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News
June 22, 2026
‘In Science, You Are Your Own Boss
Polina Nasledskova is interested in identifying gaps in linguistics and topics that have been overlooked by other researchers. In an interview for the  Young Scientists of HSE University project, she spoke about rare ordinal numerals in Nakh-Daghestanian languages, the benefits of knitting for concentration, and the beauty of the Patriarshy Bridge.
June 19, 2026
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
June 5, 2026
'Im Used to Producing Distilled Knowledge'
Ivan Rubachev works in a HSE University laboratory established jointly with Yandex Research, where he focuses on machine learning with tabular data. In this interview with the HSE Young Scientists project, he discusses why following a vibe can be better than goal-setting, explains the concept of the Neural Turing Machine, and argues why withholding scientific knowledge is counterproductive.

 

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On the Limits and Best Practice for NB-Fi: A New LPWAN Technology

IEEE Internet of Things Journal. 2023. Vol. 10. No. 14. P. 12352–12365.
Bankov D., Levchenko P., Lyakhov A., Khorov E.

NB-Fi is a new low-power wide-area network technology, which has become widely used for smart cities, smart grids, the Industrial Internet of Things, and telemetry applications. Although many countries use NB-Fi, almost no papers study NB-Fi, and its peak performance is unknown. This article aims to fill this gap by analyzing this technology and studying the problem of rate assignment in NB-Fi networks. For that, this article develops a mathematical model used to find the packet loss ratio, packet error rate, and the average delay for various rate assignment approaches. The performance evaluation results are used to develop the guidelines for NB-Fi configuration to optimize the network performance.

Research target: Computer Science Electronics and Electrical Engineering
Language: English
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DOI
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Keywords: mathematical modelingInternet of things (IoT)low-power wide area networksNB-Fi
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