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528 articles for “real data”
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Research ArticleOpen accessIn the abstractEfficient Detection and Mitigation of Rushing Attacks in VANETs Using RAID: A Novel Intrusion Detection SystemVamshi Krishna Kapu, Ganesh Reddy KarriThe vehicle manufacturing hub has evolved over the last decade with the emergence of self-driving vehicles and human-driven vehicles that use the concept of Artificial Intelligence (AI). Vehicular Ad Hoc Network (VANET) is a subset of Mobile Ad Hoc Network (MANET) that allows vehicles to communicate with one another and the Road Side Unit (RSU). VANET has been a game … …Journal of Computer Science, Vol. 19, Issue 9 · 26 Aug 2023 · 5,746 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Analytics for Imbalanced DatasetMadhura Prabha R, Sasikala SThe primary issue in real-time big data classification is imbalanced datasets. Even though we have many balancing techniques to reduce imbalance ratio which is not suitable for big data that has scalability issues. This study is envisioned to explore different balancing techniques with experimental study. We tried comparing the effectiveness of various balancing strategies, including cutting-edge approaches for severely unbalanced … …Journal of Computer Science, Vol. 20, Issue 2 · 11 Jan 2024 · 5,473 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain Based Solution for Secure and Efficient Agricultural Supply Chain SystemsYassir Farooqui, Syed Ibad Ali, Kush Bhushanwar et al.The agricultural supply chain forms the backbone for feeding the world and supporting economies, but there is always a challenge to it such as traceability, inefficiencies, fraud risk, and poor transparency. Trust is hampered as many traditional systems still depend on manual procedures and distributed data records. So as to overcome the issues and improve the security, overall effectiveness, and … …Journal of Computer Science, Vol. 22, Issue 10 · 28 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutoencoder-Based Intrusion Detection for ARP Poisoning in SDN ControllersKago Seemela, Banyatsang Mphago, Thabo Semong, Phephisa MethulaAddress Resolution Protocol (ARP) poisoning is still a critical control plane attack in Software Defined Networks (SDNs), and spoofing of ARP mappings can trick SDNs controller and accomplish man in the middle, eavesdropping and denial of service attacks. Current SDN intrusion detection systems of ARP attacks rely on supervised learning and labelled attack data which is rather expensive and not … …Journal of Computer Science, Vol. 22, Issue 7 · 21 Jul 2026 · 869 accessesView PDFCite
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 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 · 1,762 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Air-Written Real-Time Multilingual Numeral String Recognition System Using Deep Convolutional Neural NetworksMeenal Jabde, Chandrashekhar Himmatrao Patil, Amol D. Vibhute, Shankar MaliAir-writing is a modern practice for free-space writing of characters or words with hand or finger movements. In the new era, hand gestures are commonly used for Human-Computer Interaction (HCI) or controlling machines in several applications. Writing with a finger or holding any object in hand and 3-D movement in the air is helpful for several applications. However, it is … …Journal of Computer Science, Vol. 20, Issue 12 · 8 Nov 2024 · 5,248 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Analysis of Longitudinal Ordinal Data Using Non-Identifiable Multivariate Probit ModelsXiao ZhangMultivariate probit models have been explored foranalyzing longitudinal ordinal data. However, the inherent identification issuein multivariate probit models requires the covariance matrix of the underlyinglatent multivariate normal variables to be a correlation matrix and thushinders the development of efficient Bayesian sampling methods. It is knownthat non-identifiable models may produce Markov Chain Monte Carlo (MCMC)samplers with better convergence and mixing than … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 14 Nov 2022 · 6,044 accessesView PDFCite