Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Madini O. Alassafi"'
Autor:
Madini O. Alassafi, Wajid Aziz, Rayed AlGhamdi, Abdulrahman A. Alshdadi, Malik Sajjad Ahmed Nadeem, Ishtiaq Rasool Khan, Adel Bahaddad, Ali Altalbe, Nabeel Albishry
Publikováno v:
Journal of Infection and Public Health, Vol 17, Iss 4, Pp 601-608 (2024)
Background: Coronavirus disease 2019 (COVID-19) is a respiratory illness that leads to severe acute respiratory syndrome and various cardiorespiratory complications, contributing to morbidity and mortality. Entropy analysis has demonstrated its abili
Externí odkaz:
https://doaj.org/article/5fdc5a09d6514578bfa49d4d37679de3
Autor:
Xin Wang, Dongsheng Yang, D Raveena Judie Dolly, Shuang Chen, Madini O. Alassafi, Fawaz E. Alsaadi, Jianhui Lyu
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 13, Iss 1, Pp 1-17 (2024)
Abstract Research has recently grown on multi-agent systems (MAS) and their coordination and secure cooperative control, for example in the field of edge-cloud computing. MAS offers robustness and flexibility compared to centralized systems by distri
Externí odkaz:
https://doaj.org/article/ed490033691f4a1db69803f98c033e75
Publikováno v:
Mathematics, Vol 12, Iss 7, p 1055 (2024)
Recently, the number of Internet of Things (IoT)-connected devices has increased daily. Consequently, cybersecurity challenges have increased due to the natural diversity of the IoT, limited hardware resources, and limited security capabilities. Intr
Externí odkaz:
https://doaj.org/article/9a32137ae4b24490ac44af6804229032
Publikováno v:
IEEE Access, Vol 11, Pp 99847-99861 (2023)
Depression and anxiety are prevalent mental illnesses that are frequently disregarded as disorders. It is estimated that more than 5% of the population suffers from depression or anxiety. Although there have been a number of studies in these fields,
Externí odkaz:
https://doaj.org/article/7279580a4e4b49b0b5092123fddba62d
Autor:
Madini O. Alassafi, Muhammad Sohail Ibrahim, Imran Naseem, Rayed AlGhamdi, Reem Alotaibi, Faris A. Kateb, Hadi Mohsen Oqaibi, Abdulrahman A. Alshdadi, Syed Adnan Yusuf
Publikováno v:
IEEE Access, Vol 11, Pp 59204-59216 (2023)
Face presentation attack detection (PAD) is considered to be an essential and critical step in modern face recognition systems. Face PAD aims at exposing an imposter or an unauthorized person seeking to deceive the authentication system. Presentation
Externí odkaz:
https://doaj.org/article/65c39ea5422f4aa3965395866b9bb648
Publikováno v:
Digital Communications and Networks, Vol 8, Iss 6, Pp 1122-1129 (2022)
With the rapid development of wireless technologies, wireless access networks have entered their Fifth-Generation (5G) system phase. The heterogeneous and complex nature of a 5G system, with its numerous technological scenarios, poses significant cha
Externí odkaz:
https://doaj.org/article/d53e65621c0e44d08d89b60dd3d62736
Autor:
Muhammad Javed Iqbal, Muhammad Aasem, Iftikhar Ahmad, Madini O. Alassafi, Sheikh Tahir Bakhsh, Neelum Noreen, Ahmed Alhomoud
Publikováno v:
Foods, Vol 12, Iss 21, p 3993 (2023)
Rice is one of the fundamental food items that comes in many varieties with their associated benefits. It can be sub-categorized based on its visual features like texture, color, and shape. Using these features, the automatic classification of rice v
Externí odkaz:
https://doaj.org/article/7a7c7378e6b3427b8363b1585a790817
Publikováno v:
Mathematics, Vol 11, Iss 21, p 4501 (2023)
Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns in network data. To solve this, we present the Hybrid Deep Learning Intrusion Detection Model (HD-
Externí odkaz:
https://doaj.org/article/583c1703068e4f61b5ea89b16073948d
Autor:
Tapotosh Ghosh, Md Istakiak Adnan Palash, Mohammad Abu Yousuf, Md. Abdul Hamid, Muhammad Mostafa Monowar, Madini O. Alassafi
Publikováno v:
Mathematics, Vol 11, Iss 12, p 2633 (2023)
Alzheimer’s disease has become a major concern in the healthcare domain as it is growing rapidly. Much research has been conducted to detect it from MRI images through various deep learning approaches.However, the problems of the availability of me
Externí odkaz:
https://doaj.org/article/ddaf2fd843104c79accd585af185049c
Autor:
Syed Adnan Yusuf, Abdulrahman A. Alshdadi, Rayed Alghamdi, Madini O. Alassafi, David J. Garrity
Publikováno v:
IEEE Access, Vol 8, Pp 98281-98294 (2020)
This work presents an artificial neural network-based linearly regressive technique for the prediction of a temperature rise event caused by a fire in enclosed building environments. The method predicts temperature range in a burning compartment base
Externí odkaz:
https://doaj.org/article/d41600ada328414f896f061a96432bc6