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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Item type:Publication, An analytical review of optimization techniques in information retrieval for enhanced decision support(Elsevier BV, 2025-12); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 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); ; 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Using the BBC Micro:bit in Educational Settings: Recommendations for N. Macedonia(Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Macedonia, 2025-12); ; Atanaskoski, ZivkoThe integration of the BBC Micro:bit into educational settings has been gaining momentum across various countries due to its potential to foster computational thinking, digital literacy, and hands-on learning. This paper examines the role of the Micro:bit in enhancing STEM education through case studies from Slovakia, Sweden, and the UK. The study explores teaching approaches, technical considerations, student engagement, pedagogical insights, challenges, and cultural contexts, offering valuable insights into the effectiveness of the BBC Micro:bit in different educational environments. Further, based on the findings, we propose a set of recommendations for N. Macedonia. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Testing Strategy for Multi-Tenant Web Applications Using TestContainers with Use Case: MealMatrix(2025-11); This paper addresses the problem of missing a standardized approach for verifying the architectural setup of multi-tenant applications by offering a testing strategy that covers scenarios of common problems that multitenant applications face (divided in 3 areas: data isolation, data integrity and constraints, tenant context). Using TestContainers to create a replica of a production environment, with a big bang integration testing approach, we showcase the practical usage of the proposed testing strategy with a Spring Boot and Kotlin web application for managing meal orders – MealMatrix. The results show that the testing approach is effective in identifying faulty setup for multi-tenant environments, with a limitation that TestContainers does not cover an easy-setup for the multiple databases, multiple schemas model with a single instance of the application serving multiple tenants. This work contributes to the field of software testing by offering an easily applicable, high-level testing approach for multi-tenant web applications. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Relocation of container-based services in a MEC-NFV orchestrated environment(Springer, 2024); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Smart System for Real-time Monitoring of Vital Parameters(University of Novi Sad, Faculty of Sciences, Department of mathematics and informatics, Novi Sad, Serbia, 2024-11-28); ; Wearable real-time systems that collect and intelligently analyze data on respiration, heart rate, oxygen saturation, blood pressure, and body temperature could assist medical personnel in selecting the most appropriate response during highly stressful situations in both military and civilian contexts, such as terrorist attacks, IED incidents, or rescue operations. These systems will issue an alert if there is a change in a person’s health status to prevent overlooking critical health changes. We propose designing and developing a prototype of a patch-like device and a methodology that enables the continuous monitoring of vital parameters of personnel or victims. The system involves using Artificial Intelligence to create software capable of real-time prediction of the parameters and alerting. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Processing MIMIC-III for Evaluation of Various Blood Pressure Estimation Models(2024); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Full-mesh VPN performance evaluation for a secure edge-cloud continuum(John Wiley & Sons Ltd., 2024-03-11); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing Quality Requirements for Onboarding Web Services to the European Open Science Cloud (EOSC): A Case Study of the Gaussian API(Slovak University of Technology in Bratislava, Slovakia, Faculty of Informatics and Information Technologies, 2023-12-14); The European Open Science Cloud (EOSC) is an initiative by the European Commission to support EU science by establishing a virtual environment for publishing, hosting, and reusing research. It promotes common standards, interoperability, and best practices for sharing and utilizing data and services. The EOSC platform contributes significantly to open science and facilitates transparent and accessible knowledge sharing. The resource onboarding process to the EOSC requires compliance with the established quality criteria. This paper focuses on accessing quality criteria for successful onboarding, including a case study on the RESTful web service for fitting repulsive potentials in density-functional tight-binding with Gaussian process regression - Gaussian API. The onboarding process follows a sequential evaluation of a set of criteria. The examination of The Gaussian API integration into EOSC provides valuable insights into three main aspects: improving service quality, considering the benefits of Open Science, and addressing challenges related to the smooth onboarding process. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Estimation of Blood Pressure from Arterial Blood Pressure using PPG Signals(Faculty of Computer Science and Engineering, Skopje, North Macedonia, 2023-08); ; Predicting Blood pressure from Photoplethysmography (PPG) signals is an active area of research and there have been many studies exploring the feasibility of this approach. This paper elaborates on a technique for the estimation of continuous Arterial blood pressure (ABP) waveform using PPG signals as inputs in a developed deep-learning model. The ultimate goal is estimating the Blood pressure, but unlike the standard regression models for predicting Blood pressure by systolic BP (SBP) and Diastolic BP (DBP), this approach calculates SBP and DBP from the estimated ABP waveform, which enables further analysis to enhance the BP estimation. The best-obtained results are an MAE of 8.40mmHg, and an MAE of 11.1mmHg and 7mmHg for SBP and DBP respectively. The promising prediction of SBP and DBP using our proposed machine learning model has the potential to improve clinical decision-making and resource allocation process in emergency situations.