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 PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Review ArticleOpen accessIn the abstractExploring Applications, Datasets, Algorithms, and Technologies in Satellite Image ProcessingBijeesh TV, Bejoy BJ, Michael Moses Thiruthuvanthan, Raju GAmidst an era filled with complex local and global problems, satellite data presents itself as a revolutionary tool with unmatched potential to tackle practical problems in a variety of fields. This article investigates how satellite imagery, which is available through open data programs and repositories, is a valuable tool for applications including wildlife conservation, urban planning, precision agriculture, and disaster … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,584 accessesView PDFCite
Review ArticleOpen accessIn the abstractUtilizing Large Language Models in Business Process Management: Applications and ChallengesMahmoud Boghdady Abdel Wahab, Sherif A. Mazen, Iman M. A. HelalLarge Language Models (LLMs) have recently been used in numerous domains, such as Business Process Management (BPM), which has significantly advanced. With LLMs' ability to understand language, reason, and tackle new challenges with minimal guidance, they offer an exciting opportunity to rethink and improve BPM practices. This systematic literature review examines insights from 42 peer-reviewed studies to understand how LLMs … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 4,462 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Binary Patterns Pyramid and Gabor Filters for Machine Learning-Based Nail Disease DetectionJagadeeswari Boopalan, Maruthu Perumal SabtharishiNail diseases, including Onychomycosis and Psoriasis, are common conditions that pose diagnostic challenges due to subtle clinical presentations and reliance on invasive methods. This study investigates the effectiveness of Binary Patterns Pyramid Filter (BPPF) and Gabor Filter (GF) as feature extraction techniques for machine learning-based nail disease detection, addressing three categories: Healthy, Onychomycosis, and Psoriasis. Using a dataset of 1,466 … …Journal of Computer Science, Vol. 21, Issue 8 · 2 Oct 2025 · 2,178 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Experimental Study on the Embedded Software Development Approach Using TI-RTOSAloysio Augusto Rabello de Carvalho, Luiz Eduardo Galvão MartinsEmbedded systems have experienced significant growth in recent years. These systems, which power a wide range of devices from smart appliances to industrial machinery, have become integral to our daily lives and industries. However, this rapid expansion introduces new challenges for developers. A critical decision involves whether to employ a Real-Time Operating System (RTOS) or to forgo it, depending on … …Journal of Computer Science, Vol. 21, Issue 6 · 17 Jul 2025 · 3,068 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite