Objectives. One of the most commonly used authentication methods in computer systems, password authentication is susceptible to various attacks including brute-force and dictionary attacks. This susceptibility requires not only the strict protection of user credentials, but also the definition of criteria for increasing a password’s strength to minimize the possibility of its exploitation by an attacker. Thus, an important task is the development of a verifier for checking passwords for strength and prohibiting the user from setting passwords that are susceptible to cracking. The use of machine learning methods to construct a verifier involves algorithms for formulating requirements for password complexity based on lists of known passwords available for each strength category.

Methods. The proposed supervised machine learning algorithms comprise support vector machines, random forest, boosting, and long short-term memory (LSTM) recurrent neural network types. Embedding and term frequency–inverse document frequency (TF-IDF) methods are used for data preprocessing, while cross-validation is used for selecting hyperparameters.

Results. Password strength recommendations and requirements from international and Russian standards are described. The existing methods of password strength verification in various operating systems are analyzed. The experimental results based on existing datasets comprising passwords having an associated level of strength are presented.

Conclusions. A LSTM recurrent neural network is highlighted as one of the most promising areas for building a password strength verifier.

Objectives. A multi-agent knowledge representation and processing system (MKRPS) comprises a distributed artificial intelligence system designed to solve problems that are difficult or impossible to solve using monolithic systems. Solving complex problems in an MKRPS is accomplished by communities of intelligent software agents that use cognitive data structures, logical inference, and machine learning. Intelligent software agents are able to act rationally under conditions of incompleteness and ambiguity of incoming information. The aim of the present work is to identify models and methods, as well as software modules and tools, for use in developing a highly efficient MKRPS.

Methods. Agent-based modeling methods were used to formally describe and programmatically simulate the rational behavior of intelligent agents, expert evaluation methods, the mathematical apparatus of automata theory, Markov chains, fuzzy logic, neural networks, and reinforcement learning.

Results. An MKRPS structure diagram, a multi-agent solver, and microservices access control diagram were developed. Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.

Conclusions. The proposed approach to the development and use of intelligent software agents combines knowledge-based reasoning mechanisms with neural network models. The developed MKRPS structure and DKB control diagram includes described methods for optimizing the DKB, determining the availability of microservices used by the agents, ensuring the reliability assurance and coordinated functioning of the computing nodes of the system, as well as instrumental software tools to simplify the design and implementation of the MKRPS. The results demonstrate the effectiveness of the presented approach to knowledge management and the development of a high-performance problem-oriented MKRPS.

Objectives. At present, increasing rates of pollution of vast areas by various types of household waste are becoming an increasingly serious problem. In this connection, the creation of a robotic complex capable of performing autonomous litter collection functions becomes an urgent need. One of the key components of such a complex comprises a vision system for detecting and interacting with target objects. The purpose of this work is to develop the underlying algorithmics for the vision system of robots executing area cleaning functions.

Methods. Within the framework ofthe proposed structure ofthe system for visual analysis ofthe external environment, algorithms for detecting and classifying objects of various appearance have been developed using convolutional neural networks. The neural network detector was set up by gradient descent on the open dataset of TACO training samples. To determine the geometric parameters of a surface in the field of view of the robot and estimate the coordinates of objects on the ground, a homography matrix was formed to take into account information about the characteristics and location of the video camera.

Results. The developed software and algorithms for a mobile robot equipped with a monocular video camera are capable of implementing the functions of neural network detection and classification of litter objects in the frame, as well as projection of found objects on a terrain map for their subsequent collection.

Conclusions. Experimental studies have shown that the developed system of visual analysis of the external environment of an autonomous mobile robot has sufficient efficiency to solve the tasks of detecting litter in the field of view of an autonomous mobile robot.

Objectives. A DC/DC Zeta topology converter represents a unipolar electronic device for converting an input positive voltage into a stabilized output voltage of the same polarity, which can be set at voltages both below and above the input voltage. The aim of this work is to analyze Zeta converter circuitry, which requires the following tasks to be solved: using Kirchhoff’s Circuit Laws, obtain systems of equations describing converter operation in the phase of energy accumulation and in the phase of energy transfer; using a method proposed by A.I. Korshunov, combine the resulting systems of equations into a marginal continuous mathematical model; using expressions describing constant components of currents and voltages in Zeta converter, analyze their ripples and obtain equations for their calculation; compare the current and voltage values obtained from the continuous limiting mathematical model with the Zeta simulation results.

Methods. The tasks are solved using Kirchhoff’s rules and the method for obtaining the limiting continuous mathematical model proposed by A.I. Korshunov. The results are analyzed using a circuit modelling in NI Multisim.

Results. It is shown that the phase coordinates of the mathematical model tend to real values of converter currents and voltages at a switching frequency of the power switch of more than 200 kHz. A strong correspondence was established between the calculated ripple values and their values obtained in the simulation (when changing the duty factor).

Conclusions. Mathematical models comprise the basis of unified calculation methods for any radio electronic circuit. The developed limiting continuous mathematical model allows a range of changes in current flowing through the choke windings and voltages on capacitor plates to be evaluated, including their maximum and minimum values for various converter parameters, such as power switch switching frequency, duty factor, element ratings, etc. Obtaining this information in turn enables the rational selection of the electronic component base of the converter.

Objectives. Automatic modulation recognition of unknown signals is an important task for various fields oftechnology such as radio control, radio monitoring, and identification of interference and sources of radio emission. The paper aims to develop a method for recognizing the types of signal modulation under conditions of parametric a priori uncertainty, including the uncertainty of carrier frequency- and initial signal phase values. An additional task consists in estimating the offset values of the carrier frequency or signal phase at the initial stage of the recognition process.

Methods. A multi-task learning with artificial neural network and the theory of cumulants of random variables are used.

Results. For signals with a carrier frequency and initial phase shift, cumulant approaches for QAM-8, APSK-16, QAM-64, and PSK-8 modulations are calculated. A multi-task learning with artificial neural network using cumulant features and a data standardization algorithm is presented. The results of the experiment show that using multi-task learning with an artificial neural network provides high accuracy of recognizing QAM-8 and APSK-16, QAM-64 and PSK-8 modulations with small mismatches of the carrier frequency or initial phase. The accuracy of determining the offset values from the carrier frequency or the initial phase for QAM-8, APSK-16, QAM-64, and PSK-8 modulation is high.

Conclusions. The multi-task learning with neural network using high-order signal cumulants makes it possible not only to recognize modulation types with high accuracy under conditions of a priori uncertainty of signal parameters, but also to determine the offset values of carrier frequency or initial signal phase from expected values.

Objectives. COVID-19 has a number of specific characteristics that distinguish it from past pandemics. In addition to the high infection rate, the high spread rate is due to the increased mobility of contemporary populations. The aim of the present work is to construct a mathematical model for the spread of the pandemic and identify patterns under the assumption that Moscow comprises the main source of viral infection in Russia. For this purpose, a twoparameter kinetic model describing the spatial spread of the epidemic is developed. The parameters are determined using theoretical constructions alongside statistical vehicle movement and population density data from various countries, additionally taking into account the development of the first wave on the examples of Russia, Italy and Chile with verification of values obtained from subsequent epidemic waves. This paper studies the development of epidemic events in Russia, starting from the third and including the most recent fifth and sixth waves. Our twoparameter model is based on a kinetic equation. The investigated possibility of predicting the spatial spread of the virus according to the time lag of reaching the peak of infections in Russia as a whole as compared to Moscow is connected with geographical features: in Russia, as in some other countries, the main source of infection can be identified. Moscow represents such a source in Russia due to serving as the largest transport hub in the country.

Methods. Mathematical modeling and data analysis methods are used.

Results. A predicted time lag between peaks of daily infections in Russia and Moscow is confirmed. Identified invariant parameters for COVID-19 epidemic waves can be used to predict the spread of the disease. The checks were carried out for the wave sequence for which predictions were made about the development of infection for Russia and when the recession following peak would occur. These forecasts for all waves were confirmed from the third to the last sixth waves to confirm the found pattern, which can be important for predicting future events.

Conclusions. The confirmed forecasts for the timing and rate of the recession can be used to make good predictions about the fifth and sixth waves of infection of the Omicron variant of the COVID-19 virus. Earlier predictions were confirmed by the statistical data.

Objectives. The aim of the work is to create algorithms for approximating a sequence of points on a plane by arcs of clothoids and circles. Such a problem typically arises in the design of railroad and highway routes. The plan (projection onto a horizontal plane) of the road route is a curve (spline) consisting of a repeating bundle of elements “straight line + clothoid arc + circle arc + clothoid arc + ...”. Such a combination of elements provides continuity not only for the curve and its tangent, but also for the curvature. Since the number of spline elements is not known in advance, and their parameters are subject to restrictions, there is no mathematically consistent algorithm for this problem. The two-stage scheme for solving the problem is developed at RTU MIREA only for a spline with lines and circles (i.e., without clothoid elements). At the first stage, the scheme uses dynamic programming to determine the number of spline elements. At the second stage, the scheme optimizes parameters of the spline using nonlinear programming. This scheme has yet to be implemented for a spline with clothoids due to a significantly more complicated nature of this problem. Therefore, the design of route plans in existing computer aided design (CAD) systems is carried out in interactive mode using iterative selection of elements. In this regard, it makes sense to develop mathematically consistent algorithms for element-by-element approximation.

Methods. The problem of element-by-element approximation by a circle and a clothoid is formalized as a lowdimensional non-linear programming problem. The objective function is the sum of squared deviations from the original points. Since a clothoid can only be represented in Cartesian coordinates by power series, there are difficulties in calculating the derivatives of the objective function with respect to the desired parameters of the spline elements. The proposed mathematically consistent algorithm for calculating these derivatives is based on the integral representation of the Cartesian coordinates of the points of the clothoid as functions of its length.

Results. A mathematical model and algorithms have been developed for approximating a sequence of points on a plane by clothoids and circles using the method of nonlinear programming. A second-order algorithm is implemented with the calculation and inversion of the matrix of second derivatives (Hesse matrix).

Conclusions. For approximation by circles and clothoids using nonlinear programming, it is not necessary to have an analytical expression of the objective function in terms of the required variables. The proposed algorithms make it possible to calculate not only the first, but also the second derivatives in the absence of such expressions.

Objectives. Theoretical studies of the waveguide properties of interfaces between nonlinear optical and graded-index media are important for application in optoelectronics. Waveguides combining layers with different optical properties seem to be the most promising, since they can be matched to optimal characteristics using a wide range of control parameters. The paper aims to develop a theory of composite optically nonlinear gradedindex waveguides with an arbitrary profile, within which it is possible to obtain exact analytical expressions for surface waves and waveguide modes in an explicit form. The main feature of the theory proposed in this paper is its applicability for describing surface waves and waveguide modes, in which the field is concentrated inside the gradient layer and does not exceed its boundary, avoiding contact with the nonlinear layer.

Methods. Analytical methods of the theory of optical waveguides and nonlinear optics are used.

Results. A theoretical description of the waveguide properties of the interface between two media having significantly different optical characteristics is carried out. The formulated model of a plane waveguide is applicable to media having an arbitrary spatial permittivity profile. An analytical expression describing a surface wave propagating along the interface between a medium having stepwise nonlinearity and a gradient layer with an arbitrary permittivity profile is obtained. Additionally, analytical expressions for surface waves propagating along the interface between a medium with Kerr nonlinearity (both self-focusing and defocusing), as well as graded-index media characterized by exponential and linear permittivity profiles, are obtained.

Conclusions. The proposed theory supports a visual description in an explicit analytical form of a narrowly localized light beam within such waveguides. It is shown that by combining different semiconductor crystals in a composite waveguide, it is possible to obtain a nonlinear optical layer on one side of the waveguide interface and a layer with a graded-index dielectric permittivity profile on the other.

Objectives. When processing images of the Earth’s surface obtained from satellites, the problem of restoring a blurry image of a moving object is of great practical importance. The aim of this work is to study the possibility of improving the quality of restoration of blurry images obtained at the limit of the resolution of the camera.

Methods. Digital signal processing methods informed by the theory of incorrect and ill-conditioned problems were used.

Results. The proposed method for restoring a blurred photographic image of a moving object differs from traditional approaches in that the discrete convolution equation, to which the problem of restoring a blurred image is reduced, is obtained by approximating the corresponding integral equation based on the Kotelnikov interpolation series rather than on the traditional basis of the quadrature formula. In the work, formulas are obtained for calculating the kernel of the convolution obtained using the Kotelnikov interpolation series. The discrete convolution inversion problem, which belongs to the class of ill-posed problems, requires regularization. Results of traditional approaches to restoring blurred images using the quadrature formula with Tikhonov regularization and the proposed method based on the Kotelnikov interpolation series are compared. Although the quality of the blurred image restoration is almost the same in both cases, in the quadrature formula the blur value is expressed as an integer number of pixels, while, when using the Kotelnikov series, this value can also be specified in fractions of a pixel.

Conclusions. The expediency of discretizing the convolution describing the image distortion of the blur type on the basis of the Kotelnikov interpolation series when processing a blurred image obtained at the limit of the resolution of the camera is demonstrated. In this case, the amount of blur can be expressed in fractions of a pixel. This situation typically arises when processing satellite photography of the Earth’s surface.

Objectives. Following the imposition of sanctions against the Russian Federation, which included a ban on the supply of foreign electronic equipment—including automation systems—to Russian enterprises, the continuing development of science and technology in Russia became a question of ensuring technological sovereignty according to the principle of import substitution. According to plans developed by the Ministry of Industry and Trade of the Russian Federation, the policy of import substitution, including automation systems, will ensure the replacement of imported equipment with domestic counterparts.

Methods. Approaches underlying the joint project of MIREA ‒ Russian Technological University and Environmental Industrial Policy Center to solve the problems of import substitution are described. Various substitution strategies available in the world experience, as well as objective and subjective obstacles to their implementation in Russia, including the insufficiency of domestic regulatory legal acts and previously formed attachments to imported technologies and regulatory frameworks, are considered. Distinctive features of contemporary external relations are adduced to the necessity and urgency of developing technological sovereignty. The main functional requirements for a software and hardware platform for developing modern automated control systems (ACS) for mechanical engineering applications, as well as the required capabilities of an engineering center for solving applied problems of overcoming import dependence, are described. The components of the production of capital goods (engineering) and its role in the product life cycle are shown.

Results. The selection of a pilot engineering object comprising a sectional glass-forming machine, along with a software-hardware complex including elements of industrial electronics and ACS, is justified. The main functional elements of the ACS and their interrelations are shown.

Conclusions. The results confirm the necessity of achieving complete import substitution for the creation of digital products. Prospects for cooperation with interested organizations are shown.