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News
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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Use of Patent Classification in Searching for Biomedical Information

Russian Journal of Bioorganic Chemistry. 2021. Vol. 47. No. 6. P. 1225–1230.
Blokhina Y. V., Ilin A.
Translator: L. Solovyova

Patent literature is an integral and significant part of human knowledge, the disrespect for which can negatively affect the quality of a researcher’s work. A search in patent databases helps both to look for detailed technical data on objects or processes and to evaluate the possibility of patenting one’s own results. At the same time, such a search is somewhat different from using standard Internet search engines or scientific citation systems. In this work, detailed practical recommendations are given for searching information in patent databases using the IPC (International Patent Classification) and CPC (Cooperative Patent Classification). A description of the classifiers is given and an example of how to search for information on nanoelectronic biosensors is presented.

Research target: Education Computer Science Nanotechnologies
Language: English
DOI
Text on another site
Keywords: наноэлектроникаnanoelectronicspatent classificationPatent Searchпатентный поискМПКbiosensorIPCCPCпатентная классификацияСПКбиосенсор
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