Les infections urinaires (IUs) sont un motif très fréquent de consultation et de prescription d’antibiotique en médecine générale. Le choix de l’antibiotique repose sur les caractéristiques du patient, la susceptibilité des germes aux antibiotiques et des analyses de coût. Cette démarche thérapeutique est devenue de plus en plus complexe en raison de l’augmentation des résistantes aux antibiotiques. Dans ce contexte, mon travail de thèse repose sur deux principales études :A partir des données d’IMS-health France, une analyse spectrale des ventes d’antibiotiques urinaires a montré l’existence d’une saisonnalité annuelle entre 2001 et 2012 avec des pics estivaux. A partir des données de recherche de Google en France et dans six autres pays, le même phénomène a été observé. Ceci représente un argument en faveur d’une saisonnalité des cystites aigues simples.Une étude a été mise en place, visant à estimer l’incidence des IUs à germes résistants et à déterminer les facteurs associés à l’acquisition de ces germes. Un taux d'incidence annuel des IUs présumées en médecine générale a été estimé à 3 200 pour 100 000 femmes en France [IC 95%: 2 400-4 000], avec un taux d'incidence annuel des infections urinaires à E. coli résistant au fluoroquinolone en médecine générale à 102 pour 100 000 femmes en France [IC 95%: 30-50]. Les facteurs associés aux IU à entérobactéries résistantes à plus de trois classes d’antibiotique étaient l'utilisation de la pénicilline par la patiente (OR = 3,1 ; [1,2-8,0]), avoir fourni un hébergement à un résident d'un pays à haut risque de résistance aux antibiotiques (OR = 4,0 [1,2-15,1]) et la consommation de viande crue (OR = 0,3 ; [0,1-0,9]). / Urinary tract infections (IUs) are a frequent reason for consultation and prescription of antibiotics in general practice. The choice of the antibiotic is based on the patient’s characteristics, the antibiotic susceptibility of bacteria and cost analyzes. This therapeutic approach has become increasingly complex due to the increase in antibiotic resistance. In this context, my thesis is based on two main studies:From the data of IMS health France, a spectral analysis of urinary antibiotic sales was shown the existence of an annual seasonality between 2001 and 2012 with summer peaks. The same phenomenon was been observed from Google search data in France and in six other countries. This is an argument for seasonality in acute cystitis.Another study was set up, to estimate the incidence of resistant germs in IUs and identify factors associated with the acquisition of these germs. An annual incidence rate of IUs in general practice was estimated at 3,200 per 100,000 women in France [95% CI: 2,400-4,000], with an annual incidence rate of IUs due to E. coli resistant to fluoroquinolone in general practice at 102 per 100,000 women in France [95% CI: 30-50]. Factors associated with IU due to Enterobacteriaceae resistant to more than three classes of antibiotic were having used penicillin by the patient (OR = 3.1; [1.2 to 8.0]), having provided accommodation to a resident of a country at high risk for antibiotic resistance (OR = 4.0 [1.2 to 15.1]) and raw meat consumption (OR = 0.3; [0.1-0.9] ).

This thesis deals with the topic of high resolution spectral analysis. In the first part, selected methods are presented and afterwards compared based on the Matlab implementations. The problematics of reduction of crossterms in quadratic time–frequency distributions is also covered. The second part is focused on the implementation and optimization of the algorithm for real-time computation of smoothed Wigner distribution function.

The thesis deals with methods of identification of dynamic systems in time and frequency domain. Nonparametric and parametric methods of identification are analyzed. Selected methods are implemented in Matlab & Simulink sotware. Finally, the user guide for the created Python application is introduced.

This work deals with the possibility of a fast football match analysis from audio part of record with the possibility of implementation of some methods for other than football matches as well. The first intention was concentrated on detection of whiz of the soccer whistle that has specific frequency in its specter, which is out of common speech frequency. After detection harmonic frequency , the attention was focused on the definition of whiz meaning. Referee was helpful with the issue as he informed me about the number of whiz styles and provided me with referential samples for whiz classification. Neural network with back propagation was used for definition of whiz meaning. Another subject for detection of important moments of the match was concentration on the commentator’s basic tone. In case the commentator is really excited with the match, his basic speech tone automatically intensifies with every important action of the game. Analysis of commentator’s intensified basic speech tone was realized in this work too. Also the national hymns of teams playing against each other are a significant moment of the match. That is why detection of a hymn became another subject of analysis. Advantages of MFCC were used to obtain audio signal feature, from which 20 coefficients were gained. These were used as an entrance for classifier based on neural network with back propagation. For easy usage of these methods a graphic user interface with possibility of well-arranged look on gained results and also with possibility of replaying chosen section was created.

Hlavním cílem této diplomové práce byla texturní analýzou fundus snímku se zaměřením na směrovost vrstvy nervových vláken. Úvodní část popisuje fyziologii lidského oka a glaukomové onemocnění. Jedná se tedy o literární rešerši. Hlavní část této práce je pak zaměřena na metody texturní analýzy za účelem zobrazení směrovosti nervových vláken. Metody byly realizovány a otestovány v programovém prostředí Matlab R2009b.

The master's thesis focuses on vortical structures with cavitating core, which might develop in Francis turbines at non-optimal discharges in a form of unstable vortex cord. The cavitating vortex core is to be generated in a lab by flow rotation and a convergent nozzle. The objective of this thesis is to compare experimental results with mathematical model of pressure drop in vortical flow and with numerical calculation in Fluent based on finite volumes method. Other objective is to messure high frequency pressure vibrations generated by cavitating vortex core and spectrally analyze the data.

This master's thesis deals with phone call detection in recordings of radio broadcast data. I will introduce an approach, that will diarize broadcast record to segments with phone calls and segment where moderator speaks. Efficiency will be evaluated at frame level against manually annotated record.

This thesis deals with automated tuning of drive controller. To achieve this goal, system identification is needed. Therefore, the issue of identification is described at the beginning of this thesis. Spectral analysis was selected from many described methods. It was implemented in Matlab and also in C# language where was used averaging and Blackman-Tukey method. The C# application is linked to Beckhoff TwinCAT 3 and TwinCAT 2 runtime sytems that enable connections with real drive. Next, the problem of drive regulation is discussed and the results of using spectral analysis on real drives are shown. At the end of the thesis is described the algorithm of setting the speed controller with different types of frequency converters.

Pour évaluer l'impact d’un rejet accidentel ou chronique de polluants dans les écosystèmes, il est important d’étudier le dépôt sec des aérosols en milieu rural. Le manque de données expérimentales en milieu rural sur la vitesse de dépôt sec des particules ayant une taille inférieure à 1 μm conduit à des incertitudes au vu des modèles et de leurs différences, qui vont jusqu’à dépasser un ordre de grandeur. Le but de cette étude est de développer une mesure directe de la vitesse de dépôt sec des aérosols (Vd), notamment en utilisant un impacteur à basse pression (Electrical Low Pressure Impactor, ELPI, DEKATI), à travers des mesures expérimentales in situ. L’originalité de la méthode est le calcul des flux de dépôt par corrélation turbulente. Les vitesses de dépôt sec ont été obtenues pour des aérosols atmosphériques de tailles comprises entre 7 nm et 2 μm, sur un terrain plat dans le sud-ouest de la France, sous différentes conditions atmosphériques, ainsi que sur différents couverts (maïs, herbe, sol nu). Vd est analysée en fonction du diamètre des particules et l’impact des conditions micro météorologiques est étudié. / To evaluate the impact of accidental or chronic pollutant releases on ecosystems, we must study the dry deposition of aerosols in rural areas. The lack of experimental data on the dry deposition velocity of particle sizes below 1 μm over rural environments leads to uncertainties regarding models and differences between them, which exceed one order of magnitude. The aim of thisstudy is to develop a method, especially using an Electrical Low Pressure Impactor (Outdoor ELPI, DEKATI) to determine aerosol dry deposition velocities (Vd) over rural areas through experimental measurements. This method is based on eddy covariance flux calculation and spectral analysis correction. Dry deposition velocities were obtained for atmospheric aerosols sizing from 7 nm to2 μm, in the South-West of France on a flat terrain under varied meteorological conditions andvaried substrates (maize, grass and earth). Vd was analysed as a function of the particle diameters, and the impact of micrometeorological parameters was studied.

abstract: The human brain controls a person's actions and reactions. In this study, the main objective is to quantify reaction time towards a change of visual event and figuring out the inherent relationship between response time and corresponding brain activities. Furthermore, which parts of the human brain are responsible for the reaction time is also of interest. As electroencephalogram (EEG) signals are proportional to the change of brain functionalities with time, EEG signals from different locations of the brain are used as indicators of brain activities. As the different channels are from different parts of our brain, identifying most relevant channels can provide the idea of responsible brain locations. In this study, response time is estimated using EEG signal features from time, frequency and time-frequency domain. Regression-based estimation using the full data-set results in RMSE (Root Mean Square Error) of 99.5 milliseconds and a correlation value of 0.57. However, the addition of non-EEG features with the existing features gives RMSE of 101.7 ms and a correlation value of 0.58. Using the same analysis with a custom data-set provides RMSE of 135.7 milliseconds and a correlation value of 0.69. Classification-based estimation provides 79% & 72% of accuracy for binary and 3-class classication respectively. Classification of extremes (high-low) results in 95% of accuracy. Combining recursive feature elimination, tree-based feature importance, and mutual feature information method, important channels, and features are isolated based on the best result. As human response time is not solely dependent on brain activities, it requires additional information about the subject to improve the reaction time estimation. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2019