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Development of Cross-Platform Mobile Application “Health Care for Pets”

The aim of this work was to develop a cross-platform mobile application, “Health Care for Pets,” with the main objective of providing pet owners a comprehensive, user-friendly tool for effective pet care.In the course of the work, an analysis of the subject area was conducted, and existing analogues were analysed. The system and functional requirements, as well as the main users for the application, were identified. Based on the analysis and requirements, the application, server, data access component and database were designed. The system was implemented using Visual Studio, in the C# programming language. The developed application was tested in the final stage.The application created during the bachelor's thesis meets all the requirements.

Author: Roberts Dubovskis

Supervisor: Karina Kostjkina

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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Improving the accuracy of optical character recognition of stone engravings using image pre-processing methods

This study focuses on the development of preprocessing methods to improve the accuracy of Optical Character Recognition (OCR) for stone engravings. The primary goal is to enhance the precision of widely used OCR tools, particularly for texts engraved on stone surfaces, which present unique challenges that differ from traditional OCR applications. Emphasis is placed on developing image preprocessing methods as a software product. Customized image manipulation scripts were used to improve recognition accuracy and address issues such as contrast, alignment, noise, and resolution. The preprocessing stage was integrated into the workflow designed for image transformation before OCR processing. Subsequently, the recognition improvements were evaluated based on text similarity metrics analysis. Iterative text recognition and repeated recognition of images after applying preprocessing demonstrated significant improvements in OCR accuracy. This work provides a solid foundation for further enhancement of OCR workflows by employing adaptable preprocessing techniques specifically designed for particular problem areas, achieving higher precision in text recognition.

Author: Romans Urbans-Orbans

Supervisor: Aleksandrs Grakovskis

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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CNN-Based pipeline-related artifact and damage recognition in IHC staining as preprocessing step for pathological analysis

This work proposes automated solution for artifact and damage segmentation in biomedical images using machine learning algorithms. The development process includes data preprocessing, label classification using a clustering algorithm and segmentation model. CNN architectures like YOLO and U-NET are utilized for segmentation, and K-Means and DBSC algorithms are evaluated for clustering. The outcomes include a set of data preprocessing precodures, clustering algorithm testing and results analysis, segmentation model and recommendations for further development.

Author: Taisija Kožarina

Supervisor: Jeļena Kijonoka

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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Research on Software Development Aspects Using node.js Technology

To explore the aspects of software development, an application was created using Node.js and NestJS to build a REST API. This API integrates Google Natural Language AI to analyze submitted user reviews. The application includes multiple REST API endpoints that can process, analyze, and aggregate user review data. Performance measurements were conducted, analyzing event loop latency, memory and CPU usage, and other key metrics. MongoDB was used for data storage. The work also includes API and its performance evaluation. The system was tested to ensure it meets the set criteria and provides practical application.

Author: Valērijs Sergejevs

Supervisor: Mihails Savrasovs

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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Shooter game development using Unity

This bachelor's thesis revolves around exploring the development of a game in the shoot 'em up (SHMUP) genre by using C# scripting in Unity. The project's aim is to understand the challenges faced by indie developers and the game creation process itself. This is achieved through implementing core mechanics, designing user-friendly interfaces, creating diverse levels, optimizing performance, and conducting playtesting. The resulting product serves as a practical example of applying fundamental gaming algorithms while providing insights into indie game development.

Author: Vladislavs Jevstifejevs

Supervisor: Irina Pticina

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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