Zobrazeno 1 - 10
of 2 344
pro vyhledávání: '"BENTAHAR"'
Autor:
Makhlouf Yasmina, Bouaziz Amel, Benazi Nabil, Djidel Saliha, Bentahar Assia, Barghout Nihed, Khennouf Seddik, Dahamna Saliha
Publikováno v:
Archives of Biological Sciences, Vol 76, Iss 2, Pp 161-174 (2024)
Colometric assays were used to quantify the secondary metabolites obtained by a decoction of the extract of Anabasis articulata (DEAA) flowers and leaves. Antioxidant activity was examined using several methods: total antioxidant capacity, the 2,2-di
Externí odkaz:
https://doaj.org/article/47f9537c7e1f4912948f638ef97810d8
Autor:
Zouhayr Souirti, Mohammed Hmidani, Abdelaziz Lamkadddem, Kawtar Khabbach, Salma Belakhdar, Doae Charkani, Driss Mhandez Tlemcani, Nabila Lahmadi, Maroua El Akramine, Samira Erriouiche, Asmae Berrada, Asmae Ahniba, Mohammed Omari, Samira El Fakir, Nabil Tachfouti, Mohammed Abdoh Rafai, Imane Chahid, Bentahar Meriam, Mariam Jilla, Aayad Ghaname, Youssef Benmansour, Younes Filali Zegzouti, Najib Kissani, Abdelhakim Lakhdar, Rachid Belfkih, Mohamed Aggouri, Reda Ouazzani, Abderrahmane Chahidi, Abdelkrim Janati Idrissi
Publikováno v:
Epilepsia Open, Vol 8, Iss 4, Pp 1340-1349 (2023)
Abstract Objective In Morocco, there was a lack of data related to the epidemiology of epilepsy. This data serves as a useful basis for the development of any national intervention or action program against epilepsy in Morocco. Through this study, we
Externí odkaz:
https://doaj.org/article/ab13cbf5252a4425a35efb64d8ce6190
Publikováno v:
Comptes Rendus. Chimie, Vol 24, Iss S1, Pp 23-37 (2021)
An investigation has been carried out for biogas production from dairy raw materials (DRM) and Ulva sp. macroalgae as a co-substrate in order to find a usefulness for these species. Some nutrient media have been selected to optimize methane yield. Th
Externí odkaz:
https://doaj.org/article/8add636b21194b3a8be473b39006b619
In Federated Learning (FL), the limited accessibility of data from diverse locations and user types poses a significant challenge due to restricted user participation. Expanding client access and diversifying data enhance models by incorporating dive
Externí odkaz:
http://arxiv.org/abs/2405.07175
Containerization technology plays a crucial role in Federated Learning (FL) setups, expanding the pool of potential clients and ensuring the availability of specific subsets for each learning iteration. However, doubts arise about the trustworthiness
Externí odkaz:
http://arxiv.org/abs/2405.00395
The proliferation of the Internet of Things (IoT) has led to an explosion of data generated by interconnected devices, presenting both opportunities and challenges for intelligent decision-making in complex environments. Traditional Reinforcement Lea
Externí odkaz:
http://arxiv.org/abs/2404.04205
Autor:
Islam, Saidul, Elmekki, Hanae, Elsebai, Ahmed, Bentahar, Jamal, Drawel, Najat, Rjoub, Gaith, Pedrycz, Witold
Transformer is a deep neural network that employs a self-attention mechanism to comprehend the contextual relationships within sequential data. Unlike conventional neural networks or updated versions of Recurrent Neural Networks (RNNs) such as Long S
Externí odkaz:
http://arxiv.org/abs/2306.07303
Autor:
Sami, Hani, Hammoud, Ahmad, Arafeh, Mouhamad, Wazzeh, Mohamad, Arisdakessian, Sarhad, Chahoud, Mario, Wehbi, Osama, Ajaj, Mohamad, Mourad, Azzam, Otrok, Hadi, Wahab, Omar Abdel, Mizouni, Rabeb, Bentahar, Jamal, Talhi, Chamseddine, Dziong, Zbigniew, Damiani, Ernesto, Guizani, Mohsen
The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advance
Externí odkaz:
http://arxiv.org/abs/2304.09240
Autor:
Rjoub, Gaith, Bentahar, Jamal, Wahab, Omar Abdel, Mizouni, Rabeb, Song, Alyssa, Cohen, Robin, Otrok, Hadi, Mourad, Azzam
The black-box nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create machine learnin
Externí odkaz:
http://arxiv.org/abs/2303.12942