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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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Согласование сказуемого с именной группой, включающей слова "сколько", "столько", "много", "немало", "несколько"

Научно-техническая информация. Серия 2: Информационные процессы и системы. 2014. № 9. С. 24–32.
Kuvshinskaya Y. M.

This study considers predicate agreement with quantifier phrases that include the words neskolko, stolko, skolko, mnogo, nemalo. We analyze the evolution of  predicate agreement with neskolko, stolko, skolko, nemalo and mnogo and describe the modern standard of usage based on the data from the Russian National Corpus. The influence of grammatical properties of the numeral on the predicate choice as well as certain factors that favor  the non-typical plural predicate (such as predicate  type, animacy of the NP, syntactic  structure of the NP) are also considered.

Research target: Philology and Linguistics
Language: Russian
Full text
Keywords: предикативное согласование в русском языке, количественно-именные сочетания, корпусные методы в лингвистикеpredicate agreementquantifier phrasecorpus studyвариативность грамматических форм
Publication based on the results of:
Corpus technologies in linguistic and interdisciplinary research (2014)
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