Browsing by Subject "Machine learning"

Browsing by Subject "Machine learning"

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  • Agro Guard: A Smart IoT and Machine Learning-Based Assistant for Climate-Resilient Precision Agriculture 
    Libisanan, J.A.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Agriculture plays a vital role in ensuring global food security amid growing population pressures. However, climate change, soil degradation, and natural disasters such as floods pose serious challenges to maintaining soil ...
  • AI Based Student Absenteeism Prediction with Personalized Recommendations: A Study in Batticaloa Manmunai West Zone 
    Mathilojana, S.; Mithushika, M.; Shandru, M. (Faculty of Applied Science University of Vavuniya Sri Lanka, 2025)
    Student absenteeism is a growing issue, especially in rural and under-resourced areas like the Manmunai West Educational Zone in Bat ticaloa, Sri Lanka. Poor attendance has a strong impact on students’ academic performance ...
  • 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. ...
  • THE APPROACHES OF PERSONALIZED ADVERTISEMENTS IN TELEVISION USING MACHINE LEARNING 
    Anuruddha, I.D.; Suthaharan, S.S. (Faculty of Applied Science, University of Vavuniya, 2023-10-25)
    In recent years, personalized television advertising that uses machine learning methods to boost interaction with viewers and the success of advertisers have received a lot of attention. In this investigation, we have ...
  • Assessing Heart Disease Risk in Patients with Anemia through Predictive Modeling 
    Thulashika, R.; Elango, R. (Faculty of Applied Science University of Vavuniya Sri Lanka, 2025)
    Cardiovascular diseases are one of the leading causes of death worldwide and anemia is a common condition marked by low hemoglobin levels. Despite its prevalence anemia is often overlooked even though it plays a significant ...
  • 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 ...
  • Automated Student Attendance Management Using Real-Time Face Recognition 
    Kavindya, S.A.S.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This paper presents a facial recognition-based student attendance management system aimed at automating and improving accuracy for students attending extra classes. Traditional manual attendance methods are time-consuming ...
  • Carbon Sequestration Estimation in Paddy Fields Using Synthetic Aperture Radar (SAR) Data in Sri Lanka 
    Uthayadharshini, S.; Gajanthan, S.; Madhushani, S.I.S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Soil organic carbon (SOC) is essential for keeping soil healthy, improving crop growth, and tackling climate change. In rice-growing areas such as those in Sri Lanka, knowing how SOC is distributed helps farmers adopt ...
  • Cardiovascular Diseases Risk in People with Mental Illnesses 
    Indika, P.G.N.S.; Dias, G.K.A. (Faculty of Applied Science, University of Vavuniya, 2024-10-30)
    Cardiovascular diseases (CVD), including coronary heart disease, stroke, and peripheral arterial disease, are major global health concerns. Mental health disorders, such as depression, anxiety, and Post-traumatic stress ...
  • Cinnamon Price Prediction and Grade Identification: A Comprehensive Study in the Galle District 
    Helitha, E.D.K.; Pathulpana, D.G.S.; Nishadhi, R.P.B.; Ranasooriya, U.E.; Ekanayake, E.M.U.W.J.B. (Faculty of Applied Science University of Vavuniya Sri Lanka, 2025)
    The cinnamon industry in Sri Lanka, centered in the Galle District, one of the most important economic pillars, represents over 85% of the world supply of Ceylon cinnamon. However, the industry faces challenges from ...
  • Comparative Analysis of Machine Learning Models for Brown Spot Disease Detection in Rice Leaves 
    Kulaksiga, J.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Rice is a vital crop that feeds more than half of the world’s population, but its productivity is seriously threatened by diseases like Brown Spot, caused by the fungus Bipolaris oryzae. While many studies have shown that ...
  • Comparative Study of Machine Learning Models for Non-Communicable Disease Prediction 
    Mahendran, L.; Kuhaneshwaran, B.; Rasathurai, V.; Karunaharan, L.; Abishethvarman, V.; Prasanth, S.; Kumara, B.T.G.S. (Faculty of Applied Science University of Vavuniya Sri Lanka, 2025)
    Cardiovascular and other non-communicable diseases (NCDs), especially diabetes and cancers, are some of the critical global health problems that are resulting in a high rate of morbidity and mortality. The prevalence of ...
  • A Comprehensive Study of Hate Speech Detection in Child Abuse-Related YouTube Comments: Insights from Traditional and Deep Learning Approaches 
    Sweshthika, S.; Yasotha, R. (Faculty of Applied Science, University of Vavuniya, 2024-10-30)
    The widespread use of social media has significantly contributed to the proliferation of user comments by posing serious threats to individuals and communities. Due to the emotionally charged and nuanced nature of the ...
  • Detecting Hate Speech on YouTube Comments: A Comparative Study of Machine Learning and Deep Learning Techniques 
    Sweshthika, S.; Yasotha, R. (Korea Database Strategy Society (KDSS), 2026)
    The proliferation of social media has significantly amplified user interactions, but it also poses serious threats to communities through the spread of harmful content such as hate speech. The emotionally charged and ...
  • 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 ...
  • Efficient and Interpretable Machine Learning for Encrypted Malicious Traffic Classification 
    Chamuditha, P.G.L.; Madhuwantha, P.L.G.H.K; Senarathna, P.K.C.; Mayuran, P.; Senthooran, V. (Korea Database Strategy Society (KDSS), 2026)
    Communications that are encrypted, such as HTTPS, TLS, and VPN, have become popular tools for ensuring privacy; yet, they can be used for hiding malicious payloads, making intrusion detection more challenging. This study ...
  • EMOTION DETECTION FROM TEXT BASED SENTENCES USING MACHINE LEARNING 
    Jayasinghe, H.; Thirukumaran, S. (Faculty of Applied Science, University of Vavuniya, 2023-10-25)
    In the realm of digital communication, extracting emotions from text assumes a pivotal role in deciphering human sentiment. This research delves into the significance of discerning sentiments from textual content, leveraging ...
  • 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), ...
  • Extracting knowledge from Noise Information 
    Chowuraya, T.; Kirushanth, S.; Kabaso, B. (Academic Conference International (ACI), 2018-11-12)
    Information is an important part of creating knowledge. We live at a time when so much information is created. Unfortunately, much of the information is redundant. There is huge amount of online information in the form of ...