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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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?

Technological Landscape of the Agriculture and Food Sector: A Long-Term Vision

Ch. 10. P. 203–227.
Gokhberg L., Kuzminov I., Khabirova E.

This chapter presents the overview of global challenges and trends, as well as technological landscape and future prospects for science, technology and innovation (STI) in agriculture and food sector. Our study is based on a systemic mapping of trends and technologies with the combination of big data analysis (text mining) and expert-based methods. The focus of the study is the interaction of agrifood sector with biotechnology and digital technology domains in shaping the future of bioeconomy-driven sustainable and socially inclusive bioagrifood sector. The latter is understood not only in terms of food production but also as a societal ecosystem providing opportunities for human-centred and environment-oriented activities on the land involving certain groups of the population based on traditions and collective and individual values. New opportunities for long-desired wide implementation of the principles of sustainable development and bioeconomy provided by breakthroughs in biotechnologies, nanotechnologies and artificial intelligence give hopes of deep transformation in the sector not only in the most technologically and economically advanced countries but also in mid-tier ones. 

Language: English
DOI
Text on another site
Keywords: foresighttext miningglobal trendsbig datafood sectoragriculture and food sectortrend spottingTechnological landscape
Publication based on the results of:
Challenges and opportunities for science, technology, and innovation during and after the COVID-19 pandemic (2021)

In book

Bio#Futures. Foreseeing and Exploring the Bioeconomy
Cham: Springer, 2021.
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