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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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Estimation of thermodynamic parameters of the biosphere, based on remote sensing

Ecological Modelling. 2011. Vol. 222. No. 16. P. 2913–2923 .
Puzachenko Y. G., Sandlerskiy R., Svirejeva-Hopkins A.

A method that allows the estimation of the thermodynamic parameters of the biosphere has been developed. It results in the subdivision of the following four phase states of the biosphere: three equilibrium states: "white planet" with high albedo and low entropy; temperate forest in winter with high entropy; and desert with high entropy; and one nonequilibrium state: the "active forests" with low entropy, high information gain and the highest exergy values. The phase shift to a nonequilibrium state happens when albedo is less than 0.2.

Research target: Earth Sciences Biology
Language: English
Full text
DOI
Text on another site
Keywords: entropyэнтропиябиосфераprinciple of maximum entropyпринцип максимума энтропииexergyэксергияIncrement of informationприращение информацииbiosphere
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