This study presents a method for recognizing and classifying micro-expressions using optical flow analysis and the YOLOv11 architecture. Unlike previous binary detection approaches, this research enables multi-class classification while considering gender differences, as facial expressions may vary between males and females. A novel optical flow algorithm and a discretization technique improve classification stability, while the Micro ROC-AUC metric addresses class imbalance. Experimental results show that the proposed method achieves competitive accuracy, with gender-specific models further enhancing performance. Future work will explore ethnic variations and advanced learning strategies for improved recognition.

Keywords: microexpressions, pattern recognition, optical flow, YOLOv11

This article discusses the basic concepts and practical aspects of programming using the actor model on the Akka platform. The actor model is a powerful tool for creating parallel and distributed systems, providing high performance, fault tolerance and scalability. The article describes in detail the basic principles of how actors work, their lifecycle, and messaging mechanisms, as well as provides examples of typical patterns such as Master/Worker and Proxy. Special attention is paid to clustering and remote interaction of actors, which makes the article useful for developers working on distributed systems.

Keywords: actor model, akka, parallel programming, distributed systems, messaging, clustering, fault tolerance, actor lifecycle, programming patterns, master worker, proxy actor, synchronization, asynchrony, scalability, error handling

Mathematical modeling, numerical methods and program complexes (technical sciences). Geopolitical situation analysis of a number of episodes of the American Revolution in the context of applying structural balance and mathematical modeling methods. Structural balance management can help to find the most optimal strategies for interacting parties. This approach is used in a set of disciplines. In this article, the author analyzes examples of actors' interaction in the context of the American Revolution, which allows us to evaluate the state of affairs at this historical stage in an illustrative form. This approach is universal and is able to emphasize the management of structural balance in systems with actors, each of which has its own features and interests. A number of specific historical episodes serves as an example of the balanced and unbalanced systems. Each episode has its explanation in the frame of history. During the American Revolution, actors (countries and specific politicians, as well as indigenous peoples) had their own goals and interests, and their positive or negative interactions shaped the course of history in many ways.

Keywords: mathematical modeling, structural balance, discrete models, sign graph, U.S. history

Drilling of hardened steel 40 HRC 24...32 is investigated using numerical simulation in Abaqus/Explicit. The stress-strain state is analyzed. It has been found that optimization of cutting modes (feed speeds and revolutions) reduces Mises stresses to 55% of the ultimate strength, increasing tool durability. The results show the dependence of stress distribution on cutting parameters and the influence of drill geometry on the machining process.

Keywords: drilling, hardened steel, numerical modeling, finite element method, Mises stresses, tool durability, optimization of cutting modes, drill geometry

The article is devoted to the development of a tool for automated generation of time constraints in the context of circuit development in the basis of programmable logic integrated circuits (FPGAs). The paper analyzes current solutions in the field of interface tools for generating design constraints. The data structure for the means of generating design constraints and algorithms for reading and writing Synopsys Design Constraints format files have been developed. Based on the developed structures and algorithms, a software module was implemented, which was subsequently implemented into the circuit design flow in the FPGA basis - X-CAD.

Keywords: computer-aided design, field programmable gate array, automation, design constraints, development, design route, interface, algorithm, tool, static timing analysis

The article presents an analysis of the application of the Socratic method for selecting machine learning models in corporate information systems. The study aims to explore the potential of utilizing the modular architecture of Socratic Models for integrating pretrained models without the need for additional training. The methodology relies on linguistic interactions between modules, enabling the combination of data from various domains, including text, images, and audio, to address multimodal tasks. The results demonstrate that the proposed approach holds significant potential for optimizing model selection, accelerating decision-making processes, and reducing the costs associated with implementing artificial intelligence in corporate environments.

Keywords: Socratic method, machine learning, corporate information systems, multimodal data, linguistic interaction, business process optimization, artificial intelligence

The article examines the modular structure of interactions between various models based on the Socratic dialogue. The research aims to explore the possibilities of synthesizing neural networks and system analysis using Socratic methods for managing corporate IT projects. The application of these methods enables the integration of knowledge stored in pre – trained models without additional training, facilitating the resolution of complex management tasks. The research methodology is based on analyzing the capabilities of multimodal models, their integration through linguistic interactions, and system analysis of key aspects of IT project management. The results include the development of a structured framework for selecting suitable models and generating recommendations, thereby improving the efficiency of project management in corporate environments. The scientific significance of the study lies in the integration of modern artificial intelligence approaches to implement system analysis using multi – agent solutions.

Keywords: neural networks, system analysis, Socratic method, corporate IT projects, multimodal models, project management

The article discusses the problem of heating the wall in connection with the occurrence of a fire source. The conditions of convective heat exchange with the environment are considered on the wall surface. At a known ignition temperature of wood, the time it takes for the wall surface to reach this temperature is found. The problem is solved for a homogeneous wall made of a single material, as well as for an inhomogeneous wall in which a thin layer of wood is followed by a thick thermal insulation layer. The problem is solved analytically, as well as by the finite element method. The solution of the problem by the finite difference method is also considered.

Keywords: wood, thermal insulation layer, ignition temperature, convection, finite element method, finite difference method, thermal conductivity problem

This article investigates the application of a digital operational model to enhance the efficiency of maintenance and repair processes for capital construction projects. The study focuses on the operational phase within the building lifecycle, analyzing maintenance procedures and categorizing structural defects. The research identifies limitations in traditional defect reports, which lack quantitative data and spatial referencing to the building structure. These limitations hinder their effectiveness in organizational and technical planning for repair works. The proposed digital model optimizes building condition management, improves the accuracy of technical assessments, and facilitates precise quantification of repair scopes. It also enhances collaboration between facility management and contracting entities. A case study of the educational and laboratory building at the Northern (Arctic) Federal University demonstrates the model's implementation. Key benefits include cost reduction, improved maintenance quality, and streamlined operational workflows. The findings highlight the potential of digital tools to transform building maintenance practices, offering a data-driven approach to facility management in the construction sector.

Keywords: maintenance and repair, operational digital model, defect, defect list, technical condition

The construction of a mathematical model for solving the problem of planning construction excavation, which is interpreted as a problem with a linear objective function and constraints, is considered. The calculation algorithm is implemented by software in Python using the scipy.optimize.linprog library, which provides effective methods for solving linear programming problems. The developed program visualizes the results, making the allocation of time for the operation of machines. When testing the program, scenarios with different input data were considered, allowing us to conclude that the developed tool helps to make the best decision when planning construction work and analyze the impact of changes in input parameters on the result.

Keywords: organization of construction, linear programming, distribution tasks, optimization, planning, mathematical modeling, simplex method

The paper considers simulation models of the adaptive tire pressure control system, the calculation of the rollover coefficient and the magnitude of the lateral deflection of tractor wheels in the MathLab Simulink environment; it is revealed that compensation of the angle of lateral slope by changing the suspension height has a more effective effect on ensuring a rational wheel deflection angle and the rollover coefficient than reducing the center of mass.

Keywords: surface with a transverse slope, roll angle, rollover coefficient, wheel deflection angle, steeply inclined tractor

The paper presents a calculation model for assessing the wear resistance of radial plain bearings with a polymer coating and a groove, taking into account inertial effects and nonlinear properties of the medium under steady-state friction. Clarified analytical dependencies have been developed to improve the accuracy of calculations of the hydrodynamic characteristics of the bearing. The main objective of the study is to create a multifactorial model that takes into account the influence of the bearing geometric parameters (the presence and configuration of the groove), the properties of the polymer coating and the inertial force. The model allows predicting the bearing life in real operating conditions, taking into account the influence of various factors, which increases the accuracy of design and optimization of the design. The results of the work are aimed at improving the operational reliability of plain bearings due to more accurate prediction of their wear resistance and optimization of design parameters.

Keywords: modified design, nonlinear factors, polymer coating, axial groove, load capacity, friction coefficient, increased wear resistance

This article examines the support structures of a wind turbine designed for operation in the extreme climatic conditions of the Russian High North. The relevance of the study is driven by the strategic objectives of developing the Arctic zone of Russia and the necessity to account for specific environmental and climatic factors in the design of energy infrastructure. A modular structural system is proposed, taking into consideration transportation and technological constraints associated with Arctic wind turbines. A CAD-model of the structural system has been developed, comprising a three-section tubular conical tower and a compound pile cap with a three-point support configuration. CAE-based simulations were conducted to evaluate the load-bearing capacity of the structural system under extreme load combination. The results demonstrate that the proposed structural configuration meets transportation limitations while ensuring the strength and stability of the Arctic wind turbine under critical load combination. The proposed design solution is suitable for simplifying transportation and on-site assembly of Arctic wind turbine in remote northern energy infrastructure projects.

Keywords: Arctic wind turbine, modular structures, supporting structures, CAD modeling, CAE simulation, permafrost

The article presents the results of a numerical experiment comparing the accuracy of neural network recognition of objects in images using various types of data set extensions. It describes the need to expand data sets using adaptive approaches in order to minimize the use of image transformations that may reduce the accuracy of object recognition. The author considers such approaches to data set expansion as random and automatic augmentation, as they are common, as well as the developed method of adaptive data set expansion using a reinforcement learning algorithm. The algorithms of operation of each of the approaches, their advantages and disadvantages of the methods are given. The work and main parameters of the developed method of expanding the dataset using the Deep-Q-Network algorithm are described from the point of view of the algorithm and the main module of the software package. Attention is being paid to one of the machine learning approaches, namely reinforcement learning. The application of a neural network for approximating the Q-function and updating it in the learning process, which is based on the developed method, is described. The experimental results show the advantage of using data set expansion using a reinforcement learning algorithm using the example of the Squeezenet v1.1 classification model. The comparison of recognition accuracy using data set expansion methods was carried out using the same parameters of a neural network classifier with and without the use of pre-trained weights. Thus, the increase in accuracy in comparison with other methods varies from 2.91% to 6.635%.

Keywords: dataset, extension, neural network models, classification, image transformation, data replacement

Modern intelligent control systems (ICS) are complex software and hardware systems that use artificial intelligence, machine learning, and big data processing to automate decision-making processes. The article discusses the main tools and technologies used in the development of ICS, such as neural networks, deep learning algorithms, expert systems and decision support systems. Special attention is paid to the role of cloud computing, the Internet of Things and cyber-physical systems in improving the efficiency of intelligent control systems. The prospects for the development of this field are analyzed, as well as challenges related to data security and interpretability of models. Examples of the successful implementation of ICS in industry, medicine and urban management are given.

Keywords: intelligent control systems, artificial intelligence, machine learning, neural networks, big data, Internet of things, cyber-physical systems, deep learning, expert systems, automation

The technology of applying the variational principle in problems of development and testing of complex technical systems is described. Let there be a certain set of restrictions imposed on random variables in the form of given statistical moments and/or in the form of a restriction by some estimates from above and below the range of possible values of these random variables. The task is set: without knowing anything except these restrictions, to construct for further research, ultimately, for assessing the efficiency of the complex technical system being developed, the probability distribution function of its determining parameter. By varying the functional, including Shannon entropy and typical restrictions on the distribution density function of the determining parameter of a complex technical system, the main stages of constructing the distribution density function are described. It is shown that, depending on the type of restriction, the constructed distribution density function can have an analytical form, be expressed through special mathematical functions, or be calculated numerically. Examples of applying the variational principle to find the distribution density function are given. It is demonstrated that the variational principle allows obtaining both the distribution laws widely used in probability theory and mathematical statistics, and specific distributions characteristic of the problems of developing and testing complex technical systems. The technology of applying the variational principle presented in the article can be used in the model of managing the self-diagnostics process of intelligent control systems with machine consciousness.

Keywords: variational principle, distribution density function, Shannon entropy, complex technical system

The paper considers the problem of the stress state of a rock array with continuous inhomogeneity. This type of inhomogeneity can be observed in rock arrays with cavities created by explosion. In this case, the dependence was chosen when the main mechanical characteristics depend only on one coordinate - the radius. It was also taken into account that the chosen dependence gives an opportunity to obtain relatively simple methods of solving the problems. The chosen calculation scheme of the problem allows to reduce it to the solution of one-dimensional task. For the case of the centrally symmetric problem we consider the solving equation, which is an ordinary inhomogeneous differential equation of the second order with variable coefficients. Using the substitution of variables, we can proceed to the solution of the hypergeometric equation. Solutions of hypergeometric equations are given in the form of hypergeometric series, which are known to converge. Using inverse substitutions, the stresses are found. The stress state of the rock array at different degrees of its heterogeneity is determined. The results are presented in the form of graphs. Comparison with similar solutions for homogeneous arrays is carried out. The presented results allow us to conclude that when solving problems on the stress state of rock arrays with cavities, it is necessary to take into account the heterogeneity of the arrays obtained in the process of creating such cavities with the help of explosion.

Keywords: heterogeneity of the medium, rock array, spherical cavity, stress state

The article explores the actor model as implemented in the Elixir programming language, which builds upon the principles of the Erlang language. The actor model is an approach to parallel programming where independent entities, called actors, communicate with each other through asynchronous messages. The article details the main concepts of Elixir, such as comparison with a sample, data immutability, types and collections, and mechanisms for working with the actors. Special attention is paid to the practical aspects of creating and managing actors, their interaction and maintenance. This article will be valuable for researchers and developers interested in parallel programming and functional programming languages.

Keywords: actor model, elixir, parallel programming, pattern matching, data immutability, processes, messages, mailbox, state, recursion, asynchrony, distributed systems, functional programming, fault tolerance, scalability

Increasing the accuracy of steady-state calculation is possible by taking into account the thermal processes occurring in electrical energy conductors. The wind flow velocity, in turn, is of significant importance in determining the conductor temperature. In this paper, the values of wind speed for an 11-year period are considered. The time series is analyzed and the prediction models of the target variable are tested and the prediction results are compared.

Keywords: power grid mode calculation, thermal processes, wind flow velocity, prediction models, feed forward neural network, ensemble methods

The paper considers the plane motion of a heavy material point in a quasi-static medium under the influence of gravity, aerodynamic forces and thrust forces. This problem can be considered as a continuation of Zhukovsky's problem of modeling the longitudinal flight of an aircraft, assuming that the angle of attack is constant, taking into account the effect of thrust. The equations of motion in different coordinate systems are obtained. Stationary flight modes have been found. The stability of the most basic modes is investigated. A numerical solution of the equations of motion is found and the behavior of trajectories in various flight modes is investigated.

Keywords: thrust force, material point, Zhukovsky's problem

In this work, we present the development and analysis of a feature model for dynamic handwritten signature recognition to improve its effectiveness. The feature model is based on the extraction of both global features (signature length, average angle between signature vectors, range of dynamic characteristics, proportionality coefficient, average input speed) and local features (pen coordinates, pressure, azimuth, and tilt angle). We utilized the method of potentials to generate a signature template that accounts for variations in writing style. Experimental evaluation was conducted using the MCYT_Signature_100 signature database, which contains 2500 genuine and 2500 forged samples. We determined optimal compactness values for each feature, enabling us to accommodate signature writing variability and enhance recognition accuracy. The obtained results confirm the effectiveness of the proposed feature model and its potential for biometric authentication systems, presenting practical interest for information security specialists.

Keywords: dynamic handwritten signature, signature recognition, biometric authentication, feature model, potential method, MCYT_Signature_100, FRR, FAR

The paper considers the issue of using a computer vision system to control the quality of products in the control algorithm of a mechatronic sorting station. Shoe products are chosen as an example. The developed system is based on machine learning methods for image recognition by segmentation. As a result, a neural network model was created, and a program was written for identifying and selecting objects using a camera for subsequent sorting of defective products. The program contains three modules: initialization for declaring all variables, models, classes, video stream from the camera; the main module, containing an internal loop for each segmented object; a subroutine for completing the work. The introduction of computer vision into the control algorithm increases the efficiency and flexibility of the quality control system, and improves the accuracy of measuring the parameters of objects for their subsequent sorting.

Keywords: mechatronic station, sorting, computer vision, image segmentation, neural network training, control algorithm

The article examines how the replacement of the original data with transformed data affects the quality of training of deep neural network models. The author conducts four experiments to assess the impact of data substitution in tasks with small datasets. The first experiment consists in training the model without making changes to the original data set, the second is to replace all images in the original set with transformed ones, the third is to reduce the number of original images and expand the original data set using transformations applied to images, and also in the fourth experiment, the data set is expanded in order to balance the number of images There are more in each class.

Keywords: dataset, extension, neural network models, classification, image transformation, data replacement

The article is devoted to the consideration of the features of using game theory to model review manipulation on marketplaces. In the course of the study, a model was proposed that is based on evolutionary theory and allows us to determine how susceptible buyers and marketplaces are to review manipulation, and what benefits all participants in these relationships receive. Special attention is paid to the audit that is conducted by the marketplace in relation to the processes of review manipulation by the seller, and the losses that the parties incur if it is detected.

Keywords: marketplace, reviews, buyer, seller, benefit

This paper presents the results of an investigation into the adhesion properties of release coatings based on polyisobutylene applied to metallic substrates. A software tool was developed in Microsoft Visual Studio using the C++ programming language to compute the composition and effective technological parameters for forming coatings that ensure optimal adhesion to protected surfaces. As a case study, the method of calculating the relationships between composition, temperature, and formation time is demonstrated for coatings achieving the highest adhesion, corresponding to a score of “zero” on the standardized six-point cross-cut adhesion test. It is shown that the application of the developed software enables parameter evaluation within 1–2 seconds. The computational results are experimentally validated. The morphology of the coatings was examined using optical microscopy. It was observed that no delamination occurs at the intersection points of cuts or within the grid pattern.

Keywords: coating, adhesion, microstructure, cross-cut test, polyisobutylene, optimization