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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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О сложности построения 3-раскраски с короткими гранями

Журнал Средневолжского математического общества. 2018. Т. 20. № 2. С. 199–205.
Sirotkin D.

The vertex 3-colourability problem is to determine for a given graph whether one can divide its vertex set into three subsets of pairwise non-adjacent vertices. This problem is NP-complete in the class of planar graphs, but it becomes polynomial-time solvable for planar triangulations, i.e. planar graphs, all facets of which (including external) are triangles. Additionally, the problem is NP-complete for planar graphs whose vertices have degrees at most 4, but it becomes linear-time solvable for graphs whose vertices have maximal degree at most 3. So it is an interesting question to nd a threshold for lengths of facets and maximum vertex degree, for which the complexity of the vertex 3-colourability changes from polynomial-time solvability to NP-completeness. In this paper we answer this question and prove NP-completeness of the vertex 3-colourability problem in the class of planar graphs of the maximum vertex degree at most 5, whose facets are triangles and quadrangles only.

Research target: Mathematics
Priority areas: IT and mathematics
Language: Russian
Full text
DOI
Keywords: вычислительная сложностьplanar graphпланарный графComputational ComplexityVertex 3-colorability problem
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