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The Path to Mastery (Mastered Activity) - Narrative Analysis of the Story of Becoming a Musician
Bartoň, Matěj ; Heider, David (advisor) ; Chrz, Vladimír (referee)
This thesis focuses on a narrative analysis of the process of becoming a master musician and the identification of the key factors that the subject perceives as important in their journey towards achieving mastery of a musical instrument. The thesis is divided into two parts. The theoretical part of the thesis discusses the concept of mastery and the process of achieving it, the importance of the flow state and its connection to mastery, the theory of Affordance, the differences between master and beginner players in chess, and the connection between psychology and music. The empirical part of the thesis implements a qualitative research design, specifically conducting seven narrative interviews with musicians who have achieved a certain level of mastery. Analysis of these interviews reveals that the key resources in achieving mastery are disposition, motivation, self-awareness, the influence of significant others, managing nervousness, and state of flow. These resources may interact with each other. The discussion presents a comparison of the results obtained with the existing literature and identifies possible limitations of the work. The contribution of this thesis lies in the detailed mapping and identification of key factors leading to mastery in music. Particular attention is paid not only to...
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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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Multilayer neural network
Kačer, Petr ; Klusáček, Jan (referee) ; Jirsík, Václav (advisor)
Bachelor's thesis describes the basics of issue of multilayer neural networks and explains principle of backpropagation algorithm. Next part of thesis is about development of a software for learning and testing multilayer neural networks and describes its graphical user interface. Last part of thesis is dedicated to tutorial examples and practical demonstrations of multilayer neural network usage.
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Intelligent Fighting Units
Kužela, Martin ; Janeček, Petr (referee) ; Drahanský, Martin (advisor)
The field training of army units includes high financial, material and human resource investments. From this reason, an emphasis on the simulator training of these units arised recently. But the training in simulator needs to have the simulated units as intelligent as a human beings are, so the field training with real human opponents can be successfully replaced with the simulator training. This work deals with the design of fighting unit's intelligent behaviour, that will be applicable in the E-COM simulator environment. Work covers the description of intelligent agents and ways how to achieve their rational and autonomous behaviour. The proposal and the analysis of intelligent fighting unit's implementation and unit's communication with surrounding environment, basic implementation of this proposal and experiments with created implementation are also described in this work.
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Character recognition in the soundtrack with SOM
Malásek, Jan ; Honzík, Petr (referee) ; Honzík, Petr (referee) ; Pohl, Jan (advisor)
This bachelor´s thesis describes a history of neural networks evolution and their using in speech recognition systems and shows problems with working and learning neural networks. It presents three chosen systems for speech recognition including their evaluation in experiments, their advantages and disadvantages. It is also about human speech characteristics and systems of its recognition. The last part is focused on frequency spectrums of different types of vowels and gives instructions for programming neural networks using MATLAB.
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Neural Network Number Recognition
Doupovec, Zdeněk ; Juránek, Roman (referee) ; Šilhavá, Jana (advisor)
This work describes the basic concepts and principles in the field of neural networks. Closer then deals with the problem of multilayer perceptron networks, namely back-propagation method. There are analyzed the advantages and disadvantages of these methods, the proposal of possible digits recognition system using back-propagation. The aim is to obtain concrete results from the program whitch is able to recognize numbers.
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AI Algorithms
Petrželka, Jan ; Hrubý, Martin (referee) ; Janoušek, Vladimír (advisor)
This master's thesis describes artificial intelligence algorithms based on the book Artificial Inteligence: A Modern Approach by S. Russel and P. Norvig and implementation of the algorithms in the Squeak Smalltalk programming language with object oriented approach. Algorithms are based on pseudocode in the book and existing implementations in Lisp, Python and Java language. Main concepts are intelligent agents, agent simulation environments, state space search, game playing, planning, uncertainty and learning.
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Professional Image
Horáčková, Lenka ; Kilinger, Miroslav (referee) ; Pokorný, Jiří (advisor)
This bachelorś thesis deal with forming and problems professional image for an individual and a firm connected with firm prosperity and profession growth of individual. It includes directions, procedures and necessary informations to form professional image and that carry to enhance firm prosperity and better profession and personal growth of individual.
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Image similarity measuring using deep learning
Štarha, Dominik ; Šeda, Pavel (referee) ; Rajnoha, Martin (advisor)
This master´s thesis deals with the reseach of technologies using deep learning method, being able to use when processing image data. Specific focus of the work is to evaluate the suitability and effectiveness of deep learning when comparing two image input data. The first – theoretical – part consists of the introduction to neural networks and deep learning. Also, it contains a description of available methods, their benefits and principles, used for processing image data. The second - practical - part of the thesis contains a proposal a appropriate model of Siamese networks to solve the problem of comparing two input image data and evaluating their similarity. The output of this work is an evaluation of several possible model configurations and highlighting the best-performing model parameters.
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