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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Bidirectional CLLLC resonant dc-dc converters with an asymmetric tank can narrow the switching frequency bandwidth required to meet the asymmetric voltage gains in the two directions of power flow. Consequently, highe...
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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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3D integration promises to resolve many of the heat and die size limitations of 2D integrated circuits. A critical step in the design of 3D many-cores and MPSOCs is the layout of their 3D network-on-chip (NoC). In thi...
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Deep Learning (DL)-based models have been successfully applied for medical image classifications. However, the performance of traditional medical image classifiers is limited by insufficient training samples and inacc...
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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.
In this work, a chemical sensor for concentration measurement of hydrogen peroxide is proposed based on localized surface plasmon resonance (LSPR). The silver nanoparticles coated by polyvinyl alcohol (PVA) have been ...
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Crop diseases pose a significant threat to global food security, affecting the livelihoods of millions of smallholder farmers. Identifying these diseases is crucial yet challenging due to lack of proper infrastructure...
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In this study, the indium-zinc-oxide(IZO) thin mms were deposited on silicon substrates by r.f. sputtering. The IZO/Si sensing structure was used as a disposable sensor head and connected to the gate terminal of MOSFE...
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With the development of edge technology in the fields of transportation, wireless sensor networks, and the internet of things, more and more intelligent optimization algorithms are implemented in hardware structures. ...
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