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

The article proposes a variant of an electromagnetic drive for controlling an unmanned aerial vehicle for monitoring power facilities and develops calculation ratios that determine its electromechanical and dynamic processes. The structure and main characteristics of the pulse drive control have been developed. The conducted research can be used in the implementation of the steering drive project of a modern unmanned aerial vehicle.

Keywords: electromagnetic drive, pulse control, multipolar pulse width modulation, block diagram, magnetic induction, moment, constant, pulse element, control current, inertia

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 discusses identification methods in industry and equipment presented on the Russian market for marking and identification of objects. The purpose of the article is to analyze the equipment and installations available on the Russian market for marking and identification of straight-seam steel pipes in production. A comparison of methods based on a scoring system for marking and identification of straight-seam steel pipes in production is presented. Barcode marking technologies using labels, laser marking and RFID tags are presented and considered as identification methods.

Keywords: barcoding, laser marking, RFID tag, straight-seam steel pipe, thermal label printer, automated identification system

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

The high relevance of issues related to the import substitution of foreign controller equipment with domestic developments for automated process control systems at mining and metallurgical companies is dictated by the lack of possibility of purchasing and technical support for automated process control components to ensure continuous production of mining and metallurgical enterprises, as well as to meet the needs of the country ferrous metallurgy products. This article discusses the development of an automated control system for the technological process of steel production in an oxygen converter at the Novolipetsk Metallurgical Plant using controllers from a domestic manufacturer. The transition to automated control systems based on domestic controller equipment is a strategically important step for the enterprise, aimed at increasing the efficiency of production processes, increasing system reliability and production stability, by optimizing technological processes and reducing production dependence on imported equipment.

Keywords: import substitution, converter, oxygen-converter production, steel production, controller, automated control systems

The traditional cycle of manufacturing high-tech electronic products was examined, and a methodology for its optimization was developed. The interrelation between the stages of design documentation development and the electronic structure of the product was established. The methodology significantly reduced the manufacturing time of products by parallel development of the electronic structure alongside the product. The rationale for applying the methodology in design was provided.

Keywords: electronic structure of the product, eBOM, 1C:PLM, procurement of components

Currently one of the promising trends in the global energy sector is the introduction of renewable energy sources (RES) into the existing grid. The use of RES can be favourable in autonomous power systems where fuel costs are high. However the stochastic nature of power generation creates a number of difficulties in maintaining the power balance. To solve this problem, it is proposed to connect a hybrid energy storage system (HESS) consisting of a battery and a supercapacitor to the load busbars. The efficiency of such HESS depends mainly on the way of its connection to the grid and the choice of control method. The article gives an overview of the existing mechanisms for controlling the power consumption of HESS.

Keywords: Renewable energy, hybrid electricity storage, power converter topology, electricity storage control strategy

The subject of this article is the development of a behavior pattern with AI elements for an opponent bot in the single-player game Steal Tower. The essence of which is to collect resources to build a tower faster than opponents. To create the illusion that the same people are playing against the player, an imitation stochastic model based on the Monte Carlo method for Markov chains has been developed. Based on the results of its tests, balanced system parameters were determined, which are embedded in the behavioral pattern of the bot, which is implemented using the Enum AIStates enumeration consisting of five states: Idle (inactivity), GoTo (movement) and GoToWarehouse (return to the warehouse), Win (victory), Loose (scoring). Each of them has developed functions for the optimal behavior of the bot given in the article. So for the GoTo state, functions have been created that analyze the benefits of different types of behavior: steal or collect, or walk to the warehouse or to the tower.

Keywords: game intelligence, behavioral pattern, live world emulation, bot behavior scenario, state structure, Markov chains, Monte Carlo method, simulation model, Unity environment, C# language

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 validity of analytical models of the process of one-parameter selective assembly of two elements was evaluated by comparison with the results of simulation modelling. A series of machine experiments including one-factor and two-factor experiments were carried out. At the accepted levels of variation of factors, the confidence interval of the probability of yield of good products from the initial population of elements that did not pass sorting was determined using Student's criterion at the given level of significance and number of degrees of freedom. Comparison of the simulation results revealed the facts of reaching the specified process indicator, determined by the analytical model, for all experiments within the confidence intervals and the presence of relatively small deviations from their centres.

Keywords: selective assembly, analytical model, simulation model, measurement error, simulation results

This article explores the introduction and implementation of neural network models in the field of agriculture, with an emphasis on their use in smart greenhouses. Smart greenhouses are innovative systems for controlling the microclimate and other factors affecting plant growth. Using neural networks trained on data on soil moisture, temperature, illumination and other parameters, it is possible to predict future indicators with high accuracy. The article discusses the stages of data collection and preparation, the learning process of neural networks, as well as the practical implementation of this approach. The results of the study highlight the prospects for the introduction of neural networks in the agricultural sector and their important role in optimizing plant growth processes and increasing the productivity of agricultural enterprises.

Keywords: neural network, predicting indicators, smart greenhouse, artificial intelligence, data modeling, microclimate

The work is devoted to an urgent problem - the development of automated process control systems for the production of bricks with improved characteristics. The purpose of the article is to define and systematize the tasks of automation of brick production control systems, to develop both an algorithm for managing brick production and a generalized structure of automated control systems for brick production, and the tasks of the work are: optimization of control automation levels that determine the generalized structure of automated control systems for brick production, determination of information collection subsystems corresponding to the stages of brick production, and development of their structures, the choice of basic measurement tools for information collection subsystems. The results of the work are: systematization of requirements for modern automated process control systems, development of an algorithm for controlling technological processes and a generalized structural scheme of automated process control systems for brick production, development of information collection subsystems for the developed automated process control system, development of the structure of a local automated process control system in brick production - brick drying. The developed technical solutions can be recommended for control automation in various industries.

Keywords: brick production, technological process, drying, firing, control algorithm, automated control system, structural scheme, information collection subsystem, single-channel circuit, multi-channel circuit, measuring circuit, four-arm bridge circuit

This paper examines and compares two neural networks, U-Net-Attention and SegGPT, which use different attention mechanisms to find relationships between different parts of the input and output data. The U-Net-Attention architecture is a dual-layer attention U-Net neural network, an efficient neural network for image segmentation. It has an encoder and decoder, combined connections between layers and connections that pass through hidden layers, which allows information about the local properties of feature maps to be conveyed. To improve the quality of segmentation, the original U-Net architecture includes an attention layer, which helps to enhance the search for the image features we need. The SegGPT model is based on the Visual Transformers architecture and also uses an attention mechanism. Both models focus attention on important aspects of a problem and can be effective in solving a variety of problems. In this work, we compared their work on segmenting cracks in road surface images to further classify the condition of the road surface as a whole. An analysis and conclusions are also made about the possibilities of using architectural transformers to solve a wide range of problems.

Keywords: machine learning, Transformer neural networks, U-Net-Attention, SegGPT, roadway condition analysis, computer vision

This article discusses the basic principles and design patterns of an application for collecting data from third-party sources. Research has been carried out on various methods of obtaining data, including web scraping, using APIs and file parsing. It also describes various approaches to extracting information from structured and unstructured sources.

Keywords: internet sources, API, parsing, web, headless browser, scraping, etag, data collection

The article presents aspects of the development of a device for wirelessly picking up a vibration acceleration signal from the surface of a ball mill drum. The results of measuring vibration acceleration for a ball mill model for various levels of loading with crushed material are presented. According to these results, with an increase in the load of crushed materials relative to the ball, the level of vibration decreases. The work also presents the obtained pie diagrams of the distribution of vibration load across the mill drum, from which one can judge its current operating mode.

Keywords: ball mill, wireless signal, vibration acceleration, mill loading control

The modeling of a multi-motor linear electric drive of a conveyor train is considered. A diagram of the simulation model made in the Simulink program is given. Graphs of the speed and force of the electric drive during the relay transmission of the secondary element are given. The conclusion is formulated that the system fulfills the requirements placed on it.

Keywords: simulation modeling, Simulink, linear asynchronous motor, electric drive, conveyor train, relay transmission

The drilling and blasting method is currently the most widely used for mining rocks. An indicator of the high–quality drilling and blasting operations is the uniform granulometric composition of the exploded rock mass - the percentage of oversized ore pieces should be minimal. The percentage of oversized and its increase have a significant impact on the technical processes of transporting rock mass, leading to an increase in the costs of loading and transportation operations and secondary crushing of oversized ore masses. The paper describes the results of a study of methods for determining the granulometric composition of drilling and blasting operations using neural networks of segmentation Unet and FPN. Images taken from UAVs are used for analysis. A method of classifying ore by size has also been developed, which ensures the accuracy of the proportion of correct answers of more than 0.91. The expected result of the introduction of the system for automatic determination of the granulometric composition of drilling and blasting operations is the possibility of more accurate control over the quality of their performance.

Keywords: granulometric composition, Unet, FPN, classification, segmentation

This article explores a method for executing data collection systems based on the widely-used industrial protocol, Modbus TCP. In this configuration, the server is a program emulating the Modbus TCP protocol.To implement the client an algorithm and furnished a practical Python programming illustration that employs a lower-level socket library.

Keywords: python, socket, modbus

The paper provides a comparative analysis of additive technologies in the field of formation of electromechanical designs of functional devices. In particular, the problem of using additive technologies, their relevance in relation to modern needs in different fields of science and technology is put, the essence of additive technological processes for the production of various kinds of products is revealed and a specific design and technological approach for creating a modular product on the basis of these technologies is defined.

Keywords: additive technologies, printed circuit board, 3D printing, fused deposition modeling , selective laser sintering, stereolithography, digital light processing, direct metal laser sintering, selective laser melting, direct ink writing

This article discusses the features of the use of neural network detectors in the tasks of recognizing protective helmets and helmets. Nowadays, workplace safety is becoming an increasingly relevant topic, especially in industries with a high level of injuries. There 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: convolutional neural network, object recognition, protective helmets. helmets, SSD, YOLOv5, Faster R-CNN, machine learning, deep learning, image classification

In this work, the developed system for detecting areas with defects in the development of corn crops was investigated from a photograph taken by an unmanned aerial vehicle (UAV) using computer vision. To solve the problem of detecting such sites, the structures of the YOLOv5 and YOLOv8 neural networks were considered. The use of the developed software will reduce labor and time costs for image analysis, which in turn will reduce the response time when problem areas are detected in agricultural fields to achieve higher yields.

Keywords: instance segmentation, YOLOv5, YOLOv8

Existing methods for determining the geometry of an enclosed space using echolocation assume the presence of a large amount of additional equipment (sound sources and receivers) in the room. This paper investigates a method for determining the geometry of enclosed spaces using sound location. The method does not assume the presence of a priori knowledge about the surrounding space. One sound source and one sound receiver were used to create and capture real impulse characteristics. A microphone was used as a sound receiver and a finger snap was used as a sound source to produce the impulse response. In this work, we used convolutional neural networks that were trained on a large dataset consisting of 48000 impulse responses and a number of room geometry parameters corresponding to them. The trained convolutional neural network was tested on the recorded impulse responses of a real room and showed accuracy ranging from 92.2 to 98.7% in estimating room size from various parameters.

Keywords: convolutional neural networks, room geometry, echolocation, impulse response, robotics, recognition, contactless methods of measuring objects, sonar, geometry prediction, virtual reality

This paper presents the concept of using fuzzy control methods in the construction of energy efficient systems based on photovoltaic modules. An analysis was made of methods to improve efficiency in the case of weather in Vietnam on a sunny summer day for photovoltaic modules. The results show that the efficiency of the proposed system is increased by 27.91%, 23.30% and 4.95% compared to the PV module, respectively, with a fixed tilt system, a water-cooled system, and a solar tracking system. The simulation results can serve as a prerequisite for future experimental models.

Keywords: Photovoltaic module, thermoelectric model, solar tracking, water cooling, efficiency, fuzzy logic