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Assessing Selected Indicators Using Statistical Methods
Bednářová, Veronika ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The diploma thesis is focused on the assessment of selected indicators using statistical methods. The first part is devoted to theoretical background, which describes financial indicators, time series analysis and regression and correlation analysis. The second part deals with the analysis of selected indicators and statistical analysis, which predicts the values of indicators for the next two years. Then correlation analysis is created, which determines the dependence between selected financial indicators. The last part is devoted to proposals leading to the improvement of the current situation of the company.
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Automated Detection of graphic elements in EEG signal
Jančová, Ivana ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with the analysis of EEG, namely detection of graphic elements. The aim of the thesis is to describe methods suitable for detection of graphic elements and implementation of the two methods in MATLAB. The first part of the thesis describes the basics rhythms, artifacts and epileptiform transients occurring in the EEG. The second part deals with the methods of detection and their mutual comparison. The discussed methods are spectral analysis, correlation analysis, wavelet transform, cluster analysis and matched filter. Other parts of the thesis describe the database PhysioBank and implementation of the correlation analysis and matched filter. In the last part is the comparison of the success of selected methods and comparison is done by calculating sensitivity and positive predictive value.
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Determinants of the Wage Development in the Regions of the Czech Republic
Brodová, Zuzana ; Dohnal, Mirko (referee) ; Luňáček, Jiří (advisor)
This master´s thesis deals with the creation of a model that explains the relationship between the amount of gross wages and selected economic factors in different regions of the Czech Republic. First part contains an explanation of terms of economic and statistical area. The second part deals with the creation of data basis and numerical model calculations. In this section the results of the analyzes are presented. The third part is focused on evaluation of the obteined results.
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Extraction of texture features aimed to detect glaucoma defects
Daněk, Daniel ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with an automatic method of texture analysis using Markov random fields texture modeling. The main aim of this work is to find out relevant textural features, which can be used for appropriate classification of the degree of retinal nerve fiber layer loss. The model of Markovian statistic uses a circular symmetric neighborhood structure and a least square error estimation of the model's parameter. Obtained textural features were quantitatively evaluated using correlation analysis. The results show, that there is a significant correlation between proposed textural features and RNFL thickness measured by OCT. Thus, the features can potentially serve for glaucoma diagnosis.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Mucha, Jakub ; Ponížilová, Veronika (referee) ; Doubravský, Karel (advisor)
This diploma thesis deals with the evaluation of the economic situation Šálek s.r.o. in the years 2013 to 2020. The theoretical part describes the financial indicators, time series, regression and correlation analysis. The analytical part contains calculations of financial indicators, some of which are subjected to static analysis, which is designed to determine the expected development of indicators in the next two years or to show the dependence between selected indicators. The last part of the thesis deals with proposals to improve the current economic situation of the company.
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Application of statistical analysis of speech in patients with Parkinson's disease
Bijota, Jan ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
This thesis deals with speech analysis of people who suffer from Parkinson’s disease. Purpose of this thesis is to obtain statistical sample of speech parameters which helps to determine if examined person is suffering from Parkinson’s disease. Statistical sample is based on hypokinetic dysarthria detection. For speech signal pre-processing DC-offset removal and pre-emphasis are used. The next step is to divide signal into frames. Phonation parameters, MFCC and PLP coefficients are used for characterization of framed speech signal. After parametrization the speech signal can be analyzed by statistical methods. For statistical analysis in this thesis Spearman’s and Pearson’s correlation coefficients, mutual information, Mann-Whitney U test and Student’s t-test are used. The thesis results are the groups of speech parameters for individual long czech vowels which are the best indicator of the difference between healthy person and patient suffering from Parkinson’s disease. These result can be helpful in medical diagnosis of a patient.
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Cryptanalysis using neural networks
Budík, Lukáš ; Mačák, Jaromír (referee) ; Martinásek, Zdeněk (advisor)
This dissertation deals with analysis of current side canal by means of neural network. First part describes basis of cryptografy and dilemma of side canal. In the second part is theoretickly described neural network and correlative analysis. Third part describes practical analysis of calibres of current side canals by means of classifier which uses neural network in Matlab surrounding. This classifier is confronted with classifier which uses correlative analysis.
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Water demand in water supply systems
Pikal, Martin ; Tureček, Jan (referee) ; Ručka, Jan (advisor)
Within this diploma thesis were evaluated factors, affecting consumption of drinking water from water supply system. Evaluation of time series of water consumption and chosen factors was performed using tools of mathematical statistics. In the last step was performed a dependence analysis of water consumption using artificial neuron network ANN. Diploma thesis was solved in cooperation with company Vodárenská akciová společnost, PLC and Severomoravské vodovody a kanalizace Ostrava, PCL.
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Assessing the Efficiency of a Company Using Statistical Method
Pastyřík, Jaroslav ; Kopka,, Radomír (referee) ; Doubravský, Karel (advisor)
The master’s thesis deals with the evaluation of financial efficiency of the company Bučovice Tools, a.s. using statistical methods. The theoretical part describes financial analysis, time series analysis, regression analysis and correlation analysis. In the practical part, the selected indicators of financial analysis are subjected to statistical analysis to detect dependence between indicators and to determine the prediction of the future development. Based on the financial results, the company is compared with a chosen company and with average indicators of the industry and are designed possibilities to improve the economic situation.
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Power analysis attack on masked AES implementation
Jakubíková, Radka ; Dzurenda, Petr (referee) ; Martinásek, Zdeněk (advisor)
The cryptographic algorithms are commonly used as a security item today. In some situations, the special device is used to run the cryptographic algorithm, so the data are protected against the attack from the internet. Naturally, the attack can be loaded on the device as well using the side channel attack. The data are under the great danger, because nowadays plenty of power consumption analyses exist. The side channel attack uses knowledge about the cryptographic algoritm and simple or differential analysis. The diploma thesis focuses on the differential power analysis attack for the data published under the DPA contest. This thesis covers different types of analyss and attacks, and describes the new DPACv4.2 implementation. The correlation analysis is presented for the DPACv4.2 and the possible attack is discussed at the conclusion.
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