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Research ArticleOpen accessIn the abstractIntegration of Local Large Language Models, Retrieval-Augmented Generation, and Adaptive LearningAnass Belcaid, Kamal ReklaouiIn recent years, many schools and teachers have started using closed Large Language Models (LLMs) to help with learning. These tools can be very helpful for tutoring and personal learning, but they also bring serious problems. One big issue is that they use cloud systems, which means student data is sent to outside servers. This can put privacy at risk … …Journal of Computer Science, Vol. 22, Issue 4 · 26 Mar 2026 · 3,923 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 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 · 1,807 accessesView PDFCite
InvestigationOpen accessIn the abstractSurvey of Websites and Web Application Security Threats Using Vulnerability AssessmentVincent Appiah, Michael Asante, Isaac Kofi Nti, Owusu Nyarko-BoatengNowadays information has become anasset to many institutions and as a result these institutions have become targets for people with malicious intents to attack these institutions. The web is now an important means of transacting business and without security, websites cannot thrive in today’s complex computer ecosystem as there are new threats emerging as old ones are being tackled. Vulnerability … …Journal of Computer Science, Vol. 15, Issue 10 · 27 Jan 2018 · 9,316 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
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Survey on Fake News Detection Using Machine LearningShraddha Shah, Sachin PatelIn the age of information data surplus and social media impact, the propagation of fake news has developed a significant societal concern. This challenge requires robust tools and methodologies for addressing, with machine learning emerging as a promising approach. The paper reviews different machine learning techniques in fake news detection, including supervised, unsupervised and semi-supervised methods. Supervised methods utilize labelled … …Journal of Computer Science, Vol. 21, Issue 4 · 20 Mar 2025 · 9,212 accessesView PDFCite
Literature ReviewOpen accessIn the abstractA Comprehensive Survey on Tools for Effective Alzheimer’s Disease DetectionN. Vinutha, G. U. Vasanthakumar, P. Deepa Shenoy, K. R. VenugopalNeuroimaging is considered as a valuable technique to study the structure and function of the human brain. Rapid advancement in medical imaging technologies has contributed significantly towards the development of neuroimaging tools. These tools focus on extracting and enhancing the relevant information from brain images, which facilitates neuroimaging experts to make better and quick decision for diagnosing enormous number of … …Neuroscience International, Vol. 9, Issue 1 · 4 Oct 2017 · 10,232 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic PatientBiplov Paneru, Bishwash Paneru, Krishna Bikram Shah et al.The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and refined, including Support Vector Machines (SVM), Random Forest, XGBoost, Multi-Layer Perceptron (MLP) and a hybrid model that combines MLP and SVM. To evaluate the durability of the … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation of Adaptability and Stability of Nellore Sires, based on the Productive Progeny Performance Raised in Brazilian SavannaJúlio César De Souza, Fabio Fábio Rafael Leão Fialho, Carolina Fregonesi De Souza et al.The study investigates the performance and adaptability of Nellore sires across different regions, focusing on weight traits at 205 days (W205) and 550 days (W550). Analysis reveals significant variations in progeny weight means among evaluated sires, highlighting the importance of sire selection for herd improvement. Notably, certain sires consistently exhibit superior weight traits across diverse environmental conditions, indicating their potential … …American Journal of Agricultural and Biological Sciences, Vol. 19, Issue 1 · 2 Jul 2024 · 5,529 accessesView PDFCite