Zobrazeno 1 - 10
of 434
pro vyhledávání: '"Mohammad, Sultan"'
Autor:
Sourav, Md Sakib Ullah, Mahmud, Mohammad Sultan, Talukder, Md Simul Hasan, Sulaiman, Rejwan Bin, Yasin, Abdullah
Biomedical Engineering's Internet of Medical Things (IoMT) is helping to improve the accuracy, dependability, and productivity of electronic equipment in the healthcare business. Real-time sensory data from patients may be delivered and subsequently
Externí odkaz:
http://arxiv.org/abs/2308.16857
In this research, we propose a complete set of approaches for identifying and extracting emotions from Bangla texts. We provide a Bangla emotion classifier for six classes: anger, disgust, fear, joy, sadness, and surprise, from Bangla words using tra
Externí odkaz:
http://arxiv.org/abs/2210.06405
Autor:
Khuroo, Mohammad Sultan1 (AUTHOR) khuroo@yahoo.com, Khuroo, Naira Sultan1 (AUTHOR), Rather, Ajaz Ahmad2 (AUTHOR) drajazrather@gmail.com
Publikováno v:
Life (2075-1729). Jul2024, Vol. 14 Issue 7, p794. 25p.
Publikováno v:
In Project Leadership and Society December 2024 5
Publikováno v:
In Information Fusion January 2024 101
Publikováno v:
Journal of Chinese Economic and Foreign Trade Studies, 2023, Vol. 16, Issue 1, pp. 64-82.
Publikováno v:
Life, Vol 14, Iss 7, p 794 (2024)
A prospective study on 110 patients with echinococcosis at Dr. Khuroo’s Medical Clinic, Srinagar, Kashmir, India, from March 2019 to April 2024 identified 12 cases (4 males, 8 females; mean age of 46.58 ± 11.97 years) of Alveolar echinococcosis (A
Externí odkaz:
https://doaj.org/article/5ae47c72122c4a118958119ad5e907a4
Publikováno v:
In Information Sciences January 2025 686
Autor:
Kuanishbay Sadatdiynov, Laizhong Cui, Lei Zhang, Joshua Zhexue Huang, Salman Salloum, Mohammad Sultan Mahmud
Publikováno v:
Digital Communications and Networks, Vol 9, Iss 2, Pp 450-461 (2023)
Handling the massive amount of data generated by Smart Mobile Devices (SMDs) is a challenging computational problem. Edge Computing is an emerging computation paradigm that is employed to conquer this problem. It can bring computation power closer to
Externí odkaz:
https://doaj.org/article/537f6234107942b892831a0fa801ac8f
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-33 (2023)
Abstract Clustering a big dataset without knowing the number of clusters presents a big challenge to many existing clustering algorithms. In this paper, we propose a Random Sample Partition-based Centers Ensemble (RSPCE) algorithm to identify the num
Externí odkaz:
https://doaj.org/article/fd86b4da6db542a487c3aef204d0855b