60 articles for “heterogeneous network”

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 PDF Cite

Research ArticleOpen accessIn the abstractAuto Weight Dilated Convolutional Ensemble Network for the Severity Analysis of Lung Cancer in CT ImagesL. Sandhya, K. MarimuthuLung cancer is one of the world's leading causes of morbidity and mortality; improving patient outcomes requires an early and precise diagnosis. Lesion and tumor segmentation remains a challenging task in CT images due to their inherent imaging limitations, such as the small size of nodules, heterogeneous textures, blurry boundaries, and adjacent structures, leading to misclassification and difficulty in delineating … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,541 accessesView PDF Cite

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 PDF Cite

Research ArticleOpen accessIn the abstractSEAchain: A Privacy-Preserving Dual-Credential Model on BlockchainS. Balachander, A. MuruganAll facets of daily life are now impacted by transaction data. The complex and heterogeneous network created by millions of users, devices, online services, and applications makes digital identity management more difficult. Users can maintain control over their personal information via distributed identity, a potentially useful model for resolving identity issues. Nevertheless, current state-of-the-art techniques are inappropriate because of persistent … …Journal of Computer Science, Vol. 22, Issue 5 · 25 May 2026 · 1,310 accessesView PDF Cite

Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDF Cite

Research ArticleOpen accessIn the abstractLatent Feature-Based Trust-Aware Model for Service Delegation in Social Internet of Things (SIoT)Rahul, Venkatesh, Satish B BasapurThe integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different … …Journal of Computer Science, Vol. 21, Issue 12 · 9 Jan 2026 · 1,802 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMonetary Policy, Sub-National Inflation Dynamics and Regional Spillovers in NigeriaChioma Peace Nwosu, Usenobong Friday AkpanThis study evaluates the relationship between monetary policy shocks and sub-national inflation dynamics in Nigeria, using the SVAR framework. Furthermore, using the Diebold-Yilmaz (DY) methodology, it also examines the extent of inflation volatility spillovers among the regions. Results show that monetary policy shock generates a heterogeneous but insignificant influence on sub-national inflation in Nigeria. We also found substantial evidence of … …Journal of Social Sciences, Vol. 20, Issue 1 · 2 Jul 2024 · 5,486 accessesView PDF Cite