This paper is a sequel of that published in the proceedings of Optima 2023, where the problem of stabilizing a chain of three integrators by a piecewise continuous constrained control in the form of three nested saturators was studied. In this work, we propose a more advanced stabilizing control law. The new feedback control is continuous and ensures the fulfillment of a phase constraint imposed on the third state variable. We study global stability of the closed-loop system and set an optimization problem of determining feedback coefficients that ensure the greatest convergence rate near the equilibrium while preserving global asymptotic stability of the system. We show that the loss of global stability is associated with arising hidden attractors, which come to existence when the convergence rate reaches a critical value depending on the control resource. A numerical procedure for constructing hidden attractors is developed, and the discussion is illustrated by numerical examples.

This paper examines a simulation model of information cascade formation (a sequence of comments) on a social network post. It assumes that a user has two parameters characterizing their opinion and action. User opinions are influenced by previously written comments (including those by bots) that the user sees. Additionally, some comments may be removed during moderation.

The method of rapid monitoring of linguistic analysis of translated written texts is presented as part of the development of a large-scale information and analytical system. This method is based on the comparison of idiostylistic indicators, using service words as identification markers. These markers characterize the unique features of translated texts, and their weight coefficients are calculated to compare the volume of words in translations produced by “manual” and machine methods

The principles of organizing the new network service, designed to implement the pipelined data processing in a multi-server environment, are considered. The main idea of the approach is to remove pipeline processing from client workstations to servers and use it to organize multi-server processing of information queries in distributed systems. The results of measuring the processing rate of the service are presented.

A method for tracking key points in aortography using a hybrid model of convolutional and recurrent neural networks is proposed, achieving a classification accuracy of 98% and an average regression error of 4%. This improves the positioning of the aortic valve in the TAVI procedure.