Zobrazeno 1 - 5
of 5
pro vyhledávání: '"H. M. Attar"'
Autor:
Saifur Rahman, Ahmad Shaf, Tariq Ali, Hamad Ali Abosaq, Maryam Zafar, Muhammad Irfan, Faisal Althobiani, H. M. Attar
Publikováno v:
IEEE Access, Vol 12, Pp 30146-30163 (2024)
This paper presents two Elliptical Trajectories for Efficient Data-gathering and Delay-tolerant (TETD2) routing schemes for Underwater Wireless Sensor Networks (UWSNs). The TETD2 protocol consists of two phases. The first phase involves creating an a
Externí odkaz:
https://doaj.org/article/94ad79196fff4c70b4a7a15e0489df4b
Autor:
Muhammad Irfan, Ahmad Shaf, Tariq Ali, Maryam Zafar, Faisal AlThobiani, Majid A. Almas, H. M. Attar, Abdulmajeed Alqhatani, Saifur Rahman, Abdulkarem H. M. Almawgani
Publikováno v:
AIP Advances, Vol 14, Iss 3, Pp 035137-035137-15 (2024)
Producing and supplying energy efficiently are important for many countries. Using models to predict energy production can help reduce costs, improve efficiency, and make energy systems work better. This research predicts solar electricity production
Externí odkaz:
https://doaj.org/article/f06876ac1da945ef9281576bd7891cd2
Publikováno v:
Applied Composite Materials. 17:441-452
In this article, initiation and propagation of delamination of a double cantilevered beam (DCB) is studied. The delamination of DCB specimen occurs between 0 o and θ 0 layers. Due to damage induced, during the loading, in the matrix of θ 0 layer, v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a90b83b16f1269fa566aa16fe865489
https://doi.org/10.1007/s10443-010-9139-x
https://doi.org/10.1007/s10443-010-9139-x
Publikováno v:
IEEE Sensors Journal. 13:1397-1398
Using simultaneous photoplethysmogram (PPG) and pulse transducer signals from the same finger, a high correlation (Mean: 98.6, STD: 1) is obtained between the AC part of the PPG and estimated volume changes (after normalization). These results point
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37af10dd78eebf836947d180d190fcb0
https://doi.org/10.1109/jsen.2013.2240677
https://doi.org/10.1109/jsen.2013.2240677
Autor:
Muhammad Irfan, Ahmad Shaf, Tariq Ali, Mariam Zafar, Saifur Rahman, Salim Nasar Faraj Mursal, Faisal AlThobiani, Majid A Almas, H M Attar, Nagi Abdussamiee
Publikováno v:
PLoS ONE, Vol 18, Iss 5, p e0285456 (2023)
Electricity consumption prediction plays a vital role in intelligent energy management systems, and it is essential for electricity power supply companies to have accurate short and long-term energy predictions. In this study, a deep-ensembled neural
Externí odkaz:
https://doaj.org/article/59fc4d24e0be44559e29d8c5d1b76868