Research Publications Authored by SLIIT Staff
Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4195
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.
Browse
116 results
Filters
Advanced Search
Filter by
Settings
Search Results
Publication Embargo Interactive Mobile Application for Initial Skills Development of Primary Students in Sri Lanka(IEEE, 2022-12-09) Liyanage, C.; Kavinda, U. A. D. S.; Dasanayaka, D. S.; Shehara, P. G. J.; De Silva, D. I.In many cases, children between this age are using smartphones and other technology devices, to play games, watch cartoons, take photos and sometimes the chance is getting higher than we think that children access unnecessary contents due to lack of guidance and unawareness of parents. This interactive mobile application is used as an adaptive learning tool for the primary school students. Utilizing children’s comfort with technology allows for the development of their talents. In math skills development, some attractively designed gamified activities to solve basic math questions are given according to the skill level the child is currently in. The accuracy was much higher in the Convolutional Neural Network approach as it recorded a value of 0.9919. In environmental skills development component, the app will ask child to identify the surroundings according to a flow, starting from the house and towards the garden using object detection and the results were detected with a higher accuracy level around 0.9-0.99 after training the Machine Learning model. And in the language skills development component the child is given activities to develop pronunciation skills using audio processing and finally the verification of online achievements of a child by Non-Fungible Token technology, is fulfilled via the app.Publication Embargo Rubber Buddy: A Mobile Application to Empower Rubber Planters of Sri Lanka(IEEE, 2022-12-09) Jayawardena, A; Ganegoda, K; Imbulana, S; Gunapala, G; Kodagoda, N; Jayasinghe, TThis research was conducted to develop a mobile application that provides expert solutions for the common problems faced by rubber planters in Sri Lanka. The application developed consists of four components, namely, identification of pests in immature rubber plantations and rubber nurseries; leaf disease identification; cover crop identification; and weed identification. Images taken using the mobile phone cameras are recognized using machine learning models developed using several convolutional neural network (CNN) architectures such as mobile net version 2 (MobileNet v2), VGG 16, VGG19, and residual networks (ResNet). After the images were recognized, the application will provide expert solutions and management strategies to the rubber planters. As most of the rubber plantations are located in areas with low network coverage, the application was designed to be operated in offline mode using TensorFlow lite technology.Publication Embargo Comparison of ARIMA and LSTM in Forecasting the Retail Prices of Vegetables in Colombo, Sri Lanka(IEEE, 2022-12-09) Fonseka, D.D; Karunasena, AIdentification of vegetable price trends is important to make better decisions in the production and market. Due to several factors, including seasonality, perishability, an imbalanced supply-demand market, customer choice, and the availability of raw materials, vegetable prices fluctuate quickly and are highly unstable. In this study price prediction was concluded using two models ARIMA and LSTM with retail price data for Cabbage, Carrot, and Green beans in Colombo from 2009 to 2018. According to the decision criteria of RMSE and MAPE, the LSTM model is superior to the ARIMA model in predicting the retail prices of vegetables. There were no studies have focused on predicting prices with novel technology in the Sri Lankan vegetable market. Hence the results of this study can be used to build an advanced forecasting model by the government and decision-makers in agriculture in Sri Lanka.Publication Embargo System to Improve the Quality of Water Resources in Sri Lanka Using Machine Learning and Image Processing(IEEE, 2022-12-09) Liyanage, M. H. S; Gajanayake, G.M.B. S; Wijewickrama, O; Fernando A, S.D.S. A; Wijendra, D; Gamage, A. IWater covers approximately 71% of the earth’s surface, but only 1.2% of it can be used for drinking. However, due to the amount of waste water released into water resources, the presence of harmful microorganisms, and natural occurrences such as eutrophication, even that water cannot be used directly for drinking purposes without purification. One method of purifying water is chlorination. However, if the chlorine level exceeds the standard, it can cause both long-term and short-term illnesses. As a result, a system is imposed to solve four problems: predicting the pH value of chlorinated drinking water, determining the quantification value of active sludge in a wastewater plant, detecting microorganisms in drinking water, and predicting the percentage of eutrophication in a water resource.Publication Embargo Machine Learning Based Solution for Improving the Efficiency of Sugar Production in Sri Lanka(IEEE, 2022-12-26) Kulasekara, S; Kumarasiri, K; Sirimanna, T; Dissanayake, D; Karunasena, A; Pemadasa, NAlthough sugar is a popularly used commodity in Sri Lanka, sugar manufactured within the country fulfill only a very small portion of the demanded amount. Sugar production is an intricate process which requires a considerable amount of expertise especially in the areas of cultivation, production and revenue prediction which may not exist in novice farmers. This research proposes a methodology which provides novice sugarcane farmers with expert knowledge on four main areas related to farming including weather forecast, sugarcane maturity estimation, production forecast and prediction of return sugarcane amounts from lands. ARIMA model is used for weather forecast whereas machine learning methods and multiple regression models were used for sugarcane maturity estimation and production of forecasts and returns respectively. The final ARIMA time series model was validated with p-value greater than 0.05 for Ljung-Box test with three different lag values. The Support Vector Machines model was identified as the best model with an accuracy of 81.19% for the sugarcane maturity estimation. The SVM model was trained using the HSV and texture features extracted from sugarcane stalk images using image processing techniques. The prediction of sugar production received a testing R-squared score of 87.75% and mean squared error of 0. Prediction of yield received a mean squared error of approximately 0 and R squared score of 98% on test data. The methodology used in this research could be used by novice farmers to increase their cultivation as well as sugar production.Publication Open Access Analysis on Current and Future Training Needs in Health Sector of Sri Lanka(SRAC - Romanian Society for Quality, 2022-08) Rajapakshe, W; Weerarathna, R. S; Pathirana, G.Y; Malage, M. HSri Lanka holds a unique position in South Asia as one of the developing nations to provide universal health. Government spending on welfare mainly involves compromising or constraining a country's development budget. It requires sound management strategies to utilize limited resources, including the human resource of the health sector. Training and development of health professionals can be identified as a critical component in strengthening the quality of health services. Fewer studies exist on Training Needs Analysis (TNA) on health professionals in Sri Lanka, and this study assessed the Training Needs of Sri Lanka's healthcare professionals. This is a cross-sectional study collecting data from 240 health sector professionals in Sri Lanka. The Hennessey Hicks Training Need questionnaire was used to obtain data. Data from the source was analysed through the oneway ANOVA to compare the training needs of various professional groups, and the Word Cloud Online tool was applied to analyse the open-ended questions. The study identifies published research evaluation, communicates with patients, identifies viable research, introduces new ideas, prioritizing works, assessing patients' needs, using technology, undertaking health promotion activities, collecting research information, and undertaking administrative duties as current training needs. While computer literacy training, training on new medical equipment, awareness programs on workplace stress-reducing, training on quality assurance certifications like ISO, programs on effectively communicating with patients, management training, and language training were identified as future training needs of professionals in the health sector. The study concluded that, continuous training programs as the preferred approach to access the performance gap. It also demonstrates that this awareness of information regarding the training needs is beneficial for the health sector policymakers, managers, employees, and the community. Having a better understanding of their job roles, performance needs, and involvement in the decision-making process is likely to motivate healthcare sector employees to improve service quality. These benefits will be reflected in positive outcomes on service quality, improving the overall healthcare system in the country.Publication Open Access Factors influencing the timely completion of construction projects in Sri Lanka(Public Library of Science, 2022-12-15) Abeysinghe, N; Jayathilaka, RTimely completion is a crucial factor for the success of a construction project, especially in the Sri Lankan context. This study aims to identify the most influential factors that affect the timely completion of construction projects in Sri Lanka. Thirty-nine factors were identified through a comprehensive literature review and experts’ opinions. A questionnaire incorporating the 39 project delay factors was distributed among 163 Civil Engineers, and responses were obtained. Random sampling method was adopted to select the sample. The Relative Importance Index (RII) analysed and ranked the project delay factors. The top ranked significant project delay factors were identified as shortage of skilled subcontractors/suppliers, shortage of labourers (Skilled, semi-skilled, unskilled), financial difficulties of contractors, delay in delivering materials to the site, and Covid-19 pandemic situation. According to the main three respondent types, i.e., clients/owners, contractors and consultants, the contractor related factors was the key group among others that delay a construction project. The scientific value of the study includes assisting the Sri Lankan construction industry to identify the factors affecting the timely completion of construction projects, and developing mitigation methods and strategies. Also, the stakeholders could duly schedule the construction work by identifying areas that need more attention. The contribution of this study would assist stakeholders to adopt a proactive approach by identifying mistakes on their part and minimising potential issues that lead to construction project delays in Sri Lanka. FiguresPublication Open Access Spatio-Temporal Rainfall Variability and Concentration over Sri Lanka(Hindawi, 2022-09-28) Pawar, U; Karunathilaka, P; Rathnayake, UChanges in precipitation patterns significantly affect flood and drought hazard management and water resources at local to regional scales. Therefore, the main motivation behind this paper is to examine the spatial and temporal rainfall variability over Sri Lanka by Standardized Rainfall Anomaly Index (SRAI) and Precipitation Concentration Index (PCI) from 1990 to 2019. The Mann–Kendall (MK) trend test and Sen’s slope (SS) were utilized to assess the trend in the precipitation concentration based on PCI. The Inverse Distance Weighting (IDW) interpolation method was incorporated to measure spatial distribution. Precipitation variability analysis showed that seasonal variations are more than those of annual variations. In addition, wet, normal, and dry years were identified over Sri Lanka using SRAI. The maximum SRAI (2.27) was observed for the year 2014 for the last 30 years (1990–2019), which shows the extremely wet year of Sri Lanka. The annual and seasonal PCI analysis showed moderate to irregular rainfall distribution except for the Jaffna and Ratnapura areas (annual scale-positive changes in Katugastota for 21.39% and Wellawaya for 17.6%; seasonal scale-Vavuniya for 33.64%, Trincomalee for 31.26%, and Batticaloa for 18.79% in SWMS). The MK test, SS-test, and percent change analyses reveal that rainfall distribution and concentration change do not show a significant positive or negative change in rainfall pattern in Sri Lanka, despite a few areas which experienced significant positive changes. Therefore, this study suggests that the rainfall in Sri Lanka follows the normal trend of precipitation with variations observed both annually and seasonally.Publication Embargo A Smart Aquaponic System for Enhancing The Revenue of Farmers in Sri Lanka(IEEE, 2022-10-19) Ekanayake, D; de Alwis, P; Harshana, P; Munasinghe, D; Jayakody, A; Gamage, NSri Lanka's agricultural sector confronts serious challenges from fertilizer shortages and agriculture-related chemical scarcity. Innovations comparable to aquaponic systems may be offered to Sri Lankan farmers to overcome these difficulties using IoT and ML technology. This research scope is to implement a smart and secure aquaponic environment monitoring system to forecast plant and fish growth factors, provide Sri Lankan farmers with insights into the environment's behaviors, and take measures according to the predictions utilizing control mechanisms. In this research, more exact predictions have been generated by the Random Forest algorithm model rather than the LSTM model, and most of the investigated parameters given good accuracy according to the absolute mean error (Media TDS-1.95, Media pH-0.06, Media Temperature-0.49, Env. Temperature- 0.94, Env. Humidity-2.70) except the environment light intensity (64.11). The ML solution studied in this research paper would increase the quality of traditional agriculture in Sri Lanka for greater productivity and economic benefit.Publication Open Access Challenging Arbitral Awards in the Construction Industry(SLIIT, 2022-02-11) Jayasinghe, R; Dahanayake, R; Edirisinghe, VOne of the most common alternative dispute resolution methods used in the Sri Lankan construction industry is arbitration. However, challenging arbitration awards based on legal grounds at the courts has been a current trend by the disagreeing party. If this situation occurs continuously, the purpose of having arbitration as an alternative dispute resolution method can be abandoned. Therefore, the study aims to identify the causes where arbitration is challenged in multi-story building construction projects in Sri Lanka through a case study. The methodological choice was qualitative and used semistructured interviews from six arbitrators and 2 case studies that referred to courts to challenge arbitration awards as research strategies. The study found the poor attitude of parties, lack of technical knowledge, reliability, and capability of the arbitrator to act according to the arbitrary acts imposed by the government as the main causes. Further. The study recommends arbitrators consider the reasons to act well enough and reject the cases if the arbitration is likely to be challenged in courts, train arbitrators to be reliable and on technical knowledge, and improve parties' attitudes by educating on the arbitration procedure and its benefits.