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17 articles for “Federated”

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Research ArticleOpen accessEvery word in the titleSecuring Mobile Devices from Malware: A Faceoff Between Federated Learning and Deep Learning Models for Android Malware ClassificationNarayan Subramanian, Logesh Ravi, Mithin Jain Shaan et al.Amidst the escalating threats of android malware, urgency mounts to detect issues while safeguarding user privacy. Traditional machine learning and deep learning methods, dealt with scalability challenges and privacy compromises, finding a potential remedy in federated learning. This study introduces a groundbreaking federated learning-based methodology and compares federated learning with traditional deep learning techniques for Android malware classification, employing renowned … …Journal of Computer Science, Vol. 20, Issue 3 · 23 Jan 2024 · 6,284 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA UDDI Search Engine for SVG Federated Medical Imaging Web ServicesSabah Mohammed, Jinan Fiaidhi, Marshal HahnWith more and more medical web services appearing on the web, web service's discovery mechanism becomes essential. UDDI is an online registry standard to facilitate the discovery of business partners and services. However, most medical imaging applications exist within their own protected domain and were never designed to participate and operate with other applications across the web. However, private UDDI … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 7,008 accessesView PDFCite
Review ArticleOpen accessIn the keywordsHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparision of Imagej Analysis of Structure of Two Constructional SteelAlo Francis Ireti, Ajoge Emmanuel Omeiza, Kunle Michael Oluwasegun et al.An image analysis processing method for the measurement of structure of Federated and Ukraine steel from optical microscope images using imagej program is studied. Some parameters like calculation of area, pixel value statistics, distances and angles measurements, edge detection, such as the circularity, ferret angle, solidity and perimeter, average area and the percentage area was examined. Federated grain count was … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 12 Mar 2018 · 7,571 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 · 1,306 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Advancements for Lung Cancer Detection: An In-Depth Review and Future ProspectsAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarLung cancer is a major cause of cancer-related mortality globally, underscoring the necessity for efficient diagnostic instruments. The review paper summarizes the role of ML and DL in detection, staging, and prognostication of lung cancer. We evaluate the relative efficacy of several models, such as CNNs, SVMs, and ensemble approaches, by analyzing publically accessible imaging and molecular information. We emphasize … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Mar 2026 · 1,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractExtending Binary Large Object Support to Open Grid Services Architecture-Data Access and Integration Middleware Client ToolkitKiran Kumar Patnaik, Bollam NagarjunProblem statement: OGSA-DAI middleware allows data resources to be federated and accessed via web services on the web or within grids or clouds. It provides a client API for writing programs that access the exposed databases. Migrating existing applications to the new technology and using a new API to access the data of DBMS with BLOB is difficult and discouraging. … …Journal of Computer Science, Vol. 7, Issue 6 · 14 Jun 2011 · 6,663 accessesView PDFCite