Research Publications
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Publication Open Access LEXISGURU: Mobile Application for Learning Basic Lexis in English for Kids(Springer Science and Business Media Deutschland GmbH, 2021-11-05) Jayasinghe, M. J. W; Hennayaka, W. H. M. A. D. H; Fernando, M. P. M; Thilakarathne, K. N. U; Samarakoon, U; Kumari, SLexis is an essential part of English vocabulary that puts a good foundation on a child’s English knowledge. In this rapidly globalizing world, it is fundamentally essential to learn English from a young age. In recent years eLearning, mobile applications have been developed for teaching Lexis to children. The market of educational mobile apps, especially for English language learning, has been rapidly growing. Especially in a country like Sri Lanka, English is not the mother tongue, it is the second language. So, when that second language is not taught right the child will lose interest in learning that language. The problem is that the existing lexical learning mobile applications does not aim at keeping the child interested and interactive in the learning process and in Sri Lanka, children find it difficult to understand these lexical parts. As a result, teachers and parents had to spend a lot of time to teach them those lexical parts. We designed and developed a mobile application called “LexisGuru” that uses interactive and effective ways to teach three lexical parts that are homophones, synonyms, and antonyms to children aged between 8–10 in Sri Lanka. This mobile application uses Machine Learning (ML), Image Processing (IP), gamification that includes collaborative environments, and speech recognition techniques. The developed mobile application was introduced to primary level learners, and they were all very attracted and interested while using this application. The attractive user interfaces, the pretests, and posttests, notifying the child when he loses focus while learning, using interesting stories and activities to teach lexis, playing a game with multiple players, and asking questions from the lesson and taking the voice inputs gave a new experience and showed that making the mobile application interactive as possible is an effective way to teach lexis to children.Publication Embargo E-Learning Education System For Children With Down Syndrome(Institute of Electrical and Electronics Engineers, 2022-09-16) Sampath, A.S.T; Vidanapathirana, M.W.; Gunawardana, T.B.A; Sandeepani, P.W.H.; Chandrasiri, L.H.S.S; Attanayaka, BThe World Health Organization assesses that Down Syndrome (DS) affects about 1 in 1000 births worldwide. Children with DS cannot learn, as usual, instigating numerous inadequacies that lead to formative issues such as trouble encoding information and low intelligence to interpret data for decision-making. As a superior technique for these kids' intercom-municating and logical intellect, free-hand sketch drawing, Voice training, and word prediction activities can be success-fully utilized. As the best way to express the mindset of such chil-dren, introducing an E-Learning system makes a friendlier ac-tivity than learning about the past. Because of the improvement of Artificial intelligence and its encouragement, E-Learning-re-lated exploration and applications are moving at an enormous advancement rate. The main objective of this project is to de-velop a reliable and efficient approach to predicting the devel-opment of DS children. Classifying and identifying those hand-written images and voice samples and those samples are given by children with DS compared to the teacher through the construction of a model structure. This research project specially considered local down syndrome children's hand-drawn images, voice samples, letters, numbers, and words as the input. As a result, it gives accuracy and similarity with the teacher's sam-ples and relates parts in the down syndrome children's samples. The system uses artificial intelligence technologies. Through that, the knowledge capacity of the DS children and their con-veyed articulation of that knowledge can be assessed for additional correlations and investigation.Publication Embargo Kaizen: Computer Vision Based Interactive Karate Training Platform(Institute of Electrical and Electronics Engineers Inc., 2022-11-04) Jayasekara, S. M; Weerasinghe, S. S.; Abayawardana, D.Y.W.; Welagedara, A. R.; Siriwardana, S.E.R.; Koralalage, M. NAll types of martial arts consist of several forms of combat used in self-defense, which are deeply rooted in many countries. Of all the martial art types, karate is considered the most well-known out of them all. Due to the pandemic situation in Sri Lanka, karate enthusiasts have lost the opportunity to train in a well-guided environment. As a result, even though virtual training came into play, it has continuously proved its ineffectiveness in evaluating the performance and accuracy of the trainees. The main objective of this proposed system is to virtualize the processes of a physical karate dojo. Kaizen - A Computer Vision-Based Interactive Karate Training Platform is a web-based application that functions as a virtual instructor. The proposed system consists of two main core components for Training and Assessments. The karate training component evaluates the techniques against a set of predefined joint angles. The BlazePose model is used for keypoint detection, and Analytic Geometry is used to extract joint angles. It is also integrated with Amazon Polly, a Deep Learning-based Text-To-Speech (TTS) service to produce real-time audio feedback. The assessment component has the capability to evaluate the trainees through a built-in Smart Evaluator based on a Recurrent Neural Network (RNN). Additionally, the capability to manage the assessments supports the instructors in conducting all the assessments virtually, overcoming the barriers in physical training.Publication Embargo Arunalu: Learning Ecosystem to Overcome Sinhala Reading Weakness due to Dyslexia(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Sandathara, L.; Tissera, S.; Sathsarani, R.; Hapuarachchi, H.; Thelijjagoda, S.Dyslexia is an impairment in ability in reading. People having Dyslexia has difficulties in identifying specific letters and words and identifying speech sounds and decoding the letters which leads to difficulties in comprehension, spelling and writing. Dyslexia may severely affects language development and impacts reading and other language based improvement and functioning. “ARUNALU: Learning ecosystem to overcome reading disabilities in Sinhala language due to Dyslexia” has been proposed as a multi-sensory mobile solution, in native language of Sri Lanka (Sinhala) and with effective screening and intervention methodologies recommended by health professionals. Objective is to deliver, a phonological support to enhance reading skills of dyslexic children by providing a machine learning based automated screening and intervention mobile solution. Through these reading environments, there's a reward system in intervention process to encourage the user, and also users and respective parties can analyze user's progress. The proposed system is mainly based on Voice recognition, Natural Language Processing, Machine Learning and Deep Learning concepts collaborating with reading and gaming environments. Core Objective of the proposed system is to come up with a better and effective screening and intervention methodologies for early identification of Dyslexia and provide phonological training to overcome Sinhala reading difficulties due to Dyslexia in a user friendly manner.Publication Embargo Dogodo: IoT Based Mobile Application to Provide Essential Health Services to Dogs(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Thilakarathne, L.V.I.S.; Salay, M.S.; Wijethilaka, M.G.R.; Fernando, T.S.C.; Sriyaratna, D.; Rupasinghe, S.Voice of dogs can be heard by people who listen to them. The more you listen, the more you learn about the dogs. This study proposes a platform to identify and observe dogs’ behavior and their activities by using the newest technologies. The proposed system will mainly cover the relevant areas that are supposed to be covered to full fill the pet owners’ expectations by providing necessary services such as internal health, voice recognition, and emotion translations and external issues such as skin diseases, breeding patterns, and breeding outcomes. Our priority is to emphasize necessary services in the mobile application and provide fluid services with fewer interruptions. Primarily research will offer an IoT device and a mobile application that covers the dog’s internal health and external health consecutively. The study revealed current developments and