Browsing Faculty Annual Research Session by Title

Browsing Faculty Annual Research Session by Title

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  • A DATA MINING APPROACH TO IDENTIFY THE FACTORS AFFECTING FOR THE ICT RESULTS IN G.C.E ORDINARY LEVEL EXAMINATION 
    Weerasooriya, P.G.P.S.; Kumara, K.K.P.L.; Kumasaru, W.L.S.; Kariyawasam, K.B.G.S.G.; Niroshi, P. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    he main aim of the paper is to identify the factors affecting the Information Communication Technology results in the G.C.E. Ordinary Level examination in Sri Lanka. The dataset was collected from the students who are ...
  • Deep Learning for Intelligent Waste Sorting in Sri Lanka: A Conceptual Review 
    Herath, H.M.P.H.S.; Kuruneru, R.P.D.; Logeesan, R.; Venuja, N. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Urban waste management in Sri Lanka is increasingly challenged by rising waste volumes, reliance on manual sorting, and inefficient collection systems. This review paper aims to examine how deep learning, particularly ...
  • Deep Learning-Based Detection of Deficiencies and Leaf Diseases in Chili Plants Using Image Processing 
    Kavindu Rashmika, W.A.D.; Semasinghe, T.M.N.M.; Vithanage, M.V.S.C.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Early detection of nutrient deficiencies and foliar diseases is essential to improve chili productivity, especially in rural communities where traditional testing is expensive and inaccessible. This study developed a deep ...
  • Deep Learning-Based Detection of Diseases in Mangifera indica (Mango) 
    Bandara, B.M.A.U.; Chathuranga, T.D.K.; Madhuwantha, D.A.J.A.; Saranga, T.A.D.S.; Mishawrnilanthi, S.; Hasitha Viduranga, G.R.; Dhanaranga, K.W.I.B.; Vinoharan, V.; Suthaharan, S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Mango (Mangifera indica) is one of the most commercially viable fruit crops in Sri Lanka. However, its cultivation faces increasing challenges due to various pests and diseases, which significantly reduce both yield quantity ...
  • Deep Learning-Based Plant Identification in Sri Lanka 
    Chayanthithan, C.; Rajagopal; Bandara, P.R.D.N.; Farhana, M.F.F.; Dharmasiri, T.N.; Bandara, U.M.J.M.; Jayasekara, J.M.T.N.; Saliny, N.; Nirosi, P. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Sri Lanka is home to a diverse range of plant species, many of which play critical roles in agriculture, biodiversity conservation, and ecological balance. Traditional methods of plant identification are often manual, ...
  • Designing a Socio-Technologically Adaptable, Scalable Peer-to-Peer Accommodation Platform to Support SMEs in Sri Lanka After the Crisis 
    Rajapaksha, R.W.V.A.S.C.; Ranasooriya, U.E. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The tourism industry is a globally significant sector that contributes substantially to economic growth. However, small and medium-sized enterprises (SMEs) in the tourism\sector face challenges in accessing global digital ...
  • Detecting Pests in Mango Crops using Machine Learning (ML) 
    Sankeetha, V.; Agalya, V.; Vinoharan, V. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Mango is one of the most important fruit crops in Sri Lanka, playing a vital role in both the agricultural sector and rural livelihoods. Despite its economic value, mango cultivation faces persistent challenges due to pest ...
  • Development of a Voice-Controlled Front-End User Interface Using AI-Based Command Recognition 
    Rakshika, U.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Artificial Intelligence (AI) innovations have revolutionized digital interactions, enhancing accessibility and usability in modern web applications. This project presents a voice-controlled front-end user interface (UI) ...
  • E-Document Classification Using Deep Learning 
    Wijesuriya, M.W.A.S.P.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The proliferation of digital content in the form of electronic documents necessitates efficient classification methods to manage and analyze this growing body of information. This research explores the application of ...
  • THE EFFECT OF FEATURE SELECTION TECHNIQUES ON THE ACCURACY OF HEART DISEASE PREDICTION USING MACHINE LEARNING 
    Lojana, J. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    Artificial intelligence has recently had a significant impact, particularly on the healthcare sector. The use of machine learning has made it possible to predict a number of serious diseases that are now difficult to ...
  • Enhancing Flow Rule Eviction Policy in Software Defined Network 
    Vithuckshiha, P.; Shriparen, S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Traditional network architectures struggle under high-volume, real-time traffic. Software Defined Networking (SDN) separates control and data planes to enable centralized control, but switch flow-table capacity remains a ...
  • Explainable Machine Learning-Based Fake News Detection Using NLP Techniques 
    Nawodi, N.A.R.; Wijegunasinghe, U.S.; Lakshan, W.K.; Vithuckshiha, P. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The rapid spread of misinformation on social media poses significant societal risks. This study develops an interpretable and accurate fake-news detection system that combines traditional supervised learning with Explainable ...
  • Exploring the Biometric Potential of Fingerprints for Blood Group Identification: A Survey 
    Weerasinghe, W.D.; Banu, N.F.N.; Sewmini, A.R.M.N.; Venuja, N.; Saliny, N. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Successful identification of a blood type quickly and correctly is essential for patient centered care and emergency settings. Traditional methods could include technically invasive blood collection (e.g., fingerstick), ...
  • A Framework for Offline Screen Time Control Inchildren: Focus on TV, Gaming Behaviour Studies 
    Asana Sajahan, F. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Effective management of children’s screen time has become a significant concern for parents, particularly working parents, as excessive exposure to digital devices can adversely affect children’s psychological and developmental ...
  • HANDWRITTEN CHARACTER RECOGNITION USING CONVOLUTIONAL NEURAL NETWORK IN THE CONTEXT OF TAMIL LANGUAGE 
    Mariyathas, Janotheepan (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    English language is having a high impact on handwritten character recognition. It is a difficult task to generate a model for character recognition especially for south Asian languages while they are having curves and dots ...
  • Harvest Guardian: A Mobile Toolkit for AI-Based Crop Disease Diagnosis and Farmer Decision Support 
    Thivakaran, V.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Agriculture in Sri Lanka is predominantly driven by smallholder farmers who face challenges in timely disease detection, access to localized expert advice, and planning around weather conditions. These issues contribute ...
  • HYPER PARAMETER TUNED ENSEMBLE APPROACH FOR HEART DISEASE PREDICTION 
    Premananthan, P.; Prasanth, S.; Mauran, K. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    Heart disease is the one of the leading causes of death globally. Despite the fact that the causes of heart disease varied from nation to nation. However, the risk variables would be practically the same. Heart disease ...
  • IDENTIFICATION OF EXTENSION NEEDS IN TEA PROCESSING: CASE OF LOW COUNTRY TEA FACTORIES 
    Samaraweera, M.K.; Wijeratne, M. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    Sri Lankan tea industry plays a major role in the Sri Lankan economy being one of the important sectors as a foreign exchange earner (SLRs. 240.6 billion in 2019) while providing employment opportunities for 400,000 families. ...
  • Image-Based Recognition for Sri Lankan Traffic Signs 
    Dhilakshan, T.; Disne, K.; Thadchanamoorthy, S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This research describes the development of an image-based traffic sign recognition system specifically designed for Sri Lankan road environments. The objective is to enhance road safety by accurately identifying local ...
  • Intelligent Handwriting Recognition for Preschool Children Using Convolutional Neural Networks (CNNs) 
    Abirami, S.; Jayarathna, J.H.S.S.M.; Abeysinghe, A.K.U.S.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This study addresses the challenge of recognizing handwritten numbers and alphabetic letters produced by preschool children. At this developmental stage, handwriting is often irregular, unstructured, and inconsistent in ...

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