Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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Has files: YesSubject: search.filters.subject.Machine Learning (ML)

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    PublicationOpen Access
    Guru Gedara: Smart Mathematical e-learning Platform for Grade Five Students
    (Department of Computing and Information Systems, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, PO Box 02, Belihuloya, 70140, Sri Lanka., 2021-02-24) Rajapaksha, S. K; Thilakarthna, T; Wijesundara, W. G. M. V. S; Wickramasooriya, M, K; Ekanayake, E. M. O. M; Katupitiya, S. R. M. J. S
    This paper introduces a web-based educational support system developed aiming optimize mathematical knowledge of Grade 5 students. This application can be also used as a distance learning method for the lockdown situations occurred due to COVID-19 pandemic. Both primary class students and teachers face various difficulties, due to competitiveness of grade 5 scholarship examination. Consequently, emotion analysis which is a sub section in this system, uses sentiment analyzing to boosts the students’ emotional state, while Automated MCQ generated sub section can be used to gain mathematical knowledge, by facing MCQ quizzes. Additionally, Smart Video-based Learning Environment sub section can be used to gain knowledge related to mathematics by searching relevant videos, besides the Voicebased Question Answering section can be used to get answers orally for the questions asked in voice format. However, some sections use IQ level of each student to provide better solutions. Above all, it can be used at home as an online service while identifying and solving student’s weakness.
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    PublicationEmbargo
    ASD Screening for Toddlers via Physical Interpretation through Advanced AI
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Jayasekera, D.; Alwis, H.; Dissanayaka, H.; Mudalinayake, R.; Piyawardana, V.; Pulasinghe, K.
    Autism Spectrum Disorders (ASD) are generally causing challenges for significant communication, social interaction, and behavioral patterns to elderly people and children. Providing early treatments can make a huge advancement in the lives of children. Meanwhile, there is a limited number of systems to screen and identify ASD children. This research project is about developing a set of tools bonding together to one system called “AI - Bot Simon” to screen kids with ASD by filling the gap. In the system development process mainly, Audio, Facial expressions, Gestures, and the Gates of a targeted group of children are considered for screening. Since the target group is 6 months to 4 years, they are in early language development age. On the technical side of view Machine Learning (ML) and Deep Learning (DL) with Neural Networks (NN) are used for advanced screening and monitoring for automation of the process. In the last step of the development, all the outputs or information gathered from each tool or model, processed, analyzed, and provided to the users of the system by an Artificial Intelligence (AI) bot implemented with a web application and a mobile application whether children are suffering from ASD or not.