In recent years, there has been a notable increase in the popularity of modular construction in Russia and in other countries. This form of construction offers a number of advantages, including a reduction in construction time, a decrease in costs, an improvement in the quality of modular construction, and a reduction in the negative environmental impact.

Keywords: еhe subject matter encompasses modular construction, prospects, Russia, international experience, construction technologies, housing construction, and innovations

The paper presents a method for quantitative assessment of zigzag trajectories of vehicles, which allows to identify potentially dangerous behavior of drivers. The algorithm analyzes changes in direction between trajectory segments and includes data preprocessing steps: merging of closely spaced points and trajectory simplification using a modified Ramer-Douglas-Pecker algorithm. Experiments on a balanced data set (20 trajectories) confirmed the effectiveness of the method: accuracy - 0.8, completeness - 1.0, F1-measure - 0.833. The developed approach can be applied in traffic monitoring, accident prevention and hazardous driving detection systems. Further research is aimed at improving the accuracy and adapting the method to real-world conditions.

Keywords: trajectory, trajectory analysis, zigzag, trajectory simplification, Ramer-Douglas-Pecker algorithm, yolo, object detection

Based on the analysis of behavioral characteristics, the main indicators that provide the greatest accuracy in identifying users of mobile devices are identified. As part of the research, software has been written to collect touchscreen data when performing typical user actions. Identification algorithms are implemented based on machine learning algorithms and accuracy is shown. The results obtained in the study can be used to build continuous identification systems.

Keywords: user behavior, touch screen, continuous identification, biometrics, dataset, classification, deep learning, recurrent neural network, mobile device

A method is proposed for cascading connection of encoding and decoding devices to implement code division of channels. It is shown that by increasing the number of cascading levels, their implementation is significantly simplified and the number of operations performed is reduced. In this case, as many pairs of subscribers can simultaneously exchange information, what is the minimum order of the encoding and decoding devices in the system. The proposed approach will significantly simplify the design of encoding and decoding devices used in space and satellite communication systems.

Keywords: telecommunications systems, telecommunications devices, multiplexing, code division of channels, orthogonal matrices, integers, cascaded connection

The development, research and construction of devices that speed up the process of interaction between various modules (for example, telemetry and remote control systems), and in general, hybrid communication systems of a digital city that include a variety of systems used in an Intelligent Building is an urgent problem. One of these devices presented in the article is the optimal multi–frequency modem developed. In addition to the developed modem, the article presents examples of the development of similar types of devices and systems by both Russian and foreign researchers. At the same time, the authors proved that the use of the proposed modem provides a gain in spectral and energy efficiency in comparison with analogues. The proposed approach can be used to organize high-speed data transmission over frequency-limited communication channels based on new wired technologies of the digital subscriber line standard, as well as wireless systems.

Keywords: telemetry and remote control system, intelligent building, digital city hybrid communications system, modem, multi-frequency modulation, digital subscriber line, optimal finite signal, modulator, demodulator, wireless communication system

The article presents a comprehensive analysis of a systematic approach to the implementation and development of innovative information technologies aimed at preventing offenses committed by foreign citizens. The introduction provides an overview of the growing importance of employing advanced technological solutions in law enforcement, particularly in addressing challenges associated with foreign nationals. The main objectives of the study are to explore how the integration of technologies such as big data processing, artificial intelligence, and geographic information systems can enhance the efficiency of preventive measures. The article details the use of data analysis techniques, machine learning models, and system integration to create a unified information platform. This platform enables the consolidation of data from diverse sources, thereby improving the coordination between different law enforcement units and facilitating faster and more informed decision-making processes. The integration of these technologies also supports process standardization, reducing data inconsistencies and ensuring more reliable operations across various departments. The results highlight the benefits of utilizing big data analytics to process vast amounts of information that would be otherwise impossible to handle efficiently. Artificial intelligence, through predictive models and risk assessment tools, plays a crucial role in identifying potential threats and allocating resources effectively. Geographic information systems contribute by mapping crime hotspots and providing spatial analysis, which aids in targeted intervention strategies. The discussion emphasizes the importance of a unified approach to technology implementation, focusing on the creation of an integrated information system that can adapt to ongoing changes in the social and legal environment. The adaptability of the system is critical for maintaining its effectiveness in the face of new challenges and evolving regulatory requirements. The development of standardized data collection and processing protocols further enhances the system's resilience and operational efficiency. In conclusion, the article underscores that a systematic and integrated use of innovative information technologies significantly improves the effectiveness of crime prevention efforts and the overall efficiency of law enforcement agencies. The proposed approach not only facilitates proactive measures but also ensures a high level of responsiveness to emerging security threats, thereby strengthening public safety.

Keywords: systemic approach, innovative information technologies, crime prevention, foreign citizens, big data, artificial intelligence, geoinformation systems, information platform, standardization, law enforcement agencies, efficiency management, data integration

This study examines the structure and characteristics of multilayer autoencoders (MAEs) used in detecting computer attacks. The potential of MAEs for improving detection capabilities in cybersecurity is analyzed, with a focus on their role in reducing the dimensionality of large datasets involved in identifying computer attacks. The study explores the use of different neuron activation functions within the network and the most commonly applied loss functions that define reconstruction quality of the original data. Additionally, an optimization algorithm for autoencoder parameters is considered, designed to accelerate model training, reduce the likelihood of overfitting, and minimize the loss function.

Keywords: neural networks, layers, neurons, loss function, activation function, mobile applications, attacks, hyperparameters, optimization, machine learning

Abstract. The purpose of the article is to study the information security of critical parameters of the organization's IT infrastructure processes and its digital infrastructure using Security Monitoring Centers. Such risk factors as adaptability, stability in the middle and long period, the influence of uncertainties ("white noise") are emphasized. In addition to system analysis and synthesis, methods of mathematical (simulation, operator) modeling, computational mathematics and statistics are used in the work. Based on the analysis and synthesis, the following main results were obtained: 1) the classification of the effects of various attacks on the distributed infrastructure was carried out; 2) a scheme, a multiplicative model of integral interactions of protective measures and an integral measure of security are proposed; 3) an algorithm has been developed to identify the constructed multiplicative model based on the least squares criterion, both by the set of factors and by risk classes; 4) shows an example of an operator equation taking into account random noise in the system. Scientific and practical value of work: the results can be used to assess the security of the system and reduce the risks of targeted attacks, damage from them. In addition, the proposed schemes will facilitate situational modeling to detect risk situations and assess the damage from their implementation.

Keywords: assessment, sustainability, maturity, information security center, monitoring, risk, management

When evaluating student work, the analysis of written assignments, particularly the analysis of source code, becomes particularly relevant. This article discusses an approach for evaluating the dynamics of feature changes in students' source code. Various metrics of source code are analyzed and key metrics are identified, including quantitative metrics, program control flow complexity metrics, and the TIOBE quality indicator. A set of text data containing program source codes from a website dedicated to practical programming, was used to determine threshold values for each metric and categorize them. The obtained results were used to conduct an analysis of students' source code using a developed service that allows for the evaluation of work based on key features, the observation of dynamics in code indicators, and the understanding of a student's position within the group based on the obtained values.

Keywords: machine learning, text data analysis, program code analysis, digital footprint, data visualization

There is often a need to analyze unstructured data when assessing the risk of emergency situations. Traditional analysis methods may not take into account the ambiguity of information, which makes them insufficiently effective for risk assessment. The article proposes the use of a modified hierarchy process analysis method using fuzzy logic, which allows for more effective consideration of uncertainties and subjective assessments in the process of analyzing emergency risks. In addition, such methods allow for consideration of not only quantitative indicators, but also qualitative ones. This, in turn, can lead to more informed decisions in the field of risk management and increased preparedness for various situations. The integration of technologies for working with unstructured data in the process of assessing emergency risks not only increases the accuracy of forecasting, but also allows for adapting management strategies to changing conditions.

Keywords: artificial intelligent systems, unstructured data, risk assessment, classical hierarchy analysis method, modified hierarchy analysis method, fuzzy logical inference system

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

In systems for monitoring, diagnostics and recognition of the state of various types of objects, an important aspect is the reduction of the volume of measured signal data for its transmission or accumulation in information bases with the ability to restore it without significant distortion. A special type of signals in this case are packet signals, which represent sets of harmonics with multiple frequencies and are truly periodic with a clearly distinguishable period. Signals of this type are typical for mechanical, electromechanical systems with rotating elements: reducers, gearboxes, electric motors, internal combustion engines, etc. The article considers a number of models for reducing these signals and cases of priority application of each of them. In particular, the following are highlighted: the discrete Fourier transform model with a modified formula for restoring a continuous signal, the proposed model based on decomposition by bordering functions and the discrete cosine transform model. The first two models ideally provide absolute accuracy of signal restoration after reduction, the last one refers to reduction models with information loss. The main criteria for evaluating the models are: computational complexity of the implemented transformations, the degree of implemented signal reduction, and the error in restoring the signal from the reduced data. It was found that in the case of application to packet signals, each of the listed models can be used, the choice being determined by the priority indicators of the reduction assessment. The application of the considered reduction models is possible in information and measuring systems for monitoring the state, diagnostics, and control of the above-mentioned objects.

Keywords: reduction model, measured packet signal, discrete cosine transform, decomposition into bordering functions, reduction quality assessment, information-measuring system

In operational diagnostics and recognition of states of complex technical systems, an important task is to identify small time-determined changes in complex measured diagnostic signals of the controlled object. For these purposes, the signal is transformed into a small-sized image in the diagnostic feature space, moving along trajectories of different shapes, depending on the nature and magnitude of the changes. It is important to identify stable and deterministic patterns of changes in these complex-shaped diagnostic signals. Identification of such patterns largely depends on the principles of constructing a small-sized feature space. In the article, the space of decomposition coefficients of the measured signal in the adaptive orthonormal basis of canonical transformations is considered as such a space. In this case, the basis is constructed based on a representative sample of realizations of the controlled signal for various states of the system using the proposed algorithm. The identified shapes of the trajectories of the images correspond to specific types of deterministic changes in the signal. Analytical functional dependencies were discovered linking a specific type of signal change with the shape of the trajectory of the image in the feature space. The proposed approach, when used, simplifies modeling, operational diagnostics and condition monitoring during the implementation of, for example, low-frequency diagnostics and defectoscopy of structures, vibration diagnostics, monitoring of the stress state of an object by analyzing the time characteristics of response functions to impact.

Keywords: modeling, functional dependencies, state recognition, diagnostic image, image movement trajectories, small changes in diagnostic signals, canonical decomposition basis, analytical description of image trajectory

The article discusses the issues of organizational and technological approaches in the design of facilities to be reconstructed. During the operation of buildings, the reliability of their structures is subject to cyclical changes. The dynamics of loads, as well as damage resulting from operation, can have a significant impact on the strength and durability of construction facilities. The reasons for the technical inspection during reconstruction are analyzed. The diagnosis of structural failure is analyzed. In most cases, emergencies are the result of missed errors at the design stage of the project, construction of the construction site and its operation. To minimize such risks, additional measures are being implemented aimed at quality control at all stages - from design to commissioning. A number of conditions have been identified under which most defects in the design and operation of structures can be prevented even at the stage of development of the reconstruction project.

Keywords: reconstruction, construction and technical expertise, reliability, organizational and technological solutions, defects, quality control, efficiency

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