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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
'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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Гендерный разрыв в заработных платах выпускников российских колледжей: между образовательной и отраслевой сегрегацией

Вопросы образования. 2025. № 4. С. 45–75.
Yemelina N., Rozhkova K., Roshchin S.

The article uses administrative data from the Monitoring of Graduate Employment to assess the gender wage gap among graduates of secondary vocational education programs and the contribution of educational and work characteristics to the size of this gap. At the labour market entry, the gender wage gap is already 23% for professionals and clerks and 12% for middle-level professionals. Three years after graduation, the gap more than doubles for both qualification levels. A significant portion of the gap is explained by occupational segregation, arising due to the uneven gender distribution by fields of study. Among middle-level professionals, diplomas in health and education, which are mostly obtained by women, are more highly paid than other fields of study. Thus, the negative effect of occupational segregation is compensated by the positive effect of educational segregation. At the same time, among professionals and clerks, women work in low-paid trade, regardless of their field of study. Therefore, educational segregation at this qualification level contributes to the gender wage gap. Although female professionals often hold jobs above their qualifications, they earn less than men in lower positions, resulting in the highest gender gap among young professionals.

Research target: Education
Language: Russian
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Keywords: среднее профессиональное образованиеsecondary vocational educationрынок труда выпускниковgender wage gapgraduate labour marketгендерный разрыв в оплате трудаstarting wagesстартовые заработные платы
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