Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Open Access Alcohol brings burdens: A global and continent wise study on alcohol consumption and global burden of diseases(researchgate.net, 2022-07) Jayathilaka, R; Athukorala, o; Ishara, S; Silva, D; Pathirageid, TThis article investigates alcohol consumption attributable burden of diseases. The present study considers the overall effect of Human Development Index (HDI), Socio Demographic Index (SDI) and Gross Domestic Product (GDP) for income to measure how these variables impact Global Burden of Diseases (GDB), bringing a different perspective to the results. Data from over 177 countries mainly including European, Asian, North American, South American, African and Australian regions were analysed from 2000 to 2019. A Panel regression technique was applied, and Fixed Effects (FE) and Random Effects (RE) estimations were chosen to derive outcomes of the Hausman test. The findings reflected that alcohol consumption (wine, beer, spirit and other alcohol) has a positive significant relationship with the Global Burden of Diseases (GBD) globally and in the African continent excluding North America and South America. Human Development Index (HDI) have a negative impact on GBD on all countries. Particularly HDI have a negative impact on GBD in African continent except other continents. Also, in the African continent and globally, GBD has a significant positive and in Europe, a significant negative impact on the Socio Demographic Index (SDI). The findings demonstrate the overall picture of the impact of alcohol consumption and other variables on GBD and provide suggestions on how these variables should be tackled in the future to reduce GBD. This is the initial empirical study that investigates the impact of alcohol consumption, analysing the combined effect of HDI, SDI and income on the GBD of continent wise and globally.Publication Embargo IoT-based Monitoring System for Oyster Mushroom Farming(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Surige, Y.D.; Perera, W.S.M.; Gunarathna, P.K.N.; Ariyarathna, K.P.W.; Gamage, N.; Nawinna, D.Agriculture plays a major segment in the economy of Sri Lanka, a developing country. Mushrooms, farming is a popular option among the farmers as it consumes less space and less time for growing while offering a high nutritional value, but most farmers fail to obtain the best yield from their cultivations due to the defects and inefficiencies in the manual methods that are being presently used. This paper presents an ICT solution to avoid inefficiencies in the mushroom farming process. The system is developed focusing one of the popular mushroom type ‘Oyster Mushrooms’. The system offers four functionalities to perform mushroom farming precisely The system offers four functionalities to perform mushroom farming precisely. The Environmental Monitoring function is built with the support of a Long Short Term Memory (LSTM), Harvest time detection function is developed with the support of Convolutional Neural Networks (CNN) with Mobile Net V2 model, The Disease detection and control recommendation function is based on the support of CNN with mobile Net V2 model and the Yield prediction function is developed using the support of Long Short Term Memory (LSTM), The farmer is connected to the system through a mobile application. The system can monitor the environmental factors with an accuracy of 89% and the harvest time can be detected with an accuracy of 92%. Also, the system detects the mushroom diseases with an accuracy of 99% and predicts the monthly yield of a mushroom cultivation with an accuracy of 97%. The intense use of precise farming will eventually lead to high mushroom yields.