Purpose.of reseach is to identify zones of greatest stress under the action of internal static pressure, assess the limit states of the structure, and check its compliance with strength criteria.

Methods. This article uses the finite element calculation of a welded structure of an industrial gas meter in the APM FEM software package for KOMPAS-3D v23.0.0.8. The structure was modeled in the KOMPAS V23 program, the welds of the structure according to GOST 16037-80-C17-ZP and GOST 16037-80-U19-ZP were modeled using the "Permanent Joints" application. In places where welds are located, the transformation of welds into a body was applied to take them into account when generating a finite element mesh.

Results. Based on the analysis, it can be stated that the structure has a high margin of safety and rigidity under both standard and forced loads. The permissible values of displacements and safety factors confirm its reliability and operability under real operating conditions, including test modes. Thus, the structure can be recommended for manufacturing and subsequent testing without the need to make changes to its geometry or welding method.

Conclusion. The numerical strength analysis of the welded structure of an industrial gas meter housing, performed using the APM FEM module for KOMPAS-3D, confirmed the structural integrity under all pressure conditions, including test pressure up to 30 N/mm². The obtained von Mises stress values and safety factors meet the requirements of applicable regulatory standards, including GOST 34233.1–2017 and PB 03-576–03. The total displacements remain within acceptable limits, indicating high stiffness and the absence of plastic deformation risks during operation.

Purpose of reseach. The article presents the results of a study of a water heating system based on wall units with capillary tubes. This technology is a system in which a heat carrier (water) circulates through multiple capillary tubes that are uniformly embedded in building blocks or panels of walls and ceilings. Such systems are already used not only for heating, but also for cooling rooms, creating a comfortable microclimate. An analysis of studies of similar heating systems was carried out. The main advantage of such systems is their energy efficiency. Capillary systems can reduce the overall consumption of heating systems and, consequently, operating costs. However, at the moment, the introduction and use of units with capillary tubes requires additional research and development, especially in terms of universalizing technological solutions, reducing the cost of materials and simplifying installation. To obtain theoretical results, a model of a capillary system embedded in a wall was constructed. The system has been divided into several sections, which should reduce pressure losses. The hypothesis that capillary heating systems can ensure uniform heat distribution at a relatively low temperature of the coolant has been tested. The paper presents the results of a thermal calculation: a graph of changes in the temperature of the coolant when moving through the system, a graph of changes in pressure in the system, and patterns of temperature changes on the wall surface. The analysis of the data obtained was carried out and conclusions were drawn about the effectiveness and expediency of using such systems. This work can be used for further research of capillary water heating systems.

Methods. To build a wall block model and perform thermal calculations, the SolidWorks program and the built-in FlowSimulation tool were used.

Results. The study made it possible to obtain the dependences of temperature and pressure changes in the capillary system, as well as the pattern of temperature changes on the wall surface.

Conclusion. The results of the study showed that the heating system based on capillary tubes allows for uniform heating of the wall surface, which in turn will allow for uniform heating of the indoor air. This result is achieved at a low temperature of the coolant. In addition, the separation of the system into separate sections proposed by the authors makes it possible to reduce pressure losses.

Purpose of research. Evaluation of the effectiveness and optimization of the developed local ventilation device using modern fluid modeling methods.

Methods. The study considers methods for modeling a complex technical system – an industrial bath, with separate functional units for trapping harmful evaporating substances and pressing them to the surface of the solution – a double-side suction and a boost system, respectively. For each subsystem, which cannot be described by a single mathematical apparatus, methods of complex potential of gas flows and computer modeling were used, followed by comparison and search for optimal results.

Results. The maximum height of trapping harmful substances above the surface of the bath solution is found, the condition for which takes into account the ratio of the amount of air evaporated from the bath solution and the total amount of air removed by the on-board suction. For the constructed model of an exhaust device from a bath for carrying out technological operations with metals, according to the developed utility model, a study of the movement of air flows was conducted and the effectiveness of the developed exhaust on-board suction was analyzed using computer modeling.

Conclusion. The study showed that the effectiveness of a complex supercharged local exhaust ventilation system, determined by the spread of harmful substances in the work area, can be assessed and improved using modeling methods that allow you to change the design of on-board suction systems, calculate and select the parameters of the elements, establish and analyze the principle of operation of the device model as a whole, affecting the effectiveness of removal of harmful substances.

Purpose of research. The aim of the work is to study the mathematical model of the automatic control system (ACS), consisting of a regulator and a control object for execution on a microprocessor system with support for a realtime operating system. The structure of the ACS, the coefficients of transfer of the transfer functions of the links, time constants and transport delays are adopted as variable parameters. The output data are presented in the form of transient processes. The task is to compare the analytical and numerical methods for software implementation of the mathematical model of the ACS using a programmable logical controller (PLC) as part of a test bench with a microprocessor electric drive. The objective is to compare analytical and numerical methods for software implementation of a mathematical model of automatic control system using a programmable logic controller (PLC) as part of a test bench with a microprocessor electric drive.

Methods. The methods of system analysis, automatic control theory, numerical methods of differentiation and integration, differential and difference equations were used.

Results. Practical recommendations for choosing a PLC when solving problems of modeling objects and control systems based on the inertia of the links included in the control loop. The relative error (integral, for the ACS as a whole) and the fulfillment of the requirement for the stability of the digital model are used as an evaluation criterion.

Conclusion. The studies have shown that for canonical ACS with 1st and 2nd order objects and transport delay with certain criteria, such as digital model stability and relative error (integral), there is a connection between the speed of the simulated ACS links and the PLC performance. Additional studies are required for practical confirmation of the obtained results.

Purpose of research. The purpose of this research is to improve the accuracy of monitoring the condition of the road surface of an urban agglomeration by analyzing accelerometer signals in real time based on the developed integrated method for assessing evenness indicators.

Methods. The following methods were used in this research: analysis of existing methods for monitoring road surface conditions; methods and algorithms for filtering accelerometer signal noise (a model for preprocessing accelerometer signals was developed and described, including a Butterworth low-pass filter, a median filter, an exponential smoothing method, and calculation of threshold values); fuzzy logic algorithms (a model for classifying road surface conditions into 5 categories was developed); simulation modeling (test runs were conducted using the author's simulation model developed in the Unity environment).

Results. The presented method provides automated monitoring of the road surface condition with an accuracy of at least 93%, and the possibility of integration into the smart city system. The method allows monitoring the road surface condition in real time, and the classification of the road surface condition is of a recommendatory nature for road repairs. The prospects of the research include conducting a full-scale experiment, visualizing data with reference to a city map, and using trajectory clustering algorithms to determine the general trajectories of a vehicle when going around uneven surfaces.

Conclusion. Based on the developed method of monitoring the condition of the road surface, an integrated assessment of the compliance of the accuracy of monitoring the condition of the road surface of at least 93% was obtained.

Purpose of research. Development and experimental evaluation of a Bayesian classification algorithm for the person re-identification task using images from multiple surveillance cameras. The study aims to improve identification accuracy through integrating features derived from facial and silhouette images.

Methods. The proposed algorithm utilizes a Bayesian classification model based on multivariate normal distributions of features. These features are extracted by neural encoders built on the Vision Transformer architecture and trained using the ArcFace loss function. Integration of modality-specific features is performed by computing logarithmic posterior probabilities of class membership. The effectiveness of the method was evaluated using the open CUHK03 dataset, quantitative analysis via ROC curves, and feature space visualization using the t-SNE method.

Results. The algorithm demonstrated high classification performance: precision of 95.65% on CUHK03, up to 97.7% on Market-1501, and 89.2% on MARS. ROC analysis confirmed strong class separability, while t-SNE visualizations showed compact and well-defined clusters. The algorithm is deterministic, robust to noise, and scalable to larger datasets.

Conclusion. The developed Bayesian classification algorithm has proven its effectiveness and feasibility for person re-identification tasks in intelligent video surveillance systems. Its advantages include high accuracy, interpretability, and potential for integrating additional features. Future research should focus on incorporating extra attributes and evaluating algorithm performance on significantly larger and more diverse datasets..

Purpose of research. The purpose of this study is to develop and substantiate a methodology for the formation of an individual educational trajectory in online courses by analyzing the educational activity of students and their level of academic achievement.

Methods. Hidden Markov models are used in the work, which are well combined with modern machine learning approaches, which enhances their potential in terms of analytics and accurate selection of educational trajectories. The key characteristics of students' learning activity that can be used as observations are highlighted, and a suitable number of hidden states corresponding to different levels of students' academic performance are selected.

Results. The scikit-learn library, developed for the Python programming language, was used for experimental model construction. The model was trained on two data arrays: the real sample included 48942 records of students' results in the online course «Internet Resource Development Technologies», and an additional data set contained 18052 records from the Kaggle open repository. The conducted testing confirmed the effectiveness of the proposed methodology, demonstrating an improvement in the quality of education due to an accurate assessment of the student's current state (academic activity, academic achievement), flexible selection of educational materials and other forms of interaction.

Conclusion. The obtained results proved the prospects of using the proposed approach, which helps to increase student engagement due to the peculiarities of the perception of educational material, increase the speed of mastering new competencies by optimizing the sequence of presentation of educational material and the possibility of automating the processes of monitoring student progress. The study is of particular interest to specialists working to improve the effectiveness of online learning, and developers of educational platforms who want to integrate such models into their services to support teachers and organizers of the educational process.

Purpose of research. Wavelet transform is widely used to solve a wide range of digital image processing problems in various applied and scientific and technical fields. At the same time, modern visual information processing systems face the problem of insufficient performance against the background of a rapid increase in digital data volumes. This circumstance requires the development of computationally efficient wavelet processing algorithms suitable for implementation in modern computing devices. This study is aimed at reducing the computational complexity of wavelet image processing based on the use of a modification of the Winograd method. The article proposes the use of a new approach to organizing calculations for one-dimensional filtering with decimation.

Methods. The study used a method for organizing calculations based on the Winograd transform and hardware simulation on a programmable valve matrix in Xilinx Vivado 2018.2 environment using Verilog language for Virtex 7 family model “xc7vx485tffg1157-1”, using standard synthesis and implementation parameters: “Vivado Synthesis Defaults” and “Vivado Implementation Defaults”, respectively.

Results. Experimental modeling of the wavelet transform has demonstrated that the application of the Winograd method in wavelet image processing tasks allows for a reduction the computational delay by 34-63% compared to the direct method when using fourth-order wavelets and by 39-66% when using sixth-order wavelets.

Conclusion. The application of the Winograd method provides a significant increase in the computation speed with some increase in hardware complexity and energy consumption. The results of the study can find wide application in modern signal, image and video processing systems, as well as in the development of machine learning systems.

Purpose of research. The objective of this study is to develop a software solution for automated presentation generation, focused on integrating principles of cognitive psychology and aesthetics. The research aims to create an intelligent platform capable of generating presentations that not only convey information but also ensure its effective visual perception, capturing and retaining audience attention. In an era of rapidly increasing data volumes and decreasing time resources, there is a growing need for tools that can automate the creation of visual content without compromising its quality. The proposed solution takes into account the specific characteristics of human information perception by relying on cognitive principles such as cognitive load theory, Gestalt laws, and visual emphasis. In addition, it applies aesthetic design techniques to create a balanced and expressive visual structure.

Methods. The study combines various approaches and methods, including cognitive and aesthetic aspects, objectoriented programming, and integration with artificial intelligence technologies. This allows the system to automatically generate both textual and visual content, adapting it to the predefined structure of the presentation.

Results. The developed software solution demonstrated advantages over existing tools across several key parameters: reduced presentation creation time, improved visual quality, adaptability, and alignment with cognitive strategies of information perception. Experimental results involving users confirmed the high efficiency of the proposed approach in terms of usability, design quality, and content perception.

Conclusion. The proposed solution, based on the cognitive-aesthetic paradigm, represents a promising direction in the field of automated visual communication. It demonstrates potential for scalability and integration across various domains that require the creation of presentation content combining informativeness, visual expressiveness, and a human-centered design approach. 

Purpose of research. To increase the accuracy of forecasting by developing optimal predictive models that increase the reliability of the identified estimates in the diagnosis of osteoporosis using an expert system.

Methods. In this work, parametric statistical methods were used to confirm the validity of the assumption of the normal distribution of all studied sample populations. Based on the results obtained, correlation and regression analyses are considered as the best approach for studying interrelations, for developing predictive models with determining the confidence interval of prediction and comparing the range of the final indicator with the probability of disease occurrence.

Result. During the study, predictive models were constructed for each identified patient group along with limits of confidence intervals for predicted values of key parameters. Regularities in the mutual dependence between specific target factor ranges and degrees of pathology progression probabilities have been established. An expert information system has been developed, implementing a complete informational support system designed to identify risks of diseases development in patients based on provided data regarding chest tissue density.

Conclusion. The developed information system enables predicting the likelihood of illness for patients (both men and women) whose age exceeds the specified range (10–70 years); however, the reliability of such predictions remains ambiguous since the prognostic models underlying the system's operation are built upon data from individuals aged within the period of approximately 10 to 72 years.

Purpose of reseach. Development of a software package for the automatic creation of photorealistic threedimensional models of faces based on a single input image, which will provide a high degree of detail and realism of models, as well as ease of use,

Methods. The study uses an integrated approach to create photorealistic three-dimensional models of faces from two-dimensional images based on reverse rendering methods and cascading convolutional neural networks (CNN). The main element is a three-dimensional transformable model (3DMM), which describes the geometry and albedo of a face through linear combinations of principal component bases (PCA). To match the 3D geometry and the 2D image, a weak perspective projection is used, taking into account Euler angles and lighting conditions. Optimization of the objective function using the Gauss-Newton method minimizes the differences between the input and rendered images, and correction of depth and facial details is achieved through the adaptation of 3D graphics. Linear albedo interpolation clarifies the details of the model in key areas, which contributes to the creation of high-quality and realistic 3D models of faces.

Results. This article successfully implements a software package capable of generating photorealistic threedimensional models of faces from one-dimensional images using reverse rendering and cascading convolutional neural networks. The experiments have confirmed the algorithm's ability to perceive important facial characteristics and create opportunities for further applications in the fields of computer graphics, animation and virtual interfaces.

Conclusion. The results obtained indicate the high efficiency of the developed algorithm for generating photorealistic three-dimensional models of faces from two-dimensional images. In addition, the results confirm that the use of reverse rendering methods in conjunction with cascading convolutional neural networks allows for significant improvements in visualization quality.

Purpose of research.  To analyze and model the performance of computing systems, including the calculation and comparison of various metrics such as system utilization, peak and asymptotic performance, system acceleration and real performance, using mathematical models to evaluate the performance of systems under dynamic tasks and multitasking. Special attention is given to the effect of various system parameters on the system's ability to perform computational operations and resource management efficiently.

Methods. In this paper, mathematical modeling techniques were used to analyze the performance of computing systems, calculating the system load as the arithmetic average of the loads of all devices, determining the peak performance of the system through the number of devices and the performance of each, calculating the system acceleration as the sum of device loads and the ratio of operations performed to time, estimating the real and asymptotic performance through minimum peak values, comparing different systems in terms.

Results. The study analyzes the performance of heterogeneous computing systems including Intel Xeon processors and Intel Xeon Phi coprocessors. It was revealed that the classical performance evaluation model based on a simple sum of nodes' capabilities significantly overestimates real performance due to ignoring architectural and system peculiarities such as data transfer latency and interconnect bandwidth. A modern model that takes into account AVX512 vectorization, multi-level memory, and PCIe 4.0 bus limitation resulted in a more accurate estimate of about 1.99 TFLops for a homogeneous CPU+GPU configuration. In this case, the PCIe bandwidth acts as a bottleneck in the joint operation of CPU and GPU. Analysis of heterogeneous configurations with Xeon Phi 7120P and Xeon E5-2683 v4 showed a significant performance gain of up to 2.67 TFLops, which exceeds the capabilities of homogeneous systems. The key parameter affecting the performance was the unload queue size factor mmm, which determines the maximum size of the processed data block. Experiments have shown that for small values of mmm, the communication overhead increases the total computation time, whereas the optimal range of m=25-35m = 25\text{}35m=25-35 achieves the minimum execution time due to the balance between queue size and communication overhead. Further increase in mmm leads to stabilization or slight increase in runtime due to increased complexity of load balancing and delays. The obtained data confirm that proper selection of queueing parameters is an important factor in the optimization of heterogeneous systems.

Conclusion. This research has confirmed the necessity of using modern performance evaluation models that take into account architectural features, bandwidth, interconnects and system limitations to accurately predict the computational capabilities of heterogeneous platforms. Classical evaluation methods prove to be insufficient as they do not take into account data transfer latency, memory features and parallelism, resulting in overestimated and unrealistic predictions. Modern models taking into account AVX vectorization, multi-level memory and PCIe bandwidth allow us to obtain an adequate evaluation and identify real bottlenecks important for optimization.