6 articles for “Graph Convolutional Network”

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Research ArticleOpen accessIn the keywordsAraSenti-MARBERT-DynGCN: An Advanced Framework for Sarcasm Detection in Arabic TextBassma M Mousa, Mohammed H. Haggag, Mervat GheithSarcasm detection in Arabic texts is challenging because of the complexity in Arabic morphology, the multitudes of dialects used by native speakers, and its strong reliance on context. The lack of standardized orthography in most written forms of Arabic, combined with the frequent use of colloquialisms and metaphorical expressions, makes the task all the more difficult when trying to detect … …Journal of Computer Science, Vol. 21, Issue 11 · 12 Feb 2026 · 1,562 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPredictive Modeling Applied to Structured Clinical Data Extracted from Electronic Health Records: An Architectural Hypothesis and A First ExperimentAlessandra Pieroni, Alessandro Cabroni, Francesca Fallucchi, Noemi ScarpatoPredictive analysis is one of current important issues in the healthcare context. A lot of patients’ input data can be obtained from their Electronic Health Records. In our research, we propose a general architecture named Health Prediction Architecture. Initially, we consider that data refer to strongly structured health datasets (no free text). Our objectives are related to exploring some problems … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,571 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDF Cite

Research ArticleOpen accessIn the abstractIdentification of Influential Nodes With Topological Structure Via GRAPH Neural Network (GNN) Approach in Social Media NetworksRajnish Kumar, Laxmi Ahuja, Suman Mann, Sanmukh KaurThe amount of data in social networks is vast these days, and constantly changing, making influential node identification crucial. The existing topologies are constantly changing due to the evolving behavior of the applied dataset. Node and leaf topology or feature-based value form the basis for machine learning and centrality computation. Hence, influential node value determination is based on the node … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,830 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDF Cite