20.04.2026

Vol. 23, No. 1, 2026

INFORMATION TECHNOLOGY AND COMPUTER ENGINEERING
 
ISSN 1999-9941
e-ISSN 2078-6387
 
Publisher: VINNYTSIA NATIONAL TECHNICAL UNIVERSITY
13 Articles
19 Authors

ChaCha: Development and modification of Salsa20 in modern cryptographic systems

26.03.2026

Oleksii Palii, Oleksandr Dudnyk
  • Keywords stream cipher; Advanced Encryption Standard; TLS 1.3; cryptanalysis; resource-constrained systems
  • DOI https://doi.org/10.31649/vitce/1.2026.09

Prompt engineering for large language models in test case generation

26.03.2026

Anatolii Husakovskyi
  • Keywords CodeLlama; StarCoder; zero-shot prompting; few-shot prompting; chain-of-thought prompting; role prompting; CI/CD integration
  • DOI https://doi.org/10.31649/vitce/1.2026.22

Interactive visualisation and analysis of risks with a human factor

26.03.2026

Viktoriia Trofymchuk
  • Keywords mathematical modelling; data visualisation; Bayesian analysis; Markov processes; social engineering
  • DOI https://doi.org/10.31649/vitce/1.2026.35

Comparative analysis of machine learning algorithms for personalising educational content in distance learning

26.03.2026

Vitalii Yanishevskyi
  • Keywords digital environment; Learning Management System; hyperparameter optimisation; neural networks; synthetic dataset
  • DOI https://doi.org/10.31649/vitce/1.2026.46

Method for protection of unstructured information on modern mobile platforms: Threat modelling and effectiveness analysis

26.03.2026

Evgen Brovchenko, Valeriy Samaraj
  • Keywords multi-factor authentication; recurrent neural networks; logistic regression; adaptive encryption; hybrid blockchain architecture
  • DOI https://doi.org/10.31649/vitce/1.2026.60

Forecasting of time series using a neural network with parallel-stacked LSTM blocks

26.03.2026

Yurii Futryk, Ivan Peleshchak
  • Keywords deep learning; Dropout-regularisation; Nadam-optimisation; EMA; RSI
  • DOI https://doi.org/10.31649/vitce/1.2026.72

Method of dynamic trust assessment in Zero Trust Architecture based on explainable artificial intelligence

26.03.2026

Andriy Palamarchuk
  • Keywords cybersecurity; machine learning; SHAP; XGBoost; anomaly detection; adaptive protection
  • DOI https://doi.org/10.31649/vitce/1.2026.83

Algorithms and software architecture for automated user behaviour analysis in cyber threat detection systems

26.03.2026

Denys Kovalchuk
  • Keywords User and Entity Behaviour Analytics; large language models; artificial intelligence; machine learning; data-driven approach
  • DOI https://doi.org/10.31649/vitce/1.2026.94

Improving the efficiency of Whisper-based audio stream processing with CTranslate2 and FFMpeg tools

26.03.2026

Vladyslav Radin, Myroslav Riabyi
  • Keywords quantisation; automatic speech recognition; operator fusion; video memory; resource efficiency
  • DOI https://doi.org/10.31649/vitce/1.2026.110

Effectiveness of artificial intelligence for test prioritisation in distributed systems of Ukrainian and international software development

26.03.2026

Andrii Zadorozhnii
  • Keywords intelligent algorithms; machine learning; hybrid methods; optimisation algorithms; scalability; testing efficiency
  • DOI https://doi.org/10.31649/vitce/1.2026.125

A hybrid A-UKF-PINN digital twin architecture for real-time state estimation in Smart Grids

26.03.2026

Vladimir Vychuzhanin, Alexey Vychuzhanin
  • Keywords hybrid modelling; Physics-Informed Neural Networks; Unscented Kalman Filter; functional superiority; Edge-Cloud
  • DOI https://doi.org/10.31649/vitce/1.2026.140

Analysis of the construction of a communication network of the tactical control link based on software-defined radio communication means

26.03.2026

Hryhorii Radzivilov, Dmytro Pavliuk
  • Keywords communication network; self-organising network; multichannel architecture; gateway node; satellite communication channel; electronic warfare
  • DOI https://doi.org/10.31649/vitce/1.2026.153

Application of deep learning methods to image processing and enhancement: A case study on seismic data

26.03.2026

Ruslan Malikov
  • Keywords image restoration; image denoising; structural preservation; seismic image reconstruction; supervised learning
  • DOI https://doi.org/10.31649/vitce/1.2026.170