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178 results for “Network Architecture”

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Research ArticleOpen accessIn the abstractRoute Optimization using Hybrid GRU Learning Model for SDN and Edge-Based VANET TopologySavitha Kumar, Chandrasekar ChinnasamyIntelligent Transportation System (ITS) offersoutstanding features, including security applications and emergency alerts.Unfortunately, ITS limits traffic control services, adaptability, andadjustability due to the traffic volume. Hence, expanding the standard VehicularAd hoc Networks (VANET) framework is a requirement. As a result, in the latestdays, the concept of Software-Defined Networking based Vehicular Ad hocNetworks (SDN-VANETs) has drawn considerable attention, creating VANETssmarter. The SDN-VANETs … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,169 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 · 6,243 accessesView PDFCite
Review ArticleOpen accessIn the abstractEvaluating Common Reconnaissance Tools and Techniques for Information GatheringIsaac Odun-Ayo, Emmanuel Owoka, Otavie Okuoyo et al.A reconnaissance attack is a commonly overlooked step in penetration testing but a critical step that could help increase the effectiveness of an attack on a target. However, it is a common attack faced by companies and institutions, among others. It enables the attacker or penetration tester to gain valuable information on the target and select the best tools and … …Journal of Computer Science, Vol. 18, Issue 2 · 16 Mar 2022 · 7,812 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Multi-Layer Perceptron Deep Neural Networks using Genetic Algorithms for Hand Gesture RecognitionKhanh Nguyen-Trong, Thi-Thanh-Tan NguyenApplications of wearable sensors for Hand Gesture Recognition (HGR) have been gaining popularity in recent years. Among the proposed methods, deep neural networks with many hidden layers are promising to address the requirements of this wearable activity recognition. They can directly uncover features tied to the dynamics of HGR, from simple motion encoding in lower layers to more complex motion … …Journal of Computer Science, Vol. 18, Issue 2 · 8 Feb 2022 · 7,184 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 3,001 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Modeling Applied to Structured Clinical Data Extracted from Electronic Health Records: An Architectural Hypothesis and A First ExperimentAlessandra Pieroni, Alessandro Cabroni, Francesca Fallucchi, Noemi ScarpatoPredictive analysis is one of current important issues in the healthcare context. A lot of patients’ input data can be obtained from their Electronic Health Records. In our research, we propose a general architecture named Health Prediction Architecture. Initially, we consider that data refer to strongly structured health datasets (no free text). Our objectives are related to exploring some problems … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,575 accessesView PDFCite
EditorialOpen accessIn the abstractVolume 4: Face-to-Face with SGAMR-2020 AwardeesChiara Bedon, Mario D’Aniello, Flavio Stochino…New Year and new results for the SGAMR community!! The year 2021 begins with the announcement of Awardees for the first (ongoing) edition of SGAMR awards for Young Investigator (SGAMR-YRA-2020), Best Paper (SGAMR-BPA-2020) and Outstanding Reviewer (SGAMR-ORA-2020)!! In this editorial, we want further to congratulate the Winners, but also present them to our Readers, Supporters, Authors, Reviewers as well as … …International Journal of Structural Glass and Advanced Materials Research, Vol. 5, Issue 1 · 15 Feb 2021 · 7,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractFed-Deep CTRL (Light GBM)-Scalable, Interpretable, and Privacy-Preserving Federated Learning Framework for Wireless Intrusion Detection SystemSudaroli Vijayakumar, V. MuthumanikandanA learning-based intrusion detection system automates the understanding and reporting of network traffic information. The systems using neural networks and machine learning have demonstrated good detection accuracy, but the accuracy is entirely reliant on the type and volume of data. Additionally, there are issues with its scalability, privacy, efficiency, and interpretability. With the innovative fed-deep CTRL (light GBM) method, this … …Journal of Computer Science, Vol. 20, Issue 4 · 29 Feb 2024 · 5,327 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,786 accessesView PDFCite