Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Baoming QIAO"'
Autor:
Huaxin Dai, Jinpeng Yang, Lidong Teng, Zhong Wang, Taibo Liang, Waleed Amjad Khan, Ruiwei Yang, Baoming Qiao, Yanling Zhang, Chunlei Yang
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
The lack of irrigation water in agricultural soils poses a significant constraint on global crop production. In-depth investigation into microRNAs (miRNAs) has been widely used to achieve a comprehensive understanding of plant defense mechanisms. How
Externí odkaz:
https://doaj.org/article/bc0c4589aa434137b2ac5ed00e40e432
Autor:
Jinpeng Yang, Di Wan, Baoming Qiao, Jun Yu, Zongping Li, Daisong Liu, Peijun Lv, Jinwen Hu, Xiongfei Rao, Fangsen Xu, Sheliang Wang, Chunlei Yang
Publikováno v:
Agronomy Journal. 115:1265-1278
Publikováno v:
Wuhan University Journal of Natural Sciences. 28:1-10
In this paper, we study the dimension estimate of global attractor for a 3D Brinkman-Forchheimer equation. Based on the differentiability of the semigroup with respect to the initial data, we show that the global attractor of strong solution of the 3
Autor:
Jinpeng Yang, Di Wan, Baoming Qiao, Jun Yu, Zongping Li, Daisong Liu, Peijun Lv, Jinwen Hu, Xiongfei Rao, Fangsen Xu, Sheliang Wang, Chunlei Yang
The harvest time is a key factor for cigar leaves with high quality, which varies greatly depending on the environment. Here, we performed a genome-scale mRNA transcriptomic analysis on the cigar cultivar CX-26 (Nicotiana tabacum L.) to evaluate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71f4c84811a6f96a53a1b217e6cf6797
https://doi.org/10.1101/2022.09.26.509548
https://doi.org/10.1101/2022.09.26.509548
Publikováno v:
3D Imaging Technologies—Multi-dimensional Signal Processing and Deep Learning ISBN: 9789811633904
Buildings extracted from remote sensing images play a crucial part in resource development and urban planning. With the development of convolutional neural networks for the past several years, the use of deep learning to automatically extract feature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f98b56db18a8fed26cfdf041e796f8f
https://doi.org/10.1007/978-981-16-3391-1_21
https://doi.org/10.1007/978-981-16-3391-1_21
Publikováno v:
CIS
In order to improve the classification performance of the speech recognition system, aiming at the problem that the traditional artificial fish swarm algorithm runs the late search blindness, low optimization precision and slow calculation speed, the
Publikováno v:
CIS
In this paper, we propose a mixed conjugate gradient method for unconstrained optimization problem based on the HS method and DY method. The new method has taken advantages of two methods. The global convergence of the mixed conjugate gradient method
Publikováno v:
CIS
The conundrum of the non-convex global optimization is that there are multiple local minima which are not global optimal solution, and conventional algorithms drop into local optimum easily. Filled function method is an available way which generally
Publikováno v:
CIS
In the original algorithm for grey correlation analysis, the detected edge is comparatively rough and the thresholds need determining in advance. Thus, an adaptive edge detection method based on grey correlation analysis is proposed, in which the bas
Autor:
Jing Li, Baoming Qiao
Publikováno v:
CIS
In this paper, we propose a feasible method for solving the NP-hard absolute value equation (AVE) Ax -- |x| = b, which has 2n-solutions. The method mixes differential evolution, K-Means and Simplex Search Method together and achieves an effective bal