|
|
Detection of atrial fibrillation in short-term ECG
Ambrožová, Monika ; Janoušek, Oto (referee) ; Ronzhina, Marina (advisor)
Atrial fibrillation is diagnosed in 1-2% of the population, in next decades, it expects a significant increase in the number of patients with this arrhythmia in connection with the aging of the population and the higher incidence of some diseases that are considered as risk factors of atrial fibrillation. The aim of this work is to describe the problem of atrial fibrillation and the methods that allow its detection in the ECG record. In the first part of work there is a theory dealing with cardiac physiology and atrial fibrillation. There is also basic descreption of the detection of atrial fibrillation. In the practical part of work, there is described software for detection of atrial fibrillation, which is provided by BTL company. Furthermore, an atrial fibrillation detector is designed. Several parameters were selected to detect the variation of RR intervals. These are the parameters of the standard deviation, coefficient of skewness and kurtosis, coefficient of variation, root mean square of the successive differences, normalized absolute deviation, normalized absolute difference, median absolute deviation and entropy. Three different classification models were used: support vector machine (SVM), k-nearest neighbor (KNN) and discriminant analysis classification. The SVM classification model achieves the best results. Results of success indicators (sensitivity: 67.1%; specificity: 97.0%; F-measure: 66.8%; accuracy: 92.9%).
|
|
|
Use of value engineering elements for realization of building in the municipality
Chytková, Markéta ; Hanák,, Tomáš (referee) ; Puchýř, Bohumil (advisor)
The aim of my thesis Use of value engineering elements for the realization of buildings in the municipality is to compare the evaluation methods of procurement in municipality and evaluation methods using elements of value engineering. A tender for reconstruction Šubertovo square was realized in the city Dobruška. In the thesis is shown way of evaluation of competing offers of the city Dobruška itself in sublimit simplified procedure and evaluation of competing offers by selecting more evaluation criteria and selecting the best offer with the highest degree of effectiveness.
|
|
|
Statistical Classification Methods
Barvenčík, Oldřich ; Žák, Libor (referee) ; Michálek, Jaroslav (advisor)
The thesis deals with selected classification methods. The thesis describes the basis of cluster analysis, discriminant analysis and theory of classification trees. The usage is demonstrated by classification of simulated data, the calculation is made in the program STATISTICA. In practical part of the thesis there is the comparison of the methods for classification of real data files of various extent. Classification methods are used for solving of the real task – prediction of air pollution based of the weather forecast.
|
|
|
Automatic sleep scoring using polysomnographic data
Vávrová, Eva ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
The thesis is focused on analysis of polysomnographic signals based on extraction of chosen parameters in time, frequency and time-frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EMG and EOG signals recorded during different sleep stages. The parameters used for automatic classification of sleep stages are selected according to statistical analysis. The classification is realized by artificial neural networks, k-NN classifier and linear discriminant analysis. The program with a graphical user interface was created using Matlab.
|
|
|
Bankruptcy prediction modelling in construction business
Burdych, Filip ; Kuběnka,, Michal (referee) ; Karas, Michal (advisor)
This master thesis deals with bankruptcy prediction models for construction companies doing business in Czech Republic. Terms important for understanding the issue are defined in the theoretical part. In analytical part, there are five current bankruptcy prediction models tested on the analysed sample and resulted accuracy compared with original ones. On the basis of knowledges acquired, there is developed a brand-new bankruptcy prediction model.
|
|
|
Credit Risk Measurement in Manufacturing Industry Companies in the Czech Republic
Karas, Michal ; Dohnal, Mirko (referee) ; Hrvolová, Božena (referee) ; Myšková, Renáta (referee) ; Režňáková, Mária (advisor)
The purpose of this doctoral thesis is to create a new bankruptcy prediction model and also to design how to use this model for the purposes of credit risk measuring. The starting-point of this work is the analysis of traditional bankruptcy models. It was found out that the traditional bankruptcy model are not enough effective in the current economic conditions and it is necessary to create a new ones. Based on the identified deficiencies of the traditional models a set of two new model series was created. The first series of the created models is based on the use of parametric methods, and the second one is based on the use of newer nonparametric approach. Moreover, a set of factors which are able to identify an imminent bankruptcy was analyzed. It was found, that significant signs of imminent bankruptcy can be identified even five years before the bankruptcy occurs. Based on these findings a new model was created. This model incorporates variables of static and even dynamic character for bankruptcy prediction purposes. The overall classification accuracy of this model is 92.27% of correctly classified active companies and 95.65% of correctly classified bankrupt companies.
|
|
|
Processing of image sequences from fundus camera
Klimeš, Filip ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.
|
|
|
Bankruptcy Prediction Modelling in Construction Business
Srbová, Pavla ; Kuběnka,, Michal (referee) ; Karas, Michal (advisor)
The diploma thesis is aimed at creating a bankruptcy model for companies of the construction industry in the Czech Republic by using discriminant analysis. In the theoretical part, the concept of bankruptcy model is defined; this part is focused on the inclusion of bankruptcy models in economics, a look into their history, a description of selected models and a brief characteristic of the construction industry. In the practical part, the reliability of selected bankruptcy models is counted and a new bankruptcy model is built.
|
|
| |
|
|
Weighted Data Depth and Depth Based Discrimination
Vencálek, Ondřej ; Hlubinka, Daniel (advisor) ; Anděl, Jiří (referee) ; Malý, Marek (referee)
The concept of data depth provides a powerful nonparametric tool for multivariate data analysis. We propose a generalization of the well-known halfspace depth called weighted data depth. The weighted data depth is not affine invariant in general, but it has some useful properties as possible nonconvex central areas. We further discuss application of data depth methodology to solve discrimination problem. Several classifiers based on data depth are reviewed and one new classifier is proposed. The new classifier is a modification of k-nearest- neighbour classifier. Classifiers are compared in a short simulation study. Advantage gained from use of the weighted data depth for discrimination purposes is shown.
|
guest ::
