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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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Avoidance of cognitive efforts as a risk factor in interaction

Discourse Studies. 2022. Vol. 24. No. 3. P. 269–290.
Mustajoki A., Baikulova A.

In an ordinary interaction, communicants have various, mostly unconscious goals which reflect
their interactional, social and personal needs. In these interactions, people’s minds try to find a
balance between reaching these goals and consuming cognitive energy. If a speaker puts too little
effort into speech production, she risks not achieving her communicative goals. This is especially
typical when the atmosphere is relaxed, a good example of which is family discourse. An analysis
of recorded conversations shows that there are certain regular manifestations of risk-taking
in family discourse, such as expressing immature thoughts, raising a large variety of topics and
overguessing. A substantial amount of risk-taking in family discourse is in one way or another
connected with false confidence in the interlocutors’ common ground. Family members know
each other well, which results in an overestimation of the similarity of their understanding of
words and objects. This attitude leads them to use cryptic, hard-to-comprehend speech. Quick,
everyday interactions are mostly automated, and the speakers do not recognise that their speech
is full of implicitness and underdeterminacy.

Research target: Philology and Linguistics
Language: English
Full text
DOI
Text on another site
Keywords: interactionrisk-takingfamily discoursecommon ground fallacyrecipient designCognitive energycryptic speechimplicitnessunderdeterminacy
Publication based on the results of:
Constants and variables in oral and written discourse (2022)
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