Semi-automatic generation of learning domain modules for technology supported learning systems

In a time when Technology Supported Learning Systems are being widely used, there is a lack of tools that allows their development in an automatic or semi-automatic way. Technology Supported Learning Systems require an appropriate Domain Module, ie. the pedagogical representation of the domain to be mastered, in order to be effective. However, content authoring is a time and effort consuming task, therefore, efforts in automatising the Domain Module acquisition are necessary.Traditionally, textbooks have been used as the main mechanism to maintain and transmit the knowledge of a certain subject or domain. Textbooks have been authored by domain experts who have organised the contents in a means that facilitate understanding and learning, considering pedagogical issues.Given that textbooks are appropriate sources of information, they can be used to facilitate the development of the Domain Module allowing the identification of the topics to be mastered and the pedagogical relationships among them, as well as the extraction of Learning Objects, ie. meaningful fragments of the textbook with educational purpose.Consequently, in this work DOM-Sortze, a framework for the semi-automatic construction of Domain Modules from electronic textbooks, has been developed. DOM-Sortze uses NLP techniques, heuristic reasoning and ontologies to fulfill its work. DOM-Sortze has been designed and developed with the aim of automatising the development of the Domain Module, regardless of the subject, promoting the knowledge reuse and facilitating the collaboration of the users during the process.

Development of catalytic methane reforming systems integrating hydrogen selective PdCu membrane modules

En la presente tesis doctoral se ha estudiado la integración del proceso de producción de hidrógeno con su purificación mediante el empleo de membranas selectivas de hidrógeno. La producción de hidrógeno se realiza empleando catalizadores no convencionales de níquel soportado sobre magnesia y alúmina en un reactor catalítico. Se analiza la actividad de los catalizadores y la producción de hidrógeno mediante distintos procesos con metano como son la oxidación parcial catalítica (OPC), OPC húmeda y reformadoLa purificación de hidrógeno se realiza en un módulo provisto de una membrana selectiva de hidrógeno de PdCu depositado en un soporte poroso cerámico. Una vez optimizada su preparación mediante deposición no electrolítica se caracterizan. Para ello se determina su permeabilidad a distintas temperaturas y realizando ciclos térmicos en atmósferas inerte y de hidrógeno, que puede fragilizar el metal. Una vez preparados los catalizadores y las membranas se integran los dos sistemas y se determinan los parámetros de operación óptimos como la presión de la línea de alimentación y el caudal de gas de arrastre en el módulo de membrana. Ambos parámetros se optimizan para lograr la máxima recuperación de hidrógeno en el módulo de membrana. Por últimos se realizan ensayos completos de producción y purificación, que permiten observar el rendimiento del sistema y también el efecto que los compuestos de la mezcla compleja alimentada a las membranas tienen en su comportamiento. Para concluir la integración de procesos se realizan ensayos añadiendo azufre de forma que el sistema sea más similar al proceso real. Esto permite también analizar el efecto del azufre tanto en los catalizadores como en las membranas.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals

A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90 degrees. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMB) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each sholder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figute eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activatoin. From these results, we surmise that both "discrete-rhythmic movements" such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the vertical and the other aligned with the horizontal.

LiDom builder: Automatising the construction of multilingual domain modules

136 p.

The Metabolic Core and Catalytic Switches Are Fundamental Elements in the Self-Regulation of the Systemic Metabolic Structure of Cells

19 p.

Communities in complex networks

The study of complex networks has attracted the attention of the scientific community for many obvious reasons. A vast number of systems, from the brain to ecosystems, power grid, and the Internet, can be represented as large complex networks, i.e, assemblies of many interacting components with nontrivial topological properties. The link between these components can describe a global behaviour such as the Internet traffic, electricity supply service, market trend, etc. One of the most relevant topological feature of graphs representing these complex systems is community structure which aims to identify the modules and, possibly, their hierarchical organization, by only using the information encoded in the graph topology. Deciphering network community structure is not only important in order to characterize the graph topologically, but gives some information both on the formation of the network and on its functionality.

Parodia épica y gastronomía: el Ἀττικὸν Δεῖπνον de Matrón de Pítane

[ES] En la antigua Grecia existió una floreciente literatura de tema gastronómico, poco conocida porque sólo se ha conservado una pequeña parte de ella. Uno de los escasos ejemplos que conservamos es el Ἀττικὸν Δεῖπνον de Matrón de Pítane, que, por medio de la parodia de los poemas homéricos, describe un pantagruélico banquete en el que predominan los platos de pescado. El anfitrión, los comensales, incluso los alimentos servidos adoptan las maneras de los héroes y los dioses, creándose un profundo contraste entre la forma seria y el contenido ligero, con el único propósito de divertir.

Towards multilingual domain module acquisition

Máster y Doctorado en Sistemas Informáticos Avanzados, Informatika Fakultatea - Facultad de Informática

Design and evaluation of an optical switching node

[EN]For a good development of elastic optical networks, the design of flexible optical switching nodes is required. This work analyses the previously proposed flexible architectures and, based on the most appropriate, which is the Architecture on Demand (AoD), proposes a specific configuration of the node that includes spatial and spectral switching and the wavelength conversion functionality with a low blocking probability and the minimum amount of modules; the characteristics of the traffic that the designed node is able to cope with are specified in the last chapter. An evaluation of the designed node is also done, and, compared to the other architectures, it is shown that the Architecture on Demand gives better results than others and that it has a higher potential for future developments.

Algoritmos multi-objetivos para la optimización de una secuencia de matrices generadoras en computación cuántica topológica

Quantum Computing is a relatively modern field which simulates quantum computation conditions. Moreover, it can be used to estimate which quasiparticles would endure better in a quantum environment. Topological Quantum Computing (TQC) is an approximation for reducing the quantum decoherence problem1, which is responsible for error appearance in the representation of information. This project tackles specific instances of TQC problems using MOEAs (Multi-objective Optimization Evolutionary Algorithms). A MOEA is a type of algorithm which will optimize two or more objectives of a problem simultaneously, using a population based approach. We have implemented MOEAs that use probabilistic procedures found in EDAs (Estimation of Distribution Algorithms), since in general, EDAs have found better solutions than ordinary EAs (Evolutionary Algorithms), even though they are more costly. Both, EDAs and MOEAs are population-based algorithms. The objective of this project was to use a multi-objective approach in order to find good solutions for several instances of a TQC problem. In particular, the objectives considered in the project were the error approximation and the length of a solution. The tool we used to solve the instances of the problem was the multi-objective framework PISA. Because PISA has not too much documentation available, we had to go through a process of reverse-engineering of the framework to understand its modules and the way they communicate with each other. Once its functioning was understood, we began working on a module dedicated to the braid problem. Finally, we submitted this module to an exhaustive experimentation phase and collected results.

Insights into mechanism kinematics for protein motion simulation

Background: The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein's movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost. Results: In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion. Conclusions: The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.

Simulación de redes para el análisis de rendimiento en enlaces de datos bajo técnicas ARQ.

[ES]Hoy en día la simulación de elementos de red y de redes completas supone una herramienta esencial para las telecomunicaciones, pudiendo ayudar en el dimensionado y el análisis de las mismas, así como en el estudio de problemáticas y escenarios que puedan darse. Uno de estos puntos de gran interés para el estudio es ARQ, y más concretamente, las técnicas de Stop & Wait y Go Back N. Así pues, nace dentro del grupo de investigación NQAS la necesidad de elaborar un conjunto de simulaciones sobre estas técnicas, con especial interés sobre la recolección de datos relacionados con el rendimiento de las mismas. Se pretende diseñar y simular una serie de escenarios de red partiendo de módulos simples con funciones de envío, conmutación y recepción de paquetes, escalándolo gradualmente para aumentar las funcionalidades de los mismos, hasta conseguir el diseño e implementación de redes basadas en dicha arquitectura cuyos enlaces estén bajo la cobertura de instancias de protocolo ARQ (Stop & Wait, Go Back N). Se tratará el resultado de las simulaciones mediante la recolección de estadísticas relacionadas con rendimiento y desempeño de las técnicas.

A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.