Zobrazeno 1 - 10
of 3 461
pro vyhledávání: '"A. Abou-Zeid"'
Foundation deep learning (DL) models are general models, designed to learn general, robust and adaptable representations of their target modality, enabling finetuning across a range of downstream tasks. These models are pretrained on large, unlabeled
Externí odkaz:
http://arxiv.org/abs/2411.09996
Foundational deep learning (DL) models are general models, trained on large, diverse, and unlabelled datasets, typically using self-supervised learning techniques have led to significant advancements especially in natural language processing. These p
Externí odkaz:
http://arxiv.org/abs/2411.09849
The industrial Internet of Things (IIoT) under Industry 4.0 heralds an era of interconnected smart devices where data-driven insights and machine learning (ML) fuse to revolutionize manufacturing. A noteworthy development in IIoT is the integration o
Externí odkaz:
http://arxiv.org/abs/2403.14120
The open radio access network (O-RAN) architecture supports intelligent network control algorithms as one of its core capabilities. Data-driven applications incorporate such algorithms to optimize radio access network (RAN) functions via RAN intellig
Externí odkaz:
http://arxiv.org/abs/2309.07265
The success of immersive applications such as virtual reality (VR) gaming and metaverse services depends on low latency and reliable connectivity. To provide seamless user experiences, the open radio access network (O-RAN) architecture and 6G network
Externí odkaz:
http://arxiv.org/abs/2309.00489
Automatic modulation classification (AMC) plays a critical role in wireless communications by autonomously classifying signals transmitted over the radio spectrum. Deep learning (DL) techniques are increasingly being used for AMC due to their ability
Externí odkaz:
http://arxiv.org/abs/2308.11100
Autor:
Heba Emad El-Gazar, Hanaa Elgohari, Ahmed Loutfy, Mona Shawer, Ahmed Hashem El-Monshed, Mennat Allah G. Abou Zeid, Mohamed Ali Zoromba
Publikováno v:
BMC Nursing, Vol 23, Iss 1, Pp 1-9 (2024)
Abstract Aim To examine the effect of internet addiction on emotional intelligence among nursing students. Internet addiction, especially among nursing students, is an ongoing and urgent issue globally. Despite studies acknowledging its negative effe
Externí odkaz:
https://doaj.org/article/1fe50e53b5c44511b695b70113914278
Autor:
Peter Mikula, Martin Bulla, Daniel T. Blumstein, Yanina Benedetti, Kristina Floigl, Jukka Jokimäki, Marja-Liisa Kaisanlahti-Jokimäki, Gábor Markó, Federico Morelli, Anders Pape Møller, Anastasiia Siretckaia, Sára Szakony, Michael A. Weston, Farah Abou Zeid, Piotr Tryjanowski, Tomáš Albrecht
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-13 (2024)
Abstract The coronavirus disease 2019 (COVID-19) pandemic and respective shutdowns dramatically altered human activities, potentially changing human pressures on urban-dwelling animals. Here, we use such COVID-19-induced variation in human presence t
Externí odkaz:
https://doaj.org/article/32fda3b970c34749bfbb8c7a87f0e721
Publikováno v:
BMC Gastroenterology, Vol 24, Iss 1, Pp 1-7 (2024)
Abstract Background Different split regimens of polyethylene glycol are routinely used and no guidelines are available to select an optimal protocol of ingestion. This study aims to compare the efficacy and side effect profile of two different regime
Externí odkaz:
https://doaj.org/article/e3717c6317524fe789611e50e38d7db0
Autor:
Erak, Omar, Abou-Zeid, Hatem
The recent advances in machine learning and deep neural networks have made them attractive candidates for wireless communications functions such as channel estimation, decoding, and downlink channel state information (CSI) compression. However, most
Externí odkaz:
http://arxiv.org/abs/2304.01914