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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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The Influence Of Financial Constraints And Attitude Towards Risk In Corporate Investment Decisions

NRU Higher School of Economics , 2014. No. WP BRP 36/FE/2014.
Kuzmicheva E. E.
This paper presents evidence of the combined effect of financial constraints and attitudes towards risk in corporate investment. Using panel data on public companies functioning in developed countries, the author shows that demand uncertainty provokes a firm with limited resources to invest sub-optimally, compared to an unconstrained company. Also, with a given level of financial constraints, risk-taking companies tend to decrease investment to a lesser extent in comparison with risk-averse companies. To show this, an index of financial constraints has been constructed, and the optimal threshold values of the index and the risk aversion coefficient have been found.
Priority areas: economics
Language: English
Full text
Keywords: инвестиционные решениянеопределенность спросаinvestment decisionsattitude towards riskdemand uncertaintyотношение к рискуindex of financial constraintsиндекс финансовых ограничений
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