artificial intelligence

This review paper provides a comprehensive comparative analysis of abandoned object detection algorithms, specifically contrasting rule-based approaches with artificial intelligence (AI-based) models. The manuscript synthesizes existing research, technical documentation, and publicly available benchmark data to evaluate the applicability of these approaches in dynamic video surveillance environments.

Academicism in scientific research was a breeding ground for theories of mass communication of past times and eras. We express our deep conviction here that it should remain so for new times, for the following modernized versions of media theories. In previous monographs, we have already called the outdated theory of mass communication a new term: the theory of interaction with the mass audience – and, as its synonym, the theory of mass media [1; 2].

This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

In the modern world, software security has become a top priority, as it directly determines the reliability of digital solutions and user trust. The growing number of cyber threats and the increasing complexity of software systems highlight the necessity of using effective tools for control and vulnerability prevention.

This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

his article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

Paper presents a comprehensive analytical review and synthesis of modern approaches to the development of decision support systems (DSS) based on multi-agent system (MAS) technologies. The evolution of corporate DSS from classical centralized architectures to distributed intelligent systems is examined.

The formation of project teams, the allocation of resources, the assessment of specialists' competencies, and the forecasting of project results all require analysing a significant number of interrelated factors. Traditional approaches to IT project management often rely on expert assessments and managers' experience, leading to subjectivity in decision-making and reduced team performance.

The article examines the design of the architecture of neural network–based image generation systems, their operating algorithm, principles, and components, as well as their functional characteristics, interconnections, and the modern technologies and tools used to implement individual subsystems. An architecture for a neural network image generation system was developed, featuring a modular structure composed of several typical components, including a data input processing subsystem, a generative core, a result quality control system, and a user interaction interface.

The study aims to justify and test an approach to the automated conceptualization of the DevOps subject area using large language models. This paper explores the potential applications of LLMs in concept classification, ontology construction, and configuration structure explanation. Additionally, it analyzes the models' capabilities in supporting the training and auditing of DevOps processes. The research methodology consists of four stages. First, an initial set of DevOps concepts was generated using an LLM.