Zobrazeno 1 - 10
of 798
pro vyhledávání: '"LI Yuyan"'
Publikováno v:
Di-san junyi daxue xuebao, Vol 44, Iss 8, Pp 829-834 (2022)
Objective To investigate the impact of chronic endometritis (CE) on pregnancy outcome in patients with assisted reproduction and to evaluate the clinical significance of normative therapy. Methods A retrospective analysis was performed on infertile p
Externí odkaz:
https://doaj.org/article/6295542337b84c46a1f641b4a8b99bcd
Publikováno v:
Di-san junyi daxue xuebao, Vol 44, Iss 5, Pp 484-488 (2022)
Objective To analyze and compare the clinical features and outcomes of in vitro fertilization-embryo transfer (IVF-ET) cycles in normal responders using gonadotrophin (Gn) releasing hormone (GnRH) antagonist or GnRH agonist long protocol. Methods The
Externí odkaz:
https://doaj.org/article/abcb00ea6d954a00a383f0aec7ea62ba
Autor:
Li, Yuyan
This review explores the application of intelligent optimization algorithms to Multi-Objective Optimal Power Flow (MOPF) in enhancing modern power systems. It delves into the challenges posed by the integration of renewables, smart grids, and increas
Externí odkaz:
http://arxiv.org/abs/2404.09203
In the Coded Aperture Snapshot Spectral Imaging (CASSI) system, deep unfolding networks (DUNs) have demonstrated excellent performance in recovering 3D hyperspectral images (HSIs) from 2D measurements. However, some noticeable gaps exist between the
Externí odkaz:
http://arxiv.org/abs/2311.08808
Autor:
Li, Yuyan
Transformer fault diagnosis (TFD) is a critical aspect of power system maintenance and management. This review paper provides a comprehensive overview of the current state of the art in TFD using artificial intelligence (AI) and dissolved gas analysi
Externí odkaz:
http://arxiv.org/abs/2304.11880
To acquire a snapshot spectral image, coded aperture snapshot spectral imaging (CASSI) is proposed. A core problem of the CASSI system is to recover the reliable and fine underlying 3D spectral cube from the 2D measurement. By alternately solving a d
Externí odkaz:
http://arxiv.org/abs/2211.06891
In this paper, we present a comprehensive point cloud semantic segmentation network that aggregates both local and global multi-scale information. First, we propose an Angle Correlation Point Convolution (ACPConv) module to effectively learn the loca
Externí odkaz:
http://arxiv.org/abs/2206.13628
Publikováno v:
In Journal of Alloys and Compounds 25 December 2024 1009
Publikováno v:
In MethodsX December 2024 13
Publikováno v:
In ISA Transactions December 2024 155:261-273