Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Saifullah Bin Ansar"'
Autor:
Fahmida Yeasmin Sami, Md. Nazmul Haque, Md. Mojammel Hoque, Gitisree Biswas, Asma Amin Rimi, Syed Riad Morshed, Md. Abdul Fattah, Saifullah Bin Ansar
Publikováno v:
International Journal of Social Economics. 48:1121-1138
PurposeKhan Jahan Ali (KJA) Bridge was constructed to promote industrial and commercial activity and improve economic and employment activity for local people. This study assessed the post-socioeconomic and environmental impacts of KJA Bridge on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0daad0b8e8dba517e3db21899bd48b6c
https://doi.org/10.1108/ijse-01-2021-0023
https://doi.org/10.1108/ijse-01-2021-0023
Drought is a stochastic climatic phenomenon that has detrimental and widespread effects that spread throughout the local community, the global economy, and ecological environments. Consideration of wet and dry periods' calculations through various dr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa37f55bf98f220b898b8c8a23dd2c44
https://doi.org/10.21203/rs.3.rs-1416977/v1
https://doi.org/10.21203/rs.3.rs-1416977/v1
Publikováno v:
Journal of Engineering Science. 11:117-126
This paper aims to provide a small-scale quantitative overview about the impact on socio economic condition in lockdown wards of Khulna City Corporation (KCC), Bangladesh due to this pandemic. Online survey for primary data was conducted through 158
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d056480d19b5a15c4eb27490d5171276
https://doi.org/10.3329/jes.v11i2.50903
https://doi.org/10.3329/jes.v11i2.50903
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52028c78197a0b2b29298fa45ecd4fa3
https://doi.org/10.2139/ssrn.4245551
https://doi.org/10.2139/ssrn.4245551
Autor:
Showmitra Kumar Sarkar, Saifullah Bin Ansar, Khondaker Mohammed Mohiuddin Ekram, Mehedi Hasan Khan, Swapan Talukdar, Mohd Waseem Naikoo, Abu Reza Towfiqul Islam, Atiqur Rahman, Amir Mosavi
Publikováno v:
Sustainability; Volume 14; Issue 7; Pages: 3982
The present study intends to improve the robustness of a flood susceptibility (FS) model with a small number of parameters in data-scarce areas, such as northwest Bangladesh, by employing machine learning-based sensitivity analysis and an analytical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c009c21a3f348847e516f1f24fc731f0
https://doi.org/10.3390/su14073982
https://doi.org/10.3390/su14073982