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Subject
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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Digital Transformation in Governance and Society: 7th International Conference, DTGS 2024, St Petersburg, Russia, June 24–26, 2024, Revised Selected Papers

Springer, 2025.
Academic editor: G. Li, F. Joaquim, X. Zhiwei
Editor-in-chief: A. Chugunov, O. Filatova, Y. Kabanov, H. Misra, L. Smorgunov, W. Zhang

This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Chapters
Interface Elements and Trust in Online Media: A Conjoint Analysis Approach
Artemenko E., Faizova L., , in: Digital Transformation in Governance and Society: 7th International Conference, DTGS 2024, St Petersburg, Russia, June 24–26, 2024, Revised Selected Papers.: Springer, 2025. P. 47–61.
In the age of the Internet, where misinformation is spread with great ease, trustworthiness of news sources has become an important issue. The aim of this study is to assess how users perceive credibility of different online news interfaces by employing experimental methodology. An online experiment was conducted using the conjoint analysis approach. Participants were ...
Added: August 18, 2025
Research target: Sociology (including Demography and Anthropology Psychology
Language: English
Full text
DOI
Text on another site
Keywords: Digital transformation (DT)
Publication based on the results of:
Analysis of Human Interaction with Information and Improvement of Algorithms of Information Processing (2025)
Digital Transformation in Governance and Society: 7th International Conference, DTGS 2024, St Petersburg, Russia, June 24–26, 2024, Revised Selected Papers
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