The paper investigates the specifics of the digital implementation of a rotor synchronization control algorithm for the SV-2M two-rotor vibration unit. The influence of the sampling period on the stability of the synchronous mode is evaluated using computer simulations in MATLAB/Simulink, with time quantization and zero-order hold delay explicitly accounted for. A comparative analysis of the digital and analog versions of the algorithm has been performed. The boundary values of the discretization periods for different values of the given total energy of the system have been determined. The obtained results confirm the applicability of the proposed approach for digital control systems of vibratory equipment.

Keywords: digital control, rotor synchronization, two-rotor vibration unit, speed-gradient algorithm, extrapolator

The article focuses on the development of a web portal for monitoring and forecasting atmospheric air quality in the Khabarovsk Territory. The study analyzes existing solutions in the field of environmental monitoring, identifying their key shortcomings, such as the lack of real-time data, limited functionality, and outdated interfaces. The authors propose a modern solution based on the Python/Django and PostgreSQL technology stack, which enables the collection, processing, and visualization of air quality sensor data. Special attention is given to the implementation of harmful gas concentration forecasting using a recurrent neural network, as well as the creation of an intuitive user interface with an interactive map based on OpenStreetMap. The article provides a detailed description of the system architecture, including the backend, database, and frontend implementation, along with the methods used to ensure performance and security. The result of this work is a functional web portal that provides up-to-date information on atmospheric air conditions, forecast data, and user-friendly visualization tools. The developed solution demonstrates high efficiency and can be scaled for use in other regions.

Keywords: environmental monitoring, air quality, web portal, forecasting, Django, Python, PostgreSQL, neural networks, OpenStreetMap

The article is devoted to the application of modern methods of generative image compression using variational autoencoders and neural network architectures. Special attention is paid to the analysis of existing approaches to image generation and restoration, as well as a comparative assessment of compression quality in terms of visual perception and metric indicators. The aim of the study is to systematize deep image compression methods and identify the most effective solutions based on the variational Bayesian approach. The paper considers various architectures, including conditional autoencoders and hypernetwork models, as well as methods for evaluating the quality of the data obtained. The main research methods used were the analysis of scientific literature, a comparative experiment on the architectures of generative models and a computational estimation of compression based on metrics. The results of the study showed that the use of variational autoencoders in combination with recurrent and convolutional layers makes it possible to achieve high-quality image recovery with a significant reduction in data volume. The conclusion is made about the prospects of using conditional variational autoencoders in image compression tasks, especially in the presence of additional information (for example, metadata). The presented approaches can be useful for developing efficient systems for storing and transmitting visual data.

Keywords: variational autoencoders, generative models, image compression, deep learning, neural network architectures, data recovery, conditional models

The article presents numerical modeling of flow dividers (separators) with different hole diameters (3.5 mm, 7.0 mm, 14.0 mm) to prevent cavitation damage. The hole diameters, number, and rows in the separators have equivalent significance, as they determine the distribution of local velocities and pressures in the flow. This minimizes the risk of vapor bubble formation and subsequent collapse, which can lead to erosion of metal surfaces. For clarity, the simulation results are presented in the form of pictures of the distribution of pressure and velocities in each of the separators with different diameters. In order to prevent cavitation, the authors have presented a design of a "short-stroke" valve in which it is allowed to use flow dividers with enlarged holes.

Keywords: valve, cavitation, distribution pattern, separator, holes, rotation, simulation, flow divider

An oil field is a complex system the operability of which depends on the power supply reliability. The main disturbance in the electrical system is voltage sag which causes transient processes which can lead to a halt in oil production.
The article discusses the transients modeling in the oil production well electrical system, consisting of a transformer, a cable line and a submersible induction motor. The mathematical model has been compiled for calculating transient processes in such systems while each element is described as a separate module containing algebraic and differential equations which allows modeling dynamic and steady-state modes of operation. Dependences of longitudinal and transverse components of stator current and rotor speed of submersible induction motor at start-up, voltage sag and power supply disconnection are obtained.

Keywords: transient processes, electrical system, oil production, submersible induction motor, voltage sag, mathematical modeling

The paper considers the problem of classifying discharge and thermal defects in power transformers according to chromatographic analysis of dissolved gases, for which an expanded feature space has been formed based on concentrations of key gases and diagnostic ratios according to the International Electrotechnical Commission IEC 60599 standard. A comparison of various machine learning methods was carried out, among which the random forest algorithm showed the best results, which ensured maximum accuracy and stability of classification. The developed classifier complements the existing decision support system, providing automatic identification of the nature of defects based on chromatographic analysis of dissolved gases. The results of the study demonstrate the effectiveness of artificial intelligence methods in improving the reliability of transformer equipment diagnostics.

Keywords: power transformer, chromatographic analysis of dissolved gases, defect diagnostics, partial discharge, automated machine learning, ensemble methods, random forest, extra-trees

The issue of developing a prototype for an unmanned aerial vehicle (UAV) and creating a control system based on a computer-aided design (CAD) model as part of a project for inspecting construction sites is under consideration. Special attention has been paid to constructing a computer model of a quadcopter. Based on existing methods, energy calculations have been performed and a process for synthesizing controllers in orientation and positioning control circuits has been proposed, considering the sampling rate of the sensors utilized. The outcomes obtained through modeling confirm the suggested algorithm for adjusting controllers. The solution can be utilized by students and professionals in the development of autonomous UAVs or their computer models.

Keywords: quadcopter, computer modeling, PD controller synthesis, UAV design, stereo camera, room inspection

This article reveals the features of the operation of information and measuring systems during gas transportation. The issues reflected in the article are particularly relevant in the context of the need to achieve the efficiency of information and measuring systems in the oil and gas industry. The purpose of the scientific research is to develop an approach to information and measuring systems in oil and gas organizations based on the digital twin model. To achieve this goal, the article analyzes practical cases of information and measuring systems in oil and gas organizations, reflects the features of certification of information and measuring systems used in oil and gas organizations, and presents the results of developing an approach to information and measuring systems in oil and gas organizations based on the digital twin model.

Keywords: information and measuring systems; oil and gas industry; certification; digital twin model; gas transportation; approach; work efficiency

The article examines the features of dismantled paving slabs as raw materials for the production of recycled aggregate for concrete. The effect of crushed fine fractions of secondary crushed stone screenings on the properties of fine-grained self-compacting concrete was investigated. It was experimentally shown that the use of this material as a mineral additive leads to an increase in the water demand of the self-compacting fine-grained mixture and a significant decrease in strength.

Keywords: demolition waste, vibro-pressed paving slabs, recycling, screening of secondary crushed stone, mineral additive, self-compacting fine-grained concrete, consistency of concrete mix, strength, shrinkage

The article discusses the use of a recurrent neural network in the task of predicting pollutants in the air based on simulated data in the form of a time series. Neural recurrent network models with long Short-Term Memory (LSTM) are used to build the forecast. Unidirectional LSTM (hereinafter simply LSTM), as well as bidirectional LSTM (Bidirectional LSTM, hereinafter Bi-LSTM). Both algorithms were applied for temperature, humidity, pollutant concentration, and other parameters, taking into account both seasonal and short-term changes. The Bi-LSTM network showed the best performance and the least errors.

Keywords: environmental monitoring, data analysis, forecasting, recurrent neural networks, long-term short-term memory, unidirectional, bidirectional

The importance of recycling construction waste for the development of closed-loop economy technologies in the construction industry is considered. The effect of replacing high-quality granite and limestone crushed stone with secondary aggregate obtained by crushing concrete scrap on the strength properties of geopolymer concrete was investigated. It was established that such a replacement does not lead to a decrease in the strength of such concrete, and the impact resistance increases significantly.

Keywords: demolition waste, concrete scrap, recycling, geopolymer concrete, blast furnace granular slag, crushed stone crushing screening, closed-loop economy technologies, secondary aggregate, strength, impact resistance

This article explores the development and implementation of an intelligent chatbot for information support for university staff and students. The solution is integrated into a unified personal account and is based on the locally deployed Gemma language model, the n8n automation platform, and the Supabase vector database. The design methodology, technology comparison, system architecture, implementation process, and testing results are described. Implementation of the system enabled the automation of 85% of routine queries, reduced the average response time to 1.8–2.1 seconds, and increased user satisfaction to 4.58 out of 5. The study's results can be adapted for various automated educational systems, particularly for providing information support to operators in computer simulator training courses.

Keywords: intelligent chatbot, language models, artificial intelligence, information support, higher education, semantic search

Deviation of forestry equipment from the designated route leads to environmental, legal, and economic issues, such as soil damage, tree destruction, and fines. Autonomous route correction systems are essential to address these problems. The aim of this study is to develop a system for deviation detection and trajectory calculation to return to the designated route. The system determines the current position of the equipment using global positioning sensors and an inertial measurement unit. The Kalman filter ensures positioning accuracy, while the A* algorithm and trajectory smoothing methods are used to compute efficient routes considering obstacles and turning radii. The proposed solution effectively detects deviations and calculates a trajectory for returning to the route.

Keywords: deviation detection, route correction, mobile application, Kalman filter, logging operations

The annual growth of the load on data centers increases many times over, which is due to the growing growth of users of the information and telecommunications network Internet. Users access various resources and sources, using search engines and services for this. Installing equipment that processes telecommunications traffic faster requires significant financial costs, and can also significantly increase the downtime of the data center due to possible problems during routine maintenance. It is more expedient to focus resources on improving the software, rather than the hardware of the equipment. The article provides an algorithm that can reduce the load on telecommunications equipment by searching for information within a specific subject area, as well as by using the features of natural language and the process of forming words, sentences and texts in it. It is proposed to analyze the request based on the formation of a prefix tree and clustering, as well as by calculating the probability of the occurrence of the desired word based on the three sigma rule and Zipf's Law.

Keywords: Three Sigma Rule, Zipf's Law, Clusters, Language Analysis, Morphemes, Prefix Tree, Probability Distribution

The study is devoted to the development of electronic and distance learning tools for mastering the skills of applying mathematical methods by specialists in the field of automated systems development. The concept (structure) of an automated information system (AIS) for managing the life cycle of exercises to study optimization methods has been developed and schematically presented. An important element of decision support in the AIS is software simulators (training and training components) that generate exercise options and automatically check them based on the properties of mathematical models of optimization problems. An algorithmic and prototype software for the training subsystem for monitoring the skills of solving optimization problems have been developed. Variations in the interfaces for constructing a mathematical model for an optimization problem by a student when performing an exercise in the AIS are demonstrated. Building a model in the interface and, accordingly, the complexity of the exercise depends on the number of model parameters that can be changed by the student. The simulator provides an integral assessment of the student's actions when performing the task. The introduction of the simulator into the digital educational environment of the university will automate and simplify the implementation of current and intermediate control of knowledge and skills in the disciplines studied.

Keywords: optimization problems, mathematical programming, decision support, software simulator, mathematical modeling of systems and processes, visual modeling