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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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Zaidiyyah Minority at the Yemeni Socio-Political Continuum

St. Petersburg Annual of Asian and African Studies. 2016. Vol. 4. P. 175–186.
Issaev L., Korotayev A.

The study aims to analyze the phenomenon of the Zaidiyyah minority in Yemen. Particular attention is paid to formation of the Zaidiyyah identity. The difficulties of reaching a compromise between the Zaidiyyah minority and the Sunni majority in the recent history of Yemen have been identified. This article shows that one of the fundamental causes of the current Yemeni conflict which began as a response to the events of the so-called ‘Arab Spring’ of 2011, is destruction of status quo between the Zaidiyyah religious elite (Sayyid and Qadi) and the sheikhs of Zaidiyyah tribes existed in Yemen for centuries. The attempt of al Ahmar family to break this balance in favor of tribal sheikhs by spreading the Wahhabi ideology led to the fact that the Yemeni conflict of the 21st century has taken a multi-dimensional and deep character.

Research target: Political Science, International Relations, and Public Administration
Language: English
Full text
Keywords: «Al-Qaeda»YemenhouthisZaidiyyahtribesAli Saleh
Publication based on the results of:
The Arab Spring as the Trigger of a Global Phase Transition (2016)
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