Vol 31, No 4 (2025)

This article describes a brief history of the development of the CAD system for integrated circuit design in Russia. The background of the beginning of the import-independent Russian CAD for digital integrated circuit design "Obiidian" is presented. What tasks were set for the developers and which results have been achieved up to the present. The results of a large set of tests obtained by "Obiidian" to compare this system with commercial CAD tools for digital integrated circuit design are presented. Further directions of the development of CAD of digital integrated circuits have been determined for separate stages of the design route.

The article is devoted to the development of a method for optimal placement of access points and gateways in indoor environments taking into account the mobility of end devices. The paper proposes a mathematical optimization model based on the Non-dominated Sorting Genetic Algorithm II and the Technique for Order of Preference by Similarity to Ideal Solution, and successfully applies the method in a real situation.

When developing computer networks, it is necessary to analyze the data transmission routes being developed to compile their best sets. The purpose of the article is to develop methods for generating sets of data transmission routes for specialized computer networks. The developed methods can be used in specialized software for developing computer networks.

The article is devoted to binary video signal multi-parameter classifiers for object deformation measurement. The study examines an applied task. It is the rail deformation estimation of a railway track, which consists of several parts with different rail types. The problem is related to ensuring traffic safety on the railway. If the rail type is incorrectly recognized, the deformation parameters will be measured with a high error, which can lead to an incorrect assessment of the track condition and the omission of a potentially dangerous situation. The rail shape is measured using a machine vision system installed on a track measuring car. The signal of this system, representing a binary video signal(contour), is input to the classifier. Then the signal and the result of rail type recognition are used to estimate the deformation. The classifier meets the requirements to ensure real-time processing and high quality recognition. Therefore, the classifier takes into account the properties of the processed signals, on the one hand, simplifies processing, and on the other hand, ensures a low probability of classification error. One of the features of the classifier is its parametricity. The matching parameters were introduced into the classifier model: offset along the abscissa and ordinary axis, rotation angle. Parametricity allows to reduce the likelihood of recognition error. The classifier can be expanded to any number of types of rails, which makes it a universal solution for various roads, both Russian and European. The analysis of the measured deformation parameters showed that the proposed multi-parameter classifier provides a high accuracy (0.1 mm in the "wear side ' parameter as the maximum absolute difference for the 0.95 level quantile). The proposed classifier can be used to estimate the condition of railway tracks.

This paper discusses approaches to preparing educational data on students’ learning outcomes to improve the accuracy of predicting their academic performance over a given period. The rules for checking initial data for using them in a forecasting model are considered, implemented, and investigated. The rules help to work with poor-quality initial data and improve the accuracy of modeling. Modeling of students’ learning outcomes is based on a nonparametric estimate of the Nadaraya-Watson regression function. The article presents some fragments of computational experiments that show acceptable results from a practical point of view.