Advances in Automation V

The article examines the main aspects of implementing adaptive management of plant production technology in the context of the dynamics of the greenhouse effect, based on the construction of automated systems endowed with the functions of scientifically based zoning of agricultural territories, taking into account the results of model assessment and forecasting of the dispersion and accumulation of greenhouse gases. Systems of this class include a special module - a digital platform that generates and updates a complex of necessary models, algorithms, their software implementation, and a knowledge base for automated operational comparison and selection of a technological map and type of crops for their cultivation, ensuring a consistently high yield in the existing/predictable natural and climatic and man-made conditions. Effective solutions for the stated tasks and the choice of the best technology from alternatives are achieved based on the synthesized use of methods of intelligent data analysis, geoinformation technologies, and 3D modeling. The digital platform not only implements the dynamic formation and use of required predictive models and algorithms but also ensures the operational response of all components of the investigated automated system to current changes in the control object and the surrounding environment. The adaptive management scenarios generated in the system are aimed at increasing the productivity of agricultural territories based on the rational use of causal links between the natural potential of soil and plants with climatic factors.

The authors have developed an approach to the search for structurally similar projects of software systems. Teachers can use the proposed approach to search for borrowings in the works of students. The concept behind this proposal is that it can to locate projects that students have used as parts of a current project. The authors propose a new algorithm for determining the similarity between the structures of software projects. The proposed algorithm is based on finding similar structural elements in the source code of the program in an abstract syntax trees analyzing. The authors developed a software system to evaluate the proposed algorithm. The current version of the system only supports Java programs. However, the system operates with its own representation of the abstract syntax tree, which allows you to add support for new programming languages.

The article discusses the technological processes of cutting during drilling and the operation of technological equipment. The article considers the possibility of solving the problem of self-regulation, self-tuning of the machine to operating modes and parameters close to optimal by increasing the level of automation of the control process. The process of operation of an automated drilling machine was also studied, its characteristics were determined, the change in the strength of the material of the destroyed rock and other factors affecting the efficiency of the drilling process were studied. At the same time, it was revealed that the method of automating the drilling process using electronic automatic control systems and control systems with adjustable drives requires an accurate description of the characteristics of the material being destroyed and their variability, which is possible only with a certain degree of accuracy due to the stochastic nature of changes in these characteristics. Thus, there are no sensors in machines and units with an adaptive structure, feedback is carried out through kinematic links. At the same time, self-regulation can be provided within certain restrictive limits.

Currently commercial losses of electric power are an actual global problem for electric grid companies and final consumers, since a high level of losses is the reason for a significant increase in electricity tariffs and a decrease in the quality of supplied energy. The solution to this problem is the creation of monitoring systems for operational search and detection of abnormal electricity consumption using elements of artificial intelligence. The algorithm of operational intelligent search for non-technical electricity losses (NTL) in 0.4 kV distribution networks is presented and applied in the study. The peculiarity of the developed algorithm is that the identification of energy consumers with abnormally low consumption is carried out without a pre-marked sample on the presence/absence of NTL. This significantly increases the value of the proposed algorithm, since in developing energy systems such accounting is not always carried out in digital form. Statistical analysis and machine learning methods were applied during the research. An experiment was also conducted on real energy consumption data of a sample site with 126 final consumers, all of which are fully equipped with advanced metering infrastructure (AMI). As a result of the experiment, the effectiveness of the algorithm was demonstrated as a basis for a monitoring system and management decision support in minimizing losses in the energy system.

The article is devoted to the problem of ensuring the accuracy of measuring the flow rate of natural gas at temperatures below 250 K. To determine the amount of gas corrected to standard conditions, special algorithms based on state equations are used. One of the parameters included in the equation of state is the gas compressibility factor, which is reliably determined for temperatures above 250 K. The article considers the main algorithms for determining the natural gas compressibility factor at temperatures below 250 K, used in practice gas metering units. It has been shown that when using the substitution values of T and Z, a significant additional systematic error occurs. A numerical estimate of the values of this error is given. According to the results of the study, this additional error is systematic, increases with a decrease in temperature and leads to an underestimation of the amount of natural gas corrected to standard conditions. The key methods of the study presented in this paper are comparative analysis and numerical experiment.

There is a tendency to expand the list of types of distributed generation sources (DG) and increase their total installed capacity. Much attention is paid to the introduction of renewable energy sources (RES), which are environmentally friendly compared to traditional power plants. Their integration into power systems can be achieved with the help of a virtual power plant (VPP). The object of study is the VPP which connects DG power plants through electrical networks with a voltage of 0.4–10 kV. The VPP uses a multi-agent system (MAS) to control energy exchange. The agents are defined: generation, load and a centralized power system. When developing algorithms for the functioning of the generation and load agents, the rating of generation agents criterion in terms of environmental friendliness is primarily taken into account. This provides the advantage of consuming electricity from the most environmentally friendly power plants. A methodology has been developed for determining the environmental friendliness rating of DG sources, taking into account the life cycle of power plants. The environmental rating is determined by the installed power, the materials used, the fuel used, the service life and the location of the DG sources. Several approaches to the application of the environmental rating in the management of the VPP are considered.

The work describes a list of modern requirements and existing approaches to developing user interfaces. It provides a description of the task formulation for developing a control program for a hydrogen generation system based on a user interface. During the work, the authors proposed and described an approach and methodology for developing software for automated control systems of technical systems based on a user interface in the form of a mnemonic diagram. This methodology allows for designing a clear, convenient, and simple user interface, despite the possible complexity of the described system, thanks to the visualization of measurement, control objects, and the connections between them. Each stage of the methodology is described in detail. The stage of the technological process automation methodology describes the system’s states and transitions between them using the Backus-Naur form. The work with the interpreter is described in detail, and its improvement gradually occurs with the introduction of new functionality according to the mnemonic diagram of the system. The proposed methodology allows for creating a control system similar to supervisory control and data acquisition systems.

As a part of distributed production, the resources required for the technological preparation of production and equipment units can be located in different geographic locations. This paper presents a method to work with CAM and CAE software packages over the Internet, which allows to simulate the machining processes and then to program CNC machines remotely. Software from different developers, CAE FIDESYS and CAM ADEM, was integrated to solve common task of machining semi-conductor material. Stress analysis in CAE software as a part of the integrated CAE/CAM solution is used to search for the parameters of machining technology. In accordance with the developed method, technological preparation of production can be organized distantly, in particular, from a mobile phone, by accessing servers with installed licensed programs via a web interface. From a local server (or personal computer, mobile phone, smartphone, tablet PC) on a remote computer (or supercomputer) with the FIDESYS program installed, the source code written in the APREPRO programming language can be launched in a console. The code contains the parameters of the computational model and performs simulation of the technological process. Then the technologist launches the ADEM program on another remote computer and creates a control program for CNC machine, using the calculated CAE results. When the control program is ready, it can be transferred to the production area to control CNC machine and carry out the technological process. The proposed production system does not contain restrictions on the type of materials, machining technologies and tools.

The article proposes the concept of category theory for describing metagraphs. In particular, a metavertex is considered as a category built on the generating set of a metagraph. This approach made it possible to consider vertices and metavertices as objects, and relations between them as morphisms. In this case, the metavertex is not a hyperedge, but a subset of the generating set, i.e., an object, along with the elements of the generating set, which does not contradict graph theory. Metavertices are a generalization of the corresponding objects of the generating set and carry a certain informational (semantic) load. At the same time, objects from the generating set can also be a generalization of some metavertices. The concepts of a static and dynamic metagraph are introduced, as well as matrix representations of a static metagraph. A static metagraph is defined by a category based on the generating set and the set of morphisms (arcs, edges) defined on the generating set, as well as the set of metavertices and the set of morphisms (metaarcs, metaedges) defined on the union of the set of metavertices and the generating set. The semantics of vertices, metavertices, arcs and metaarcs is determined by their attributes.

Analysis and evaluation of various factors affecting the transportation process are associated with identifying complex dependencies that can also change over time. This fact calls for the need to use a relevant mathematical framework; we suggest it be system dynamics as it, inter alia, allows to explore nonlinear feedback between operational factors. Since this approach views a motor transport company as a holistic system, it is possible to assess its performance taking into account an integrated effect of various factors. System dynamics models allow to employ indicators from engineering sciences, as well as economics, sociology, ecology, and other areas to describe any cause-effect relations, including nonlinear ones. Moreover, system dynamics allows to analyze various interactions between elements of complex systems, including ‘soft’ ones such as social relations.

One of the main areas of training for a modern technical systems engineer is complex automation. Analysis of the functioning of automation systems, their design is carried out using the so-called typical effects, that is, signals with known parameters. In a large number of cases, complex effects can be represented as power functions of time. In some cases, such series can reach a large number of terms. And this is not the only example in engineering practice when the approximation of some processes is realized through expansions into long functional series. It is a mistake to believe that the speeds of modern processors are so high that they can free the programmer from the sometimes-difficult search for recurrent formulas and confine them to programming the sum of a series, based on a ready-made formula for the general term of the series. The aim of this study is to show that the use of recurrent relations not only allows to increase the speed of calculations, but is often the only condition for obtaining the correct final result. The codes of programs presented in the article that implement the processing of a series by two methods and a comparison of their results are quite convincing evidence of the need to search for and use recurrent relations in the development of algorithms based on the use of various types of series.

The article discusses the issues and outlines ways to address them related to the early stage of any design, the selection of the layout of the final product. Scientifically grounded choice of layout is a complex process. It requires not only the use of information technology, but more importantly, the use of expert knowledge in the process. There must be a clear understanding of what a layout is, what a layout element is, what a structure is, what a composition is, and how it all interrelates. A wealth of historical experience in design, must be gathered and adapted for automated synthesis. This applies especially to the stage of selecting and justifying the layout of the designed product. This knowledge must be evaluated, systematized, and uniformly formulated for unambiguous understanding by users. A clear structure of presentation will allow to formalize expert knowledge in the form of rules for its further use in automated synthesis. This article does not provide specific rules and algorithms for evaluating the quality of a rule, although they exist and have been developed. The rules for each subject area will be different, and the criteria for assessing the rules for each subject area will also be different. The article deals with the sequence of rules and their docking with automated synthesis. But most importantly, the docking stage is very important and should not be ignored at the initial stage.

The article describes a method for modeling a technological process, which can be represented as a non-linear system. The proposed method allows building a hierarchical structure of models of nonlinear systems or processes in accordance with the described principles of decomposition and the principles of the system approach. The resulting hierarchical structures of the models make it possible to fully describe the dynamics of the technological process as a whole. The resulting hierarchical model makes it possible to single out input, output, control and auxiliary sub-processes, which makes it possible to increase the efficiency of the technological process as a whole, taking into account its purpose and internal relationships. A hierarchical model can be obtained with varying degrees of detail, which is determined by the purpose and objectives of the process modeling. The article also provides a proof of the finiteness and countability of the levels and nodes of the hierarchical structure of the process.

Due to the global shortage of energy resources and a sharp increase in their cost, the problems of energy conservation become more and more urgent. A promising approach to solving the problem of energy saving is based on the principle of trigeneration, which implies the simultaneous production of electrical and thermal energy and makes it possible to reduce the energy intensity of production and the cost of agricultural products. Based on this method, the structural diagram of thermoelectric climate control system and its equivalent functional model have been developed. Transient processes of the linear and nonlinear thermoelectric climate control system for agricultural facilities with various coefficients of two saturation blocks have been obtained using the MatLAB Simulink environment. From their analysis it was found that the use of nonlinear control has significant advantages over the linear control and can reduce the time of transients, dynamic control error and oscillation.

Phasometric control methods in relation to the tasks of technological monitoring of various objects involve the isolation, analysis and tracking of the dynamics of the phases of their transfer functions in real time. At the same time, the number of spatially spaced point sources of the field should correspond to the detail of the network of phasometric control points. In this case, the generated signals can generally be arbitrary, and the differences between their parameters consist in setting certain amplitude-phase ratios that depend on the relative spatial location of the phase control points and point sources. Based on the proposed method, a multiphase field simulation was carried out using the example of geoelectric control, which has shown the effectiveness of phase-measuring methods and devices for recording variations of the object of control with sufficient sensitivity of the measuring installation.

The article presents a mathematical modeling of the spectral characteristics of the links of the path of generation of the control signal of the phase distortion autocompensator of digital computational synthesizers. The sources of distortion of the output signal of these devices are shown, which have a significant impact on their spectral purity and lead to undesirable phase modulation of the useful signal. The possibility of using automatic compensation to reduce the phase distortion of the output signal of direct digital synthesizers is considered. The functioning of the control signal generation of the autocompensator presupposes the isolation and processing of phase noise of the output signal. A model of the output signal of a direct digital synthesizer is obtained, taking into account parasitic phase modulation and distortions caused by truncation of the phase code, amplitude quantization and the nonlinearity of the converter from digital to analog form. The results of mathematical modeling confirm the effectiveness of the proposed algorithm for detecting phase impurities of the output signal of a direct digital synthesizer and reflect the functioning of the path forming the control signal of the phase distortion auto-compensator.

The problem of one-parameter one-variant selective set-making and assembly of two elements forming a precision one-parameter joint is considered. The key step in the selective assembly of products is the sorting of elements into groups by measuring their parameters, accompanied by mistakes caused by measurement errors. An analytical model has been built to take into account the influence of measurement error on the sorting process and to determine the number of assembly sets. A method is proposed to determine the number of suitable assembly sets from their total amount. The simulation results are presented. The results obtained are the basis for constructing models of more complex selective assembly systems.

In this paper, we discuss modeling and manipulation problem of the deformable linear objects (DLOs). The DLO is represented as a set of small rigid links connected with each other by points. Then, it is modeled as a mass-spring chain, which has linear and torsional components to represent the DLO internal potential energy (stretching and bending energies) and capture its deformable nature. Assuming that the DLO is controllable at its two ends, any change in these ends position leads to change in its internal energy. The developed model simulates the DLO behavior by updating the DLO points, excluding the end points, aiming to minimize the internal energy. To deform the DLO to a desired shape we formulate an optimization problem aims to reduce the error between the DLO and the desired shape and maintains its characteristics. The developed approach is evaluated in simulation experiments for several scenarios that prove its potential applications. The experimental results show a proper and stable performance of the developed approach.

Currently, there is an intensive development of digital communication systems, such as space, satellite, mobile communications, etc. During transmission, the signal undergoes a significant impact from interference of various physical nature (natural and anthropogenic). As a result, the task arises of ensuring reliable transmission of information over channels with interference, while the operating conditions of such communication systems are often such that the characteristics of input signals and interference are either not accurately known or change significantly over time. When transmitting data via communication channels, useful (user) information and service information are transmitted (destination address, redundancy introduced to protect data from unauthorized access to them, information necessary for all network participants to set up correct routing, etc.). It is important to note that already in 2017, the volume of useful and service information equaled, which has exacerbated the need to find ways to manage a complex high - speed data flow.

The article is devoted to the issues of automating the process of designing a technological route for machining machine parts. The problems of modern CAD systems that provide similar functionality, methods and approaches to building software modules for automating route design based on advanced scientific developments in this area are considered. An approach to route design based on network programming methods, graph theory and a probabilistic approach to meeting the specified requirements for the accuracy and quality of the machined surface is proposed. The approach involves the reduction of existing reference data on various parameters of the cutting process into a single structure - “tables of accuracy”. Using the methods of mathematical statistics, the probability of achieving certain quality indicators for various machining methods is estimated. Thus, the issue of route design comes down to solving an optimization problem with a number of restrictions (the probability of achieving the required operational properties of the surface, the range of machine tools, etc.) and the objective function - for example, the cost, the shortest route in terms of the number of technological operations and technological installations, etc. An approach is also proposed for integrating such a system in parallel with the process of designing and layout of technological documentation, linking to an electronic digital model of a part (electronic product passport).

This article is devoted to the practical implementation of the path following algorithm based on Line of Sight. The object of the study is a small autonomous underwater vehicle named as MiddleAUV. The motion control is implemented by means of PID controllers based on the distance to the point and on the course angle to the waypoint. The desired route is constructed from several waypoints. The transition from one waypoint to another occurs when the specified distance to the current waypoint is reached. Experiments were carried out in a special pool, and position fixation with the help of a video camera attached to the bottom of the submersible, and a marker chessboard. The experiments contained movement along a rectangle and an octagon, and were conducted in series to verify the validity of the results. The results of the experiments showed that the movement of the robot occurs in accordance with the planned route, the quality of movement corresponds to what was done earlier in numerical experiments.

In this paper, a control algorithm of three phase four-wired transformerless hybrid power filter (HPF) based on extended Kalman filter (EKF) with hysteresis current control is proposed to improve the performance of the HPF under real grid condition. The proposed control algorithm is designed to provide current harmonics mitigation and dc bus voltage regulation under distorted and unbalanced supply conditions. Compensating performance of a HPF controlled with traditional instantaneous reactive power control algorithm and control algorithm based a proposed Kalman filter approach with hysteresis current control is analyzed under distorted and unbalanced supply conditions using MATLAB-Simulink. The performance of the traditional control algorithm was found unsatisfactory under distorted and unbalanced supply conditions. Finally simulation results show superior performance in terms of high level of robustness and current harmonics mitigation of HPF’s efficiency under steady state conditions against grid supply imperfections for the EKF based control algorithm with hysteresis current control.

The results of work on the analysis of business processes of a private commercial educational organization are presented. The authors proposed an original toolkit based on the PM4Py Python library (developed by the Fraunhofer Institute for Applied Information Technology) for assessing the effectiveness of an organization. The developed toolkit allows the manager, based on a visual image of the process map and numerical metrics, to evaluate the performance of specific employees and branches of the organization, and the client's involvement in the educational process. During the implementation of the project, the tasks of adapting a set of events received from corporate CRM based on HCL Notes and integrating the developed tools into this system were solved.

This article considers the issues of automating the processes of student physical training for professional activity as part of engineering education under the society's transition to Industry 4.0. In these conditions the role of scientific, theoretical, methodological and practical substantiation of the necessity to use information and communication technologies for the student physical fitness in the professional activity is actualized. One of the main areas of optimizing the process of student physical training in engineering universities is the construction of individual path of student physical training based on the differentiation of training loads adapted to the level of student physical fitness. The problem of educational and training load managing on the basis of continuous record of the indicators of the main morphofunctional body systems can be solved by creating and implementing the innovative methods of educational process arrangement using the information systems. Building a system to control the physical training process with the use of information technologies defines the mathematical formulation of the control task and the development of algorithms for its solution. To formalize the process of physical training, mathematical and functional models have been developed as the basis for building an information system to control student physical training. The article also provides the substantiation of the proposal to use the Industry 4.0 technology for solving the automation problems of physical training management for engineering students.

This article discusses the software components and tools used to gather and present technical data for users of CNC machines. It outlines the key features required for remote data collection and analysis in CNC systems and explores how web technologies can be applied to monitor the performance of these machines. The article also provides a practical example of a monitoring system, called “AxiOMA Control,” which allows CNC operators and adjusters to select and adjust the parameters they see on a web page.

Text is one of the most common sources of information. Due to this, there is an urgent need for automated processing of text data. In vast majority of cases, classifiers are applied in text data processing. The object of this work is to develop a text classification processor for a decision support system in the Helpdesk-service-like applications. The modern approach to the text classification based on machine learning method with the engagement of artificial neural network is widely known. The article describes the most common methods for text processing and neural networks architecture. Considered are such text processing methods as: stemming, lemmatization, bag-of-words, N-gram count, TF-IDF. The following neural network architectures: multilayer perceptron, convolutional neural network and long short-term memory network. To find the most optimal algorithm for building up a processor there were considered 36 processors with the use of various combinations of the above methods and neural networks architectures. The article has an analysis and a comparison of a work quality of various classification processors conducted on such characteristic as accuracy. It was established that the processors learned on the data processed though stemming and N-gram count show the highest accuracy. The processor, at the construction of which were used stemming, N-gram count and a convolutional neural network, showed a maximum accuracy of multiclass classification. The accomplished work found an optimum choice of a classifier to be used in form of a module in decision support systems in the Helpdesk-service-like applications.

In this article the results of the development of integrated assessment modelling and forecasting of the agricultural areas productivity are presented depending on the technogenic and natural impacts, which include the dispersion and accumulation of greenhouse gases based on neuro-fuzzy data analysis. The digital transformation of crop production is part of a federal strategy aimed at adapting agricultural areas to climate change and obtaining a consistently high yield through the introduction of Industry 4.0 digital technologies and platform services. The software-algorithmic tools are presented to implement the method. The group of researchers considered a new approach to the adaptation of agricultural areas in the context of the greenhouse effect dynamics and proposed a new method of agro-ecological and natural-agricultural zoning of territories to increase the amount of crop yields. Practical implementation makes it possible to select evidence-based measures for zoning agricultural areas, thereby improving the efficiency of specific control actions for the adaptation of territories in terms of the greenhouse effect dynamics. Practical implementation of the approach is expected to increase the level of environmental and food security.

The paper considers the task of developing the house management company chatbot. The tasks solved by the chatbot are receiving and processing messages from citizens, conducting a dialogue, preparing and sending requests, and providing the necessary information to citizens. The main goal of chatbot development is to automate the work of dispatchers for house management companies. The paper presents the results of the study: the developed architecture of the chatbot system and methods for solving the main tasks that arise in the development of the chatbot, such as classifying messages and extracting named entities. Dialogue management that uses scripts is proposed. A tree-like structure of dialogues has been developed; a general diagram of the dialogue has been given in the form of a business process diagram and an example of a dialogue has been given.

Intelligent technologies are used in recruitment for the purpose of accelerating its procedure and hiring the most suitable for the vacant position and qualified staff. Despite extensive research in the field of applying artificial intelligence, data and text mining in recruitment, the issue related to the need of taking into account specifics of a job, for which a person is employed, has not been discussed yet. There are jobs for which using resumes, questionnaires, interviews or standard qualified tests as the basis for recruitment is insufficient. In manufacturing companies there is a number of positions whose responsibility is the design documentation control. The incumbents of these posts must not only have knowledge about how to develop the documentation in a particular aspect correctly, but also must be able to identify errors in it and formulate clear and focused remarks for designers. The paper offers an approach to intelligent support and system in hiring staff for the design documentation control, which are based on the combined use of rubric and text mining in assessing the professional skills of candidates. The proposed solution was tested for the possibility of its application in evaluating the professional skills of candidates on the example of the software design documentation.

The design documentation development and control of its quality is an important stage of the production process. The unsatisfactory control of this documentation made by approving persons will lead to problems such as: defects in products, financial loss, etc. in the future. Therefore, it is very important that as a result of the control carried out, the design documentation has had a minimum number of missed errors, and if possible—zero number. A large body of research is devoted to issues of increasing the design documentation quality, in particular the analysis of the errors identified in it. However, the analysis of the dependence between errors does not receive enough attention. A method and an intelligent system of approving person information support based on mining of association rules, reflecting the dependence between errors in the design documentation, are proposed in the paper. The suggested method and the system were tested during the normative control at one of the technical universities.

The existing methods for controlling the process of plasma-electrolytic oxidation are analyzed. A neural network model for calculating the coating thickness is developed based on the approximation of the experimental dependences of the coating thickness on time and the current parameters of the transient model. The developed solutions are proposed to be used for intelligent prediction of the thickness and properties of the coating based on the joint processing of information on all known and available dependencies of the parameters of the PEO process and the properties of the coatings. Machine learning and neural network models will make it possible to identify the most significant factors for ensuring the specified coating properties: structure (grain size, porosity), properties (corrosion and wear resistance), coating uniformity and their relationship with the characteristics of PEO modes (different current densities, treatment duration, plate arrangement, characteristics of the electrical signal, sound and optical radiation).

This work is dedicated to the problem of automatically creating structural models of text documents written in different languages. We describe the proposed method for creating structural models which is based on extracting sentences that correspond to various aspects of documents using BERT Question Answering model. We analyze BERT-based models and consider their application to the task of question answering in different languages. The analysis shows that monolingual models can provide higher quality than multilingual ones. We consider the problem of creating structural models when processing multilingual collections of text documents. We analyze several approaches to this problem based on monolingual and multilingual Question Answering models and show that the most promising approach consists in preliminary classification of documents by languages and subsequent processing of each document using a respective monolingual model. We also demonstrate results of experiments carried out on sets of articles in English and Russian languages that prove the advantage of the proposed two-step approach.

The article presents a study and analysis of known solutions and implementations of DNS servers, as well as the development of DNS server software, for which modern programming tools and technologies are used. In the process of development, the requirements for performance, scalability, security and reliability of DNS server are taken into account. The development of an efficient DNS server is an urgent task in today's digital economy. This paper aims to develop an efficient and reliable DNS server that will meet the requirements of the infrastructure of the digital economy. The results obtained can be used by organizations and enterprises to ensure stable and efficient operation of their network infrastructure. Also, the results of this work can be used to improve the quality of user experience in the field of Internet services, as DNS servers play an important role in ensuring the availability of web resources. The results are verified in real world conditions by testing the developed DNS server. Experiments are conducted to evaluate the performance and reliability of DNS server under different loads and usage conditions. The main results of this research are given in conclusion.

This article discusses an approach to the development of a software module for analyzing data that comes from process equipment. Various systems are analyzed, which are either complex vendor lock or simple systems for data collection, which lack the module of pre-active analytics and finding anomalies. The article proposes an algorithm for analyzing data from industrial equipment using machine learning. The k-mean method was used to cluster anomalies in technological data. The advantages and disadvantages of this method are described. The developed system architecture is described, which includes ClickHouse database with JDBC driver used, Apache Airflow data processing task management and scheduling module, and Pyspark, Scikit Learn libraries. After pre-processing the process data from the dataset (reciprocating compressor), a Random Forest model is trained on the labeled data, which why classifies the data into anomalous and non-anomalous. An interpretation of the results is given at the end of the paper.

The article is devoted to the development of software for building a behavioral assessment of a person based on the analysis of tones of texts from social networks. This software is aimed at collecting, storing and processing data of users of the social network “VKontakte”. The paper deals with natural language processing using deep machine learning techniques. In the paper, we need to analyze the tone of the text. One of our goals is to solve the problem of analyzing posts in social networks. The intonation analysis of the text allows us to understand what intonation coloring a particular post in social networks has - positive or negative. Based on the results of the work, we have proposed a working prototype of a web application for building a behavioral assessment of a person based on the analysis of tones of texts from social networks. The results of the research will be useful to organizations when hiring employees, when it is possible to get data on a particular person from a social network and preview them. Based on the conducted research with trained models, the most accurately trained model with the highest accuracy equal to 75.10% was identified. It was obtained while training the neural networks on a group consisting of 4 examples. This accuracy was achieved at the 5th epoch of training. The main results of this research are given in conclusion.

The environmental agenda and the issue of electricity shortage in some regions of the Russian Federation is acute in the industrial areas of the Russian Federation. Introduction of renewable energy sources along with traditional energy sources such as coal, gas, oil, etc. can solve this problem. However, the introduction of renewable energy sources is associated with a number of difficulties and limitations existing in the Russian Federation, at the moment. The paper provides an overview of renewable energy sources, potential for their development in the forthcoming years, threats and opportunities for these technologies introduction, as well as recommendations for the possibility of renewable energy introducing and developing in the Russian Federation.

The transition to reconfigurable manufacturing systems is not only a matter of modernization and development of production, but also it’s survival in modern conditions, where market changes dictate the situation. Since the beginning of research on this topic, a huge number of articles have been written by a large number of authors around the world, who, despite all this diversity, still do not specify the practical image of the reconfigurable system and it’s element—the reconfigurable machine tool, and the main problem remains the main reason for the beginning of the development of reconfigurable systems—acceleration their settings (reconfigurations) when changing external conditions, which largely depends on the units of equipment. This article summarizes and concretizes the subject area of the reconfigurable machine tool with the help of structural and functional modeling of IDEF0 and an ontological approach. A review of articles on reconfigurable machine tools was made to highlight practical features and requirements, the key materials for this article are given in the introductory part. The analysis of the developed ontology with aspects of the design of the reconfigurable machine tool made it possible to generalize the factors affecting the speed of equipment restructuring and highlight the solution consisting in the proposal of a reconfiguration plan. The construction of this plan aims to reduce the reconfiguration time by choosing a sequence of configurations that contains fewer elements involved and moves during the transition from one configuration to another. A metasystem approach has been proposed and described to form this sequence.

Using the Cognex In-Sight 8401 vision system alongside the ABB IRB-140 industrial robot, the researchers successfully engineered a software package that facilitates the creation of a sorting system. This remarkable accomplishment took place within the interdepartmental laboratory of automation and industrial robots at Moscow Polytechnic University. The authors not only created this innovative software package but also assessed its performance to ascertain its effectiveness. The collaboration between the Cognex In-Sight 8401 vision system and the ABB IRB-140 industrial robot enabled the development of a sophisticated software package capable of achieving efficient sorting processes. This cutting-edge technology was realized through the diligent efforts of the researchers at the interdepartmental laboratory of automation and industrial robots, situated within Moscow Polytechnic University. In addition to designing the software package, the authors went a step further by conducting an in-depth evaluation of its functionality. This assessment aimed to provide comprehensive insights into the system’s operational capabilities and potential areas for improvement. By meticulously analyzing its performance, the researchers ensured that the sorting system not only functions seamlessly but also meets the desired objectives. Ultimately, the pioneering work carried out by the authors within the interdepartmental laboratory showcases the successful integration of the Cognex In-Sight 8401 vision system, the ABB IRB-140 industrial robot, and advanced software development techniques. Through their collaborative efforts, they have not only developed a sophisticated sorting system but also thoroughly evaluated its performance, further advancing automation and industrial robotics research.

One of the important tasks of computer vision is non-destructive testing. This technology allows you to find faults and deviations from the norm by photo and video images. One of the applications of non-destructive testing technology is the analysis of metal products for defects. For this, computer vision algorithms such as convolutional neural networks, transformers, and others can be used. The paper considers the problem of defect segmentation in images. Four types of defects are identified for images of steel. Severstal data was relabeled using the Roboflow service. Segmentation models were trained and their comparative analysis was carried out. The results of the study showed that the transformer architecture models, namely SegFormer, provide the highest accuracy. In particular, the gain in terms of the Dice coefficient metric was about 1.5% when segmenting the test sample. However, the use of such an architecture leads to a slowdown in processing speed. It is shown that with the use of segmentation models it is possible to automate some of the tasks of monitoring steel products.

This article provides a methodology for analyzing the impact of digital transformation of the information security management process on the enterprise architecture based on internal indicators of the information security management process. The main internal indicators of information security management, which are changed during the digital transformation, were identified and described during the formation of the methodology. The following objects were formed to identify internal indicators: a description of the unified information security management process and a unified description of the enterprise architecture levels involved in digital transformation based on the TOGAF standard. The following internal indicators were considered: the level of information security, the effectiveness of information security, and the total cost of ownership of information security management processes. Thus, the main changes in the enterprise architecture were identified during the digital transformation of the information security management process.

A method for detecting particles in nanomaterial images based on normalized graph sections and binary segmentation is presented in the article. The method includes the following calculations: preliminary segmentation of the image into regions using the simple linear iterative clustering method; segmentation of the obtained regions by the method of normalized cuts on graphs, binary segmentation of the image based on the automatic selection of the threshold by the image histogram. The scientific novelty of the proposed method is the calculation of the threshold for binary segmentation based on a histogram. The binary segmentation threshold is calculated iteratively. The studies were carried out on images of nanomaterials obtained using transmission electron microscopy. The accuracy was used to numerically evaluate the results of the proposed method. The method does not require prior training. Also, the method does not require large computing resources. The practical application of the method consists in further calculation of the particle size on images of nanomaterials for the analysis of structures.

This article addresses the issue of traffic congestion in urban areas specifically related to intersection regulation. The second chapter focuses on an analysis of applicable computer vision technologies for traffic flow analysis. The third chapter discusses the selection of a neural network for analyzing vehicles at intersections. The fourth chapter covers data preparation and neural network training. The conclusion summarizes the obtained results. The study explores the use of computer vision techniques to improve traffic management and proposes the application of neural networks for efficient analysis of vehicle behavior at intersections. By leveraging computer vision technologies, it becomes possible to accurately monitor and regulate traffic flow, leading to improved road safety and reduced congestion. The research analyzes various neural network models and evaluates their effectiveness in vehicle detection, tracking, and classification tasks. Experimental results demonstrate promising outcomes, indicating the potential of computer vision techniques in addressing urban traffic challenges. The findings highlight the importance of data preparation and the significant role of neural network training in achieving reliable and accurate results. Overall, the study contributes to the growing body of knowledge on computer vision-based approaches for traffic analysis and offers insights into their practical implementation for addressing traffic-related issues in cities.

This article focuses on the analysis of vehicle movement at intersections in urban transportation networks using deep learning. The problem of optimizing traffic flow in cities, particularly related to intersection regulation, is a pressing issue that requires effective solutions. The second chapter of the article explores various methods for collecting raw data to build models for analyzing the congestion of urban road networks. Different approaches and technologies used in this process are analyzed. The third chapter provides an overview of deep learning models for object detection and recognition on images. Various models and architectures applicable for accurate and efficient analysis of traffic flows at intersections are discussed. The fourth chapter presents the methodology of the system, outlining the key steps and processes necessary for the successful implementation and operation of the vehicle movement analysis system at intersections. The methodology covers both technical and algorithmic aspects of the system. The conclusion summarizes the findings and describes the results of the developed system for analyzing vehicle movement at intersections. The presented results demonstrate the effectiveness of deep learning in optimizing traffic flow and improving intersection management in cities. The article makes a significant contribution to the field of traffic flow analysis and road movement by proposing a novel approach based on deep learning. The obtained results can be valuable for designing and optimizing urban transportation networks, reducing road congestion, and enhancing road safety.

Transportation is one of the most important parts of Russia’s industrial infrastructure. Its consistent and effective operation is necessary for stabilizing, evolving and restructuring the economy, ensuring the integrity, national security and defense capability of the country, improving the living conditions and standards of the population. This paper focuses on the security issues of transportation infrastructure facilities. It describes the general characteristics of a facility (a case study of Platov Airport, Rostov-on-Don) and its provision with engineering safeguards to ensure transportation, information and integrated security of a transportation infrastructure facility. The article provides statistics on the acts of unlawful interference in transportation infrastructure facilities between 2019 and 2021 (Platov Airport in Rostov-on-Don and Catherine II Airport in Krasnodar), facility categorization and vulnerability assessment.

By now, technological progress has reached high levels, simplifying human life, but also bringing new challenges to attention. Information security is one of such challenges. Information security of a city electric bus is critical for ensuring the safe and comfortable transfer of passengers. It involves targeted measures to provide confidentiality and protection of information, as well as to prevent potential cyber attacks. In addition to information security, it is also necessary to ensure transport security. Regular inspections of the technical condition of the rolling stock, training of drivers and passengers in the rules of safe behavior in transport are just a few of the measures that contribute to improving transport security in a city electric bus. This article intends to describe the main aspects of the transport security of an electric bus and the automation of this process.

This article describes the objects of the first category of power supply in the example of maternity hospital of the clinic of the Medical University of Chelyabinsk. There is a current power Supply Scheme and a group of electric consumers. The costs are calculated for electricity consumption under various schemes of power supply of the facility. It is also shown how the reduction in electricity consumption is associated with a reduction of carbon dioxide emissions into the atmosphere. It was suggested to use renewable energy sources as a way of power supply of the objects of the first category, such as wind turbines and Solar power plants. The cost of the equipment was calculated based on technical characteristics. It was also calculated the cost of savings on electricity consumptions from centralized sources. The benefits and the possibility of application of the renewable energy sources for objects of the first category are shown.