Zobrazeno 1 - 10
of 6 866
pro vyhledávání: '"A. Jaradat"'
Publikováno v:
Alexandria Engineering Journal, Vol 90, Iss , Pp 197-207 (2024)
This study mainly focuses on finding new forms of optical soliton solutions of a modified complex Ginzburg-Landau equation. A versatile integration approach, the extended sinh-Gordon expansion technique is utilized. This technique yields complex hype
Externí odkaz:
https://doaj.org/article/85c141f6e78b4ff098ecd3a9addcf2d0
We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with d
Externí odkaz:
http://arxiv.org/abs/2410.07970
Autor:
AlNuaimi, Khaled, Marti, Gautier, Ravaut, Mathieu, AlKetbi, Abdulla, Henschel, Andreas, Jaradat, Raed
Enriching datasets with demographic information, such as gender, race, and age from names, is a critical task in fields like healthcare, public policy, and social sciences. Such demographic insights allow for more precise and effective engagement wit
Externí odkaz:
http://arxiv.org/abs/2409.11491
Autor:
Jaradat, Ghadeer, Tolba, Mohammed, Alsuhli, Ghada, Saleh, Hani, Al-Qutayri, Mahmoud, Stouraitis, Thanos, Mohammad, Baker
In the world of deep learning, Transformer models have become very significant, leading to improvements in many areas from understanding language to recognizing images, covering a wide range of applications. Despite their success, the deployment of t
Externí odkaz:
http://arxiv.org/abs/2407.12893
Autor:
Elhenawy, Mohammed, Abutahoun, Ahmad, Alhadidi, Taqwa I., Jaber, Ahmed, Ashqar, Huthaifa I., Jaradat, Shadi, Abdelhay, Ahmed, Glaser, Sebastien, Rakotonirainy, Andry
Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in visually solv
Externí odkaz:
http://arxiv.org/abs/2407.00092
Object detection is a critical component of transportation systems, particularly for applications such as autonomous driving, traffic monitoring, and infrastructure maintenance. Traditional object detection methods often struggle with limited data an
Externí odkaz:
http://arxiv.org/abs/2406.10712
This study explores traffic crash narratives in an attempt to inform and enhance effective traffic safety policies using text-mining analytics. Text mining techniques are employed to unravel key themes and trends within the narratives, aiming to prov
Externí odkaz:
http://arxiv.org/abs/2406.09438
Autor:
Elhenawy, Mohammed, Abdelhay, Ahmed, Alhadidi, Taqwa I., Ashqar, Huthaifa I, Jaradat, Shadi, Jaber, Ahmed, Glaser, Sebastien, Rakotonirainy, Andry
Multimodal Large Language Models (MLLMs) have demonstrated proficiency in processing di-verse modalities, including text, images, and audio. These models leverage extensive pre-existing knowledge, enabling them to address complex problems with minima
Externí odkaz:
http://arxiv.org/abs/2406.06865
Cherry-picking refers to the deliberate selection of evidence or facts that favor a particular viewpoint while ignoring or distorting evidence that supports an opposing perspective. Manually identifying cherry-picked statements in news stories can be
Externí odkaz:
http://arxiv.org/abs/2401.05650
Publikováno v:
Arab Gulf Journal of Scientific Research, 2023, Vol. 42, Issue 3, pp. 1080-1089.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AGJSR-01-2023-0035