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264 results for “e-learning application”
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Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,924 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssociation Rule Analysis of Qualitative Contribution Evaluation of Faculty Using Distributed Mining with Apriori AlgorithmMylene Bello Ragobrio, Rhoderick D. Malangsa, Rujube Hinoguin-HermanoTeacher evaluation, where students serve as evaluators, is common in Philippine educational institutions. Student input based on teacher performance is considered crucial for fostering faculty development and professional advancement. The government implemented National Budget Circular (NBC) No. 461 which standardizes promotion procedures, encouraging equity and uniformity in faculty promotions among State Universities and Colleges (SUCs). Financial assistance comes from the … …Journal of Computer Science, Vol. 21, Issue 11 · 27 Jan 2026 · 1,596 accessesView PDFCite
Research ArticleOpen accessIn the abstractICT-Based Blended Learningin the Information Age: AnApproach for Enhanced Learning MotivationFayez Khazalah, Yousef Aljaraideh, Anas Husain, Ahmad RabeeBlended Learning (BL) learning has emerged as a transformative approach in higher education, combining traditional face-to-face instruction with the advantages of online learning to enhance the educational process. BL has recently relied on Information and Communication Technology (ICT) to facilitate its implementation and usefulness. This study relies on Self-Determination Theory (SDT) to demonstrate the potential of ICT-based BL to support … …Journal of Computer Science, Vol. 21, Issue 12 · 26 Jan 2026 · 1,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractMERAKI: An Online Collaborative Learning Platform Developed Using the UWE MethodologyPercy De-la-Cruz-VdV, Yesenia Torres-Donayre, Hugo Vega-Huerta et al.In the digital era, education has evolved with the integration of technologies that optimize the teaching-learning process. This article presents the need for more efficient online collaborative environments that overcome the limitations of traditional platforms, fostering meaningful interaction between students and teachers. To address this need, the collaborative platform “MERAKI” was developed using the UML-Based Web Engineering (UWE) methodology. This … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,149 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,655 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnnotation of Facial Expressions (Navarasa) in Videos Using Deep LearningReshma M R, Kannan B, Jagathy Raj V P, Shailesh SFacial expression plays a significant role in understanding human behavior, alongside other relevant elements such as body posture, gait, and hand gestures. In the context of Indian Classical Dance (ICD), these elements work together to convey the stories depicted by characters from Indian mythology. Accompanying songs and shlokas evoke emotions, reflected in performers' facial expressions known as the performance. In … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 4,097 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,947 accessesView PDFCite