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Bidirectional path planning
Semeniuk, Andrii ; Nevoral, Tomáš (referee) ; Dvořák, Jiří (advisor)
This bachelor thesis deals with path planning of a mobile robot using artificial intelligence algorithms. The theoretical part describes different approaches to path planning with a focus on their bidirectional modifications. Furthermore, attention is paid to selected algorithms. In the practical part of the thesis, the emphasis is on the comparison of the selected algorithms by carrying out experiments in a self-developed simulation environment.
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Artefacts Removal from Brain EEG Signals Using Adaptive Algorithms
Hatala, Juraj ; Jawed, Soyiba (referee) ; Shakil, Sadia (advisor)
Tato práce se zabývá problémem artefaktů ve záznamech elektroencefalografie (EEG) a metodami jejich odstranění s důrazem na adaptivní filtrace. Artefakty jsou neodmys- litelnou součástí metody EEG a negativně ovlivňují analýzu výsledků tím, že překrývají zájmové mozkové signály. Adaptivní filtrace je všestrannou metodou, kterou lze použít pro odstranění těchto artefaktů, pokud je k dispozici referenční signál korelovaný s arte- faktem. Hlavním cílem této práce je návrh a implementace frameworku, který umožní aplikaci metod adaptivní filtrace na EEG data. Druhotným cílem je posouzení účinnosti nového algoritmu Q-LMS při odstraňování artefaktů z EEG, protože dosud nebyl v tomto scénáři použit. Práce představuje knihovnu v prostředí Python pro adaptivní filtrace EEG a ukazuje a hodnotí experimenty pro scénáře odstraňování artefaktů s použitím Q-LMS fil- tru implementovaného v navržené knihovně. V této knihovně je uživatel schopen vytvářet přizpůsobitelné filtrační pipeliny. Knihovna nabízí různé adaptivní filtry a metody vytváření referenčního signálu s důrazem na zpracování neurologických dat ve formátu BIDS. Uži- vatel však může sdílet vlastní filtry s frameworkem a také používat vlastní vstupní data a referenční signály. Experimenty s Q-LMS algoritmem ukázaly, že se jedná o dobře fun- gující adaptivní algoritmus, avšak výsledky filtrace byly průměrný ve srovnání s výsledky dosaženými jinými standardními adaptivními algoritmy
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Algoritmy bezeztrátové komprese a jejich vizualizace
Košvica, David
This work introduces the area of lossless compression algorithms and aims to create a visualization of an algorithm that belongs to this category. The algorithm that was chosen for visualization purposes was an algorithm named Arithmetic coding and its visualization was implemented as a web application running inside a web browser.
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Polynomial time primality testing
Bednaříková, Alžběta ; Žemlička, Jan (advisor) ; Čech, Martin (referee)
The topic of my thesis is the testing of prime numbers in polynomial time. The text focuses on the specific algorithm published in 2002 by Manindra Agrawal, Neeraj Kayal and Nitin Saxena and it is known as the AKS primality test. In the introduction of this work, important properties and concepts essential for the text understanding are revised. Then the basic idea of the test is explained. The description of the algorithm itself continues. The aim of the work is to prove the Theorem on the correctness of the AKS test from a gradually built-up theory and to calculate the time complexity of the algorithm. Finally, it is proved that the calculated time complexity is polynomial.
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Advanced methods of mobile robot path planning
Maňáková, Lenka ; Šoustek, Petr (referee) ; Dvořák, Jiří (advisor)
This work is focused on advanced methods of mobile robot's path planning. The theoretical part describes selected graphical methods, which are useful for speeding up the process of finding the shortest paths, for example through reduction of explored nodes of the state space. In the practical part was created simulate environment in the Python language and in this environment, selected algorithms was implemented.
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Knowledge Discovery in Text
Smékal, Luděk ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This MSc Thesis handles with so-called data mining. Data mining is about obtaining some data or informations from databases, where these data or informations are not directly visible, but they are accessible by using special algorithms. This MSc Thesis mainly aims documents clasifying by selected method in scope of digital library. The selected method is based on sets of items called "itemsets method". This method extends Apriori algorithm application field originally designed for transaction databases processing and generation of sets of frequented items.
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Knowledge Discovery from Process Logs
Kluska, Martin ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
This Master's describes knownledge discovery from process logs by using process mining algorithms. Chosen algorithms are described in detail. These aim to create process model based on event log analysis. The goal is to design such components, which would be able to import the process and run the simulations. Results from components can be used for short term planning.
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RNA secondary structure prediction
Hadwigerová, Michaela ; Provazník, Ivo (referee) ; Maděránková, Denisa (advisor)
Since the time RNA has been discovered by the nature scientist Miescher the structure and function of it has been forgotten for a long time. The prime role in science had always DNA. An increase of interest in RNA came with the discovery of the tRNA structure and its catalytic and enzymatic properties. These discoveries led to a great development wave of bioinformatics and structure and function analysis of RNA.
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