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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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The 15th International Conference on Concept Lattices and Their Applications CLA2020

Issue 2668. CEUR-WS, 2020.
Leading author: F. J. Valverde-Albacete

Proceedings of the Fifthteenth International Conference on Concept Lattices and Their Applications

Tallinn, Estonia, June 29–July 1, 2020.
Edited by

Francisco J. Valverde-Albacete
Martin Trnecka

Chapters
Gradual Discovery with Closure Structure of a Concept Lattice
Kuznetsov S., Napoli A., Makhalova T., , in: The 15th International Conference on Concept Lattices and Their Applications CLA2020Issue 2668.: CEUR-WS, 2020. P. 145–157.
An approximate discovery of closed itemsets is usually based on either setting a frequency threshold or computing a sequence of projections. Both approaches, being incremental, do not provide any estimate of the size of the next output and do not ensure that “more interesting patterns” will be generated first. We propose to generate closed itemsets ...
Added: October 29, 2020
Towards Stable Significant Subgroup Discovery
Jyoti -., Buzmakov Aleksey, Kailasam S., , in: The 15th International Conference on Concept Lattices and Their Applications CLA2020Issue 2668.: CEUR-WS, 2020. P. 287–292.
Added: July 10, 2021
Priority areas: IT and mathematics business informatics mathematics
Language: English
Text on another site
Keywords: concept lattices
The 15th International Conference on Concept Lattices and Their Applications CLA2020
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