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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
'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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Institutions of Personal Data in Russia and Personal Information in China: a Comparative Legal Analysis

Legal Issues in the Digital Age. 2025. Vol. 6. No. 3. P. 77–98.
Olga Aleksandrovna Berzin, Zakhar Olegovich Mitianov

The authors analyze and compare Russian and Chinese approaches to legal regulation of personal data in Russia and of personal information in China institutions to identify their similarities and differences, as well as to determine the optimal practices of formation of these legal institutions. The concept and essential features of personal data and personal information in each of two countries are studied and compared, their similarities and differences are pointed out. International and national legal systems and the hierarchy of legal norms/spheres regulating in the field in Russia and China are analyzed; structural construction of regulatory and legislative bases in the spheres mentioned in Russia and China is studied and compared. The article examines state authorities regulating in the field in Russia and China, theirs system, structure and spheres of competence, as well as the capabilities of appropriate normative legal regulation. Proposals on the expediency of borrowing the more progressive and nationally oriented Chinese norms covering personal information into the Russian Federation legislation on personal data are substantiated.

Research target: Law
Language: English
DOI
Text on another site
Keywords: personal datapersonal information comparative analysislegal institutionlegislative frameworkregulation in the field
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