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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.
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A large-scale study of academic specialization and sex effects on Corsi block performance

Frontiers in Education. 2025. Vol. 10. Article 1639086.
Malykh S., Anna Pavlova, Malykh A., Adamovich T., Tikhomirova T.

This study aimed to investigate the relationship between sex, educational specialization (science, technology, engineering, and mathematics (STEM) vs. non-STEM), and performance on the Corsi block-tapping task (CBT). Behavioral outcomes included the total number of correct responses, mean reaction time (RT), and mean RT for correct responses. The sample comprised 5,455 first-year Russian university students (mean age = 18.5; 62% female). Data were analyzed using rank-based analysis of variance (ANOVA) and hierarchical linear regression models. On average, male students outperformed female students in terms of both accuracy and response speed, while STEM students achieved higher scores than non-STEM students but did not differ in RT. Notably, sex differences in the number of correct responses disappeared within educational groups, whereas sex differences in RT persisted among educational groups, regardless of educational specialization. Regression analysis revealed that mean RT (correct responses), age, sex, and educational specialization collectively explained approximately 20% of the variance in performance accuracy. The predictive contribution of educational specialization exceeded that of sex, while the interaction between these variables was not significant. These findings suggest that, while both educational specialization and sex contribute to individual differences in visuospatial working memory performance, educational specialization emerges as a slightly more influential predictor of accuracy than sex, particularly in the number of correct responses. In contrast, reaction time appears to be more consistently associated with sex-related differences, irrespective of educational specialization. The results highlight the importance of considering both cognitive and contextual factors in the assessment of spatial working memory.

Research target: Psychology Education
Language: English
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Keywords: reaction timesex differencesSTEM EDUCATIONCorsi block-tapping taskvisuospatial working memoryeducational specialization
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