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This work deals with numerical modeling of motion of the multibody systems consisting of rigid bodies with arbitrary masses and inertial properties. We consider both planar and spatial systems which may contain kinematic loops.

The numerical modeling is fully automatic and its computational algorithm contains three principal steps. On step one a graph of the considered mechanical system is formed from the userinput data. This graph represents the hierarchical structure of the mechanical system. On step two the differential-algebraic equations of motion of the system are derived using the so-called Joint Coordinate Method. This method allows to minimize the redundancy and lower the number of the equations of motion and thus optimize the calculations. On step three the equations of motion are integrated numerically and the resulting laws of motion are presented via user interface or files.

The aforementioned algorithm is implemented in the software complex that contains a computer algebra system, a graph library, a mechanical solver, a library of numerical methods and a user interface.

Original representation of statistical digital model of measurement of a macroroughness on a local site (to 15) consisting of determined (bias), correlated (standard periodic making and periodic deviations from flatness) and actually casual making (values of a macroroughness) Is offered.

A new method of statistical analysis of texts is suggested. The frequency distribution of the first significant digits in numerals of English-language texts is considered. We have taken into account cardinal as well as ordinal numerals expressed both in figures, and verbally. To identify the author’s use of numerals, we previously deleted from the text all idiomatic expressions and set phrases accidentally containing numerals, as well as itemizations and page numbers, etc. Benford’s law is found to hold approximately for the frequencies of various first significant digits of compound literary texts by different authors; a marked predominance of the digit 1 is observed. In coherent authorial texts, characteristic deviations from Benford’s law arise which are statistically stable significant author peculiarities that allow, under certain conditions, to consider the problem of authorship and distinguish between texts by different authors. The text should be large enough (at least about 200 kB). At the end of $\{1, 2, \ldots, 9\}$ digits row, the frequency distribution is subject to strong fluctuations and thus unrepresentative for our purpose. The aim of the theoretical explanation of the observed empirical regularity is not intended, which, however, does not preclude the applicability of the proposed methodology for text attribution. The approach suggested and the conclusions are backed by the examples of the computer analysis of works by W.M. Thackeray, M. Twain, R. L. Stevenson, J. Joyce, sisters Bront¨e, and J.Austen. On the basis of technique suggested, we examined the authorship of a text earlier ascribed to L. F. Baum (the result agrees with that obtained by different means). We have shown that the authorship of Harper Lee’s “To Kill a Mockingbird” pertains to her, whereas the primary draft, “Go Set a Watchman”, seems to have been written in collaboration with Truman Capote. All results are confirmed on the basis of parametric Pearson’s chi-squared test as well as non-parametric Mann –Whitney U test and Kruskal –Wallis test.

The distribution of the first significant digit in numerals of connected texts is considered. Benford's law is found to hold approximately for them. Deviations from Benford's law are statistically significant author peculiarities that allow, under certain conditions, to distinguish between parts of the text with a different authorship.

The paper describes a method for recognizing authors of literary texts by the proximity of fragments into which a separate text is divided to the standard of the author. The standard is the empirical frequency distribution of letter combinations, built on a training sample, which included expertly selected reliably known works of this author. A set of standards of different authors forms a library, within which the problem of identifying the author of an unknown text is solved. The proximity between texts is understood in the sense of the norm in L1 for the frequency vector of letter combinations, which is constructed for each fragment and for the text as a whole. The author of an unknown text is assigned the one whose standard is most often chosen as the closest for the set of fragments into which the text is divided. The length of the fragment is optimized based on the principle of the maximum difference in distances from fragments to standards in the problem of recognition of «friend–foe». The method was tested on the corpus of domestic and foreign (translated) authors. 1783 texts of 100 authors with a total volume of about 700 million characters were collected. In order to exclude the bias in the selection of authors, authors whose surnames began with the same letter were considered. In particular, for the letter L, the identification error was 12%. Along with a fairly high accuracy, this method has another important property: it allows you to estimate the probability that the standard of the author of the text in question is missing in the library. This probability can be estimated based on the results of the statistics of the nearest standards for small fragments of text. The paper also examines statistical digital portraits of writers: these are joint empirical distributions of the probability that a certain proportion of the text is identified at a given level of trust. The practical importance of these statistics is that the carriers of the corresponding distributions practically do not overlap for their own and other people’s standards, which makes it possible to recognize the reference distribution of letter combinations at a high level of confidence.

Data hiding in digital images is a promising direction of cybersecurity. Digital steganography methods provide imperceptible transmission of secret data over an open communication channel. The information embedding efficiency depends on the embedding imperceptibility, capacity, and robustness. These quality criteria are mutually inverse, and the improvement of one indicator usually leads to the deterioration of the others. A balance between them can be achieved using metaheuristic optimization. Metaheuristics are a class of optimization algorithms that find an optimal, or close to an optimal solution for a variety of problems, including those that are difficult to formalize, by simulating various natural processes, for example, the evolution of species or the behavior of animals. In this study, we propose an approach to data hiding in the hybrid spatial-frequency domain of digital images based on metaheuristic optimization. Changing a block of image pixels according to some change matrix is considered as an embedding operation. We select the change matrix adaptively for each block using metaheuristic optimization algorithms. In this study, we compare the performance of three metaheuristics such as genetic algorithm, particle swarm optimization, and differential evolution to find the best change matrix. Experimental results showed that the proposed approach provides high imperceptibility of embedding, high capacity, and error-free extraction of embedded information. At the same time, storage of change matrices for each block is not required for further data extraction. This improves user experience and reduces the chance of an attacker discovering the steganographic attachment. Metaheuristics provided an increase in imperceptibility indicator, estimated by the PSNR metric, and the capacity of the previous algorithm for embedding information into the coefficients of the discrete cosine transform using the QIM method [Evsutin, Melman, Meshcheryakov, 2021] by 26.02% and 30.18%, respectively, for the genetic algorithm, 26.01% and 19.39% for particle swarm optimization, 27.30% and 28.73% for differential evolution.

The article proposes a space-time approach to modeling the diffusion of information and communication technologies based on the Fisher –Kolmogorov– Petrovsky – Piskunov equation, in which the diffusion kinetics is described by the Bass model, which is widely used to model the diffusion of innovations in the market. For this equation, its equilibrium positions are studied, and based on the singular perturbation theory, was obtained an approximate solution in the form of a traveling wave, i. e. a solution that propagates at a constant speed while maintaining its shape in space. The wave speed shows how much the “spatial” characteristic, which determines the given level of technology dissemination, changes in a single time interval. This speed is significantly higher than the speed at which propagation occurs due to diffusion. By constructing such an autowave solution, it becomes possible to estimate the time required for the subject of research to achieve the current indicator of the leader.

The obtained approximate solution was further applied to assess the factors affecting the rate of dissemination of information and communication technologies in the federal districts of the Russian Federation. Various socio-economic indicators were considered as “spatial” variables for the diffusion of mobile communications among the population. Growth poles in which innovation occurs are usually characterized by the highest values of “spatial” variables. For Russia, Moscow is such a growth pole; therefore, indicators of federal districts related to Moscow’s indicators were considered as factor indicators. The best approximation to the initial data was obtained for the ratio of the share of R&D costs in GRP to the indicator of Moscow, average for the period 2000–2009. It was found that for the Ural Federal District at the initial stage of the spread of mobile communications, the lag behind the capital was less than one year, for the Central Federal District, the Northwestern Federal District — 1.4 years, for the Volga Federal District, the Siberian Federal District, the Southern Federal District and the Far Eastern Federal District — less than two years, in the North Caucasian Federal District — a little more 2 years. In addition, estimates of the delay time for the spread of digital technologies (intranet, extranet, etc.) used by organizations of the federal districts of the Russian Federation from Moscow indicators were obtained.

The modern digitalization of cities occurs according to laws that are not yet clearly defined. The difficulty in understanding these laws is due to the high uncertainty of urban events and the difficulties in developing adequate analytical models for them. To substantiate management decisions on city digitalization in these conditions, effective methods for processing multidimensional time series are necessary. The objective is to develop a promising method. The proposed method is based on a new model of a neural network control system and algorithms for implementing its main functions. Distinctive features of the model include both structural aspects and new rules for neural network-based substantiation of management decisions on city digitalization, using unsupervised training of the applied recurrent neural network. This model provides for adaptive neural network management of city digitalization according to a sliding program. New rules are proposed for the forward and backward transformation of multidimensional time series, modeling the operation of a streaming recurrent neural network, and identifying feasible programs for city digitalization. By adhering to the proposed rules, it is possible not only to eliminate information loss in such a network but also to ensure its stable operation. The features of this neural network’s operation in substantiating feasible urban digitalization programs are described. The requirements for the software implementation of the proposed method are substantiated. The results of experiments using data for St. Petersburg are presented. These data included monthly volumes of shipped computers, electronic and optical products, as well as monthly volumes of shipped products for all manufacturing industries minus the first-time series values ??for the period from January 2021 to December 2025. The effectiveness of management decisions on the city’s digitalization was predicted based on the total volumes of shipped products to the horizon from January to December 2026. It is shown that the application of the proposed method allows for expanded capabilities for adaptively substantiating feasible management decisions on the city’s digitalization while reducing computer modeling costs.

The article discusses the approach to the improvement of information processing technology on the basis of logical-semantic network (LSN) Question–Answer–Reaction aimed at formation and support of the catalog service providing efficient search of answers to questions.

The basis of such a catalog service are semantic links, reflecting the logic of presentation of the author's thoughts within the framework this publication, theme, subject area. Structuring and support of these links will allow working with a field of meanings, providing new opportunities for the study the corps of digital libraries documents. Cataloging of the information fund includes: formation of lexical dictionary; formation of the classification tree for several bases; information fund classification for question–answer topics; formation of the search queries that are adequate classification trees the question–answer; automated search queries on thematic search engines; analysis of the responses to queries; LSN catalog support during the operational phase (updating and refinement of the catalog). The technology is considered for two situations: 1) information fund has already been formed; 2) information fund is missing, you must create it.