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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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Senior Customer Satisfaction in Hospitality: Drivers and Challenges by Gender

P. 55–74.
Rudchenko V., Volkova N.

Purpose. Population aging increased all around the world that has underlined the importance of senior tourism investigation in hospitality. However, the satisfaction of senior customers in hospitality are mostly presented by English-speaking researchers, and there is a significant gap in other countries such as Russia. The purpose of this paper is to gain insight into the satisfaction of the senior customers in the hospitality segment using such variables as age, gender, origin, accommodation preferences, trip duration, income, and type of the trip.

Language: English
Full text
Keywords: satisfactionhospitalitysenior clientscustomer genderaging customers

In book

Gender and Tourism: Challenges and Entrepreneurial Opportunities
Gender and Tourism: Challenges and Entrepreneurial Opportunities
Bingley: Emerald Publishing Limited, 2021.
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