963 resultados para COUNT DATA MODELS


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The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

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This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

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In Sub-Saharan Africa, non-democratic events, like civil wars and coup d'etat, destroy economic development. This study investigates both domestic and spatial effects on the likelihood of civil wars and coup d'etat. To civil wars, an increase of income growth is one of common research conclusions to stop wars. This study adds a concern on ethnic fractionalization. IV-2SLS is applied to overcome causality problem. The findings document that income growth is significant to reduce number and degree of violence in high ethnic fractionalized countries, otherwise they are trade-off. Income growth reduces amount of wars, but increases its violent level, in the countries with few large ethnic groups. Promoting growth should consider ethnic composition. This study also investigates the clustering and contagion of civil wars using spatial panel data models. Onset, incidence and end of civil conflicts spread across the network of neighboring countries while peace, the end of conflicts, diffuse only with the nearest neighbor. There is an evidence of indirect links from neighboring income growth, without too much inequality, to reduce the likelihood of civil wars. To coup d'etat, this study revisits its diffusion for both all types of coups and only successful ones. The results find an existence of both domestic and spatial determinants in different periods. Domestic income growth plays major role to reduce the likelihood of coup before cold war ends, while spatial effects do negative afterward. Results on probability to succeed coup are similar. After cold war ends, international organisations seriously promote democracy with pressure against coup d'etat, and it seems to be effective. In sum, this study indicates the role of domestic ethnic fractionalization and the spread of neighboring effects to the likelihood of non-democratic events in a country. Policy implementation should concern these factors.

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A method is given for proving efficiency of NPMLE directly linked to empirical process theory. The conditions in general are appropriate consistency of the NPMLE, differentiability of the model, differentiability of the parameter of interest, local convexity of the parameter space, and a Donsker class condition for the class of efficient influence functions obtained by varying the parameters. For the case that the model is linear in the parameter and the parameter space is convex, as with most nonparametric missing data models, we show that the method leads to an identity for the NPMLE which almost says that the NPMLE is efficient and provides us straightforwardly with a consistency and efficiency proof. This identify is extended to an almost linear class of models which contain biased sampling models. To illustrate, the method is applied to the univariate censoring model, random truncation models, interval censoring case I model, the class of parametric models and to a class of semiparametric models.

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The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

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OBJECTIVES Patients with inflammatory bowel disease (IBD) have a high resource consumption, with considerable costs for the healthcare system. In a system with sparse resources, treatment is influenced not only by clinical judgement but also by resource consumption. We aimed to determine the resource consumption of IBD patients and to identify its significant predictors. MATERIALS AND METHODS Data from the prospective Swiss Inflammatory Bowel Disease Cohort Study were analysed for the resource consumption endpoints hospitalization and outpatient consultations at enrolment [1187 patients; 41.1% ulcerative colitis (UC), 58.9% Crohn's disease (CD)] and at 1-year follow-up (794 patients). Predictors of interest were chosen through an expert panel and a review of the relevant literature. Logistic regressions were used for binary endpoints, and negative binomial regressions and zero-inflated Poisson regressions were used for count data. RESULTS For CD, fistula, use of biologics and disease activity were significant predictors for hospitalization days (all P-values <0.001); age, sex, steroid therapy and biologics were significant predictors for the number of outpatient visits (P=0.0368, 0.023, 0.0002, 0.0003, respectively). For UC, biologics, C-reactive protein, smoke quitters, age and sex were significantly predictive for hospitalization days (P=0.0167, 0.0003, 0.0003, 0.0076 and 0.0175 respectively); disease activity and immunosuppressive therapy predicted the number of outpatient visits (P=0.0009 and 0.0017, respectively). The results of multivariate regressions are shown in detail. CONCLUSION Several highly significant clinical predictors for resource consumption in IBD were identified that might be considered in medical decision-making. In terms of resource consumption and its predictors, CD and UC show a different behaviour.

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At the time when at least two-thirds of the US states have already mandated some form of seller's property condition disclosure statement and there is a movement in this direction nationally, this paper examines the impact of seller's property condition disclosure law on the residential real estate values, the information asymmetry in housing transactions and shift of risk from buyers and brokers to the sellers, and attempts to ascertain the factors that lead to adoption of the disclosur law. The analytical structure employs parametric panel data models, semi-parametric propensity score matching models, and an event study framework using a unique set of economic and institutional attributes for a quarterly panel of 291 US Metropolitan Statistical Areas (MSAs) and 50 US States spanning 21 years from 1984 to 2004. Exploiting the MSA level variation in house prices, the study finds that the average seller may be able to fetch a higher price (about three to four percent) for the house if she furnishes a state-mandated seller's property condition disclosure statement to the buyer.

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This paper extends the existing research on real estate investment trust (REIT) operating efficiencies. We estimate stochastic-frontier, panel-data models specifying a translog cost function. The specified model updates the cost frontier with new information as it becomes available over time. The model can identify frontier cost improvements, returns to scale, and cost inefficiencies over time. The results disagree with most previous research in that we find no evidence of scale economies and some evidence of scale diseconomies. Moreover, we also generally find smaller inefficiencies than those shown by other REIT studies. Contrary to previous research, higher leverage associates with more efficiency.

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In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative.

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La Internet de las Cosas (IoT), como parte de la Futura Internet, se ha convertido en la actualidad en uno de los principales temas de investigación; en parte gracias a la atención que la sociedad está poniendo en el desarrollo de determinado tipo de servicios (telemetría, generación inteligente de energía, telesanidad, etc.) y por las recientes previsiones económicas que sitúan a algunos actores, como los operadores de telecomunicaciones (que se encuentran desesperadamente buscando nuevas oportunidades), al frente empujando algunas tecnologías interrelacionadas como las comunicaciones Máquina a Máquina (M2M). En este contexto, un importante número de actividades de investigación a nivel mundial se están realizando en distintas facetas: comunicaciones de redes de sensores, procesado de información, almacenamiento de grandes cantidades de datos (big--‐data), semántica, arquitecturas de servicio, etc. Todas ellas, de forma independiente, están llegando a un nivel de madurez que permiten vislumbrar la realización de la Internet de las Cosas más que como un sueño, como una realidad tangible. Sin embargo, los servicios anteriormente mencionados no pueden esperar a desarrollarse hasta que las actividades de investigación obtengan soluciones holísticas completas. Es importante proporcionar resultados intermedios que eviten soluciones verticales realizadas para desarrollos particulares. En este trabajo, nos hemos focalizado en la creación de una plataforma de servicios que pretende facilitar, por una parte la integración de redes de sensores y actuadores heterogéneas y geográficamente distribuidas, y por otra lado el desarrollo de servicios horizontales utilizando dichas redes y la información que proporcionan. Este habilitador se utilizará para el desarrollo de servicios y para la experimentación en la Internet de las Cosas. Previo a la definición de la plataforma, se ha realizado un importante estudio focalizando no sólo trabajos y proyectos de investigación, sino también actividades de estandarización. Los resultados se pueden resumir en las siguientes aseveraciones: a) Los modelos de datos definidos por el grupo “Sensor Web Enablement” (SWE™) del “Open Geospatial Consortium (OGC®)” representan hoy en día la solución más completa para describir las redes de sensores y actuadores así como las observaciones. b) Las interfaces OGC, a pesar de las limitaciones que requieren cambios y extensiones, podrían ser utilizadas como las bases para acceder a sensores y datos. c) Las redes de nueva generación (NGN) ofrecen un buen sustrato que facilita la integración de redes de sensores y el desarrollo de servicios. En consecuencia, una nueva plataforma de Servicios, llamada Ubiquitous Sensor Networks (USN), se ha definido en esta Tesis tratando de contribuir a rellenar los huecos previamente mencionados. Los puntos más destacados de la plataforma USN son: a) Desde un punto de vista arquitectónico, sigue una aproximación de dos niveles (Habilitador y Gateway) similar a otros habilitadores que utilizan las NGN (como el OMA Presence). b) Los modelos de datos están basado en los estándares del OGC SWE. iv c) Está integrado en las NGN pero puede ser utilizado sin ellas utilizando infraestructuras IP abiertas. d) Las principales funciones son: Descubrimiento de sensores, Almacenamiento de observaciones, Publicacion--‐subscripcion--‐notificación, ejecución remota homogénea, seguridad, gestión de diccionarios de datos, facilidades de monitorización, utilidades de conversión de protocolos, interacciones síncronas y asíncronas, soporte para el “streaming” y arbitrado básico de recursos. Para demostrar las funcionalidades que la Plataforma USN propuesta pueden ofrecer a los futuros escenarios de la Internet de las Cosas, se presentan resultados experimentales de tres pruebas de concepto (telemetría, “Smart Places” y monitorización medioambiental) reales a pequeña escala y un estudio sobre semántica (sistema de información vehicular). Además, se está utilizando actualmente como Habilitador para desarrollar tanto experimentación como servicios reales en el proyecto Europeo SmartSantander (que aspira a integrar alrededor de 20.000 dispositivos IoT). v Abstract Internet of Things, as part of the Future Internet, has become one of the main research topics nowadays; in part thanks to the pressure the society is putting on the development of a particular kind of services (Smart metering, Smart Grids, eHealth, etc.), and by the recent business forecasts that situate some players, like Telecom Operators (which are desperately seeking for new opportunities), at the forefront pushing for some interrelated technologies like Machine--‐to--‐Machine (M2M) communications. Under this context, an important number of research activities are currently taking place worldwide at different levels: sensor network communications, information processing, big--‐ data storage, semantics, service level architectures, etc. All of them, isolated, are arriving to a level of maturity that envision the achievement of Internet of Things (IoT) more than a dream, a tangible goal. However, the aforementioned services cannot wait to be developed until the holistic research actions bring complete solutions. It is important to come out with intermediate results that avoid vertical solutions tailored for particular deployments. In the present work, we focus on the creation of a Service--‐level platform intended to facilitate, from one side the integration of heterogeneous and geographically disperse Sensors and Actuator Networks (SANs), and from the other the development of horizontal services using them and the information they provide. This enabler will be used for horizontal service development and for IoT experimentation. Prior to the definition of the platform, we have realized an important study targeting not just research works and projects, but also standardization topics. The results can be summarized in the following assertions: a) Open Geospatial Consortium (OGC®) Sensor Web Enablement (SWE™) data models today represent the most complete solution to describe SANs and observations. b) OGC interfaces, despite the limitations that require changes and extensions, could be used as the bases for accessing sensors and data. c) Next Generation Networks (NGN) offer a good substrate that facilitates the integration of SANs and the development of services. Consequently a new Service Layer platform, called Ubiquitous Sensor Networks (USN), has been defined in this Thesis trying to contribute to fill in the previous gaps. The main highlights of the proposed USN Platform are: a) From an architectural point of view, it follows a two--‐layer approach (Enabler and Gateway) similar to other enablers that run on top of NGN (like the OMA Presence). b) Data models and interfaces are based on the OGC SWE standards. c) It is integrated in NGN but it can be used without it over open IP infrastructures. d) Main functions are: Sensor Discovery, Observation Storage, Publish--‐Subscribe--‐Notify, homogeneous remote execution, security, data dictionaries handling, monitoring facilities, authorization support, protocol conversion utilities, synchronous and asynchronous interactions, streaming support and basic resource arbitration. vi In order to demonstrate the functionalities that the proposed USN Platform can offer to future IoT scenarios, some experimental results have been addressed in three real--‐life small--‐scale proofs--‐of concepts (Smart Metering, Smart Places and Environmental monitoring) and a study for semantics (in--‐vehicle information system). Furthermore we also present the current use of the proposed USN Platform as an Enabler to develop experimentation and real services in the SmartSantander EU project (that aims at integrating around 20.000 IoT devices).

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We propose a linear regression method for estimating Weibull parameters from life tests. The method uses stochastic models of the unreliability at each failure instant. As a result, a heteroscedastic regression problem arises that is solved by weighted least squares minimization. The main feature of our method is an innovative s-normalization of the failure data models, to obtain analytic expressions of centers and weights for the regression. The method has been Monte Carlo contrasted with Benard?s approximation, and Maximum Likelihood Estimation; and it has the highest global scores for its robustness, and performance.

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Una gestión más eficiente y equitativa del agua a escala de cuenca no se puede centrar exclusivamente en el recurso hídrico en sí, sino también en otras políticas y disciplinas científicas. Existe un consenso creciente de que, además de la consideración de las cambiantes condiciones climáticas, es necesaria una integración de ámbitos de investigación tales como la agronomía, planificación del territorio y ciencias políticas y económicas a fin de satisfacer de manera sostenible las demandas de agua por parte de la sociedad y del medio natural. La Política Agrícola Común (PAC) es el principal motor de cambio en las tendencias de paisajes rurales y sistemas agrícolas, pero el deterioro del medio ambiente es ahora una de las principales preocupaciones. Uno de los cambios más relevantes se ha producido con la expansión e intensificación del olivar en España, principalmente con nuevas zonas de regadío o la conversión de olivares de secano a sistemas en regadío. Por otra parte, el cambio de las condiciones climáticas podría ejercer un papel importante en las tendencias negativas de las aportaciones a los ríos, pero no queda claro el papel que podrían estar jugando los cambios de uso de suelo y cobertura vegetal sobre las tendencias negativas de caudal observadas. Esta tesis tiene como objetivo mejorar el conocimiento de los efectos de la producción agrícola, política agraria y cambios de uso de suelo y cobertura vegetal sobre las condiciones de calidad del agua, respuesta hidrológica y apropiación del agua por parte de la sociedad. En primer lugar, el estudio determina las tendencias existentes de nitratos y sólidos en suspensión en las aguas superficiales de la cuenca del río Guadalquivir durante el periodo de 1998 a 2009. Desde una perspectiva de política agraria, la investigación trata de evaluar mediante un análisis de datos de panel las principales variables, incluyendo la reforma de la PAC de 2003, que están teniendo una influencia en ambos indicadores de calidad. En segundo lugar, la apropiación del agua y el nivel de contaminación por nitratos debido a la producción del aceite de oliva en España se determinan con una evaluación de la huella hídrica (HH), teniendo en cuenta una variabilidad espacial y temporal a largo de las provincias españolas y entre 1997 y 2008. Por último, la tesis analiza los efectos de los cambios de uso de suelo y cobertura vegetal sobre las tendencias negativas observadas en la zona alta del Turia, cabecera de la cuenca del río Júcar, durante el periodo 1973-2008 mediante una modelización ecohidrológica. En la cuenca del Guadalquivir cerca del 20% de las estaciones de monitoreo muestran tendencias significativas, lineales o cuadráticas, para cada indicador de calidad de agua. La mayoría de las tendencias significativas en nitratos están aumentando, y la mayoría de tendencias cuadráticas muestran un patrón en forma de U. Los modelos de regresión de datos de panel muestran que las variables más importantes que empeoran ambos indicadores de calidad del agua son la intensificación de biomasa y las exportaciones de ambos indicadores de calidad procedentes de aguas arriba. En regiones en las que el abandono agrícola y/o desintensificación han tenido lugar han mejorado las condiciones de calidad del agua. Para los nitratos, el desacoplamiento de las subvenciones a la agricultura y la reducción de la cuantía de las subvenciones a tierras de regadío subyacen en la reducción observada de la concentración de nitratos. Las medidas de modernización de regadíos y el establecimiento de zonas vulnerables a nitratos reducen la concentración en subcuencas que muestran una tendencia creciente de nitratos. Sin embargo, el efecto de las exportaciones de nitratos procedente de aguas arriba, la intensificación de la biomasa y los precios de los cultivos presentan un mayor peso, explicando la tendencia creciente observada de nitratos. Para los sólidos en suspensión, no queda de forma evidente si el proceso de desacoplamiento ha influido negativa o positivamente. Sin embargo, los mayores valores de las ayudas agrarias aún ligadas a la producción, en particular en zonas de regadío, conllevan un aumento de las tasas de erosión. Aunque la cuenca del Guadalquivir ha aumentado la producción agrícola y la eficiencia del uso del agua, el problema de las altas tasas de erosión aún no ha sido mitigado adecuadamente. El estudio de la huella hídrica (HH) revela que en 1 L de aceite de oliva español más del 99,5% de la HH está relacionado con la producción de la aceituna, mientras que menos del 0,5% se debe a otros componentes, es decir, a la botella, tapón y etiqueta. Durante el período estudiado, la HH verde en secano y en regadío representa alrededor del 72% y 12%, respectivamente, del total de la HH. Las HHs azul y gris representan 6% y 10%, respectivamente. La producción de aceitunas se concentra en regiones con una HH menor por unidad de producto. La producción de aceite de oliva ha aumentado su productividad del agua durante 1997-2008, incentivado por los crecientes precios del aceite, como también lo ha hecho la cantidad de exportaciones de agua virtual. De hecho, las mayores zonas productoras presentan una eficiencia alta del uso y de productividad del agua, así como un menor potencial de contaminación por nitratos. Pero en estas zonas se ve a la vez reflejado un aumento de presión sobre los recursos hídricos locales. El aumento de extracciones de agua subterránea relacionadas con las exportaciones de aceite de oliva podría añadir una mayor presión a la ya estresada cuenca del Guadalquivir, mostrando la necesidad de equilibrar las fuerzas del mercado con los recursos locales disponibles. Los cambios de uso de suelo y cobertura vegetal juegan un papel importante en el balance del agua de la cuenca alta del Turia, pero no son el principal motor que sustenta la reducción observada de caudal. El aumento de la temperatura es el principal factor que explica las mayores tasas de evapotranspiración y la reducción de caudales. Sin embargo, los cambios de uso de suelo y el cambio climático han tenido un efecto compensatorio en la respuesta hidrológica. Por un lado, el caudal se ha visto afectado negativamente por el aumento de la temperatura, mientras que los cambios de uso de suelo y cobertura vegetal han compensado positivamente con una reducción de las tasas de evapotranspiración, gracias a los procesos de disminución de la densidad de matorral y de degradación forestal. El estudio proporciona una visión que fortalece la interdisciplinariedad entre la planificación hidrológica y territorial, destacando la necesidad de incluir las implicaciones de los cambios de uso de suelo y cobertura vegetal en futuros planes hidrológicos. Estos hallazgos son valiosos para la gestión de la cuenca del río Turia, y el enfoque empleado es útil para la determinación del peso de los cambios de uso de suelo y cobertura vegetal en la respuesta hidrológica en otras regiones. ABSTRACT Achieving a more efficient and equitable water management at catchment scale does not only rely on the water resource itself, but also on other policies and scientific knowledge. There is a growing consensus that, in addition to consideration of changing climate conditions, integration with research areas such as agronomy, land use planning and economics and political science is required to meet sustainably the societal and environmental water demands. The Common Agricultural Policy (CAP) is a main driver for trends in rural landscapes and agricultural systems, but environmental deterioration is now a principal concern. One of the most relevant changes has occurred with the expansion and intensification of olive orchards in Spain, taking place mainly with new irrigated areas or with the conversion from rainfed to irrigated systems. Moreover, changing climate conditions might exert a major role on water yield trends, but it remains unclear the role that ongoing land use and land cover changes (LULCC) might have on observed river flow trends. This thesis aims to improve the understanding of the effects of agricultural production, policies and LULCC on water quality conditions, hydrological response and human water appropriation. Firstly, the study determines the existing trends for nitrates and suspended solids in the Guadalquivir river basin’s surface waters (south Spain) during the period from 1998 to 2009. From a policy perspective, the research tries to assess with panel data analysis the main drivers, including the 2003 CAP reform, which are having an influence on both water quality indicators. Secondly, water appropriation and nitrate pollution level originating from the production of olive oil in Spain is determined with a water footprint (WF) assessment, considering a spatial temporal variability across the Spanish provinces and from 1997 to 2008 years. Finally, the thesis analyzes the effects of the LULCC on the observed negative trends over the period 1973-2008 in the Upper Turia basin, headwaters of the Júcar river demarcation (east Spain), with ecohydrological modeling. In the Guadalquivir river basin about 20% of monitoring stations show significant trends, linear or quadratic, for each water quality indicator. Most significant trends of nitrates are augmenting than decreasing, and most significant quadratic terms of both indicators exhibit U-shaped patterns. The panel data models show that the most important drivers that are worsening nitrates and suspended solids in the basin are biomass intensification and exports of both water quality indicators from upland regions. In regions that agricultural abandonment and/or de-intensification have taken place the water quality conditions have improved. For nitrates, the decoupling of agricultural subsidies and the reduction of the amount of subsidies to irrigated land underlie the observed reduction of nitrates concentration. Measures of irrigation modernization and establishment of vulnerable zones to nitrates ameliorate the concentration of nitrates in subbasins showing an increasing trend. However, the effect of nitrates load from upland areas, intensification of biomass and crop prices present a greater weight leading to the final increasing trend in this subbasins group, where annual crops dominate. For suspended solids, there is no clear evidence that decoupling process have influenced negatively or positively. Nevertheless, greater values of subsidies still linked to production, particularly in irrigated regions, lead to increasing erosion rates. Although agricultural production has augmented in the basin and water efficiency in the agricultural sector has improved, the issue of high erosion rates has not yet been properly faced. The water footprint (WF) assessment reveals that for 1 L Spanish olive oil more than 99.5% of the WF is related to the olive fruit production, whereas less than 0.5% is due to other components i.e. bottle, cap and label. Over the studied period, the green WF in rainfed and irrigated systems represents about 72% and 12%, respectively, of the total WF. Blue and grey WFs represent 6% and 10%, respectively. The olive production is concentrated in regions with the smallest WF per unit of product. The olive oil production has increased its apparent water productivity from 1997 to 2008 incentivized by growing trade prices, but also did the amount of virtual water exports. In fact, the largest producing areas present high water use efficiency per product and apparent water productivity as well as less nitrates pollution potential, but this enhances the pressure on the available water resources. Increasing groundwater abstractions related to olive oil exports may add further pressure to the already stressed Guadalquivir basin. This shows the need to balance the market forces with the available local resources. Concerning the effects of LULCC on the Upper Turia basin’s streamflow, LULCC play a significant role on the water balance, but it is not the main driver underpinning the observed reduction on Turia's streamflow. Increasing mean temperature is the main factor supporting larger evapotranspiration rates and streamflow reduction. In fact, LULCC and climate change have had an offsetting effect on the streamflow generation during the study period. While streamflow has been negatively affected by increasing temperature, ongoing LULCC have positively compensated with reduced evapotranspiration rates, thanks to mainly shrubland clearing and forest degradation processes. The research provides insight for strengthening the interdisciplinarity between hydrological and spatial planning, highlighting the need to include the implications of LULCC in future hydrological plans. These findings are valuable for the management of the Turia river basin, as well as a useful approach for the determination of the weight of LULCC on the hydrological response in other regions.

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This paper introduces a road map for ICTs (Information and communication technologies) supporting planning, operation and management of energy systems in smart cities. The road map summarises different elements that form energy systems in cities and proposes research and technical development (RTD) and innovation activities for the development and innovation of ICTs for holistic design, planning and operation of energy systems. In addition, synergies with other ICT systems for smart cities are considered. There are four main target groups for the road map: 1) citizen; 2) building sector; 3) energy sector; and 4) municipality level. As an example for enabling active participation of citizens, the road map proposes how ICT can enable citizens? involvement among others into building design. The building sector roadmap proposes how ICTs can support the planning of buildings and renovations in the future, as well as how to manage building energy systems. The energy sector road map focuses on city?s energy systems and their planning and management, including e.g. demand side management, management of different district level energy systems, energy performance validation and management, energy data models, and smarter use of open energy data. Moreover, the municipality level road map proposes among others ICTs for better integration of city systems and city planning enabling maximised energy efficiency. In addition, one road map section suggests development needs related to open energy data, including among others the use of energy data and the development and harmonisation of energy data models. The road map has been assembled in the READY4SmartCities project (funded by EU 7th Framework Programme), which focuses on the energy system at the city level, consisting of centralised energy systems and connections to the national level energy grids, as well as interconnections to the neighbourhood and building level energy systems.

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La tecnología de múltiples antenas ha evolucionado para dar soporte a los actuales y futuros sistemas de comunicaciones inalámbricas en su afán por proporcionar la calidad de señal y las altas tasas de transmisión que demandan los nuevos servicios de voz, datos y multimedia. Sin embargo, es fundamental comprender las características espaciales del canal radio, ya que son las características del propio canal lo que limita en gran medida las prestaciones de los sistemas de comunicación actuales. Por ello surge la necesidad de estudiar la estructura espacial del canal de propagación para poder diseñar, evaluar e implementar de forma más eficiente tecnologías multiantena en los actuales y futuros sistemas de comunicación inalámbrica. Las tecnologías multiantena denominadas antenas inteligentes y MIMO han generado un gran interés en el área de comunicaciones inalámbricas, por ejemplo los sistemas de telefonía celular o más recientemente en las redes WLAN (Wireless Local Area Network), principalmente por la mejora que proporcionan en la calidad de las señales y en la tasa de transmisión de datos, respectivamente. Las ventajas de estas tecnologías se fundamentan en el uso de la dimensión espacial para obtener ganancia por diversidad espacial, como ya sucediera con las tecnologías FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access) y CDMA (Code Division Multiplexing Access) para obtener diversidad en las dimensiones de frecuencia, tiempo y código, respectivamente. Esta Tesis se centra en estudiar las características espaciales del canal con sistemas de múltiples antenas mediante la estimación de los perfiles de ángulos de llegada (DoA, Direction-of- Arrival) considerando esquemas de diversidad en espacio, polarización y frecuencia. Como primer paso se realiza una revisión de los sistemas con antenas inteligentes y los sistemas MIMO, describiendo con detalle la base matemática que sustenta las prestaciones ofrecidas por estos sistemas. Posteriormente se aportan distintos estudios sobre la estimación de los perfiles de DoA de canales radio con sistemas multiantena evaluando distintos aspectos de antenas, algoritmos de estimación, esquemas de polarización, campo lejano y campo cercano de las fuentes. Así mismo, se presenta un prototipo de medida MIMO-OFDM-SPAA3D en la banda ISM (Industrial, Scientific and Medical) de 2,45 Ghz, el cual está preparado para caracterizar experimentalmente el rendimiento de los sistemas MIMO, y para caracterizar espacialmente canales de propagación, considerando los esquemas de diversidad espacial, por polarización y frecuencia. Los estudios aportados se describen a continuación. Los sistemas de antenas inteligentes dependen en gran medida de la posición de los usuarios. Estos sistemas están equipados con arrays de antenas, los cuales aportan la diversidad espacial necesaria para obtener una representación espacial fidedigna del canal radio a través de los perfiles de DoA (DoA, Direction-of-Arrival) y por tanto, la posición de las fuentes de señal. Sin embargo, los errores de fabricación de arrays así como ciertos parámetros de señal conlleva un efecto negativo en las prestaciones de estos sistemas. Por ello se plantea un modelo de señal parametrizado que permite estudiar la influencia que tienen estos factores sobre los errores de estimación de DoA, tanto en acimut como en elevación, utilizando los algoritmos de estimación de DOA más conocidos en la literatura. A partir de las curvas de error, se pueden obtener parámetros de diseño para sistemas de localización basados en arrays. En un segundo estudio se evalúan esquemas de diversidad por polarización con los sistemas multiantena para mejorar la estimación de los perfiles de DoA en canales que presentan pérdidas por despolarización. Para ello se desarrolla un modelo de señal en array con sensibilidad de polarización que toma en cuenta el campo electromagnético de ondas planas. Se realizan simulaciones MC del modelo para estudiar el efecto de la orientación de la polarización como el número de polarizaciones usadas en el transmisor como en el receptor sobre la precisión en la estimación de los perfiles de DoA observados en el receptor. Además, se presentan los perfiles DoA obtenidos en escenarios quasiestáticos de interior con un prototipo de medida MIMO 4x4 de banda estrecha en la banda de 2,45 GHz, los cuales muestran gran fidelidad con el escenario real. Para la obtención de los perfiles DoA se propone un método basado en arrays virtuales, validado con los datos de simulación y los datos experimentales. Con relación a la localización 3D de fuentes en campo cercano (zona de Fresnel), se presenta un tercer estudio para obtener con gran exactitud la estructura espacial del canal de propagación en entornos de interior controlados (en cámara anecóica) utilizando arrays virtuales. El estudio analiza la influencia del tamaño del array y el diagrama de radiación en la estimación de los parámetros de localización proponiendo, para ello, un modelo de señal basado en un vector de enfoque de onda esférico (SWSV). Al aumentar el número de antenas del array se consigue reducir el error RMS de estimación y mejorar sustancialmente la representación espacial del canal. La estimación de los parámetros de localización se lleva a cabo con un nuevo método de búsqueda multinivel adaptativo, propuesto con el fin de reducir drásticamente el tiempo de procesado que demandan otros algoritmos multivariable basados en subespacios, como el MUSIC, a costa de incrementar los requisitos de memoria. Las simulaciones del modelo arrojan resultados que son validados con resultados experimentales y comparados con el límite de Cramer Rao en términos del error cuadrático medio. La compensación del diagrama de radiación acerca sustancialmente la exactitud de estimación de la distancia al límite de Cramer Rao. Finalmente, es igual de importante la evaluación teórica como experimental de las prestaciones de los sistemas MIMO-OFDM. Por ello, se presenta el diseño e implementación de un prototipo de medida MIMO-OFDM-SPAA3D autocalibrado con sistema de posicionamiento de antena automático en la banda de 2,45 Ghz con capacidad para evaluar la capacidad de los sistemas MIMO. Además, tiene la capacidad de caracterizar espacialmente canales MIMO, incorporando para ello una etapa de autocalibración para medir la respuesta en frecuencia de los transmisores y receptores de RF, y así poder caracterizar la respuesta de fase del canal con mayor precisión. Este sistema incorpora un posicionador de antena automático 3D (SPAA3D) basado en un scanner con 3 brazos mecánicos sobre los que se desplaza un posicionador de antena de forma independiente, controlado desde un PC. Este posicionador permite obtener una gran cantidad de mediciones del canal en regiones locales, lo cual favorece la caracterización estadística de los parámetros del sistema MIMO. Con este prototipo se realizan varias campañas de medida para evaluar el canal MIMO en términos de capacidad comparando 2 esquemas de polarización y tomando en cuenta la diversidad en frecuencia aportada por la modulación OFDM en distintos escenarios. ABSTRACT Multiple-antennas technologies have been evolved to be the support of the actual and future wireless communication systems in its way to provide the high quality and high data rates required by new data, voice and data services. However, it is important to understand the behavior of the spatial characteristics of the radio channel, since the channel by itself limits the performance of the actual wireless communications systems. This drawback raises the need to understand the spatial structure of the propagation channel in order to design, assess, and develop more efficient multiantenna technologies for the actual and future wireless communications systems. Multiantenna technologies such as ‘Smart Antennas’ and MIMO systems have generated great interest in the field of wireless communications, i.e. cellular communications systems and more recently WLAN (Wireless Local Area Networks), mainly because the higher quality and the high data rate they are able to provide. Their technological benefits are based on the exploitation of the spatial diversity provided by the use of multiple antennas as happened in the past with some multiaccess technologies such as FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access), and CDMA (Code Division Multiplexing Access), which give diversity in the domains of frequency, time and code, respectively. This Thesis is mainly focus to study the spatial channel characteristics using schemes of multiple antennas considering several diversity schemes such as space, polarization, and frequency. The spatial characteristics will be study in terms of the direction-of-arrival profiles viewed at the receiver side of the radio link. The first step is to do a review of the smart antennas and MIMO systems technologies highlighting their advantages and drawbacks from a mathematical point of view. In the second step, a set of studies concerning the spatial characterization of the radio channel through the DoA profiles are addressed. The performance of several DoA estimation methods is assessed considering several aspects regarding antenna array structure, polarization diversity, and far-field and near-field conditions. Most of the results of these studies come from simulations of data models and measurements with real multiantena prototypes. In the same way, having understand the importance of validate the theoretical data models with experimental results, a 2,4 GHz MIMO-OFDM-SPAA2D prototype is presented. This prototype is intended for evaluating MIMO-OFDM capacity in indoor and outdoor scenarios, characterize the spatial structure of radio channels, assess several diversity schemes such as polarization, space, and frequency diversity, among others aspects. The studies reported are briefly described below. As is stated in Chapter two, the determination of user position is a fundamental task to be resolved for the smart antenna systems. As these systems are equipped with antenna arrays, they can provide the enough spatial diversity to accurately draw the spatial characterization of the radio channel through the DoA profiles, and therefore the source location. However, certain real implementation factors related to antenna errors, signals, and receivers will certainly reduce the performance of such direction finding systems. In that sense, a parameterized narrowband signal model is proposed to evaluate the influence of these factors in the location parameter estimation through extensive MC simulations. The results obtained from several DoA algorithms may be useful to extract some parameter design for directing finding systems based on arrays. The second study goes through the importance that polarization schemes can have for estimating far-field DoA profiles in radio channels, particularly for scenarios that may introduce polarization losses. For this purpose, a narrowband signal model with polarization sensibility is developed to conduct an analysis of several polarization schemes at transmitter (TX) and receiver (RX) through extensive MC simulations. In addition, spatial characterization of quasistatic indoor scenarios is also carried out using a 2.45 GHz MIMO prototype equipped with single and dual-polarized antennas. A good agreement between the measured DoA profiles with the propagation scenario is achieved. The theoretical and experimental evaluation of polarization schemes is performed using virtual arrays. In that case, a DoA estimation method is proposed based on adding an phase reference to properly track the DoA, which shows good results. In the third study, the special case of near-field source localization with virtual arrays is addressed. Most of DoA estimation algorithms are focused in far-field source localization where the radiated wavefronts are assume to be planar waves at the receive array. However, when source are located close to the array, the assumption of plane waves is no longer valid as the wavefronts exhibit a spherical behavior along the array. Thus, a faster and effective method of azimuth, elevation angles-of-arrival, and range estimation for near-field sources is proposed. The efficacy of the proposed method is evaluated with simulation and validated with measurements collected from a measurement campaign carried out in a controlled propagation environment, i.e. anechoic chamber. Moreover, the performance of the method is assessed in terms of the RMSE for several array sizes, several source positions, and taking into account the effect of radiation pattern. In general, better results are obtained with larger array and larger source distances. The effect of the antennas is included in the data model leading to more accurate results, particularly for range rather than for angle estimation. Moreover, a new multivariable searching method based on the MUSIC algorithm, called MUSA (multilevel MUSIC-based algorithm), is presented. This method is proposed to estimate the 3D location parameters in a faster way than other multivariable algorithms, such as MUSIC algorithm, at the cost of increasing the memory size. Finally, in the last chapter, a MIMO-OFDM-SPAA3D prototype is presented to experimentally evaluate different MIMO schemes regarding antennas, polarization, and frequency in different indoor and outdoor scenarios. The prototype has been developed on a Software-Defined Radio (SDR) platform. It allows taking measurements where future wireless systems will be developed. The novelty of this prototype is concerning the following 2 subsystems. The first one is the tridimensional (3D) antenna positioning system (SPAA3D) based on three linear scanners which is developed for making automatic testing possible reducing errors of the antenna array positioning. A set of software has been developed for research works such as MIMO channel characterization, MIMO capacity, OFDM synchronization, and so on. The second subsystem is the RF autocalibration module at the TX and RX. This subsystem allows to properly tracking the spatial structure of indoor and outdoor channels in terms of DoA profiles. Some results are draw regarding performance of MIMO-OFDM systems with different polarization schemes and different propagation environments.

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En la mayoría de problemas de decisión a los que nos enfrentamos no hay evidencia sobre cuál es la mejor elección debido a la complejidad de los mismos. Esta complejidad está asociada a la existencia de múltiples objetivos conflictivos y a que en muchos casos solo se dispone de información incompleta o imprecisa sobre los distintos parámetros del modelo de decisión. Por otro lado, el proceso de toma de decisiones se puede realizar en grupo, debiendo incorporar al modelo las preferencias individuales de cada uno de los decisores y, posteriormente, agregarlas para alcanzar un consenso final, lo que dificulta más todavía el proceso de decisión. La metodología del Análisis de Decisiones (AD) es un procedimiento sistemático y lógico que permite estructurar y simplificar la tarea de tomar decisiones. Utiliza la información existente, datos recogidos, modelos y opiniones profesionales para cuantificar la probabilidad de los valores o impactos de las alternativas y la Teoría de la Utilidad para cuantificar las preferencias de los decisores sobre los posibles valores de las alternativas. Esta tesis doctoral se centra en el desarrollo de extensiones del modelo multicriterio en utilidad aditivo para toma de decisiones en grupo con veto en base al AD y al concepto de la intensidad de la dominancia, que permite explotar la información incompleta o imprecisa asociada a los parámetros del modelo. Se considera la posibilidad de que la importancia relativa que tienen los criterios del problema para los decisores se representa mediante intervalos de valores o información ordinal o mediante números borrosos trapezoidales. Adicionalmente, se considera que los decisores tienen derecho a veto sobre los valores de los criterios bajo consideración, pero solo un subconjunto de ellos es efectivo, teniéndose el resto solo en cuenta de manera parcial. ABSTRACT In most decision-making problems, the best choice is unclear because of their complexity. This complexity is mainly associated with the existence of multiple conflicting objectives. Besides, there is, in many cases, only incomplete or inaccurate information on the various decision model parameters. Alternatively, the decision-making process may be performed by a group. Consequently, the model must account for individual preferences for each decision-maker (DM), which have to be aggregated to reach a final consensus. This makes the decision process even more difficult. The decision analysis (DA) methodology is a systematic and logical procedure for structuring and simplifying the decision-making task. It takes advantage of existing information, collected data, models and professional opinions to quantify the probability of the alternative values or impacts and utility theory to quantify the DM’s preferences concerning the possible alternative values. This PhD. thesis focuses on developing extensions for a multicriteria additive utility model for group decision-making accounting for vetoes based on DA and on the concept of dominance intensity in order to exploit incomplete or imprecise information associated with the parameters of the decision-making model. We consider the possibility of the relative importance of criteria for DMs being represented by intervals or ordinal information, or by trapezoidal fuzzy numbers. Additionally, we consider that DMs are allowed to provide veto values for the criteria under consideration, of which only a subset are effective, whereas the remainder are only partially taken into account.