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Biomedical data visualization using Matlab
Zvončák, Vojtěch ; Mekyska, Jiří (referee) ; Galáž, Zoltán (advisor)
The thesis deals with the visualization of biomedical data in MATLAB environment. The thesis contains following statistical methods and their descriptions: P-P plot, Q-Q plot, histogram, box plot, kernel denstity estimation, scatter plot and several time series metrics. Some functions are programmed from buil-in functions of MATLAB and others using external functions, which are changed to fit to this thesis’s purpose. First part of the thesis conserns theoretical background, whereas the second part conserns practical programmed realizations of mentioned functions. The program contains a graphical user interface - GUI, which the thesis describes in detail. The purpose of the GUI is to ensure ease of use and also data processing. The output graphs of GUI are shown in chapter 5. The last part deals with the possible extensions of the program.
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Game Web Portal - Object-oriented Programming
Hůla, Vladimír ; Galáž, Zoltán (referee) ; Povoda, Lukáš (advisor)
This thesis deals with design and implementation of programming structure of game web portal. The web portal will serve as a communication and information center to simplify coordination among players and allow them to gain new experience. In the thesis are analyzed the needs of players, existing solutions and their drawbacks. The results of this analysis are used to design individual functions of the portal. Implementation of the most important parts of the website has been described, the implementation of these parts were evaluated and some enhancemets were eventually suggested. In the end of this thesis several functionalities were suggested, which could extend the portal in the future.
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Visualization of multidimensional data using web technologies
Burian, Vojtěch ; Galáž, Zoltán (referee) ; Mžourek, Zdeněk (advisor)
Scope of this work is the problematic of data visualization. Data visualization is a useful tool to present and gather new information and thus get to better decisions. In theoretical part, data analysis topics are dealt with. Then specific types of graphs are listed and explained, and in next part problems with graph creation are pinpointed. Basics of graphic and web design are also mentioned. Practical part is focused on visualization of data of processed results of speech analysis, gathered from patients with Parkinson disease. Because majority of people in medical industry do not have, or is not able to work with specialized software (such as Matlab), outputs in HTML table and SVG format were created based on Python programming language. Both these parts are accommodated into webpage, which can be easily opened in web browser installed in most of computers regardless of operation system used.
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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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Acoustic analysis of poem recitation in patients with Parkinson's disease
Mucha, Ján ; Smékal, Zdeněk (referee) ; Galáž, Zoltán (advisor)
Diploma thesis is focused on the acoustic analysis of poetry recitation in patients with Parkinson's disease. This disease is associated with speech disorder called hypokinetic dysarthria. One objective of this thesis was familiarization with process, symptoms and treatment of these diseases. In thesis is described preprocessing and parametrization of the speech signal and the binary classification methods. Subsequently, it is the above proposal modular system of auto-diagnosis of Parkinson's disease based on acoustic analysis of the speech. The proposed system is implemented in MATLAB. Classification of calculated parameters is realized using the method of Random forest and Support vector machine. The results of these methods are compared and listed in the thesis. The main objective and the result of this thesis is a system of automatic diagnosis of Parkinson's disease based on acoustic analysis of the poem recitation.
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Calculation of speech rate
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
his semestral thesis deals with a design of system for calculating the rate of speech. The sys-tem consists of several block, such as signal pre-processing block and its segmentation into smaller parts, block of the feature calculation, block of the feature vector quantization and finally block calculating the actual rate. The first step is a change of the input speech signal into a form suitable for the feature extraction. In next step these features are assigned to the calculated centroids. The change of centroid means change of phonemes. The system will record the following boundaries of fonems contained in speech and calculates its rate.
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Improved Prediction of Social Tags Using Data Mining
Harár, Pavol ; Galáž, Zoltán (referee) ; Kříž, Jiří (advisor)
This master’s thesis deals with using Text mining as a method to predict tags of articles. It describes the iterative way of handling big data files, parsing the data, cleaning the data and scoring of terms in article using TF-IDF. It describes in detail the flow of program written in programming language Python 3.4.3. The result of processing more than 1 million articles from Wikipedia database is a dictionary of English terms. By using this dictionary one is capable of determining the most important terms from article in corpus of articles. Relevancy of consequent tags proves the method used in this case.
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Analysis of hand-written text of patients with neurological disorders
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
The master‘s thesis deals with the analysis of the hand-written text. There is a design and a realization of a system for the purpose of diagnosing a Parkinson’s desease based on the analysis of hand-written text. The system consists from several modules and it is programmed in the programming environment of MATLAB. The first module provides pre-processing of the records to adjust records to the form suitable for the segmentation. Afterwards, the records are divided into those with signals onto the surface of the tablet and those with the signals above the surface of the tablet. In the next module the records are segmented by the two-phase metod of automatic segmentation.High-level featuresare calculated from the extracted features. The results of the statistical analysis are exported in the form suitable for the classification process. The classification is performed by the proposed model made in the programming environment of RapidMiner. The output of designed system is the trained model capable of automatic classification of the Parkinson’s disease by the analysis of the hand-written text.
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Analysis of hand-written text of patients with neurological disorders
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
The master‘s thesis deals with the analysis of the hand-written text. There is a design and a realization of a system for the purpose of diagnosing a Parkinson’s desease based on the analysis of hand-written text. The system consists from several modules and it is programmed in the programming environment of MATLAB. The first module provides pre-processing of the records to adjust records to the form suitable for the segmentation. Afterwards, the records are divided into those with signals onto the surface of the tablet and those with the signals above the surface of the tablet. In the next module the records are segmented by the two-phase metod of automatic segmentation.High-level featuresare calculated from the extracted features. The results of the statistical analysis are exported in the form suitable for the classification process. The classification is performed by the proposed model made in the programming environment of RapidMiner. The output of designed system is the trained model capable of automatic classification of the Parkinson’s disease by the analysis of the hand-written text.
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Preliminary Acoustic Analysis of Noise Components in Patients with Parkinson's Disease
Galáž, Z.
This paper deals with acoustic analysis of noise components extracted from speech signals of patients with Parkinson’s disease (PD) who recited a poem. Experimental dataset consisted of 97 PD patients with different disease progress and 55 healthy controls (HC). The analysis is based on parametrization of 2 rhymes recitation using dysphonia features. We obtained classification accuracy 76.66% for female speakers, 69.65% for male speakers and 69.24% for the mixture of both genders.
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