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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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О применении некоторых специальных критериев проверки нормальности распределения результатов педагогических измерений

Законодательная и прикладная метрология. 2014. № 6. С. 28–33.
Maksimenkova O. V., Podbelskiy V.

The paper is devoted to analysis of results of educational measurements. Authors describes the range of applicability of classical test theory and item response theory. Not only mathematical but also procedural limitation of both theories are taken in consideration. Classical test theory is presented in the paper in its historical view, as an heir of methods of physics measurements. Capabilities of the classical test theory methods in daily educational practice are justified and evaluated. The main topic of the paper is testing for normality raw scores distribution and the adjacent topics. Authors represents recommendations in application of special tests for normality (given in ISO 5479-2002) to analysis of results of educational measurement. Those recommendations are based on researches in the field of mathematical statistics. 

Research target: Computer Science Mathematics Education
Priority areas: IT and mathematics
Language: Russian
Full text
Keywords: нормальное распределениеnormal distributionmeasurementsизмерения в образованииeducational measurementstest for normalityкритерий проверки нормальности
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