Towards architectural foundations for cognitive self-aware systems

In this talk we address a proposal concerning a methodology for extracting universal, domain neutral, architectural design patterns from the analysis of biological cognition. This will render a set of design principles and design patterns oriented towards the construction of better machines. Bio- inspiration cannot be a one step process if we we are going to to build robust, dependable autonomous agents; we must build solid theories first, departing from natural systems, and supporting our designs of artificial ones.

Scaling in Soil and Other Complex Porous Media

Scaling is becoming an increasingly important topic in the earth and environmental sciences as researchers attempt to understand complex natural systems through the lens of an ever-increasing set of methods and scales. The guest editors introduce the papers in this issue’s special section and present an overview of some of the work being done. Scaling remains one of the most challenging topics in earth and environmental sciences, forming a basis for our understanding of process development across the multiple scales that make up the subsurface environment. Tremendous progress has been made in discovery, explanation, and applications of scaling. And yet much more needs to be done and is being done as part of the modern quest to quantify, analyze, and manage the complexity of natural systems. Understanding and succinct representation of scaling properties can unveil underlying relationships between system structure and response functions, improve parameterization of natural variability and heterogeneity, and help us address societal needs by effectively merging knowledge acquired at different scales.

Building resilience to water scarcity in Southern Spain: A case study of rice farming in Doñana protected wetlands

Agricultural water management needs to evolve in view of increased water scarcity, especially when farming and natural protected areas are closely linked. In the study site of Don?ana (southern Spain), water is shared by rice producers and a world heritage biodiversity ecosystem. Our aim is to contribute to defining adaptation strategies that may build resilience to increasing water scarcity and minimize water conflicts among agricultural and natural systems. The analytical framework links a participatory process with quantitative methods to prioritize the adaptation options. Bottom-up proposed adaptation measures are evaluated by a multi-criteria analysis (MCA) that includes both socioeconomic criteria and criteria of the ecosystem services affected by the adaptation options. Criteria weights are estimated by three different methods?analytic hierarchy process, Likert scale and equal weights?that are then compared. Finally, scores from an MCA are input into an optimization model used to determine the optimal land-use distribution in order to maximize utility and land-use diversification according to different scenarios of funds and water availability. While our results show a spectrum of perceptions of priorities among stakeholders, there is one overriding theme that is to define a way to restore part of the rice fields to natural wetlands. These results hold true under the current climate scenario and evenmore so under an increased water scarcity scenario.

How can irrigated agriculture adapt to climate change? Insights from the Guadiana Basin in Spain

Climate change is already affecting many natural systems and human environments worldwide, like the semiarid Guadiana Basin in Spain. This paper illustrates a systematic analysis of climate change adaptation in the Guadiana irrigation farming region. The study applies a solution-oriented diagnostic framework structured along a series of sequential analytical steps. An initial stage integrates economic and hydrologic modeling to evaluate the effects of climate change on the agriculture and water sectors. Next, adaptation measures are identified and prioritized through a stakeholder-based multi-criteria analysis. Finally, a social network analysis identifies key actors and their relationships in climate change adaptation. The study shows that under a severe climate change scenario, water availability could be substantially decreased and drought occurrence will augment. In consequence, farmers will adapt their crops to a lesser amount of water and income gains will diminish, particularly for smallholder farms. Among the various adaptation measures considered, those related to private farming (new crop varieties and modern irrigation technologies) are ranked highest, whereas public-funded hard measures (reservoirs) are lowest and public soft measures (insurance) are ranked middle. In addition, stakeholders highlighted that the most relevant criteria for selecting adaptation plans are environmental protection, financial feasibility and employment creation. Nonetheless, the social network analysis evidenced the need to strengthen the links among the different stakeholder groups to facilitate the implementation of adaptation processes. In sum, the diagnostic framework applied in this research can be considered a valuable tool for guiding and supporting decision making in climate change adaptation and communicating scientific results.

Expansión y transformación del territorio : la ineficiencia de los fraccionamientos urbanizados : zona conurbada de Veracruz, México

La expansión de la ciudad y zona conurbada de Veracruz, se encuentra en una dinámica en donde convergen el medio artificial construido por el hombre y que ha generado una ciudad fragmentada; el medio natural, en el que se encuentran importantes componentes ecosistémicos de la zona costera; las políticas y estrategias que establecen los cinco Programas de ordenamiento urbano vigentes, sujetos al patrón de acumulación de capital, favoreciendo los intereses de la iniciativa privada. Bajo este panorama encontramos un territorio complejo que se encuentra cada vez más vulnerado y en riesgo de que los sistemas humano y natural colapsen. Lo anterior se evidencia en los nuevos desarrollos urbanizados, a partir del estudio de la problemática que presentan los fraccionamientos habitacionales, donde cada vez son más vulnerables, lo que constata su ineficiencia dentro del sistema urbano. ABSTRACT The expansion of the city and metropolitan area of Veracruz, is in a dynamic where converge the artificial environment built by the man and that has generated a fragmented city; natural environment, in which there are important ecosystem components of the coastal zone; policies and strategies that establish the five existing urban planning programs, subject to the pattern of accumulation of capital, favoring the private enterprises interests. Under this scenario is found a complex area that is more vulnerable every time and at risk of human and natural systems collapse. The above mentioned is evident in the new urbanized development, from studies of the problem posed by housing developments, finding that more and more vulnerable, which finds its inefficiency within the urban system.

Participatory modeling for sustainable development in water and agrarian systems: potential and limits of stakeholder involvement

Public participation is increasingly advocated as a necessary feature of natural resources management. The EU Water Framework Directive (WFD) is such an example, as it prescribes participatory processes as necessary features in basin management plans (EC 2000). The rationale behind this mandate is that involving interest groups ideally yields higher-quality decisions, which are arguably more likely to meet public acceptance (Pahl-Wostl, 2006). Furthermore, failing to involve stakeholders in policy-making might hamper the implementation of management initiatives, as controversial decisions can lead pressure lobbies to generate public opposition (Giordano et al. 2005, Mouratiadou and Moran 2007).

Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

Empowering and assisting natural human mobility: The simbiosis walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staff

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain.

Contributions to the contextualization of human-machine spoken interaction systems

The design and development of spoken interaction systems has been a thoroughly studied research scope for the last decades. The aim is to obtain systems with the ability to interact with human agents with a high degree of naturalness and efficiency, allowing them to carry out the actions they desire using speech, as it is the most natural means of communication between humans. To achieve that degree of naturalness, it is not enough to endow systems with the ability to accurately understand the user’s utterances and to properly react to them, even considering the information provided by the user in his or her previous interactions. The system has also to be aware of the evolution of the conditions under which the interaction takes place, in order to act the most coherent way as possible at each moment. Consequently, one of the most important features of the system is that it has to be context-aware. This context awareness of the system can be reflected in the modification of the behaviour of the system taking into account the current situation of the interaction. For instance, the system should decide which action it has to carry out, or the way to perform it, depending on the user that requests it, on the way that the user addresses the system, on the characteristics of the environment in which the interaction takes place, and so on. In other words, the system has to adapt its behaviour to these evolving elements of the interaction. Moreover that adaptation has to be carried out, if possible, in such a way that the user: i) does not perceive that the system has to make any additional effort, or to devote interaction time to perform tasks other than carrying out the requested actions, and ii) does not have to provide the system with any additional information to carry out the adaptation, which could imply a lesser efficiency of the interaction, since users should devote several interactions only to allow the system to become adapted. In the state-of-the-art spoken dialogue systems, researchers have proposed several disparate strategies to adapt the elements of the system to different conditions of the interaction (such as the acoustic characteristics of a specific user’s speech, the actions previously requested, and so on). Nevertheless, to our knowledge there is not any consensus on the procedures to carry out these adaptation. The approaches are to an extent unrelated from one another, in the sense that each one considers different pieces of information, and the treatment of that information is different taking into account the adaptation carried out. In this regard, the main contributions of this Thesis are the following ones: Definition of a contextualization framework. We propose a unified approach that can cover any strategy to adapt the behaviour of a dialogue system to the conditions of the interaction (i.e. the context). In our theoretical definition of the contextualization framework we consider the system’s context as all the sources of variability present at any time of the interaction, either those ones related to the environment in which the interaction takes place, or to the human agent that addresses the system at each moment. Our proposal relies on three aspects that any contextualization approach should fulfill: plasticity (i.e. the system has to be able to modify its behaviour in the most proactive way taking into account the conditions under which the interaction takes place), adaptivity (i.e. the system has also to be able to consider the most appropriate sources of information at each moment, both environmental and user- and dialogue-dependent, to effectively adapt to the conditions aforementioned), and transparency (i.e. the system has to carry out the contextualizaton-related tasks in such a way that the user neither perceives them nor has to do any effort in providing the system with any information that it needs to perform that contextualization). Additionally, we could include a generality aspect to our proposed framework: the main features of the framework should be easy to adopt in any dialogue system, regardless of the solution proposed to manage the dialogue. Once we define the theoretical basis of our contextualization framework, we propose two cases of study on its application in a spoken dialogue system. We focus on two aspects of the interaction: the contextualization of the speech recognition models, and the incorporation of user-specific information into the dialogue flow. One of the modules of a dialogue system that is more prone to be contextualized is the speech recognition system. This module makes use of several models to emit a recognition hypothesis from the user’s speech signal. Generally speaking, a recognition system considers two types of models: an acoustic one (that models each of the phonemes that the recognition system has to consider) and a linguistic one (that models the sequences of words that make sense for the system). In this work we contextualize the language model of the recognition system in such a way that it takes into account the information provided by the user in both his or her current utterance and in the previous ones. These utterances convey information useful to help the system in the recognition of the next utterance. The contextualization approach that we propose consists of a dynamic adaptation of the language model that is used by the recognition system. We carry out this adaptation by means of a linear interpolation between several models. Instead of training the best interpolation weights, we make them dependent on the conditions of the dialogue. In our approach, the system itself will obtain these weights as a function of the reliability of the different elements of information available, such as the semantic concepts extracted from the user’s utterance, the actions that he or she wants to carry out, the information provided in the previous interactions, and so on. One of the aspects more frequently addressed in Human-Computer Interaction research is the inclusion of user specific characteristics into the information structures managed by the system. The idea is to take into account the features that make each user different from the others in order to offer to each particular user different services (or the same service, but in a different way). We could consider this approach as a user-dependent contextualization of the system. In our work we propose the definition of a user model that contains all the information of each user that could be potentially useful to the system at a given moment of the interaction. In particular we will analyze the actions that each user carries out throughout his or her interaction. The objective is to determine which of these actions become the preferences of that user. We represent the specific information of each user as a feature vector. Each of the characteristics that the system will take into account has a confidence score associated. With these elements, we propose a probabilistic definition of a user preference, as the action whose likelihood of being addressed by the user is greater than the one for the rest of actions. To include the user dependent information into the dialogue flow, we modify the information structures on which the dialogue manager relies to retrieve information that could be needed to solve the actions addressed by the user. Usage preferences become another source of contextual information that will be considered by the system towards a more efficient interaction (since the new information source will help to decrease the need of the system to ask users for additional information, thus reducing the number of turns needed to carry out a specific action). To test the benefits of the contextualization framework that we propose, we carry out an evaluation of the two strategies aforementioned. We gather several performance metrics, both objective and subjective, that allow us to compare the improvements of a contextualized system against the baseline one. We will also gather the user’s opinions as regards their perceptions on the behaviour of the system, and its degree of adaptation to the specific features of each interaction. Resumen El diseño y el desarrollo de sistemas de interacción hablada ha sido objeto de profundo estudio durante las pasadas décadas. El propósito es la consecución de sistemas con la capacidad de interactuar con agentes humanos con un alto grado de eficiencia y naturalidad. De esta manera, los usuarios pueden desempeñar las tareas que deseen empleando la voz, que es el medio de comunicación más natural para los humanos. A fin de alcanzar el grado de naturalidad deseado, no basta con dotar a los sistemas de la abilidad de comprender las intervenciones de los usuarios y reaccionar a ellas de manera apropiada (teniendo en consideración, incluso, la información proporcionada en previas interacciones). Adicionalmente, el sistema ha de ser consciente de las condiciones bajo las cuales transcurre la interacción, así como de la evolución de las mismas, de tal manera que pueda actuar de la manera más coherente en cada instante de la interacción. En consecuencia, una de las características primordiales del sistema es que debe ser sensible al contexto. Esta capacidad del sistema de conocer y emplear el contexto de la interacción puede verse reflejada en la modificación de su comportamiento debida a las características actuales de la interacción. Por ejemplo, el sistema debería decidir cuál es la acción más apropiada, o la mejor manera de llevarla a término, dependiendo del usuario que la solicita, del modo en el que lo hace, etcétera. En otras palabras, el sistema ha de adaptar su comportamiento a tales elementos mutables (o dinámicos) de la interacción. Dos características adicionales son requeridas a dicha adaptación: i) el usuario no ha de percibir que el sistema dedica recursos (temporales o computacionales) a realizar tareas distintas a las que aquél le solicita, y ii) el usuario no ha de dedicar esfuerzo alguno a proporcionar al sistema información adicional para llevar a cabo la interacción. Esto último implicaría una menor eficiencia de la interacción, puesto que los usuarios deberían dedicar parte de la misma a proporcionar información al sistema para su adaptación, sin ningún beneficio inmediato. En los sistemas de diálogo hablado propuestos en la literatura, se han propuesto diferentes estrategias para llevar a cabo la adaptación de los elementos del sistema a las diferentes condiciones de la interacción (tales como las características acústicas del habla de un usuario particular, o a las acciones a las que se ha referido con anterioridad). Sin embargo, no existe una estrategia fija para proceder a dicha adaptación, sino que las mismas no suelen guardar una relación entre sí. En este sentido, cada una de ellas tiene en cuenta distintas fuentes de información, la cual es tratada de manera diferente en función de las características de la adaptación buscada. Teniendo en cuenta lo anterior, las contribuciones principales de esta Tesis son las siguientes: Definición de un marco de contextualización. Proponemos un criterio unificador que pueda cubrir cualquier estrategia de adaptación del comportamiento de un sistema de diálogo a las condiciones de la interacción (esto es, el contexto de la misma). En nuestra definición teórica del marco de contextualización consideramos el contexto del sistema como todas aquellas fuentes de variabilidad presentes en cualquier instante de la interacción, ya estén relacionadas con el entorno en el que tiene lugar la interacción, ya dependan del agente humano que se dirige al sistema en cada momento. Nuestra propuesta se basa en tres aspectos que cualquier estrategia de contextualización debería cumplir: plasticidad (es decir, el sistema ha de ser capaz de modificar su comportamiento de la manera más proactiva posible, teniendo en cuenta las condiciones en las que tiene lugar la interacción), adaptabilidad (esto es, el sistema ha de ser capaz de considerar la información oportuna en cada instante, ya dependa del entorno o del usuario, de tal manera que adecúe su comportamiento de manera eficaz a las condiciones mencionadas), y transparencia (que implica que el sistema ha de desarrollar las tareas relacionadas con la contextualización de tal manera que el usuario no perciba la manera en que dichas tareas se llevan a cabo, ni tampoco deba proporcionar al sistema con información adicional alguna). De manera adicional, incluiremos en el marco propuesto el aspecto de la generalidad: las características del marco de contextualización han de ser portables a cualquier sistema de diálogo, con independencia de la solución propuesta en los mismos para gestionar el diálogo. Una vez hemos definido las características de alto nivel de nuestro marco de contextualización, proponemos dos estrategias de aplicación del mismo a un sistema de diálogo hablado. Nos centraremos en dos aspectos de la interacción a adaptar: los modelos empleados en el reconocimiento de habla, y la incorporación de información específica de cada usuario en el flujo de diálogo. Uno de los módulos de un sistema de diálogo más susceptible de ser contextualizado es el sistema de reconocimiento de habla. Este módulo hace uso de varios modelos para generar una hipótesis de reconocimiento a partir de la señal de habla. En general, un sistema de reconocimiento emplea dos tipos de modelos: uno acústico (que modela cada uno de los fonemas considerados por el reconocedor) y uno lingüístico (que modela las secuencias de palabras que tienen sentido desde el punto de vista de la interacción). En este trabajo contextualizamos el modelo lingüístico del reconocedor de habla, de tal manera que tenga en cuenta la información proporcionada por el usuario, tanto en su intervención actual como en las previas. Estas intervenciones contienen información (semántica y/o discursiva) que puede contribuir a un mejor reconocimiento de las subsiguientes intervenciones del usuario. La estrategia de contextualización propuesta consiste en una adaptación dinámica del modelo de lenguaje empleado en el reconocedor de habla. Dicha adaptación se lleva a cabo mediante una interpolación lineal entre diferentes modelos. En lugar de entrenar los mejores pesos de interpolación, proponemos hacer los mismos dependientes de las condiciones actuales de cada diálogo. El propio sistema obtendrá estos pesos como función de la disponibilidad y relevancia de las diferentes fuentes de información disponibles, tales como los conceptos semánticos extraídos a partir de la intervención del usuario, o las acciones que el mismo desea ejecutar. Uno de los aspectos más comúnmente analizados en la investigación de la Interacción Persona-Máquina es la inclusión de las características específicas de cada usuario en las estructuras de información empleadas por el sistema. El objetivo es tener en cuenta los aspectos que diferencian a cada usuario, de tal manera que el sistema pueda ofrecer a cada uno de ellos el servicio más apropiado (o un mismo servicio, pero de la manera más adecuada a cada usuario). Podemos considerar esta estrategia como una contextualización dependiente del usuario. En este trabajo proponemos la definición de un modelo de usuario que contenga toda la información relativa a cada usuario, que pueda ser potencialmente utilizada por el sistema en un momento determinado de la interacción. En particular, analizaremos aquellas acciones que cada usuario decide ejecutar a lo largo de sus diálogos con el sistema. Nuestro objetivo es determinar cuáles de dichas acciones se convierten en las preferencias de cada usuario. La información de cada usuario quedará representada mediante un vector de características, cada una de las cuales tendrá asociado un valor de confianza. Con ambos elementos proponemos una definición probabilística de una preferencia de uso, como aquella acción cuya verosimilitud es mayor que la del resto de acciones solicitadas por el usuario. A fin de incluir la información dependiente de usuario en el flujo de diálogo, llevamos a cabo una modificación de las estructuras de información en las que se apoya el gestor de diálogo para recuperar información necesaria para resolver ciertos diálogos. En dicha modificación las preferencias de cada usuario pasarán a ser una fuente adicional de información contextual, que será tenida en cuenta por el sistema en aras de una interacción más eficiente (puesto que la nueva fuente de información contribuirá a reducir la necesidad del sistema de solicitar al usuario información adicional, dando lugar en consecuencia a una reducción del número de intervenciones necesarias para llevar a cabo una acción determinada). Para determinar los beneficios de las aplicaciones del marco de contextualización propuesto, llevamos a cabo una evaluación de un sistema de diálogo que incluye las estrategias mencionadas. Hemos recogido diversas métricas, tanto objetivas como subjetivas, que nos permiten determinar las mejoras aportadas por un sistema contextualizado en comparación con el sistema sin contextualizar. De igual manera, hemos recogido las opiniones de los participantes en la evaluación acerca de su percepción del comportamiento del sistema, y de su capacidad de adaptación a las condiciones concretas de cada interacción.

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

MEIA SYSTEMS: Membrane Encrypted Information Applications Systems

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined,developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is a new model that deals with encrypted information which provides security the membrane systems communication. Moreover we find non deterministic and random applications in nature that are suitable to MEIA systems. The inherent parallelism and non determinism make this applications perfect object to implement MEIA systems.

Simulating accepting networks of evolutionary processors with filtered connections by accepting evolutionary P systems

In this work, we propose a variant of P system based on the rewriting of string-objects by means of evolutionary rules. The membrane structure of such a P system seems to be a very natural tool for simulating the filters in accepting networks of evolutionary processors with filtered connections. We discuss an informal construction supporting this simulation. A detailed proof is to be considered in an extended version of this work.

Influence of the composition of natural gas-hydrogen blends (HCNG) on performance an CO2 emissions of a spark ignition engine

Addition of hydrogen to natural gas could be a short-term alternative to nowadays fossil fuels as the emissions of greenhouse gases may be reduced. The aim of this study is to evaluate the performance and emissions of a park ignition engine fuelled with pure natural gas, pure hydrogen and different blends of hydrogen and natural gas (HCNG). The increase of the hydrogen fraction leads to variations in the cylinder pressure and CO2 emissions. In this work, a combustion model based on thermodynamic equations is used considering separated zones for the burned and unburned gases. The results show that the maximum cylinder pressure gets higher as the fraction of hydrogen in the blend increases. The presence of hydrogen in the blend leads to a drecrease in the CO2 emissions. Due to hydrogen properties, leaner fuel-air mixtures can be used along with the appropiate spark timing, leading to an engine emissions improvement without a performance worsening.

Modelo basado en técnicas de procesamiento de lenguaje natural para extraer y anotar información de publicaciones científicas

La rápida evolución experimentada en los últimos años por las tecnologías de Internet ha estimulado la proliferación de recursos software en varias disciplinas científicas, especialmente en bioinformática. En la mayoría de los casos, la tendencia actual es publicar dichos recursos como servicios accesibles libremente a través de Internet, utilizando tecnologías y patrones de diseño definidos para la implementación de Arquitecturas Orientadas a Servicios (SOA). La combinación simultánea de múltiples servicios dentro de un mismo flujo de trabajo abre la posibilidad de crear aplicaciones potencialmente más útiles y complejas. La integración de dichos servicios plantea grandes desafíos, tanto desde un punto de vista teórico como práctico, como por ejemplo, la localización y acceso a los recursos disponibles o la coordinación entre ellos. En esta tesis doctoral se aborda el problema de la identificación, localización, clasificación y acceso a los recursos informáticos disponibles en Internet. Con este fin, se ha definido un modelo genérico para la construcción de índices de recursos software con información extraída automáticamente de artículos de la literatura científica especializada en un área. Este modelo consta de seis fases que abarcan desde la selección de las fuentes de datos hasta el acceso a los índices creados, pasando por la identificación, extracción, clasificación y “curación” de la información relativa a los recursos. Para verificar la viabilidad, idoneidad y eficiencia del modelo propuesto, éste ha sido evaluado en dos dominios científicos diferentes—la BioInformática y la Informática Médica—dando lugar a dos índices de recursos denominados BioInformatics Resource Inventory (BIRI) y electronic-Medical Informatics Repository of Resources(e-MIR2) respectivamente. Los resultados obtenidos de estas aplicaciones son presentados a lo largo de la presente tesis doctoral y han dado lugar a varias publicaciones científicas en diferentes revistas JCR y congresos internacionales. El impacto potencial y la utilidad de esta tesis doctoral podrían resultar muy importantes teniendo en cuenta que, gracias a la generalidad del modelo propuesto, éste podría ser aplicado en cualquier disciplina científica. Algunas de las líneas de investigación futuras más relevantes derivadas de este trabajo son esbozadas al final en el último capítulo de este libro. ABSTRACT The rapid evolution experimented in the last years by the Internet technologies has stimulated the proliferation of heterogeneous software resources in most scientific disciplines, especially in the bioinformatics area. In most cases, current trends aim to publish those resources as services freely available over the Internet, using technologies and design patterns defined for the implementation of Service-Oriented Architectures (SOA). Simultaneous combination of various services into the same workflow opens the opportunity of creating more complex and useful applications. Integration of services raises great challenges, both from a theoretical to a practical point of view such as, for instance, the location and access to the available resources or the orchestration among them. This PhD thesis deals with the problem of identification, location, classification and access to informatics resources available over the Internet. On this regard, a general model has been defined for building indexes of software resources, with information extracted automatically from scientific articles from the literature specialized in the area. Such model consists of six phases ranging from the selection of data sources to the access to the indexes created, covering the identification, extraction, classification and curation of the information related to the software resources. To verify the viability, feasibility and efficiency of the proposed model, it has been evaluated in two different scientific domains—Bioinformatics and Medical Informatics—producing two resources indexes named BioInformatics Resources Inventory (BIRI) and electronic-Medical Informatics Repository of Resources (e-MIR2) respectively. The results and evaluation of those systems are presented along this PhD thesis, and they have produced different scientific publications in several JCR journals and international conferences. The potential impact and utility of this PhD thesis could be of great relevance considering that, thanks to the generality of the proposed model, it could be successfully extended to any scientific discipline. Some of the most relevant future research lines derived from this work are outlined at the end of this book.