This PDF file contains the front matter associated with SPIE Proceedings Volume 12564, including the Title Page, Copyright information and Conference Committee lists.

A new conceptual approach to the creation of educational information systems is proposed. The relevance is due to a sharp increase in the number of students in IT specialties and an increased workload on teachers. The purpose of the development is to improve the quality of education for IT specialists while preservation an individual approach and attention of the teacher to each student. The developed cross-platform information system is packaged in a web-solution. The system contains the main website and three microservices: a plagiarism checker, a code tester, and an analytics module. The code testing module is a multi-threaded hierarchical system. The uniqueness check module searches for similar solutions to a specific task within the system. The analytical module processes data, including information about the quality of task solving to form a profile of each student. The Django framework was used to develop the server part of the software product. А traditional bundle of HTML + CSS + JS is used for implement the user interface. As a DBMS, PostgreSQL is used, which is implemented in Mospolyteсh, exists in the form of a beta version and corresponds to the modern practice of teaching IT at Russian universities

This article proposes an algorithm for automatic calculation of total cost of ownership (TCO) and server compute efficiency (ScE) metrics for data centers. The approaches described in the article allow to evaluate the efficiency of the data center. A comparative analysis of data sources is given, and, on its basis, information is presented on the possibility of calculating data center usage metrics. The developed algorithm was finalized to the software. The architecture of the software tool is presented, which allows calculating the TCO and ScE metrics. The results of the experimental application of a software solution are presented, which made it possible to calculate the ScE for a loaded machine and a machine operating in normal mode. And also with the help of the software tool, the results of TCO metric calculation for Dell server are presented.

The article discusses an approach to the analysis of static information based on the use of neural network technologies and regression models. The forecast for the neural network was made on the basis of official statistics, data on the development of advanced technologies, and also taking into account the current situation in the dynamics of the incidence in Russia for the period from 2003 to 2020. As a result, forecasts for the next 5 years were determined. Growth is expected to continue, but at a slower pace. At this stage, the incidence and the introduction of quarantine measures adversely affect the situation and lead to a reduction in consumption. It is worth noting that the trends in the production of innovative technologies will continue, despite the negative consequences of the pandemic. This is evidenced by forecast data.

The paper presents the developed approach and software system for the Data Mining of public channels and groups in the Telegram messenger, for which emotionally colored vocabulary is identified in the texts and the emotional assessment is calculated in relation to objects, processes, events, phenomena, i.e., the opinion of the author is formed. The opinions of the authors are divided into two types: direct opinion and comparison, and the tonality receives three main assessments: positive, negative, neutral. The software system is implemented in the Python using the Dostoevsky library. RuSentiment dataset was used for training. The software system evaluates public opinion based on the analysis of comments in public channels and groups, for which the software system searches for comments and analyzes them, generates results as graphs and statistical values. The developed software system was tested for certain search parameters, which showed the practical applicability of the solution. The software system evaluates the crowd reaction to a post or evaluate how they relate to any fact based on the comments under the post in Telegram.

The paper presents a two-step approach for detection and identification of fake (forged) fragments in photographic images. At the first step, the image is assigned to an original or a fake class by sequentially analyzing the image metadata (EXIF), then performing the error level analysis (ELA), and finally performing neural network analysis of the image. At the second step, the fake image is divided into fragments, each one is analyzed using a neural network for the fake detection, then the fragments that had recognized as a fake are analyzed by a classifying neural network, which makes it possible to identify specific types of fakes. Software has been developed that implements the proposed approach. The training of the used neural networks was carried out on the CASIA V2 dataset, which contains 4795 images (1701 genuine and 3274 fakes). Studies have been carried out to verify the effectiveness, for which, using the developed software 60 photo images were processed, 30 of which are genuine, and 30 are fakes. The developed software correctly identified both the fake fragments and determined their types.

The paper considers an active reconfigurable reflector based on an active metamaterial with the possibility of dynamic control of antenna characteristics. Due to the use of the developed design, it is possible to ensure the formation of a multifunctional dynamically tunable antenna. It is capable of generating both omnidirectional radiation and directed in the main directions: 0, 45, 90, 135, 180, 225, 270, 315 degrees. Using switching devices (pin-diodes) it is possible to achieve fast switching of antenna operating modes, as well as to ensure the operation of an active reflector in a wide frequency range. The results obtained during the simulation are supported by experimental studies of the antenna model with a reflector. Switching of operating modes is possible based on a computer.

The article considers the possibility of studying the characteristics of the electromagnetic field to ensure improved coverage by mobile stations. When ensuring optimal coverage, it is required to correctly determine the direction of arrival of electromagnetic waves, however, the housing that the direction finder carrier has makes errors in measurements. To solve this problem, it is proposed to form a virtual magnetic direction finder, which will detect the wave arrival with high accuracy. The article presents a mathematical calculation algorithm and simulation results.

The article proposes a solution to the problem of handwriting recognition using the capabilities of convolutional neural networks. The architecture of the created ConvNet is described. The main stages of the neural network design process are listed. The created neural network allows to recognize the numbers and letters of the Russian and English alphabets received at the input using various input devices (mouse, graphics tablet, touchpad, etc.). This algorithm can be applied to the analysis of handwriting calligraphy and its correction. Examples of the use in practice of a digital tool created by the authors are given.

The article discusses the possibilities of involving citizens in managing the quality of the urban environment by extracting and evaluating their opinions from unofficial sources of information, namely social networks. Currently, the method for assessing the emotional sentiment of text messages is used extremely limited due to the high costs of attracting groups of analysts. The development of a model for analyzing emotional sentiment makes it possible to expand the capabilities of assessment tools used for making management decisions by involving the population in issues of managing the urban environment. Due to the software implementation of the model for collecting and analyzing emotional sentiment, one can analyze actively discussed topics on improving the quality of the transport sector. Variants of estimates have been obtained, which can already be used in operational management. The role of the population in improving the quality of life is growing, especially with the development of the concepts of a "digital city", therefore, adaptation and development of the method of assessing emotional sentiment itself can be in demand in all areas.

The aim of the work is to develop a motion control system using an object-oriented programming approach. The objectives of the work are to build a mathematical model of the motion control system and develop an interface for user interaction with the program. The developed interface can be used as a simulation of the operation of surface vehicles, testing and debugging of the control system.

Based on the intellectual analysis of the momentum effective scattering surface (EPS), a physically interpretable set of initial features for recognizing 3D objects of optical location is proposed. The space of informative features was formed by the method of principal components and its cluster structure was studied using the example of three anthropogenic objects. A technique for synthesizing a Bayesian classifier of 3D objects is presented. Classification errors of the first and second kind are analyzed.

This paper proposes a three-level modular architecture of an automated process control system for a modern greenhouse complex that uses the CAN bus as an interface. The lower level contains sensors, actuators, edge analog interfaces. The intermediate level contains input and output modules, data collection, control units. The upper level is the SCADA system, a personal computer on which a server is deployed, which receives and aggregates information from logic and data collection modules and provides the user with a graphical interface for monitoring and controlling the process. The architecture is characterized by scalability, modularity, and coverage of all technological processes of modern greenhouse cultivation. The block diagram for the architecture is provided. As an automation object, we consider a greenhouse for vertical cultivation of microgreens using low-pressure aeroponics technology. The experiments show the ability of a system based on such architecture to meet the time criteria of technological processes and interaction with users. Further work consists in developing a specification for the described modules, formulating requirements for them, performing the design, development, manufacturing and testing.

Nowadays medicine needs high information technologies. Automation of the processes of diagnosis, stratification and treatment of diseases belongs to the priority tasks in modern medicine, since it allows increasing the efficiency and reliability of working with information, data accuracy and completeness at all stages of the medical process. Smart ward is an integral approach to automation of this process. This paper proposes an approach to creating a module for diagnosing, stratifying and selecting treatment of the paroxysmal sympathetic hyperactivity syndrome and highlights the advantages of using this module as an intelligent component of the smart ward. A data model defining medical data for this particular task is built and described using UML class diagrams. It can be seen that the model entities and their properties partially correspond to the entities and properties in the smart ward model, which allows linking local and global databases and provide higher completeness and reliability of patient information, which, in turn, will increase the efficiency of the system in general. Further research includes building a behavioral model of a smart ward and defining the scenarios of its operation, taking into account specific tasks, such as identifying paroxysmal sympathetic hyperactivity or other syndromes, determining the set of ward components necessary for the implementation of these processes, and choosing protocols for their interaction.

This paper presents the result of the development of a software package for the study of MIMO systems, in which various methods of detecting MIMO systems in channels with fading and in channels with space-time coding can be investigated. In addition, the work presents a research of the MMSE algorithm using a modified Kalman filter. The package can be useful both from a research point of view and in the design of the most optimal telecommunication systems.

One of the priority tasks in the field of meteorology is the search for solving problems related to the assessment and forecasting of the quality of the air environment. The article presents an analysis of existing information systems for air quality control. Thus, in many cities there are no instrumental and automatic controls that allow assessing the state of atmospheric air in real time, as well as around the clock. The presented automated air pollution control systems of the ANKOS-AM and ASKOS-A types require further improvement in order to expand the number of determined ingredients or install a large number of automatic stations in the city, which is not feasible on a regional scale. For automated control of the concentration of pollutants, programs have been developed, one of which is the "Ecolog" program, designed for use in local monitoring systems within the city. For regional monitoring, it is necessary to develop and adapt your own mathematical and simulation models of the transfer and dispersion of pollutants, taking into account the specifics of the region (relief, type of underlying surface, weather conditions, etc.). The mathematical model of the transport of pollutants on a regional scale proposed in the article allows taking into account the specifics of a given region. It is built on the basis of statistical (Gaussian) models. This mathematical model can take into account special processes (initial jet rise, chemical interactions, washing out and settling of particles), affecting the transfer of impurities on a regional scale.The developed software package allows you to build a unified regional system of analysis and control.

The use of various modern technologies is increasingly being used in agriculture, which has formed such a direction as precision farming. At the same time, the goal of this direction is to increase productivity while optimizing the use of pesticides and fertilizers while minimizing costs. The main analyzed indicator is the state of the biomass, for the assessment of which, mainly, the indications of the optical range are used, on the basis of which various vegetation indices are calculated. These readings are collected, as a rule, using UAVs. However, the introduction of Internet of Things (IoT) technologies also makes it possible to obtain a number of soil indicators that are significant for the state of biomass. At the same time, the integration of various sources of information is not performed. The use of information integration makes it possible to refine the readings of the optical range and cut off a number of necessary analyzes to normalize the state of the biomass. The authors have proposed a mathematical model based on the fuzzy clustering algorithm for identifying the state of biomass, which makes it possible to integrate optical and radio data. The experiment showed that the proposed model allows not only to assess whether a biomass site belongs to a certain state, but also to track transient processes by calculating the degree of correspondence to clusters.

At present, it is generally recognized that robotics classes develop the engineering thinking of children, give them ideas about the work of designers, engineers, programmers, etc. In this article, we present the solution of one production problem by schoolchildren using computer vision technology. The paper details how, with the help of different robotic kits, three different solutions to the same task were designed and constructed, each of which differs in functions and characteristics. The process of building an automated robotic complex allows students to understand how the choice of design affects the performance of the system. The paper describes the problems that arose at various stages of solving the noted problem. Successful overcoming of all problems was achieved using a minimum number of robotic modules.

Population models that take into account migration are considered. The purpose of this study is to construct a system of differential equations, taking into account the peculiarities of the life of acridids. To take into account such phenomenological observations of the spatiotemporal dynamics ¬of the population size, it is necessary to introduce migration terms that depend on the size. One way to take this into account is to introduce ¬gradient terms into the reaction-diffusion equation. One approach to solving this problem can be the assumption that the mobility of individuals, that is, the diffusion coefficient is not a constant value, but ¬depends on the density of the population. The paper considers the case of dependence on population density in a power-law manner.

Currently, the rational distribution of cotton and fodder crops with their combination in crop rotation fields is relevant. This task is solved in two stages. The first is the placement of cotton and other crops in the fields of crop rotation. The implementation allows determining in which field a particular crop should been sown. Such a task considers as a static one and its model develops taking into account the main natural and economic conditions of the economy. The second task considers as dynamic. It allows to determine in which years of rotation in which field a particular crop should been sown. The development model of the task bases on information obtained from the static task and from the crop rotation table in the crop rotation. The main purpose of the article is to solve the problems of optimizing the placement and rotation of crops in the cotton crop rotation. The genetic algorithm is used to solve this problem. The computational experiment was implemented

In this paper, the aggregated random event sequence, representing network traffic, obtained by combining multiple random event streams with known statistical characteristics is analyzed. For this, an algorithm to generate random event streams representing a sequence of received network packets with a certain distribution law and correlation function is used. Random event streams simulating on/off traffic sources, where one part represents packet inter-arrival times and the other represents packet processing delays. Then two or more on/off source sequences are combined into one using original algorithm based on the Virtual Output Queueing (VOQ) approach used in network switches to mitigate head-of-line blocking issue, taking into account the priority of the input sequences. Then the statistical properties of the resulting aggregated sequence are analyzed.

Providing the population with high-quality drinking water depends on a number of factors: the state of water supply sources, sanitary zones, and the sanitary condition of water supply networks. The use of worn-out water supply networks has a direct negative impact on the quality of water supplied to consumers and unpredictable failure of the distribution network (pipes) and valves. In this regard, there is a need for a hygienic assessment, analysis, forecast of the centralized water supply system of cities and towns using modern information technologies. In the presented work, the structure of information and analytical support for the centralized water supply monitoring system has been developed. There are three main levels for monitoring the centralized water supply system. The technical implementation of the control of the sanitary and technical condition of the centralized water supply system is considered. An information model of a centralized water supply monitoring system using GIS is presented. The GIS subsystem generates the data necessary to present on the electronic map of the region information about control points and characteristics of electrical conductivity, hydrodynamic properties and the current sanitary and technical condition of centralized water supply. A software package for data collection using a SCADA system, visualization tools for presenting statistical data and forecasting results on an electronic map is presented.

The article discusses the principles of using digital tools as a means of improving the efficiency of the processes of the agro-industrial complex. In addition to direct use, the stages that allow the digitalization of a process or operation of the agro-industrial complex are considered and algorithmized. The relevance of this topic is confirmed by the strategic focus of all processes of the agro-industrial complex on improving the energy efficiency of both final products and technological processes. It is proved that it is possible to solve effectively the problem by using notational methodologies that allow decomposing digitized objects. Decomposition is carried out by projecting a cybernetic approach: entry, exit, restrictions. Since the fulfillment of the requirements for the energy efficiency of products and developments imposes, in addition to economic restrictions, also environmental ones, the process of manure utilization was taken as an example of a digitalized object. With regard to this object, a positive experience of using the described principles has been obtained. It has been established that the efficiency of the implementation of this process using digital tools increases by at least 18 ... 27%. Further increase in efficiency requires an increase in arrays, available data, and refinement of the used approximating connection functions. The results obtained in this article can be used in the digitalization and intellectualization of most processes in the agro-industrial complex.

Every year, international peer-reviewed databases of publications, such as Scopus or Web of Science, are replenished with tens of thousands of papers, which entails the need for a systematic analysis of such databases. An effective solution to this problem is to create a software system that allows to analyze the publication activity of both countries, cities, universities, and individual authors. This article is focused on developing system for Scopus publications analysis. The analysis was conducted for articles published between 1985 and 2022. The volume of processed data is 200 GB. The list of analytics tasks is presented. It includes statistics of changes in the number of articles on the portal, a rating of the most widely published countries, cities, universities and authors, statistics of changes in the size of publications by year were revealed, an analysis of the most popular research areas, the most frequent months of publications. A number of limitations of working with the Scopus API were identified, and the paper presents ways to circumvent them. Proposed software solution is described. The paper contains approach to collect, handle, and visualize dataset. The practical significance of the work is to create a flexible big data analytics tool for Scopus publication activity.

The research is devoted to the use of artificial neural networks (ANN) for signal processing. The features of the simplest feed forward neural networks (multilayer perceptrons, MLP) application are analyzed. When using MLP in a sliding time window, it allows to solve problems of signal approximation with high accuracy and to determine their parameters when analyzing dynamic processes. If the signal can be set by analytical formulas with random parameters on separate time intervals, then after training, MLP can be implemented in microprocessor equipment for real-time signal processing. The ANN training algorithms and the errors of the proposed signal processing method are discussed. The approach does not require "deep learning" and a complex ANN structure, it allows one to control the accuracy of algorithms at intermediate stages of calculations. The results are of interest for electrical engineering and smart energy systems.

It is advisable to use mathematical modeling of industrial enterprise operating with the help of information technologies when there is a limited number of options, that`s why the problem of acceptable complexity arises while developing decision-making algorithm for computer system recognition in different technical, industrial, economic and management areas. The problem acquires a special importance when the recognition algorithm is based on the compound Bayesian procedures of decision-making which are characterized by a great calculating complexity. The article considers the peculiarities of recognition algorithm operation based on graph-scheme presentation of a priory information to make a decision about the situation class with compound Bayesian procedures. The algorithm complexity is assessed, the approaches to introduce the graph-schemes in the memory of computer systems which reduce the memory requirements are studied. The mathematical methods of graph theory, probability theory, complexity and combinatorial theory are used. The research results in a new method for space complexity reduction of the compound graph-scheme algorithm for situation recognition which enables to provide the efficiency of its calculating complexity. A revised version of the algorithm was suggested. Analytic expressions for calculating parameters of space representation of modified graph-schemes were obtained, their correctness was proved on specific examples.

In this article, simulation modeling was carried out in the AnyLogic system. A simulation model was created that simulates cardiovascular diseases in people depending on age. This model can be used for statistical diagnostics and identification of risk groups for diseases of the cardiovascular system and in the future will allow taking the necessary measures to prevent and reduce the likelihood of these diseases in people at risk.

Rodent control stays an urgent problem for the modern agriculture. Rodents can damage more than 30% of the crop. One way of the rodent control is rodent burrows counting, which can be done using agricultural robots that can automatically gather images of the agricultural fields with the rodent burrows and perform semantic segmentation of that images in order to establish the number of rodent burrows. This work is devoted to the problem of agricultural robot computer vision system development, namely rodent burrows semantic segmentation using deep convolutional neural networks. This work presents a new dataset which contains 247 manually segmented images with rodent burrows on various surfaces. Rodent burrows semantic segmentations are performed using the following deep neural networks: SegNet, U-Net. Training these models on the presenting dataset show the following sematic segmentation results according Intersection over Union metric: 0.511 and 0.548 SegNet and U-Net correspondingly. The experiment shows that SegNet outperforms other considering models in semantic segmentation results. At the same time, it has minimum among the other model’s computation complexity, which is crucial for robots onboard computer system

Corona discharges that occur on the conductive elements of power lines are serious problems that can lead to failures in the power system. Corona discharge produces ultraviolet (UV) radiation, which can be detected using special UV sensors. One way to automate inspection of the corona discharge is using of autonomous unmanned aerial vehicles (UAVs) equipped with UV sensor. At the same time, the trajectory of the autonomous UAV flight should be built taking into account the spatial and geometric features of the inspected power lines, as well as the requirements for the gathered data. This work describes a new method for autonomous UAV trajectory planning. The trajectory is planned in accordance with the spatial and geometric characteristics of the inspected powerline, peculiarities of the powerline damage type and in accordance with the quality requirements for the gathered data (representativeness, sample size, unification of the gathering procedure). The trajectory planning method and UV image gathering were simulated in Blender software. As a result, by the fully automated data gathering process, we collected a representative dataset of 200 images in UV spectrum for one lattice tower and two simulated discharges with 326 manually segmented corona discharge areas.

The manuscript deals with the features of the development of control programs, working with which is similar to performing laboratory work. The development of such programs is based on computer visualization of graphs. To depict the work of algorithms on graphs, different color schemes and different designations are used to convey the processes of manipulation with graph elements. The developed programs provide interactive work with the material and implement learning by action. The article deals with the algorithms “Search in Breadth” and “Search in Depth”, the Ford-Bellman shortest path search algorithm, the Terry algorithm for finding a route between two different vertices. When writing programs, object-oriented programming technology was used. Various classes have been created to model the structure of the graph and its various states

In object recognition systems based on template matching by calculating the distance metric between preassigned templates and given object, the template selection can severely affect the recognition quality. This article presents a novel method for image selection in object recognition systems, which can improve the identification quality. Its uniqueness lies in the fact that the images, what is the best for further recognition, were selected automatically in a way that provides the best quality. The technique is based on a SOM (Self-Organizing Map) and k-mean clustering. In this article, we describe the selection procedure and show the result of its usage in the system.

In the clinical practice of medical diagnostics, special attention is paid to the problems of the formation of symptom complexes that classify diagnostic objects by world researchers as a result of an increase in the number of symptoms that correctly identify diseases. As a rule, this research was limited to the transition from the entire proposed group of symptoms to a small group of symptoms, that is, the selection of a significant group of symptoms, the size of which was small, based on a rule of law or criterion. And this group of symptoms is called symptom complexes. According to recent studies by scientists from all over the world, the total sum of the totality of selected symptom complexes in relation to the number given as symptom complexes is understood as the result of an increase in the number of symptoms included in this group compared to the previously indicated quantitative indicators. Here, the research is carried out in two stages: initially, a set of all symptom complexes is determined in relation to the required number, then the total amount of the complexes is obtained. These suggested actions will be related to the development of strictly based mathematical methods and algorithms, theoretical research and algorithmic and software for solving practical problems. The article analyzes the diagnosis (classification) of medical logotypes based on informative symptomatic complexes (see Table 2) selected for ischemic heart dis-eases (5 classes, so class X1-,“Stenocardia tension”, class X2-“Acute myo-cardial infarction”, class X3 -“Arrhythmic form”, class X4-“Postinfarction cardiosclerosis”, class X5- “Permanent form of atrial fibrillation”) obtained as an object of study, based on the proposed algorithm.

The study of permanent state satellite networks and triangulation points is carried out in the article. During field research, the error of determining coordinates and distances by satellite methods was studied as they moved away from the reference station based on the materials of the authors' research works in the Samarkand region. The construction of a network of reference stations is a new technology based on the use of satellite facilities, in order to increase accuracy for solving geodetic support.

This article presents the results of the conducted field research of two electronic total station, included in the park of geodetic devices performing geodetic work. The article is written on the materials of research work that the authors carried out in the Samarkand region of the Bulungur reference satellite geodetic test site. Electronic total stations, along with receivers for Global Navigation Satellite Systems (GNSS), are now among the most popular tools for surveying and geodesy. One of the important requirements of users to these geodetic instruments is the accuracy of their measurements, on which the accuracy of the surveying and geodesy work performed depends. The studies were carried out on a specialized reference geodetic network, approved for such tests, which is a reference tool for metrological certification of geodetic instruments.

The purpose of the study is to evaluate the technological process of suction of a road estimate by a vacuum sweeper at production sites. The article presents the results of using computer simulation when choosing the design and technological parameters of a suction device with a receiving window.

Currently, one of the most pressing issues in the deployment of smart contracts is security. Concerns about inefficiency, security, and dishonest behavior are well-founded, so ignoring them when using the blockchain network to create smart contracts can lead to extremely high additional costs. The article deals with the most common tools for smart contracts auditing. The purpose of this article is to compare the most popular software tools for smart contract security analysis. Smart contracts were used for this purpose that were recognized as secure with a high degree of probability (hereinafter, for simplicity, known as secure or secure smart contracts), as well as vulnerable or simply vulnerable smart contracts. In total, 20 DeFi smart contracts from the Ethereum blockchain network written in the Solidity programming language were used for analysis.

This study provides an overview of encrypted unregulated digital assets (cryptocurrency). Recent developments in various countries of the world are analyzed. A forecast is made on the development of the cryptocurrency market in the next 10-15 years. A conclusion is made about the relevance of cryptocurrency today and in the near future. Prospects for the development of encrypted unregulated digital assets (cryptocurrency) are considered and analyzed.

This article is devoted to developing a management model for public services on digital platforms in the Republic of Angola. The digitization of public services provided by the Angolan government to its citizens is now a reality and an integral part of the adopted modernization programs. Since 2019, when the e-government platform was launched, the definition of digital governance policies and digital citizenship platforms in public administration has become an important issue. The aim of this work is to propose a digital public service management model focused on the services most urgently needed by Angolan citizens. In addition, an administrative survey was conducted to identify the needs of citizens and/or officials related to the digitization of public services in the Government of Angola. The focus of this study is to search for results that will help improve the quality of services provided and to provide tools for designing ideal ways to support digitization to meet the needs of citizens. In Angola, however the efforts the government has shown in implementing, simplifying and modernizing e-Government to bring citizens closer to services, the government needs to keep pace with advances in the digitalization of the service sector, better identify citizen needs, evaluate existing technologies, and determine what how to apply them, and look for ways to more actively involve citizens in the digitization process and the use of these services. In this regard, an urgent task is the development and implementation of models for managing public services on digital platforms.

The article discusses the main features of the use of digital technologies in the design of light industry products, identifies the main aspects of digitalization in the fashion industry, offers a technology for digital design of models, developed digital models of samples of materials, accessories, sportswear, taking into account ergonomic requirements.

The work considers the use of information technologies, taking into account the digitalization of the energy sector in the training of personnel for the operation of electrical installations. Changes are considered in the new edition of the Rules on Labor Protection during the Operation of Electrical Installations (RLPOEI) taking into account the digitalization of the economy. It is shown that in the training of qualified personnel for the digital economy, the use of end-to-end technologies, VR-technologies is necessary. The digitalization of the educational process is considered on the example of the use of information technologies to ensure the optimal ratio of distance learning and full-time. In the educational process, information technologies are used - VR-technologies to develop the skills of working in electrical installations under various operating modes of the equipment.

The article presents a three-factor demand forecasting model based on a regression-correlation analysis of the economic process of demand for industrial products. The model, based on many factors, will make it possible to assess the attractiveness of each settlement, which implies a phased expansion of the network of industrial enterprises in the territory of the Russian Federation. The model compiled on the basis of regression-correlation analysis includes two factors: an indicator of the efficiency of small and medium-sized businesses and an indicator of the effectiveness of corporate business. Performance indicators for each line of business are calculated as the sum of the factors that explain this indicator, weighted by significance factors. In the performance indicators of small, medium and corporate businesses, the most important factors are the quantitative characteristics and financial condition of small, medium and corporate businesses, and the least significant factor is the personnel of these entities.

This article deals with the analysis of data obtained from databases of learning management systems to organize student-centred learning with the application of course adaptation methods by changing the set of asynchronous and synchronous learning tools. The relevance of the research in this area is due to the current teaching paradigm as well as the increasing volume of digital data available to universities. The aim of the study is to investigate the possibility of effectively influencing the educational process based on the results of data aggregated from learning management systems (LMS) using cluster analysis. The results of the study confirm the possibility of dividing students into clusters based on their success in perceiving synchronous and asynchronous educational methods, and the effectiveness of corrective impact on the respective clusters of students to improve academic performance. As a conclusion the author made a statement about the effectiveness of practical everyday application of learning analytics aimed at person-centered learning.

This paper provides an overview of the economic state of the market, taking into account objective risks affecting economic security. The possibility of constructing simulation models using systems of nonlinear equations is considered and justified. The understanding of global and local sustainability is substantiated. By using mathematical apparatus, the possibility of the existence of a negative impact of competing players operating in a particular market sector is considered. We define the conditions necessary for the existence of civilized competition, taking into account the peculiarities of matrix calculus. The possibility of presenting the described conditions of local stability of the stationary state of the system using a parametric approach is substantiated, and the conditions of stable competitive equilibrium of the system are formulated.

Digitalization of economic processes has influenced the existing mechanisms of analysis and structuring of market relations and created new forms of organization of interaction between companies and potential consumers. The digital economy has led to the development of a new business orientation – customer orientation. The basis of the successful digitalization of the economy is a marketing approach. The result of planning marketing activities in a digital environment is the development of digital marketing strategies. As part of strategic planning, the main elements of future interaction between companies and consumers are being worked out, content in demand from customers is being created, and new ways of supporting the target audience are being formed not only in the process of making a purchase decision but also in after-sales service.

Currently, a very urgent problem is the development of approaches related to risk assessment in the Internet of Things systems. We consider a number of objects in the IoT system. For each of the objects, a certain set of risk factors can be designated. The approach that uses cluster analysis is considered. The criterion is used, that relate IoT objects with corresponding vulnerabilities. The illustration of the main steps of the algorithm for generating models for determining the risk associated with vulnerabilities in the Internet of Things is given. The results of analysis of the significance of risk factors and assessing the adequacy of the model for determining the degree of risk deterioration among objects of the IoT system are shown.

Currently, a very urgent problem is the development of approaches related to the management of organizational systems. It is necessary to develop an apparatus for formalized description, optimization and expert assessment, focused on decision-making with the multivariate nature of the interaction of digital means of the control center and objects of the logistic part of the organizational system. The decision-making algorithm for the optimal choice on the set of fixed options for the structure of digital control is considered. The decision-making algorithm for the optimal choice on the set of variable options for the cluster structure of digital control, considering the boundary requirement is shown.

Researcher has presented the modern software systems which are used to train food industry specialists in the bachelor's program of the Moscow State University of Food Production. Author has presented the features of the modern Russian Federation education system. It has been highlighted the most significant elements in the process of training specialists at the bachelor education level. There are the main virtual laboratory installations which are used to train specialists in the areas of 19.00.00 (Industrial ecology and biotechnology), 16.03.03 (Refrigeration, cryogenic equipment and life support systems), 16.04.03 (Refrigeration, cryogenic equipment and life support systems) at the department of Processes, apparatus, refrigeration equipment and technologies. The main elements of three virtual laboratory complexes, which are used for conducting laboratory classes, has described in this paper by author. Researcher has considered the summary plan of the laboratory works, as well as the main positions of the methods for conducting these laboratory classes in the virtual software systems. There is a review of modern virtual laboratory complexes, which are used in the training of specialists in different fields of study in bachelor's and master's programs in this article. Author has described the modern trends in the improvement of the developed educational laboratory work. Also researcher has considered the teaching methods for them in this paper.

Theoretical information about network equipment and protocols for their interaction, information about implemented hardware, such as switches and routers in connection with the active spread of such a profession as a programmer are considered in the article. The introduction of a large number of information equipment in people's lives has led to a global transformation of the digital space. Due to the digital transformation and the need for uninterrupted and high-quality sending of information over long distances with minimal losses, as well as the need to introduce theoretical and practical material on modern technologies for information data transmission networks, principles for constructing telecommunications systems and networks are being developed, specialized hardware for resolving configuration issues by checking the functionality of networks is being designed. In the work, authors have analyzed the demand for the transfer of information data today, have noted the principles of interconnection and building of local networks, have reflected the revised and supplemented material of the manuals. Information about the functioning of devices is also presented on the example of CISCO software and hardware. Based on the studied data, a step-by-step instruction has been developed to teach students to network security technologies, gain theoretical knowledge about the main commands used in the Cisco IOS operating system and about the concept of configuration. It is noted that in order to carry out proper configuration of network equipment, it is necessary to use a software network emulator called Cisco Packet Tracer. On the basis of the data, a laboratory work has been developed. This laboratory work allows to develop the professional competencies of young specialists. Due to the presented work, engineers consider the features of the operation of switches and routers, study the routing of networks and other software and hardware devices.

The role of packet switching technology for modern networks is analyzed. "Cisco Packet Tracer" software network emulator is considered to determine the functionality of configuring networks, as well as the formation of professional competencies of students in the field of network technologies. The positive and negative aspects of working with a network resource are given. The Cisco Virtual Academy is being analyzed. This allows to highlight the actual problems and features associated with the tasks of forming a student as a highly qualified specialist in the field of packet switching.