International Journal of Electrical Engineering and Computing

Impressum

Nataša Popović — Tue, 24 Jun 2025 13:20:33 +0000

Editorial

Nataša Popović — Tue, 24 Jun 2025 13:22:55 +0000

CodeCrafter – Efficient Code Generator for Modern Single-page Web Applications

Danijela Vukosav, Danijela Banjac, Miloš Ljubojević, Mihajlo Savić — Tue, 24 Jun 2025 13:12:26 +0000

Web applications and REST API based applications can be seen as a most common type of application today and their number is constantly increasing. Due to the pressure to produce more code and be faster at producing it, developers have been using various programming languages, libraries and frameworks suitable for such applications. Two of the most popular technologies are Spring on the back-end, and React on the front-end. While each technology provides a satisfiable functionality, the amount of code that needs to be produced is non-trivial, especially in cases where the application has to provide even basic security and auditing functionalities. One solution for this issue is use of code generator tools that produce both back- and front-end code from a model. While a wide variety of generators exist, none of the analyzed ones fulfill all the requirements of a modern web application. In this paper, we present CodeCrafter, a web-based code generation application that produces Spring and React code based on relational data model in DDL or JSON format, and provides developers with simple and efficient tool to generate fully functional foundational code. We compare it to existing code generation tools and measure its performance as a function of number of tables in the database. We show that CodeCrafter produces code in very short amount of time even for very complex databases, while providing features and functionalities not present in other analyzed tools. We also give a short overview of possible use in conjunction with LLM based coding tools.

Population Genetic Analysis of Allele Frequencies for Hereditary Thrombophilia in Pregnant Women Using Artificial Intelligence

Katarina Živojinović, Marko Milun Živanović, Stefan Erčić, Vanja Luković — Tue, 24 Jun 2025 13:13:40 +0000

Thrombophilia is an inherited condition characterized by an increased tendency for blood clot formation, affecting approximately 8-11% of the European population. It is typically inherited in an autosomal dominant manner and includes approximately 10 different subtypes, classified based on genetic factors. This condition often leads to complications in pregnant women, including spontaneous miscarriage, fetal deformities, and an increased risk of heart attack, stroke, pulmonary embolism, and deep vein thrombosis. The goal of this study was to conduct a detailed genetic analysis of thrombophilia using population genetics methods (Hardy–Weinberg equilibrium, Shannon index, genotype frequencies) and to develop an AI-based predictive model for high-risk genotypes, evaluated via confusion matrices. The research focused on assessing allele frequencies, genetic diversity, and deviations from Hardy-Weinberg equilibrium in a cohort of 2,760 pregnant women to enhance the understanding of the genetic basis of this condition. Our analysis revealed significant correlations between coagulation factor genes and identified distinctive patterns of genetic diversity across 12 thrombophilia-associated markers. The results provide key insights into genetic variations and their potential implications for pregnancy complications. This study opens new perspectives for improving early detection and more effective risk management of thrombophilia during pregnancy.

Two and Three Dimensional Support Vector Algorithm for Students’ Classification

Marina Milicevic — Tue, 24 Jun 2025 13:14:43 +0000

In an era where technology with its development is constantly reshaping the field of professional practice, it is evident that educating engineers nowadays is a challenging task. This is supported by the increasingly popular teaching methods in which traditional learning methods are combined with modern technologies, all with the aim of greater motivation for learning and work among the students. The subject of research in this paper is specifically one teaching method, adapted for teaching at technical faculties, which uses machine learning methods (support vector method) in its background. The introduced method recognizes the importance of assessing students' abilities and knowledge because a good classification of students allows the teacher to plan the lesson more easily and choose the approach they believe will give the best results.

Residue Number System-Based Hash Function: Design and Cryptographic Analysis

Milija Ljubiša Pavlović, Tijana Talić, Boris Damjanović, Negovan Stamenković — Tue, 24 Jun 2025 13:15:57 +0000

In this paper, we propose a novel cryptographic hash function based on the Residue Number System (RNS). The design leverages the inherent parallelism of RNS to enhance computational efficiency and resilience against certain classes of attacks. Through modular processing across independent residues, the function achieves notable improvements in hardware acceleration capabilities, making it particularly suitable for resource-constrained environments. To assess the robustness of the proposed function, we conduct a series of tests including the distribution of Hamming weights, bit balance evaluation, and avalanche effect analysis. The results demonstrate that the hash function produces uniformly distributed outputs, exhibits strong avalanche characteristics, and maintains high resistance to input structure correlation. These properties confirm the potential of the proposed RNS-based approach for secure and efficient hashing in modern cryptographic applications.

Operational planning and security management in modern power systems under regional coordination conditions

Anđela Krljaš, Tijana Milovanović, Marta Gačić, Dušan Prešić — Tue, 24 Jun 2025 13:17:09 +0000

Deregulation of the electricity market has brought not only numerous benefits but also significant challenges in the domain of operational planning and management of the power system. The increase in cross-border trade required improved coordination and data exchange among Transmission System Operators (TSOs). In response, Regional Security Coordinators (RSCs) were established to centralise the coordination of TSOs' operations and provide forecasts of the power system state over short- and medium-term time intervals. This paper aims to provide insight into the key aspects of RSC operations, emphasizing their significant role in planning, coordinating, and implementing security strategies at the regional and Pan-European level. Although the data presented in this paper is mainly theoretical due to the confidentiality of information managed by RSCs, this paper nevertheless serves as a valuable resource given that the concept of RSCs has been insufficiently addressed in professional literature and scientific studies.