The use of machine learning when working with text documents significantly increases the efficiency of work and expands the range of tasks to be solved. The paper provides an analysis of the main methods of presenting data in a digital format and machine learning algorithms, and a conclusion is made about the optimal solution for generative and discriminative tasks.

Keywords: machine learning, natural language processing, transformer architecture models, gradient boosting, large language models

The article focuses on the integration of digital educational technologies (EdTech) into the management of organizational systems in the context of digital transformation in education. Special attention is given to the analysis of the interconnection between technological, organizational, and market components of EdTech, as well as their impact on optimizing business processes and management strategies in educational institutions. The aim of the study is to develop a comprehensive definition of EdTech that reflects its evolution and role as a tool for management transformation. The research methodology includes a systematic analysis of the EdTech concept, modeling the interaction between technologies and educational organizations, and a critical evaluation of case studies on digital platform implementation. As a result, the paper proposes defining EdTech as a dynamic ecosystem that integrates digital management, personalized learning, and organizational culture adaptation. The conclusions emphasize the necessity of an ecosystem approach to EdTech management, considering infrastructure limitations, staff training, and regulatory aspects. The findings can be applied to the development of digital transformation strategies for educational institutions, resource planning optimization, and the formation of sustainable business models in the EdTech sector.

Keywords: EdTech, digital transformation, educational technologies, business processes, system analysis, management

The article explores parametric wooden installations to reimagine public architecture by combining the natural properties of wood with computational strategies. It explores how iterative modeling, digital fabrication and user-centric awareness reveal aesthetic and structural possibilities in open or semi-public spaces. A qualitative approach that combines experimental design, prototypes, and field feedback shows that it is effective in creating interactive forms, optimizing material use, and promoting community participation. While environmental factors and cultural ideas influence longevity, the results highlighted by the ZCB bamboo pavilion as an example of how digital workflows are adapted to sustainability, craft traditions and changing needs, ultimately confirming the promise of these structures to architects, policymakers and communities.

Keywords: parametric design, urban architecture, wooden installations, prototypes, digital fabrication, zcb bamboo pavilion, sustainability, digital form, lightweight, innovation

Modern web applications are becoming more complex and feature-rich, which creates the need for effective tools for dependency management, optimization, and project assembly. Buider allow you to optimize your code, which directly affects the download and execution speed of applications. The purpose of the work is to conduct a comparative analysis of JavaScript builders: Webpack, Parcel, and Rollup in order to identify their advantages and disadvantages from the point of view of frontend development ergonomics. This includes evaluating the convenience of configuration, resource efficiency, build speed, and other factors that affect developer productivity and the final quality of web applications. Practical testing of the builders was carried out using the example of a standard web project. The ergonomics of working with tools is evaluated: criteria are identified and a comparison is made based on the data obtained. Recommendations have been developed for choosing the optimal tool for various types of projects in front-end development. The research results can be used as a basis for training new specialists, as well as for improving existing practices in developing web applications when making informed decisions on the choice of technologies for long-term projects.

Keywords: web development, development efficiency, ergonomics, frontend development, testing, builder

This paper explores the content-based filtering approach in modern recommender systems, focusing on its key principles, implementation methods, and evaluation metrics. The study highlights the advantages of content-based systems in scenarios that require deep object analysis and user preference modeling, especially when there is a lack of data for collaborative filtering.

Keywords: сontent - oriented filtering, recommendation systems, feature extraction, similarity metrics, personalization

As a result of changes in regulatory documents on acceptance of residential premises, there is a need to develop illustrative methodological materials that would allow the future owner to independently, i.e. without the involvement of an external qualified specialist, to perform the acceptance of the apartment, pointing out to the representative of the developer involved in the acceptance of significant construction defects. The purpose of the study is to determine the structure of construction defects in residential premises and to identify the most common defects in this structure, which will allow the future owner to independently perform the acceptance of the apartment. In the article, based on the analysis of a significant number of claims from apartment owners to the builder and the results of the authors' research in the scope of forensic examinations and pre-trial construction-technical investigations, the structure of construction defects, which are massively identified in the process of acceptance of apartments, is defined and presented. The groups of defects that are most frequently encountered in practice are presented. To ensure the clarity of practical use of the obtained analytical materials, a list of mass construction defects identified in the process of acceptance of residential premises, indicating their category necessary for making a decision on the mandatory elimination of defects is defined.

Keywords: acceptance of apartments, construction defects, structure, defect groups, construction defect, substantial defect, non-substantial defect, building and technical expertise, translucent construction, engineering networks, finishing of premises

This article examines several key aspects related to the impact of high-rise buildings on human health and psychological state. First of all, the impact of high-rise buildings on mental health is analyzed, paying special attention to problems such as depression, anxiety and stress that can arise as a result of living in multi-storey buildings. We explore the social aspects of living in such conditions and the impact of architectural design on the quality of life. In addition, we would like to draw attention to the health problems of residents of high-rise buildings, including physical illnesses that can occur as a result of lack of natural light, poor ventilation and other factors associated with high-rise buildings. An important part will also be the discussion of possible solutions to improve the quality of life in multi-storey buildings.

Keywords: megapolis, high-rise buildings, high-rise buildings, building density, architectural design, emotional state, health, comfortable environment, quality of life.

This paper describes the process of concatenation of neural network architectures in face image and voice recognition during training. For training of neural networks the extracted features of face image and acoustic signal are used as input vectors. The results obtained and comparative performance of different methods of user recognition of computer information system based on neural networks are presented.

Keywords: biometric authentication, voice, dataset, face image, computer information system, concatenation, neural network

This paper describes a virtualized environment designed to conduct comprehensive experiments involving peer-to-peer networks and information security algorithms. The architecture is based on integrating the VMware hypervisor with the EVE-NG network device emulation platform, providing flexible resource allocation and realistic topology simulation. A MikroTik router serves as the central node, enabling a “star-shaped” scheme of interaction among virtual machines running various operating systems (Windows 7, 10, 11, Linux Debian). The chosen configuration simplifies testing the multiple initial connections and multi-level cryptography algorithms, ensures stable routing, and supports further automation of software installation using Bash or PowerShell scripts.

Keywords: information security, virtualized environment, multiple initial connections, peer-to-peer network, virtual private network

This article presents a comprehensive analysis of Russian-language texts utilizing neural network models based on the Bidirectional Encoder Representations from Transformers (BERT) architecture. The study employs specialized models for the Russian language: RuBERT-tiny, RuBERT-tiny2, and RuBERT-base-cased. The proposed methodology encompasses morphological, syntactic, and semantic levels of analysis, integrating lemmatization, part-of-speech tagging, morphological feature identification, syntactic dependency parsing, semantic role labeling, and relation extraction. The application of BERT-family models achieves accuracy rates exceeding 98% for lemmatization, 97% for part-of-speech tagging and morphological feature identification, 96% for syntactic parsing, and 94% for semantic analysis. The method is suitable for tasks requiring deep text comprehension and can be optimized for processing large corpora.

Keywords: BERT, Russian-language texts, morphological analysis, syntactic analysis, semantic analysis, lemmatization, RuBERT, natural language processing, NLP

Introduction: Mobile Gaming Addiction (MGA) has emerged as a significant public health concern, with the World Health Organization recognizing it as a gaming disorder. Russia, with its growing mobile gaming market, is no exception. Aims and Objectives: This study aims to explore the feasibility of using neural networks for early MGA detection and intervention, with a focus on the Russian context. The primary objective is to develop and evaluate a neural network-based model for identifying behavioral patterns associated with MGA. Methods: A proof of concept study was conducted, employing a simplified neural network architecture and a dataset of 101 observations. The model's performance was evaluated using standard metrics, including accuracy, precision, recall, F1-score, and AUC-ROC score. Results: The study demonstrated the potential of neural networks in detecting MGA, achieving an F1-score of 0.75. However, the relatively low AUC-ROC score (0.58) highlights the need for addressing dataset limitations. Conclusion: This study contributes to the growing body of literature on MGA, emphasizing the importance of considering regional nuances and addressing dataset limitations. The findings suggest promising avenues for future research, including dataset expansion, advanced neural architectures, and region-specific mobile applications.

Keywords: neural networks, neural network architectures, autoencoder, digital addiction, gaming addiction, digital technologies, machine learning, artificial intelligence, mobile game addiction, gaming disorder

The article analyzes the existing programs for training the population in actions and organization of actions in the field of civil defense, as well as in the field of protecting the population from natural and man-made emergencies. Conclusions are drawn about the relevance of existing programs, problems in this area are highlighted, and solutions are proposed to increase the effectiveness of these teaching methods.

Keywords: natural emergencies, civil defense, emergency situations, civil defense, training program, population training, avalanches, life safety, railway

The article presents an analysis of modern methods of image generation: variational autoencoders (VAE), generative adversarial networks (GAN) and diffusion models. The main attention is paid to a comparative analysis of their performance, generation quality and computational requirements. The Frechet Inception Distance (FID) metric is used to assess the image quality. Diffusion models showed the best results (FID 20.8), outperforming VAE (FID 59.75) and GAN (FID 38.9), but require significant resources. VAEs are stable, but generate blurry images. GANs provide high quality, but suffer from training instability and mode collapse. Diffusion models, due to step-by-step noise decoding, combine detail and structure, which makes them the most promising. Also considered are methods of image-to-image generation used for image modification. The results of the study are useful for specialists in the field of machine learning and computer vision, contributing to the improvement of algorithms and expansion of the areas of application of generative models.

Keywords: deepfake, deep learning, artificial intelligence, GAN, VAE, diffusion model

The article focuses on the application of machine learning methods for predicting failures in industrial equipment. A review of modern approaches such as Random Forest, SVM, and XGBoost is presented, with emphasis on their accuracy, robustness, and suitability for engineering tasks. Based on the analysis of real-world data (temperature, pressure, vibration, humidity), models were trained and compared, with XGBoost demonstrating the best performance. Key parameters influencing failures were identified, and a recommendation system was proposed, combining statistical analysis and predictive modeling. The developed solution enables timely detection of failure risks and optimization of maintenance processes.

Keywords: machine learning, predictive modeling, equipment management, failure prediction, data analysis

For neural network algorithms to work successfully when processing 3D point clouds, it is necessary to provide a detailed point cloud of the external environment. A similar task arises when a manipulative robot is operating in a new environment, where before processing a cloud of scene points, it is necessary to obtain a detailed representation of the external environment using an RGB-D camera mounted on the end link of the robot. To solve this problem, this study proposes an algorithm for adaptive control of a manipulative robot to build a model of the external environment. By applying an adaptive approach, during the research of the external environment, the manipulative robot moves the RGB-D camera, taking into account the changes in the current environment model introduced by the previous RGB-D image. The results obtained allow us to judge the effectiveness of the proposed approach, showing that due to adaptability, it allows us to achieve high scene coverage rates.

Keywords: environment model, manipulative robot, adaptive control algorithm, surface reconstruction, RGB-D camera, visual information processing, TSDF volume

The main tasks in optimizing the automated control system for dosing and preparation of the electrode mass are considered. The tasks set to improve the accuracy of charge dosing, as well as to speed up the dosing time, are proposed to be performed using acoustic rapid analysis. The method is based on the decomposition of the acoustic signal generated by the interaction of the moving flow of the charge mixture and the charge line. The decomposition of the signal using fast Fourier transform into spectra and the allocation of sub-spectra responsible for fractional components will increase the accuracy of dosing.

Keywords: automated control system, charge, electrode mass, acoustic signal, spectral analysis, discrete Fourier transform, fractional composition of the charge mixture

This paper examines methods for modeling the spread of infectious diseases. It discusses the features of the generalized compartmental approach to epidemic modeling, which divides the population into non-overlapping groups of individuals. The forecast of models built using this approach involves estimating the size of these groups over time. The paper proposes a method for estimating model parameters based on statistical data. It also introduces a method for estimating confidence intervals for the model forecast, based on a series of stochastic model runs. A computational experiment demonstrates the effectiveness of the proposed methods using data on the spread of influenza in European countries. The results show the model's efficiency in predicting the dynamics of the epidemic and estimating confidence intervals for the forecast. The paper also justifies the applicability of the described methods to modeling chronic diseases.

Keywords: epidemic modeling, computer modeling, compartmental models, SIR, stochastic modeling, parameter estimation, confidence interval, forecast, influenza

A non-stationary system of automatic speed control of a DC motor with an adaptive controller is considered. Comparative simulation modeling in Simulink of the system with and without an adapter is performed. The results of the modeling confirm the stability of the adaptive system in a larger range of change of the non-stationary parameter compared to the conventional system. At the same time, the speed and quality of transient processes are maintained at the level recommended for such systems.

Keywords: automatic control system, non-stationarity, adaptive controller, subordinate control system, electromechanical object, DC motor

The method of synthesis of control of a territorially distributed complex technical system with metrological support is presented. The synthesis method is based on the method for identifying the parameters of a stationary semi-Markov model of operation of a complex technical system, developed by the author, based on solving a system of algebraic equations, which includes the linear invariants of the semi-Markov stationary model identified in the article. The results of modeling changes in the parameters of a complex technical system are presented, taking into account the current state of the fleet of complex technical systems with an optimal choice of the interval between checks, rational use of redundancy and stationary maintenance. The obtained results can find application in the decision support system for managing a fleet of complex technical systems. by choosing the optimal interval between checks, using redundancy and carrying out stationary maintenance.

Keywords: park of complex technical systems, control synthesis method, system invariants

The paper presents a simulation of flight control of an unmanned aerial vehicle (UAV). A distributed control system is proposed that sequentially includes internal and external circuits to control the state of motion of the aircraft. The control efficiency of a cascade PD controller (proportional-differential) is higher than that of a traditional PID controller (proportional-integral-differentiating). A new cascade control algorithm with a PD controller is proposed. First, the dynamics of the UAV is modeled based on the Newton-Euler method, then the state of motion of the device is controlled by a distributed control system based on cascaded levels of proportional derivatives of the internal and external contours. The simulation results show that the controller, developed on the basis of proportional-derivative control speed of internal and external circuits, is able to achieve fast tracking of the position and orientation of the UAV in case of external disturbances and has good control quality. The developed algorithm has increased the control efficiency by 5-7% compared to the traditional PID algorithm.

Keywords: Unmanned Aerial Vehicle, PID controller, Cascade PD controller, Algorithm Optimization, UAV Control Algorithm

The article discusses the process of developing and modeling an impeller for an unmanned aircraft of the airplane type. Aerodynamic and strength calculations were carried out, key design parameters were determined, including the number of blades, engine power and choice of material. The developed models were created in the CAD system Compass 3D and manufactured by 3D printing using PETG plastic. Impeller thrust tests were carried out depending on engine speed, which allowed the design to be optimized for maximum efficiency.

Keywords: impeller, unmanned aircraft, aerodynamics, 3D modeling, 3D compass, additive technologies, thrust, testing, APM FEM

The article discusses modern machine learning algorithms used to detect and prevent denial of service (DoS) attacks. The work analyzes various approaches, such as traffic classification, system behavior anomaly, and network packet analysis, which allow the authors to develop an early warning system for possible attacks. The prospects for using machine learning to provide more reliable protection for network infrastructure are also discussed based on the results of the experiments. The results of the paper are of great scientific and practical value for specialists in cybersecurity and in modeling defense systems.

Keywords: information security, denial of service, machine learning, network traffic

This article examines the issue of increasing the performance and scalability of transactional systems using the example of a sharded blockchain architecture. Particular attention is paid to the use of a search query—based approach, a model in which the user's transactional intentions are processed asynchronously and aggregatively. This allows you to significantly reduce the load on the network and achieve high throughput without compromising the user experience. The proposed architecture is based on fully controlled smart accounts, embedded wallets, and third-party processing of user search queries through a specialized module. As a result, scalability is achieved that meets the requirements of high-frequency trading and automated decentralized applications. Key performance metrics and application scenarios outside the financial sector are presented.

Keywords: blockchain, distributed ledger, transactional systems, distributed systems