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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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Uncovering Driving Forces for Better Product Innovation: Have Russian Firms Learned to Balance the Focus on Internal and External Partners?

Ch. 12. P. 197–222.
Rebiazina V. A., Smirnova M., Podmetina D., Volchek D.

The current study focuses on exploring how cooperation can help companies to reach their targets in new product development and market launch successfully. The overarching research question of the study is whether cooperation in innovation can help Russian companies to overcome market and institutional context inefficiencies and achieve better performance outcomes. More specifically, we address two aspects of cooperation: the role of cooperation with external partners as a factor of innovation success and the balance of internal versus external stakeholders’ interests in framing innovation strategy. The study is empirically based on a cross-industry quantitative dataset of Russian innovative firms.

Language: English
Full text
DOI
Keywords: инновациибизнес-партнерыbusiness partnershipsstakeholdersзаинтересованные лица (стейкхолдеры)business innovation
Publication based on the results of:
Business model research in emerging markets (2015)

In book

Adoption of Innovation. Balancing Internal and External Stakeholders in the Marketing of Innovation
Adoption of Innovation. Balancing Internal and External Stakeholders in the Marketing of Innovation
Switzerland: Springer, 2015.
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