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Geography pre-service teachers' perceptions of using artificial intelligence in education
Balvín, Vojtěch ; Krajňáková, Lenka (advisor) ; Cimová, Tereza (referee)
The bachelor thesis focuses on pre-service teachers'perspective of artificial intelligence. The thesis aims to explore how geography pre-service teachers perceive using artificial intelligence during their study and teaching. The stated aim was achieved through semi-structured interviews with twelve students. For the evaluation of the students' responses, the content analysis method was utilised. The findings show that most of the interviewed pre-service teachers have a positive view of artificial intelligence, and each of them has used it at least once during their studies. It is mostly used by them for writing seminar papers and for information retrieval during their studies. When teaching in lower- or higher-secondary schools, AI is then mainly used by the students to prepare lessons and educational materials. Respondents themselves are trying to deepen their knowledge and skills regarding artificial intelligence. They would also like to attend courses where they would be given the basics of how to work properly with artificial intelligence.
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Personalized Treatment of Respiratory Diseases Using Artificial Intelligence and Interoperability with e-Health Systems
Myška, Vojtěch ; Drotár,, Peter (referee) ; Brezany, Peter (referee) ; Burget, Radim (advisor)
Corticosteroid (CS) treatment in patients with Long COVID aims to prevent the progression from active post-inflammatory changes to fibrosis scarring. However, CS have side effects, which may sometimes be severe. Some patients might not require any treatment as their post-inflammatory changes resolve spontaneously. This dissertation thesis aims to develop an artificial intelligence (AI) based approach that allows personalized treatment of patients with Long COVID and a design of modular architecture allowing seamless interoperability of AI models with the information systems used in healthcare facilities. The first part of the thesis deals with the foundation of the state-of-the-art of using AI algorithms to recommend CS treatment in patients with Long COVID, who have the risk of permanent lung damage. This study examines how various parameters from different examinations influence the accuracy of the AI models. The most effective model achieves an accuracy of 73.68 %, a balanced accuracy of 73.52 %, and an AUC of 0.7469. These results prove that a trained AI model on a correctly chosen set of parameters from various medical examinations is effective and can be used as a decision-support tool for further treatment courses. The second part focuses on developing a modular architecture that allows interoperability between AI models and the information system of health facilities. Its specific implementation for early COVID-19 detection, incorporating DeepCovidXR models, is presented. In the performance test, the average processing time of X-ray images is 11.53 seconds using the CPU and 2.78 seconds with the GPU. Both values meet the maximum permissible analysis time set at 20 seconds. The results presented in both sections have been implemented and are currently used at the Olomouc University Hospital.
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Interviews 2.0 - Using AI for oral historians
Haubert, Marek ; Hlaváček, Jiří (advisor) ; Wohlmuth Markupová, Jana (referee)
This diploma thesis explores the integration of oral history with modern information technologies (IT), especially Artificial Intelligence (AI), aiming to investigate how these technologies can enrich the practice of oral historians and make the processing of oral historical interviews more efficient. It demonstrates, through practical examples, the possibilities of integrating AI and IT services at all stages of oral historical research, from interview preparation to realization, subsequent transcription, analysis, interpretation, and up to its security, archiving, and public publication. The thesis emphasizes practical demonstrations of technology use and research on available services and tools that can facilitate recording interviews, their transcription, sentiment analysis, or metadata creation.
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Artificial intelligence in web development
Vaň, Denis ; Štípek, Jiří (advisor) ; Procházka, Josef (referee)
This bachelor thesis deals with the use of modern artificial intelligence, specifically OpenAI's GPT-4 model, for web development and applications. The introductory section provides an overview of artificial intelligence and details the key characteristics and development of the GPT-4 model. The basic principles of its operation are explained, including the transformer architecture and technologies such as Multi-Head Attention and Positional Encoding that are essential to its performance. Furthermore, the paper explores tokenization processes, including Byte Pair Encoding, and their impact on model efficiency. Token count limits, pricing policy and token management are also considered. The broader context of the importance of GPT-4 for the future of artificial intelligence and natural language processing is also discussed. The theoretical section also shows how and where GPT-4 can be applied. The practical part of the bachelor thesis presents how the GPT-4 model can independently create web projects of varying complexity, ranging from simple HTML and CSS pages to more complex applications using JavaScript, PHP and databases. It starts with projects such as personal business cards and interactive forms that demonstrate GPT-4's basic capabilities in creating and styling web content. Gradually, more...
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Using artificial intelligence tools in education
Budský, Dominik ; Leipert, Jiří (advisor) ; Beneš, Martin (referee)
This bachelor thesis deals with the use of artificial intelligence, especially generative predictive text models such as the GPT model, in the educational process. The aim of the thesis is to provide teachers, pupils and students with a comprehensive guide on how to use these tools effectively to enrich the learning process, foster creativity and enhance effective preparation. The work details the application of AI in education, including lesson preparation, organization and inspiration for educators, as well as the benefits for students in learning and working with information. Practical applications and prompts for chatbots are demonstrated to show how educators, pupils and students can use these tools to their advantage. The paper highlights that integrating AI into pedagogical practice offers a range of benefits, from personalising learning to improving accessibility to education, and emphasises the potential of AI to transform traditional educational methods, with an emphasis on accessibility for all educators, pupils and students.
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Modern vibrodiagnostics of machines and evaluation of datasets by neural networks
Koníček, Tomáš ; Holoubek, Tomáš (referee) ; Hammer, Miloš (advisor)
This Master‘s thesis focuses on technical diagnostics with an emphasis on vibrodiagnostics of machines and equipment. The aim is to carry out research on vibration monitoring using modern on-line systems and to investigate the possibilities of processing the acquired data files using neural networks. Vibration monitoring from Siemens SIPLUS CMS is analyzed, including a description of individual hardware and software components. The work also focuses on machine diagnostics using a real model equipped with the SIPLUS CMS system in cooperation with the SIMATIC S7-1200 programmable automaton. The obtained data will be transferred via the FTP protocol for further processing in the Matlab program. Neural network models will be designed and used, which will be trained on the measured data. Convolutional neural network model will be used. The results will be evaluated and a conclusion will be drawn.
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Ritterkreuz: Action Game with Artificial Intelligence
Kubala, Jan ; Vlnas, Michal (referee) ; Milet, Tomáš (advisor)
Tato práce si klade za cíl vytvořit akční počítačovou hru, která krom očekávaných herních mechanik dokáže také zajímavým způsobem poskytnout informace o historii. Hra je tvořena v herním enginu Unity a kvůli rozsahu práce využívá i placené assety pro balistiku, pathfinding a prostředí úrovně. Hra obsahuje jednu úroveň, která se snaží autenticky vyobrazit jablunkovský incident, což byla přestřelka mezi německou záškodnickou jednotkou a polskou posádkou na Česko-polském pohraničí. Je to plíživá taktická střílečka z prvního pohledu, která se zaměřuje na vylepšený pohyb hráče, umělou inteligenci nepřátel a věrné vyobrazení tamější oblasti. Pohyb hráče je řešení založené na fyzice dělané na míru s rozšířenými možnostmi pohybu, jako přikrčení s několika úrovněmi, či dynamické lezení přes překážky. Umělá inteligence nepřátel jim umožňuje se pohybovat v klidném i bojovém prostředí a stejně jako hráč používají zbraně, jejichž projektily jsou balisticky simulované. Pro co nejbližší příblížení se dané oblasti byla využita reálná cloud pointová data z dané lokality, pomocí nichž se vygeneroval terén mapy. Dále byla přidána sekce s dokumenty a popisky zkompilované z různých výpovědí, které mají za úkol hráče obeznámit s okolnostmi této přestřelky.
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Počítačová hra s umělou inteligencí
Ludrovan, Tomáš ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
This thesis focuses on the development of multiplayer computer game and the examination of possibilites of using artificial intelligence for implementing entities controlled by the computer. The game code is written in C++ programming language and uses SDL2 library for user input and screen output. Besides others, some of the commonly used artificial intelligence algorithms are described here, which are used by the game either directly or as a modified version.
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Recognition of movements of an active upper limb prosthesis for modern needs.
Pelypenko, Ihor ; Mézl, Martin (referee) ; Harabiš, Vratislav (advisor)
Tato práce zkoumá oblast moderních náhrad končetin s důrazem na optimalizaci ovládání pohybových funkcí aktivních protéz. Cílem projektu je analyzovat a zpracovat data k vytvoření klasifikačního systému pro následné použití na vlastních datech. První část je věnována výsledkům průzkumu dvou skupin dobrovolníků (fyzicky zdraví a jedinci s omezením), porovnávání těchto výsledků a výběru nejrelevantnějších funkcí horní končetiny. Poté jsou studovány metody zpracování EMG, následované výběrem nejvhodnější metody. Popsán je také proces pořízení vlastní databáze a její zpracování. V poslední části jsou popsány vytvoření a testování funkcionality modelu umělé inteligence a zhodnoceno, zda dosažené výsledky jsou úspěšné.
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Methods for Playing the Game 'Liar's Dice' Using Dynamic Programming
Lohn, Marek ; Šátek, Václav (referee) ; Zbořil, František (advisor)
This project is about Methods of playing game Liar’s Dice using dynamic programming. The algorithm that was chosen for my study is SARSA, short for State Action Reward State Action algorithm. It is a modified version of algorithm named Q-Learning. It comparing algorithm SARSA with other algorithms by letting them play against each other in application, that was made in Unity Engine. Algorithms that were compared to SARSA are Q-Learning and Counterfactual Regret Minimization. SARSA achieved a 69,147 % win ratio in a game against Q-Learning. In games against Counterfactual Regret Minimization it was only 25 % win ratio. The main outcome of this study is that modified SARSA is effective against Q-Learning algorithm in a game of Liar’s Dice. On the other hand the SARSA algorithm was very ineffective against the Counterfactual Regret Minimization algorithm.
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