Pub Date : 2002-11-04DOI: 10.1109/TAI.2002.1180801
K. Kim
Mobile agent structuring is an increasingly practiced branch of distributed computing software engineering. In this paper we discuss the major issues encountered in producing real-time (RT) agents which are designed to perform output actions in a manner meeting specified timing requirements. An approach to structuring RT agents, which is an extension of a high-level real-time distributed object programming approach called the time-triggered message-triggered object (TMO) programming scheme, is also presented. The TMO based approach is promising because it provides a sound framework in which timeliness issues can be resolved in a cost-effective manner.
{"title":"A TMO based approach to structuring real-time agents","authors":"K. Kim","doi":"10.1109/TAI.2002.1180801","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180801","url":null,"abstract":"Mobile agent structuring is an increasingly practiced branch of distributed computing software engineering. In this paper we discuss the major issues encountered in producing real-time (RT) agents which are designed to perform output actions in a manner meeting specified timing requirements. An approach to structuring RT agents, which is an extension of a high-level real-time distributed object programming approach called the time-triggered message-triggered object (TMO) programming scheme, is also presented. The TMO based approach is promising because it provides a sound framework in which timeliness issues can be resolved in a cost-effective manner.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124596673","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180782
J. Prentzas, I. Hatzilygeroudis, A. Tsakalidis
Neurules are a kind of hybrid rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Each neurule is represented as an adaline unit. One way that the neurules can he produced is from training examples (empirical source knowledge). However, in certain application fields not all of the training examples are available a priori. A number of them become available over time. In these cases, updating the corresponding neurules is necessary. In this paper, methods for updating a hybrid rule base, consisting of neurules, to reflect the availability of new training examples are presented The methods are efficient, since they require the least possible retraining effort and the number of the produced neurules is kept as small as possible.
{"title":"Updating a hybrid rule base with new empirical source knowledge","authors":"J. Prentzas, I. Hatzilygeroudis, A. Tsakalidis","doi":"10.1109/TAI.2002.1180782","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180782","url":null,"abstract":"Neurules are a kind of hybrid rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Each neurule is represented as an adaline unit. One way that the neurules can he produced is from training examples (empirical source knowledge). However, in certain application fields not all of the training examples are available a priori. A number of them become available over time. In these cases, updating the corresponding neurules is necessary. In this paper, methods for updating a hybrid rule base, consisting of neurules, to reflect the availability of new training examples are presented The methods are efficient, since they require the least possible retraining effort and the number of the produced neurules is kept as small as possible.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124307209","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180823
Ruofei Zhang, Zhongfei Zhang
This paper addresses the issue of effective and efficient content based image retrieval by presenting a novel indexing and retrieval methodology that integrates color, texture, and shape information for the indexing and retrieval, and applies these features in regions obtained through unsupervised segmentation, as opposed to applying them to the whole image domain. In order to address the typical color feature "inaccuracy" problem in the literature, fuzzy logic is applied to the traditional color histogram to solve for the problem to a certain degree. The similarity is defined through a balanced combination between global and regional similarity measures incorporating all the features. In order to further improve the retrieval efficiency, a secondary clustering technique is developed and employed to significantly save query processing time without compromising the retrieval precision. An implemented prototype system has demonstrated a promising retrieval performance for a test database containing 2000 general-purpose color images, as compared with its peer systems in the literature.
{"title":"A clustering based approach to efficient image retrieval","authors":"Ruofei Zhang, Zhongfei Zhang","doi":"10.1109/TAI.2002.1180823","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180823","url":null,"abstract":"This paper addresses the issue of effective and efficient content based image retrieval by presenting a novel indexing and retrieval methodology that integrates color, texture, and shape information for the indexing and retrieval, and applies these features in regions obtained through unsupervised segmentation, as opposed to applying them to the whole image domain. In order to address the typical color feature \"inaccuracy\" problem in the literature, fuzzy logic is applied to the traditional color histogram to solve for the problem to a certain degree. The similarity is defined through a balanced combination between global and regional similarity measures incorporating all the features. In order to further improve the retrieval efficiency, a secondary clustering technique is developed and employed to significantly save query processing time without compromising the retrieval precision. An implemented prototype system has demonstrated a promising retrieval performance for a test database containing 2000 general-purpose color images, as compared with its peer systems in the literature.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122482310","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180849
É. Grégoire
In this paper, the problem of fusing logic-based technical specification knowledge components of a physical device or process, is investigated. It is shown that most standard logic approaches to beliefs fusion are not relevant in this context since some rules should be merged even in the case of a consistent fusion. Accordingly, we discuss the various types of formulas that should be merged during a fusion process, in order to avoid necessary conditions for the absence of failure to become sufficient conditions. This transformation is then described formally. It can be performed as an efficient preprocessing step on the knowledge components to be fused. The properties of this transformation schema are then investigated from a semantical point of view. Finally, a series of subsumption tests are proposed, preventing conditions of absence of failure from being overridden by subsumption.
{"title":"Fusing cooperative technical-specification knowledge components","authors":"É. Grégoire","doi":"10.1109/TAI.2002.1180849","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180849","url":null,"abstract":"In this paper, the problem of fusing logic-based technical specification knowledge components of a physical device or process, is investigated. It is shown that most standard logic approaches to beliefs fusion are not relevant in this context since some rules should be merged even in the case of a consistent fusion. Accordingly, we discuss the various types of formulas that should be merged during a fusion process, in order to avoid necessary conditions for the absence of failure to become sufficient conditions. This transformation is then described formally. It can be performed as an efficient preprocessing step on the knowledge components to be fused. The properties of this transformation schema are then investigated from a semantical point of view. Finally, a series of subsumption tests are proposed, preventing conditions of absence of failure from being overridden by subsumption.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115174117","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180804
Kalyani K. Manchi, Xindong Wu
Given a set of training examples in the form of (input, output) pairs, induction generates a set of rules that when applied to an input example, can come up with a target output or class for that example. At deduction time, these rules can be applied to a pre-classified test set to evaluate their accuracy. With existing rule induction systems, the rules are "frozen" on the training set, and they cannot adapt to a changing distribution of examples. In this paper we propose two approaches to dynamically refine the rules at deduction time, to overcome this limitation. For each test example, we perform a classification using existing rules. Depending on whether the classification is correct or not, the rule which was responsible for the classification is refined. When the correct classification is found, we refine the associated rule in one of two ways: by increasing the coverages of all conjunctions associated with the rule, or by increasing the coverage of the rule's most important conjunction only for the test example in question. These refined rules are then used for deducing the classifications for remaining examples. Of the two deduction methods, the second method has been shown to significantly improve the accuracy of the rules when compared to the regular non-dynamic deduction process.
{"title":"Dynamic refinement of classification rules","authors":"Kalyani K. Manchi, Xindong Wu","doi":"10.1109/TAI.2002.1180804","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180804","url":null,"abstract":"Given a set of training examples in the form of (input, output) pairs, induction generates a set of rules that when applied to an input example, can come up with a target output or class for that example. At deduction time, these rules can be applied to a pre-classified test set to evaluate their accuracy. With existing rule induction systems, the rules are \"frozen\" on the training set, and they cannot adapt to a changing distribution of examples. In this paper we propose two approaches to dynamically refine the rules at deduction time, to overcome this limitation. For each test example, we perform a classification using existing rules. Depending on whether the classification is correct or not, the rule which was responsible for the classification is refined. When the correct classification is found, we refine the associated rule in one of two ways: by increasing the coverages of all conjunctions associated with the rule, or by increasing the coverage of the rule's most important conjunction only for the test example in question. These refined rules are then used for deducing the classifications for remaining examples. Of the two deduction methods, the second method has been shown to significantly improve the accuracy of the rules when compared to the regular non-dynamic deduction process.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127302691","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180821
K. Turkowski, B. Hamidzadeh
In concatenative Text-to-Multimedia composition systems, accurate endpoint detection of the uttered audio words, used as input into such systems, is needed to ensure optimal audio concatenation. In this paper, we outline a method of endpoint detection that takes advantage of the fact that the text of the audio word is known before endpoint detection actually takes place. From the text, the associated phonemes for an uttered audio word can be determined and used to fine tune the endpoint detection for a specific given phoneme.
{"title":"Word endpoint correction techniques for a text-to-multimedia composition system","authors":"K. Turkowski, B. Hamidzadeh","doi":"10.1109/TAI.2002.1180821","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180821","url":null,"abstract":"In concatenative Text-to-Multimedia composition systems, accurate endpoint detection of the uttered audio words, used as input into such systems, is needed to ensure optimal audio concatenation. In this paper, we outline a method of endpoint detection that takes advantage of the fact that the text of the audio word is known before endpoint detection actually takes place. From the text, the associated phonemes for an uttered audio word can be determined and used to fine tune the endpoint detection for a specific given phoneme.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129696341","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180822
D. Cooke
To help meet NASA's computer science research needs, the number one priority at the NASA Ames Research Center is now computer science research. NASA's change in focus has arisen out of its realization that the major technological roadblocks impeding the nation's ability to perform earth and space science, and to achieve its exploration goals, center on computation and Artificial Intelligence (AI). Communication delays on long distance missions compel NASA to focus on Computer Science research. With roundtrip communication delays ranging from 6 to 45 minutes between Earth and Mars, human and robotic missions cannot be effectively controlled remotely from earth. Much of the intelligence provided by Mission Controllers will, in the future, necessarily accompany human and virtual explorers.
{"title":"Projecting our presence in space and in time","authors":"D. Cooke","doi":"10.1109/TAI.2002.1180822","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180822","url":null,"abstract":"To help meet NASA's computer science research needs, the number one priority at the NASA Ames Research Center is now computer science research. NASA's change in focus has arisen out of its realization that the major technological roadblocks impeding the nation's ability to perform earth and space science, and to achieve its exploration goals, center on computation and Artificial Intelligence (AI). Communication delays on long distance missions compel NASA to focus on Computer Science research. With roundtrip communication delays ranging from 6 to 45 minutes between Earth and Mars, human and robotic missions cannot be effectively controlled remotely from earth. Much of the intelligence provided by Mission Controllers will, in the future, necessarily accompany human and virtual explorers.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122010757","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180799
A. Lim, B. Rodrigues, Fei Xiao, Yi Zhu
We examine crane scheduling for ports. This important component of port operations management is studied when certain spatial constraints, which are common to crane operations, are considered. Although there has been some work on crane scheduling, such spatial constraints have not been previously developed. We assume that ships can be divided into holds and that cranes can move from hold to hold but that only one crane can work on one hold or job at any one time. The objective is to find a crane-to-job matching which will maximize throughput for such operations under these basic spatial constraints. We propose two dynamic programming algorithms, prove NP-completeness of the problem and provide heuristics to solve the crane scheduling problem with spatial constraints. We develop probabilistic tabu search techniques for application to the problem which are easy to implement. In experiments, we compare the performance of tabu search with other algorithms applied to the crane scheduling problem.
{"title":"Crane scheduling using tabu search","authors":"A. Lim, B. Rodrigues, Fei Xiao, Yi Zhu","doi":"10.1109/TAI.2002.1180799","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180799","url":null,"abstract":"We examine crane scheduling for ports. This important component of port operations management is studied when certain spatial constraints, which are common to crane operations, are considered. Although there has been some work on crane scheduling, such spatial constraints have not been previously developed. We assume that ships can be divided into holds and that cranes can move from hold to hold but that only one crane can work on one hold or job at any one time. The objective is to find a crane-to-job matching which will maximize throughput for such operations under these basic spatial constraints. We propose two dynamic programming algorithms, prove NP-completeness of the problem and provide heuristics to solve the crane scheduling problem with spatial constraints. We develop probabilistic tabu search techniques for application to the problem which are easy to implement. In experiments, we compare the performance of tabu search with other algorithms applied to the crane scheduling problem.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126830926","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180831
Boris Chidlovskii
We address the problem of automatic maintenance of Web wrappers used in data integration systems to encapsulate an access to Web information providers. The maintenance of Web wrappers is critical as providers often changes the page format and/or structure making wrappers inoperable. The solution we propose extends the conventional wrapper architecture with a novel component of automatic maintenance and recovery. We consider the automatic recovery as special type of the classification problem and use ensemble methods of machine learning to build alternative views of provider pages. We combine extraction rules of conventional wrappers with content features of extracted information to accurate recovery from three types of format changes, namely, content, context and structural changes. We report results of the recovery performance for format changes at widely used Web providers.
{"title":"Automatic repairing of Web wrappers by combining redundant views","authors":"Boris Chidlovskii","doi":"10.1109/TAI.2002.1180831","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180831","url":null,"abstract":"We address the problem of automatic maintenance of Web wrappers used in data integration systems to encapsulate an access to Web information providers. The maintenance of Web wrappers is critical as providers often changes the page format and/or structure making wrappers inoperable. The solution we propose extends the conventional wrapper architecture with a novel component of automatic maintenance and recovery. We consider the automatic recovery as special type of the classification problem and use ensemble methods of machine learning to build alternative views of provider pages. We combine extraction rules of conventional wrappers with content features of extracted information to accurate recovery from three types of format changes, namely, content, context and structural changes. We report results of the recovery performance for format changes at widely used Web providers.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130654122","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 : 2002-11-04DOI: 10.1109/TAI.2002.1180832
E. Schikuta
The NeuroWeb project is an Internet-based framework for the simulation of neural networks. It aims for using the Internet as a transparent environment to allow users the exchange of information (neural network objects, neural network paradigms) and the exploit of available computing resources for neural network specific tasks (specifically training of neural networks). NeuroWeb's design principles are acceptance, homogeneity, and efficiency.
{"title":"NeuroWeb: an Internet-based neural network simulator","authors":"E. Schikuta","doi":"10.1109/TAI.2002.1180832","DOIUrl":"https://doi.org/10.1109/TAI.2002.1180832","url":null,"abstract":"The NeuroWeb project is an Internet-based framework for the simulation of neural networks. It aims for using the Internet as a transparent environment to allow users the exchange of information (neural network objects, neural network paradigms) and the exploit of available computing resources for neural network specific tasks (specifically training of neural networks). NeuroWeb's design principles are acceptance, homogeneity, and efficiency.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125172213","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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