Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Gueorgui Mihaylov"'
Autor:
Gueorgui Mihaylov, Matteo Spallanzani
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 4 (2016)
The efficiency behaviour of an industrial plant, part of a huge international structure of plants, is modelled as an emergent phenomenon in a complex adaptive system. The study is based on real in-service data obtained from an industrial production l
Externí odkaz:
https://doaj.org/article/a9d637644fa64fe9853d0efd352c6473
Autor:
Giuseppe Puglisi, Gueorgui Mihaylov, Georgia V Panopoulou, Davide Poletti, Josquin Errard, Paola A Puglisi, Giacomo Vianello
Publikováno v:
Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society, 2022, 511 (2), pp.2052-2074. ⟨10.1093/mnras/stac069⟩
Monthly Notices of the Royal Astronomical Society, 2022, 511 (2), pp.2052-2074. ⟨10.1093/mnras/stac069⟩
Characterizing the sub-mm Galactic emission has become increasingly critical especially in identifying and removing its polarized contribution from the one emitted by the cosmic microwave background (CMB). In this work, we present a parametric foregr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e8735eaf20cc9f27de011a521afe4f4
https://hal.science/hal-03536664
https://hal.science/hal-03536664
Publikováno v:
Advances in Data Analysis and Classification, 16 (3)
In this paper, we describe the fingerprint method, a technique to classify bags of mixed-type measurements. The method was designed to solve a real-world industrial problem: classifying industrial plants (individuals at a higher level of organisation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6925b7d3d34d9058d20d6d9c6df13591
http://hdl.handle.net/11583/2912532
http://hdl.handle.net/11583/2912532
Autor:
Matteo Spallanzani, Gueorgui Mihaylov
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 4 (2016)
The efficiency behaviour of an industrial plant, part of a huge international structure of plants, is modelled as an emergent phenomenon in a complex adaptive system. The study is based on real in-service data obtained from an industrial production l
High-dimensional changepoint analysis is a growing area of research and has applications in a wide range of fields. The aim is to accurately and efficiently detect changepoints in time series data when both the number of time points and dimensions gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5582b1b7d8967646a1e7f59eb287057e
http://arxiv.org/abs/2001.05241
http://arxiv.org/abs/2001.05241
Publikováno v:
Journal of Nondestructive Evaluation. 38
Components made of polymeric composite materials, such as wings and stabilizers of aircrafts, are periodically inspected using non-destructive testing methods. Ultrasonic testing is one of the primary inspection methods applied in the aircraft/aerosp
Publikováno v:
IFAC-PapersOnLine. 48:571-576
An innovative integrated self-learning health monitoring system has been developed and implemented on a fleet of helicopters in actual service. This system improves significantly the efficiency of a previous accelerometric vibrational monitoring tool
A set of logistic mathematical models to estimate the daylight amount and the energy demand for lighting of a room is presented. The models were built upon a database of results obtained for a sample room through Daysim simulations: features such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edaa829450ac5465a655cbccf2da1cd7
http://hdl.handle.net/11583/2683497
http://hdl.handle.net/11583/2683497
Autor:
Gueorgui Mihaylov
Coadjoint orbits for the group SO(6) parametrize Riemannian G-reductions in six dimensions, and we use this correspondence to interpret symplectic fibrations between these orbits, and to analyse moment polytopes associated to the standard Hamiltonian
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0ff5b591fea6f60e3eebf44767640e7