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May 25, 2026
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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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?

E-Participation Portals Automated Monitoring System for Political and Social Research

P. 290–298.
Chugunov A., Kabanov Y., Zenchenkova K.

This paper presents the opportunities, advantages and limitations of e-participation portals automated monitoring system (AMS) in social and political research. The system was initially developed in 2013 to analyse petitioning and voting dynamics of the Russian e-petitions portal – the Russian Public Initiative – and then was further expanded. In the paper the architecture and working principles of the system are described. It is argued and exemplified that the data collected automatically from e-petition portals can be used to advance research in several areas: media and PR effects on political participation, issue salience, as well as factors of voting behavior and online political engagement.

Language: English
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Keywords: deliberative democracy

In book

Digital Transformation & Global Society: First International Conference, DTGS 2016, St. Petersburg, Russia, June 22-24, 2016, Revised Selected Papers
Digital Transformation & Global Society: First International Conference, DTGS 2016, St. Petersburg, Russia, June 22-24, 2016, Revised Selected Papers
Cham: Springer, 2016.
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