No. 6 (2023)

This paper investigates the problem of integrating local and global motion planning methods
in a robot control system. The current level of technological development allows mobile robots
not only to follow predetermined coordinates, but also to make real-time decisions independently
of the operator, reacting to changes in the environment. However, the dynamic nature of the environment and the constraints on planning time, as well as the high speeds of mobile robots, complicate
the problems solved by planning algorithms. In this paper, some motion planning methods
based on cellular decomposition (such as A*, D* and Wavefront) and random search procedures
on graphs (such as fast growing random RRT trees and probabilistic roadmaps PRM) integrated
with a motion trajectory prediction algorithm (DWA) are reviewed. A study of the performance
characteristics of each of the above algorithms has been conducted, as well as a series of numerical
and in-situ experiments to analyze the effect of map topology on the execution time and
memory usage of the algorithms. The effect of the speed of local and global planning under different
configurations of the external environment was investigated. To confirm the effectiveness of the
investigated algorithms in real conditions, software for a mobile robot based on a wheeled chassis
has been created. The paper presents structural and functional schemes of interaction between the
implemented modules of planning and motion control of the mobile robot and the environment.
It also presents a mathematical model of a wheeled platform, for which, based on the considered
methods, motion planning algorithms are developed. In this paper, quantitative measures including
the computation time of the motion planning algorithm and the amount of memory used by the
algorithms under different environment maps are evaluated. Both environments with randomly
placed obstacles and different types of mazes are considered. The implementation of the developed
algorithms in the ROS-2 environment is also described. It is shown that the implemented system
provides real-time control and motion planning of the mobile robot.

The emergence of new technologies for manufacturing components of digital electronic devices
has led to the need to improve the efficiency of computer-aided design methods. Increasing
requirements for elements causes an increase in the size of the problems being solved. To solve
problems that were previously impossible to automate, new methods and software applications are
being developed. Specialists are faced with the task of developing fundamental principles for constructing
next-generation design systems. The development of devices with such characteristics as
reliability, survivability, and automatic damage repair is an urgent task. This paper proposes an
approach to solving the problem of synthesizing combinational circuits based on the use of evolutionary
design methods. Evolutionary design of a technical system refers to the purposeful use of
computer models of evolution at all stages of system development. The goal is to enable fully automatic
design. The main idea of self-reconfigurable hardware systems is to replace generalpurpose
hardware systems with systems that can adapt to the specifics of the software being executed.
The synthesis of a programmable circuit is based on the principle of “bottom-up” design –
from the lowest to the highest level. This allows you to configure the hardware individually by
programming logic elements. To implement this task, evolutionary algorithms are used. Logic
functions can be described by combinational circuits. One of the advantages of combinational
circuits is their high performance. The task is to develop the structure of a combinational logic
circuit based on a given truth table and nomenclature of logical elements. The work proposed an
evolutionary algorithm for the synthesis of combinational logic circuits. A technique for encoding
alternative solutions and modified evolutionary operators for synthesizing new solutions were
developed. A software implementation of the proposed algorithm has been completed. The computational
experiments carried out confirmed the correctness of the chosen approach. The use of
evolutionary methods for the synthesis of combinational logic circuits makes it possible to increase
the intelligence of design systems.

This article discusses recursive filters with finite impulse response and filter banks. The filter
bank is an array of bandpass filters. The analysis filter block divides the input signal into several
components, with each of the sub-filters carrying one frequency sub-band of the original signal.
On the contrary, the synthesis filter block combines the output data of the sub-bands to restore
the original input signal. In most applications, certain frequencies are more important than others.
Filter blocks can isolate various frequency components in the signal. This way we can put more
effort into processing more important components and less effort into processing less important
components. Subband filters can be combined with step-down or step-up sampling to form a bank
of multi-speed filters. Filter banks are widely used for speech recognition and speech quality improvement.
Currently, filter banks have expanded their application to video and image processing.
In addition, filter blocks are very useful in communication systems, including digital receivers and
transmitters, pre-coding of filter blocks for channel alignment, discrete multi-tone modulation and
blind channel alignment. The use of these filters for hearing aids is considered. An 8-band heterogeneous
bank of recursive filters with finite impulse response (FIR) with high computational efficiency
for hearing aids has been developed. The computational complexity (BC) of a recursive
filter with a finite impulse response (RCIHF) is also compared with the computational complexity
of non-recursive filters with a finite impulse response (NCIHF).

The paper is an exploration of a new approach to the systematic analysis and classification
of quantum circuits based on the functional configuration of qubits. The article examines in detail
the role of elementary gates in changing the elements of the state vector and highlights the importance
of functional configurations of qubits in the collective modification of quantum states.
The main aspects covered in the article include the characterization of quantum circuits with functional
configurations of qubits, analysis of the impact of elementary gates on the state of a quantum
vector, and determination of the number of possible types of functional configurations.
The results of the study could have important implications for optimizing quantum circuits and
improving our understanding of their general properties. A qubit functional configuration is a
mathematical structure that can collectively classify the properties and behavior of quantum circuits.
The development of quantum algorithms with efficient quantum circuits has been a central
part of quantum computing, which has seen enormous progress both theoretically and experimentally
over the past 30 years. The paper makes a contribution to the field of quantum computing by
providing a systematic approach to classify and analyze quantum circuits based on their functional
qubit configurations. Quantum algorithms are an innovative class of algorithms based on the
principles of quantum mechanics and using qubits instead of classical bits to process information.
Unlike classical algorithms, which operate on bits that take on the values 0 or 1, quantum algorithms
can use the principles of quantum superposition and quantum interaction, which allows
them to perform many calculations simultaneously. One of the key advantages of quantum algorithms
is their ability to solve certain problems much more efficiently than classical algorithms.
However, the design and implementation of quantum algorithms pose significant technical and
algorithmic challenges, such as managing quantum states, minimizing errors, and creating robust
quantum gates. Despite these challenges, quantum algorithms offer promising opportunities to
revolutionize computing and solve problems that have traditionally been too complex for classical
computers

This paper concerns the problems of modeling nonlinear causal systems. The aim of the paper
is to transform the nonlinear Riccati differential equation into operator form. The brief review
of approaches to modeling nonlinear dynamic systems is provided. Problems of projection the
original equation into differential equations with Volterra kernels and solving the resulting equations
are solved for Volterra series model. A short description of the method of projection into
hyperspace using the Frechet functional derivative is given. The result of projection is differential
equations with solutions in the form of Volterra kernels is shown. The linear kernel is a solution to
an ordinary differential equation, and kernels higher than first order are found by solving partial
differential equations with respect to time domain variables. The model with only the first two
kernels of the series is considered. Attention is paid to the equation with a bilinear kernel. Search
of such kernel by analytical methods is more complicated compared to the equation with a linear
kernel, which is why this work attempts to calculate it using a numerical method. The detailed
description of the developed algorithm for calculating the bilinear kernel using the finite element
method is given. Using this method, the general operator model will the semi-analytic structure in
the form of a sum of convolutions with the analytical linear kernel and the finite element bilinear
kernel. An operator model for the weakly nonlinear system has been developed. The simulation
modeling was done for verify the operator model. The computational experiment consisted of obtaining
the transient response by test signal in the form of the Heaviside function. The responses of
the linearized and proposed operator model were calculated using discrete convolution. The obtained
characteristics were compared with the fourth-order Runge-Kutta solution as a reference
solution of the basic equation. The developed operator model gives a response closer to the reference
response, which is confirmed by the results of residual calculations.

This paper proposes a new approach to the organization of computational structures of layers
and inter-layer connections in the construction of artificial neural networks for solving a wide
range of problems of multidimensional data processing. The main problem of building deep learning
networks is the necessity of introducing a large number of network training parameters. Available
working instances of such networks contain billions of parameters, which allows to achieve
high efficiency of such networks. The downside of such a widely used structure of networks in the
form of multilayer sieve structures is the high cost of training networks with a large number of
structurally similar convolution layers by the back-propagation method. A solution to the problem
of increasing the efficiency of such multilayer structures can be found in the use of hybrid layers
realizing data granularity operations, which were developed in our work. The new hybrid models
use matrix information elements instead of vector values of training parameters, which allow encoding
subsets of data values (information granules) instead of encoding individual data points as
in classical convolutional networks. The proposed hybrid layers are trained without a teacher and
allow parallel implementation of learning algorithms, which is fundamentally different from sequential
backpropagation algorithms as a result, the computational efficiency of similar hybrid
neural networks can be significantly increased. The theoretical approach to modeling and optimizing
the structures of deep learning networks proposed in this paper can be extended to a wide
range of computational intelligence problems.

Integral transformations have played an important role in the development of the theory and
its applications for processing information-bearing processes. Mathematically, integral transformations
map the space of the original variable into a new space of a new variable, that is, they
map sets of elements of the space of the "many into one" type. In signal theory, the integral Fourier
transform has been widely used not only as a representation of signals, but also in their spectral
analysis. The Hilbert integral transformation served as a development of the theory of digital representation
of broadband signals. The paper discusses the theory of the integral Mellin transform,
which is not as well known as the previous ones, for its use in signal processing and interference,
as well as some problems of an applied nature in signal theory. We presented the theory of spectral
correlation analysis of random processes in the basis of the integral Mellin transform. In particular, a theorem (analogous to the Wiener-Hinchin theorem for the Fourier transform) is proved
on its basis on the relationship of the correlation function of noise in the basis of the Fourier
transform with the spectral density of noise power in the basis of the Mellin transform. These results
can be used as the basis for the synthesis of signal processing algorithms against interference
in the basis of the integral Mellin transform. Based on it, the functional structure of the signal
detector has been developed against the background of Gaussian noise with unknown a priori
correlation function and signal duration. It should be noted that the authors' work considers rather
complex mathematical calculations. For beginners who get acquainted with the integral
Mellin transformation, we recommend that you first familiarize yourself with the textbook.

Risk assessment is an important task in any field, from manufacturing to medicine. Risks accompany
a project, product or process throughout its life, from the moment of planning until its
complete termination. Each of them has its own approaches. These include FMEA (Failure Mode
and Effects Analysis) - analysis of the types and consequences of failures. The proposed model is
based on the FMEA method, which is based on risk assessment according to three criteria: the
severity of the consequences when a threat is realized and the complexity of identifying a failure,
the probability of occurrence. The first two criteria are based on expert assessment obtained in
accordance with artificial intelligence methods. The authors proposed a modification of the third
criterion. In our work, we replaced the expert assessment of the “probability of occurrence” criterion
with a machine learning model capable of predicting this indicator based on statistical data.
We carried out the first stage of research into the task at hand on NASA’s open dataset about engine
operating cycles before failure. Initially, the task was set to predict the remaining number of
cycles before failure, then we moved to the classification task, determining whether the equipment
is at risk, depending on its potential remaining life. The best result was obtained by the support
vector machine (SVM), with a classification accuracy of 80%. The goal of the work is to create a
risk assessment model based on the FMEA methodology, which allows to improve the quality of
assessment, reduce subjectivity in decision making, making a forecast based on historical data,
and not just the subjective experience of an expert.

An important role in the perception of image quality is sharpness, that is, the An important
role in the perception of image quality is played by sharpness, that is, the magnitude of the brightness
gradient in areas near the boundaries of objects. This characteristic is responsible for the
clarity and detail of small image elements. Defocusing the camera lens and insufficient illumination
are the main factors that can lead to digital image blurring. To increase the sharpness, various
processing methods are used, such as filtering in the frequency domain, for example, the use of
fast Fourier transform to emphasize the boundaries and textures of the image. The use of this typeof filtering allows you to control the contrast and frequency content of the image, which leads to
an improvement in visual perception. However, this method has a number of significant drawbacks,
such as logarithmic complexity and performing additional calculations associated with
forward and inverse Fourier transforms. Therefore, the preferred method of image sharpening is
the so-called spatial processing, which provides direct filtering of image pixels without additional
transformations, and the reuse of processing results (recursive component) in the filter allows you
to reduce the number of operations, reduce computational complexity. The article describes the
development of an effective recursive separable two-dimensional digital filter to sharpen largedimensional
RGB images. The algorithms of its construction are given, the corresponding block
diagrams are designed. The filter has the property of more uniform detail of image objects, and is
less susceptible to the creation of pulse noise. Also, for the original high-resolution RGB image, a
blur filter is modeled, the matrix of which is filled according to the normal (Gaussian) law.
To assess the filtration quality, the developed filter is compared with the algorithm of classical
two-dimensional convolution with a 5x5 Laplace high-pass filter core.

Until the 2000s, the concept of non-statistical methods was used to solve the problem of
automatic extraction of causal relationships (CR). These methods used manually constructed
linguistic templates. Obviously, the CR that did not fit into the built templates could not be
defined. Non-statistical methods required constant manual control by experts, up to the evaluation.
Almost all methods were aimed at extracting explicit CR. In some methods, attempts
were made to untie the extraction system from a specific subject area. To eliminate the above
disadvantages, the methods developed in the future began to shift towards statistical data
processing and machine learning. In this article, statistical and machine methods of CR e xtraction
are considered. A few valuable papers related to the new paradigm of CR extraction
were analyzed. The aim of the research was to evaluate new methods with the ability to identify
their advantages and disadvantages. The great advantage of machine and statistical
methods is independence from the subject area while maintaining the accuracy of extraction.
Such methods are worse in accuracy, but they are not tied to a specific problem area. The
methods themselves, unlike non-statistical ones, which used linguistic and syntactic comparison
with templates manually, are focused on finding these templates. Even though machine
and statistical methods are mostly independent of the subject area and use large corpora oftext for teaching, they are intended mainly for the English language. There is also no standardized
data set that would allow methods to be compared with each other. All works devoted
to methods ignored the extraction of implicit CR.

The article presents a comparative analysis of the numerical and analytical modeling results
of the electrode effect in the atmosphere, as well as experimental studies of electrodynamic processes
taking place in the surface layer. For the analysis, several electrical characteristics of the
surface layer in the atmosphere were used, namely, the values of the parameters of the electrode
effect determined by the number of positive and negative aeroions at different altitudes from the
earth's surface. Studies have been carried out for various models under various meteorological
conditions in approximations of the classical (non-turbulent) and turbulent electrode effect, both
in a clean atmosphere and taking into account aerosol air pollution. The independence regularity
of the electrode effect value as a whole (the amplification of the electric field at the surface compared with the upper boundary of the formed electrode layer) from atmospheric conditions with
various methods of mathematical and numerical modeling is revealed. It is established that the
height of the electrode layer and, accordingly, the scale of the electrical characteristics distribution
change significantly when various factors, such as ionization and aerosol air pollution, the
presence and intensity of turbulent and convective transport, act on the near-surface layer of the
atmosphere. The verification of approximate analytical models was carried out by establishing the
correspondence between the results of numerical modeling, theoretical calculations and experimental
studies obtained earlier. The data of theoretical and numerical calculations in various
ways are in good agreement with each other and with the results of experimental atmosphericelectrical
observations. Conclusions are drawn about the possibility of using approximate analytical
expressions obtained by mathematical modeling methods to describe the electrodynamic
structure of the atmospheric lower layer.

The measurement accuracy of a microprocessor-based physical measurement sensor is
measured to the extent determined by its conversion characteristic, which is constructed from data
obtained from various calibration tests. Characteristics of the sensor converter, on which the
measurement accuracy depends, within a certain degree of approximation of the characteristics of
the sensor converter. Sensor calibration tests are carried out in accordance with the test procedure.
In the process of fulfilling obligations, errors arise due to exceptions of individual loops
made on each other. Therefore, small deviations from the conduction scheme can lead to a decrease
in the quality of the conversion characteristics and a decrease in the metrological characteristics
of the sensor. It is important that the results of several test cycles under constant environmental
conditions are independent of each other. The article presents a method for determiningthe quality of the results of calibration tests of a microprocessor pressure sensor. The method
allows you to evaluate previous test cycles for violation of the conditions of their conduct. An artificial
time series constructed using test data is analyzed. For construction, a specialized procedure
was implemented for connecting individual cycles into a single structure, similar to a time series.
A separate time series was constructed for each constant temperature value. Since the resulting
time series is a linear function, its Hurst exponent should be close to one. In this case, the series is
trend-resistant, and experimental cycles check independence and calculate a single linear trend
with minor deviations from it. If during the test any conditions for their conduct were violated, for
example, the conditions for transition from one temperature regime to a procedure, then based on
the results of the current test regime, the temperature conditions of the cycle regime will be observed.
To determine such scales, a procedure is proposed for comparing the Hurst exponent of a
time series, which presents data from an unreliable test cycle, with a range of acceptable results.
If the Hurst exponent meets the established limits, the test results can be used to construct a highquality
calibration characteristic. Otherwise, the results of the analyzed cycle describe the test
cycle conditions and recommend repeated test cycles.

Due to the accelerated growth in the use of groups of autonomously functioning unmanned
aerial vehicles (UAVs) in various environments, solving the problem of optimizing the functioning
of groups of such vehicles according to the criterion of the minimum energy consumed is an urgent
scientific task. In this article, a new approach is being developed to ensure energy saving of a
group of unmanned aerial vehicles (UAVs) by using a distributed system of UAV charging modules
that provide the necessary versatility in servicing different types of vehicles. It is assumed that
the charging modules are installed at a subset of service stations, between which multicopter-type
UAVs ply, carrying out a cargo delivery mission. It is necessary to determine such a number and adirectly specified subset of service stations equipped with such modules that would deliver the
optimum of some quality functional characterizing the functioning of a group of UAVs. The article
suggests as such a functional the ratio of the number of UAVs that have successfully fulfilled the
tasks assigned to them for the delivery of goods to the number of stations with charging modules.
The model of UAV movement between destinations assumes taking into account not only the cruising
mode, but also the maneuvering of the device during takeoff and landing; the dependence of
the energy consumption rate on the current kinematic values of the device is also taken into account.
It is envisaged that the device will fall if it consumes energy below the maximum threshold
value. A simplified model of a service station with a charging module (CM) has been developed,
implying the replacement of discharged batteries. The waiting mode of the UAV in the queue is
taken into account. To study the developed algorithms for motion planning and choosing the optimal
distribution of charging modules across service stations, software based on the Unity environment
has been created and tested. The flexibility of the latter allows modeling various algorithms
of information interactions of elements within a group of UAVs, a group of CM, as well as
cross-interactions between UAVs and CM.

The paper covers the problems of the development of digital photonic computers. Along with
quantum computers, they are one of the possible ways to overcome the crisis of computing performance.
The data processing implementation in digital photonic computers at terahertz frequencies
potentially provides the performance exceeding by two or more decimal orders of magnitude the
performance of the most modern computing systems. Modern research suggests the prospects for
the development of digital photonics. It can provide the performance, significantly exceeding the
performance of microelectronic computers with the same calculation accuracy. At the same time,
largely, the efforts of researchers are aimed at creating digital photonic logic elements, while
architectural issues are considered very superficially. The authors consider the development problems
of the digital photonic computer architecture, which could provide a solution to a wide class
of computationally time-consuming problems in the paradigm of structural calculations.
It is shown that the synchronization and switching subsystem must have a hierarchical topology
with the configuration of information links both in the programming process of a photonic computer
and in the process of solving problems to use this calculation paradigm. The principles of
ensuring the performance and accuracy at solving problems on digital photonic computer with the
chosen data representation method are considered. The authors have developed models of
functional devices of basic arithmetic operations in the basis of photonic logic: the addition
and multiplication in the IEEE 754 standard. The devices are implemented according to the
scheme of linear conveyor with low-order processing forward. Unlike traditional microelectronics,
the proposed approach to the construction of conveyor functional devices does not
involve the use of latch registers. Its implementation leads to excessive hardware co sts in
digital photonic logic. In addition, the branching factor of hardware information links b etween
logical elements is limited at development the computational circuits. This will reducethe problem of signal attenuation. The FPGA has been used to prototype the developed functional
addition and multiplication devices and to evaluate the performance of computing
structures, implemented on DPC, similar to structures in mathematical physics problems at
performing operations such as "matrix multiplication by vector".

The work is devoted to the study of reflections of electromagnetic fields from images corresponding
to the limitations of the Kirchhoff method. An analysis of wave work known in the field of
diffraction allows us to conclude that solutions to problems of diffraction of wave characteristics
by uneven surfaces are reduced to one degree or another when deriving simplifying hypotheses.
Among the main simplifications are: limitation of radiation areas and, as a theory, fixation of
multipliers of integrated expressions, refusal to take into account the variability of local indicators
of the Fresnel reflection coefficient, solution of a single-position problem of wave diffraction in
conditions of combining points and reception, isotropic nature of the spatial structure of the reflecting
surface. The work solves the problem of estimating the range of voltage fluctuations of a
radar signal reflecting a small-scale rough sea surface, without accepting the main simplifying
hypotheses. Based on the general solution for the scattering fields of the main polarizations obtained
within the Kirchhoff method, analytical solutions for the intensity of fluctuations of the
complex amplitude of the field and the power of the incoherent component of the reflected signal
are analyzed. The relations obtained for the case of small heights of surface irregularities show
their differences from the known results. Functional dependences of the intensity of fluctuations of
the complex amplitude of the field and the power of the incoherent component on the electrical
parameters of the reflecting surface, on the magnitude of the spatial separation of the transmitting
and receiving antennas, on the wavelength and length of sea wave crests, on the width of the antenna
radiation pattern (APP) and on the magnitude of the surface inclinations were obtained.
Spatial separation of the transmitting and receiving antennas reduces the amount of power of the
incoherent component. The effect of diversity weakens as the beam expands and the flight altitude
increases. As the length of sea waves and the length of sea wave crests increase, the degree of
their influence on the power of the incoherent component weakens. It also weakens as the width of
the bottom expands and with a decrease in the radio wavelength. It is shown that in the decameter
range of radio waves, taking into account the slopes of the surface leads to a change in the intensity
of fluctuations of the reflected signal by a few percent only at sea wavelengths approaching the
radio wave length.

The work is devoted to the issues signals simulation in systems with moving objects. The relevance
of the problem is determined by the growing interest in application of ultra-wideband signals,
progress in the field of creation of hypersonic aircraft and low-orbit spacecraft, as well as
the widespread use of radar and sonar systems with long accumulation of signals.
The geometry of the problem of location for a rather general case (bistatic location with moving
transmitter, reflector and receiver) is considered, as well as the method and algorithm for solving
the problem of modeling echo signal for the simplified case of homogeneous and isotropic medium.
The necessity of numerical methods usage for realization of the proposed simulation method,
suggestions on the choice of numerical methods are given: Runge-Kutta method is suggested for
solving differential equations, for solution of algebraic equations Newton's method is suggested.
Recommendations are given on the choice of parameters of each of the numerical methods. The
applicability of the proposed method and algorithm to the problem of wireless communication with
mobile objects is shown. Several important special cases for each of the problems are considered
with the indication of areas of radio engineering and hydroacoustics, in which each of the special
cases are relevant. It is shown that in a number of simple special cases the proposed method leads
to solutions already obtained by other authors and published in open sources. Recommendations
are given on generalization of the algorithm to more complex variants of the problem formulation

Frequency synthesizer models with a phase-locked loop (PLL) system have been obtained for
the 4,4…4,99 GHz range, which is the most promising for the fifth generation (5G) communication
systems in the Russian Federation. The 4,4...4,99 GHz operating band is intended to provide wireless
communications of the 5G standard within the city and is not used by other wireless communications
networks for civil or military purposes. The goal of this work is to determine the parameters of a PLL
system to implement the frequency synthesizer that provides maximum attenuation of spurs with the
minimum setting time of the specified frequency in the band allocated for 5G communication systems.
In accordance with the present goal, the following problems are solved: description of frequency
synthesizers models based on a PLL system with loop filters of various orders; analysis of the transfer
characteristics of the PLL system in the frequency domain; determination of the dependences of
the PLL system spurs attenuation and the operation speed upon the order and the parameters of loop
filters; calculation of the optimal parameters of the loop filters to ensure maximum spurs attenuation
and minimum setting time of the specified frequency. To solve the assigned problems, the dependences
of the spurs attenuation upon the optimization parameters were calculated for the cases of using
loop filters of the 2nd, 3rd and 4th orders. In addition, an analysis of the dependences of the setting
time upon the optimized parameters was performed. It has been shown that the use of high-order
loop filters with optimal parameters can significantly increase the level of attenuation of higher spurs
and at the same time reduce the setting time of the specified frequency. In particular, the fourth-order
loop filter makes it possible to provide 18 dB more attenuation of higher spurs and 12,5% less setting
time of the specified frequency than the second-order loop filter. In addition, the use of higher-order
filters makes it possible to increase the attenuation of the main spurs by 5 dB compared to the second-
order loop filter.

This article discusses approaches and their analysis to the design and implementation of
medical information systems based on the concept of a cyberphysical system for solving problems
of verifying the state of fragments of medical biological objects in the process of diagnosing diseases.
The relevance of the development of tools and methods for automating diagnostic and
treatment processes based on advanced technologies with the widespread introduction of medical
information systems (MIS), medical automated information systems (MAIS), medical automated
diagnostic information systems (MADIS) based on a complex of technical means (CTS) of computer
technology (VT), a complex of software (KPS,) system and instrumental, network technologies
and computer networks, new information technologies in general, when implementing a model for
the development of domestic production of technological equipment and medical products. An
analysis is made of what should be included in its composition, according to which principle it
should be built, which principles of construction should satisfy the MIS, as a cyberphysical system
(CFS). The technological sequence is shown, which is the analysis of X-ray images, decisionmaking
based on the analysis of these images, diagnosis based on the decisions made by the decision-
making subsystem of the MIS, which should be carried out by developing and applying algorithms
for automating the diagnostic process implemented by the developed software and information
support for the maintenance of the decision-making subsystem. The implementation of the
process of verifying the state of fragments of biological objects using computed tomographic images
of MIS is described. The article focuses on the analysis of X-ray images, decision-making
based on the analysis of these images, diagnosis based on the decisions made. Examples of applied,
practical implementation of software and information support for the process of automation
of verification of medical facilities in the form of screen forms for working with fragments of the
object under study and the results of the analysis of radiographic images are given. All this makes
it possible to increase the efficiency, accuracy of verification of the state of medical biological
objects, the reliability of the disease diagnosis process. The scientific novelty, the results of the
approbation of the material presented in the article at international, All-Russian conferences,
scientific journals are shown.

This article examines the influence of various parameters of the blockchain network on each
other. Due to the mathematical complexity of forming an absolutely accurate emulator of the block
chain formation process and the unpredictability of a number of factors, the process is considered
stochastic. The study found a close to directly proportional relationship between the size of the
mempool and the value of the cryptocurrency. A mempool is a set of transactions awaiting confirmation
on the blockchain. The cost of cryptocurrency can affect the number of miners processing
transactions, attracting them with high earnings, which can affect the speed of transaction processing
and, as a result, the size of the mempool. The paper describes the application of the Monte
Carlo method to determine the ratio between the size of a mempool and the price of a
cryptocurrency, as well as the preliminary preparation of data and the formation of distributions.
A stochastic process simulation is described to determine the relationship between the size of a
mempool and the price of a cryptocurrency. To do this, the Monte Carlo method is used, which
allows you to estimate the probability of various scenarios. The paper considers various stochasticmodels for the analysis of blockchain systems, for the construction of which the Monte Carlo
method is used. The author proposes a methodology for predicting and establishing a correlation
between the parameters under consideration based on data collected from the BitCoin network
over the past three years. The results of the study confirmed the hypothesis that there is a relationship
between the value of cryptocurrency and the volume of unprocessed transactions. Due to the
lack of a complete data set, it remains impossible to predict the load on the network at a specific
cost. A solution to this problem was presented using probabilistic methods, including the Monte
Carlo method, based on the distribution of the historical data obtained. Using the Monte Carlo
method to model the relationship between the size of a mempool and the price of a cryptocurrency
and other similar tasks in similar conditions can be a useful tool for researchers to draw conclusions
about the stable operation of the network

The problem of increasing traffic intensity in megacities is becoming more and more urgent
every year, which leads to increased delays at intersections, increased fuel consumption and unjustified
wear of vehicle units. One of the possible solutions to this problem is the improvement of
traffic control methods. The development of new control systems presupposes the availability of
sufficiently accurate mathematical models for describing the traffic flow in order to evaluate control
quality, as well as to forecast the properties and parameters of traffic flow. Research objective
is to study existing traffic description models, to identify their shortcomings; to improve these
models in describing traffic flow not only at individual intersections, but also within a cluster of
several intersections. The paper analyzes the model of vehicle delays at the intersection by
M.J. Beckmann. It is established that this model is quite accurate in describing isolated intersections
with a uniform intensity of traffic flow, but it is unsuitable in cases with intersections that
have a traffic flow relationship with interconnected traffic light objects and bursts of traffic intensity
during the traffic light control cycle. The reasons for the discrepancy between the experimental
data and the data obtained using the M. J. Beckmann delay model are analyzed. A modification of the M. J. Beckmann delay model is proposed, which takes into account the factor of the
shift of the resolving phase of regulation between interconnected intersections. The resulting addition
of the M. J. Beckmann delay model has significantly improved the accuracy of calculating the
delay of vehicles in relation to interconnected intersections

Diagnostics of electrical equipment, according to regulations, is a complex and multifactorial
process which is regularly carried out at industrial enterprises and is characterized by a wide
range of uncertainties related to inaccurate, fuzzy and incomplete initial data, high labor intensity
and risk situations. This results in accumulation and growth of various defects, disruption of power
supply to industrial enterprises and technological processes, as well as equipment failure.To improve the efficiency of operation and high level of equipment fault tolerance, it is necessary
to develop methods, models and means of diagnostics using modern information technologies including
methods and technologies of artificial intelligence, taking into account not only quantitative
but also qualitative initial information. This paper proposes a systematic approach to the assessment
of the technical condition of electrical equipment at the stage of its operation. The approach
is aimed at the implementation of system-wide principles, as well as the consideration of
this process as an open system, thus making it possible to best organize the decision-making process
in the control system. These principles will provide an opportunity to formulate various tasks
to assess the technical condition of equipment using information technologies and artificial intelligence
technologies, as well as to determine the ways and means of their solution. The authors
proposed the structure of a unified complex of EE assessment for intelligent diagnostic systems
which sets the sequence of tasks to be solved and the methods and approaches to be used for them.
The unified complex will increase the informativeness of decision-making situations and reliability
of conclusions about the technical condition of equipment under conditions of incomplete and
fuzzy information.

The article is devoted to the development of a method of non-destructive testing of the insulating
material of cable systems. The destruction of a polymer material caused by a radical chain
mechanism of destruction is considered. The mechanism of destruction of polyethylene caused by
electron and ion bombardment under the action of partial discharges (PD) is given. The formation
of cross-links associated with the activation of double bonds during the transfer of electronic excitation
energy from a polyethylene chain is shown. When exposed to CR, the number of
transvinylene-type double bonds reaches saturation with an increase in the dose of absorbed energy.
The PD diagnostic system using a complex of characteristics of PD inclusions (SB, qCR, hB) by
the amount of heat generated (Q) and ignition voltage (UV) obtained by the developed software is
effective both for assessing the current state of insulation and for predicting its residual resource.
The detected CR sources indicate the presence of inclusions in the cable insulation. Within the
framework of the conducted research, a neural network (NS) model describing the architecture of
a cyber-physical system power cable lines (PCL) for predicting the resource of EM cable electrical
networks was built. The algorithm of the adaptive system operation, selection of parameters
and training of the NS with subsequent prediction of the PCL resource is synthesized, which makesit possible to increase the reliability of the PCL by reducing the time to create the optimal configuration
of the NS. The obtained NS model can be effectively used for the analysis of thermal fluctuation
processes occurring in the control object – PCL, and the prediction of the behavior of the
object. The method of diagnosis of IM CL in operating conditions is given. The analysis of the
obtained results showed that the measurement of the parameters of the PD allows us to assess the
impact of various factors on the electrical insulation of the CL and determine the degree of its
degradation. PD is a measure of the degree of electrical aging.

The article is devoted to the topical problem - reducing the radar cross-section (RCS) of cylindrical
objects using anisotropic metasurfaces (MS). The purpose of the work is to study anisotropic impedance
MSs for self-adaptive (to the irradiation frequency) RCS suppression of cylindrical metal surfaces
when irradiated by linear (LP) and circular (CP) polarized waves. To achieve this goal, the known
principles of operation, design and capabilities of MSs for reducing the RCS of both flat and cylindrical
metal surfaces, including surfaces of electrically small radius, were analyzed. The 2D problem of scattering
a plane electromagnetic wave on the model of a cylindrical metasurface (CMS) in the form of a
circular cylinder with anisotropic homogenized impedance boundary conditions of a general form is
considered. Using the eigenfunction method, analytical expressions are obtained for the scattering matrices
of a cylindrical metasurface in linear and circular polarization bases. Scattering matrices make it
possible to solve various problems of synthesizing the impedance tensor of the CMS on given scattering
characteristics in the LP and CP bases. In particular, a diagonal impedance tensor of the CMS has been
synthesized, which provides that the fields of scattering of TE-, TM-polarized waves as well as two circular
co-polarized waves are antiphase. The problem of synthesizing the impedance tensor of the CMS
from a given zero trace of a diagonal scattering matrix with self-adaptive (to the irradiation frequency)
cancellation of waves with any polarization in the low-frequency region has been solved. It is shown that
the radar cross-section reduction of the CMS in the reverse direction is from 60 to 10 dB in an ultrawide
range of ka values from 0.02 to 0.4. The scattering characteristics of two models of camouflage
coatings are calculated. It is shown that the reactance CMS based on meta-particles in the form of rectangular
strips reduces the RCS by 10 dB in the low-frequency band of 200– 520 MHz with the incidence
of the TM polarized wave and by 5 dB in the band of 480–720 MHz in the case of incident TE
polarized wave.

The development of the global market of unmanned aerial vehicles and the Russian market of
unmanned aerial vehicles is considered and analyzed. Prospects for the development and growth of the
unmanned aerial vehicles market. The importance of reliable measurement of the effective scattering
surface of stealth unmanned aerial vehicles is considered. The methods of reducing parasitic reflection
from a pivoting support device inside an anechoic chamber are considered - the use of a column made
of radio–transparent material and the use of a pylon made of conductive material. The results of
calculations in HFSS using a column made of radio-transparent material and a pylon made of
conductive material are presented. The effect of taking into account the background of an anechoic
chamber on the reliability of measuring the effective scattering surface of stealth aircraft is considered.
The existing methods of accounting for the background of an anechoic chamber are analyzed, which
allow reducing parasitic back reflections in an anechoic chamber when measuring stealth objects. The
shadow zone that appears on the back wall of an anechoic chamber when measuring objects in an
anechoic chamber is considered. The contribution of the shadow zone arising on the back wall of the
anechoic chamber when measuring objects to the reliability of measuring stealth objects inside the
anechoic chamber is analyzed and the need to take into account the contribution of the shadow zone
when measuring stealth objects in the anechoic chamber is shown. The classical method of accounting
for the camera background, which is the basis of the proposed method, is described. The main drawback
of the classical method of accounting for the background of an anechoic chamber is described. A new
method for measuring mono static backscattering diagrams is proposed and described. The new method
of measuring backscattering diagrams allows us to take into account the disadvantage of the classical
method of accounting for the background of an anechoic chamber when measuring i stealth objects
inside an anechoic chamber. The essence of the new method is to use a wedge of conductive material,
which is located in the shadow zone of the back wall of the anechoic chamber, directly behind the
measured stealth object. The effectiveness of the new method is shown in the HFSS software
environment, based on the HFSS model of an anechoic chamber of the Southern Federal University.

An analysis of existing methods for synthesizing antennas according to a given radiation
pattern, in which the generated radiation pattern is the sum of partial rays, is carried out. It has
been established that in these methods an iterative process is organized, at each step of which a
new additional beam is added to the already formed beam. In this case, search optimization algorithms
are used to determine the parameters of the additional beam. The existence of these methods
allows us to separately consider algorithms for determining the parameters of additional rays
at each step of the iterative process, as processes for solving independent problems. A variation of
such a problem is the search for parameters of additional rays to form a one-dimensionally extended
radiation pattern. An analytical algorithm for the formation of a one-dimensionally expanded
beam of a linear antenna is proposed and justified, represented as a sum of three narrower
partial beams after determining two unknown parameters: the angle of separation of additional
beams and the complex amplitude of these beams. Relationships have been obtained that make it
possible to reduce the problem of forming an extended beam of a linear antenna to the problem of
optimizing the expression for one parameter - the angle of separation of additional beams relative
to the central one. It is shown that the second required parameter, the complex amplitude of the
additional beam, is determined analytically. It was established that the choice of the required parameters
of the optimization problem should be based on the requirements for maximizing the
directional coefficient. After solving the optimization problem, the amplitude-phase distribution in
the aperture of a linear antenna is represented as a superposition of three amplitude-phase distributions
to form the corresponding partial rays. It is shown that the algorithm has limitations associated
with the expansion of rays, since the feasibility of the requirements is related to the width of
the used partial rays. In this regard, it is indicated that the proposed algorithm should be considered
as an integral part of an iterative process, at each step of which additional beam expansion
occurs. The results of the implementation of the proposed algorithm when forming several extended
beams are presented, which confirm the performance of the proposed algorithm.