Zobrazeno 1 - 10
of 651
pro vyhledávání: '"Ayaz, Ahmad"'
Autor:
CH, Nadeem Jabbar, Saghir, Aqib, Meer, Ayaz Ahmad, Sahi, Salman Ahmad, Hassan, Bilal, Yasir, Siddiqui Muhammad
Deepfake is a generative deep learning algorithm that creates or changes facial features in a very realistic way making it hard to differentiate the real from the fake features It can be used to make movies look better as well as to spread false info
Externí odkaz:
http://arxiv.org/abs/2406.13295
Autor:
Bello, Abdulkabir Opeyemi, Eje, Doris Omonogwu, Idris, Abdullahi, Semiu, Mudasiru Abiodun, Khan, Ayaz Ahmad
Publikováno v:
Journal of Engineering, Design and Technology, 2023, Vol. 22, Issue 6, pp. 2043-2062.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JEDT-11-2022-0571
Autor:
Naila Shah, Muhammad Irshad, Waheed Murad, Muhammad Hamayun, Muhammad Qadir, Anwar Hussain, Hussan Ara Begum, Abdulwaahed Fahad Alrefaei, Mikhlid H. Almutairi, Ayaz Ahmad, Sajid Ali
Publikováno v:
BMC Plant Biology, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Enhanced phytoremediation offers a rapid and eco-friendly approach for cleaning agricultural soil contaminated with copper and cadmium which pose a direct threat to food scarcity and security. The current study aimed to compare the effective
Externí odkaz:
https://doaj.org/article/bbc981e5b8c74cab8500da5a3ea1e6a9
Autor:
Muhammad Nasir Amin, Roz-Ud-Din Nassar, Muhammad Tahir Qadir, Ayaz Ahmad, Kaffayatullah Khan, Muhammad Faisal Javed
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103305- (2024)
This study aims to investigate the compressive strength (CS) of foamcrete (FC), with a specific emphasis on its 7-day and 28-day performance. The multi-layer perceptron (MLP) and random forest (RF) machine learning techniques have been selected for f
Externí odkaz:
https://doaj.org/article/2f6f63d957f34ac38d69b922e8e1d18e
Publikováno v:
Engineering, Construction and Architectural Management, 2023, Vol. 31, Issue 8, pp. 3148-3164.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ECAM-10-2022-1001
Autor:
Hannan Younis, Mohammad Ayaz Ahmad, Umair Azeem, Mohammed Rafi Shaik, Abdulrahman Al-Warthan, Baji Shaik, Antalov Jagnandan, Shawn Jagnandan, Muhammad Ajaz
Publikováno v:
ACS Omega, Vol 9, Iss 19, Pp 21089-21096 (2024)
Externí odkaz:
https://doaj.org/article/60bd8d9a1cd64db793463de48d5c0471
Autor:
Imdad Ullah Khan, Yusra Jamil, Fareeha Shams, Salman Farsi, Muhammad Humayun, Anwar Hussain, Ayaz Ahmad, Amjad Iqbal, Abdulwahed Fahad Alrefaei, Sajid Ali
Publikováno v:
Heliyon, Vol 10, Iss 17, Pp e36797- (2024)
Inflammation coupled with oxidative stress contribute to the pathogenicity of various clinical disorders. Oxidative stress arises from an imbalance between production of reactive oxygen species (ROS) and antioxidant defense system, leading to cellula
Externí odkaz:
https://doaj.org/article/371eb57b7e6e4cc2b0469fff832c4faa
Autor:
Mohammed Awad Abuhussain, Ayaz Ahmad, Muhammad Nasir Amin, Fadi Althoey, Yaser Gamil, Taoufik Najeh
Publikováno v:
Case Studies in Construction Materials, Vol 20, Iss , Pp e02920- (2024)
Alkali-activated composites (AACs) have attracted considerable interest as a promising alternative to reduce CO2 emissions from Portland cement production and advance the decarbonisation of concrete construction. This study describes the data-driven
Externí odkaz:
https://doaj.org/article/d2e0c0f4565c47578cae835380b3f015
Autor:
Mohammed Alarfaj, Azzam Al Madini, Ahmed Alsafran, Mohammed Farag, Slim Chtourou, Ahmed Afifi, Ayaz Ahmad, Osama Al Rubayyi, Ali Al Harbi, Mustafa Al Thunaian
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Human motion detection technology holds significant potential in medicine, health care, and physical exercise. This study introduces a novel approach to human activity recognition (HAR) using convolutional neural networks (CNNs) designed for individu
Externí odkaz:
https://doaj.org/article/dc3fb3b5fbea4903bf0fdc1df3630fe0
Autor:
Muhammad Qadir, Anwar Hussain, Mohib Shah, Muhammad Hamayun, Amjad Iqbal, Muhammad Irshad, Ayaz Ahmad, Abdulwahed Fahad Alrefaei, Sajid Ali
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionArsenate, a metalloid, acting as an analog to phosphate, has a tendency to accumulate more readily in plant species, leading to adverse effects.MethodsIn the current study, sunflower seedlings were exposed to 25, 50 and 100 ppm of the ars
Externí odkaz:
https://doaj.org/article/a87529251c8943fa90e4e9d7953b8adc