Spatio-temporal filtering with morphological operators for robust cell migration estimation in "in-vivo" images

The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the "in-toto" reconstruction based on different modalities of "in-vivo" imaging techniques -spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive manual interaction -time and human resources- is always required to enforce coherence. Because of this limitation it is necessary to restrict the experiments or assume an uncontrolled error rate. Is it possible to obtain automated reliable measurements of migration? can we provide a seed for biologists to complete cell lineages efficiently? We propose a filtering technique that considers trajectories as spatio-temporal connected structures that prunes out those that might introduce noise and false positives by using multi-dimensional morphological operators.

Implementation of the disruption predictor APODIS in JET Real Time Network using the MARTe framework

Disruptions in tokamaks devices are unavoidable, and they can have a significant impact on machine integrity. So it is very important have mechanisms to predict this phenomenon. Disruption prediction is a very complex task, not only because it is a multi-dimensional problem, but also because in order to be effective, it has to detect well in advance the actual disruptive event, in order to be able to use successful mitigation strategies. With these constraints in mind a real-time disruption predictor has been developed to be used in JET tokamak. The predictor has been designed to run in the Multithreaded Application Real-Time executor (MARTe) framework. The predictor ?Advanced Predictor Of DISruptions? (APODIS) is based on Support Vector Machine (SVM).

Water scarcity and climate change impact and vulnerability in irrigated agriculture in Mediterranean river basins

Actualmente, la escasez de agua constituye un importante problema en muchos lugares del mundo. El crecimiento de la población, la creciente necesidad de alimentos, el desarrollo socio-económico y el cambio climático ejercen una importante y cada vez mayor presión sobre los recursos hídricos, a la que muchos países van a tener que enfrentarse en los próximos anos. La región Mediterránea es una de las regiones del mundo de mayor escasez de recursos hídricos, y es además una de las zonas más vulnerables al cambio climático. La mayoría de estudios sobre cambio climático prevén mayores temperaturas y una disminución de las precipitaciones, y una creciente escasez de agua debida a la disminución de recursos disponibles y al aumento de las demandas de riego. En el contexto actual de desarrollo de políticas se demanda cada vez más una mayor consideración del cambio climático en el marco de las políticas sectoriales. Sin embargo, los estudios enfocados a un solo sector no reflejan las múltiples dimensiones del los efectos del cambio climático. Numerosos estudios científicos han demostrado que el cambio climático es un fenómeno de naturaleza multi-dimensional y cuyos efectos se transmiten a múltiples escalas. Por tanto, es necesaria la producción de estudios y herramientas de análisis capaces de reflejar todas estas dimensiones y que contribuyan a la elaboración de políticas robustas en un contexto de cambio climático. Esta investigación pretende aportar una visión global de la problemática de la escasez de agua y los impactos, la vulnerabilidad y la adaptación al cambio climático en el contexto de la región mediterránea. La investigación presenta un marco integrado de modelización que se va ampliando progresivamente en un proceso secuencial y multi-escalar en el que en cada etapa se incorpora una nueva dimensión. La investigación consta de cuatro etapas que se abordan a lo largo de cuatro capítulos. En primer lugar, se estudia la vulnerabilidad económica de las explotaciones de regadío del Medio Guadiana, en España. Para ello, se utiliza un modelo de programación matemática en combinación con un modelo econométrico. A continuación, en la segunda etapa, se utiliza un modelo hidro-económico que incluye un modelo de cultivo para analizar los procesos que tienen lugar a escala de cultivo, explotación y cuenca teniendo en cuenta distintas escalas geográficas y de toma de decisiones. Esta herramienta permite el análisis de escenarios de cambio climático y la evaluación de posibles medidas de adaptación. La tercera fase consiste en el análisis de las barreras que dificultan la aplicación de procesos de adaptación para lo cual se analizan las redes socio-institucionales en la cuenca. Finalmente, la cuarta etapa aporta una visión sobre la escasez de agua y el cambio climático a escala nacional y regional mediante el estudio de distintos escenarios de futuro plausibles y los posibles efectos de las políticas en la escasez de agua. Para este análisis se utiliza un modelo econométrico de datos de panel para la región mediterránea y un modelo hidro-económico que se aplica a los casos de estudio de España y Jordania. Los resultados del estudio ponen de relieve la importancia de considerar múltiples escalas y múltiples dimensiones en el estudio de la gestión de los recursos hídricos y la adaptación al cambio climático en los contextos mediterráneos de escasez de agua estudiados. Los resultados muestran que los impactos del cambio climático en la cuenca del Guadiana y en el conjunto de España pueden comprometer la sostenibilidad del regadío y de los ecosistemas. El análisis a escala de cuenca hidrográfica resalta la importancia de las interacciones entre los distintos usuarios del agua y en concreto entre distintas comunidades de regantes, así como la necesidad de fortalecer el papel de las instituciones y de fomentar la creación de una visión común en la cuenca para facilitar la aplicación de los procesos de adaptación. Asimismo, los resultados de este trabajo evidencian también la capacidad y el papel fundamental de las políticas para lograr un desarrollo sostenible y la adaptación al cambio climático es regiones de escasez de agua tales como la región mediterránea. Especialmente, este trabajo pone de manifiesto el potencial de la Directiva Marco del Agua de la Unión Europea para lograr una efectiva adaptación al cambio climático. Sin embargo, en Jordania, además de la adaptación al cambio climático, es preciso diseñar estrategias de desarrollo sostenible más ambiciosas que contribuyan a reducir el riesgo futuro de escasez de agua. ABSTRACT Water scarcity is becoming a major concern in many parts of the world. Population growth, increasing needs for food production, socio-economic development and climate change represent pressures on water resources that many countries around the world will have to deal in the coming years. The Mediterranean region is one of the most water scarce regions of the world and is considered a climate change hotspot. Most projections of climate change envisage an increase in temperatures and a decrease in precipitation and a resulting reduction in water resources availability as a consequence of both reduced water availability and increased irrigation demands. Current policy development processes require the integration of climate change concerns into sectoral policies. However, sector-oriented studies often fail to address all the dimensions of climate change implications. Climate change research in the last years has evidenced the need for more integrated studies and methodologies that are capable of addressing the multi-scale and multi-dimensional nature of climate change. This research attempts to provide a comprehensive view of water scarcity and climate change impacts, vulnerability and adaptation in Mediterranean contexts. It presents an integrated modelling framework that is progressively enlarged in a sequential multi-scale process in which a new dimension of climate change and water resources is addressed at every stage. It is comprised of four stages, each one explained in a different chapter. The first stage explores farm-level economic vulnerability in the Spanish Guadiana basin using a mathematical programming model in combination with an econometric model. Then, in a second stage, the use of a hydro-economic modelling framework that includes a crop growth model allows for the analysis of crop, farm and basin level processes taking into account different geographical and decision-making scales. This integrated tool is used for the analysis of climate change scenarios and for the assessment of potential adaptation options. The third stage includes the analysis of barriers to the effective implementation of adaptation processes based on socioinstitutional network analysis. Finally, a regional and country level perspective of water scarcity and climate change is provided focusing on different possible socio-economic development pathways and the effect of policies on future water scarcity. For this analysis, a panel-data econometric model and a hydro-economic model are applied for the analysis of the Mediterranean region and country level case studies in Spain and Jordan. The overall results of the study demonstrate the value of considering multiple scales and multiple dimensions in water management and climate change adaptation in the Mediterranean water scarce contexts analysed. Results show that climate change impacts in the Guadiana basin and in Spain may compromise the sustainability of irrigation systems and ecosystems. The analysis at the basin level highlights the prominent role of interactions between different water users and irrigation districts and the need to strengthen institutional capacity and common understanding in the basin to enhance the implementation of adaptation processes. The results of this research also illustrate the relevance of water policies in achieving sustainable development and climate change adaptation in water scarce areas such as the Mediterranean region. Specifically, the EU Water Framework Directive emerges as a powerful trigger for climate change adaptation. However, in Jordan, outreaching sustainable development strategies are required in addition to climate change adaptation to reduce future risk of water scarcity.

Advances in global instability computations: from incompressible to hypersonic flow

Esta tesis constituye un gran avance en el conocimiento del estudio y análisis de inestabilidades hidrodinámicas desde un punto de vista físico y teórico, como consecuencia de haber desarrollado innovadoras técnicas para la resolución computacional eficiente y precisa de la parte principal del espectro correspondiente a los problemas de autovalores (EVP) multidimensionales que gobiernan la inestabilidad de flujos con dos o tres direcciones espaciales inhomogéneas, denominados problemas de estabilidad global lineal. En el contexto del trabajo de desarrollo de herramientas computacionales presentado en la tesis, la discretización mediante métodos de diferencias finitas estables de alto orden de los EVP bidimensionales y tridimensionales que se derivan de las ecuaciones de Navier-Stokes linealizadas sobre flujos con dos o tres direcciones espaciales inhomogéneas, ha permitido una aceleración de cuatro órdenes de magnitud en su resolución. Esta mejora de eficiencia numérica se ha conseguido gracias al hecho de que usando estos esquemas de diferencias finitas, técnicas eficientes de resolución de problemas lineales son utilizables, explotando el alto nivel de dispersión o alto número de elementos nulos en las matrices involucradas en los problemas tratados. Como más notable consecuencia cabe destacar que la resolución de EVPs multidimensionales de inestabilidad global, que hasta la fecha necesitaban de superordenadores, se ha podido realizar en ordenadores de sobremesa. Además de la solución de problemas de estabilidad global lineal, el mencionado desarrollo numérico facilitó la extensión de las ecuaciones de estabilidad parabolizadas (PSE) lineales y no lineales para analizar la inestabilidad de flujos que dependen fuertemente en dos direcciones espaciales y suavemente en la tercera con las ecuaciones de estabilidad parabolizadas tridimensionales (PSE-3D). Precisamente la capacidad de extensión del novedoso algoritmo PSE-3D para el estudio de interacciones no lineales de los modos de estabilidad, desarrollado íntegramente en esta tesis, permite la predicción de transición en flujos complejos de gran interés industrial y por lo tanto extiende el concepto clásico de PSE, el cuál ha sido empleado exitosamente durante las pasadas tres décadas en el mismo contexto para problemas de capa límite bidimensional. Típicos ejemplos de flujos incompresibles se han analizado en este trabajo sin la necesidad de recurrir a restrictivas presuposiciones usadas en el pasado. Se han estudiado problemas vorticales como es el caso de un vórtice aislado o sistemas de vórtices simulando la estela de alas, en los que la homogeneidad axial no se impone y así se puede considerar la difusión viscosa del flujo. Además, se ha estudiado el chorro giratorio turbulento, cuya inestabilidad se utiliza para mejorar las características de funcionamiento de combustores. En la tesis se abarcan adicionalmente problemas de flujos compresibles. Se presenta el estudio de inestabilidad de flujos de borde de ataque a diferentes velocidades de vuelo. También se analiza la estela formada por un elemento rugoso aislado en capa límite supersónica e hipersónica, mostrando excelentes comparaciones con resultados obtenidos mediante simulación numérica directa. Finalmente, nuevas inestabilidades se han identificado en el flujo hipersónico a Mach 7 alrededor de un cono elíptico que modela el vehículo de pruebas en vuelo HIFiRE-5. Los resultados comparan favorablemente con experimentos en vuelo, lo que subraya aún más el potencial de las metodologías de análisis de estabilidad desarrolladas en esta tesis. ABSTRACT The present thesis constitutes a step forward in advancing the frontiers of knowledge of fluid flow instability from a physical point of view, as a consequence of having been successful in developing groundbreaking methodologies for the efficient and accurate computation of the leading part of the spectrum pertinent to multi-dimensional eigenvalue problems (EVP) governing instability of flows with two or three inhomogeneous spatial directions. In the context of the numerical work presented in this thesis, the discretization of the spatial operator resulting from linearization of the Navier-Stokes equations around flows with two or three inhomogeneous spatial directions by variable-high-order stable finite-difference methods has permitted a speedup of four orders of magnitude in the solution of the corresponding two- and three-dimensional EVPs. This improvement of numerical performance has been achieved thanks to the high-sparsity level offered by the high-order finite-difference schemes employed for the discretization of the operators. This permitted use of efficient sparse linear algebra techniques without sacrificing accuracy and, consequently, solutions being obtained on typical workstations, as opposed to the previously employed supercomputers. Besides solution of the two- and three-dimensional EVPs of global linear instability, this development paved the way for the extension of the (linear and nonlinear) Parabolized Stability Equations (PSE) to analyze instability of flows which depend in a strongly-coupled inhomogeneous manner on two spatial directions and weakly on the third. Precisely the extensibility of the novel PSE-3D algorithm developed in the framework of the present thesis to study nonlinear flow instability permits transition prediction in flows of industrial interest, thus extending the classic PSE concept which has been successfully employed in the same context to boundary-layer type of flows over the last three decades. Typical examples of incompressible flows, the instability of which was analyzed in the present thesis without the need to resort to the restrictive assumptions used in the past, range from isolated vortices, and systems thereof, in which axial homogeneity is relaxed to consider viscous diffusion, as well as turbulent swirling jets, the instability of which is exploited in order to improve flame-holding properties of combustors. The instability of compressible subsonic and supersonic leading edge flows has been solved, and the wake of an isolated roughness element in a supersonic and hypersonic boundary-layer has also been analyzed with respect to its instability: excellent agreement with direct numerical simulation results has been obtained in all cases. Finally, instability analysis of Mach number 7 ow around an elliptic cone modeling the HIFiRE-5 flight test vehicle has unraveled flow instabilities near the minor-axis centerline, results comparing favorably with flight test predictions.

Digital Coherent Receivers and Advanced Optical Modulation Formats in 100 and 200 Gb/s DWDM Systems

Recent advances in coherent optical receivers is reviewed. Digital-Signal-Processing (DSP) based phase and polarization management techniques make coherent detection robust and feasible. With coherent detection, the complex field of the received optical signal is fully recovered, allowing compensation of linear and nonlinear optical impairments including chromatic dispersion (CD) and polarization-mode dispersion (PMD) using digital filters. Coherent detection and advanced optical modulation formats have become a key ingredient to the design of modern dense wavelength-division multiplexed (DWDM) optical broadband networks. In this paper, firstly we present the different subsystems of a digital coherent optical receiver, and secondly, we will compare the performance of some multi-level and multi-dimensional modulation formats in some physical impairments and in high spectral-efficiency (SE) and high-capacity DWDM transmissions, simulating the DSP with Matlab and the optical network performance with OptiSystem software.

Conditional density approximations with mixtures of polynomials

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method.

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Wavelet-based image fusion in multi-view three-dimensional microscopy

Multi-view microscopy techniques such as Light-Sheet Fluorescence Microscopy (LSFM) are powerful tools for 3D + time studies of live embryos in developmental biology. The sample is imaged from several points of view, acquiring a set of 3D views that are then combined or fused in order to overcome their individual limitations. Views fusion is still an open problem despite recent contributions in the field. We developed a wavelet-based multi-view fusion method that, due to wavelet decomposition properties, is able to combine the complementary directional information from all available views into a single volume. Our method is demonstrated on LSFM acquisitions from live sea urchin and zebrafish embryos. The fusion results show improved overall contrast and details when compared with any of the acquired volumes. The proposed method does not need knowledge of the system's point spread function (PSF) and performs better than other existing PSF independent fusion methods.

Effect of Aspect Ratio on the Three-Dimensional Global Instability Analysis of Incompressible Open Cavity Flows

The stability analysis of open cavity flows is a problem of great interest in the aeronautical industry. This type of flow can appear, for example, in landing gears or auxiliary power unit configurations. Open cavity flows is very sensitive to any change in the configuration, either physical (incoming boundary layer, Reynolds or Mach numbers) or geometrical (length to depth and length to width ratio). In this work, we have focused on the effect of geometry and of the Reynolds number on the stability properties of a threedimensional spanwise periodic cavity flow in the incompressible limit. To that end, BiGlobal analysis is used to investigate the instabilities in this configuration. The basic flow is obtained by the numerical integration of the Navier-Stokes equations with laminar boundary layers imposed upstream. The 3D perturbation, assumed to be periodic in the spanwise direction, is obtained as the solution of the global eigenvalue problem. A parametric study has been performed, analyzing the stability of the flow under variation of the Reynolds number, the L/D ratio of the cavity, and the spanwise wavenumber β. For consistency, multidomain high order numerical schemes have been used in all the computations, either basic flow or eigenvalue problems. The results allow to define the neutral curves in the range of L/D = 1 to L/D = 3. A scaling relating the frequency of the eigenmodes and the length to depth ratio is provided, based on the analysis results.

Multi-criteria selection of structural adhesives to bond ABS parts obtained by rapid prototyping

One of the most used methods in rapidprototyping is Fused Deposition Modeling (FDM), which provides components with a reasonable strength in plastic materials such as ABS and has a low environmental impact. However, the FDM process exhibits low levels of surface finishing, difficulty in getting complex and/or small geometries and low consistency in “slim” elements of the parts. Furthermore, “cantilever” elements need large material structures to be supported. The solution of these deficiencies requires a comprehensive review of the three-dimensional part design to enhance advantages and performances of FDM and reduce their constraints. As a key feature of this redesign a novel method of construction by assembling parts with structuraladhesive joints is proposed. These adhesive joints should be designed specifically to fit the plastic substrate and the FDM manufacturing technology. To achieve this, the most suitable structuraladhesiveselection is firstly required. Therefore, the present work analyzes five different families of adhesives (cyanoacrylate, polyurethane, epoxy, acrylic and silicone), and, by means of the application of technical multi-criteria decision analysis based on the analytic hierarchy process (AHP), to select the structuraladhesive that better conjugates mechanical benefits and adaptation to the FDM manufacturing process

Aplicaciones de interés forestal de las imágenes obtenidas con el sensor Multi-angle Imaging SpectroRadiometer (MISR)

Las aplicaciones de la teledetección al seguimiento de lo que ocurre en la superficie terrestre se han ido multiplicando y afinando con el lanzamiento de nuevos sensores por parte de las diferentes agencias espaciales. La necesidad de tener información actualizada cada poco tiempo y espacialmente homogénea, ha provocado el desarrollo de nuevos programas como el Earth Observing System (EOS) de la National Aeronautics and Space Administration (NASA). Uno de los sensores que incorpora el buque insignia de ese programa, el satélite TERRA, es el Multi-angle Imaging SpectroRadiometer (MISR), diseñado para capturar información multiangular de la superficie terrestre. Ya desde los años 1970, se conocía que la reflectancia de las diversas ocupaciones y usos del suelo variaba en función del ángulo de observación y de iluminación, es decir, que eran anisotrópicas. Tal variación estaba además relacionada con la estructura tridimensional de tales ocupaciones, por lo que se podía aprovechar tal relación para obtener información de esa estructura, más allá de la que pudiera proporcionar la información meramente espectral. El sensor MISR incorpora 9 cámaras a diferentes ángulos para capturar 9 imágenes casi simultáneas del mismo punto, lo que permite estimar con relativa fiabilidad la respuesta anisotrópica de la superficie terrestre. Varios trabajos han demostrado que se pueden estimar variables relacionadas con la estructura de la vegetación con la información que proporciona MISR. En esta Tesis se ha realizado una primera aplicación a la Península Ibérica, para comprobar su utilidad a la hora de estimar variables de interés forestal. En un primer paso se ha analizado la variabilidad temporal que se produce en los datos, debido a los cambios en la geometría de captación, es decir, debido a la posición relativa de sensores y fuente de iluminación, que en este caso es el Sol. Se ha comprobado cómo la anisotropía es mayor desde finales de otoño hasta principios de primavera debido a que la posición del Sol es más cercana al plano de los sensores. También se ha comprobado que los valores máximo y mínimo se van desplazando temporalmente entre el centro y el extremo angular. En la caracterización multiangular de ocupaciones del suelo de CORINE Land Cover que se ha realizado, se puede observar cómo la forma predominante en las imágenes con el Sol más alto es convexa con un máximo en la cámara más cercana a la fuente de iluminación. Sin embargo, cuando el Sol se encuentra mucho más bajo, ese máximo es muy externo. Por otra parte, los datos obtenidos en verano son mucho más variables para cada ocupación que los de noviembre, posiblemente debido al aumento proporcional de las zonas en sombra. Para comprobar si la información multiangular tiene algún efecto en la obtención de imágenes clasificadas según ocupación y usos del suelo, se han realizado una serie de clasificaciones variando la información utilizada, desde sólo multiespectral, a multiangular y multiespectral. Los resultados muestran que, mientras para las clasificaciones más genéricas la información multiangular proporciona los peores resultados, a medida que se amplían el número de clases a obtener tal información mejora a lo obtenido únicamente con información multiespectral. Por otra parte, se ha realizado una estimación de variables cuantitativas como la fracción de cabida cubierta (Fcc) y la altura de la vegetación a partir de información proporcionada por MISR a diferentes resoluciones. En el valle de Alcudia (Ciudad Real) se ha estimado la fracción de cabida cubierta del arbolado para un píxel de 275 m utilizando redes neuronales. Los resultados muestran que utilizar información multiespectral y multiangular puede mejorar casi un 20% las estimaciones realizadas sólo con datos multiespectrales. Además, las relaciones obtenidas llegan al 0,7 de R con errores inferiores a un 10% en Fcc, siendo éstos mucho mejores que los obtenidos con el producto elaborado a partir de datos multiespectrales del sensor Moderate Resolution Imaging Spectroradiometer (MODIS), también a bordo de Terra, para la misma variable. Por último, se ha estimado la fracción de cabida cubierta y la altura efectiva de la vegetación para 700.000 ha de la provincia de Murcia, con una resolución de 1.100 m. Los resultados muestran la relación existente entre los datos espectrales y los multiangulares, obteniéndose coeficientes de Spearman del orden de 0,8 en el caso de la fracción de cabida cubierta de la vegetación, y de 0,4 en el caso de la altura efectiva. Las estimaciones de ambas variables con redes neuronales y diversas combinaciones de datos, arrojan resultados con R superiores a 0,85 para el caso del grado de cubierta vegetal, y 0,6 para la altura efectiva. Los parámetros multiangulares proporcionados en los productos elaborados con MISR a 1.100 m, no obtienen buenos resultados por sí mismos pero producen cierta mejora al incorporarlos a la información espectral. Los errores cuadráticos medios obtenidos son inferiores a 0,016 para la Fcc de la vegetación en tanto por uno, y 0,7 m para la altura efectiva de la misma. Regresiones geográficamente ponderadas muestran además que localmente se pueden obtener mejores resultados aún mejores, especialmente cuando hay una mayor variabilidad espacial de las variables estimadas. En resumen, la utilización de los datos proporcionados por MISR ofrece una prometedora vía de mejora de resultados en la media-baja resolución, tanto para la clasificación de imágenes como para la obtención de variables cuantitativas de la estructura de la vegetación. ABSTRACT Applications of remote sensing for monitoring what is happening on the land surface have been multiplied and refined with the launch of new sensors by different Space Agencies. The need of having up to date and spatially homogeneous data, has led to the development of new programs such as the Earth Observing System (EOS) of the National Aeronautics and Space Administration (NASA). One of the sensors incorporating the flagship of that program, the TERRA satellite, is Multi-angle Imaging Spectroradiometer (MISR), designed to capture the multi-angle information of the Earth's surface. Since the 1970s, it was known that the reflectance of various land covers and land uses varied depending on the viewing and ilumination angles, so they are anisotropic. Such variation was also related to the three dimensional structure of such covers, so that one could take advantage of such a relationship to obtain information from that structure, beyond which spectral information could provide. The MISR sensor incorporates 9 cameras at different angles to capture 9 almost simultaneous images of the same point, allowing relatively reliable estimates of the anisotropic response of the Earth's surface. Several studies have shown that we can estimate variables related to the vegetation structure with the information provided by this sensor, so this thesis has made an initial application to the Iberian Peninsula, to check their usefulness in estimating forest variables of interest. In a first step we analyzed the temporal variability that occurs in the data, due to the changes in the acquisition geometry, i.e. the relative position of sensor and light source, which in this case is the Sun. It has been found that the anisotropy is greater from late fall through early spring due to the Sun's position closer to the plane of the sensors. It was also found that the maximum and minimum values are displaced temporarily between the center and the ends. In characterizing CORINE Land Covers that has been done, one could see how the predominant form in the images with the highest sun is convex with a maximum in the camera closer to the light source. However, when the sun is much lower, the maximum is external. Moreover, the data obtained for each land cover are much more variable in summer that in November, possibly due to the proportional increase in shadow areas. To check whether the information has any effect on multi-angle imaging classification of land cover and land use, a series of classifications have been produced changing the data used, from only multispectrally, to multi-angle and multispectral. The results show that while for the most generic classifications multi-angle information is the worst, as there are extended the number of classes to obtain such information it improves the results. On the other hand, an estimate was made of quantitative variables such as canopy cover and vegetation height using information provided by MISR at different resolutions. In the valley of Alcudia (Ciudad Real), we estimated the canopy cover of trees for a pixel of 275 m by using neural networks. The results showed that using multispectral and multiangle information can improve by almost 20% the estimates that only used multispectral data. Furthermore, the relationships obtained reached an R coefficient of 0.7 with errors below 10% in canopy cover, which is much better result than the one obtained using data from the Moderate Resolution Imaging Spectroradiometer (MODIS), also onboard Terra, for the same variable. Finally we estimated the canopy cover and the effective height of the vegetation for 700,000 hectares in the province of Murcia, with a spatial resolution of 1,100 m. The results show a relationship between the spectral and the multi-angle data, and provide estimates of the canopy cover with a Spearman’s coefficient of 0.8 in the case of the vegetation canopy cover, and 0.4 in the case of the effective height. The estimates of both variables using neural networks and various combinations of data, yield results with an R coefficient greater than 0.85 for the case of the canopy cover, and 0.6 for the effective height. Multi-angle parameters provided in the products made from MISR at 1,100 m pixel size, did not produce good results from themselves but improved the results when included to the spectral information. The mean square errors were less than 0.016 for the canopy cover, and 0.7 m for the effective height. Geographically weighted regressions also showed that locally we can have even better results, especially when there is high spatial variability of estimated variables. In summary, the use of the data provided by MISR offers a promising way of improving remote sensing performance in the low-medium spatial resolution, both for image classification and for the estimation of quantitative variables of the vegetation structure.

Neighborhood-corrected interface discontinuity factors for multi-group pin-by-pin diffusion calculations for LWR

Performing three-dimensional pin-by-pin full core calculations based on an improved solution of the multi-group diffusion equation is an affordable option nowadays to compute accurate local safety parameters for light water reactors. Since a transport approximation is solved, appropriate correction factors, such as interface discontinuity factors, are required to nearly reproduce the fully heterogeneous transport solution. Calculating exact pin-by-pin discontinuity factors requires the knowledge of the heterogeneous neutron flux distribution, which depends on the boundary conditions of the pin-cell as well as the local variables along the nuclear reactor operation. As a consequence, it is impractical to compute them for each possible configuration; however, inaccurate correction factors are one major source of error in core analysis when using multi-group diffusion theory. An alternative to generate accurate pin-by-pin interface discontinuity factors is to build a functional-fitting that allows incorporating the environment dependence in the computed values. This paper suggests a methodology to consider the neighborhood effect based on the Analytic Coarse-Mesh Finite Difference method for the multi-group diffusion equation. It has been applied to both definitions of interface discontinuity factors, the one based on the Generalized Equivalence Theory and the one based on Black-Box Homogenization, and for different few energy groups structures. Conclusions are drawn over the optimal functional-fitting and demonstrative results are obtained with the multi-group pin-by-pin diffusion code COBAYA3 for representative PWR configurations.

Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

Efficient Monte Carlo optimization for multi-label classifier chains

Multi-label classification (MLC) is the supervised learning problem where an instance may be associated with multiple labels. Modeling dependencies between labels allows MLC methods to improve their performance at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies. On the one hand, the original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors down the chain. On the other hand, a recent Bayes-optimal method improves the performance, but is computationally intractable in practice. Here we present a novel double-Monte Carlo scheme (M2CC), both for finding a good chain sequence and performing efficient inference. The M2CC algorithm remains tractable for high-dimensional data sets and obtains the best overall accuracy, as shown on several real data sets with input dimension as high as 1449 and up to 103 labels.

dOTM: a mechanism for distributing centralized multi-party video conferencing in the cloud

One of the key factors for a given application to take advantage of cloud computing is the ability to scale in an efficient, fast and reliable way. In centralized multi-party video conferencing, dynamically scaling a running conversation is a complex problem. In this paper we propose a methodology to divide the Multipoint Control Unit (the video conferencing server) into more simple units, broadcasters. Each broadcaster receives the media from a participant, processes it and forwards it to the rest. These broadcasters can be distributed among a group of CPUs. By using this methodology, video conferencing systems can scale in a more granular way, improving the deployment.