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pro vyhledávání: '"Duarte, Marcus"'
The monitoring of rotating machinery has now become a fundamental activity in the industry, given the high criticality in production processes. Extracting useful information from relevant signals is a key factor for effective monitoring: studies in t
Externí odkaz:
http://arxiv.org/abs/2212.01852
Artificial Intelligence (AI) is one of the approaches that has been proposed to analyze the collected data (e.g., vibration signals) providing a diagnosis of the asset's operating condition. It is known that models trained with labeled data (supervis
Externí odkaz:
http://arxiv.org/abs/2210.02974
Estudamos neste trabalho as propriedades globais dos superaglomerados de galáxias com uma amostra de galáxias observadas espectroscopicamente pelo Sloan Digital Sky Survey (SDSS). Nossa amostra limitada em volume possui 121.002 galáxias com $M_r
The monitoring of rotating machinery is an essential task in today's production processes. Currently, several machine learning and deep learning-based modules have achieved excellent results in fault detection and diagnosis. Nevertheless, to further
Externí odkaz:
http://arxiv.org/abs/2102.11848
Publikováno v:
In ISA Transactions September 2024
Autor:
Retsi, Vasiliki, Alfenas Duarte, Marcus, Boonen, Sten, Vangansbeke, Dominiek, Pekas, Apostolos
Publikováno v:
In Biological Control December 2023 187
Publikováno v:
In Expert Systems With Applications 1 December 2023 232
Autor:
Brito, Lucas Costa, Gomes, Milla Caroline, de Oliveira, Déborah, Bacci da Silva, Márcio, Viana Duarte, Marcus Antonio
Publikováno v:
In Precision Engineering January 2023 79:7-15
Akademický článek
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Autor:
Brouwer, Margot M., Demchenko, Vasiliy, Harnois-Déraps, Joachim, Bilicki, Maciej, Heymans, Catherine, Hoekstra, Henk, Kuijken, Konrad, Alpaslan, Mehmet, Brough, Sarah, Cai, Yan-Chuan, Costa-Duarte, Marcus V., Dvornik, Andrej, Erben, Thomas, Hildebrandt, Hendrik, Holwerda, Benne W., Schneider, Peter, Sifón, Cristóbal, van Uitert, Edo
Publikováno v:
MNRAS, Volume 481, Issue 4, 21 December 2018, Pages 5189-5209
We study projected underdensities in the cosmic galaxy density field known as 'troughs', and their overdense counterparts, which we call 'ridges'. We identify these regions using a bright sample of foreground galaxies from the photometric Kilo-Degree
Externí odkaz:
http://arxiv.org/abs/1805.00562