http://dspace.aiub.edu:8080/jspui/handle/123456789/104 <P> Provide information on Journal articles here </P> tags Tue, 31 Mar 2026 20:46:55 GMT 2026-03-31T20:46:55Z http://dspace.aiub.edu:8080/jspui/handle/123456789/2897 Title: Fully thermal radiation and electric field on magneto-hydrodynamic nanofluid convective mass transfer flow with activation energy Authors: Yasmin, Dilruba; Maleque, Kh. Abdul Abstract: The chemical reaction, viscous dissipation, non-linear thermal radiation, and activation energy on MHD laminar nano fluid flow across the vertical flat plate are considered in our present study. We also considered the uniform electric field (0,0,-E_0 )which is perpendicular to xy-plane. By taking suitable similarity functions and variables, Prandtl boundary layer typed momentum and energy equations are changed to simultaneous ordinary nonlinear differential equations (ODEs). The numerical solutions program of Simultaneous ODEs is constructed by bvp5c (Explicit Finite Difference Codes) built in MATLAB software. The numerical results are then displayed graphically with the help of MS-excel in the form of required physical properties (velocity, temperature and concentration) for considering various parameters. Skin friction (〖Re〗^(1/2) C_f ), Nusselt number (Nu 〖Re〗^(-1/2) ) and Sherwood number (Sh 〖Re〗^(-1/2) ) are provided in tabular form that is our physical interest. Validation of numerical results of the present mathematical model with previously published data are provided in table1. Tue, 09 Sep 2025 00:00:00 GMT http://dspace.aiub.edu:8080/jspui/handle/123456789/2897 2025-09-09T00:00:00Z http://dspace.aiub.edu:8080/jspui/handle/123456789/2896 Title: Fully thermal radiation and electric field on magneto hydrodynamic nanofluid convective mass transfer flow with activation energy Authors: Yasmin, Dilruba; Maleque, Kh. A. Abstract: The chemical reaction, viscous dissipation, non-linear thermal radiation, and activation energy on MHD laminar nano fluid flow across the vertical flat plate are considered in our present study. We also considered the uniform electric field (0,0,-E_0 )which is perpendicular to xy-plane. By taking suitable similarity functions and variables, Prandtl boundary layer typed momentum and energy equations are changed to simultaneous ordinary nonlinear differential equations (ODEs). The numerical solutions program of Simultaneous ODEs is constructed by bvp5c (Explicit Finite Difference Codes) built in MATLAB software. The numerical results are then displayed graphically with the help of MS-excel in the form of required physical properties (velocity, temperature and concentration) for considering various parameters. Skin friction (〖Re〗^(1/2) C_f ), Nusselt number (Nu 〖Re〗^(-1/2) ) and Sherwood number (Sh 〖Re〗^(-1/2) ) are provided in tabular form that is our physical interest. Validation of numerical results of the present mathematical model with previously published data are provided in table1. Mon, 22 Sep 2025 00:00:00 GMT http://dspace.aiub.edu:8080/jspui/handle/123456789/2896 2025-09-22T00:00:00Z http://dspace.aiub.edu:8080/jspui/handle/123456789/2806 Title: A customized ensemble machine learning approach: predicting students’ exam performance Authors: Ahmed, Rasel; Fahad, Nazif; Miah, Md Saef Ullah; Hossen, Md Jakir; Morol, Md Kishor; Mahmud, Mufti Abstract: Accurately predicting students’ exam performance is crucial for fostering academic success and timely interventions. This study addresses the significant challenge of predicting whether a student will pass or fail based on key factors such as study hours and previous exam scores. Using a dataset of 500 students sourced from Kaggle, we introduce a novel customized ensemble machine learning model, combining Random Forest (RF) and AdaBoost classifiers with a custom-weighted soft voting method (weights of 0.2 for RF and 0.8 for AdaBoost). The model’s hyperparameters were optimized via GridSearchCV with 10-fold cross-validation, ensuring robustness. The performance of the ensemble model was evaluated using metrics like Cohen’s Kappa, achieving superior predictive accuracy compared to baseline models. Our findings indicate that the proposed model not only improves prediction accuracy but also reduces prediction time, offering practical implications for educators and policymakers to design tailored interventions for at-risk students, ultimately enhancing educational outcomes. Sat, 26 Apr 2025 00:00:00 GMT http://dspace.aiub.edu:8080/jspui/handle/123456789/2806 2025-04-26T00:00:00Z http://dspace.aiub.edu:8080/jspui/handle/123456789/2801 Title: A Study on South American Economic and Environmental Interactions Through LSTM-Driven Analysis Authors: Ahmmed, Md. Mortuza; Babu, Md Ashraful; Puri, Shalini; Dadhich, Anjali; Mohapatra, Srikanta Kumar Abstract: Nowadays, energy utilization is crucial in driving a nation’s or a large territory’s economic progress. The focus of this proposed study delves into investigating the interconnection between economic progress and energy utilization, as well as examining the consequences of CO2 emissions in seven South American countries from 1971 to 2014. The panel model uses a cointegration method and Granger causality analysis to test the links among these factors in the chosen countries. The findings indicate a robust cointegration among the variables, notably highlighting a unidirectional long-term causality from energy utilization, CO2 emissions, and economic progress. Furthermore, a bidirectional long-term relationship between energy utilization and CO2 secretions is observed. The Long Short-Term Memory technique forecasts these regions’ economic progress, energy utilization, and CO2 emissions for the upcoming four years. Based on the empirical findings, the research suggests increasing energy utilization and renewable energy applications to stimulate economic progress in these regions while simultaneously implementing measures to reduce CO2 emissions. Mon, 23 Jun 2025 00:00:00 GMT http://dspace.aiub.edu:8080/jspui/handle/123456789/2801 2025-06-23T00:00:00Z