DSpace Фонд:

Development of a system of indices for monitoring and assessing the sustainability of underground utilities

2026-01-01T00:00:00Z

Назва: Development of a system of indices for monitoring and assessing the sustainability of underground utilities Автори: Liubynskyi P. Короткий огляд (реферат): The paper proposes a comprehensive system of indices to monitor and assess the operational sustainability of urban underground utility networks. Modern municipal engineering infrastructures face critical issues such as accelerating infrastructure aging, highly aggressive operating environments, and stringent financial constraints. To systematically address these challenges, this study identifies seven distinct categories of performance indices: availability, funding sources, effectiveness of rehabilitation work, accident mitigation, environmental safety, efficient use of funds, and efficiency of monitoring implementation. Each index is formalized mathematically to measure a specific operational or socio-economic dimension of utility networks. The developed methodology establishes strict regulation for calculating these indicators, determines their variations across stable intervals, and uncovers synergistic correlations between proactive organizational-technological monitoring and long-term network durability. The practical significance lies in providing municipal utility managers with a reliable decision-making framework to optimize capital investments, mitigate environmental hazards, and sustain public service provision stability.

Prerequisites for developing a business process automation system for an IT enterprise

2026-01-01T00:00:00Z

Назва: Prerequisites for developing a business process automation system for an IT enterprise Автори: Pochanskyi O. Короткий огляд (реферат): The article examines the prerequisites for creating and implementing business process automation systems at information technology (IT) enterprises. The evolution of IT infrastructure management approaches from a resource-based model to a service-oriented concept (ITSM) based on the ITIL library of best practices is analyzed. The architectural features of building modern information systems, particularly the client-server architecture, as well as tools for modeling business processes and databases (ERwin, BPwin, PowerDesigner) are investigated. A comparative analysis of current ServiceDesk/HelpDesk software solutions available on the market (BPM'online service, ITSM 365, ServiceNow, ITSM InfraManager) is conducted, highlighting their advantages, disadvantages, and pricing characteristics. The necessity of developing affordable specialized automation systems for small IT businesses is substantiated.

Hybrid Rule-Based / Machine-Learning Autoscaler for Kubernetes: Reducing Resource Over-Provisioning on a Real Cluster

2026-01-01T00:00:00Z

Назва: Hybrid Rule-Based / Machine-Learning Autoscaler for Kubernetes: Reducing Resource Over-Provisioning on a Real Cluster Автори: Murzha D. Короткий огляд (реферат): Resource allocation for microservice applications in Kubernetes is still handled, in most deployments, by reactive mechanisms. The Horizontal Pod Autoscaler (HPA) and extensions such as KEDA change the replica count only after a monitored metric has already crossed a fixed threshold, which in practice means over-provisioning under noisy load and a sluggish response when demand genuinely spikes. This paper presents HMRO (Hybrid Microservices Resource Optimizer), an autoscaler that pairs a deterministic rule-based engine with an ensemble of machine-learning load predictors whose influence on each decision is not fixed but adjusted continuously according to how accurate the predictors have recently been. HMRO was evaluated on a real Kubernetes cluster (Minikube) against the standard HPA across memory and combined CPU+memory workloads, each with three scenarios and ten iterations. HMRO reduced the average replica count (a direct proxy for over-provisioning) by 36–42% for memory (all p < 0.05) and 20–28% for combined workloads (significant in two of three scenarios), while triggering a comparable number of scaling actions – that is, without losing responsiveness. A comparable reduction was observed for CPU-driven workloads in an earlier evaluation on a prior prototype version. An ablation study isolates the source of the saving: it comes primarily from the asymmetric rule engine, whereas the ML component adds proactivity rather than resource reduction.

Intelligent decision support systems in cybersecurity: from fuzzy logic to LLM agents

2026-01-01T00:00:00Z

Назва: Intelligent decision support systems in cybersecurity: from fuzzy logic to LLM agents Автори: Khavina I.; Limarenko V.; Hnusov Yu.; Mozhayev O.; Tsuranov M. Короткий огляд (реферат): The monograph presents a holistic scientific concept of intelligent cybersecurity management at the enterprise level. The mathematical apparatus of hierarchical structuring of security parameters and strategic selection of protection systems using the analysis of hierarchies (AHI) method by T. Saati is highlighted. The development of decision support systems (DSS) based on the Mamdani fuzzy inference algorithm in the MATLAB environment is described in detail. Decentralized multi-agent systems built on the basis of the cooperative problem solving (CPS) model and optimized by auction algorithms for task distribution based on the “regret” criterion are considered. Special attention is paid to the integration of autonomous artificial intelligence agents and the development of corporate search-augmented generation (Agentic RAG) systems for proactive detection of zero-day threats and anomalous user behavior. The publication is intended for scientists, cybersecurity and information protection specialists, developers of intelligent systems, as well as graduate students and senior students in relevant specialties.