Research Papers - Dept of Computer Systems Engineering
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Publication Embargo Evaluating the Success of Digital Learning in Sri Lankan Tertiary Education(IEEE, 2022-12-09) Weerapperuma, J; Nawinna, D; Gamage, NThis paper takes a social capital perspective to explain the underlying mechanisms that drive the success of digital learning in tertiary education in an emerging economy. It is crucial to explore ways in which the success of tertiary education can be maximized since these students will immediately contribute to the economy. Although digital-learning initiatives have advanced in developed countries, it is still in its early phases in many developing countries, including Sri Lanka. This study focuses on structural, relational, and cognitive dimensions of social capital and provides a new theoretical framework to examine its relationship to digital educational success. The study uses a quantitative approach where the data is collected from University students in Sri Lanka using a survey deployed online. The model is validated using the structural equation modeling technique. The findings of this study indicated that the three dimensions of social capital positively influence the success of digital education at the tertiary level. Further, this paper contributes to the existing literature on Social Capital Theory and provides valuable insights and recommendations for policymakers in the educational sector on improving digital learning achievements.Publication Embargo Solution to Measure Employee Productivity with Employee Emotion Detection(IEEE, 2022-12-09) De Silva, T.R.S.; Dayananda, K.Y.; Galagama Arachchi, R.C.; Amerasekara, M.K.S.B.; Silva, S; Gamage, NHealth and safety of workers has become a top priority in modern businesses. The reason is that it will have an impact on both individual and team output. In the last few decades, automatic facial expression analysis using machine learning has emerged as a promising and bustling field of study. In this study, the system primarily evaluates the efficiency of workers and, through the detection of their emotional states, determines their levels of motivation. The task completion rate of employees is measured by the system in the first component, and the system predicts the level of satisfaction that the employees will have. In place of linear regression, this component makes use of random forest regression, which boasts a higher degree of precision than its counterpart. The performance of workers on their tasks will be evaluated periodically, about once every fifteen minutes, and the results will be shown on a dashboard. The system will pick up on the emotions of the staff members throughout the second phase of the process. These characteristics will be used to assess the level of motivation inside the organization, with the end goal of increasing overall productivity. The accuracy of this emotion detection will also be checked periodically, namely once every fifteen minutes. The following part of the process monitors the use of the PC and calculates the level of productivity. It will be possible to get an increase in productivity if one monitors and keeps track of the application usage of each employee. The final components monitor the websites that employees visit and how they use the network. This component makes it easier to generate reports based on the utilization of the internet and the network, as well as information on performance and reports that summarize website traffic. When it is fully operational as an integrated system, most businesses will rely on this system as their primary driver of success.Publication Embargo LAWSUP - A Smart Platform to Assist Stakeholders of Business Law(IEEE, 2022-12-09) Sulakshi, U L H; Opatha, S D; De Silva, K S D; Sandeepa, M M A D N; Nawinna, D; Harasgama, H; Gamage, NCorporate law, sometimes known as business law, is the body of law that governs the rights, relationships, and behavior of persons, corporations, organizations, and businesses. Business Organizations, employees/laborers, and the public are involved in this area of the law accompanying lawyers, and legal advisors. Business organizations need legal advice. Employees face many difficulties and injustices at their workplaces. People who wish to start a new business, search for legal guidance. When one of these parties needs support, they must seek a lawyer, go to the lawyer, and get legal support. When delivering legal support to clients, lawyers are still going through a manual process. There are very few systems that have been implemented for the law domain so far, and those only search engine types of systems that are unable to support every stakeholder of this domain. There is no common platform for all these stakeholders to find solutions, connect with a good lawyer and get support. We have identified the main issues faced by business organizations, employees that need legal support, the general public, and lawyers, and developed a web solution by implementing Machine Learning, Classification Algorithms, Text mining, Natural Language Processing, and Web Crawlers.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 Embargo E-Medic – Autonomous Drone for Healthcare System(IEEE, 2021-04-12) Abeygunawaradana, p.; Gamage, N; De Alwis, L; Ashan, S; Nilanka, C; Godamune, PThis paper presents the implementation of a platform for the delivery of medicine using an autonomous drone. The platform consists of a Healthcare platform that connects doctors and patients and an autonomous drone that handles the delivery of medicine to the patients. This platform mainly contains several functionalities for the E-prescribing and delivery management of a drone. For patient management, the E-medic system uses a mobile application with facial recognition-based Authentication. Also, this platform is developed with separate web-applications to handle prescriptions, orders, and delivery management. Since this system uses an autonomous drone for deliveries, this platform also has functionalities to operate the delivery drone using a web application. the system uses REST APIs to operate the drone regardless of the distance to the ground station. The delivery drone can discover the shortest path to the destination and fly to that destination autonomously with the help of the computer vision-based obstacle avoidance system.Publication Embargo Agro-Mate: A Virtual Assister to Maximize Crop Yield in Agriculture Sector(IEEE, 2021-12-09) Dayalini, S; Sathana, M; Navodya, P. R. N; Weerakkodi, R. W. A. I. M. N; Jayakody, A; Gamage, NInformation Technology plays a vital role in the agriculture industry. The main goal of the project is to develop a mobile application to support farmers to take accurate decisions and help them with activities such as soil quality determination, best crop selection, rice disease prediction, and disaster prediction for the wet zone of Sri Lanka. To achieve the main goal the project has incorporated advanced technologies such as Deep Learning, Image Processing (IP), Internet of Things (IoT), and Machine Learning that can support farmers or investors in a way to maximize yield. ‘Agro-Mate’ application is developed in a way to facilitate the agriculture industry. ‘Agro-Mate’ consists of four components such as soil quality determination and fertilizer recommendation, best crop selection, rice disease prediction and recommendation, and natural disaster prediction and providing the recommendation. Also, the application suggests fertilizer when soil is lacking quality and provides recommendations whenever rice diseases or natural disasters are identified. The usage of android mobile devices in agriculture is one of the key components of the sector's growth, which facilitates the farmer's inaccurate decision-making to gain more quality and quantity of crops. Agro-mate’ is more likely to increase the productivity of crops and indirectly increase the GDP of Sri Lanka.Publication Embargo E-Medic–Autonomous Drone for Healthcare System(IEEE, 2021-02-19) Abeygunawaradana, P; Gamage, N; De Alwis, L; Ashan, S; Nilanka, S; Godamune, PThis paper presents the implementation of a platform for the delivery of medicine using an autonomous drone. The platform consists of a Healthcare platform that connects doctors and patients and an autonomous drone that handles the delivery of medicine to the patients. This platform mainly contains several functionalities for the E-prescribing and delivery management of a drone. For patient management, the E-medic system uses a mobile application with facial recognition-based Authentication. Also, this platform is developed with separate web-applications to handle prescriptions, orders, and delivery management. Since this system uses an autonomous drone for deliveries, this platform also has functionalities to operate the delivery drone using a web application. the system uses REST APIs to operate the drone regardless of the distance to the ground station. The delivery drone can discover the shortest path to the destination and fly to that destination autonomously with the help of the computer vision-based obstacle avoidance system.Publication Open Access Forecasting accuracy of Holt-Winters Exponential Smoothing: evidence from New Zealand.(New Zealand Journal of Applied Business Research, 2020) Dassanayake, W; Ardekani, I; Jayawardena, C; Sharifzadeh, H; Gamage, NFinancial time series is volatile, dynamic, nonlinear, nonparametric, and chaotic. Accurate forecasting of stock market prices and indices is always challenging and complex endeavour in time series analysis. Accurate predictions of stock market price movements could bring benefits to different types of investors and other stakeholders to make the right trading strategies. Adopting a technical analysis perspective, this study examines the predictive power of Holt-Winters Exponential Smoothing (HWES) methodology by testing the models on the New Zealand stock market (S&P/NZX50) Index. Daily time-series data ranging from January 2009 to December 2017 are used in this study. The forecasting performance of the investigated models is evaluated using the root mean square error (RMSE], mean absolute error (MAE) and mean absolute percentage error (MAPE). Employing HWES on the undifferenced S&P/NZX50 Index (model 1) and HWES on the differenced S&P/NZX50 Index (model 2) we find that model 1 is the superior predictive algorithm for the experimental dataset. When the tested models are evaluated overtime of the sample period we find the supportive evidence to our original findings. The evaluated HWES models could be employed effectively to predict the time series of other stock markets or the same index for diverse periods (windows) if substantiate algorithm training is carried out.Publication Open Access Sustainable manufacturing: application of optimization to textile manufacturing plants(Global Journals, 2020-10-21) Liyanage, I; Nuwanga, S; Anjana, R; Rankothge, W; Gamage, NThe main goal of manufacturing industry is to produce the end products on time with good quality and keep the resource wastage low. However, manufacturing industry face several challenges such as bottle necks in the workflow, unsynchronized production, and sudden increase in product demands.In this paper, we are proposing a management platform for textile manufacturing plants with following modules: (1) sewing workflow optimization (2) quality assurance workflow optimization and (3) finishing workflow optimizations. We have used Genetic Programming (GP) approach, to optimize the workflows, considering different factors that affect each workflow. Our results show that, using our proposed platform, the manufacturing workflows can be optimized and reduce the bottle necks in the workflows and resource wastage in the manufacturing plant.Publication Embargo AwareME: public awareness through game-based learning(IEEE, 2020-11-16) Dassanayake, D. K. M. P. M. M; Wijesinghe, S. N; Jayasiri, T. L. C; Keenawinna, K. A. R. T; Rankothge, W. H; Gamage, NIt is widely recognized that a nation with minimum problems relating to areas such as health, environment, infrastructure, and technology is a developed country [1]. However, the developing/ lower-middle income countries need many improvements in the above-mentioned areas, as they are still lacking in those areas [1]. Apart from the risk associated with these problems, the main challenge faced by developing countries is, making the public aware of these problems. In this paper, we are proposing a mobile game-based learning platform: "AwareME" which focuses on following problems: (1) health awareness (dengue fever), (2) environmental awareness (garbage disposal), (3) cyber security awareness (social media) and (4) safety awareness (road safety). The "AwareME" platform includes quizzes, 2D/3D puzzle games, and 3D action games with activities to improve the cognitive skills and awareness of the public. We have provided the results of an initial performance evaluation of "AwareME" platform.