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Real-Time Signal Processing Techniques for Biomedical Applications
Real-time signal processing in biomedical applications plays a crucial role in the acquisition, analysis, and interpretation of physiological signals such as electrocardiograms (ECG), electroencephalograms (EEG), and electromyograms (EMG). This manuscript reviews engineering methodologies that enable real-time…
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Application of IoT in Smart Grid Fault Detection and Isolation
The integration of the Internet of Things (IoT) in smart grid infrastructure has revolutionized the way utilities manage energy distribution, monitor asset health, and respond to faults. Traditional fault detection and isolation techniques are often constrained…
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Vol. 9, Issue 11, November 2021
PUBLISHED: 2021-10-31 Original Research Article e-certificate Download Article Page No. Application of IoT in Smart Grid Fault Detection and Isolation Aryan Singh 1-7 Real-Time Signal Processing Techniques for Biomedical Applications Anurag Singh 8-24 Energy-Efficient…
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The Evolution of Cyber Defense: How AI Enhances Traditional Security Mechanisms
Cyber defence has undergone a paradigm shift over the past three decades, transitioning from perimeter-focused protection to intelligent, adaptive, and predictive security architectures. The rapid expansion of digital ecosystems—cloud computing, IoT, 5G, virtualized networks, and edge…
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Ergonomics and Human Factor Considerations in Industrial Workstation Design
Ergonomics and human factors play a critical role in designing industrial workstations to ensure worker comfort, safety, and productivity. This manuscript presents a comprehensive examination of ergonomic principles applied to industrial workstation design up to the…
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A Survey on Federated Learning Applications in Healthcare Data Privacy
The rapid digitization of healthcare has led to an exponential increase in sensitive medical data, necessitating robust privacy-preserving techniques for data analytics. Federated Learning (FL), an emerging distributed machine learning paradigm, enables collaborative model training across…
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Comparative Analysis of Traditional Machine Learning Models for Network Intrusion Detection
This manuscript presents a comparative analysis of traditional machine learning models for network intrusion detection, considering technologies and methods available up to 2021. Network security remains a critical concern as cyber threats evolve continually. Intrusion detection…
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Vol. 9, Issue 10, October 2021
PUBLISHED: 2021-09-30 Original Research Article e-certificate Download Article Page No. Comparative Analysis of Traditional Machine Learning Models for Network Intrusion Detection Sunita Singhal 1-13 A Survey on Federated Learning Applications in Healthcare Data Privacy…
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Six Sigma Methodology for Reducing Defects in Automotive Component Manufacturing
In the highly competitive automotive industry, quality improvement and defect reduction in component manufacturing are critical for maintaining product reliability and customer satisfaction. This manuscript presents an in-depth analysis of the application of Six Sigma methodology…
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Predictive Maintenance in Manufacturing Using Legacy IoT Sensors and Python-based Analytics
Predictive maintenance (PdM) is a transformative approach in manufacturing aimed at optimizing equipment uptime and minimizing unplanned downtimes by forecasting potential failures before they occur. With the increasing deployment of Internet of Things (IoT) sensors, even…