Zobrazeno 1 - 10
of 2 176
pro vyhledávání: '"A Elmahdy"'
Information retrieval across different languages is an increasingly important challenge in natural language processing. Recent approaches based on multilingual pre-trained language models have achieved remarkable success, yet they often optimize for
Externí odkaz:
http://arxiv.org/abs/2408.10536
Night time semantic segmentation is a crucial task in computer vision, focusing on accurately classifying and segmenting objects in low-light conditions. Unlike daytime techniques, which often perform worse in nighttime scenes, it is essential for au
Externí odkaz:
http://arxiv.org/abs/2407.06016
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Floods accompanied by thunderstorms in developed cities are hazardous, causing damage to infrastructure. To secure infrastructure, it is important to employ an integrated approach, combining remote sensing, GIS and precipitation data. The mo
Externí odkaz:
https://doaj.org/article/5121f99021a648c4b67e0568d287e061
Autor:
Mohamed N. F. Shaheen, Elmahdy Mohamed Elmahdy, Neveen M. Rizk, Sayeda M. Abdo, Nahla A. Hussein, Asmaa Elshershaby, Yasser E. Shahein, Mariam E. Fawzy, Mohamed Azab El-Liethy, Mohamed A. Marouf, Fagr Kh. Abdel-Gawad, Anyi Hu, Mahmoud Gad
Publikováno v:
Environmental Sciences Europe, Vol 36, Iss 1, Pp 1-19 (2024)
Abstract Wastewater treatment plants (WWTPs) contain a diverse array of microbes, underscoring the need for regular monitoring to ensure treatment efficacy and protect health. However, detailed studies on waste stabilization ponds (WSPs) are scarce.
Externí odkaz:
https://doaj.org/article/bede7f01352f4ac29264001f20e61d9c
Autor:
Elmahdy, Adel, Salem, Ahmed
Natural language processing (NLP) models have become increasingly popular in real-world applications, such as text classification. However, they are vulnerable to privacy attacks, including data reconstruction attacks that aim to extract the data use
Externí odkaz:
http://arxiv.org/abs/2306.13789
Autor:
Samah Mohammed Awad, Eman Helmy El Batanony, Shaimaa K. Elmahdy, Esraa Tawfik Allam, Sara Kamal Rizk, Ahmed B. Zaid, Mohammad Taha, Radwa H. Salem
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The aim of this study is to evaluate the role of serum level of Interleukin 6(IL-6) and Interleukin 17 (IL-17) in liver transplantation outcome for living recipients, Analyze the relation between the gene polymorphism and the occurrence of r
Externí odkaz:
https://doaj.org/article/49dd99fcb895413b8d697cc2e607dba1
Autor:
Hossein Ahmadian, Tianfeng Zhou, A. Alansari, A. Senthil Kumar, A. Fathy, M. Elmahdy, Qian Yu, Guo Weijia
Publikováno v:
Journal of Materials Research and Technology, Vol 31, Iss , Pp 4088-4103 (2024)
This study examines the mechanical properties and wear mechanisms of magnesium (Mg) metal matrix composites reinforced with titanium (Ti) and silicon carbide (SiC) particles. Three different composite formulations were investigated: Mg-30 wt% Ti (A),
Externí odkaz:
https://doaj.org/article/543e22d1c0aa4d12aa58699793c0604e
Autor:
Amany M. Hamed, Dalia A. Elbahy, Ahmed RH. Ahmed, Shymaa A. Thabet, Rasha Abdeen Refaei, Islam Ragab, Safaa Mohammed Elmahdy, Ahmed S. Osman, Azza MA. Abouelella
Publikováno v:
Heliyon, Vol 10, Iss 24, Pp e41043- (2024)
Background and objective: Insulin resistance is a primary feature of type 2 diabetes. This study compared the effects of curcumin and its nanoformulation on insulin resistance, fasting blood sugar, liver function, GLUT4, lipid profile, and oxidative
Externí odkaz:
https://doaj.org/article/bfaf6a427d24423fa939046bd5c6c0ff
Publikováno v:
Cogent Business & Management, Vol 11, Iss 1 (2024)
In contrast to prior research on female directors’ participation, this study focuses on female directors playing a monitoring role within boardrooms. In addition, the current study investigates whether these female directors freeride from other str
Externí odkaz:
https://doaj.org/article/ef008b76f4224648beb5d65d7c30f2fa
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103007- (2024)
Owing to the absence of scientific methods for predicting nanocomposites' wear rates, a freshly updated machine learning method that uses an Artificial Protozoa Optimizer (APO) to forecast the tribological performance of Cu-ZrO2 nanocomposites was pr
Externí odkaz:
https://doaj.org/article/2f210044e9b049438ce1261931e67272