Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Chengxu Yang"'
Publikováno v:
Sensors, Vol 23, Iss 22, p 9105 (2023)
Secure and reliable active debris removal methods are crucial for maintaining the stability of the space environment. Continuum robots, with their hyper-redundant degrees of freedom, offer the ability to capture targets of varying sizes and shapes th
Externí odkaz:
https://doaj.org/article/fd8acb3a16a14d7d8dd678a086d153a6
Publikováno v:
Sensors, Vol 22, Iss 14, p 5081 (2022)
An integrated navigation algorithm based on a multiple fading factors Kalman filter (MFKF) is proposed to solve the problems that the Kalman filtering (KF) algorithm easily brings about diffusion when the model becomes a mismatched or noisy, and the
Externí odkaz:
https://doaj.org/article/ca6d110c78ed4285a44ad00317fc8453
Publikováno v:
International Journal of Research -GRANTHAALAYAH. 10:99-111
Gutman proposed a new alternative interpretation of vertex-degree-based topological index, called Sombor index. It is defined via the term . In this paper, we determine the explicit expressions of Sombor index for line and total graphs and several pe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f3aa93102d79f5d93f2566657435757
https://doi.org/10.29121/granthaalayah.v10.i8.2022.4730
https://doi.org/10.29121/granthaalayah.v10.i8.2022.4730
Autor:
Wengang Zhang, Ling Zou, Yan Wang, Jianping Liu, Chengxu Yang, Jianping Di, Haiyang Hu, Zhuang Yang
Publikováno v:
Arabian Journal for Science and Engineering. 47:12521-12533
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::560b044878d649c3eabc8a0c23422626
https://doi.org/10.1007/s13369-021-06550-2
https://doi.org/10.1007/s13369-021-06550-2
Autor:
Chengxu Yang, Mengwei Xu, Qipeng Wang, Zhenpeng Chen, Kang Huang, Yun Ma, Kaigui Bian, Gang Huang, Yunxin Liu, Xin Jin, Xuanzhe Liu
Publikováno v:
IEEE Transactions on Mobile Computing. :1-18
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91a93f3b90e9ac8e79714cad75fce9aa
https://doi.org/10.1109/tmc.2022.3214234
https://doi.org/10.1109/tmc.2022.3214234
Autor:
Jian Wang, Jingchun Chen, Haiwei Chen, Siyuan Wang, Boxin Xue, Zedong Zhao, Jiandong Huang, Jiaolong Ren, Yinshan Xu, Chengxu Yang
Publikováno v:
Materials, Vol 14, Iss 6144, p 6144 (2021)
Materials
Volume 14
Issue 20
Materials
Volume 14
Issue 20
Cement grouting material is one of the most important materials in civil construction at present, for seepage prevention, rapid repair, and reinforcement. To achieve the ever-increasing functional requirements of civil infrastructures, cement groutin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d33164efc5154eea648f3f27ef1e17b
https://www.mdpi.com/1996-1944/14/20/6144
https://www.mdpi.com/1996-1944/14/20/6144
Autor:
Jiaolong, Ren, Zedong, Zhao, Yinshan, Xu, Siyuan, Wang, Haiwei, Chen, Jiandong, Huang, Boxin, Xue, Jian, Wang, Jingchun, Chen, Chengxu, Yang
Publikováno v:
Materials
Cement grouting material is one of the most important materials in civil construction at present, for seepage prevention, rapid repair, and reinforcement. To achieve the ever-increasing functional requirements of civil infrastructures, cement groutin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::e6cbeecc6357aa9ed6695801ec0e167f
https://pubmed.ncbi.nlm.nih.gov/34683736
https://pubmed.ncbi.nlm.nih.gov/34683736
Publikováno v:
ESEC/SIGSOFT FSE
Big data has become valuable property for enterprises and enabled various intelligent applications. Today, it is common to host data in big data platforms (e.g., Spark), where developers can submit scripts to process the original and intermediate dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f22552b880f72b1c11cce4c410134801
https://doi.org/10.1145/3468264.3468532
https://doi.org/10.1145/3468264.3468532
Autor:
Chengxu, Yang
Publikováno v:
Studia Diplomatica, 1996 Jan 01. 49(4/5), 9-18.
Externí odkaz:
https://www.jstor.org/stable/44837536
Publikováno v:
WWW
Federated learning (FL) is an emerging, privacy-preserving machine learning paradigm, drawing tremendous attention in both academia and industry. A unique characteristic of FL is heterogeneity, which resides in the various hardware specifications and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::140a195803dce4d1c958b050cf756b14
http://arxiv.org/abs/2006.06983
http://arxiv.org/abs/2006.06983
