IIUC Journals
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Item Investigation of some heterocyclic derivatives as sars-cov-2 main protease inhibitors: An in-silico approach(CRP, International Islamic University Chittagong, 2023-12) Kabir, EmranulA respiratory disease termed COVID-19 is brought on by one of the most potent ribonucleic acids (RNA) viruses. It has captivated the interest of scientists, virologists, and medical experts to create mechanisms to fight the disease. Computational research is needed on COVID-19 proteins and drugs due to their health risks. Till now, the only appropriate therapy was a vaccination. As a consequence, in the current study, a few heterocyclic derivatives with isoxazole, as well as pyrazole functionalities, are selected for docking studies with the primary proteases of SARS-CoV-2 (PDB ID: 7BQY and 6LU7). Compared to well-known antibiotics like azithromycin, remdesivir, and hydroxychloroquine, heterocyclic analogs 2-7 have significant docking scores (-8.0 to -6.2 kcal/mol). This study clearly showed that the pyrazole analogue 7 exhibited the most binding affinity with both 7BQY and 6LU7 (-8.0 and -7.1 respectively) proteins as well as the interactions between the residues of amino acid in proteins and drugs in the docked conformers to explain such high scores incorporating B3LYP and 6-31G+ DFT method.Item A comparative study on machine learning algorithms for improved prediction measures for COVID-19(International Islamic University Chittagong, 2022-02) Rahman, Md. ZiaurThe Corona-virus (COVID-19) is an emerging disease responsible for infecting millions of people since the first notification until nowadays. Corona virus causes respiratory ailment like influenza with symptoms for example, cold, coughs, fatigue, fever and gradually increases the breathing problem. The disease and symptoms are changing frequently thus due to time constraints it is literally impossible to test. Analysis of Covid-19 data using machine learning paradigm is becoming a major interest of the researchers in this situation. The aim of this study is to develop a better predicting model for Covid-19 patients. Patients feature can be assessed statistically and traditionally. But with this day and age of advanced machine learning approaches Covid-19 can be predicted using machine learning techniques with better accuracy. In this work four well known machine learning approaches was used for better prediction in Covid-19. However, this study focuses on optimizing machine learning approaches. Two optimization approaches employed for Grid Search and Random Search are used for fine tune in prediction.Item Security of E-Banking transactions in Bangladesh: Does it need more importance from COVID-19 perspective?(International Islamic University Chittagong, 2021-12) Islam, Md. Shahidul; Ahmmed, Monir; Chowdhury, Md. Shahnur AzadElectronic banking service has grown in Bangladesh since 2001. Now, it has become most suitable and convenient fund transfer method in COVID-19 pandemic situation. The security risk issue is the most vital in the e-banking fund transfer. A survey was conducted where the risk factors were measured on five-point Likert scale by 200 bankers and customers in the pandemic period through phone and E-mail. After necessary modification and correction of collected data, descriptive statistics, Cronbach’s Alpha, Kolmogorov-Smirnov test, Shapiro-Wilk test, Mann Whitney U test and Kruskal-Wallis H test were conducted in IBM SPSS Statistics 20 and MS Excel 2010to test the hypothesis of the risk factor. Result shows the highest banking transaction risk factor is Account Information Security and lowest banking transaction risk factor is Double Check identity from the perspective of customers. The result also shows that less than 2 years experiences of e-banking are significantly more satisfied than the risk factor of 2 years to 6 years and more than 6 years e-banking experiences