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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.
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Test Takers’ Perceptions towards BEC Exams: a Case Study of a Russian University

Journal of Language and Education. 2017. Vol. 3. No. 4. P. 27–35.
Smirnova E. A., Permyakova T. M., Sheveleva M. S.

This is a qualitative study of candidates’ motivation to take BEC exams and their expectations towards the exam results, which was conducted at the Cambridge Exam Preparation Center in a Russian university. The research dataset comprised 33 participants who took part in faceto- face in-depth semi-structured interviews. Overall, candidates show a positive attitude to BEC at different exam levels. The main reasons for preparing for and taking the exams are extrinsic and defined by the institutional environment. The respondents opt for BEC exams as they intend to receive an international education (master’s level) and/or build a successful career in international organizations. The study also revealed a connection between candidates’ expectations toward exam results and their age and level of language proficiency.

Research target: Education Psychology
Priority areas: humanitarian
Language: English
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DOI
Text on another site
Keywords: РоссияRussiaмотивацияделовой английский языкmotivationожиданиякачественное исследованиеМЕЖДУНАРОДНЫЕ ЭКЗАМЕНЫ ПО АНГЛИЙСКОМУ ЯЗЫКУqualitative studyinternational English language examsBECexpectations
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