Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-04-20T12:09:28Z No. of bitstreams: 1 thiagorodriguesoliveira.pdf: 2429204 bytes, checksum: b1904f2bde31b546890c5bfa77d58c80 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-04-20T12:44:42Z (GMT) No. of bitstreams: 1 thiagorodriguesoliveira.pdf: 2429204 bytes, checksum: b1904f2bde31b546890c5bfa77d58c80 (MD5) / Made available in DSpace on 2017-04-20T12:44:42Z (GMT). No. of bitstreams: 1 thiagorodriguesoliveira.pdf: 2429204 bytes, checksum: b1904f2bde31b546890c5bfa77d58c80 (MD5) Previous issue date: 2010-09-28 / Esta dissertação apresenta, de forma detalhada, um conjunto de metodologias e técnicas destinadas à análise de redes de energia elétrica como meio de transmissão de dados (power line communication - PLC). As características das redes elétricas que influenciam um sistema de comunicação de dados consideradas neste trabalho são as seguintes: a impedância de acesso à rede elétrica, a resposta ao impulso e o ruído. Para tanto, técnicas de processamento de sinais para estimação da resposta em frequência, estimação do comprimento efetivo da resposta ao impulso, detecção e segmentação de ruídos impulsivos e análise espectral de ruídos aditivos são propostas e discutidas na presente contribuição. Os desempenhos objetivos e a apreciação subjetiva das técnicas propostas, a partir de dados sintéticos e medidos, evidenciam a adequação destas técnicas para a análise em questão. Além disso, formulações matemáticas para a resposta ao impulso de canais PLC invariantes, variantes e periodicamente variantes no tempo, derivadas a partir do modelo de multi-propagação para canais PLC, são apresentadas. Tais formulações proporcionam de forma simples e objetiva a emulação dos possíveis comportamentos temporais de canais PLC reais e, portanto, podem se constituir como ferramentas de grande utilidade para o projeto e a avaliação de sistemas de comunicações baseados na tecnologia PLC. / This thesis addresses a set of methodologies and techniques for the analysis of electric grids as a medium for data communications (power line communications - PLC). The main features influencing a communication system that are considered in this work are the input impedance, the channel impulse response, and the noise. In this regards, signal processing-based techniques are investigated, proposed and analyzed for the estimations of the channel frequency response and the effective length of the channel impulse response; the detection and segmentation of impulsive noise; and the power spectral analysis of the additive noise at the channel output. The numerical performance and subjective analysis regarding the use of the proposed techniques in synthetic and measured data indicate that those techniques fit well in the thesis purposes. In addition, mathematical formulation for invariant, time-varying, and periodically time-varying PLC channel models, which are based on multi-path channel model approach, are presented. These formulations are simple and elegant ones for the emulation of possible temporal behavior of existing PLC channels and, as a result, can constitute a useful tool for the design and analysis of PLC systems.

VINTERA, J. Spectral anlysis with superesolution. Brno: University of Technology, The Faculty of Electrical Engineering and Communication, 2008. 85 p. Master’s thesis. This thesis deals with the topic of super-resolution spectral analysis in the Signal Processing Toolset. The Signal Processing Toolset is a software component of the LabVIEW 8.1. program equipment. The thesis consists of three main parts. In the first part the basic theoretic concepts of the Model-Based Frequency Analysis are described. The second part serves as a user manual for the super-resolution spectral analysis in the Signal Processing Toolset. The last part describes the application of the theory introduced in the first part, by means of testing the properties of the methods used by the Toolset.

Die vorliegende Arbeit beschreibt einen semi-analytischen Ansatz zur Modellierung der Dichteverteilung von DM im Galaktischen Halo. Aus den verschiedenen Substrukturmodellen wird die γ-Strahlungsintensität, welche die Erde erreicht, berechnet. Eine Spannbreite plausibler γ-Strahlungsintensitäten aufgrund der Paarvernichtung Galaktischer DM wird vorgeschlagen, welche die Vorhersagen verschiedener früherer Studien umfasst, und es werden die durchschnittlichen Massen, Abstände und ausgedehnten Strahlungsprofile der γ-strahlungsintensivsten DM-Verdichtungen berechnet. Schließlich werden die DM-Modelle für eine umfassende Berechnung der Nachweismöglichkeit Galaktischer Substrukturen mit CTA verwendet. Die instrumentelle Sensitivität zum Nachweis der γ-strahlungsintensivsten DM-Substruktur wird für eine mit CTA geplanten großflächigen Himmelsdurchmusterung außerhalb der Galaktischen Ebene berechnet. Die Berechnung wird mit CTA Analyse- Software und einer Methode durchgeführt, welche auf einer Likelihood beruht. Eine alternative, ebenfalls Likelihood-basierte Analysemethode wird entwickelt, mit welcher DM-Substrukturen als äumliche Anisotropien im Multipolspektrum des Datensatzes einer Himmelsdurchmusterung nachgewiesen werden können. Die Analysen ergeben, dass eine Himmelsdurchmusterung mit CTA und eine anschließende Suche nach γ-Strahlung von DM-Substrukturen Wirkungsquerschnitte für eine Paarvernichtung in der Größenordnung von (σv) > 1 × 10−24 cm3 s−1 für eine DM-Teilchenmasse von mχ ∼ 500 GeV auf einem Vertrauensniveau von 95% ausschließen kann. Diese Sensitivität ist vergleichbar mit Langzeitbeobachtungen einzelner Zwerggalaxien mit CTA. Eine modellunabhängige Analyse ergibt, dass eine Himmelsdurchmusterung mit CTA Anisotropien im diffusen γ-Strahlungshintergrund oberhalb von 100 GeV für relative Schwankungen von CPF > 10−2 nachweisen kann. / In the current understanding of structure formation in the Universe, the Milky Way is embedded in a clumpy halo of dark matter (DM). Regions of high DM density are expected to emit enhanced γ-radiation from the DM relic annihilation. This γ-radiation can possibly be detected by γ-ray observatories on Earth, like the forthcoming Cherenkov Telescope Array (CTA). This dissertation presents a semi-analytical density modeling of the subclustered Milky Way DM halo, and the γ-ray intensity at Earth from DM annihilation in Galactic subclumps is calculated for various substructure models. It is shown that the modeling approach is able to reproduce the γ-ray intensities obtained from extensive dynamical DM simulations, and that it is consistent with the DM properties derived from optical observations of dwarf spheroidal galaxies. A systematic confidence margin of plausible γ-ray intensities from Galactic DM annihilation is estimated, encompassing a variety of previous findings. The average distances, masses, and extended emission profiles of the γ-ray-brightest DM clumps are calculated. The DM substructure models are then used to draw reliable predictions for detecting Galactic DM density clumps with CTA, using the most recent benchmark calculations for the performance of the instrument. A Likelihood-based calculation with CTA analysis software is applied to find the instrumental sensitivity to detect the γ-ray-brightest DM clump in the projected CTA extragalactic survey. An alternative Likelihood-based analysis method is developed, to detect DM substructures as anisotropies in the angular power spectrum of the extragalactic survey data. The analyses predict that the CTA extragalactic survey will be able to probe annihilation cross sections of ⟨σv⟩ > 1 × 10−24 cm3 s−1 at the 95% confidence level for a DM particle mass of mχ ∼ 500 GeV from DM annihilation in substructures. This sensitivity is compatible with long-term observations of single dwarf spheroidal galaxies with CTA. Independent of a particular source model, it is found that the CTA extragalactic survey will be able to detect anisotropies in the diffuse γ-ray background above 100 GeV at a relative amplitude of CP_F > 10−2.

This work is focused on the description of the dynamic contrast-enhanced CT examination and its contribution in the pneumooncology. It includes a program for creating a two-dimensional model of the scan from the thorax and for the perfuse examination simulation using the time-density curve. Real CT data are simulated more authentic using rigid geometric transformations and noise. The model will be used for the validation of registration algorithms that is used to suppress the spatial deformation generated by patient motions during the long time examination.

This thesis aims to use vibration and acoustic noise analysis to help a production line of a certain motor type to ensure good quality. Noise from the gearbox is sometimes present and the way it is detected is with a human listening to it. This type of error detection is subjective, and it is possible for human error to be present. Therefore, an automatic test that pass or fail the produced Brush Less Direct Current (BLDC)-motors is wanted. Two measurement setups were used. One was based on an accelerometer which was used for vibration measurements, and the other based on a microphone for acoustic sound measurements. The acquisition and analysis of the measurements were implemented using the data acquisition device, compactDAQ NI 9171, and the graphical programming software, NI LabVIEW. Two methods, i.e., power spectrum analysis and machine learning, were used for the analyzing of vibration and acoustic signals, and identifying faults in the gearbox. The first method based on the Fast Fourier transform (FFT) was used to the recorded sound from the BLDC-motor with the integrated planetary gearbox to identify the peaks of the sound signals. The source of the acoustic sound is from a faulty planet gear, in which a flank of a tooth had an indentation. Which could be measured and analyzed. It sounded like noise, which can be used as the indications of faults in gears. The second method was based on the BLDC-motors vibration characteristics and uses supervised machine learning to separate healthy motors from the faulty ones. Support Vector Machine (SVM) is the suggested machine learning algorithm and 23 different features are used. The best performing model was a Coarse Gaussian SVM, with an overall accuracy of 92.25 % on the validation data.

Splitter plates are passive flow control devices for reducing drag and suppressing vortex shedding from bluff bodies. Most studies of splitter plates involve the flow around an “infinite” circular cylinder, however, in the present study the flow around a surface-mounted finite-height circular cylinder, with a wake-mounted splitter plate, was studied experimentally in a low-speed wind tunnel using a force balance and single-component hot-wire anemometry. Four circular cylinders of aspect ratios AR = 9, 7, 5 and 3 were tested for a Reynolds number range of Re = 1.9×10^4 to 8.2×10^4. The splitter plates had lengths, relative to the cylinder diameter, of L/D = 1, 1.5, 2, 3, 5 and 7, thicknesses ranging from T/D = 0.10 and 0.15, and were the same height as the cylinder being tested. The cylinders were partially immersed in a flat-plate turbulent boundary layer, where the range of boundary layer thickness relative to the cylinder diameter was δ/D = 1.4 to 1.5. Measurements were made of the mean drag force coefficient, the Strouhal number at the mid-height position, and the Strouhal number and power spectra along the cylinder height. For all four finite circular cylinders, the splitter plates were effective at reducing the magnitude of the Strouhal number, and weakening or even suppressing vortex shedding, depending on the specific combination of AR and L/D. Compared to the case of an infinite circular cylinder, the splitter plate is less effective at reducing the mean drag force coefficient of a finite circular cylinder. The largest drag reduction was obtained for the cylinder of AR = 9 and splitter plates of L/D = 1 to 3, while negligible drag reduction occurred for the shorter cylinders.

The aim of this work is describe common methods of biological feedback therapy that is used to treat some psychosomatic diseases. Subsequently, the description is focused on minimal brain dysfunction treatment by the help of EEG biofeedback. Properties and technical requirements for this therapy are concretized. The last part of this thesis is dedicated to the design and realization of practical software tool for EEG biofeedback therapy which is made in LabView 7.1. The M535 acquisition unit and NI USB-6221 measuring device are used for hardware solution.