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

Information technologies have become increasingly used in various fields, be it document management or payment systems. One of the most popular and promising technologies is cryptocurrency. Since they require ensuring the security and reliability of data in the system, most of them use blockchain and complex cryptographic protocols, such as zero-knowledge proof protocols (ZKP). Therefore, an important aspect for achieving the security of these systems is verification, since it can be used to assess the system's resistance to various attacks, as well as its compliance with security requirements. This paper will consider both the concept of verification itself and the methods for its implementation. A comparison of methods for identifying a proof suitable for zero-knowledge protocols is also carried out. And as a result, a conclusion is made that an integrated approach to verification is needed, since choosing only one method cannot cover all potential vulnerabilities. In this regard, it is necessary to apply various verification methods at various stages of system design.

Keywords: cryptocurrency, blockchain, verification, formal method, static analysis, dynamic method, zero-knowledge proof protocol

This paper proposes a novel model of computer network behavior that incorporates weighted multi-label dependencies to identify rare anomalous events. The model accounts for multi-label dependencies not previously encountered in the source data, enabling a "preemptive" assessment of their potential destructive impact on the network. An algorithm for calculating the potential damage from the realization of a multi-label dependency is presented. The proposed model is applicable for analyzing a broad spectrum of rare events in information security and for developing new methods and algorithms for information protection based on multi-label patterns. The approach allows for fine-tuning the parameters of multi-label dependency accounting within the model, depending on the specific goals and operating conditions of the computer network.

Keywords: multi-label classification, multi-label dependency, attribute space, computer attacks, information security, network traffic classification, attack detection, attribute informativeness, model, rare anomalous events, anomalous events

The paper investigates the specifics of the digital implementation of a rotor synchronization control algorithm for the SV-2M two-rotor vibration unit. The influence of the sampling period on the stability of the synchronous mode is evaluated using computer simulations in MATLAB/Simulink, with time quantization and zero-order hold delay explicitly accounted for. A comparative analysis of the digital and analog versions of the algorithm has been performed. The boundary values of the discretization periods for different values of the given total energy of the system have been determined. The obtained results confirm the applicability of the proposed approach for digital control systems of vibratory equipment.

Keywords: digital control, rotor synchronization, two-rotor vibration unit, speed-gradient algorithm, extrapolator

Many major cities around the world are seeing a trend toward compact housing units, typically located in central areas and fully integrated with existing urban infrastructure. Despite similarities in size and location, each project offers unique architectural and social solutions to address the housing crisis and adapt to limited space. With urban density increasing and real estate prices rising, compact housing projects, typically located in central areas and fully integrated with existing infrastructure, are becoming increasingly relevant. Despite the general trend toward smaller spaces, each project offers unique architectural and social responses to the challenges of modern urbanism.

Keywords: micro-housing, urbanization, architecture, city, infrastructure, mobility, sustainability, renovation, miniaturization, accessibility, autonomy, flexibility, project, space, concept

The article discusses the development of a method for protecting confidential images in instant messengers based on masking with orthogonal matrices. The vulnerability of the system to brute-force attacks and account compromise is analyzed. The main focus is on the development of an architecture for analyzing abnormal activity and adaptive authentication. The article presents a system structure with independent security components that provide blocking based on brute-force attacks and flexible session management. The interaction of the modules within a unified security system is described, with the distribution of functions between server and client components.

Keywords: information security, messenger, messaging, communications, instant messaging systems, security audits, and brute-force attacks

This article examines transportation network modeling using the Ford–Fulkerson algorithm. It describes the process of finding a minimum cut using a graphical editor and library developed in the C# programming language. Key concepts of graph and network theory are presented to clarify the problem statement. An example of solving a transportation problem using the developed software is shown, and the program's results are compared with a control example.

Keywords: transportation network, maximum flow problem, Ford–Fulkerson algorithm, minimum cut in the network, software library, graphical editor, C# programming language

The article presents a comparative analysis of the performance of three solver programs (based on the libraries lpSolve, Microsoft Solver Foundation and Google OR-Tools) when solving a large-dimensional linear Boolean programming problem. The study was conducted using the example of the problem of identifying the parameters of a homogeneous nested piecewise linear regression of the first type. The authors have developed a testing methodology that includes generating test data, selecting hardware platforms, and identifying key performance metrics. The results showed that Google OR-Tools (especially the SCIP solver) demonstrates the best performance, surpassing analogues by 2-3 times. The Microsoft Solver Foundation has shown stable results, while the lpSolve IDE has proven to be the least productive, but the easiest to use. All solvers provided comparable accuracy of the solution. Based on the analysis, recommendations are formulated for choosing a solver depending on performance requirements and integration conditions. The article is of practical value for specialists working with optimization problems and researchers in the field of mathematical modeling.

Keywords: regression model, homogeneous nested piecewise linear regression, parameter estimation, method of least modules, linear Boolean programming problem, index set, comparative analysis, software solvers, algorithm performance, Google OR-Tools

The article is devoted to the development of an innovative neural network decision support system for firefighting in conditions of limited visibility. A comprehensive approach based on the integration of data from multispectral sensors (lidar, ultrasonic phased array, temperature and hygrometric sensors) is presented. The architecture includes a hybrid network that combines three-dimensional convolutional and bidirectional LSTM neurons. To improve the quality of processing, a cross-modal attention mechanism is used to evaluate the physical nature and reliability of incoming signals. A Bayesian approach is used to account for the uncertainty of forecasts using the Monte Carlo dropout method. Adaptive routing algorithms allow for quick response to changing situations. This solution significantly improves the efficiency of firefighting operations and reduces the risk to personnel.

Keywords: mathematical model, intelligence, organizational model, gas and smoke protection service, neural networks, limited visibility, fire department, management, intelligent systems, decision support

Problem statement. When modeling a complex technical system, the issues of parameter estimation are of primary importance. To solve this problem, it is necessary to obtain a methodology that allows eliminating errors and inaccuracies in obtaining numerical parameters. Goal. The article is devoted to a systematic analysis of the methodology for estimating the parameters of a complex technical system using the interval estimation method. The research method. A systematic analysis of the methods of using interval estimates of numerical parameters is carried out. The decomposition and structuring of the methods were carried out. Results. The expediency of using a methodology for describing the parameters of a complex technical system using the interval estimation method is shown. An analysis of the use of various interval estimation models is presented. Practical significance. Application in the analysis and construction of complex systems is considered as a practical application option. The method of estimating the parameters of a complex technical system using the interval estimation method can be used as a practical guide.

Keywords: interval estimation, parameter estimation, numerical data, fuzzy data, complex technical systems

This paper is devoted to the theoretical analysis and comparative characteristics of methods and algorithms for automatic identity verification based on the dynamic characteristics of a handwritten signature. The processes of collecting and preprocessing dynamic characteristics are considered. An analysis of classical methods, including hidden Markov models, support vector machines, and modern neural network architectures, including recurrent, convolutional, and Siamese neural networks, is conducted. The advantages of using Siamese neural networks in verification tasks under the condition of a small volume of training data are highlighted. Key metrics for assessing the quality of biometric systems are defined. The advantages and disadvantages of the considered methods are summarized, and promising areas of research are outlined.

Keywords: verification, signature, machine learning, dynamic characteristic, hidden Markov models, support vector machine, neural network approach, recurrent neural networks, convolutional neural networks, siamese neural networks, type I error

This article investigates the problem of structured data schema matching and aggregates the results from previous stages of the research. The systematization of results demonstrated that while the previously considered approaches show promising outcomes, their effectiveness is often insufficient for real-world application. One of the most effective methods was selected for further study. The Self-Organizing Map method was analyzed, which is based on a criterial analysis of the attribute composition of schemas, using an iterative approach to minimize the distance between points (in the current task, a point represents a schema attribute). An experiment on schema matching was conducted using five examples. The results revealed both the strengths and limitations of the method under investigation. It was found that the selected method exhibits insufficient robustness and reproducibility of results on diverse real-world datasets. The verification of the method confirmed the need for its further optimization. The conclusion outlines directions for future research in this field.

Keywords: data management, fusion schemes, machine learning, classification, clustering, machine learning, experimental analysis, data metrics

The article discusses the application of a systematic approach to the development and optimization of lithium-ion batteries (LIBs). Traditional methods that focus on improving individual components (anode, cathode, and electrolyte) often do not lead to a proportional increase in the overall performance of the battery system. The systematic approach views LIBs as a complex, interconnected system where the properties of each component directly influence the behavior of others and the overall performance, including energy and power density, life cycle, safety, and cost. The work analyzes the key aspects of the approach: the interdependence between the main components of a lithium-ion battery, as well as the features of selecting materials for each component. It is proven that only a multidisciplinary approach that combines chemistry, materials science, and engineering can achieve a synergistic effect and create highly efficient, safe, and reliable battery systems for modern applications.

Keywords: lithium-ion battery, system approach, electrode materials, degradation, optimization, cathode, LTO, NMC

Choosing the best video compression method is becoming increasingly important as the volume of online video grows rapidly. By 2026, people are predicted to watch 82% more video online than in 2020. This means finding a balance between image quality, processing speed, and file size. To achieve the desired parameters, it's crucial to choose the right codec.
This paper compares five popular codecs—MPEG-2, MPEG-4, VP9, ​​MJPEG, and ProRes. Each codec offers its own unique method for compressing video, yielding different file sizes and image quality. The goal was to determine which codec is best suited for various applications: video calls, professional filming, and online broadcasts.
The experiments were conducted on a server with four processor cores, 8 GB of RAM, and an 80 GB SSD. Measurements were taken to determine the speed of each codec, the resulting file size, and the video quality. Based on the results of these tests, recommendations were made on which codec to choose and how it can be improved in different scenarios.

Keywords: video codec, MPEG-2, MPEG-4, VP9, MJPEG, ProRes, AVC, compression, coding

The principles of biophilic design are becoming a key component of the architectural design of medical facilities due to the well-known psychological impact of natural elements on patients and medical staff. The inclusion of natural elements, such as the use of plants, natural light and shade, colors found in nature, and naturally occurring patterns and curves, in medical facilities has been shown to create a psychologically safe environment that promotes the health and well-being of patients and staff. This article explores the fundamental principles of biophilic design, the scientific evidence supporting its therapeutic effects, and practical examples of its use in healthcare settings to improve psychological health and well-being. This work contributes to the existing body of knowledge on biophilic design by providing an up-to-date review of recent research and real-world applications, including challenges

Keywords: biophilia, biophilic design, sustainable architecture, healthcare architecture, well-being, sustainability, biophilic architecture