DAEDALUS at ImageCLEF 2011 Plant Identification Task: Using SIFT Keypoints for Object Detection

This paper describes the participation of DAEDALUS at ImageCLEF 2011 Plant Identification task. The task is evaluated as a supervised classification problem over 71 tree species from the French Mediterranean area used as class labels, based on visual content from scan, scan-like and natural photo images. Our approach to this task is to build a classifier based on the detection of keypoints from the images extracted using Lowe’s Scale Invariant Feature Transform (SIFT) algorithm. Although our overall classification score is very low as compared to other participant groups, the main conclusion that can be drawn is that SIFT keypoints seem to work significantly better for photos than for the other image types, so our approach may be a feasible strategy for the classification of this kind of visual content.

Characterization of vineyard's canopy through fuzzy clustering and svm over color images

In this work we propose an image acquisition and processing methodology (framework) developed for performance in-field grapes and leaves detection and quantification, based on a six step methodology: 1) image segmentation through Fuzzy C-Means with Gustafson Kessel (FCM-GK) clustering; 2) obtaining of FCM-GK outputs (centroids) for acting as seeding for K-Means clustering; 3) Identification of the clusters generated by K-Means using a Support Vector Machine (SVM) classifier. 4) Performance of morphological operations over the grapes and leaves clusters in order to fill holes and to eliminate small pixels clusters; 5)Creation of a mosaic image by Scale-Invariant Feature Transform (SIFT) in order to avoid overlapping between images; 6) Calculation of the areas of leaves and grapes and finding of the centroids in the grape bunches. Image data are collected using a colour camera fixed to a mobile platform. This platform was developed to give a stabilized surface to guarantee that the images were acquired parallel to de vineyard rows. In this way, the platform avoids the distortion of the images that lead to poor estimation of the areas. Our preliminary results are promissory, although they still have shown that it is necessary to implement a camera stabilization system to avoid undesired camera movements, and also a parallel processing procedure in order to speed up the mosaicking process.

Si(100) versus Ge(100): Watching the interface formation for the growth of III-V-based solar cells on abundant substrates

We investigated the atomic surface properties of differently prepared silicon and germanium (100) surfaces during metal-organic vapour phase epitaxy/chemical vapour deposition (MOVPE/MOCVD), in particular the impact of the MOVPE ambient, and applied reflectance anisotropy/difference spectroscopy (RAS/RDS) in our MOVPE reactor to in-situ watch and control the preparation on the atomic length scale for subsequent III-V-nucleation. The technological interest in the predominant opto-electronic properties of III-V-compounds drives the research for their heteroepitaxial integration on more abundant and cheaper standard substrates such as Si(100) or Ge(100). In these cases, a general task must be accomplished successfully, i.e. the growth of polar materials on non-polar substrates and, beyond that, very specific variations such as the individual interface formation and the atomic step structure, have to be controlled. Above all, the method of choice to grow industrial relevant high-performance device structures is MOVPE, not normally compatible with surface and interface sensitive characterization tools, which are commonly based on ultrahigh vacuum (UHV) ambients. A dedicated sample transfer system from MOVPE environment to UHV enabled us to benchmark the optical in-situ spectra with results from various surfaces science instruments without considering disruptive contaminants. X-ray photoelectron spectroscopy (XPS) provided direct observation of different terminations such as arsenic and phosphorous and verified oxide removal under various specific process parameters. Absorption lines in Fourier-transform infrared (FTIR) spectra were used to identify specific stretch modes of coupled hydrides and the polarization dependence of the anti-symmetric stretch modes distinguished different dimer orientations. Scanning tunnelling microscopy (STM) studied the atomic arrangement of dimers and steps and tip-induced H-desorption proved the saturation of dangling bonds after preparati- n. In-situ RAS was employed to display details transiently such as the presence of H on the surface at lower temperatures (T <; 800°C) and the absence of Si-H bonds at elevated annealing temperature and also surface terminations. Ge buffer growth by the use of GeH4 enables the preparation of smooth surfaces and leads to a more pronounced amplitude of the features in the spectra which indicates improvements of the surface quality.

Glottal Parameter Estimation by Wavelet Transform for Voice Biometry

Voice biometry is classically based on the parameterization and patterning of speech features mainly. The present approach is based on the characterization of phonation features instead (glottal features). The intention is to reduce intra-speaker variability due to the `text'. Through the study of larynx biomechanics it may be seen that the glottal correlates constitute a family of 2-nd order gaussian wavelets. The methodology relies in the extraction of glottal correlates (the glottal source) which are parameterized using wavelet techniques. Classification and pattern matching was carried out using Gaussian Mixture Models. Data of speakers from a balanced database and NIST SRE HASR2 were used in verification experiments. Preliminary results are given and discussed.

Desintegración vertical en la industria del automóvil en España: un caso de estudio = Vertical disintegration in the automotive industry in Spain: a case study

En los años recientes se ha producido un rápido crecimiento del comercio internacional en productos semielaborados que son diseñados, producidos y ensamblados en diferentes localizaciones a lo largo de diferentes países, debido principalmente a los siguientes motivos: el desarrollo de las tecnologías de la información, la reducción de los costes de transporte, la liberalización de los mercados de capitales, la armonización de factores institucionales, la integración económica regional que implica la reducción y la eliminación de las barreras al comercio, el desarrollo económico de los países emergentes, el uso de economías de escala, así como una desregulación del comercio internacional. Todo ello ha incrementado la competencia a nivel mundial en los mercados y ha posibilitado a las compañías tener más facilidad de acceso a potenciales mercados, así como a la adquisición de capacidades y conocimientos en otros países y a la realización de alianzas estratégicas internacionales con terceros, creando un entorno con mayor incertidumbre y más exigente para las compañías que componen una industria, y que tiene consecuencias directas en las operaciones de las compañías y en la organización de su producción. Las compañías, para adaptarse, ser competitivas y beneficiarse de este nuevo escenario globalizado y más competitivo, han externalizado partes del proceso productivo hacia proveedores especializados, creando un nuevo mercado intermedio que divide el proceso productivo, anteriormente integrado en las compañías que conforman una industria, entre dos conjuntos de empresas especializadas en esa industria. Dicho proceso suele ocurrir conservando la industria en que tiene lugar, los mismos servicios y productos, la tecnología empleada y las compañías originales que la conformaban previamente a la desintegración vertical. Todo ello es así debido a que es beneficioso tanto para las compañías originales de la industria como para las nuevas compañías de este mercado intermedio por diversos motivos. La desintegración vertical en una industria tiene unas consecuencias que la transforman completamente, así como la forma de operar de las compañías que la integran, incluso para aquellas que permanecen verticalmente integradas. Una de las características más importantes de esta desintegración vertical en una industria es la posibilidad que tiene una compañía de adquirir a una tercera la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por la compañía adquiriente con la práctica del outsourcing; así mismo, una compañía puede realizar la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por una tercera compañía con la práctica de la fragmentación. El principal objetivo de la presente investigación es el estudio de los motivos, los facilitadores, los efectos, las consecuencias y los principales factores significativos, microeconómicos y macroeconómicos, que desencadenan o incrementan la práctica de la desintegración vertical en una industria; para ello, la investigación se divide en dos líneas completamente diferenciadas: el estudio de la práctica del outsourcing y, por otro lado, el estudio de la fragmentación por parte de las compañías que componen la industria del automóvil en España, puesto que se trata de una de las industrias más desintegradas verticalmente y fragmentadas, y este sector posee una gran importancia en la economía del país. En primer lugar, se hace una revisión de la literatura existente relativa a los siguientes aspectos: desintegración vertical, outsourcing, fragmentación, teoría del comercio internacional, historia de la industria del automóvil en España y el uso de las aglomeraciones geográficas y las tecnologías de la información en el sector del automóvil. La metodología empleada en cada uno de ellos ha sido diferente en función de la disponibilidad de los datos y del enfoque de investigación: los factores microeconómicos, utilizando el outsourcing, y los factores macroeconómicos, empleando la fragmentación. En el estudio del outsourcing, se usa un índice basado en las compras externas sobre el valor total de la producción. Así mismo, se estudia su correlación y significación con las variables económicas más importantes que definen a una compañía del sector del automóvil, utilizando la técnica estadística de regresión lineal. Aquellas variables relacionadas con la competencia en el mercado, la externalización de las actividades de menor valor añadido y el incremento de la modularización de las actividades de la cadena de valor, han resultado significativas con la práctica del outsourcing. En el estudio de la fragmentación se seleccionan un conjunto de factores macroeconómicos, comúnmente usados en este tipo de investigaciones, relacionados con las principales magnitudes económicas de un país, y un conjunto de factores macroeconómicos, no comúnmente usados en este tipo de investigaciones, relacionados con la libertad económica y el comercio internacional de un país. Se emplea un modelo de regresión logística para identificar qué factores son significativos en la práctica de la fragmentación. De entre todos los factores usados en el modelo, los relacionados con las economías de escala y los costes de servicio han resultado significativos. Los resultados obtenidos de los test estadísticos realizados en el modelo de regresión logística han resultado satisfactorios; por ello, el modelo propuesto de regresión logística puede ser considerado sólido, fiable y versátil; además, acorde con la realidad. De los resultados obtenidos en el estudio del outsourcing y de la fragmentación, combinados conjuntamente con el estado del arte, se concluye que el principal factor que desencadena la desintegración vertical en la industria del automóvil es la competencia en el mercado de vehículos. Cuanto mayor es la demanda de vehículos, más se reducen los beneficios y la rentabilidad para sus fabricantes. Estos, para ser competitivos, diferencian sus productos de la competencia centrándose en las actividades que mayor valor añadido aportan al producto final, externalizando las actividades de menor valor añadido a proveedores especializados, e incrementando la modularidad de las actividades de la cadena de valor. Las compañías de la industria del automóvil se especializan en alguna o varias de estas actividades modularizadas que, combinadas con el uso de factores facilitadores como las economías de escala, las tecnologías de la información, las ventajas de la globalización económica y la aglomeración geográfica de una industria, incrementan y motivan la desintegración vertical en la industria del automóvil, desencadenando la coespecialización en dos sectores claramente diferenciados: el sector de fabricantes de vehículos y el sector de proveedores especializados. Cada uno de ellos se especializa en unas actividades y en unos productos o servicios específicos de la cadena de valor, lo cual genera las siguientes consecuencias en la industria del automóvil: se reducen los costes de transacción en los productos o servicios intercambiados; se incrementan la relación de dependencia entre fabricantes de vehículos y proveedores especializados, provocando un aumento en la cooperación y la coordinación, acelerando el proceso de aprendizaje, posibilitando a ambos adquirir nuevas capacidades, conocimientos y recursos, y creando nuevas ventajas competitivas para ambos; por último, las barreras de entrada a la industria del automóvil y el número de compañías se ven alteradas cambiando su estructura. Como futura línea de investigación, los fabricantes de vehículos tenderán a centrarse en investigar, diseñar y comercializar el producto o servicio, delegando el ensamblaje en manos de nuevos especialistas en la materia, el contract manufacturer; por ello, sería conveniente investigar qué factores motivantes o facilitadores existen y qué consecuencias tendría la implantación de los contract manufacturer en la industria del automóvil. 1.1. ABSTRACT In recent years there has been a rapid growth of international trade in semi-finished products designed, produced and assembled in different locations across different countries, mainly due to the following reasons: development of information technologies, reduction of transportation costs, liberalisation of capital markets, harmonisation of institutional factors, regional economic integration, which involves the reduction and elimination of trade barriers, economic development of emerging countries, use of economies of scale and deregulation of international trade. All these factors have increased competition in markets at a global level and have allowed companies to gain easier access to potential markets and to the acquisition of skills and knowledge in other countries, as well as to the completion of international strategic alliances with third parties, thus creating a more demanding and uncertain environment for these companies constituting an industry, which has a direct impact on the companies' operations and the organization of their production. In order to adapt, be competitive and benefit from this new and more competitive global scenario, companies have outsourced some parts of their production process to specialist suppliers, generating a new intermediate market which divides the production process, previously integrated in the companies that made up the industry, into two sets of companies specialized in that industry. This process often occurs while preserving the industry where it takes place, its same services and products, the technology used and the original companies that formed it prior to vertical disintegration. This is because it is beneficial for both the industry's original companies and the companies belonging to this new intermediate market, for various reasons. Vertical disintegration has consequences which completely transform the industry where it takes place as well as the modus operandi of the companies that are part of it, even of those who remain vertically integrated. One of the most important features of vertical disintegration of an industry is the possibility for a company to acquire from a third one the first part of the production process or a semi-finished product, which will then be finished by the acquiring company through the practice of outsourcing; also, a company can perform the first part of the production process or a semi-finish product, which will then be completed by a third company through the practice of fragmentation. The main objective of this research is to study the motives, facilitators, effects, consequences and major significant microeconomic and macroeconomic factors that trigger or increase the practice of vertical disintegration in a certain industry; in order to do so, research is divided into two completely differentiated lines: on the one hand, the study of the practise of outsourcing and, on the other, the study of fragmentation by companies constituting the automotive industry in Spain, since this is one of the most vertically disintegrated and fragmented industries and this particular sector is of major significance in this country's economy. First, a review is made of the existing literature, on the following aspects: vertical disintegration, outsourcing, fragmentation, international trade theory, history of the automobile industry in Spain and the use of geographical agglomeration and information technologies in the automotive sector. The methodology used for each of these aspects has been different depending on the availability of data and the research approach: the microeconomic factors, using outsourcing, and the macroeconomic factors, using fragmentation. In the study on outsourcing, an index is used based on external purchases in relation to the total value of production. Likewise, their significance and correlation with the major economic variables that define an automotive company are studied, using the statistical technique of linear regression. Variables related to market competition, outsourcing of lowest value-added activities and increased modularisation of the activities of the value chain have turned out to be significant with the practice of outsourcing. In the study of fragmentation, a set of macroeconomic factors commonly used for this type of research, is selected, related to the main economic indicators of a country, as well as a set of macroeconomic factors, not commonly used for this type of research, which are related to economic freedom and the international trade of a certain country. A logistic regression model is used to identify which factors are significant in the practice of fragmentation. Amongst all factors used in the model, those related to economies of scale and service costs have turned out to be significant. The results obtained from the statistical tests performed on the logistic regression model have been successful; hence, the suggested logistic regression model can be considered to be solid, reliable and versatile; likewise, it is in line with reality. From the results obtained in the study of outsourcing and fragmentation, combined with the state of the art, it is concluded that the main factor that triggers vertical disintegration in the automotive industry is competition within the vehicle market. The greater the vehicle demand, the lower the earnings and profitability for manufacturers. These, in order to be competitive, differentiate their products from the competition by focusing on those activities that contribute with the highest added value to the final product, outsourcing the lower valueadded activities to specialist suppliers, and increasing the modularity of the activities of the value chain. Companies in the automotive industry specialize in one or more of these modularised activities which, combined with the use of enabling factors such as economies of scale, information technologies, the advantages of economic globalisation and the geographical agglomeration of an industry, increase and encourage vertical disintegration in the automotive industry, triggering co-specialization in two clearly distinct sectors: the sector of vehicle manufacturers and the specialist suppliers sector. Each of them specializes in certain activities and specific products or services of the value chain, generating the following consequences in the automotive industry: reduction of transaction costs of the goods or services exchanged; growth of the relationship of dependency between vehicle manufacturers and specialist suppliers, which causes an increase in cooperation and coordination, accelerates the learning process, enables both to acquire new skills, knowledge and resources, and creates new competitive advantages for both; finally, barriers to entry the automotive industry and the number of companies are altered, changing their structure. As a future line of research, vehicle manufacturers will tend to focus on researching, designing and marketing the product or service, delegating the assembly in the hands of new specialists in the field, the contract manufacturer; for this reason, it would be useful to investigate what motivating or facilitating factors exist in this respect and what consequences would the implementation of contract manufacturers have in the automotive industry.

Electrical Power Fluctuations in a Network of DC/AC inverters in a Large PV Plant: relationship between correlation, distance and time scale

This paper analyzes the correlation between the fluctuations of the electrical power generated by the ensemble of 70 DC/AC inverters from a 45.6 MW PV plant. The use of real electrical power time series from a large collection of photovoltaic inverters of a same plant is an impor- tant contribution in the context of models built upon simplified assumptions to overcome the absence of such data. This data set is divided into three different fluctuation categories with a clustering proce- dure which performs correctly with the clearness index and the wavelet variances. Afterwards, the time dependent correlation between the electrical power time series of the inverters is esti- mated with the wavelet transform. The wavelet correlation depends on the distance between the inverters, the wavelet time scales and the daily fluctuation level. Correlation values for time scales below one minute are low without dependence on the daily fluctuation level. For time scales above 20 minutes, positive high correlation values are obtained, and the decay rate with the distance depends on the daily fluctuation level. At intermediate time scales the correlation depends strongly on the daily fluctuation level. The proposed methods have been implemented using free software. Source code is available as supplementary material.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

Guidelines for the design of an environmental flow regime program at the regional scale: Application of the ELOHA framework in the Ebro River basin

La gestión de los recursos hídricos se convierte en un reto del presente y del futuro frente a un panorama de continuo incremento de la demanda de agua debido al crecimiento de la población, el crecimiento del desarrollo económico y los posibles efectos del calentamiento global. La política hidráulica desde los años 60 en España se ha centrado en la construcción de infraestructuras que han producido graves alteraciones en el régimen natural de los ríos. Estas alteraciones han provocado y acrecentado los impactos sobre los ecosistemas fluviales y ribereños. Desde los años 90, sin embargo, ha aumentado el interés de la sociedad para conservar estos ecosistemas. El concepto de caudales ambientales consiste en un régimen de caudales que simula las características principales del régimen natural. Los caudales ambientales están diseñados para conservar la estructura y funcionalidad de los ecosistemas asociados al régimen fluvial, bajo la hipótesis de que los elementos que conforman estos ecosistemas están profundamente adaptados al régimen natural de caudales, y que cualquier alteración del régimen natural puede provocar graves daños a todo el sistema. El método ELOHA (Ecological Limits of Hydrological Alteration) tiene como finalidad identificar las componentes del régimen natural de caudales que son clave para mantener el equilibrio de los ecosistemas asociados, y estimar los límites máximos de alteración de estas componentes para garantizar su buen estado. Esta tesis presenta la aplicación del método ELOHA en la cuenca del Ebro. La cuenca del Ebro está profundamente regulada e intervenida por el hombre, y sólo las cabeceras de los principales afluentes del Ebro gozan todavía de un régimen total o cuasi natural. La tesis se estructura en seis capítulos que desarrollan las diferentes partes del método. El primer capítulo explica cómo se originó el concepto “caudales ambientales” y en qué consiste el método ELOHA. El segundo capítulo describe el área de estudio. El tercer capítulo realiza una clasificación de los regímenes naturales de la cuenca (RNC) del Ebro, basada en series de datos de caudal mínimamente alterado y usando exclusivamente parámetros hidrológicos. Se identificaron seis tipos diferentes de régimen natural: pluvial mediterráneo, nivo-pluvial, pluvial mediterréaneo con una fuerte componente del caudal base, pluvial oceánico, pluvio-nival oceánico y Mediterráneo. En el cuarto capítulo se realiza una regionalización a toda la cuenca del Ebro de los seis RNC encontrados en la cueca. Mediante parámetros climáticos y fisiográficos se extrapola la información del tipo de RNC a puntos donde no existen datos de caudal inalterado. El patrón geográfico de los tipos de régimen fluvial obtenido con la regionalización resultó ser coincidente con el patrón obtenido a través de la clasificación hidrológica. El quinto capítulo presenta la validación biológica de los procesos de clasificación anteriores: clasificación hidrológica y regionalización. La validación biológica de los tipos de regímenes fluviales es imprescindible, puesto que los diferentes tipos de régimen fluvial van a servir de unidades de gestión para favorecer el mantenimiento de los ecosistemas fluviales. Se encontraron diferencias significativas entre comunidades biológicas en cinco de los seis tipos de RNC encontrados en la cuenca. Finalmente, en el sexto capítulo se estudian las relaciones hidro-ecológicas existentes en tres de los seis tipos de régimen fluvial encontrados en la cuenca del Ebro. Mediante la construcción de curvas hidro-ecológicas a lo largo de un gradiente de alteración hidrológica, se pueden sugerir los límites de alteración hidrológica (ELOHAs) para garantizar el buen estado ecológico en cada uno de los tipos fluviales estudiados. Se establecieron ELOHAs en tres de los seis tipos de RNC de la cuenca del Ebro Esta tesis, además, pone en evidencia la falta de datos biológicos asociados a registros de caudal. Para llevar a cabo la implantación de un régimen de caudales ambientales en la cuenca, la ubicación de los puntos de muestreo biológico cercanos a estaciones de aforo es imprescindible para poder extraer relaciones causa-efecto de la gestión hidrológica sobre los ecosistemas dependientes. ABSTRACT In view of a growing freshwater demand because of population raising, improvement of economies and the potential effects of climate change, water resources management has become a challenge for present and future societies. Water policies in Spain have been focused from the 60’s on constructing hydraulic infrastructures, in order to dampen flow variability and granting water availability along the year. Consequently, natural flow regimes have been deeply altered and so the depending habitats and its ecosystems. However, an increasing acknowledgment of societies for preserving healthy freshwater ecosystems started in the 90’s and agreed that to maintain healthy freshwater ecosystems, it was necessary to set environmental flow regimes based on the natural flow variability. The Natural Flow Regime paradigm (Richter et al. 1996, Poff et al. 1997) bases on the hypothesis that freshwater ecosystems are made up by elements adapted to natural flow conditions, and any change on these conditions can provoke deep impacts on the whole system. Environmental flow regime concept consists in designing a flow regime that emulates natural flow characteristics, so that ecosystem structure, functions and services are maintained. ELOHA framework (Ecological Limits of Hydrological Alteration) aims to identify key features of the natural flow regime (NFR) that are needed to maintain and preserve healthy freshwater and riparian ecosystems. Moreover, ELOHA framework aims to quantify thresholds of alteration of these flow features according to ecological impacts. This thesis describes the application of the ELOHA framework in the Ebro River Basin. The Ebro River basin is the second largest basin in Spain and it is highly regulated for human demands. Only the Ebro headwaters tributaries still have completely unimpaired flow regime. The thesis has six chapters and the process is described step by step. The first chapter makes an introduction to the origin of the environmental flow concept and the necessity to come up. The second chapter shows a description of the study area. The third chapter develops a classification of NFRs in the basin based on natural flow data and using exclusively hydrological parameters. Six NFRs were found in the basin: continental Mediterranean-pluvial, nivo-pluvial, continental Mediterranean pluvial (with groundwater-dominated flow pattern), pluvio-oceanic, pluvio-nival-oceanic and Mediterranean. The fourth chapter develops a regionalization of the six NFR types across the basin by using climatic and physiographic variables. The geographical pattern obtained from the regionalization process was consistent with the pattern obtained with the hydrologic classification. The fifth chapter performs a biological validation of both classifications, obtained from the hydrologic classification and the posterior extrapolation. When the aim of flow classification is managing water resources according to ecosystem requirements, a validation based on biological data is compulsory. We found significant differences in reference macroinvertebrate communities between five over the six NFR types identified in the Ebro River basin. Finally, in the sixth chapter we explored the existence of significant and explicative flow alteration-ecological response relationships (FA-E curves) within NFR types in the Ebro River basin. The aim of these curves is to find out thresholds of hydrological alteration (ELOHAs), in order to preserve healthy freshwater ecosystem. We set ELOHA values in three NFR types identified in the Ebro River basin. During the development of this thesis, an inadequate biological monitoring in the Ebro River basin was identified. The design and establishment of appropriate monitoring arrangements is a critical final step in the assessment and implementation of environmental flows. Cause-effect relationships between hydrology and macroinvertebrate community condition are the principal data that sustain FA-E curves. Therefore, both data sites must be closely located, so that the effects of external factors are minimized. The scarce hydro-biological pairs of data available in the basin prevented us to apply the ELOHA method at all NFR types.

Modeling of GRBAS perceptual evaluation using spectral features obtained from an auditory-based filterbank.

Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained.

Quantifying the relationship between drainage networks at hillslope scale and particle size distribution at pedon scale

Nowadays, translating information about hydrologic and soil properties and processes across scales has emerged as a major theme in soil science and hydrology, and suitable theories for upscaling or downscaling hydrologic and soil information are being looked forward. The recognition of low-order catchments as self-organized systems suggests the existence of a great amount of links at different scales between their elements. The objective of this work was to research in areas of homogeneous bedrock material, the relationship between the hierarchical structure of the drainage networks at hillslope scale and the heterogeneity of the particle-size distribution at pedon scale. One of the most innovative elements in this work is the choice of the parameters to quantify the organization level of the studied features. The fractal dimension has been selected to measure the hierarchical structure of the drainage networks, while the Balanced Entropy Index (BEI) has been the chosen parameter to quantify the heterogeneity of the particle-size distribution from textural data. These parameters have made it possible to establish quantifiable relationships between two features attached to different steps in the scale range. Results suggest that the bedrock lithology of the landscape constrains the architecture of the drainage networks developed on it and the particle soil distribution resulting in the fragmentation processes.

Quantifying the relationship between drainage networks at hillslope scale and particle size distribution at pedon scale

Nowadays, translating information about hydrologic and soil properties and processes across scales has emerged as a major theme in soil science and hydrology, and suitable theories for upscaling or downscaling hydrologic and soil information are being looked forward. The recognition of low-order catchments as self-organized systems suggests the existence of a great amount of links at different scales between their elements. The objective of this work was to research in areas of homogeneous bedrock material, the relationship between the hierarchical structure of the drainage networks at hillslope scale and the heterogeneity of the particle-size distribution at pedon scale. One of the most innovative elements in this work is the choice of the parameters to quantify the organization level of the studied features. The fractal dimension has been selected to measure the hierarchical structure of the drainage networks, while the Balanced Entropy Index (BEI) has been the chosen parameter to quantify the heterogeneity of the particle-size distribution from textural data. These parameters have made it possible to establish quantifiable relationships between two features attached to different steps in the scale range. Results suggest that the bedrock lithology of the landscape constrains the architecture of the drainage networks developed on it and the particle soil distribution resulting in the fragmentation processes.