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Wyszukujesz frazę "Zhao, Shan" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Comparative effectiveness of biochar derived from tropical feedstocks on the adsorption for ammonium, nitrate and phosphate
Autorzy:
Zou, Ganghua
Shan, Ying
Dai, Minjie
Xin, Xiaoping
Nawaz, Muhammad
Zhao, Fengljang
Powiązania:
https://bibliotekanauki.pl/articles/2203133.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
nutrients
soil amendment
adsorption model
biochars
tropical feedstock
składniki odżywcze
model adsorpcji
odżywianie gleby
biowęgle
surowce tropikalne
Opis:
Biochar has been extensively studied as a soil amendment to reduce nutrients losses. However, the comparative effectiveness of biochar adsorption capacity for ammonium (NH4 -N), nitrate (NO3 -N), and phosphate (PO4-P) remains unknown. In the present study, the effects of feedstock (banana stem and coconut shell) and temperature (300, 500, and 700°C) on biochar adsorption ability for NH4-N, NO3-N, and PO4-P were investigated and fitted by three adsorption models, viz Freundlich, Langmuir, and linear. Freundlich (R2 = 0.95–0.99) and Langmuir (R2 = 0.91–0.95) models were found suitable for adsorption of NH4 -N. The maximum adsorption capacity (Qm) for coconut shell biochar increased with pyrolysis temperature (Qm = 12.8–15.5 mg g-1) and decreased for banana stem biochar (Qm = 12.9–9.7 mg g-1). In the case of NO3 -N adsorption, Freundlich (R2 = 0.82–0.99) and linear model (R2 = 1.00) were found suitable while Langmuir model showed much less contribution, similarly adsorption of PO4-P, was not supported by these three models. The minimum concentrations required for adsorption of phosphate were recorded as 36, 8, and 3 mg L-1 using pyrolyzed biochar at the temperatures of 300, 500, and 700°C, respectively. These results indicate that the feedstock and pyrolysis temperature, as well as aquatic nutrient concentration, were important factors for the adsorption of inorganic nitrogen and phosphorus.
Źródło:
Archives of Environmental Protection; 2022, 48, 4; 25--34
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
RFID tag group recognition based on motion blur estimation and YOLOv2 improved by Gaussian algorithm
Autorzy:
Li, Lin
Yu, Xiao-Lei
Liu, Zhen-Lu
Zhao, Zhi-Min
Zhang, Ke
Zhou, Shan-Hao
Powiązania:
https://bibliotekanauki.pl/articles/2051852.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
RFID
YOLOv2
neural network
GRNN
Opis:
Effective recognition of tags in the dynamic measurement system would significantly improve the reading performance of the tag group, but the blurred outline and appearance of tag images captured in motion seriously limit the effectiveness of the existing tag group recognition. Thus, this paper proposes passive tag group recognition in the dynamic environment based on motion blur estimation and improved YOLOv2. Firstly, blur angles are estimated with a Gabor filter, and blur lengths are estimated through nonlinear modelling of a Generalized Regression Neural Network (GRNN). Secondly, tag recognition based on YOLOv2 improved by a Gaussian algorithm is proposed. The features of the tag group are analyzed by the Gaussian algorithm, the region of interest of the dynamic tag is effectively framed, and the tag foreground is extracted; Secondly, the data set of tag groups are trained by the end-to-end YOLOv2 algorithm for secondary screening and recognition, and finally the specific locations of tags are framed to meet the effective identification of tag groups in different scenes. A considerable number of experiments illustrate that the fusion algorithm can significantly improve recognition accuracy. Combined with the reading distance, the research presented in this paper can more accurately optimize the three-dimensional structure of the tag group, improve the reading performance of the tag group, and avoid the interference and collision of tags in the communication channel. Compared with the previous template matching algorithm, the tag group recognition ability put forward in this paper is improved by at least 13.9%, and its reading performance is improved by at least 6.2% as shown in many experiments.
Źródło:
Metrology and Measurement Systems; 2022, 29, 1; 53-74
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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