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Issue Date	Title	Author(s)
2023	Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and machine learning techniques	Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023	A mathematical model to predict the porosity and compressive strength of pervious concrete based on the aggregate size, aggregate‑to‑cement ratio and compaction effort	Sathushka Heshan, W.; Thirugnasivam, S.; Daniel Niruban, S.; Sathiparan, N.
2023	Characterization of the shape of aggregates using image analysis and machine learning classification tools	Daniel Niruban, S.; Sajeevan, M.; Pratheeba, J.; Sathushka Heshan, B.W.; Sathiparan, N.
2023	Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete	Sajeevan, M.; Daniel Niruban, S.; Rinduja, R.; Pratheeba, J.
2023	Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach	Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023	Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity	Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023	Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivity	Sathiparan, N.; Pratheeba, J.
2023	Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete	Sathiparan, N.; Pratheeba, J.
2023	Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parameters	Sathiparan, N.; Pratheeba, J.
2023	Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powder	Sathiparan, N.; Pratheeba, J.
2023	Protein data in the identification and stage prediction of bronchopulmonary dysplasia on preterm infants: a machine learning study	Pratheeba, J.; Bandara, K.M.D.D.; Nayanqjith, Y.G.A.
2023	SARS-CoV-2 Diagnosis Using Transcriptome Data: A Machine Learning Approach	Pratheeba, J.
2023	Role of Different types of RNA molecules in the severity prediction of SARS-CoV - 2 patients.	Pratheeba, J.
2022	Prolonged viral shedding prediction on non-hospitalized, uncomplicated SARS-CoV-2 patients using their transcriptome data	Pratheeba, J.
2022	Feasibility of Waste Calicut Tiles as Aggregates in Structural Concrete	Jayasekara, D.A.B.P.M.; Jayathilaka, S.T.N.; Somarathna, H.M.C.C
2022	Flexural Behaviour of Waste-based Natural Fibre Reinforced Composite from Palmyra Fibre and Waste Polythene	Wijesena, P.C.M.; Karunarathna, D.M.S.M.; Somarathna, H.M.C.C
2022	Feasibility of Cement Mortar System with Industrial Metal Fibre Waste	Perera, K.D.Y.G.; Ahamed, Y. L. F.; Somarathna, H.M.C.C
2022	Comparative Study of the Wind Codes: An Application to Forty-Six Storied Wall-Frame Structure	Kiriparan, B.; Jayasinghe, J.A.S.C.; Dissanayake, U.I.
2022	Iron removal from groundwater using granular activated carbon filters by oxidation coupled with the adsorption process	Thinojah, T.; Ketheesan, B.
2022	Community-based water governance for adaptation to water reduction and scarcity in Badulla district of Sri Lanka	Daluwatte, D.D.S.; Sivakumar, S.