Federated Learning (FL) in Intelligent Internet of Things (IIoT) environments faces critical challenges, including sparse client participation, non-IID local data distributions, and unreliable communication, which lea...
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Performance modeling is a key bottleneck for analog design automation. Although machine learning-based models have advanced the state-of-the-art, they have so far suffered from huge data preparation cost, very limited...
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This paper presents a super twisting sliding mode control (STSMC) system to stabilize a parallel-plate electrostatic actuator (ESA) and extend its operating range beyond the pull-in point. A voltage-controlled ESA is ...
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CMOS technology evolution enhances integrated circuits (ICs) performance characteristics at the cost of their increased susceptibility to radiation and thus to the occurrence of single-event upsets (SEUs) that may lea...
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The paper introduces an innovative Internet of Things (IoT)-based scale sensor that measures the water level in the alternate wetting and drying (AWD) system and displays data in the mobile app to enable remote monito...
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In industry, the advancement of digital engineering and the digital thread aims to reduce the impact of knowledge ‘siloes’ by providing a way to integrate data across the entire system lifecycle and across multiple ...
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We present a novel approach for efficient task scheduling on hierarchical fog nodes, catering to real-time (RT) and non-real-time (NRT) tasks with varying sizes and deadline constraints. Leveraging machine learning (M...
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Wireless Sensor Networks (WSNs) have advanced quickly due to the fast expansion of wireless networks. Yet, because of their ease of use and versatility, security concerns have grown. This means that conducting researc...
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ISBN:
(纸本)9798350348460
Wireless Sensor Networks (WSNs) have advanced quickly due to the fast expansion of wireless networks. Yet, because of their ease of use and versatility, security concerns have grown. This means that conducting research on intrusion protection in WSNs is now essential. Denial of Service (DoS) assaults are among the most common types of network attacks. They are dangerous because they take down the target network in order to accomplish their goal. Within WSNs, where devices function with limited resources, a denial-of-service attack has the potential to be disastrous. This research suggests a novel solution for WSNs, which are susceptible to assaults because to their devices' little storage capacity. To find abnormalities in DoS traffic within WSNs, the technique combines a Deep Convolutional Neural Network (DCNN) with Principal Component Analysis (PCA). By detecting and reducing the effects of DoS assaults, and by utilising the complementary capabilities of PCA and DCNN in this particular situation, the goal is to improve the security of WSNs. Compared with other traditional DL architectures, the proposed model has a more simplified structure and better feature extraction capabilities. This special combination gives it the power to quickly identify anomalous network activity in WSNs devices, especially those with limited storage. Because of its lightweight design, the suggested model addresses the inherent resource limits and guarantees optimal performance in the context of WSNs. A variety of assessment measures, such as confusion matrices, different classification metrics, and Receiver Operating Characteristic (ROC) curves, are used to verify the effectiveness of the suggested model. These metrics are used to evaluate the model's categorization performance in a rigorous manner. Extensive experimental comparisons reveal that the small size of the proposed model outperforms other popular models for anomalous traffic detection with regards to classification performance
Phishing URL detection is crucial in cybersecurity as malicious websites disguise themselves to steal sensitive information. Traditional machine learning techniques struggle to perform well in complex real-world scena...
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The quality of teaching and learning process can be improved through innovative methods like use of virtual reality. We introduce EnVision, a groundbreaking Virtual Reality based approach to revolutionize Artificial I...
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