Research Publications

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Author: search.filters.author.Kodagoda, NHas files: Yes

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Now showing 1 - 10 of 56
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    PublicationOpen Access
    Web Block Craft: web development for children using Google Blockly
    (Institute of Advanced Engineering and Science, 2024-10) Gunaratne, M; Weerasekara, S; Weerakkody, D; Sashmitha, N; De Zoysa, R; Kodagoda, N
    Web Block Craft is an innovative educational application that uses the Google Blockly framework to teach web development to children aged eleven and above. The application serves as a comprehensive learning tool, allowing users to explore both frontend project and backend project development. The frontend project includes HTML, CSS, JavaScript, and DOM manipulation, while the backend project covers server building, web app security, application programming interfaces(APIs), and database management. Web Block Craft's unique block-based interface allows users to easily drag anddrop components into a dynamic working environment, resulting in an engaging experience with live output display and simultaneous code presentation. A unique feature of Web Block Craft is the integration of a platform within the application, which allows teachers to create lessons with step-by-step instructions for students. This new feature allows for a more structured learning experience, which improves understanding of web development concepts. To enhance the learning experience, the application provides extensive documentation, serving as a valuable resource for users to grasp the intricacies of web programming. By combining the power of Google Blockly with a creative user interfaceand educational resources, Web Block Craft provides a comprehensive learning environment that empowers creative web programming with confidence.
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    PublicationEmbargo
    Static Code Analyser to Enhance Developer Productivity
    (IEEE, 2023-05-23) Peiris, D. R. I.; Kodagoda, N
    One of the main metrics important to software development is productivity. The measure of productivity helps a organization/ individual or team identify how well their employees/ software runs and how they could improve. In this research paper, a new software is proposed along with a background study of how improving code quality will improve developers productivity and efficiency. The software proposed to aid developer productivity is a custom built static code analyser using python and it’s rule set has been tailored through carefully selected research papers and with feedback from experts of the software industry
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    PublicationEmbargo
    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, T
    This 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.
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    PublicationEmbargo
    Mobile Medical Assistant System for Laboratory Report Analysis and Medical Drug Identification
    (IEEE, 2022-12-09) Warnakulasuriya, D; Dewangi, T; Sewwandi, N; Rathnayake, M; Kodagoda, N; Suriyawansha, K
    It is quite common for medical drugs and prescriptions to be misidentified by hospitals and after drugs are being dispensed to the patients. Misidentification of medical drugs is more common among elderly and visually impaired patients. In hospital organizations, the leading medical error is adverse drug events. Another most common issue patients face is keeping track of medical lab reports. Our proposed mobile medical assistant system uses image processing to identify drugs with or without packaging, identifying prescription and medical lab reports. Furthermore, the mobile application will identify the trends of medical lab reports and predict next month’s results of the medical lab report of the patient using machine learning.
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    PublicationEmbargo
    EDUZONE – A Educational Video Summarizer and Digital Human Assistant for Effective Learning
    (IEEE, 2022-12-26) Wangchen, T; Tharindi, P.N; De Silva, K. C. C. C; Sandeepa, W. D. T; Kodagoda, N; Suriyawansa, K
    The availability of technology and the expansive nature of the internet have created a surge in the demand for online learning. Despite so many advantages, there are some existing drawbacks related to online learning. The lengthy recorded video lectures of different subjects and modules in a static manner, are extremely tedious for the learner to understand the contents available. And lack of assistance for academic-related problems of students is also stated as a major issue that comes with online education. EDUZONE provides a reliable solution to mitigate and overcome these challenges. This tool is educational assistance that generates a summarized version of the video lectures which depicts the overall idea of the whole video with the capability of a lecture notes generator along with a digital human which helps to clarify students’ problems and build an efficient conversational flow. The summarized video content can be used by the learners for revisions and as a quick reference before any examinations. In addition to generating short and precise content, EDUZONE also indexes any specific topics to make it easier to find content and generate class notes, highlighting all the important content. Overall EDUZONE can be considered a time-efficient educational assistant which helps students with their studies.
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    PublicationEmbargo
    Deep Vision-Data Mining To Find Insights and Visualization in Code Repositories
    (Institute of Electrical and Electronics Engineers, 2022-09-16) Ariyarathne, I.G.P.S; Wimalasuriya, M.K; Abesinghe, N.D.N.S; Edirisinghe, E.A.S.H.; Kodagoda, N; Kasthurirathna, D
    Deep Vision is a code mining system for analyzing and visualizing a repository's codebase so that its users may obtain a sense of the repository's insights. This system will examine codebases and support as many languages as feasible. This system visualizes the file structure, vocabulary and length change rates, comprehensibility and defect rates, etc. It is vital to have a comprehensive grasp of the codebase to manage the program's complexity by calculating multiple factors and presenting them in a descriptive and engaging dashboard to enhance the quality of the software process and the project's controllability. Improved code visualization may help improve code understandability while lowering development costs. In addition, our visualization regions and methodologies are one-of-a-kinds. To get rapid and reliable results, we will create new machine learning models and algorithms for analysis and new categories of a code repository. Our dataset for this research will be GitHub open-source code repositories
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    PublicationEmbargo
    Comparative Study of Parameter Selection for Enhanced Edge Inference for a Multi-Output Regression model for Head Pose Estimation
    (Institute of Electrical and Electronics Engineers Inc., 2022-11-04) Lindamulage, A; Kodagoda, N; Reyal, S; Samarasinghe, P; Yogarajah, P
    Magnitude-based pruning is a technique used to optimise deep learning models for edge inference. We have achieved over 75% model size reduction with a higher accuracy than the original multi-output regression model for head-pose estimation
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    PublicationEmbargo
    Automatic Question Extractor and Answer Detector in a Recorded Webinar
    (IEEE, 2022-08-18) Dissanayake, C; Kodagoda, N; Suriyawansa, K
    Online learning becomes the primary method of education due to the novel coronavirus (COVID 19). This research paper describes the automatic extraction of domain-related questions in a lecture video, identifies the answers given by the lecturer for both voice-based questions and chat questions. The paper also presents a method to identify whether a lecturer gave a valid answer for the chat-based questions in the later section of the video. Additionally, this paper describes the approach to identify the most accurate solutions from the custom search engine-based responses.
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    PublicationEmbargo
    A Gamified Virtual Learning Environment to Enhance Online Teaching and Learning Experience
    (IEEE, 2022-07-18) Tharaka, W.C.M. K; Dilanka, R. M. T; Perera, H.D.D. S; Rathnayake, R.H.C. S; Kodagoda, N; Suriyawansa, K
    In-class teaching not only concentrates on lecture content delivery but also on maintaining strong mutuality between lecturer-students and student-student. Online lectures are gaining popularity due to the Covid-19 pandemic. However, the learning-teaching process has become ineffective because existing video conferencing solutions are not intended for academic purposes. This research was conducted to identify the pain points of online education and develop an enhanced software solution. A user survey confirmed that an isolated environment tends to diminish attentiveness during online lectures. Also, it is difficult for teachers to observe the attentiveness of all the students. As a solution, student attentiveness was measured using their facial expressions and collected data shown to lecturers through a virtual student behavioural environment. The physical separation causes students to feel isolated during lectures, which can negatively affect their academic development and social and psychological development. The developed application also provides a virtual group study environment as a feature. According to the results gathered in the user acceptance testing phase, it was found that the attention detection feature helps students keep their attention at a significant level. Further, 9 out of 10 teachers who participated in the testing acknowledged that the simulated student behavioural view could provide a more immersive experience. 71% of students preferred the new collaborative virtual environment, and students further elaborated that the virtual environment was more likely the physical group studies. 72% of students mentioned that the collaborative group study tool helped eliminate isolation during group studies.
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    PublicationOpen Access
    LEARNING STYLES BASED CHECKLIST FOR INSTRUCTIONAL MATERIAL FEATURES IN E-LEARNING
    (researchgate.net, 2020-03) Suriyawansa, K; Kodagoda, N
    E-learning is a rapidly growing industry with a large number of users around the globe. The learning process of e-learning mainly depends on different learning techniques of instructional materials provided in the learning environment. Learning materials are the key component of comprehending information in an e-learning environment. Thus, it is vital to develop e-learning learning materials that are beneficial for the target learners. Different learners have different preferences in learning. Several learning style models have proposed over the years to define the different characteristics of different types of learners. This paper describes seven such learning style models and define learner characteristics focused on each of these models. Then the defined characteristics of each learner style in all seven learning style models are tabularized to emphasize the overlaps of learner characteristics focused in different learning style models. As the next step, a list of unique learner characteristics with reference to learning styles was defined using the information in the table with all learner characteristics. This paper also defines features available in e-learning materials. At present, MOOCs (Massive Open Online Course) can be defined as the key pillar of e-learning. Thus, several MOOCs provided by Coursera platform were analyzed to derive features of e-learning materials or elearning environments. The identified unique learner characteristics of learning styles are then mapped with the list of features in learning materials in an e-learning environment. The final result of this research is a checklist which can be used by e-learning content developers to classify how the instructional materials are effective for the target learners. This checklist defines the satisfied learning styles of all seven learning style models by each identified feature of e-learning instructional materials. It can be used as a guideline for e-learning content developers to determine the features that has to be included in the learning materials to provide an effective learning environment for the target learners