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    An Analysis of Social Networking for E-learning in Institutions of Higher Learning using Perceived Ease of use and Perceived Usefulness
    (Phcog.Net, 2022) Ajibade, Samuel-Soma M.; Adhikari, Nirmal; Ngo-Hoang, Dai-Long
    Higher education students and faculty use Facebook and Twitter. Researchers have also looked at social networking platforms in higher education. Social media has facilitated student-professor communication, collaboration, and engagement. To embrace students and teachers who utilize technology to learn and teach, it must be determined what influences their readiness to do so. This report tests the adoption of social networking media for e-learning in Nigerian utilizing the Technology Acceptance Model (TAM), which emphasizes perceived ease of use, perceived usefulness, and behavioural intention to utilize new technologies. Surveys were utilized for quantitative research. This study polled teachers and students from 4 Nigerian schools. Structural Equation Modeling was used to anticipate the model’s recommended factors (SEM). The study indicated that students’ and teachers’ behavioral intentions to use social media for e-learning in Nigerian universities are influenced by perceived ease of use and perceived usefulness.
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    Gaussian map to improve firefly algorithm performance
    (Institute of Electrical and Electronics Engineers Inc., 2022) Rabbi, Fazle; Ayaz, Muhammad; Dayupay, Johnry P.; Oyebode, Oluwadare Joshua; Gido, Nathaniel G.; Adhikari, Nirmal; Tabuena, Almighty C.; Ajibade, Samuel-Soma M.; Bassey, Mbiatke Anthony
    Firefly Algorithm (FA) mimics firefly behavior by flashing and attracts them. Firefly's global search mobility is improved for dependable global optimization using chaotic maps in this work. Investigations of benchmark problems with chaotic maps are carried out in depth. The system uses eight separate chaotic maps to fine-tune the firefly's enticing movements. By using planned chaotic transmissions instead of fixed values, the new method beats classic firefly methods. According to statistical data and the success rates of FA, the new algorithms improve the solution's performance and the reliability of global optimality.