Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Estimating the colors of paintings

Observers can adjust the spectrum of illumination on paintings for optimal viewing experience. But can they adjust the colors of paintings for the best visual impression? In an experiment carried out on a calibrated color moni- tor images of four abstract paintings obtained from hyperspectral data were shown to observers that were unfamiliar with the paintings. The color volume of the images could be manipulated by rotating the volume around the axis through the average (a*, b*) point for each painting in CIELAB color space. The task of the observers was to adjust the angle of rotation to produce the best subjective impression from the paintings. It was found that the distribution of angles selected for data pooled across paintings and observers could be de- scribed by a Gaussian function centered at 10o, i.e. very close to the original colors of the paintings. This result suggest that painters are able to predict well what compositions of colors observers prefer.

Investigations on relational control of time perception

Tese de Doutoramento em Psicologia Básica

Una estimación del coste marginal en bienestar del sistema impositivo en España

Actual tax systems do not follow the normative recommendations of yhe theory of optimal taxation. There are two reasons for this. Firstly, the informational difficulties of knowing or estimating all relevant elasticities and parameters. Secondly, the political complexities that would arise if a new tax implementation would depart too much from current systems that are perceived as somewhat egalitarians. Hence an ex-novo overhaul of the tax system might just be non-viable. In contrast, a small marginal tax reform could be politically more palatable to accept and economically more simple to implement. The goal of this paper is to evaluate, as a step previous to any tax reform, the marginal welfare cost of the current tax system in Spain. We do this by using a computational general equilibrium model calibrated to a point-in-time micro database. The simulations results show that the Spanish tax system gives rise to a considerable marginal excess burden. Its order of magnitude is of about 0.50 money units for each additional money unit collected through taxes.

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

Real time GPS precise positioning of LEO satellites

Report for the scientific sojourn at the German Aerospace Center (DLR) , Germany, during June and July 2006. The main objective of the two months stay has been to apply the techniques of LEO (Low Earth Orbiters) satellites GPS navigation which DLR currently uses in real time navigation. These techniques comprise the use of a dynamical model which takes into account the precise earth gravity field and models to account for the effects which perturb the LEO’s motion (such as drag forces due to earth’s atmosphere, solar pressure, due to the solar radiation impacting on the spacecraft, luni-solar gravity, due to the perturbation of the gravity field for the sun and moon attraction, and tidal forces, due to the ocean and solid tides). A high parameterized software was produced in the first part of work, which has been used to asses which accuracy could be reached exploring different models and complexities. The objective was to study the accuracy vs complexity, taking into account that LEOs at different heights have different behaviors. In this frame, several LEOs have been selected in a wide range of altitudes, and several approaches with different complexity have been chosen. Complexity is a very important issue, because processors onboard spacecrafts have very limited computing and memory resources, so it is mandatory to keep the algorithms simple enough to let the satellite process it by itself.

A New Model Of Trend Inflation

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.

Caught Between Theory and Practice: Government, Market, and Regulatory Failure in Electricity Sector Reforms

The world-wide electricity sector reforms of the early 1990s have revealed the considerable complexities of making market driven reforms in network and infrastructure industries. This paper reflects on the experiences to date with the process and outcomes of marketbased electricity reforms across less-developed, transition and developed economies. The reforms outcomes suggest similar problems facing the electricity sector of these countries though their contexts vary significantly. Many developing and developed economies continue to have investment inadequacy concerns and the need to balance economy efficiency, sustainability and social equity after more than two decades of experience with reforms. We also use a case study of selected countries that in many respects represent the current state of the reform though they are rarely examined. Nepal, Belarus and Ireland are chosen as country-specific case studies for this purpose. We conclude that the changing dynamics of the electricity supply industry (ESI) and policy objectives imply that analysing the success and failure of reforms will indeed remain a complex process.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

Luc-Actes: une unité à construire

(Résumé de l'ouvrage) This volume contains the papers presented at the 47th Colloquium Biblicum Lovaniense (Leuven, 1998). The general theme of the meeting was the unity of the Gospel of Luke and the Acts of the Apostles. Main papers on this topic were read by R.L. Brawley, J. Delobel, A. Denaux, J.A. Fitzmeyer, F.W. Horn, J. Kremer, A. Lindemann, O. Mainville, D. Marguerat, F. Neirynck, W. Radl, M. Rese, J. Taylor, C.M. Tuckett, and J. Verheyden. While a large majority of scholars agree that Luke intended his work to cover both the past and the continuing history of Jesus (Gospel and Acts), the essays also illustrate the complexities of this view on the unity of Luke-Acts when it comes to interpret the various aspects of Lukan theology, christology, pneumatology, and ecclesiology, the expansion of the Church in light of its Jewish origins, the genre of Luke-Acts, and the literary and stylistic means Luke used to make his work a unity. In total the volume includes some 40 papers, of which 24 are offered papers: L. Alexander, H. Baarlink, M. Bachmann, D. Bechard, T.L. Brodie, G.P. Carras, A. del Agua, C. Focant, G. Geiger, B.J. Koet, V. Koperski, D.P. Moessner, G. Oegema, J. Pichler, E. Plümacher, A. Puig i Tarrèch, U. Schmid, B. Schwank, N. Taylor, P.J. Tomson, S. Van den Eynde, S. Walton, G. Wasserberg, F. Wilk. This collection is an invaluable contribution to current discussions in Lukan study and to a nuanced understanding of the relationship between Luke's two volumes.

Els horts urbans a la ciutat de Barcelona: les experiències d'horts urbans comunitaris com a formes d'intervenció social i ambiental

Aquest estudi presenta la situació actual dels horts urbans (i periurbans) a la ciutat de Barcelona, els quals s'han classificat segons el tipus d'organització desenvolupada a cada projecte. Així, podem trobar horts de gestió: a) individual i autogestionada; b) comunitària i autogestionada; c) individual i supervisada, i d) comunitària i supervisada. Els horts urbans es presenten, en general, com una eina interessant en la millora de la sostenibilitat urbana. A més de tenir una clara funció d'entreteniment, són propostes que consideren la internalització a les ciutats de la producció de part dels aliments que s'hi consumeixen i alhora aprofiten part dels residus que s'hi produeixen. En particular, els horts urbans comunitaris i autogestionats – el centre d'aquest estudi – es plantegen com espais de participació i autogestió d'acord a la complexitat del context local, d'integració social a través de noves formes de relació i de creació, d'educació ambiental i de transmissió i intercanvi de coneixements inter-generacional. A més, es presenten com una alternativa d'organització realment participativa del territori urbà. Finalment, i d'acord amb l'anterior, es destaquen un conjunt de característiques dels projectes d'horts urbans comunitaris, que juguen un rol fonamental en la capacitat d'aquests per intervenir en aspectes socials i ambientals de la ciutat; característiques que s'haurien de tenir en compte a l'hora de promocionar i implementar projectes d'horts urbans de qualsevol tipus.

Estudio sobre la extracción de puntos característicos en imágenes y sus aplicaciones

En aquest treball realitzem un estudi sobre la detecció y la descripció de punts característics, una tecnologia que permet extreure informació continguda en les imatges. Primerament presentem l'estat de l'art juntament amb una avaluació dels mètodes més rellevants. A continuació proposem els nous mètodes que hem creat de detecció i descripció, juntament amb l'algorisme òptim anomenat DART, el qual supera l'estat de l'art. Finalment mostrem algunes aplicacions on s'utilitzen els punts DART. Basant-se en l'aproximació de l'espai d'escales Gaussià, el detector proposat pot extreure punts de distint tamany invariants davant canvis en el punt de vista, la rotació i la iluminació. La reutilització de l'espai d'escales durant el procés de descripció, així com l'ús d'estructures simplificades i optimitzades, permeten realitzar tot el procediment en un temps computacional menor a l'obtingut fins al moment. Així s'aconsegueixen punts invariants i distingibles de forma ràpida, el qual permet la seva utilització en aplicacions com el seguiment d'objectes, la reconstrucció d'escenaris 3D i en motors de cerca visual.

Extended truncated Tweedie-Poisson model

It has been argued that by truncating the sample space of the negative binomial and of the inverse Gaussian-Poisson mixture models at zero, one is allowed to extend the parameter space of the model. Here that is proved to be the case for the more general three parameter Tweedie-Poisson mixture model. It is also proved that the distributions in the extended part of the parameter space are not the zero truncation of mixed poisson distributions and that, other than for the negative binomial, they are not mixtures of zero truncated Poisson distributions either. By extending the parameter space one can improve the fit when the frequency of one is larger and the right tail is heavier than is allowed by the unextended model. Considering the extended model also allows one to use the basic maximum likelihood based inference tools when parameter estimates fall in the extended part of the parameter space, and hence when the m.l.e. does not exist under the unextended model. This extended truncated Tweedie-Poisson model is proved to be useful in the analysis of words and species frequency count data.