J. Pasquier, I.K. Balich, D. W. Carr, C. López-Martín
This paper presents a comparative study of three metaheuristics: Genetic Algorithm (GA), ant Colony Optimization (AC) and Simulated Annealing (SA), implemented to solve the classical Traveling Salesman Problem (TSP). The efficiency of each approach is evaluated taking into account the execution time of the algorithm and the quality of the generated solution. Additionally, metrics of the program, including McCabe complexity, development effort and lines of code, are calculated to complete the comparative study. Finally, an evaluation of the difficulty of implementation and the quality of the results corresponding to each metaheuristic is given. The present research will help programmers understand, evaluate and implement the three metaheuristics.
{"title":"A Comparative Study of Three Metaheuristics Applied to the Traveling Salesman Problem","authors":"J. Pasquier, I.K. Balich, D. W. Carr, C. López-Martín","doi":"10.1109/MICAI.2007.14","DOIUrl":"https://doi.org/10.1109/MICAI.2007.14","url":null,"abstract":"This paper presents a comparative study of three metaheuristics: Genetic Algorithm (GA), ant Colony Optimization (AC) and Simulated Annealing (SA), implemented to solve the classical Traveling Salesman Problem (TSP). The efficiency of each approach is evaluated taking into account the execution time of the algorithm and the quality of the generated solution. Additionally, metrics of the program, including McCabe complexity, development effort and lines of code, are calculated to complete the comparative study. Finally, an evaluation of the difficulty of implementation and the quality of the results corresponding to each metaheuristic is given. The present research will help programmers understand, evaluate and implement the three metaheuristics.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"41 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":"124008854","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. Gómez-Villouta, Jean-Philippe Hamiez, Jin-Kao Hao
This paper introduces DGA, a new dedicated genetic algorithm for a two-dimensional (2D) non-guillotine strip packing problem (2D-SPP). DGA integrates two key features: a hierarchical fitness function and a problem-specific crossover operator (WAX for "wasted area based crossover"). The fitness function takes into account not only the final height of the strip (to be minimized), but also the wasted areas. The goal of the meaningful (and "visual'') WAX crossover operator is to preserve the good property of parent packing configurations. To assess the proposed DGA, experimental results are shown on a set of well-known zero-waste benchmark instances and compared with previously reported genetic algorithms as well as the best performing meta-heuristic algorithms.
{"title":"A Dedicated Genetic Algorithm for Two-Dimensional Non-Guillotine Strip Packing","authors":"G. Gómez-Villouta, Jean-Philippe Hamiez, Jin-Kao Hao","doi":"10.1109/MICAI.2007.36","DOIUrl":"https://doi.org/10.1109/MICAI.2007.36","url":null,"abstract":"This paper introduces DGA, a new dedicated genetic algorithm for a two-dimensional (2D) non-guillotine strip packing problem (2D-SPP). DGA integrates two key features: a hierarchical fitness function and a problem-specific crossover operator (WAX for \"wasted area based crossover\"). The fitness function takes into account not only the final height of the strip (to be minimized), but also the wasted areas. The goal of the meaningful (and \"visual'') WAX crossover operator is to preserve the good property of parent packing configurations. To assess the proposed DGA, experimental results are shown on a set of well-known zero-waste benchmark instances and compared with previously reported genetic algorithms as well as the best performing meta-heuristic algorithms.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"73 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":"129164523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J.C. Riao-Rojas, F. A. Prieto-Ortiz, L.J. Morantes, E. Sanchez-Camperos, F. Jaramillo‐Ayerbe
A methodology for segmentation and extraction morphologic feature from nailfold capillaroscopic images is presented. The main characteristic of the images studied here is the low contrast between the background and the capillaries.For this reason, three fundamental steps were applied in the preprocess: correction of the illumination, highlight and smoothing. For segmenting these images, Laplacians of the most contrasted component in each color space and the connectedness by threshold (region growth) were integrated. The extraction was carried out using image processing techniques such as principal components analysis (PCA), fractal geometry and tortuosity index (TI); their properties were proven. Tortuosity index is a clinical variable subjective to the expert, it is presented as the ratio between the area and the fractal dimension (FD) of the capillary region. Other features obtained were width and height, density of capillaries, area and perimeter, orientation and polarity. The work was carried out on 300 capillaries obtained from images of subjects that do not suffer vascular diseases of the connective tissues and 250 capillaries of patients that have Lupus erythematosus (SLE). Images were taken from the third and fourth fingers of both subjectpsilas hands. The application of the automatic segmentation allowed the classification of the capillary tortuosity and the comparison to the manual segmentation which was made on 47 capillary images by an expert in dermatology.
{"title":"Segmentation and Extraction of Morphologic Features from Capillary Images","authors":"J.C. Riao-Rojas, F. A. Prieto-Ortiz, L.J. Morantes, E. Sanchez-Camperos, F. Jaramillo‐Ayerbe","doi":"10.1109/MICAI.2007.40","DOIUrl":"https://doi.org/10.1109/MICAI.2007.40","url":null,"abstract":"A methodology for segmentation and extraction morphologic feature from nailfold capillaroscopic images is presented. The main characteristic of the images studied here is the low contrast between the background and the capillaries.For this reason, three fundamental steps were applied in the preprocess: correction of the illumination, highlight and smoothing. For segmenting these images, Laplacians of the most contrasted component in each color space and the connectedness by threshold (region growth) were integrated. The extraction was carried out using image processing techniques such as principal components analysis (PCA), fractal geometry and tortuosity index (TI); their properties were proven. Tortuosity index is a clinical variable subjective to the expert, it is presented as the ratio between the area and the fractal dimension (FD) of the capillary region. Other features obtained were width and height, density of capillaries, area and perimeter, orientation and polarity. The work was carried out on 300 capillaries obtained from images of subjects that do not suffer vascular diseases of the connective tissues and 250 capillaries of patients that have Lupus erythematosus (SLE). Images were taken from the third and fourth fingers of both subjectpsilas hands. The application of the automatic segmentation allowed the classification of the capillary tortuosity and the comparison to the manual segmentation which was made on 47 capillary images by an expert in dermatology.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"22 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":"115281683","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}
We have developed an affective behavior model for intelligent tutoring systems. The aim of the model is to provide students with a tutorial action taking into account both, the affective and the pedagogical state of the student. The affective behavior model considers the student’s pedagogical and affective state, this last one is based on the OCC and Five-factor models. To select the tutorial actions according to the pedagogical and affective state, we propose the use of a dynamic decision network with a utility measure on both, learning and affect. We have integrated the affective behavior model to an educational game to learn number factorization and evaluated its performance with a group of students. To evaluate the affective behavior model we designed a user study with a group of students playing with the educational game without the affective behavior model, and another group that included the affective behavior model. After that, we compared the learning gain in both groups. In this paper we describe the affective behavior model and present the results of the user study.
{"title":"Intelligent Tutoring System with Affective Behavior","authors":"Y. Hernández, G. Arroyo-Figueroa, L. Sucar","doi":"10.1109/MICAI.2007.15","DOIUrl":"https://doi.org/10.1109/MICAI.2007.15","url":null,"abstract":"We have developed an affective behavior model for intelligent tutoring systems. The aim of the model is to provide students with a tutorial action taking into account both, the affective and the pedagogical state of the student. The affective behavior model considers the student’s pedagogical and affective state, this last one is based on the OCC and Five-factor models. To select the tutorial actions according to the pedagogical and affective state, we propose the use of a dynamic decision network with a utility measure on both, learning and affect. We have integrated the affective behavior model to an educational game to learn number factorization and evaluated its performance with a group of students. To evaluate the affective behavior model we designed a user study with a group of students playing with the educational game without the affective behavior model, and another group that included the affective behavior model. After that, we compared the learning gain in both groups. In this paper we describe the affective behavior model and present the results of the user study.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"181 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":"128202880","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}
Juan Pablo Nieto González, L. Castañón, R. M. Menéndez
Power systems monitoring is particularly challenging due to the presence of dynamic load changes in normal operation mode of network nodes, as well as the presence of both continuous and discrete variables, noisy information and lack or excess of data. This paper proposes a fault diagnosis framework that is able to locate the set of nodes involved in multiple fault events and detects the type of fault in those nodes. The framework is composed of two phases: In the first phase a probabilistic neural network is trained with the eigenvalues of voltage data collected during symmetrical and unsymmetrical fault disturbances. The eigenvalues are computed from the correlation matrix built from historical data, and are used as neural network inputs. The neural network is able to carry out a first classification/discrimination process of nodes states, obtaining in this way a reduction on data analysis. In the second phase a sample magnitude comparison is used to detect and locate the presence of a fault. A set of simulations are carried out over an electrical power system to show the performance of the proposed framework and a comparison is made against a diagnostic system based on probabilistic logic.
{"title":"Multiple Fault Diagnosis in Electrical Power Systems with Probabilistic Neural Networks","authors":"Juan Pablo Nieto González, L. Castañón, R. M. Menéndez","doi":"10.1109/MICAI.2007.31","DOIUrl":"https://doi.org/10.1109/MICAI.2007.31","url":null,"abstract":"Power systems monitoring is particularly challenging due to the presence of dynamic load changes in normal operation mode of network nodes, as well as the presence of both continuous and discrete variables, noisy information and lack or excess of data. This paper proposes a fault diagnosis framework that is able to locate the set of nodes involved in multiple fault events and detects the type of fault in those nodes. The framework is composed of two phases: In the first phase a probabilistic neural network is trained with the eigenvalues of voltage data collected during symmetrical and unsymmetrical fault disturbances. The eigenvalues are computed from the correlation matrix built from historical data, and are used as neural network inputs. The neural network is able to carry out a first classification/discrimination process of nodes states, obtaining in this way a reduction on data analysis. In the second phase a sample magnitude comparison is used to detect and locate the presence of a fault. A set of simulations are carried out over an electrical power system to show the performance of the proposed framework and a comparison is made against a diagnostic system based on probabilistic logic.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"43 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":"124836447","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}
An orthogonal neural network with Hermite activation function to reduce nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over a Multicarrier Transmitter is proposed. The neural network has the fixed input weights and only linear output weights are estimated using the Moore-Penrose generalized inverse method. Computer simulation results show that proposed neural network achieves excellent performance in nonlinearities reduction caused by TWTA. In addition, proposed scheme has a low complexity and fast convergence speed.
{"title":"Orthogonal Neural Network for Nonlinearities Reduction of Multicarrier Transmitters","authors":"Nibaldo Rodríguez, Orlando Durán, Claudio Cubillos","doi":"10.1109/MICAI.2007.45","DOIUrl":"https://doi.org/10.1109/MICAI.2007.45","url":null,"abstract":"An orthogonal neural network with Hermite activation function to reduce nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over a Multicarrier Transmitter is proposed. The neural network has the fixed input weights and only linear output weights are estimated using the Moore-Penrose generalized inverse method. Computer simulation results show that proposed neural network achieves excellent performance in nonlinearities reduction caused by TWTA. In addition, proposed scheme has a low complexity and fast convergence speed.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"66 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":"122773212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J.G. Avia-Cervantes, S. Ledezma-Orozco, M. Torres-Cisneros, D. Hernández-Fusilier, J. González-Barbosa, A. Salazar-Garibay
This paper presents a recognition method for natural images based on color texture histograms in the context of image interpretation and scene modeling. A color histogram of sums and differences is proposed to obtain texture features which are faster to compute than correlograms ( i.e., colored version of co-occurrence matrices) and improving substantially object recognition. Outdoor natural images are generally affected by color casting artifacts which can affect object recognition. Therefore, an on-line color balancing algorithm based on chromatic adaptation models, eliminates these color deviations. The proposed approach globally involves functions as color segmentation, histogram texture analysis and a region recognition step. Our approach has been extensively tested and validated to obtain an accurate 2D scene interpretation from natural images. This technique may be used in robot navigation by identifying navigable regions ( e.g., roads or fairly flat surfaces) on natural scenes, scene modeling and image categorization.
{"title":"Color Texture Histograms for Natural Images Interpretation","authors":"J.G. Avia-Cervantes, S. Ledezma-Orozco, M. Torres-Cisneros, D. Hernández-Fusilier, J. González-Barbosa, A. Salazar-Garibay","doi":"10.1109/MICAI.2007.19","DOIUrl":"https://doi.org/10.1109/MICAI.2007.19","url":null,"abstract":"This paper presents a recognition method for natural images based on color texture histograms in the context of image interpretation and scene modeling. A color histogram of sums and differences is proposed to obtain texture features which are faster to compute than correlograms ( i.e., colored version of co-occurrence matrices) and improving substantially object recognition. Outdoor natural images are generally affected by color casting artifacts which can affect object recognition. Therefore, an on-line color balancing algorithm based on chromatic adaptation models, eliminates these color deviations. The proposed approach globally involves functions as color segmentation, histogram texture analysis and a region recognition step. Our approach has been extensively tested and validated to obtain an accurate 2D scene interpretation from natural images. This technique may be used in robot navigation by identifying navigable regions ( e.g., roads or fairly flat surfaces) on natural scenes, scene modeling and image categorization.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"76 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":"134244261","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}
We elaborate in this paper on the idea of translating situation calculus specifications into logic programs, thus making these specifications executable. We show a Topor-Lloyd-like procedure that transforms situation calculus specifications, mainly intended to stem from database environments, into logic program rules that can be subsequently executed or that could be transformed into deductive or relational database programs. Basically we stress the concept of query safeness, that is central in the database context and we combine for that purpose the concepts of allowed formula and of simple formula into a formal framework with a formal logic programming semantics.
{"title":"An Interface between the Situation Calculus and Logic Programming","authors":"Pablo D. Sáez","doi":"10.1109/MICAI.2007.38","DOIUrl":"https://doi.org/10.1109/MICAI.2007.38","url":null,"abstract":"We elaborate in this paper on the idea of translating situation calculus specifications into logic programs, thus making these specifications executable. We show a Topor-Lloyd-like procedure that transforms situation calculus specifications, mainly intended to stem from database environments, into logic program rules that can be subsequently executed or that could be transformed into deductive or relational database programs. Basically we stress the concept of query safeness, that is central in the database context and we combine for that purpose the concepts of allowed formula and of simple formula into a formal framework with a formal logic programming semantics.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"10 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":"128279622","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 work, four different causal relevancy (CR) approaches are implemented within the inference engine of the fuzzy inductive reasoning (FIR) methodology. The idea behind CR is to quantify how much influence each system feature has, on the forecasting of the output. This paper presents and discusses the FIR inference engine, and describes how it can be enhanced using the causal relevancy methods proposed in this study. The first two CR methods compute the relevancy of each feature by means of the quality of the optimal mask, obtained in the qualitative model identification step of the FIR methodology. The last two CR methods are based on the prediction error of a validation data set, not used in the model identification process. The CR approaches presented in the paper are applied to a real e-learning course with the goal of improve studentspsila behavior predictions. The experiments carried out with the available data indicate that lower prediction errors are obtained using the CR approaches when compared with the results obtained by the classical FIR inference engine. The new approaches help to improve the understanding of the educative process by describing how much influence each system feature has on the output.
{"title":"Causal Relevancy Approaches to Improve the Students' Prediction Performance in an e-Learning Environment","authors":"F. Castro, F. Mugica, À. Nebot","doi":"10.1109/MICAI.2007.28","DOIUrl":"https://doi.org/10.1109/MICAI.2007.28","url":null,"abstract":"In this work, four different causal relevancy (CR) approaches are implemented within the inference engine of the fuzzy inductive reasoning (FIR) methodology. The idea behind CR is to quantify how much influence each system feature has, on the forecasting of the output. This paper presents and discusses the FIR inference engine, and describes how it can be enhanced using the causal relevancy methods proposed in this study. The first two CR methods compute the relevancy of each feature by means of the quality of the optimal mask, obtained in the qualitative model identification step of the FIR methodology. The last two CR methods are based on the prediction error of a validation data set, not used in the model identification process. The CR approaches presented in the paper are applied to a real e-learning course with the goal of improve studentspsila behavior predictions. The experiments carried out with the available data indicate that lower prediction errors are obtained using the CR approaches when compared with the results obtained by the classical FIR inference engine. The new approaches help to improve the understanding of the educative process by describing how much influence each system feature has on the output.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"18 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":"121986962","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 work basic mathematical morphology operations, such as dilation, erosion, opening, and closing, are reformulated and characterized by means of equivalent cellular automata. In this manner, it becomes possible to take advantage of the broad extent of solid results of theory and applications of cellular automata in creating new algorithms where mathematical morphology is applied, with the advantages of its cellular formulation.
{"title":"Cellular Mathematical Morphology","authors":"B. L. Benoso, J. Nazuno, C.Y. Marquez, I.L. Yaez","doi":"10.1109/MICAI.2007.30","DOIUrl":"https://doi.org/10.1109/MICAI.2007.30","url":null,"abstract":"In this work basic mathematical morphology operations, such as dilation, erosion, opening, and closing, are reformulated and characterized by means of equivalent cellular automata. In this manner, it becomes possible to take advantage of the broad extent of solid results of theory and applications of cellular automata in creating new algorithms where mathematical morphology is applied, with the advantages of its cellular formulation.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"22 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":"127931114","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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