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Research ArticleOpen accessEvery word in the titleA Secured Blockchain-based Information-Centric NetworkAbdelrahman Sheham Abdellah, Sherif Saif, Hesham E. ElDeeb et al.In this study, we propose an Information-Centric Network (ICN) approach for the Internet as an alternative to the present host-centric architecture. The proposed approach solves present Internet challenges, where most Internet users nowadays are involved in seeking knowledge by searching through large amounts of data, independent of the data's physical locations and these users usually have requests that need prompt … …Journal of Computer Science, Vol. 18, Issue 4 · 17 Apr 2022 · 6,239 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEvaluation of Biochemical Characteristics of Exercise Fatigue and Recovery of Energy and Materials Based on Neural Network TechnologyPeng HuA remarkable feature of modern sports is that the training load intensity of athletes is constantly increasing, and training would bring great pressure to the athletes' bodies. One of the important problems is to improve the performance of athletes and effectively solve the problem of high load and scientific recovery. To use recovery methods meaningfully, it is necessary to understand … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 13 Jul 2026 · 903 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntrusion-Resistant Multi-Hop Communication Protocol for Secure Wireless Sensor NetworksRakesh Ranjan, Vaishali Singh, Hitendra SinghModern Internet of Things (IoT) systems are based on Wireless Sensor Networks (WSNs), which can be distributed to various environments to perform a range of sensing and data aggregation. Their intrinsic deficiencies in computation, energy, and bandwidth, however, make them very vulnerable to routing-layer attacks like black hole and selective forwarding as well as Sybil intrusion. The current studies on … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 935 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Wireless Sensor Network Clustering Using a Hybrid Firefly–Bat Algorithm (HFBA)J. Jegan, Senthil kumar P, S. Saravanakumar et al.Wireless Sensor Networks (WSNs) are composed of numerous sensor nodes that collaborate to observe and evaluate various environmental parameters, transmitting the data to a central base station. Each node is equipped with a unique transmitter, receiver, and processor to facilitate sensing, processing, and communication. These networks are often installed in extremely remote and inaccessible areas. A significant challenge arises from … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,431 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTowards 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
Research ArticleOpen accessEvery word in the titleRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite