6 papers indexed
Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake, Adithya Galwatta
Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications. In high-resource languages, this has been extended a step further, and instead of predicting sentiment at…
Rahim Iqbal, Asfi Ahamed, Izzath Nisfer, Shazan Shaheed, Muhammadu Ilham, Nathali Athukorala, et al.
Sri Lanka has experienced a decade of progressive forest degradation and rising atmospheric pollution, yet district-level respiratory admissions have paradoxically declined, pointing to the confounding role of healthcare access. This study addresses that gap by constructing an 11…
Dilusha Chandrasiri, Maneesha Herath, Yasith Hewarathna, Muditha Herath, Gishan Bandara, Madara Mendis, et al.
This study presents a comprehensive analysis of bird diversity across Sri Lanka by integrating spatial, temporal, and environmental data. Bird observation records were combined with environmental variables, including weather conditions, air pollution, the Normalized Difference Ve…
Sonath Kirindage, Vihanga Nimsara, Sakindu Rajapaksa, Kavyanga Hathurusinghe, Lahiru Dilshan, Subavarshana Arumugam, et al.
Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have expanded, the transition to definitive care remains a critical bottleneck. This study evaluates national emergency resilience by q…
Ranuga Weerasekara, Heshan Nethmina, Manuja Ranathunga, Vinma Wettasinghe, Dinithi Navodya, Subavarshana Arumugam, et al.
Vegetable prices in Sri Lanka are highly volatile because the market is largely import-isolated, so supply disruptions quickly drive prices up. This study develops a machine learning framework to forecast such volatility by incorporating supply-chain-aware features and explicitly…
Dhinanjaya Fernando, Dinura Ginige, Kalana Lakshan, Chanupa Gurusinghe, Lasana Pahanga, Subavarshana Arumugam, et al.
This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data analysis, stationarity corrected time-series modeling (ADF, Johansen, VAR/VECM), and supervised learning. Results reveal remittance…