Zobrazeno 1 - 10
of 6 861
pro vyhledávání: '"Khaled, N."'
Designing generalized in-memory computing (IMC) hardware that efficiently supports a variety of workloads requires extensive design space exploration, which is infeasible to perform manually. Optimizing hardware individually for each workload or sole
Externí odkaz:
http://arxiv.org/abs/2410.16759
Wireless device pairing is a critical security mechanism to bootstrap the secure communication between two devices without a pre-shared secret. It has been widely used in many Internet of Things (IoT) applications, such as smart-home and smart-health
Externí odkaz:
http://arxiv.org/abs/2405.03045
The globalization of the Integrated Circuit (IC) supply chain, driven by time-to-market and cost considerations, has made ICs vulnerable to hardware Trojans (HTs). Against this threat, a promising approach is to use Machine Learning (ML)-based side-c
Externí odkaz:
http://arxiv.org/abs/2401.02342
Autor:
Guesmi, Amira, Alouani, Ihsen, Khasawneh, Khaled N., Baklouti, Mouna, Frikha, Tarek, Abid, Mohamed, Abu-Ghazaleh, Nael
Machine-learning architectures, such as Convolutional Neural Networks (CNNs) are vulnerable to adversarial attacks: inputs crafted carefully to force the system output to a wrong label. Since machine-learning is being deployed in safety-critical and
Externí odkaz:
http://arxiv.org/abs/2211.01182
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract In agriculture, hydrogels can be addressed for effective operation of water and controlled-release fertilizers. Hydrogels have a significant ability for retaining water and improving nutrient availability in soil, enhancing plant growth whil
Externí odkaz:
https://doaj.org/article/9765557a6cc4489aa8fe3d8659115e2d
Autor:
Amira S. Diab, Khaled N. M. Elsayed, Ahmed M. El-Sherbeeny, Wail Al Zoubi, Stefano Bellucci, Mostafa R. Abukhadra
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Turbinaria ornata marine macro-algae (TUN) have been applied as carriers for the metallic zinc/ZnO blended nanoparticles, which were synthesized by implementing the extracted phytochemicals of the algae. The resulting hybrid bio-composite (Zn@ZnO/TUN
Externí odkaz:
https://doaj.org/article/4b85bb3d91c04f98918e4d1d947953bb
Empowered by the backpropagation (BP) algorithm, deep neural networks have dominated the race in solving various cognitive tasks. The restricted training pattern in the standard BP requires end-to-end error propagation, causing large memory cost and
Externí odkaz:
http://arxiv.org/abs/2205.07141
Autor:
Fernando Aguirre, Abu Sebastian, Manuel Le Gallo, Wenhao Song, Tong Wang, J. Joshua Yang, Wei Lu, Meng-Fan Chang, Daniele Ielmini, Yuchao Yang, Adnan Mehonic, Anthony Kenyon, Marco A. Villena, Juan B. Roldán, Yuting Wu, Hung-Hsi Hsu, Nagarajan Raghavan, Jordi Suñé, Enrique Miranda, Ahmed Eltawil, Gianluca Setti, Kamilya Smagulova, Khaled N. Salama, Olga Krestinskaya, Xiaobing Yan, Kah-Wee Ang, Samarth Jain, Sifan Li, Osamah Alharbi, Sebastian Pazos, Mario Lanza
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-40 (2024)
Abstract Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing units operating in parallel. The low communication bandwidth between memory and proc
Externí odkaz:
https://doaj.org/article/2747dc5462eb47f38960b290c0cdbb9e
Advances in deep learning have enabled a wide range of promising applications. However, these systems are vulnerable to Adversarial Machine Learning (AML) attacks; adversarially crafted perturbations to their inputs could cause them to misclassify. S
Externí odkaz:
http://arxiv.org/abs/2201.01621
Autor:
Nasr, Mustafa M., Anwar, Saqib, Al-Samhan, Ali M., Alqahtani, Khaled N., Alhaag, Mohammed H., Omar, Rayan Saleem M.
Publikováno v:
In Journal of Manufacturing Processes 30 August 2024 124:778-792