Aplicación de técnicas de inteligencia artificial a la predicción de contaminantes atmosféricos

Abstract Air pollution is a big threat and a phenomenon that has a specific impact on human health, in addition, changes that occur in the chemical composition of the atmosphere can change the weather and cause acid rain or ozone destruction. Those are phenomena of global importance. The World Health Organization (WHO) considerates air pollution as one of the most important global priorities. Salamanca, Gto., Mexico has been ranked as one of the most polluted cities in this country. The industry of the area led to a major economic development and rapid population growth in the second half of the twentieth century. The impact in the air quality is important and significant efforts have been made to measure the concentrations of pollutants. The main pollution sources are locally based plants in the chemical and power generation sectors. The registered concerning pollutants are Sulphur Dioxide (SO2) and particles on the order of ∼10 micrometers or less (PM10). The prediction in the concentration of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this PhD thesis we propose a model to predict concentrations of pollutants SO2 and PM10 for each monitoring booth in the Atmospheric Monitoring Network Salamanca (REDMAS - for its spanish acronym). The proposed models consider the use of meteorological variables as factors influencing the concentration of pollutants. The information used along this work is the current real data from REDMAS. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms are used. The type of ANN used is the Multilayer Perceptron with a hidden layer, using separate structures for the prediction of each pollutant. The meteorological variables used for prediction were: Wind Direction (WD), wind speed (WS), Temperature (T) and relative humidity (RH). Clustering algorithms, K-means and Fuzzy C-means, are used to find relationships between air pollutants and weather variables under consideration, which are added as input of the RNA. Those relationships provide information to the ANN in order to obtain the prediction of the pollutants. The results of the model proposed in this work are compared with the results of a multivariate linear regression and multilayer perceptron neural network. The evaluation of the prediction is calculated with the mean absolute error, the root mean square error, the correlation coefficient and the index of agreement. The results show the importance of meteorological variables in the prediction of the concentration of the pollutants SO2 and PM10 in the city of Salamanca, Gto., Mexico. The results show that the proposed model perform better than multivariate linear regression and multilayer perceptron neural network. The models implemented for each monitoring booth have the ability to make predictions of air quality that can be used in a system of real-time forecasting and human health impact analysis. Among the main results of the development of this thesis we can cite: A model based on artificial neural network combined with clustering algorithms for prediction with a hour ahead of the concentration of each pollutant (SO2 and PM10) is proposed. A different model was designed for each pollutant and for each of the three monitoring booths of the REDMAS. A model to predict the average of pollutant concentration in the next 24 hours of pollutants SO2 and PM10 is proposed, based on artificial neural network combined with clustering algorithms. Model was designed for each booth of the REDMAS and each pollutant separately. Resumen La contaminación atmosférica es una amenaza aguda, constituye un fenómeno que tiene particular incidencia sobre la salud del hombre. Los cambios que se producen en la composición química de la atmósfera pueden cambiar el clima, producir lluvia ácida o destruir el ozono, fenómenos todos ellos de una gran importancia global. La Organización Mundial de la Salud (OMS) considera la contaminación atmosférica como una de las más importantes prioridades mundiales. Salamanca, Gto., México; ha sido catalogada como una de las ciudades más contaminadas en este país. La industria de la zona propició un importante desarrollo económico y un crecimiento acelerado de la población en la segunda mitad del siglo XX. Las afectaciones en el aire son graves y se han hecho importantes esfuerzos por medir las concentraciones de los contaminantes. Las principales fuentes de contaminación son fuentes fijas como industrias químicas y de generación eléctrica. Los contaminantes que se han registrado como preocupantes son el Bióxido de Azufre (SO2) y las Partículas Menores a 10 micrómetros (PM10). La predicción de las concentraciones de estos contaminantes puede ser una potente herramienta que permita tomar medidas preventivas como reducción de emisiones a la atmósfera y alertar a la población afectada. En la presente tesis doctoral se propone un modelo de predicción de concentraci ón de los contaminantes más críticos SO2 y PM10 para cada caseta de monitorización de la Red de Monitorización Atmosférica de Salamanca (REDMAS). Los modelos propuestos plantean el uso de las variables meteorol ógicas como factores que influyen en la concentración de los contaminantes. La información utilizada durante el desarrollo de este trabajo corresponde a datos reales obtenidos de la REDMAS. En el Modelo Propuesto (MP) se aplican Redes Neuronales Artificiales (RNA) combinadas con algoritmos de agrupamiento. La RNA utilizada es el Perceptrón Multicapa con una capa oculta, utilizando estructuras independientes para la predicción de cada contaminante. Las variables meteorológicas disponibles para realizar la predicción fueron: Dirección de Viento (DV), Velocidad de Viento (VV), Temperatura (T) y Humedad Relativa (HR). Los algoritmos de agrupamiento K-means y Fuzzy C-means son utilizados para encontrar relaciones existentes entre los contaminantes atmosféricos en estudio y las variables meteorológicas. Dichas relaciones aportan información a las RNA para obtener la predicción de los contaminantes, la cual es agregada como entrada de las RNA. Los resultados del modelo propuesto en este trabajo son comparados con los resultados de una Regresión Lineal Multivariable (RLM) y un Perceptrón Multicapa (MLP). La evaluación de la predicción se realiza con el Error Medio Absoluto, la Raíz del Error Cuadrático Medio, el coeficiente de correlación y el índice de acuerdo. Los resultados obtenidos muestran la importancia de las variables meteorológicas en la predicción de la concentración de los contaminantes SO2 y PM10 en la ciudad de Salamanca, Gto., México. Los resultados muestran que el MP predice mejor la concentración de los contaminantes SO2 y PM10 que los modelos RLM y MLP. Los modelos implementados para cada caseta de monitorizaci ón tienen la capacidad para realizar predicciones de calidad del aire, estos modelos pueden ser implementados en un sistema que permita realizar la predicción en tiempo real y analizar el impacto en la salud de la población. Entre los principales resultados obtenidos del desarrollo de esta tesis podemos citar: Se propone un modelo basado en una red neuronal artificial combinado con algoritmos de agrupamiento para la predicción con una hora de anticipaci ón de la concentración de cada contaminante (SO2 y PM10). Se diseñó un modelo diferente para cada contaminante y para cada una de las tres casetas de monitorización de la REDMAS. Se propone un modelo de predicción del promedio de la concentración de las próximas 24 horas de los contaminantes SO2 y PM10, basado en una red neuronal artificial combinado con algoritmos de agrupamiento. Se diseñó un modelo para cada caseta de monitorización de la REDMAS y para cada contaminante por separado.

Influencia de la información termográfica infrarroja en el protocolo de prevención de lesiones de un equipo de fútbol profesional español

El fútbol es un deporte en cuya práctica existe una alta incidencia de lesión. Además, en el ámbito profesional las lesiones suponen un duro proceso de recuperación para el futbolista, una reducción del rendimiento deportivo para éste y para el equipo, y unos grandes costes económicos para el club. Dentro de esta problemática, la bibliografía consultada concluye que en las pretemporadas se produce una mayor incidencia de lesión por sobrecarga, es decir, sin contacto; un tipo de lesiones que está a nuestro alcance poder prevenir. Por ello, consideramos importante el conocer y desarrollar métodos, herramientas y principios para obtener programas preventivos efectivos, que reduzcan las elevadas cifras de incidencia de lesión mostradas por la literatura. El presente estudio observa y registra las lesiones, a través del cuestionario F-MARC, de un equipo profesional de fútbol de la Liga Española durante las pretemporadas 2008 (n=24) y 2009 (n=24). Además, durante la pretemporada 2009 se aplicó la termografía infrarroja para adquirir información sobre la asimilación de la carga de entrenamiento por parte de los jugadores, y dicha información se utilizarón para mejorar las tomas de decisiones de protocolos post-ejercicio específicos en prevención de lesiones, los cuales fueron los mismos que se utilizaron previamente en la pretemporada 2008. El estudio tiene un diseño con características pre-post sin grupo de control. Es un estudio longitudinal donde, tras un registro inicial de lesiones en la pretemporada 2008, los sujetos fueron expuestos a la variable independiente, utilización de la termografía infrarroja, en el protocolo de prevención de lesiones durante la pretemporada 2009. Los resultados de este trabajo muestran una reducción significativa de hasta el 60% en la frecuencia de lesión durante la pretemporada 2009, y un descenso de la incidencia de lesión total que pasa de 8,3 lesiones por cada 1000 horas de exposición en 2008 a 3,4 en 2009. Con ello, la probabilidad de lesión se redujo considerablemente pasando de un 85% de los jugadores lesionados en 2008 a un 26% en 2009; además, las lesiones de carácter muscular descendieron en 2009 un 70% con respecto al 2008, y los días de baja que causaron todas las lesiones pasó a reducirse un 91,8% en la pretemporada 2009. Por otro lado, el perfil térmico de los jugadores en función de su lateralidad y dominancia, guarda una gran similitud en sus temperaturas, tanto medias como máximas, con temperaturas más elevadas en la zona corporal lumbar y poplítea, y con temperaturas más bajas en tobillos y rodillas. Todas las zonas corporales estudiadas, exceptuando el tobillo (p<0,05), no presentan diferencias significativas entre ambos hemicuerpos, estableciendo un promedio de diferencia entre ambos lados de 0,06±0,16 ºC. Teniendo en cuenta estos resultados, consideramos el límite superior de normalidad de asimetría térmica bilateral en 0,3ºC para todas las zonas corporales estudiadas del miembro inferior exceptuando los tobillos. El parámetro ambiental que más relación tiene con la temperatura registrada por la cámara termográfica es la temperatura de la sala con un coeficiente de correlación cercano a r=1,00, seguido de la presión atmosférica con un coeficiente de correlación cercano r=0,50, y, por último, la humedad que no guarda ningún tipo de relación con la temperatura registrada en cada zona corporal en el rango de valores considerados en el estudio. Por otro lado, los resultados del ANOVA de un factor nos indican que existen diferencias de medias entre los tres grupos formados de temperatura ambiente de sala (1º=18º-21ºC, 2º=22º-24ºC y 3º=25º-31ºC). Además, los resultados de la prueba HSD de Tukey nos indican que existen diferencias entre cada uno de los grupos en todas las zonas corporales estudiadas exceptuando los tobillos. Por último, se propone la ecuación; TC-estándar = TC-real – [0,184 * (TS – 21ºC)] para predecir la influencia de la temperatura ambiente sobre la temperatura registrada por la cámara termográfica. Para concluir, tras los resultados obtenidos, podemos afirmar que la aplicación de un protocolo post-ejercicio de prevención de lesiones basado en la información adquirida a través de valoraciones con termografía infrarroja reduce la incidencia de lesión en el grupo de futbolistas profesionales estudiado. Tenemos que ser conscientes que nos encontramos ante un estudio de campo, donde existen muchos factores que han podido influenciar en los resultados y que son difíciles de controlar. Por lo tanto, debemos ser cautos y concluir que la información adquirida de las evaluaciones termográficas ha sido uno de los aspectos que ayudó a la reducción significativa de la incidencia de lesión en la pretemporada 2009 en el equipo de fútbol profesional español de este estudio, pero que seguramente hayan podido existir otros factores que también hayan favorecido este hecho. ABSTRACT Soccer is a sport with a high incidence of injury. Moreover, in professional soccer injuries lead to a tough recovery process for the players, a reduction athletic performance for them and for their teams, and large economic costs for the club. In this issue, the literature concludes that in the preseason a greater incidence of overuse injury occurs (ie, without contact), and this is a type of injury that we can prevent. Therefore, we consider that it is important to know and develop methods, tools and principles to obtain effective preventive programs that reduce the high injury incidence figures shown in the literature. This study observed and recorded injuries, through the questionnaire F-MARC, from a professional soccer team in the Spanish league during the preseason 2008 (n = 24) and 2009 (n = 24). Moreover, during the 2009 preseason infrared thermography was applied to acquire information about the assimilation of the training load by the players, and this information was used to improve the decision making in the specific post-exercise injury prevention protocols, which were the same used in the previous season 2008. The study had a pre-post design without control group. Is a longitudinal study where, after an initial registration of injuries in the 2008 preseason, subjects were exposed to the independent variable, using infrared thermography, included in the protocol for injury prevention during the 2009 preseason. The results of this study show a significant reduction of up to 60% in the frequency of injury during the 2009 preseason, and a decrease in total injury incidence passing from 8.3 injuries per 1000 hours of exposure in 2008 to 3.4 in 2008. With this, the likelihood of injury decreased significantly from 85% of the players injuried in 2008 to 26% in 2009, also muscle injuries in 2009 fell 70% compared to 2008, and sick leave days that caused by all the injuries happened were reduced a 91.8% in the 2009 preseason. On the other hand, the thermal profile of the players according to their laterality and dominance, is quiet similar in their temperatures, both average and maximum values, with an estimated average of the highest temperatures in the lower back and popliteal areas in the back areas, and lower temperatures in the ankles and knees. All body areas studied, except for the ankle (p <0.05), had no significant differences between both sides of the body, establishing an average difference between both sides of 0.06 ± 0.16 °C. Given these results, we consider the upper limit of normal bilateral thermal asymmetry 0.3 °C for all body areas studied in the lower limb except for ankles. The environmental parameter higher related with temperature recorded by the camera is the temperature of the room with a correlation coefficient close to r = 1.00, followed by atmospheric pressure with a correlation coefficient near r = 0.50, and finally, the humidity that, in the range of values considered in the study, it is not related with temperature in each body area. On the other hand, the results of one-way ANOVA indicate that there are differences between the three temperature of the room groups (1 ° = 18-21 °C, 2 º = 22-24 ºC and 3 º = 25-31 ºC). Moreover, the results of the Tukey HSD test indicate that there are differences between each of the groups for all body areas studied except the ankles. Finally, we propose the equation TC-standard = TC-real – [0,184 * (TS – 21ºC)] to predict the influence of temperature on the temperature recorded by the thermographic camera. In conclusion, we can say from our results that the implementation of a post-exercise injury prevention protocol based on information from assessments with infrared thermography reduces the incidence of injury in professional soccer players. We must be aware that we are facing a field study, where there are many factors that could influence the results and they are difficult to control. Therefore, we must be cautious and conclude that the information acquired from the thermographic evaluation has been one of the aspects that helped to significantly reduce the incidence of injury in the preseason 2009 in the Spanish professional football team, but probably they could exist other factors with a positive effect on the reduction of the injury rates.

High definition video quality assessment metric built upon full reference ratios

Métrica de calidad de video de alta definición construida a partir de ratios de referencia completa. La medida de calidad de video, en inglés Visual Quality Assessment (VQA), es uno de los mayores retos por solucionar en el entorno multimedia. La calidad de vídeo tiene un impacto altísimo en la percepción del usuario final (consumidor) de los servicios sustentados en la provisión de contenidos multimedia y, por tanto, factor clave en la valoración del nuevo paradigma denominado Calidad de la Experiencia, en inglés Quality of Experience (QoE). Los modelos de medida de calidad de vídeo se pueden agrupar en varias ramas según la base técnica que sustenta el sistema de medida, destacando en importancia los que emplean modelos psicovisuales orientados a reproducir las características del sistema visual humano, en inglés Human Visual System, del que toman sus siglas HVS, y los que, por el contrario, optan por una aproximación ingenieril en la que el cálculo de calidad está basado en la extracción de parámetros intrínsecos de la imagen y su comparación. A pesar de los avances recogidos en este campo en los últimos años, la investigación en métricas de calidad de vídeo, tanto en presencia de referencia (los modelos denominados de referencia completa), como en presencia de parte de ella (modelos de referencia reducida) e incluso los que trabajan en ausencia de la misma (denominados sin referencia), tiene un amplio camino de mejora y objetivos por alcanzar. Dentro de ellos, la medida de señales de alta definición, especialmente las utilizadas en las primeras etapas de la cadena de valor que son de muy alta calidad, son de especial interés por su influencia en la calidad final del servicio y no existen modelos fiables de medida en la actualidad. Esta tesis doctoral presenta un modelo de medida de calidad de referencia completa que hemos llamado PARMENIA (PArallel Ratios MEtric from iNtrInsic features Analysis), basado en la ponderación de cuatro ratios de calidad calculados a partir de características intrínsecas de la imagen. Son: El Ratio de Fidelidad, calculado mediante el gradiente morfológico o gradiente de Beucher. El Ratio de Similitud Visual, calculado mediante los puntos visualmente significativos de la imagen a través de filtrados locales de contraste. El Ratio de Nitidez, que procede de la extracción del estadístico de textura de Haralick contraste. El Ratio de Complejidad, obtenido de la definición de homogeneidad del conjunto de estadísticos de textura de Haralick PARMENIA presenta como novedad la utilización de la morfología matemática y estadísticos de Haralick como base de una métrica de medida de calidad, pues esas técnicas han estado tradicionalmente más ligadas a la teledetección y la segmentación de objetos. Además, la aproximación de la métrica como un conjunto ponderado de ratios es igualmente novedosa debido a que se alimenta de modelos de similitud estructural y otros más clásicos, basados en la perceptibilidad del error generado por la degradación de la señal asociada a la compresión. PARMENIA presenta resultados con una altísima correlación con las valoraciones MOS procedentes de las pruebas subjetivas a usuarios que se han realizado para la validación de la misma. El corpus de trabajo seleccionado procede de conjuntos de secuencias validados internacionalmente, de modo que los resultados aportados sean de la máxima calidad y el máximo rigor posible. La metodología de trabajo seguida ha consistido en la generación de un conjunto de secuencias de prueba de distintas calidades a través de la codificación con distintos escalones de cuantificación, la obtención de las valoraciones subjetivas de las mismas a través de pruebas subjetivas de calidad (basadas en la recomendación de la Unión Internacional de Telecomunicaciones BT.500), y la validación mediante el cálculo de la correlación de PARMENIA con estos valores subjetivos, cuantificada a través del coeficiente de correlación de Pearson. Una vez realizada la validación de los ratios y optimizada su influencia en la medida final y su alta correlación con la percepción, se ha realizado una segunda revisión sobre secuencias del hdtv test dataset 1 del Grupo de Expertos de Calidad de Vídeo (VQEG, Video Quality Expert Group) mostrando los resultados obtenidos sus claras ventajas. Abstract Visual Quality Assessment has been so far one of the most intriguing challenges on the media environment. Progressive evolution towards higher resolutions while increasing the quality needed (e.g. high definition and better image quality) aims to redefine models for quality measuring. Given the growing interest in multimedia services delivery, perceptual quality measurement has become a very active area of research. First, in this work, a classification of objective video quality metrics based on their underlying methodologies and approaches for measuring video quality has been introduced to sum up the state of the art. Then, this doctoral thesis describes an enhanced solution for full reference objective quality measurement based on mathematical morphology, texture features and visual similarity information that provides a normalized metric that we have called PARMENIA (PArallel Ratios MEtric from iNtrInsic features Analysis), with a high correlated MOS score. The PARMENIA metric is based on the pooling of different quality ratios that are obtained from three different approaches: Beucher’s gradient, local contrast filtering, and contrast and homogeneity Haralick’s texture features. The metric performance is excellent, and improves the current state of the art by providing a wide dynamic range that make easier to discriminate between very close quality coded sequences, especially for very high bit rates whose quality, currently, is transparent for quality metrics. PARMENIA introduces a degree of novelty against other working metrics: on the one hand, exploits the structural information variation to build the metric’s kernel, but complements the measure with texture information and a ratio of visual meaningful points that is closer to typical error sensitivity based approaches. We would like to point out that PARMENIA approach is the only metric built upon full reference ratios, and using mathematical morphology and texture features (typically used in segmentation) for quality assessment. On the other hand, it gets results with a wide dynamic range that allows measuring the quality of high definition sequences from bit rates of hundreds of Megabits (Mbps) down to typical distribution rates (5-6 Mbps), even streaming rates (1- 2 Mbps). Thus, a direct correlation between PARMENIA and MOS scores are easily constructed. PARMENIA may further enhance the number of available choices in objective quality measurement, especially for very high quality HD materials. All this results come from validation that has been achieved through internationally validated datasets on which subjective tests based on ITU-T BT.500 methodology have been carried out. Pearson correlation coefficient has been calculated to verify the accuracy of PARMENIA and its reliability.

Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation

Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

Genetic diversity and relationships in accessions from different cultivar groups and origins in the tree tomato (Solanum betaceum Cav.)

Abstract Tree tomato (Solanum betaceum) is an Andean small tree cultivated for its juicy fruits. Little information is available on the characterization of genetic resources and breeding of this neglected crop. We have studied the molecular diversity with AFLP markers using 11 combinations of primers of a collection of 25 S. betaceum accessions belonging to four cultivar groups, most of which had been previously morphologically characterized, as well as one accession of the wild relative S. cajanumense.Atotal of 197 AFLP fragments were scored, of which 84 (43 %) were polymorphic. When excluding S. cajanumense from the analysis, the number of polymorphic AFLP fragments was 78 (40 %). Unique AFLP fingerprints were obtained for every accession, but no AFLP fragments specific and universal to any of the four cultivar groups were found. The total genetic diversity (HT) of cultivated accessions was HT = 0.2904, while for cultivar groups it ranged from HT = 0.1846 in the orange group to HT = 0.2498 in the orange pointed group. Genetic differentiation among cultivar groups (GST) was low (GST = 0.2248), which was matched by low values of genetic distance among cultivar groups. The diversity of collections from Ecuador, which we hypothesize is a center of diversity for tree tomato, was similar to that from other origins (HT = 0.2884 and HT = 0.2645, respectively). Cluster and PCoA analyses clearly separated wild S. cajanumense from the cultivated species. However, materials of different cultivar groups and origins were intermingled in both analyses. The Mantel test correlation coefficient of the matrices of morphological and AFLP distances was low (-0.024) and non-significant. Overall, the results show that a wide diversity is present in each of the cultivar groups, indicate that Ecuador may be regarded as a center of accumulation of diversity for this crop, and confirm that AFLP and morphological characterization data are complementary. The results obtained are of value for the conservation of genetic resources and breeding of tree tomato, as an assessment of the genetic diversity and relationships among differen

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

Reliability and reproductibility of skin temperature of overweight subjects by an infrared thermograpy software designed for human beings

The technical improvement and new applications of Infrared Thermography (IRT) with healthy subjects should be accompanied by results about the reproducibility of IRT measurements in different popula-tion groups. In addition, there is a remarkable necessity of a larger supply on software to analyze IRT images of human beings. Therefore, the objectives of this study were: firstly, to investigate the reproducibility of skin temperature (Tsk) on overweight and obese subjects using IRT in different Regions of Interest (ROI), moments and side-to-side differences (?T); and secondly, to check the reliability of a new software called Termotracker®, specialized on the analysis of IRT images of human beings. Methods: 22 overweight and obese males (11) and females (11) (age: 41,51±7,76 years; height: 1,65±0,09 m; weight: 82,41±11,81 Kg; BMI: 30,17±2,58 kg/m²) were assessed in two consecutive thermograms (5 seconds in-between) by the same observer, using an infrared camera (FLIR T335, Sweden) to get 4 IRT images from the whole body. 11 ROI were selected using Termotracker® to analyze its reproducibility and reliability through Intra-class Correlation Coefficient (ICC) and Coefficient of Variation (CV) values. Results: The reproducibility of the side-to-side differences (?T) between two consecutive thermograms was very high in all ROIs (Mean ICC = 0,989), and excellent between two computers (Mean ICC = 0,998). The re-liability of the software was very high in all the ROIs (Mean ICC = 0,999). Intraexaminer reliability analysing the same subjects in two consecutive thermograms was also very high (Mean ICC = 0,997). CV values of the different ROIs were around 2%. Conclusions: Skin temperature on overweight subjects had an excellent reproducibility for consecutive ther-mograms. The reproducibility of thermal asymmetries (?T) was also good but it had the influence of several factors that should be further investigated. Termotracker® reached excellent reliability results and it is a relia-ble and objective software to analyse IRT images of humans beings.

Dominance intensity methods for ranking of alternatives in mcdm with imprecise information

Los decisores cada vez se enfrentan a problemas más complejos en los que tomar una decisión implica tener que considerar simultáneamente muchos criterios que normalmente son conflictivos entre sí. En la mayoría de los problemas de decisión es necesario considerar criterios económicos, sociales y medioambientales. La Teoría de la Decisión proporciona el marco adecuado para poder ayudar a los decisores a resolver estos problemas de decisión complejos, al permitir considerar conjuntamente la incertidumbre existente sobre las consecuencias de cada alternativa en los diferentes atributos y la imprecisión sobre las preferencias de los decisores. En esta tesis doctoral nos centramos en la imprecisión de las preferencias de los decisores cuando éstas pueden ser representadas mediante una función de utilidad multiatributo aditiva. Por lo tanto, consideramos imprecisión tanto en los pesos como en las funciones de utilidad componentes de cada atributo. Se ha considerado el caso en que la imprecisión puede ser representada por intervalos de valores o bien mediante información ordinal, en lugar de proporcionar valores concretos. En este sentido, hemos propuesto métodos que permiten ordenar las diferentes alternativas basados en los conceptos de intensidad de dominación o intensidad de preferencia, los cuales intentan medir la fuerza con la que cada alternativa es preferida al resto. Para todos los métodos propuestos se ha analizado su comportamiento y se ha comparado con los más relevantes existentes en la literatura científica que pueden ser aplicados para resolver este tipo de problemas. Para ello, se ha realizado un estudio de simulación en el que se han usado dos medidas de eficiencia (hit ratio y coeficiente de correlación de Kendall) para comparar los diferentes métodos. ABSTRACT Decision makers increasingly face complex decision-making problems where they have to simultaneously consider many often conflicting criteria. In most decision-making problems it is necessary to consider economic, social and environmental criteria. Decision making theory provides an adequate framework for helping decision makers to make complex decisions where they can jointly consider the uncertainty about the performance of each alternative for each attribute, and the imprecision of the decision maker's preferences. In this PhD thesis we focus on the imprecision of the decision maker's preferences represented by an additive multiattribute utility function. Therefore, we consider the imprecision of weights, as well as of component utility functions for each attribute. We consider the case in which the imprecision is represented by ranges of values or by ordinal information rather than precise values. In this respect, we propose methods for ranking alternatives based on notions of dominance intensity, also known as preference intensity, which attempt to measure how much more preferred each alternative is to the others. The performance of the propose methods has been analyzed and compared against the leading existing methods that are applicable to this type of problem. For this purpose, we conducted a simulation study using two efficiency measures (hit ratio and Kendall correlation coefficient) to compare the different methods.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

Validation of an instrument for injury data collection in strength training

Purpose: To provide for the basis for collecting strength training data using a rigorously validated injury report form. Methods: A group of specialist designed a questionnaire of 45 item grouped into 4 dimensions. Six stages were used to assess face, content, and criterion validity of the weight training injury report form. A 13 members panel assessed the form for face validity, and an expert panel assessed it for content and criterion validity. Panel members were consulted until consensus was reached. A yardstick developed by an expert panel using Intraclass correlation technique was used to assess the reability of the form. Test-retest reliability was assessed with the intraclass correlation coefficient (ICC).The strength training injury report form was developed, and the face, content, and criterion validity successfully assessed. A six step protocol to create a yardstick was also developed to assist in the validation process. Both inter-rater and intra rater reliability results indicated a 98% agreement. Inter-rater reliability agreement of 98% for three injuries. Results: The Cronbach?s alpha of the questionnaire was 0.944 (pmenor que0.01) and the ICC of the entire questionnaire was 0.894 (pmenor que0.01). Conclusion: The questionnaire gathers together enough psychometric properties to be considered a valid and reliable tool for register injury data in strength training, and providing researchers with a basis for future studies in this area. Key Words: data collection; validation; injury prevention; strength training

Towards a unified sentiment lexicon based on graphics processing units

This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral {P, Z, N} depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times.

The unified sentiment lexicon using GPUs

This approach aims at aligning, unifying and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. A sentiment lexicon is a critical and essential resource for tagging subjective corpora on the web or elsewhere. In many situations, the multilingual property of the sentiment lexicon is important because the writer is using two languages alternately in the same text, message or post. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and the UnifiedMetrics procedure for CPU and GPU, respectively.

Hacia un Lexicón Unificado de Sentimientos basado en Unidades de Procesamiento Gráfico

Esta tesis presenta un modelo, una metodología, una arquitectura, varios algoritmos y programas para crear un lexicón de sentimientos unificado (LSU) que cubre cuatro lenguas: inglés, español, portugués y chino. El objetivo principal es alinear, unificar, y expandir el conjunto de lexicones de sentimientos disponibles en Internet y los desarrollados a lo largo de esta investigación. Así, el principal problema a resolver es la tarea de unificar de forma automatizada los diferentes lexicones de sentimientos obtenidos por el crawler CSR, porque la unidad de medida para asignar la intensidad de los valores de la polaridad (de forma manual, semiautomática y automática) varía de acuerdo con las diferentes metodologías utilizadas para la construcción de cada lexicón. La representación codificada de la estructura de datos de los términos presenta también una variación en la estructura de lexicón a lexicón. Por lo que al unificar en un lexicón de sentimientos se hace posible la reutilización del conocimiento recopilado por los diferentes grupos de investigación y se incrementa, a la vez, el alcance, la calidad y la robustez de los lexicones. Nuestra metodología LSU calcula un valor unificado de la intensidad de la polaridad para cada entrada léxica que está presente en al menos dos de los lexicones de sentimientos que forman parte de este estudio. En contraste, las entradas léxicas que no son comunes en al menos dos de los lexicones conservan su valor original. El coeficiente de Pearson resultante permite medir la correlación existente entre las entradas léxicas asignándoles un rango de valores de uno a menos uno, donde uno indica que los valores de los términos están perfectamente correlacionados, cero indica que no existe correlación y menos uno significa que están inversamente correlacionados. Este procedimiento se lleva acabo con la función de MetricasUnificadas tanto en la CPU como en la GPU. Otro problema a resolver es el tiempo de procesamiento que se requiere para realizar la tarea de unificación de la intensidad de la polaridad y con ello alcanzar una cobertura mayor de lemas en los lexicones de sentimientos existentes. Asimismo, la metodología LSU utiliza el procesamiento paralelo para unificar los 155 802 términos. El algoritmo LSU procesa mediante cargas iguales el subconjunto de entradas léxicas en cada uno de los 1344 núcleos en la GPU. Los resultados de nuestro análisis arrojaron un total de 95 430 entradas léxicas donde 35 201 obtuvieron valores positivos, 22 029 negativos y 38 200 neutrales. Finalmente, el tiempo de ejecución fue de 2,506 segundos para el total de las entradas léxicas, lo que permitió reducir el procesamiento de cómputo hasta en una tercera parte con respecto al algoritmo secuencial. De estos resultados se concluye que al lograr un lexicón de sentimientos unificado que permite homogeneizar la intensidad de la polaridad de las unidades léxicas (con valores positivos, negativos y neutrales) deriva no sólo en el análisis semántico del corpus basado en los términos con una mayor carga de polaridad, o del resumen de las valoraciones o las tendencias de neuromarketing, sino también en aplicaciones como el etiquetado subjetivo de sitios web o de portales sintácticos y semánticos, por mencionar algunas. ABSTRACT This thesis presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral P, N, Z depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and - 1 , where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155,802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95,430 lexical entries, out of which there are 35,201 considered to be positive, 22,029 negative, and 38,200 neutral. Finally, the runtime was 2.505 seconds for 95,430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times with respect to the sequential implementation. A key contribution of this work is that we preserve the use of a unified sentiment lexicon for all tasks. Such lexicon is used to define resources and resource-related properties that can be verified based on the results of the analysis and is powerful, general and extensible enough to express a large class of interesting properties. Some applications of this work include merging, aligning, pruning and extending the current sentiment lexicons.

Aislamiento acústico a ruido aéreo en techos con materiales ecológicos

El incremento de la contaminación acústica se ha convertido en un problema medioambiental lo cual ha generado un aumento en la demanda del aislamiento de los edificios para lograr el confort acústico. Existen métodos de medición de aislamiento acústico a ruido aéreo de fachadas bajo ensayo “in situ” pero no para techos. El objetivo de esta investigación consiste en determinar el aislamiento acústico de prototipos de techos ecológicos multicapas adaptando la metodología recomendada por normas internacionales. Se propusieron cuatro prototipos de techos con distintos materiales naturales como especies vegetales y sustratos de fibra de coco, superpuestos sobre un techo base liviano. Al sustrato se le varió su espesor de 10 a 20 cm, sus condiciones seca o húmeda y su densidad: 100%, 66% y 33% fibra de coco. En los resultados se determinó que las especies vegetales no aportaron aislamiento, pero al incrementar el espesor y densidad del sustrato mejoró el aislamiento sonoro. También se determinó que el aislamiento acústico en condición seca fue mejor que en condición húmeda. Se planteó una metodología para determinar el aislamiento acústico a ruido aéreo en techos bajo ensayo “in situ” empleando el método global con altavoz, ésta se estructuró en tres partes: la primera describe el módulo experimental y la plataforma tecnológica; la segunda aborda procedimientos para medir los niveles de presión sonora, niveles de ruido de fondo y los tiempos de reverberación, en bandas de frecuencia de tercios de octava; en la tercera se explica el cálculo de los promedios de estos parámetros, así como también la diferencia de niveles estandarizada, el índice de reducción sonora aparente con sus valores globales y su incertidumbre. Así mismo, se determinó un algoritmo de predicción del aislamiento acústico, analizando los valores obtenidos en las mediciones “in situ” como la Diferencia de nivel estandarizada ponderada y el Índice ponderado de reducción sonora, los cuales se relacionaron con el peso y el espesor de los materiales de las diferentes multicapas. A través de un análisis de regresión se establecieron modelos para predecir la Diferencia de nivel estandarizada y el Índice de reducción sonora aparente en bandas de octavas. Los resultados del modelo propuesto son cercanos a los datos medidos “in situ”. Por otra parte, se realizaron mediciones térmicas en un módulo experimental y otro de referencia en tres períodos del día. En el módulo experimental se construyeron los prototipos de techos ecológicos y en el de referencia un techo de construcción tradicional, se compararon los resultados de ambos módulos y su interacción con la temperatura exterior. Se detectó que las temperaturas internas del módulo experimental en condición seca tienden a mantener sus valores durante todo el día, en horas de la mañana sus valores son superiores a los del módulo de referencia y temperatura exterior. Al mediodía y en la tarde las temperaturas internas del módulo experimental son inferiores a las del módulo de referencia, incrementándose esta última a medida que aumenta temperatura exterior. Finalmente, a partir de las mediciones “in situ” se realizaron cuatro modelos de correlación acústica-térmica, los tres primeros relacionando la temperatura y el nivel de presión sonora en tres momentos del día, en la tarde se aprecia que a medida que aumenta la temperatura aumentan los niveles de presión sonora. En el cuarto modelo se estableció una correlación acústica-térmica entre la resistencia térmica de los materiales de las multicapas con su índice de reducción sonora, obteniéndose un coeficiente de correlación moderado. La presente investigación plantea retos desde el punto de vista ambiental, permite cuantificar el aislamiento acústico de los techos y mejorar la calidad de vida en áreas urbanas; el empleo de los materiales de procedencia local como los utilizados fomenta el respeto por la naturaleza y producen un menor impacto ambiental. ABSTRACT Sound contamination increase has generated a raise in insulation demand of buildings in order to achieve a sound comfort, and this has become into an environmental problem. There are measurements methods for air borne soundproofing in facades through “in situ” test but there are not for roofs. The purpose of this research is to determine sound insulation of multilayer green roof prototypes following the methodology suggested by international standards. Four prototypes of roofs with different types of vegetation and overlapped coconut fiber substrates over a light roof were proposed. Thickness of substrate varied from 10 to 20 cm, as well as its dry a humid condition and its density: 100%, 66% y 33% of coconut fiber. Results determined that vegetation did not contribute to insulation but when increasing substrate’s thickness and density, sound insulation was improved. Likewise, it was determined that sound insulation in dry condition was greater than in humid condition. A methodology to determine airborne sound insulation in roofs through “in situ” test using a speaker global method was stated. This was structured in three parts: the first part describes the experimental module and the technological platform; the second one establishes the procedures to measure sound pressure levels; levels of background noise and time of reverberation in frequency bands of thirds of octave, and in the third part, averages of these parameters, as well as the difference of standardized levels, the apparent sound reduction with its global values and uncertainty were calculated. Likewise, a prediction algorithm of sound insulation was determined by analyzing values obtained in “in-situ” measures such as the difference of weighted standardized level and the weighted index of sound reduction which they were related to weight and thickness of different multilayer materials. Models to predict the standardized level difference and the apparent sound reduction index in bands of octaves were established by a regression analysis. Results for the proposed model are close to data measured “in situ”. On the other hand, thermal measures were done in an experimental module, as well as in another as for reference in three periods of the day. Green prototypes roofs were built in the experimental module and a traditional roof were built in the reference one. Results of both modules were compared as well as the interaction with outside temperature. Internal temperatures of the experimental module in dry condition tend to keep their values throughout the day; in the morning, its values are higher than those of the reference module and external temperatures. Finally, four models of sound-thermal correlation were done from measures “in situ”. The first three were related to temperature and sound pressure level in three moments of the day. In the afternoon, it is observed that when temperature increases, sound pressure levels increases too. In the fourth model, a sound and thermal correlation was established between thermal resistance of multilayer materials with their sound reduction index, and a moderated correlation coefficient was obtained. This research poses challenges from the environmental point of view, and it allows quantifying sound insulation of roofs as well as improving quality of life in urban areas; the use of local vegetation promotes respect for nature and it produces a smaller environmental impact as well.