The article consider the influence of illumination and distance on the recognition quality for various models of neural networks of embedded systems. The platforms on which the testing was carried out, as well as the models used, are described. The results of the study of the influence of illumination on the quality of recognition are presented.

Keywords: artificial intelligence, computer vision, embedded systems, pattern recognition, YOLO, Inception, Peoplenet, ESP 32, Sipeed, Jetson, Nvidia, Max

5G wireless networks are of great interest for research. Network Slicing is one of the key technologies that allows efficient use of resources in fifth-generation networks. This paper considers a method of resource allocation in 5G wireless networks using Network Slicing technology. The paper examined a model for accessing radio network resources, which includes several solutions to improve service efficiency by configuring the logical part of the network. This model uses network slicing technology and elastic traffic. In the practical part of the work, transition intensity matrices were constructed for two different configurations.

Keywords: queuing system, 5G, two - service queuing system, resource allocation, Network Slicing, elastic traffic, minimum guaranteed bitrate

The article examines methods for assessing the structural stability of raster images. The study proposes a comprehensive approach, including texture analysis, color characteristics, and object shape analysis. The author presents experimental results demonstrating the effectiveness of the proposed method on various types of images. The findings obtained enable the optimization of processes for processing and storing graphical information, which is important for various fields, including medicine, geology, and computer vision.

Keywords: raster image, filtering, morphology, relative mean square error rrmse, OpenCV, Python

With the development of scientific and technological progress, the use of modern data forecasting methods is becoming an increasingly necessary and important task in analyzing the economic activity of any enterprise, since business operations can generate a very large amount of data. This article is devoted to the study of methods for forecasting financial and trade indicators using neural networks for enterprises of the Krasnodar Territory. The indicators under consideration are the company's revenue for the reporting period, the number of published (available for sale) goods, as well as the number of ordered goods during the day, week and month. In this study, a multilayer perceptron is considered in detail, which can be used in revenue forecasting tasks using neural networks, and neural network predictive models "MLP 21-8-1", "MLP 21-6-1", and "MLP 20-10-1" are built based on data from the online auto chemistry store Profline-23.

Keywords: automated neural networks, marketplaces, forecasting, neural network models, mathematical models, forecasting methods

The article discusses the features and prospects of implementing distributed management of critical urban infrastructure facilities based on the principles of autonomy. Based on the analysis, the main technologies, directions of development and features of energy transfer in an urban environment are highlighted, contributing to the introduction of distributed management of urban infrastructure facilities. The study focuses on the analysis of the distributed structure of integrated security of critical urban infrastructure facilities and the development of general principles of distributed management of critical infrastructure facilities using the «Autonomous Building» technology. t is shown that the reliable and safe functioning of critical infrastructure facilities in the city is ensured through the synthesis of special technical systems for complex protection of the facility from major security threats based on the combined use of elements of life support and safety systems. At the same time, technical life support systems for autonomous objects of critical infrastructure of the city are built on the basis of the combined use of autonomous energy sources, including non-renewable energy sources, on the principles of joint operation of electric and static power converters, storage, frequency regulation and energy conversion, and technical safety systems of autonomous objects are built using combined optical and electronic means event detection and recognition with the ability to control the full spectrum of electromagnetic radiation.

Keywords: distributed management, technology, energy, energy transfer, urban infrastructure, critical facility, electrification, decentralization, automation, autonomy

The present paper examines the actual problem of using graphics processing units (GPUs) in computing processes that are traditionally performed on central processing units (CPUs). With the development of technology and the advent of specialized architectures and libraries, GPUs have become indispensable in areas requiring intensive computing. The article examines in detail the advantages of using GPUs compared to traditional CPUs, justifying this with their ability to process in parallel and high throughput, which makes them an ideal tool for working with large amounts of data.are accidents caused by violations of rules and regulations at work sites, among them cases related to non-compliance with the rules of wearing protective helmets. The article examines methods and algorithms for recognizing protective helmets and helmets, and assesses their effectiveness.

Keywords: graphics processors, GPU, CUDA, OpenCL, cuBLAS, CL Blast, rocBLAS, parallel data processing, mathematical calculations, code optimization, memory management, machine learning, scientific research

Equipping roads with communications is complicated by the almost complete lack of roadside infrastructure, including power lines, as well as difficult terrain. When emergencies occur on this kind of country roads, residents are forced to seek help from nearby settlements that are well-connected. Therefore, providing suburban routes with communications is a key social task. Using an existing base station as an example, this article calculates the attenuation and propagation range of a radio signal for LTE technology and GSM technology, provides a comparative analysis, and uses methods of mathematical modeling and system analysis.

Keywords: LTE, GSM, Okumura-Hata model, Lee model, Longley-Rice model

The development of digital technologies stimulates widespread automation of processes in enterprises. This article discusses the problem of determining the values of the oil indicator of a transformer from the resulting image using computer vision. During the study, the device of the MS-1 and MS-2 oil indicators was studied and the features that must be taken into account when recognizing the device in the image and determining its value were considered. Based on the processed material, a method for recognizing device elements in an image has been developed using the OpenCV library and the Python programming language. The developed method determines instrument readings at different angles of rotation and in different weather conditions, which confirms the effectiveness of the proposed method.

Keywords: technical vision, oil indicator, contour recognition, OpenCV library

This study examines the combination of several non-destructive partial discharge (PD) detection methods to improve the accuracy of their detection. An analysis of methods for detecting PD in high-voltage insulation, a consideration of their features, and an analysis of the possibility of combining them to achieve the most accurate measurements were carried out. Analysis of the practical effectiveness of combining methods based on the developed variations of installations operating on the principles of two or more detection methods. Options for installations for PD detection that combine two or more detection methods are considered. A conclusion is given about the possibility of combining various methods of detecting partial discharges, taking into account the peculiarities of this type of combination. The simplest and most effective at the moment is the use of measuring cells that combine electromagnetic and acoustic detection methods.

Keywords: partial discharges; non-destructive testing of insulation; high voltage insulator; diagnostic methods for insulators

The paper describes a multifactorial nonlinear regression model of revenue dynamics of the mining and metallurgical company Severstal, based on retrospective information for 2009-2021. Production volumes by type were used as independent variables: hot-rolled and cold-rolled sheet, galvanized sheet and sheet with other metal coating, rolled products, large diameter pipes, other pipe products and profiles. The criteria of multiple definition and Fisher, as well as the average absolute approximation error, were used as criteria for the adequacy of the model. A model competition was held to select the best regression dependence. As a result, a model is constructed containing inverse transformations of two independent variables in the right part.

Keywords: regression model, least squares method, adequacy criteria, mining and metallurgical company, revenue, model competition

The paper provides a brief overview of publications on the application of mathematical modeling methods in the study of the patterns of functioning of hydroelectric power plants (HPPs). In particular, the following are considered: mathematical models of the total minimum water consumption for a cascade hydropower system in China; a mathematical model of hydropower plants; a mathematical model of two small hydroelectric power plants operating in tandem; accurate modeling of hydraulic transient characteristics in a complex drainage system. The task of filling in the gaps in the data concerning the operation of hydroelectric power plants is formulated. The approach to its solution is proposed to be based on the use of the method described in previous publications by one of the authors and based on the use of regression analysis apparatus. The specific task of filling in data gaps for a hydroelectric unit of one of the Siberian hydroelectric power plants has been solved. The following factors are used: active and reactive power of the electric generator, voltage, current and temperature of the stator iron, rotor current, air cooler hot air temperature.

Keywords: hydroelectric power plant, electric generator, data gaps, predictive analytics, regression model, adequacy criteria

Stepper motors are often used in automated laser cutting systems. The control circuit of a stepper motor requires a special electronic device - a driver, which receives logical signals as input and changes the current in the motor windings to provide motion parameters. This research study evaluated stepper motor drivers to determine the feasibility of their use - PLDS880, OSM-42RA, OSM-88RA. To control the system, software code was written, which was connected to the controller via a link board. With each driver, in different modes, optimal parameters were selected (initial speed, final speed and acceleration), that is, the movement of the carriage without stalling for ten passes with a minimum travel time. The results of the experiments are presented in the form of tables.

Keywords: laser, laser cutting, automation, technological process, stepper motor, performance, driver, controller, control circuit, optimal parameters

The article describes the automation of the audio recording recognition process in order to identify the ordered song on the radio station. The Golos Russian speech recognition model from the SberDevices was used. An algorithm for correcting the text obtained as a result of audio recording analysis using the Golos model based on the Levenshtein distance method has been developed. For recognized requests from radio listeners, interaction with the DIGISPOT II database is organized (formation and execution of queries to search for artists and their songs).

Keywords: speech recognition, Golos, Digispot II

In the work, based on the previously constructed multifactor dynamic regression model of water level in the Iya River (Eastern Siberia), the authors forecast this indicator for June 2023 in three options: pessimistic, optimistic and neutral (base). A comparison of the forecasting results with the actual value of the water level confirmed the high adequacy of the model and good prospects for its future successful use to solve a wide range of applied and practical problems.

Keywords: regression model, river water level, lag time, seasonal variable, forecast, adequacy, criteria

This paper analyzes the performance of solving the classification problem using various open-source artificial intelligence and machine learning libraries in the field of marketing and customer relationship management; based on the results of experiments, the best library is selected for the purpose of introducing artificial intelligence into domestic CRM systems based on numerical performance indicators.

Keywords: artificial intelligence, machine learning, big data, classification, marketing, customer relationship management, import substitution, open source

An approach to solving the problem of justifying a project for the development of a complex system, taking into account the possibility of realizing the values of its characteristics and the presence of restrictions on their values is proposed . The general goal is formulated in terms of the theory of fuzzy sets and the theory of possibilities. Based on the global development goal of a complex system, local goals and objectives are determined. The problem of taking into account factors influencing the achievement of a global goal is considered. Achieving the general goal is associated with taking into account restrictions on the values of system indicators, as well as the need to determine their optimal values. Unlike existing models, the proposed approach allows us to consider a more general relationship between the elements of the system and take into account the fuzzy nature of the implementation of the parameters. To solve this problem, an effective decomposition method has been developed.

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

The integration of blockchain technology with the Internet of Things (IoT) offers transformative potential for various sectors. This article delves into 16 distinct methods of integrating blockchain with IoT, emphasizing that there isn't a one-size-fits-all solution. Each method has its unique advantages and potential drawbacks, necessitating careful consideration based on specific IoT system requirements. For instance, integrating with public blockchains like Bitcoin and Ethereum offers transparency and decentralization but faces scalability issues. Sidechains introduce flexibility but might pose security risks. Blockchain platforms like Hyperledger Fabric expedite development but can lead to vendor lock-in. The diversity of these methods underscores the importance of a well-thought-out approach tailored to the specific needs of the IoT system in question. As technology evolves, we anticipate more innovative approaches to emerge, emphasizing the continuous need for research, experimentation, and collaboration to fully harness the potential of IoT and blockchain integration.

Keywords: blockchain , IOT , BIoT, smart contracts, IoT security

The study presents an extensive analysis of methods for low-level optimization of the matrix multiplication algorithm for computing systems with shared memory. Based on a comparison of various approaches, including block optimization, parallel execution with OpenMP, vectorization with AVX and the use of the Intel MKL library, significant improvements in the performance of the resulting software implementations are revealed. In particular, block optimization reduces the number of cache misses, parallelism effectively uses multicore, and vectorization and Intel MKL demonstrate maximum acceleration due to more efficient software optimizations. The obtained results emphasize the importance of careful selection of optimization methods and their compliance with the architecture of the computing system in order to achieve the required performance parameters of the designed software.

Keywords: low-level optimization, block optimization, parallel execution, OpenMP, vectorization, AVX, Intel MKL, performance, benchmarking, matrix multiplication

Assessment of the technical condition (hereinafter TC) of technical systems is a prerequisite for a modern strategy for their operation. The study of new methods and algorithms that provide express assessments of the condition of technical devices and reduce the subjective component in these assessments is an urgent and in demand task. The paper presents a constructive approach to assessing the TC indicators of complex technical systems based on a modified method of analyzing hierarchies and the TC index (hereinafter referred to as ITS) of equipment, which is determined on the basis of weights and ITS of the main components of the equipment in question. The ITS of the main nodes is calculated based on the comparative characteristics of the operating parameters of the equipment during its operation, and the weights of the nodes are determined based on the methods of the matrix of paired comparisons (Saaty method) and the degree of importance of the line (DIL - Degree Importance Line method). The testing of the methodology and algorithms in this study was carried out on the basis of statistical data from a NASA turbojet engine (hereinafter referred to as turbofan engine), published in 2008.

Keywords: technical condition, technical condition index, complex technical system, maintenance and repair, hierarchy analysis method, DIL method, constructive method for assessing technical condition, algorithm for express assessment of technical condition

Bar structures are widespread in construction due to their economy, freedom of design shapes and sizes. As a result, automation of design and calculation of such structures is an urgent task. As part of the study, the task of developing a software module that generates a map of optimal cutting of rolled metal based on the results of calculations of rod structures has been implemented. The algorithm under consideration takes into account such features of the cutting optimization problem as taking into account the width of the blade, the possibility of using half the size of the rolled product, support for optimization of several sections, and welding of parts in case the length of the workpiece is exceeded. The software module is developed using JavaScript and C# languages. The ability to automatically generate cutting maps based on the results of optimization of rod structures increases the efficiency of designing building structures.

Keywords: Design in construction, bar structure, computing system, web development, design in construction, rod structure, computer system, web development, optimal cutting, rolled metal, cutting map

The article explores the problem of creating aircraft flight models in the Simulink environment. The reference systems in which transformations are carried out are considered. The equations of motion used in the simplest converters are given. The initial conditions for the equations are determined: the speed of the body, the angular orientation of the body's pitch position, the angle between the velocity vector and the body, the speed of rotation of the body, the initial position, the mass and inertia of the body, the source of gravity, the acceleration due to gravity, the curb and total mass of the body, speed of air flow, inertia of an empty and full body, flight trajectory, etc. An analysis of converters of aerodynamic forces and moments into the trajectory of motion as part of an aerospace package in the Simulink environment was carried out. Recommendations are given for their use for various modeling purposes. The results of modeling a simple converter with three degrees of freedom are presented.

Keywords: modeling, MatLab, Simulink, equations of motion, aerodynamic torque, flight path, coordinate transformations, reference system, degrees of freedom

A method for recording holograms using digital cameras with high spatial resolution is considered. To register holograms obtained in optical setups with an inclined reference beam, a high resolution of registration systems is required. To do this, it is necessary to use media with a resolution of 2000-4000 lines per mm. The use of photographic plates requires a fairly long exposure and development time, which is usually done separately from the optical setup. In the case of holographic interferometry systems, it is necessary to provide for mounting the hologram back into the optical setup with sufficiently high accuracy. Therefore, digital holography methods have been developed to record holograms on photomatrices with limited resolution. These methods are based on the use of optical schemes at small angles (less than 5 degrees) between interfering beams. Recently, sensors with a single element size of 1.33 µm and 0.56 µm have appeared. This resolution makes it possible to return to registration schemes with angles between interfering beams of 30-60 degrees. This allows us to hope for the revival of holographic methods and methods of holographic interferometry at the modern level without the use of intermediate recording media.

Keywords: digital holography, high spatial resolution photo matrix, tilted reference beam holography, Fourier transform

This paper considers the problem of removing noise from an image based on the discrete cosine transform (DCT) algorithm. Despite its simplicity, the algorithm is still popular in image conversion. However, recently there has been a strong development of convolutional neural networks, leaving behind “traditional” signal processing methods. In this paper, we study image denoising using DCT and convolutional neural networks and creating an interpretable convolutional neural network to obtain accurate data. The basis was the Python programming language and the library for working with neural networks – PyTorch. Based on this, a neural network model was trained on The Berkeley Segmentation Dataset. Experiments have shown that the trained neural network shows results comparable to traditional image denoising algorithms.

Keywords: noise reduction, convolutional neural network, discrete cosine transform, machine learning, signal processing, Canny operator

The article proposes a general formalized model of the task of processing and extracting potential key skills from job descriptions to determine the relevance of training areas and possible areas of employment for graduates. The formalized model is used in the software implementation of the job clustering module based on the obtained sets of key skills within the framework of a comprehensive toolkit for remote career guidance.

Keywords: vacancies, demand for training areas, career guidance, digitalization of career guidance, formalized model, clustering, professions, key skills

This paper presents the process of developing an algorithm that is able to extract style and content from two different images and create a new image, preserving the content structure of one image and simultaneously applying the stylistic characteristics of the other image. This algorithm is able to adapt the style of one image to the content of the other image, creating unique artworks.

Keywords: neural networks, style transfer, image, machine learning, algorithm, dataset, software