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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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EU–Central Asian interactions: perceptions, interests and practices

Central Asian Survey. 2022. Vol. 41. No. 4. P. 617–638.
Fawn R., Kluczewska K., Korneev O.

By shifting the study of European Union (EU)–Central Asian relations from its fixed category of black-boxing both the EU and Central Asia, this article advances the case for the approach of examining multi-level and multi-actor interactions that identify the dynamic processes of reciprocal action and meaning-making that characterize the mutual cooperation. It distinguishes perceptions, interests and practices, pointing to the rationales and modes of behaviour of multiple EU and Central Asian actors. The article also advances five reasons why EU studies should take more interest in Central Asia, given that the EU’s larger external relations and security agenda extends to this region. Similarly, it shows that Central Asian studies can benefit from the analysis of the region’s interactions with external actors, including the EU, given that external actors contribute to reshaping national policy agendas and influence everyday life.

Research target: Political Science, International Relations, and Public Administration
Language: English
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Keywords: Европейский СоюзЦентральная АзияEuropean Unioninternational organizationsCentral Asiaмеждународные организациивнешняя политика ЕСмеждународные практикиInternational PracticesEuropean Union external action
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