TSI logo 25 years
LV EN
Home > About Us > Structure and Government > Abstracts

DEGREE

PROGRAMME

FACULTY

YEAR

LANGUAGE

Development of a 2D Platformer Game using Godot Engine

This Bachelor thesis details the development of "Parry Knight," a 2D endless runner game using the Godot Engine. The game, featuring a knight navigating dynamically generated platforms while avoiding or parrying attacks from hostile NPCs, draws inspiration from Jetpack Joyride, Knightmare Tower, Cuphead, and Shovel Knight. The project highlights the practical application of game design principles and programming skills through Godot's GDScript. Key aspects include the creation of core gameplay mechanics, user interface design, and testing. The thesis presents comprehensive diagrams, including use case, sequence, and class diagrams, to illustrate the development process. The game was developed and tested. This software and work that describes it follows all requirements set for it.

Author: Jurijs Luņovs

Supervisor: Karina Kostjkina

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

More...

Boosting Algorithms for Credit Card Fraud Detection Across Varied Datasets

Manual reviews and rule-based systems, as well as data mining techniques such as clustering and classification algorithms, are crucial for identifying credit card fraud since they help identify fraudulent transactions. Despite obstacles in gathering training data, more data has lately been available, however, a complete comparison of current machine learning approaches has yet to be conducted. Algorithms like XGBoost, AdaBoost, and Gradient Boosting Machine frequently outperform older approaches. This study compares boosting algorithms to traditional approaches using three different credit card transaction datasets: synthetic, balanced with 50% fraudulent transactions, and very unbalanced with only 0.17% fraudulent transactions. The genuine transaction datasets contained 28 anonymized parameters such as time and location. Each method was evaluated using the F1 score, accuracy, precision, and recall. This study makes recommendations on which algorithms to use in real-world scenarios, giving important insights for future research and practical use in credit card fraud detection.

Author: Justs Vīdušs

Supervisor: Nadežda Spiridovska

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

More...

PREDICTIVE ANALYTICS FOR ONLINE CASINO REVENUE IN THE AUSTRALIAN MARKET.

This thesis investigates the influence of economic indicators and weather conditions on online slot machine gambling habits and revenues in Australia. By reviewing the interplay of GDP, CPI, and unemployment rates, the study uncovers their impact on gambling behaviors, revealing that a healthier economy boosts gambling expenditures while financial strain reduces participation. Weather's impact was minimal, likely due to the indoor nature of gambling. Predictive models, including Multiple Linear Regression, ARIMAX, and SARIMAX, were developed and evaluated. ARIMAX and SARIMAX models proved more accurate for predicting gross gaming revenue and winning bets, capturing seasonal and external influences effectively. This research provides insights for policymakers and industry stakeholders, emphasizing the need for localized studies to better understand these dynamics and improve strategic planning in the gambling sector. Future work should focus on expanding datasets and incorporating diverse economic and weather patterns to enhance predictive accuracy and industry applicability.

Author: Jānis Želannovs

Supervisor: Nadežda Spiridovska

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

More...

Development of a personal financial management application

Nowadays, financial management is essential in people's lives, as price increases and economic instability require more careful planning of personal finances. Technological development makes this process accessible to everyone, offering various expenditure tracking and budget planning solutions. In the bachelor's thesis, the most popular financial management applications were reviewed, showing that although they offer an intuitive interface and automated budget functions, they also have shortcomings.The goal of the work is to create an application that provides a convenient and digitally enhanced tool for financial planning and tracking. To achieve the goal, tasks included reviewing similar applications, defining requirements, creating the interface and database, developing transaction management and budgeting functionality, and testing the application. All tasks were fully completed.The application uses Python and Flask, SQLite database, HTML, CSS, and JavaScript. As a result, an application with a clear interface was developed, providing manual transaction entry and bank account Excel format upload, editing, and deletion, as well as budget control and transaction visualizations. These functions help users manage their finances more effectively and make better decisions.

Author: Jūlija Ivčenkova

Supervisor: Olga Dribeņeca

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

More...

COMPARATIVE ANALYSIS OF LLM-BASED APPROACHES FOR SQL GENERATION

The rapid development of Large Language Models has unlocked opportunities for restructuring software development processes in general as well as in such cases as converting natural language into SQL queries. This study seeks to experimentally evaluate the effects of four LLM-based methods on the efficiency and quality of SQL generation. Evaluation is being held based on following metrics: Correctness, Completeness and Consistency. Studied LLM-based SQL generation methods include Specific LLMs tailored for SQL code generation like SQL Coder frameworks for generating SQL code (Vanna.ai, 2023; Llamaindex, 2023) and Multi agent collaborative networks for transforming language into SQL.The research utilizes a mix of literature review case studies and simulations. It offers a comprehensive review of the advancements in LLM-driven SQL generation encompassing concepts, technologies, methodologies, strengths, limitations, and ethical considerations.This research successfully bridges the gap between theoretical foundations and practical application of AI-augmented approaches while promoting the integration of LLM-based SQL generation, into automated software development processes.

Author: Maksim Ilin

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

More...

Table View
Text View