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Anion-exchange enabled tuning of caesium lead mixed-halide perovskites for high-energy radiation detection
Matula, Radovan ; Friák, Martin (oponent) ; Dvořák, Petr (vedoucí práce)
Lead halide perovskites (LHPs) with their unprecedented functional qualities which are only enhanced by the simple band gap tuning, have taken the world of semiconductors by storm. The process of anion exchange, possible even post-synthesis, allows for band gap tuning of LHPs, resulting in lead mixed-halide perovskites (LMHPs), thus expanding their potential for applications, notably in tuneable detectors. The widespread adoption of LMHPs is, however, hindered by their chemical instability, which leads to halide segregation in the material, seriously inhibiting reliable operation of any LMHP-based device. Understanding the kinetics of the halide segregation over extended periods remains a challenge, motivating the use of theoretical simulations like Monte Carlo (MC) methods. Yet, MC simulations rely on well-defined potential energy surfaces (PES), typically derived from computationally intensive density functional theory (DFT) calculations. In this thesis, we propose a novel approach for constructing well-defined PES from high-fidelity DFT data with fraction of the computational load. Utilizing activation-relaxation technique noveau (ARTn) motivated searches for transition points in the PES combined with state-of-the-art machine learning approaches, we aim to to significantly reduce computational costs. Additionally, employing classical theory, we assess the detection capabilities of selected LMHPs.
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Porovnání klasifikačních metod
Dočekal, Martin ; Zendulka, Jaroslav (oponent) ; Burgetová, Ivana (vedoucí práce)
Tato práce se zabývá porovnáním klasifikátorů. Nejprve jsou popsány klasifikační techniky založené na strojovém učení, poté je navržen a implementován systém pro porovnání klasifikátorů. Dále jsou popsány klasifikační úlohy a datové sady, na kterých je systém otestován. Vyhodnocení je prováděno pomocí standardních metrik. V rámci práce je též navržen a implementován klasifikátor založený na principu evolučních algoritmů.
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Pilot proficiency classification from gaze
Ruta, Dominik ; Vlk, Jan (oponent) ; Chudý, Peter (vedoucí práce)
This work deals with the classification of pilot proficiency level and basic flight maneuvers from gaze. The goal is to provide additional valuable tool for aviation instructors to evaluate proficiency of pilot students and provides them with feedback. This idea is based on results of numerous relevant studies, which discovered correlation between effective scanning patterns and domain performance. This thesis considers two proficiency levels~---~amateur and experienced. This work utilizes common analysis metrics of visual scanning and machine-learning classification techniques. The Support Vector Machine algorithm is used for the proficiency classification and Hidden Markov Models are utilized in basic flight maneuvers classification. The result of this thesis is a high accuracy proficiency classification and good ability to distinguish between individual basic flight maneuvers performed by pilots.
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Mining of soluble enzymes from genomic databases
Hon, Jiří ; Brejová, Bronislava (oponent) ; Šafránek, David (oponent) ; Zendulka, Jaroslav (vedoucí práce)
Enzymes are proteins accelerating chemical reactions, which makes them attractive targets for both pharmaceutical and industrial applications. The enzyme function is mediated by several essential amino acids which form the optimal chemical environment to catalyse the reaction. In this work, two integrated bioinformatics tools for mining and rational selection of novel soluble enzymes, EnzymeMiner and SoluProt, are presented. EnzymeMiner uses one or more enzyme sequences as input along with a description of essential residues to search the protein database. The description of essential amino acids is used to increase the probability of similar enzymatic function. EnzymeMiner output is a set of annotated database hits. EnzymeMiner integrates taxonomic, environmental, and protein domain annotations to facilitate selection of promising targets for experiments. The main prioritization criterion is solubility predicted by the second tool being presented, SoluProt. SoluProt is a machine-learning method for the prediction of soluble protein expression in Escherichia coli . The input is a protein sequence and the output is the probability of such protein to be soluble. SoluProt exploits a gradient boosting machine to decide on the output prediction class. The tool was trained on TargetTrack database. When evaluated against a balanced independent test set derived from the NESG database, SoluProt accuracy was 58.5% and its AUC 0.62, slightly exceeding those of a suite of alternative solubility prediction tools. Both EnzymeMiner and SoluProt are frequently used by the protein engineering community to find novel soluble biocatalysts for chemical reactions. These have a great potential to decrease energetic consumption and environmental burden of many industrial chemical processes.
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Pilot proficiency classification from gaze
Ruta, Dominik ; Vlk, Jan (oponent) ; Chudý, Peter (vedoucí práce)
This work deals with the classification of pilot proficiency level and basic flight maneuvers from gaze. The goal is to provide additional valuable tool for aviation instructors to evaluate proficiency of pilot students and provides them with feedback. This idea is based on results of numerous relevant studies, which discovered correlation between effective scanning patterns and domain performance. This thesis considers two proficiency levels~---~amateur and experienced. This work utilizes common analysis metrics of visual scanning and machine-learning classification techniques. The Support Vector Machine algorithm is used for the proficiency classification and Hidden Markov Models are utilized in basic flight maneuvers classification. The result of this thesis is a high accuracy proficiency classification and good ability to distinguish between individual basic flight maneuvers performed by pilots.
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Porovnání klasifikačních metod
Dočekal, Martin ; Zendulka, Jaroslav (oponent) ; Burgetová, Ivana (vedoucí práce)
Tato práce se zabývá porovnáním klasifikátorů. Nejprve jsou popsány klasifikační techniky založené na strojovém učení, poté je navržen a implementován systém pro porovnání klasifikátorů. Dále jsou popsány klasifikační úlohy a datové sady, na kterých je systém otestován. Vyhodnocení je prováděno pomocí standardních metrik. V rámci práce je též navržen a implementován klasifikátor založený na principu evolučních algoritmů.
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ITAT 2014. Information Technologies - Applications and Theory. Part II
Kůrková, Věra ; Bajer, Lukáš ; Peška, L. ; Vojtáš, P. ; Holeňa, Martin ; Nehéz, M.
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague : Institute of Computer Science AS CR, 2014. 145 p. ISBN 978-80-87136-19-5. This volume is the second part of the two-volume proceedings of the 14th conference Information Technologies – Applications and Theory (ITAT 2014), which was held in Jasná, Demänovská Dolina, Slovakia, on September 25–29, 2014. ITAT is a computer science conference with the primary goal of exchanging information on recent research results. Overall, 51 papers were submitted to all conference tracks. This volume presents papers from the workshops and an extended abstract of a poster. Three specialized workshops were held as a part of the conference: Data Mining and Preference Learning on Web, Computational Intelligence and Data Mining, and Algorithmic Aspects of Complex Networks Analysis.
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ITAT 2014. Information Technologies - Applications and Theory. Part I
Kůrková, Věra ; Bajer, Lukáš
ITAT 2014. Information Technologies - Applications and Theory. Part I. Prague : Institute of Computer Science AS CR, 2014. 101 p. ISBN 978-80-87136-18-8. This volume is the first part of the two-volume proceedings of the 14th conference Information Technologies – Applications and Theory (ITAT 2014). The conference was held in Jasná, Demänovská Dolina, Slovakia, on September 25–29, 2014. ITAT is a computer science conference with the primary goal of exchanging information on recent research results between Czech and Slovak scientific communities, and it presents a platform for young researchers and PhD students to start new collaborations. This year, it was held in parallel with two collocated conferences Datakon and Znalosti with which it shared some invited plenary talks and a poster session. Overall, 51 papers were submitted to all conference tracks. This volume presents 16 papers of the main track, which were selected by the program committee based on at least two reviews by the program committee members. Papers from the three workshops and extended abstracts of posters are included in the second volume.
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