An approach on the implementation of full batch, online and mini-batch learning on a Mamdani based neuro-fuzzy system with center-of-sets defuzzification: Analysis and evaluation about its functionality, performance, and behavior.

Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the methods for its processing have to adapt to this condition, focusing mainly on ensuring the computation is efficient, especially when the analysis tools are based on computational intelligence techniques. As we know, if you do not have a good control of the handling of the volume of the data, some techniques that are based on learning iterative processes could represent an excessive load of computation and could take a prohibitive time in trying to find a solution that could not come close to desired. There are learning methods known as full batch, online and mini-batch, and they represent a good strategy to this problem since they are oriented to the processing of data according to the size or volume of available data samples that require analysis. In this first approach, synthetic datasets with a small and medium volume were used, since the main objective is to define its implementation and in experimentation phase through regression analysis obtain information that allows us to assess the performance and behavior of different learning methods under distinct conditions. To carry out this study, a Mamdani based neuro-fuzzy system with center-of-sets defuzzification with support of multiple inputs and outputs was designed and implemented that had the flexibility to use any of the three learning methods, which were implemented within the training process. Finally, results show that the learning method with best performances was Mini-Batch when compared to full batch and online learning methods. The results obtained by mini-batch learning method are as follows; mean correlation coefficient [Formula: see text] with 0.8268 and coefficient of determination [Formula: see text] with 0.7444, and is also the method with better control of the dispersion between the results obtained from the 30 experiments executed per each dataset processed.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.

Fuzzy Index to Evaluate Edge Detection in Digital Images.

In literature, we can find different metrics to evaluate the detected edges in digital images, like Pratt's figure of merit (FOM), Jaccard's index (JI) and Dice's coefficient (DC). These metrics compare two images, the first one is the reference edges image, and the second one is the detected edges image. It is important to mention that all existing metrics must binarize images before their evaluation. Binarization step causes information to be lost because an incomplete image is being evaluated. In this paper, we propose a fuzzy index (FI) for edge evaluation that does not use a binarization step. In order to process all detected edges, images are represented in their fuzzy form and all calculations are made with fuzzy sets operators and fuzzy Euclidean distance between both images. Our proposed index is compared to the most used metrics using synthetic images, with good results.

[Narrative review of scales assessing attention-deficit/hyperactivity disorder in children and adolescents]. / Una revisión narrativa de las escalas de evaluación usadas para el diagnóstico del trastorno por déficit de atención e hiperactividad en niños y adolescentes.

CONTEXT: Attention-deficit/hyperactivity disorder is a common neurobehavioral disorder in school-age population and is a major driver of mental health consultation. Diagnosis is hindered by the difficulty of objectively assessing subjective aspects such as inattention or impulsivity. PURPOSE: To briefly describe the most widely used rating scales as tools for the diagnosis of attention-deficit/hyperactivity disorder, subtypes and comorbidities, based on a review of information available in MEDLINE, Medic America, Academic Search Complete and Mendeley databases. ANALYSIS: This disorder is poorly understood in the family and school environment, which hampers detection and timely treatment. Rating scales have advantages and disadvantages, but they are undoubtedly important for an initial approach to the clinical manifestations of attention-deficit/hyperactivity disorder. CONCLUSION: There is a need for better diagnostic tools or scales that take into account the stage of neurodevelopment, other developmental stages, gender differences, sociocultural aspects and diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, fifth edition.

CONTEXTO: El trastorno por déficit de atención e hiperactividad es un trastorno neuroconductual frecuente en la población escolar y representa uno de los principales motivos de consulta en servicios de salud mental. Su diagnóstico es complicado por la dificultad que representa la evaluación objetiva de aspectos subjetivos como la desatención o la impulsividad. OBJETIVO: Describir de manera resumida las escalas de valoración más utilizadas como herramientas para el diagnóstico del trastorno por déficit de atención e hiperactividad, los subtipos y comorbilidades, fundada en una revisión de la información disponible en las bases de datos MEDLINE, Medic Latina, Academic Search Complete y Mendeley. ANÁLISIS: Este trastorno es poco comprendido en el entorno familiar y escolar, lo que dificulta su detección y tratamiento oportuno. Las escalas de evaluación presentan ventajas y desventajas, pero sin duda son importantes para un primer acercamiento a las manifestaciones clínicas del trastorno por déficit de atención e hiperactividad. CONCLUSIÓN: Se observa la necesidad de buscar mejores herramientas diagnósticas o escalas que tomen en cuenta la etapa del neurodesarrollo, las demás etapas evolutivas, las diferencias por género, aspectos socioculturales y los criterios diagnósticos del Manual Diagnóstico y Estadístico de Trastornos Mentales, quinta edición.

Una revisión narrativa de las escalas de evaluación usadas para el diagnóstico del trastorno por déficit de atención e hiperactividad en niños y adolescentes / Narrative review of scales assessing attention-deficit/hyperactivity disorder in children and adolescents

Contexto: el trastorno por déficit de atención e hiperactividad es un trastorno neuroconductual frecuente en la población escolar y representa uno de los principales motivos de consulta en servicios de salud mental. Su diagnóstico es complicado por la dificultad que representa la evaluación objetiva de aspectos subjetivos como la desatención o la impulsividad. Objetivo: describir de manera resumida las escalas de valoración más utilizadas como herramientas para el diagnóstico del trastorno por déficit de atención e hiperactividad, los subtipos y comorbilidades, fundada en una revisión de la información disponible en las bases de datos MEDLINE, Medic Latina, Academic Search Complete y Mendeley. Análisis: este trastorno es poco comprendido en el entorno familiar y escolar, lo que dificulta su detección y tratamiento oportuno. Las escalas de evaluación presentan ventajas y desventajas, pero sin duda son importantes para un primer acercamiento a las manifestaciones clínicas del trastorno por déficit de atención e hiperactividad. Conclusión: se observa la necesidad de buscar mejores herramientas diagnósticas o escalas que tomen en cuenta la etapa del neurodesarrollo, las demás etapas evolutivas, las diferencias por género, aspectos socioculturales y los criterios diagnósticos del Manual Diagnóstico y Estadístico de Trastornos Mentales, quinta edición.

Context. Attention-deficit/hyperactivity disorder is a common neurobehavioral disorder in school-age population and is a major driver of mental health consultation. Diagnosis is hindered by the difficulty of objectively assessing subjective aspects such as inattention or impulsivity. Purpose. To briefly describe the most widely used rating scales as tools for the diagnosis of attention-deficit/hyperactivity disorder, subtypes and comorbidities, based on a review of information available in MEDLINE, Medic America, Academic Search Complete and Mendeley databases. Analysis. This disorder is poorly understood in the family and school environment, which hampers detection and timely treatment. Rating scales have advantages and disadvantages, but they are undoubtedly important for an initial approach to the clinical manifestations of attention-deficit/hyperactivity disorder. Conclusion. There is a need for better diagnostic tools or scales that take into account the stage of neurodevelopment, other developmental stages, gender differences, sociocultural aspects and diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, fifth edition.