SLIIT Conference and Symposium Proceedings

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All SLIIT faculties annually conduct international conferences and symposiums. Publications from these events are included in this collection.

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    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, N
    Health 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.
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    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, N
    Corporate 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.
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    Easy Learning: Augmented Reality Based Environmental Studies for Primary Students
    (IEEE, 2019-12-05) Wickramapala, T; Jayawardhana, L; Tharaki, S; Senevirathna, S; Gamage, N; Wickramarathna, J
    Primary education is every child's fundamental right. According to the United Nations Educational, Scientific and Cultural Organization (UNESCO), primary schooling offers learning and educational activities typically intended to provide learners with basic abilities in reading and writing. The students find it difficult to identify trees and animals around them due to the lack of exposure to the natural environment. This research study introduces mobile based application (Easy Learning) which embraced augmented reality technology (AR) to motivate and aid learners in studying Environmental Studies in terms of identification of animals and trees. In order to provide sufficient knowledge about trees and animals, this research focuses on safe internet browsing and summarization for trees and animals. Easy learning suggest safe videos for kids and generates knowledge based questions to evaluate themselves as well. The study also evaluates whether the students like the features of the Easy Learning and the rate of knowledge change, through pre and post questionnaires given at the beginning and at the end of the implementation of Easy Learning. The findings proves that the Easy Learning as an interactive AR based learning instrument, for Environmental Studies which improves the learning curve.
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    Smart Platform for Cloud Service Providers
    (IEEE, 2019-12-05) Dharmapriya, W. A. S. P; Supipi, K. G; Ravindu Nimesh, G. G; Muhandiram, M. A. B. K; Rankothge, W. H; Gamage, N
    Cloud computing offers many types of computer related services without the direct active management of their users. Cloud Service Providers (CSPs) are responsible to manage these services such as placement of services in the cloud, resource allocation, network monitoring etc. The cloud service provider is required to monitor the network traffic, predict the dynamic traffic changes, and scale out the resources accordingly. We have proposed a platform for cloud service providers that automates the cloud management related services with following modules: (1) traffic monitoring, (2) traffic prediction, (3) virtual service instances placement and (4) traffic load balancing. We have used continuous and periodic approaches for traffic monitoring, Auto-Regressive Integrated Moving Average (ARIMA) model for traffic prediction, Randomized Weighted Majority Algorithm (RWMA) for virtual service instances placement and a threshold-based approach for load balancing. In this paper, we are presenting the performances of our cloud management platform, specially an evaluation of the algorithms used in above mentioned modules. Our results show that, using our proposed modules, the cloud management related services can be automated efficiently and reliably.