No. 3 (2020)

The development of modern air supply systems for cooling technical systems requires new ap-proaches in which instrumentation uses piezoceramic technologies. At the same time, it is necessary to conduct research both at the level of selection of new perspective piezomaterials, which was done in the work, and of new types of device layout from the point of view of design. Traditionally used cooling systems have rotating parts that create additional acoustic noise. These drawbacks are devoid of air supply devices using piezoceramic components. The article contains materials on the development of modern cooling devices based on the use of piezoceramic plates. The analysis of the processes occur-ring in the air in accordance with modern ideas about the theory of matter. Various design options for such devices are given. The design process from mathematical modeling to implementation in mock-upsis considered. Both the piezoceramic devices themselves and the flow distribution processes in the air were subjected to modeling. In the process of modeling, the simplest to manufacture and reliable in operation structures were investigated. All considered variants belong to the piezoelectric bimorph type, and are piezoelectric actuators that convert electrical signals into mechanical forces. Various layout schemes for such oscillatory systems are presented, variants of their mathematical modeling, finite ele-ment models of the air environment, amplitude-frequency and phase-frequency characteristics of the simulated models are shown. A comparative analysis of products, their electrophysical characteristics, based on the prospects for their further application is carried out. For research, various piezoceramic materials were used, both traditional and repeatedly tested, and new promising materials. A number of products are presented in sizes with a detailed description, their comparative characteristics are given. At the end of the work, conclusions were made about promising options for the further design of such devices and areas of research.

One of the most relevant areas of robotics development is the design of group cont rol
systems. In the proposed structure, a group of five robotic platforms (RP) is controlled from a
wearable or stationary remote control. This composition of the group determines schemeswith tunable connections between the components and changes in the principles of operation.
The article presents experimental studies of the computational efficiency of methods for planning
RP trajectories in space and defines the optimal method and the required parameters of
the RP computer. Variants of schemes with different numbers of RP are considered, as well
as models of cold backup of RP, remote controls, and the entire system. With such a variety
of configurations, problems arise in justifying and selecting calculation methods, and in
providing an unambiguous, generalized representation of the reliability parameters of a
group control system. Increased requirements for the reliability of components of the group
management system require an accurate assessment of reliability and are dictated by the
significant cost of equipment and functional purpose. The developed method is intended for
modeling the reliability of the developed system of group control of robotic platforms RP.
The proposed method shows the use of structural, probabilistic and matrix methods for ca lculating
reliability models of a group control system. An approach to modeling the reliabi lity
of integer, redundant, sliding, and cold redundancy of RP and control panels is also pr oposed.
The results of numerical calculations of the reliability parameters of the group management
system allow us to assess the risks and choose modes, depending on the required
efficiency of the mission.

The work is devoted to the synergetic synthesis of the harmonic disturbance asymptotic observer
for the aircraft hierarchical control system. The paper contains the general description of “flying platform”
type vertical take-off & landing aircraft & an asymptotic observer of external disturbing influences
(for example, wind) that have a harmonic dynamics & cause periodic changes in flight height, as
well as in pitch & roll angles. An asymptotic observer must ensure the asymptotic stability of a reserved
system, the implementation of technological invariants, the estimation of unobservable external influences
from the current values of the observed state-space variables, & the absorption of harmonic wind
disturbances. The article also presents an extended mathematical model of the “flying platform” in the
vertical movement mode under external harmonic disturbing influences, including a mathematical description
of the disturbance dynamics, & the upper hierarchy level control algorithms based on the
given technological invariants are synthesized. In addition, the equations of the disturbing influences
asymptotic observer are calculated, which supplement the mathematical model of the “flying platform”
under disturbed motion, & the equations for asymptotic estimates of unobserved variables are calculated,
which are further included in the upper hierarchy level control laws. The possibility of the disturbance
observer synthesis was verified using the observability criterion. Finally, the results of computer
simulation of the upper & the lower hierarchy levels’ nonlinear dynamics under disturbed motion with
suppression of external disturbances by an asymptotic observer are shown, as well as the results of
computer simulation of the vehicle’s nonlinear dynamics under disturbed motion without an asymptotic
observer to allow a visual assessment of the observer’s performance by comparison. The relevance of
the work consists in the necessity of “flying platform” type vertical take-off & landing aircraft creation
to increase the effectiveness of people rescue operations in those disaster areas where helicopters &
other modern means don’t cope with a task. The scientific novelty of the work consists in synergetic
approach application to the design of the vehicle’s spatial position system equipped with an asymptotic
observer to suppress disturbing influences.

Recently, there has been a rapid increase in interest in quantum computers. Their work is
based on the use of quantum-mechanical phenomena such as superposition and entanglement for
computing input data into output data that can actually provide effective performance 3 to 4 orders of
magnitude higher than any modern computing devices, which will solve the above and others tasks in
a natural and accelerated time scale. This article is devoted to solving the problem of research and
development of corrective codes for correcting several types of quantum errors that appear during
computational processes in quantum algorithms and models of quantum computing devices. The aim
of the work is to study existing methods for correcting various types and types of quantum errors and
to create a 3-qubit corrective code for quantum error correction. The work touches upon the tasks of
research and development of the functioning methods of quantum circuits and models of quantum
computing devices. The relevance of these studies lies in the mathematical and software modeling
and implementation of corrective codes for correcting several types of quantum errors as part of the
development and implementation of quantum algorithms for solving classes of classical problems.
The scientific novelty of this area is expressed in the exclusion of one of the shortcomings of the
quantum computing process. The scientific novelty of this area is primarily expressed in the constant
updating and addition of the field of quantum research in a number of areas, and computer simulation of quantum physical phenomena and features is poorly illuminated in the world. The aim of the work is computer simulation of a quantum computing process using the method of correcting
phase types of errors, which allows one to evaluate the own phase of a unitary gate that has
gained access to the quantum state in proportion to its own vector.

One of the important tasks of monitoring technical objects is the prevention of emergency
situations. This task is associated with the implementation of a reliable and adequate assessment
of the health of the object. The assessment of the object’s health is based on an analysis of the
behavior of its controlled parameters in real time. Only then it will be relevant. A method for determining
the nature of a parameter change based on an analysis of a sequence of special spatial
graphical forms called Poincare graphs is proposed. The selected parameter should largely determine
the operability of the controlled object. Charts are formed on the basis of the time series
of the controlled parameter. A time window is selected that cuts the specified number of parameter
values. A graph is plotted for each step of moving the window along the time series of the parameter.
The transformation of the form of a given type is analyzed, which is superimposed on the totality of
parameter values presented in the form of a graph. By changing the form parameters, a conclusion is
drawn on the nature of the parameter changes. The paper shows the possibility of using Poincare
graphs to track changes in the state of a technical object in real time. This takes into account the
peculiarities of information retrieval from sensors. The assessment is implemented using a microprocessor
module included in the monitoring system. The structure of a generalized one-factor model is
also proposed, which tracks the change in the state of an object based on an analysis of Poincare
graphs. The option of assessing the state of the object by comparing the characteristics of the graph
with the criteria is given. The criteria are obtained after preliminary processing of a large array of
data on the behavior of the controlled parameter. Each criterion value is associated with an expert
assessment that determines the state of the object. The assessment allows you to determine the degree
of operability of the facility and implement the necessary actions in case of danger.

The article is aimed at measuring the parameters of the harmonic process by the multiplication-
conversion method. The simulation was carried out through the use of the LabVIEW software
environment, as applied to the digital multiplier-conversion method, the main points of which are
presented in the form of a progressive chain: a) development of the first harmonic process; b) the
multiplication of the indicator of the first harmonic process by four; c) the arrival of to
the band-pass filter PF1 tuned to the highest frequency, in this case, d) simultaneously, using
the generator Г2, a second source signal is generated; e) This oscillation is raised to the
fifth power, f) using the filter PF2 tuned to a frequency of 5 , select the fifth harmonic g) The
signals received at the outputs of the filters are added and the result of the sum is subjected to nonlinear
transformation h) Then, from the resulting square of the sum of the signals and using a
band-pass filter PF3, we extract only the low-frequency harmonic with the frequency i) Then,
using the Hilbert transform, we extract the total instantaneous phase from the harmonic and it
becomes the object of the derivative operation, which leads us to obtain the instantaneous frequency
function, characterized by a fixed dispersion. j) The law of fluctuations of the frequency
resulting from the use of multiplication-conversion operations is compared with a given frequency,
and we proceed to determine the mathematical expectation and standard deviation. The conclusion
about the frequency instability is based on the discrepancies obtained. Applying nonlinear
transformations of oscillations of oscillators similar in instability and obtaining the oscillations of
a given frequency in the same way, the measured frequency instability is established. If you apply
this method many times to the oscillations of highly stable devices, you can develop an oscillation
with increased instability, and then evaluate it with available measuring equipment. Thus, we bypass
without high costs by performing this operation. Then, determine the initial instability by the
formulas given in this article.

Heat treatment of dielectric materials and food products is one of the important directions in
the development of the production of various products. The use of the electromagnetic field energy
of ultrahigh frequencies for drying, heating, defrosting and pasteurizing food products is promising,
since such technologies are suitable for processing various dielectric materials and, at the
same time, are efficient and environmentally friendly. Despite many developments in the field of
microwave processing of materials, the creation of a universal device suitable for heat treatment of
any kind of materials is difficult because of the variety of their shapes and sizes, as well as the
significant difference in the electrical properties of variouse dielectrics. Therefore, in each specific
case, it is required to create an optimal design of the device and choose the option for exciting the
electromagnetic field. This work is devoted to modeling the absorption of energy of the microwave
electromagnetic field in a device for milk pasteurization. Using CAD FEKO, a 3D model of the
device was built and its operation was modeled. The study of the influence of the angle of inclination
of quartz tubes on the distribution of the electromagnetic field in the waveguide is carried out.
The results show that most of the power is absorbed closer to the beginning of the waveguide, and
this phenomenon is more pronounced with an increase in the angle of inclination of the tubes.
On the basis of performed calculations, the optimal angle of inclination of the tubes was determined.
The influence of the diameter and material of the tubes was also considered. The distributions
of the electric field and specific power absorbed per kg of dielectric in the waveguide are
obtained. The accuracy of the results is evaluated. Possible modifications of the proposed design
of the pasteurization device can be made by choosing other variants of the arrangement of the
tubes with milk. The thickness of the tube's walls can also affect the absorbed power. In addition,
the composition of milk can change its electrophysical properties, and therefore can also affect the
level of absorbed power. However, these questions require further research.

High speed and efficiency of microwave heating of dielectrics makes it possible to use the
electromagnetic field to heat and dry almost any material containing moisture. One of the promising
areas for the use of microwave energy is the intensification of the grain drying process.
To ensure rapid prototyping and reduce the possibility of losses caused by errors at various stages
of equipment development and implementation, model development is of particular importance.
The purpose of this work is to perform simulation of a slotted waveguide grating for grain drying.
The main task of the simulation is to ensure an even distribution of power to each slot. A specialized
software package FEKO is used as a modeling environment. To describe the model, an exact
calculation method is used - the method of moments. The distribution of the electric field and specific
absorbed power in a layer of grain exposed to microwave radiation is obtained. The models
were verified by comparing the results obtained with different mesh values of surface elements.
Modeling the distribution of the electric field strength showed that moving the waveguides away
from the cell with the grain leads to the leveling of the field irregularities, but in this case some of
the radiated power is dissipated into space. In this case, an increase in the distance between the
waveguides and the cell with grain does not affect the antenna SWR. It should be noted that in a
real situation, the wave nature of the field is smoothed out due to heat transfer, and this phenomenon
cannot be taken into account in the process of electromagnetic simulation. In addition, the
entire variety of possible changes in the dielectric parameters of grain should be investigated in
order to analyze the process of wave propagation in grain with high moisture. It is also advisable
to consider other modifications of slotted waveguide antennas, which can provide more uniform
heating in the container with grain.

Currently, there is growing interest in the tasks of efficient packet network management:
quality of service, ensuring information security, optimization of the network hardware and software
resources. All these tasks rely heavily on the analysis and classification of network traffic.
This traffic is heterogeneous, as a rule, has a pulsating nature, difficult to predict and described by
the mathematical apparatus of random processes. At different times, the conditions for passingpackets along the same path can vary significantly. At the same time, a significant number of applications
are appearing requiring latency and jitter. The administration task in this context is to
correctly configure the switching and routing nodes. Traffic classification allows you to identify
packages of various applications and services and ensure their prioritization during transmission
over the network. For example, video conferencing traffic needs to be transmitted first of all, since
it is very sensitive to delays and jitter, data traffic can be transmitted last. The classification of
traffic today is an urgent task both in terms of network administration and in terms of ensuring its
security. Due to the fact that a large number of applications now encrypt the transmitted information
and it is very difficult to view its contents, the traffic classification is of particular interest,
which allows indirect signs to determine anomalies in the network, signs of intrusion. In this paper,
we consider the features of solving the classification problem of encrypted traffic. The aim of
the work is to study the classification features of encrypted traffic using correlation analysis and
an algorithm based on the difference in integral areas. Research Objectives: – develop a traffic
classification algorithm based on correlation and known patterns; – develop an algorithm based
on the difference of the integral areas under the traffic intensity curves; – conduct a practical
study of the accuracy of solving the classification problem. The work considers the classification
of traffic into three groups: audio, video, data. As a result, a sufficient accuracy of the correlation
algorithm in determining audio and data traffic was revealed. To identify video traffic, it is better
to use an algorithm based on the difference of the integral areas under the intensity curves.

Usually, an information graph with associative operations has a sequential (“head/tail”) or
parallel (“half-splitting”) topology with invariable quantity of operational vertices. If computational
resource is insufficient for the implementation of all vertices, the reduction transformations
of graphs with basic topologies do not allow for the creation of an efficient resource-independent
program. In fact, the “half-splitting” variant is characterized by irregular connections between
iterations, and the “head/tail” structure has an increased data duty cycle in the reduced form.
In this paper, we propose to transform the topology of a graph with associative operations into a
combined variant with sequential and parallel fragments of calculations. The resultant combined
topology depends on computational resource of a parallel computer system, and such transformation
provides the improvement of specific performance for the reduced computing structure.
The considered topology contains isomorphic subgraphs with the “half-splitting” topology, which
include the maximal number of hardwarily implemented operational vertices, but the processing of
intermediate data is performed using the “head/tail” principle. The computing structure for the
combined topology has minimal latency and includes one basic subgraph and one vertex with
feedback. This vertex is obtained as a result of the “head/tail” block reduction. We develop an
algorithm for the conversion of the initial sequential graph to various combined topologies or to
the limiting case of the “half-splitting” topology with regard to available hardware resource.
Within traditional methods of parallel programming, it is possible to describe the variety of topologies
only as a set of separated subprograms. To create an efficient resource-independent program,
we propose the application of the Set@l programming language. We describe the
“head/tail” and “half-splitting” principles as the attributes of set processing methods in Set@l.
Resource-independent program uses these types and parallelism attributes for the modification of
topology and further reduction of performance in the corresponding aspects.

The quality monitoring system for traditional and distance education requires the development
of machine learning classification and quantification techniques necessary to predict individual
and collective student performance. This article theoretically and experimentally shows that
the most promising approach that simultaneously solves both forecast tasks is to create heterogeneous
ensembles consisting of an odd number of different base classifiers, such as decision trees,
simple neural networks, naive Bayesian classifier and others. By training and testing 11 different
binary classifiers on six different samples of educational data, we show that the individual determined
forecast of such ensembles exceeds the accuracy of forecasts of both individual base classifiers
and homogeneous ensembles created by bagging and busting technologies. The advantage of
heterogeneous ensembles is decisive when we deal with the imbalance of sample characteristic ofeducational data. In these cases, only the forecasts with accuracies exceeding the relative frequency
of the class of objects dominating in the sample of data can be considered as useful forecasts.
The main advantage of the heterogeneous ensemble is the ability to transform the deterministic
forecast into a probabilistic forecast, when instead of referring the object to a particular class, the
probability of its belonging to individual classes is given. On this basis, we have proposed a new
method of binary quantification, where individual probabilities of belonging to each of the classes
of objects are summed up separately, and the resulting total probabilities are interpreted as relative
frequencies of objects in the sample. As a result of experiments, it is shown that such ensemble
binary quantification is significantly superior to the traditional "classify and count" method.

The article discusses the features of the application of certification methods for protected
premises. Such techniques are developed and regulated by the Federal Service for Technical and
Export Control. The need for certification is associated with the presence of technical channels for
information leakage, through which an attacker can obtain information constituting a commercial,
state or other secret. The presence of technical channels for information leakage is due to physical
processes associated with the propagation of acoustic, electromagnetic, and optical waves.
Through such channels, leakage of acoustic, specific information, information processed by technical
means and systems is possible. In the framework of this work, the features of certification of
protected premises against leakage of acoustic information are considered. Certification includes
instrumental measurements that allow you to detect an informative signal in communication lines,
on the air, in heating, water supply, ventilation, etc. In addition to measurements, certification
involves calculations based on which a conclusion is made about the conformity or noncompliance
of the level of protection. The calculation part is rather cumbersome and complex,
therefore the purpose of the work is to develop an algorithm that allows you to determine the degree
of security of the selected premises from the leakage of speech information. The objectives of
the work are: the development of auxiliary algorithms for calculating the security parameters of
the room for each type of voice information leakage channel; implementation of software that
allows you to determine the degree of security of the room; conducting a study of the dependence
of room security on the noise level using the developed software. As the results of the work, the
synthesized algorithm and the developed software tool should be noted, which can significantly
reduce the time for the procedure for assessing the security of the room and avoid errors.
The result of the work is the study of the dependence of verbal intelligibility of speech on the noise
level in various octaves. Studies have shown that verbal intelligibility, which determines the security
of a room by acoustic parameters, decreases non-linearly with an increase in the noise level at
a fixed signal level.

In the process of solving a wide range of applied problems, it becomes necessary to decompose
objects. As a result, the classification problem is an urgent problem in modern data mining
systems. Binary classification is one of the most important tasks, and has a number of unsolved
problems. One such problem is the effectiveness of automated classification. In the tasks of automated
classification, it is relevant to use the algorithmic apparatus of evolutionary computing.
Thus, it is advisable to use genetic and bio-inspired algorithms in the task of finding the optimalvalues of the classifier parameters. To solve this problem, it is proposed to apply the particle
swarm algorithm (PSO). This algorithm in the context of the task of finding suboptimal values of
the parameters of the classifier is able to provide high quality classification. A modification of the
algorithm is a dynamic change in the coordinate values that are responsible for the type of kernel
function. This revision can significantly reduce the time spent developing the classifier. To increase
the classification efficiency, it is advisable to use ensembles of algorithms. The paper presents
the structure of a two-level classifier. At the first level of this classifier, an ensemble of simple
classifiers is formed that form the training set, which is further used by the particle swarm
algorithm in the second stage. This approach can significantly reduce time costs, as well as improve
the quality of the resulting solutions. The particle swarm algorithm (PSO), in the context of
the task of finding suboptimal values of the parameters of the classifier, is able to provide high
quality classification. The proposed two-level algorithm has been experimentally tested. A comparison
is made with analogues, comparative charts are given. The described studies show that
the work is of high theoretical significance, and the conducted experimental studies prove high
practical significance.

Research in the field of artificial intelligence is carried out with increasing interest every
year. The fields of application of artificial intelligence are quite extensive: automation, analysis of
a large amount of data, smart home technology, machine vision, etc. Artificial intelligence technologies
are based on the use of artificial neural networks, which are based on the principles of
the animal nervous system. In this case, the actual issue is the implementation of artificial neural
networks on various software and hardware platforms: programmable logic integrated circuits of
the FPGA type (Field Programmable Gate Array), on special purpose integrated circuits (Application-
Specific Integrated Circuit, ASIC), GPU, CPU etc. FPGA performs best in low-power mobile
systems. ASIC demonstrates the highest performance at a fairly high development cost.
The problem of rapid prototyping of projects based on the use of artificial neural networks for
FPGAs using conventional methods (using HDL languages, HDL encoders, graphic programming)
is that either such a project is complex and time-consuming to debug (HDL languages), or
the resulting code is not optimal (HDL encoders), or the duration of the project development and
the complexity of reconfiguring the neural network (graphical programming) are high. Therefore,
in the framework of this work, an effective method for designing fully connected and convolutional
neural networks for their implementation on FPGAs using the Xilinx System Generator for DSP
and Matlab / Simulink package is considered. Artificial neural networks generated in this way are
easily reconfigurable and allow solving the following problems: image recognition, optimal filtering
(for example, for problems of subsurface radar).

The article is devoted to the problem of identifying implicit information threats of a user's
search activity in the internet space based on an analysis of his activity in the course of this interaction.
The use of knowledge stored in the Internet space for the implementation of criminal intentions
poses a threat to the whole society. Identifying malicious intent in the users’ actions of the
global information network is not always a trivial task. The proven technologies for analyzing the
context of user interests fail in the case of cautious and competent actions of attackers who do not
explicitly demonstrate the goal they are pursuing. The paper analyzes the threats associated with
certain scenarios for the implementation of search procedures that manifest themselves in search
activities. Criteria of inefficient and effective search scenarios estimation are described. Among
the signs indicating the possibility of a threat, the following main ones are highlighted: avoiding
solving the problem in aimless navigation or attractive resources, superficial search, lack of
meaningful immersion in solving the search problem, and chaotic actions during the search.
To determine the presence of adverse signs, a system of indicators is built. The features of an effective
scenario for organizing a search in the Internet space are formulated, options for the presence
of implicit threats for a similar situation are described.An approach for identification the
described threats is presented taking into account the specified criteria for evaluating various
scenarios of user behavior in the global information space. A machine learning algorithm has
been developed to identify problem scenarios by comparing with key behavioral patterns. The
software implementation of the subsystem for identifying information threats has been created,
experimental studies have been conducted to confirm the effectiveness of the subsystem. Experimental
studies were carried out on the basis of processing open data from social networks, as well
as using analysis of user search activity in the university corporate information environment.

We are living in the today’s society, where we have fairly-enough storage capacity and processing
power, the only issue is with security. As, the technologies are evolving with faster rate, we
are tend to grow the use of electronic devices rapidly in todays’ society, it started to flow or leakage
of personal information around/across, which then leads to breach of this information. Now,
personal or identical verification is key problem is being crucial. So whatever traditional methods
we have for providing authentication or security those have proven inadequate to be unreliable
and do not provide strong security. Biometric template protection is one of the most important
issues in securing today’s biometric system. We have many algorithms which don’t give adequate
solution for the same. So we tried to give a method which will reach to the expectations more satisfactorily
and certainly to the extent required. In this paper we have discussed a hybrid method for
finger vein biometric recognition based on deep learning approach using BDD and fuzzy commitment
schemes. The proposed hybrid method consists of four parts, namely Finger vein feature
extraction, BDD-based secure template generation, Fuzzy commitment scheme and ML based
finger vein recognition and decision making. Thus it has four module and each module works efficiently
and gives accurate results on all databases.

Land-use and vegetation cover are the natural state of the earth's surface. Remote sensing is a
very important land use study (LULC) method. Various classification methods are used to analyze land
cover in remote sensing. These methods do not require prior information on land cover or land use
types. Two classification methods are most commonly used to analyze remote sensing images. These
include controlled classification and uncontrolled classification. The objectives of the proposed work
are to use unsupervised classification methods to find clusters, determine land use types, and compare
these methods with interactive analysis of self-organization data (ISODATA). Hyperion sensor images
were used for land use analysis. The Hyperion sensor has two hundred and forty-two bands, but fewbands provide useful information for spectral analysis. Therefore, bands that do not contain useful information
are identified and removed. After processing the input image according to this algorithm, out
of 242 bands, only one hundred and sixty-five bands remain. This takes into account radiometric calibration
and an important correction of atmospheric factors. Then, based on the results of processing
using the proposed methods, clusters are formed to study land use using a hyperspectral image. To form
clusters, the pixels were grouped based on the selected data. Pixels from the same cluster have more
similarity, while pixels from different clusters differ from each other. Based on the results, it is concluded
that the clustering method (k-means) allows better identification or prediction of land use based on a
high-resolution hyperspectral image than the Interactive Self-Organization Data Analysis (ISODATA)
method. The output image, which is the result of clustering, can be used to identify different types of land
use objects. The LULC classes predicted are Water Body, Agriculture Land, other Vegetation, Built Up
or settlement, Bare Land and Rocky region.

The work is devoted to experiments with various methods of selecting special points on images,
followed by their description with a binary descriptor and comparison by a full search method.
This paper actively uses the method of describing the neighborhood of singular points, based
on the construction of a binary string that characterizes changes in the brightness of pixels in the
described neighborhood. The resulting string is obtained by comparing the brightness of pixels
according to a specific template. Today, the use of special points when working with images allows
you to develop applied methods in various areas of computer vision with increased requirements
for working time and resistance to sudden changes in scenes. The paper presents the results
of experiments with special points of various classes, the classification is given in section 1. During
the experiments, methods implemented in the OpenCV library were used. The paper provides
brief descriptions of the methods used in experiments. Section 1 of the paper offers a classification
of modern types of singular points of images and provides a brief description of popular methods
for detecting the described types of singular points. In section 2, the authors give a General description
of methods for working with special image points. Section 3 describes the experiments
that are being carried out with the comparison of special points of different types described by a
single descriptor, and reveals their results. The experiments performed allow us to identify the
strengths and weaknesses of bundles of different types of singular points when comparing them.

The paper provides an overview of some studies on the recognition of images of crops,
plants and forests. These image recognition systems use various methods of pre-processing, computer
vision, and deep learning. Recently recognition systems based on mobile devices are increasing,
which increases their availability and wide distribution. The articles on recognition,
classification of fruits and fruits in orchards, the creation of a data bank of these agricultural
products (apples, pears, kiwi) to assess ripening and yield are considered. The works devoted to
the automation of harvesting grain crops are described on the example of the work of a combine
harvester using machine vision. Crop production plays an important role in providing feed for
animal husbandry; articles on the recognition of agricultural plants based on leaf images are
analyzed. Also, by the condition of the leaves of potato bushes, you can determine their disease,
assess the condition of the soil. The work on the development of mobile systems for monitoring and
recognition of the process of growing mushrooms based on the "green house" technology for
farms is presented. Using remote diagnostics, you can analyze and monitor the state of the surface
of land and seas. For remote environmental monitoring of the landscape of the earth's surface,
work is described on the recognition, classification of forests, water resources using hyperspectral
analysis of satellite images.

The paper investigates the possibility of changing the properties of piezoelectric ceramics for various purposes.
The aim of the study is to correct properties by changing technological factors in the manufacture of
piezoceramics without modifying their chemical composition. At the most important technological stage – sintering
– the density, hardness and strength of piezoceramics are formed, which directly affect its electrophysical
parameters, since the piezoelectric effect is an Electromechanical transformation. Of particular interest are sintering
methods that combine the process of compaction of particles with heating - hot pressing and spark plasma
sintering. Such methods, due to the created uniaxial pressure, activate the diffusion processes of mass transfer
during sintering, contributing to the production of high-density piezoceramics while lowering the sintering temperatures. However, unlike hot pressing, spark plasma sintering generates spark discharges between the powder
particles, which, in combination with ultra-fast heating (up to 1000 ° C/min), forms a fine-grained monophase
structure of ceramics. This microstructure increases the mechanical and electrophysical parameters of the resulting
ceramics. The aim of the study was to test the proposed sintering methods on piezoelectric materials of different
compositions in order to control their properties. The objects of research were piezoceramic materials based
on the zirconate-titanate-lead system and their modifications, including multicomponent materials with high application
potential, as well as lead-free ferroelectric material Ba0.55Sr0.45TiO3 (BST). The dependences of the
formed ceramic structure on the sintering method and temperature were determined using scanning electron
microscopy. The regularities of "sintering method – microstructure – properties" are established. The effectiveness
of hot pressing and spark plasma sintering methods for correcting the properties of piezoceramics of various
types of applications has been confirmed, which together with a decrease in sintering temperatures, as well as a
reduction in the duration of the process (by 36 times!) relevant for energy saving purposes.