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Comparison of Pharmacokinetic models for DCE-MRI
Bačovská, Kristýna ; Mézl, Martin (referee) ; Jiřík, Radovan (advisor)
This thesis deals with perfusion analysis using DCE-MRI (Dynamic contrast-enhanced magnetic resonance imaging). DCE-MRI is commonly used for microcirculation evaluation mainly in oncology and in recent years also in cardiology. The theoretical overview focuses on the issue of pharmacokinetic modeling and the estimation of perfusion parameters using selected models. The experimental part describes research software PerfLab and then it is aimed at the proposed program for synthetic data generation. Simulated data obtained under ideal conditions and in the presence of noise were used to compare models for the accuracy and reliability of DCE-MRI analysis.
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Framework for Data Generators
Kříž, Blažej ; Ráb, Jaroslav (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis is focused on the problem of data generation. At the beginning, it presents several applications for data generation and describes the data generation process. Then it deals with development of framework for data generators and demonstrational application for validating the framework.
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Image-Based Clustering of Microbial Colonies
Láncoš, Jan ; Kišš, Martin (referee) ; Beneš, Karel (advisor)
Laboratorní analýza mikrobiálních kolonií pěstovaných na Petriho miskách je v současné době předmětem intenzivního výzkumu ve snaze o dosažení totální laboratorní automatizace. Jádro tohoto problému spočívá v přesné lokalizaci kolonií při obrazové analýze. Současná řešení nejčastěji využívají strojové učení, které je však obecně závislé na kvalitních datech, kterých je v tomto odvětví k dispozici jen velmi málo. Abych adresoval tento problém, vytvořil jsem víceúčelový generátor syntetických dat. Úspěšně jsem jej aplikoval jak při segmentaci tak při shlukování kolonií. Výsledné segmentační F1 skóre se mi podařilo navýšit z 0,518 na 0,729 a při shlukování jsem s využitím této segmentace dosáhl V-measure skóre 0,830. Prací navržený přístup ke generování syntetických dat nás posouvá o krok blíže k plné laboratorní automatizaci.
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Automatic Generation of Synthetic XML Documents
Betík, Roman ; Holubová, Irena (advisor) ; Svoboda, Martin (referee)
The aim of this thesis is to research the current possibilities and limitations of automatic generation of synthetic XML and JSON documents used in the area of Big Data. The first part of the work discusses the properties of the most used XML data generators, Big Data and JSON generators and compares them. The next part of the thesis proposes an algorithm for data generation of semistructured data. The main focus of the algorithm is on the parallel execution of the generation process while preserving the ability to control the contents of the generated documents. The data generator can also use samples of real data in the generation of the synthetic data and is also capable of automatic creation of simple references between JSON documents. The last part of the thesis provides the results of experiments with the data generator exploited for the purpose of testing database MongoDB, describes its added value and compares it to other solutions. Powered by TCPDF (www.tcpdf.org)
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Comparison of Pharmacokinetic models for DCE-MRI
Bačovská, Kristýna ; Mézl, Martin (referee) ; Jiřík, Radovan (advisor)
This thesis deals with perfusion analysis using DCE-MRI (Dynamic contrast-enhanced magnetic resonance imaging). DCE-MRI is commonly used for microcirculation evaluation mainly in oncology and in recent years also in cardiology. The theoretical overview focuses on the issue of pharmacokinetic modeling and the estimation of perfusion parameters using selected models. The experimental part describes research software PerfLab and then it is aimed at the proposed program for synthetic data generation. Simulated data obtained under ideal conditions and in the presence of noise were used to compare models for the accuracy and reliability of DCE-MRI analysis.
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Comparison of Approaches to Synthetic Data Generation
Šejvlová, Ludmila ; Šimůnek, Milan (advisor) ; Pavlíčková, Jarmila (referee)
The diploma thesis deals with synthetic data, selected approaches to their generation together with a practical task of data generation. The goal of the thesis is to describe the selected approaches to data generation, capture their key advantages and disadvantages and compare the individual approaches to each other. The practical part of the thesis describes generation of synthetic data for teaching knowledge discovery using databases. The thesis includes a basic description of synthetic data and thoroughly explains the process of their generation. The approaches selected for further examination are random data generation, the statistical approach, data generation languages and the ReverseMiner tool. The thesis also describes the practical usage of synthetic data and the suitability of each approach for certain purposes. Within this thesis, educational data Hotel SD were created using the ReverseMiner tool. The data contain relations discoverable with SD (set-difference) GUHA-procedures.
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Automatic Generation of Synthetic XML Documents
Betík, Roman ; Holubová, Irena (advisor) ; Svoboda, Martin (referee)
The aim of this thesis is to research the current possibilities and limitations of automatic generation of synthetic XML and JSON documents used in the area of Big Data. The first part of the work discusses the properties of the most used XML data generators, Big Data and JSON generators and compares them. The next part of the thesis proposes an algorithm for data generation of semistructured data. The main focus of the algorithm is on the parallel execution of the generation process while preserving the ability to control the contents of the generated documents. The data generator can also use samples of real data in the generation of the synthetic data and is also capable of automatic creation of simple references between JSON documents. The last part of the thesis provides the results of experiments with the data generator exploited for the purpose of testing database MongoDB, describes its added value and compares it to other solutions. Powered by TCPDF (www.tcpdf.org)
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Polarization analysis of strong ground motions recorded during the aftershock sequence of the 2009 L'Aquila earthquake
Čejka, František ; Gallovič, František (advisor) ; Zahradník, Jiří (referee)
During broadband modelling of selected events from the aftershock sequence of the l'Aquila earthquake using 1-D model of media, we observe interesting difference between model and real particle polarization on high frequencies. There are two basic types of these polarization disorders. Polarization of particle motion keeps its linear form, but changes its direction or linear polarization changes its linear form to circle polarization. It offers the explanation that these disorders of polarization occur due to the 3D heterogeneities in the crust. In this work, we analyze polarization of published synthetic seismograms modeled with random 3D heterogenitites. It has been shown that the biggest disorders occur in directions in which parcticle movement heads toward the source, and that we can find examples, which qualitatively explain observed polarization disorders.
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Automatic Generation of Synthetic XML Documents
Betík, Roman ; Holubová, Irena (advisor) ; Klímek, Jakub (referee)
The aim of this thesis is to research the current possibilities and limitations of automatic generation of synthetic XML documents. The first part of the work discusses the properties of the most used XML data generators and compares them to each other. The next part of the thesis proposes an algorithm for XML data generation which focuses on subset of the main XML data characteristics (number of elements, number of attributes, fan-out, mixed contents etc.). The main target of the algorithm is to generate XML documents using a set of settings which are easy to understand. The last part of the work compares the proposed solution with the existing ones. The comparison focuses on how easy it is to generate XML documents, what structures can be created and finally it compares properties of the similar XML data created using different XML data generators. Powered by TCPDF (www.tcpdf.org)
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Automatic Generation of Synthetic XML Documents
Betík, Roman ; Holubová, Irena (advisor) ; Malý, Jakub (referee)
The aim of this thesis is to research the current possibilities and limitations of automatic generation of synthetic XML documents. The first part of the work discusses the properties of the most used XML data generators and compares them to each other. The next part of the thesis proposes an algorithm for XML data generation which focuses on subset of the main XML data characteristics (number of elements, number of attributes, fan-out, mixed contents etc.). The main target of the algorithm is to generate XML documents using a set of settings which are easy to understand. The last part of the work compares the proposed solution with the existing ones. The comparison focuses on how easy it is to generate XML documents, what structures can be created and finally it compares properties of the similar XML data created using different XML data generators. Powered by TCPDF (www.tcpdf.org)
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