This master’s thesis takes aim with the use of statistical methods for progression evaluation of Parkinson’s disease. There is a brief description of Parkinson’s disease. It is further stated processing and evaluation of values of speech parameters which are affected by Parkinson’s disease. The thesis describes the process using the values of classification and regression trees and evaluate results using the mean absolute error and estimated error. Processing and evaluation of values was done in MATLAB software.

This thesis describes searching for high-risk clusters of portals in the Ingress game by using data mining techniques. The work contains background for descibed problematics and methods and experiments used to search for theese information.

The Operable Unit 5 (OU 5) area of Hill Air Force Base currently has two trichloroethene-contaminated groundwater plumes underneath residential areas in Sunset and Clinton, Utah. Bioremediation by biological reductive dechlorination can be an important mechanism for the removal of chlorinated compounds from the plumes. The presence of suitable bacteria to carry on reductive dechlorination is the key in the bioremediation process. The goal of this study was to determine the distribution and population density of the 16S rRNA genes of Bacteria, Dehalococcoides ethenogenes, Desulfuromonas michiganensis, Geobacter spp and Rhodoferax ferrireducens-like bacteria, as well as the functional genes trichloroethene reductive dehalogenase (tceA) and vinyl chloride reductase gene (vcrA). This study also evaluated the influence of the physical-chemical properties of the OU 5 aquifer material on the observed bacterial distribution. Twenty OU 5 soil cores were obtained from a 14-ha area that included a trichloroethene (TCE) plume. DNA was extracted from each core. Molecular analysis with qRT-PCR was used to quantify the densities of the mentioned 16S rRNA and functional genes. Separately, total arsenic and iron in the II and II+III oxidation states were extracted by two methods (HCl and hydroxylamine HCl in HCl) in each core. Concentrations of TCE, cis-dichloroethene (cis-DCE), vinyl chloride (VC) and ethane in well water were included. Dehalococcoides population density was low and its distribution was uneven with densities lower than 3.2x104 copies/g (detection limit of 2.5x103). D. michiganensis distribution was not uniform but was clustered near the TCE-source area with densities of 7.9x103-1x105 copies/g (detection limit of 6.3x103). Geobacter spp. distribution was uneven but broader, with densities of 4x103-1.6x106 copies/g (detection limit of 3.2x103). The vcrA gene distribution was relatively uniform and broad. Densities were the lowest measured (detection limit of 63 copies/g). TceA was measured in two cores with densities close to detection limit of 1.6x103 copies/g. Rhodoferax ferrireducens-like bacteria had a broader distribution with the highest densities of 1.6x106-1.3x108 copies/g (detection limit of 7.9x103). Total Bacteria were measured in all cores with densities 3.2x104-3.2x106 copies/g (detection limit of 1x103). Three multivariate statistical methods were used to determine the effect of physical-chemical properties on the target gene distributions. Cluster and discriminant analysis selected five properties (pH, sand and silt content, NO3--N and NH4+-N) as the most discriminating factors among thirty-one physical-chemical properties. However, no effect in the bacterial distribution was observed. The tree classification method identified nine variables that described higher or lower densities of the target genes. Variables such as Bacteria, Fe(II+III) (by hydroxylamine HCl in HCl), organic matter and cis-DCE were selected by the method.. All methods agreed on the selection of pH and sand content as the physical/chemical factors most influencing in the bacterial distribution. Based on the findings of low densities of dechlorinating bacteria and dechlorinating-associated functional genes, low available carbon donor and sandy mineral composition, the partial TCE-dechlorination at this site can be ascribed to the nature of the site and incomplete set of required factors for complete reductive dechlorination.

Nacionalinių mokinių pasiekimų tyrimo metodologija yra nuolat plėtojama. Pasitarus su Švietimo plėtotės centro tyrimo skyriaus darbuotojais, buvo nuspręsta įsigilinti į klasterinės ir diskriminantinės analizės metodus, jų pritaikomumą nacionalinių tyrimų rezultatų analizei. Tai įtakojo šio darbo pasirinkimą ir tikslą - susipažinti su Klasterinės ir Diskriminantinės analizės metodais, pateikti ir aptarti jų taikymo pavyzdžius. Darbe išnagrinėti du daugiamačiai statistiniai metodai: klasterinė ir diskriminantinė analizė. Yra aptarti šių metodų teoriniai aspektai bei pateikti originalūs šių metodų pritaikymo mokinių pasiekimų tyrimams pavyzdžiai. Padarytos išvados apie šių metodų pritaikomumą nacionalinių mokinių pasiekimų tyrimo analizei atlikti. / National research of student marches are continually evolving. With Educational evolve center’s help I decided to analyse Cluster and Disckriminant analysis methods and how they can be used in National research analysis. This was a reason of my work purpose - to have a look at Cluster and Disckriminant analysis methods, to offer examples of practical use. There are two statistical multidimensional methods discussed in this work (Cluster and Disckriminant analysis). There are discussed theoretical side of these methods, also you can find original examples of practical use. In conclusion I discuss about practical use of these methods in national research of student marches.

This thesis focuses on classification and evaluation of brownfiled sites in the South region in the Czech republic. The thesis is divided into two parts, theoretical and practical. The theoretical part is aimed at defining the issues of brownfields, particulary to the development and current status of brownfileds not only in the South region. The classification of brownfields is part of the chapter. In the second part is applied the model based on the scoring of the parameters.

The aim of my thesis is to aprise the reader with the meaning and purpose of classification of accommodation in the Czech Republic. I am trying to compare the classification of 2009 with the present classification valid since 2010 till 2012 but also with classifications of other countries. For this comparison I chose the classification of the accommodation in Great Britain which is according my opinion very detailed but also with the classification of other, mainly European countries (with the American classification I compare the classification only in general terms).

Automated recognition of selected terrain features from their cartographic representation. This diploma thesis is dedicated to automatic classification of selected terrain shapes and their cartographic representation. The main aim of this thesis is to design methodological approach for automatic recognition of terrain shapes (hills and valleys) with the use of Machine Learning (Deep Learning). The first part of suggested method divides rough terrain segmentation into two categories, which will be then classified with convolutional neural network. The second part of the thesis is dedicated to the very classification of pre-segmented terrain shapes using Machine Learning. Both parts of the processing are using photos SRTM30 as an input data. The whole proposed method was developed in Python programming language with the usage of Arcpy, TensorFlow and Keras libraries. Keywords: Digital cartography, GIS, terrain shapes, Machine Learning, Deep Learning, recognition, classification, segmentation

The thesis is focused on methods of machine learning used for recognising the first stage of schizophrenia in images from nuclear-magnetic resonance. The introduction of this paper is focused primarily on physical principles. Further in this work, the attention is given to registration methods, reduction of data set and machine learning. In the classification part, simmilarity rates, support vectors´ method, K-nearest neighbour classification and K-means are described. The last stage of theoretical part is focused on evaluation of the clasification. In practical part the results of reduction data set by methods PCA, CRLS-PCA and subjects PCA are described. Furthermore, the practical part is focused on pattern recognition by methods K-NN, K-means and test K-NN method on real data. Abnormalities which are recognised by some classification methods can distinguish patients with schizophrenia from healthy controls.

Segmentation of the vasculature is an important step in the process of the retinal image analysis.Theresultsoftheanalysiscanbeusedtodiagnoseseveraleyeandcardiovascular diseases. The aim of this thesis is to search for possibilities in video-sequences from experimental fundus camera.

Segmentation of the vasculature is an important step in the process of the retinal image analysis.Theresultsoftheanalysiscanbeusedtodiagnoseseveraleyeandcardiovascular diseases. The aim of this thesis is to search for possibilities in video-sequences from experimental fundus camera.