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

Settings

Author: search.filters.author.Gushev, Marjan

Search Results

Now showing 1 - 10 of 211
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Improving the QRS detection for one-channel ECG sensor
    (SAGE Publications, 2019-11-07)
    Domazet, Ervin
    ;
    We analyzed several QRS detection algorithms in order to build a quality industrial beat detector, intended for a small, wearable, one channel electrocardiogram sensor with a sampling rate of 125 Hz, and analog-to-digital conversion of 10 bits. The research was a lengthy process that included building several hundred rules to cope with the QRS detection problems and finding an optimal threshold value for several parameters. We obtained 99.90% QRS sensitivity and 99.90% QRS positive predictive rate measured on the first channel of rescaled and resampled MIT-BIH Arrhythmia ECG database. Even more so, our solution works better than the algorithms for the original signals with a sampling rate of 360 Hz and analog-to-digital conversion of 11 bits.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A new model for cloud elastic services efficiency
    (Informa UK Limited, 2018-02-09)
    Ristov, Sasko
    ;
    Mathá, Roland
    ;
    Kimovski, Dragi
    ;
    Prodan, Radu
    ;
    The speedup measures the improvement in performance when the computational resources are being scaled. The efficiency, on the other side, provides the ratio between the achieved speedup and the number of scaled computational resources (processors). Both parameters (speedup and efficiency), which are defined according to Amdahl’s Law, provide very important information about performance of a computer system with scaled resources compared with a computer system with a single processor. However, as cloud elastic services’ load is variable, apart of the scaled resources, it is vital to analyse the load in order to determine which system is more effective and efficient. Unfortunately, both the speedup and efficiency are not sufficient enough for proper modeling of cloud elastic services, as the assumptions for both the speedup and efficiency are that the system’s resources are scaled, while the load is constant. In this paper, we extend the scaling of resources and define two additional scaled systems by (i) scaling the load and (ii) scaling both the load and resources. We introduce a model to determine the efficiency for each scaled system, which can be used to compare the efficiencies of all scaled systems, regardless if they are scaled in terms of load or resources. We have evaluated the model by using Windows Azure and the experimental results confirm the theoretical analysis. Although one can argue that web services are scalable and comply with Gustafson’s Law only, we provide a taxonomy that classifies scaled systems based on the compliance with both the Amdahl’s and Gustafson’s laws. For three different scaled systems (scaled resources R, scaled load L and combination RL), we introduce a model to determine the scaling efficiency. Our model extends the current definition of efficiency according to Amdahl’s Law, which assumes scaling the resources, and not the load.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability
    (Wiley, 2020-01-06)
    ;
    ;
    Spasevski, Gjoko
    ;
    ;
    Diabetes is one of today’s greatest global problems, and it is only becoming bigger. Constant measuring of blood glucose level is a prerequisite for monitoring glucose blood level and establishing diabetes treatment procedures. The usual way of glucose level measuring is by an invasive procedure that requires finger pricking with the lancet and might become painful and obeying, especially if this becomes a daily routine. In this study, we analyze noninvasive glucose measurement approaches and present several classification dimensions according to different criteria: size, invasiveness, analyzed media, sensing properties, applied method, activation type, response delay, measurement duration, and access to results. We set the focus on using machine learning and neural network methods and correlation with heart rate variability and electrocardiogram, as a new research and development trend.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Dew Computing Architecture for Cyber-Physical Systems and IoT
    (Elsevier BV, 2020-09)
    The concept to be on the edge of the Internet network means that the analyzed devices and systems will work only as a part of a general common integrated system, such as in the case of cyber-physical systems and various devices that act as an Internet of connected Things. Although post-cloud architectures are most commonly associated with edge computing, a focus in this paper is set on dew computing architecture that extends this concept with a specific architecture out of the edge. The dew computing implementation in cyber-physical systems allows autonomous devices and smart systems, that can collaborate and exchange information with the environment, still be independent of other external systems or perform in a connected more complex cyber-physical system of systems. This paper aims at presenting an architecture of applying dew computing for cyber-physical systems, elaborating the new features and functionalities and comparing it to other similar architectures.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    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%.