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Research ArticleOpen accessIn the abstractPrivacy-Preserving Deep Federated Learning on the Edge Using Homomorphic Encryption and Secure Multiparty ComputationNoman Aasif Gudur, Mohamed El-Dosuky, Sherif KamelThe increasing volume of consumer data necessitates reliable edge devices for personalized user experiences. Federated Learning (FL) offers a state-of-the-art approach to decentralized machine learning by leveraging data distributed across multiple client devices. However, user data privacy remains vulnerable to corruption through feature heterogeneity and malicious attacks. While several privacy-preserving techniques have been previously implemented, they suffer from implementation constraints … …Journal of Computer Science, Vol. 21, Issue 11 · 21 Dec 2025 · 4,381 accessesView PDFCite
Review ArticleOpen accessIn the abstractModeling the Nile: A Comprehensive Water Budget and Flow Assessment with the River Basin Flow Model (RBFM)Youssef Ismail HafezThe Nile River basin, covering 2.9 million km³ across 11countries, is one of the world's most complex hydrological systems. With an annual historical discharge of 84 billion m³ at Aswan, Egypt, and rainfall of around 1,660 billion m³ per year over the Nile basin, effective management of this vital transboundary resource requires a deep understanding of its hydrology. This study … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 18 Jun 2025 · 8,740 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 PDFCite
Research ArticleOpen accessIn the abstractA Recommendation-Based Contextual Model for Talent AcquisitionChannabasamma A., Yeresime SureshIt is important to assist the job seekers in selecting the perfect jobs, which suit candidates' current skills and career objectives. Given the job description and resumes in the unstructured form, choosing the best job manually is a tedious task, so there is a need for an automated system to deal with raw data. The extraction of structured information from … …Journal of Computer Science, Vol. 18, Issue 7 · 20 Jul 2022 · 6,122 accessesView PDFCite
Review ArticleOpen accessIn the abstractCirculating Immune Complexes as an Important Link between Inflammation and Lipid Alterations in AtherosclerosisAnastasia Vladimirovna Poznyak, Nikolay Alexandrovich Orekhov, Vasily Nikolaevich Sukhorukov et al.This review article rigorously investigates the emerging facets of atherosclerosis pathogenesis through an exhaustive examination of the existing data on the intricate interplay between lipid metabolism disorders and inflammation. A primary objective of this study is to thoroughly explore the role of Circulating Immune Complexes (CIC) as a pivotal indicator of this multifaceted interaction. The focus of this review centers … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 14 Aug 2024 · 3,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractStudent Course Recommendation System Using Semantic Aware Temporal Gating With Time TransformerJoshi Vinay Kumar, Dahlia Sam, N. KanyaCourse recommendation system works by analyzing users’ interests and recognizes their historical behavior such as course enrollment and previously watched videos to recommend relevant courses. However, the existing course recommendation systems in Massive Open Online Courses (MOOCs) face challenges in capturing complex semantic information, which impacts student requirements with an unsatisfied recommendation. By combining historical behaviors without temporal awareness, the … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 580 accessesView PDFCite
Research ArticleOpen accessIn the abstractHMA-RAG: A Hierarchical Memory Augmented Retrieval Augmented Generation Framework for Fake News DetectionAfnan Altarjami, Sawsan AlshattnawiExisting methods for detecting fake news, such as traditional machine learning and transformer-based models, often work as separate classifiers that do not use outside evidence, historical knowledge, or ways to make the results easier to understand. This paper presents a framework that combines retrieval augmentation and hierarchical memory to overcome three primary constraints: Insufficient external evidence, the absence of memory, … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 735 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite