Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Jiaji Luo"'
Publikováno v:
Earthquake Research Advances, Vol 4, Iss 3, Pp 100307- (2024)
We employ the block negative dislocation model to invert the distribution of fault coupling and slip rate deficit on the different segments of the Tanlu (Tancheng-Lujiang) fault zone, according to the GPS horizontal velocity field from 1991 to 2007 (
Externí odkaz:
https://doaj.org/article/a15e0fea268441c88d43d03f4ef53a2c
Autor:
Yonglin Chen, Keer Yang, Mingxin Xu, Yishuo Zhang, Xiquan Weng, Jiaji Luo, Yanshuo Li, Yu-Heng Mao
Publikováno v:
Nutrients, Vol 16, Iss 11, p 1634 (2024)
The intestinal tract of humans harbors a dynamic and complex bacterial community known as the gut microbiota, which plays a crucial role in regulating functions such as metabolism and immunity in the human body. Numerous studies conducted in recent d
Externí odkaz:
https://doaj.org/article/8e2025fe2f714001b39e38b7d9199bf0
Publikováno v:
IET Radar, Sonar & Navigation, Vol 16, Iss 5, Pp 786-798 (2022)
Abstract The electromagnetic environment of modern battlefields becomes increasingly complex, and radar receivers may receive multiple radar signals simultaneously. However, current deep learning models can only predict a single class and cannot reco
Externí odkaz:
https://doaj.org/article/f51d8078601848578ee40dfa40e20731
Autor:
Lingli Li, Huajian Yao, Bing Zhang, Junhui Li, Peng Shu, Yuanyuan Yang, Xiaoli Wang, Dongrui Zhou, Peng Zhao, Jiaji Luo
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Huoshan “seismic window” is located in the northern margin of the Dabie Orogen belt, the contact zone between North China and the Yangtze plate, where the seismic activity is mainly concentrated in this area. Small earthquake swarms in this regio
Externí odkaz:
https://doaj.org/article/d96d8a3d5058435e9e40a22cec90746b
Publikováno v:
Electronics Letters, Vol 58, Iss 12, Pp 480-482 (2022)
Abstract As the electromagnetic environment becomes increasingly complex, the radar receivers may receive multiple radar signals simultaneously. However, the current radar signal recognition algorithm based on deep learning can only predict a single
Externí odkaz:
https://doaj.org/article/8f170a618f1a4a858362bb9ab0de8a9b
Autor:
Chenxia Wan, Liqun Fang, Shaodong Cao, Jiaji Luo, Yijing Jiang, Yuanxiao Wei, Cancan Lv, Weijian Si
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 44:3107-3114
The investigation on brain magnetic resonance imaging (MRI) of cerebral small vessel disease (CSVD) classification algorithm based on deep learning is particularly important in medical image analyses and has not been reported. This paper proposes an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04faade90c13594ec2c2378f1bde6ca9
https://doi.org/10.3233/jifs-213212
https://doi.org/10.3233/jifs-213212
Publikováno v:
IET Radar, Sonar & Navigation. 16:1641-1655
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7aac48e46c4aa8976dce6a70873e99c5
https://doi.org/10.1049/rsn2.12286
https://doi.org/10.1049/rsn2.12286
The central and southern sections of the Tanlu fault zone experience frequent seismic activity and have a dense population distribution. Infrastructure, such as high-speed rail and the South–North Water Diversion project, as well as world heritage
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::064e71eb6571b78f7cef4d1433ba2b55
https://doi.org/10.21203/rs.3.rs-2955801/v1
https://doi.org/10.21203/rs.3.rs-2955801/v1
The central and southern section of Tanlu fault zone is a section with frequent seismic activity and dense population distribution.Along the fault are infrastructure such as high-speed rail and the South-north Water Diversion project, as well as worl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a858f2e1fbe0a72e561bb794b1038e2d
https://doi.org/10.21203/rs.3.rs-2822849/v1
https://doi.org/10.21203/rs.3.rs-2822849/v1
Publikováno v:
Journal of Sensors. 2022:1-13
The recognition technology of the radar signal modulation mode plays a critical role in electronic warfare, and the algorithm based on deep learning has significantly improved the recognition accuracy of radar signals. However, the convolutional neur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::481a969d8668f5882c54c85e8c2dc91a
https://doi.org/10.1155/2022/9970879
https://doi.org/10.1155/2022/9970879