This thesis deals with the design of a sporttester, which is a device capable of calculating the cadence of the taken steps and monitoring the impact force of foot on the ground while running. Exposure to long-term strong impacts while running can cause serious fatigue fractures of the hip, calf bone or the foot area. The purpose of the sporttester is to monitor and signal strong impacts to the runner, thus helping to prevent fatigue fractures. The aforementioned features are evaluated based on the change in acceleration measured by the accelerometer. The calculated values of step cadence, running speed and impact force are sent via Bluetooth Low Energy to a compatible mobile application.

The paper details the usage of mmWave radars to track people and monitor their movement through predefined zones of interest. The theoretical part describes the physical nature of the technology and then describes algorithms which can be used to monitor using it to monitor the movement of people. In the practical part, I have developed a concrete algorithm which can be used to monitor customer queues and cash registers in shops and inform the cashiers when their presence is needed, as well as gather impersonal GDPR-compliant data about the customer's habits. Afterwards, I have developed a visualization for the Windows platform, which can be used to communicate with the radar, manage its configuration, visualize the events in real time and perform further analysis of the measured data.

This thesis dissert on traffic monitoring. There are couple of different methods of background extraction and four methods vehicle detection described here. Furthermore there is one method that describes vehicle counting. All of these methods was realized in Matlab where was created graphical user interface. One whole chapter is dedicated to process of practical realization. All methods are compared by set of testing videos. These videos are resulting in statistics which diagnoses about efficiency of single one method.

In this thesis, we deal with rainbow colorings of graphs. We engage not with the rainbow connection number but with counting of rainbow colorings in graphs with k colors. We introduce the rainbow polynomial and prove some results for some special graph classes. Furthermore, we obtain bounds for the rainbow polynomial. In addition, we define some edge colorings related to the rainbow coloring, like the s-rainbow coloring and the 2-rainbow coloring. For this edge colorings, polynomials are defined and we prove some basic properties for this polynomials and present some formulas for the calculation in special graph classes. In addition, we consider in this thesis counting problems related to the rainbow coloring like rainbow pairs and rainbow dependent sets. We introduce polynomials for this counting problems and present some general properties and formulas for special graph classes.

This project arose from the need to filter the sampled data and eliminate non-useful information in Serial Crystallography in Microfluidic Device (MFD)by using a portable optical detector placed around the channel. By testing sixteen different configurations, always using an LED as a source and a photodiode as a light sensor, changes in the channel due to the passage of air bubbles were detected. These changes corresponded to a 13,25% in relation to the changes due to light switching, with a gain factor of 10,11V/V. However, it was not sensitive enough to detect when a microcrystal passed through it, although it can detect bubbles and opens the door to design such sensors for these applications in the future.

Contrast agents are often crucial in medical imaging for disease diagnosis. Novel contrast agents, such as gold nanoparticles (AuNPs) and lanthanides, are being ex- plored for a variety of clinical applications. Preclinical testing of these contrast agents is necessary before being approved for use in humans, which requires the use of small animal imaging techniques. Small animal imaging demands the detection of these contrast agents in trace amounts at acceptable imaging time and radiation dose. Two such imaging techniques include x-ray fluorescence computed tomography (XFCT) and photon-counting CT (PCCT). XFCT combines the principles of CT with x-ray fluorescence by detecting fluorescent x-rays from contrast agents at various projections to reconstruct contrast agent maps. XFCT can image trace amounts of AuNPs but is limited to small animal imaging due to fluorescent x-ray attenuation and scatter. PCCT uses photon-counting detectors that separate the CT data into energy bins. This enables contrast agent detection by recognizing the energy dependence of x-ray attenuation in different materials, independent of AuNP depth, and can provide anatomical information that XFCT cannot. To achieve the best of both worlds, we modeled and built a table-top x-ray imaging system capable of simultaneous XFCT and PCCT imaging. We used Monte Carlo simulation software for the following work in XFCT imaging of AuNPs. We simulated XFCT induced by x-ray, electron, and proton beams scanning a small animal-sized object (phantom) containing AuNPs with Monte Carlo techniques. XFCT induced by x-rays resulted in the best image quality of AuNPs, however high-energy electron and medium-energy proton XFCT may be feasible for on-board x-ray fluorescence techniques during radiation therapy. We then simulated a scan of a phantom containing AuNPs on a table-top system to optimize the detector arrangement, size, and data acquisition strategy based on the resulting XFCT image quality and available detector equipment. To enable faster XFCT data acquisition, we separately simulated another AuNP phantom and determined the best collimator geometry for Au fluorescent x-ray detection. We also performed experiments on our table-top x-ray imaging system in the lab. Phantoms containing multiples of three lanthanide contrast agents were scanned on our tabletop x-ray imaging system using a photon-counting detector capable of sustaining high x-ray fluxes that enabled PCCT. We used a novel subtraction algorithm for reconstructing separate contrast agent maps; all lanthanides were distinct at low concentrations including gadolinium and holmium that are close in atomic number. Finally, we performed the first simultaneous XFCT and PCCT scan of a phantom and mice containing both gadolinium and gold based on the optimized parameters from our simulations. This dissertation outlines the development of our tabletop x-ray imaging system and the optimization of the complex parameters necessary to obtain XFCT and PCCT images of multiple contrast agents at biologically-relevant concentrations. / Graduate

La compréhension des mécanismes impliqués dans les cas sains, les maladies neurodégénératives ainsi que le développement de nouvelles approches thérapeutiques repose sur l’utilisation de modèles expérimentaux pertinents et de techniques d’imagerie adaptées. Dans ce contexte, la microscopie virtuelle offre la possibilité unique d’analyser ces modèles à l’échelle cellulaire avec une très grande variété de marquages histologiques. Mon projet de thèse consiste à mettre en place et à appliquer une méthode d’analyse d’images histologiques en couleur permettant de segmenter et de synthétiser l’information relative aux neurones à l’aide de l’anticorps NeuN sur des coupes de cerveau de macaque. Dans ce travail, nous appliquons d’abord la méthode de Random Forest (RF) pour segmenter les neurones ainsi que le tissu et le fond. Ensuite, nous proposons une méthode originale pour séparer les neurones qui sont accolés afin de les individualiser. Cette méthode s’adapte à l’ensemble des neurones présentant une taille variable (diamètre variant entre 5 et 30 μm). Elle est également efficace non seulement pour des régions dites « simples » caractérisées par une faible densité de neurones mais aussi pour des régions dites « complexes » caractérisées par une très forte densité de plusieurs milliers de neurones. Le travail suivant se concentre sur la création de cartes paramétriques synthétisant la morphologie et la distribution des neurones individualisés. Pour cela, un changement d’échelle est mis en œuvre afin de produire des cartographies présentant des résolutions spatiales plus faibles (résolution originale de 0,22 μm et cartographies créées proposant une résolution spatiale adaptative de quelques dizaines à quelques centaines de micromètres). Plusieurs dizaines de paramètres morphologiques (rayon moyen, surface, orientation, etc.) sont d’abord calculés pour chaque neurone ainsi que des paramètres colorimétriques. Ensuite, il est possible de synthétiser ces informations sous la forme de cartes paramétriques à plus basse résolution à l’échelle de régions anatomiques, de coupes voire, à terme, de cerveaux entiers. Cette étape transforme des images microscopiques qualitatives couleur en images mésoscopiques quantitatives, plus informatives et plus simples à analyser. Ce travail permet d’analyser statistiquement de très grands volumes de données, de synthétiser l’information sous la forme de cartographies quantitatives, d’analyser des problèmes extrêmement complexes tels que la mort neuronale et à terme de tester de nouveaux médicaments voire de confronter ces informations acquises post mortem avec des données acquises in vivo. / Understanding the mechanisms involved in healthy cases, neurodegenerative diseases and the development of new therapeutic approaches is based on the use of relevant experimental models and appropriate imaging techniques. In this context, virtual microscopy offers the unique possibility of analyzing these models at a cellular scale with a very wide variety of histological markers. My thesis project consists in carrying out and applying a method of analyzing colored histological images that can segment and synthesize information corresponding to neurons using the NeuN antibody on sections of the macaque brain. In this work, we first apply the Random Forest (RF) method to segment neurons as well as tissue and background. Then, we propose an original method to separate the touching or overlapping neurons in order to individualize them. This method is adapted to process neurons presenting a variable size (diameter varying between 5 and 30 μm). It is also effective not only for so-called "simple" regions characterized by a low density of neurons but also for so-called "complex" regions characterized by a very high density of several thousands of neurons. The next work focuses on the creation of parametric maps synthesizing the morphology and distribution of individualized neurons. For this purpose, a multiscale approach is implemented in order to produce maps with lower spatial resolutions (0.22 μm original resolution and created maps offering adaptive spatial resolution from a few dozens to a few hundred of micrometers). Several dozens of morphological parameters (mean radius, surface, orientation, etc.) are first computed as well as colorimetric parameters. Then, it is possible to synthesize this information in the form of lower-resolution parametric maps at the level of anatomical regions, sections and even, eventually, the entire brains. This step transforms qualitative color microscopic images to quantitative mesoscopic images, more informative and easier to analyze. This work makes it possible to statistically analyze very large volumes of data, to synthesize information in the form of quantitative maps, to analyze extremely complex problems such as neuronal death, to test new drugs and to compare this acquired information post mortem with data acquired in vivo.

No description available.

This licentiate thesis presents contributions to the luminosity measurement from the data recorded by the ATLAS detector in 2017 using a track-counting technique, as well as a search for dark matter in the ATLAS experiment using 139 fb-1 of √s = 13 TeV pp collision data delivered by the LHC from 2015 to 2018. Track-counting luminosity measurements in low-luminosity operations are performed to study the effect of low collision rates on luminosity determination. The luminosity measured in a calibration transfer procedure using the track-counting technique is used to correct the pile-up dependence observed in ATLAS’s main luminosity detector called LUCID. A search in the final state of a lepton, jets and missing transverse energy, where the final state is produced from a pair of top quarks and a spin-0 scalar/pseudoscalar mediator, is presented. A dedicated signal region is designed to target this final state in which the mediator decays into dark matter particles. The signal region covers the search in the mass plane of the mediator and the dark matter particle. Dedicated control regions are designed to estimate the top-quark background events, as well as the events where a Zboson is produced in association with the top quarks. The signal region event counts in the data have not been unblinded yet, but expected exclusion limits at 95% confidence level as a function of mediator mass are presented. Scalar and pseudoscalar mediators are expected to be excluded up to 200 and 250 GeV, respectively, for the dark matter mass of 1 GeV, and the coupling strengths of the mediator to the dark matter and Standard Model particles of 1.

No description available.