Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Amer AlGhadhban"'
Autor:
Abderrahim Allal, Zakaria Lammouchi, Abderrahmane Khechekhouche, Naoui Mohamed, Khalid Alqunun, Amer Alghadhban, Ismail Marouani, Tawfik Guesmi
Publikováno v:
IEEE Access, Vol 12, Pp 143515-143530 (2024)
Induction motors, known for their reliability and efficiency, are widely used in various industrial applications. However, their susceptibility to failure, particularly in harsh environments, poses significant operational challenges. Early detection
Externí odkaz:
https://doaj.org/article/acabd0ff929147c8ad250f0163325832
Publikováno v:
Systems, Vol 11, Iss 9, p 482 (2023)
Free Space Optical Communication (FSO) is a promising technology to address wired Data Center Network (DCN) challenges like power consumption, low scalability and flexibility, congestion and cabling. Scholars have developed indirect line-of-sight (Lo
Externí odkaz:
https://doaj.org/article/2a51cc07d64e4914a8f03f96fcffe5a7
Publikováno v:
IEEE Access, Vol 10, Pp 15845-15859 (2022)
We propose in this work to employ the Box-LASSO, a variation of the popular LASSO method, as a low-complexity decoder in a massive multiple-input multiple-output (MIMO) wireless communication system. The Box-LASSO is mainly useful for detecting simul
Externí odkaz:
https://doaj.org/article/02bd9e31ae5c4dcb94a423296dd30837
Autor:
Hassan Ali, Muhammad Suleman Khan, Amer Alghadhban, Meshari Alazmi, Ahmad Alzamil, Khaled Al-Utaibi, Junaid Qadir
Publikováno v:
IEEE Access, Vol 9, Pp 81678-81692 (2021)
With the hyperconnectivity and ubiquity of the Internet, the fake news problem now presents a greater threat than ever before. One promising solution for countering this threat is to leverage deep learning (DL)-based text classification methods for f
Externí odkaz:
https://doaj.org/article/4b05e66a03f749f598f6c00a58e6da06
Autor:
Amer AlGhadhban, Ahmad Showail
Publikováno v:
Systems, Vol 10, Iss 5, p 165 (2022)
Middleboxes are critical components in today’s networks. Due to the variety of network/security policies and the limitations of routing protocols, middleboxes are installed in multiple physical locations to face high traffic with few considerations
Externí odkaz:
https://doaj.org/article/e3c43fe8a8dc4ade88266c33c3d26dbc
Publikováno v:
IEEE Access, Vol 7, Pp 10515-10522 (2019)
In this paper, we analyze a delay-sensitive underwater wireless optical network used for livevideo applications. The video streams are generated at the sender and are transmitted through underwater multi-channel paths that span over several meters of
Externí odkaz:
https://doaj.org/article/94901d93fb7c48258058536ee38c559e
Publikováno v:
Mathematics, Vol 10, Iss 15, p 2721 (2022)
Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a chal
Externí odkaz:
https://doaj.org/article/8153719d093d4bfd803c04ea0f0461f1
Publikováno v:
Mathematics, Vol 10, Iss 14, p 2510 (2022)
In recent years, the occurrence of cascading failures and blackouts arising from cyber intrusions in the underlying configuration of power systems has increasingly highlighted the need for effective power management that is able to handle this issue
Externí odkaz:
https://doaj.org/article/a652fc0f1572431abce4b292d8b0e1d1
Autor:
Hafiza Tayyaba Shahzadi, Saman Fatima, Naseem Akhter, Meshari Alazmi, Alshammari Nawaf, Kamaleldin B. Said, Amer AlGhadhban, Abdel Moneim E. Sulieman, Rahman Shah Zaib Saleem, Ghayoor Abbas Chotana
Publikováno v:
ACS Omega. 7:11460-11472
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b71b369bcef9a007449e55ab2f36537
https://doi.org/10.1021/acsomega.2c00773
https://doi.org/10.1021/acsomega.2c00773
Autor:
Junaid Qadir, Khaled AlUtaibi, Ahmad Alzamil, Meshari Alazmi, Amer AlGhadhban, Adnan Qayyum, Rana Tallal Javed, Hassan Ali
Recent works have highlighted how misinformation is plaguing our online social networks. Numerous algorithms on automated misinformation detection are centered around deep learning~(DL) which requires large data for training. However, privacy and eth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::338a91bbb1814666e2ef23b96ac7ad07
https://doi.org/10.36227/techrxiv.19351679.v2
https://doi.org/10.36227/techrxiv.19351679.v2
