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.

Browse

Search Results

Now showing 1 - 10 of 72
  • Some of the metrics are blocked by your 
    Item type:Publication,
    ANTI-VIRUS TOOLS ANALYSIS USING DEEP WEB MALWARES
    (AIRCC Publication Corporation, 2018-12-22)
    ;
    Šćepanović, Sanja
    ;
    ;
    Knowledge about the strength of the anti-virus engines (i.e. tools) to detect malware files on the Deep web is important for people and companies to devise proper security polices and to choose the proper tool in order to be more secure. In this study, using malware file set crawled from the Deep web we detect similarities and possible groupings between plethora of anti-virus tools (AVTs) that exist on the market. Moreover, using graph theory, data science and visualization we find which of the existing AVTs has greater advantage in detecting malware over the other AVTs, in a sense that the AVT detects many unique. Finally, we propose a solution, for the given malware set, what is the best strategy for a company to defend against malwares if it uses a multi-scanning approach.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Contribution to the Quasigroup Based Error-Detecting Code
    (IEEE, 2023-07-19)
    In the last years we have developed few error-detecting codes based on quasigroups. One of them is the code which is a subject of this paper. The previous analyses of the code shows that the code has very high probability of detecting transmission errors. We have previously identified so-called best class of quasigroups of order 4, with the highest probability of detecting errors when the coding process is performed with a quasigroups of order 4. But, there is one more class of quasigroups of order 4, second-best class, whose quasigroups give approximately equal probability of undetected errors as the quasigroups from the best one. Therefore, we proceeded with the examination of the code when it uses quasigroups from this second-best class of quasigroups of order 4. In this paper we will analytically obtain the second important parameter of every error-detecting code, i.e. the number of errors that the code surely detects when for coding it uses a quasigroup from this second-best class of quasigroups of order 4. At the end we will conclude whether the quasigroups from these top two classes have overall equal ability to detect errors with this code.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Simulating the error-detecting capability of the error-detecting code
    (IEEE, 2018-05)
    Using simulations, we analyze an error-detecting code from the aspect of the number of errors that the code surely detects. In order to conclude whether and how the order of the quasigroup used for coding affects the number of errors that the code surely detects, we use quasigroups of different orders for coding. Also, we code input blocks of different lengths in order to conclude whether the number of errors that the code surely detects depends on the length of the input block, i.e., the length of the code word.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    A Comparison of GEC Tools for Grammatical Error Correction in English
    (IEEE, 2025-06-02)
    Virtanen, Johanna
    ;
    Using the Building Educational Application (BEA) benchmark11https://codalab.lisn.upsaclay.fr/competitions/4057, this study compares the capabilities of Google Gemini22https://gemini.google.com/, ChatGPT33https://openai.com/chatgpt, DeepSeek44https://www.deepseek.com/en, and the builtin grammar checkers in Google Docs and Microsoft Word for grammatical error correction (GEC). These tools correct a variety of errors, some of which overlap. Based on the BEA benchmark evaluation results, Google Gemini and the Google Docs grammar checker achieve the best F0.5 scores of 60.2 and 65.86, respectively. Google Docs grammar checker is easy to use and, according to this evaluation, performs well, thus proving to be a viable option for GEC. However, standard grammar checkers are not typically designed for rewriting text to the same extent as GenAI tools; hence, it may be advisable especially for non-native speakers to combine traditional and GenAI grammar correction for the best possible results. However, it is necessary to check the grammatical corrections of LLMs, since generative AI tools suffer from hallucinations, which refers to their tendency to generate information that can be factually incorrect [1].
  • Some of the metrics are blocked by your 
    Item type:Publication,
    A Programmatic Approach for Development of the ViewHRV Service Platform with Accurate and Reliable Results
    (IEEE, 2020-09-28)
    Shaqiri, E.
    ;
    There are dozens of available packages and libraries that claim to calculate HRV. This paper aims at comparing the results from the calculation of a single array of intervals between normal beats, including the most popular open source Python HRV measurement packages available on GitHub. Furthermore, the same array was ran through the Kubios software and compared to the previous results. In order to compare the accuracy of the results, as a benchmark we used the C programs provided by Physionet. The results showed a huge difference in the results with almost all the indices, in fact the simplest measurement that of Standard Deviation of NN Intervals showed to be incorrect in Kubios and in most of the Python packages. Results like these are the reason we decided to develop our own package to calculate HRV. Finally, the goal of this paper is to present details on developing a publicly available web service platform ViewHRV with guaranteed precision obtaining accurate and reliable results.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Impact of Dew Computing on Cyber-Physical Systems and IoT
    (IEEE, 2020-09-28)
    Cyber-physical systems and IoT devices are part of today's interconnected networked world and participate in huge data exchange transfer. Owners of related devices and systems tend to use them independently of external systems and in addition, to be autonomous devices and systems that can perform their tasks without any external support. Edge computing refers to devices on the edge of the Internet, as they integrate into a more complex cyber-physical system. The concept of edge computing means that the corresponding cloud and edge servers are always connected to the edge devices and IoT. In the analyzed case, although these devices and systems can work in an integrated environment, they are rather classified into the dew computing concept, giving them an environment for autonomous performance, independent of surrounding devices and systems. This paper elaborates the underlying concept, benefits, market trends and impact of integrating the dew computing concept to the cyber-physical systems and IoT devices.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Correlating Short-Term Heart Rate Variability and Instantaneous Blood Glucose Measurements
    (IEEE, 2020-11-24)
    Vishinov, Ilija
    ;
    ;
    ;
    In this research, we aim to analyze the correlations between instantaneous blood glucose measurements and short term (30 seconds to 5 minutes) heart rate variability (HRV) parameters and check the research hypothesis that these HRV parameters indicate the ability of a patient to control the blood glucose level. Methodology: Pearson and Spearman's Rank correlations are used as methods within this paper. Although 155 patients with heart problems and arrhythmia were included in the study, only intervals between normal heartbeats were evaluated. Data: The HRV parameters correlated to the blood glucose levels are divided into time-domain (TD) HRV parameters: SDNN, SDNN Prima (SDNN-1), ASDNN, ASDNN Prima (ASDNN-1), ASDNN Secunda (ASDNN-2), ASDNN Tertia (ASDNN-3), SDANN Secunda (SDANN-2), SDANN Tertia (SDANN-3), NN50, NN50 Prima (NN50-1), pNN50, pNN50 Prima (pNN50-1), rMSSD and rMSSD Prima (rMSSD-1); and non-linear HRV parameters: SD1, SD2, SD1/SD2. Several methods were utilized to process the ECG signal strip and eliminate the ectopic beats, artifacts, lost signals, noise, and other segments that influence HRV metrics. Conclusion: We found that SD1/SD2 showed the strongest positive correlations for 5 minute ECG recordings, 45-40 minutes before ( r = 0.36) and 20-25 minutes after ( r = 0.31) the fasting glucose measurement satisfying the condition p ≤ 0.05. We conclude that short term HRV parameters can't indicate a strong linear or monotonic correlation to the blood glucose regulation ability, but can motivate further research including deep learning.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Design of a Non-invasive ECG-based Glucose Measurement System
    (IEEE, 2020-09-28)
    ;
    Guseva, E.
    ;
    Poposka, L.
    Diabetic patients have to pay for each glucose reading with a blood drop and a small fortune. In addition, routine finger pricking is troublesome for diabetic patients because it can lead to scarring. It is no surprise then that the idea that glucose measurement can be done cheaply and in a non-invasive way surpasses the wildest dreams of diabetic patients. The goal of this paper is to present the design of a new technology solution for non-invasive glucose measurement based on processing the electrocardiogram obtained via a light easy-to-wear ECG monitor. We present details on how to develop a service that tracks glucose levels based on real-time ECG monitoring, and using sophisticated machine learning and related technologies. Our initial analysis shows that no similar solution is present on the market today, although several research initiatives are ongoing.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Trends from Minimally Invasive to Non-invasive Glucose Measurements
    (IEEE, 2020-09-28)
    ;
    Poposka, L.
    ;
    Guseva, E.
    ;
    ;
    Approximately 7% of the elderly over 45 are diagnosed in several diabetes forms and it is believed that 3% of the population is undiagnosed. As the number of diabetes diagnoses has been increasing, so too has the technology for managing the disease. The traditional way of measuring glucose levels is to apply a blood drop to a chemically treated, disposable ”test-strip” and insert it into an electronic device. In this study, we overview the latest technology for continuous glucose measurement, as they trend from minimally invasive to non-invasive glucose measurement methods.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Detection of Uninterpretable ECG Signal Segments
    (IEEE, 2020-09-28)
    Krluku, E. Ajdaraga
    ;
    Remote diagnosis represents one of the fundamental reasons for the introduction of telemedicine services. Specialized wearable health monitoring devices collect large amounts of data, which are transmitted to cloud collection centers for further monitoring and interpretation. However, the presence of noise corrupts the ECG signals, especially in wearable sensors, due to physical activities and movements. This significantly decreases the diagnosis accuracy and performance. Therefore, timely noise detection and identification of uninterpretable ECG segments are crucial for wearable devices.In this paper, we present results from our research to detect noisy segments in ECG signals without a goal to eliminate them and improve the QRS detection, but to detect where QRS detection would be impossible and avoid detection and interpretation mistakes. Our work includes two algorithms and multiple related variables that add to the success of the proposed algorithms. Finally, we achieved high performance for detecting signals where the signal to noise ratio is lower than 6 dB, with sensitivity and a positive predictive rate of over 90%.