A new off-line writer recognition method for Farsi text is presented in this paper. 8 different types of features obtained from the handwritten line of text were considered to identify writers based on theirs handwritten. These features are associated with height and width of text. A typical feed forward neural network was used for classification. This method was applied to 20 writers who wrote 5 to 7 lines and 86.5% recognition rate was obtained.
{"title":"Off-Line Writer Recognition for Farsi Text","authors":"A. Rafiee, H. Motavalli","doi":"10.1109/MICAI.2007.37","DOIUrl":"https://doi.org/10.1109/MICAI.2007.37","url":null,"abstract":"A new off-line writer recognition method for Farsi text is presented in this paper. 8 different types of features obtained from the handwritten line of text were considered to identify writers based on theirs handwritten. These features are associated with height and width of text. A typical feed forward neural network was used for classification. This method was applied to 20 writers who wrote 5 to 7 lines and 86.5% recognition rate was obtained.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123311325","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 article presents the main features of a novel construction, symbolic analysis, for automatic source code processing. The method is superior to the known methods, because it uses a semiotic, interpretative approach. Its most important processes and characteristics are considered here. We describe symbolic information retrieval and the process of analysis in which it can be used in order to obtain pragmatic information. This, in turn, is useful in understanding a current Java program version when developing a new version.
{"title":"Symbolic Reductionist Model for Program Comprehension","authors":"E. Laitila, S. Legrand","doi":"10.1109/MICAI.2007.7","DOIUrl":"https://doi.org/10.1109/MICAI.2007.7","url":null,"abstract":"This article presents the main features of a novel construction, symbolic analysis, for automatic source code processing. The method is superior to the known methods, because it uses a semiotic, interpretative approach. Its most important processes and characteristics are considered here. We describe symbolic information retrieval and the process of analysis in which it can be used in order to obtain pragmatic information. This, in turn, is useful in understanding a current Java program version when developing a new version.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122606543","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}
M. Díaz-Galiano, M. Martín-Valdivia, A. Montejo-Ráez, L.A. Urea-Lopez
This paper studies the combination of textual and visual information in a database of medical records in order to improve the performance of the multi-modal information retrieval system. The proposed model consists of two subsystems: a content-based information retrieval subsystem that performs the image retrieval and a textual information retrieval subsystem that performs the textual retrieval. The images and text are independently retrieved and then the partial resulting lists are mixed. A study of different weighting schemes has been accomplished and analyzed. The results obtained show that the proper integration of textual information improves conventional multi-modal systems.
{"title":"Improving Performance of Medical Images Retrieval by Combining Textual and Visual Information","authors":"M. Díaz-Galiano, M. Martín-Valdivia, A. Montejo-Ráez, L.A. Urea-Lopez","doi":"10.1109/MICAI.2007.12","DOIUrl":"https://doi.org/10.1109/MICAI.2007.12","url":null,"abstract":"This paper studies the combination of textual and visual information in a database of medical records in order to improve the performance of the multi-modal information retrieval system. The proposed model consists of two subsystems: a content-based information retrieval subsystem that performs the image retrieval and a textual information retrieval subsystem that performs the textual retrieval. The images and text are independently retrieved and then the partial resulting lists are mixed. A study of different weighting schemes has been accomplished and analyzed. The results obtained show that the proper integration of textual information improves conventional multi-modal systems.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121171233","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 use of present pedagogical methods with Information and Communication Technologies produce a new quality that favors the task of generating, transmitting and sharing knowledge. That is the case of the pedagogical effect that produces the use of the concept maps, which are considered a learning technique as a way to increase meaningful learning in the sciences. It is also used for the knowledge management as an aid to personalize the Teaching-Learning process, to exchange knowledge, and to learn how to learn. Concept Maps provides a framework for making this internal knowledge explicit in a visual form that can easily be examined and shared. In this paper the authors present two different approaches to elaborate intelligent teaching-learning systems, in each approach concept maps and artificial intelligence are combined, using in the first one the case-based reasoning and in the other Bayesian networks as a knowledge representation forms and inference mechanisms for the decision making, supporting the student model. The authors also show the facilities and the difficulties they had using each artificial intelligence technique combined with concept maps. The proposed models have been implemented in the computational systems HESEI and MacBay, whose have been successfully used in the Teaching-Learning process by laymen in the Computer Science field to generate them owns adaptive systems.
{"title":"Two Approaches to Generate Intelligent Teaching-Learning Systems Using Artificial Intelligence Techniques","authors":"M. Leon, D. Medina, N. Martínez, Z. García","doi":"10.1109/MICAI.2007.46","DOIUrl":"https://doi.org/10.1109/MICAI.2007.46","url":null,"abstract":"The use of present pedagogical methods with Information and Communication Technologies produce a new quality that favors the task of generating, transmitting and sharing knowledge. That is the case of the pedagogical effect that produces the use of the concept maps, which are considered a learning technique as a way to increase meaningful learning in the sciences. It is also used for the knowledge management as an aid to personalize the Teaching-Learning process, to exchange knowledge, and to learn how to learn. Concept Maps provides a framework for making this internal knowledge explicit in a visual form that can easily be examined and shared. In this paper the authors present two different approaches to elaborate intelligent teaching-learning systems, in each approach concept maps and artificial intelligence are combined, using in the first one the case-based reasoning and in the other Bayesian networks as a knowledge representation forms and inference mechanisms for the decision making, supporting the student model. The authors also show the facilities and the difficulties they had using each artificial intelligence technique combined with concept maps. The proposed models have been implemented in the computational systems HESEI and MacBay, whose have been successfully used in the Teaching-Learning process by laymen in the Computer Science field to generate them owns adaptive systems.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129919843","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}
Abel Rodríguez Morffi, Luisa Manuela González González, Darien Rosa Paz, M. M. Hing
The data distribution problem is a critical one that affects the global performance of the distributed database systems because it directly influences the efficiency of the querying process. Due to the complexity of the problem, most of the proposed solutions divide the design process in two parts: the fragmentation and the allocation of the fragments on the different locations in the network. Here we consider the allocation problem with the possibility to replicate fragments, minimizing the total cost, which is in general NP-complete, and propose a method based on Q-learning to solve the allocation of fragments in the design of a distributed database. As a result we obtain for several cases, logical allocation of fragments in a reasonable time.
{"title":"An Intelligent Agent Using a Q-Learning Method to Allocate Replicated Data in a Distributed Database","authors":"Abel Rodríguez Morffi, Luisa Manuela González González, Darien Rosa Paz, M. M. Hing","doi":"10.1109/MICAI.2007.8","DOIUrl":"https://doi.org/10.1109/MICAI.2007.8","url":null,"abstract":"The data distribution problem is a critical one that affects the global performance of the distributed database systems because it directly influences the efficiency of the querying process. Due to the complexity of the problem, most of the proposed solutions divide the design process in two parts: the fragmentation and the allocation of the fragments on the different locations in the network. Here we consider the allocation problem with the possibility to replicate fragments, minimizing the total cost, which is in general NP-complete, and propose a method based on Q-learning to solve the allocation of fragments in the design of a distributed database. As a result we obtain for several cases, logical allocation of fragments in a reasonable time.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116465343","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 notion of collective intentionally is controversial. This has been object of research by philosophers (Tuomela and Miller, 1988; Searle, 1979; Tuomela, 1994), AI scientists (Hobbs, 1990) and communication scientists (Conte and Castelfranchi, 1995). Related notions, such as joint intentions, teamwork, and mutual beliefs underlie much work both in formal models and computer models of multi-agent systems research in DAI (Cohen and Levesque, 1990; OpsilaHare and Jennings, 1996). In this paper we will show that the EDA model (Epistemic-Deontic-Axiological) has the required expressiveness to represent normative multi-agent coordination in organisations, using notions such as commitment, responsibility, organisational role, obligation, authorisation and other notions related to goal-governed normative systems.
集体故意的概念是有争议的。这一直是哲学家们研究的对象(Tuomela和Miller, 1988;塞尔,1979;Tuomela, 1994)，人工智能科学家(Hobbs, 1990)和通信科学家(Conte和Castelfranchi, 1995)。相关概念，如共同意图、团队合作和共同信念，是DAI中多智能体系统研究的正式模型和计算机模型的基础(Cohen和Levesque, 1990;OpsilaHare and Jennings, 1996)。在本文中，我们将展示EDA模型(认识论-道义论-价值论)具有所需的表达能力来表示组织中规范的多主体协调，使用诸如承诺，责任，组织角色，义务，授权和其他与目标治理的规范系统相关的概念。
{"title":"Collective Agents and Collective Intentionality Using the EDA Model","authors":"J. Filipe, A. Fred","doi":"10.1109/MICAI.2007.43","DOIUrl":"https://doi.org/10.1109/MICAI.2007.43","url":null,"abstract":"The notion of collective intentionally is controversial. This has been object of research by philosophers (Tuomela and Miller, 1988; Searle, 1979; Tuomela, 1994), AI scientists (Hobbs, 1990) and communication scientists (Conte and Castelfranchi, 1995). Related notions, such as joint intentions, teamwork, and mutual beliefs underlie much work both in formal models and computer models of multi-agent systems research in DAI (Cohen and Levesque, 1990; OpsilaHare and Jennings, 1996). In this paper we will show that the EDA model (Epistemic-Deontic-Axiological) has the required expressiveness to represent normative multi-agent coordination in organisations, using notions such as commitment, responsibility, organisational role, obligation, authorisation and other notions related to goal-governed normative systems.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121902682","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}
I. I. Méndez-Gurrola, A. Laureano-Cruces, A. Santillan-Gonzalez, J. Ramírez-Rodríguez
In our work, the design of the elementary components of a knowledge based system for the prediction of supernova effects is described. The domain is related with the modeling of the two supernova effects using fuzzy cognitive maps as knowledge representation and the maps feedback as inference engine to make the prediction. This work also describes the characteristics of (1) the application dominion and its representation, and (2) the results of the model through experimental tests and interpretations which represent the inference process.
{"title":"A Knowledge Based System Design for the Prediction of Supernova Effects in the Interstellar Environment","authors":"I. I. Méndez-Gurrola, A. Laureano-Cruces, A. Santillan-Gonzalez, J. Ramírez-Rodríguez","doi":"10.1109/MICAI.2007.24","DOIUrl":"https://doi.org/10.1109/MICAI.2007.24","url":null,"abstract":"In our work, the design of the elementary components of a knowledge based system for the prediction of supernova effects is described. The domain is related with the modeling of the two supernova effects using fuzzy cognitive maps as knowledge representation and the maps feedback as inference engine to make the prediction. This work also describes the characteristics of (1) the application dominion and its representation, and (2) the results of the model through experimental tests and interpretations which represent the inference process.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121823450","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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