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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 семиотической модели образа

Слово.ру: балтийский акцент. 2018. Т. 9. № 2. С. 37–51.
Fomin I.

The article is devoted to the development of a fundamental semiotic model of images that is based on the categorical apparatus of Ch. S. Peirce (on the concepts of Firstness, icon, hypoicon and metaphor). The image is proposed to be defined as a complex sign (two-level hypoicon-metaphor), which has a certain “primary” sign as its sign vehicle that represents the object constituted by all the facts (cases of semiosis) that are similar to that primary sign. Three key functions of the image are defined: a) the memory function (the accumulation of semiotic experience inherent in a certain discourse), b) the transfer function (transmission (synchronic and diachronic) of semiotic experience from one discourse to another), c) logonomic function (prescription and enabling of the future of acts of semiosis, similar to a certain exemplary act). The author explores the relationship between the category of image and a number of similar concepts. In particular, the definitions of the category of symbol (by S. S. Averintsev and Yu. M. Lotman), the category of myth (in the interpretation of R. Barthes) and the concept of meme (by R. Dawkins) are analysed and juxtaposed with the notion of image.

Research target: Other social sciences Other Humanities Media and Communications
Priority areas: sociology humanitarian
Language: Russian
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DOI
Text on another site
Keywords: metaphorсемиотикасимволобразмифsymbolmythimagesemioticsметафорызнаки-иконыiconicity
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