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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
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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Анализ опросника дошкольной родительской вовлеченности с использованием рейтинговой модели Раша

Современная зарубежная психология. 2018. Т. 7. № 3. С. 75–86.
Antipkina I.

The paper presents a procedure for analysis and improvement of the questionnaire of preschool parental involvement, created on the basis of the questionnaire for parents and designed for the international comparative study TIMSS-PIRLS 2011. The article introduces a detailed description of methodology of analysiswith the reference to one of Rasch rating scale model (RSM). The article shows the characteristics of modified scales. It describes the levels of preschool parental involvement and makes it possible to use this scale in work of researchers and school psychologists.

Research target: Education
Language: Russian
DOI
Keywords: Современная теория тестирования (IRT)IRTродительская вовлеченностьадаптация опросникаparental involvement
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