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  • Вклад системы СПО в развитие человеческого капитала: опыт стран Европейского Союза
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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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Вклад системы СПО в развитие человеческого капитала: опыт стран Европейского Союза

Педагогический имидж. 2018. № 3. С. 162–168.
Dudyrev F., Romanova O.

The article provides an overview of the best practices of the European
Union in the field of vocational education and training (VET). The selected projects
from vocational educational organizations in Germany, Denmark, Ireland, the
Netherlands, Norway, Croatia and some other countries deal with training workers
for high-tech sectors of economy, as well as for reintegration of yearly school leavers
to education. Particular attention is paid to the mechanisms of public-private
partnership in the field of VET, the most effective organizational solutions and
models of cooperation among educational organizations, business structures and
governmental bodies. The best foreign experience in the field of qualified employees’
training for the post-industrial economy, as well as in the field of social inclusion,
can be used for the development of the VET system in the Russian Federation.

Priority areas: humanitarian
Language: Russian
DOI
Text on another site
Keywords: образовательные инновациисоциальная инклюзия среднее профессиональное образование (СПО) государственно-частное партнерство
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