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Family Trees Making from Archive Records
Haltmar, Adam ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
This thesis is about optimalization and increasing precision of already existing program for processing, comparing and linking archive records about people in a way to store them in a graph database while constructing family pedigrees as a side effect. It shows where the algorithm was approached badly and makes better alternatives for lowering the computation time. It also presents new methods for increasing the precision of record linking like name standardization and compares tests with the original program. Result of these changes is accelerating the program by more than 5000 %.
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User Interface for the bee hive management system
Torbin, Evgeny ; Rozman, Jaroslav (referee) ; Veigend, Petr (advisor)
The aim of this thesis is to create a user interface for the bee hive management system and its implementation as a multiplatform application. The user will be able to view statistics about their hives, apiaries and manage them. This information is provided by the server and received from special sensors installed directly in the hives. To solve this problem, Ionic framework written in JavaScript language and web technologies HTML and CSS were used. Communication with the server is done using REST API. The final application provides an interactive and user-friendly interface for managing bee hives, and is available on different platforms. The main result of this work is to prove that it is currently possible to create a full-fledged application without knowledge of platform-specific technologies. This approach makes the development of similar projects cheaper, more efficient and much faster.
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Web for Displaying Archive Materials
Malík, Oto ; Veigend, Petr (referee) ; Rozman, Jaroslav (advisor)
The thesis deals with the websites analysis of the archives in the Czech Republic and used technologies. The aim of the thesis is to design an intuitive user interface and to create a datacentric web application for displaying archival materials from eight main archives in the Czech Republic. The server part of the application is implemented by using the Java programming language with Spring Boot. The client part of the application is built by using Angular, and the part of the application that is designed for a detailed browsing of the digitized attachments is created by using the OpenSeadragon JavaScript library.
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Web for Displaying Archive Materials
Šesták, Pavel ; Veigend, Petr (referee) ; Rozman, Jaroslav (advisor)
The aim of the thesis is to unify the data of the individual archives into one system, within which the user will be able to search and view the data. In particular, it is about scanned archival materials and their metadata. The thesis describes the different types of archival data and analyses the current systems. The thesis compares four scraping systems on the basis of dataset size, missing values and consistency between datasets. The archival imaging system is then modeled using behavioral and structural UML diagrams. The work also includes a graphical design produced in Figma. The thesis also includes a description of the implementation, testing and deployment procedure using Docker on the school infrastructure.
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Integrating Artificial Intelligence into Fast-Moving Consumer Goods
Bagi, Juraj ; Hříbek, David (referee) ; Rozman, Jaroslav (advisor)
Accurate sales forecasting is pivotal for operational efficiency in the Fast-Moving Consumer Goods (FMCG) sector. This thesis explores the application of Long Short-Term Memory (LSTM) models, a specialized form of recurrent neural networks, to enhance the precision of sales predictions. Unlike traditional statistical methods, LSTMs are adept at capturing temporal dependencies within sales data, potentially offering more accurate forecasts. By applying LSTM models to historical sales data from a food industry company, this research demonstrates improvements over conventional forecasting techniques. The findings suggest that LSTMs can significantly help FMCG companies in optimizing inventory management and demand planning, thereby contributing valuable insights into artificial intelligence applications in supply chain management. These results emphasize the practical implications for FMCG stakeholders to embrace advanced artificial intelligence technologies to remain competitive in a dynamic market environment.
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Movement Planning of a Hexapod Robot
Hostačná, Kristína ; Šátek, Václav (referee) ; Rozman, Jaroslav (advisor)
Táto práca predstavuje riešenie na dosiahnutie autonómnej navigácie šesťnohých robotov k cieľu v zornom poli pomocou neurónových sietí. Toto riešenie bolo implementované na dvoch verziách robotov – jednoduchý dizajn s dvoma kĺbmi na každej nohe a zložitejší dizajn s tromi kĺbmi na každej nohe. Hlavná výzva tohto problému - tj. zložitosť ovládania viacerých kĺbov narástla, aby sa umožnil širší rozsah pohybov a tým aj zväčšenie možností využitia robota. Metodológia výskumu zahŕňa využitie experimentov v simulácii aj v reálnom svete na modelovanie a zber údajov. Údaje z rôznych senzorov, vrátane kamier a pozícií serv, sú využité na trénovanie modelov neurónových sietí schopných interpretovať senzorické vstupy a generovať riadiace signály pre aktuátory robota. Základná architektúra neurónovej siete bola spočiatku nasadená pre obe konfigurácie, zatiaľ čo sofistikovanejší prístup zahŕňajúci konvolučné a rekurentné neurónové siete bol použitý neskôr. Vo výsledku, trénované neurónové siete demonštrujú schopnosť navigácie k cieľu.
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Comparison of Databases Systems for Genealogy
Sadovskyi, Dmytro ; Rozman, Jaroslav (referee) ; Kočí, Radek (advisor)
This bachelor's thesis aims to select the most suitable database management system for storing genealogical data. The study will involve selecting databases of various types, which will be compared based on predefined criteria. Evaluation criteria will focus on database performance, ease of use, and the licensing terms under which the database is distributed.The chosen databases will also be compared with the current relational database, and the results will indicate whether it is advisable to stay with the current model or switch to a different one.
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Automated trading systems
Šafář, Vítězslav ; Hříbek, David (referee) ; Rozman, Jaroslav (advisor)
Trading in the financial market is something almost everyone has heard of these days, but automated trading is still a novelty for most. The aim of this bachelor's thesis is to design and create several automatic trading systems using the application programming interface provided by XTB, and subsequently evaluate these automated trading systems using historical data. The thesis presents four differently complex automated trading systems, achieving various profits at certain risk levels. Furthermore, the thesis demonstrates the usability of the mentioned XTB application programming interface. The best-designed system evaluated was the one utilizing the MACD indicator,which achieved an average annual return of around 13.5 % with a level of risk of loss, approximately 39 %.
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Lokalizace na bázi Bluetooth
Machyňák, Augustin ; Rozman, Jaroslav (referee) ; Janoušek, Vladimír (advisor)
The thesis deals with the development of a device localization system using ESP. The system uses signal strength information to estimate the distance and then uses multilateration techniques to estimate device positions. To obtain the relative positions of the receivers it also uses signal strength, making it very user friendly to setup and configure. The resulting positions are either processed on the ESP itself with simple visualization or it is possible to use an external server implementation to process them with historical data and a more suitable visualisation of the positions. However, the accuracy is not satisfactory and only suggests the use of map generating techniques for each specific environment using which to determine, what combinations of received signal strength values correspond to each position is a more appropriate method for localization.
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Object Detection on the i.MX RT Microcontroller
Kravchuk, Marina ; Rozman, Jaroslav (referee) ; Janoušek, Vladimír (advisor)
This work focuses on the use of machine learning, particularly convolutional neural networks, in industrial applications. The course of work involves investigating the implementation of these networks directly on embedded devices, specifically NXP i.MX RT microcontrollers. During the course of the study, materials related to the training and use of neural networks and their optimization for deployment on low power devices were reviewed. Several neural network models were trained and tested, the best of which was used in the final version of the application. The application itself is divided into two parts: one part is written in C/C++ in the MCUXpresso IDE, where the main functionality of the program is implemented, while the other part of the work, i.e. the creation of a graphical user interface to control the program, is done in Python. The result is a functional application for the MIMXRT1170-EVK microcontroller that is able to detect and recognize small colored objects of certain shapes from a predefined data set.
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