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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
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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.
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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?

Knowledge Triangle: The Right Concept to Align Universities Missions?

Ch. 2. P. 19–32.
Groumpos P., Meissner D.

Despite long-lasting discussions about Knowledge Triangle and Triple Helix universities missions have not changed much. Discussions about these concepts remain at aggregate level resulting in several approaches for measuring universities performance but are clearly less developed in terms of management concepts and practical applicability. Accordingly policy measures target at the sympthoms and might show some initial impact but it is doubtful if they achieve sustainable impact if not implemented at the operational level, e.g., targeting the cause. Eventually, it appears that universities are following the Knowledge Triangle thinking for a while already whereas debates have always stressed the importance of transferring knowledge and technology toward achieving impact, especially economic impact, but less attention as paid to the transfer of competences from research to teaching which is among the main functions of universities. This is only one observation from Knowledge Triangle and Triple Helix thinking. Eventually, it appears that both approaches are suitable analytical frameworks for assessing the actual missions and position of universities but not suitable for designing and implementing institutional strategies and governance models. Instead, the perception should be changed toward “Knowledge for the Triangle” which requires a dedicated balanced scorecard for institutional governance and performance boost.

Language: English
DOI
Text on another site
Keywords: Knowledge Triangleuniversities missions
Publication based on the results of:
Research on the efficiency of innovation generation processes: resources and factors (2021)

In book

The Knowledge Triangle. Changing Higher Education and Research Management Paradigms
Aanstad S., Benner M., Borlaug S. B., Čadil V., Cervantes M. Switzerland: Springer, 2021.
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