Dance movement patterns recognition

"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

The word problem distinguishes counter languages

Counter automata are more powerful versions of finite state automata where addition and subtraction operations are permitted on a set of n integer registers, called counters. We show that the word problem of Zn is accepted by a nondeterministic m-counter automaton if and only if m &= n.

Bioinformàtica: add-in d'anàlisi i manipulació de seqüències per Microsoft Word

L'objectiu del projecte consisteix en el desenvolupament d'un add-in d'anàlisi i manipulació de seqüències, senzill i de fàcil ús, integrable en l'entorn Microsoft Word per permetre la manipulació de seqüències genètiques directament des de Microsoft Word, estalviant temps, en evitar haver de canviar constantment de programa i format per treballar amb elles; i, també, complicacions a l'usuari final. L'add-in ha estat desenvolupat en Visual Basic + VSTO i ofereix diverses funcionalitats d'edició i anàlisi de seqüències, com ara el complement, la recerca de motius o l'alineament.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Effects of Bilingualism on Multi-Word Production

It has been shown that bilinguals are disadvantaged on some language production tasks when compared to monolinguals. The present study investigated the effects of bilingualism on lexical retrieval in single and multi-word utterances. To this purpose, we tested three groups of 35 participants each (Spanish monolinguals, highly proficient Spanish-Catalan and Catalan-Spanish bilinguals) in two sets of picture naming experiments. In the first one, participants were asked to name black-and-white object drawings by single words. In the second one, participants had to name colored pictures with determiner adjectival noun phrases (NP) like “the red car”. In both sets of experiments, bilinguals were slower than monolinguals, even when naming in their dominant language. We also examined the articulatory durations of both single word and NP productions for this bilingual disadvantage. Furthermore, response onset times and durations of all groups in both experiments were affected by lexical variables of the picture names. These results are consistent with previous studies (Ivanova & Costa, 2008, Gollan et al., 2005) showing a bilingual disadvantage in single word production and extend these findings to multiword-utterances and response durations. They also support the claim that articulatory processes are influenced by lexical variables.

Detecció automàtica de còpies en un conjunt de documents MS Word

L'objectiu d'aquest projecte és l'estudi de la plagiabilitat dels lliuraments de les Proves d'Avaluació Continuada i pràctiques dels estudiants de la UOC així com l'estudi dels diferents mitjans per evitar-la.

Referencias cruzadas de Microsoft Word con Delicious (.NET)

Complemento para Microsoft Word 2007 encargado de incluir marcadores de una cuenta Delicious como notas al final de un documento.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Evaluation of free libraries for visual recognition of art imagery on mobile devices

This paper describes a systematic research about free software solutions and techniques for art imagery computer recognition problem.

OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature

Background: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. Results: Our group has previously reported the development of OSIRIS, a system aimed at the retrieval of literature about allelic variants of genes http://ibi.imim.es/osirisform.html. Here we describe the development of a new version of OSIRIS (OSIRISv1.2, http://ibi.imim.es/OSIRISv1.2.html webcite) which incorporates a new entity recognition module and is built on top of a local mirror of the MEDLINE collection and HgenetInfoDB: a database that collects data on human gene sequence variations. The new entity recognition module is based on a pattern-based search algorithm for the identification of variation terms in the texts and their mapping to dbSNP identifiers. The performance of OSIRISv1.2 was evaluated on a manually annotated corpus, resulting in 99% precision, 82% recall, and an F-score of 0.89. As an example, the application of the system for collecting literature citations for the allelic variants of genes related to the diseases intracranial aneurysm and breast cancer is presented. Conclusion: OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and therefore is suitable for collecting current knowledge on gene sequence variations and supporting the functional annotation of variation databases. The application of OSIRISv1.2 in combination with controlled vocabularies like MeSH provides a way to identify associations of biomedical interest, such as those that relate SNPs with diseases.

Goal recognition over POMDPs: inferring the intention of a POMDP agent

Plan recognition is the problem of inferring the goals and plans of an agent from partial observations of her behavior. Recently, it has been shown that the problem can be formulated and solved usingplanners, reducing plan recognition to plan generation.In this work, we extend this model-basedapproach to plan recognition to the POMDP setting, where actions are stochastic and states are partially observable. The task is to infer a probability distribution over the possible goals of an agent whose behavior results from a POMDP model. The POMDP model is shared between agent and observer except for the true goal of the agent that is hidden to the observer. The observations are action sequences O that may contain gaps as some or even most of the actions done by the agent may not be observed. We show that the posterior goal distribution P(GjO) can be computed from the value function VG(b) over beliefs b generated by the POMDPplanner for each possible goal G. Some extensionsof the basic framework are discussed, and a numberof experiments are reported.

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