SLIIT Conference and Symposium Proceedings
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All SLIIT faculties annually conduct international conferences and symposiums. Publications from these events are included in this collection.
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Publication Open Access Predictive Modeling for Personalized Cancer Therapy Using Reinforcement Learning(Faculty of Engineering, 2025-09-09) Edirisinghe M.M; Gunarathne,J H M S MAdaptive therapy is transforming cancer treatment by enabling dynamic, patient-specific interventions that adapt to tumor progression and individual variability. Unlike traditional fixed-dose regimens, adaptive therapy leverages the evolutionary dynamics of tumors to extend treatment effectiveness and delay resistance. Reinforcement Learning (RL), an area of artificial intelligence focused on sequential decision-making, offers a robust framework for optimizing these adaptive strategies. RL can learn optimal treatment policies by interacting with computational models of tumor growth and drug response, continuously adjusting regimens based on observed tumor states, resistant cell populations, and biomarkers. This approach allows for the creation of personalized therapies that maintain long-term tumor control while minimizing toxicity and the emergence of resistance. The integration of RL into predictive modeling for cancer therapy represents a paradigm shift, enabling smarter, safer, and more effective treatments that are dynamically tailored to each patient’s evolving disease. This paper reviews the foundational concepts of adaptive therapy and RL discusses tumor modeling approaches, examines RL algorithms, and addresses current challenges and future directions in the field.Publication Embargo 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.Publication Embargo Crime Analysis, Prediction and Simulation Platform Based on Machine Learning(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12) Herath, I.S.; Dinalankara, R.; Wijenayake, U.As a global social-economical problem, crime has shown complex correlations with spatial-temporal, socio-economical, and environmental factors. Understanding patterns and interactions in the crimes is essential to prepare better to respond to those criminal activities. This study is focused on research and development of crime analysis, prediction and simulation platform that provides descriptive analysis, predictive crime analysis, Reinforcement learning based crime entity simulations and safest route navigation services based on crime data from the city of San Francisco. Ultimately, the proposed crime analysis, prediction and simulation platform provides critical information on root causes and statistical patterns of crime and future crime predictions for the policymakers and security officials to create strategies to minimise the crimes.