Research ArticleOpen accessIn the abstractAn Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks FrameworkP Subhash, Madana Srinivas, A. Ranjith et al.The IoV enables the formation of VANETs that require a strong selection of CHs for effective communication within high-velocity changing traffic scenarios. Existing approaches often face issues related to scalability, privacy, and adaptability. To meet the aforementioned urgent needs, we design a decentralized scheme for intelligent CH selection based on Federated Learning with Diffusion Convolutional Recurrent Neural Networks (DCRNNs). According … …Journal of Computer Science, Vol. 22, Issue 10 · 1 Oct 2026 · 612 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Privacy-Preserving Access Control for Electronic Health Records Using Smart ContractsG. Bhanu Prasad, M. Venkateswara RaoElectronic medical records are crucial for providing high-quality healthcare, but they also raise serious privacy and security issues. Traditional centralised storage systems are vulnerable to manipulation, hacking, and illegal access. This study suggests a smart contract-based blockchain architecture that provides decentralised, unaltered, and privacy-preserving access control for EMRs. The model integrates cryptographic techniques like AES-256 encryption and SHA-256 hashing for … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Adaptive Filters for Dynamic Mass Measurement of Moving Objects on Flexible PlatformsSergio Bimbi Junior, Flavio Celso Trigo, Agenor de Toledo FleuryDynamic mass measurement of moving objects on flexible platforms remains a significant challenge due to mechanical vibrations, structural flexibility, and the inherently low Signal-to-Noise Ratio (SNR) of strain gauge sensors. Traditional analog filtering approaches, such as Tow– Thomas active filters, exhibit limitations since gain stages propagate and may even amplify intrinsic noise, compromising metrological accuracy. This work proposes a hybrid … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 22 Apr 2026 · 2,669 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-NFV for Smart Digital and Secure Physical Structures in E-Government, Healthcare, and Network SystemsHayder Abdulsattar Nahi, Ebtehal Akeel Hamed, Rusul A. Salman, Akmam Majed MosaThis paper proposed a combined model that melds Blockchain technology with Network Function Virtualization (NFV) to promote many areas, such as smart, secure, and scalable physical and digital infrastructures in E-Government, Healthcare, and Network Systems. The model treats the principal objections in conventional systems, including centralization, slowed service deployment, and restricted safety. By employing decentralized Digital Identity Decentralized identifiers (DIDs), … …Journal of Computer Science, Vol. 22, Issue 4 · 21 Apr 2026 · 1,328 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,769 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Deep Learning for Kidney Stone Detection in CT Scans With Noise Reduction and Feature EnhancementU. M. Fernandes Dimlo, Sreenu Banoth, Priti Bihade et al.The identification of kidney stones using CT scans is an essential but difficult effort in medical diagnostics, frequently obstructed by imaging noise and the complexity of manual interpretation. Although conventional methods are widely used, they suffer from inaccuracies and inefficiencies, necessitating the development of automated diagnostic solutions. This study tackles these issues by presenting HDCNRNet, a hybrid deep learning network … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 2,174 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of the Cytogenetic Status, Genome Instability, and Adaptive Potential of the Kazakh Tobet DogOksana Cherednichenko, Anastassiya Pilyugina, Dinara Azizbekova et al.In recent years, interest in indigenous dog breeds has increased. The Tobet is a unique breed of Kazakh livestock guardian dogs adapted to nomadic pastoralism that developed over thousands of years across Central Asia and Turkestan. Currently, the Tobet breed faces critical endangerment. Its conservation and sustainable breeding require thorough analysis of hereditary characteristics, genome stability, and adaptive potential. In … …American Journal of Animal and Veterinary Sciences, Vol. 20, Issue 4 · 19 Feb 2026 · 1,896 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,924 accessesView PDFCite