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15 articles for “Workflows”
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Research ArticleOpen accessEvery word in the titleSafeguarding Electronic Health Records: A Review of Privacy and Security in EHR WorkflowsGayathri Hegde M, P. Deepa Shenoy, Venugopal K RElectronic Health Records (EHRs) have revolutionized the healthcare industry by improving the accessibility to patient data, optimizing workflows and refining clinical decision making. The increasing use of digital records raises serious privacy and security concerns, particularly about healthcare data storage and management, access and retrieval, and sharing and interoperability. This survey paper comprehensively reviews existing privacy-preserving and security-enhancing approaches across … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,233 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCost-Efficient Deadline Constrained Scientific Workflow Scheduling in Infrastructure-as-a-Service Clouds by Disqualifying Tasks with AnomaliesAnver Shahabdeen Rahumath, Santhosh Rajendran, Natarajan Mohanasundaram, Abdul Rahiman MalangaiCloud computing has transformed the way businesses and consumers think about their data and businesses. As a result, cloud computing is described as the on-demand availability of all computer system resources via the Internet as a paid service. Enhancing security is a major problem in cloud computing, which is also a major research topic because data is stored and processed … …Journal of Computer Science, Vol. 18, Issue 6 · 27 Jun 2022 · 5,793 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCost Effective Expa-Max-Min Scientific Workflow Allocation and Load Balancing Strategy in Cloud ComputingJames Kok Konjaang, Fahrul Hakim Ayob, Abdullah MuhammedThe rise in demand for cloud resources (network, hardware and software) requires cost effective scientific workflow scheduling algorithm to reduce cost and balance load of all jobs evenly for a better system throughput. Getting multiple scientific workflows scheduled with a reduced makespan and cost in a dynamic cloud computing environment is an attractive research area which needs more attention. Scheduling … …Journal of Computer Science, Vol. 14, Issue 5 · 13 Jan 2018 · 8,585 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCWDRL: Multi-Cloud Workflow Scheduling Using Deep Reinforcement Learning and Improved Workflow Segmentation for Multi-Cloud EnvironmentsS. Gowri, A. SumathiThe rapid growth of cloud computing has led to complex workflow scheduling challenges in multi-cloud environments, where efficient resource utilization, minimized makespan, and reduced costs are paramount. Traditional scheduling algorithms often struggle to adapt to the dynamic nature of cloud resources and workflows, leading to suboptimal performance. To overcome this issue, the paper proposed a novel Multi-Cloud Workflow Scheduling using … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 933 accessesView PDFCite
Research ArticleOpen accessIn the abstractLess Biased Approach for Sandstone Pore SegmentationDaffa Abiyyu Murtadha Kurnia, Iman Herwidiana KartowisastroReservoir characterization is a fundamental process in estimating reserves within petroleum and hydrogeological systems, where the precise determination of pore space dictates the validity of fluid flow models. Although X-Ray Computerized Tomography (XRCT) has become the standard non-destructive evaluation method for visualizing the internal structure of rocks, the data interpretation process still faces challenges during the image segmentation stage. Conventional … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,191 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 · 2,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Stroke Lesion Segmentation With U-Net Variants: Classical, Transfer Learning, and MRI Sequence-Specific Customized ApproachesSonia Flora Panesar, Amit P. GanatraIschemic stroke, caused by restricted cerebral blood flow, is a leading cause of death and disability worldwide. Accurate segmentation of stroke lesions in MRI is essential for timely diagnosis but remains labor-intensive when done manually. This study presents a comparative evaluation of three U-Net variants for automated ischemic stroke lesion segmentation using the ISLES 2022 dataset: (1) Classical U-Net with … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvergence of GenAI and RPA: A Digital Heaven in Supply Chain Optimization ProcessSaurabh A. Pahune, Zahid Akhtar, Manoj Chandrasekharan et al.One of the most groundbreaking advances in the field of intelligent automation is the merging of Generative Artificial Intelligence (GenAI) and Robotic Process Automation (RPA). This combination unlocks previously unachievable capabilities in automation. RPA (software bots) improves speed and operational efficiency by automating rule-based tasks, Standard Operating Procedures (SOPs), and repetitive workflows. At the same time, it minimizes manual labor … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Feb 2026 · 2,040 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite