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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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Программа секций XVIII Апрельской конференции. Сессия P-04. Исследование демографических последовательностей

HSE, 2017.
Leading author: Ignatov D. I.
Chapters
Деревья решений для классификации демографических последовательностей
Muratova A., Ignatov D. I., В кн.: Программа секций XVIII Апрельской конференции. Сессия P-04. Исследование демографических последовательностей.: НИУ ВШЭ, 2017. С. 1–13.
Анализ демографических последовательностей становится все более востребованным в последние годы. В рамках данной работы был осуществлен анализ демографических последовательностей с помощью деревьев решений. Для демографических и социоэкономических событий были определены (предсказаны) первые и последние значимые события в жизни человека с учетом всех его признаков и уже произошедших событий. Также выявлены взаимосвязи событий для признаков пол ...
Added: February 9, 2020
Поиск закономерностей в индивидуальных демографических траекториях
Gizdatullin D., Ignatov D. I., Baixeries J., В кн.: Программа секций XVIII Апрельской конференции. Сессия P-04. Исследование демографических последовательностей.: НИУ ВШЭ, 2017. С. 1–11.
В данной работе представлены результаты применения узорных структур (pattern structures) и “контрастных” закономер- ностей (emerging patterns) в анализе демографических последова- тельностей для данных по России. Панельные данные Российской части исследования GGS (Generation and Gender Survey) на основе трех волн опроса в 2004, 2007, и 2011 описывают 11 поколений ре- спондентов, начиная с 1930 по 1984. ...
Added: February 9, 2020
Research target: Sociology (including Demography and Anthropology Computer Science
Priority areas: sociology IT and mathematics
Language: Russian
Text on another site
Keywords: demographic sequencessequence miningанализ демографических последовательностей
Publication based on the results of:
Разработка и апробация методик анализа демографических последовательностей (2016)
Программа секций XVIII Апрельской конференции. Сессия P-04. Исследование демографических последовательностей
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The recognition-by-components method
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The evolution of identity politics in Bangladesh: historical roots, contemporary challenges, and implications for civil society
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