The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Increasing the Intelligence of Virtual Sales Assistants through Knowledge Modeling Techniques

Shopping agents are web-based applications that help consumers to find appropriate products in the context of e-commerce. In this paper we argue about the utility of advanced model-based techniques that recently have been proposed in the fields of Artificial Intelligence and Knowledge Engineering, in order to increase the level of support provided by this type of applications. We illustrate this approach with a virtual sales assistant that dynamically configures a product according to the needs and preferences of customers.

Introducing non-linear analysis into sustained speech characterization to improve sleep apnea detection

We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients' voices, and to think about tools which could be used to improve short-time analysis.

Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.

A multi-level analysis of innovation diffusion: The case of solar photovoltaic systems in Germany and the disillusion of grid parity

¿Suministrarán las fuentes de energía renovables toda la energía que el mundo necesita algún día? Algunos argumentan que sí, mientras que otros dicen que no. Sin embargo, en algunas regiones del mundo, la producción de electricidad a través de fuentes de energía renovables ya está en una etapa prometedora de desarrollo en la que su costo de generación de electricidad compite con fuentes de electricidad convencionales, como por ejemplo la paridad de red. Este logro ha sido respaldado por el aumento de la eficiencia de la tecnología, la reducción de los costos de producción y, sobre todo, los años de intervenciones políticas de apoyo financiero. La difusión de los sistemas solares fotovoltaicos (PV) en Alemania es un ejemplo relevante. Alemania no sólo es el país líder en términos de capacidad instalada de sistemas fotovoltaicos (PV) en todo el mundo, sino también uno de los países pioneros donde la paridad de red se ha logrado recientemente. No obstante, podría haber una nube en el horizonte. La tasa de difusión ha comenzado a declinar en muchas regiones. Además, las empresas solares locales – que se sabe son importantes impulsores de la difusión – han comenzado a enfrentar dificultades para manejar sus negocios. Estos acontecimientos plantean algunas preguntas importantes: ¿Es ésta una disminución temporal en la difusión? ¿Los adoptantes continuarán instalando sistemas fotovoltaicos? ¿Qué pasa con los modelos de negocio de las empresas solares locales? Con base en el caso de los sistemas fotovoltaicos en Alemania a través de un análisis multinivel y dos revisiones literarias complementarias, esta tesis doctoral extiende el debate proporcionando riqueza múltiple de datos empíricos en un conocimiento de contexto limitado. El primer análisis se basa en la perspectiva del adoptante, que explora el nivel "micro" y el proceso social que subyace a la adopción de los sistemas fotovoltaicos. El segundo análisis es una perspectiva a nivel de empresa, que explora los modelos de negocio de las empresas y sus roles impulsores en la difusión de los sistemas fotovoltaicos. El tercero análisis es una perspectiva regional, la cual explora el nivel "meso", el proceso social que subyace a la adopción de sistemas fotovoltaicos y sus técnicas de modelado. Los resultados incluyen implicaciones tanto para académicos como políticos, no sólo sobre las innovaciones en energía renovable relativas a la paridad de red, sino también, de manera inductiva, sobre las innovaciones ambientales impulsadas por las políticas que logren la competitividad de costes. ABSTRACT Will renewable energy sources supply all of the world energy needs one day? Some argue yes, while others say no. However, in some regions of the world, the electricity production through renewable energy sources is already at a promising stage of development at which their electricity generation costs compete with conventional electricity sources’, i.e., grid parity. This achievement has been underpinned by the increase of technology efficiency, reduction of production costs and, above all, years of policy interventions of providing financial support. The diffusion of solar photovoltaic (PV) systems in Germany is an important frontrunner case in point. Germany is not only the top country in terms of installed PV systems’ capacity worldwide but also one of the pioneer countries where the grid parity has recently been achieved. However, there might be a cloud on the horizon. The diffusion rate has started to decline in many regions. In addition, local solar firms – which are known to be important drivers of diffusion – have started to face difficulties to run their businesses. These developments raise some important questions: Is this a temporary decline on diffusion? Will adopters continue to install PV systems? What about the business models of the local solar firms? Based on the case of PV systems in Germany through a multi-level analysis and two complementary literature reviews, this PhD Dissertation extends the debate by providing multiple wealth of empirical details in a context-limited knowledge. The first analysis is based on the adopter perspective, which explores the “micro” level and the social process underlying the adoption of PV systems. The second one is a firm-level perspective, which explores the business models of firms and their driving roles in diffusion of PV systems. The third one is a regional perspective, which explores the “meso” level, i.e., the social process underlying the adoption of PV systems and its modeling techniques. The results include implications for both scholars and policymakers, not only about renewable energy innovations at grid parity, but also in an inductive manner, about policy-driven environmental innovations that achieve the cost competiveness.

Modeling of dangerous phenomena and innovative techniques for hazard evaluation and risk mitigation

Society is frequently exposed to and threatened by dangerous phenomena in many parts of the world. Different types of such phenomena require specific actions for proper risk management, from the stages of hazard identification to those of mitigation (including monitoring and early-warning) and/or reduction. The understanding of both predisposing factors and triggering mechanisms of a given danger and the prediction of its evolution from the source to the overall affected zone are relevant issues that must be addressed to properly evaluate a given hazard.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Assessment of CTF boiling transition and critical heat flux modeling capabilities using the OECD/NRC BFBT and PSBT benchmark databases

The need to refine models for best-estimate calculations, based on good-quality experimental data, has been expressed in many recent meetings in the field of nuclear applications. The modeling needs arising in this respect should not be limited to the currently available macroscopic methods but should be extended to next-generation analysis techniques that focus on more microscopic processes. One of the most valuable databases identified for the thermalhydraulics modeling was developed by the Nuclear Power Engineering Corporation (NUPEC), Japan. From 1987 to 1995, NUPEC performed steady-state and transient critical power and departure from nucleate boiling (DNB) test series based on the equivalent full-size mock-ups. Considering the reliability not only of the measured data, but also other relevant parameters such as the system pressure, inlet sub-cooling and rod surface temperature, these test series supplied the first substantial database for the development of truly mechanistic and consistent models for boiling transition and critical heat flux. Over the last few years the Pennsylvania State University (PSU) under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC) has prepared, organized, conducted and summarized the OECD/NRC Full-size Fine-mesh Bundle Tests (BFBT) Benchmark. The international benchmark activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and Japan Nuclear Energy Safety (JNES) organization, Japan. Consequently, the JNES has made available the Boiling Water Reactor (BWR) NUPEC database for the purposes of the benchmark. Based on the success of the OECD/NRC BFBT benchmark the JNES has decided to release also the data based on the NUPEC Pressurized Water Reactor (PWR) subchannel and bundle tests for another follow-up international benchmark entitled OECD/NRC PWR Subchannel and Bundle Tests (PSBT) benchmark. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known subchannel code COBRA-TF, namely CTF, to the critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks

A region based approach to background modeling in a wavelet multi-resolution framework

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-resolution framework. Based on a segmentation of the background, characterization is made for each region independently as a mixture of K Gaussian modes, considering the model of the approximation and detail coefficients at the different wavelet decomposition levels. Background region characterization is updated along time, and the detection of elements of interest is carried out computing the distance between background region models and those of each incoming image in the sequence. The inclusion of the context in the modeling scheme through each region characterization makes the model robust, being able to support not only gradual illumination and long-term changes, but also sudden illumination changes and the presence of strong shadows in the scene

An Interval-based Multiobjective Approach to Feature Subset Selection Using Joint Modeling of Objectives and Variables

This paper studies feature subset selection in classification using a multiobjective estimation of distribution algorithm. We consider six functions, namely area under ROC curve, sensitivity, specificity, precision, F1 measure and Brier score, for evaluation of feature subsets and as the objectives of the problem. One of the characteristics of these objective functions is the existence of noise in their values that should be appropriately handled during optimization. Our proposed algorithm consists of two major techniques which are specially designed for the feature subset selection problem. The first one is a solution ranking method based on interval values to handle the noise in the objectives of this problem. The second one is a model estimation method for learning a joint probabilistic model of objectives and variables which is used to generate new solutions and advance through the search space. To simplify model estimation, l1 regularized regression is used to select a subset of problem variables before model learning. The proposed algorithm is compared with a well-known ranking method for interval-valued objectives and a standard multiobjective genetic algorithm. Particularly, the effects of the two new techniques are experimentally investigated. The experimental results show that the proposed algorithm is able to obtain comparable or better performance on the tested datasets.

Efficient numerical methods for global linear instability. Analysis and modeling of non-orthogonal swept attachment-line boundary layer flow

The aim of this thesis is to study the mechanisms of instability that occur in swept wings when the angle of attack increases. For this, a simplified model for the a simplified model for the non-orthogonal swept leading edge boundary layer has been used as well as different numerical techniques in order to solve the linear stability problem that describes the behavior of perturbations superposed upon this base flow. Two different approaches, matrix-free and matrix forming methods, have been validated using direct numerical simulations with spectral resolution. In this way, flow instability in the non-orthogonal swept attachment-line boundary layer is addressed in a linear analysis framework via the solution of the pertinent global (Bi-Global) PDE-based eigenvalue problem. Subsequently, a simple extension of the extended G¨ortler-H¨ammerlin ODEbased polynomial model proposed by Theofilis, Fedorov, Obrist & Dallmann (2003) for orthogonal flow, which includes previous models as particular cases and recovers global instability analysis results, is presented for non-orthogonal flow. Direct numerical simulations have been used to verify the stability results and unravel the limits of validity of the basic flow model analyzed. The effect of the angle of attack, AoA, on the critical conditions of the non-orthogonal problem has been documented; an increase of the angle of attack, from AoA = 0 (orthogonal flow) up to values close to _/2 which make the assumptions under which the basic flow is derived questionable, is found to systematically destabilize the flow. The critical conditions of non-orthogonal flows at 0 _ AoA _ _/2 are shown to be recoverable from those of orthogonal flow, via a simple analytical transformation involving AoA. These results can help to understand the mechanisms of destabilization that occurs in the attachment line of wings at finite angles of attack. Studies taking into account variations of the pressure field in the basic flow or the extension to compressible flows are issues that remain open. El objetivo de esta tesis es estudiar los mecanismos de la inestabilidad que se producen en ciertos dispositivos aerodinámicos cuando se aumenta el ángulo de ataque. Para ello se ha utilizado un modelo simplificado del flujo de base, así como diferentes técnicas numéricas, con el fin de resolver el problema de estabilidad lineal asociado que describe el comportamiento de las perturbaciones. Estos métodos; sin y con formación de matriz, se han validado utilizando simulaciones numéricas directas con resolución espectral. De esta manera, la inestabilidad del flujo de capa límite laminar oblicuo entorno a la línea de estancamiento se aborda en un marco de análisis lineal por medio del método Bi-Global de resolución del problema de valores propios en derivadas parciales. Posteriormente se propone una extensión simple para el flujo no-ortogonal del modelo polinomial de ecuaciones diferenciales ordinarias, G¨ortler-H¨ammerlin extendido, propuesto por Theofilis et al. (2003) para el flujo ortogonal, que incluye los modelos previos como casos particulares y recupera los resultados del analisis global de estabilidad lineal. Se han realizado simulaciones directas con el fin de verificar los resultados del análisis de estabilidad así como para investigar los límites de validez del modelo de flujo base utilizado. En este trabajo se ha documentado el efecto del ángulo de ataque AoA en las condiciones críticas del problema no ortogonal obteniendo que el incremento del ángulo de ataque, de AoA = 0 (flujo ortogonal) hasta valores próximos a _/2, en el cual las hipótesis sobre las que se basa el flujo base dejan de ser válidas, tiende sistemáticamente a desestabilizar el flujo. Las condiciones críticas del caso no ortogonal 0 _ AoA _ _/2 pueden recuperarse a partir del caso ortogonal mediante el uso de una transformación analítica simple que implica el ángulo de ataque AoA. Estos resultados pueden ayudar a comprender los mecanismos de desestabilización que se producen en el borde de ataque de las alas de los aviones a ángulos de ataque finitos. Como tareas pendientes quedaría realizar estudios que tengan en cuenta variaciones del campo de presión en el flujo base así como la extensión de éste al caso de flujos compresibles.

Modeling impact assessment of transport policies through a multiregional input-output integrated approach

El objetivo de esta investigación es desarrollar una metodología para estimar los potenciales impactos económicos y de transporte generados por la aplicación de políticas en el sector transporte. Los departamentos de transporte y otras instituciones gubernamentales relacionadas se encuentran interesadas en estos análisis debido a que son presentados comúnmente de forma errónea por la insuficiencia de datos o por la falta de metodologías adecuadas. La presente investigación tiene por objeto llenar este vacío haciendo un análisis exhaustivo de las técnicas disponibles que coincidan con ese propósito. Se ha realizado un análisis que ha identificado las diferencias cuando son aplicados para la valoración de los beneficios para el usuario o para otros efectos como aspectos sociales. Como resultado de ello, esta investigación ofrece un enfoque integrado que incluye un modelo Input-Output de múltiples regiones basado en la utilidad aleatoria (RUBMRIO), y un modelo de red de transporte por carretera. Este modelo permite la reproducción con mayor detalle y realismo del transporte de mercancías que por medio de su estructura sectorial identifica los vínculos de las compras y ventas inter-industriales dentro de un país utilizando los servicios del transporte de mercancías. Por esta razón, el modelo integrado es aplicable a diversas políticas de transporte. En efecto, el enfoque se ha aplicado para estudiar los efectos macroeconómicos regionales de la implementación de dos políticas diferentes en el sistema de transporte de mercancías de España, tales como la tarificación basada en la distancia recorrida por vehículo-kilómetro (€/km) aplicada a los vehículos del transporte de mercancías, y para la introducción de vehículos más largos y pesados de mercancías en la red de carreteras de España. El enfoque metodológico se ha evaluado caso por caso teniendo en cuenta una selección de la red de carreteras que unen las capitales de las regiones españolas. También se ha tenido en cuenta una dimensión económica a través de una tabla Input-Output de múltiples regiones (MRIO) y la base de datos de conteo de tráfico existente para realizar la validación del modelo. El enfoque integrado reproduce las condiciones de comercio observadas entre las regiones usando el sistema de transporte de mercancías por carretera, y que permite por comparación con los escenarios de políticas, determinar las contribuciones a los cambios distributivos y generativos. Así pues, el análisis estima los impactos económicos en cualquier región considerando los cambios en el Producto Interno Bruto (PIB) y el empleo. El enfoque identifica los cambios en el sistema de transporte a través de todos los caminos de la red de transporte a través de las medidas de efectividad (MOEs). Los resultados presentados en esta investigación proporcionan evidencia sustancial de que en la evaluación de las políticas de transporte, es necesario establecer un vínculo entre la estructura económica de las regiones y de los servicios de transporte. Los análisis muestran que para la mayoría de las regiones del país, los cambios son evidentes para el PIB y el empleo, ya que el comercio se fomenta o se inhibe. El enfoque muestra cómo el tráfico se desvía en ambas políticas, y también determina detalles de las emisiones de contaminantes en los dos escenarios. Además, las políticas de fijación de precios o de regulación de los sistemas de transporte de mercancías por carretera dirigidas a los productores y consumidores en las regiones promoverán transformaciones regionales afectando todo el país, y esto conduce a conclusiones diferentes. Así mismo, este enfoque integrado podría ser útil para evaluar otras políticas y otros países en todo el mundo. The purpose of this research is to develop a methodological approach aimed at assessing the potential economic and transportation impacts of transport policies. Transportation departments and other related government parties are interested in such analysis because it is commonly misrepresented for the insufficiency of data and suitable methodologies available. This research is directed at filling this gap by making a comprehensive analysis of the available techniques that match with that purpose. The differences when they are applied for the valuation of user benefits or for other impacts as social matters have been identified. As a result, this research presents an integrated approach which includes both a random utility-based multiregional Input-Output model (RUBMRIO), and a road transport network model. This model accounts for freight transport with more detail and realism because its commodity-based structure traces the linkages of inter-industry purchases and sales that use freight services within a given country. For this reason, the integrated model is applicable to various transport policies. In fact, the approach is applied to study the regional macroeconomic effects of implementing two different policies in the freight transport system of Spain, such as a distance-based charge in vehicle-kilometer (€/km) for Heavy Goods Vehicles (HGVs), and the introduction of Longer and Heavier Vehicles (LHVs) in the road network of Spain. The methodological approach has been evaluated on a case by case basis considering a selected road network of highways linking the capitals of the Spanish regions. It has also considered an economic dimension through a Multiregional Input Output Table (MRIO) and the existing traffic count database used in the model validation. The integrated approach replicates observed conditions of trade among regions using road freight transport systems that determine contributions to distributional and generative changes by comparison with policy scenarios. Therefore, the model estimates economic impacts in any given area by considering changes in Gross Domestic Product (GDP), employment (jobs), and in the transportation system across all paths of the transport network considering Measures of effectiveness (MOEs). The results presented in this research provide substantive evidence that in the assessment of transport policies it is necessary to establish a link between the economic structure of regions and the transportation services. The analysis shows that for most regions in the country, GDP and employment changes are noticeable when trade is encouraged or discouraged. This approach shows how traffic is diverted in both policies, and also provides details of the pollutant emissions in both scenarios. Furthermore, policies, such as pricing or regulation of road freight transportation systems, directed to producers and consumers in regions will promote different regional transformations across the country, and this lead to different conclusions. In addition, this integrated approach could be useful to assess other policies and countries worldwide.

FPLA: a modeling framework for describing flexible software product line architecture

Nowadays, Software Product Line (SPL) engineering [1] has been widely-adopted in software development due to the significant improvements that has provided, such as reducing cost and time-to-market and providing flexibility to respond to planned changes [2]. SPL takes advantage of common features among the products of a family through the systematic reuse of the core-assets and the effective management of variabilities across the products. SPL features are realized at the architectural level in product-line architecture (PLA) models. Therefore, suitable modeling and specification techniques are required to model variability. In fact, architectural variability modeling has become a challenge for SPLE due to the fact that PLA modeling requires not only modeling variability at the level of the external architecture configuration (see [3,4] literature reviews), but also at the level of internal specification of components [5]. In addition, PLA modeling requires preserving the traceability between features and PLAs. Finally, it is important to take into account that PLA modeling should guide architects in modeling the PLA core assets and variability, and in deriving the customized products. To deal with these needs, we present in this demonstration the FPLA Modeling Framework.

Knowledge representation tool for cognitiveprocesses modeling

In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions.