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, MetriKG: Profiling Static and Evolving Knowledge Graphs(ACM, 2026-05-28); Hose, KatjaKnowledge graphs (KGs) are a foundational technology for representing and integrating information across heterogeneous domains. As some KGs evolve, understanding how their structural and semantic properties change over time is crucial for ensuring quality, consistency, and interpretability. Existing methods for KG evaluation often focus on static graphs or analyze evolution solely at the data level, leaving schema-level dynamics underexplored. To address this gap, we introduce MetriKG, a web-based application that computes a comprehensive set of metrics for both static and evolving KGs. MetriKG enables users to evaluate KGs provided as RDF files or through SPARQL endpoints, allowing for multi-dimensional analysis of aspects such as cohesion, connectivity, and inheritance depth. By supporting metric computation at both data and schema levels, MetriKG allows for systematic profiling, classification, and temporal monitoring of KGs. MetriKG is open-source and publicly available. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, MetriKG: Profiling Static and Evolving Knowledge Graphs(ACM, 2026-05-28); Hose, Katja - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Privacy preserving synchronization of directed dynamical networks with periodic data-sampling(Elsevier BV, 2025-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, VulnerSec: A Flexible, Automated and Open-Source Cybersecurity Framework(Faculty of Computer Science and Engineering, 2025) - Some of the metrics are blocked by yourconsent settings
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 yourconsent settings
Item type:Publication, A Comparison of GEC Tools for Grammatical Error Correction in English(IEEE, 2025-06-02) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A 12-Bit 20-kS/s 640-nW SAR ADC With a VCDL-Based Open-Loop Time-Domain Comparator(Institute of Electrical and Electronics Engineers (IEEE), 2022-02); ; Zhang, YanlongThis brief presents a 12-bit ultra-low-power asynchronous successive approximation register (SAR) analog-to-digital converter (ADC). A voltage-controlled delay line (VCDL) based open-loop time-domain comparator is proposed and analyzed, achieving low noise and ultra-low power performance. By employing the mixed switching scheme, the segmented capacitive digital-to-analog converter (CDAC) arrays as well as the synchronous data-weighted averaging (DWA) calibration block, the proposed SAR ADC can operate from 1.8 V down to 0.8 V at 20–200 kS/s. The designed ADC is fabricated in a 0.18- μm CMOS process and the measurement results show the proposed SAR ADC achieves an SNDR of 65-dB with power consumption of 647 nW from a 0.8 V power supply at 20 kS/s. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Detection of Premature Heartbeats(IEEE, 2022-05-23)Premature heartbeats are those that appear earlier than the regular ones due to contractions not originating from the Sinus Atrial Node, out of the normal heart rhythm. Although one might think this is a trivial task to detect, the distribution of premature heartbeats in the benchmark electrocardiograms shows it is not the case. We aim at finding the optimal method to detect premature heartbeats, threshold value and context level for temporal based approach. Methodology: Several methods are specified to calculate the relation of the premature heartbeat to a set of several previous instances and conduct experiments to present which averaging method (arithmetic, geometric and harmonic mean) delivers the best solution. Then, we calculate the deviation ratio to the average of these beats that affect the prematurity condition. Particularly, the goal is to find an average AV G of previous k beat-to-beat intervals RR, such that the ratio between the difference dRR of the analyzed RR and AV G versus AV G is more than a specific threshold T hr. Data: The comprehensive MIT-BIH Arrhythmia Electrocardiogram benchmark database is used in our evaluation. The analysis is conducted on the array of beat-to-beat intervals for the heartbeats preceding the premature one. Conclusion: The results show that the optimal method is based on the arithmetic mean AM We found that the larger k, the better performance is achieved. A sufficient performance with F1 score over 85% is achieved for k = 5 and T hr = 15%. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparing AWS Streaming Services: A Use Case on ECG Data Streams(IEEE, 2022-05-23) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Network Traffic Impact on Cloud Usage at Different Providers(IEEE, 2022-05-23); Markozanov, V.The research question focuses on finding an optimal cost-less and efficient solution, analyzing the differences between uploading and downloading data between different cloud solutions. The conducted experiments compare AWS cloud platform offered by Amazon and use two of its products: computational cloud platform EC2 and storage cloud platform S3. We explore three different versions of S3 storage and S3 Standard, each of them with its own purposes, characteristics and costs. Additionally we test the data transfer and computational capabilities of a t2.micro instance of the EC2 virtual machine. Then, we compare the experiment on the European Cloud provider - Scaleway Elements and use two of its products - Virtual Instances based on the Stardust instances for computations and Object Storage a S3 compatible storage platform.We conclude that the network connection between Amazon nodes is far superior than any other, both in performance and costs. Fetching results from an AWS computational service (EC2) is much cheaper and faster when using an AWS platform as an intermediary (S3) compared to a direct transfer to the local machine. We observe a similar superior network performance in the comparison of Scaleway Cloud Infrastructure.