Zobrazeno 1 - 10
of 2 627
pro vyhledávání: '"M. Javed"'
Autor:
Abdul Qadeer, Mohd Parvez, Osama Khan, Pratibha Kumari, Zeinebou Yahya, Aiyeshah Alhodaib, M. Javed Idrisi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In past years, concentrated solar power (CSP) with an energy backup system has been a unique renewable energy utilization system among intermittent renewable energy systems. It could allow a CSP plant to operate as a base load system in the
Externí odkaz:
https://doaj.org/article/c8b1e3df700240aba29d242986202ca0
Autor:
Aiyeshah Alhodaib, Zeinebou Yahya, Osama Khan, Azhar Equbal, Md Shaquib Equbal, Mohd Parvez, Ashok Kumar Yadav, M. Javed Idrisi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract The underutilization of digestate-derived polymers presents a pressing environmental concern as these valuable materials, derived from anaerobic digestion processes, remain largely unused, contributing to pollution and environmental degradat
Externí odkaz:
https://doaj.org/article/f1611f683df446f481d26388a8aacac0
Autor:
F M Javed Mehedi Shamrat, Mohd Yamani Idna Idris, Xujuan Zhou, Majdi Khalid, Sharmin Sharmin, Zeseya Sharmin, Kawsar Ahmed, Mohammad Ali Moni
Publikováno v:
Heliyon, Vol 10, Iss 19, Pp e38596- (2024)
Pollen grains play a critical role in environmental, agricultural, and allergy research despite their tiny dimensions. The accurate classification of pollen grains remains a significant challenge, mainly attributable to their intricate structures and
Externí odkaz:
https://doaj.org/article/1c7ff0d4314541c8b9059e7098b4f522
Autor:
Ananda Sutradhar, Sharmin Akter, F M Javed Mehedi Shamrat, Pronab Ghosh, Xujuan Zhou, Mohd Yamani Idna Bin Idris, Kawsar Ahmed, Mohammad Ali Moni
Publikováno v:
Heliyon, Vol 10, Iss 17, Pp e36556- (2024)
The worldwide prevalence of thyroid disease is on the rise, representing a chronic condition that significantly impacts global mortality rates. Machine learning (ML) approaches have demonstrated potential superiority in mitigating the occurrence of t
Externí odkaz:
https://doaj.org/article/e2b123d9c5724246b22f6b8599d5f41c
Autor:
Shamrat, F M Javed Mehedi a, Idna Idris, Mohd Yamani a, Zhou, Xujuan b, ⁎⁎, Khalid, Majdi c, Sharmin, Sharmin a, Sharmin, Zeseya d, Ahmed, Kawsar e, f, g, ⁎, Moni, Mohammad Ali h, i
Publikováno v:
In Heliyon 15 October 2024 10(19)
Autor:
Sutradhar, Ananda a, Akter, Sharmin a, Shamrat, F M Javed Mehedi b, Ghosh, Pronab c, Zhou, Xujuan d, ⁎⁎, Idris, Mohd Yamani Idna Bin b, Ahmed, Kawsar e, f, g, ⁎, Moni, Mohammad Ali h
Publikováno v:
In Heliyon 15 September 2024 10(17)
Autor:
Idrisi, M. Javed a, Ullah, M. Shahbaz b, ⁎
Publikováno v:
In Chaos, Solitons and Fractals: the interdisciplinary journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena August 2024 185
Autor:
F M Javed Mehedi Shamrat, Rashiduzzaman Shakil, Sharmin, Nazmul Hoque ovy, Bonna Akter, Md Zunayed Ahmed, Kawsar Ahmed, Francis M. Bui, Mohammad Ali Moni
Publikováno v:
Healthcare Analytics, Vol 5, Iss , Pp 100303- (2024)
Diabetic retinopathy (DR) involves retina damage due to diabetes, often leading to blindness. It is diagnosed via color fundus injections, but the manual analysis is cumbersome and error-prone. While computer vision techniques can predict DR stages,
Externí odkaz:
https://doaj.org/article/492d041e53fb45569f93e0bc02c1a49d
Publikováno v:
IEEE Access, Vol 12, Pp 78641-78656 (2024)
Recently, thyroid disease has been a leading cause of mortality, underscoring the importance of early diagnosis to mitigate its impact. Researchers have randomly employed static selection ensemble methods aiming to forecast the disease in its initial
Externí odkaz:
https://doaj.org/article/58c194b817694b8c8307581f4bb1ffc1
Autor:
Ananda Sutradhar, Mustahsin Al Rafi, F M Javed Mehedi Shamrat, Pronab Ghosh, Subrata Das, Md Anaytul Islam, Kawsar Ahmed, Xujuan Zhou, A. K. M. Azad, Salem A. Alyami, Mohammad Ali Moni
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Heart failure (HF) is a leading cause of mortality worldwide. Machine learning (ML) approaches have shown potential as an early detection tool for improving patient outcomes. Enhancing the effectiveness and clinical applicability of the ML m
Externí odkaz:
https://doaj.org/article/e1d56422569b4c19aa89960088b8b0cc