Octavio Gutiérrez, Héctor Rafael Orozco-Aguirre, V. Landassuri-Moreno
The effects of crime are diverse and complex, ranging from psychological and physical traumas faced by crime victims, to negative impacts on the economy of a whole nation. In this paper, an agent-based crime simulation framework to analyze crime and its causes is proposed and implemented. The agent-based simulation framework models and simulates both 1) crime events as a consequence of a set of interrelated social and individual-level crime factors, and 2) crime opportunities, i.e., combinations of circumstances that enable a person to commit a crime. The selection of crime factors and design of agent models are supported by, and based on, existing criminological literature. In addition, the simulation results are validated and compared with macro-level crime patterns reported by various criminological research efforts.
{"title":"Agent-Based Simulation of Crime","authors":"Octavio Gutiérrez, Héctor Rafael Orozco-Aguirre, V. Landassuri-Moreno","doi":"10.1109/MICAI.2013.9","DOIUrl":"https://doi.org/10.1109/MICAI.2013.9","url":null,"abstract":"The effects of crime are diverse and complex, ranging from psychological and physical traumas faced by crime victims, to negative impacts on the economy of a whole nation. In this paper, an agent-based crime simulation framework to analyze crime and its causes is proposed and implemented. The agent-based simulation framework models and simulates both 1) crime events as a consequence of a set of interrelated social and individual-level crime factors, and 2) crime opportunities, i.e., combinations of circumstances that enable a person to commit a crime. The selection of crime factors and design of agent models are supported by, and based on, existing criminological literature. In addition, the simulation results are validated and compared with macro-level crime patterns reported by various criminological research efforts.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123793747","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}
G. Ortiz-Hernández, A. Guerra-Hernández, G. Hoyos-Rivera
In this paper we propose and implement a modularization framework for Jason that enables developers to decompose agents into separate code units called modules, and by fulfilling an agent-module design contract to conceive agents behaviour design into different levels of abstraction - from a software engineering perspective. Thus, we promote code reuse as well as facilitate independent development, maintainability and extensibility. For our implementation we use annotations mechanism and customizable components in Jason.
{"title":"JasMo - A Modularization Framework for Jason","authors":"G. Ortiz-Hernández, A. Guerra-Hernández, G. Hoyos-Rivera","doi":"10.1109/MICAI.2013.6","DOIUrl":"https://doi.org/10.1109/MICAI.2013.6","url":null,"abstract":"In this paper we propose and implement a modularization framework for Jason that enables developers to decompose agents into separate code units called modules, and by fulfilling an agent-module design contract to conceive agents behaviour design into different levels of abstraction - from a software engineering perspective. Thus, we promote code reuse as well as facilitate independent development, maintainability and extensibility. For our implementation we use annotations mechanism and customizable components in Jason.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115206567","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}
Luis Carlos Gonzalez-Sua, O. Barron, R. Soto, Leonardo Garrido, Iván González, J. L. Gordillo, Alejandro Garza
This article presents a novel obstacle avoidance algorithm. Using a combination of fuzzy logic and gain scheduling theories, a new methodology that reduces computational costs compared to conventional fuzzy methodologies, specially when the variables to be controlled are too many. For comparison purposes, a potential field algorithm was implemented. Both algorithms are tested in a series of experiments to determine if the new algorithm is at least as good as the potential field algorithm. The metrics defined for these experiments are: the number of times that the agent collides (collisions), the time spent to finish a traced course (time spent) and the remaining stamina of an agent at the end of an experiment (stamina consumption). The results show that the proposed algorithm achieve a low level of collisions. Also, the proposed algorithm shows a considerable improvement in the time spent for the completion of the proposed tasks. Last but not least, the results demonstrate a considerable reduction in the stamina consumption using the proposed algorithm over the potential field algorithm.
{"title":"Design and Implementation of a Fuzzy-Based Gain Scheduling Obstacle Avoidance Algorithm","authors":"Luis Carlos Gonzalez-Sua, O. Barron, R. Soto, Leonardo Garrido, Iván González, J. L. Gordillo, Alejandro Garza","doi":"10.1109/MICAI.2013.11","DOIUrl":"https://doi.org/10.1109/MICAI.2013.11","url":null,"abstract":"This article presents a novel obstacle avoidance algorithm. Using a combination of fuzzy logic and gain scheduling theories, a new methodology that reduces computational costs compared to conventional fuzzy methodologies, specially when the variables to be controlled are too many. For comparison purposes, a potential field algorithm was implemented. Both algorithms are tested in a series of experiments to determine if the new algorithm is at least as good as the potential field algorithm. The metrics defined for these experiments are: the number of times that the agent collides (collisions), the time spent to finish a traced course (time spent) and the remaining stamina of an agent at the end of an experiment (stamina consumption). The results show that the proposed algorithm achieve a low level of collisions. Also, the proposed algorithm shows a considerable improvement in the time spent for the completion of the proposed tasks. Last but not least, the results demonstrate a considerable reduction in the stamina consumption using the proposed algorithm over the potential field algorithm.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123707149","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}
Hiram Madero Orozco, O. Vergara-Villegas, Humberto Ochoa Domínguez, V. Sánchez
In this paper a computational alternative to classify lung nodules using computed tomography (CT) thorax images is presented. The novelty of the method is the elimination of the segmentation stage. The contribution consist of several steps. After image acquisition, eight texture features were extracted from the histogram and the gray level coocurrence matrix (with four different angles) for each CT image. The features were used to train a non-parametric classifier called support vector machine (SVM), used to classify lung tissues into two classes: with lung nodules and without lung nodules. A total of 128 public clinical data set (ELCAP, NBIA) with different number of slices and diagnoses were used to train and evaluate the performance of the methodology presented. After the tests stage, five false negative (FN) and seven false positive (FP) results were obtained. The results obtained were validated by a radiologist to finally obtain a reliability index of 84%.
{"title":"Lung Nodule Classification in CT Thorax Images Using Support Vector Machines","authors":"Hiram Madero Orozco, O. Vergara-Villegas, Humberto Ochoa Domínguez, V. Sánchez","doi":"10.1109/MICAI.2013.38","DOIUrl":"https://doi.org/10.1109/MICAI.2013.38","url":null,"abstract":"In this paper a computational alternative to classify lung nodules using computed tomography (CT) thorax images is presented. The novelty of the method is the elimination of the segmentation stage. The contribution consist of several steps. After image acquisition, eight texture features were extracted from the histogram and the gray level coocurrence matrix (with four different angles) for each CT image. The features were used to train a non-parametric classifier called support vector machine (SVM), used to classify lung tissues into two classes: with lung nodules and without lung nodules. A total of 128 public clinical data set (ELCAP, NBIA) with different number of slices and diagnoses were used to train and evaluate the performance of the methodology presented. After the tests stage, five false negative (FN) and seven false positive (FP) results were obtained. The results obtained were validated by a radiologist to finally obtain a reliability index of 84%.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122403343","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}
Carlos Martínez, J. Mosterín, D. Fuente, P. Priore, N. García
In this paper, for zoning a large set of location's data we apply the k-means clustering algorithm. The results were plotted graphically and were satisfactory, so we conclude that the algorithm is useful despite the size of the data, at least for low data dimensions (latitude, longitude).
{"title":"Zoning by k-Means over a Large Data Set","authors":"Carlos Martínez, J. Mosterín, D. Fuente, P. Priore, N. García","doi":"10.1109/MICAI.2013.13","DOIUrl":"https://doi.org/10.1109/MICAI.2013.13","url":null,"abstract":"In this paper, for zoning a large set of location's data we apply the k-means clustering algorithm. The results were plotted graphically and were satisfactory, so we conclude that the algorithm is useful despite the size of the data, at least for low data dimensions (latitude, longitude).","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131604941","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 coordination model for multi-robot systems based on cooperative behaviors, where the low level behaviors are obtained through artificial neural networks and evolutionary algorithms to achieve a common goal. For this purpose, we have defined two strategies of self-alignment to carry out the docking process between two robots. Both strategies share the same goal of achieving an optimal alignment between two robots. The main difference between these strategies is that: the strategy 1 consists of having one active and one inactive robot, and in the strategy 2 both robots are active. Experimental results are presented by a robotic device simulator (Player) and a multi-robot simulator 2D (Stage) for each strategy displaying differences between both strategies and benefits in time execution. The paper ends with a critical discussion of experimental results.
{"title":"Coordination Model for Multi-robot Systems Based on Cooperative Behaviors","authors":"Y. Quiñonez, Ivan Tostado, O. Sánchez","doi":"10.1109/MICAI.2013.46","DOIUrl":"https://doi.org/10.1109/MICAI.2013.46","url":null,"abstract":"In this paper we present a coordination model for multi-robot systems based on cooperative behaviors, where the low level behaviors are obtained through artificial neural networks and evolutionary algorithms to achieve a common goal. For this purpose, we have defined two strategies of self-alignment to carry out the docking process between two robots. Both strategies share the same goal of achieving an optimal alignment between two robots. The main difference between these strategies is that: the strategy 1 consists of having one active and one inactive robot, and in the strategy 2 both robots are active. Experimental results are presented by a robotic device simulator (Player) and a multi-robot simulator 2D (Stage) for each strategy displaying differences between both strategies and benefits in time execution. The paper ends with a critical discussion of experimental results.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114551650","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}
Ramón Zataraín-Cabada, María Lucía Barrón Estrada, José Luis Olivares Camacho, C. A. R. García
This paper presents two software systems for visual affect and learning styles recognition. The first system recognizes Paul Ekman's seven basic emotions in student expressions which are surprise, fear, disgust, anger, happiness, sadness, and neutral. The second system recognizes the student learning style using the Felder-Silverman Model. Both systems are integrated into an intelligent tutoring system in a math social network. The automatic recognition was implemented using Kohonen networks which were trained to recognize and classify emotions and learning styles. We show and discuss results by using different methods with respect to affect or emotion recognition and present the automatic response to affect results. We also present the software architecture where both recognizers collaborate with intelligent tutoring systems in a social network.
{"title":"Integrating Learning Styles and Affect with an Intelligent Tutoring System","authors":"Ramón Zataraín-Cabada, María Lucía Barrón Estrada, José Luis Olivares Camacho, C. A. R. García","doi":"10.1109/MICAI.2013.36","DOIUrl":"https://doi.org/10.1109/MICAI.2013.36","url":null,"abstract":"This paper presents two software systems for visual affect and learning styles recognition. The first system recognizes Paul Ekman's seven basic emotions in student expressions which are surprise, fear, disgust, anger, happiness, sadness, and neutral. The second system recognizes the student learning style using the Felder-Silverman Model. Both systems are integrated into an intelligent tutoring system in a math social network. The automatic recognition was implemented using Kohonen networks which were trained to recognize and classify emotions and learning styles. We show and discuss results by using different methods with respect to affect or emotion recognition and present the automatic response to affect results. We also present the software architecture where both recognizers collaborate with intelligent tutoring systems in a social network.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122731873","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}
Jesus Salvador Martinez-Delgado, S. Mendoza, Kimberly García
We propose an access control method based on the combination of two biometric recognitions: voice and face. In particular, our face recognition algorithm aims at determining a person's identity when he/she is involved in situations in which his/her face is rotated in a shoulder to shoulder trajectory, which is a common behavior on people with a stealth or intromission attitude. The other biometrics, the voice recognizer, allows us to confirm the prediction made by the face recognizer. Our method can be integrated into several systems, as it has been developed as a Web application and it does not require any special hardware, so it is highly flexible and multi-platform at the same time. Experiments reveal that our proposed method performs really well, as it gives 89% of accuracy, unlike traditional face recognition algorithms, which could not identify anyone, whose head presents a pronounced inclination.
{"title":"Flexible Bimodal Recognition of Collaborators in Pervasive Environments","authors":"Jesus Salvador Martinez-Delgado, S. Mendoza, Kimberly García","doi":"10.1109/MICAI.2013.26","DOIUrl":"https://doi.org/10.1109/MICAI.2013.26","url":null,"abstract":"We propose an access control method based on the combination of two biometric recognitions: voice and face. In particular, our face recognition algorithm aims at determining a person's identity when he/she is involved in situations in which his/her face is rotated in a shoulder to shoulder trajectory, which is a common behavior on people with a stealth or intromission attitude. The other biometrics, the voice recognizer, allows us to confirm the prediction made by the face recognizer. Our method can be integrated into several systems, as it has been developed as a Web application and it does not require any special hardware, so it is highly flexible and multi-platform at the same time. Experiments reveal that our proposed method performs really well, as it gives 89% of accuracy, unlike traditional face recognition algorithms, which could not identify anyone, whose head presents a pronounced inclination.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128707195","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}
Agility may be an important competitive advantage in many markets. In order to achieve it, the dynamics of the manufacturing systems must be considered. Control theory supports the development of dynamic models for production and inventory control. This paper discusses some dynamic models of production control specifically applied to scheduling and shop floor control. A comparative and critical analysis of the models is presented and directions for future works are provided.
{"title":"Dynamic Models for Production Control and Scheduling: A Brief Review","authors":"J. K. Sagawa, M. S. Nagano","doi":"10.1109/MICAI.2013.10","DOIUrl":"https://doi.org/10.1109/MICAI.2013.10","url":null,"abstract":"Agility may be an important competitive advantage in many markets. In order to achieve it, the dynamics of the manufacturing systems must be considered. Control theory supports the development of dynamic models for production and inventory control. This paper discusses some dynamic models of production control specifically applied to scheduling and shop floor control. A comparative and critical analysis of the models is presented and directions for future works are provided.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125000026","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}
Clustering algorithms are being widely used on biomedical data. They aim to extract important information that can be used to improve life conditions by helping specialized technicians on the decision process. Clustering algorithms based on information theory concepts claim that by using higher order statistic they are able to extract more information from the data and therefore provide much better results. In this work we try to verify this claim by comparing the performance of some entropic clustering algorithms against more conventional ones. Results of the performed experiments are not conclusive but they seem to indicate that this kind of entropic algorithms may provide some improvements when clustering biomedical data.
{"title":"Evaluating Entropic Based Clustering Algorithms on Biomedical Data","authors":"Jorge M. Santos, Frederico Morais","doi":"10.1109/MICAI.2013.31","DOIUrl":"https://doi.org/10.1109/MICAI.2013.31","url":null,"abstract":"Clustering algorithms are being widely used on biomedical data. They aim to extract important information that can be used to improve life conditions by helping specialized technicians on the decision process. Clustering algorithms based on information theory concepts claim that by using higher order statistic they are able to extract more information from the data and therefore provide much better results. In this work we try to verify this claim by comparing the performance of some entropic clustering algorithms against more conventional ones. Results of the performed experiments are not conclusive but they seem to indicate that this kind of entropic algorithms may provide some improvements when clustering biomedical data.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129337578","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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