Research ArticleOpen accessIn the abstractTransfer Learning-Driven Binary Classification of Chest X-ray for Pneumonia Using Deep Convolutional ArchitecturesNusrath Fathima, Pradeep KumarPneumonia is the most common infectious cause of lung inflammation, resulting from the presence of viruses or bacteria in the microscopic air sacs. In recent years, artificial intelligence, particularly deep learning, has gained significant traction in the field of medical imaging. Early detection and diagnosis of pneumonia using chest X-rays can support radiologists in clinical decision-making and subsequent treatment planning, … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,547 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review on Data Integration: Issues, Data Types, ArchitectureMimi Haryani Tasani, Mohd Kamir YusofData integration is an important process that enables organizations to merge data from various sources, creating a consolidated viewpoint that supports better decision-making, increased effectiveness, and deeper insights. Although data integration has advantages, it also comes with difficulties like maintaining data quality, adhering to compliance regulations, resolving technical issues, and merging with older systems. Effective management of data quality, robust … …Journal of Computer Science, Vol. 22, Issue 2 · 18 Feb 2026 · 1,815 accessesView PDFCite
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 · 2,043 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence in Quality Control: Transforming Manufacturing ProcessesGopinath KathiresanThe integration of Artificial Intelligence (AI) into Quality Control (QC) is transforming manufacturing by enhancing accuracy, efficiency, and productivity. Traditional QC methods, reliant on manual inspection and basic automation, often fall short in addressing the complexities of modern production environments. This paper presents a review on the application of AI, particularly machine learning, deep learning, and reinforcement learning, in manufacturing … …Journal of Computer Science, Vol. 22, Issue 1 · 12 Feb 2026 · 6,509 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Online Learning in India: Insights from StudentsRitu Gupta, Anuradha Khattar, Meetu Bhatia Grover et al.As technology has advanced, the educational system has undergone numerous modifications. The benefits of online teaching and learning include increased accessibility, reduced costs, and the opportunity to learn at any time and from any location. However, a few drawbacks of this approach include a decline in student involvement, a lack of face-to-face interaction with classmates and teachers, and technical difficulties. … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvergence of GenAI and RPA: A Digital Heaven in Supply Chain Optimization ProcessSaurabh A. Pahune, Zahid Akhtar, Manoj Chandrasekharan et al.One of the most groundbreaking advances in the field of intelligent automation is the merging of Generative Artificial Intelligence (GenAI) and Robotic Process Automation (RPA). This combination unlocks previously unachievable capabilities in automation. RPA (software bots) improves speed and operational efficiency by automating rule-based tasks, Standard Operating Procedures (SOPs), and repetitive workflows. At the same time, it minimizes manual labor … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Feb 2026 · 2,049 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractCuckoo Search Optimized Random Forest for Breast Cancer PrognosisPrasad S. Sase, Debabrata Swain, Shailesh KumarBreast cancer remains a major global health concern due to its high mortality rate, particularly when diagnosis occurs at an advanced stage. Accurate and early differentiation between benign and malignant tumors is therefore critical for improving patient outcomes. Conventional diagnostic practices largely depend on manual assessment and clinical expertise, which may lead to subjective variability in decision-making. To overcome this … …Journal of Computer Science, Vol. 22, Issue 1 · 31 Jan 2026 · 2,107 accessesView PDFCite
Research ArticleOpen accessIn the abstractWeb 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 · 1,715 accessesView PDFCite