Problem-based learning supported by semantic techniques

Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behaviour of a dynamic system. The learner?s task then is to bridge the gap between their initial model, as their first attempt to represent the system, and the target models that provide solutions to that problem. We propose the use of semantic technologies and resources to help in bridging that gap by providing links to terminology and formal definitions, and matching techniques to allow learners to benefit from existing models.

Electrophoretic Deposition of Transparent ZnO Thin Films from Highly Stabilized Colloidal Suspensions

The parameters that control the stability of ZnO-nanoparticles suspensions and their deposition by electrophoretic deposition were studied, so as to organize the assembly and compaction of nanoparticles. The addition of cationic polyelectrolyte - Polyethylenimine (PEI) - with different molecular weights was investigated, in order to study their effectiveness and the influence of the molecular weight of the organic chain on suspensions dispersion. It was found that PEI with the highest molecular weight provided better dispersion conditions. Cathodic EPD was performed under previously optimized suspensions conditions and over electropolished stainless steel substrates. Experimental results showed that the EPD process in these conditions allows obtaining dense transparent ZnO thin films. Deposition times and intensities were optimized by analyzing the resulting thin films characteristics. Finally, the deposits were characterized by FE-SEM, AFM, and different spectroscopic techniques.

Reaction pathways in the solid state synthesis of multiferroic BiFeO3

The obtaining of multiferroic BiFeO3 as a pure single-phase product is particularly complex since the formation of secondary phases seems to be unavoidable. The process by which these secondary impurities are formed is studied by analyzing the diffusion and solid state reactivity of the Bi2O3?Fe2O3 system. Experimental evidence is reported which indicates that the progressive diffusion of Bi3+ ions into the Fe2O3 particles governs the solid state synthesis of the perovskite BiFeO3 phase. However a competition is established between the diffusion process which tends to complete the formation of BiFeO3, and the crystallization of stable Bi2Fe4O9 mullite crystals, which tend to block that formation reaction.

Modernidad y contextualidad regional : el caso de Emilio Duhart

Es recurrente lo transmitido en la mayoría de los escritos y por los estudiosos, en el sentido de que el Movimiento Moderno tanto en Latinoamérica como particularmente en Chile, ha sido un movimiento de carácter exógeno, con un alto contenido de desarraigo, sin considerar factores sociales, culturales ni territoriales y que en nuestro país ha sido impuesto como un acto de imitación sin más. Esta tesis pretende dar a conocer a través de la muestra de algunas obras realizadas desde las décadas del cuarenta hasta el sesenta, por un arquitecto reconocido internacionalmente como eximio representante del Movimiento Moderno, cómo esta visión reduccionista queda contradicha en estos trabajos, en los que exhibe notables acercamientos a la problemática social, política, territorial y regional. Con el objeto de precisar mejor el estudio, ha parecido pertinente entregar una visión genérica de nuestro variado territorio, su geografía, las raíces étnicas y su arquitectura; asimismo, se ha considerado importante la comprensión de los procesos históricos, y la forma cómo este movimiento se ha incorporado al territorio y su circunstancia, evoluciones y procesos, frente a los estilos y los acontecimientos políticos, sociales, culturales, guerras y terremotos, comprendidos tanto antes como durante su instauración, consolidación y puesta en marcha o desarrollo, desde las décadas de los veinte al sesenta. Analizaremos algunos ejemplos de obras diseñadas por el arquitecto Emilio Duhart, en diferentes épocas, comenzando por el Proyecto de fin de carrera, y otros tipos de proyectos; urbanos, institucionales, viviendas; que dan cuenta de situaciones y compromisos con la estructura, el territorio, la sociedad, la cultura o la producción local; que permitan comprobar el distanciamiento de este arquitecto con el Movimiento Moderno reduccionista. Además, se mostrarán comparativamente, obras de otros autores, de manera de conformar un cuerpo más sólido, donde se estima han involucrado aspectos similares de territorio, cultura y sociedad.

Multilingual Variation in the context of Linked Data

In this paper we present a revisited classification of term variation in the light of the Linked Data initiative. Linked Data refers to a set of best practices for publishing and connecting structured data on the Web with the idea of transforming it into a global graph. One of the crucial steps of this initiative is the linking step, in which datasets in one or more languages need to be linked or connected with one another. We claim that the linking process would be facilitated if datasets are enriched with lexical and terminological information. Being that the final aim, we propose a classification of lexical, terminological and semantic variants that will become part of a model of linguistic descriptions that is currently being proposed within the framework of the W3C Ontology-Lexica Community Group to enrich ontologies and Linked Data vocabularies. Examples of modeling solutions of the different types of variants are also provided.

Robustness and Recoverability in Transport Logistics

Abstract Transport is the foundation of any economy: it boosts economic growth, creates wealth, enhances trade, geographical accessibility and the mobility of people. Transport is also a key ingredient for a high quality of life, making places accessible and bringing people together. The future prosperity of our world will depend on the ability of all of its regions to remain fully and competitively integrated in the world economy. Efficient transport is vital in making this happen. Operations research can help in efficiently planning the design and operating transport systems. Planning and operational processes are fields that are rich in combinatorial optimization problems. These problems can be analyzed and solved through the application of mathematical models and optimization techniques, which may lead to an improvement in the performance of the transport system, as well as to a reduction in the time required for solving these problems. The latter aspect is important, because it increases the flexibility of the system: the system can adapt in a faster way to changes in the environment (i.e.: weather conditions, crew illness, failures, etc.). These disturbing changes (called disruptions) often enforce the schedule to be adapted. The direct consequences are delays and cancellations, implying many schedule adjustments and huge costs. Consequently, robust schedules and recovery plans must be developed in order to fight against disruptions. This dissertation makes contributions to two different fields: rail and air applications. Robust planning and recovery methods are presented. In the field of railway transport we develop several mathematical models which answer to RENFE’s (the major railway operator in Spain) needs: 1. We study the rolling stock assignment problem: here, we introduce some robust aspects in order to ameliorate some operations which are likely to fail. Once the rolling stock assignment is known, we propose a robust routing model which aims at identifying the train units’ sequences while minimizing the expected delays and human resources needed to perform the sequences. 2. It is widely accepted that the sequential solving approach produces solutions that are not global optima. Therefore, we develop an integrated and robust model to determine the train schedule and rolling stock assignment. We also propose an integrated model to study the rolling stock circulations. Circulations are determined by the rolling stock assignment and routing of the train units. 3. Although our aim is to develop robust plans, disruptions will be likely to occur and recovery methods will be needed. Therefore, we propose a recovery method which aims to recover the train schedule and rolling stock assignment in an integrated fashion all while considering the passenger demand. In the field of air transport we develop several mathematical models which answer to IBERIA’s (the major airline in Spain) needs: 1. We look at the airline-scheduling problem and develop an integrated approach that optimizes schedule design, fleet assignment and passenger use so as to reduce costs and create fewer incompatibilities between decisions. Robust itineraries are created to ameliorate misconnected passengers. 2. Air transport operators are continuously facing competition from other air operators and different modes of transport (e.g., High Speed Rail). Consequently, airline profitability is critically influenced by the airline’s ability to estimate passenger demands and construct profitable flight schedules. We consider multi-modal competition including airline and rail, and develop a new approach that estimates the demand associated with a given schedule; and generates airline schedules and fleet assignments using an integrated schedule design and fleet assignment optimization model that captures the impacts of schedule decisions on passenger demand.

MEDVIR: 3D visual interface applied to gene profile analisys.

The origins for this work arise in response to the increasing need for biologists and doctors to obtain tools for visual analysis of data. When dealing with multidimensional data, such as medical data, the traditional data mining techniques can be a tedious and complex task, even to some medical experts. Therefore, it is necessary to develop useful visualization techniques that can complement the expert’s criterion, and at the same time visually stimulate and make easier the process of obtaining knowledge from a dataset. Thus, the process of interpretation and understanding of the data can be greatly enriched. Multidimensionality is inherent to any medical data, requiring a time-consuming effort to get a clinical useful outcome. Unfortunately, both clinicians and biologists are not trained in managing more than four dimensions. Specifically, we were aimed to design a 3D visual interface for gene profile analysis easy in order to be used both by medical and biologist experts. In this way, a new analysis method is proposed: MedVir. This is a simple and intuitive analysis mechanism based on the visualization of any multidimensional medical data in a three dimensional space that allows interaction with experts in order to collaborate and enrich this representation. In other words, MedVir makes a powerful reduction in data dimensionality in order to represent the original information into a three dimensional environment. The experts can interact with the data and draw conclusions in a visual and quickly way.

Robust rolling stock under uncertain demand in rapid transit networks

This paper focuses on the railway rolling stock circulation problem in rapid transit networks where the known demand and train schedule must be met by a given fleet. In rapid transit networks the frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The previous circumstances and the reduced capacity of the depot stations and that the rolling stock is shared between the different lines, force the introduction of empty trains and a careful control on shunting operation. In practice the future demand is generally unknown and the decisions must be based on uncertain forecast. We have developed a stochastic rolling stock formulation of the problem. The computational experiments were developed using a commercial line of the Madrid suburban rail network operated by RENFE (The main Spanish operator of suburban trains of passengers). Comparing the results obtained by deterministic scenarios and stochastic approach some useful conclusions may be obtained.

Modeling and optimization of frequencies on congested bus lines

In this paper some mathematical programming models are exposed in order to set the number of services on a specified system of bus lines, which are intended to assist high demand levels which may arise because of the disruption of Rapid Transit services or during the celebration of massive events. By means of this model two types of basic magnitudes can be determined, basically: a) the number of bus units assigned to each line and b) the number of services that should be assigned to those units. In these models, passenger flow assignment to lines can be considered of the system optimum type, in the sense that the assignment of units and of services is carried out minimizing a linear combination of operation costs and total travel time of users. The models consider delays experienced by buses as a consequence of the get in/out of the passengers, queueing at stations and the delays that passengers experience waiting at the stations. For the case of a congested strategy based user optimal passenger assignment model with strict capacities on the bus lines, the use of the method of successive averages is shown.

Efficient adaptive methods based on adjoint equations and truncation error estimation for unstructured grids

El propósito de esta tesis es la implementación de métodos eficientes de adaptación de mallas basados en ecuaciones adjuntas en el marco de discretizaciones de volúmenes finitos para mallas no estructuradas. La metodología basada en ecuaciones adjuntas optimiza la malla refinándola adecuadamente con el objetivo de mejorar la precisión de cálculo de un funcional de salida dado. El funcional suele ser una magnitud escalar de interés ingenieril obtenida por post-proceso de la solución, como por ejemplo, la resistencia o la sustentación aerodinámica. Usualmente, el método de adaptación adjunta está basado en una estimación a posteriori del error del funcional de salida mediante un promediado del residuo numérico con las variables adjuntas, “Dual Weighted Residual method” (DWR). Estas variables se obtienen de la solución del problema adjunto para el funcional seleccionado. El procedimiento habitual para introducir este método en códigos basados en discretizaciones de volúmenes finitos involucra la utilización de una malla auxiliar embebida obtenida por refinamiento uniforme de la malla inicial. El uso de esta malla implica un aumento significativo de los recursos computacionales (por ejemplo, en casos 3D el aumento de memoria requerida respecto a la que necesita el problema fluido inicial puede llegar a ser de un orden de magnitud). En esta tesis se propone un método alternativo basado en reformular la estimación del error del funcional en una malla auxiliar más basta y utilizar una técnica de estimación del error de truncación, denominada _ -estimation, para estimar los residuos que intervienen en el método DWR. Utilizando esta estimación del error se diseña un algoritmo de adaptación de mallas que conserva los ingredientes básicos de la adaptación adjunta estándar pero con un coste computacional asociado sensiblemente menor. La metodología de adaptación adjunta estándar y la propuesta en la tesis han sido introducidas en un código de volúmenes finitos utilizado habitualmente en la industria aeronáutica Europea. Se ha investigado la influencia de distintos parámetros numéricos que intervienen en el algoritmo. Finalmente, el método propuesto se compara con otras metodologías de adaptación de mallas y su eficiencia computacional se demuestra en una serie de casos representativos de interés aeronáutico. ABSTRACT The purpose of this thesis is the implementation of efficient grid adaptation methods based on the adjoint equations within the framework of finite volume methods (FVM) for unstructured grid solvers. The adjoint-based methodology aims at adapting grids to improve the accuracy of a functional output of interest, as for example, the aerodynamic drag or lift. The adjoint methodology is based on the a posteriori functional error estimation using the adjoint/dual-weighted residual method (DWR). In this method the error in a functional output can be directly related to local residual errors of the primal solution through the adjoint variables. These variables are obtained by solving the corresponding adjoint problem for the chosen functional. The common approach to introduce the DWR method within the FVM framework involves the use of an auxiliary embedded grid. The storage of this mesh demands high computational resources, i.e. over one order of magnitude increase in memory relative to the initial problem for 3D cases. In this thesis, an alternative methodology for adapting the grid is proposed. Specifically, the DWR approach for error estimation is re-formulated on a coarser mesh level using the _ -estimation method to approximate the truncation error. Then, an output-based adaptive algorithm is designed in such way that the basic ingredients of the standard adjoint method are retained but the computational cost is significantly reduced. The standard and the new proposed adjoint-based adaptive methodologies have been incorporated into a flow solver commonly used in the EU aeronautical industry. The influence of different numerical settings has been investigated. The proposed method has been compared against different grid adaptation approaches and the computational efficiency of the new method has been demonstrated on some representative aeronautical test cases.

A methodology to compare dimensionality reduction algorithms in terms of loss of quality

Dimensionality Reduction (DR) is attracting more attention these days as a result of the increasing need to handle huge amounts of data effectively. DR methods allow the number of initial features to be reduced considerably until a set of them is found that allows the original properties of the data to be kept. However, their use entails an inherent loss of quality that is likely to affect the understanding of the data, in terms of data analysis. This loss of quality could be determinant when selecting a DR method, because of the nature of each method. In this paper, we propose a methodology that allows different DR methods to be analyzed and compared as regards the loss of quality produced by them. This methodology makes use of the concept of preservation of geometry (quality assessment criteria) to assess the loss of quality. Experiments have been carried out by using the most well-known DR algorithms and quality assessment criteria, based on the literature. These experiments have been applied on 12 real-world datasets. Results obtained so far show that it is possible to establish a method to select the most appropriate DR method, in terms of minimum loss of quality. Experiments have also highlighted some interesting relationships between the quality assessment criteria. Finally, the methodology allows the appropriate choice of dimensionality for reducing data to be established, whilst giving rise to a minimum loss of quality.

VR BioViewer - A new interactive-visual model to represent medical information

Virtual reality (VR) techniques to understand and obtain conclusions of data in an easy way are being used by the scientific community. However, these techniques are not used frequently for analyzing large amounts of data in life sciences, particularly in genomics, due to the high complexity of data (curse of dimensionality). Nevertheless, new approaches that allow to bring out the real important data characteristics, arise the possibility of constructing VR spaces to visually understand the intrinsic nature of data. It is well known the benefits of representing high dimensional data in tridimensional spaces by means of dimensionality reduction and transformation techniques, complemented with a strong component of interaction methods. Thus, a novel framework, designed for helping to visualize and interact with data about diseases, is presented. In this paper, the framework is applied to the Van't Veer breast cancer dataset is used, while oncologists from La Paz Hospital (Madrid) are interacting with the obtained results. That is to say a first attempt to generate a visually tangible model of breast cancer disease in order to support the experience of oncologists is presented.

MedVir: 3D visual interface applied to gene profile analysis

The use of data mining techniques for the gene profile discovery of diseases, such as cancer, is becoming usual in many researches. These techniques do not usually analyze the relationships between genes in depth, depending on the different variety of manifestations of the disease (related to patients). This kind of analysis takes a considerable amount of time and is not always the focus of the research. However, it is crucial in order to generate personalized treatments to fight the disease. Thus, this research focuses on finding a mechanism for gene profile analysis to be used by the medical and biologist experts. Results: In this research, the MedVir framework is proposed. It is an intuitive mechanism based on the visualization of medical data such as gene profiles, patients, clinical data, etc. MedVir, which is based on an Evolutionary Optimization technique, is a Dimensionality Reduction (DR) approach that presents the data in a three dimensional space. Furthermore, thanks to Virtual Reality technology, MedVir allows the expert to interact with the data in order to tailor it to the experience and knowledge of the expert.

Identification and dynamics of polyglycine II nanocrystals in Argiope trifasciata flagelliform silk

Spider silks combine a significant number of desirable characteristics in one material, including large tensile strength and strain at breaking, biocompatibility, and the possibility of tailoring their properties. Major ampullate gland silk (MAS) is the most studied silk and their properties are explained by a double lattice of hydrogen bonds and elastomeric protein chains linked to polyalanine β-nanocrystals. However, many basic details regarding the relationship between composition, microstructure and properties in silks are still lacking. Here we show that this relationship can be traced in flagelliform silk (Flag) spun by Argiope trifasciata spiders after identifying a phase consisting of polyglycine II nanocrystals. The presence of this phase is consistent with the dominant presence of the –GGX– and –GPG– motifs in its sequence. In contrast to the passive role assigned to polyalanine nanocrystals in MAS, polyglycine II nanocrystals can undergo growing/collapse processes that contribute to increase toughness and justify the ability of Flag to supercontract.

The variability and interdependence of spider viscid line tensile properties

True stress-true strain curves of naturally spun viscid line fibers retrieved directly from the spiral of orb-webs built by Argiope trifasciata spiders were measured using a novel methodology. This new procedure combines a method for removing the aqueous coating of the fibers and a technique that allows the accurate measurement of their cross sectional area. Comparison of the tensile behaviour of different samples indicates that naturally spun viscid lines show a large variability, comparable to that of other silks, such as major ampullate gland silk and silkworm silk. Nevertheless, application of a statistical analysis allowed identifying two independent parameters that underlie the variability and characterize the observed range of true stress-true strain curves. Combination of this result with previous mechanical and microstructural data suggested the assignment of these two independent effects to the degree of alignment of the protein chains and to the local relative humidity which, in turn, depends on the composition of the viscous coating and on the external environmental conditions.