CSIT - 2026 рік

Постійне посилання зібрання

https://elar.khmnu.edu.ua/handle/123456789/20852

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Перегляд CSIT - 2026 рік за Ключові слова "004.9"

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  • Ескіз
    Документ
    Analysis of information technologies and methods for automatic updating of threat detection models in computer systems
    (Хмельницький національний університет, 2026) Isaiev, Tymur; Atamaniuk, Olha
    The development of intelligent adaptive information technologies for automatic updating of threat detection models in computer systems is one of the most important directions in modern research on information technologies. Computer systems today operate in environments that are constantly changing, influenced by new software, evolving hardware, and diverse data processing methods. Traditional static approaches, which rely on fixed rules or predefined models, often become outdated quickly and fail to provide the necessary adaptability. Existing approaches to detection in computer systems have been studied extensively, and while they provide valuable insights, they also demonstrate clear limitations. Signature-based methods depend heavily on known patterns and therefore struggle to identify new or unexpected phenomena. Heuristic analysis allows for broader generalization but is frequently associated with high rates of false positives, which reduces its practical usefulness. Behavioral monitoring can capture dynamic changes in system activity, yet it requires significant computational resources and may slow down performance. Machine learning models offer adaptability and the ability to learn from data, but they demand large amounts of training information and careful tuning to avoid errors. Hybrid approaches attempt to combine the strengths of multiple techniques, but they often face difficulties in seamless integration and optimization within existing infrastructures. Because of these limitations, researchers are increasingly focused on developing frameworks that incorporate automatic updating mechanisms. Such frameworks are designed to be self-adaptive, meaning they can evolve continuously in response to new conditions without requiring manual intervention. Real-time adaptation is a central feature of these systems, enabling them to improve accuracy, reduce false positives, and optimize the use of computational resources. By integrating intelligent updating mechanisms, information infrastructures can achieve higher levels of stability and efficiency. This not only enhances the overall performance of computer systems but also ensures that they remain relevant and effective in environments where change is constant. The ability to evolve automatically, without relying on outdated static methods, positions these technologies as a cornerstone of future developments in information systems. The continuous evolution of computational environments demands solutions that are flexible, intelligent, and capable of real-time adaptation. By embracing adaptive frameworks, researchers and developers can create systems that are not only more accurate and efficient but also more resilient and scalable. This marks a decisive step toward the next generation of computer systems, where adaptability and automation are essential for long-term reliability and success.
  • Ескіз
    Документ
    Modeling the process of recognition of pacemaker dysfunction
    (Хмельницький національний університет, 2026) Medzatyi, Dmytro; Hryshchuk, Illia
    The article presents a comprehensive study aimed at solving a pressing scientific and practical problem - modeling and designing information technology for recognizing pacemaker dysfunctions to increase the efficiency of diagnostics and reliability of life support systems. The relevance of the work is due to the rapid growth of the number of cardiovascular diseases in the world and in Ukraine in particular, which leads to an increase in the number of operations for implanting pacemakers, the functioning of which requires continuous and highprecision monitoring. The authors analyzed the world experience in using modern diagnostic tools, including neural networks for analyzing radiographs, mobile applications for remote monitoring, and machine learning algorithms for ECG analysis, which revealed the lack of integrated solutions that would combine different methods for detecting technical and clinical failures. The proposed approach is based on the use of multimodal input data, such as information about the patient's symptoms (dizziness, arrhythmia, weakness), device hardware reports (pacing rate, battery status, intracardiac signals), ECG and Holter monitoring results, as well as data from physical activity and intracardiac pressure sensors. The scientific novelty of the study lies in the development of a mathematical model of the process of recognizing pacemaker dysfunction, presented as a sequence of tuples and transformations that provide data preparation, selection of the most informative signs of cardiac activity and direct recognition of the system state. Special attention is paid to the stages of signal normalization and artifact filtering, which guarantees high accuracy of classification of disorders even under difficult operating conditions or during physical exertion of the patient. The practical significance of the work is confirmed by the creation of a structure of output results, which include not only automated fixation of anomalies, but also the formation of specific recommendations for changing pacemaker settings and instant notification of medical personnel, relatives and the patient himself. The proposed technology allows to ensure a continuous monitoring cycle, minimize the risk of human error when interpreting complex diagnostic data and significantly improve the prognosis for patients with high dependence on an artificial pacemaker. Thus, the results obtained create a reliable foundation for building modern information technologies for cardiac care.
  • Ескіз
    Документ
    Seamless tiling of quasi-periodic textures via an optimal cyclic shift on a discrete torus
    (Хмельницький національний університет, 2026) Bedratiuk, Anna
    In practical computer vision and computer graphics pipelines, it is often necessary to repeatedly replicate a single texture sample to construct a large canvas, background, or regular covering. When the mosaic is not strictly periodic, visible seams appear at the boundaries during repetition, disrupting the perceptual continuity of the texture and often manifesting as a regular grid of artifacts. Such seams not only degrade visual quality but can also alter local gradients and spectral components, which is critical for subsequent processing stages. Common seamless stitching methods increase computational complexity, introduce additional hyperparameters, and modify the local image statistics, which is undesirable in reproducible pipelines and in tasks where the invariance of pixel values is essential. The goal of this work is to propose a simple, reproducible, and computationally efficient method for seam reduction in quasiperiodic textures by selecting an optimal cyclic shift of the pattern that minimizes the energy of mismatch between opposite boundaries. The tile is modeled as a function on the discrete torus ℤ𝑀 × ℤ𝑁. A cyclic shift group 𝐺 = ℤ𝑀 × ℤ𝑁 is introduced, acting as a permutation of pixels. For each shift 𝜏𝑎,𝑏 , the boundary seam energy 𝐸(𝜏𝑎,𝑏 𝐼) is computed in a band of width 𝑤 for opposite boundary pairs, and the minimizing shift is selected. When needed, the evaluation is accelerated via cyclic correlations and FFT. Experiments on synthetic and real textures show that the optimal cyclic shift significantly reduces seam energy and the visual prominence of boundaries during tiling without modifying pixel values. For strictly periodic tiles, the method does not degrade the result. The proposed approach is a lightweight baseline tool for seamless tiling: it does not perform stitching but selects the best cut of the torus. The method is easy to integrate into production pipelines and can be used as a preprocessing step before further processing
  • Ескіз
    Документ
    Survey of tools and technologies for psychoemotional screening and determining the status of patients with depression
    (Хмельницький національний університет, 2026) Pytlyak, Maksym
    The article is devoted to a comprehensive analysis of the current state and prospects for the development of information technologies for psychoemotional screening of patients with depressive disorders. The relevance of the study is due to the global increase in the prevalence of mental disorders, which in the conditions of modern challenges, in particular martial law, is becoming a critical threat to public health and economic stability. The work systematizes scientific sources, which made it possible to identify key trends in the field of digital psychiatry. The main attention is paid to a comparative analysis of existing methods according to eight fundamental criteria that determine the suitability of the technology for real clinical implementation. Among them, the availability of decision-making algorithms, patient routing mechanisms in the primary care setting, the use of validated psychometric tools, integration with electronic medical records, real-time notification systems, adaptation to the individual user norm, ethical transparency, and research on objective behavioral markers. The results of the analysis indicate a significant fragmentation of existing solutions - with a high interest of researchers in the use of biomarkers (voice, eye tracking, electroencephalography and locomotor activity) and artificial intelligence, there is an almost complete absence of systems integrated into the state medical infrastructure. It was found that most of the existing mobile applications and cyber-physical systems operate in isolation from the primary care level, which complicates timely diagnostics and continuity of treatment. The work places special emphasis on the importance of digital phenotyping, which allows objectifying the patient's condition through monitoring motor activity, but it is proven that such data must necessarily be combined with classical clinical protocols. It is substantiated that the lack of integration with electronic medical records and formalized routing algorithms are the main barriers to creating an effective national screening system. Based on the identified "blank spots" in world scientific practice, the author has proven the need to develop a unified information technology that would act as a full-fledged link in the medical process. The analytical basis of the article serves as a theoretical basis for designing a new information technology capable of providing a closed cycle of "monitoring - diagnostics - routing - treatment". The scientific novelty of the work lies in the systematic approach to evaluating screening technologies, which allows us to clearly identify the vectors of further research in the direction of creating information technology adapted to the needs of the modern healthcare system.