The integration of artificial intelligence into mobile devices is fraught with serious challenges, especially due to the limited resources available and the requirements for real-time data processing. The article discusses modern approaches to reducing computing costs and resources in systems for mobile objects with artificial intelligence, including model optimization, and computing allocation strategies for mobile platforms with limited resources.

Keywords: artificial intelligence, moving objects, lightweight models, peripheral models, hardware acceleration, knowledge distillation, quantization

The study addresses the problem of reducing the probability of emergency situations involving unmanned aerial systems. Accidents are regarded as outcomes of combinations of events that are individually of relatively low hazard. Causal relationships are represented by fault trees, in which the root node corresponds to an accident, the leaves correspond to basic events, and intermediate nodes describe their logical combinations. Accident scenarios are associated with the minimal cut sets of the fault tree. To identify accident prevention strategies, the concept of successful-operation paths is employed. Each such path is defined as a set of nodes having a non-empty intersection with all minimal cut sets. It is assumed that preventing all events included in a successful-operation path renders the development of accident scenarios impossible.
The study additionally accounts for the fact that the same flight mission may be executed along routes of differing complexity. Route complexity influences the cost estimates of measures aimed at preventing the events that form accident-related combinations. A model example is provided that includes the assessment of the complexity of two routes, a table of mitigation costs for basic events, and the selection of an appropriate successful-operation path for accident prevention. The proposed methodology is intended to reduce the probability of the realization of accident-inducing event combinations to an acceptable level while adhering to operational constraints and the mission-specific requirements of the flight task.

Keywords: unmanned aerial systems, emergency combination of events, fault tree, route complexity, logical-probabilistic security analysis

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 provides an overview of the most pressing issues arising from the widespread use of LED lamps in buildings and structures. This work is a precursor to a series of articles devoted to research in this field. The features of operation of electric lamps currently used in lighting systems are considered. The influence of lighting quality on human health and the effect of lamps on the electrical network is shown. The radiation spectra of lamps and their key difference from the natural solar spectrum are considered. The article presents the influence of the nature of the nonlinearity of the load of electric lamps on the quality of the power supply network and its individual components. The characteristic of the service life of energy-saving lamps is given.

Keywords: lighting, fixtures, lamps, lighting spectrum, nonlinear load, harmonic distortion, duration of operation, LED

The article presents the results of a comprehensive analysis of existing methods and approaches to prevent progressive collapse of reinforced concrete structures.  As part of the work, a systematic study was conducted of both the theoretical foundations of the phenomenon of progressive collapse and practical methods for ensuring structural stability. The theoretical basis of the work was made up of domestic regulatory and technical documents, as well as scientific publications and specialized research in the field of survivability of building structures. The practical significance of the research lies in the systematization of knowledge about methods of countering progressive collapse, which is valuable for design engineers working to create safe and reliable structures. The results of the study can be used to further improve approaches to the design of structures, taking into account the requirements of resistance to progressive collapse.

Keywords: progressive collapse, structural survivability, construction, reinforced concrete, large-panel building, monolithic reinforced concrete building, loss of stability, primary structural system, secondary structural system, volumetric and planning solution

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

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 article presents a comparative analysis of modern database management systems (PostgreSQL/PostGIS, Oracle Database, Microsoft SQL Server, and MongoDB) in the context of implementing a distributed storage of geospatial information. The aim of the study is to identify the strengths and limitations of different platforms when working with heterogeneous geospatial data and to evaluate their applicability in distributed GIS solutions. The research covers three main types of data: vector, raster, and point cloud. A comprehensive set of experiments was conducted in a test environment close to real operating conditions, including functional testing, performance benchmarking, scalability analysis, and fault tolerance assessment.
The results demonstrated that PostgreSQL/PostGIS provides the most balanced solution, showing high scalability and stable performance across all data types, which makes it a versatile platform for building GIS applications. Oracle Database exhibited strong results when processing raster data and proved effective under heavy workloads in multi-node architectures, which is especially relevant for corporate environments. Microsoft SQL Server showed reliable performance on vector data, particularly in distributed scenarios, though requiring optimization for binary storage. MongoDB proved suitable for storing raster content and metadata through GridFS, but its scalability is limited compared to traditional relational DBMS.
In conclusion, PostgreSQL/PostGIS can be recommended as the optimal choice for projects that require universality and high efficiency in distributed storage of geospatial data, while Oracle and Microsoft SQL Server may be preferable in specialized enterprise solutions, and MongoDB can be applied in tasks where flexible metadata management is a priority.

Keywords: geographic information system, database, postgresql, postgis, oracle database, microsoft sql server, mongodb, vector, raster, point cloud, scalability, performance, fault tolerance

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

Methods of increasing the efficiency of data analysis based on topology and analytical geometry are becoming increasingly popular in modern information systems. However, due to the high degree of complexity of topological structures, the solution of the main tasks of processing and storing information is provided by spatial geometry in combination with modular arithmetic and analytical assignment of geometric structures, the description of which is involved in the development of new methods for solving optimization problems. The practical application of elliptic cryptography, including in network protocols, is based on the use of interpolation methods for approximating graphs of functions, since a loss of accuracy may occur when performing many sequential mathematical operations. This problem is related to the features of the computing architecture of modern devices. It is known that an error can have a cumulative effect, so data approximation methods must be used sequentially as calculations are performed.

Keywords: elliptic curve, information system, data analysis, discrete logarithm, point order, scalar, subexponential algorithm

The article discusses the conceptual foundations of the transformation of the fire extinguishing management system based on the theory of complex organizational systems. The author substantiates the need to move from linear-hierarchical models to adaptive and networked structures capable of providing high stability and efficiency of response in conditions of uncertainty and dynamics of emergency situations. The analysis of the compliance of the fire extinguishing system with the characteristics of a complex organizational system has been carried out, contradictions between its complex nature and primitive control mechanisms have been identified, the causes and consequences of this paradox have been identified. Multi-agent digital platforms, the use of digital twins, situation centers, as well as the use of game theory methods to optimize resource allocation and decision support are proposed as ways to solve the identified problems.

Keywords: system approach, organizational system, firefighting, network structures, management, digitalization, transformation, game theory, optimization, criteria

The paper provides a comparative analysis of the accuracy of determining the coordinates of an aircraft using the classical correlation extreme algorithm (CEA) and the machine irradiation method based on a fully convolutional neural network (FCN) based on terrain maps. Two-dimensional correlated random functions are used as relief models.  It has been shown that CEA is effective with small amounts of data, whereas FCN demonstrates high noise immunity after training on representative samples. Both methods showed the dependence of the accuracy of determining the coordinates of the aircraft on the size of the reference area, the number of standards, entropy, and the correlation coefficient of the random relief.

Keywords: correlation-extreme algorithm, deep learning, convolutional neural network, aircraft guidance, digital terrain model, Fourier filtering, spatial correlation, noise immunity, algorithm comparison, autonomous navigation, hybrid systems, terrain entropy

The article forms the task of hierarchical classification of texts, describes approaches to hierarchical classification and metrics for evaluating their work, examines in detail the local approach to hierarchical classification, describes different approaches to local hierarchical classification, conducts a series of experiments on training local hierarchical classifiers with various vectorization methods, compares the results of evaluating the work of trained classifiers.

Keywords: classification, hierarchical classification, local classification, hierarchical presicion, hierarchical recall, hierarchical F-measure, natural language processing, vectorization

The work is devoted to the application of a linear Kalman filter (KF) for estimating the roll angle of a quadcopter with structural asymmetry, under which the control input contains a nonzero constant component. This violates the standard assumption of zero mathematical expectation and reduces the efficiency of traditional KF implementations. A filter synthesis method is proposed based on the optimization of the covariance matrices ratio using a criterion that accounts for both the mean square error and the transient response time. The effectiveness of the approach is confirmed by simulation and experimental studies conducted on a setup with an IMU-6050 and an Arduino Nano. The obtained results demonstrated that the proposed Kalman filter provides improved accuracy in estimating the angle and angular velocity, thereby simplifying its tuning for asymmetric dynamic systems.

Keywords: Kalman filter, quadcopter with asymmetry, optimization of covariance matrices, functional with mean square error and process time, complementary filter, roll and pitch control

The article is devoted to the analysis of the typological features of Orthodox churches. This topic is related to the spread of Orthodoxy throughout the world, which prompted the authors to analyze and systematize some of the features of decorative and artistic techniques of temple construction, as well as the canons of Orthodoxy in time, originating from Byzantine architecture.

Keywords: orthodox architecture, temple architecture, typological analysis, semantics of temples, Byzantine style, cross‑domed structure, tent temples, Russian patterned, Naryshkin style, architectural styles, sacred meaning, three-part division, domed completion