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pro vyhledávání: '"Hasan, Mohammed"'
Gradient descent computed by backpropagation (BP) is a widely used learning method for training artificial neural networks but has several limitations: it is computationally demanding, requires frequent manual tuning of the network architecture, and
Externí odkaz:
http://arxiv.org/abs/2410.00745
Context: The advent of Large Language Model-driven tools like ChatGPT offers software engineers an interactive alternative to community question-answering (CQA) platforms like Stack Overflow. While Stack Overflow provides benefits from the accumulate
Externí odkaz:
http://arxiv.org/abs/2409.17473
Tracking statements in the commit history of a project is in many cases useful for supporting various software maintenance, comprehension, and evolution tasks. A high level of accuracy can facilitate the adoption of code tracking tools by developers
Externí odkaz:
http://arxiv.org/abs/2409.16185
Autor:
Rashad Alsanosy, Mohamed Salih Mahfouz, Abdulelah Mohammed Arishi, Siddig Ibrahim Abdelwahab, Manal Taha, Osama Albasheer, Hasan Mohammed Daghriri, Khalid Ahmed Majrashi, Abdullah Farasani, Ahmed A. A. Altraifi, Isameldin E. Medani, Nasser Hakami
Publikováno v:
Tobacco Induced Diseases, Vol 22, Iss July, Pp 1-14 (2024)
Introduction Previous studies have identified several risk factors for acute coronary syndrome (ACS). This study was intended to examine the potential risk of ACS associated with khat and tobacco use. Methods A case-control study of 344 people (172
Externí odkaz:
https://doaj.org/article/9cff52f6276b489fb7d6a0f5019954b9
The structural, electrical, optical, and mechanical characteristics of the lead-free halide double perovskites Cs2NaTlX6 X = F, Cl, Br are calculated by utilizing PBE functional within generalized gradient approximation GGA under the context of densi
Externí odkaz:
http://arxiv.org/abs/2302.02201
Autor:
Zaidoon Hasan Mohammed, Thanaa Ghani Nema, Sohaib Fadhil Mohammed, Hamsa Zaki Al-Assadi, Ala Mahdi Muhamed Ali, Aya Alaa Hussein
Publikováno v:
Dentistry 3000, Vol 12, Iss 2 (2024)
Objective: The characteristic of dentin hypersensitivity is brief, intense pain that results from exposed dentin in reaction to a variety of stimuli, including mechanical, thermal, osmotic, or chemical factors. This study aimed to evaluate the level
Externí odkaz:
https://doaj.org/article/e89eaac77ab6426a8eb07cd9f2a20c28
Autor:
Hasan, Mohammed A.1 (AUTHOR) moalaa@med.nvu.edu.eg, El-Sayed, Amr2 (AUTHOR), Ezzat, Mostafa3 (AUTHOR), Safoury, Yasser3 (AUTHOR)
Publikováno v:
BMC Musculoskeletal Disorders. 11/19/2024, Vol. 25 Issue 1, p1-7. 7p.
Autor:
Mohammad Natami, Amirsasan Gorgzadeh, Arsalan Gholipour, Seyedeh Narges Fatemi, Nima Firouzeh, Maryam Zokaei, Saad Hasan Mohammed Ali, Hadis Kheradjoo, Somayeh Sedighi, Omid Gholizadeh, Shaylan Kalavi
Publikováno v:
Journal of Nanobiotechnology, Vol 22, Iss 1, Pp 1-25 (2024)
Abstract The human monkeypox virus (Mpox) is classified as a member of the Poxviridae family and belongs to the Orthopoxvirus genus. Mpox possesses double-stranded DNA, and there are two known genetic clades: those originating in West Africa and the
Externí odkaz:
https://doaj.org/article/556d10d6d7a3483e810dbf395d8e692d
Autor:
Dalia Yahia M. El Kheir, Alnouf Zayed Alghamdi, Alaa Mohammed Alaali, Hasan Mohammed Alswiket, Hoor Mohammad AlSaffar, Fatimah Mohammed Alalwiat
Publikováno v:
Journal of Infection and Public Health, Vol 17, Iss 3, Pp 412-416 (2024)
Background: COVID-19 pandemic has significantly disrupted healthcare systems worldwide, raising concerns about its impact on cancer patients' access to healthcare services. This study aims to explore the experiences of cancer patients and assess effe
Externí odkaz:
https://doaj.org/article/be07fde075164dccaac1837285c94e60
Autor:
Joshi, Gargi, Srivastava, Ananya, Yagnik, Bhargav, Hasan, Mohammed, Saiyed, Zainuddin, Gabralla, Lubna A, Abraham, Ajith, Walambe, Rahee, Kotecha, Ketan
In this work, the integration of two machine learning approaches, namely domain adaptation and explainable AI, is proposed to address these two issues of generalized detection and explainability. Firstly the Domain Adversarial Neural Network (DANN) d
Externí odkaz:
http://arxiv.org/abs/2203.11724