Browsing by Author "Islam, Anik"

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    Efficient carbon dioxide mitigation strategies for indoor spaces
    (BRAC University, 2025-05) Ahsan, Ahmmed Fardan; Islam, Anik; Karim, Md. Junayed; Poll, Md. Jakaria; Mohsin, Abu S. M.
    Indoor CO₂ accumulation poses significant risks to human health and cognitive function, especially in confined and poorly ventilated spaces. This project investigates and compares three strategies for efficient CO₂ mitigation indoors: chemical absorption, electrochemical conversion, and a microalgae-based bioreactor system. Based on sustainability, cost, and effectiveness, the microalgae-based approach was selected and implemented. The designed system monitors environmental parameters in real time on display and remotely and optimizes CO₂ absorption by microalgae. Results indicate notable improvements in indoor air quality, demonstrating the potential of bio-integrated solutions for future smart and sustainable indoor environments.
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    Measuring the Effectiveness of Software Code Review Comments
    (Communications in Computer and Information Science, Springer, 2020-07-18) Hossain, Syeda Sumbul; Arafat, Yeasir; Hossain, Md. Ekram; Arman, Md. Shohel; Islam, Anik
    Code reviewing becomes a more popular technique to find out early defects in source code. Nowadays practitioners are going for peer reviewing their codes by their co-developers to make the source code clean. Working on a distributed or dispersed team, code review is mandatory to check the patches to merge. Code reviewing can also be a form of validating functional and non-functional requirements. Sometimes reviewers do not put structured comments, which becomes a bottle neck to developers for solving the findings or suggestions commented by the reviewers. For making the code review participation more effective, structured and efficient review comments is mandatory. Mining the repositories of five commercialized projects, we have extracted 15223 review comments and labelled them. We have used 8 different machine learning and deep learning classifiers to train our model. Among those Stochastic Gradient Descent (SGD) technique achieves higher accuracy of 80.32%. This study will help the practitioners to build up structured and effective code review culture among global software developers.