A framework for goal-oriented discovery of resources in the RESTful architecture

One of the challenges facing the current web is the efficient use of all the available information. The Web 2.0 phenomenon has favored the creation of contents by average users, and thus the amount of information that can be found for diverse topics has grown exponentially in the last years. Initiatives such as linked data are helping to build the Semantic Web, in which a set of standards are proposed for the exchange of data among heterogeneous systems. However, these standards are sometimes not used, and there are still plenty of websites that require naive techniques to discover their contents and services. This paper proposes an integrated framework for content and service discovery and extraction. The framework is divided into several layers where the discovery of contents and services is made in a representational stateless transfer system such as the web. It employs several web mining techniques as well as feature-oriented modeling for the discovery of cross-cutting features in web resources. The framework is used in a scenario of electronic newspapers. An intelligent agent crawls the web for related news, and uses services and visits links automatically according to its goal. This scenario illustrates how the discovery is made at different levels and how the use of semantics helps implement an agent that performs high-level tasks.

Characterization of the Wikipedia Traffic

Since its inception, Wikipedia has grown to a solid and stable project and turned into a mass collaboration tool that allows the sharing and distribution of knowledge. The wiki approach that basis this initiative promotes the participation and collaboration of users. In addition to visits for browsing its contents, Wikipedia also receives the contributions of users to improve them. In the past, researchers paid attention to different aspects concerning authoring and quality of contents. However, little effort has been made to study the nature of the visits that Wikipedia receives. We conduct such an study using a sample of users' requests provided by the Wikimedia Foundation in the form of Squid log lines. Our sample contains more that 14,000 million requests from users all around the world and directed to all the projects maintained by the Wikimedia Foundation, including different editions of Wikipedia. This papers describes the work made to characterize the traffic directed to Wikipedia and consisting of the requests sent by its users. Our main aim is to obtain a detailed description of its composition in terms of the percentages corresponding to the different types of requests making part of it. The benefits from our work may range from the prediction of traffic peaks to the determination of the kind of resources most often requested, which can be useful for scalability considerations.

Counting, scoring and classifying hunger to allocate resources targeted to solve the problem

A proper allocation of resources targeted to solve hunger is essential to optimize the efficacy of actions and maximize results. This requires an adequate measurement and formulation of the problem as, paraphrasing Einstein, the formulation of a problem is essential to reach a solution. Different measurement methods have been designed to count, score, classify and compare hunger at local level and to allow comparisons between different places. However, the alternative methods produce significantly reach different results. These discrepancies make decisions on the targeting of resource allocations difficult. To assist decision makers, a new method taking into account the dimension of hunger and the coping capacities of countries, is proposed enabling to establish both geographical and sectoral priorities for the allocation of resources.

Counting, scoring and classifying hunger to allocate resources targeted to solve the problem

A proper allocation of resources targeted to solve hunger is essential to optimize the efficacy of actions and maximize results. This requires an adequate measurement and formulation of the problem as, paraphrasing Einstein, the formulation of a problem is essential to reach a solution. Different measurement methods have been designed to count, score, classify and compare hunger at local level and to allow comparisons between different places. However, the alternative methods reach significantly different results. These discrepancies make decisions on the targeting of resource allocations difficult. To assist decision makers, a new method taking into account the dimension of hunger and the coping capacities of countries is proposed enabling to establish both geographical and sectoral priorities for the allocation of resources

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Remote Delivery of Video Services over video links

The spreading of new systems of broadcasting and distribution of multimedia content has had as a consequence a larger need for aggregation of data and metadata to traditionally based contents of video and audio supply. Broadcasting chains of this type of channels have become overwhelmed by the quantity of resources, infrastructures and development needed for these channels to provide information. In order to avoid this kind of shortcomings, several recommendations and standards have been created to exchange metadata between production and distribution of taped programs. The problem lies in live programs, producers sometimes offer data to channels but most often, channels are not able to face required developments. The key to this problem is cost reduction. In this work, a study is conducted on added services which producers may provide to the media about content; a system is found by which additional communication expenses are not made and a model of information transfer is offered which allows low cost developments to supply new media platforms.

4CaaSt: Comprehensive management of Cloud services through a PaaS

The 4CaaSt project aims at developing a PaaS framework that enables flexible definition, marketing, deployment and management of Cloud-based services and applications. The major innovations proposed by 4CaaSt are the blueprint and its management and lifecycle, a one stop shop for Cloud services and the management of resources in the PaaS level (including elasticity). 4CaaSt also provides a portfolio of ready to use Cloud native services and Cloud- aware immigrant technologies.

Decarbonization of toll plazas: impact assessment of toll collection system management

Transport climate change impacts have become a worldwide concern. The use of Intelligent Transport Systems (ITS) could contribute to a more effective use of resources in toll road networks. Management of toll plazas is central to the reduction of greenhouse gas (GHG) emissions, as it is there that bottlenecks and congestion occur. This study focuses on management strategies aimed at reducing climate change impacts of toll plazas by managing toll collection systems. These strategies are based on the use of different collection system technologies – Electronic Toll Collection (ETC) and Open Road Tolling (ORT) – and on queue management. The carbon footprint of various toll plazas is determined by a proposed integrated methodology which estimates the carbon dioxide (CO2) emissions of the different operational stages at toll plazas (deceleration, service time, acceleration, and queuing) for the different toll collection systems. To validate the methodology, two main-line toll plazas of a Spanish toll highway were evaluated. The findings reveal that the application of new technologies to toll collection systems is an effective management strategy from an environmental point of view. The case studies revealed that ORT systems lead to savings of up to 70% of CO2 emissions at toll plazas, while ETC systems save 20% comparing to the manual ones. Furthermore, queue management can offer a 16% emissions savings when queue time is reduced by 116 seconds. The integrated methodology provides an efficient environmental management tool for toll plazas. The use of new technologies is the future of the decarbonization of toll plazas.

Collaborative semantic editing of linked data lexica.

The creation of language resources is a time-consuming process requiring the efforts of many people. The use of resources collaboratively created by non-linguists can potentially ameliorate this situation. However, such resources often contain more errors compared to resources created by experts. For the particular case of lexica, we analyse the case of Wiktionary, a resource created along wiki principles and argue that through the use of a principled lexicon model, namely lemon, the resulting data could be better understandable to machines. We then present a platform called lemon source that supports the creation of linked lexical data along the lemon model. This tool builds on the concept of a semantic wiki to enable collaborative editing of the resources by many users concurrently. In this paper, we describe the model, the tool and present an evaluation of its usability based on a small group of users.

Efficient management of available technologies. Aplication to mining operations for industry supplies

Nowadays, processing Industry Sector is going through a series of changes, including right management and reduction of environmental affections. Any productive process which looks for sustainable management is incomplete if Cycle of Life of mineral resources sustainability is not taken into account. Raw materials for manufacturing are provided by mineral resources extraction processes, such as copper, aluminum, iron, gold, silver, silicon, titanium? Those elements are necessary for Mankind development and are obtained from the Earth through mineral extractive processes. Mineral extraction processes are operations which must take care about the environmental consequences. Extraction of huge volumes of rock for their transformation into raw materials for industry must be optimized to reduce ecological cost of the final product as l was possible. Reducing the ecological balance on a global scale has no sense to design an efficient manufacturing in secondary industry (transformation), if in first steps of the supply chain (extraction) impact exceeds the savings of resources in successive phases. Mining operations size suggests that it is an environmental aggressive activity, but precisely because of its great impact must be the first element to be considered. That idea implies that a new concept born: Reduce economical and environmental cost This work aims to make a reflection on the parameters that can be modified to reduce the energy cost of the process without an increasing in operational costs and always ensuring the same production capacity. That means minimize economic and environmental cost at same time. An efficient design of mining operation which has taken into account that idea does not implies an increasing of the operating cost. To get this objective is necessary to think in global operation view to make that all departments involved have common guidelines which make you think in the optimization of global energy costs. Sometimes a single operational cost must be increased to reduce global cost. This work makes a review through different design parameters of surface mining setting some key performance indicators (KPIs) which are estimated from an efficient point of view. Those KPIs can be included by HQE Policies as global indicators. The new concept developed is that a new criteria has to be applied in company policies: improve management, improving OPERATIONAL efficiency. That means, that is better to use current resources properly (machinery, equipment,?) than to replace them with new things but not used correctly. As a conclusion, through an efficient management of current technologies in each extractive operation an important reduction of the energy can be achieved looking at downstream in the process. That implies a lower energetic cost in the whole cycle of life in manufactured product.

A model of the spatially dependent mechanical properties of the axon during its growth

Neuronal growth is a complex process involving many intra- and extracellular mechanisms which are collaborating conjointly to participate to the development of the nervous system. More particularly, the early neocortical development involves the creation of a multilayered structure constituted by neuronal growth (driven by axonal or dendritic guidance cues) as well as cell migration. The underlying mechanisms of such structural lamination not only implies important biochemical changes at the intracellular level through axonal microtubule (de)polymerization and growth cone advance, but also through the directly dependent stress/stretch coupling mechanisms driving them. Efforts have recently focused on modeling approaches aimed at accounting for the effect of mechanical tension or compression on the axonal growth and subsequent soma migration. However, the reciprocal influence of the biochemical structural evolution on the mechanical properties has been mostly disregarded. We thus propose a new model aimed at providing the spatially dependent mechanical properties of the axon during its growth. Our in-house finite difference solver Neurite is used to describe the guanosine triphosphate (GTP) transport through the axon, its dephosphorylation in guanosine diphosphate (GDP), and thus the microtubules polymerization. The model is calibrated against experimental results and the tensile and bending mechanical stiffnesses are ultimately inferred from the spatially dependent microtubule occupancy. Such additional information is believed to be of drastic relevance in the growth cone vicinity, where biomechanical mechanisms are driving axonal growth and pathfinding. More specifically, the confirmation of a lower stiffness in the distal axon ultimately participates in explaining the controversy associated to the tensile role of the growth cone.

Empirical analysis of traffic volume for the application of the options theory to highway concessions

*************************************************************************************** EL WCTR es un Congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte que hasta el 2010 publicaba sus libros de abstracts con ISBN. Por ello consideramos que debería seguir teníendose en cuenta para los indicadores de calidad ******************************************************************************************* Investment projects in the field of transportation infrastructures have a high degree of uncertainty and require an important amount of resources. In highway concessions in particular, the calculation of the Net Present Value (NPV) of the project by means of the discount of cash flows, may lead to erroneous results when the project incorporates certain flexibility. In these cases, the theory of real options is an alternative tool for the valuation of concessions. When the variable that generates uncertainty (in our case, the traffic) follows a random walk (or Geometric Brownian Motion), we can calculate the value of the options embedded in the contract starting directly from the process followed by that variable. This procedure notably simplifies the calculation method. In order to test the hypothesis of the evolution of traffic as a Geometric Brownian Motion, we have used the available series of traffic in Spanish highways, and we have applied the Augmented Dickey-Fuller approach, which is the most widely used test for this kind of study. The main result of the analysis is that we cannot reject the hypothesis that traffic follows a Geometric Brownian Motion in the majority of both toll highways and free highways in Spain.

Analysis of advanced European nuclear fuel cycle scenarios including transmutation and economic estimates

Four European fuel cycle scenarios involving transmutation options (in coherence with PATEROS and CPESFR EU projects) have been addressed from a point of view of resources utilization and economic estimates. Scenarios include: (i) the current fleet using Light Water Reactor (LWR) technology and open fuel cycle, (ii) full replacement of the initial fleet with Fast Reactors (FR) burning U?Pu MOX fuel, (iii) closed fuel cycle with Minor Actinide (MA) transmutation in a fraction of the FR fleet, and (iv) closed fuel cycle with MA transmutation in dedicated Accelerator Driven Systems (ADS). All scenarios consider an intermediate period of GEN-III+ LWR deployment and they extend for 200 years, looking for long term equilibrium mass flow achievement. The simulations were made using the TR_EVOL code, capable to assess the management of the nuclear mass streams in the scenario as well as economics for the estimation of the levelized cost of electricity (LCOE) and other costs. Results reveal that all scenarios are feasible according to nuclear resources demand (natural and depleted U, and Pu). Additionally, we have found as expected that the FR scenario reduces considerably the Pu inventory in repositories compared to the reference scenario. The elimination of the LWR MA legacy requires a maximum of 55% fraction (i.e., a peak value of 44 FR units) of the FR fleet dedicated to transmutation (MA in MOX fuel, homogeneous transmutation) or an average of 28 units of ADS plants (i.e., a peak value of 51 ADS units). Regarding the economic analysis, the main usefulness of the provided economic results is for relative comparison of scenarios and breakdown of LCOE contributors rather than provision of absolute values, as technological readiness levels are low for most of the advanced fuel cycle stages. The obtained estimations show an increase of LCOE ? averaged over the whole period ? with respect to the reference open cycle scenario of 20% for Pu management scenario and around 35% for both transmutation scenarios. The main contribution to LCOE is the capital costs of new facilities, quantified between 60% and 69% depending on the scenario. An uncertainty analysis is provided around assumed low and high values of processes and technologies.

Energy rehabilitation of social housing for rent, as demonstrator in the LIFE 'New4Old' Project

The main goal of the cofounded by the European Commission LIFE Project, New4Old (LIFE10 ENV/ES/439), is to define the most appropriate method and the best available practice in social housing rehabilitation with energy and environmental sustainability criteria, as well as to apply innovative technologies in the fight against climate change through an efficient use of resources and energy. The institutions involved in the Project are the Technological Centre AITEMIN, Madrid Polytechnic University (UPM), Portugal Technological Centre for Ceramics and Glass (CTCV) and the Zaragoza City Housing Society (SMZV). The demonstrator project consists in the energy rehabilitation of a rental social housing building located in Zaragoza?s historic quarter, according to the conclusions and strategies developed for the LIFE project. In actions taken in households of this nature passive design strategies are essential due to the limited income of owners, who often cannot afford energy bills. Therefore, the proposed actions will help improve the building?s passive performance and reach a higher thermal comfort, without increasing the economic cost linked to energy consumption.

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

El auge y penetración de las nuevas tecnologías junto con la llamada Web Social están cambiando la forma en la que accedemos a la medicina. Cada vez más pacientes y profesionales de la medicina están creando y consumiendo recursos digitales de contenido clínico a través de Internet, surgiendo el problema de cómo asegurar la fiabilidad de estos recursos. Además, un nuevo concepto está apareciendo, el de pervasive healthcare o sanidad ubicua, motivado por pacientes que demandan un acceso a los servicios sanitarios en todo momento y en todo lugar. Este nuevo escenario lleva aparejado un problema de confianza en los proveedores de servicios sanitarios. Las plataformas de eLearning se están erigiendo como paradigma de esta nueva Medicina 2.0 ya que proveen un servicio abierto a la vez que controlado/supervisado a recursos digitales, y facilitan las interacciones y consultas entre usuarios, suponiendo una buena aproximación para esta sanidad ubicua. En estos entornos los problemas de fiabilidad y confianza pueden ser solventados mediante la implementación de mecanismos de recomendación de recursos y personas de manera confiable. Tradicionalmente las plataformas de eLearning ya cuentan con mecanismos de recomendación, si bien están más enfocados a la recomendación de recursos. Para la recomendación de usuarios es necesario acudir a mecanismos más elaborados como son los sistemas de confianza y reputación (trust and reputation) En ambos casos, tanto la recomendación de recursos como el cálculo de la reputación de los usuarios se realiza teniendo en cuenta criterios principalmente subjetivos como son las opiniones de los usuarios. En esta tesis doctoral proponemos un nuevo modelo de confianza y reputación que combina evaluaciones automáticas de los recursos digitales en una plataforma de eLearning, con las opiniones vertidas por los usuarios como resultado de las interacciones con otros usuarios o después de consumir un recurso. El enfoque seguido presenta la novedad de la combinación de una parte objetiva con otra subjetiva, persiguiendo mitigar el efecto de posibles castigos subjetivos por parte de usuarios malintencionados, a la vez que enriquecer las evaluaciones objetivas con información adicional acerca de la capacidad pedagógica del recurso o de la persona. El resultado son recomendaciones siempre adaptadas a los requisitos de los usuarios, y de la máxima calidad tanto técnica como educativa. Esta nueva aproximación requiere una nueva herramienta para su validación in-silico, al no existir ninguna aplicación que permita la simulación de plataformas de eLearning con mecanismos de recomendación de recursos y personas, donde además los recursos sean evaluados objetivamente. Este trabajo de investigación propone pues una nueva herramienta, basada en el paradigma de programación orientada a agentes inteligentes para el modelado de comportamientos complejos de usuarios en plataformas de eLearning. Además, la herramienta permite también la simulación del funcionamiento de este tipo de entornos dedicados al intercambio de conocimiento. La evaluación del trabajo propuesto en este documento de tesis se ha realizado de manera iterativa a lo largo de diferentes escenarios en los que se ha situado al sistema frente a una amplia gama de comportamientos de usuarios. Se ha comparado el rendimiento del modelo de confianza y reputación propuesto frente a dos modos de recomendación tradicionales: a) utilizando sólo las opiniones subjetivas de los usuarios para el cálculo de la reputación y por extensión la recomendación; y b) teniendo en cuenta sólo la calidad objetiva del recurso sin hacer ningún cálculo de reputación. Los resultados obtenidos nos permiten afirmar que el modelo desarrollado mejora la recomendación ofrecida por las aproximaciones tradicionales, mostrando una mayor flexibilidad y capacidad de adaptación a diferentes situaciones. Además, el modelo propuesto es capaz de asegurar la recomendación de nuevos usuarios entrando al sistema frente a la nula recomendación para estos usuarios presentada por el modo de recomendación predominante en otras plataformas que basan la recomendación sólo en las opiniones de otros usuarios. Por último, el paradigma de agentes inteligentes ha probado su valía a la hora de modelar plataformas virtuales complejas orientadas al intercambio de conocimiento, especialmente a la hora de modelar y simular el comportamiento de los usuarios de estos entornos. La herramienta de simulación desarrollada ha permitido la evaluación del modelo de confianza y reputación propuesto en esta tesis en una amplia gama de situaciones diferentes. ABSTRACT Internet is changing everything, and this revolution is especially present in traditionally offline spaces such as medicine. In recent years health consumers and health service providers are actively creating and consuming Web contents stimulated by the emergence of the Social Web. Reliability stands out as the main concern when accessing the overwhelming amount of information available online. Along with this new way of accessing the medicine, new concepts like ubiquitous or pervasive healthcare are appearing. Trustworthiness assessment is gaining relevance: open health provisioning systems require mechanisms that help evaluating individuals’ reputation in pursuit of introducing safety to these open and dynamic environments. Technical Enhanced Learning (TEL) -commonly known as eLearning- platforms arise as a paradigm of this Medicine 2.0. They provide an open while controlled/supervised access to resources generated and shared by users, enhancing what it is being called informal learning. TEL systems also facilitate direct interactions amongst users for consultation, resulting in a good approach to ubiquitous healthcare. The aforementioned reliability and trustworthiness problems can be faced by the implementation of mechanisms for the trusted recommendation of both resources and healthcare services providers. Traditionally, eLearning platforms already integrate recommendation mechanisms, although this recommendations are basically focused on providing an ordered classifications of resources. For users’ recommendation, the implementation of trust and reputation systems appears as the best solution. Nevertheless, both approaches base the recommendation on the information from the subjective opinions of other users of the platform regarding the resources or the users. In this PhD work a novel approach is presented for the recommendation of both resources and users within open environments focused on knowledge exchange, as it is the case of TEL systems for ubiquitous healthcare. The proposed solution adds the objective evaluation of the resources to the traditional subjective personal opinions to estimate the reputation of the resources and of the users of the system. This combined measure, along with the reliability of that calculation, is used to provide trusted recommendations. The integration of opinions and evaluations, subjective and objective, allows the model to defend itself against misbehaviours. Furthermore, it also allows ‘colouring’ cold evaluation values by providing additional quality information such as the educational capacities of a digital resource in an eLearning system. As a result, the recommendations are always adapted to user requirements, and of the maximum technical and educational quality. To our knowledge, the combination of objective assessments and subjective opinions to provide recommendation has not been considered before in the literature. Therefore, for the evaluation of the trust and reputation model defined in this PhD thesis, a new simulation tool will be developed following the agent-oriented programming paradigm. The multi-agent approach allows an easy modelling of independent and proactive behaviours for the simulation of users of the system, conforming a faithful resemblance of real users of TEL platforms. For the evaluation of the proposed work, an iterative approach have been followed, testing the performance of the trust and reputation model while providing recommendation in a varied range of scenarios. A comparison with two traditional recommendation mechanisms was performed: a) using only users’ past opinions about a resource and/or other users; and b) not using any reputation assessment and providing the recommendation considering directly the objective quality of the resources. The results show that the developed model improves traditional approaches at providing recommendations in Technology Enhanced Learning (TEL) platforms, presenting a higher adaptability to different situations, whereas traditional approaches only have good results under favourable conditions. Furthermore the promotion period mechanism implemented successfully helps new users in the system to be recommended for direct interactions as well as the resources created by them. On the contrary OnlyOpinions fails completely and new users are never recommended, while traditional approaches only work partially. Finally, the agent-oriented programming (AOP) paradigm has proven its validity at modelling users’ behaviours in TEL platforms. Intelligent software agents’ characteristics matched the main requirements of the simulation tool. The proactivity, sociability and adaptability of the developed agents allowed reproducing real users’ actions and attitudes through the diverse situations defined in the evaluation framework. The result were independent users, accessing to different resources and communicating amongst them to fulfil their needs, basing these interactions on the recommendations provided by the reputation engine.