Facial mask detection in low light environment

• Main Author: Kennedy Gregory Mojuntin
• Format: Academic Exercise
• Language: English; English
• Published: 2022
• Subjects: QA76.75-76.765 Computer software
• Online Access: https://eprints.ums.edu.my/id/eprint/33273/1/FACIAL%20MASK%20DETECTION%20IN%20LOW%20LIGHT%20ENVIRONMENT.24pages.pdf; https://eprints.ums.edu.my/id/eprint/33273/2/FACIAL%20MASK%20DETECTION%20IN%20LOW%20LIGHT%20ENVIRONMENT.pdf; https://eprints.ums.edu.my/id/eprint/33273/

Cloud computing is on-demand service and resources available for the computing systems nowadays, especially in the data storage without interference from humans. Task scheduling and resource allocation are essential aspects of cloud computing. This research proposes task scheduling in cloud computing using a hybrid genetic algorithm and naked mole rat algorithm to solve the task scheduling problem. Genetic Algorithm (GA) was widely used because of its accuracy and simplicity. However, it will become slower in some instances that include a more significant problem size. Hence, Naked Mole Rat Algorithm (NMRA) can optimize the efficiency and performance because it provides an efficient scheduling mechanism. NMRA also will minimize the execution time and deadline. This research will compare hybrid Genetic Algorithm and Naked Mole Rat Algorithm (GA-NMRA) with other meta-heuristic algorithms. Other than that, this research will use Waterfall Model Methodology as its research methodology. Furthermore, this research will apply hybrid GA-NMRA for task scheduling in cloud computing environments. This research will conduct several experiments in Cloud Computing Environment Simulation comparing GA, NMRA and the hybrid GA-NMRA to get research results. The result will show that GA-NMRA will improve the quality of service, minimize the time execution and deadline for a given task.