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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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Признаки неконкурентного поведения в системе государственных закупок

С. 224–228.
Ерёмина А. В., Maksimov A. G.

The modern procurement system in Russia is considered to function economically and efficiently on the basis of principles of fair competition among its main participants. Practically the important principles of the procurement system are not implemented in all cases. The research agenda of authors focuses on the analysis of interactions between the economic agents in the procurement process, aimed at revealing the indicators of noncompetitive behavior between the buyers and the suppliers and only between the suppliers by means of econometrics (fuels and lubricants market of Moscow region as an example). The empirical data for the analysis consists of the information about the fulfilled purchases of oil-products in 4 neighboring districts of Moscow region: Orehovo-Zuevo, Pavlovskiy Posad, Egorievsk and Shatura in the period of 2007-2011.

Language: Russian
Full text
Keywords: коррупциягосударственные закупкиcorruptionгосударственный заказсговор public procurementpublic purchase competition in public purchase collusion

In book

Системное моделирование социально-экономических процессов: труды 39-й Международной научной школы-семинара
Воронеж: Воронежский государственный педагогический университет, 2016.
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