No. 6 (2021)

In the modern world interference logic gates (ILG) are an integral part of computers in the
modern world. One of the most important tasks of developers of new computing technology is to
reduce the duration of logical operations. This ensures the perfomance of various computing systems
used in large objects modeling with a large number of details in various industries and in
processing a large amount of information. A possible way to solve this problem is to use ILGs
based on the element base of the optical wavelength range. These models microwave ILG are being
developed for implement the functions of ILG based on a microstrip line in the ultra-high frequency
(UHF). The paper presents the result of modeling, engineering, manufacturing and testing models of microwave ILG which form a complete functional basis. A numerical simulation microwave
model ILG, which implements the functions “AND“, “XOR“ and “NOT“, has been carried
out. The model consists of four types microwave functional units: circulators, single-stage ring
power adder and power take-off elements, which are directional couplers, with lateral coupling
and with a given branch coefficient. The finite integration method in the time domain for numerical
system modelling is used to confirm the operational principle of ILGs and their realizability.
ILG mock-ups implement the functions “AND“, “XOR“ and “NOT“. The identity of the intensity
values corresponding to the logical “0“ and “1“, generated by different elements, is observed.
The execution duration of logical operations is determined by the duration of the pulse propagation
in the waveguide. The use of reactive elements in the design of the ILG makes it possible to
minimize the loss of microwave energy during the propagation of an electromagnetic pulse.

The problem of printed gratings application is considered as converters of electromagnetic
waves polarization and polarizing modulators. Two directions in development of antenna engineering
are considered in this paper. In each of them the scattering fields control of an antenna
arrays allows essentially to expand functionalities of radio engineering sets. The first direction is
the creation of auxiliary depolarizing reflectors for two-mirror reflector antennas and folded
lenses. In addition, in twist-reflectors based on printed gratings, it is possible to constructively
realize the necessary phase distributions of the field on their surfaces. Thus, it becomes possible to
use such twist-reflectors to create phase-correcting twist-reflectors. The second direction is connected
to application of antenna arrays for a reduction of a radar cross section of the radartracking
targets. Transformation of a field polarization by an antenna array allows to achieve both
these purposes. In an aspect of high cost and complexity of arrays experimental researches as a method of the analysis the mathematical simulation is selected. Besides, it is shown that introduction
of impedance loads in the construction of the re-radiating elements of the printed grating
opens additional possibilities for controlling the field scattered by it. Thus, twist reflectors with
improved characteristics can be realized on the basis of microstrip-pin gratings. The given results
can be used for choosing the most of rational electrodynamic structure geometry variant at decision
of particular problems by antennas engineering. The possible flat arrays based on printed
complicated shape elements application area is also discussed and it's shown these arrays are the
very attractive type for controllable radioelectronic covers designing at microwaves. Some numerical
results presented prove the possibility of a printed reflectarrays application as smart covers
microwave modules.

The article shows the possibility of using the Poincare-Steklov filter to ensure the stability of
harware in the loop (HIL) simulation of nonlinear systems.HIL simulation involves splitting the
initial system into parts, with one part being modeled numerically on a computer, and the second
part is represented by a real physical object. The parts of the system exchange data with each
other through a hardware-software interface, which can be implemented in different ways and
should ensure stability, as well as convergence of the results of HIL simulation to the results of
modeling the original system. The variants of constructing software and hardware interfaces ITM,
TLM, TFA, PCD, DIM, GCS and the Poincare-Steklov filter are described in the relevant literature
sources. The article shows how the original nonlinear system was divided into parts using the
Poincare-Steklov filter, which, accordingly, led to the splitting into parts of the system of equations
describing the behavior of the original system. Next, it was shown how the values of the stabilizing
parameters of the Poincare-Steklov filter were calculated and the systems of equations of the system
divided into parts were corrected in accordance with the obtained values. At the next stage,
the article presents the results of numerical modeling of the initial and partitioned system in
MATLAB. When modeling in parts, the parts of the system exchanged data with each other at each
step of the simulation only once with a delay of h. This method of numerical modeling of a system
divided into parts is as close as possible to the processes occurring during semi-natural modeling
of systems. A comparison of the obtained simulation results of the initial and the system divided
into parts allowed us to conclude that the Poincare-Steklov filter, with the correct choice of the
values of the stabilizing parameters, allows for the stability and convergence of the results of seminatural
modeling of both linear and nonlinear systems

The article considers the possibility of using the Poincare-Steklov filter to build an interface
for hardware in the loop (HIL) simulation of system. The Z and Y forms of the filter representation
are given. HIL simulation involves splitting the initial system into parts, with one part being modeled
numerically on a computer, and the second part is represented by a real physical object. The
parts of the system exchange data with each other through a hardware-software interface, which
can be implemented in different ways and should ensure stability, as well as convergence of the
results of HIL simulation to the results of modeling the original system. The variants of constructing
software and hardware interfaces ITM, TLM, TFA, PCD, DIM, GCS and the Poincare-Steklov
filter are described in the relevant literature sources.The article shows how the original nonlinear
system was divided into parts using the Poincare-Steklov filter, which, accordingly, led to the splitting
into parts of the system of equations describing the behavior of the original system. Next, it
was shown how the values of the stabilizing parameters of the Poincare-Steklov filter were calculated
and the systems of equations of the system divided into parts were corrected in accordance
with the obtained values. At the next stage, the article presents the results of numerical modeling
of the initial and partitioned system in MATLAB. When modeling in parts, the parts of the system
exchanged data with each other at each step of the simulation only once with a delay of h. This method of numerical modeling of a system divided into parts is as close as possible to the processes occurring
during semi-natural modeling of systems. A comparison of the obtained simulation results of
the initial and the system divided into parts allowed us to conclude that the Poincare-Steklov filter,
with the correct choice of the values of the stabilizing parameters, allows for the stability and convergence
of the results of semi-natural modeling of both linear and nonlinear systems.

Phase-locked loop (PLL) frequency synthesizers that use phase detectors (PD) with various
nonlinear transfer characteristics have been considered. The goal of this work is comparative analysis
of the frequency synthesizers operation speed depending on the type of the PD nonlinearity and
mathematical description of the PD nonlinear characteristic which ensure the maximum operation
speed of the frequency synthesizer. In accordance with the present goal, the following problems are
solved in this work: the generalized model of the PLL frequency synthesizer is developed; mathematical
models of static characteristics of the PLL system nonlinear link are described when using various
types of known PDs and a modified PD with aperiodic characteristic; the analysis of the PLL
system dynamics when changing the static characteristic of the nonlinear link is carried out. The
modified PD provides relay control of transient processes when a large phase difference occurs.
Numerical evaluation of the PLL synthesizers operation speed depending on the initial frequency
deviation have been obtained when using known PDs and the modified PD. It is shown that the use of
the modified PD allows to reduce frequency settling time about 1.5 times in comparison with the best
in operation speed conventional PD. Optimal values of the control signal ensuring the maximum
operation speed of the PLL synthesizer with the modified PD have been obtained for the specified
frequency deviations in the large disturbance mode. The results of this work are valid for PLL frequency
synthesizers of the UHF, L, S and C-bands (from 300 MHz to 8 GHz) which are used in wireless
communication systems of the fourth generation (4G) and the fifth generation (5G).

Large amounts of video data captured by sensor sensors in various spectral ranges, the significant
size of convolutional neural network architectures create problems with the implementation of
neural network algorithms on peripheral devices due to significant limitations of computing resources
on embedded computing devices. The article discusses the use of algorithms for automatic search and
pattern recognition based on machine learning methods, implemented on embedded devices with a
computing resource Graphics Processing Unit. Detection convolutional neural networks «You Only
Look Once V3» and «You Only Look Once V3-Tiny» are used as a search and pattern recognition algorithm,
which are implemented on embedded computing devices of the NVIDIA Jetson line, located in
different price ranges and with different computing resources ... Also, in the work, the estimates ofalgorithms on embedded devices are experimentally calculated for such indicators as power consumption,
forward passage time of a convolutional neural network, and detection accuracy.
On the basis of solutions implemented, both at the hardware level and in software, presented by
NVIDIA, it becomes possible to use deep neural network algorithms based on the convolution
operation in real time. Computational optimization methods offered by NVIDIA are considered.
Experimental studies of the influence of computations with reduced accuracy on the speed and
accuracy of object detection in images of the investigated architectures of convolutional neural
networks, which were previously trained on a sample of images consisting of the PASCAL VOC
2007 and PASCAL VOC 2012 datasets, have been carried out.

This article discusses and presents the main problems and principles of the data clustering
process, in particular, the principles and tasks of clustering text arrays of linguistic expert information.
In the course of this work, the main difficulties arising in the design of such systems were
identified, for example: the need for preprocessing data, reducing the size of the initial sample,
etc. To effectively perform the presented tasks, the implemented solution must have an integrated
approach that takes into account the efficiency indicators of methods aimed at solving individual
subtasks, as well as the ability to provide high efficiency indicators for the implementation of each
stage of the clustering process. In the presented work, various groups of hierarchical clustering
algorithms are considered, in particular, a subgroup of agglomerative clustering algorithms was
considered in relation to the problems of clustering linguistic expert information. In the described
work, a formal statement of the text clustering problem is given, and the main group of implemented
solutions based on the principles of agglomerative clustering is determined: ROCK, CURE,
CHAMELEON. A detailed review of each of the presented algorithms is carried out, and the main
advantages and disadvantages of each of them are formulated. The advantage of this work can be
considered the totality of the presented data on the algorithms, as well as the results of a comparative analysis, which make it possible to further assess the feasibility and potential probability of
using these solutions from the presented group of agglomerative clustering algorithms. The novelty
of this work lies in the formation of an overview analysis of existing approaches in the field of
hierarchical clustering for solving the problems of cluster analysis of linguistic expert information,
as well as the formation of the results of the comparative analysis of the considered algorithms.

The article discusses a bioinspired algorithm for solving the problems of intellectual analysis.
The integration of bioinspired algorithms for solving data mining problems is a promising
area of research. As a bioinspired algorithm, an algorithm based on the adaptive behavior of an
ant colony is considered. The ant colony algorithm allows for a high-quality search for promising
solutions to obtain optimal and quasi-optimal solutions. The algorithm has the ability to search for
suitable logical conditions. The ant colony algorithm is based on the example of the behavior of
living ants in nature. Ants are able to find the shortest solution by adapting to changes in the environment.
The authors proposed a modified ant colony algorithm for solving the problem of data
mining. The clustering problem was chosen as the task of data mining. Clustering is a combining
of similar objects into groups, is one of the fundamental tasks in the field of data analysis and
Data Mining. The list of application areas where it is applied is wide: image segmentation, marketing,
anti-fraud, forecasting, text analysis and many others. The solution to this problem is of particular relevance in the context of the constantly growing volume of generated, transmitted and
processed data. Classical clustering methods are optimized by combining with the proposed
bioinspired optimization algorithm - the ant algorithm. The proposed method is a model in which
ants are represented as agents that randomly move in the solution space with some restrictions
(for example, obstacles in their path). To determine the effectiveness of the developed modified ant
algorithm (ALA) with the clustering algorithm, the authors carried out a series of computational
experiments. For comparison, we took the genetic algorithm, the monkey algorithm and the wolf
algorithm. The simulation results prove that the clustering-based ant algorithm gives better results
than other proposed algorithms.

In this work, a neural network of deep learning of a special structure is used. The neural
network allows a mobile robot to move without encountering obstacles in an unknown environment.
The main problems that the efforts of researchers in the field of neural network traffic planners
are aimed at solving are improving the performance of neural networks, optimizing their
structure and automating learning processes. The main result of this article is a new iterative algorithm
for developing a training set. At the first iteration, the initial training set is developed and
the initial training of the neural network is performed. In the following iterations, the neural network
trained at the previous stage is used as a filter for the following training sets. The filter selects
trajectories with collisions caused by neural network errors. During the learning process, the
number of convolutional and fully connected layers increases iteratively. Thus, the proposed algorithm
makes it possible to develop both a training set and a neural network architecture. Training
results are compared for filtered and unfiltered sets. The high efficiency of filtering has been confirmed,
as a result of which the distribution of examples in the training sample changes. The algorithm
can be used to develop a planning block for a mobile ground control system. The article
provides an example of training a neural network in a Matlab modeling environment. In the example,
five iterations of training were carried out, during which an accuracy of more than 90% was
achieved. This accuracy was obtained using the collected statistics on the movement of the mobile
robot in a randomly generated environment. The density of filling the environment with obstacles
was up to 40%, which corresponds to urban conditions. The comparison of neural network planners
trained using the proposed iterative procedure and with conventional training is carried out.
The comparison showed that the use of an iterative procedure increases the accuracy of planning
up to 12-15%. At the same time, the initial volume of the resulting sample is reduced several times
due to the applied filtering.

The problem of diophantine equations solving is considered in this article. This problem can
be applied in cryptography and cryptanalysis. The description of the genetic algorithm solving
diophantine equations is stated briefly in the article. The rule of calculation the value of fitness
function of chromosome is determined, the coding system in the genetic algorithm is described.
The genetic operators used in the algorithm are mentioned and the conditions for their execution
are determined. The criterion for stopping the genetic algorithm is described. One of the shortcomings
of the genetic algorithm is analyzed. The shortcoming of the algorithm lies in its attempts
to solve any diophantine equation, including one that has no solutions. A method eliminating this
shortcoming in some cases is proposed. This method is based on number theory. An explanation is
given in which cases this method will be used. The definition of residue and nonresidue of fixed
power for fixed modulus is given before describing this method. After describing this method the
implementation of the algorithm for solving diophantine equations and systems of them is described
in detail. Then the results of experimental studies of the time and quality of the genetic
algorithm are presented. Then the result of the algorithm is presented for an equation that has no
solutions and for a system of equations that also has no solutions, but in which the total number of
unknowns is too large for the proposed method to work. The algorithm running time is compared
when solving an equation and when solving a system of equations. The conclusion is made about
the usefulness of the proposed method in solving diophantine equations and systems of diophantine
equations.

In connection with the industrialization of modern society, the growth of the transport systems
of our country, an increase in certain necessary for the development of the needs of the citizens
of our country, the number of vehicles of various types continues to increase every year very
fast, causing huge traffic jams on transport roads, especially in large cities and megacities. Thus,
forecasting traffic flows is an important and necessary component of optimal traffic control in
modern conditions of transport network development. As a solution to this problem, this article
aims to analyze and describe the application of artificial intelligence methods, in particular neural
networks, which represent a modern approach to modeling in complex and nonlinear situations
that arise when predicting a traffic flow model. The shown accuracy method is based on the development
of a neural network to predict the daily traffic flow. The expected traffic flow is then compared
with the actual dataset recorded on the road section and provided by the infrastructure
manager. In fact, neural networks are able to learn from past situations and predict future situations
on the transport network. In this study, various neural network structures were examined, and the simulation results showed that the best predictions were obtained using the multilayer
perceptron architecture, which has a good generalization system with a root mean square error of
0.00927 with the current set of vehicles. The first part of the article is devoted to defining various
concepts related to the current research area, including a review of the literature on traffic prediction
and neural networks. The second part is devoted to describing the problem of traffic congestion
using forecasting problems and presenting the proposed solution method with an emphasis on
artificial neural networks as a means of forecasting demand and its various structures. Then, numerical
experiments are illustrated by analyzing the forecast results after the formation and testing
of various neural network architectures.

Optimization algorithms inspired by the natural world have turned into powerful tools for solving
complex problems. However, they still have some disadvantages that require the study of new and
more advanced optimization algorithms. In this regard, when solving NP complete problems, there is
a need to develop new methods for solving this class of problems. One of these methods can be
metaheuristics based on the behavior of a colony of white moles. This paper proposes a new
metaheuristic algorithm called the blind white moles algorithm. This algorithm was developed based
on the social behavior of blind moles in search of food and protecting the colony from intruders. The
proposed solution will be able to overcome many disadvantages of conventional optimization algorithms,
including falling into the trap of local minima or a low convergence rate. The purpose of this
work is to develop an algorithm for optimizing a complex objective function. The scientific novelty
lies in the development of a genetic algorithm based on the behavior of a colony of white moles for
solving NP complete problems. The problem statement in this paper is as follows: to optimize the
search for solutions to complex functions by applying an algorithm based on the behavior of a colony
of white moles. The practical value of the work lies in the creation of a new search architecture that
allows using the developed algorithm for the effective solution of NP complete problems, as well as
conducting a comparative analysis with existing analogues. The fundamental difference from the
known approaches is in the application of a new bioinspired search structure based on the behavior
of a colony of white moles, which will allow to exclude falling into a local minimum or a low convergence
rate. The presented results of the computational experiment showed the advantages of the proposed
multidimensional approach to solving the problems of placing VLSI elements in comparison
with existing analogues. Thus, the problem of creating methods, algorithms and software for solving
NP complete problems is currently of particular relevance.

As part of the research and development work "Lens" carried out at the enterprise JSC
"TNIIS", a design of a four-stage Luneberg lens was developed on the basis of a homogeneous
stepped dielectric, a model with an external diameter of 210 mm was made (dielectric material
PT-3 distribution of rays at the exit of the lens aperture. The width of the BP ranged from 10 -14
degrees. The level of side lobes at frequencies fw, fav, fn does not exceed -13 dB in level, weight
0.3 kg. According to these parameters at the given frequencies, the lens differs from previously
developed analogs. The purpose of the work is to develop a design and manufacture a model of a
four-stage Luneberg lens based on a homogeneous stepped dielectric, which will not be inferior in
its characteristics to foreign counterparts, which will provide the possibility of import substitution.
And also one of the goals of the work is to simplify the coordination of such a lens with a feeder
path and transceiver equipment, the production of which would be economically feasible in comparison
with analogs. It is also necessary to conduct an experimental study of the beamforming
device based on this lens in order to obtain the directional patterns of the central beam and in all
7 output beams of the Luneberg lens at the given three frequencies.

Manufacturers of intraocular lenses are constantly improving the parameters of artificial lenses,
functionally bringing them closer to their natural counterpart. In this work, an experimental study of a
number of important physical and technical parameters of intraocular lenses of the world's leading
manufacturers, affecting the quality of vision of operated patients, was carried out. The transmission
spectra of optical radiation of intraocular lenses in the range of 200–800 nm were investigated. In the
short-wavelength part, the measurement results showed a high efficiency of the protective properties of
intraocular lenses from ultraviolet radiation. It is shown that radiation with a wavelength of up to
350 nm is completely absorbed by the lens material, and the transmission of waves with a wavelength of
400 nm is 20 %. Further, up to a wavelength of 550 nm, an increase in the transmittance of the studied
intraocular lens to 100 % is observed, after which it gradually decreases to the end of the visible range
to 85%. The work also investigated the influence of the quality of the surface treatment of intraocular
lenses on the likelihood of secondary cataract development in the long-term period. According
to postoperative statistics, the likelihood of secondary cataract is 20–35 %. The appearance of
areas of optical opacity is due to various factors, one of which is the quality of the surface treatment
of intraocular lenses. The smoothness of the surface profile of the lens depends on the model,
manufacturing technology and material of the artificial lens. The study of the quality of surface
treatment of soft and hard intraocular lenses was carried out by atomic force microscopy. An
analysis of the results of scanning the surface of intraocular lenses and a statistical analysis of
630 clinical cases of secondary cataract in the long-term postoperative period (6 months or more)
showed their relationship. If the height of irregularities (protrusions) on the lens surface increases
to 70 nm or more, the likelihood of secondary cataract in the postoperative period increases from
6 to 15 %.

The work is devoted to the problem of diagnostics of automotive internal combustion engines.
The problem of monitoring the state of internal combustion engine is now most relevant due
to the increase in the number of cars and the tightening of environmental requirements. In the
work the consequences of operation of faulty internal combustion engine are considered. The purpose
of the work is to justify the choice from existing diagnostic methods of such a method, which
can help to detect the fault most accurately and quickly. For this purpose, the work details modern
diagnostic tools, highlights the principles of work, advantages and disadvantages. With the advent
of modern technologies, the long-known method of estimating the state of internal combustion
engine by sound can become the most advanced, as the human factor is excluded, for signal processing
the computational technique of analysis of the audio spectrum in which is carried out with
the help of artificial neural networks is used. The use of artificial neural networks for sound spectrum
analysis has found application in speech recognition and for diagnosis of respiratory system
diseases. The article considers mechanisms that are capable of generating sound signals during
internal combustion engine operation, some of them are phased, i.e. they are tied to operating
cycles, some are not phased. The proposed diagnostic technique allows to distinguish "useful"
sounds from the total number of internal combustion engine noises, after comparative analysis to
point to the node the sound of which differs from the reference, serviceable one. Scientific novelty
consists in the fact that the diagnostic process becomes automated, all sounds captured by sensors
are processed in a computer or a special scanner, the display shows information about the condition of certain nodes, unlike traditional methods where the diagnosis is carried out visually or by
ear. This increases diagnostic accuracy and reduces overall labor intensity by avoiding partial or
complete engine disassembly

Areas of application of CALS technologies are considered to be: improvement of activities
in the field of heterogeneous processes occurring at all stages of the life cycle (LC) of products;
supply chain management throughout the entire LC of products (from the creation of the product
concept to its disposal); electronic integration of organizations (enterprises) involved in these
processes at various stages of LC; management of support for LC products One of the most relevant
areas of development in the aviation industry are: multi-agent technologies for improving the
efficiency of aircraft (aircraft of various types in a group and a single mission) and CALS technologies.
The article proposes a methodology for analyzing the fault safety of systems and aggregates
of the multi-agent group of aircraft as a whole, by types of aircraft, their systems, and aggregates.
The methodology is given on the example of statistical data of AP and PAP 16 systems: flight navigation,
exhaust, ignition, fuel, control, power supply, air conditioning; hydraulic, radio communication
equipment, control devices, and aggregates: engine, propellers, wings, windows, lantern,
ten aircraft AN-2, L-410, Yak-40, An-24, Tu-134, Yak-42, Tu-154, IL-62, IL-62M, IL-86. In the
proposed methodology for analyzing statistical data of AP and PAP, transformations with matrices
are used, which allow not to be limited to the number of systems, aggregates, and the aircraft
themselves. The operating time before the functional failure of systems and aggregates by types of
aircraft was calculated, the average probability of functional failure of each of the systems and
aggregates in a multi-agent group was determined, and the time before the functional failure of a
multi-agent group of 10 aircraft as a whole, which was 132.5 hours, and it was determined that
PAP and AP are more likely to occur with the chassis and engine of the aircraft. The given methodology
allows: to correlate quantitative reliability requirements for systems and aggregates,
taking into account random factors and uncertainty factors; to assess the feasibility of the established
reliability requirements; to conduct a comparative analysis and justification of the choice of
a rational variant of the composition of the aircraft group.

The article is devoted to research on the creation of a method for assessing the durability of
the main insulation of power cable lines based on the thermofluctuation theory of destruction of solids.
The features of breakdown development in homogeneous and inhomogeneous dielectrics are
considered. The problematic issues of insulating materials of power cable systems (PCS) are considered
on the basis of the development and development of non-destructive testing methods. The main
components that destroy the insulation of the PCS are installed. The thermofluctuation theory of
destruction and the evaluation of the durability of electrical insulation of power cables are described.
An analytical method is proposed for evaluating the processes of cellulose oxidation with the determination
of the most probable. The proposed approach to identifying the main processes of insulation
destruction allows us to present in more detail the prerequisites for the development of partial discharges
(PD) in isolation and to determine measures to minimize the processes leading to the destruction
of PCS insulation. The results of experiments on the study of the service life of the insulating
material of aged ends of a power cable in a thermal cabinet, to determine the aging criteria, are
presented. The experimental data are interpreted from the standpoint of the thermofluctuation theory.
The dependence of the increase in the temperature difference ΔT on the degree of wear of the electrical
insulating properties of the material is revealed and investigated, which makes it possible to predict
its resource. The thermofluctuation theory of the destruction of insulating materials caused by
the thermofluctuation rupture of chemical bonds and the evaluation of the durability of electrical
insulation of cables made of cross-linked polyethylene are considered. It is shown that, in order to
calculate the average energy of the monomeric link of various polymer materials, it is necessary to
know: the chemical formula of the monomeric link and the values of the binding energies. In the
work, the time before the breakdown of the main insulation of the PCS was determined under the
action of temperature. The model can be used in devices and systems for continuous diagnosis of
power cables according to temperature conditions.