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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.
May 25, 2026
'The Humanities Serve as a Conscience'
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.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Повышает ли стоимость компании публикация нефинансовых отчетов по стандартам GRI? (на примере стран БРИКС)

Учет, анализ и аудит. 2017. № 2. С. 28–36.
Kuzubov S. A., Евдокимова М. С.

This paper provides a review of the literature about the impact of non-financial reporting (NFR) on the 

market to book ratio and empirical research based on the comparison of the companies that issued the  reports according to the General Reporting Initiative (GRI) standards in 2004–2014 with the companies  which published only financial statements. The sample is drawn from the companies based in Brazil, Russia,  India, China and South Africa (BRICS). Financial data were taken from the Compustat database, the list of  companies producing non-financial statements has been obtained from the GRI website. Using the latest  version of the Olson’s model it has been revealed that the issue of a report in accordance with the GRI  guidelines has a positive significant effect during that year and the year after the release. Also, there have  been identified some sectors for which the publication of such statements is significant.

Priority areas: economics
Language: Russian
Full text
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Keywords: интеллектуальный капиталnon-financial reportingIntellectual capital, intellectual capital disclosure, disclosure index, emerging markets, BRICS, valueфинансовая и нефинансовая отчетностьGRIGRI
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