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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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?

Towards an innovation ecosystem: The case for stimulating collaboration in the Russian energy sector

P. 1–10.
Yakovleva A. Y., Volkova I.

Increasing cooperation through greater interdependency of the organizational networks structures is a topical issue for a diverse range of industries, including the energy sector However, despite the advantages of such form of activity, Russian organizations do not tend to cooperate. An extensive analysis of the techno-economic network of the Russian power sector innovation ecosystem made it possible to identify hub-organizations which could be regarded as the catalysts for partnership development. Hence, the purpose of this paper is to elaborate the mechanisms of target network creation behind hubs' involvement in the network expansion. Thus, it could provide a solid foundation not only for an increased number of partnerships but could also serve the purpose of embedding companies in the strategic activity ultimately enabling them to achieve competitive parity with the rest of the world.

Language: English
DOI
Text on another site
Keywords: energy sectorecosystemsorganizational networksnetwork creationnetwork expansionpartnership development

In book

IOP Conference Series: Earth and Environmental Science, Vol. 188
Vol. 188: 2018 International Conference on New Energy and Future Energy System (NEFES 2018), 21–24 August 2018, Shanghai, China. , IOP Publishing, 2018.
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