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News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Forecasting the residual stress components in wires using an artificial neural network

International Journal of Advanced Manufacturing Technology. 2025. Vol. 141. P. 1847–1858.
Dmitriy Demin, Ilya Grebenkin, Alexey Barinov

In this paper, a computer simulation of round wire drawing processes with different equations of state for steel A12 has been carried out. In addition, the methods of improving the configuration of neural networks based on a multilayer perceptron (MLP) for estimating the distributions of residual stress tensor components have been investigated. The study demonstrated that the strain rate exerted a significant influence on the character of the processes, particularly within the central region () of the investigated specimens. In addition, the employment of software tools for the purpose of tuning the hyperparameters of trained machine learning models, including Optuna, BayesianOpt, and Skopt, has been demonstrated to enhance the predictive capability of the models. Consequently, this results in an improvement in the accuracy of the obtained distributions of the required characteristics.

Research target: Engineering and Technology Mechanics and Mechanical Engineering Natural Sciences
Language: English
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DOI
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Keywords: FEMresidual stressesWire drawingMLPOptunaBayesianOptSkopt
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Added: November 10, 2020
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