Browsing by Author "Rajapaksha, U.U.S."

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Early Warning for Pre and Post Flood Risk Management by Using IoT and Machine Learning
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Ilukkumbure, S.P.M.K.W.; Samarasiri, V.Y.; Mohamed, M.F.; Selvaratnam, V.; Rajapaksha, U.U.S.
Flooding has been a very treacherous situation in Sri Lanka. Therefore, developing a structure to forecast risky weather conditions will be a great aid for citizens who are affected from flood d isasters. I n t his s tudy, t he a uthors explore the use of Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT), and crowdsourcing to provide insights into the development of the pre and post flood r isk management system as a solution to manage and mitigate potential flood risks. Machine learning and deep learning algorithms are used to predict upcoming flooding s ituations and r ainfall occurrences by using predicted weather information and historical data set of flood a nd r ainfall. Crowdsourcing i s u sed a s a n ovel method for identifying flood t hreatening a reas. Weather i nformation is gathered from citizens and it will help to build a procedure to notify the public and authorities of imminent flood risks. The IoT device tracks the real-time meteorological conditions and monitors continuously. The overall outcome showcases that machine learning models, deep learning algorithms, IoT and crowdsourcing information are equally contributing to predict and forecast risky weather conditions. The integration of the above components with machine learning techniques, together with the availability of historical data set, can forecast flood occurrences and disastrous weather conditions with above 0.70 accuracy in specific areas of Sri Lanka.
Embargo
Ontology Based Question Answering System for Sri Lankan Online School Education
(IEEE, 2022-10-04) Jayabahu, J.M.G.R.; Rajapaksha, U.U.S.
Today, distance education is one of the world’s most popular forms of education, and there are several opportunities for students to receive education online. Here, ontology can be considered one of the leading knowledge representation ways in e-learning systems. This research addressed students’ learning difficulties in Sri Lankan online education during the past two years. Students had to learn from home via online video conferences or audio series taught by teachers. However, students could not learn by asking questions or referring to the library materials to improve their self-studying knowledge. To overcome this issue, this research developed an ontology for school children in Sri Lanka, focusing on their IT syllabus and improving their self-education knowledge. This aims to provide personalized content while improving information searching. Students can ask questions from UI, and questions are taken as an input parameter and generate a query while cleansing for matching processes. Answers are generated by connecting to the index database and ontology repository, and the end output is displayed in the user interface. In the evaluation, it was targeted to categorize the questions according to relevant components, and the research shows the questions that are categorized into relevant categories while enhancing the performance.
Embargo
Question and Answering System For Investment Promotion Based on NLP
(IEEE, 2023-04-03) Panditharathna, P M R A; Rajapaksha, U.U.S.
Smart Question and Answering System for Investment Promotion is one such software/tool which will enable users (Investors, Investment Promotion Officers, Researchers, Professionals, etc.) to systematically ask the questionnaires related to the Investment and giving answers anytime anywhere. Preparing questions will be categorized according to investment sector based on Natural Processing Language. The levels would be, Knowledge, Comprehension, Application, Analysis, Synthesis and evaluation. Accordingly, Smart Question Generator will be modified to achieve the aspects related to each of the levels in investment promotion concept.Most likely these prepared questions would be of high standard predicting the questions as expected. This will also be a greater advantage for the investors to gain the potential out of this enabling them to invest money for projects and various information accordingly. Time consumption and communication gap is one such major issue which has not yet been practically attempted to. In order to overcome this issue, Smart Question and Answering will be a good assistant.