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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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Measurement of the branching fraction and CP asymmetry for B→D0π decays

Physical Review D - Particles, Fields, Gravitation and Cosmology. 2022.
Aushev T., Mizuk R., Pakhlova G., Попов В. Е.
Research target: Physics
Language: English
Full text
DOI
Keywords: Belle detector
Publication based on the results of:
Search for Physics beyond the Standard Model in the decays of heavy leptons and hadrons at Belle and Belle II experiments (2022)
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Added: November 30, 2023
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