Eines interactives per l'aprenentatge de la dinàmica i el control dels convertidors de potència

El projecte s'ha centrat en el disseny i desenvolupament de laboratoris virtuals per a la docència del dispositius i mètodes de gestió d’energia. Això s’ha realitzat a dos nivells clarament diferenciats, el primer grup de laboratoris correspon als convertidors electrònics de potencia i el segon grup de laboratoris correspon a un conjunt de casos d’aplicacions concretes. En el primer grup es descriu el detall del funcionament dels diferents elements mentre que en el segon els descriuen les idees i conceptes bàsics de funcionament. Els laboratoris virtuals de convertidors electrònics de potència inclouen el convertidor elevador (boost), el convertidor reductor (buck), i convertidors acobladors magnèticament. Aquestes permeten estudiar el comportament dinàmica des d’un punt de vista commutat o bé promitjat, les aplicacions incorporen també la possibilitat de sintonitzar els controladors. Aquestes aplicacions han estat desenvolupades per ser un complement per les sessions de pràctiques presencials. Els laboratoris virtuals d’aplicacions, inclouen els sistema de transport metropolità, el vehicle híbrid i els sistemes de gestió de talls transitoris en el subministrament d’energia principalment. Aquestes laboratoris permeten introduir els estudiants de forma qualitativa en els diferents conceptes i tècniques emprades en els sistemes de generació, transport i transformació d’energia. Totes les aplicacions han estat desenvolupades emprant Easy JAVA Simulations, aquesta eina permet desenvolupar laboratoris multiplataforma fàcilment distribuïbles a través d’internet.

Justifying Institutional Investment in OER Development : OERs as Marketing Vehicle

The higher education sector has become increasingly competitive and prospective students are adopting a consumerist approach to institution and programme choice. In response, higher education marketing has become more complex, market-oriented and business-like. Financial sustainability of open education resource (OER) projects is a widespread concern. This paper explores the extent to which a classical product placement framework can be applied to OERs to justify institutional funding in OER projects as a marketing investment. It is argued that OERs designed on this premise can increase cognitive, affective and conative brand outcomes while providing the traditional educational and societal benefits associated with OERs. A series of propositions are presented that may form the basis of a future research agenda.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Preliminary study of cooperation in hybrid ad-hoc networks

In this paper, we present a first approach to evolve a cooperative behavior in ad hoc networks. Since wireless nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. On the other hand, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios are unfavorable to the interests of a user. In this paper we deal with the issue of user cooperation in ad hoc networks by developing the algorithm called Generous Tit-For-Tat. We assume that nodes are rational, i.e., their actions are strictly determined by self-interest, and that each node is associated with a minimum lifetime constraint. Given these lifetime constraints and the assumption of rational behavior, we study the added behavior of the network.

L’art com a vehicle : la dimensió sagrada de les arts performatives.

Jerzy Grotowski, director de teatre i recercador que va transformar profundament l’escena teatral de la segona meitat del segle vint, l’any 1970 va anunciar que no dirigiria més produccions teatrals. Apocalypsis Cum Figuris, una de les grans produccions escèniques del segle XX, marcaria un punt de transició en la trajectòria de l’investigador polonès obrint nous horitzons de vida creativa. Impulsat per una gran inquietud interior que trobaria la seva culminació en l’allunyament dels límits estrictament teatrals, Grotowski inicia el passatge de l’àmbit de l’Art com a representació, teatre en un sentit clàssic del terme, al domini de l’Art com a vehicle, en el que el mestre polonès recupera un aspecte antic i oblidat de l’art, que el situaria al nivell d’un coneixement superior, esdevenint un vehicle espiritual.

Productive efficiency and regulatory reform: The case of vehicle inspection services

Measuring productive efficiency provides information on the likely effects of regulatory reform. We present a Data Envelopment Analysis (DEA) of a sample of 38 vehicle inspection units under a concession regime, between the years 2000 and 2004. The differences in efficiency scores show the potential technical efficiency benefit of introducing some form of incentive regulation or of progressing towards liberalization. We also compute scale efficiency scores, showing that only units in territories with very low population density operate at a sub-optimal scale. Among those that operate at an optimal scale, there are significant differences in size; the largest ones operate in territories with the highest population density. This suggests that the introduction of new units in the most densely populated territories (a likely effect of some form of liberalization) would not be detrimental in terms of scale efficiency. We also find that inspection units belonging to a large, diversified firm show higher technical efficiency, reflecting economies of scale or scope at the firm level. Finally, we show that between 2002 and 2004, a period of high regulatory uncertainty in the sample’s region, technical change was almost zero. Regulatory reform should take due account of scale and diversification effects, while at the same time avoiding regulatory uncertainty.

Ampliació i millora d'un vehicle teledirigit

En el projecte Ampliació i millora d’un vehicle teledirigit s’ha dut a terme l’ampliació d’un prototip de vehicle ràdio controlat fent servir dues plaques Arduino Duemilanove. Una es situa en el comandament i l’altra en el vehicle i controlen el comportament dels dos dispositius. Es transmet la informació necessària entre elles a través de dos mòduls XBee que posteriorment se’ls hi incorpora. Les plaques fetes servir en el prototip inicial eren unes SARD-13192 de Freescale i el primer que es fa en aquest sentit és una revisió del codi font utilitzat i l’adaptació a les plaques Arduino. Un acceleròmetre ADXL335 que s’incorpora a una de les plaques permet que el prototip es pugui controlar segons la posició del comandament. A més, un cop finalitzat el nou prototip és capaç de desplaçar-se endavant i endarrere, girar aturat i en moviment, i a diferents velocitats que es representen en tot moment en uns LEDs. També guarda l’últim circuit efectuat que es pot reproduir a voluntat de l’usuari, i emmagatzema les dades del recorregut de tota una sessió per exportar a l’ordinador. Per últim s’han dut a terme les proves necessàries per constatar que totes les millores s’han implementat amb èxit.

Implementació de les físiques d'un vehicle en un videojoc 3D

En la carrera del mundo de los videojuegos por alcanzar insospechables cotas de realismo con las que seguir sorprendiendo y enganchando al público, los motores de física se han convertido en la herramienta de presente y futuro. Atraídos por el auge de esta nueva tecnología, hemos lidiado con los motores referencia hoy día en el mercado, seleccionando luego uno de ellos e implementando un humilde videojuego de carreras como muestra de su potencial y de los conocimientos adquiridos.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Merging the hypothetical extraction method and the classical multiplier approach: a hybrid possibility for identifying key distributive sectors

The two main alternative methods used to identify key sectors within the input-output approach, the Classical Multiplier method (CMM) and the Hypothetical Extraction method (HEM), are formally and empirically compared in this paper. Our findings indicate that the main distinction between the two approaches stems from the role of the internal effects. These internal effects are quantified under the CMM while under the HEM only external impacts are considered. In our comparison, we find, however that CMM backward measures are more influenced by within-block effects than the proposed forward indices under this approach. The conclusions of this comparison allow us to develop a hybrid proposal that combines these two existing approaches. This hybrid model has the advantage of making it possible to distinguish and disaggregate external effects from those that a purely internal. This proposal has also an additional interest in terms of policy implications. Indeed, the hybrid approach may provide useful information for the design of ''second best'' stimulus policies that aim at a more balanced perspective between overall economy-wide impacts and their sectoral distribution.

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

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

An approach to vision-based station keeping for an unmanned underwater vehicle

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task