Zobrazeno 1 - 10
of 210
pro vyhledávání: '"See Kiong Ng"'
Publikováno v:
Actuators, Vol 13, Iss 9, p 357 (2024)
Truck cranes, which are crucial construction equipment, need to maintain good operational performance to ensure safe use. However, the complex and ever-changing working conditions they face often make it challenging to test their performance effectiv
Externí odkaz:
https://doaj.org/article/255127f6d5fc4fd08ce30843d3d7873f
Publikováno v:
Actuators, Vol 13, Iss 4, p 121 (2024)
Bearing fault diagnosis is a pivotal aspect of monitoring rotating machinery. Recently, numerous deep learning models have been developed for intelligent bearing fault diagnosis. However, these models have typically been established based on two key
Externí odkaz:
https://doaj.org/article/a1604e439e36465aaf598b6d5c999e90
Publikováno v:
Actuators, Vol 13, Iss 1, p 38 (2024)
The hydraulic pump plays a pivotal role in engineering machinery, and it is essential to continuously monitor its operating status. However, many vital signals for monitoring cannot be directly obtained in practical applications. To address this, we
Externí odkaz:
https://doaj.org/article/b47683ce60cc459b8e71ca1adbad8f59
Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarra
Autor:
Ying Zhang, Yifang Yin, Roger Zimmermann, Guanfeng Wang, Jagannadan Varadarajan, See-Kiong Ng
Publikováno v:
IEEE Access, Vol 8, Pp 176704-176716 (2020)
Location-based service significantly relies on accurate and up-to-date maps. The conventional map generation involves labor-intensive and time-consuming manual efforts, which restricts the map-update frequency to a few years or even longer. In recent
Externí odkaz:
https://doaj.org/article/80b4160726ac468cbdd2d9d43894ed95
Publikováno v:
Mathematics, Vol 10, Iss 21, p 3953 (2022)
Traditional data-driven intelligent fault diagnosis methods have been successfully developed under the closed set assumption (CSA). CSA-based fault diagnosis assumes that the fault types in the test set are consistent with that in the training set, w
Externí odkaz:
https://doaj.org/article/67222990de974f5ab2924b91440469ae
Publikováno v:
Mathematics, Vol 10, Iss 21, p 3970 (2022)
Benefiting extensively from the Internet of Things (IoT) and sensor network technologies, the modern smart building achieves thermal comfort. It prevents energy wastage by performing automatic Fault Detection and Diagnosis (FDD) to maintain the good
Externí odkaz:
https://doaj.org/article/db9432345ce04c0e817337e7d803341a
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 4 (2021)
Externí odkaz:
https://doaj.org/article/190b7dcbc901451095c9be79881593a5
Publikováno v:
IEEE Access, Vol 6, Pp 66367-66384 (2018)
Traditional intelligent fault diagnosis works well when the labeled training data (source domain) and unlabeled testing data (target domain) are drawn from the same distribution. However, in many real-world applications, the working conditions can va
Externí odkaz:
https://doaj.org/article/ba20ce8ed14e42efb511f0d9d3770f60
Publikováno v:
Knowledge and Information Systems. 65:1221-1242
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e844269ca72e401cd509e1d7cdd833a0
https://doi.org/10.1007/s10115-022-01793-3
https://doi.org/10.1007/s10115-022-01793-3