The article discusses modern methods for protecting bank customers' personal information based on differential anonymization of data using trusted neural networks. It provides an overview of the regulatory framework, analyzes technological approaches and describes a developed multi-level anonymization model that combines cryptographic and machine learning techniques. Special attention is paid to balancing between preserving data utility and minimizing the risk of customer identity disclosure.

Keywords: differential anonymization, trusted neural network, personal data, banking technologies, information security, cybersecurity

The article discusses integrated development environments based on artificial intelligence as an innovative programming tool that provides automation of routine software development tasks. The Cursor development environment, developed by Anywhere, is the main object of research. The architectural features of the system are analyzed, including an agent-based approach to interacting with code, context management mechanisms through generation supplemented with extracted data, and code base indexing using vector representations and Merkle trees to optimize updates. The key limitations of modern integrated development environments based on artificial intelligence have been identified: problems with the size of the context window, indexing performance of large repositories, accuracy of context extraction, as well as privacy and security issues. Special attention is paid to the human factor – the lack of competence of developers in the field of effective context management and the creation of high-quality products. The article substantiates the need to create a preliminary context management agent capable of technically optimizing processes and directing users to effective practices of working with integrated development environments based on artificial intelligence.

Keywords: integrated development environment, artificial intelligence, Cursor development environment, large language models, context management, generation with addition of extracted data, code base indexing, Merkle trees, agent-based approach, software developmen

This article systematizes reinforcement methods based on their operating principle and the materials used, identifying key trends: the dominance of technologies based on composite external reinforcement materials and the active development of hybrid systems. A classification scheme has been developed that allows for the informed selection of reinforcement methods based on the technical condition of the structure and the desired result.
The article demonstrates the high effectiveness of composite materials in increasing strength and seismic resistance with a minimal increase in cross-sectional weight. It is determined that traditional methods (reinforced concrete casings, shotcrete) remain relevant when a significant increase in rigidity is required. Promising areas for implementation are identified: the adaptation of international standards, the development of domestic equivalents of high-performance composites, and the creation of digital reinforcement models.of investments in interests of the organization and development of new production on available floor spaces. The most important organizational economic targets of a diversification of management are presented by innovative activity of the industrial enterprise.

Keywords: structural reinforcement, operational load, columns, composite materials, carbon fiber, seismic resistance, shotcrete, steel casings, fiber-reinforced concrete, hybrid reinforcement

The article presents a hybrid approach to recognizing human actions, combining neural network extraction of skeletal features with deterministic geometric analysis based on vector algebra and affine transformations. A review of research on this issue has been conducted. Unlike traditional solutions that require re-training the model when adding a new action, the proposed system allows the user to dynamically set and modify a set of recognizable actions without the involvement of a specialist in the field of machine learning. Each action is defined as a sequence of poses described by the relative location of key body points. The comparison of the current and reference poses is carried out through the cosine similarity of the vectors, and resistance to angle changes is provided by three-dimensional affine transformations. The software is implemented in Python using the MediaPipe and OpenCV frameworks, has an intuitive graphical interface, and works with a regular webcam. Experimental testing has confirmed the correctness of recognition of specified actions with an accuracy of at least 85% under natural conditions. The solution is focused on application in behavior management systems in organizational environments where flexibility of configuration, interpretability and a low entry threshold are important.

Keywords: human action recognition, vector algebra, affine transformations, hybrid model, behavioral management, human–machine interfaces

The article presents the results of calculations of the stress-strain state of the Sophie Germain-Lagrange plate obtained using approximate methods for solving differential equations: the Bubnov-Galerkin method, the finite difference method and the differential quadrature method. It is shown that the differential quadrature method using the Chebyshev grid is an effective method for solving bending problems of thin rectangular plates and allows obtaining high-precision results using a limited number of nodes.

Keywords: differential equation, approximate solution, differential quadrature method, Chebyshev grid, Sophie Germain-Lagrange plate, plate bending, stress-strain state

The article discusses the current threats posed by unmanned aerial vehicles and their impact on the development of the legal and regulatory framework for construction safety in Russia. Based on an analysis of regulatory documents, the article explores the phenomenon of law substitution and the obsolescence of the legal and regulatory framework for construction safety. The author proposes an initial approach to addressing these issues by modernizing the legal framework for building and structure safety. To achieve this, the author has formulated new concepts that are recommended for inclusion in the key law and that lay the foundation for a new institution of unmanned (anti-drone) security in the construction industry.

Keywords: regulatory legal act, regulatory technical act, law replacement, unmanned aerial vehicle, threat of an unmanned aerial vehicle, unmanned anti-drone security, unmanned danger

The article discusses current threats and vulnerabilities of telephone subscribers in the context of mass digitalization, the development of artificial intelligence and machine learning technologies, and their use in fraudulent scenarios. The study analyzes the main vulnerability factors and provides statistical data on telephone fraud incidents in Russia and abroad. Special attention is given to the phenomena of trust in authority, insufficient digital literacy, and the use of voice synthesis and deepfake technologies for social engineering attacks.

Keywords: social engineering, fraud, vishing, deepfake, artificial intelligence, digital literacy, information security

Two approaches to weighting vertices in rooted trees of hierarchical classifiers that characterize subject domains of various information retrieval systems are presented. Weight characteristics are examined depending on the position of vertices in the rooted tree — namely, on the level, depth, number of directly subordinate vertices (the «sons» clan), and number of hierarchically subordinate leaf vertices. The specifics of vertex weighting in a rooted tree are illustrated based on: weighted summation of level‑based, depth‑based, clan‑based, and leaf‑based vertex weights; hierarchically additive summation of leaf weight characteristics.

Keywords: information retrieval systems, hierarchical subject classifiers, hierarchical categorizers, subject indexing, vertex weighting in a rooted tree, level‑based weight characteristic of a vertex, depth‑based weight characteristic of a vertex

The article considers the problem of constructing a continuous displacement trajectory based on nodal feedback data in control systems with prediction of external load. The use of interpolation by cubic Fergusson splines is proposed. The proposed approach has computational efficiency and is applicable in adaptive control systems, including control of rotational movements in a non-deterministic environment.

Keywords: control, predictive models, MPC, external load, interpolation, spline, trajectory of the control object

Electrocardiogram (ECG)-based biometric authentication systems offer intrinsic resistance to spoofing due to their physiological uniqueness. However, their performance in dynamic real-world settings, such as wearable devices or stress-induced conditions, is often compromised by noise, electrode displacement, and intra-subject variability. This study proposes a novel hybrid framework that enhances robustness, ensuring high authentication accuracy and reliability in adverse conditions, through integrated wavelet-based signal processing for noise suppression and a deep-learning classifier for adaptive feature recognition. The system employs preprocessing, QRS complex detection, distance–deviation modeling, a statistical comparison method that quantifies morphological similarity between ECG templates by analyzing amplitude and shape deviations and an averaging-threshold mechanism, combined with a feedforward Multi-Layer Perceptron (MLP) neural network for classification. The MLP is trained on extracted ECG features to capture complex nonlinear relationships between waveform morphology and user identity, ensuring adaptability to variable signal conditions. Experimental validation on the ECG-ID dataset achieved 98.8% accuracy, 95% sensitivity, an Area Under the Curve (AUC) of 0.98, and a low false acceptance rate, outperforming typical wearable ECG authentication systems that report accuracies between 90% and 95%. With an average processing time of 8 seconds, the proposed method supports near real-time biometric verification suitable for healthcare information systems, telehealth platforms, and IoT-based access control. These findings establish a scalable, adaptive, and noise-resilient foundation for next-generation physiological biometric authentication in real-world environments

Keywords: electrocardiogram biometrics, wavelet decomposition, QRS complex detection, feedforward neural network, deep learning classification, noise-resilient authentication, biometric security

A comprehensive method of system analysis and processing of financial information is proposed without prior training in five complementary taxonomies (genre, type of event, tonality, level of influence, temporality) with simultaneous extraction of entities. The method is based on an ensemble of three specialized instructions for a local artificial intelligence model with an adapted majority voting algorithm and a two-level mechanism for explicable failures. The protocol was validated by comparative testing of 14 local models on 100 expertly marked units of information, while the model achieved 90% processing accuracy. The system implements the principles of self-consistency and selective classification, is reproduced on standard equipment and does not require training on labeled data.

Keywords: organizational management, software projects, intelligent decision support system, ontological approach, artificial intelligence

This paper presents a decision support model for responding to forest fires in mountainous areas using fuzzy logic. The research methods include the Mamdani method for constructing a fuzzy inference system, the use of linguistic variables to describe environmental conditions and risk factors, and the formation of a rule base based on expert knowledge. The developed model implements the principles of situational management and enables determination of the fire danger level, selection of extinguishing methods, response tactics, and optimal resource allocation. Its practical significance lies in the potential application of the model in decision support systems of the Russian Ministry of Emergency Situations for operational planning and forecasting during forest fire suppression in challenging mountainous conditions.

Keywords: forest fires, mountainous terrain, fuzzy logic, decision support, intelligent systems, situational management

The article presents the architecture and implementation of an intelligent software package (ISP) for predicting the thermal resistance of semiconductor devices, in particular MOSFET transistors, at the design stage. The developed system combines physical and mathematical modeling of multilayer heat-conducting structures with machine learning methods, which allows for an accurate prediction of thermal parameters based on engineering characteristics and case design. The ISP implements a mechanism for automatically supplementing incomplete data using a knowledge base of typical parameters of domestic and foreign devices. Models were trained on a synthetically expanded sample formed taking into account the thermal conductivity of structural materials and layer geometry. Among the algorithms used are ensembles of random forests and gradient boosting, as well as neural network models. An analysis of the importance of features was carried out, key parameters that determine them were identified, and the possibility of using the ISP for early assessment of thermal conditions in CAD and CAE environments was demonstrated.

Keywords: thermal resistance, MOSFET, machine learning, intelligent software system, multilayer structure, predictive model, CAD, thermal conductivity

This article examines the problem of control and management in transport systems using the example of passenger rail rolling stock operation processes using information technology and automation tools. The main proposed methods for improving the efficiency of vehicle operation management are the use of digital modeling of transport complex objects and processes and the automation of probabilistic-statistical analysis of data on the technical and operational characteristics of the system. The objective of the study is to improve the operational efficiency, reliability, and safety of passenger rail rolling stock by developing digital twins of the rolling stock and digital models of its operation processes. The main objectives of the study are to develop approaches to automating methods of  analysis of the flow of data on the operation and technical condition of passenger rolling stock, as well as to develop a concept for applying digital modeling to solve current problems of passenger rail transport. The research hypothesis is based on the assumption of the effectiveness of applying new information technologies to solving practical problems of rolling stock operation management. The use of digital models of rolling stock units and the digitalization of the repair process are considered. The paper proposes the use of automated Pareto analysis methods for data on technical failures of railcars and least-squares modeling of distribution and density functions for passenger wagon operating indicators as continuous random variables. It is demonstrated that digital modeling of transport system objects and processes using big data analysis enables the improvement of transportation processes. General recommendations are provided for the use of information tools to improve the management of passenger rolling stock operations in rail transport.

Keywords: information technologies, digital modeling, digital twin, automated control, system analysis, process approach, reliability, rolling stock operation, maintenance and repair, monitoring systems

The paper examines the nature of exponential behavior and identifies the conditions under which the probabilistic distribution of the project completion period deviates from the exponential one. For this purpose, a model has been developed in which the evolution of the project is described as a Markov process with a transition matrix containing a constant in all elements of the first row. This structure corresponds to a situation in which the project can be restarted at any time. Project completion times can follow various statistical distributions, including normal, exponential, and more complex forms. Examples of such projects can be research, exploration, venture and other similar projects. An analysis of the dynamics shows that the model reliably reproduces the exponential distribution in cases where the probability of a restart remains moderate. This indicates the limit of applicability of the exponential description.: it is adequate for low and medium restart probabilities, but loses accuracy with a high level of uncertainty.

Keywords: Markov processes, project management, exponential distribution, project completion time, risk assessment, probabilistic forecasting, uncertainty in projects, risks of assumptions, dynamics of project evolution

Construction work often involves risks when carrying out complex sets of tasks described in the form of network schedules, in particular, risks of violating tender deadlines and project costs. One of the main reasons for increased project risks is a lack of resources. The main objective of this study is to develop a methodology for modeling network schedules under resource constraints, taking into account the stochastic influence of risks on project completion deadlines. The paper analyzes tools for modeling project schedules; describes a mathematical model for estimating project cost based on a network schedule under resource constraints; proposes a method for modeling a network schedule in the AnyLogic environment; develops an algorithm for modeling parallel branches of a project schedule under resource constraints; and describes a method for modeling a network schedule for project work. Testing was conducted based on a network schedule for a project to construct a contact line support. It has been shown that the method allows for obtaining probabilistic estimates of project deadlines and costs under conditions of risk and limited resources. The methodology can be applied to various projects described by network schedules and will allow solving a number of practical tasks: optimizing resources allocated for project implementation, taking into account the time and cost of the project, analyzing risks affecting project implementation, and developing optimal solutions for project risk management.

Keywords: network schedule, work plan, simulation modeling, risk analysis, project duration, project cost

This article describes a developed method for automatically optimizing the parameters of an intelligent controller based on an adaptive genetic algorithm. The key goal of this development is to improve the mechanism for generating an intelligent controller rule base through multiparameter optimization. The genetic algorithm is used to eliminate linguistic uncertainty in the design of control systems based on intelligent controllers. A unique algorithm is proposed that implements a comprehensive optimization procedure structured in three sequential stages: identifying optimal control system parameters, optimizing the structure of the intelligent controller rule base, simulating the automatic generation process, and then optimizing the intelligent controller parameters. Implementation of this approach optimizes the weights of fuzzy logic rules and the centers of the membership functions of linguistic variables.

Keywords: intelligent controller, optimization, genetic algorithm, uncertainty, term set

The paper discusses issues related to the use of graph-theoretic models in text analysis. One of the tasks is to aggregate such models to identify more "simple" graphs, the vertices of which correspond to subsets of the vertices of the original model, and the edges reflect the "strong connections" between the vertices. Using the example of a Russian folk tale plot, it is shown how to build an aggregated model with a given threshold of significance and present it for further analysis. To conduct the experiments, a set of graph-theoretical models for fairy-tale plots from the collection of A.M. Afanasyev was built using the Folklore information system, where the graph aggregation module was improved.

Keywords: text analysis, graph-theoretical model, aggregation, significance threshold, storage format, folklore text, fairy tale plot, information system "Folklore"

The article deals with the problem of quantifying the security of objects of the penal correction system based on mathematical modeling. The authors propose a modified genetic algorithm in which the traditional fitness function is replaced by a mechanism of "virtual movement" of individuals in a discrete space, which allows taking into account both the individual characteristics of safety measures and their cumulative impact. A step-by-step example of applying the algorithm to choosing the optimal set of protective measures based on expert assessments based on several criteria is given. The results demonstrate the effectiveness of the proposed approach for solving multi-criteria tasks of assessing and improving security in conditions of uncertainty and the absence of an explicit analytical relationship between system parameters.

Keywords: security, vulnerability, event, penal enforcement system, genetic algorithm, mathematical modeling, optimization, expert assessment, criterion, security, security regime, discrete space, coalition, crossing, fitness function

The article provides a reasonable definition of an intelligent digital twin of an information security protection object and identifies the main stages of its development. The article also develops set-theoretic models of the protection object and the intelligent digital twin, which allow for the identification of their identical components and distinctive features that determine the mechanism for countering threats. Based on the provisions of the conflict theory, the relationship between the protected object and the threat was identified in the absence of an intelligent digital twin, as well as in the presence of an intelligent digital twin in the system of protecting the object from information security threats. The obtained macro-dynamic models of the considered situations allow us to justify the feasibility of implementing a mechanism for protecting the object from information security threats based on the use of its intelligent digital twin and to assess the overall effect of its application.

Keywords: information security, object of protection, intelligent digital twin, threat, set-theoretic model, conflict theory, macrodynamic model

The aim of this study is to evaluate the environmental and economic efficiency of using hydrogen-natural gas mixtures in existing fuel systems. The work is based on a stoichiometric calculation of emissions and a comparative cost analysis. It was found that the linear relationship between the hydrogen content and CO₂ emission reduction allows for a 30% reduction for a mixture containing 30% vol. H₂. Water vapor emissions are also reduced by 15%, which is explained by the difference in the combustion stoichiometry of methane and hydrogen. The article substantiates the economic feasibility of this technology when using inexpensive hydrogen produced locally, for example, through waste recycling.

Keywords: gas, natural gas, hydrogen, greenhouse gases, gas mixture, carbon dioxide

The article examines the features of adaptive design in construction as a fundamental component for ensuring life safety in the zone of a special military operation. The modern world is changing at an incredible pace: climate anomalies are becoming more frequent, technological paradigms are being replaced within years, and social and economic conditions are undergoing constant transformations. Nowhere are these challenges manifested as acutely and concentratedly as in the zone of a special military operation (SMO). It is precisely here that the traditional approach to construction, focused on creating static, "frozen" objects, proves not only ineffective but also dangerous. It is being replaced by adaptive design – a philosophy and methodology that views a building or infrastructure object not as a final product, but as a living, evolving organism capable of evolving in response to direct threats and changing operational conditions. Adaptive design is a strategy for creating architectural objects and urban planning systems that can be easily modified, transformed, or repurposed in response to changes in external or internal conditions. In peacetime, this is a response to changing markets and technologies. In the zone of a special military operation, it is a matter of ensuring life safety. This is not simply post-factum repair or reconstruction, but the inherent ability of an object to instantly change its function and protective properties without radical rebuilding. The experience of the special military operation zone has openly proven that adaptive design is not an abstract idea from construction textbooks, but a critically important discipline upon which people's lives and the success of the assigned task depend. The principles of flexibility, modularity, and multifunctionality that are being tested today in extreme conditions will tomorrow become the new standard for the entire construction complex of the Russian Federation. They will form the basis for the restoration of cities, the creation of sustainable civil infrastructure, and the formation of new, anti-crisis architecture capable of withstanding the challenges of both wartime and peacetime. In the zone of a special military operation, architectural heritage is being tested and created, which will remain functional, in demand, and sustainable tomorrow. The future of construction belongs to those who design not for years, but for possibilities.

Keywords: adaptive construction, modern trends, modern design technologies, construction industry, construction processes, special military operation