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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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Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Relationship of Property Structure and Performance of High-Tech Technology

Studies on Russian Economic Development. 2020. Vol. 31. No. 3. P. 264–270.
Rybalka A.

Based on data from high-tech companies in Eastern and Western Europe, the article analyzes the relationship between ownership structure parameters, some corporate governance factors, and company performance. The main purpose is to examine the established patterns of ownership structure of successful companies. It is revealed that at the initial stage of development of companies, the “Sole leader and like-minded people” is a more favorable model of ownership structure, and at the second stage of development, when the company becomes a large business, the “Leader Team” with a less concentrated level of ownership is a higher priority model. Relationship of Property Structure and Performance of High-Tech Technology

Priority areas: economics management
Language: English
DOI
Text on another site
Keywords: concentration of ownershipfirm performancehigh-tech companies
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