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Parking Assistant
Mareček, David ; Dluhoš, Ondřej (referee) ; Kubát, David (advisor)
This thesis deals with design and implementation of parking assistant. It introduces the types of sensors for distance measurement and possibilities of using camera system. In implementation there are used ultrasonic sensors, namely rangefinder SRF08 and web cameras. User interface that combines data from individual sensors was designed and implemented. Parking assistant provides function for edge detection, sound and graphics signalization together with automatic night mode.
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Strategic Brand Development of Company
Botek, Aleš ; Mareček, David (referee) ; Zich, Robert (advisor)
This diploma thesis focuses on the determination of StarkGlass brand strategy, which focuses on the online sale of protective films for mobile phones. The work explores the experience of the existing customers of the brand, which is then used for proposals for improvement and for the determination of the future StarkGlass branding strategy.
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Preparation of graphene samples for experiments under UHV conditions
Mareček, David ; Mach, Jindřich (referee) ; Čechal, Jan (advisor)
This bachelor thesis deals with electrical conductivity of a graphene sample and preparation of a graphene field-effect transistor. In the theoretical part of the thesis, we describe electronic properties of graphene, preparation of graphene by CVD and its transfer to SiO_2. Experimental part of this thesis is focused on the preparation of a graphene field-effect transistor with long distance between Source and Drain electrodes. Thesis deals with a design of a chip expander for contact of graphene in UHV conditions. The last part describes measurement of dependency of graphene layer conductivity on the gate voltage with emphasis on the position of Dirac point during adjustments of the sample in UHV conditions.
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Influence of electron beam on graphene field effect transistors
Mareček, David ; Čech,, Vladimír (referee) ; Čechal, Jan (advisor)
This diploma thesis deals with electrical conductivity of a graphene sample, preparation of a graphene field-effect transistor and his irradiation by electron beam. In the theoretical part of the thesis, we describe electronic properties of graphene, preparation of graphene by CVD and its transfer to Si substrate with SiO_2 layer. Experimental part of this thesis is focused on the preparation of a graphene field-effect transistor for use in UHV conditions. Futher describes electron beam scanning over the transistor and creation of current maps of tranzistor. In the last part, the thesis deals with influence of electron beam on transport properties of graphene layer and doping of graphene layer by electron beam.
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Automatic detection of fake-news on Slovak texts
Romanský, Patrik ; Mareček, David (advisor) ; Novák, Michal (referee)
Fake news is a problem in recent years. This study focuses on detecting fake news written in the Slovak language using text classification methods. It is unique because it is the first to conduct such a comprehensive set of experiments on Slovak. During the study, a balanced dataset was created, and over 80 experiments were conducted to find the optimal classifier for the problem. Pre-trained transformer-based language models, including BERT, mBERT, RoBERTA, XLM-RoBERTa, and SlovakBERT, were used in the initial step of the study, and their performance was compared against other machine learning methods using standard metrics. The models were fine-tuned with LIAR and COVID19 FN, English-language datasets, to test the impact of fake news topics and language transfer properties. SlovakBERT combined with training exclusively on Slovak datasets achieved the best results with an (acc = 0.9610). This study can contribute to the development of tools to automatically detect fake news in Slovak, aiding in the fight against the spread of false information. 1
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Unsupervised segmentation of Gregorian chant melodies for exploring chant modality
Lanz, Vojtěch ; Hajič, Jan (advisor) ; Mareček, David (referee)
Gregorian chant, as an oral musical tradition, was performed by singers that had to memorize thousands of melodies. Each melody has a set of properties, one of which is what mode it belongs to within the modal system. To understand the learning process principles of chants, it may be helpful to decompose melodies into smaller units and analyze their relationship to modality. In this work, we compare Bayesian and neural network unsupervised segmentation methods. We measure their performance on evalu- ation metrics we design in order to examine the chant's properties with respect to the memorization challenge considering the modality aspects. For this purpose, we have two datasets, one with over thirteen thousand antiphons and the other with over seven thousand responsories. We find the Pitman-Yor process to be a more fitting model than BERT for this particular task, especially the conditional Pitman-Yor process model we proposed to segment each mode independently. We provide several clear arguments that modality and chant segmentation are closely connected. We also dispute the claim by Cornelissen et al. [2020] that the natural segmentation by chant words or syllables is best in terms of mode classification, and we provide a new state-of-the-art performance on the mode classification task. 1
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Automatic generation of Einstein's puzzles in natural language
Hubená, Michaela ; Mareček, David (advisor) ; Hajič, Jan (referee)
In this bachelor thesis was created command line application for generat- ing Einstein's riddles in natural language using language model GPT-3 (third generation Generated Pre-trained Transformer). The few-shot method was used to generate Einstein's riddles, where, in addition to entering the required task, the language model is also given several solved examples of this task, with which the language model is supposed to learn the task directly during generation. The created application allows user to generate Einstein's riddles of various sizes and difficulties on any topic in Czech or English language. During generation the emphasis is placed on the creativity and originality of Einstein's riddles.
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Development of a mobile application and question generator for the game Smart10.
Tomiška, Tadeáš ; Mareček, David (advisor) ; Rosa, Rudolf (referee)
This bachelor's thesis focuses on creating a mobile application for Android that allows playing an online version of the game Smart10. The work also includes generating questi- ons for the game, which will be generated using web pages from Wikipedia. The technique of web page parsing will be used to obtain the necessary data. The application will be written in Java and will be intended for Android versions 10 and higher. A client-server architecture will be used for communication between devices, with communication via Wifi technology. The application will have the same rules as the game Smart10 and will support two gaming modes. It will be playable in an online mode with other players or in a friend mode with friends. 1
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Automatic detection of fake-news on Slovak texts
Romanský, Patrik ; Mareček, David (advisor) ; Novák, Michal (referee)
Fake news is a problem in recent years. This study focuses on detecting fake news written in the Slovak language using text classification methods. It is unique because it is the first to conduct such a comprehensive set of experiments on Slovak. During the study, a balanced dataset was created, and over 80 experiments were conducted to find the optimal classifier for the problem. Pre-trained transformer-based language models, including BERT, mBERT, RoBERTA, XLM-RoBERTa, and SlovakBERT, were used in the initial step of the study, and their performance was compared against other machine learning methods using standard metrics. The models were fine-tuned with LIAR and COVID19 FN, English-language datasets, to test the impact of fake news topics and language transfer properties. SlovakBERT combined with training exclusively on Slovak datasets achieved the best results with an (acc = 0.9610). This study can contribute to the development of tools to automatically detect fake news in Slovak, aiding in the fight against the spread of false information. 1
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Question Answering in Czech via Machine Translation and Cross-lingual Transfer
Macková, Kateřina ; Straka, Milan (advisor) ; Mareček, David (referee)
Reading comprehension and question answering are computer science disciplines in the field of natural language processing and information retrieval. Reading comprehension is the ability of the model to read text, process it and understand its meaning. One of its applications is in question answering tasks, which is concerned with building a system that can automatically find an answer in the text to a certain question relied on the content of the text. It is a well-studied task, with huge training datasets in English. However, there are no Czech datasets and models for this task. This work focuses on building reading comprehension and question answering systems for Czech, without requiring any manually annotated Czech training data. Our main focus is to create Czech training and development datasets, create the models for the Czech question answering system using Czech data, and create the models for the Czech question answering system using English data and cross-lingual transfer and compare the results and select the best model. First of all, we translated freely available English question answering datasets SQuAD 1.1 and SQuAD 2.0 to Czech to create training and development datasets. We then trained and evaluated several BERT and XLM-RoBERTa baseline models used for the question answering task in...
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