Assessing user bias in affect detection within context-based spoken dialog systems

This paper presents an empirical evidence of user bias within a laboratory-oriented evaluation of a Spoken Dialog System. Specifically, we addressed user bias in their satisfaction judgements. We question the reliability of this data for modeling user emotion, focusing on contentment and frustration in a spoken dialog system. This bias is detected through machine learning experiments that were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. The target used was the satisfaction rating and the predictors were conversational/dialog features. Our results indicated that standard classifiers were significantly more successful in discriminating frustration and contentment and the intensities of these emotions (reflected by user satisfaction ratings) from annotator data than from user data. Indirectly, the results showed that conversational features are reliable predictors of the two abovementioned emotions.

Project based learning activities as a means of adapting conventional curricula to the demands of the 21st century aeronautical engineer: The design and building of the EYEFLY 1.

In this paper we report the process of designing and building the EYEFLY 1, a real UAS platform which has just performed its maiden flight. For the development of this aircraft, 30 groups of students from successive years at the Escuela Universitaria de Ingeniería Técnica Aeronáutica (EUITA) of the Universidad Politécnica de Madrid (UPM) carried out their compulsory End of Degree Project as a coordinated Project Based learning activity. Our conclusions clearly indicate that Project Based Learning activities can provide a valid complement to more conventional, theoretically-based, teaching methods. The combination of both approaches will allow us to maintain traditional but well-tested methods for providing our students with a sound knowledge of fundamental engineering disciplines and, at the same time, to introduce our students to exciting and relevant engineering situations and sceneries where social and business skills, such as communication skills, team-working or decision-taking, can be put into practice.

Evaluating new interaction paradigms in SEN teaching: defining the experiment

New devices have made their way into everyday life in recent years, opening the doors to new ways of interacting with computers, providing different, and potentially better, solutions to some problems. But this raises the question of if there is any way of measuring whether or not these new devices are suitable. This paper presents a strategy for evaluating the suitability of new interaction devices in the context of teaching children with special educational needs

Exploring the logic of mobile search

After more than a decade of development work and hopes, the usage of mobile Internet has finally taken off. Now, we are witnessing the first signs of evidence of what might become the explosion of mobile content and applications that will be shaping the (mobile) Internet of the future. Similar to the wired Internet, search will become very relevant for the usage of mobile Internet. Current research on mobile search has applied a limited set of methodologies and has also generated a narrow outcome of meaningful results. This article covers new ground, exploring the use and visions of mobile search with a users' interview-based qualitative study. Its main conclusion builds upon the hypothesis that mobile search is sensitive to a mobile logic different than today's one. First, (advanced) users ask for accessing with their mobile devices the entire Internet, rather than subsections of it. Second, success is based on new added-value applications that exploit unique mobile functionalities. The authors interpret that such mobile logic involves fundamentally the use of personalised and context-based services.

Opportunities in the Mobile Search Market

Success in the mobile search market will come to those who provide value-added apps that exploit unique mobile functionalities, especially those related to personalized and context-based services.

Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation

Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily. Nevertheless, multilingual semantic applications are still rare, owing to the fact that most online ontologies are monolingual in English. In order to solve this issue, techniques for ontology localisation and translation are needed. However, traditional machine translation is difficult to apply to ontologies, owing to the fact that ontology labels tend to be quite short in length and linguistically different from the free text paradigm. In this paper, we propose an approach to enhance machine translation of ontologies based on exploiting the well-structured concept descriptions contained in the ontology. In particular, our approach leverages the semantics contained in the ontology by using Cross Lingual Explicit Semantic Analysis (CLESA) for context-based disambiguation in phrase-based Statistical Machine Translation (SMT). The presented work is novel in the sense that application of CLESA in SMT has not been performed earlier to the best of our knowledge.

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 conceptual insight on digital paralell workshops for urban planning

The educational realm in Urban Plan ning needs a review because of the global challenges that human settlements will face in the near futu re. In this scenario, international boards of research call for the development of common frameworks of research, accredita tion, and planning best-pra ctices, that need to transcend the limits of local competences, which at the same time affect educational structures. A central issue on achieving this pursued consensus is in ternational cooperation among academic institutions, seeking global awareness on urban challenges, built equally upon a variety of context-based experiences. The rise of ICT's and digital tools are widely perceived as a great field of opportunity to establish complex and de-centralized networks of knowledge-bu ilding that can be critical to address these needs.

Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.

Project Management Learning in a Collaborative Distant Learning Context - An Actual On-going Experience

The goal of this paper is to show the results of an on-going experience on teaching project management to grade students by following a development scheme of management related competencies on an individual basis. In order to achieve that goal, the students are organized in teams that must solve a problem and manage the development of a feasible solution to satisfy the needs of a client. The innovative component advocated in this paper is the formal introduction of negotiating and virtual team management aspects, as different teams from different universities at different locations and comprising students with different backgrounds must collaborate and compete amongst them. The different learning aspects are identified and the improvement levels are reflected in a rubric that has been designed ad hoc for this experience. Finally, the effort frameworks for the student and instructor have been established according to the requirements of the Bologna paradigms. This experience is developed through a software-based support system allowing blended learning for the theoretical and individual?s work aspects, blogs, wikis, etc., as well as project management tools based on WWW that allow the monitoring of not only the expected deliverables and the achievement of the goals but also the progress made on learning as established in the defined rubric

Competence Monitoring in Project Teams by using Web based portfolio management systems

This paper reports a learning experience related to the acquisition of project management competences. Students from three different universities and backgrounds, cooperate in a common project that drives the learning-teaching process. Previous related works on this initiative have already evaluated the goodness of this multidisciplinary, project-based learning approach in the context of a new educative paradigm. Yet the innovative experience has allowed the authors to define a rubric in order to measure specific competences in project management. The study shows the rubric’s main aspects as well as competence acquisition evaluation alternatives, based in the metrics defined. Key indicators and specific reports obtained from data base fields in the web tool will support this work. As a result, new competences can be assessed, such ones like teamwork, problem solving, communication and leadership. Final goal is to provide an overall competence map to the students at the same time they improve their skills.

Intelligent context-aware services based on internet of things architectures

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

Enhanced recommendations for e-learning authoring tools based on a proactive context-aware recommender

Authoring tools are powerful systems in the area of e-Learning that make easier for teachers to create new learning objects by reusing or editing existing educational resources coming from learning repositories or content providers. However, due to the overwhelming number of resources these tools can access, sometimes it is difficult for teachers to find the most suitable resources taking into account their needs in terms of content (e.g. topic) or pedagogical aspects (e.g. target level associated to their students). Recommender systems can take an important role trying to mitigate this problem. In this paper we propose a new model to generate proactive context-aware recommendations on resources during the creation process of a new learning object that a teacher carries out by using an authoring tool. The common use cases covered by the model for having recommendations in online authoring tools and details about the recommender model itself are presented.

Teaching based on the case method of building collective protection

One of the fundamental aspects in the adaptation of the teaching to the European higher education is changing based models of teacher education to models based on student learning. In this work we present an educational experience developed with the teaching method based on the case method, with a clearly multidisciplinary. The experience has been developed in the teaching of analysis and verification of safety rails. This is a multidisciplinary field that presents great difficulties during their teaching. The use of the case method has given good results in the competences achieved by students

Analysis of teaching experience based on teaching by the case method. Application to reinforcing wooden floors

The technique of reinforcement of wooden floors is a matter clearly multidisciplinary. The teaching of the subject using the "traditional" method, explaining the theory first and then proposing and solving problems has not been successful. This paper discusses the results of a teaching experiencie. It has been the teaching of the subject by the case method. The results are clearly superior to those obtained with the traditional methodology.