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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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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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The typical infringements against consumer energy market

Justitias Welt. 2011. No. 15. P. 1–9.
Pogosova Z. M.

The most widespread infringements on consumer energy market are analysed in the article. Exemplary components and provisions of relevant types of legal liability are generalised for the purposes of consumer energy market.

Priority areas: economics law
Language: English
Text on another site
Keywords: уголовная ответственностьадминистративная ответственностьadministrative liabilityгражданская ответственностьполитический рынокCriminal liabilitycivil liabilityправонарушенияInfringementsconsumer energy market
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