Zobrazeno 1 - 10
of 605
pro vyhledávání: '"Alghamdi, Ahmed"'
Autor:
Alghamdi Ahmed
Publikováno v:
Polish Journal of Chemical Technology, Vol 26, Iss 2, Pp 1-7 (2024)
Seawater Desalination uses hydrophobic membranes. Many techniques have been developed to improve membrane hydrophobicity by depositing particles on the membrane surface. In this study, a nanocomposite membrane utilizing Triethylenetetramine (TETA) is
Externí odkaz:
https://doaj.org/article/df7a67885126425689f8285c123f972b
Autor:
AlGhamdi, Ahmed Saeed1 (AUTHOR) asjannah@tu.edu.sa
Publikováno v:
Traitement du Signal. Jun2024, Vol. 41 Issue 3, p1245-1262. 18p.
Autor:
Dizaji, Hamed Sadighi, Alghamdi, Ahmed, Aldawi, Fayez, Alqahtani, Sultan, Alshehery, Sultan, Anqi, Ali E.
Publikováno v:
In Applied Thermal Engineering 15 May 2024 245
Autor:
Al-Zahrani, Ibrahim A., Aljabri, Ahmed, Alhazmi, Wafaa A., Yasir, Muhammad, Abujamel, Turki, Alghamdi, Ahmed K., Azhar, Esam I.
Publikováno v:
In Journal of Infection and Public Health April 2024 17(4):669-675
Autor:
Luo, Jie, Alghamdi, Ahmed, Aldawi, Fayez, Moria, Hazim, Mouldi, Abir, Loukil, Hassen, Deifalla, Ahmed Farouk, Ghoushchi, S.P.
Publikováno v:
In Case Studies in Thermal Engineering January 2024 53
Autor:
Shi, Lu-min, Alghamdi, Ahmed, Ponnore, Joffin Jose, Alqahtani, Sultan, Alshehery, Sultan, Anqi, Ali E.
Publikováno v:
In Applied Thermal Engineering 25 November 2023 235
Autor:
Balkhi, Bander, Alghamdi, Ahmed, Alqahtani, Saeed, Al Najjar, Marwan, Al Harbi, Abdullah, Bin Traiki, Thamer
Publikováno v:
In Saudi Pharmaceutical Journal November 2023 31(11)
Autor:
Alghamdi, Ahmed
Publikováno v:
In South African Journal of Chemical Engineering October 2023 46:386-393
Autor:
Atta, Ihab Shafek, Elnady, Mohamed R., Alghamdi, Ali G., Alghamdi, Ahmed Hassan, Aboulata, Alaa A., Shatla, Ibrahim M.
Publikováno v:
In Heliyon May 2023 9(5)
Autor:
Alghamdi, Ahmed, Hammad, Mohamed, Ugail, Hassan, Abdel-Raheem, Asmaa, Muhammad, Khan, Khalifa, Hany S., El-Latif, Ahmed A. Abd
In this paper, an effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart cities. Two types of transfer learning techniques are employed to retrain the
Externí odkaz:
http://arxiv.org/abs/1906.09358