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News
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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Возможность сотрудничества крупного бизнеса с социальными предпринимателями

Векторы благополучия: экономика и социум. 2023. Т. 48. № 1. С. 173–189.
Nazarova I. B., Moskovskaya A. A.

The article discusses the expediency of a rating assessment that takes into account the cooperation of large
companies operating in Russia with social entrepreneurs. The current situation in Russia demonstrates the lack of the cooperation and the great need for the support of social enterprises from big business. Purpose. Determine the possibility of big businesses and social entrepreneur’s cooperation in ratings. Results. Analysis of the methodology of the most reputable organizations/rating agencies (assessing big businesses) operating in Russia shows that the goals of rating agencies are related to identifying the best charitable programs, best practices of corporate social policy of companies, and their social orientation, the best managers of large companies in the field of corporate social responsibility and informing the public about the activities of companies. Conclusions. The analysis of the methodology also showed that there are nominations and indicators that could take into account the interaction of companies with social entrepreneurs. In particular, sustainable development, corporate social responsibility of the company, including charitable activities and activities to preserve environmental well-being can be assessed taking into account interaction with social enterprises. Social entrepreneurs can offer their cooperation to big business in the implementation of social projects from which big business, social enterprises and society can benefit. Big business could play the role of supporting social entrepreneurship, participating in the development of social business and creation of new jobs in the region

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: Russian
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Text on another site
Keywords: социальное предпринимательствокорпоративная социальная ответственностькрупный бизнесрейтинговые агентствамалый бизнесрейтингиsmall businesssocial entrepreneurshipcorporate ratingsrating agenciesCorporate social responsibilitybig business
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