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

Monolithic reinforced concrete structures are widely used in construction practice. When concreting massive structures, technological and organizational difficulties may arise in ensuring the continuity of the concrete mix, which leads to the need to organize working joints. Studies conducted earlier show a decrease in strength characteristics in this area and the bearing capacity of the entire structure. Known and practical solutions to the problem cause additional labor, material and time costs. In this paper, we propose a method for installing a technological seam caused by unplanned interruptions in concreting for technological and organizational reasons, based on previously conducted experimental and pilot studies by the author of this article. The proposed method consists in the fact that, when a break occurs, subsequent concreting is carried out with a break from the previously concreted section, while a stepped profile is formed with the help of fasteners, as a result of which a space is organized bounded by the surface of the first and second concreted sections and a formwork of a shape close to pyramidal, similar to the run-in fines, during the construction of brickwork. After holding the concrete of both sections and dismantling the cut-offs, a concrete mixture of the same class on Portland cement is laid within the free space of the applied slag-alkali solution with the characteristics: slag with a basicity modulus of more than 1.0; an alkaline solution with a hydrogen index level above 12.0. The technological features of performing forced seam concreting according to the proposed method are given.

Keywords: concrete contact zone, technological concreting joint, unplanned concreting working joint, monolithic reinforced concrete structures

The reuse of ash and slag waste from coal combustion is of great economic and environmental importance. The most material-intensive area of their reuse is the stabilization of ash and slag mixtures with Portland cement for the construction of layers of highways. A technical understanding of the processes of structure formation in stabilized ash and slag mixtures makes it possible to regulate the final properties and quality of the layers of road clothing and the roadbed. Strengthening of ash and slag mixtures with Portland cement makes it possible to increase the physical and mechanical properties of ash and slag mixtures: strength, frost resistance, density, etc.

Keywords: ash and slag mixtures, stabilized ash and slag mixtures, structure formation of stabilized ash and slag mixtures, sportland cement, microstructure of the ash and slag mixture

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

The ecology of modern megacities is one of the most relevant and acute topics of our time. Rapid growth of cities, increase in the urban population and development of industry have led to significant changes in the environment. This article examines the main environmental problems of modern megacities, factors affecting the ecology of urban areas. An analysis of the influence of solar radiation on the formation of the microclimate and ecology of the air basin of cities is carried out. The conditions for the occurrence of air flows of thermal origin, which contribute to the improvement of the aeration regime of urban areas, are studied.

Keywords: ecology, urban area, air exchange, convective flows, insolation, aeration regime, dense development, solar radiation, air basin, microclimate, heat island

The analysis of the environmental impact of the largest enterprises located in the Southern and Northern industrial zones of the linear city of Volgograd has been carried out, and the need to change approaches to designing a comfortable urban environment, which currently take into account the average data for characterizing the ecological state of a particular territory, has been shown. The analysis confirmed the need to take into account the local impact of industrial enterprises on the components of the urban environment when justifying the selection and planning of appropriate modern spaces within the framework of the Federal Project "Creating a comfortable Urban environment".

Keywords: urban environment, comfort, urban environment quality index, modern spaces, environmental analysis, environmental friendliness, environmental safety

The article analyzes the design features in the conditions of the Far North. Attention is focused on the need to take into account climatic, geographical and socio-economic factors, as well as the use of innovative approaches to ensure economic development. The authors propose compensatory measures aimed at mitigating the negative conditions of the region, contributing to the successful implementation of projects in the Far North, as well as ensuring safety and reducing the duration of construction projects. The study of the most significant compensatory measures and their effective application is conducted.

Keywords: design, Far North, Arctic, regional features, unique factors, climatic conditions, geographical conditions, innovative approaches, development, compensatory measures

The transition from scheduled maintenance and repair of equipment to maintenance based on its actual technical state requires the use of new methods of data analysis based on machine learning. Modern data collection systems such as robotic unmanned complexes allow generating large volumes of graphic data in various spectra. The increase in data volume leads to the task of automating their processing and analysis to identify defects in high-voltage equipment. This article analyzes the features of using computer vision algorithms for images of high-voltage equipment of power plants and substations in the infrared spectrum and presents a method for their analysis, which can be used to create intelligent decision support systems in the field of technical diagnostics of equipment. The proposed method uses both deterministic algorithms and machine learning. Classical computer vision algorithms are applied for preliminary data processing in order to highlight significant features, and models based on unsupervised machine learning are applied to recognize graphic images of equipment in a feature space optimized for information space. Image segmentation using a spatial clustering algorithm based on the density distribution of values ​​taking into account outliers allows detecting and grouping image fragments with statistically close distributions of line orientations. Such fragments characterize certain structural elements of the equipment. The article describes an algorithm that implements the proposed method using the example of solving the problem of detecting defects in current transformers, and presents a visualization of its intermediate steps.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production

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

in modern dynamically developing cities, renovation processes are often accompanied by new construction in already built-up areas. In recent years, in Yekaterinburg, the loss of urban facilities that were well known to citizens has caused more and more resonance and attracted the attention of public organizations that oppose demolition. This article attempts to analyze the changes that have occurred in four Ural cities in terms of the loss of architectural objects, compare the reaction of citizens to these losses and determine the most significant losses for cities.

Keywords: demolition, historical heritage, preservation, loss, cities, renewal, urban environment, public organizations, citizens, significance, value

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

Two capacitive methods of measuring the linear density of one-dimensional fibrous products are considered. The sensitivity of the measurement results to variations in the geometric and physical parameters of the measuring device for the differential and resonance measurement methods is estimated. A weak, almost linear dependence of the measurement error on parameter variations in a wide variation range is established. The good suitability of both methods for measuring the linear density of one-dimensional products by the capacitive method and the high correlation between the measured value and the measurement results are substantiated.

Keywords: fibrous materials, one-dimensional products, linear density, capacitive measurement method, capacitive method, differential circuit, resonant measurement circuit, parameter variations

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

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 presented article reveals the issue of using waste from the automotive industry of rubber products as one of the possible ways to improve the quality of asphalt pavement and, accordingly, reduce the number of repair activities and material costs for their implementation and increase the service life of the roadway. The tests carried out show that the asphalt-concrete mixture using a modifier based on active rubber powder demonstrates the best mechanical and operational characteristics. The strength and elasticity of asphalt concrete increases, as well as the abrasion resistance decreases, which leads to a longer use time of this web. Such changes in the characteristics of the roadway have a positive effect on the economic side of the issue. Improving the quality of the finished product increases the time intervals between repair actions, which reduces material and resource costs. The adhesion of the road to the rubber of cars is improved.

Keywords: asphalt concrete, asphalt mix, automobile waste, rubber crumb, modifier, active rubber powder