Multi-objective metaheuristics for preprocessing EEG data in brain–computer interfaces

In the field of brain–computer interfaces, one of the main issues is to classify the electroencephalogram (EEG) accurately. EEG signals have a good temporal resolution, but a low spatial one. In this article, metaheuristics are used to compute spatial filters to improve the spatial resolution. Additionally, from a physiological point of view, not all frequency bands are equally relevant. Both spatial filters and relevant frequency bands are user-dependent. In this article a multi-objective formulation for spatial filter optimization and frequency-band selection is proposed. Several multi-objective metaheuristics have been tested for this purpose. The experimental results show, in general, that multi-objective algorithms are able to select a subset of the available frequency bands, while maintaining or improving the accuracy obtained with the whole set. Also, among the different metaheuristics tested, GDE3, which is based on differential evolution, is the most useful algorithm in this contextThis work has been funded by the Spanish Ministry of Science under contract TIN2008-06491-C04-03 (MSTAR project).Publicad

An experimental study on fitness distributions of tree shapes in GP with one-point crossover

Proceeding of: 12th European Conference, EuroGP 2009, Tübingen, Germany, April 15-17In Genetic Programming (GP), One-Point Crossover is an alternative to the destructive properties and poor performance of Standard Crossover. One-Point Crossover acts in two phases, first making the population converge to a common tree shape, then looking for the best individual within that shape. So, we understand that One-Point Crossover is making an implicit evolution of tree shapes. We want to know if making this evolution explicit could lead to any improvement in the search power of GP. But we first need to define how this evolution could be performed. In this work we made an exhaustive study of fitness distributions of tree shapes for 6 different GP problems. We were able to identify common properties on distributions, and we propose a method to explicitly evaluate tree shapes. Based on this method, in the future, we want to implement a new genetic operator and a novel representation system for GP.This work has been funded by the Spanish Ministry of Education and Science and FEDER under contract TIN2005-08818-C04 (the OPLINK project) and by Comunidad de Madrid under contract 2008/00035/001 (Técnicas de Aprendizaje Automático Aplicadas al Interfaz Cerebro-Ordenador)Publicad

Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types

Recent research has shown that the integration or blending of different forecasting models is able to improve the predictions of solar radiation. However, most works perform model blending to improve point forecasts, but the integration of forecasting models to improve probabilistic forecasting has not received much attention. In this work the estimation of prediction intervals for the integration of four Global Horizontal Irradiance (GHI) forecasting models (Smart Persistence, WRF-solar, CIADcast, and Satellite) is addressed. Several short-term forecasting horizons, up to one hour ahead, have been analyzed. Within this context, one of the aims of the article is to study whether knowledge about the synoptic weather conditions, which are related to the stability of weather, might help to reduce the uncertainty represented by prediction intervals. In order to deal with this issue, information about which weather type is present at the time of prediction, has been used by the blending model. Four weather types have been considered. A multi-objective variant of the Lower Upper Bound Estimation approach has been used in this work for prediction interval estimation and compared with two baseline methods: Quantile Regression (QR) and Gradient Boosting (GBR). An exhaustive experimental validation has been carried out, using data registered at Seville in the Southern Iberian Peninsula. Results show that, in general, using weather type information reduces uncertainty of prediction intervals, according to all performance metrics used. More specifically, and with respect to one of the metrics (the ratio between interval coverage and width), for high-coverage (0.90, 0.95) prediction intervals, using weather type enhances the ratio of the multi-objective approach by 2%¿. Also, comparing the multi-objective approach versus the two baselines for high-coverage intervals, the improvement is 11%¿% over QR and 10%¿% over GBR. Improvements for low-coverage intervals (0.85) are smaller.The authors are supported by projects funded by Agencia Estatal de Investigación, Spain (PID2019-107455RB-C21 and PID2019-107455RB-C22/AEI/10.13039/501100011033). Also supported by Spanish Ministry of Economy and Competitiveness, project ENE2014-56126-C2-1-R and ENE2014-56126-C2-2-R (http://prosol.uc3m.es). The University of Jaén team is also supported by FEDER, Spain funds and by the Junta de Andalucía, Spain (Research group TEP-220

Optimization Algorithms for Large-Scale Real-World Instances of the Frequency Assignment Problem

Nowadays, mobile communications are experiencing a strong growth, being more and more indispensable. One of the key issues in the design of mobile networks is the Frequency Assignment Problem (FAP). This problem is crucial at present and will remain important in the foreseeable future. Real world instances of FAP typically involve very large networks, which can only be handled by heuristic methods. In the present work, we are interested in optimizing frequency assignments for problems described in a mathematical formalism that incorporates actual interference information, measured directly on the field, as is done in current GSM networks. To achieve this goal, a range of metaheuristics have been designed, adapted, and rigourously compared on two actual GSM networks modeled according to the latter formalism. In order to generate quickly and reliably high quality solutions, all metaheuristics combine their global search capabilities with a local-search method specially tailored for this domain. The experiments and statistical tests show that in general, all metaheuristics are able to improve upon results published in previous studies, but two of the metaheuristics emerge as the best performers: a population-based algorithm (Scatter Search) and a trajectory based (1+1) Evolutionary Algorithm. Finally, the analysis of the frequency plans obtained offers insight about how the interference cost is reduced in the optimal plans.Publicad

GHEP-ISFG collaborative exercise on mixture profiles of autosomal STRs (GHEP-MIX01, GHEP-MIX02 and GHEP-MIX03): results and evaluation

One of the main objectives of the Spanish and Portuguese-Speaking Group of the International Society for Forensic Genetics (GHEP-ISFG) is to promote and contribute to the development and dissemination of scientific knowledge in the area of forensic genetics. Due to this fact, GHEP-ISFG holds different working commissions that are set up to develop activities in scientific aspects of general interest. One of them, the Mixture Commission of GHEP-ISFG, has organized annually, since 2009, a collaborative exercise on analysis and interpretation of autosomal short tandem repeat (STR) mixture profiles. Until now, three exercises have been organized (GHEP-MIX01, GHEP-MIX02 and GHEP-MIX03), with 32, 24 and 17 participant laboratories respectively. The exercise aims to give a general vision by addressing, through the proposal of mock cases, aspects related to the edition of mixture profiles and the statistical treatment. The main conclusions obtained from these exercises may be summarized as follows. Firstly, the data show an increased tendency of the laboratories toward validation of DNA mixture profiles analysis following international recommendations (ISO/IEC 17025:2005). Secondly, the majority of discrepancies are mainly encountered in stutters positions (53.4%, 96.0% and 74.9%, respectively for the three editions). On the other hand, the results submitted reveal the importance of performing duplicate analysis by using different kits in order to reduce errors as much as possible. Regarding the statistical aspect (GHEP-MIX02 and 03), all participants employed the likelihood ratio (LR) parameter to evaluate the statistical compatibility and the formulas employed were quite similar. When the hypotheses to evaluate the LR value were locked by the coordinators (GHEP-MIX02) the results revealed a minor number of discrepancies that were mainly due to clerical reasons. However, the GHEP-MIX03 exercise allowed the participants to freely come up with their own hypotheses to calculate the LR value. In this situation the laboratories reported several options to explain the mock cases proposed and therefore significant differences between the final LR values were obtained. Complete information concerning the background of the criminal case is a critical aspect in order to select the adequate hypotheses to calculate the LR value. Although this should be a task for the judicial court to decide, it is important for the expert to account for the different possibilities and scenarios, and also offer this expertise to the judge. In addition, continuing education in the analysis and interpretation of mixture DNA profiles may also be a priority for the vast majority of forensic laboratories.Fil: Sala, Adriana Andrea. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Crespillo, M.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Barrio, P. A.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Luque, J. A.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Alves, Cíntia. Universidad de Porto; PortugalFil: Aler, M.. Servicio de Laboratorio. Sección de Genética Forense y Criminalística; EspañaFil: Alessandrini, F.. Università Politecnica delle Marche. Department of Biomedical Sciences and Public Health; ItaliaFil: Andrade, L.. Instituto Nacional de Medicina Legal e Ciências Forenses, Delegação do Centro. Serviço de Genética e Biologia Forenses; PortugalFil: Barretto, R. M.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bofarull, A.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Costa, S.. Instituto Nacional de Medicina Legal y Ciencias Forenses; PortugalFil: García, M. A.. Servicio de Criminalística de la Guardia Civil. Laboratorio Central de Criminalística. Departamento de Biología; EspañaFil: García, O.. Basque Country Police. Forensic Genetics Section. Forensic Science Unit; EspañaFil: Gaviria, A.. Cruz Roja Ecuatoriana. Laboratorio de Genética Molecular; EcuadorFil: Gladys, A.. Corte Suprema de Justicia de la Nación; ArgentinaFil: Gorostiza, A.. Grupo Zeltia. Genomica S. A. U.. Laboratorio de Identificación Genética; EspañaFil: Hernández, A.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Herrera, M.. Laboratorio Genda S. A.; ArgentinaFil: Hombreiro, L.. Jefatura Superior de Policía de Galicia. Brigada de Policía Científica. Laboratorio Territorial de Biología – ADN; EspañaFil: Ibarra, A. A.. Universidad de Antioquia; ColombiaFil: Jiménez, M. J.. Policia de la Generalitat – Mossos d’Esquadra. Divisió de Policia Científica. Àrea Central de Criminalística. Unitat Central de Laboratori Biològic; EspañaFil: Luque, G. M.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Madero, P.. Centro de Análisis Genéticos; EspañaFil: Martínez Jarreta, B.. Universidad de Zaragoza; EspañaFil: Masciovecchio, M. Verónica. IACA Laboratorios; ArgentinaFil: Modesti, Nidia Maria. Provincia de Córdoba. Poder Judicial; ArgentinaFil: Moreno, F.. Servicio Médico Legal. Unidad de Genética Forense; ChileFil: Pagano, S.. Dirección Nacional de Policía Técnica. Laboratorio de Análisis de ADN para el CODIS; UruguayFil: Pedrosa, S.. Navarra de Servicios y Tecnologías S. A. U.; EspañaFil: Plaza, G.. Neodiagnostica S. L.; EspañaFil: Prat, E.. Comisaría General de Policía Científica. Laboratorio de ADN; EspañaFil: Puente, J.. Laboratorio de Genética Clínica S. L.; EspañaFil: Rendo, F.. Universidad del País Vasco; EspañaFil: Ribeiro, T.. Instituto Nacional de Medicina Legal e Ciências Forenses, Delegação Sul. Serviço de Genética e Biologia Forenses; PortugalFil: Santamaría, E.. Instituto Nacional de Toxicología y Ciencias Forenses; EspañaFil: Saragoni, V. G.. Servicio Médico Legal. Departamento de Laboratorios. Unidad de Genética Forense; ChileFil: Whittle, M. R.. Genomic Engenharia Molecular; Brasi

A GHEP-ISFG collaborative study on the genetic variation of 38 autosomal indels for human identification in different continental populations

A collaborative effort was carried out by the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) to promote knowledge exchange between associate laboratories interested in the implementation of indel-based methodologies and build allele frequency databases of 38 indels for forensic applications. These databases include populations from different countries that are relevant for identification and kinship investigations undertaken by the participating laboratories. Before compiling population data, participants were asked to type the 38 indels in blind samples from annual GHEP-ISFG proficiency tests, using an amplification protocol previously described. Only laboratories that reported correct results contributed with population data to this study. A total of 5839 samples were genotyped from 45 different populations from Africa, America, East Asia, Europe and Middle East. Population differentiation analysis showed significant differences between most populations studied from Africa and America, as well as between two Asian populations from China and East Timor. Low FST values were detected among most European populations. Overall diversities and parameters of forensic efficiency were high in populations from all continents.RP is supported by a postdoctoral fellowship (SFRH/BPD/81986/2011) awarded by the Portuguese Foundation for Science and Technology (FCT) and co-financed by the European Social Fund (Human Potential Thematic Operational Programme – POPH

A GHEP-ISFG collaborative study on the genetic variation of 38 autosomal indels for human identification in different continental populations

A collaborative effort was carried out by the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) to promote knowledge exchange between associate laboratories interested in the implementation of indel-based methodologies and build allele frequency databases of 38 indels for forensic applications. These databases include populations from different countries that are relevant for identification and kinship investigations undertaken by the participating laboratories. Before compiling population data, participants were asked to type the 38 indels in blind samples from annual GHEP-ISFG proficiency tests, using an amplification protocol previously described. Only laboratories that reported correct results contributed with population data to this study. A total of 5839 samples were genotyped from 45 different populations from Africa, America, East Asia, Europe and Middle East. Population differentiation analysis showed significant differences between most populations studied from Africa and America, as well as between two Asian populations from China and East Timor. Low FST values were detected among most European populations. Overall diversities and parameters of forensic efficiency were high in populations from all continents.Instituto Multidisciplinario de Biología CelularFacultad de Ciencias Naturales y Muse