New generation wireless communication systems should support the increasing demand for efficient utilization of the electromagnetic spectrum. The Cognitive Radio (CR) paradigm is envisioned as a new technique to realize this goal. Nowadays, Software Defined Radios (SDRs) are the foundations on which the CR will be achieved. In this thesis we implemented an SDR network testbed based on a GNU radio platform. The test network was used to evaluate the actual performance of two methods that attempt to contribute as constituents of a Radio Environment Map (REM). REMs are a new approach to provide situation awareness for CRs. The first technique under analysis was a colouring-based frequency allocation mechanism that optimizes the assignment of frequency channels in the 2.4 GHz band. Its effectiveness was demonstrated using several performance tests in different scenarios and conditions. This study also explores the viability of using our SDR testbed to execute real-time power measurements to estimate the dynamics of indoor radio propagation. This is a preliminary step to obtain complete radio environment awareness, and thus contribute towards realizing the REM and CR approaches. 

The number of distributed resources into electrical network systems is increasing and it is challenging the way these systems are designed and operated. For traditional power systems, transmission and distribution networks play a passive role in voltage control. When distributed generation is presented these levels of the electrical network can play an important role in voltage regulation. The mini CHP technology is an interesting option for this active role. In this study, a voltage control strategy using mini CHP units is proposed. For this purpose a dynamic model of a mini CHP system using experimental data is developed and is represented in Matlab/Simulink for simulation. An electrical network for performing these studies is built in DIgSILENT PowerFactory and the mini CHP system model is integrated into the electrical network. The proposed voltage control operation mode is compared with a heat lead operation mode for determining advantages and disadvantages of both operations. The voltage control operation is an interesting option for regulating voltage in the distribution network when distributed resources are introduced. Further studies and developments are required to find a compromise between voltage regulation and thermal demand matching.

En el campo de estudio de los Agentes Autónomos Inteligentes, uno de los retos más complejos de lograr es la simulación de los procesos cognitivos. Generalmente, la meta de integrar diversas micro-teorías en un solo modelo cognitivo que sea capaz de procesar ingentes cantidades de variables, las cuales cambian continuamente con una complejidad incremental, resulta ser una tarea intrincada cuyos frutos no siempre suelen reflejar las expectativas iniciales de sus diseñadores. En el área de la Cognición Artificial es posible distinguir tres grandes aproximaciones: la Cognitivista, basada en sistemas de representación simbólica y mecanismos de aprendizaje explícito; la Emergente, fundamentada en sistemas de representación sub-simbólica y procesos cognitivos de naturaleza implícita; y la Híbrida, que busca integrar lo mejor de cada aproximación. Esta última, a pesar de ser un enfoque conciliador que pretende compensar las debilidades y potenciar las fortalezas de cada aproximación, es un área de investigación muy reciente cuyos resultados son aún incipientes. En la presente tesis, se propone un modelo cognitivo híbrido y original, denominado Metáfora, cuyas aportaciones principales son: (1) la integración de teorías multi-disciplinares -- psicocognitivas, neurológicas, biológicas, de inteligencia artificial, etc. -- sobre la cognición; (2) un diseño arquitectónico basado en bloques de construcción cibernéticos, que adapta lo mejor de los modelos cognitivos más representativos -- diseño por capas, modular, multi-componente, descentralizado, y distribuido; (3) la fusión de los principios propuestos tanto por la aproximación cognitivista como por la aproximación emergente, y la definición de los mecanismos de integración y sincronización necesarios para comunicar estos dos niveles; y (4) un diseño innovador que articula tres niveles de auto-organización inspirados en principios de la biología evolutiva y del desarrollo: la epigénesis, la ontogénesis, y la filogénesis, a partir de los cuales emergen las diversas estructuras cognitivas de la arquitectura. En el nivel epigenético se define una capa cognitiva controlada por dos clases de máquinas autopoiéticas (i.e., los Sistemas Inmunes Artificiales y las Redes Neuronales Artificiales), cuya responsabilidad es crear las estructuras cognitivas de bajo nivel y dotar a la arquitectura con un grado significativo de plasticidad. En el nivel ontogenético, por un lado, se precisa un mecanismo atencional adaptativo el cual es capaz de orquestar los diversos comportamientos y procesos conscientes y subconscientes del agente, empleando para ello un modelo evolutivo de dispersión de energía de activación y, por otro, se define un mecanismo que evoluciona las estructuras cognitivas de orden superior. Por último, en el nivel filogenético, se propone un mecanismo basado en la ingeniería memética, encargado de co-evolucionar y trasmitir las estructuras cognitivas a través de la sociedad de agentes.

Our society is increasingly demanding situation-aware smarter software (SASS) systems, whose goals change over time and depend on context situations. A system with such properties must sense their dynamic environment and respond to changes quickly, accurately, and reliably, that is, to be context-aware and self-adaptive. The problem addressed in this dissertation is the dynamic management of context information to improve the relevance of SASS systems' context-aware capabilities with respect to changes in their requirements and execution environment. Therefore, this dissertation focuses on the investigation of dynamic context management and self-adaptivity to: (i) improve context-awareness and exploit context information to enhance quality of user experience in SASS systems, and (ii) improve the dynamic capabilities of self-adaptivity in SASS systems. Context-awareness and self-adaptivity pose significant challenges for the engineering of SASS systems. Regarding context-awareness, the first challenge addressed is the impossibility of fully specifying environmental entities and the corresponding monitoring requirements at design-time. The second challenge arises from the continuous evolution of monitoring requirements due to changes in the system caused by self-adaptation. As a result, context monitoring strategies must be modeled and managed in such a way that they support the addition and deletion of context types and monitoring conditions at runtime. Concerning self-adaptivity, the third challenge is to control the dynamicity of adaptation goals, adaptation mechanisms, and monitoring infrastructures, and the way they affect each other in the adaptation process. This is to preserve the effectiveness of context monitoring requirements and thus self-adaptation. The fourth challenge, related also to self-adaptivity concerns the assessment of adaptation mechanisms at runtime to prevent undesirable system states as a result of self-adaptation.

In the Healthcare field, Business Intelligence and Data Mining techniques have been proven efficient mainly in the fields of contagious diseases and hospital productivity, however their usage is today still very limited, specially in specific fields like chronic disease management. This paper presents a methodology to develop Data Mining and Business Intelligence based on remote chronic patient management databases. This document also introduces a technical methodology to build a conceptual Data Model for Data Mining based on HL7-v3, with the objective of analyzing patient behavior, detecting triggers for future patient crisis, predicting patient behavior and contribute to improve management plans, resource usage optimization and higher Returns on Investment. Distinciones: Graduado como mejor estudiante de la promoción.

The sum of small and big decisions made in all levels of companies determines its performance. Also, the quality of the decisions can be improved when there is information available to help decision makers in their task. All this has motivated the development of specific types of information systems aimed to provide the information necessary in the different levels of the company to support structured and semi-structured decision making. This research will be focused on a specific group of information systems to support decisions that make intensive use of historic data integrated from multiple sources; Data-driven Decision Support Systems (DDSS). On the other hand the features of the systems to support decisions together with tasks and techniques that are unique for these systems demanded the creation of specific development methodologies to perform the development process. In response to that demand, several proposals have been elaborated but there is no consensus in the field. Currently there is a debate around two development methodologies that are analysed on this paper. After the analysis of the proposed methodologies a case study organization with experience on the development of DDSS will be analysed. The research aims to understand and present the development process carried out in the organization to develop DDSS. In the analysis the influence of the existing methodologies and other sources, like traditional development methodologies and standardization is included. Finally a proposal to improve the development of DDSS in the case study organization is presented. The proposal is generated in the light of the existing methodologies and other particular proposals that deal with single tasks on the development process.

In this thesis two different studies are presented separately because each study has a different purpose even though the two studies are complementary. For the first study an available dataset for BCI is used. This dataset is consistent with the aim of the first study because it allows the implementation and development of the proposed technique for BCI based on imaginary limb movement with a small amount of electrodes. The technique I implemented trough this study is a reliable option to be used for a BCI-based on imaginary movements. In the second study a different dataset is used because the requirements for the technique to be implemented are different. Training and testing dataset are necessary to describe a practical computational technique that is applied for a single trial classification based on a Common Spatial Pattern and complemented with a linear discriminator. The training data is used to build a classifier and the testing data allows measuring the performance of the classifier implemented. After testing the classifier the good performance obtained makes this technique of great interest for any imaginary movement based-BCI.

Unnamed Aerial Vehicles (UAV) are known for their application in surveillance and tracking with on-board cameras. Videos from UAV usually suffer from jitter and high frequency unintended movements which makes necessary stabilize the footage. This is a Computer Vision problem, particularly difficult due to level of noise in acquisition and different types of scenarios which make hard to implement online stabilizer (on the fly). The present thesis explains in depth algorithms, methods and implementations of the OpenCV module videostab. We presented a version in C++ of videostab in context of video from UAV. Two main blocks constitute the current implementation: motion estimation and motion stabilization. In the former, the system robustly estimates global displacement in between every consecutive pair of frames. The latter can be used in two possible ways: Assuming that estimated motion contains intended UAV motion and high frequency vibrations or assuming that all estimated motion is undesirable. The first case is solved with a Gaussian filter to smooth motions and, in the second case, a filter called Zero Motion was implemented to give sensation of stillness. Results show that the implementation is robust and can work in different scenarios of UAV. Moreover, it is possible to run it in a general purpose computer with high speed performance. Online performance can be achieved using some function with graphic processing unit (GPU).

Los dos tomos que configuran esta obra ofrecen información y análisis especializados útiles para la investigación y la academia, para el trabajo de ingenieros civiles con fundamentos en el área de estructuras y con experiencia específica en labores de inspección, patología y rehabilitación de puentes.

Desde el descaro otorgado por una amplia e intensa experiencia en diseño y fabricación de componentes y equipos del sector aeroespacial, se ha intentado plasmar en este texto lo aprendido durante estos años. Se ha intentado hacer hincapié en las buenas prácticas a la hora de interpretar documentación técnica pero es importante aprender de los errores y, por lo tanto, también se han mostrado algunos de los errores más comunes encontrados durante estos años de trabajo. El texto, desde el mismo momento de su inicio, ha sufrido multitud de cambios en la estrategia comunicativa, pero no por ello ha...