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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.
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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Обзор подходов к определению и решению проблемы взаимодействия маркетинга и логистики торгового предприятия

Научно-технические ведомости Санкт-Петербургского государственного политехнического университета. Экономические науки. 2015. Т. 233. № 6. С. 123–137.
Ильин И. В., Рыбаков Д. С.

Logistics has passed a long way of development, transformed from one of the directions of marketing activity into an independent field of activity, providing competitive advantages to companies. Nevertheless, marketing and logistics still remain interrelated and interdependent. The problems of interaction between marketing and logistics are recognized by the scientific community, as evidenced by a large amount of materials dedicated to this topic. The aim of the present study is the specification and definition of the problem of cross-functional coordination of marketing and logistics at a trade enterprise, and also defining its solution direction. The study conducted a retrospective analysis of the development of logistics as a scientific and practical field of activity connected to marketing. Various points of view on the mechanism of interaction between marketing and logistics are examined. The most significant obstacles to the coordination of marketing and logistics, often cited in scientific literature, have been identified. Mathematical methods applied for searching for optimal solutions in the logistics systems of enterprises and supply chains have been analyzed. The research was based on the study of Russian and foreign literature sources. As a result, it has been established that marketing determines the level of customer service by setting up the values of a number of indicators which reveal the marketing mix. Some of these indicators are also indicators of the services provided by logistics. The problem consists in the lack of a mathematical model optimizing the values of logistics service indicators. Optimal values are understood as indicator values yielding maximum profit. The problem can be solved through using the methods of mathematical programming. Further research is required, aimed at creating integrated optimization models of logistics systems of trade enterprises, taking into account the marketing solutions and the logistics possibilities. The application of mathematical methods provides a systematic approach to solving the problem, since it takes into account the widely known obstacles of cross-functional coordination and helps eliminate them.

Research target: Economics and Management
Priority areas: management
Language: Russian
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DOI
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Keywords: логистикамаркетингоптимизациялогистический сервисуровень обслуживания
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