Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

Handrub Consumption Mirrors Hand Hygiene Compliance

We assessed handrub consumption as a surrogate marker for hand hygiene compliance from 2007 to 2014. Handrub consumption varied substantially between departments but correlated in a mixed effects regression model with the number of patient-days and the observed hand hygiene compliance. Handrub consumption may supplement traditional hand hygiene observations. Infect. Control Hosp. Epidemiol. 2016;1-4.

Associations between vaccination and childhood cancers in Texas counties

Background. In Dr. Mel Greaves "delayed-infection hypothesis," postponed exposure to common infections increases the likelihood of childhood cancer. Hygienic advancements in developed countries have reduced children's exposure to pathogens and children encounter common infectious agents at an older age with an immune system unable to deal with the foreign antigens. Vaccinations may be considered to be simulated infections as they prompt an antigenic response by the immune system. Vaccinations may regulate the risk of childhood cancer by modulating the immune system. The aim of the study was to determine if children born in Texas counties with higher levels of vaccination coverage were at a reduced risk for childhood cancer.^ Methods. We conducted a case-control study to examine the risk of childhood cancers, specifically leukemia, brain tumors, and non-Hodgkin lymphoma, in relation to vaccination rates in Texas counties. We utilized a multilevel mixed-effects regression model of the individual data from the Texas Cancer Registry (TCR) with group-level exposure data (i.e., the county- and public health region-level vaccination rates).^ Results. Utilizing county-level vaccination rates and controlling for child's sex, birth year, ethnicity, birth weight, and mother's age at child's birth the hepatitis B vaccine revealed negative associations with developing all cancer types (OR = 0.81, 95% CI: 0.67–0.98) and acute lymphoblastic leukemia (ALL) (OR = 0.63, 95% CI: 0.46–0.88). The decreased risk for ALL was also evident for the inactivated polio vaccine (IPV) (OR = 0.67, 95% CI: 0.49–0.92) and 4-3-1-3-3 vaccination series (OR = 0.62, 95% CI: 0.44-0.87). Using public health region vaccine coverage levels, an inverse association between the Haemophilus influenzae type b (Hib) vaccine and ALL (OR: 0.58; 95% CI: 0.42–0.82) was present. Conversely, the measles, mumps, and rubella (MMR) vaccine resulted in a positive association with developing non-Hodgkin lymphoma (OR = 2.81, 95% CI: 1.27–6.22). ^

Whence a healthy mind: Correlation of physical fitness and academic performance among schoolchildren

Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^

Measured daily precipitation sums over Central Sulawesi for the period 1981-1999

Data compiled within the IMPENSO project. The Impact of ENSO on Sustainable Water Management and the Decision-Making Community at a Rainforest Margin in Indonesia (IMPENSO), http://www.gwdg.de/~impenso, was a German-Indonesian research project (2003-2007) that has studied the impact of ENSO (El Nino-Southern Oscillation) on the water resources and the agricultural production in the PALU RIVER watershed in Central Sulawesi. ENSO is a climate variability that causes serious droughts in Indonesia and other countries of South-East Asia. The last ENSO event occurred in 1997. As in other regions, many farmers in Central Sulawesi suffered from reduced crop yields and lost their livestock. A better prediction of ENSO and the development of coping strategies would help local communities mitigate the impact of ENSO on rural livelihoods and food security. The IMPENSO project deals with the impact of the climate variability ENSO (El Niño Southern Oscillation) on water resource management and the local communities in the Palu River watershed of Central Sulawesi, Indonesia. The project consists of three interrelated sub-projects, which study the local and regional manifestation of ENSO using the Regional Climate Models REMO and GESIMA (Sub-project A), quantify the impact of ENSO on the availability of water for agriculture and other uses, using the distributed hydrological model WaSiM-ETH (Sub-project B), and analyze the socio-economic impact and the policy implications of ENSO on the basis of a production function analysis, a household vulnerability analysis, and a linear programming model (Sub-project C). The models used in the three sub-projects will be integrated to simulate joint scenarios that are defined in collaboration with local stakeholders and are relevant for the design of coping strategies.

Enhanced Failure Detection Mechanism in MapReduce

The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general.

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

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

Optimización de algoritmos para procesado de imágenes con GPUs

El objetivo de este proyecto es evaluar la mejora de rendimiento que aporta la paralelización de algoritmos de procesamiento de imágenes, para su ejecución en una tarjeta gráfica. Para ello, una vez seleccionados los algoritmos a estudio, fueron desarrollados en lenguaje C++ bajo el paradigma secuencial. A continuación, tomando como base estas implementaciones, se paralelizaron siguiendo las directivas de la tecnología CUDA (Compute Unified Device Architecture) desarrollada por NVIDIA. Posteriormente, se desarrolló un interfaz gráfico de usuario en Visual C#, para una utilización más sencilla de la herramienta. Por último, se midió el rendimiento de cada uno de los algoritmos, en términos de tiempo de ejecución paralela y speedup, mediante el procesamiento de una serie de imágenes de distintos tamaños.---ABSTRACT---The aim of this Project is to evaluate the performance improvement provided by the parallelization of image processing algorithms, which will be executed on a graphics processing unit. In order to do this, once the algorithms to study were selected, each of them was developed in C++ under sequential paradigm. Then, based on these implementations, these algorithms were implemented using the compute unified device architecture (CUDA) programming model provided by NVIDIA. After that, a graphical user interface (GUI) was developed to increase application’s usability. Finally, performance of each algorithm was measured in terms of parallel execution time and speedup by processing a set of images of different sizes.

Contributions to the Resilience Management in the Internet of Things

El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.

Optimizing the reliability and resource efficiency of MapReduce-based systems

Debido al gran incremento de datos digitales que ha tenido lugar en los últimos años, ha surgido un nuevo paradigma de computación paralela para el procesamiento eficiente de grandes volúmenes de datos. Muchos de los sistemas basados en este paradigma, también llamados sistemas de computación intensiva de datos, siguen el modelo de programación de Google MapReduce. La principal ventaja de los sistemas MapReduce es que se basan en la idea de enviar la computación donde residen los datos, tratando de proporcionar escalabilidad y eficiencia. En escenarios libres de fallo, estos sistemas generalmente logran buenos resultados. Sin embargo, la mayoría de escenarios donde se utilizan, se caracterizan por la existencia de fallos. Por tanto, estas plataformas suelen incorporar características de tolerancia a fallos y fiabilidad. Por otro lado, es reconocido que las mejoras en confiabilidad vienen asociadas a costes adicionales en recursos. Esto es razonable y los proveedores que ofrecen este tipo de infraestructuras son conscientes de ello. No obstante, no todos los enfoques proporcionan la misma solución de compromiso entre las capacidades de tolerancia a fallo (o de manera general, las capacidades de fiabilidad) y su coste. Esta tesis ha tratado la problemática de la coexistencia entre fiabilidad y eficiencia de los recursos en los sistemas basados en el paradigma MapReduce, a través de metodologías que introducen el mínimo coste, garantizando un nivel adecuado de fiabilidad. Para lograr esto, se ha propuesto: (i) la formalización de una abstracción de detección de fallos; (ii) una solución alternativa a los puntos únicos de fallo de estas plataformas, y, finalmente, (iii) un nuevo sistema de asignación de recursos basado en retroalimentación a nivel de contenedores. Estas contribuciones genéricas han sido evaluadas tomando como referencia la arquitectura Hadoop YARN, que, hoy en día, es la plataforma de referencia en la comunidad de los sistemas de computación intensiva de datos. En la tesis se demuestra cómo todas las contribuciones de la misma superan a Hadoop YARN tanto en fiabilidad como en eficiencia de los recursos utilizados. ABSTRACT Due to the increase of huge data volumes, a new parallel computing paradigm to process big data in an efficient way has arisen. Many of these systems, called dataintensive computing systems, follow the Google MapReduce programming model. The main advantage of these systems is based on the idea of sending the computation where the data resides, trying to provide scalability and efficiency. In failure-free scenarios, these frameworks usually achieve good results. However, these ones are not realistic scenarios. Consequently, these frameworks exhibit some fault tolerance and dependability techniques as built-in features. On the other hand, dependability improvements are known to imply additional resource costs. This is reasonable and providers offering these infrastructures are aware of this. Nevertheless, not all the approaches provide the same tradeoff between fault tolerant capabilities (or more generally, reliability capabilities) and cost. In this thesis, we have addressed the coexistence between reliability and resource efficiency in MapReduce-based systems, looking for methodologies that introduce the minimal cost and guarantee an appropriate level of reliability. In order to achieve this, we have proposed: (i) a formalization of a failure detector abstraction; (ii) an alternative solution to single points of failure of these frameworks, and finally (iii) a novel feedback-based resource allocation system at the container level. Finally, our generic contributions have been instantiated for the Hadoop YARN architecture, which is the state-of-the-art framework in the data-intensive computing systems community nowadays. The thesis demonstrates how all our approaches outperform Hadoop YARN in terms of reliability and resource efficiency.

New methods for the synthesis of radiation patterns of coupled antenna arrays = Nuevos métodos de síntesis de diagramas de radiación de agrupaciones de antenas acopladas

El principal objetivo de esta tesis es el desarrollo de métodos de síntesis de diagramas de radiación de agrupaciones de antenas, en donde se realiza una caracterización electromagnética rigurosa de los elementos radiantes y de los acoplos mutuos existentes. Esta caracterización no se realiza habitualmente en la gran mayoría de métodos de síntesis encontrados en la literatura, debido fundamentalmente a dos razones. Por un lado, se considera que el diagrama de radiación de un array de antenas se puede aproximar con el factor de array que únicamente tiene en cuenta la posición de los elementos y las excitaciones aplicadas a los mismos. Sin embargo, como se mostrará en esta tesis, en múltiples ocasiones un riguroso análisis de los elementos radiantes y del acoplo mutuo entre ellos es importante ya que los resultados obtenidos pueden ser notablemente diferentes. Por otro lado, no es sencillo combinar un método de análisis electromagnético con un proceso de síntesis de diagramas de radiación. Los métodos de análisis de agrupaciones de antenas suelen ser costosos computacionalmente, ya que son estructuras grandes en términos de longitudes de onda. Generalmente, un diseño de un problema electromagnético suele comprender varios análisis de la estructura, dependiendo de las variaciones de las características, lo que hace este proceso muy costoso. Dos métodos se utilizan en esta tesis para el análisis de los arrays acoplados. Ambos están basados en el método de los elementos finitos, la descomposición de dominio y el análisis modal para analizar la estructura radiante y han sido desarrollados en el grupo de investigación donde se engloba esta tesis. El primero de ellos es una técnica de análisis de arrays finitos basado en la aproximación de array infinito. Su uso es indicado para arrays planos de grandes dimensiones con elementos equiespaciados. El segundo caracteriza el array y el acoplo mutuo entre elementos a partir de una expansión en modos esféricos del campo radiado por cada uno de los elementos. Este método calcula los acoplos entre los diferentes elementos del array usando las propiedades de traslación y rotación de los modos esféricos. Es capaz de analizar agrupaciones de elementos distribuidos de forma arbitraria. Ambas técnicas utilizan una formulación matricial que caracteriza de forma rigurosa el campo radiado por el array. Esto las hace muy apropiadas para su posterior uso en una herramienta de diseño, como los métodos de síntesis desarrollados en esta tesis. Los resultados obtenidos por estas técnicas de síntesis, que incluyen métodos rigurosos de análisis, son consecuentemente más precisos. La síntesis de arrays consiste en modificar uno o varios parámetros de las agrupaciones de antenas buscando unas determinadas especificaciones de las características de radiación. Los parámetros utilizados como variables de optimización pueden ser varios. Los más utilizados son las excitaciones aplicadas a los elementos, pero también es posible modificar otros parámetros de diseño como son las posiciones de los elementos o las rotaciones de estos. Los objetivos de las síntesis pueden ser dirigir el haz o haces en una determinada dirección o conformar el haz con formas arbitrarias. Además, es posible minimizar el nivel de los lóbulos secundarios o del rizado en las regiones deseadas, imponer nulos que evitan posibles interferencias o reducir el nivel de la componente contrapolar. El método para el análisis de arrays finitos basado en la aproximación de array infinito considera un array finito como un array infinito con un número finito de elementos excitados. Los elementos no excitados están físicamente presentes y pueden presentar tres diferentes terminaciones, corto-circuito, circuito abierto y adaptados. Cada una de estas terminaciones simulará mejor el entorno real en el que el array se encuentre. Este método de análisis se integra en la tesis con dos métodos diferentes de síntesis de diagramas de radiación. En el primero de ellos se presenta un método basado en programación lineal en donde es posible dirigir el haz o haces, en la dirección deseada, además de ejercer un control sobre los lóbulos secundarios o imponer nulos. Este método es muy eficiente y obtiene soluciones óptimas. El mismo método de análisis es también aplicado a un método de conformación de haz, en donde un problema originalmente no convexo (y de difícil solución) es transformado en un problema convexo imponiendo restricciones de simetría, resolviendo de este modo eficientemente un problema complejo. Con este método es posible diseñar diagramas de radiación con haces de forma arbitraria, ejerciendo un control en el rizado del lóbulo principal, así como en el nivel de los lóbulos secundarios. El método de análisis de arrays basado en la expansión en modos esféricos se integra en la tesis con tres técnicas de síntesis de diagramas de radiación. Se propone inicialmente una síntesis de conformación del haz basado en el método de la recuperación de fase resuelta de forma iterativa mediante métodos convexos, en donde relajando las restricciones del problema original se consiguen unas soluciones cercanas a las óptimas de manera eficiente. Dos métodos de síntesis se han propuesto, donde las variables de optimización son las posiciones y las rotaciones de los elementos respectivamente. Se define una función de coste basada en la intensidad de radiación, la cual es minimizada de forma iterativa con el método del gradiente. Ambos métodos reducen el nivel de los lóbulos secundarios minimizando una función de coste. El gradiente de la función de coste es obtenido en términos de la variable de optimización en cada método. Esta función de coste está formada por la expresión rigurosa de la intensidad de radiación y por una función de peso definida por el usuario para imponer prioridades sobre las diferentes regiones de radiación, si así se desea. Por último, se presenta un método en el cual, mediante técnicas de programación entera, se buscan las fases discretas que generan un diagrama de radiación lo más cercano posible al deseado. Con este método se obtienen diseños que minimizan el coste de fabricación. En cada uno de las diferentes técnicas propuestas en la tesis, se presentan resultados con elementos reales que muestran las capacidades y posibilidades que los métodos ofrecen. Se comparan los resultados con otros métodos disponibles en la literatura. Se muestra la importancia de tener en cuenta los diagramas de los elementos reales y los acoplos mutuos en el proceso de síntesis y se comparan los resultados obtenidos con herramientas de software comerciales. ABSTRACT The main objective of this thesis is the development of optimization methods for the radiation pattern synthesis of array antennas in which a rigorous electromagnetic characterization of the radiators and the mutual coupling between them is performed. The electromagnetic characterization is usually overlooked in most of the available synthesis methods in the literature, this is mainly due to two reasons. On the one hand, it is argued that the radiation pattern of an array is mainly influenced by the array factor and that the mutual coupling plays a minor role. As it is shown in this thesis, the mutual coupling and the rigorous characterization of the array antenna influences significantly in the array performance and its computation leads to differences in the results obtained. On the other hand, it is difficult to introduce an analysis procedure into a synthesis technique. The analysis of array antennas is generally expensive computationally as the structure to analyze is large in terms of wavelengths. A synthesis method requires to carry out a large number of analysis, this makes the synthesis problem very expensive computationally or intractable in some cases. Two methods have been used in this thesis for the analysis of coupled antenna arrays, both of them have been developed in the research group in which this thesis is involved. They are based on the finite element method (FEM), the domain decomposition and the modal analysis. The first one obtains a finite array characterization with the results obtained from the infinite array approach. It is specially indicated for the analysis of large arrays with equispaced elements. The second one characterizes the array elements and the mutual coupling between them with a spherical wave expansion of the radiated field by each element. The mutual coupling is computed using the properties of translation and rotation of spherical waves. This method is able to analyze arrays with elements placed on an arbitrary distribution. Both techniques provide a matrix formulation that makes them very suitable for being integrated in synthesis techniques, the results obtained from these synthesis methods will be very accurate. The array synthesis stands for the modification of one or several array parameters looking for some desired specifications of the radiation pattern. The array parameters used as optimization variables are usually the excitation weights applied to the array elements, but some other array characteristics can be used as well, such as the array elements positions or rotations. The desired specifications may be to steer the beam towards any specific direction or to generate shaped beams with arbitrary geometry. Further characteristics can be handled as well, such as minimize the side lobe level in some other radiating regions, to minimize the ripple of the shaped beam, to take control over the cross-polar component or to impose nulls on the radiation pattern to avoid possible interferences from specific directions. The analysis method based on the infinite array approach considers an infinite array with a finite number of excited elements. The infinite non-excited elements are physically present and may have three different terminations, short-circuit, open circuit and match terminated. Each of this terminations is a better simulation for the real environment of the array. This method is used in this thesis for the development of two synthesis methods. In the first one, a multi-objective radiation pattern synthesis is presented, in which it is possible to steer the beam or beams in desired directions, minimizing the side lobe level and with the possibility of imposing nulls in the radiation pattern. This method is very efficient and obtains optimal solutions as it is based on convex programming. The same analysis method is used in a shaped beam technique in which an originally non-convex problem is transformed into a convex one applying symmetry restrictions, thus solving a complex problem in an efficient way. This method allows the synthesis of shaped beam radiation patterns controlling the ripple in the mainlobe and the side lobe level. The analysis method based on the spherical wave expansion is applied for different synthesis techniques of the radiation pattern of coupled arrays. A shaped beam synthesis is presented, in which a convex formulation is proposed based on the phase retrieval method. In this technique, an originally non-convex problem is solved using a relaxation and solving a convex problems iteratively. Two methods are proposed based on the gradient method. A cost function is defined involving the radiation intensity of the coupled array and a weighting function that provides more degrees of freedom to the designer. The gradient of the cost function is computed with respect to the positions in one of them and the rotations of the elements in the second one. The elements are moved or rotated iteratively following the results of the gradient. A highly non-convex problem is solved very efficiently, obtaining very good results that are dependent on the starting point. Finally, an optimization method is presented where discrete digital phases are synthesized providing a radiation pattern as close as possible to the desired one. The problem is solved using linear integer programming procedures obtaining array designs that greatly reduce the fabrication costs. Results are provided for every method showing the capabilities that the above mentioned methods offer. The results obtained are compared with available methods in the literature. The importance of introducing a rigorous analysis into the synthesis method is emphasized and the results obtained are compared with a commercial software, showing good agreement.

Optimization of water procurement decisions in an irrigation district: the role of option contracts

Water supply instability is one of the main risks faced by irrigation districts and farmers. Water procurement decision optimisation is essential in order to increase supply reliability and reduce costs. Water markets, such as spot purchases or water supply option contracts, can make this decision process more flexible. We analyse the potential interest in an option contract for an irrigation district that has access to several water sources. We apply a stochastic recursive mathematical programming model to simulate the water procurement decisions of an irrigation district?s board operating in a context of water supply uncertainty in south-eastern Spain. We analyse what role different option contracts could play in securing its water supply. Results suggest that the irrigation district would be willing to accept the proposed option contract in most cases subject to realistic values of the option contract financial terms. Of nine different water sources, desalination and the option contract are the main substitutes, where the use of either depends on the contract parameters. The contract premium and optioned volume are the variables that have a greater impact on the irrigation district?s decisions. Key words: Segura Basin, stochastic recursive programming, water markets, water supply option contract, water supply risk.

Analysis of linear trade models and relation to scale economies

We discuss linear Ricardo models with a range of parameters. We show that the exact boundary of the region of equilibria of these models is obtained by solving a simple integer programming problem. We show that there is also an exact correspondence between many of the equilibria resulting from families of linear models and the multiple equilibria of economies of scale models.

Impactos de regulações ambientais sobre o transporte de cargas no Brasil: uma análise para o transporte de soja

O aumento da concentração de gases de efeito estufa na atmosfera levou a uma preocupação de como se reduzir as emissões destes gases. Desta preocupação surgiram instrumentos de regulação a fim de reduzir ou controlar os níveis de poluição. Dentro deste contexto, esta pesquisa analisou o setor de transportes de cargas, com ênfase no transporte de soja. No Brasil, o setor de transportes é um dos principais responsáveis pelas emissões de gases de efeito estufa provenientes da queima de combustíveis fósseis. No setor de transportes, as emissões diferem entre os modais, sendo que as ferrovias e hidrovias poluem menos que as rodovias. Desta forma, simulou-se por meio de um modelo de programação linear se a adoção de medidas regulatórias sobre as emissões de CO2 traria uma alteração no uso das ferrovias e hidrovias. Uma das constatações, ao se utilizar o modelo de Minimização de Fluxo de Custo Mínimo para o transporte de soja em 2013, foi que a capacidade de embarque nos terminais ferroviários e hidroviários desempenha um papel fundamental na redução das emissões de CO2. Se não houver capacidade suficiente, a adoção de uma taxa pode não provocar a redução das emissões. No caso do sistema de compra e crédito de carbono, seria necessária a compra de créditos de carbono, numa situação em que a capacidade de embarque nos terminais intermodais seja limitada. Verificou-se, ainda, que melhorias na infraestrutura podem desempenhar um papel mitigador das emissões. Um aumento da capacidade dos terminais ferroviários e hidroviários existentes, bem como o aumento da capacidade dos portos, pode provocar a redução das emissões de CO2. Se os projetos de expansão das ferrovias e hidrovias desenvolvidos por órgãos governamentais saírem do papel, pode-se chegar a uma redução de pouco mais de 50% das emissões de CO2. Consideraram-se ainda quais seriam os efeitos do aumento do uso de biodiesel como combustível e percebeu-se que seria possível obter reduções tanto das emissões quanto do custo de transporte. Efeitos semelhantes foram encontrados quando se simulou um aumento da eficiência energética. Por fim, percebeu-se nesta pesquisa que a adoção de uma taxa não traria tantos benefícios, econômicos e ambientais, quanto a melhoria da infraestrutura logística do país.

Youth Sport Programs: An Avenue to Foster Positive Youth Development

Concern about the growth in adolescent problem behaviours (e.g. delinquency, drug use) has led to increased interest in positive youth development, and a surge in funding for ‘after school programs.’ We evaluate the potential of youth sport programs to foster positive development, while decreasing the risk of problem behaviours. Literature on the positive and negative outcomes of youth sport is presented. We propose that youth sport programs actively work to assure positive outcomes through developmentally appropriate designs and supportive child–adult (parent/coach) relationships. We also highlight the importance of sport programs built on developmental assets (Benson, 1997 ) and appropriate setting features (National Research Council and Institute of Medicine, 2002 ) in bringing about the five ‘C’s of positive development (competence, confidence, character, connections, and compassion/caring: Lerner et al., 2000 ). An applied sport-programming model, which highlights the important roles of policy-makers, sport organizations, coaches and parents in fostering positive youth development is presented as a starting point for further applied and theoretical research.