The article presents the results of a study devoted to the development of an identification subsystem for an industrial process operator in a mobile simulator used for training and monitoring professional skills. The functional requirements for the operator identification subsystem based on neural network technologies, the processes of user interaction with the personality recognition subsystem, and loading a reference image for further identification of the operator during training and monitoring on the simulator are formalized using visual models in UML notation. A prototype of the subsystem has been developed based on the Kotlin programming language and the TensorFlow library. The developed image analysis subsystem has a high speed of face detection and initialization, reaching less than 0.5 s, which makes it especially effective for real-time tasks where performance plays a key role. Local data processing on mobile devices ensures protection of user privacy by eliminating data transfer to remote servers, which minimizes the risks of information leaks. Optimization of power consumption ensures long-term operation on devices with limited battery capacity, which makes the system convenient and practical to use. The considered subsystem is planned to be adapted for monitoring the formation of skills for working on equipment during operator training on mobile simulators. The subsystem, based on VR/AR technologies, as well as a trained neural network, will analyze data on user reactions in real time.

Keywords: mobile simulators, neural networks, user identification, professional training, UML diagrams, TensorFlow

The present study aims to explore the methodologies employed in practice to ascertain the parameters of processes occurring in supercritical fluid media. A primary focus of this investigation lies in the solubility of key components of the system in supercritical fluid solvents, with a view to understanding the limitations of mathematical models in qualitatively predicting solubility outside the investigated ranges of values. This analysis seeks to elucidate the potential challenges and opportunities in conducting experimental studies in this domain. However, within the domain of supercritical fluid technologies, the optimization of processes and the prediction of their properties is attainable through the utilization of models and machine learning methodologies, leveraging both accumulated experimental and calculated data. The present study is dedicated to the examination of this approach, encompassing the consideration of system input parameters, solvent properties, solute properties, and the designated output parameter, solubility. The findings of the present study demonstrate the efficacy of this approach in predicting the solubility process through machine learning.

Keywords: supercritical fluids, solubility of substances, solubility factors, solubility prediction, machine learning, residue analysis, feature importance analysis

Optimization of the composition of heavy cement concretes modified with a complex additive based on industrial waste (alumina-containing component - aluminum slag (ASH), spent molding mixture (OFS) using the PlanExp B-D13 software package is a three-factor planned experiment, according to the criteria: compressive strength on the 2nd and 28th days of hardening.

Keywords: heavy cement concretes, fast-hardening concretes, optimization, experiment planning, strength indicators, industrial waste, spent molding mixture, aluminum slag

The article is devoted to the development and implementation of a two-stage magnetometer calibration algorithm integrated into the navigation system of a small-class unmanned underwater vehicle. At the first stage, an ellipsoidal approximation method is used to compensate for soft iron and hard iron distortion, ensuring the correct geometric location of magnetometer measurements. The second stage of calibration involves a method for estimating rotation between the coordinate systems of the magnetometer and accelerometer using quaternions as rotation parameters. Experimental verification of the algorithm demonstrated its effectiveness. Following completion of the two-step calibration, calibration parameters were determined and their use confirmed good consistency between magnetometer readings and actual magnetic field data, indicating the feasibility of using this technique for calibrating magnetometers.. The proposed algorithm for two-stage magnetometer calibration does not require laboratory equipment and can be carried out under real-world operating conditions. This makes it possible to integrate it into the onboard software of unmanned underwater vehicles.

Keywords: calibration, magnetometer, accelerometer, MEMS sensor, AHRS, navigation system, unmanned underwater vehicle, ellipsoid approximation, quaternion, magnetic inclination

When evaluating student work, the analysis of written assignments, particularly the analysis of source code, becomes particularly relevant. This article discusses an approach for evaluating the dynamics of feature changes in students' source code. Various metrics of source code are analyzed and key metrics are identified, including quantitative metrics, program control flow complexity metrics, and the TIOBE quality indicator. A set of text data containing program source codes from a website dedicated to practical programming, was used to determine threshold values for each metric and categorize them. The obtained results were used to conduct an analysis of students' source code using a developed service that allows for the evaluation of work based on key features, the observation of dynamics in code indicators, and the understanding of a student's position within the group based on the obtained values.

Keywords: machine learning, text data analysis, program code analysis, digital footprint, data visualization

The study presents an approach to modelling multivariate time series using parameterisation, using yield curve as an example. The effectiveness of adding parameterisation coefficients to predicates is evaluated, and new loss functions are proposed that focus on modelling the shape of the curve. Prediction models including LSTM, Prophet and hybrid combinations were applied. A Python-based system was developed to automate data processing and evaluation. The method improves the accuracy and interpretability of forecasts, offering a promising tool for financial modelling.

Keywords: machine learning, financial engineering, stock market modeling, bond market

In the article, based on the estimate of the Euclidean norm of the deviation of the coordinates of the transition and stationary states of the dynamic system, the compression condition of the generalized projection operator of the dynamic system with restrictions is derived. From the principle of contracting mappings, taking into account the derived compression condition of the projection operator, estimates are obtained for the sufficient condition for the stability of the dynamic system of stabilization of the equilibrium position and program motions. The obtained estimates generalize the previously obtained results. Ensuring the stability of the operator of a limited dynamic system is demonstrated experimentally.

Keywords: sufficient condition for stability, projection operator, stabilization of equilibrium position. stabilization of program motions, SimInTech

This article discusses two of the most popular algorithms for constructing dominator trees in the context of static code analysis in the Solidity programming language. Both algorithms, the Cooper, Harvey, Kennedy iterative algorithm and the Lengauer-Tarjan algorithm, are considered effective and widely used in practice. The article compares these algorithms, evaluates their complexity, and selects the most preferable option in the context of Solidity. Criteria such as execution time and memory usage were used for comparison. The Cooper, Harvey, Kennedy iterative algorithm showed higher performance when working with small projects, while the Lengauer-Tarjan algorithm performed better when analyzing larger projects. However, overall, the Cooper, Harvey, Kennedy iterative algorithm was found to be more preferable in the context of Solidity as it showed higher efficiency and accuracy when analyzing smart contracts in this programming language. In conclusion, this article may be useful for developers and researchers who are involved in static code analysis in the Solidity language, and who can use the results and conclusions of this study in their work.

Keywords: dominator tree, Solidity, algorithm comparison

A characteristic feature of urban construction is an increase in the density of buildings and, accordingly, the tightness of working conditions. The need to ensure the safety of existing buildings and reduce negative impacts on the urban environment requires the development of rational solutions at the stage of organizational and technological design during construction in conditions of dense development. The factors of constraint affect already at the stage of preparation of the construction site. The purpose of the study is to select and justify the methods of work during the removal of engineering networks from the construction site. The existing methods of network re-routing and technology comparison are considered. An example of a construction object shows a variant of an organizational and technological solution for the removal of networks using trenchless technologies.

Keywords: engineering training, construction site, dense buildings, cramped conditions, trenchless laying of networks

A method of power and kinematic analysis of the differential drive of vehicle wheels is proposed, in which uncertainty is eliminated by using the principle of minimum potential energy.

Keywords: external load modeling, differential drive, vehicle, driver, optimization problem

Nowadays, educational organisations face the need to effectively manage growing volumes of heterogeneous data from academic performance and digital educational resources to administrative processes. The article is dedicated to the study of modern approaches to building an Corporate data warehouse (DWH) using Data Lake technology to manage educational organisations. The article considers the integration of traditional methods of structured data storage with the flexibility and scalability of Data Lake, which allows to work effectively with large volumes of heterogeneous data. The description of DWH architecture adapted for educational institutions is given. The description of Apache Airflow platform is given.

Keywords: Data Lake, corporate data warehouse, Apache Airflow, Greenplum, ETL

The purpose of the article is a software implementation of a module for analyzing the activity of site users based on a heat map of clicks, compatible with domestic web services, for example, combining the functionality of correlation and regression analysis and visualization in the form of dashboards before and after making changes to site elements. All functionality is carried out directly in the web analytics service. Based on the data obtained on the analyzed site element, a decision is made to adjust the design and/or content to increase the click rate. Thus, the proposed solution allows us to expand the functionality of the web analytics service and reduce labor costs. The software module has been successfully tested. As a result of the analysis and making the necessary adjustments to the site, the click rate increased

Keywords: user activity, correlation and regression analysis, dashboard, program module, trend line, coefficient of determination

The article considers the possibility of modeling the random forest machine learning algorithm using the mathematical apparatus of Petri net theory. The proposed approach is based on the use of three types of Petri net extensions: classical, colored nets, and nested nets. For this purpose, the paper considers the general structure of decision trees and the rules for constructing models based on a bipartite directed graph with a subsequent transition to the random forest machine learning algorithm. The article provides examples of modeling this algorithm using Petri nets with the formation of a tree of reachable markings, which corresponds to the operation of both decision trees and a random forest.

Keywords: Petri net, decision tree, random forest, machine learning, Petri net theory, bipartite directed graph, intelligent systems, evolutionary algorithms, decision support systems, mathematical modeling, graph theory, simulation modeling

The article presents a system research of the factors of formation of architectural and typological models of a medium-rise dwelling. The research was conducted in two stages. At the first stage, the main internal and external factors of building architectural and typological models based on the study and processing of literary sources, analysis of modern domestic and foreign experience in designing medium-rise housing are collected and systematized. The structural elements of the factors are systematized according to well-established architectural concepts. At the second stage of the study, a matrix of dependencies between external and internal factors was formed, and the number of dependencies between internal and external factors was calculated. Based on the data obtained, the internal factors were grouped by the number of links with external factors. The obtained results of the system research provide the basis for further construction of a limited number of the most versatile and flexible architectural and typological models that take into account the greatest number of environmental conditions.

Keywords: architectural and typological models, urban planning conditions, cultural conditions, national and ethnographic conditions, natural and climatic conditions, socio-demographic conditions, medium-rise housing

This article analyzes the main causes of fatal injuries in the construction industry of the Russian Federation and a number of other foreign countries, including falls from heights, electric shock, injuries associated with the use of construction machinery and mechanisms, as well as exposure to harmful substances. In conclusion, the article highlights the importance of joint efforts by employers, employees and regulators to create a safer and healthier work environment in the construction industry. The implementation of the preventive measures described in the article can significantly reduce the risk of accidents and improve the well-being of employees.

Keywords: construction industry, industrial injuries, accidents, causes of injuries, working conditions, occupational risks, working at height, occupational safety, environmental factors, workplace organization, training