A prominent problem in planar resonant wire-less power transfer (WPT) systems is instability of efficiency and load power due to position misalignment of the receiver (RX) coil relative to postion of the transmitter (...
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In this paper, we present an architecture for the deployment of an edge computing system based on Named Data Networking (NDN) as part of a private 5G network. Our proposed architecture integrates IP-based and non-IP-b...
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Internet of Things solutions typically involve interaction between sensors, actuators, the cloud, embedded systems and user applications. Often in such cases, there are time constraints specifying the maximum response...
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This paper examines the impact of virtual impedance control in an inverter-dominated microgrid (MG) system. The goal is to provide a clear understanding of Virtual Impedance (VI) control toward MG stability. This anal...
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This paper addresses the urgent need for enhanced agricultural practices by pinpointing the significant limitations of existing crop prediction and monitoring systems. Traditional methods, often characterized by low a...
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In this work, a design method of a dual-frequency high-gain omnidirectional antenna is investigated and implemented. The antenna is based on the bidirectional leaky-wave antenna (Bi-LWA) theory, which can generate the...
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This work proposes simply wideband four-element L-shaped notch-patch (LNP) MIMO antenna for 5G new radio (NR) networks. The proposed LNP MIMO antenna comprised of four-port antenna elements. The single antenna scheme ...
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Positioning and communication systems hold intriguing potentials in the context of the mining industry. The need for safety and environmental precautions in mining has grown clearer for governments and scientists acro...
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In bilingual translation,attention-based Neural Machine Translation(NMT)models are used to achieve synchrony between input and output sequences and the notion of *** model has obtained state-of-the-art performance for...
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In bilingual translation,attention-based Neural Machine Translation(NMT)models are used to achieve synchrony between input and output sequences and the notion of *** model has obtained state-of-the-art performance for several language ***,there has been little work exploring useful architectures for Urdu-to-English machine *** conducted extensive Urdu-to-English translation experiments using Long short-term memory(LSTM)/Bidirectional recurrent neural networks(Bi-RNN)/Statistical recurrent unit(SRU)/Gated recurrent unit(GRU)/Convolutional neural network(CNN)and *** results show that Bi-RNN and LSTM with attention mechanism trained iteratively,with a scalable data set,make precise predictions on unseen *** trained models yielded competitive results by achieving 62.6%and 61%accuracy and 49.67 and 47.14 BLEU scores,*** a qualitative perspective,the translation of the test sets was examined manually,and it was observed that trained models tend to produce repetitive output more *** attention score produced by Bi-RNN and LSTM produced clear alignment,while GRU showed incorrect translation for words,poor alignment and lack of a clear ***,we considered refining the attention-based models by defining an additional attention-based dropout *** dropout fixes alignment errors and minimizes translation errors at the word *** empirical demonstration and comparison with their counterparts,we found improvement in the quality of the resulting translation system and a decrease in the perplexity and over-translation *** ability of the proposed model was evaluated using Arabic-English and Persian-English datasets as *** empirically concluded that adding an attention-based dropout layer helps improve GRU,SRU,and Transformer translation and is considerably more efficient in translation quality and speed.
Microelectromechanical system (MEMS) based pressure sensors have been utilized for decades;however, new trends in pressure sensors have recently emerged, such as increased sensitivity, a broader range and reduced chip...
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