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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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Proceedings of the 27th Conference of Open Innovations Association FRUCT

IEEE, 2020.

Proceedings of the 27th Conference of Open Innovations Association FRUCT

Chapters
Sociolinguistic Variability of Russian Everyday Speech: A Corpus-Based Study
Sherstinova T., Богданова-Бегларян Н. В., Баева Е. et al., , in: Proceedings of the 27th Conference of Open Innovations Association FRUCT.: IEEE, 2020. P. 288–293.
The paper presents recent results of a multilevel analysis of representative corpus data, conducted in order to identify key speech parameters (lexical, morphological and syntactic) that can diagnose some social/biological characteristics of a speaker or, more broadly, a modern Russian urban sociolect. The study is based on the everyday Russian speech corpus “One Speaker’s Day”. ...
Added: October 31, 2020
Frequency Word Lists and Their Variability (the Case of Russian Fiction in 1900-1930)
Sherstinova T., Гребенников А. О., Скребцова Т. Г. et al., , in: Proceedings of the 27th Conference of Open Innovations Association FRUCT.: IEEE, 2020. P. 366–373.
Lexical system is an essential component of any natural language. Frequency word lists are a convenient representation of words functional activity in language as a whole or in some particular text. The parameters and properties of frequency word lists are in the center of attention of NLP experts, since they are used in numerous practical ...
Added: October 31, 2020
Measures of Syntactic Complexity and their Change over Time (the Case of Russian)
Sherstinova T., Ушакова Е. О., Мельник А. Г., , in: Proceedings of the 27th Conference of Open Innovations Association FRUCT.: IEEE, 2020. P. 221–229.
Syntactic complexity is an important feature of any text, both written and oral. The information about syntactic complexity is crucial for successful solution of many practical NLP tasks starting from intellectual understanding of texts and ending with automatic machine translation. Because of this, syntactic complexity and its measures are in the center of attention of ...
Added: November 1, 2020
Language: English
Text on another site
Keywords: computer technologiestelecommunicationsinformation studies
Proceedings of the 27th Conference of Open Innovations Association FRUCT
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