Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

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Author: search.filters.author.Dodevska, Mila

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    An Empirical Study of Knowledge Graph-Enhanced RAG for Information Security Compliance
    (MDPI AG, 2026-04-20)
    Jovanovski, Dimitar
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    Stojcheva, Marija
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    Dodevska, Mila
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    Information security compliance has become critical for organizations worldwide, with the ISO/IEC 27000 family serving as the most widely adopted framework for establishing information security management systems. Despite their global acceptance, these standards present significant interpretation challenges due to their formal language, abstract structure, and extensive cross-referencing across 97 documents. Traditional retrieval-augmented generation (RAG) systems, which rely on independent text chunking and dense vector retrieval, prove inadequate for such highly interconnected regulatory materials, often fragmenting contextual relationships and reducing accuracy. This study introduces a privacy-preserving RAG framework that integrates LightRAG, a knowledge graph-based retrieval system, with locally hosted open-source language models. Unlike chunk-based RAG systems that treat document segments independently, the system in this study constructs a semantic knowledge graph that explicitly models relationships between clauses through typed edges representing cross-references, semantic similarity, and hierarchical dependencies. To enable rigorous evaluation, we developed a curated benchmark dataset of 222 multiple-choice questions with authoritative ground-truth answers, systematically constructed from official ISO standards, certification preparation materials, and academic sources. Through systematic evaluation on this benchmark, we show that knowledge graph-based retrieval achieves higher accuracy than chunk-based RAG and non-retrieval LLM baselines within the evaluated setup. The analysis indicates that embedding model quality is strongly associated with system performance, that hybrid retrieval modes combining local and global graph traversal tend to yield better accuracy, and that mid-sized open-source models paired with strong retrievers can approach the performance of larger proprietary systems. The best configuration achieves 90.54% accuracy, demonstrating the promising effectiveness of graph-structured retrieval for multiple-choice regulatory questions.
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    Virtual reality as a learning tool: Evaluating the use and effectiveness of simulation laboratories in educational settings
    (Elsevier BV, 2025-01-01)
    Dodevska, Mila
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    Branco, Frederico
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    Virtual Reality Laboratories (VRLs) are essential progress towards educational solutions that would allow students to learn the sometimes complex experimental processes without spending physical resources. The resources used in some experiments often require significant procurement effort, significantly impacting the environment where an experiment would be conducted. The main focus of this research is to review the possibility of using VR solutions as educational tools and innovative approaches to scientific knowledge production. This paper systematically reviews relevant publications in this area while covering several existing virtual lab solutions. The analysis shows that VRL tools can be effectively used for educational purposes, allow access to lab resources for people with disabilities, and could be used to reach the desired learning outcomes. A gap exists between natural laboratories and VRLs, especially in the collaborative aspect of the laboratory exercises. However, there is significant ongoing research on this topic and a high potential for development.
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    Exploring the Educational Potential of Virtual Reality and Mixed Reality: Immersive Learning, Student Engagement, and Knowledge Retention
    (Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Macedonia, 2025-12)
    Dodevska, Mila
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    Atanaskoski, Zivko
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    The integration of Virtual Reality (VR) and Mixed Reality (MR) technologies in education presents new opportunities for immersive and interactive learning. This paper reviews recent applications of VR/MR in educational contexts, emphasizing their impact on student engagement, cognitive development, and knowledge retention. The analysis highlights key benefits such as enhanced motivation, improved practical skills, and effective visualization of abstract content, while also acknowledging limitations including cognitive load and motion sickness. In addition to the literature review, the grounds of an experimental study are presented.