Modelo de un sistema para la selección automática en dominios complejos con una estrategia cooperativa, de conjuntos de entrenamiento y arquitecturas ideales de redes de neuronas artificiales ulilizando alogaritmos genéticos

[Resumen] Esta tesis estudia el desarrollo de un modelo de sistema evolutivo y distribuido para la automatización y optimización de la construcción de RR,NN.AA. que se apliquen a dominios complejos. Los trabajos de investigación se centran en cuatro áreas: * Identificar, de forma automática, configuraciones óptimas de capas, elementos de proceso (EP) y parámetros de los EP, evitando el proceso de prueba y error que, actualmente, realiza el diseñador de la red. * Diseñar un método para la selección de un conjunto de entrenamiento óptimo a partir de series temporales, complementando así los métodos existentes para la discriminación de variables de entrada. * Se propone un método alternativo para el proceso de entrenamiento de RR.NN.AA. ya que, al aplicarlas a problemas complejos, como la predicción en el dominio temporal, los métodos de gradiente presentan problemas de mínimos locales. * Por último, se pretende armonizar, con una aproximación cooperativa, las distintas fases de desarrollo de la RNA: diseño del conjunto de entrenamiento, ajuste de los parámetros de la arquitectura y proceso de entrenamiento

Approach for solving multimodal problems using Genetic Algorithms with Grouped into Species optimized with Predator-Prey

Over recent years, Genetic Algorithms have proven to be an appropriate tool for solving certain problems. However, it does not matter if the search space has several valid solutions, as their classic approach is insufficient. To this end, the idea of dividing the individuals into species has been successfully raised. However, this solution is not free of drawbacks, such as the emergence of redundant species, overlapping or performance degradation by significantly increasing the number of individuals to be evaluated. This paper presents the implementation of a method based on the predator-prey technique, with the aim of providing a solution to the problem, as well as a number of examples to prove its effectiveness

Classification of Signals by Means of Genetic Programming

[Abstract] This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. Instead of it, GP is able to extract the most relevant features needed for classification. This technique has been applied for the solution of a well-known problem: the classification of EEG signals in epileptic and healthy patients. In this problem, signals obtained from EEG recordings must be correctly classified into their corresponding class. The aim is to show that the technique described here, with the automatic extraction of features, can return better results than the classical techniques based on manual extraction of features. For this purpose, a final comparison between the results obtained with this technique and other results found in the literature with the same database can be found. This comparison shows how this technique can improve the ones found.Instituto de Salud Carlos III; RD07/0067/0005Xunta de Galicia; 10SIN105004P

Developing a Secure Low-Cost Radon Monitoring System

[Abstract] Radon gas has been declared a human carcinogen by the United States Environmental Protection Agency (USEPA) and the International Agency for Research on Cancer (IARC). Several studies carried out in Spain highlighted the high radon concentrations in several regions, with Galicia (northwestern Spain) being one of the regions with the highest radon concentrations. The objective of this work was to create a safe and low-cost radon monitoring and alert system, based on open source technologies. To achieve this objective, the system uses devices, a collection of sensors with a processing unit and a communication module, and a backend, responsible for managing all the information, predicting radon levels and issuing alerts using open source technologies. Security is one of the largest challenges for the internet of things, and it is utterly important in the current scenario, given that high radon concentrations pose a health risk. For this reason, this work focuses on securing the entire end-to-end communication path to avoid data forging. The results of this work indicate that the development of a low-cost, yet secured, radon monitoring system is feasible, allowing one to create a network of sensors that can help mitigate the health hazards that high radon concentrations pose.This project was funded by the Consolidation and Structuring of Competitive Research Units-Competitive Reference Groups (ED431C 2018/49) and Accreditation, Structuring, and Improvement of Consolidated Research Units and Singular Centers (ED431G/01), funded by the Ministry of Education, University and Vocational Training of the Xunta de Galicia endowed with EU FEDER funds. This research was supported by the Spanish Ministry of Economy, Industry and Competitiveness, R & D National Plan, via the project BIA2017-86738-R. This research and the APC were also supported by Instituto de Salud Carlos III, grant number PI17/01826 (Collaborative Project in Genomic Data Integration (CICLOGEN) funded by the Instituto de Salud Carlos III from the Spanish National plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—“A way to build Europe.”. This project was also supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia ED431D 2017/16 and “Drug Discovery Galician Network” Ref. ED431G/01 and the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23), and finally by the Spanish Ministry of Economy and Competitiveness through the funding of the unique installation BIOCAI (UNLC08-1E-002, UNLC13-13-3503) and the European Regional Development Funds (FEDER) by the European UnionXunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/2

Obtendo información útil para a mellora dunha materia a partir dos resultados dos exames de resposta múltiple

[Resumo] Os procesos de avaliación, deben aplicarse ós docentes e mesmo á materia en si, non só ós alumnos. Con esta finalidade formúlase unha análise dos resultados acadados polo alumnado durante a proba de avaliación empregada na materia de Marcos de Desenvolvemento (Grao en Enxeñaría Informática – Facultade de Informática). O exame é de resposta múltiple (4 opcións por pregunta, só unha válida e restando puntos as respostas erróneas). Os exames analízanse en dúas ramas: por unha banda, estúdanse as taxas de acerto/fallo/en branco de cada unha das preguntas; por outra, a porcentaxe de opcións (a,b,c,d, branco) en cada pregunta. Este sinxelo estudo, automatizado mediante o emprego dunha folla de cálculo, permite, non obstante, obter interesantes conclusións: • Detecta ambigüidades ou erros na formulación das preguntas que, polo xeral, se derivan nunha elevada porcentaxe de respostas en branco. • Detecta lagoas de coñecemento nalgunha das áreas da materia, que orixinan preguntas cunha elevada taxa de erros. Cada pregunta está asociada a un bloque teórico, polo que se podes establecer en qué aspectos os alumnos presentan máis ou menos coñecementos. Ambos aspectos poden ser empregados para detectar erros na formulación da materia e/ou exame e facer posible así a definición de plans de mellora de cara ós vindeiros cursos académicos

Two-Dimensional Gel Electrophoresis Image Registration Using Block-Matching Techniques and Deformation Models

[Abstract] Block-matching techniques have been widely used in the task of estimating displacement in medical images, and they represent the best approach in scenes with deformable structures such as tissues, fluids, and gels. In this article, a new iterative block-matching technique—based on successive deformation, search, fitting, filtering, and interpolation stages—is proposed to measure elastic displacements in two-dimensional polyacrylamide gel electrophoresis (2D–PAGE) images. The proposed technique uses different deformation models in the task of correlating proteins in real 2D electrophoresis gel images, obtaining an accuracy of 96.6% and improving the results obtained with other techniques. This technique represents a general solution, being easy to adapt to different 2D deformable cases and providing an experimental reference for block-matching algorithms.Galicia. Consellería de Economía e Industria; 10MDS014CTGalicia. Consellería de Economía e Industria; 10SIN105004PRInstituto de Salud Carlos III; PI13/0028

Exploring Patterns of Epigenetic Information With Data Mining Techniques

[Abstract] Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are mitotically and/or meiotically heritable determining gene expression and cellular differentiation, as well as cellular fate. Epigenetic lesions and genetic mutations are acquired by individuals during their life and accumulate with ageing. Both defects, either together or individually, can result in losing control over cell growth and, thus, causing cancer development. Data mining techniques could be then used to extract the previous patterns. This work reviews some of the most important applications of data mining to epigenetics.Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; 209RT-0366Galicia. Consellería de Economía e Industria; 10SIN105004PRInstituto de Salud Carlos III; RD07/0067/000