No. 2 (2024)

A promising solution to global optimization problems are metaheuristics inspired by nature, which
are non-deterministic algorithms that explore the search space, solutions, learning in the search process,
not tied to a specific task, although they do not guarantee accurate solutions. The purpose of this study is to develop an effective algorithm for solving applied problems of global optimization of multidimensional
single-modal and multimodal functions found in engineering design, image processing and computer vision,
energy and energy management, data analysis and machine learning, robotics. To achieve this goal, the article
proposes a computational model of the collective behavior of a group of animals and an effective algorithm
for differential vector motion. The model includes various patterns of behavior in a group of animals:
to hold the current position; to move towards the nearest neighbors or, conversely, from the nearest neighbors;
to move randomly; to compete for a position. The collective memory stores information about the location
of the dominant individuals of the group and the direction of movement of the group, the best positions of
agents, taking into account the mechanisms of competition and dominance in the group. The algorithm was
experimentally tested on seven known multidimensional single-modal and multimodal functions. The results
were compared with a genetic algorithm, a particle swarm algorithm, and a gravitational search for differential
evolution. The proposed algorithm showed better results than competing algorithms on all test functions.
This is due to the better balance of the new algorithm between the rate of convergence and the diversification
of the solution search space. Verification of the results obtained using the Wilcoxon sum of ranks T-test for
independent samples showed that the results of the algorithm are statistically significant. A comparison was
also made with one of the most effective continuous optimization algorithms of BFGS - a quasi-Newtonian
iterative numerical optimization algorithm designed to find the local extremum of single-modal functions. The
results were comparable for multidimensional functions. The algorithm was also compared with the
multistart method in the problem of global optimization of multi-extreme functions and proved its advantage
in terms of time and accuracy of the solutions found.

A hybrid model of the system of text-independent dynamic verification of users of information systems,
which is based on the integrated use of artificial immune systems and artificial neural networks, is
proposed. The verifiable data of text-independent dynamic user biometrics are represented by two sequences
of information units of fixed-size feature vectors corresponding to the images of two classes –
‘friend’ and ‘stranger’. This representation is oriented towards the massively parallel decentralized data
processing adopted in artificial immune systems. The subsequent verification of the users of both classes is
realized by a probabilistic artificial neural network, which computes the probability densities of the concentration
of information units of both classes in the feature space. In addition to the probability density
characteristics of the information units, the allowable 1st and 2nd kind error prices for images of each
class are used. The final result of biometric verification of the working user is controlled based on the
current comparison of the aggregate statistical estimates of the probability density and the acceptable
price of errors of the images of each of the two classes. The proposed approach to verifying the identity of
a working user allows to propose a general scheme of this procedure for significantly different modalities
of dynamic biometrics: voice, handwriting, and keyboard typing. The implementation of such an approach
for specific modality biometrics will be slightly different, but the general verification scheme can be maintained.
The advantages of the proposed approach are: the possibility of text-independent analysis of dynamic
biometry of different modality, arbitrary volume, content and language; possibility of making a verification decision in continuous mode at the rate of user's work arrival; in the future to increase the
accuracy of the verification system by increasing the dimensionality of the neural network; the possibility
of using the history of analysis of verification results of real users for further more accurate tuning of the
system. A relative disadvantage of the work is the necessity of program realization of a neural network of
large dimensionality. However, in the future, this disadvantage will be quickly leveled with the increase of
computing performance.

This article proposes a wide-format image processing algorithm for use in systems operating in real
time with a high-speed video data stream. The issue of image preprocessing, its clustering, segmentation
and labeling is of particular importance for systems for processing high-resolution video streams in real
time. In addition, when implementing such algorithms, there is an urgent issue of minimizing the cost of
computational resources of programmable logic integrated circuits (FPGAs), on which the direct deployment
of streaming image processing algorithms takes place. Minimal resource consumption is ensured by
single-pass marking algorithms, which eliminate the need for image buffering, which is especially important
when processing high-resolution wide-format images. However, when implementing a single pass
of an image through the processing system, many additional markers may be created that are subject to
further combining, especially when analyzing images with high resolution. The additional markers created
require an increase in the requirements for the number of usable memory cells on the FPGA. The algorithm
for streaming high-resolution wide-format images described in the article makes it possible to label
high-resolution streaming video images, reducing the likelihood of creating additional tags that need to be
further combined. The essence of improving the algorithm relative to the standard one-pass one is to add
additional elements to the scanning mask, which avoid the appearance of different labels corresponding to
the same object, which allows, with a minimal increase in the amount of memory used on the FPGA, to
avoid duplication of labels and overuse of device memory. The algorithm was simulated for implementation
on an FPGA using the Xilinx System Generator for DSP tool in conjunction with the Matlab Simulink
environment for model-based design (MBD). The results of the algorithm are presented on images obtained
from a high-speed linear camera TELEDYNE DALSA LA-CC-04K05B-00-R using the Integre
Technologies LLC FMC-200-A mezzanine, as well as the Xilinx ZYNQ Ultrascale+ MPSoC ZCU106 development
board.

The article considers the problem of controlling the distribution of energy power in an area covered
by an intelligent energy network. The management objective is to stabilize the energy flow in the presence
of external influences caused by changes in the surrounding environment. Vulnerabilities in the system are
inherent due to the nature of energy networks and under certain circumstances can lead to anomalies in
energy supply. External environmental factors vary in content, making it difficult to confidently predict
current threats. Geoinformation models utilizing image-based knowledge representation are described.
Their use enables the assessment of the relevance of known threats. Conceptually, an image comprises a
center and permissible transformations of that center within a certain context. The case is considered
where the threat to the functioning of the intelligent network is assessed by transforming the image into a
specified area of space where the intelligent network is located. The key feature of the proposed approach
is the evaluation of the feasibility of an event occurring in a given space. The operation of transferring the
situation requires consideration of the topology of the specified area. The attributes of the generating
infrastructure become more significant than the attributes of the situation itself in this approach. A distinctive
feature of the proposed approach is the transfer of semantic context represented by permissible transformations
of the image. The software transformation function is linked to a layer of cartographic representation.
For a given object in the original precedent, its placement area is determined, with the boundary
being defined by the object's properties. If the size of the placement area allows for the construction of
an object of the corresponding class, that object is created. The credibility of the result is evaluated by
applying expert knowledge about the quality of objects of the considered class. The listed actions are performed
not only on the geometry of spatial objects but also on their temporal and semantic attributes, akin
to the concept of image-based representation of geometry. Forming a list of threats given a specific state
of the external environment constitutes the essence of stability management. The features of algorithmizing
the image transformation procedure are analyzed, and a method for assessing the credibility of transformation
is provided. The application of the proposed approach holds promise for intelligent energy supply
systems, whose behavior is intricately linked to external environmental factors.

The article is devoted to solving the scientific problem of creating a top-level description of a
knowledge ontology model for intelligent systems for processing and analyzing texts in natural language,
built on the basis of an original component architecture that provides the necessary level of detail in the
specifications of the analyzed text information. The relevance of this task is due to the need to develop the
theoretical foundations for constructing information models of semantic dependencies within texts in natural
language. The author gives definitions to the main terms of the subject area under study. A formalized
definition of the problem being solved is presented. The problem of the “information explosion,” which
was caused by the exponential growth in the volume of digital information, has led to a situation where up
to 95% of the information flow contains unstructured data. In such conditions, the task of creating effective
intelligent systems for searching and acquiring knowledge, including intelligent systems for processing
and analyzing texts in natural language, becomes extremely urgent. The scientific direction for
solving this particular problem is Text Mining (TM) – the excavation of knowledge in text information.
As an example of the applied task of using acquired knowledge, this study examines the significant problem
of information support for the processes of preventing and/or eliminating the consequences of emergency
situations. In this task, the initial data are streams of text messages (news information, reports on
the technical condition of man-made objects, information about natural phenomena, etc.) arriving at decision-
making centers, and the output is formed by predictive assessments and/or specific instructions regarding
the assessment situations and actions taken by certain specialists. One of the reasons hindering
the development of intelligent text processing and analysis systems for solving problems of searching,
acquiring and using knowledge is the insufficiently high level of models and algorithms efficiency that
provide a comprehensive solution to the above-described problems of artificial intelligence, taking into
account the peculiarities of semantics and context.

A carrier vessel is used to transport an underwater cargo. The given vessel is equipped with a unit for
lifting underwater cargoes designed to capture it, lift it, secure it on the vessel and transport it to the base
point. The given unit includes the following components: the descent module, the lifting mechanism, the locking
mechanism, the damping mechanism and the control system. The paper presents the findings of the mathematical
model development of the main components for the unit to make a crucial contribution to obtaining
reliable results – an underwater cargo, an asynchronous motor, a cable suspension and a compensation
mechanism. The underwater cargo is described based on the theorems about the change in the amount of
motion and kinetic moment of the mechanical system. In the equations of linear and angular displacement of
a cargo, there is a mass of liquid in it. The cable suspension model takes into account its deformation in motion
while operating. The model of an asynchronous motor with a short-circuited rotor is obtained from a
generalized circuit. A vector control method is provided, the rotor flow coupling vector is taken as the base
vector. The compensation mechanism model is based on an adiabatic process in a macroscopic system,
where there is no heat released into. For the control system synthesis, the cargo is represented by a transfer
function in the form of an aperiodic link of the second order. There is a three-loop PID controller synthesized
with feedback in position, speed and current. Equations are obtained for calculating the generalized dynamic
characteristics of a closed second-order system, and the controller parameters are calculated. The findings
carried out on mathematical models of the system help us to obtain initial information about the linear and
angular displacement of the descent module in steady state, the movement of points of external and internal
suspensions, the magnitude of the force on the cables, the torque and speed developed by electric motors of
winches. Modeling of descent, stabilization and ascent modes made it possible to adjust the parameters of the
equipment and achieve satisfactory results of the complex's operation.

The article is devoted to the actual problem of catamaran roll imitation, software and algorithms
that allow to implement this simulation. The relevance arises from the need to test navigation devices and
their algorithms, to build large simulator complexes to reproduce roll and impulses of surface, air and
ground-based vehicles. This article will focus on the description of software and algorithms for developing
a roll simulator of a catamaran located on the sea surface when it disturbed by windwave influences.
The simulation test bench for reproducing the catamaran roll includes a Stewart platform, sensors, microcontrollers
and an operator's personal computer. The upper part of the platform moves like the deck of a
catamaran, and the lower part is rigidly fixed. The experimental results are taken into account by sensors
mounted on a movable part and processed by a microcontroller-navigation system prototype. It is believed
that the navigation system should receive data about the pitching object and return to the operator a state
vector containing the angle and speed of roll, angle and speed of pitch, height and speed of heave.
The applied mathematical models describe the dynamics of a catamaran and a control system that reduces
the amplitude of pitching, external disturbances of the sea wave formed by the Pearson-Moskowitz spectrum.
To obtain the catamaran's roll trajectories, the Runge-Kutta 4th order algorithm with a fixed step is
implemented, and for filtering and restoring the full vector of catamaran states the Kalman filter is implemented
according to the “delayed” scheme. Software has been developed to reproduce the roll of a catamaran
on a simulation test bench, filter and restore the state vector, graphically display the results of the
experiment in the form of graphs, and save the results in files. For a better interpretation of the results, the
input parameters of the graphical interface and algorithms have simple visual parameters: the wind speed
and direction, the initial state of the catamaran and the service ones, and the results are presented in the
form of graphs. The article provides a detailed description of the relationship between program modules,
applied mathematical algorithms, and input and output parameters. The simulation results show a sufficient
quality of reproduction of the rolling of the catamaran. However, minor errors were identified due to
the mechanical limitations of the applied kinematic model.

The aim of this work is to conduct a systemic analysis of mobile robotic platforms that can be used
in agriculture for cargo transportation and weed control. This study is relevant due to the increasing population,
decreasing arable land, natural population outflow from rural areas, and reduction in agricultural
machinery. To achieve the set goal, a "tree" of objectives for the systemic analysis of the constructive
implementation of platforms has been formed, which precedes and decomposes the stages of designing
and developing agricultural robots. Due to the presence of fuzzy and verbal evaluation indicators by experts
of robotic platforms, the authors suggest defining them in the form of fuzzy intervals, which, with the
use of additive convolution, allow obtaining a composite indicator that can be presented either in fuzzy
form or in the form of pessimistic, optimistic, or neutral assessments. At the same time, the weighting coefficients
of additive convolution can also be presented in fuzzy form. For this purpose, operations of multiplication
and addition of fuzzy intervals are proposed. To conduct simulation modeling, the structure of
software is presented using an object-oriented approach. By overloading classical addition and multiplication
operations, it was possible to implement algebraic operations with fuzzy intervals without complicating
calculations. The modeling results confirmed the feasibility of the approach and allowed determining
the constructive implementation, layout, engines, and actuators for the agricultural platform. The
proposed methods can be used before the stages of designing and developing robots for various purposes,
and the use of indicators in fuzzy form allows reducing the burden on experts.

Complex socio-humanitarian systems are a type of systems that are studied in sociology, anthropology,
economics, political science, and other humanities. These systems are characterized by the complexity of
interactions between their constituent elements, which can be both human (individuals, groups) and cultural,
social, economic and political aspects. For example, society as a socio-humanitarian system consists of various
elements, such as people, culture, institutions, values, and so on. They interact with each other, forming a
complex network of connections and influences that determines the behavior and development of society.
To better understand such systems, various approaches are used, including systems analysis, social network
theory, complexity theory, and other methods. These approaches help to identify the main patterns in the
functioning of complex socio-humanitarian systems and predict their development in the future. This article
discusses approaches to identifying cause-and-effect relationships and highlights the basic requirements for
building these connections in the context of complex socio-humanitarian systems that deal mainly with semistructured
information, often in the form of natural language and texts. The strengths and weaknesses of the
identified approaches were identified, and examples of the use of modern methods of constructing graphs on
various tasks were considered: identifying risks in business, analyzing social phenomena, identifying the
presence of causality in texts. The study showed that the most productive methods are machine learning, for
example, language models for extracting knowledge from text in combination with neural network technologies
and graph representations of knowledge. They require solid knowledge of mathematics, statistics and
programming, at least in Python, with the most impressive tool support for solving machine learning problems.
Also, identifying causality is based not only on correlation but also on other methods such as the
Granger test used for time series analysis.

Currently, the relevance of using crypto assets is growing rapidly. In recent years, cryptocurrency
trading has become one of the most discussed topics in the world of finance and investment.
Cryptocurrencies such as Bitcoin, Ethereum, attract the attention of millions of people due to their innovativeness,
high profit potential, and decentralization possibilities. The blockchain technology, on which
cryptocurrencies are based, is one of the most innovative and promising technologies in the market. Studying
cryptocurrency trading helps understand how private investors and companies can use blockchain
technologies for investment and business development. One of the main reasons for the popularity of
cryptocurrency trading is its high level of volatility. The cryptocurrency exchange rate can change quickly,
providing opportunities for profit. This article focuses on exploring the use of predictive analytics for
decision-making in decentralized systems using cryptocurrency trading on centralized and decentralized
exchanges as an example. The research conducted in this work aims to investigate decentralized and centralized
systems to further develop decision support systems. A general description and operation schemes
of decentralized and centralized dynamic systems are provided using cryptocurrency exchanges as a research
example. This scientific article examines the typical structure of centralized and decentralized
cryptocurrency exchanges, analyzing the fundamental components and principles of their functioning.
The article discusses the internal organization of the exchange, including the system for storing digital assets, transaction execution mechanisms, security provisions, and risk management. It also examines the
interaction between the exchange and market participants, as well as regulatory bodies. Furthermore, this
scientific article explores the rules and principles of operation for traders and market makers on centralized
and decentralized cryptocurrency exchanges. It covers the main strategies and tactics used by market
participants to ensure liquidity and optimize trading operations. The article compares the trading approaches
on different types of cryptocurrency exchanges considering their specific features and impact on
cryptocurrency price dynamics. The presented results can contribute to a deeper understanding of
cryptocurrency trading processes and optimize decision-making strategies for investors and traders in the
crypto asset market.

The article presents open source software for automating the design of radiation protection screens
using Geant4 to protect electronic equipment from heavy charged particles. The article presents the chosen
architecture for the implementation of the proposed approach, and also formulates the required input
data and the resulting output data. The route of designing a screen based on input data about the material
is described as a sequence of creating appropriate successor classes. This article is an in-depth study
devoted to the development of open source software based on the Geant4 framework, which uses the Monte
Carlo method aimed at automating the design process of radiation protection screens in order to ensure
effective protection of electronic equipment from the effects of heavy charged particles. The article examines
in detail the architecture of the developed software, including a description of the main components
and technologies used in its creation, as well as determining the necessary input data and formulating
requirements for the software product. The presented screen design route is described as a sequence of
creating appropriate successor classes and their interaction within the framework of the developed architecture,
which ensures the efficiency and accuracy of radiation protection calculations. The results of this
work represent a new innovative approach to the design of radiation protection screens, which has the
potential to significantly increase the reliability and safety of electronic systems under the influence of
heavy charged particles. They are of great practical importance for specialists in the field of radiation
protection and electronics development, providing them with an effective tool for analyzing and optimizing
radiation protection screens. In addition, the results of the study are of interest to researchers working in
the field of modeling radiation effects and developing new methods for protecting electronics from radiation
exposure. In general, the article represents a significant contribution to the field of radiation protection
and electronics, and is also the basis for further research and development in this direction.

The aim of the study is to evaluate the effectiveness of using a nonlinear metasurface on a wedgeshaped
object to control the electromagnetic field reflected from it. In the study, a nonlinear meta-surface
is a two-dimensional ordered array, the elements of which, interacting with the electromagnetic field of an incident wave, are able to control the amplitude and phase of the transmitted and reflected waves, thus
allowing the wavefront to be controlled. The task of the research is to find and verify a method for analyzing
wedge-shaped structures with nonlinear loads of various configurations. When solving the researching
task, a model of the trailing edge of a wing of an aircraft with longitudinal nonlinear loads on both sides
is considered. The studied nonlinear elements are modeled by concentrated loads in zones on the surface
of the trailing edge of the aircraft wing. By selecting the parameters of concentrated loads, the type of
their nonlinearity is set. A method of numerical analysis of the model based on solving the scattering problem
and the problem of electromagnetic field radiation is described. A step-by-step sequence of actions is
presented from creating a three-dimensional model of the trailing edge of an aircraft wing, to setting calculation
parameters and obtaining results. The results of modeling the trailing edge of an aircraft wing
with a different number of nonlinear loads, different positions of loads relative to each other and from the
edge, and different parameters of concentrated loads are presented. The obtained results of
electrodynamic modeling allow us to do conclusions regarding the parameters of loads, their number and
location. Various combinations of loads were investigated, notably two, three and four nonlinear loads on
each face. The results for an ideally conducting wedge with two loads showed low efficiency in terms of
the possibility of increasing the levels of multiple harmonics relative to the main level in an electromagnetic
field scattered from the structure. The analysis of a wedge with three loads showed the possibility of
increasing the levels of multiple harmonics by 13 dB in the ±5° angle sector. Stable, in a wide frequency
band, an increase in the level of multiple harmonics by 13-23 dB in the ±80° angle sector is achieved
when four loads are placed on the trailing edge of the aircraft wing.

Modern technologies and urban infrastructure require innovative approaches to detecting fire hazards.
Effective and ultra-fast fire detection is becoming an integral part of safety. For this purpose, systems capable of
detecting and informing about a fire hazard situation in a matter of seconds are synthesized and implemented;
one of such systems is synthesized in the article. The research and synthesis of a mathematical model of a digital
universal fire sensor, which in turn is a complex of interconnected sensors, is relevant due to the constant development
of system infrastructure, the increasing complexity of electrical equipment and the need to reduce damage
arising from the outbreak and spread of fires. Predictive diagnostics of electrical equipment performance
allows timely identification and elimination of potential fire safety threats. Within the framework of this research,
a theoretical mathematical model of a real digital universal fire sensor is presented, first in a simplified
version, then in a more complicated version, taking into account the design and statistical approach to the problem
of finding the sensor response thresholds, a description of the parameters of the mathematical model and the
sequential principle of operation is given. This sensor is an innovative fire safety solution that provides a high
level of control and efficiency in real time. Based on the theoretical models presented in the article, a mathematical
model of the sensor has been developed, which is simulated using the Simulink software tool on real data
obtained from the sensor manufacturer. The simulation results showed that the model correctly describes the
behavior of a real sensor on all channels and can be used in further research, such as predicting and detecting
fire situations using neural networks. The synthesis of the proposed system is necessary for further research in
the field of forecasting and detection of fire hazardous situations based on the obtained mathematical model.

Wireless data transmission networks generate threats that cannot be protected against by means
traditional for wired networks, because in this case it is impossible to provide equivalent security of wired
networks due to the physical properties of the communication channel. The purpose of the article is to
determine the actual problems that exist in ensuring information security (IS) in wireless segments of data
networks. To achieve this goal, a selection of threats potentially realizable in wireless networks has been
made from the information security threat bank of FSTEC of Russia. It is established that the realization of
such threats can lead to a full set of violations of the state of IS, namely: violation of confidentiality, integrity
and availability of information. The existing practical ways of providing IS in wireless segments of
networks are considered. The analysis of these methods pointed out the technical possibility of creating an
additional boundary in the system of echeloned information protection. In turn, this provides the potential
to detect vulnerabilities and intrusions at the link layer of network communication both in local networks
of enterprises and in large-scale public networks. In accordance with the goal, aspects of building such a
defense frontier are grouped, related to control of the link layer of network interaction of wireless devices,
reduction of frequency-territorial clusters and legal support. The review of publications reveals a gap
between the existing approaches to radio monitoring and IS provision, and also reveals poor development
of the direction related to research in the field of detection and prevention of wireless intrusions. The obtained
result indicates the need to revise the existing concept of radio monitoring and develop appropriate
organizational and technical measures for its integration into the system of measures to ensure IS, which
should help to solve the problem of timely detection and prevention of intrusions into wireless segments of
data networks, as well as the identification of vulnerable elements of the infrastructure of these networks.

Currently, piezoelectric materials based on films, for example, polyvinylidene fluorides, have found
wide application in various industries. The interest in these materials is justified, first of all, by the advantageous,
in comparison with materials based on piezoceramic compositions, values of the density of the
film material, as well as the values of the effective piezoelectric coefficients, which makes it possible to implement new principles of loading in products in order to convert mechanical energy into electrical
energy. In addition, the lower rigidity of film polymer materials, compared to the rigidity of sensitive elements
of electroacoustic transducers based on piezoceramic compositions, makes it possible to create
designs of large-area transducers or antenna apertures assembled from these transducers, repeating the
contours of carrier housings. The article describes the prospects for the introduction of film polymer
piezomaterials into hydroacoustic and electric generating equipment products. Obviously, the introduction
of new materials into hydroacoustic and piezoelectric generator technology requires a rethinking of methods
for calculating the characteristics of products based on film piezoactive materials. One of the main
characteristics of electroacoustic transducers, used both in hydroacoustic technology and in products for
generating electrical energy through the use of sea or ocean surface waves, is the energy coefficient of
electromechanical coupling. The specified coefficient is a tensor physical quantity, and, accordingly, for
anisotropic materials, which are piezoactive films, for example, from polyvinylidene fluorides, a mathematical
apparatus is needed that would allow determining the components of the tensor of the energy coefficient
of electromechanical coupling during the design of hydroacoustic and piezoelectric generator
products. An attempt to develop such a mathematical apparatus was made by the authors of the article,
but in the course of the work performed, the analytical uncertainty of the components of the tensor of the
energy coefficient of electromechanical coupling was established. The article presents a scientific substantiation
of the identified analytical uncertainty of the components of the tensor of the energy coefficient of
electromechanical coupling from equations that establish the dependence of these components on coefficients
characterizing the mechanical and piezoelectric properties of film materials, taking into account
their anisotropy.

When designing microwave devices, an important role is played by the introduction of additional
structural elements or parameters into the filter topology, the appropriate choice of which allows you to optimize
the characteristics of the device according to a given criterion. The paper considers a method for expanding
the barrier band of a comb-type microstrip filter by introducing a longitudinal displacement between
the resonators. It is shown that a certain choice of the length of the coupling region between the resonators
makes it possible to minimize or reduce to zero the coupling between them in the vicinity of the tripled average
frequency of the main bandwidth, and thereby significantly suppress the parasitic attenuation dip in this
frequency range. In the process of designing the filter, a synthesis method was used based on the transition
from the filter to the corresponding 2n-pole, where n is the number of filter resonators. This approach allows
us to consider the filter as a set of individual resonators connected to each other, and to introduce the concept
of potential bandwidth, which can be easily determined by the characteristics of the 2n-pole and positioned
in the desired frequency axis interval by an easily formalized algorithm for selecting the geometric
dimensions of the device. The electrical characteristics of the 2n-pole used to synthesize the device within the
baseband and at the stage of optimizing the device parameters in the vicinity of the tripled value of the baseband
frequencies are the intrinsic conductivities of the resonators and the conductivities of the connection
between them. The aim of the work is to study the effect of the length of the coupling region between the resonators of a two-resonator microstrip comb filter on its electrical characteristics. It is shown that the
choice of the optimal value of the length of the coupling region between the resonators makes it possible to
expand the barrier band of the filter at a level of minus 30-35 dB by more than two times due to the suppression
of the parasitic bandwidth formed in the vicinity of the tripled average frequency of the main
bandwidth. This positive effect, which consists in expanding the filter barrier band, is confirmed by the
results of designing a comb filter on two offset resonators in the HFSS program.

In control and monitoring systems, low-pass filters and band-pass filters are most often used.
To limit the spectrum of signals from sensors, analog, discrete-analog and digital filters are widely used,
the amplitude-frequency characteristics of which are approximated by various mathematical functions,
incl. Legendre polynomials. The use of Legendre filters in the circuit of an automatic control system leads
to a change in its dynamic characteristics. The nature of this influence depends on the order of the filter
transfer function, as well as on the type of approximation that are chosen when designing the control and
monitoring system. The information delay in such filters causes the appearance of a dynamic component
of their error, which affects the overall error of the control and monitoring system, which reduces the
permissible speed of its operation. The article provides an analytical assessment of the dependence of the
magnitude of the dynamic error for low-pass and bandpass Legendre filters. This allows you to quickly
solve the direct and inverse problems of error distribution of the control and monitoring system and justify
the speed of its operation. The article analyzes the Legendre bandpass filter circuits of the first, second
and third orders, and then the results obtained are generalized to the Legendre bandpass filter of an arbitrary
order. It is shown that for low-pass filters the values of maximum dynamic errors can be obtained
with high accuracy. For Legendre bandpass filters, the errors in approximation of the mathematical dependence
of the maximum dynamic errors on the filter parameters are determined in units of percent, but
in some cases they can reach 20%.

Advances in microelectronics, especially the development of CMOS technology, have made it possible
to create devices with extremely low power consumption. This made it possible to develop autonomous
wireless devices that, using radio waves, not only receive, process, and transmit information, but also
receive power from the terminals. For wireless and battery-free power supply, harvesting of radio frequency
energy from the environment can be used: radiation energy from cellular stations, radio and television
stations, microwave ovens, Wi-Fi, Bluetooth, and other sources. To convert radio frequency energy
into supply voltage, rectifiers based on nanometer diode-connected MOSFETs are most often used. When
wireless powered devices are located far from the terminal or harvest energy from the environment, the
power density of the electromagnetic field and therefore the amplitude of the input voltage can be quite
small. The urgent task is to develop and study such devices capable of operating at very low input voltages. The purpose of the study is to analyze the rectifying properties of diodes based on nanometer
MOSFETs in weak inversion mode at ultra-low input voltages and to develop recommendations for the
choice of technology and design of microcircuits with wireless power. Expressions are obtained for estimating
the rectification coefficients of diodes in terms of current and power. Calculations using the obtained
expressions and modeling using the BSIM4v4.8.2 model of current-voltage characteristics and
dependences of diode rectification coefficients for current and power on voltage for a typical 90 nm
CMOS technology were performed. The possibility of constructing rectifiers based on MOSFETs at ultralow
voltages down to units of mV has been demonstrated. Recommendations are given for justifying technological
and design parameters when designing modules for converting and harvesting energy of wireless
devices.

Generators stabilized by dielectric resonators have found wide application in communications, radar,
radio navigation and electronic warfare. A large number of works have been devoted to their research,
but increasing requirements for them forces radio equipment developers to look for new technical
solutions. Especially important is the stability of the frequency of microwave generators under the influence
of vibrations, shocks, temperature changes, changes in supply voltage. The influence of external influencing
factors leads to the appearance of parasitic signal parameters – frequency departures, expansion
of the spectral line, increase of harmonics and subharmonics. The purpose of this work is to measure
the parasitic parameters of the output signal. The object of the study is a serial microwave generator.
The paper gives a brief description of it. The generator has the following requirements: – calculation of a
dielectric resonator; – simulation of a microstrip filter from the frequency multiplier; – operating frequency
17490 ± 3.5 MHz; – output power of at least 10 dBm; – load resistance 50 ohms; – supply voltage
15 V; – consumption current no more than 215 mA. As the results of the study are presented: – frequency
run-out in 15 minutes after switching on; – frequency dependence on supply voltage; – the spectrum of the
output signal in the 100 kHz band; – the spectrum of the output signal in the 20 GHz band. The results
obtained can be used by students and teachers of radio engineering disciplines, engineers – developers of
radio equipment. The article complements the well-known results on the experimental study of generators
in terms of parasitic parameters of the output signal. For novice researchers, the experimental technique
may be useful.

In the design tasks of microstrip filters, a good choice of the initial approximation for the values of
the required geometric dimensions of the filter elements plays an important role. This is especially important
if the filter being designed has new design features and synthesis methods for this device are still
under development. The paper considers some results of the design of band-pass microstrip filters consisting
of counter-directional hairpin resonators with a metallized hole in the middle of each resonator. Such
a technical solution makes it possible to significantly expand the barrier band of the filter by suppressing
the parasitic bandwidth, which is inevitably formed in a traditional filter on half-wave resonators due to
the occurrence of resonance at twice the frequency of the main bandwidth. The introduction of metallized
holes into the resonator leads to the need to study the properties of these resonators and to determine the
potential capabilities of a bandpass filter consisting of such resonant elements. The most important characteristic
of a bandpass filter, specified in any design specification, is the width of the main bandwidth and
its position on the frequency axis. Estimates of the relative bandwidth of the filter are obtained depending
on the width of the microstrip conductor forming the hairpin and on the gap between the half of the hairpin.
As a result, the potential capabilities of the filters in question are determined by the relative bandwidth
they implement. The physical feasibility of the filter is understood as the ability to technologically
realize the values of all geometric dimensions of the filter elements, based on reasonable restrictions imposed
on them. These limits are determined by technological tolerances for minimum geometric dimensions
and dimensional and frequency limits for maximum dimensions. The paper defines a range of realizable
geometric dimensions. The method of solving the problem of filter synthesis is based on the transition
from a filter to a 2n pole, and in this work it is used as a tool to determine the potential capabilities of the
studied filters in the electrodynamic environment of HFSS modeling. The realized values of the relative
bandwidth of the filter range from 10% to 32%, which makes it possible to attribute this type of filter to
devices with moderate bandwidth. The results of designing filters on two hairpin resonators for cases of
extremely narrow and extremely wide bandwidth are presented.

High-temperature integrated circuits, which remain operational at temperatures above 150°C, are
required in many areas of industry: aerospace, aviation and automotive instrumentation, the petrochemical
industry, electric power, and military electronics. Currently, foreign enterprises are mass-producing
several high-temperature analog and analog-to-digital microcircuits based on silicon CMOS SOI structures
– ADS1278-HT, ADS1282-HT, ADS8320-HT, INA129-HT, INA333-HT, OPA2333-HT, etc. Hightemperature
silicon operational amplifiers and ADCs have also been developed in the Russian Federation.
However, the maximum operating temperature of such products does not exceed 200°C due to the limitations
of silicon technologies. For this reason, wide-bandgap semiconductors such as silicon carbide (SiC),
gallium nitride (GaN) and gallium arsenide (GaAs) are most often considered as semiconductors intended
for high-temperature microcircuits, which provide a number of characteristics necessary for hightemperature
applications: wide bandgap, high carrier saturation velocity and low concentration of intrinsic
charge carriers. An overview of the problems of developing high-temperature analog microcircuits
based on GaN and GaAs transistors is presented. The features of the current-voltage characteristics of
GaN and GaAs field-effect transistors operating in depletion and enhancement modes, electrical circuits
of typical analog devices (charge-sensitive and operational amplifiers, comparators, current followers)
and logical gates are considered. It is concluded that it is advisable to carry out the circuit synthesis of
GaAs analog microcircuits using field-effect transistors with an n-type channel operating in depletion
mode and p-n-p heterostructure bipolar transistors. Examples of such schemes are given. The relevance of
the above research is related to the problems of import substitution of microcircuits based on widebandgap
semiconductors (GaN, GaAs), providing a wide range of operating temperatures (over +150°C).

The choice of parameter values in evolutionary algorithms greatly affects their performance. Many
popular parameter tuning methods are constrained by the maximum number of fitness function evaluations
to find a good set of parameter values. Recently, an approach to algorithm selection for optimization
problems has been proposed, which uses the analysis of the fitness function landscape and machine learning
to select the optimal algorithm based on the characteristics of its landscape. Such application of fitness
landscape analysis motivates further research, particularly in the context of parameter tuning in evolutionary
algorithms. The use of landscape features allows for the identification of similar problems and
the use of parameter tuning data obtained from testing on benchmark problems, significantly reducing the
number of required fitness function evaluations during tuning. This work considers an approach to automatic
parameter selection using landscape analysis of the objective function and machine learning, using a genetic algorithm as an example. The proposed solution evaluates the characteristics of the
landscape of the optimization problem's objective function and suggests optimal parameter values for the
algorithm using a neural network. This network was trained on a dataset of landscape features expressed
as numerical features and their corresponding optimal algorithm parameter sets. In contrast to approaches
for automatic algorithm selection for a specific problem, this work addresses the problem of regressing
algorithm parameters instead of classifying the most suitable algorithm from a given set. The results of
experiments on different configurations of the W-model problem, as well as on the MAX-3SAT problem,
show that the proposed approach to automatic parameter selection considering the landscape of the objective
function can help determine appropriate values for the static parameters of the genetic
algorithm. The algorithm with the proposed parameter values outperforms other considered
options on average, requiring fewer evaluations of the objective function to find the optimum
compared to the other algorithms considered.

In order to develop an object detection algorithm for embedded computing systems of opticalelectronic
complexes, an analysis of the existing world scientific and technical experience was carried out,
aimed at improving the process of identifying contours. Based on the analysis, the authors of the article
developed a new method for correcting contour images. This method implements an approach that allows
you to merge broken contours and apply filtering based on various parameters for optimal contour analysis.
The first step of the algorithm is to apply blur to the image, followed by the application of the Kenny
edge detection algorithm. Then the contours are thinned and the contour image is filtered to remove the
weakest contours. The next steps are the creation and processing of each individual contour, as well as
filtering outliers. The final stage is to connect and search for inflection points of the contour. The work
highlights both the advantages and disadvantages of classical edge extraction methods in the context of
their use in object detection algorithms. The authors of the study analyzed two classical morphological
operators - dilatation and erosion, as well as the existing basic variations of their use, such as opening
and closing, as methods for combining contours. As a result of a comparative analysis of the results of the
work of morphological operators of dilatation and erosion, as well as the main variations of their application,
with a recursive algorithm for analyzing and restoring contours, the advantage of the latter in terms
of preserving the integrity of the morphological characteristics of objects was revealed. The authors also
proposed ideas for further development of a recursive algorithm for analysis and restoration of contours,
as well as its further application in problems of detecting objects in images.

This paper addresses the problem of generating occupancy maps of the surrounding space for robotic
platforms using data from a multispectral vision system. The aim of the work is to qualitatively improve
the generated passability model by combining geometric and semantic data from lidars and stereo
cameras, as well as direct velocity measurements from millimeter-wave radars. The presented algorithms
and their modifications are universal to the data source and do not require physical synchronization of
sensors. The paper solves the problem of constructing both static a priori and real-time dynamic occupancy
maps. An approach for combining an a priori semantic map with the one generated in the runtime is
proposed. Approaches for accumulating and updating semantic information in the maps are described.
The problem of detecting dynamic obstacles in occupancy maps based on a modified particle filtering
algorithm is also considered. The combined method described in the paper increases the accuracy of dynamic
obstacle detection and enables correct obstacle detection even if the dynamics detection algorithm
fails. Metrics for quantifying occupancy maps are defined. The developed algorithm has been tested on
Semantic KITTI, nuScenes open datasets in the automotive data domain, and on a small service cleaning
robot both in the CARLA simulator and in real-world conditions with active pedestrian traffic. The software
implementation of the algorithm runs in real time on Jetson AGX Xavier and Jetson AGX Orin embedded
computers.

The purpose of the study is to formulate and generalize the approaches used in the design of software
for navigation systems of ground-based moving objects. The article describes the experience of developing
software for navigation systems of various ground objects. Depending on the type of chassis, the nature of the
functional tasks being solved, ergonomic requirements, degree of autonomy and a number of other factors,
the complexity of the software and algorithmic solutions used will be determined. Algorithms for the operation
of a navigation system with all its components, as a rule, are not demanding on computing power, with
the exception of the implementation of work with digital terrain maps. In this regard, despite the significant
lag of the domestic element base from foreign analogues, the formation of an integrated navigation solution
can be implemented on its basis. Another feature of the design of software for navigation systems is the need
for them to function in real time. This is necessary for synchronous processing coming from various sources
of primary information and ensuring the formation of a navigation solution for the consumer with a stable
frequency. The modular approach to software design is built on the principles of unifying the internal functions
of the navigation system and the portability of previously obtained solutions between projects. With this
approach, each element is made in the form of an independent module, which is a complete subroutine with a
set of input and output parameters. The implementation of interaction between modules depends on the type
of its execution and can be performed both at the level of embedding source code and at the level of exchanging
parameters through information interaction channels. The use of a modular approach to the design of
software for navigation systems of ground objects allows us to create fully functional technical solutions that
meet the needs of the end user in a short period of time. At the same time, the risk of subsequent design errors
and modifications is reduced due to the increased volume of checks and the accumulated experience in using
the previously developed algorithm.

Relevance. The paper discusses a theoretical approach to organizing parallel computing based on a
production model of data flow control. The production paradigm of parallel computing has the necessary
conditions for building new architectures and organizing high-performance parallel computing. We consider
production (mathematical) systems that control sets of left-hand sides of productions (samples). The
goal is to increase the efficiency of parallel inference of solutions by reducing unproductive time spent
searching through possible alternatives in the inference graph space. The research is based on the creation
of an extended symbolic computation machine for implementing parallel steps. A symbolic computing
machine is an abstract system that systematizes production output as a sequence of four computational
and search stages. The inference engine defines the general appearance of a homogeneous computing
system. The main difference is the decomposition of the base of production rules into separate subsets
based on the algebra of production and the structuring of relations between products. Instead of a single
“flat” structure, it is proposed to decompose the product base into parts - to introduce a system of independent
subsets of products. Parallel inference is implemented for individual subsets without loss of generality,
while the search for possible alternatives is reduced. Each subset of productions has a special
marker word, the value of which activates only one subset of productions. It is loaded into the operating
part of a homogeneous computing system for parallel execution. Results. It is shown that quantitative
estimates of the reduction in output time depend on the total number of productions, the number of subsets
formed and their size. Simulation has shown that even the simplest decomposition into two subsets (one subset consists of 2 productions) gives a time gain of (1.07-1.52) times, proportional to the total number of
productions. Conclusions. The created extended symbolic computing machine is the basis for the subsequent
creation of the architecture of a homogeneous computing system with a combination of centralized
and local control. This property allows computational units of a homogeneous operating part to work in
parallel without excessive access to shared memory.

Under modern conditions when the transfer to the sixth waves of innovation is realized and the
global competition is escalated the problem of technological parity and technological superiority becomes
very important for various levels of review. The main way to solve this problem is to develop the
science investigations and first of all – to develop the investigations in the area of creation the new and
effective technologies everywhere. The roadmap procedure for technological trends and technologies
development under information incompleteness and fuzziness is represented. The procedure provides the
carrying of analysis for world technological trends in the set of predetermined areas, the definition of
possible technological development alternatives and the strategy for technological parity and technological
superiority achievement under predetermined restrictions. The realization of the procedures proposed
allows to determine the strategy to get the technological parity for various levels of review as well as to
form the list for technological trends to insure the technological superiority. It is determined that the road
maps methodology development for technological trends and technologies under restrictions must include:
1. The development analyses of the worldwide technological trends for the predetermined subject areas
in the national (namely in Russia), branch and corporativ levels. 2. The analyses and construction of the
strategy for support the technological priority and technological superiority under existing restrictions.
In difference of other investigations the exist methodology submitted permits: – to build the quantity forecasts
estimations for technological trends and compiling technologies on the base of future events constructing;
– to support the possibilities to construct the roadmaps for technological trends and technologies
on national, branch and corporation levels under the restrictions. As a bases of the investigation
made on the methodology creation the system approach is used when the strategy for technological trends
and technologies roadmaps construction is considered as a whole complex of associated elements made to
solve the tasks put. As a result of the supposed procedure realization there is a chance to define: – the
organization strategy to reach the technological parity; – the time to reach the parity; – the methodology
list to form the technological trends to reach the technological superiority.

When preparing for the laser lithotripsy procedure, choosing the parameters of the laser installation,
the doctor considers many factors, such as the mass and density of concretions found in the kidney,
the location of kidney stones, and the proximity of blood vessels. Another important parameter is the time
of exposure to the stone with a laser beam before the stone is destroyed. At the same time, calculating the
time of destruction of a stone is a rather time–consuming procedure, the time of destruction depends on
the mass of the stone and the parameters of the laser energy and its frequency. Therefore, it is relevant to
create a system to support medical decision-making during the laser lithotripsy procedure, which allows
you to calculate the time of stone destruction and select the values of laser parameters. The article proposes
an algorithm to support the choice of the laser operating mode by a urologist during the laser lithotripsy
procedure in the treatment of human urolithiasis, which is part of the medical decision support system
in surgery and urology using computer vision technologies. The proposed algorithm for fuzzy estimation
of laser parameters when choosing its operating mode, depending on the mass of the stone and the
selected time of destruction of the stone and other factors (distribution of stone density, location of the
stone in the kidney, proximity of walls and vessels) generates recommendations for setting the parameters
of the laser. The medical decision support system made it possible to reduce the time for a doctor to decide,
to avoid mistakes when choosing the parameters of the laser installation for crushing kidney stones.