The purpose of this study is to develop and describe software for the organization of labor protection during the construction of the Amur Gas Processing Plant (AGPP). The described methodology is based on risk assessment and selection of measures for managing the organization of construction and installation works. The professional risk management system was developed and put into practice in the 4th quarter of 2020. In 2022, based on the established database of identified hazards and their management measures, work was carried out to automate the process of hazard identification, as well as the formation of risk management maps and the familiarization of employees with the contents of these maps. The development and implementation of the proposed methodology has led to a significant reduction in the rates of health disorders of AGPZ employees both in terms of work-related diseases and injuries. The software developed as a result of the conducted research for professional risk assessment and management is recommended for practical use in the construction of new petrochemical and gas chemical plants.

A comprehensive understanding of the characteristics of the road network is imperative for implementing fundamental measures to enhance traffic efficiency and mitigate delays. The objective of the present study is twofold: firstly, to classify the urban street network in the city of Karbala; and secondly, to evaluate its effectiveness. Following the delineation of the area of study, traffic data is collected through the utilisation of video imaging technology and subsequently extracted from video files. Following this, the city streets are divided into multiple sections, and the speed of movement in each is calculated, as well as the speed of free flow. The primary objective of this study is to determine and compare the level of service (LOS) of a road based on Highway Capacity Recommendations (HCM 2000), including traffic speed, capacity to assess each segment of the network. The findings of the study revealed that roads of the first category constituted 25% of the total, while roads of the second category comprised 75% of the total. Furthermore, the level of maintenance of street sections is 25% when working with LOS C, 31.25% when working with LOS D, 12.5% when working with LOS E and 31.25% when working with LOS F, according to the assessment of transport operations based on average traffic speed.

The development of unmanned aerial vehicles is one of the promising directions for civil aviation with a wide range of applications. Neural networks can be trained for real-time decision making, adapting to changing battlefield conditions and ensuring optimal task execution. Among many UAV navigation and control tasks, the challenge of automatic landing of an unmanned aerial vehicle on a mobile landing platform (ships, vehicles, specialized platforms) remains relevant. Automated landing of an unmanned aerial vehicle on a mobile carrier is particularly significant.The article examines the system of automatic landing of an unmanned aerial vehicle (UAV) on a mobile platform using neural network technologies. The research method is based on the application of artificial neural networks for developing an adaptive control system capable of real-time decision-making during landing maneuvers.As a result of the research, a control algorithm was developed that ensures precise landing of UAVs on various types of moving platforms (ships, vehicles, specialized platforms), which significantly expands the operational range of unmanned vehicles and increases their efficiency in various operating conditions.

The use of PIRS (Polozov Information Rating System) technology in working with the Russian men’s national futsal team (head coach S.L. Skorovich) in the period from 2010 to 2018 allowed it to move from 5th place in the world ranking to first. The problem of managing a high-level sports team is to selectthe control indicators and their values in order to get the best result of the next match. Usually such parameters are: optimization of the composition, the direction of the game, the placement of their players, the tasks recommended to them. The aim of the study was to structure the activities for the transition from PIRS technology in working with top-level teams to the creation of the PIRSonline system. The description of the PIRSonline system for the development of its technical part required obtaining a number of schemes with their description, which regulated the development of the project. This is the composition of documentation, subsystems, functional diagram, component diagram, function-component matrix. The resulting sequence of actions for the development of PIRSonline includes image acquisition, a block for initializing game parameters, ball detection, determining the 3D coordinates of the ball, detecting players, tracking, classifying players and referees, determining the player’s pose. This made it possible to implement an integrated approach to online management of competitive activities of top-level teams. The use of modern computer vision and machine learning methods has made it possible to create interactive data visualization.

Methods of building a multidisciplinary expert decision support system in the field of construction have been developed. The architectural solution underlying the study is based on the theory of fuzzy sets. Software approaches to the design of specialized expert systems are considered, as well as the tasks solved by the decision support system at the stage of preparing an object for construction. The purpose of the study is to develop the architecture of an expert system consisting of logical inference systems and a set of interconnected fuzzy expert modules of the knowledge base. The objective of the research is to develop a generalized algorithm for the functioning of the expert system, the architecture of the knowledge base and a prototype of the software implementation of the expert system. As a result of the research, two software products have been developed in Python and a prototype in Matlab. Examples of interfaces and program code of the developed expert decision support system in the field of construction are given.

Nowadays, in the era of information technology, intelligent data processing methods play an important role in various spheres of life. These methods, together with modern algorithms and computer models, allow extracting valuable information from huge volumes of raw data, as well as analyzing and forecasting various phenomena and trends. The key concepts and principles of operation of the wavelet transform and stochastic methods, as well as their interrelation and possibilities of combined application in solving data processing problems are considered. Intelligent data processing methods focused on the wavelet transform and stochastic methods, which have become an integral part of modern business processes, providing forecasts essential for informed decisions, are investigated. The study used the wavelet transform and stochastic methods to detect hidden patterns and trends in data. These methods provided an opportunity to analyze data of various structures and scales, including texts, images, sound and video. The wavelet transform provided efficient data representation and multiscale analysis, while stochastic methods were used to model uncertainty and perform probabilistic analysis. It was demonstrated that the use of the wavelet transform contributed to the identification of significant features in the analyzed data, while stochastic methods provided reliable forecasts based on statistical models. Practical application of these methods on examples from various fields showed their high efficiency and significance in scientific and applied applications, which confirmed the relevance and prospects of further study and development of intelligent data processing methods. The importance of the wavelet transform and stochastic methods in the context of analyzing large amounts of data and predicting various phenomena was confirmed.

A method for determining the degree of loading of rolling elements in the working area of roller radial single-row bearings has been developed, according to this method the load distribution between rolling elements in the working area of these bearings depends on their location in this zone and the size of the contact pad between the maximally loaded rolling element and the outer ring of the bearing. Using the developed methodology, the radial force acting on the bearing is calculated for specific examples. As a result, the ratio between the radial force of the bearing and the force acting on the most loaded rolling body is obtained, which differs from the calculation of these bearings accepted in modern practice. It is also shown that this ratio is not constant, but depends on the magnitude of the force acting on the most loaded rolling body and the size of the rings and rolling bodies of the bearing. In this regard the following is proposed, in order to determine the maximum load on the rolling bodies-rollers in the working area of the bearing using the developed methodology, the method of iterations or successive approximations is suggested to be used, the essence of which consists in the initial approximate determination of the force acting on the most loaded rolling body, subsequent determination of the load on the bearing and comparing it with the actual force. By repeating this process many times, it is possible to obtain the maximum force acting on the rolling elements in the working area of the bearing with any degree of accuracy.

Presented method allows one to calculate the of maneuvers performed on several turns using a low-thrust engine. These maneuvers ensure the flight of an active spacecraft within a given area of the target space object. The flight is carried out in the vicinity of a circular orbit. Simplified mathematical models of motion are used to solve this problem. The influence of the non-centrality of the gravitational field and atmosphere is not taken into account in the calculations. The process of determining the parameters of the maneuvers is divided into several stages: in the first and third stages, the parameters of the impulse transfer and the transfer carried out by the low-thrust engine are calculated using analytical methods. In the second stage, the distribution of maneuvering between turns, ensuring a successful solution to the meeting problem, is determined by changing one variable. This method is characterized by its simplicity and high reliability in determining the parameters of maneuvers, which makes it applicable on board a spacecraft. As part of the study, an analysis of the dependence of the total characteristic velocity of solving the meeting problem on the amount of engine thrust was also carried out. The maneuver parameters can be refined using an iterative procedure to take into account the main disturbances.

Currently, unmanned aerial vehicles are widely used with navigation based on data from onboard integrated systems including inertial and satellite sensors. In this case, to solve many target tasks, their preliminary exit to a given point of the flight route along the shortest horizontal trajectory is provided. However, in practice, there may be situations when the information received from navigation satellites may no longer be available, which leads to a decrease in navigation accuracy. Considered a technique for detecting the trajectory of unmanned aerial vehicles under conditions of loss of signals from navigation satellites using the underlying surface images. As a criterion indicating the occurrence of deviations of unmanned aerial vehicles from a specified trajectory, it is proposed to use the change in parallaxes of adjacent pairs of images. Analytical relations describing the functional relationship between changes in image parallaxes and parameters of linear and angular deviations of unmanned aerial vehicles from a specified trajectory. All possible options of these deviations are also considered. The obtained results provide an a priori estimate of the threshold value of parallax changes corresponding to the acceptable level of unmanned aerial vehicles deviations from the specified trajectory by means of modelling. Based on this estimate, it is possible to improve the accuracy of trajectory detection of unmanned aerial vehicles under conditions of loss of signals from navigation satellites.

Porphyry copper deposits are accompanied by extensive aureoles of hydrothermally altered rocks which make it possible to detect them on satellite images in the absence of vegetation. The study is devoted to using the Earth’s remote sensing data, particularly, satellite images from the Japanese sensor ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), which are used to identify areas that are promising for the discovery of porphyry copper deposits and ore occurrences within the copper belt of Kazakhstan. The analysis of numerous publications that offer various methods for processing ASTER images for the interpretation of hydrothermally altered rocks accompanying porphyry copper occurrences showed that the most effective method for this region is the Crosta technique. The Crosta technique, unlike other methods, does not use primary bands, but their combinations are obtained by the principal components analysis method. Thus, the combination of the results of the principal components analysis with the use of index images and analysis of the geological map made it possible to identify areas of hydrothermally altered rocks in the study area. The described technique helps to predict promising areas for porphyry copper mineralization of varying degrees of reliability, associated with their hydrothermal processing.