The article is devoted to the study of the problem of estimating unknown parameters of linear regression models using the least absolute deviations method. Two well-known approaches to identifying regression models are considered: the first is based on solving a linear programming problem; the second, known as the iterative least-squares method, allows one to obtain an approximate solution to the problem. To test this method, a special program was developed using the Gretl software package. A dataset of house prices and factors influencing them, consisting of 20640 observations, was used for computational experiments. The best results were obtained using the quantreg function built into Gretl, which implements the Frisch-Newton algorithm; the second result was obtained using an iterative method; and the third result was achieved by solving a linear program using the LPSolve software package.

Keywords: regression analysis, least absolute deviations method, linear programming, iterative least squares method, variational weighted quadratic approximation method

For accurate modeling of the stress-strain state of the lithospheric plate, it is necessary to correctly define boundary conditions that reflect the interaction with the geological environment. The Dirichlet edge problem, in this context, involves setting displacements at the boundary of the calculated region. The problem is that the true displacements at the craton boundary are generally unknown and can change over time under the influence of tectonic processes and load changes.

Keywords: boundary conditions, stress-strain state, mathematical modeling, model, lithospheric plate, finite element method, geotectonics, stretching, compression, computer modeling, asthenosphere

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

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

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

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

Many problems related to high-speed interaction with soil represent an interesting area of ​​research. For example, the fall of heavy objects on the ground surface not only creates a dynamic impact effect, but can also serve as an effective method of soil compaction under future foundations of buildings and structures. This process, along with the penetration of objects into the soil, poses new challenges for researchers. The most accurate results in these complex scenarios can be obtained by using a nonlinear dynamic formulation, which allows for a deeper understanding of the interaction mechanisms and ensures the reliability of structures under extreme loads. This requires using appropriate modeling approaches. In addition, under such an impact, the soil exhibits the properties of a liquid or gas, so it is necessary to use special soil models. The paper presents the main basic relationships and main parameters of soil models required for dynamic calculations of soils, which can be useful in modeling the operation of a soil massif in modern software packages.

Keywords: physical nonlinearity, damping, soil, foundation of buildings and structures, dilatancy, soil compaction, pore pressure, soil density, deformation modulus, numerical soil model

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 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

This paper proposes a low-cost digital toolchain based on SketchUp-ComfyUI collaborative workflow to validate its technical feasibility in modern Functionalist architectural design. The research establishes a tripartite methodology comprising "geometric modeling - parameter extraction - rendering verification": initially developing core parameters through fundamental geometric models (cubes, cylinders) in SketchUp, followed by constructing visual workflows via ComfyUI's nodular interface for Functionalist architectural rendering. Key findings demonstrate: (1) Total time expenditure for residential unit prototyping and rendering reaches 26 minutes, meeting rapid design requirements; (2) ComfyUI accurately recognizes SketchUp geometries through AI parametric control mechanisms, yet constrained by SD training data limitations (Functionalist cases constituting merely 12.7%), exhibiting 55% semantic hallucination rates in massing generation while enabling reverse-engineering analysis of rendering visual semantics; (3) This toolchain achieves zero-cost implementation on standard computing hardware, pioneering democratized design approaches for Functionalist architecture.

Keywords: toolchain, functionalist architecture, SketchUp, ComfyUI, collaborative workflow, low-cost design, efficacy verification, parametric design, architectural rendering verification, low-cost computational design

Predictive analytics is one of the most important areas of data analysis, which allows predicting future events based on historical data. The relevance of predictive analytics in the modern world is due to the rapid development of technology, the growth of data volumes and the growing need for informed management decision-making. The article discusses the main approaches such as regression models, time series, decision trees, clustering methods and neural networks, as well as their advantages and disadvantages.

Keywords: predictive analytics, regression models, time series, decision trees, neural networks, clustering, big data, predictive analytics methods, big data analysis, forecasting

The article presents the development of an analytical hydraulic model of the side branch pipe of a three-way fire branch DN80. The relevance of the work is due to the need for accurate hydraulic calculation of fire water supply systems, the effectiveness of which directly depends on the correct assessment of pressure loss in the fittings. The model is based on the method of element-by-element calculation, which takes into account local hydraulic resistances in areas with a sharp change in the flow geometry. The model includes losses at four bends (three at 45° and one at 90°), a straight-flow valve, and sudden expansion and contraction sections. The contribution of linear head losses, similar to the central branch pipe, was considered insignificant, accounting for only about 6% of the local losses. This confirms the key role of local resistances in determining the overall head loss in this element. The model was verified by comparing the calculated data with the results of experimental studies. It has been established that the discrepancy between the theoretically calculated value of the head loss (6.86 m) and the experimental value (6.97 m) is minimal, with a difference of only 1,6 %, indicating the high accuracy and adequacy of the developed model. The key practical result of the study is the calculation of the total coefficient of local resistances for the lateral branch pipe of the fire branch, which was found to be ζ = 3.4. This value can be directly used for simplified and accurate hydraulic calculations of pump-hose systems with three-way branches.

Keywords: Model, fire three-way junction, hydraulic resistance, head, pressure, flow rate

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

In this paper, an inverse wavelet image transform method for JPEG XS format is proposed. The said format uses Le Gall wavelet filter and the lifting scheme is used as a wavelet transform. This method of wavelet processing of images and video signal has low computation speed. To improve the computation speed, it is proposed to use the Winograd method as this method allows parallel processing of groups of pixels. The paper analyses the impact of accuracy in obtaining high quality image for fixed point format computation. The simulation results show that processing of 2 pixels using Winograd's method is sufficient to use 3 decimal places to obtain high quality image. When processing 3 and 4 pixels of the image it is sufficient to use 7 decimal places each. When processing 5 pixels of the image it is enough to use 12 decimal places. A promising direction for further research is the development of hardware accelerators for performing the inverse discrete wavelet transform by the Winograd method.

Keywords: inverse discrete wavelet transform, Le Gall filter, Winograd method, image processing, digital filtering, JPEG XS

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 main maintenance of a diversification of production as activity of subjects of managing is considered. being shown in purchase of the operating enterprises, the organizations of the new enterprises, redistribution of investments in interests of the organization and development of new production on available floor spaces. The most important organizational economic targets of a diversification of management are presented by innovative activity of the industrial enterprise.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production

The article presents the results of the development of an algorithm and a desktop application for recognizing Russian-language handwritten text in images using computer vision and deep learning technologies. Classical and modern recognition methods have been studied and an algorithm has been developed and implemented that ensures 71% recognition accuracy. The application allows the user to upload images receive digitized text and save the results in his personal account. The software implementation includes a training block for the model with an assessment of accuracy and completeness metrics. The application meets all the set requirements providing ease of use and functionality.

Keywords: deep learning, handwritten text, image, data, model training, computer vision, feature extraction, CTC, RNN, CNN, CRNN

In this article, an analysis of the main methods for solving the linear cutting problem (LCP) with the criterion of minimizing the number of knife rearrangements is presented. The linear cutting problem in its general form represents an optimization problem that involves placing given types of material (rolls) in such a way as to minimize waste and/or maximize the use of raw materials, taking into account constraints on the number of knives, the width of the master roll, and the required orders. This article discusses a specific case of the problem with an additional condition for minimizing knives' changes and the following approaches for its solution: the exhaustive search method, which ensures finding a global optimal solution but can be extremely inefficient for problems with a large number of orders, as well as random search based on genetic and evolutionary algorithms that model natural selection processes to find good solutions. Pseudocode is provided for various methods of solving the LCP. A comparison is made in terms of algorithmic complexity, controllability of execution time, and accuracy. The random search based on genetic and evolutionary algorithms proved to be more suited for solving the LCP with the minimization of waste and knife rearrangements.

Keywords: paper production planning, linear cutting, exhaustive search, genetic algorithm, waste minimization, knife permutation minimization

The article contains the results of stress analysis in dangerous sections of a single-span steel box beam made of two channels, strengthened with two metal strips welded at the top and bottom between the channels, with different geometric characteristics of the strengthened elements. The results of a numerical experiment of strengthened beams are presented. According to the results of the numerical experiment, it was found that equalization of stresses in dangerous sections allows to reduce the material consumption of the structure in comparison with beams selected according to the assortment for the required moment of resistance.

Keywords: steel beam, load-bearing capacity, stresses, displacements, finite element method, structural strengthening

Numerical analysis of stress-strain state of monolithic slab with account of corrosion damage of concrete and reinforcement of compressed and tensile zones in the span part of the slab in PC LIRA-SAPR is carried out. 6 variants of corrosion damage depending on the area of spreading and degree of degradation are considered. The calculations have been carried out taking into account physical and geometrical nonlinearity. The peculiarities of structural deflections changes at different variants of corrosion damage and loading levels of the floor slab have been revealed. Redistributions of forces in spans and on supports arising at local changes of concrete and rebars stiffnesses are analyzed. No structural failure stage has been identified for the adopted design characteristics and damage variants.

Keywords: monolithic slab, corrosion damage of reinforced concrete, numerical analysis, redistribution of forces, bearing capacity, deformation capacity

The article provides a brief analysis of obtaining data using remote sensing of the Earth and ground-based instruments to solve the problem of optimizing the production of crop products on heterogeneous agricultural land. The article proposes models for optimizing the production of crop products under average conditions and taking into account adverse extreme events. The developed models of parametric and stochastic programming meet the requirements of modern information support for agricultural producers.

Keywords: monitoring, data, optimization, deterministic model, multi-level parametric model, stochastic model, crop production

Modeling natural convection from steel panel radiators presents a significant scientific and technical challenge. When heating the radiator's vertical surface, a boundary layer of warm air forms and ascends along the wall. Flow remains typically laminar in the lower section, but as the boundary layer develops, it becomes unstable and transitions to turbulence. Beyond temperature head, transition conditions depend critically on heater geometry. Height, panel count, and vertical finning elements directly impact convective flow formation, where optimized geometry promotes early laminar-turbulent transition and intensified convection. While heat transfer is conventionally evaluated through dimensionless correlations (with Grashof numbers near 10⁹ serving as critical transition thresholds for vertical surfaces, corresponding to ~70°C temperature head at 0.5–1 m height), real-world radiator operation maintains laminar flow in lower zones with upper-height transition to turbulence – a process indeterminable via correlation methods. This study proposes a CFD simulation methodology calibrated against laboratory tests conducted per GOST R 53583-2009, enhancing computational result reliability. The calibrated numerical model ensures high-precision prediction of integral heat emission characteristics. CFD implementation enables preliminary radiator behavior analysis without physical prototyping through parametric variation of geometry and thermal properties. The model is readily parameterized by panel dimensions, finning configuration, and material/medium properties, ensuring computational repeatability across configurations. The proposed calibration method (achieved by imposing experimentally measured heat flux values per GOST R 53583-2009) enhances accuracy in predicting radiator's integral performance metrics and improves model-experiment alignment. This approach guarantees computational reproducibility and flexibility in simulating diverse designs (panel sizes, fin arrangements, materials). Validation challenges persist: Absence of experimental temperature/velocity fields complicates mesh sensitivity analysis, while single-dataset calibration risks model overfitting. Nevertheless, this methodology proves strategically valuable for transitioning toward digital certification of heating devices, as it substitutes physical testing with numerically derived integral parameters of comparable accuracy.

Keywords: heating devices, natural convection, free air flow, heat transfer efficiency, laminar-turbulent transition

Deviation of forestry equipment from the designated route leads to environmental, legal, and economic issues, such as soil damage, tree destruction, and fines. Autonomous route correction systems are essential to address these problems. The aim of this study is to develop a system for deviation detection and trajectory calculation to return to the designated route. The system determines the current position of the equipment using global positioning sensors and an inertial measurement unit. The Kalman filter ensures positioning accuracy, while the A* algorithm and trajectory smoothing methods are used to compute efficient routes considering obstacles and turning radii. The proposed solution effectively detects deviations and calculates a trajectory for returning to the route.

Keywords: deviation detection, route correction, mobile application, Kalman filter, logging operations

The article is devoted to numerical modeling of corrosion-damaged reinforced concrete columns under low-cycle horizontal loading by static load in LS DYNA software package. The comparison of numerical calculation and experimental data on research of strength of reinforced concrete columns with corrosion damage of reinforcement under low-cycle horizontal loading is carried out.

Keywords: corrosion, reinforcement, seismics, reinforced concrete, corrosion damage, low-cycle strength, numerical modeling