16 resultados para Impact analysis

em Universidad Politécnica de Madrid


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Software architecture is a key factor to scale up Agile Software Development ASD in large softwareintensive systems. Currently, software architectures are more often approached through mechanisms that enable to incrementally design and evolve software architectures aka. agile architecting. Agile architecting should be a light-weight decision-making process, which could be achieved by providing knowledge to assist agile architects in reasoning about changes. This paper presents the novel solution of using change-impact knowledge as the main driver for agile architecting. The solution consists of a Change Impact Analysis technique and a set of models to assist agile architects in the change -decision-making- process by retrieving the change-impact architectural knowledge resulting from adding or changing features iteration after iteration. To validate our approach, we have put our solution into practice by running a project of a metering management system in electric power networks in an i-smart software factory.

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This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

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

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Software Product Line Engineering (SPLE) has proved to have significant advantages in family-based software development, but also implies the up¬front design of a product-line architecture (PLA) from which individual product applications can be engineered. The big upfront design associated with PLAs is in conflict with the current need of "being open to change". However, the turbulence of the current business climate makes change inevitable in order to stay competitive, and requires PLAs to be open to change even late in the development. The trend of "being open to change" is manifested in the Agile Software Development (ASD) paradigm, but it is spreading to the domain of SPLE. To reduce the big upfront design of PLAs as currently practiced in SPLE, new paradigms are being created, one being Agile Product Line Engineering (APLE). APLE aims to make the development of product-lines more flexible and adaptable to changes as promoted in ASD. To put APLE into practice it is necessary to make mechanisms available to assist and guide the agile construction and evolution of PLAs while complying with the "be open to change" agile principle. This thesis defines a process for "the agile construction and evolution of product-line architectures", which we refer to as Agile Product-Line Archi-tecting (APLA). The APLA process provides agile architects with a set of models for describing, documenting and tracing PLAs, as well as an algorithm to analyze change impact. Both the models and the change impact analysis offer the following capabilities: Flexibility & adaptability at the time of defining software architectures, enabling change during the incremental and iterative design of PLAs (anticipated or planned changes) and their evolution (unanticipated or unforeseen changes). Assistance in checking architectural integrity through change impact analysis in terms of architectural concerns, such as dependencies on earlier design decisions, rationale, constraints, and risks, etc.Guidance in the change decision-making process through change im¬pact analysis in terms of architectural components and connections. Therefore, APLA provides the mechanisms required to construct and evolve PLAs that can easily be refined iteration after iteration during the APLE development process. These mechanisms are provided in a modeling frame¬work called FPLA. The contributions of this thesis have been validated through the conduction of a project regarding a metering management system in electrical power networks. This case study took place in an i-smart software factory and was in collaboration with the Technical University of Madrid and Indra Software Labs. La Ingeniería de Líneas de Producto Software (Software Product Line Engi¬neering, SPLE) ha demostrado tener ventajas significativas en el desarrollo de software basado en familias de productos. SPLE es un paradigma que se basa en la reutilización sistemática de un conjunto de características comunes que comparten los productos de un mismo dominio o familia, y la personalización masiva a través de una variabilidad bien definida que diferencia unos productos de otros. Este tipo de desarrollo requiere el diseño inicial de una arquitectura de línea de productos (Product-Line Architecture, PLA) a partir de la cual los productos individuales de la familia son diseñados e implementados. La inversión inicial que hay que realizar en el diseño de PLAs entra en conflicto con la necesidad actual de estar continuamente "abierto al cam¬bio", siendo este cambio cada vez más frecuente y radical en la industria software. Para ser competitivos es inevitable adaptarse al cambio, incluso en las últimas etapas del desarrollo de productos software. Esta tendencia se manifiesta de forma especial en el paradigma de Desarrollo Ágil de Software (Agile Software Development, ASD) y se está extendiendo también al ámbito de SPLE. Con el objetivo de reducir la inversión inicial en el diseño de PLAs en la manera en que se plantea en SPLE, en los último años han surgido nuevos enfoques como la Ingeniera de Líneas de Producto Software Ágiles (Agile Product Line Engineering, APLE). APLE propone el desarrollo de líneas de producto de forma más flexible y adaptable a los cambios, iterativa e incremental. Para ello, es necesario disponer de mecanismos que ayuden y guíen a los arquitectos de líneas de producto en el diseño y evolución ágil de PLAs, mientras se cumple con el principio ágil de estar abierto al cambio. Esta tesis define un proceso para la "construcción y evolución ágil de las arquitecturas de lineas de producto software". A este proceso se le ha denominado Agile Product-Line Architecting (APLA). El proceso APLA proporciona a los arquitectos software un conjunto de modelos para de¬scribir, documentar y trazar PLAs, así como un algoritmo para analizar vel impacto del cambio. Los modelos y el análisis del impacto del cambio ofrecen: Flexibilidad y adaptabilidad a la hora de definir las arquitecturas software, facilitando el cambio durante el diseño incremental e iterativo de PLAs (cambios esperados o previstos) y su evolución (cambios no previstos). Asistencia en la verificación de la integridad arquitectónica mediante el análisis de impacto de los cambios en términos de dependencias entre decisiones de diseño, justificación de las decisiones de diseño, limitaciones, riesgos, etc. Orientación en la toma de decisiones derivadas del cambio mediante el análisis de impacto de los cambios en términos de componentes y conexiones. De esta manera, APLA se presenta como una solución para la construcción y evolución de PLAs de forma que puedan ser fácilmente refinadas iteración tras iteración de un ciclo de vida de líneas de producto ágiles. Dicha solución se ha implementado en una herramienta llamada FPLA (Flexible Product-Line Architecture) y ha sido validada mediante su aplicación en un proyecto de desarrollo de un sistema de gestión de medición en redes de energía eléctrica. Dicho proyecto ha sido desarrollado en una fábrica de software global en colaboración con la Universidad Politécnica de Madrid e Indra Software Labs.

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Urban areas benefit from significant improvements in accessibility when a new high speed rail (HSR) project is built. These improvements, which are due mainly to a rise in efficiency, produce locational advantagesand increase the attractiveness of these cities, thereby possibly enhancing their competitivenessand economic growth. However, there may be equity issues at stake, as the main accessibility benefits are primarily concentrated in urban areas with a HSR station, whereas other locations obtain only limited benefits. HSR extensions may contribute to an increase in spatial imbalance and lead to more polarized patterns of spatial development. Procedures for assessing the spatial impacts of HSR must therefore follow a twofold approach which addresses issues of both efficiency and equity. This analysis can be made by jointly assessing both the magnitude and distribution of the accessibility improvements deriving from a HSR project. This paper describes an assessment methodology for HSR projects which follows this twofold approach. The procedure uses spatial impact analysis techniques and is based on the computation of accessibility indicators, supported by a Geographical Information System (GIS). Efficiency impacts are assessed in terms of the improvements in accessibility resulting from the HSR project, with a focus on major urban areas; and spatial equity implications are derived from changes in the distribution of accessibility values among these urban agglomerations.

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1. Introduction: setting and problem definition 2. The Adaptation Pathway –2.1 Stage 1: appraising risks and opportunities •Step 1: Impact analysis •Step 2: Policy analysis •Step 3: Socio-institutional analysis –2.2 Stage 2: appraising and choosing adaptation opt ions •Step 4: identifying and prioritizing adaptation o ptions 3. Conclusions

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Sustainable transport planning requires an integrated approach involving strategic planning, impact analysis and multi-criteria evaluation. This study aims at relaxing the utility-based decision-making assumption by newly embedding anticipated-regret and combined utility-regret decision mechanisms in an integrated transport planning framework. The framework consists of a two-round Delphi survey, an integrated land-use and transport model for Madrid, and multi-criteria analysis. Results show that (i) regret-based ranking has similar mean but larger variance than utility-based ranking; (ii) the least-regret scenario forms a compromise between the desired and the expected scenarios; (iii) the least-regret scenario can lead to higher user benefits in the short-term and lower user benefits in the long-term; (iv) utility-based, regret-based and combined utility-regret-based multi-criteria analysis result in different rankings of policy packages; and (v) the combined utility-regret ranking is more informative compared with utility-based or regret-based ranking.

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La teledetección o percepción remota (remote sensing) es la ciencia que abarca la obtención de información (espectral, espacial, temporal) sobre un objeto, área o fenómeno a través del análisis de datos adquiridos por un dispositivo que no está en contacto con el elemento estudiado. Los datos obtenidos a partir de la teledetección para la observación de la superficie terrestre comúnmente son imágenes, que se caracterizan por contar con un sinnúmero de aplicaciones que están en continua evolución, por lo cual para solventar los constantes requerimientos de nuevas aplicaciones a menudo se proponen nuevos algoritmos que mejoran o facilitan algún proceso en particular. Para el desarrollo de dichos algoritmos, es preciso hacer uso de métodos matemáticos que permitan la manipulación de la información con algún fin específico. Dentro de estos métodos, el análisis multi-resolución se caracteriza por permitir analizar una señal en diferentes escalas, lo que facilita trabajar con datos que puedan tener resoluciones diferentes, tal es el caso de las imágenes obtenidas mediante teledetección. Una de las alternativas para la implementación de análisis multi-resolución es la Transformada Wavelet Compleja de Doble Árbol (DT-CWT). Esta transformada se implementa a partir de dos filtros reales y se caracteriza por presentar invariancia a traslaciones, precio a pagar por su característica de no ser críticamente muestreada. A partir de las características de la DT-CWT se propone su uso en el diseño de algoritmos de procesamiento de imagen, particularmente imágenes de teledetección. Estos nuevos algoritmos de procesamiento digital de imágenes de teledetección corresponden particularmente a fusión y detección de cambios. En este contexto esta tesis presenta tres algoritmos principales aplicados a fusión, evaluación de fusión y detección de cambios en imágenes. Para el caso de fusión de imágenes, se presenta un esquema general que puede ser utilizado con cualquier algoritmo de análisis multi-resolución; este algoritmo parte de la implementación mediante DT-CWT para luego extenderlo a un método alternativo, el filtro bilateral. En cualquiera de los dos casos la metodología implica que la inyección de componentes pueda realizarse mediante diferentes alternativas. En el caso del algoritmo de evaluación de fusión se presenta un nuevo esquema que hace uso de procesos de clasificación, lo que permite evaluar los resultados del proceso de fusión de forma individual para cada tipo de cobertura de uso de suelo que se defina en el proceso de evaluación. Esta metodología permite complementar los procesos de evaluación tradicionales y puede facilitar el análisis del impacto de la fusión sobre determinadas clases de suelo. Finalmente, los algoritmos de detección de cambios propuestos abarcan dos enfoques. El primero está orientado a la obtención de mapas de sequía en datos multi-temporales a partir de índices espectrales. El segundo enfoque propone la utilización de un índice global de calidad espectral como filtro espacial. La utilización de dicho filtro facilita la comparación espectral global entre dos imágenes, esto unido a la utilización de umbrales, conlleva a la obtención de imágenes diferencia que contienen la información de cambio. ABSTRACT Remote sensing is a science relates to information gathering (spectral, spatial, temporal) about an object, area or phenomenon, through the analysis of data acquired by a device that is not in contact with the studied item. In general, data obtained from remote sensing to observe the earth’s surface are images, which are characterized by having a number of applications that are constantly evolving. Therefore, to solve the constant requirements of applications, new algorithms are proposed to improve or facilitate a particular process. With the purpose of developing these algorithms, each application needs mathematical methods, such as the multiresolution analysis which allows to analyze a signal at different scales. One of the options is the Dual Tree Complex Wavelet Transform (DT-CWT) which is implemented from two real filters and is characterized by invariance to translations. Among the advantages of this transform is its successful application in image fusion and change detection areas. In this regard, this thesis presents three algorithms applied to image fusion, assessment for image fusion and change detection in multitemporal images. For image fusion, it is presented a general outline that can be used with any multiresolution analysis technique; this algorithm is proposed at first with DT-CWT and then extends to an alternative method, the bilateral filter. In either case the method involves injection of components by various means. For fusion assessment, the proposal is focused on a scheme that uses classification processes, which allows evaluating merger results individually for each type of land use coverage that is defined in evaluation process. This methodology allows complementing traditional assessment processes and can facilitate impact analysis of the merger on certain kinds of soil. Finally, two approaches of change detection algorithms are included. The first is aimed at obtaining drought maps in multitemporal data from spectral indices. The second one takes a global index of spectral quality as a spatial filter. The use of this filter facilitates global spectral comparison between two images and by means of thresholding, allows imaging containing change information.

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This paper proposes an economic instrument designed to assess the competitive nature of the sugar industry in Romania. In the first part of the paper is presented the theoretical background underlying index (HHI) and its calculation methodology. Then comes the results of a first application of this index for a total of 10 plants in the sugar industry, the robustness of these results is discussed. We believe HHI is a proactive tool that may prove useful competition authority, in its pursuit of continuous monitoring of various industries in the economy and in the internal decision-making on resource allocation institution (Peacock, and Prisecaru, 2013).The starting point of our research is to free competition in the European market with competitors much stronger than Romanian plants, plants that produce at a price lower than the domestic ones. In our study we will see if it is a concentration of production in factories around the strongest in Romania, concentration accompanied by the collapse of those who could not resist the market.The market concentration, competition policy, we will follow using the HHI index, for evaluation of impact analysis on existing trade, the number and size of competitors, protecting existing sales structures, avoiding disruptions in the competitive environment, etc.

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In this paper, the authors present results from a study on the usage rate of 2.0 tools and technologies among Spanish enterprises. The main objective of the study is to analyze, from the perceptions of executives, the influence of social software tools on a set of business processes. This analysis has been made using two graphic tools: the “2.0 Success Matrix” and the “Tool’s Footprint”. Both the review of literature and the empirical work have lead to important findings and conclusions.

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This paper studies the effect of different penetration rates of plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EV) in the Spanish electrical system. A stochastic model for the average trip evaluation and for the arriving and departure times is used to determine the availability of the vehicles for charging. A novel advanced charging algorithm is proposed, which avoids any communication among all agents. Its performance is determined through different charging scenarios.

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3D woven composites reinforced with either S2 glass, carbon or a hybrid combination of both and containing either polyethylene or carbon z-yarns were tested under low-velocity impact. Different impact energies (in the range of 21–316 J) were used and the mechanical response (in terms of the impact strength and energy dissipated) was compared with that measured in high-performance, albeit standard, 2D laminates. It was found that the impact strength in both 2D and 3D materials was mainly dependent on the in-plane fiber fracture. Conversely, the energy absorption capability was primarily influenced by the presence of z-yarns, having the 3D composites dissipated over twice the energy than the 2D laminates, irrespective of their individual characteristics (fiber type, compaction degree, porosity, etc.). X-ray microtomography revealed that this improvement was due to the z-yarns, which delayed delamination and maintained the structural integrity of the laminate, promoting energy dissipation by tow splitting, intensive fiber breakage under the tup and formation of a plug by out-of-plane shear.

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We show that for a tether at 800 km altitude, which is 5 km long, 2 cm wide and 0.05 mm thick, the risk of substantial damage during a 3 month period due to multiple impacts with debris or micrometeoroids is low, of about 1.4%. By substantial damage we mean that if the tape is divided in 2 cm2 cm squares, then in some square the damaged area by bombardment with debris or micrometeoroids exceeds 11% of the area of the square. Furthermore, we show that the danger posed by the micrometeoroids is negligible compared to the risk posed by the debris.

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A pesar de los importantes avances en la reducción del hambre, la seguridad alimentaria continúa siendo un reto de dimensión internacional. La seguridad alimentaria es un concepto amplio y multidimensional, cuyo análisis abarca distintas escalas y horizontes temporales. Dada su complejidad, la identificación de las causas de la inseguridad alimentaria y la priorización de las medias para abordarlas, son dos cuestiones que suscitan un intenso debate en la actualidad. El objetivo de esta tesis es evaluar el impacto de la globalización y el crecimiento económico en la seguridad alimentaria en los países en desarrollo, desde una perspectiva macro y un horizonte temporal a largo plazo. La influencia de la globalización se aborda de una manera secuencial. En primer lugar, se analiza la relación entre la inversión público-privada en infraestructuras y las exportaciones agrarias. A continuación, se estudia el impacto de las exportaciones agrarias en los indicadores de seguridad alimentaria. El estudio del impacto del crecimiento económico aborda los cambios paralelos en la distribución de la renta, y cómo la inequidad influye en el comportamiento de la seguridad alimentaria nacional. Además, se analiza en qué medida el crecimiento económico contribuye a acelerar el proceso de mejora de la seguridad alimentaria. Con el fin de conseguir los objetivos mencionados, se llevan a cabo varios análisis econométricos basados en datos de panel, en el que se combinan datos de corte transversal de 52 países y datos temporales comprendidos en el periodo 1991-2012. Se analizan tanto variables en niveles como variables en tasas de cambio anual. Se aplican los modelos de estimación de efectos variables y efectos fijos, ambos en niveles y en primeras diferencias. La tesis incluye cuatro tipos de modelos econométricos, cada uno de ellos con sus correspondientes pruebas de robustez y especificaciones. Los resultados matizan la importancia de la globalización y el crecimiento económico como mecanismos de mejora de la seguridad alimentaria en los países en desarrollo. Se obtienen dos conclusiones relativas a la globalización. En primer lugar, los resultados sugieren que la promoción de las inversiones privadas en infraestructuras contribuye a aumentar las exportaciones agrarias. En segundo lugar, se observa que las exportaciones agrarias pueden tener un impacto negativo en los indicadores de seguridad alimentaria. La combinación de estas dos conclusiones sugiere que la apertura comercial y financiera no contribuye por sí misma a la mejora de la seguridad alimentaria en los países en desarrollo. La apertura internacional de los países en desarrollo ha de ir acompañada de políticas e inversiones que desarrollen sectores productivos de alto valor añadido, que fortalezcan la economía nacional y reduzcan su dependencia exterior. En relación al crecimiento económico, a pesar del incuestionable hecho de que el crecimiento económico es una condición necesaria para reducir los niveles de subnutrición, no es una condición suficiente. Se han identificado tres estrategias adicionales que han de acompañar al crecimiento económico con el fin de intensificar su impacto positivo sobre la subnutrición. Primero, es necesario que el crecimiento económico sea acompañado de una distribución más equitativa de los ingresos. Segundo, el crecimiento económico ha de reflejarse en un aumento de inversiones en salud, agua y saneamiento y educación. Se observa que, incluso en ausencia de crecimiento económico, mejoras en el acceso a agua potable contribuyen a reducir los niveles de población subnutrida. Tercero, el crecimiento económico sostenible en el largo plazo parece tener un mayor impacto positivo sobre la seguridad alimentaria que el crecimiento económico más volátil o inestable en el corto plazo. La estabilidad macroeconómica se identifica como una condición necesaria para alcanzar una mayor mejora en la seguridad alimentaria, incluso habiéndose mejorado la equidad en la distribución de los ingresos. Por último, la tesis encuentra que los países en desarrollo analizados han experimentado diferentes trayectorias no lineales en su proceso de mejora de sus niveles de subnutrición. Los resultados sugieren que un mayor nivel inicial de subnutrición y el crecimiento económico son responsables de una respuesta más rápida al reto de la mejora de la seguridad alimentaria. ABSTRACT Despite the significant reductions of hunger, food security still remains a global challenge. Food security is a wide concept that embraces multiple dimensions, and has spatial-temporal scales. Because of its complexity, the identification of the drivers underpinning food insecurity and the prioritization of measures to address them are a subject of intensive debate. This thesis attempts to assess the impact of globalization and economic growth on food security in developing countries with a macro level scale (country) and using a long-term approach. The influence of globalization is addressed in a sequential way. First, the impact of public-private investment in infrastructure on agricultural exports in developing countries is analyzed. Secondly, an assessment is conducted to determine the impact of agricultural exports on food security indicators. The impact of economic growth focuses on the parallel changes in income inequality and how the income distribution influences countries' food security performance. Furthermore, the thesis analyzes to what extent economic growth helps accelerating food security improvements. To address the above mentioned goals, various econometric models are formulated. Models use panel data procedures combining cross-sectional data of 52 countries and time series data from 1991 to 2012. Yearly data are expressed both in levels and in changes. The estimation models applied are random effects estimation and fixed effects estimations, both in levels and in first differences. The thesis includes four families of econometric models, each with its own set of robustness checks and specifications. The results qualify the relevance of globalization and economic growth as enabling mechanisms for improving food security in developing countries. Concerning globalization, two main conclusions can be drawn. First, results showed that enhancing foreign private investment in infrastructures contributes to increase agricultural exports. Second, agricultural exports appear to have a negative impact on national food security indicators. These two conclusions suggest that trade and financial openness per se do not contribute directly to improve food security in development countries. Both measures should be accompanied by investments and policies to support the development of national high value productive sectors, to strengthen the domestic economy and reduce its external dependency. Referring to economic growth, despite the unquestionable fact that income growth is a pre-requisite for reducing undernourishment, results suggest that it is a necessary but not a sufficient condition. Three additional strategies should accompany economic growth to intensifying its impact on food security. Firstly, it is necessary that income growth should be accompanied by a better distribution of income. Secondly, income growth needs to be followed by investments and policies in health, sanitation and education to improve food security. Even if economic growth falters, sustained improvements in the access to drinking water may still give rise to reductions in the percentage of undernourished people. And thirdly, long-term economic growth appears to have a greater impact on reducing hunger than growth regimes that combine periods of growth peaks followed by troughs. Macroeconomic stability is a necessary condition for accelerating food security. Finally, the thesis finds that the developing countries analyzed have experienced different non-linear paths toward improving food security. Results also show that a higher initial level of undernourishment and economic growth result in a faster response for improving food security.

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The paper reports on a collaborative effort between the Swiss Federal Nuclear Safety Inspectorate (ENSI) and their consultants Principia and Stangenberg. As part of the IMPACT III project, reduced scale impact tests of reinforced concrete structures were carried out. The simulation of test X3 is presented here and the numerical results are compared with those obtained in the test, carried out in August 2013. The general object is to improve the safety of nuclear facilities and, more specifically, to demonstrate the capabilities of current simulation techniques to reproduce the behaviour of a reinforced concrete structure impacted by a soft missile. The missile is a steel tube with a mass of 50 kg and travelling at 140 m/s. The target is a 250 mm thick, 2,1 m by 2,1 m reinforced concrete wall, held in a stiff supporting frame. The reinforcement includes both longitudinal and transverse rebars. Calculations were carried out before and after the test with Abaqus (Principia) and SOFiSTiK (Stangenberg). In the Abaqus simulation the concrete is modelled using solid elements and a damaged plasticity formulation, the rebars with embedded beam elements, and the missile with shell elements. In SOFiSTiK the target is modelled with non-linear, layered shell elements for the reinforcement on both sides; non-linear shear deformations of shell/plate elements are approximately included. The results generally indicate a good agreement between calculations and measurements.