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Research on effective finding of network anomalies in Intrusion Detection Systems using ML/DL methods

In this paper, the process of testing datasets and ML/DL methods using the Weka platform in order to obtain results of their effectiveness and how high the accuracy of detecting network anomalies they provide is described. During the experiment, many ML/DL algorithms and the most common datasets (KDD99, NSL-KDD, UNSW-NB15) were analyzed, as a result of which it was revealed that the best result of detection accuracy and time required on the experiment was produced by the NSL-KDD dataset.

Author: Dmitrijs Bulaks

Supervisor: Jeļena Baranova

Degree: Bachelor

Year: 2024

Work Language: English

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

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Assessing the Viability of Natural Language Processing Applications within an Electronic Checklist
System for Freight Forwarders: Rule-based Information Extraction from Cargo Descriptions.

This study investigates the application of Natural Language Processing (NLP) within electronic checklist systems to enhance cargo description and securing practices for freight forwarders. The logistics industry faces significant challenges due to complex and varied legislation and the need for autonomous validation tools for cargo securing. This research aims to develop a rule-based Named Entity Recognition (NER) model to standardize and automate the extraction of entities from cargo descriptions. Key components of this study include the development of an entity extraction mechanism using regular expressions and standardized codes. The research demonstrates the potential of NLP solutions to generate precise, dynamic checklists from detailed cargo descriptions, ensuring that all pertinent tasks are covered. The developed NER model's effectiveness is evaluated through a series of experiments, showcasing high precision, recall, and F1 scores, thus highlighting its practical applicability in real-world logistics operations. The findings underscore the importance of standardizing cargo-related information to facilitate the broader adoption of automated NLP solutions in the logistics industry.

Author: Nikita Mickevičs

Supervisor: Dmitry Pavlyuk

Degree: Professional Bachelor

Year: 2024

Work Language: English

Small object search with RFID tags

This bachelor's thesis focuses on the development of a device for locating small-sized objects using RFID technology. An analysis of existing RFID technologies and their applications was conducted, which led to the selection of ISO 15693 and ISO 18000-3 standards for the development of the small-sized object locating device. Experimental results were obtained to study the detection capabilities of RFID tags under various conditions using the HBE-RFID REX setup. Structural, functional, and circuit diagrams of the device were developed based on the selected components: the TRF7970A RFID module from Texas Instruments, ID ANT310/310 antenna, ATXMEGA64D3 microcontroller, LM041L LCD screen, matrix 3x2 keyboard, LP9960115 battery, 2 LED indicators (red and green), and DC-DC buck converter (LM2596). Algorithms for the device's operation were developed for searching known tags, displaying saved tags, and searching for new tags, along with the corresponding software codes.

Author: Nikita Ostroveņecs

Supervisor: Aleksandrs Kraiņukovs

Degree: Bachelor

Year: 2024

Work Language: English

Web service development for the enterprise

The aim of the work is to develop a website for a car service in accordance with the functional and non-functional requirements of a company that previously did not have a personal website. This website should help the company attract new customers, as well as retain existing ones, thanks to a more detailed description of all services provided and a pleasant interface. One of the main goals of this work is: to examine and compare an internet site that was developed using the classical method and a website whose code was written using artificial intelligence, and to provide an assessment of certain results.To find out which features are useful and what customers really want to see on the site, a survey of potential customers was conducted.Analyzing the subject areas, web pages with similar functionality were analyzed and identified, as well as the initial requirements for the website.At the design stage, development tools were analyzed and selected, a preliminary page design was developed, use case diagrams, page navigation tree were created.Also, when the code was written, manual testing was done, as well as code testing in individual applications.After the work was completed and the code was written, certain tests and code reviews were performed. The code was then fixed.

Author: Radions Kasmausks

Supervisor: Boriss Mišņevs

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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