Zobrazeno 1 - 10
of 935
pro vyhledávání: '"Alameen A"'
Publikováno v:
Drug Design, Development and Therapy, Vol Volume 18, Pp 4215-4240 (2024)
Ali Attiq,1 Sheryar Afzal,2 Habibah A Wahab,1 Waqas Ahmad,1 Mahmoud Kandeel,2,3 Yassir A Almofti,2,4 Ahmed O Alameen,2,5 Yuan Seng Wu6,7 1School of Pharmaceutical Sciences, Universiti Sains Malaysia, Gelugor, Penang, 11800, Malaysia; 2Department of B
Externí odkaz:
https://doaj.org/article/2caf5df3d9634d16bc845b65921dafb8
Autor:
Ansam Eghzawi, Alameen Alsabbah, Shatha Gharaibeh, Iktimal Alwan, Abeer Gharaibeh, Anita V. Goyal
Publikováno v:
Neurology International, Vol 16, Iss 2, Pp 406-418 (2024)
Traumatic brain injuries (TBIs) represent a significant public health concern, with mild-to-moderate cases comprising a substantial portion of incidents. Understanding the predictors of mortality among adult patients with mild-to-moderate TBIs is cru
Externí odkaz:
https://doaj.org/article/987d6ce8b7a644fdbbc91b904622d2b1
Autor:
Jehad Feras AlSamhori, Alameen Alsabbah, Lama Sami Mahafzah, Abdel Rahman Feras AlSamhori, Ahmad Feras AlSamhori
Publikováno v:
International Journal of Medical Students, Vol 11 (2023)
BACKGROUND: In an increasingly digital age, social media, particularly Facebook, has become an integral part of college students' lives. This study seeks to explore how gender and academic year may influence Facebook addiction and its impact on menta
Externí odkaz:
https://doaj.org/article/81b4c40fc3254111bb55fe4df6f3b7ad
Autor:
Abdelrahman Farag Ibrahim Ali Sherdia, Shadi Alaa Abdelaal, Mohammed Tarek Hasan, Esraa Elsayed, Mohamed Mare'y, Asmaa Ahmed Nawar, Alaa Abdelsalam, Mujtaba Zakria Abdelgader, Alameen Adam, Mohamed Abozaid
Publikováno v:
Indian Heart Journal, Vol 75, Iss 2, Pp 98-107 (2023)
Introduction: radiofrequency catheter ablation (RFA) is the first-line therapy for symptomatic Wolff Parkinson White (WPW) patients according to the American Heart Association. We conducted this study to assess the success rate, recurrence rate, and
Externí odkaz:
https://doaj.org/article/19461ce846264855bcccfb350bd04076
Autor:
Ejaz H, Ahmad M, Younas S, Junaid K, Abosalif KOA, Abdalla AE, Alameen AAM, Elamir MYM, Bukhari SNA, Ahmad N, Qamar MU
Publikováno v:
Infection and Drug Resistance, Vol Volume 14, Pp 1931-1939 (2021)
Hasan Ejaz,1 Mahtab Ahmad,2 Sonia Younas,3 Kashaf Junaid,1 Khalid Omer Abdalla Abosalif,1 Abualgasim Elgaili Abdalla,1 Ayman Ali Mohammed Alameen,1 Mohammed Yagoub Mohammed Elamir,1 Syed Nasir Abbas Bukhari,4 Naveed Ahmad,5 Muhammad Usman Qamar2 1Dep
Externí odkaz:
https://doaj.org/article/6d1c5b66ae6b4303a34e869bb044773b
Autor:
Najjar, Alameen
We empirically demonstrate that a transformer pre-trained on country-scale unlabeled human mobility data learns embeddings capable, through fine-tuning, of developing a deep understanding of the target geography and its corresponding mobility pattern
Externí odkaz:
http://arxiv.org/abs/2406.04029
Autor:
Mysara Ahmed Mohamed, Abdalla Noureldin Osman Kheiry, Abbas Elshiekh Rahama, Alameen Alwathig Alameen
Publikováno v:
Turkish Journal of Agriculture: Food Science and Technology, Vol 5, Iss 7, Pp 739-744 (2017)
The optimization machinery model was developed to aid decision-makers and farm machinery managers in determining the optimal number of tractors, scheduling the agricultural operation and minimizing machinery total costs. For purpose of model verifica
Externí odkaz:
https://doaj.org/article/cb99d095b34441af8a171377e164e0cd
Autor:
Najjar, Alameen
We present the results of training a large trajectory model using real-world user check-in data. Our approach follows a pre-train and fine-tune paradigm, where a base model is pre-trained via masked trajectory modeling and then adapted through fine-t
Externí odkaz:
http://arxiv.org/abs/2312.00076
Autor:
Najjar, Alameen, Mede, Kyle
In this paper we investigate the ability of modern machine learning algorithms in inferring basic offline activities,~e.g., shopping and dining, from location data. Using anonymized data of thousands of users of a prominent location-based social netw
Externí odkaz:
http://arxiv.org/abs/2301.13537
Autor:
Najjar, Alameen, Mede, Kyle
Trajectory-User Linking (TUL) is a relatively new mobility classification task in which anonymous trajectories are linked to the users who generated them. With applications ranging from personalized recommendations to criminal activity detection, TUL
Externí odkaz:
http://arxiv.org/abs/2212.07081