Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Shi-jian Li"'
Publikováno v:
Metals, Vol 8, Iss 11, p 868 (2018)
Simultaneously improving the toughness and strength of B-microalloyed steel by adding microalloying elements (Nb, V, Ti) has been an extensively usedmethod for researchers. However, coarse Ti(C, N) particle will precipitate during solidification with
Externí odkaz:
https://doaj.org/article/5ebf40a2ace94174b82373af13a3c250
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Access, Vol 12, Pp 76735-76743 (2024)
Dental triangular mesh is widely used in computer-aided oral medicine. Different from regular data such as digital images, the structure of triangular mesh is more complex, and traditional operations such as convolution cannot be directly applied. Th
Externí odkaz:
https://doaj.org/article/56ca089c75704c43861c186f86b44a67
Publikováno v:
Zhonghua nan ke xue = National journal of andrology. 26(10)
To investigate the relationship between the apparent diffusion coefficient (ADC) histogram parameters based on the whole tumor and the pathological grade and lymph node metastasis (LNM) of PCa.This retrospective study included 82 cases of PCa confirm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8371e251b4a7cf9370414a142d6e469a
https://pubmed.ncbi.nlm.nih.gov/33382218
https://pubmed.ncbi.nlm.nih.gov/33382218
Autor:
Shilu TONG, Ya-Bin HU, Fan JIANG, Shi-Jian LIU, Jian-Guo TAN, Guang-Jun YU, Chong-Huai YAN, Sheng-Hui LI, Yong YIN
Publikováno v:
Advances in Climate Change Research, Vol 14, Iss 4, Pp 587-591 (2023)
It is important to identify atmospheric environmental drivers of childhood asthma because asthma is the most common chronic disease in children globally. We provided an overview of the impacts of exposure to atmospheric environmental factors (e.g., m
Externí odkaz:
https://doaj.org/article/808eb309936a4e679bf2ce4779c628aa
Publikováno v:
Computational Intelligence and Neuroscience, Vol 2018 (2018)
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience
Extreme learning machine algorithm proposed in recent years has been widely used in many fields due to its fast training speed and good generalization performance. Unlike the traditional neural network, the ELM algorithm greatly improves the training
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b932c50ee009d8b5af9f9429da104fb
https://doaj.org/article/620d863e9d014a02808f88717c45c251
https://doaj.org/article/620d863e9d014a02808f88717c45c251
Publikováno v:
Applied Mechanics and Materials. 685:182-186
In this paper, a new rotor with two impact in the vertical shaft impact crusher is analyzed, an effect of the angle at the guide device thrown materials on the velocity that material reach the impact plate and rebound to a anvil in the crushing chamb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c32f93dcdc39175e1e7135db5d08ddb
https://doi.org/10.4028/www.scientific.net/amm.685.182
https://doi.org/10.4028/www.scientific.net/amm.685.182
Publikováno v:
Applied Mechanics and Materials. :150-153
This paper designed an impact testing machine to observe the movement characteristics of particles. We simulated the rotor with different blanking frequency and different rotating speed by EDEM to explore the acceleration of the rotor. Through simula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a10e49bdc1bfc901e4a8102db5cdbeeb
https://doi.org/10.4028/www.scientific.net/amm.543-547.150
https://doi.org/10.4028/www.scientific.net/amm.543-547.150
Publikováno v:
Advanced Materials Research. 853:494-499
With the aid of discrete element software EDEM simulation under the same size, the acceleration of particles under different channel model and speed, and analyze the throwing speed and force. The result show that speed is important influence factors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::792414f0569180c5d812a4bd7eb89cf2
https://doi.org/10.4028/www.scientific.net/amr.853.494
https://doi.org/10.4028/www.scientific.net/amr.853.494