Gestión de un club de pádel

Este proyecto es un estudio que pretende realizar una aplicación dirigida a centros deportivos, implementando a través de BIOMAX el acceso a las instalaciones utilizando tarjetas de proximidad. Además la aplicación permitirá gestionar de forma eficiente a sus socios e instalaciones. De esta manera se consigue automatizar - mejorando en tiempo y calidad -una tarea imprescindible de realizar, control de accesos de forma sencilla y con un mantenimiento fácil por parte de los usuarios que la utilicen. Para ello se utilizará un dispositivo KIMALDI que nos permitirá gestionar el control de accesos

Exemplar-based interpolation of sparsely sampled images

A nonlocal variational formulation for interpolating a sparsel sampled image is introduced in this paper. The proposed variational formulation, originally motivated by image inpainting problems, encouragesthe transfer of information between similar image patches, following the paradigm of exemplar-based methods. Contrary to the classical inpaintingproblem, no complete patches are available from the sparse imagesamples, and the patch similarity criterion has to be redefined as here proposed. Initial experimental results with the proposed framework, at very low sampling densities, are very encouraging. We also explore somedepartures from the variational setting, showing a remarkable ability to recover textures at low sampling densities.

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.

A non-linear VAD for noisy environments

This paper deals with non-linear transformations for improving the performance of an entropy-based voice activity detector (VAD). The idea to use a non-linear transformation has already been applied in the field of speech linear prediction, or linear predictive coding (LPC), based on source separation techniques, where a score function is added to classical equations in order to take into account the true distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if the signal is clean, the estimated entropy is essentially the same; if the signal is noisy, however, the frames transformed using the score function may give entropy that is different in voiced frames as compared to nonvoiced ones. Experimental evidence is given to show that this fact enables voice activity detection under high noise, where the simple entropy method fails.

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

A Robust Multiple Feature Approach To Endpoint Detection In Car Environment Based On Advanced Classifiers

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection.

Disseny d'un sistema de control del consum d'aigua automàtic

Avui en dia s’ha convertit en una necessitat tenir cura del medi ambient i optimitzar els recursos naturals. En el camp per estalviar energia s’han fet grans progressos i disposem d’un gran ventall de dispositius que ens ajuden i ens faciliten l’optimització del consum d’energia. Però és una realitat que en l’estalvi del consum d’aigua el progrés ha estat molt menor i es limita molt a donar consells i repartir dosificadors d’aigua. Qui no ha vist carrers o jardins o cases inundades amb milers de litres d’aigua? Aquesta realitat m’ha portat a dissenyar i desenvolupar un prototip que em permeti tenir un millor control del consum d’aigua. El prototip, a trets principals, consta d’un sensor, una electrovàlvula i una placa Arduino Atmega. El sensor ens permet mesurar els litres consumits durant un cert període de temps. Passat aquest temps de mostreig es compara els litres consumits amb el consum habitual, en aquell període de temps. En cas de sobrepassar el volum programat es tancarà l’electrovàlvula de forma automàtica i rebrem un SMS al telèfon. L’activació de l’alarma es pot ajustar que sigui al igualar-se els dos valors, litres programats i litres consumits. També es pot programar el percentatge que cal sobrepassar de litres consumits per activar l’alarma, com el temps de mostreig. El fet de poder programar tots aquests valors ens permet fer un ajust ideal per a la instal·lació que es vol tenir controlada. A més, el prototip es pot utilitzar per enviar a la companyia d’aigua el valor del comptador de forma automàtica. D’aquesta forma la companyia d’aigua també optimitza recursos estalviant-se el desplaçament de personal a la instal·lació per fer la lectura corresponent. El prototip està basat amb un Arduino Atmega que ens permet el processament de les dades programades i capturades pel sensor. També s’ha incorporat una pantalla TFT Touch 2’8”, que permet visualitzar i programar els valors d’una forma molt més intuïtiva. Per enviar els SMS s’utilitza una placa d’Arduino Cel·lular Shield - SM5100B, a la qual només cal afegir una targeta SIM. A priori, el prototip té un elevat cost al fabricar una sola unitat i pot semblar poc útil. Però ens pot estalviar alguna sorpresa en les factures d’aigua si tenim una fuita i no ens n’adonem fins a veure el rebut de la companyia. Si es fabriqués a grans quantitats es podria abaratir el preu i fer-lo encara més engrescador.

Plataforma de resolució de problemes RCPSP utilitzant SMT

El problema d'operacions (scheduling) és un procés de presa de decisions quejuga un paper molt important en organitzacions de manufactura i serveis, jaque té una aplicació a la producció, transport i distribució, i a la comunicaciói processament d'informació, entre d'altres. Consisteix en assignar d'unamanera apropiada els recursos disponibles per al processament de tasquesde manera que es puguin optimitzar els objectius de l’organització.Com cas particular de la programació d'operacions, hi ha la programacióde projectes (Project Scheduling), que és el procés de planificar, organitzari controlar activitats i recursos per aconseguir un objectiu concret, generalmentamb limitacions de temps, recursos o costos. Dins aquest grup essituen els problemes de programació de projectes (PSP), que és un nomgenèric que es dóna a tota una classe de problemes en els quals és necessàriala programació de manera òptima el temps, el cost i els recursos dels projectes.La finalitat d'aquest projecte és crear una plataforma RCPSP que puguillegir diferents formats d'entrada (fitxers del tipus :.rcp,.sch,.sm,.data,.pat),pre-processar-los, codificar-los a través de diferents modelitzacions (TaskRD,TimeRD...) per tal de poder-los passar a instàncies SMT i poder executar-losa través de la API de Yices. L'objectiu és trobar el temps d'inici percada activitat de manera que es minimitzi la longitud del makespan senseque es violin les restriccions.Cal dissenyar una aplicació en C++, que sigui escalable i que puguiaconseguir el resultat del problema en el temps més òptim possible

The underestimation of compliance to direct help requests explained by adaptive sampling

Helping behavior is any intentional behavior that benefits another living being or group (Hogg & Vaughan, 2010). People tend to underestimate the probability that others will comply with their direct requests for help (Flynn & Lake, 2008). This implies that when they need help, they will assess the probability of getting it (De Paulo, 1982, cited in Flynn & Lake, 2008) and then they will tend to estimate one that is actually lower than the real chance, so they may not even consider worth asking for it. Existing explanations for this phenomenon attribute it to a mistaken cost computation by the help seeker, who will emphasize the instrumental cost of “saying yes”, ignoring that the potential helper also needs to take into account the social cost of saying “no”. And the truth is that, especially in face-to-face interactions, the discomfort caused by refusing to help can be very high. In short, help seekers tend to fail to realize that it might be more costly to refuse to comply with a help request rather than accepting. A similar effect has been observed when estimating trustworthiness of people. Fetchenhauer and Dunning (2010) showed that people also tend to underestimate it. This bias is reduced when, instead of asymmetric feedback (getting feedback only when deciding to trust the other person), symmetric feedback (always given) was provided. This cause could as well be applicable to help seeking as people only receive feedback when they actually make their request but not otherwise. Fazio, Shook, and Eiser (2004) studied something that could be reinforcing these outcomes: Learning asymmetries. By means of a computer game called BeanFest, they showed that people learn better about negatively valenced objects (beans in this case) than about positively valenced ones. This learning asymmetry esteemed from “information gain being contingent on approach behavior” (p. 293), which could be identified with what Fetchenhauer and Dunning mention as ‘asymmetric feedback’, and hence also with help requests. Fazio et al. also found a generalization asymmetry in favor of negative attitudes versus positive ones. They attributed it to a negativity bias that “weights resemblance to a known negative more heavily than resemblance to a positive” (p. 300). Applied to help seeking scenarios, this would mean that when facing an unknown situation, people would tend to generalize and infer that is more likely that they get a negative rather than a positive outcome from it, so, along with what it was said before, people will be more inclined to think that they will get a “no” when requesting help. Denrell and Le Mens (2011) present a different perspective when trying to explain judgment biases in general. They deviate from the classical inappropriate information processing (depicted among other by Fiske & Taylor, 2007, and Tversky & Kahneman, 1974) and explain this in terms of ‘adaptive sampling’. Adaptive sampling is a sampling mechanism in which the selection of sample items is conditioned by the values of the variable of interest previously observed (Thompson, 2011). Sampling adaptively allows individuals to safeguard themselves from experiences they went through once and turned out to lay negative outcomes. However, it also prevents them from giving a second chance to those experiences to get an updated outcome that could maybe turn into a positive one, a more positive one, or just one that regresses to the mean, whatever direction that implies. That, as Denrell and Le Mens (2011) explained, makes sense: If you go to a restaurant, and you did not like the food, you do not choose that restaurant again. This is what we think could be happening when asking for help: When we get a “no”, we stop asking. And here, we want to provide a complementary explanation for the underestimation of the probability that others comply with our direct help requests based on adaptive sampling. First, we will develop and explain a model that represents the theory. Later on, we will test it empirically by means of experiments, and will elaborate on the analysis of its results.

Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

Estudi de la viabilitat econòmica de la implantació d'una planta de piròlisi per a la producció de biochar en un context local i comarcal

En aquest document es pretén estudiar de la viabilitat econòmica de la implantació d’una planta de piròlisi per a la producció de biochar o char en un context local i comarcal. La biomassa és una font d’energia que genera uns rendiments energètics prou interesants i d’una manera respectuosa amb el medi ambient. Així doncs, la teòrica planta utilitzarà biomassa que, a traves del tractament termoquímic de la piròlisi, ens generarà uns productes que són d’utilitat per l’obtenció d’energia d’una manera respectuosa amb el medi ambient. Abans de fer l’anàlisi econòmic, hi ha una explicació extensa dels processos termoquímics, com són la piròlisi, la gasificació i la torrefacció. Posteriorment, es du a terme una revisió de l’estat actual de les tecnologies de conversió de biomassa a Catalunya i finalment es realitza un inventari i anàlisi dels usos de la biomassa a Catalunya, en el qual es parla principalment de l’estella el pèl·let, així com també de la seva producció, consum i exportació. El nostre anàlisi econòmic de la planta de processament de biomassa es durà a terme a nivell local, és a dir en un municipi, i també a nivell comarcal a Catalunya. A partir del processament de biomassa per mitja de la piròlisi, obtindrem uns productes, entre els quals el biochar, que serà un dels productes finals per poder vendre. L’altre producte serà el pèl·let de biochar, que l’obtindrem a través del procés de pel·letització. Aquest procés ens permetrà densificar el mateix biochar i obtenir-ne pèl·lets amb un poder calorífic superior, com també el seu possible preu de venda final. En aquest anàlisi econòmic plantejarem diferents escenaris tant a nivell local com comarcal, és a dir, farem variar diferents paràmetres de la planta, com poden ser els dies, les hores de treball, el sou dels treballadors, l’existència de procés de pel·letització...per veure la viabilitat del nostre projecte. Aquesta viabilitat la mesurarem amb diferents Índexs, entre els quals hi ha l’Índex de Rendibilitat, que ens determinarà si el projecte és possible si el seu valor és més gran a 1.

Intersecciones entre visión artificial y mirada artística. Semantic Intersections between Artificial and Artistic Vision.

En el presente artículo se ha desarrollado un sistema capaz de categorizar de forma automática la base de datos de imágenes que sirven de punto de partida para la ideación y diseño en la producción artística del escultor M. Planas. La metodología utilizada está basada en características locales. Para la construcción de un vocabulario visual se sigue un procedimiento análogo al que se utiliza en el análisis automático de textos (modelo 'Bag-of-Words'-BOW) y en el ámbito de las imágenes nos referiremos a representaciones 'Bag-of-Visual Terms' (BOV). En este enfoque se analizan las imágenes como un conjunto de regiones, describiendo solamente su apariencia e ignorando su estructura espacial. Para superar los inconvenientes de polisemia y sinonimia que lleva asociados esta metodología, se utiliza el análisis probabilístico de aspectos latentes (PLSA) que detecta aspectos subyacentes en las imágenes, patrones formales. Los resultados obtenidos son prometedores y, además de la utilidad intrínseca de la categorización automática de imágenes, este método puede proporcionar al artista un punto de vista auxiliar muy interesante.