Entorns col•laboratius virtuals asíncrons basats en Web i enfocats en la gestió del coneixement = Web-based Asynchronous Collaborative Environments Focused on Knowledge Management

Report for the scientific sojourn at the University of California at Berkeley, USA, from september 2007 until july 2008. Communities of Learning Practice is an innovative paradigm focused on providing appropriate technological support to both formal and especially informal learning groups who are chiefly formed by non-technical people and who lack of the necessary resources to acquire such systems. Typically, students who are often separated by geography and/or time have the need to meet each other after classes in small study groups to carry out specific learning activities assigned during the formal learning process. However, the lack of suitable and available groupware applications makes it difficult for these groups of learners to collaborate and achieve their specific learning goals. In addition, the lack of democratic decision-making mechanisms is a main handicap to substitute the central authority of knowledge presented in formal learning.

Processament de música basat en el seu contingut

Projecte de recerca elaborat a partir d’una estada a la National University of Singapore Singapur, entre juliol i octubre del 2007. Donada l'explosió de la música a l'internet i la ràpida expansió de les col•leccions de música digital, un repte clau en l'àrea de la informació musical és el desenvolupament de sistemes de processament musical eficients i confiables. L'objectiu de la investigació proposada ha estat treballar en diferents aspectes de l'extracció, modelatge i processat del contingut musical. En particular, s’ha treballat en l'extracció, l'anàlisi i la manipulació de descriptors d'àudio de baix nivell, el modelatge de processos musicals, l'estudi i desenvolupament de tècniques d'aprenentatge automàtic per a processar àudio, i la identificació i extracció d'atributs musicals d'alt nivell. S’han revisat i millorat alguns components d'anàlisis d'àudio i revisat components per a l'extracció de descriptors inter-nota i intra-nota en enregistraments monofónics d'àudio. S’ha aplicat treball previ en Tempo a la formalització de diferents tasques musicals. Finalment, s’ha investigat el processat d'alt nivell de música basandonos en el seu contingut. Com exemple d'això, s’ha investigat com músics professionals expressen i comuniquen la seva interpretació del contingut musical i emocional de peces musicals, i hem usat aquesta informació per a identificar automàticament intèrprets. S’han estudiat les desviacions en paràmetres com to, temps, amplitud i timbre a nivell inter-nota i intra-nota.

Comunidad y ciudadanía activa: fenomenología de una ocupación ética en un contexto de inmigración

La teoria i la praxi de la investigació qualitativa actual és hereva de la tradició fenomenològica. L’objectiu de la investigació està relacionat amb la comprensió profunda de les dimensions de l’educació i el treball, així com la seva significació per a les dones i els homes amb històries de vida marcades per la immigració. També, el treball de la investigació actual analitza la construcció de una identitat individual i col•lectiva de les dones i els homes amb una història d’immigració i reflexiona com desenvolupen el seu compromís a través d’una ocupació ètica. Es fa èmfasi en els elements transversals de la cultura i les construccions de gènere dins del domini de treball i educació. El mètode biogràfic narratiu es va utilitzar per estudiar les qüestions plantejades per la investigació. El procés de triangulació de les veus de les dones, els homes i de l’organització participant es va duu a terme per assegurar la validesa dels resultats i es van interpretar els indicadors de la recerca des del marc teòric proposat. A mode de conclusió, el treball es refereix a la formació permanent i considera que la violació del dret a l’educació és un factor que limita les oportunitats d’experimentar aquest tipus d’ocupació i, té efectes en la integritat personal i col·lectiva. Esperem que aquesta investigació pugui contribuir a la política d’immigració de les diferents organitzacions.

Educational pathways of minority youth in Norway: intersections of gender, ethnicity and social class

Educational aspirations during lower secondary school and choice of upper secondary education are important for young people’s future trajectories into higher education and labour market positions. In line with ideas about reflexive, autonomous individuals (Giddens, 1991), choice of education is often represented as a young person’ individual decision, and educational guidance as aimed at discovering what ‘fits’ an individual’s personality, interests and abilities. Educational aspirations and choices are also social patterns that are reproduced. Some population categories represent exceptions from expected patterns of social reproduction of educational level and professions. In several countries, one such category is young people from families with migration experiences (Lauglo, 2000; Modood, 2004). In Norway, students have a legal right to non-compulsory upper secondary schooling and 96 percent of the students continue from lower to upper secondary school. In spite of positive developments regarding minority youths’ completion of upper secondary and higher education in later years, studies still persistently show lower educational attainment among minority youth, particularly among boys (Fekjaer, 2006). However, in lower secondary school, minor ity youth tend to have markedly higher educational aspirations and stronger learning motivation than their majority peers, as well as greater effort in school and strong adherence to school values (Lauglo, 2000) despite lower educational attainment or lower socio-economic backgrounds. In addition, gender differences in educational aspirations seem to be smaller among minority youth. The principal objective of the study in progress that will be presented in this paper, is to describe how processes relating to gendered, ethnic and class-based identities influence young people’s educational choices. The study is undertaken as a PhD project in social anthropology. The methodological approach is ethnographic longitudinal fieldwork in two multicultural lower secondary schools in Oslo. The study is part of a larger project that also include quantitative analyses of longitudinal data covering 9th graders in Oslo 2006 through four data collections during lower and upper secondary school.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

La formació permanent en el context de l'Espai Europeu de la Formació Permanent

La importància de la formació permanent és indiscutible en qualsevol context laboral i molt especialment en les actuals circumstàncies de crisi econòmica mundial. Però en l'actual espai europeu d'educació superior (EEES), les tendències i els plans de formació contínua adquireixen una dimensió global, que supera o, millor dit, hauria de superar els plantejaments reduccionistes. Per això, la construcció i el desenvolupament de l'espai europeu de formació permanent, EEFP (Comissió de les Comunitats Europees, 2001a), ha d'entendre's com un procés que està immers en un teixit més ampli. Es tracta d'una acció en xarxa on és necessària la implicació de molts agents actius professionals i on la convergència, el reconeixement i la cohesió han de ser els seus màxims elements qualitatius

Activity in inferior parietal and medial prefrontal cortex signals the accumulation of evidence in a probability learning task.

In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.

Information systems for water resources management improvement in developing countries

Water resources management, as also water service provision projects in developing countries have difficulties to take adequate decisions due to scarce reliable information, and a lack of proper information managing. Some appropriate tools need to be developed in order to improve decision making to improve water management and access of the poorest, through the design of Decision Support Systems (DSS). On the one side, a DSS for developing co-operation projects on water access improvement has been developed. Such a tool has specific context constrains (structure of the system, software requirements) and needs (Logical Framework Approach monitoring, organizational-learning, accountability and evaluation) that shall be considered for its design. Key aspects for its successful implementation have appeared to be a participatory design of the system and support of the managerial positions at the inception phase. A case study in Tanzania was conducted, together with the Spanish NGO ONGAWA – Ingeniería para el Desarrollo. On the other side, DSS are required also to improve decision making on water management resources in order to achieve a sustainable development that not only improves the living conditions of the population in developing countries, but that also does not hinder opportunities of the poorest on those context. A DSS made to fulfil these requirements shall be using information from water resources modelling, as also on the environment and the social context. Through the research, a case study has been conducted in the Central Rift Valley of Ethiopia, an endhorreic basin 160 km south of Addis Ababa. There, water has been modelled using ArcSWAT, a physically based model which can assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time. Moreover, governance on water and environment as also the socioeconomic context have been studied.

LittleProc 2.0. : l'evolució als 16 bits, amb arquitectura superescalar i amb pipeline

Aquest projecte consisteix en evolucionar el LittleProc 1.0, un processador simple dissenyat per ser destinat al món de la docència per tres professors de la UAB. Aquestes evolucions consisteixen en aplicar diversos mètodes i arquitectures diferents per tal d’obtenir un millor rendiment del processador, arribant a executar programes amb la meitat de temps que tardava el LittleProc 1.0. Un cop implementades les diferents arquitectures per tal de millorar el rendiment, es realitzarà un estudi de quin tant per cent de millora ha sigut aquest rendiment.

Dynamics of the recruitment of lateral amygdala neurons following successive fear learning to different conditional stimuli

In fear conditioning, an animal learns to associate an unconditioned stimulus (US), such as a shock, and a conditioned stimulus (CS), such as a tone, so that the presentation of the CS alone can trigger conditioned responses. Recent research on the lateral amygdala has shown that following cued fear conditioning, only a subset of higher-excitable neurons are recruited in the memory trace. Their selective deletion after fear conditioning results in a selective erasure of the fearful memory. I hypothesize that the recruitment of highly excitable neurons depends on responsiveness to stimuli, intrinsic excitability and local connectivity. In addition, I hypothesize that neurons recruited for an initial memory also participate in subsequent memories, and that changes in neuronal excitability affect secondary fear learning. To address these hypotheses, I will show that A) a rat can learn to associate two successive short-term fearful memories; B) neuronal populations in the LA are competitively recruited in the memory traces depending on individual neuronal advantages, as well as advantages granted by the local network. By performing two successive cued fear conditioning experiments, I found that rats were able to learn and extinguish the two successive short-term memories, when tested 1 hour after learning for each memory. These rats were equipped with a system of stable extracellular recordings that I developed, which allowed to monitor neuronal activity during fear learning. 233 individual putative pyramidal neurons could modulate their firing rate in response to the conditioned tone (conditioned neurons) and/or non- conditioned tones (generalizing neurons). Out of these recorded putative pyramidal neurons 86 (37%) neurons were conditioned to one or both tones. More precisely, one population of neurons encoded for a shared memory while another group of neurons likely encoded the memories' new features. Notably, in spite of a successful behavioral extinction, the firing rate of those conditioned neurons in response to the conditioned tone remained unchanged throughout memory testing. Furthermore, by analyzing the pre-conditioning characteristics of the conditioned neurons, I determined that it was possible to predict neuronal recruitment based on three factors: 1) initial sensitivity to auditory inputs, with tone-sensitive neurons being more easily recruited than tone- insensitive neurons; 2) baseline excitability levels, with more highly excitable neurons being more likely to become conditioned; and 3) the number of afferent connections received from local neurons, with neurons destined to become conditioned receiving more connections than non-conditioned neurons. - En conditionnement de la peur, un animal apprend à associer un stimulus inconditionnel (SI), tel un choc électrique, et un stimulus conditionné (SC), comme un son, de sorte que la présentation du SC seul suffit pour déclencher des réflexes conditionnés. Des recherches récentes sur l'amygdale latérale (AL) ont montré que, suite au conditionnement à la peur, seul un sous-ensemble de neurones plus excitables sont recrutés pour constituer la trace mnésique. Pour apprendre à associer deux sons au même SI, je fais l'hypothèse que les neurones entrent en compétition afin d'être sélectionnés lors du recrutement pour coder la trace mnésique. Ce recrutement dépendrait d'un part à une activation facilité des neurones ainsi qu'une activation facilité de réseaux de neurones locaux. En outre, je fais l'hypothèse que l'activation de ces réseaux de l'AL, en soi, est suffisante pour induire une mémoire effrayante. Pour répondre à ces hypothèses, je vais montrer que A) selon un processus de mémoire à court terme, un rat peut apprendre à associer deux mémoires effrayantes apprises successivement; B) des populations neuronales dans l'AL sont compétitivement recrutées dans les traces mnésiques en fonction des avantages neuronaux individuels, ainsi que les avantages consentis par le réseau local. En effectuant deux expériences successives de conditionnement à la peur, des rats étaient capables d'apprendre, ainsi que de subir un processus d'extinction, pour les deux souvenirs effrayants. La mesure de l'efficacité du conditionnement à la peur a été effectuée 1 heure après l'apprentissage pour chaque souvenir. Ces rats ont été équipés d'un système d'enregistrements extracellulaires stables que j'ai développé, ce qui a permis de suivre l'activité neuronale pendant l'apprentissage de la peur. 233 neurones pyramidaux individuels pouvaient moduler leur taux d'activité en réponse au son conditionné (neurones conditionnés) et/ou au son non conditionné (neurones généralisant). Sur les 233 neurones pyramidaux putatifs enregistrés 86 (37%) d'entre eux ont été conditionnés à un ou deux tons. Plus précisément, une population de neurones code conjointement pour un souvenir partagé, alors qu'un groupe de neurones différent code pour de nouvelles caractéristiques de nouveaux souvenirs. En particulier, en dépit d'une extinction du comportement réussie, le taux de décharge de ces neurones conditionné en réponse à la tonalité conditionnée est resté inchangée tout au long de la mesure d'apprentissage. En outre, en analysant les caractéristiques de pré-conditionnement des neurones conditionnés, j'ai déterminé qu'il était possible de prévoir le recrutement neuronal basé sur trois facteurs : 1) la sensibilité initiale aux entrées auditives, avec les neurones sensibles aux sons étant plus facilement recrutés que les neurones ne répondant pas aux stimuli auditifs; 2) les niveaux d'excitabilité des neurones, avec les neurones plus facilement excitables étant plus susceptibles d'être conditionnés au son ; et 3) le nombre de connexions reçues, puisque les neurones conditionné reçoivent plus de connexions que les neurones non-conditionnés. Enfin, nous avons constaté qu'il était possible de remplacer de façon satisfaisante le SI lors d'un conditionnement à la peur par des injections bilatérales de bicuculline, un antagoniste des récepteurs de l'acide y-Aminobutirique.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method