Desulfurization of pyrolysis fuel produced from waste lube oils, tyres and plastics

Sulphur compounds remaining in petroleum fractions from topping, hydroskimming or deep conversion processes are a growing concern for oil refiners since in the lapse of a few years the sulphur specification for motor fuels has dropped from 500 mg/kg to 10 mg/kg in most European countries. This increasingly stringent regulation has forced refineries to greatly improve their hydrodesulfurization units, increasing the desulfurization rates and thus consuming huge amounts of hydrogen.

A system of systems engineering approach to design new smarter and energy efficient products

The concept of smartness of energy efficient products and systems from a business perspective has been investigated by several authors. The problem of understanding, designing, engineering and governing these technologies requires new concepts. The emergence of these modern technologies causes a myriad of interconnected systems, which are working together to satisfy the necessities of modern life. The problem of understanding, designing, engineering, and governing these technologies requires new concepts. Development of System of System Engineering (SoSE) is an attempt by the systems engineering and science community to fulfill this requirement.

Biomass Gasification in a Fluidized Bed Reactor: Effect of Temperature, Stoichiometric Ratio and Biomass Type

This paper investigates the gasification of two biomass types (pine wood and olive stones) in a laboratory scale bubbling fluidized bed reactor, in order to evaluate comparatively their potential in the production of syngas.

Pulmonary Artery-Vein Segmentation in Real and Synthetic CT Images = Segmentación Arteria-Vena Pulmonares en Imágenes de CT Reales y Sintéticas

La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.

Extracting knowledge through friendsourcing: application to new financial services

Personalization has become a key factor for the success of new ICT services. However, the personal information required is not always available in a single site, but scattered in heterogeneous sources, and extracting knowledge from raw information is not an easy job. As a result, many organizations struggle to obtain knowledge on their users useful enough for their business purposes. This paper introduces a comprehensive personal data framework that opens the knowledge extraction process up to collaboration by the involvement of new actors, while enabling users to monitor and control it. The contributions have been validated in a financial services scenario where socioeconomic knowledge on some users is generated by tapping into their social network and used to assists them in raising money from their friends.

Trust-ware: A Methodology to Analyze, Design, and Secure Trust and Reputation Systems

Entendemos por inteligencia colectiva una forma de inteligencia que surge de la colaboración y la participación de varios individuos o, siendo más estrictos, varias entidades. En base a esta sencilla definición podemos observar que este concepto es campo de estudio de las más diversas disciplinas como pueden ser la sociología, las tecnologías de la información o la biología, atendiendo cada una de ellas a un tipo de entidades diferentes: seres humanos, elementos de computación o animales. Como elemento común podríamos indicar que la inteligencia colectiva ha tenido como objetivo el ser capaz de fomentar una inteligencia de grupo que supere a la inteligencia individual de las entidades que lo forman a través de mecanismos de coordinación, cooperación, competencia, integración, diferenciación, etc. Sin embargo, aunque históricamente la inteligencia colectiva se ha podido desarrollar de forma paralela e independiente en las distintas disciplinas que la tratan, en la actualidad, los avances en las tecnologías de la información han provocado que esto ya no sea suficiente. Hoy en día seres humanos y máquinas a través de todo tipo de redes de comunicación e interfaces, conviven en un entorno en el que la inteligencia colectiva ha cobrado una nueva dimensión: ya no sólo puede intentar obtener un comportamiento superior al de sus entidades constituyentes sino que ahora, además, estas inteligencias individuales son completamente diferentes unas de otras y aparece por lo tanto el doble reto de ser capaces de gestionar esta gran heterogeneidad y al mismo tiempo ser capaces de obtener comportamientos aún más inteligentes gracias a las sinergias que los distintos tipos de inteligencias pueden generar. Dentro de las áreas de trabajo de la inteligencia colectiva existen varios campos abiertos en los que siempre se intenta obtener unas prestaciones superiores a las de los individuos. Por ejemplo: consciencia colectiva, memoria colectiva o sabiduría colectiva. Entre todos estos campos nosotros nos centraremos en uno que tiene presencia en la práctica totalidad de posibles comportamientos inteligentes: la toma de decisiones. El campo de estudio de la toma de decisiones es realmente amplio y dentro del mismo la evolución ha sido completamente paralela a la que citábamos anteriormente en referencia a la inteligencia colectiva. En primer lugar se centró en el individuo como entidad decisoria para posteriormente desarrollarse desde un punto de vista social, institucional, etc. La primera fase dentro del estudio de la toma de decisiones se basó en la utilización de paradigmas muy sencillos: análisis de ventajas e inconvenientes, priorización basada en la maximización de algún parámetro del resultado, capacidad para satisfacer los requisitos de forma mínima por parte de las alternativas, consultas a expertos o entidades autorizadas o incluso el azar. Sin embargo, al igual que el paso del estudio del individuo al grupo supone una nueva dimensión dentro la inteligencia colectiva la toma de decisiones colectiva supone un nuevo reto en todas las disciplinas relacionadas. Además, dentro de la decisión colectiva aparecen dos nuevos frentes: los sistemas de decisión centralizados y descentralizados. En el presente proyecto de tesis nos centraremos en este segundo, que es el que supone una mayor atractivo tanto por las posibilidades de generar nuevo conocimiento y trabajar con problemas abiertos actualmente así como en lo que respecta a la aplicabilidad de los resultados que puedan obtenerse. Ya por último, dentro del campo de los sistemas de decisión descentralizados existen varios mecanismos fundamentales que dan lugar a distintas aproximaciones a la problemática propia de este campo. Por ejemplo el liderazgo, la imitación, la prescripción o el miedo. Nosotros nos centraremos en uno de los más multidisciplinares y con mayor capacidad de aplicación en todo tipo de disciplinas y que, históricamente, ha demostrado que puede dar lugar a prestaciones muy superiores a otros tipos de mecanismos de decisión descentralizados: la confianza y la reputación. Resumidamente podríamos indicar que confianza es la creencia por parte de una entidad que otra va a realizar una determinada actividad de una forma concreta. En principio es algo subjetivo, ya que la confianza de dos entidades diferentes sobre una tercera no tiene porqué ser la misma. Por otro lado, la reputación es la idea colectiva (o evaluación social) que distintas entidades de un sistema tiene sobre otra entidad del mismo en lo que respecta a un determinado criterio. Es por tanto una información de carácter colectivo pero única dentro de un sistema, no asociada a cada una de las entidades del sistema sino por igual a todas ellas. En estas dos sencillas definiciones se basan la inmensa mayoría de sistemas colectivos. De hecho muchas disertaciones indican que ningún tipo de organización podría ser viable de no ser por la existencia y la utilización de los conceptos de confianza y reputación. A partir de ahora, a todo sistema que utilice de una u otra forma estos conceptos lo denominaremos como sistema de confianza y reputación (o TRS, Trust and Reputation System). Sin embargo, aunque los TRS son uno de los aspectos de nuestras vidas más cotidianos y con un mayor campo de aplicación, el conocimiento que existe actualmente sobre ellos no podría ser más disperso. Existen un gran número de trabajos científicos en todo tipo de áreas de conocimiento: filosofía, psicología, sociología, economía, política, tecnologías de la información, etc. Pero el principal problema es que no existe una visión completa de la confianza y reputación en su sentido más amplio. Cada disciplina focaliza sus estudios en unos aspectos u otros dentro de los TRS, pero ninguna de ellas trata de explotar el conocimiento generado en el resto para mejorar sus prestaciones en su campo de aplicación concreto. Aspectos muy detallados en algunas áreas de conocimiento son completamente obviados por otras, o incluso aspectos tratados por distintas disciplinas, al ser estudiados desde distintos puntos de vista arrojan resultados complementarios que, sin embargo, no son aprovechados fuera de dichas áreas de conocimiento. Esto nos lleva a una dispersión de conocimiento muy elevada y a una falta de reutilización de metodologías, políticas de actuación y técnicas de una disciplina a otra. Debido su vital importancia, esta alta dispersión de conocimiento se trata de uno de los principales problemas que se pretenden resolver con el presente trabajo de tesis. Por otro lado, cuando se trabaja con TRS, todos los aspectos relacionados con la seguridad están muy presentes ya que muy este es un tema vital dentro del campo de la toma de decisiones. Además también es habitual que los TRS se utilicen para desempeñar responsabilidades que aportan algún tipo de funcionalidad relacionada con el mundo de la seguridad. Por último no podemos olvidar que el acto de confiar está indefectiblemente unido al de delegar una determinada responsabilidad, y que al tratar estos conceptos siempre aparece la idea de riesgo, riesgo de que las expectativas generadas por el acto de la delegación no se cumplan o se cumplan de forma diferente. Podemos ver por lo tanto que cualquier sistema que utiliza la confianza para mejorar o posibilitar su funcionamiento, por su propia naturaleza, es especialmente vulnerable si las premisas en las que se basa son atacadas. En este sentido podemos comprobar (tal y como analizaremos en más detalle a lo largo del presente documento) que las aproximaciones que realizan las distintas disciplinas que tratan la violación de los sistemas de confianza es de lo más variado. únicamente dentro del área de las tecnologías de la información se ha intentado utilizar alguno de los enfoques de otras disciplinas de cara a afrontar problemas relacionados con la seguridad de TRS. Sin embargo se trata de una aproximación incompleta y, normalmente, realizada para cumplir requisitos de aplicaciones concretas y no con la idea de afianzar una base de conocimiento más general y reutilizable en otros entornos. Con todo esto en cuenta, podemos resumir contribuciones del presente trabajo de tesis en las siguientes. • La realización de un completo análisis del estado del arte dentro del mundo de la confianza y la reputación que nos permite comparar las ventajas e inconvenientes de las diferentes aproximación que se realizan a estos conceptos en distintas áreas de conocimiento. • La definición de una arquitectura de referencia para TRS que contempla todas las entidades y procesos que intervienen en este tipo de sistemas. • La definición de un marco de referencia para analizar la seguridad de TRS. Esto implica tanto identificar los principales activos de un TRS en lo que respecta a la seguridad, así como el crear una tipología de posibles ataques y contramedidas en base a dichos activos. • La propuesta de una metodología para el análisis, el diseño, el aseguramiento y el despliegue de un TRS en entornos reales. Adicionalmente se exponen los principales tipos de aplicaciones que pueden obtenerse de los TRS y los medios para maximizar sus prestaciones en cada una de ellas. • La generación de un software que permite simular cualquier tipo de TRS en base a la arquitectura propuesta previamente. Esto permite evaluar las prestaciones de un TRS bajo una determinada configuración en un entorno controlado previamente a su despliegue en un entorno real. Igualmente es de gran utilidad para evaluar la resistencia a distintos tipos de ataques o mal-funcionamientos del sistema. Además de las contribuciones realizadas directamente en el campo de los TRS, hemos realizado aportaciones originales a distintas áreas de conocimiento gracias a la aplicación de las metodologías de análisis y diseño citadas con anterioridad. • Detección de anomalías térmicas en Data Centers. Hemos implementado con éxito un sistema de deteción de anomalías térmicas basado en un TRS. Comparamos la detección de prestaciones de algoritmos de tipo Self-Organized Maps (SOM) y Growing Neural Gas (GNG). Mostramos como SOM ofrece mejores resultados para anomalías en los sistemas de refrigeración de la sala mientras que GNG es una opción más adecuada debido a sus tasas de detección y aislamiento para casos de anomalías provocadas por una carga de trabajo excesiva. • Mejora de las prestaciones de recolección de un sistema basado en swarm computing y odometría social. Gracias a la implementación de un TRS conseguimos mejorar las capacidades de coordinación de una red de robots autónomos distribuidos. La principal contribución reside en el análisis y la validación de las mejoras increméntales que pueden conseguirse con la utilización apropiada de la información existente en el sistema y que puede ser relevante desde el punto de vista de un TRS, y con la implementación de algoritmos de cálculo de confianza basados en dicha información. • Mejora de la seguridad de Wireless Mesh Networks contra ataques contra la integridad, la confidencialidad o la disponibilidad de los datos y / o comunicaciones soportadas por dichas redes. • Mejora de la seguridad de Wireless Sensor Networks contra ataques avanzamos, como insider attacks, ataques desconocidos, etc. Gracias a las metodologías presentadas implementamos contramedidas contra este tipo de ataques en entornos complejos. En base a los experimentos realizados, hemos demostrado que nuestra aproximación es capaz de detectar y confinar varios tipos de ataques que afectan a los protocoles esenciales de la red. La propuesta ofrece unas velocidades de detección muy altas así como demuestra que la inclusión de estos mecanismos de actuación temprana incrementa significativamente el esfuerzo que un atacante tiene que introducir para comprometer la red. Finalmente podríamos concluir que el presente trabajo de tesis supone la generación de un conocimiento útil y aplicable a entornos reales, que nos permite la maximización de las prestaciones resultantes de la utilización de TRS en cualquier tipo de campo de aplicación. De esta forma cubrimos la principal carencia existente actualmente en este campo, que es la falta de una base de conocimiento común y agregada y la inexistencia de una metodología para el desarrollo de TRS que nos permita analizar, diseñar, asegurar y desplegar TRS de una forma sistemática y no artesanal y ad-hoc como se hace en la actualidad. ABSTRACT By collective intelligence we understand a form of intelligence that emerges from the collaboration and competition of many individuals, or strictly speaking, many entities. Based on this simple definition, we can see how this concept is the field of study of a wide range of disciplines, such as sociology, information science or biology, each of them focused in different kinds of entities: human beings, computational resources, or animals. As a common factor, we can point that collective intelligence has always had the goal of being able of promoting a group intelligence that overcomes the individual intelligence of the basic entities that constitute it. This can be accomplished through different mechanisms such as coordination, cooperation, competence, integration, differentiation, etc. Collective intelligence has historically been developed in a parallel and independent way among the different disciplines that deal with it. However, this is not enough anymore due to the advances in information technologies. Nowadays, human beings and machines coexist in environments where collective intelligence has taken a new dimension: we yet have to achieve a better collective behavior than the individual one, but now we also have to deal with completely different kinds of individual intelligences. Therefore, we have a double goal: being able to deal with this heterogeneity and being able to get even more intelligent behaviors thanks to the synergies that the different kinds of intelligence can generate. Within the areas of collective intelligence there are several open topics where they always try to get better performances from groups than from the individuals. For example: collective consciousness, collective memory, or collective wisdom. Among all these topics we will focus on collective decision making, that has influence in most of the collective intelligent behaviors. The field of study of decision making is really wide, and its evolution has been completely parallel to the aforementioned collective intelligence. Firstly, it was focused on the individual as the main decision-making entity, but later it became involved in studying social and institutional groups as basic decision-making entities. The first studies within the decision-making discipline were based on simple paradigms, such as pros and cons analysis, criteria prioritization, fulfillment, following orders, or even chance. However, in the same way that studying the community instead of the individual meant a paradigm shift within collective intelligence, collective decision-making means a new challenge for all the related disciplines. Besides, two new main topics come up when dealing with collective decision-making: centralized and decentralized decision-making systems. In this thesis project we focus in the second one, because it is the most interesting based on the opportunities to generate new knowledge and deal with open issues in this area, as well as these results can be put into practice in a wider set of real-life environments. Finally, within the decentralized collective decision-making systems discipline, there are several basic mechanisms that lead to different approaches to the specific problems of this field, for example: leadership, imitation, prescription, or fear. We will focus on trust and reputation. They are one of the most multidisciplinary concepts and with more potential for applying them in every kind of environments. Besides, they have historically shown that they can generate better performance than other decentralized decision-making mechanisms. Shortly, we say trust is the belief of one entity that the outcome of other entities’ actions is going to be in a specific way. It is a subjective concept because the trust of two different entities in another one does not have to be the same. Reputation is the collective idea (or social evaluation) that a group of entities within a system have about another entity based on a specific criterion. Thus, it is a collective concept in its origin. It is important to say that the behavior of most of the collective systems are based on these two simple definitions. In fact, a lot of articles and essays describe how any organization would not be viable if the ideas of trust and reputation did not exist. From now on, we call Trust an Reputation System (TRS) to any kind of system that uses these concepts. Even though TRSs are one of the most common everyday aspects in our lives, the existing knowledge about them could not be more dispersed. There are thousands of scientific works in every field of study related to trust and reputation: philosophy, psychology, sociology, economics, politics, information sciences, etc. But the main issue is that a comprehensive vision of trust and reputation for all these disciplines does not exist. Every discipline focuses its studies on a specific set of topics but none of them tries to take advantage of the knowledge generated in the other disciplines to improve its behavior or performance. Detailed topics in some fields are completely obviated in others, and even though the study of some topics within several disciplines produces complementary results, these results are not used outside the discipline where they were generated. This leads us to a very high knowledge dispersion and to a lack in the reuse of methodologies, policies and techniques among disciplines. Due to its great importance, this high dispersion of trust and reputation knowledge is one of the main problems this thesis contributes to solve. When we work with TRSs, all the aspects related to security are a constant since it is a vital aspect within the decision-making systems. Besides, TRS are often used to perform some responsibilities related to security. Finally, we cannot forget that the act of trusting is invariably attached to the act of delegating a specific responsibility and, when we deal with these concepts, the idea of risk is always present. This refers to the risk of generated expectations not being accomplished or being accomplished in a different way we anticipated. Thus, we can see that any system using trust to improve or enable its behavior, because of its own nature, is especially vulnerable if the premises it is based on are attacked. Related to this topic, we can see that the approaches of the different disciplines that study attacks of trust and reputation are very diverse. Some attempts of using approaches of other disciplines have been made within the information science area of knowledge, but these approaches are usually incomplete, not systematic and oriented to achieve specific requirements of specific applications. They never try to consolidate a common base of knowledge that could be reusable in other context. Based on all these ideas, this work makes the following direct contributions to the field of TRS: • The compilation of the most relevant existing knowledge related to trust and reputation management systems focusing on their advantages and disadvantages. • We define a generic architecture for TRS, identifying the main entities and processes involved. • We define a generic security framework for TRS. We identify the main security assets and propose a complete taxonomy of attacks for TRS. • We propose and validate a methodology to analyze, design, secure and deploy TRS in real-life environments. Additionally we identify the principal kind of applications we can implement with TRS and how TRS can provide a specific functionality. • We develop a software component to validate and optimize the behavior of a TRS in order to achieve a specific functionality or performance. In addition to the contributions made directly to the field of the TRS, we have made original contributions to different areas of knowledge thanks to the application of the analysis, design and security methodologies previously presented: • Detection of thermal anomalies in Data Centers. Thanks to the application of the TRS analysis and design methodologies, we successfully implemented a thermal anomaly detection system based on a TRS.We compare the detection performance of Self-Organized- Maps and Growing Neural Gas algorithms. We show how SOM provides better results for Computer Room Air Conditioning anomaly detection, yielding detection rates of 100%, in training data with malfunctioning sensors. We also show that GNG yields better detection and isolation rates for workload anomaly detection, reducing the false positive rate when compared to SOM. • Improving the performance of a harvesting system based on swarm computing and social odometry. Through the implementation of a TRS, we achieved to improve the ability of coordinating a distributed network of autonomous robots. The main contribution lies in the analysis and validation of the incremental improvements that can be achieved with proper use information that exist in the system and that are relevant for the TRS, and the implementation of the appropriated trust algorithms based on such information. • Improving Wireless Mesh Networks security against attacks against the integrity, confidentiality or availability of data and communications supported by these networks. Thanks to the implementation of a TRS we improved the detection time rate against these kind of attacks and we limited their potential impact over the system. • We improved the security of Wireless Sensor Networks against advanced attacks, such as insider attacks, unknown attacks, etc. Thanks to the TRS analysis and design methodologies previously described, we implemented countermeasures against such attacks in a complex environment. In our experiments we have demonstrated that our system is capable of detecting and confining various attacks that affect the core network protocols. We have also demonstrated that our approach is capable of rapid attack detection. Also, it has been proven that the inclusion of the proposed detection mechanisms significantly increases the effort the attacker has to introduce in order to compromise the network. Finally we can conclude that, to all intents and purposes, this thesis offers a useful and applicable knowledge in real-life environments that allows us to maximize the performance of any system based on a TRS. Thus, we deal with the main deficiency of this discipline: the lack of a common and complete base of knowledge and the lack of a methodology for the development of TRS that allow us to analyze, design, secure and deploy TRS in a systematic way.

A taste of the technical cuisine: metals and other ingredients

According to cognitive linguistics, language has an experiential origin based on perception, sensory motor activities and our knowledge of the world. Our thought operates by establishing similarities, links and associations that enable us to talk about one thing in terms of another as shown in the example of love as a journey (Lakoff and Johnson, 1980). Metaphor and metonymy are conceptual and linguistic tools that make possible most of these cognitive operations. Since metaphor is an essential element of human communication, the discourse of specialised disciplines includes metaphorical mappings and numerous examples of metaphorical expressions, for example in economics, where business is mapped in terms of war (White, 2004; Herrera & White, 2000), electrotechnics with electrical components understood as couples (Roldán- Riejos in preparation) or in civil engineering where a bridge is conceptualized as a person (Roldán-Riejos, 2013). In this paper, the metaphors: WORKING WITH METALS IS COOKING/ TRABAJAR CON METALES ES COCINAR and METALS ARE CULINARY OBJECTS/ LOS METALES SON OBJETOS CULINARIOS are explored. The main aim is to show that the cooking metaphor is widely spread in the metallurgical domain in English and Spanish, although with different nuances in each language due to socio-cultural factors. The method adopted consists of analysing examples taken from the: Bilingual Dictionary of Scientific and Technical Metaphors and Metonymies Spanish- English/English-Spanish, a forthcoming and rigorously documented bilingual dictionary that sums up research on conceptual, linguistic and visual metaphor and metonymy in different areas of engineering (Roldán-Riejos and Molina, 2013). The present paper studies in detail English and Spanish cross-linguistic correspondences related to types of metals and processes. It is suggested that they reflect synesthetic metaphoric mappings. The exploitation of cognitive conceptual metaphor in the ESP classroom is lastly recommended.

Adults'Education and Agricultural Innovation: A Social Learning Approach

Social learning processes can be the basis of a method of agricultural innovation that involves expert and empirical knowledge. In this sense, the objective of this study was to determine the effectiveness and sustainability of an innovation process, understood as social learning, in a group of small farmers in the southern highlands of Peru. Innovative proposals and its permanence three years after the process finished were evaluated. It was observed that innovation processes generated are maintained over time; however, new innovations are not subsequently generated. We conclude that adult learning processes and innovation based on social learning are more effective and sustainable; however, the farmers internalization in innovation processes is given longer term.

Development in Rural Areas Through Capacity Building and Education for Business

This paper is based on a case study located in Avila, central Spain. Its main objectives are to implement an entrepreneurship program and design a plan of capacity building and education for business in order to promote the development of rural areas. The methodological approach of the program is based on the use of tools that permit involving the various actors of the area from the early planning stages. The university's group that is carrying out the field work has relied on these participatory tools in very different areas and contexts for over 25 years. This has allowed the development of an advanced planning model called ?Working With People? that connects expert and experience knowledge in the territories where it is applied. With this methodological approach, the diagnosis of the territory and the design of the program's strategy has been carried out. Once completed the first phase of the program and in order to ensure the sustainability and applicability of future entrepreneurial initiatives, it is necessary to support and strengthen potential entrepreneurs through training activities and capacity building. It relies on ?How to learn from people who live there? to promote investment projects and to teach them with adequate educational skills. In this context, this article aims to study the implementation strategy of these training and capacity building activities studied from an academic perspective, as well as analyzing the potential effects of these actions in promoting entrepreneurship in the territories

Justice and emotions in service recovery: a complaint in B2C e-commerce

This study proposes a marketing approach to service recovery (SR) models to explain what factors affect cumulative satisfaction, loyalty and word-of-mouth (WOM) following complaint behaviour. The model has its base on the definition of perceived justice and its influence on satisfaction with service recovery (SSR) and on emotions (positive and negative). Trust acts as a central construct in the model, receiving influence from the affective and cognitive aspect. The sample for this study consists of 303 Spanish business-to-consumer e-commerce (B2C-EC) users who made a complaint after an electronic transaction. Results from the analysis show the influence of perceived justice ? mainly interactional justice and procedural justice ? on SSR and the relevance of positive emotions as a key factor in SSR processes, in contrast to the major role that negative emotions have traditionally played in these models.

Human-modified ecosystems and future evolution

Our global impact is finally receiving the scientific attention it deserves. The outcome will largely determine the future course of evolution. Human-modified ecosystems are shaped by our activities and their side effects. They share a common set of traits including simplified food webs, landscape homogenization, and high nutrient and energy inputs. Ecosystem simplification is the ecological hallmark of humanity and the reason for our evolutionary success. However, the side effects of our profligacy and poor resource practices are now so pervasive as to threaten our future no less than that of biological diversity itself. This article looks at human impact on ecosystems and the consequences for evolution. It concludes that future evolution will be shaped by our awareness of the global threats, our willingness to take action, and our ability to do so. Our ability is presently hampered by several factors, including the poor state of ecosystem and planetary knowledge, ignorance of human impact, lack of guidelines for sustainability, and a paucity of good policies, practices, and incentives for adopting those guidelines in daily life. Conservation philosophy, science, and practice must be framed against the reality of human-dominated ecosystems, rather than the separation of humanity and nature underlying the modern conservation movement. The steps scientists can take to imbed science in conservation and conservation in the societal process affecting the future of ecosystems and human well-being are discussed.

Evolutionary relationships of the coelacanth, lungfishes, and tetrapods based on the 28S ribosomal RNA gene.

The origin of land vertebrates was one of the major transitions in the history of vertebrates. Yet, despite many studies that are based on either morphology or molecules, the phylogenetic relationships among tetrapods and the other two living groups of lobe-finned fishes, the coelacanth and the lungfishes, are still unresolved and debated. Knowledge of the relationships among these lineages, which originated back in the Devonian, has profound implications for the reconstruction of the evolutionary scenario of the conquest of land. We collected the largest molecular data set on this issue so far, about 3,500 base pairs from seven species of the large 28S nuclear ribosomal gene. All phylogenetic analyses (maximum parsimony, neighbor-joining, and maximum likelihood) point toward the hypothesis that lungfishes and coelacanths form a monophyletic group and are equally closely related to land vertebrates. This evolutionary hypothesis complicates the identification of morphological or physiological preadaptations that might have permitted the common ancestor of tetrapods to colonize land. This is because the reconstruction of its ancestral conditions would be hindered by the difficulty to separate uniquely derived characters from shared derived characters in the coelacanth/lungfish and tetrapod lineages. This molecular phylogeny aids in the reconstruction of morphological evolutionary steps by providing a framework; however, only paleontological evidence can determine the sequence of morphological acquisitions that allowed lobe-finned fishes to colonize land.

Investigating and Understanding Student Learning Outcomes in an Online and Face-to-Face Graduate Level Legal Administration Course: An Embedded Mixed Methods Design

Online education is a new teaching and learning medium with few current guidelines for faculty, administrators or students. Its rapid growth over the last decade has challenged academic institutions to keep up with the demand, while also providing a quality education. Our understanding of the factors that determine quality and effective online learning experiences that lead to student learning outcomes is still evolving. There is a lack of consensus on the effectiveness of online versus face-to-face education in the current research. The U.S. Department of Education conducted a meta-analysis in 2009 and concluded that student-learning outcomes in online courses were equal to and, often times, better than face-to-face traditional courses. Subsequent research has found contradictory findings, and further inquiry is necessary. The purpose of this embedded mixed methods design research study is to further our understanding of the factors that create quality and successful educational outcomes in an online course. To achieve this, the first phase of this study measured and compared learning outcomes in an online and in class graduate-level legal administration course. The second phase of the study entailed interviews with those students in both the online and face-to-face sections to understand their perspectives on the factors contributing to learning outcomes. Six themes emerged from the qualitative findings: convenience, higher order thinking, discussions, professor engagement, professor and student interaction, and face-to-face interaction. Findings from this study indicate the factors students perceive as contributing to learning outcomes in an online course are consistent among all students and are supported in the existing literature. Higher order thinking, however, emerged as a stronger theme than indicated in the current research, and the face-to-face nature of the traditional classroom may be more an issue of familiarity than a factor contributing to learning outcomes. As education continues to reach new heights and developments in technology advance, the factors found to contribute to student learning outcomes will be refined and enhanced. These developments will continue to transform the ways in which we deliver and receive knowledge in both traditional and online classrooms. While there is a growing body of research on online education, the field’s evolution has unsettled earlier findings and posed new areas to investigate.

Distance Education and the Evolution of Online Learning in the United States

Online education is no longer a trend, rather it is mainstream. In the Fall of 2012, 69.1% of chief academic leaders indicated online learning was critical to their long-term strategy and of the 20.6 million students enrolled in higher education, 6.7 million were enrolled in an online course (Allen & Seaman, 2013; United States Department of Education, 2013). The advent of online education and its rapid growth has forced academic institutions and faculty to question the current styles and techniques for teaching and learning. As developments in educational technology continue to advance, the ways in which we deliver and receive knowledge in both the traditional and online classrooms will further evolve. It is necessary to investigate and understand the progression and advancements in educational technology and the variety of methods used to deliver knowledge to improve the quality of education we provide today and motivate, inspire, and educate the students of the 21st century. This paper explores the atioevolution of distance education beginning with correspondence and the use of parcel post, to radio, then to television, and finally to online education.

Influences of psychological and experiential processes in paintings of Sheila Sobol

"For a number of artists, the activity of making. art is an inquiry into: the nature of art, the true nature of reality, and the execution of artistic ideas. This inquiry ·is benefited by recognizing psychological processes and theories, subjectl.ve and external experiences, and technical and aesthetic knowledge. The "creative process" contains this inquiry and can be likened to a hinge which connects the art produced and the artist"