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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Применение одношаговых методов интегрирования высокого порядка точности для анализа установившихся периодических режимов в интегральных схемах

Проблемы разработки перспективных микро- и наноэлектронных систем (МЭС). 2018. № 1. С. 103–108.
Гурарий М. М., Жаров М. М., Русаков С. Г., Ulyanov S.

The application of conventional transient analysis to find the periodic steady-state solution often results in a long simulation time and hence special purpose means are needed. Unlike the transient analysis the periodic steady-state analysis solves a periodic boundary-value problem. The shooting-Newton method transforms the solution of the periodic boundary-value problem to the solution of sequence of initial value problems on one period of input signal. The initial value problem is solved using transient analysis. The efficiency of the method depends on both the computation of sensitivity matrix and the solution of linear system with dense Jacobian matrix. Another factor that determines the computational cost of the method is a numerical technique used to integrate differential equations on the period of input signal. To perform numerical integration of ordinary differential or differential-algebraic equations the comprehensive variable order and variable time step integration algorithms are used

Language: Russian
DOI
Text on another site
Keywords: схемотехническое моделированиеboundary-value problemsкраевая задачаcircuit simulationустановившийся периодический режимperiodic steady stateshooting methodintegration methodsметод пристрелкиметоды интегрирования
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