DISCRETE AND CONTINUOUS MODELS AND APPLIED COMPUTATIONAL SCIENCE

In recent years, artificial intelligence methods have been developed in various fields, particularly in education. The development of computer systems for student learning is an important task and can significantly improve student learning. The development and implementation of deep learning methods in the educational process has gained immense popularity. The most successful among them are models that consider the multimodal nature of information, in particular the combination of text, sound, images, and video. The difficulty in processing such data is that combining multimodal input data by different channel concatenation methods that ignore the heterogeneity of different modalities is an inefficient approach. To solve this problem, an inter-channel attention module is proposed in this paper. The paper presents a computer vision-linguistic system of student learning process based on the concatenation of multimodal input data using the inter-channel attention module. It is shown that the creation of effective and flexible learning systems and technologies based on such models allows to adapt the educational process to the individual needs of students and increase its efficiency.

A number of initial boundary-value problems of classical mathematical physics is generally represented in the linear operator equation and its well-posedness and causality in a Hilbert space setting was established. If a problem has a unique solution and the solution continuously depends on given data, then the problem is called well-posed. The independence of the future behavior of a solution until a certain time indicates the causality of the solution. In this article, we established the well-posedness and causality of the solution of the evolutionary problems with a perturbation, which is defined by a quadratic form. As an example, we considered the coupled system of the heat and Maxwell’s equations (the microwave heating problem).

The problem of identifying deterministic cause-and-effect relationships, initially hidden in accumulated empirical data, is discussed. Statistical methods were used to identify such relationships. A simple mathematical model of cause-and-effect relationships is proposed, in the framework of which several models of causal dependencies in data are described – for the simplest relationship between cause and effect, for many effects of one cause, as well as for chains of cause-and-effect relationships (so-called transitive causes). Estimates are formulated that allow using the de Moivre–Laplace theorem to determine the parameters of causal dependencies linking events in a polynomial scheme trials. The statements about the unambiguous identification of causeandeffect dependencies that are reconstructed from accumulated data are proved. The possibilities of using such data analysis schemes in medical diagnostics and cybersecurity tasks are discussed.

The article describes a method for calculating interpolation coefficients of expansion using Chebyshev polynomials. The method is valid when the desired function is bounded and has a finite number of maxima and minima in a finite domain of interpolation. The essence of the method is that the interpolated desired function can be represented as an expansion in Chebyshev polynomials; then the expansion coefficients are determined using the collocation method by reducing the problem to solving a well-conditioned system of linear algebraic equations for the required coefficients. Using the well-known useful properties of Chebyshev polynomials can significantly simplify the solution of the problem of function interpolation. A technique using the Clenshaw algorithm for summing the series and determining the expansion coefficients of the interpolated function, based on the discrete orthogonality of Chebyshev polynomials of the 1st kind, is outlined.

As the standardization of 5G New Radio (NR) systems operating in micro- and millimeter-wave frequency bands is over, scientific and industrial communities have begun to address the question of what 6G communications systems might or should be. While technological specifics are still in their early development phase, there is a common agreement that these systems will utilize the lower part of the terahertz band, namely, 100–300 GHz. This band poses a number of specific challenges for system designers, including the effects related to channel characteristics and the conceptually new requirements for electronics. This paper aims to report the current state-of-the-art channel characterization and communications system design. With respect to the former, we consider dynamic human body blockages and micromobility impairments. For the latter, we mainly concentrate on the physical layer devices for direct conversion schemes and the design of the so-called reconfigurable intelligent surfaces that will potentially serve as a cost-efficient blockage mitigation technique.

We introduce a numerical method to solve the two-dimensional time-dependent Schrödinger equation, which characterizes a system of two atoms with a finite-range interaction potential confined within a harmonic oscillator trap. We choose a Gaussian-shaped potential for the interaction potential. Such a system has been previously studied analytically, except that a zero-range interaction potential was used instead. We observe a strong agreement between the results for the two types of interactions. Also, we investigate the one-dimensional time-dependent Schrödinger equation for the relative motion and compute the ground state energy level as a function of the coupling strength.

This work is the first part of a large bibliographic review of active queue management algorithms of the Random Early Detection (RED) family, presented in the scientific press from 1993 to 2023. The third part will provide data on algorithms published from 2016 to 2023.

A new method for the correct identification of various complex structural elements of ancient hieroglyphs is described. The method is based on photometry of the studied surface of the ancient artifacts. The obtained data are converted into digital form in order to determine the characteristics and parameters characterizing the properties of the investigated artifact surface. Digitized data is processed in various graphic applications, including those working with vector images. Several control experiments were also carried out. In particular, the corresponding statistical characteristics and parameters of the studied artifact surface profiles were determined. The data obtained made it possible to unambiguously detect the ancient hieroglyphs on the artifact surface and determine their number. Described method of studying ancient artifacts makes it possible to obtain sufficiently reliable results that will undoubtedly be useful and promising in the study of ancient hieroglyphic signs. Our research method is characterized as: non-contact, informative, and sensitive. This testifies to its importance and prospects in the study of similar ancient artifacts.

The filtration process is studied for a popular class of filters with radial cartridges that proved their high effectiveness in purification of water. The mass balance equation for radial flows in porous media is obtained by using the lattice approximation method, the transverse diffusion process being taken into account. The Euler dynamical equations are modified by including the Darcy force proportional to the velocity of the filtration flow. The system of equations is written for the stationary axially symmetric radial flow and solved by the perturbation method, if the vertical velocity is supposed to be small.

Our group has been investigating kinetic models for quite a long time. The structure of classical kinetic models is described by rather simple assumptions about the interaction of the entities under study. Also, the construction of kinetic equations (both stochastic and deterministic) is based on simple sequential steps. However, in each step, the researcher must manipulate a large number of elements. And once the differential equations are obtained, the problem of solving or investigating them arises. The use of symbolic-numeric approach methodology is naturally directed. When the input is an information model of the system under study, represented in some diagrammatic form. And as a result, we obtain systems of differential equations (preferably, in all possible variants). Then, as part of this process, we can investigate the resulting equations (by a variety of methods). We have previously taken several steps in this direction, but we found the results somewhat unsatisfactory. At the moment we have settled on the package Catalyst. jl, which belongs to the Julia language ecosystem. The authors of the package declare its relevance to the field of chemical kinetics. Whether it is possible to study more complex systems with this package, we cannot say. Therefore, we decided to investigate the possibility of using this package for our models to begin with standard problems of chemical kinetics. As a result, we can summarize that this package seems to us to be the best solution for the symbolic-numerical study of chemical kinetics problems.