Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / O presente trabalho aborda o problema de identificação de danos em uma estrutura a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos, quanto o campo de coesão. O problema de identificação de danos é, então, definido como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura. A identificação de danos estruturais baseadas no domínio do tempo apresenta como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos danos. Estudos numéricos foram realizados considerando-se um modelo de viga de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo de Experimentos. A posição do sensor e o número de pontos foram determinados segundo o critério D-ótimo. Outros critérios complementares foram também analisados. Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura onde a resposta é mais sensível à presença de um dano em um estágio inicial. Para a resolução do problema inverso de identificação de danos foram considerados os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas com o intuito de avaliar a potencialidade da metodologia de identificação de danos, assim como a influência da posição do sensor e do número de dados considerados no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto Ótimo de Experimentos é de fundamental importância para a identificação de danos. / The present work deals with the damage identification problem in mechanical structures from their impulse response. In the adopted model, the structural integrity is continually described by a cohesion parameter and the finite element model (FEM) is used to spatially discretize both the displacement and cohesion fields. The damage identification problem is then posed as an optimization one, whose objective is to minimize, with respect to the vector of nodal cohesion parameters, a functional based on the difference between the experimentally obtained impulse response and the corresponding one predicted by an FEM of the structure. The damage identification problem built on the time domain presents some advantages, as the applicability in linear systems with high levels of damping an/or closed spaced modes, and in nonlinear systems. Besides, the time domain approaches present high sensitivities to the presence of small damages. Numerical studies were carried out considering a simply supported Euler-Bernoulli beam. Optimal experiment design techniques were considered with the aim at determining the optimal position of the displacement sensor and also the number of points of the impulse response to be considered in the identification process. The Differential Evolution optimization method and the Levenberg-Marquardt method were considered to solve the inverse problem of damage identification. Numerical analysis were carried out in order to assess the influence, on the identification results, of noise in the synthetic experimental data, of the sensor position, and of the number of points retained in the impulse response. The presented results shown the potentiality of the proposed damage identification approach and also the importance of the optimal experiment design for the quality of the identification. al importance for the identification of damage.

De nombreuses études ont été menées lors des vingt dernières années dans le domaine de l’auralisation.Elles consistent à rendre audible les résultats d’une simulation acoustique. Ces études se sont majoritairementfocalisées sur les algorithmes de propagation et la restitution du champ acoustique dans desenvironnements complexes. Actuellement, de nombreux travaux portent sur le rendu sonore en tempsréel.Cette thèse aborde la problématique du rendu sonore dynamique d’environnements complexes selonquatre axes : la propagation des ondes sonores, le traitement du signal, la perception spatiale du son etl’optimisation informatique. Dans le domaine de la propagation, une méthode permettant d’analyser lavariété des algorithmes présents dans la bibliographie est proposée. A partir de cette méthode d’analyse,deux algorithmes dédiés à la restitution en temps réel des champs spéculaires et diffus ont été extraits.Dans le domaine du traitement du signal, la restitution est réalisée à l’aide d’un algorithme optimisé despatialisation binaurale pour les chemins spéculaires les plus significatifs et un algorithme de convolutionsur carte graphique pour la restitution du champ diffus. Les chemins les plus significatifs sont extraitsgrace à un modèle perceptif basé sur le masquage temporel et spatial des contributions spéculaires.Finalement, l’implémentation de ces algorithmes sur des architectures parallèles récentes en prenant encompte les nouvelles architectures multi-coeurs et les nouvelles cartes graphiques est présenté. / During the past twenty years many studies have been conducted in the field of auralization, which aimsat rendering audible the results of an acoustic simulation. These studies have mainly focused on thepropagation algorithms and the sound field audio rendering for complex environments. Currently, muchresearch concentrates on real-time audio rendering.This thesis addresses the problematic of real-time audio rendering of complex environments accordingto four axes: sound propagation, Digital Signal Processing (DSP), spatial perception of sound andcomputational optimizations. In the field of propagation, a method that aims at analyzing the varietyof existing algorithms is proposed. This method yields two algorithms dedicated to the real-time propagationof both specular and diffuse information. In the field of DSP, the auralization is performed withan efficient binaural spatialization module for the most significant specular information, and a GPUconvolution algorithm for the diffuse sound field auralization. The most significant paths are extractedthanks to a perceptive model based on temporal and spatial masking of the specular contributions.Finally, the implementation of these algorithms on recent computer architectures, taking advantage ofthe parallel processing of the new CPUs, and the benefits of GPUs for DSP calculations is presented.

Ultra Wideband (UWB) communication has recently drawn considerable attention from academia and industry. This is mainly owing to the ultra high speeds and cognitive features it could offer. The employability of UWB in numerous areas including but not limited to Wireless Personal Area Networks, WPAN's, Body Area Networks, BAN's, radar and medical imaging etc. has opened several avenues of research and development. However, still there is a disagreement on the standardization of UWB. Two contesting radios for UWB are Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) and DS-UWB (Direct Sequence Ultra Wideband). As nearly all of the reported research on UWB hasbeen about a very narrow/specific area of the communication system, this thesis looks at the end-to-end performance of an MB-OFDM approach. The overall aim of this project has been to first focus on three different aspects i.e. interference, antenna and propagation aspects of an MB-OFDM system individually and then present a holistic or an end-to-end system analysis finally. In the first phase of the project the author investigated the performance of MB-OFDM system under the effect of his proposed generic or technology non-specific interference. Avoiding the conventional Gaussian approximation, the author has employed an advanced stochastic method. A total of two approaches have been presented in this phase of the project. The first approach is an indirect one which involves the Moment Generating Functions (MGF's) of the Signal-to-Interference-plus-Noise-Ratio (SINR) and the Probability Density Function (pdf) of the SINR to calculate the Average Probabilities of Error of an MB-OFDM system under the influence of proposed generic interference. This approach assumed a specific two-dimensional Poisson spatial/geometric placement of interferers around the victim MB-OFDM receiver. The second approach is a direct approach and extends the first approach by employing a wider class of generic interference. In the second phase of the work the author designed, simulated, prototyped and tested novel compact monopole planar antennas for UWB application. In this phase of the research, compact antennas for the UWB application are presented. These designs employ low-loss Rogers duroid substrates and are fed by Copla-nar Waveguides. The antennas have a proposed feed-line to the main radiating element transition region. This transition region is formed by a special step-generating function-set called the "Inverse Parabolic Step Sequence" or IPSS. These IPSS-based antennas are simulated, prototyped and then tested in the ane-choic chamber. An empirical approach, aimed to further miniaturize IPSS-based antennas, was also derived in this phase of the project. The empirical approach has been applied to derive the design of a further miniaturized antenna. More-over, an electrical miniaturization limit has been concluded for the IPSS-based antennas. The third phase of the project has investigated the effect of the indoor furnishing on the distribution of the elevation Angle-of-Arrival (AOA) of the rays at the receiver. Previously, constant distributions for the AOA of the rays in the elevation direction had been reported. This phase of the research has proposed that the AOA distribution is not fixed. It is established by the author that the indoor elevation AOA distributions depend on the discrete levels of furnishing. A joint time-angle-furnishing channel model is presented in this research phase. In addition, this phase of the thesis proposes two vectorial or any direction AOA distributions for the UWB indoor environments. Finally, the last phase of this thesis is presented. As stated earlier, the overall aim of the project has been to look at three individual aspects of an MB-OFDM system, initially, and then look at the holistic system, finally. Therefore, this final phase of the research presents an end-to-end MB-OFDM system analysis. The interference analysis of the first phase of the project is revisited to re-calculate the probability of bit error with realistic/measured path loss exponents which have been reported in the existing literature. In this method, Gaussian Quadrature Rule based approximations are computed for the average probability of bit error. Last but not the least, an end-to-end or comprehensive system equation/impulse response is presented. The proposed system equation covers more aspects of an indoor UWB system than reported in the existing literature.

This thesis is composed of three chapters that propose some novel approaches on tail risk for financial market and forecasting in finance and macroeconomics. The first part of this dissertation focuses on financial market correlations and introduces a simple measure of tail correlation, TailCoR, while the second contribution addresses the issue of identification of non- normal structural shocks in Vector Autoregression which is common on finance. The third part belongs to the vast literature on predictions of economic growth; the problem is tackled using a Bayesian Dynamic Factor model to predict Norwegian GDP.Chapter I: TailCoRThe first chapter introduces a simple measure of tail correlation, TailCoR, which disentangles linear and non linear correlation. The aim is to capture all features of financial market co- movement when extreme events (i.e. financial crises) occur. Indeed, tail correlations may arise because asset prices are either linearly correlated (i.e. the Pearson correlations are different from zero) or non-linearly correlated, meaning that asset prices are dependent at the tail of the distribution.Since it is based on quantiles, TailCoR has three main advantages: i) it is not based on asymptotic arguments, ii) it is very general as it applies with no specific distributional assumption, and iii) it is simple to use. We show that TailCoR also disentangles easily between linear and non-linear correlations. The measure has been successfully tested on simulated data. Several extensions, useful for practitioners, are presented like downside and upside tail correlations.In our empirical analysis, we apply this measure to eight major US banks for the period 2003-2012. For comparison purposes, we compute the upper and lower exceedance correlations and the parametric and non-parametric tail dependence coefficients. On the overall sample, results show that both the linear and non-linear contributions are relevant. The results suggest that co-movement increases during the financial crisis because of both the linear and non- linear correlations. Furthermore, the increase of TailCoR at the end of 2012 is mostly driven by the non-linearity, reflecting the risks of tail events and their spillovers associated with the European sovereign debt crisis. Chapter II: On the identification of non-normal shocks in structural VARThe second chapter deals with the structural interpretation of the VAR using the statistical properties of the innovation terms. In general, financial markets are characterized by non- normal shocks. Under non-Gaussianity, we introduce a methodology based on the reduction of tail dependency to identify the non-normal structural shocks.Borrowing from statistics, the methodology can be summarized in two main steps: i) decor- relate the estimated residuals and ii) the uncorrelated residuals are rotated in order to get a vector of independent shocks using a tail dependency matrix. We do not label the shocks a priori, but post-estimate on the basis of economic judgement.Furthermore, we show how our approach allows to identify all the shocks using a Monte Carlo study. In some cases, the method can turn out to be more significant when the amount of tail events are relevant. Therefore, the frequency of the series and the degree of non-normality are relevant to achieve accurate identification.Finally, we apply our method to two different VAR, all estimated on US data: i) a monthly trivariate model which studies the effects of oil market shocks, and finally ii) a VAR that focuses on the interaction between monetary policy and the stock market. In the first case, we validate the results obtained in the economic literature. In the second case, we cannot confirm the validity of an identification scheme based on combination of short and long run restrictions which is used in part of the empirical literature.Chapter III :Nowcasting NorwayThe third chapter consists in predictions of Norwegian Mainland GDP. Policy institutions have to decide to set their policies without knowledge of the current economic conditions. We estimate a Bayesian dynamic factor model (BDFM) on a panel of macroeconomic variables (all followed by market operators) from 1990 until 2011.First, the BDFM is an extension to the Bayesian framework of the dynamic factor model (DFM). The difference is that, compared with a DFM, there is more dynamics in the BDFM introduced in order to accommodate the dynamic heterogeneity of different variables. How- ever, in order to introduce more dynamics, the BDFM requires to estimate a large number of parameters, which can easily lead to volatile predictions due to estimation uncertainty. This is why the model is estimated with Bayesian methods, which, by shrinking the factor model toward a simple naive prior model, are able to limit estimation uncertainty.The second aspect is the use of a small dataset. A common feature of the literature on DFM is the use of large datasets. However, there is a literature that has shown how, for the purpose of forecasting, DFMs can be estimated on a small number of appropriately selected variables.Finally, through a pseudo real-time exercise, we show that the BDFM performs well both in terms of point forecast, and in terms of density forecasts. Results indicate that our model outperforms standard univariate benchmark models, that it performs as well as the Bloomberg Survey, and that it outperforms the predictions published by the Norges Bank in its monetary policy report. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Thesis focus on derivation of macro-finance model for analysis of yield curve and its dynamics using macroeconomic factors. Underlying model is based on basic Dynamic Stochastic General Equilibrium DSGE approach that stems from Real Business Cycle theory and New Keynesian Macroeconomics. The model includes four main building blocks: households, firms, government and central bank. Log-linearized solution of the model serves as an input for derivation of yield curve and its main determinants -- pricing kernel, price of risk and affine term structure of interest rates -- based on no-arbitrage assumption. The Thesis shows a possible way of consistent derivation of structural macro-finance model, with reasonable computational burden that allows for time varying term premia. A simple VAR model, widely used in macro-finance literature, serves as a benchmark. The paper also presents a brief comparison and shows an ability of both models to fit an average yield curve observed from the data. Lastly, the importance of term structure analysis is demonstrated using case of Central Bank deciding about policy rate and Government conducting debt management.

The aim of this master’s thesis is to create a multiband stop derived from Lynn filters for suppressing mains hum and baseline variation (drift). The first part of the thesis is focused on brief theoretical introduction to the distortion types affecting ECG signal and twelve lead connection. The following practical part describes free realizations of ECG filter and ECG signal filtration. The filter has been tested both on distorted and on non-distorted signal. Finally filters’ error rate was computed from CSE database signals.

This paper concentrates on the description of fractional order LTI SISO systems using generalized Laguerre functions. There are properties of generalized Laguerre functions described in the paper, and an orthogonal base of these functions is shown. Next the concept of fractional derivatives is explained. The last part of this paper deals with the representation of fractional order LTI SISO systems using generalized Laguerre functions. Several examples were solved to demonstrate the benefits of using these functions for the representation of LTI SISO systems.

Corruption is a social evil that resonates far and deep in societies, eroding trust in governance, weakening the rule of law, impairing economic development, and exacerbating poverty, social tension, and inequality. It is a multidimensional and complex societal malady that occurs in various forms and contexts. As such, any effort to combat corruption must be accompanied by a thorough examination of the attributes that might play a key role in exacerbating or mitigating corrupt environments. This dissertation identifies a number of attributes that influence corruption, using machine learning techniques, neural network analysis, and time series causal relationship analysis and aggregated data from 113 countries from 2007 to 2017. The results suggest that improvements in technological readiness, human development index, and e-governance index have the most profound impacts on corruption reduction. This dissertation discusses corruption at each phase of infrastructure systems development and engineering ethics that serve as a foundation for corruption mitigation. The dissertation then applies novel analytical efficiency measurement methods to measure infrastructure inefficiencies, and to rank infrastructure administrative jurisdictions at the state level. An efficiency frontier is developed using optimization and the highest performing jurisdictions are identified. The dissertation’s framework could serve as a starting point for governmental and non-governmental oversight agencies to study forms and contexts of corruption and inefficiencies, and to propose influential methods for reducing the instances. Moreover, the framework can help oversight agencies to promote the overall accountability of infrastructure agencies by establishing a clearer connection between infrastructure investment and performance, and by carrying out comparative assessments of infrastructure performance across the jurisdictions under their oversight or supervision.

[pt] Esta tese é composta por dois artigos. No primeiro, nós propomos e implementamos um novo índice de vulnerabilidade que é baseado em um VAR bayesiano, estrutural e que pode variar no tempo e junto com um hipótese de exogeneidade em bloco para um determinado par composto por uma economia grande e uma pequena economia aberta. O índice é baseado na soma das respostas da pequena economia aberta a choques na economia grande ao longo do tempo. Isso permite que nós consigamos distinguir e medir as fontes dos choques, varáveis impactadas e duração do co-movimento ou vulnerabilidade. Nosso índice sugere que a vulnerabilidade é determinada principalmente por características específicas de cada par de países, mas tendências mais gerais de descasamento podem ser observadas em um número considerável de pares de países, especialmente em janelas mais longas. Nós propomos uma aplicação desse método a um arcabouço de bancos globais - o que nos permite medir alguns mecanismos teóricos nunca antes medidos. Usando uma amostra de países desenvolvidos e em desenvolvimento, nós não econtramos evidência da prevalência de tais mecanismos sobre co-movimento. No segundo artigo, estudamos como incentivos fiscais impactam o comportamento da firma. Incentivos fiscais tem impacto sobre salários? Incentivos fiscais tem impacto sobre a composição da força de trabalho das firmas? E tem impacto sobre o tamanho dessas firmas? Para responder essas perguntas, combinamos a RAIS com uma nova base de dados - no nível da firma - de dois programas de incentivos fiscais do estado do Espírito Santo - Invest-ES e Compete-ES. Usando o estimador de diferenças em diferenças para efeitos de tratamento intertemporais, nós estumaos os impactos desses programas no nível municipal e, pela primeira vez, no nível das firmas. Nós não encontramos impacto significativo de de incentivos fiscais em quaisquer variáveis de nível municipal. No nível das firmas, por outro lado, nossos resultados indicam que há uma maior migração vinda de outros municípios do estado do Espírito Santo e também indicam que há um crescimento temporário no número de empregos nas firmas tratadas. Com relação a salário e níveis educacionais da força de trabalho, não foi documentado qualquer impacto significativo. / [en] This thesis is composed of two articles. In the first one, we propose and implement a new index of vulnerability which is based on a structural time-varying bayesian VAR with a block-exogeneity hypothesis for a given pair of a large economy and a small open economy. The index is based on the sum of the responses of the small open economy to shocks in the large economy over time, thus allowing us to disentangle and measure the source of the shock, impact variables and duration of the co-movement or vulnerability. Our index suggests that the business cycle co-movement is led primarily by country-pair characteristics, but decoupling trends can be observed in a considerable number of country-pairs, specially at long term windows. We provide an application of this approach to a global banks framework - which allows us to measure some yet unmeasured theoretical mechanisms. Using a sample of developed and developing countries, we find no evidence of the prevalence of such mechanisms in business cycle co-movement. In the second article, we study how tax incentives impact the firm s behavior and choices in the labor market. Do tax incentives affect wages? Do these incentives alter the composition of a firm s labor force? And what about its size? To answer these questions, we merge RAIS - a linked Brazilian employer-employee dataset - with a novel, firm-level, dataset on two fiscal incentives programs in the state of Espírito Santo - Invest-ES and Compete-ES. By using a differences-in-differences estimator of intertemporal treatment effects, we study the impacts of these programs on municipality-level and, for the first time, firm-level variables. We do not find statistically significant impact of fiscal incentives on any relevant municipality-level variables. On firm-level variables, however, our results point to higher migration from other municipalities in the state of Espírito Santo and temporary growth in the number of jobs. Regarding wages and educational levels of the labor force, no statistically significant impact was documented.

In automatic speech recognition systems (ASRs), training is a critical phase to the system?s success. Communication media, either analog (such as analog landline phones) or digital (VoIP) distort the speaker?s speech signal often in very complex ways: linear distortion occurs in all channels, either in the magnitude or phase spectrum. Non-linear but time-invariant distortion will always appear in all real systems. In digital systems we also have network effects which will produce packet losses and delays and repeated packets. Finally, one cannot really assert what path a signal will take, and so having error or distortion in between is almost a certainty. The channel introduces an acoustical mismatch between the speaker's signal and the trained data in the ASR, which results in poor recognition performance. The approach so far, has been to try to undo the havoc produced by the channels, i.e. compensate for the channel's behavior. In this thesis, we try to characterize the effects of different transmission media and use that as an inexpensive and repeatable way to train ASR systems.