A monitoração do processo de fermentação alcoólica para a obtenção de etanol é um tema de grande interesse pelo fato deste ser utilizado como fonte sustentavel de energia na indústria. Os processo de monitoração convencionalmente utilizados na indústria são dispendiosos, baseados em medições supervisionadas de densidade e estimativas de parâmetros químicos mediante procedimentos offline. O uso de técnicas de monitoração não invasivas baseadas em ultra-som vem sendo desenvolvidas para esse fim, fazendo uso de estimativas de parâmetros clássicos como a velocidade de propagação acústica e a atenuação. No entanto, a evolução do processo fermentativo não é bem descrita por esses parâmetros. Devido a isso, o presente trabalho propõe um sistema híbrido de processamento de sinais de ultra-som que utiliza um conglomerado de parâmetros para uma caracterização mais eficiente do processo fermentativo. O sistema incorpora procedimentos computacionais para a detecção, caracterização e classificação das fases do mosto em fermentação, visto como uma suspensão sólido-líquido (fase dispersa e contínua). Esses procedimentos foram baseadas em estimativas de estacionariedade dos sinais de retroespalhamento de ultra-som ( teste de hipotese não paramétrico - Teste de Run), ajuste de curvas sobre a largura de banda espectral (técnica de curve fitting), assim como a extração de atributos espectrais tais como : frequência central, largura de banda e valores de amplitude da componente fundamental, entre outros, além de parâmetros ultra-sônicos como o coeficiente de atenuação (slope) e o coeficiente integrado de retro-espalhamento (IBC). Para a classificação foi utilizado o algoritmo K-means. Os resultados obtidos mostraram a viabilidade na caracterização multiparamétrica não invasiva do fluido em fermentação, permitindo a identificação das principais fases do processo fermentativo. O trabalho contribui com uma metodología alternativa para a avaliação da cinética do crescimento microbiano como indicador da evolução da fermentação alcoólica. / Monitoring of alcoholic fermentation process for the ethanol production is a topic of great interest because it can be used as a sustainable energy source in the industry. The monitoring process conventionally used in industry are expensive, based on supervised measurements of density and parameter estimates by chemical offline procedures. The use of noninvasive monitoring techniques based on ultrasound are being developed for this purpose, using estimates of classical parameters as the acoustic propagation velocity and attenuation. However, the time evolution of the fermentation process is not well described by these parameters. For this reason, this study proposes a hybrid system of ultrasound signal processing that uses a conglomerate of parameters aiming a more efficient characterization about the fermentation process. The system incorporates computational procedures for the detection, characterization and classification of the fermentation must phases, seen as a solid-liquid suspension (dispersed and continuous phases). These procedures were based on estimates of stationarity for ultrasound backscattered signals (non-parametric statistical test - Run Test), curve fitting on the spectral bandwidth, as well as spectral attributes extraction such as center frequency, bandwidth and energy values of the fundamental frequency and so on, plus ultrasonic parameters as the attenuation coefficient (slope) and the integrated back-scattering coefficient (IBC). For classification we used the k-means algorithm. The results showed the feasibility for the multiparametric noninvasive characterization of fluid in fermentation, identifying the main stages of the fermentation process. This work contributes with an alternative methodology to evaluate the kinetics of microbial growth as an indicator of the alcoholic fermentation evolution.

Este trabalho apresenta um estudo comparativo entre análises no domínio do tempo e análises espectrais, como forma de sugerir uma abordagem alternativa para o projeto de pontes de seção celular submetidas à ação de terremotos. Com esse propósito, desenvolveu-se um programa em linguagem JAVA para a geração de sismos artificiais, usando como base o Eurocode 8. A saída do programa foi utilizada para o desenvolvimento de um estudo de caso, que consiste em uma modelagem simplificada no software ADINA, de um vão de 21 m da Ponte Alverca, em Portugal. Após a extração e comparação de resultados dos dois métodos, é possível perceber que o método alternativo proposto - no domínio do tempo, que consiste na aplicação de acelerogramas artificiais ao modelo - possui resultados bastante coerentes com a análise espectral, além de ser mais recomendado se efeitos geométricos ou fisicamente não lineares forem considerados na modelagem. / This work presents a comparative study between time-domain analysis and spectral analysis, as a way of suggesting an alternative approach for treating cell section bridges subjected to earthquakes. To reach this goal, it was developed a program in JAVA language for the artificial earthquakes generation, using the Eurocode 8 as a basis. The program output was used for a case study that consists in a simplified modeling using ADINA software, of a twenty-one-meter-long span of Alverca Bridge, in Portugal. After the results extraction of both methods, it is possible to notice that the alternative method - in the time-domain, which consists of the application of artificial accelerograms to the model - has fairly consistent results with spectral analysis, not to mention that it is the most suitable one, in case geometrical or physical non-linearities are considered in the modelling.

Neste trabalho, analisamos uma equação diferencial estocástica (EDE) do tipo Landau- Ginzburg: dφ = Aφ+dη (t, x), onde A é uma função definida no espaço das variáveis aleatórias φ (x, t) com (x, t) ∈ R X Zd. Toda a dissertação segue de perto as ideias encontradas no artigo [FdVOPS01]. Utilizando a teoria de análise estocástica (mais precisamente, a fórmula de Feynman- Kac) associamos a EDE acima com uma equação de evolução. Desta forma nosso estudo é resumido ao problema de determinação do espectro do gerador de um semigrupo de evolução. Para realizar esta análise utilizamos técnicas desenvolvidas na teoria quântica de campos. A esquematização do presente texto se dá da seguinte forma: Na introdução formulamos o nosso problema detalhadamente, fornecendo os aspectos da análise estocástica e da teoria de campos envolvidas. Também enunciamos um teorema que resume as propriedades espectrais que pretendemos obter. Nos Capítulos 2 e 3 fornecemos o aparato conceitual necessário para o desenvolvimento do problema inicial. Ainda no Capítulo 3, fazemos uma revisão rápida sobre um problema bem conhecido da mecânica quântica (modelo φ4), afim de estabelecer familiaridade com esta teoria. No Capítulo 4, inicialmente, nos restringimos à determinação de propriedades espectrais para o nosso problema no volume finito, e depois realizamos um procedimento chamado expansão em cluster para passar ao estudo do problema no volume infinito. No Capítulo 5 definimos o operador de Bethe-Salpeter, para então, no Capítulo 6, determinar propriedades do núcleo deste operador. Por fim, estas informações são utilizadas no Capítulo 7 para obtermos a caracterização espectral desejada. / Following [FdVOPS01], we study a stochastic Landau-Ginzburg differential equation of the form dφ = Aφ + dη (t, x), where A is a function defined on the space of random variables Φ (x, t), with (x, t) ∈ R X Zd. Using the stochastic analysis theory (more precisely, the Feynman-Kac formula) we are able to associate this stochastic differential equation (EDE) with an evolution equation. In this way, our study is resumed to the problem of determine the spectrum of the generator of an evolution semigroup. To do this, we use techniques developed in the quantum field theory. This work is organized as follows. In the Introduction we formulate our problem in detail, providing the aspects of the stochastic analysis and field theory that are involved. We also enunciate a theorem that resumes the spectral properties that we want to achieve. Chapters 2 and 3 are meant to provide the conceptual tools that are needed to the development of the initial problem. Yet in Chapter 3, we do a quick review of a known problem in quantum field (the model φ4), intending estabilish familiarity with this theory. Chapter 4 is restricted initially to the determination of spectral properties of our problem in the finite volume [T, T] X ∧ ⊂ R X Zd, and then we perform the cluster expansion in order to formulate the problem in infinite volume [T, T] X Zd. In Chapter 5 we define the Bethe-Salpeter operator and, in Chapter 6, we determine some properties of the kernel of this operator. This informations are used in Chapter 7 to obtain the desired spectral characterization.

Neste texto são revisados métodos de reamostragem de séries temporais discretas baseados em wavelets, como alternativas as abordagens clássicas, feitas nos domínios do tempo e da frequência. Tais métodos, conhecidos na literatura como wavestrap e wavestrapping fazem uso, respectivamente, das transformadas wavelet discreta (DWT) e wavelet packet discreta (DWPT). Existem poucos resultados sobre a aplicação da DWPT, de forma que este texto pode ser considerado uma contribuição. Aqui mostra-se também, a superioridade do wavestrapping sobre o wavestrap quando aplicados na estimação da densidade espectral de potência de séries temporais sintéticas geradas a partir de modelos autoregressivos. Tais séries possuem uma particularidade interessante que são picos, geralmente acentuados, em sua reapresentação espectral, de tal forma que grande parte dos métodos clássicos de reamostragem apresentam resultados viesados quando aplicados a estes casos. / This paper reviews resampling methods based on wavelets as an alternative to the classic approaches which are, made in the time and frequency domains. These methods, known in the literature as wavestrap and wavestrapping, make use, respectively, of the discrete wavelet transform (DWT) and of the discrete wavelet packet transform (DWPT). Since only few results are avaliable when the DWPT is applied, this text can be considered a contribution to the subject. Here we, also show the superiority of wavestrapping over wavestrap when they are applied to the estimation of power spectral densities of the synthetic time series generated from autoregressive models. These series have an interesting feature that are sharp peaks in their spectral representation, so that most of the traditional methods of resampling lead to biased results.

Atrial fibrillation (AF) is a troublesome disease often overlooked by more serious myocardial infarctions. Up until now, there has been very little or no use of high order spectral techniques in order to evaluate the organization of the atrium during AF. Cross-bicoherence algorithm can be used alongside a surrogate data threshold in order to determine significant phase coupling interactions, giving rise to an organizational metric. This proposed algorithm is used to show rotigaptide, a gap junction coupling drug, significantly increases the organization of the atria during episodes of AF due to improvement of cell-to-cell coupling.

Electrical Bioimpedance measurement has been used in clinical practice for several years for non-invasive monitoring. In recent years new applications of electrical bioimpedance measurements based in the spectral analysis has been validated.This fact have encouraged the use of spectral analysis on Electrical Bioimpedance measurements and it is a wide spread idea that spectral analysis of electrical bioimpedance data is going to open the door for new indicators for health assessment.The intended goal of this project is to develop a software tool, based in Matlab, that allows researchers to perform, both spectral and time signal analysis on the measurements performed Electrical Bioimpedance Spectrometers. This tool must incorporate the necessary display capabilities to allow quick visual inspection and visualization of the analysis results.Once this tool has been implemented, spectral analysis and validation of classification features will be possible in an easy way accelerating the process of test and analysis of experimental data analysis. This task is always critical in any research or clinical study.To facilitate the spectral analysis of electrical bioimpedance data will contribute to the developing of novel methods of non-invasive diagnosis and monitoring. / Uppsatsnivå: D

Neste texto são revisados métodos de reamostragem de séries temporais discretas baseados em wavelets, como alternativas as abordagens clássicas, feitas nos domínios do tempo e da frequência. Tais métodos, conhecidos na literatura como wavestrap e wavestrapping fazem uso, respectivamente, das transformadas wavelet discreta (DWT) e wavelet packet discreta (DWPT). Existem poucos resultados sobre a aplicação da DWPT, de forma que este texto pode ser considerado uma contribuição. Aqui mostra-se também, a superioridade do wavestrapping sobre o wavestrap quando aplicados na estimação da densidade espectral de potência de séries temporais sintéticas geradas a partir de modelos autoregressivos. Tais séries possuem uma particularidade interessante que são picos, geralmente acentuados, em sua reapresentação espectral, de tal forma que grande parte dos métodos clássicos de reamostragem apresentam resultados viesados quando aplicados a estes casos. / This paper reviews resampling methods based on wavelets as an alternative to the classic approaches which are, made in the time and frequency domains. These methods, known in the literature as wavestrap and wavestrapping, make use, respectively, of the discrete wavelet transform (DWT) and of the discrete wavelet packet transform (DWPT). Since only few results are avaliable when the DWPT is applied, this text can be considered a contribution to the subject. Here we, also show the superiority of wavestrapping over wavestrap when they are applied to the estimation of power spectral densities of the synthetic time series generated from autoregressive models. These series have an interesting feature that are sharp peaks in their spectral representation, so that most of the traditional methods of resampling lead to biased results.

abstract: In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings. The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented. Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring. A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results. State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

The thesis presents a network model, where financial institutions form linkages at various investment horizons through their interdependence measured by volatility connectedness. Applying the novel framework of frequency connectedness mea- sures Baruník & Křehlík (2018), based on spectral representation of variance de- composition, we show fundamental properties of connectedness that originate in heterogeneous frequency responses to shocks. The newly proposed network mod- els characterize financial connections and systemic risk at the short-, medium- and long-term frequency. The empirical focus of this thesis is on the interde- pendence structure of US financial system, specifically, major U.S. banks in the period 2000 - 2016. In the light of frequency volatility connectedness measures, we argue that stocks with high levels of long-term connectedness represent greater systemic risk, because they are subject to persistent shocks transmitted for longer periods. When we assess institutions' risk premiums in asset pricing model, the model confirms the significance of volatility connectedness factor for asset prices. JEL Classification C18, C58, C58, G10, G15, Keywords connectedness, frequency, spectral analysis, sys- temic risk, financial network Author's e-mail 93539385@fsv.cuni.cz Supervisor's e-mail...

The primary goal of this paper is to demonstrate the application of a relatively esoteric and interdisciplinary technique, called spectral analysis, to dyadic social sciences data. Spectral analysis is an analytical and statistical technique, commonly used in engineering, that allows times series data to be analyzed for the presence of significant regular/periodic fluctuations/oscillations. These periodic fluctuations are reflected in the frequency domain as amplitude or energy peaks at certain frequencies. Furthermore, a Magnitude Squared Coherence analysis may be used to interrogate more than one time series concurrently in order to establish the degree of frequency domain correlation between the two series, as well to establish the phase (lead/lag) relationship between the coherent frequency components. In order to demonstrate the application of spectral analysis, the current study utilizes a secondary dyadic dataset comprising 30 daily reports of perceived sexual desire for 65 couples. The secondary goal of this paper is to establish a) whether there is significant periodic fluctuation in perceived levels of sexual desire for men and/or women, and at which specific frequencies, and b) how much correlation or `cross-spectral coherence' there is between partners' sexual desire within the dyads, and c) what the phase lead-lag relationship is between the partners at any of the identified frequency components. Sexual desire was found to have significant periodic components for both men and women, with a fluctuation of once per month being the most common frequency component across the groups of individuals under analysis. Mathematical models are presented in order to describe and illustrate these principal fluctuations. Partners in couples, on average, were found to fluctuate together at a number of identified frequencies, and the phase lead/lag relationships of these frequencies are presented.