Dynamic optimization of track components to minimize rail corrugation

In this paper, the influence on corrugation of the most significant track parameters has been examined. After this parametric study, the optimization of the track parameters to minimize the undulatory wear growth has been achieved. Finally, the influence of the dispersion of the track and contact parameters on corrugation growth has been studied. A method has been developed to obtain an optimal solution of the track parameters which minimizes corrugation growth, thus ensuring that this solution remains optimum despite dispersion of track parameters and wheel-rail contact uncertainties. This work is based on the computer application RACING (RAil Corrugation INitiation and Growth) which has been developed by the authors to predict rail corrugation features.

Multiple table factor analysis applied to the higher education competences

Due to the recent implantation of the Bologna process, the definition of competences in Higher Education is an important matter that deserves special attention and requires a detailed analysis. For that reason, we study the importance given to severa! competences for the professional activity and the degree to which these competences have been achieved through the received education. The answers include also competences observed in two periods of time given by individuals of multiple characteristics. In this context and in order to obtain synthesized results, we propose the use of Multiple Table Factor Analysis. Through this analysis, individuals are described by severa! groups, showing the most important variability factors of the individuals and allowing the analysis of the common structure ofthe different data tables. The obtained results will allow us finding out the existence or absence of a common structure in the answers of the various data tables, knowing which competences have similar answer structure in the groups of variables, as well as characterizing those answers through the individuals.

Use of generalised additive models to categorise continuous variables in clinical prediction

13 P.

Skeleton based visual pattern recognition. Applications to tabletop interaction

211 p. :il.

Euskarazko ahozko grabazioen edukia egiaztatzeko sistema

[EU]Ahots teknologiaren garapenaren gorakadak, hizketan minusbaliotasunen bat duten pertsonen eguneroko bizitza ahalik eta erosoena egitearen saiakerarekin batera, Aholab ikerkuntza taldea ZURE TTS proiektua garatzera eraman du, proiektuaren helburua ahots minusbaliotasun batez jota dauden edo ahotsa guztiz galdu duten pertsonentzat hizketa sintetizadore bat garatzea delarik. Ahots sintetizatua lortzeko, ahots emaileek grabatutako esaldiez osatutako ahots naturaleko corpus bat hartzen da oinarritzat. Sintesi prozesua ahalik eta kalitate altuenekoa izateko, nahitaezkoa da datu basean gordeta dagoen ahotsa egokia izatea, eta horregatik, burutuko den proiektuak grabazioen edukiaren egiaztatzaile bat garatzea du helburu, erabiltzaileak irakurritako esaldiak zuzenak diren edo ez egiaztatzen dituena, horrela ahots sintetizatuaren kalitatea bermatuz.

Compliance verification methodology for renewable generation integration. Application to island power grids

261 p.

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.

Distribution theory and fundamental solutions of differential operators

The objective of this dissertation is to study the theory of distributions and some of its applications. Certain concepts which we would include in the theory of distributions nowadays have been widely used in several fields of mathematics and physics. It was Dirac who first introduced the delta function as we know it, in an attempt to keep a convenient notation in his works in quantum mechanics. Their work contributed to open a new path in mathematics, as new objects, similar to functions but not of their same nature, were being used systematically. Distributions are believed to have been first formally introduced by the Soviet mathematician Sergei Sobolev and by Laurent Schwartz. The aim of this project is to show how distribution theory can be used to obtain what we call fundamental solutions of partial differential equations.