Zobrazeno 1 - 10
of 20 561
pro vyhledávání: '"Leakage detection"'
Early detection of fuel leakage at service stations with underground petroleum storage systems is a crucial task to prevent catastrophic hazards. Current data-driven fuel leakage detection methods employ offline statistical inventory reconciliation,
Externí odkaz:
http://arxiv.org/abs/2410.09741
Autor:
Wei, Qian1,2 (AUTHOR) 2022345703@student.cup.edu.cn, Sun, Hongjun1 (AUTHOR) sunhj68@cup.edu.cn, Xu, Yin2 (AUTHOR) gaofeixiang01@cnpc.com.cn, Pang, Zisheng2 (AUTHOR), Gao, Feixiang2 (AUTHOR)
Publikováno v:
Energies (19961073). Nov2024, Vol. 17 Issue 22, p5633. 20p.
Autor:
Sutherland, R. Tyler
We discuss a general technique for using quantum logic spectroscopy to perform quantum non-demolition (QND) measurements that determine which of two subspaces a logic ion is in. We then show how to use the scheme to perform high fidelity state prepar
Externí odkaz:
http://arxiv.org/abs/2410.23531
Optically trapped atoms in arrays of optical tweezers have emerged as a powerful platform for quantum information processing given the recent demonstrations of high-fidelity quantum logic gates and on-demand reconfigurable geometry. Both in gate oper
Externí odkaz:
http://arxiv.org/abs/2410.23430
Autor:
Babu, Md Abu Ahammed, Pandey, Sushant Kumar, Durisic, Darko, Koppisetty, Ashok Chaitanya, Staron, Miroslaw
Data leakage is a very common problem that is often overlooked during splitting data into train and test sets before training any ML/DL model. The model performance gets artificially inflated with the presence of data leakage during the evaluation ph
Externí odkaz:
http://arxiv.org/abs/2410.23312
Autor:
Luo, Juan1 (AUTHOR) luojuan@hnu.edu.cn, Wang, Chongxiao2 (AUTHOR) wang_chongxiao@cfar.a-star.edu.sg, Yang, Jielong3 (AUTHOR) jyang@jiangnan.edu.cn, Zhong, Xionghu1 (AUTHOR) luojuan@hnu.edu.cn
Publikováno v:
Sensors (14248220). Oct2024, Vol. 24 Issue 19, p6294. 16p.
Autor:
Zhang, Zepeng, Fink, Olga
Detecting and localizing leakages is a significant challenge for the efficient and sustainable management of water distribution networks (WDN). Leveraging the inherent graph structure of WDNs, recent approaches have used graph-based data-driven metho
Externí odkaz:
http://arxiv.org/abs/2408.02797
Publikováno v:
Journal of Xihua University (Natural Science Edition). 2024, Vol. 43 Issue 5, p96-102. 7p.
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