Automatic DVB signal analyser

El problema de controlar les emissions de televisió digital a tota Europa pel desenvolupament de receptors robustos i fiables és cada vegada més significant, per això, sorgeix la necessitat d’automatitzar el procés d’anàlisi i control d’aquests senyals. Aquest projecte presenta el desenvolupament software d’una aplicació que vol solucionar una part d’aquest problema. L’aplicació s’encarrega d’analitzar, gestionar i capturar senyals de televisió digital. Aquest document fa una introducció a la matèria central que és la televisió digital i la informació que porten els senyals de televisió, concretament, la que es refereix a l’estàndard "Digital Video Broadcasting". A continuació d’aquesta part, l’escrit es concentra en l’explicació i descripció de les funcionalitats que necessita cobrir l'aplicació, així com introduir i explicar cada etapa d’un procés de desenvolupament software. Finalment, es resumeixen els avantatges de la creació d’aquest programa per l’automatització de l’anàlisi de senyal digital partint d’una optimització de recursos.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Estimation of parametric and nonparametric models for univariate claim severity distributions - an approach using R

This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Revisión de resultados en el tratamiento de las fracturas distales de radio

Es presenta un estudi de l’avaluació dels resultats en el tractament de les fractures distals de radi durant el període de temps 2008-2010 a l’Hospital Sant Joan de Reus. A partir del estudi radiogràfic i biomecànic de les fractures i mitjançant la classificació de Fernández s’avalua el tractament realitzat, en termes de funcionalitat i resultat radiogràfic posterior. Els tractament utilitzats van ser: la reducció tancada i immobilització amb guix antebraquiopalmar (ABP), la reducció tancada i fixació percutánia amb agulles de Kirchner, la reducció oberta per abordatge palmar i fixació amb placa volar DVR (Distal Volar Radius). Els resultat s’avaluen amb l’escala de valoració de Gartland modificada. Fent una revisió actualitzada de la literatura i l’evidencia que existeix pel tractament de cada tipus de fractura.

The nature of the Cr-C bond: direct estimation of aromaticity in Fischer carbenes

Report for the scientific sojourn at the the Philipps-Universität Marburg, Germany, from september to december 2007. For the first, we employed the Energy-Decomposition Analysis (EDA) to investigate aromaticity on Fischer carbenes as it is related through all the reaction mechanisms studied in my PhD thesis. This powerful tool, compared with other well-known aromaticity indices in the literature like NICS, is useful not only for quantitative results but also to measure the degree of conjugation or hyperconjugation in molecules. Our results showed for the annelated benzenoid systems studied here, that electron density is more concentrated on the outer rings than in the central one. The strain-induced bond localization plays a major role as a driven force to keep the more substituted ring as the less aromatic. The discussion presented in this work was contrasted at different levels of theory to calibrate the method and ensure the consistency of our results. We think these conclusions can also be extended to arene chemistry for explaining aromaticity and regioselectivity reactions found in those systems.In the second work, we have employed the Turbomole program package and density-functionals of the best performance in the state of art, to explore reaction mechanisms in the noble gas chemistry. Particularly, we were interested in compounds of the form H--Ng--Ng--F (where Ng (Noble Gas) = Ar, Kr and Xe) and we investigated the relative stability of these species. Our quantum chemical calculations predict that the dixenon compound HXeXeF has an activation barrier for decomposition of 11 kcal/mol which should be large enough to identify the molecule in a low-temperature matrix. The other noble gases present lower activation barriers and therefore are more labile and difficult to be observable systems experimentally.

Solvency Capital estimation and Risk Measures

This paper examines why a financial entity’s solvency capital estimation might be underestimated if the total amount required is obtained directly from a risk measurement. Using Monte Carlo simulation we show that, in some instances, a common risk measure such as Value-at-Risk is not subadditive when certain dependence structures are considered. Higher risk evaluations are obtained for independence between random variables than those obtained in the case of comonotonicity. The paper stresses, therefore, the relationship between dependence structures and capital estimation.

Stream Radio Community : comunitat web per la difusió de radio via streaming

Desenvolupament d'una aplicació web amb projecció a comunitat virtual d’usuaris, que també integra un sistema de transmissió de streaming. Mitjançant aquest sistema els usuaris són capaços d’emetre o d’escoltar un programa radiofònic en temps real o offline.

Design of Novel Frequency Generation Circuit with Application to Ultra-Wideband Distributed Oscillators

Given the urgence of a new paradigm in wireless digital trasmission which should allow for higher bit rate, lower latency and tigher delay constaints, it has been proposed to investigate the fundamental building blocks that at the circuital/device level, will boost the change towards a more efficient network architecture, with high capacity, higher bandwidth and a more satisfactory end user experience. At the core of each transciever, there are inherently analog devices capable of providing the carrier signal, the oscillators. It is strongly believed that many limitations in today's communication protocols, could be relieved by permitting high carrier frequency radio transmission, and having some degree of reconfigurability. This led us to studying distributed oscillator architectures which work in the microwave range and possess wideband tuning capability. As microvave oscillators are essentially nonlinear devices, a full nonlinear analyis, synthesis, and optimization had to be considered for their implementation. Consequently, all the most used nonlinear numerical techniques in commercial EDA software had been reviewed. An application of all the aforementioned techniques has been shown, considering a systems of three coupled oscillator ("triple push" oscillator) in which the stability of the various oscillating modes has been studied. Provided that a certain phase distribution is maintained among the oscillating elements, this topology permits a rise in the output power of the third harmonic; nevertheless due to circuit simmetry, "unwanted" oscillating modes coexist with the intenteded one. Starting with the necessary background on distributed amplification and distributed oscillator theory, the design of a four stage reverse mode distributed voltage controlled oscillator (DVCO) using lumped elments has been presented. All the design steps have been reported and for the first time a method for an optimized design with reduced variations in the output power has been presented. Ongoing work is devoted to model a wideband DVCO and to implement a frequency divider.

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Accuracy estimation of a new omnidirectional 3D vision sensor

We present a computer vision system that associates omnidirectional vision with structured light with the aim of obtaining depth information for a 360 degrees field of view. The approach proposed in this article combines an omnidirectional camera with a panoramic laser projector. The article shows how the sensor is modelled and its accuracy is proved by means of experimental results. The proposed sensor provides useful information for robot navigation applications, pipe inspection, 3D scene modelling etc

A survey addressing the fundamental matrix estimation problem

Epipolar geometry is a key point in computer vision and the fundamental matrix estimation is the only way to compute it. This article surveys several methods of fundamental matrix estimation which have been classified into linear methods, iterative methods and robust methods. All of these methods have been programmed and their accuracy analysed using real images. A summary, accompanied with experimental results, is given

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Intelligent PCA contribution analysis for quality estimation in batch processes. Application in a sequencing batch reactor for wastewater treatment

En aquest treball, es proposa un nou mètode per estimar en temps real la qualitat del producte final en processos per lot. Aquest mètode permet reduir el temps necessari per obtenir els resultats de qualitat de les anàlisi de laboratori. S'utiliza un model de anàlisi de componentes principals (PCA) construït amb dades històriques en condicions normals de funcionament per discernir si un lot finalizat és normal o no. Es calcula una signatura de falla pels lots anormals i es passa a través d'un model de classificació per la seva estimació. L'estudi proposa un mètode per utilitzar la informació de les gràfiques de contribució basat en les signatures de falla, on els indicadors representen el comportament de les variables al llarg del procés en les diferentes etapes. Un conjunt de dades compost per la signatura de falla dels lots anormals històrics es construeix per cercar els patrons i entrenar els models de classifcació per estimar els resultas dels lots futurs. La metodologia proposada s'ha aplicat a un reactor seqüencial per lots (SBR). Diversos algoritmes de classificació es proven per demostrar les possibilitats de la metodologia proposada.