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48 results for “learning module”
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Research ArticleOpen accessPhrase in the titleDevelopment and Assessment of the English Grammar Asynchronous Online Learning Module before Being Applied in Real LessonAnthony Anggrawan, Christofer SatriaCurrently the orientation of higher education in Indonesia has shifted to online-based education. Unfortunately not all universities are ready to implement asynchronous online teaching. The question is whether the developed asynchronous online teaching module can meet the desired quality qualifications. Therefore the objective of this study is to conduct an assessment of the asynchronous online learning module before it is … …Journal of Computer Science, Vol. 16, Issue 11 · 7 Nov 2020 · 7,290 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDESIGN AND DEVELOPMENT OF A RECOMMENDER SYSTEM FOR E-LEARNING MODULESBaseera, SrinathExtensive literature review revealed that, different recommender systems for E-learning were developed. A preliminary version of the development was undertaken and evaluated in an experiment during an introduction psychology course in an open university. The activities were integrated in to a model which operates on a network. No curriculum structure was assigned and the users were allowed to undergo learning … …Journal of Computer Science, Vol. 10, Issue 5 · 26 Dec 2013 · 7,097 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Framework for Design of Intelligent Simulation EnvironmentAli Azadeh, Farid GhaderiThis study describes a framework for design and development of intelligent simulation environment. The intelligent simulation environment prescribes an integrated rule-based approach to simulate and optimize a manufacturing system. An intelligent simulation model is a computer program capable of improving its performance by referring to production constraints, system's limitations and desired targets. It is a goal oriented, flexible and integrated … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 6,702 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 670 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Disease Detection via an Improved Residual NetworkGuolin Chen, Weifeng Liu, Xinyu Zou, Xiaoxia LiDeep learning has shown substantial potential across many domains, and crop disease detection is no exception. This study investigates the application of deep learning to crop disease detection, systematically evaluating the performance of convolutional neural networks of different depths. Building on the classical ResNet-50 as the base model, we introduce a Squeeze-and-Excitation (SE) attention mechanism to enhance feature extraction. The … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 31 Jul 2026 · 898 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing DevOps Pipelines With Viral Spread Optimization and Hybrid Deep LearningDileepkumar S R, Juby MathewModern software teams rely on Continuous Integration and Continuous Deployment (CI/CD) pipelines to automate testing and delivery. However, these pipelines often waste resources by running unnecessary tests and failing to predict which builds will fail. This study presents a new framework that addresses three key challenges: (1) deciding which tests to run first, (2) predicting which builds will fail, and … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jul 2026 · 935 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Integrated Probabilistic Optimization for Inventory Control Under Stochastic DemandJanardan BeheraThe identification and operationalization of increasingly nonstationary and volatile demand patterns challenge the conduct of inventory management in contemporary supply chains. The classical models, especially EOQ and static policies, rest on the stability of demand assumptions, either deterministically or distributionally, and are hence less apt under real-world uncertainty. In view of these limitations, the present study puts forward an integrated … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 6 May 2026 · 2,217 accessesView PDFCite