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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.
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?

Complexity Studies: Interdisciplinarity in Action

Ch. 18. P. 379–402.
Knyazeva H.

Modern complexity studies and their interdisciplinary character are under consideration in this article. The conceptual framework of complexity studies includes such methodologically significant notions as nonlinearity, self-organization, creative chaos, co-evolution and blow-up regimes. It is argued that interdisciplinarity corresponding to a holistic worldview becomes a powerful trend in modern science. At the same time, evolutionary holism constitutes a philosophical basis for complexity studies. The possible future developments of complexity studies as a fundamental interdisciplinary paradigm are discussed as well. It is shown that interdisciplinary research will define the character of science in the medium-term future.

Language: English
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Keywords: самоорганизацияinterdisciplinarityсложные системыself-organizationмеждисциплинарностьcomplexityсложностьcomplex systemstheory of complexityтеория сложности

In book

Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von Big Data
Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von Big Data
Wiesbaden: Springer, 2017.
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