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Collection's Items (Sorted by Submit Date in Descending order): 61 to 80 of 318
Issue DateTitleAuthor(s)
2023Prediction of characteristics of cement stabilized earth blocks using non-destructive testing: Ultrasonic pulse velocity and electrical resistivitySathiparan, N.; Jayasundara, W.G.B.S.; Samarakoon, K.S.D.; Banujan, B.
2023Utilization of agro-waste groundnut shell and its derivatives in sustainable construction and building materials – A reviewSathiparan, N.; Anburuvel, A.; Virgin Vinusha, S.
2023Characterization of the shape of aggregates using image analysis and machine learning classification toolsDaniel Niruban, S.; Mohan, S.; Pratheeba, J.; Sathushka, Heshan Bandara Wijekoon; Sathiparan, N.
2023Potential use of groundnut shell ash in sustainable stabilized earth blocksSathiparan, N.; Anburuvel, A.; Virgin Vinusha, S.; Vithurshan, P.A.
2023Characteristic evaluation of geopolymer based lateritic soil stabilization enriched with eggshell ash and rice husk ash for road construction: An experimental investigationAnburuvel, A.; Sathiparan, N.; Anuradha Dhananjaya, G.M.; Anuruththan, A.
2023Performance of sustainable cement mortar containing different types of masonry construction and demolition wastesSathiparan, N.
2023Utilization of Groundnut Shell Ash as Cement Replacement in Stabilized Earth BlocksVinusha, S.V.; Vithushan, P.A.; Sathiparan, N.
2023Mathematical Model to Predict the Compressive Strength of Pervious ConcreteSathushka Heshan, W.; Janotha, P.; Shajeefpiranath, T.; Daniel Niruban, S.; Sathiparan, N.
2023Soft computing techniques to predict the electrical resistivity of pervious concreteDaniel Niruban, S.; Pratheeba, J.; Sathiparan, N.
2023Effect 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 techniquesSathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023A mathematical model to predict the porosity and compressive strength of pervious concrete based on the aggregate size, aggregate‑to‑cement ratio and compaction effortSathushka Heshan, W.; Thirugnasivam, S.; Daniel Niruban, S.; Sathiparan, N.
2023Characterization of the shape of aggregates using image analysis and machine learning classification toolsDaniel Niruban, S.; Sajeevan, M.; Pratheeba, J.; Sathushka Heshan, B.W.; Sathiparan, N.
2023Investigation of Compaction on Compressive Strength and Porosity of Pervious ConcreteSajeevan, M.; Daniel Niruban, S.; Rinduja, R.; Pratheeba, J.
2023Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approachSathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivitySathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivitySathiparan, N.; Pratheeba, J.
2023Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concreteSathiparan, N.; Pratheeba, J.
2023Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parametersSathiparan, N.; Pratheeba, J.
2023Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powderSathiparan, N.; Pratheeba, J.
2023Protein data in the identification and stage prediction of bronchopulmonary dysplasia on preterm infants: a machine learning studyPratheeba, J.; Bandara, K.M.D.D.; Nayanqjith, Y.G.A.
Collection's Items (Sorted by Submit Date in Descending order): 61 to 80 of 318