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 EnglishBuddy–An approach for structured answer evaluation and feedback for O/L English language examinations in Sri Lanka.(GARI Publisher, 2017-12-31) Gurusinghe, A. M; Wijenayaka, W. K. D. P; Nawagamuwa, C. N; Priyadarshani, W. K. D. L; Gamage, M. P. A. WAt present, English has become a universal language. It may not be the most spoken language in the world, but it is the official language in a large number of countries. Proficiency in English both spoken and written has become a basic and a crucial requirement to get a decent white collar job and also to pursue higher studies or career development. Therefore, passing O/L with a good grade for English has become critical. But due to the busy life styles of students, teachers as well as parents, do not see this as a major problem and pay less attention to English compared to the other subjects. Since there is a limited time available for each subject at school, teachers might not be paying their full attention to the students who need teachers’ help. Sometimes parents also feel it is difficult to attend to the parents meetings and they might not know the actual grades of their children until the final results are given. This research provides a solution to the above problems by developing an automated system called “English Buddy” which will mark student’s structure based answers in English and help the students to learn and evaluate their knowledge alone. This web solution will be useful for teachers to upload material and check progress of the students and for students to learn and practice exercises and get feedback. It’ll be helpful for parents to be alert and follow the progress of their children. The systems is mainly build using techniques in Natural Language Processing and checked for accuracy with manual marking.Publication Embargo Determine the Most Appropriate Public Transportation Modes to Travel at a Given Time by Considering the Time Schedules and Live Traffic(IEEE, 2018-10-04) Gamage, M. P. A. W; Aponso, ATransportation is a need of a human being. Mainly transportation is divided into public and private transportation. However, most people prefer to use private transportation modes because it is easy to use. However, the usage of private vehicles is a reason for many problems. Some of the common problems are road traffic, environment pollution, increased fuel usage, increased cost of traveling and parking problems. There are some reasons, which discourage people from using public transportation. One of the reasons is that there is no proper method to find appropriate public transportation modes to travel. The appropriate transportation modes have to be decided by considering factors such as time schedules, road traffic, distance, cost and comfortability. It is difficult for people to find out transportation modes by considering all of these factors. This creates the need for an application, which gives suggestions of public transportation modes based on these factors. Based on the study, an application for suggesting appropriate transportation modes was implemented. As a prototype, this solution covers only the public transportation of Sri Lanka. There are few existing applications and past researches similar to the application, but there are few limitations in these existing applications. Mainly these applications have been developed not considering the road traffic as a factor that influences the modes of traveling, and they have not covered Sri Lanka yet.Publication Embargo Motorcyclists Safety Assistant App(IEEE, 2020-11-04) Fernando, A. H. V; Muthuarachchi, M. D. C; Anandakumar, D. R; Chamalka, W. N. R. B; Gamage, M. P. A. W; Amarasena, N. CMotorcycles are an important part of daily transportation. They are specially used to avoid traffic congestions downtown and most of the individuals tend to use a motorcycle because it takes less time to get to the destination. The rapid increase of motorcycle usage has led to a significant increase in the number of motorcycle-related accidents and fatalities. The reasons for accidents which were considered are speeding, collision with objects, lack of focus or drowsiness where only the rider's head is protected but not the body. And accidents may lead to death when help is not called immediately. By considering these, author introduces a Motorcyclists Safety Assistant Application (MSAA). This research tries to address four major factors that caused most road accidents and fatalities in Sri Lanka. They are excess speed, 360-degree threat detection, motorcyclist safety balloons, and emergency alert system. Here, MSAA can detect the vehicle's real-time speed and inform the user when a certain speed limit has been exceeded. Also, it has proposed a system which automatically detects threats that occur in each collision and alerts the rider via visual and audio cues. Moreover, the next system will be focusing on safeguarding the rider's body by inflating an airbag which will be connected to the rider's jacket. An automatic alert system is also introduced where the main objective is to mitigate the consequences of accidents by sending a message to the registered mobile using wireless communication techniques and checks whether an accident has occurred using vibration frequency limits. Location will be sent through the tracking system to cover the geographical coordinates over the area. The proposed domain successfully contributes to a drastic reduction in road accidents. The ultimate objective is to create a better future for everybody through road safety. The survey conducted to test the user satisfactory level, demonstrated high user satisfaction.Publication Embargo Smart Attendance and Progress Management System(Springer, Singapore, 2021) Krishnapillai, L; Veluppillai, S; Akilan, A; Saumika, V. N; De Silva, K. P; Gamage, M. P. A. WManagement of attendance may be a great burden on lecturers if done manually. This study focuses on finding an automated solution for taking attendance and keeping track of progress of a student in a smart way. The smart attendance system is generally using biometrics for identifying individuals. In this study, face recognition was considered for identification. The student's face is recognized and attendance is taken using face biometrics based on high-definition monitor camera. The images of the student are given as an input and image classification was done using CNN algorithm preventing duplicate entries for attendance. For tracking the progress of the student, the factors affecting the GPA are trained using Machine Learning algorithms. This research also aims to examine the effective progress of undergraduate students by taking past year records and find out the factors for their high and low output which will be helpful to improve their performance.Publication Open Access Knowledge Management framework for the supervision of IT postgraduate research in Sri Lanka(Springer, Singapore, 2022) Fernando, W. M. J. H; Gamage, M. P. A. WThe private sector higher education industry is increasingly attracting a knowledge-based community that depends critically on Knowledge Management (KM) and Knowledge Sharing (KS) activities to expand the quality of supervising postgraduate research students. Using the KM approach to share good research supervision knowledge will help junior research supervisors to conduct quality research with students and thereby help the supervision process to be more successful. The objective of this study is to suggest a conceptual framework that fits in the supervision process. This is conducted to investigate how KM and Information Technology (IT) can be used to develop a model for the supervision process. The framework highlights the critical KM activities in the research supervision process, and it is based on the Task/Technology Fit theory. Using this framework, the knowledge of the more experienced supervisors will be captured and used by junior supervisors in their supervision process.Publication Open Access Speecur: Intelligent pc controller for hand disabled people using nlp and image processing(GARI Publisher, 2017-06-30) Chathumali, E. J. A. P. C; Jayasekera, J. M. U. B; Pinnawala, D. C; Samaraweera, S. M. T. K; Gamage, M. P. A. WToday computers play a major role in human lives. Even though there are very sophisticated interfaces, differently abled people find it challenging to interact with the computer. There are some applications for disabled people, but people who have disabilities in hands do not have a proper application to interact with new technologies. The aim of this project is to develop software that act as an intelligent controller to facilitate hand disabled people when interacting with a computer. Proposed intelligent solution is based on speech recognition, image processing and human computer interaction. This application is capable of moving mouse cursor with face detections, activities based on voice commands, provide user authentication by voice recognitions and give suggestions using facial emotions. The solution will be using various high end techniques in Natural Language Processing, Machine Learning and Image Processing in order to improve the computer interaction. The proposed solution will be a great solution for the hand disabled people to interact with the computers like a normal user does.Publication Open Access Virtual student advisor using NLP and automatic appointment scheduler and feedback analyser(www.ijser.org, 2016-02-02) Suvethan, N; Avenash, K; Huzaim, M. A. Q; Mathusagar, R; Gamage, M. P. A. W; Imbulpitiya, AVirtual Student Advisor is a research project that mainly concerned on addressing a comprehensive solution to overcome the difficulties faced by the academic departments of any academic institutions. According to the context, the role of the Student Advisor is focused on helping students with problems related to their academic carrier at the University and also answer the general queries made by students related to the procedures conducted at the Institute. This happens to be a tedious and a very inefficient task for the Academics as they have to repeat the same answers for many students and also students coming to meet the academic in ad hoc manner without proper appointments makes both the student and the academic face lot of problems. The Virtual Student Advisor system mainly consists of three components; A Natural language based inquiry management module, Priority wise automatic appointment scheduler and Feedback analyzer. The inquiry management module is responsible in handling user queries based on frequently asked questions. Users can get the answers for a query by entering the question in natural language. This is implemented as a mobile application as it is convenient for students to ask questions from any place at any time. The system will answer the queries and if it needs more explanation it will be directed to the relevant advisor. Auto appointment scheduler handles the student appointment requests and helps in managing the schedules. This will be accessed by both Academics to set their free time slots and the students to request an appointment according to urgency. Feedback analyzer handles the entire process of student feedback taken for each subject starting from preparing feedback forms till analyzing the collected information. The lecturer can prepare a feedback form using the question bank in the system and customize it further to fit the requirements and after conducting the feedback the system can process the data and provide reports on varies views of the data such as tables and pie charts. The system uses Natural Language Processing to handle students’ queries by tokenizing the sentences and extracting answers based on keywords and comparing synonyms WordNet lexical database. The appointment scheduler uses priority based Round Robin CPU Scheduling Algorithm to schedule the appointments according to urgency. The Virtual Student Advisor system consists of a mobile application for students and a web application for both students and lecturers to access the information and conducted their daily tasks related to academic administration effectively.Publication Embargo Intelligent Trainer for Athletes using Machine Learning(IEEE, 2019-09-27) Attigala, D. A; Weeraman, R; Fernando, W. S. S. W; Mahagedara, M. M. S. U; Gamage, M. P. A. W; Jayakodi, TInternational professional athletes are looked after and trained by a team of professionals consisting of trainers and medical professionals among other. They make sure that the athlete is physically and mentally prepared to compete in a competition, and often train for years for the perfect results. Sri Lankan athletes however do not have the same luxury of being taken cared by a team of such professionals since they are young due to the lack of adequate resources in the country. `Optio' mobile application aims to provide a solution for this problem by creating a mobile application that the athlete constantly has access to, which will provide him/her with dietary, exercise and health related advice catered and customized to each individual athlete's needs. Consequently, this will provide a method which will let the athlete's trainer monitor their athletes easily as well as let them pick the most suitable athlete for a competition.Publication Open Access Agro-Genius: Crop Prediction Using Machine Learning(https://ijisrt.com/agrogenius-crop-prediction-using-machine-learning, 2019-10) Gamage, M. P. A. W; Kasthurirathna, D; Paresith, M. M; Thayakaran, S; Suganya, S; Puvipavan, PThis paper present a way to aid farmers focusing on profitable vegetable cultivation in Sri Lanka. As agriculture creates an economic future for developing countries, the demand of modern technologies in this sector is higher. Key technologies used for this problem are Deep Learning, Machine Learning and Visualization. As the product, an android mobile application is developed. In this application the users should input their location to start the prediction process. Data preprocessing is started when the location is received to the system. The collected dataset divided into 3 parts. 80 percent for training, 10 percent for testing and 10 percent for validation. After that the model is created using LSTM RNN for vegetable prediction and ARIMA for price prediction. Finally, for given location profitable crop and predicted future price of vegetables are shown in the application. Other than the prediction, optimizing for multiple crop sowing according to the user requirements and visualizing cultivation and production data on map and graphs are also given in the application. This paper elaborates the procedure of model development, model training and model testing.Publication Embargo Self-learning system with automatic feedback for text answers(IEEE, 2017-12-06) Kodithuwakku, K. T; Senevirathne, W. S. J. M. C. D; Randeniya, R. A. D. A; Wijewardane, M. M. D. D. A; Gamage, M. P. A. WThis paper presents details about a system developed using Natural Language Processing tools and methodologies to automatically evaluate a text answer by comparing the semantic similarity between the model answer with the provided student answer. System generates a score according to the matching percentage of the semantic similarity using the assigned marking pattern for the question. This system is embedded in a web application to be provided as a service for students and teachers to promote self-learning through question answering.