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Research ArticleOpen accessEvery word in the titleEvaluating E-learning Programs: An Adaptation of Kirkpatrick's Model to Accommodate E-learning EnvironmentsThair M. HamtiniProblem Statement: Kirkpatrick's model for the evaluation of training programs has been a staple in institutional learning since 1959 and is easily applicable to any training program. Approach: This model, however, was developed for traditional learning environments and has been regarded as antiquated, especially when one took into consideration the fact that institutional learning has increasingly taken on the form … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 7,957 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEffectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced PerformancePreeti Dhiman, Usha ChauhanIn this research, a pioneer passive approach for detecting and localizing tampering in images is proposed. In the past, image forgeries have created a huge impact in the world. Developments of various image processing technologies made it easier to tamper images with the objective to cover up or hide a significant feature in an image. In some situation, such as … …Journal of Computer Science, Vol. 22, Issue 10 · 3 Oct 2026 · 568 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegration of Local Large Language Models, Retrieval-Augmented Generation, and Adaptive LearningAnass Belcaid, Kamal ReklaouiIn recent years, many schools and teachers have started using closed Large Language Models (LLMs) to help with learning. These tools can be very helpful for tutoring and personal learning, but they also bring serious problems. One big issue is that they use cloud systems, which means student data is sent to outside servers. This can put privacy at risk … …Journal of Computer Science, Vol. 22, Issue 4 · 26 Mar 2026 · 3,923 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleWeb Based Multi Feature Propagation Analysis Model for Efficient Disease Interference and Recommendation Using Deep LearningM. Manoj Kumar, R. SivaAccurate prediction of chronic diseases is critical for proactive healthcare management. This paper proposes a Multi-feature Propagation Analysis-based Deep Learning Model (MPADM) to address this challenge. The model integrates diverse patient data, including medical, diagnostic, genetic, and historical features, collected from multiple sources. After preprocessing, the network is trained to calculate distinct Propagation Weights (PWs) for each feature category, Diagnosis … …Journal of Computer Science, Vol. 21, Issue 11 · 29 Jan 2026 · 1,709 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,900 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleReinforcement Learning in Financial Services: Modelling Payment Switching as a Multi-Armed Bandit ProblemIshaya Gambo, Christopher Agbonkhese, Segun Aina et al.The ever-evolving landscape of digital payments demands continuous innovation and self-improvement. This study addresses this imperative by simulating a model for payment routing, a crucial aspect of the digital payment ecosystem. To achieve this, industry professionals were interviewed to inform the approach, emphasizing data randomization for effective data collection. Using Python, a randomized dataset is created and three Reinforcement Learning … …Journal of Computer Science, Vol. 20, Issue 11 · 12 Oct 2024 · 4,710 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDFCite