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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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Big Data and travel industry

Financial and Economic Tools Used in the World Hospitality Industry: Proceedings of the 5th International Conference on Management and Technology in Knowledge, Service, Tourism & Hospitality 2017 (SERVE 2017), 21-22 October 2017 & 30 November 2017 . 2018. Vol. 1. P. 265–270.
Булгаков А. Л.

The use of Big Data technology has been a modern trend in the travel industry over the last 10 years. At present, almost all travel companies that desire to stay profitable and be customeroriented use the Big Data technology. Therefore, we have several questions to answer: should we use Big Data in tourism or should we not? How to use it? What kind of risks we should consider in order to achieve effective results? These research problems were examined through a thorough analysis of Russian and world travel markets using statistical data on several sites, programs, and organizations that are associated with the tourism industry (e.g., Booking.com, Trivago). The main result of this study is to substantiate the importance of Big Data technology for the travel industry. Big Data technology helps to personally connect companies and clients of the sector so that their interaction would lead to their mutual benefits. The net result of this interaction is an increase in the economical aspect of the sector and thus the country’s growth.

Language: English
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Keywords: industrial economicstourism industryBig data technologiesEconomical aspectsMutual benefitResearch problems
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