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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
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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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Towards the Flexibility of Software for Computer Network Simulation

P. 391–397.
Mikov A. I., Zamyatina E., Mikheev R. A.
Abstract— This paper discusses network simulator TRIADNS. It is well known that the role of computer networks becomes more important due to progress in new computer technologies (distributed information systems, GRID-computing, Cloud computing and so on). So it is necessary to have effective and flexible program tools for computer network design and simulation. Indeed this program tools have to design computer networks with a lot of computer nodes, so simulation run must be time-consuming. Besides, it is necessary to study topological characteristics of computer network, to investigate traffic, to study computing node’s behavior, to test the designed protocols, to study the behavior of routing algorithms and how these algorithms will behave when computer network topology is changed (new nodes can be added to network, some nodes can fail and so on). Network simulator must design and investigate not only hardware, but software too, explore computer networks, considering in particular the specific characteristics of a variety of computer networks.This paper considers approaches allowing to decide these problems: hierarchical model, using ontologies and Data Mining methods for the analyses of simulation results.
Language: English
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Keywords: simulationdata miningontologiescomputer networksdistributed and parallel simulationrouting algorithms

In book

Advances in Information Science and Applications. Volumes I & II. Proceedings of the 18th International Conference on Computers (part of CSCC '14)
Vol. 1-2. , Santorini Island: CSCC, 2014.
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