behavior of a system through a supervised or an unsupervised learning algorithm. In this work, we present and demonstrate a new pre-processing algorithm able to improve the performance of an ANN in the processing of biomedical datasets. The algorithm was tested analyzing lung function and fractional exhaled nitric oxide differences in the breath in children with allergic bronchial asthma and in normal population. Classification obtained using non linear PCA based on the new algorithm shows a better precision in separating asthmatic and control subjects.
{"title":"Backpropagation-Based Non Linear PCA for Biomedical Applications","authors":"A. Landi, P. Piaggi, G. Pioggia","doi":"10.1109/ISDA.2009.176","DOIUrl":"https://doi.org/10.1109/ISDA.2009.176","url":null,"abstract":"Machine learning methodologies such as artificial neural networks (ANN), fuzzy logic or genetic programming, as well as principal component analysis (PCA) and intelligent control have been recently introduced in medicine. ANNs imitate the structure and workings of the human brain by means of mathematical models able to adapt several parameters. ANNs learn the input/output behavior of a system through a supervised or an unsupervised learning algorithm. In this work, we present and demonstrate a new pre-processing algorithm able to improve the performance of an ANN in the processing of biomedical datasets. The algorithm was tested analyzing lung function and fractional exhaled nitric oxide differences in the breath in children with allergic bronchial asthma and in normal population. Classification obtained using non linear PCA based on the new algorithm shows a better precision in separating asthmatic and control subjects.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114451880","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}
R. Pirrone, V. Cannella, O. Gambino, A. Pipitone, G. Russo
The paper presents WikiArt, a new system integrating three distinct types of contents about the art: data, information, and knowledge, to generate automatically thematic paths to consult all its contents. WikiArt is a wiki, allowing to manage cooperatively documents about artists, artworks, artistic movements or techniques, and so on. It is also an expert system, provided with an ontology about arts, with which it is able to plan possible different ways of consulting and browsing its contents. This ability is made possible by a second part of the ontology of the system, describing a collection of criteria regarding how to plan thematic paths, and by a set of rules followed by the expert system to carry out this task. WikiArt is not a semantic wiki, because the ontology has not been employed to tag semantically the documents by the authors. But only their subjects. Our efforts are now devoted to the extension of the system to make it a semantic wiki too.
{"title":"WikiArt: An Ontology-Based Information Retrieval System for Arts","authors":"R. Pirrone, V. Cannella, O. Gambino, A. Pipitone, G. Russo","doi":"10.1109/ISDA.2009.219","DOIUrl":"https://doi.org/10.1109/ISDA.2009.219","url":null,"abstract":"The paper presents WikiArt, a new system integrating three distinct types of contents about the art: data, information, and knowledge, to generate automatically thematic paths to consult all its contents. WikiArt is a wiki, allowing to manage cooperatively documents about artists, artworks, artistic movements or techniques, and so on. It is also an expert system, provided with an ontology about arts, with which it is able to plan possible different ways of consulting and browsing its contents. This ability is made possible by a second part of the ontology of the system, describing a collection of criteria regarding how to plan thematic paths, and by a set of rules followed by the expert system to carry out this task. WikiArt is not a semantic wiki, because the ontology has not been employed to tag semantically the documents by the authors. But only their subjects. Our efforts are now devoted to the extension of the system to make it a semantic wiki too.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128328307","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}
Learning Object (LO) is one of the main research topics in the E-Learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse than aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. Therefore, when designing learning objects, reusability must be considered as a key consideration. This paper shows how we adapted and applied some of the metrics from the software engineering field for the purpose of measuring reusability of learning objects.
{"title":"A Metrics Suite for Measuring Reusability of Learning Objects","authors":"S. Noor, N. Yusof, S. Z. M. Hashim","doi":"10.1109/ISDA.2009.114","DOIUrl":"https://doi.org/10.1109/ISDA.2009.114","url":null,"abstract":"Learning Object (LO) is one of the main research topics in the E-Learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse than aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. Therefore, when designing learning objects, reusability must be considered as a key consideration. This paper shows how we adapted and applied some of the metrics from the software engineering field for the purpose of measuring reusability of learning objects.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128546209","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}
This paper proposes a novel two-class classifier, called IPCAC, based on the Isotropic Principal Component Analysis technique; it allows to deal with training data drawn from Mixture of Gaussian distributions, by projecting the data on the Fisher subspace that separates the two classes. The obtained results demonstrate that IPCAC is a promising technique; furthermore, to cope with training datasets being dynamically supplied, and to work with non-linearly separable classes, two improvements of this classifier are defined: a model merging algorithm, and a kernel version of IPCAC. The effectiveness of the proposed methods is shown by their application to the spam classification problem, and by the comparison of the achieved results with those obtained by Support Vector Machines SVM, and K-Nearest Neighbors KNN.
{"title":"Novel IPCA-Based Classifiers and Their Application to Spam Filtering","authors":"A. Rozza, G. Lombardi, E. Casiraghi","doi":"10.1109/ISDA.2009.21","DOIUrl":"https://doi.org/10.1109/ISDA.2009.21","url":null,"abstract":"This paper proposes a novel two-class classifier, called IPCAC, based on the Isotropic Principal Component Analysis technique; it allows to deal with training data drawn from Mixture of Gaussian distributions, by projecting the data on the Fisher subspace that separates the two classes. The obtained results demonstrate that IPCAC is a promising technique; furthermore, to cope with training datasets being dynamically supplied, and to work with non-linearly separable classes, two improvements of this classifier are defined: a model merging algorithm, and a kernel version of IPCAC. The effectiveness of the proposed methods is shown by their application to the spam classification problem, and by the comparison of the achieved results with those obtained by Support Vector Machines SVM, and K-Nearest Neighbors KNN.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134303959","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}
This study introduces a spatio–temporal lifting based algorithm to be used in compression of video signals. The temporal correlation of consecutive frames causes temporal redundancies, which are subject to lifting-like motion predictive compression. Similarly, neighbouring pixels are correlated within each frame. A method that uses both correlations might be 3D lifting-based decomposition. In this study, block-based motion compensation is added to the classical 3D lifting method. Domain of motion compensation is first selected as free, and then reverse-symmetric. It is observed that reverse-symmetric motion compensation improves the performance of the prediction step in 3D lifting based coding.
{"title":"A 3D Lifting Based Method Augmented by Motion Compensation for Video Coding","authors":"Sedat Telçeken, Sukru Gorgulu, Ö. N. Gerek","doi":"10.1109/ISDA.2009.23","DOIUrl":"https://doi.org/10.1109/ISDA.2009.23","url":null,"abstract":"This study introduces a spatio–temporal lifting based algorithm to be used in compression of video signals. The temporal correlation of consecutive frames causes temporal redundancies, which are subject to lifting-like motion predictive compression. Similarly, neighbouring pixels are correlated within each frame. A method that uses both correlations might be 3D lifting-based decomposition. In this study, block-based motion compensation is added to the classical 3D lifting method. Domain of motion compensation is first selected as free, and then reverse-symmetric. It is observed that reverse-symmetric motion compensation improves the performance of the prediction step in 3D lifting based coding.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133377683","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}
Meta-Learning has been applied to acquire useful knowledge to predict learning performance. Each training example in Meta-Learning (i.e. each meta-example) is related to a learning problem and stores features of the problem plus the performance obtained by a set of candidate algorithms when evaluated on the problem. Based on a set of such meta-examples, a meta-learner will be used to predict algorithm performance for new problems. The generation of a set of meta-examples can be expensive, since for each problem it is necessary to perform an empirical evaluation of the candidate algorithms. In a previous work, we proposed the Active Meta-Learning, in which Active Learning was used to reduce the set of meta-examples by selecting only the most relevant problems for meta-example generation. In the current work, we proposed the combination of different Uncertainty Sampling methods for Active Meta-Learning, considering that each individual method will provide useful information that can be combined in order to have a better assessment of problem relevance for meta-example generation. In our experiments, we observed a gain in Meta-Learning performance when the proposed method was compared to the individual active methods being combined.
{"title":"Combining Uncertainty Sampling Methods for Active Meta-Learning","authors":"R. Prudêncio, Teresa B Ludermir","doi":"10.1109/ISDA.2009.160","DOIUrl":"https://doi.org/10.1109/ISDA.2009.160","url":null,"abstract":"Meta-Learning has been applied to acquire useful knowledge to predict learning performance. Each training example in Meta-Learning (i.e. each meta-example) is related to a learning problem and stores features of the problem plus the performance obtained by a set of candidate algorithms when evaluated on the problem. Based on a set of such meta-examples, a meta-learner will be used to predict algorithm performance for new problems. The generation of a set of meta-examples can be expensive, since for each problem it is necessary to perform an empirical evaluation of the candidate algorithms. In a previous work, we proposed the Active Meta-Learning, in which Active Learning was used to reduce the set of meta-examples by selecting only the most relevant problems for meta-example generation. In the current work, we proposed the combination of different Uncertainty Sampling methods for Active Meta-Learning, considering that each individual method will provide useful information that can be combined in order to have a better assessment of problem relevance for meta-example generation. In our experiments, we observed a gain in Meta-Learning performance when the proposed method was compared to the individual active methods being combined.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133378348","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 new method to analyze quasi-periodic signals. This method consists of modeling these signals using a Fuzzy Finite State Machine as a particular case of a Linguistic Fuzzy Model of a dynamical system. This model defines states and transitions using a priori knowledge of the signal we want to analyze. The model is represented using fuzzy rules that make it easily comprehensible. We include a practical example analyzing quasi-periodic signals of acceleration measured during the human gait cycle where good results were achieved.
{"title":"Comprehensible Model of a Quasi-periodic Signal","authors":"A. Alvarez-Alvarez, G. Triviño","doi":"10.1109/ISDA.2009.65","DOIUrl":"https://doi.org/10.1109/ISDA.2009.65","url":null,"abstract":"In this paper we present a new method to analyze quasi-periodic signals. This method consists of modeling these signals using a Fuzzy Finite State Machine as a particular case of a Linguistic Fuzzy Model of a dynamical system. This model defines states and transitions using a priori knowledge of the signal we want to analyze. The model is represented using fuzzy rules that make it easily comprehensible. We include a practical example analyzing quasi-periodic signals of acceleration measured during the human gait cycle where good results were achieved.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123500991","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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