Browsing by Author "Samarakoon, S"

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationEmbargo
    Intruder detection using deep learning and association rule mining
    (IEEE, 2016-12-08) Thilina, A; Attanayake, S; Samarakoon, S; Nawodya, D; Rupasinghe, L; Pathirage, N; Edirisinghe, T; Krishnadeva, K
    With the upsurge of internet popularity, nowadays there are millions of online transactions that are being processed per minute thus increasing the possibilities of intruder attacks over the recent times. There have been various intruder detection techniques such as using traditional machine learning based algorithms. These algorithms were widely used to identify and prevent intruder activities in the recent past. Furthermore, multilayer neural networks[5] were also used in this regard to perform the detection. Hence multi-layer neural networks inherit fundamental drawbacks due to its inability to perform training due the problems such as overfitting, etc. In contrast, deep learning algorithms were introduced to overcome these issues effectively. We propose a novel framework to perform intruder detection and analysis using deep learning nets and association rule mining. We utilize a recurrent network to predict intruder activities and FP-Growth to perform the analysis. Our results show the effectiveness of our framework in detail.
  • Thumbnail Image
    ItemEmbargo
    MindBridge: Early Identification of Learning Difficulties in Children as a Supporting Tool for Teachers
    (Institute of Electrical and Electronics Engineers Inc., 2025) Mapa, N; Deshapriya, M; Premathilake, M; Samarakoon, S; Thelijjagoda, S; Vidanaralage, A.J
    Learning difficulties in children significantly impede academic success by affecting information processing, mathematical performance, and the learning of proper reading and writing. This paper proposes a Progressive Web Application (PWA) based on artificial intelligence (AI) and machine learning (ML) for identifying potential learning barriers. In contrast with standard diagnostic instruments, the proposed system is designed as a prediction tool with the potential for teachers to conduct timely and focused interventions. By automating feature extraction and reducing manual processing, the system overcomes the limitations of existing learning systems and improves early detection accuracy. Preliminary evaluations indicate that the PWA can effectively identify at-risk students and improve intervention methods and overall academic performance. This research contributes to the integration of computational methods and pedagogy, offering a scalable and low-cost solution for helping slow learners overcome their learning challenges.
  • Thumbnail Image
    ItemEmbargo
    WORDEX: Early Dyslexia Detection and Support
    (Institute of Electrical and Electronics Engineers Inc., 2025) Ganegoda, S.H; Dissanayake, O; Samarakoon, S; Jayawardana, N; Thelijjagoda, S; Gunathilake, P
    Dyslexia is a prevalent and complex learning disability that affects approximately 5% of primary school students worldwide. It often manifests as persistent difficulties in reading, writing, spelling, and overall academic performance, which can lead to long-term educational and psychological impacts if not addressed early. To facilitate the early identification and support of dyslexic learners aged 7 to 10, this paper introduces Wordex, an innovative and adaptive educational platform. Wordex is designed to screen for multiple dyslexia subtypes and provide targeted interventions through engaging, interactive, and personalized learning activities. The platform features an integrated machine learning-based screening system that analyzes user interactions and performance metrics to assess the risk of dyslexia. Upon identification, the platform delivers tailored remedial exercises that align with national school curricula, aiming to strengthen specific cognitive and linguistic skills. Wordex is developed using a modern technology stack including Spring Boot, Flutter, Python libraries, Firebase, and MongoDB, and incorporates capabilities such as image processing, supervised learning algorithms, real-time progress tracking, and cloud-based data management. A user-centered design approach and iterative testing cycles were employed to ensure the platform is accessible, intuitive, and pedagogically effective. Wordex contributes significantly to the field of educational technology by offering a scalable, research-informed intervention tool. Future enhancements include multilingual support, broader age group coverage, and integration with classroom learning environments.