Zobrazeno 1 - 10
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pro vyhledávání: '"Abdelaal, Mohamed A"'
Autor:
Abdelaal, Mohamed
In this paper, we explore the transformative impact of Artificial Intelligence (AI) in the manufacturing sector, highlighting its potential to revolutionize industry practices and enhance operational efficiency. We delve into various applications of
Externí odkaz:
http://arxiv.org/abs/2407.05426
Machine learning's influence is expanding rapidly, now integral to decision-making processes from corporate strategy to the advancements in Industry 4.0. The efficacy of Artificial Intelligence broadly hinges on the caliber of data used during its tr
Externí odkaz:
http://arxiv.org/abs/2404.18681
Data drifts pose a critical challenge in the lifecycle of machine learning (ML) models, affecting their performance and reliability. In response to this challenge, we present a microbenchmark study, called D3Bench, which evaluates the efficacy of ope
Externí odkaz:
http://arxiv.org/abs/2404.18673
Autor:
Nguyen, Truong Thanh Hung, Clement, Tobias, Nguyen, Phuc Truong Loc, Kemmerzell, Nils, Truong, Van Binh, Nguyen, Vo Thanh Khang, Abdelaal, Mohamed, Cao, Hung
LangXAI is a framework that integrates Explainable Artificial Intelligence (XAI) with advanced vision models to generate textual explanations for visual recognition tasks. Despite XAI advancements, an understanding gap persists for end-users with lim
Externí odkaz:
http://arxiv.org/abs/2402.12525
Autor:
Clement, Tobias, Nguyen, Hung Truong Thanh, Kemmerzell, Nils, Abdelaal, Mohamed, Stjelja, Davor
This paper presents an approach integrating explainable artificial intelligence (XAI) techniques with adaptive learning to enhance energy consumption prediction models, with a focus on handling data distribution shifts. Leveraging SHAP clustering, ou
Externí odkaz:
http://arxiv.org/abs/2402.04982
Machine learning algorithms have become increasingly prevalent in multiple domains, such as autonomous driving, healthcare, and finance. In such domains, data preparation remains a significant challenge in developing accurate models, requiring signif
Externí odkaz:
http://arxiv.org/abs/2304.13636
Autor:
Mohamed Hussein Ramadan Atta, Mohamed A. Zoromba, Maha Gamal Ramadan Asal, Eman Sameh AbdELhay, Abdelaziz Hendy, Mervat Amin Sayed, Huwida Hamdy Abd Elmonem, Omnya Sobhy Mohamad El-ayari, Ibrahim Sehsah, Islam Sameh AbdELhay, Alzahraa Abdel Aziz Omar Abdel Rahman, Selwan Mahmoud Ibrahim Balha, Heba Mostafa Ali Taha, Hanady. Sh. Shehata, Ahmed Abdellah Othman, Ahmed Zaher Mohamed, Mahitab Mohamed Abdelrahman, Noha Mohammed Ibrahim Ibrahim, Eman Hassan Mahmoud Hassan, Hend Ali Mohamed Abd El-fatah, Amal AbdElaal Mohamed Ali, Mohamed Farag Awad Elsmalosy, Eslam Reda Machaly, Mohamed Adel Ghoneam, Amal Fawzy Zaki Ali, Mira Naguib Abdelrazek Elfar, Ahmed Abdelwahab Ibrahim El-Sayed, Marwa Fouad Hanafy Mahmoud, Eman Arafa Hassan
Publikováno v:
BMC Nursing, Vol 23, Iss 1, Pp 1-17 (2024)
Abstract Background Climate changes have led to health and environmental risks, so it has become essential to measure climate change literacy among the entire population, especially nursing students. The significant role of nursing students in raisin
Externí odkaz:
https://doaj.org/article/58e0ce382f054746bac41ae0a4b36dd4
Nowadays, machine learning plays a key role in developing plenty of applications, e.g., smart homes, smart medical assistance, and autonomous driving. A major challenge of these applications is preserving high quality of the training and the serving
Externí odkaz:
http://arxiv.org/abs/2302.04726
Nowadays, machine learning (ML) plays a vital role in many aspects of our daily life. In essence, building well-performing ML applications requires the provision of high-quality data throughout the entire life-cycle of such applications. Nevertheless
Externí odkaz:
http://arxiv.org/abs/2302.04702
Autor:
Ashraf Abdelaal Mohamed Abdelaal, Roz Saeed Albatati, Danyah Mohammed Yamani, Reem Amin Abdullatif Ali, Ghaidaa Adel Salem, Lamis Hatem Mahboob, Dhay Talal Alotaibi, Maha Fawzi Alqurashi
Publikováno v:
Physiotherapy Quarterly, Vol 32, Iss 2, Pp 68-75 (2024)
Introduction To evaluate the cross-over association of moderate-to-high-intensity interval-training (M-HIIT) and low-frequency pulsed-electromagnetic field therapy (LFPMT) on functional balance (FB) and ankle-brachial index (ABI) in patients with dia
Externí odkaz:
https://doaj.org/article/453da9c4e5db4a71820fd1ec90a1fd83