Browsing by Subject "Machine learning"

Browsing by Subject "Machine learning"

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  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 Air-Writing Tamil Alphabetical Vowel Characters 
    Puvanendran, R.; Senthooran, V. (Science and Information Organization, 2023)
    In recent years, there has been a lot of focus on gesture recognition because of its potential as a means of communication for cutting-edge gadgets. As a special category of gesture recognition, air-writing is the practice ...
  • Machine Learning Algorithms to Improve Early Diagnosis of Thyroid Disease: A Sri Lankan-Based Study 
    Senani, W.M.U.; Thirukumaran, S. (Faculty of Applied Science, University of Vavuniya, 2024-10-30)
    Thyroid diseases are a major health, well-being, and health care problem across the world. This study proposes a new thyroid diagnosis system using efficient feature selection techniques and machine learning methods for ...
  • Multiclass classification approach to identify the stage of autism spectrum disorder 
    Kayanan, M.; Wijekoon, P. (Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Sri Lanka, 09-01-20)
    Autism Spectrum Disorder (ASD) is known as a neurodevelopmental disorder that affects communication, social interaction and behavioural skills. ASD affects the children at the age of two years old and continues lifelong. ...
  • 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 ...
  • A Review on Integrating IoT Devices and Machine Learning for Disease Recognition and Management of Respiratory System 
    Wickramarathne, U.C.; Jayawickrama, M.G.; Tissera, S.S. (Faculty of Applied Science, University of Vavuniya, 2024-10-30)
    The convergence of the Internet of Things (IoT) and Machine Learning (ML) has brought significant advancements in healthcare, particularly in the detection and management of respiratory diseases. This comprehensive review ...
  • SENTIMENT ANALYSIS FOR SRI LANKAN NEWS PAPER HEADLINES USING MACHINE LEARNING AND DEEP LEARNING METHODS 
    Pirakasini, M. (Faculty of Applied Science, University of Vavuniya, 2023-10-25)
    Newspaper headlines have emerged as a ubiquitous form of communication in our modern society. These succinct news snippets hold the power to shape public perception and influence opinions on a wide range of topics. However, ...
  • SPAM EMAIL CLASSIFICATION AND IDENTIFICATION 
    Keerththana, K.; Charles, E.Y.A. (Faculty of Applied Science, University of Vavuniya, 2023-10-25)
    Email has become one of the most wide spread ways of communication in today’s society. Email spam, commonly known as junk email, spam mail, or simply spam, refers to unsolicited messages sent in large quantities through ...
  • Static Tamil Sign Language Recognition using Mediapipe Hand Landmark Detection and Machine Learning 
    Perera, G.V.D.P.P.; Jeyamugan, T.; Vijayakanthan, G. (Faculty of Applied Science, University of Vavuniya, 2024-10-30)
    Sign language is essential for communication among the deaf and hard-ofhearing communities, addressing the needs of over 430 million people globally, including 34 million children. By 2050, this number is expected to surpass ...