Сonditional printed sheet Approved for publication by the Academic Council of Odesa Polytechnic National University on the issue publication (Protocol No. 12 dated 24, February 2026)

Recommended for publication by the Academic Council of the Computer Systems Institute of Odesa Polytechnic National University (Protocol No. 5 dated 23, February 2026)

DOI: https://doi.org/10.15276/hait
 

Vol. 9 No. 1 (2026)

“Herald of Advanced Information Technology”

Table of Contents

Theoretical aspects of computer science, programming and data analysis

A modified image encryption algorithm based on the  chaotic Tent map

Dmitro V. Dmitrishin, Vitaly M. Khamitov , Svitlana G. Antoshchuk, Viktor O. Boltenkov
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9–19

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Non-numerical information processing in biotechnical systems with biofeedback

Vladimir I. Mescheryakov, Dmitry V. Mescheryakov
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20–29

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A method for constructing non-basic GL-models by combining models with arbitrary graph structures

Vitaliy A. Romankevich, Kostiantyn V. Morozov, Alexei M. Romankevich, Daniil V. Halytsky, Lefteris Zacharioudakis
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30–45

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Anomaly detection on time series data for autonomous robot operation

Maksym A. Shavarskyi, Yurii P. Kryvechuk
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46–59

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Information technologies and computer systems

IMECA method of risk-based assessment and ensuring cybersecurity of Large Language Models

Oleksii S. Neretin, Vyacheslav S. Kharchenko
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60–70

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A method for detecting financial phishing in instant messengers using an ensemble of dialogical intelligent assistants based on large language models

Oleksandr G. Korchenko, Ihor A. Tereikovskyi , Oleksandr Y. Korystin, Liudmyla O. Tereikovska, Oleh I. Tereikovskyi
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71–84

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Information technologies in energy systems engineering and manufacturing

Optimizing the control of a transactive energy system with periodically changing architecture based on Internet of energy

Volodymyr V. Khilenko, Serhii P. Denysiuk , Halyna S. Bielokha, Oleksii V. Stepanov, Li-Wei Kang
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85-99

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Information technologies in socio-economic, organisational and technical systems

Comparative evaluation of deep neural networks for brain tumor classification from magnetic resonance imaging

Dmytro I. Uhryn, Yurii O. Ushenko, Artem O. Karachevtsev, Yurii O. Halin
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100–113

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Published: 2026-02-24

2663-7731 (Online)
ISSN 2663-0176 (Print)