The article provides a review and systematisation of works devoted to the application of machine learning for solving problems of research, calculation and design of reinforced concrete structures. It considers the aspects, which are relevant today, related to calculation, design, as well as assessment of the technical condition of objects with the help of various approaches that implement machine learning schemes, including deep learning, ensemble algorithms. It is shown that nowadays in the world construction science this area is rapidly developing and improving. Thus machine learning algorithms solve problems of prediction of design parameters, problems of identification of these or those parameters, defects, damages on the basis of classification algorithms and others. The materials presented in the article will allow specialists to choose the subject area of research more precisely and determine the directions of adaptation and improvement of their own developments in the field of machine learning.

Keywords: machine learning, reinforced concrete structures, regression equations, identification, approximation, artificial intelligence

The purpose of this work is to analyze the concept of the threat of ransomware, methods of their detection, as well as to consider methods of intelligent analysis in solving the problem of detection, which are a popular tool among researchers of ransomware and malicious software (malware) in general. Data mining helps to improve the accuracy and speed up the malware detection process by processing large amounts of information. Specialists can identify new, previously unknown malware. And with the help of generative adversarial networks, zero-day malware can be detected. Despite the fact that a direct and objective comparison of all the studies presented in the work is impossible, due to different data sets, it can be assumed that using the architecture of generative-adversarial networks is the most promising way to solve the problem of detection.

Keywords: malware, ransomware, intelligent analysis, machine learning, neural network, generative adversarial network

The article examines the stages of the formation of medical education in Russia, which influenced the architectural formation of medical universities in the south, namely in Rostov-on-Don, Astrakhan, Krasnodar, Volgograd and Stavropol. The stages are considered from the beginning of the 20th century to the present. The gradual development of the organizational structure and architecture of universities has been studied. The current problems in the field of organization and architecture that are required for further modernization are identified.

Keywords: medical universities, universities of the South of Russia, university architecture, regional architecture, stages of architectural development of medical universities

the article considers the development trends of the high-tech industry of quantum communications. The most popular topologies of quantum communication networks are described, including those with trusted intermediate nodes. The methods of interaction between nodes of the backbone quantum-cryptographic network are given and the main methods of ensuring secure transmission in such networks are presented. A simplified scheme for distributing a quantum secret key between the end segments of the backbone telecommunication network using trusted intermediate nodes is considered. Possible data leakage channels in the general structure of quantum-cryptographic networks are described.

Keywords: quantum communications, quantum key, network topologies, trusted nodes

Additive technologies, or 3D printing, open up new possibilities for architectural design, allowing you to create complex and unique shapes that were previously impossible using traditional methods. These technologies expand the boundaries of architectural creativity, contributing to the emergence of new organic and non-standard geometric solutions. The article examines examples of successful applications of additive technologies in architecture, such as the SOM polymer pavilion and the MARSHA Martian housing project, emphasizing their potential in creating aesthetically attractive and functionally effective structures.

Keywords: Additive technologies, 3D printing, architectural design, complex shapes, organic structures, complex geometry, MARSHA, NASA, functional efficiency, ultralight structures, aesthetics, innovation in architecture, architectural creativity, futuristic design

The article considers the causes of the formation of defects to be evaluated. The methods of obtaining information about the condition of metal corrugated pipes are presented. The main defects arising during the operation of metal corrugated pipes are shown. The most effective methods of assessing the condition of metal corrugated pipes have been determined.

Keywords: corrugated metal pipes, wear, durability, defects, factors, evaluation

An integrated information security system combining dynamism and efficiency is proposed, and a quantitative assessment of this system is presented. The study is aimed at identifying all potential switching routes of maximum length between unique states, taking into account potential difficulties that may arise when implementing a recomposition information security system. The main tool for analyzing and modeling various transition configurations in the system under study is the apparatus of graph theory. Within the framework of the proposed approach, each subsystem includes several independent options or components, and at any given time only one of these options functions. An important aspect is both the interaction between the subsystems and the ability to switch components within one subsystem. For a visual understanding of the proposed approach, an example is given that illustrates the basic principles and mechanisms of the developed system.

Keywords: information security system, state graph, DLP system, IPS/IDS system

The article is devoted to describing approaches to analyzing the information space using low-code platforms in order to identify factors that form new identities of Azerbaijan and the unique features of the country’s information landscape. The article describes the steps to identify key themes and collect big data in the form of text corpora from various Internet sources and analyze the data. In terms of data analysis, the study of the sentiment of the text and the identification of opinion leaders is carried out; the article also includes monitoring of key topics, visualized for a visual presentation of the results.

Keywords: data analytics, trend monitoring, sentiment analysis, data visualization, low-code, Kribrum, Polyanalyst, big data

The problem of optimisation of selective assembly of plunger-housing precision joints of feeders of centralised lubrication systems used in mechanical engineering, metallurgy, mining, etc. is considered. The probability of formation of assembly sets of all types is used as the target function; the controlled variables are the number and volumes of parts of batches and their adjustment centres, as well as the values of group tolerances. Several variants of solving the problem at different combinations of controlled variables are considered. An example of the solution of the optimisation problem on the basis of the previously developed mathematical models with the given initial data and constraints is given, the advantages and disadvantages of each of the variants are outlined. Optimisation allows to increase the considered indicator by the value from 5% to 20%.

Keywords: selective assembly, lubrication feeder, precision connection, mathematical model, optimisation

Automating government processes is a top priority in the digital era. Because of historical development, many existing systems for registering and storing data about individuals coexist, requiring intervening IT infrastructures. The article considers the procedure for the development, creation and implementation of software for updating and generating data about residents of the city of Astana. It defines the functional capabilities and determines the role of the information system in automation and monitoring government activities. The authors conducted the study by observing, synthesizing, analyzing, systematizing, and classifying the data received. The authors used scientific works of local and foreign authors on the topic under study and open databases as sources of literature. At the end of the work, the authors list the literature used. The authors have, for the first time, created the structure and algorithms of the information system known as ""Population Database ""Geonomics"". Specifically, they have developed the mechanism and algorithm for the interaction of the ""Geonomics"" information system with government databases. As well as, additional opportunities for using the software have been identified by developing an algorithm for planning and placing social objects when using the information system ""Geonomics"". The authors have concluded that the algorithms developed for the use of the information system ""Population Database “Geonomics"" represent a reliable and powerful tool, which plays a critical role in the optimization and automation of processes related to population accounting and urban infrastructure management. This software contributes to the development of the city and the improvement of its residents' quality of life, based on up-to-date and reliable information. In addition, the developed algorithm allows for real-time monitoring of the current data of city residents and their density, based on which decisions can be made regarding the construction and placement of social facilities for the comfortable service and living of city residents.

Keywords: automation, updating, government activities, government agency, information system, database

The article examines the man-made risks in the Arctic zone of the Russian Federation, methods of working with data related to the use of intellectual analysis, and the use of information systems for forecasting risks and is designed for the widest range of readers. The conducted research demonstrates that the use of data mining methods opens up broad prospects for data integration. This process includes the adaptation of the system to specific emergency situations typical of the Arctic zone of the Russian Federation, as well as the development of appropriate interfaces for interaction with external subsystems. As a result of the conducted research, the conclusions were obtained: 1. Intelligent methods allow you to analyze large amounts of data and identify hidden patterns, which helps you make more informed decisions. The quality of decisions is improved. 2. Intelligent data processing allows you to automate routine tasks and optimize business processes. This leads to increased productivity and lower costs. The efficiency of business processes increases. 3. Intelligent systems can analyze data about past events and predict future trends. This allows you to take measures to reduce risks and ensure safety. These processes make it possible to reduce risks. 4. Intelligent algorithms can process data in real time, which allows you to quickly respond to changes in the external environment. 5. In the future, it is planned to work out the issue of introducing intelligent data analysis algorithms into man-made emergency forecasting analytics systems and the development of the data science concept, such as the GIS Atlas of Natural Hazards and Risks.

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

Currently, one of the most extensive issues in the field of information security is the organization of user access control to information infrastructure objects. Taking into account the volume of corporate information resources, as well as the number of users requesting access, there is a need to automate the access approval process taking into account possible risks. In this case, the most optimal solution to this problem is the use of fuzzy logic. The article analyzes the process of providing access to the information infrastructure using a fuzzy classifier and develops a conceptual model of the fuzzy classifier algorithm for incoming requests for access in order to automate the process and minimize information security risks associated with possible destructive actions aimed at the confidentiality, integrity and availability of the information infrastructure.

Keywords: neural network, machine learning, information security, cybersecurity, properties and structure of a neural network, mathematical model, threats and information vulnerabilities

Nowadays, the Internet has become an integral part of our lives, providing access to a huge amount of information and services. However, along with this, the number of destructive Internet resources that can harm users, especially children and adolescents, is growing. In this regard, there is a need to create an effective system for regulating access to such resources. The article presents an expert system for regulating access to destructive Internet resources, developed on the basis of modern technologies and methods of artificial intelligence. The system allows to automatically detect and block access to resources containing malicious content, as well as provides an opportunity for manual configuration and access control. The article describes the main components of the system and presents images demonstrating the work of the system for blocking access to destructive resources. The article will be useful for specialists in the field of information security, artificial intelligence and protection of children from malicious content on the Internet.

Keywords: destructive content, expert system, information security, Internet resources, SpaCy, Keras, RNN, LSTM, PyQt5, vectorization

A complex dynamic system is defined by a structurally invariant operator. The operator structure allows formulating problems of stabilizing program motions or equilibrium positions of a complex dynamic system with constraints on state coordinates and control. The solution of these problems allows synthesizing a structurally invariant operator of a complex dynamic system with inequality-constraints on the vector of locally admissible controls and state coordinates. Computational experiments confirming the correctness of the synthesized structurally invariant projection operator are performed.

Keywords: structurally-invariant operator, stabilization of program motions, complex nonlinear dynamic system, projection operator, SimInTech

The article presents an analysis of the Modbus protocol, including its architecture, message types, implementation features and its own programming language. A production process control system based on Modbus is considered.

Keywords: Modbus, programmable logic controller, communication protocol, programming, industrial automation, process control, monitoring, registers, system integration

The article considers the method for parametric identification of a model of steady-state modes of a technological process. The method essence is to use artificial neural networks. The input of each neural network is measured values of input and output process variables, and the output is a corresponding parameter value of the technological process model. The effectiveness of the method was assessed by conducting computational experiments on regression models with two factors and models of steady-state modes of technological processes in existing industries. The average relative error of the models does not exceed 0,43%. The method for parametric identification is applicable in adaptive control of steady-state modes of the technological process. One of advantages of the method is that with a specified form of mathematical description, training a neural network does not require statistical experimental values of process variables.

Keywords: the method for parametric identification, an artificial neural network, the model of steady-state modes of the technological process, adaptive control

The article solves the problem of automated generation of user roles using machine learning methods. To solve the problem, cluster data analysis methods implemented in Python in the Google Colab development environment are used. Based on the results obtained, a method for generating user roles was developed and tested, which allows reducing the time for generating a role-based access control model.

Keywords: machine learning, role-based access control model, clustering, k-means method, hierarchical clustering, DBSCAN method

The article discusses various methods for solving the problem of lack of inputs and outputs of programmable logic controllers during construction of automated control systems. The control signals that the controller operates can be divided into two categories: the first one is responsible for direct control of the equipment system and the second one organizes the human-machine interface (HMI). The methods described in the article allow to significantly reduce the load of HMI on controller or delegate them to the operator's touch panel completely. An example of interaction between the controller and the operator panel via the MODBUS protocol is given. The pros and cons of the described methods, as well as the conditions under which they are preferable, are listed.

Keywords: programmable logic controller, programmable relay, operator touch panel, human-machine interface, control signal

The work analyzes existing approaches to forecasting contract execution, including traditional statistical models and modern methods based on machine learning. A comparative analysis of various machine learning algorithms, such as logistic regression, decision trees, random forest and neural networks, was carried out to identify the most effective forecasting models.An extensive database of information on government contracts was used as initial data, including information about contractors, contract terms, deadlines and other significant factors. A prototype of an intelligent forecasting system was developed, testing was carried out on real data, as well as an assessment of the accuracy and reliability of the resulting forecasts. The results of the study show that the use of machine learning methods can significantly improve the quality of forecasting the execution of government contracts compared to traditional approaches

Keywords: intelligent system, mathematical modeling, government procurement, government contracts, software package, forecasting, machine learning

In this article, we consider the system of quality management of legislation in the Russian Federation: we define its basic elements, the main tools for quality control (management) in the form of legal examinations, provide a generalized algorithm for quality assessment, propose a simple general classification of controlled factors in legal examinations, and introduce the concept of a bill readiness indicator. The most important legal examination - anti-corruption (ALE) - was chosen as an example for conducting quality control of legislation. Within the framework of general trends in automation, informatization, and digitalization, we considered the use of artificial intelligence (AI) for the purposes of conducting ALE, which, in some cases of "routine work", could provide all possible assistance to specialists in the field of legal examinations and their digitalization. In this regard, a step-by-step algorithm for pre-training AI was formulated using examples from regulatory legal acts (RLA) containing corruption factors (CF); a classification of CF was carried out; a scale of AI errors in detecting CF was developed; frequency characteristics of AI errors were determined; Preliminary conclusions were obtained on the possibility of using AI in AEC.

Keywords: artificial intelligence, corruption factor, anti-corruption expertise, normative legal act, corruption factor indicator, pre-training, algorithm, errors, frequency distribution, classification, dialogue.

Blurred frames pose a significant problem in various fields such as video surveillance, medical imaging and aerial photography, when solving the following object detection and identification, image-based disease diagnosis, as well as analyzing and processing data from drones to create maps and conduct monitoring. This article proposes a method for detecting blurred frames using a neural network model. The principle of operation of the model is to analyze images presented in the frequency domain in the Hough space. To further evaluate the effectiveness of the proposed author's solution, a comparison was made of existing methods and algorithms that can be used to solve the problem, namely the Laplacian method and the manual sampling method. The results obtained show that the proposed method has high accuracy in detecting blurred frames and can be used in systems where high accuracy and clarity of visual data are required for decision-making.

Keywords: blurred frames, motion blur, blur, Hough transform, spectral analysis

Providing the population with comfortable housing has always been a pressing issue. However, there are very few formalized criteria for this, apart from the regulation of minimum floor areas. In this context, the article deals with the problem of evaluating the efficiency of residential space design solutions in terms of their logistical comfort. For this purpose, a method is proposed that uses the apparatus of graph theory and allows to calculate the time cost of an "idle" move for a representative of a given social group in relation to the evaluated design solution. An idle move is a user's movement between characteristic functional zones of the layout. A special matrix is used to model the links between these zones, the construction of which is similar to that of the incident matrix in undirected graphs. As an example of the applicability of the proposed approach, several variants of layouts of one-room, two-room and three-room flats are considered. The comparison of the obtained results for different types of layouts, including those that existed 15-20 years ago and modern ones, indicates a tendency to increase the logistic comfort of modern layouts.

Keywords: planning solution, logistic comfort, idling, graph theory