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News
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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Разработка концептуальной научно-методической модели проектирования изделий легкой промышленности в цифровой среде

Костюмология. 2025. Т. 9. № 4.
Туханова В. Ю., Kankulov A.

The article presents the study focused on the development of a conceptual scientific and methodological model for designing products in the apparel and footwear industries within a digital environment. It examines the specific features of the design stages of light industry products, considering the integration of innovative technologies into higher education programs for training specialists at the bachelor's and master's levels in the "Fashion Design" specialty. The author provides an overview of the current state of digital fashion development in the light industry.

One of the key aspects shaping the consumer properties of light industry products in the modern digital economy is a set of digital property indicators that must be embedded at the stage of developing a digital prototype model. The end product of digital design to apparel industry items consists of three-dimensional static or dynamic wardrobe elements, whose accurate visualization requires accounting for and implementing quantitative and qualitative characteristics of the computer model’s properties.

The structural and logical components of the developed informational and methodological system include descriptions of digital tools that enable innovative approaches to the creation, presentation, and promotion of clothing collections in the global virtual space.

The study aims to develop a conceptual scientific and methodological model for designing collections of clothing, footwear, and accessories in a virtual environment using advanced high-tech tools. The findings are recommended for use in educational processes, as well as for the implementation of virtual design technologies for clothing collections in the industrial development programs of light industry enterprises in the Russian Federation.

Research target: Chemical Technologies
Language: Russian
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Keywords: модамоделированиедизайнmodelingтехнологияконцепцияtechnologydesign conceptfashion designdigital clothingцифровая одеждаdigital properties fashion
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