The article considers the prospects for the development of the territory of transformation of the natural and ecological framework of urban and rural settlements of the Vsevolozhsk municipal district in the Leningrad region in the zone of influence of the high-speed highway KAD-2. The analysis of the study territory was carried out, the ecological framework of the territory, the existing transport framework were considered, the urbanization nodes most susceptible to the influence of the high-speed highway were identified with the study of the urbanization process on the specified sections of the planned KAD-2 in different time periods with a threshold of 10 years, changes in natural components and transformation of functional zoning, development of the transport framework were studied and the problems of the territory were determined. The analysis made it possible to formulate the main conclusions for regional standards, for general plans of urban and rural settlements and for STP (territorial planning schemes).

Keywords: urban development, natural and ecological framework, high-speed highway KAD-2, territorial planning, urbanization nodes

The paper presents an analysis of experimental data reflecting the influence of the loading rate on the strength and deformation characteristics of concrete of class B25 under conditions of central compression. 12 prismatic samples with dimensions of 100×100×400 mm, distributed in three series with different load application rates, were prepared and tested for the study. Statistical data processing, including analysis of variances and the construction of regression models, allowed not only to predict the behavior of concrete under various loading conditions, but also to confirm the theoretical prerequisites associated with the dynamic hardening of the material. The high values of the correlation coefficients (up to 0.9943) and determination (up to 0.9922), as well as the Fisher criterion, which significantly exceeds the tabular thresholds, characterize the high reliability of the results obtained, indicating an increase in concrete strength with an increase in loading speed and a simultaneous decrease in its deformability. The derived dependences can serve as an experimental basis for the development of a nonlinear deformation method for calculating bent and non-centrally compressed reinforced concrete structures made of concrete of this class (B25), subject to short-term impacts, including classical static loads, as well as dynamic loads of medium duration, characteristic of the operating conditions of structures under the influence of factors such as the movement of overhead cranes along crane beams or the passage of fire trucks along the overpass. The results obtained contribute to a more accurate consideration of dynamic effects in the design and calculation of reinforced concrete structures operated in such conditions.

Keywords: experiment, concrete samples, central compression, loading rate, strength, marginal relative deformations, dynamic hardening, correlation and regression analysis

The relevance of accurately predicting fat content on the surface of meat products is driven by the need to ensure effective quality control in the food industry. This paper presents an efficient method for detecting and quantitatively assessing fat content on meat surfaces based on the use of color segmentation in the HSV color space. The method exploits differences in the color characteristics of fat and muscle tissues to effectively segment images of meat samples, calculate the percentage of fat, and analyze its spatial distribution. The simplicity and robustness of the algorithm make it a promising solution for real-time automated quality control systems, offering ease of use and high computational efficiency.

Keywords: computer vision, color segmentation, HSV color space, image processing, OpenCV, Flask, quality control automation

This paper provides a comprehensive comparative analysis of the performance of modern deep learning architectures for the object detection task. The research focuses on two main families of models: transformer architectures, including DETR (DEtection TRansformer) and its advanced variants such as RT-DETR (Real-Time DETR), D-FINE (DETR with Fine-grained Distribution Refinement) and DEIM (DETR with Improved Matching), as well as popular single-stage detectors of the YOLO (You Only Look Once) family, in particular, on the YOLOv11 and YOLOv12 versions. The models are evaluated on a specialized set of image data, which contains various defects of solar panels and consists of five classes, which makes it possible to identify the strengths and weaknesses of each architecture in the context of specific application tasks.

Keywords: solar panels, neural networks, detection, transformers, single-stage detectors, pattern recognition

Support for decision-making in response to forest fires is a complex multi-criteria process. This article provides a comparative assessment of the validity of decisions made using three decision support tools. The analytic hierarchy process, analytical network method, and TOPSIS method were used for the assessment. The uncertainty, volume, and degree of heterogeneity of the data taken into account when making decisions were considered as validity criteria. The conducted studies have proven the possibility of using the intelligent decision support system developed by the authors to respond to forest fire threats, as well as increasing their validity compared to other tools.management decisions. The validity of management decisions is understood as an objective representation of the state of the external environment (uncertainty of data and decisions, the volume of processed data, the dimension of the feature space) from the point of view of the problem being solved by the decision maker. The evaluation of tools allows you to determine the preference of tools in terms of the criteria under consideration.

Keywords: multi-criteria assessment, forest fires, validity, intelligent decision support system

The article explores modern approaches to the integration of image processing algorithms and sensor equipment onboard unmanned aerial vehicles (UAVs) for monitoring and mitigation of emergencies affecting railway infrastructure. The research focuses on methods for efficient interaction with high-resolution optical cameras, LiDAR systems, and GPS modules, as well as on the use of distributed and cloud computing technologies for rapid data processing. Special attention is given to adaptive data compression techniques, caching strategies, and asynchronous message queues, which ensure reliable transmission under limited or unstable communication channels.
The work demonstrates practical integration scenarios using the DJI Mini 4 Pro UAV and the WebODM photogrammetric platform, showing a reduction of preliminary processing time from 45 to 6 minutes and an improvement in georeferencing accuracy from 7.8 m to 1.3 m through the use of GPS-EXIF metadata. Point cloud optimization methods, such as Voxel Grid filtering and Statistical Outlier Removal, are shown to decrease file size from 1.2 GB to 210 MB and reduce processing time from 52 to 17 minutes with minimal loss of accuracy.
The study highlights that combining onboard sensors with advanced processing pipelines significantly improves the timeliness, reliability, and accuracy of railway infrastructure assessments after emergencies. The proposed solutions enable automation of geospatial data workflows, enhance operational decision-making, and optimize resource allocation for recovery operations. The findings are relevant for the development of UAV-based monitoring systems in transportation, urban planning, and critical infrastructure protection.

Keywords: UAV, data transfer, distributed computing, LiDAR, WebODM, DJI Mini 4 Pro, infrastructure monitoring, adaptive compression, message queue

The article is devoted to the analysis of methodological approaches to the definition and assessment of the psychofunctional state of a person. In connection with the need to improve the reliability of human-machine systems, the study of the psychofunctional state of a person controlling a dynamic object is of scientific interest, since to create reliable human-machine systems it is necessary to take into account the reliability factors of technical means and the human factor as well. The analysis of methodological approaches showed that to solve problems dedicated to increasing the reliability of "human-machine" systems, it is advisable to use a systems approach that considers a person not as an independent subject, but as an element of the system. The systems approach has a broad methodological base, allows us to study the psychofunctional state of a person in dynamics.

Keywords: psychofunctional state, functional state, systems approach, energy approach, behavioral approach, phenomenological approach, structural-integrative approach, electrophysiological methods, control of a dynamic object

The work is devoted to the problems of assessing and predicting the reliability of photovoltaic generation devices. The purpose of the work is to identify factors affecting the volume of electricity generation, as well as to build models and procedures for predicting the reliability of the panels during their use depending on these factors. An overview of the types of solar power plants and the photovoltaic panels used is given. An analysis of the factors affecting their reliability is performed, on the basis of which a hierarchy of fuzzy factors related to each other by fuzzy production rules is built. It is proposed to use a statistical two-parameter Weibull model to predict the reliability of the panels. An algorithm for neuro-fuzzy tuning of the reliability forecasting model depending on the factors considered is developed and software implemented, which can be used to create information and analytical systems for decision support in the design and operation of solar power plants.

Keywords: solar energy, photovoltaic panel, reliability prediction, statistical model, neuro-fuzzy network

Integration of heterogeneous field data and remote sensing information is a key and necessary step in modern geological exploration. This article proposes a method based on the creation of a regular spatial grid, which enables the efficient interpolation and integration of point, linear, and polygonal data represented in both vector and raster formats. The primary objective is to generate a structured and enriched dataset suitable for training predictive models, including neural networks. The proposed approach involves transforming geospatial data to ensure their accuracy and consistency within GIS environments. This method provides a reliable foundation for identifying prospective areas with high mineral potential and highlights the importance of rigorous data preparation in spatial modeling and analysis processes.

Keywords: reservoir exploration, data integration, interpolation, spatial grid, geochemistry, spatial modeling process, remote sensing, GIS

The purpose of the study is to develop a platform that allows for various types of checks to identify weaknesses in the subsystems of unmanned automated systems.
Research methods: when developing the platform, a methodology based on the construction of ontological models was used, which made it possible to link the structural and functional characteristics of unmanned automated systems with threats and vulnerabilities, as well as with attacks on such systems. The process parallelization method was used to scan radio frequency ranges. The decision-making system is based on risk assessment methods.
Research results: the platform allows for optimizing the security testing process of unmanned automated systems. For automated testing, a database is used that includes a catalog of structural and functional characteristics, threats, vulnerabilities, and attacks. The platform can determine which types of structural and functional characteristics correspond to the vulnerabilities of unmanned automated systems. A system consisting of individual components (a sensor for scanning unmanned automated systems, an intelligent system for active analysis of unmanned automated systems). The sensor for scanning unmanned automated systems is implemented as a small-sized device. The system of intelligent active analysis of unmanned automated systems is implemented as software.
The scientific novelty lies in the development of a concept for a system for analyzing the safety of unmanned automated systems based on ontological models and radio frequency range analysis to identify system vulnerabilities during pre-operational checks.

Keywords: data analysis, statistics, attacks, risks, unmanned automated systems

An experimental study of the ultimate deformations of a three-component composite of FeNiCu metal powders during rolling with different reductions is conducted, which allows us to estimate the parameters of the material's plasticity, and thereby exclude various manifestations of destruction (cracks, ruptures, delamination, etc.). Depending on the magnitude of the deformation and the proportional content of individual components, the relative density of the composite is determined. The results will be in demand in the development of technological processes for pressure treatment of composite materials, in particular, the production of powder rolled products of a given density

Keywords: composite, pseudoalloy, pressure treatment, rolling, plasticity, compression, destruction, delamination, relative density of composite

The article presents the application of fuzzy modeling to solve the systemic task of qualitative assessment of the properties of land plots by an expert method using fuzzy modeling. The set of factors by which the suitability of the plot is estimated depends on the goals of the development project. The technique includes the decomposition of the model into additive models of internal and external factors and a combining multiplicative model, which reduces the dimensionality of the task of assessing the properties of the plot. At the second stage, a fuzzy model of expert assessment of the properties of land plots is formed. It includes a fuzzyification block using linear membership functions, max-min fuzzy inference technology, and defuzzification using the height method, which most adequately translates fuzzy expert assessments into clear numerical (point) values. At the third stage, the contribution coefficients of each factor in the assessment of the properties of plots are determined using the hierarchy analysis method and the fuzzy pairwise comparison scale.

Keywords: land plot, individual assessment, expert method, fuzzy modeling

Urban water supply systems in Iran and Turkey are facing increasing pressure due to leakages, inefficient resource use, and lack of a proactive management approach. This study proposes an integrated engineering model combining Internet of Things (IoT) sensors, a loss calculation algorithm (ΔQ), and a multi-criteria demand analysis (MCDA) method to identify, prioritize, and fix water leaks in urban infrastructure. The developed system, named Smart Leak, was tested in pilot areas of Tehran (District 3) and Istanbul (Beyoğlu District) where real-world data collection and expert assessment were carried out. The model includes a digital monitoring architecture, dashboards, an alert system, and integration with Google Sheets and App Sheet. The results showed a 27% reduction in leak detection time, improved prioritization accuracy, and improved resource allocation efficiency. In addition, the MCDA–LCA criteria heat map highlighted the priority of environmental factors in decision making. The developed approach demonstrates scalability, adaptability and suitability for application in cities experiencing water shortages. The system can be integrated into smart city platforms for sustainable water management.

Keywords: sustainable development, environmental project management, socio-economic effects, renewable energy, circular economy, waste-to-energy recycling, urban infrastructure, Tehran, Mashhad, Isfahan, Shiraz, Istanbul

The article shows the importance of the role of clinical engineering departments to ensure high-quality comprehensive control of the state of medical equipment at all stages of its life cycle. The main resource of such departments is the competence resource of clinical engineers and their working time resource. In order to rationalize the use of these resources, we systematized the causes of failures of medical devices. Based on this, a number of general metrics were developed that characterize the adaptability of clinical engineering departments to the conditions of a specific medical institution, such as the competence profile of the department and the profile of the need for technical maintenance of medical devices. The use of these data made it possible to formalize the algorithm for managing the clinical engineering department, aimed at maximizing the useful use of the human capital of these departments.

Keywords: clinical engineering, clinical engineer, time budget, performance metrics, medical device maintenance

The article is a continuation of the research on increasing the durability of heavy concrete and extending the life cycle of structures. The objective of the study is to determine the effect of the action of microsilicon and trepel additives introduced into the concrete mixture on increasing the strength characteristics of concrete. A control composition of a given concrete class in terms of strength B60, class F400 frost resistance and W20 water resistance, with the addition of superplasticizer ST 5.0, was selected. A comparative analysis of various concrete compositions was carried out in order to increase their strength characteristics and density. As a result of experiments, it was found that the introduction of 5% silica or trepel, as well as their combinations, helps to achieve a given strength class of B60 and increase the density of concrete. The use of superplasticizer ST 5.0 ensures the necessary mobility of the mixture without increasing the water-cement ratio, which improves the durability and performance of the materials. The results obtained allow us to recommend additives for the production of high-strength concrete with improved technical performance.

Keywords: silica, concrete strength, trepel, concrete mix, superplasticizer, water-cement ratio, heavy concrete, active mineral additives, concrete, MCU-85

The article proposes a concept of spatially-oriented risk management in territorial systems, taking into account the relationship between threats, development goals and measures of influence. The model is based on the geographical distribution of factors and assumes scenario analysis of spatial changes. Particular attention is paid to integration with regional geoportals as means of visualization, data aggregation and decision support. The role of risks not only as constraints, but also as sources of transformation is emphasized. The presented approach is aimed at increasing the adaptability of management, coordinating spatial interests and developing an analytical infrastructure capable of supporting strategic planning in the context of natural and socio-economic instability.

Keywords: geographic information system, geoportal, risk analysis, spatial data, geosystems, geographically distributed organizational system

The majority of electrified railways, as well as the routes of external power supply overhead lines, automatic block lines and longitudinal power supply lines, are located in areas with a sharply continental climate, where climatic conditions contribute to the possibility of ice formation. The article examines the effectiveness of anti-icing measures on power supply devices of electrified railways. The results of calculation of the anti-icing scheme during preventive heating of the contact network taking into account its homogeneity by equalizing current are presented. The success of application of preventive heating for the studied section is analyzed.

Keywords: AC traction network, ice control, ice melting, preventive heating, operating voltage, equivalent circuit, selection of parameters

This paper addresses the limited accuracy of existing automatic systems for detecting deepfake audio content in real time. A solution is proposed to increase the efficiency of detecting signs of deepfake use by improving neural network models and algorithms for analyzing audio recordings of human voices. An algorithm and corresponding software for a voice attack detection system have been developed. For training and testing, datasets were created containing real voice audio recordings and deepfake audio samples. Evaluation on a real-world test set demonstrated an accuracy rate of 83%, confirming the effectiveness and practical applicability of the proposed solution in combating audio deepfake threats.

Keywords: deepfake, speech audio signal, machine learning models, convolutional neural network, vishing

During the 2024-2025 academic year, the Department of Organization and Support of Educational Activities at SFU organized a professional development program for teachers of fundamental disciplines called "Development and Implementation of Fundamental Disciplines in a Modern University." The goal of the program was to create an environment that would allow a teacher of a fundamental discipline to acquire the necessary skills to improve their professional competencies, design, and implement the discipline at a modern level. The main principles of educational design in the development of a fundamental discipline are based on the idea that the content, format, and technologies should work together to achieve the desired outcome. One of the modern active learning formats is the workshop. This paper presents the concept of a workshop that can serve as an alternative to the laboratory practice in the discipline of Physics, which is the core of modern engineering education. The article presents the principles of the workshop, its technical and material support, as well as the structure of the two-semester course "Physics". It describes an approach to the formation of students' general professional competencies through the implementation of practical tasks and case methods.

Keywords: forms of education, workshop, physics, electromagnetic field, oscillations and waves, general professional engineering competencies, laboratory practice, case studies

Inductively coupled plasma) pheroidization is currently considered the most effective technology for producing high quality powder. However, there is still no clear understanding of the process. This review examines the process in detail. We identified the main reasons for the low spheroidization ratio and agglomeration. The spheroidization ratio is decreased due to high frequency argon flow oscillations near the nozzle. These flows are capable of blowing some of the powders to the walls, where the flame cannot heat and spheroidize them. Agglomeration is caused by insufficient surface melting of large powder particles. In this case, fine powders do not receive enough energy during their merging to be melted and distributed evenly on the surface.

Keywords: spheroidization, powder preparation, additive technologies, spheroidization by inductively coupled plasma, durability