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.
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.
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.
Tiraspolsky S., Rubtsov A., Pudeyev A. et al., Proceedings of the 2006 3rd International Symposium on Wireless Communication Systems, IEEE 2006 P. 21–24
In present paper we have investigated a co-channel interference cancellation technique based on the tracking a limited number of strongest interferers only. With the assumption of synchronous base stations operation with overlapping but different training signals (pilots). Kalman filtering may be used for interfering channels estimation and further calculation of interference correlation matrix. This correlation ...
Tiraspolsky S., Malstev A., Rubtosv A. et al., Proceedings of the 2006 3rd International Symposium on Wireless Communication Systems, IEEE 2006 P. 353–357
In this paper, dynamic system level simulation methodology of mobile WiMAX (IEEE Std 802.16e) is described. The system level simulations scenarios (channel models, pathloss and shadow fading, sectorization, frequency reuse planning, system loading, etc) will be introduced. Evaluated performance of mobile WiMAX system such as signal-to-interference + noise ratio distributions, spectral efficiency and system outage ...