Scopus Index Publications

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This collection consists of all Scopus-indexed publications produced by SLIIT researchers. Scopus is recognized worldwide as a leading and reputable academic indexing database.

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    Smart Intelligent Floriculture Assistant Agent (SIFAA)
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Samaratunge, U.S.S.; Amarasinghe, D.H.L.; Kirindegamaarachchi, M.C.; Asanka, B.L.
    Technology has become a vital aspect for various functional purposes throughout the world and some industries like floriculture have not adapted technology to solve and facilitate currently facing problems and provide the supply to the demand. Consequently, we have identified and implemented a solution that will address major aspects of such industry barriers. To address these major aspects we proposed a system Smart Intelligent Floriculture Assistant Agent (SIFAA), which uses expert knowledge with solutions and guideline such as identify diseases based on deep learning techniques. It also suggests remedies for diseases based on the expert knowledge, recommend best products for customers by using Reinforcement Learning (RL) technique, motivate cultivators by using demand forecasting, and apply feature engineering by using Linear Regression (LR) and ensemble advance LightGBM Regressors techniques.
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    Personalized Assistive Learning System for Primary Education
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Yapa, Y.M.T.S.; Fernando, W.S.I.; Sampath, W.H.M.K.; Kodithuwakku, K.D.D.I.; Samaratunge, U.S.S.; Lunugalage, D.
    Due to the COVID 19 pandemic, almost all educational institutions, including schools, remain closed. This caused a dramatic change in the educational systems. The sudden shift away from the classroom made the profound transformation of the teacher-centered education system prevail so far; consequently, the education of primary level students has been collapsed. Therefore, the primary students from grades 1 to 3 cannot acquire the primary education given by the school. This research proposes a personalized assistive learning system for primary education from grade 1 to 3 students, aiming to improve their learning skills. The proposed system aims to increase the automation and self-learning of students. A novel method is proposed to acquire personalized course materials for students of grades 1 to 3 according to their knowledge level. The system is founded on a solid theoretical foundation and enables children to grow cognitive and psycho-therapeutic skills such as drawing, writing, recognizing numbers, enabling self-learning, and focusing on measuring the progress of the students and reporting it to parents. CNN is the primary classifier used in image recognition and classification tasks in computer vision. The components' median accuracy is 94.74%.
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    Intelligent Violence Video Detection System
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Jayasanka, H.K.B.; Jayasanka, B.M.R.D.; Diyunuge, K.D.C.D.R.; Jayasekara, T.H.D.Y.M.; Lunugalage, D.; Samaratunge, U.S.S.
    Due to the busy and stressful lifestyle, humans tend to feel frustrated frequently. This harmful emotional behavior results in violations of several rules, regulations and legislation. Violence is one of the serious issues which emerges due to this situation. It also results in uncontrollable human behavior. This behavior can either be verbal arguments or even physical conflicts. A trend of recording and publishing videos related to these kinds of violations in various platforms can be observed widely at present. Therefore, the terms and conditions of these platforms are subjected to frequent changes. Difficulty in identifying and controlling of violent events will result in an increase of such cases. Due to these reasons, the demand for violence detection systems will be significantly increased. Efficient violent detection systems are lacking currently. But, the usage of artificial intelligence in these systems are further limited. Four major components have been used to achieve this goal. They are video-based, embedded audio-based, abused textbased and thumbnail-based violence detection. The machine learning and image processing techniques are used along with these components to improve the clarity of violence detection.