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June 2, 2026
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.
June 2, 2026
Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan
On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.
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.

 

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Проектирование транспортно-логистических систем, устойчивых к структурным разрушениям

Теоретическая и прикладная экономика. 2020. № 1. С. 1–9.
Кочкаров А. А., Яцкин Д. В., Кочкаров Р. А.

This article is dedicated to designing of the transport and logistics systems with built-in resistance to structural failures. The sustainability indicators reflect the impact of the failure of one or several hubs (communication channels) upon working capacity of the already functioning system. In the process of designing the system, the sustainability indicators also provide opportunities for optimizing its structure from the perspective of set reliability expectations. The authors give attention to the modeling of the transportation and logistics system on the basis of theoretical-graph toolset, as well as propose sustainability indicators and articulation of optimization task. The structure of transportation and logistics system is described using the instruments of graph theory, definition of the task is presented using the criteria of optimization theory, and limitations are the feasible solutions on graphs are established in the matrix form. The authors suggest a theoretical-graph description of the structure of the transportation and logistics systems, propose multiobjective goal setting, and introduce the concept of structural stability based on the indexes and their threshold values. Proposal is made on the approach towards designing the transport and logistics systems with set parameters of structural stability and tried it on test data.

Language: Russian
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Keywords: модельпроектированиеграфgraphтранспортно-логистическая система stabilityструктурная устойчивостьstructural stabilitycomputer experimentкомпьютерный экспериментengineeringtransport and logistics systems устойчивостьпоиск решенияstructural failuresustainability indicatorsearch for a solution structural stabilityпоказатель устойчивостиструктурное разрушение
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