Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Adewale F. Lukman"'
Autor:
Adejumoke A. Inyinbor, Folahan A. Adekola, Olugbenga S. Bello, Deborah T. Bankole, Toyin A. Oreofe, Adewale F. Lukman, Gabriel A. Olatunji
Publikováno v:
South African Journal of Chemical Engineering, Vol 49, Iss , Pp 199- (2024)
Externí odkaz:
https://doaj.org/article/0824117b4b36424eaa8a593a49235e7b
Autor:
Adejumoke A. Inyinbor, Deborah T. Bankole, Pamela Solomon, Temitope S. Ayeni, Adewale F. Lukman
Publikováno v:
Heliyon, Vol 10, Iss 11, Pp e32121- (2024)
The remediation of dye pollutants remains a concern in contemporary water management practices. Hence, the need for efficient and cost-effective techniques for dye removal from wastewater. In this study, the epicarp of Raphia hookeri fruits was treat
Externí odkaz:
https://doaj.org/article/e53fa738b208462bb04130b8f2be756c
Publikováno v:
Symmetry, Vol 16, Iss 4, p 469 (2024)
We address the estimation of regression parameters for the ill-conditioned predictive linear model in this study. Traditional least squares methods often encounter challenges in yielding reliable results when there is multicollinearity. Therefore, we
Externí odkaz:
https://doaj.org/article/e1127b775a6445eb9cd3f8abd1361504
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract Linear regression models with correlated regressors can negatively impact the performance of ordinary least squares estimators. The Stein and ridge estimators have been proposed as alternative techniques to improve estimation accuracy. Howev
Externí odkaz:
https://doaj.org/article/8dc380d348de411d91a7b93f0a32f526
Autor:
Christian N. Nwaeme, Adewale F. Lukman
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 5, Iss 4 (2023)
This study introduces a robust hybrid sparse learning approach for regularization and variable selection. This approach comprises two distinct steps. In the initial step, we segment the original dataset into separate training and test sets and standa
Externí odkaz:
https://doaj.org/article/ee2ad4efc07c49fd9ec721ba2ffbeb2b
Autor:
Adejumoke A. INYINBOR, Folahan A. Adekola, Olugbenga S. Bello, Deborah T. Bankole, Toyin A. Oreofe, Adewale F. Lukman, Gabriel A. Olatunji
Publikováno v:
South African Journal of Chemical Engineering, Vol 40, Iss , Pp 144-153 (2022)
Wastes obtained from the nuts of dika fruits (Irvingia gabonensis) were treated with EDTA in surface functionalization for the adsorption of Cu2+. EDTA functionalized Irvingia gabonensis (EIG) showed strong stretching vibration of C=O. Morphological
Externí odkaz:
https://doaj.org/article/d253d3a4a99a49b5aab97a6e0bec49c4
Autor:
Adejumoke A. Inyinbor, Deborah T. Bankole, Folahan A. Adekola, Olugbenga S. Bello, Toyin Oreofe, Kelvin Amone, Adewale F. Lukman
Publikováno v:
Scientific African, Vol 19, Iss , Pp e01471- (2023)
The potential of quail eggshells for acetaminophen (PCM) removal in aqueous solution was studied. Calcination greatly increased the surface area of the raw quail eggshell (RQES). Hence, surface area as determined by the Brunauer-Emmet-Teller (BET) su
Externí odkaz:
https://doaj.org/article/bde6c8d276764b93bb7d611ba32d31ba
Autor:
Oluyemi A. Okunlola, Mohannad Alobid, Olusanya E. Olubusoye, Kayode Ayinde, Adewale F. Lukman, István Szűcs
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract In this study, we propose a robust approach to handling geo-referenced data and discuss its statistical analysis. The linear regression model has been found inappropriate in this type of study. This motivates us to redefine its error structu
Externí odkaz:
https://doaj.org/article/89c3a63ca7a04b74a86c9cd1c33f18e1
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 4, Iss 2 (2022)
The ordinary least square (OLS) method is very efficient in estimating the regression parameters in a linear regression model under classical assumptions. If the model contains outliers, the performance of the OLS estimator becomes imprecise. Multico
Externí odkaz:
https://doaj.org/article/675f97067152445a8330dfa5645d57d4
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the reg
Externí odkaz:
https://doaj.org/article/58340e7ad13e44fa92450363b9cfc469