Browsing Faculty Annual Research Session by Publication Date

Browsing Faculty Annual Research Session by Publication Date

Sort by: Order: Results:

  • 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 ...
  • 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 ...
  • LOSSY IMAGE COMPRESSION USING FREEMAN CHAIN CODE REPRESENTATION 
    Somasundaram, S.; Niranjan, V.; Pujinthan, S. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    In this study, we suggested an algorithm that made use of a Freeman chain code-based compression technique. The method consists of two segments such as compression and decompression. The first is a compression algorithm ...
  • A REVIEW ON ASSESSING STRESS METHODS USING MACHINE LEARNING AND WEARABLE SENSORS 
    Kasuni Piyumika, Y.A. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    Stress is one kind of response to pressure. It can be good according to the situation. Stress management is a very important criterion now because it keeps up one’s stress level low, and health at risk. There can have ...
  • SECURE LIGHTWEIGHT NFV ARCHITECTURE ANALYSIS FOR IOT EDGE COMPUTING 
    Raveenthiran, S. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    The IoT is a massive trend within an industry. Its exponential expansion in cloud computing creates new problems. NFV has solutions enabling service providers to scale the networks, integrate intelligence into those networks, ...
  • AN ANALYSIS ON NSL-KDD DATASET USING MACHINE LEARNING TECHNIQUES FOR INTRUSION DETECTION 
    Ranaweera, K.M.; Sakuntala, Edirisingha Dilini (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    With the growth of the usage of computers over the network, security vulnerabilities on all the computer systems seem very difficult and expensive. The Intrusion Detection System (IDS) generates huge numbers of false alerts. ...
  • QUALITY PREDICTION OF WATERMELON USING RANKING FEATURE SELECTION METHODS AND MACHINE LEARNING ALGORITHMS 
    Pirunthavi, W.; Sharnitha, T.; Mayuran, P. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    This study was performed on the aim of detecting the quality of the watermelon with eight features; sound, color, root, belly button, texture, sugar rate, density, and touch which were obtained from the Kaggle website. Two ...
  • 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 ...
  • INTERACTIVE WEB-BASED PLATFORM TO BOOST THE AGRICULTURAL SECTOR IN SRI LANKA 
    Sooriyakumar, K.; Priyashantha, A.K. H.; Pratheesh, N. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    The agriculture sector plays a vital role in Sri Lanka’s economy. Interestingly, more than 30% of Sri Lankans are involved in the agricultural sector. The vegetable sector is the second most important sub-sector of island’s ...
  • 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. ...
  • Underwater Rover using IoT to Track Objects and Organisms under the Water 
    Thivaharan, S.; Suparoopan, S.; Gopy Prasath, S.; Sanoj, S.; Dinojen, T.; Amrithaa, P.; Lojenaa, N.; Kartheeswaran, T. (Faculty of Technological Studies, University of Vavuniya, 2022-10-04)
    Since the underwater world is so complicated, monitoring the underwater has always been challenging. A successful underwater robotic technology could aid the discovery of many hidden insights. This may also facilitate the ...
  • 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 ...
  • Real-Time Elephant Movement Detection for Human Safety: An IoT-Integrated Smart Fence Approach 
    Budhdhika, W.G.T.M.; Pathiraja, S.P.M.C.P.; Kalubowila, K.D.K.A.; Vinoharan, V. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The escalating Human-Elephant Conflict (HEC) in Sri Lanka has necessitated a transition from conventional mitigation methods to more sustainable and humane solutions. This study presents an Internet of Things (IoT)-based ...
  • IoT-Enabled Face Recognition Attendance Systems for University Students in Sri Lanka 
    Jayathilaka, V.A.N.T.; Ravichandran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This study presents a comprehensive face recognition attendance system designed for educational institutions in Sri Lanka. The system leverages Insight Face's buffalo l model as the primary recognition engine, achieving ...
  • A Cloud-Integrated IOT-Based Anti-Theft System for Home Using Image Processing 
    Tharsan, S.; Nusky Ahamed, T. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Home security has become a major concern due to the rise in burglary and unauthorized access incidents. This study proposes a cloud-integrated IoT-based anti-theft system using real-time facial recognition to enhance ...
  • AI-Powered Attendance System Using or Codes and Facial Recognition 
    Adikaram, K.K.J.K.B.; Mohomed Wazeem, S.K.; Ranaweera, S.D.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This research introduces a Safe and Smart Dual Authentication Student Attendance System using Facial Recognition and QR Code verification to eliminate proxy attendance and enhance operational efficiency in academic ...
  • Audio Deepfake Detection Methods: A Review 
    Janani, W.V.M.; Nissanka, N.B.A.S.C.; Thisaravi, K.G.A. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The emergence of audio deepfake technologies has raised new concerns in the area of digital security, privacy, and trust in media. Audio deepfakes are AI-generated synthetic audio clips that are capable of accurately ...
  • 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 ...
  • 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 ...
  • Sense Step: An Innovative Smart Cane for Visually Impaired Individuals 
    Tharsayani, M.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Sense Step is an innovative smart cane designed to empower visually impaired individuals through advanced assistive technology. Traditional mobility aids lack critical features to ensure user safety and independence, leaving ...

Search


Browse

My Account