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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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?

The Role of Enterprise Architecture for Digital Transformations

Sustainability. 2021. Vol. 13. No. 4. Article 2237.
van de Wetering R., Kurnia S., Kotusev S.

In the current turbulent and unpredictable markets, competitive advantage can no longer be achieved through high product quality or efficient processes alone. Modern firms are currently pressured to increase both the efficiency and effectiveness of business operations to achieve the firm’s strategic direction and unlock the true potential of new and disruptive digital business models [1,2]. Under these conditions, firms should align and integrate their information systems (IS), information technology (IT) assets, and resources with business processes to efficaciously respond to changing environmental and market conditions [3,4]. To orchestrate these business and IT assets and resources, components, and capabilities in digital and organizational transformations, firms increasingly adopt Enterprise Architecture (EA).

Research target: Other social sciences
Language: English
Full text
DOI
Text on another site
Keywords: Enterprise Architecture (EA)digital transformation
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