Recognition and political accommodation: from regionalism to secessionism. The Catalan case

Having lived through a bloody civil war in the 1930s followed by four decades of General Franco’s dictatorship, the Spanish state carried out a transition to a democratic system at the end of the 1970s. The 1978 Constitution was the legal outcome of this transition process. Among other things, it established a territorial model – the so-called “Estado de las Autonomías” (State of Autonomous Communities) – which was designed to satisfy the historical demands for recognition and self-government of, above all, the citizens and institutions of Catalonia and the Basque Country .In recent years support for independence has increased in Catalonia. Different indicators show that pro-independence demands are endorsed by a majority of its citizens, as well as by most of the political parties and organizations that represent its civil society. This is a new phenomenon. Those in favour of independence had been in the minority throughout the 20th century. Nowadays, however, demands of a pro-autonomy and pro-federalist nature, which until recently had been dominant, have gradually lost public support in favour of demands for self-determination and secession. This paper analyses the massive increase in support for secession in Catalonia during the early years of the 21st century. After describing the different theories of secession in plurinational liberal democracies (section 1), we analyse Catalonia’s political evolution over the past decade focusing on the shortcomings with regard to constitutional recognition and accommodation displayed by the Spanish political system. The latter have been exacerbated by the reform process of Catalonia’s Statute of Autonomy (2006) and the subsequent judgement of Spain’s Constitutional Court regarding the aforementioned Statute (2010) (section 2). Finally, we present our conclusions by linking the Catalan case with theories of secession applied to plurinational contexts

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

Development of a microprocessor controlled energy harvester using a Peltier element

Nowadays it is necessary to research other types of energy alternatives and find the way to supply and save the energy we waste. The aim of the project consist of programming a microprocessor to measure if an oven radiates heat to the exterior, for the measure It is used a Peltier element that generates a voltage depending of the temperature difference between the oven and the air of the place where the oven is situated; The energy generated by the oven will be recollected in a condensor. A sensor will be used to know the exact measure. The second part of the project the main propose, is the development of a harvester. The microprocessor will use the voltage produced by the Peltier element to supply the electricity that it needs to work. A low power circuit and the appropriate software are needed to save the voltage generated.

El sistema de gestió documental de la Universitat de Barcelona en el marc de l'Administració electrònica: un element més per fomentar la millora contínua

[eng] We describe the project for the organization of the documentary management system at the University of Barcelona, which is inspired by the opportunities presented by the introduction of electronic administration. We stress the function of the documentary management system as an agent for promoting continuous innovation and improvement. We illustrate this vision with a description of the process of introducing the documentary management system in the area of research.

Application of fuzzy-rule-based postprocessing to correlation methods in pattern recognition

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

L'entorn sonor, un element educatiu de primer ordre

Este articulo pretende mostrar los avances e investigaciones màs recientes sobre el estudio del entorno en la formación del oído humano, entendiéndolo como una primera configuración pre-musical. Un breve repaso a los textos sagrados y míticos de los más variados tiempos y lugares nos permitirá reflexionar acerca de la enorme importancia del sonido en nuestra educación, tanto en el ámbito físico como emocional e intelectual. Se da un repaso a los efectos más clásicos del sonido sobre el cuerpo y la mente, a fin de entender la importancia de tomar conciencia de nuestro paisaje sonoro cotidiano. Posteriormente se explicita la evolución del oído humano en crecimiento del niño hasta llegar a la educación musical, haciendo especial hincapié en las relaciones entre la música y el lenguaje a partir de la audición y los primeros pasos en el aprendizaje del habla.

Exploring the effect of aminoglycoside guanidinylation on ligands for Tau exon 10 splicing regulatory element RNA

We describe the effect of guanidinylation of the aminoglycoside moiety on acridine-neamine-containing ligands for the stem-loop structure located at the exon 10-5′-intron junction of Tau pre-mRNA, an important regulatory element of tau gene alternative splicing. On the basis of dynamic combinatorial chemistry experiments, ligands that combine guanidinoneamine and two different acridines were synthesized and their RNA-binding properties were compared with those of their amino precursors. Fluorescence titration experiments and UV-monitored melting curves revealed that guanidinylation has a positive effect both on the binding affinity and specificity of the ligands for the stemloop RNA, as well as on the stabilization of all RNA sequences evaluated, particularly some mutated sequences associated with the development of FTDP-17 tauopathy. However, this correlation between binding affinity and stabilization due to guanidinylation was only found in ligands containing a longer spacer between the acridine and guanidinoneamine moieties, since a shorter spacer produced the opposite effect (e.g. lower binding affinity and lower stabilization). Furthermore, spectroscopic studies suggest that ligand binding does not significantly change the overall RNA structure upon binding (circular dichroism) and that the acridine moiety might intercalate near the bulged region of the stem->loop structure (UV-Vis and NMR spectroscopy).

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Place branding : a conceptual and theoretical framework

Within the context of rising competition between territories, identity has become the most important element of recognition, differentiation and commodification in the communicative process within which cities, regions and countries position themselves. Geographical spaces thus compete in terms of this identity, which is then subjected to fierce comparison and competition (Nogué, 1999; Anholt, 2007a). The territorial brand thus entails the reinvention of places through a process of brand construction (branding) based on the promotion of the individual and collective identities of geographical spaces; these identities, in turn, are imbued with the intangible factors associated with their respective territorial identities.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.