An analysis of existing traffic models is presented, and the problems of processing the data used are revealed. The evolution of approaches to traffic management is considered, from classical analytical models to modern artificial intelligence methods. Special emphasis is placed on the key role of big data as a source of information for training, calibration, and operation of these models. The challenges and prospects of this subject area are described. A classification of road traffic models is given, micro-, macro-, and mesoscopic models are described, their key features, advantages and disadvantages are listed, and a mathematical apparatus describing them is formed. It is shown that the effectiveness of any control algorithm directly depends on the volume, quality and depth of analysis of incoming data. The methods of traffic modeling are systematized and their relationship with big data analysis technologies is demonstrated. The application of machine learning in traffic management tasks is described. The scientific novelty of the fundamental traffic model proposed by the authors is substantiated — this macroscopic model has the advantage of calculation speed, ease of modeling the traffic situation, and can be used to evaluate the regulated parameters of the specified characteristics of the road infrastructure.

The analysis of time delays in control signals is of particular importance for control systems operating over wireless communication networks, where communication latency may significantly affect stability and performance. A novel control strategy for cooperative adaptive cruise control systems based on the Lyapunov stability framework is presented. The proposed approach exploits the properties of homogeneous systems to achieve rapid convergence to the desired equilibrium state while ensuring the maintenance of a safe inter-vehicle distance within a vehicle platoon equipped with cooperative adaptive cruise control. Simulation results demonstrate that the proposed control approach achieves faster convergence and improved overall system performance compared with benchmark controllers, including conventional linear controllers and existing Implicit Lyapunov Function (ILF)-based methods.

Aerodynamic angle sensors (AAS) of a vane type are widely used in aviation to obtain information on aerodynamic angles of attack and sideslip. Their vane sensing elements are installed in the oncoming airflow. It is shown that during AAS operation, in addition to external atmospheric disturbances of the oncoming airflow, the vane sensing element is adversely affected by Karman vortices formed during periodic flow separation from adjacent streamlined surfaces of the vane. This necessitates studying the influence of Karman vortices on the vane sensing element oscillation within the AAS operating ranges. Models describing the proper motion of the vane sensing element in the aerodynamic angle measurement mode, models of Karman vortex parameters, and models of the influence of Karman vortices on the amplitude and frequency of forced oscillations of the vane sensing element are presented. The results of testing the obtained models are demonstrated, indicating the possibility of reducing the amplitude of oscillations of the weather vane sensitive element and the output signal of the weather vane AAS.

When designing high-availability, fault-tolerant distributed computing systems that must ensure continuous operation with minimal request-processing delays, the consolidation of redundant computing resources through their integration into clusters with container virtualization is becoming increasingly important. To justify architectural choices and enable structural-parametric optimization of such fault-tolerant clusters, it is essential to develop reliability models that reflect the operational specifics of virtual containers as well as the processes of cluster recovery and reconfiguration during container migration. The aim of this article is to construct an analytical reliability model for a multi-node cluster employing container virtualization, in which computing nodes (servers) host multiple containers. A Markov model is proposed that captures the two-stage recovery of cluster nodes: physical restoration of servers followed by container migration with their sequential loading once the server has been physically recovered from a failure. An analysis is carried out to evaluate how the cluster’s availability coefficient depends on its architectural parameters, including the number of servers, hardware failure rates, and the number of deployed containers loaded during migration. The proposed model provides a foundation for substantiating design decisions in the development of fault-tolerant container-based clusters and modern cloud platforms.

The possibility of using telecommunication optical fiber used in fiber-optic communication lines to create a sensor for measuring the velocity of gas flows is discussed. The purpose of the article is to develop an easy–to–implement design of a fiber-optic air flow velocity sensor. The object of the study is a single-mode optical fiber G655. Various variants of fiber-optic sensors for measuring air flow velocity have been proposed, an experimental setup has been created and a methodology has been developed to study the characteristics of these sensors. A design variant of the sensor that is most sensitive to changes in air flow velocity has been determined. The range of air flow rates for which the proposed sensors can be used is estimated. It is shown that the studied sensors can be used as threshold alarms for exceeding the air flow velocity of a certain value. The results of the performed research can be used in the development and creation of information and measuring systems for determining the speed of air and gas flows, as well as in ventilation systems.

Results of a quantum chemical analysis of the spectral and electronic characteristics of a pentacene molecule, one of the most promising organic semiconductors, are presented. The calculations are performed using the TD-DFT method and the Gaussian software package. The first six excited states of pentacene are analyzed in order to identify the most effective photoactive transitions. Key parameters are computed, including the excitation energy, absorption wavelength, oscillator strength, dipole moment, rotational strength, and the energy gap between the HOMO and LUMO orbitals. It is shown that the first excited state (S1) is characterized by a low excitation energy (1.6560 eV), an absorption wavelength of 748.71 nm (near-infrared range), and a relatively high oscillator strength (0.0375), which indicates effective absorption of near-infrared radiation. The excited states S2—S6 exhibit significantly weaker absorption, mainly in the ultraviolet region of the spectrum. Analysis of the HOMO—LUMO gap indicates significant electron delocalization and a small energy gap, contributing to efficient charge transfer. It is established that the electric dipole moment is oriented predominantly along the Y axis, which may be of practical importance for devices operating with polarized radiation. In general, the results obtained confirm the expediency of using pentacene as an active material for organic photosensitive electronic devices and allow to identify areas for further optimization, including control of molecular orientation.

An analysis of modern methods for assessing the quality of prosthetic and orthotic alignment is presented. The most significant biomechanical parameters during prosthetic fitting and defines promising areas for automating the alignment process are identified. An analytical review of studies is conducted in accordance with PRISMA recommendations. Materials are selected from the PubMed, ScienceDirect, CyberLeninka, and Europe PMC databases for the period 2013–2025. An analysis of 15 studies using biomechanical analysis methods is conducted: measuring socket reaction moments, gait kinematics and kinetics, and stabilometric indicators. Particular attention is paid to studies using instrumental methods for recording alignment parameters. The results of a comparative analysis of key study parameters during fitting are presented. It is found that socket reaction moments demonstrate the greatest sensitivity to alignment changes, especially in the frontal plane, where displacements of 2–6 mm cause statistically significant changes in moments. Correlations are identified between angular changes in the prosthetic foot and the temporal characteristics of reaction moments. The data obtained substantiate the need to develop software packages for automated calculation of adjustment parameters for adjusting and connecting devices based on objective biomechanical parameters. A promising area is the implementation of such systems in clinical practice in the CIS countries, where the mass production of prosthetic and orthotic devices requires modern solutions for standardization and improved patient care. Further research is to be aimed at adapting automated adjustment algorithms to regional prosthetic specifics and state standard requirements.

Some features of modern product manufacturing are considered and emphasis is placed on assembly technological operations on circular conveyor lines. It is noted that an urgent technical task is to increase the technological flexibility of production. The possibility is considered and the expediency of the periodic participation of a human operator in the process of kitting and assembling on a conveyor line is justified in order to increase the level of technological flexibility of production

The issues related to the production of radio electronic equipment, in particular printed circuit boards, are discussed; namely, the inconsistency of certain characteristics of individual products is considered. Defects in the production of the equipment are difficult to detect, which often requires its reissue, while stricter tolerances lead to excessive production costs. The actual problem of assessing product requirements and their selection is discussed, in which the product's operability is ensured and excessive rejection does not occur. The end-to-end process of designing and manufacturing radio electronic equipment using probabilistic characteristics is considered. A methodology for assessing the correctness of product requirements is proposed using the example of the main stages of design and production of printed circuit boards. At the same time, the data obtained at the production stages is used to adjust the tolerance fields of product characteristics and parameters at the design and pre-production stages, which reduces the cost of ensuring product quality requirements. A model calculation is presented using the example of a screen-printing operation with solder paste.

A cross-platform application, QSAXSPreprocessing, with a graphical user interface is presented — a software implementation of the procedure for correcting the indicatrix of small-angle X-ray scattering, accounting for contributions from large particle agglomerates and atomic-scale inhomogeneities. The application uses the Numpy, Scipy, and Matplotlib libraries and is a software package consisting of modules written in Python3, combined into a unified interface based on the PyQt5 library. The current version of the application has been tested on Windows 10/11 and Ubuntu 28.1. QSAXSPreprocessing 1.1 has been successfully used for the analysis of small-angle X-ray scattering from nanoparticle powders.