We developed high-performance flexible oxide thin-film transistors(TFTs)using SnO_(2) semiconductor and high-k ZrO_(2) dielectric,both formed through combustion-assisted sol-gel *** method involves the exothermic reac...
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We developed high-performance flexible oxide thin-film transistors(TFTs)using SnO_(2) semiconductor and high-k ZrO_(2) dielectric,both formed through combustion-assisted sol-gel *** method involves the exothermic reaction of fuels and oxidizers to produce high-quality oxide films without extensive external *** combustion ZrO_(2) films were revealed to have an amorphous structure with a higher proportion of oxygen corresponding to the oxide network,which contributes to the low leakage current and frequency-independent dielectric *** ZrO_(2)/SnO_(2) TFTs fabricated on flexible substrates using combustion synthesis exhibited excellent electrical characteristics,including a field-effectmobility of 26.16 cm^(2)/Vs,a subthreshold swing of 0.125 V/dec,and an on/off current ratio of 1.13×10^(6) at a low operating voltage of 3 ***,we demonstrated flexible ZrO_(2)/SnO_(2) TFTs with robust mechanical stability,capable of withstanding 5000 cycles of bending tests at a bending radius of 2.5 mm,achieved by scaling down the device dimensions.
Text classification is a fundamental task in web content mining. Although the existing supervised contrastive learning (SCL) approach combined with pre-trained language models (PLMs) has achieved leading performance i...
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Text classification is one vital tool assisting web content mining. Semi-supervised text classification (SSTC) offers an approach to alleviate the burden of annotation costs by training on a few labeled texts alongsid...
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Path planning plays a crucial role in various autonomy applications, and RRT∗ is one of the leading solutions in this field. In this paper, we propose the utilization of vertex-based networks to enhance the sampling p...
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In recent years, the need to rapidly develop vaccines and therapeutic proteins to combat viral outbreaks has highlighted the importance of innovation. This study explores the application of diffusion models in de novo...
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In recent years, novel view synthesis from a monocular image has become a research hot-spot that attracts significant attention. Some recent work identifies latent vectors for high-quality view generation via iterativ...
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In recent years, novel view synthesis from a monocular image has become a research hot-spot that attracts significant attention. Some recent work identifies latent vectors for high-quality view generation via iterative optimisation, which is a time-consuming process. In contrast, some others utilise an encoder learning a mapping function to approximately estimate optimal latent codes, which significantly reduces its processing time but sacrifices reconstruction quality. Consequently, how to balance synthesis quality and its generation efficiency still remains challenging. In this paper, we propose a residual-based encoder to incorporate with a 3D Generative Adversarial Networks (GAN), named ReE3D, for novel view synthesis. It applies an iterative prediction of latent codes to ensure much higher quality of novel view synthesis with an insignificant increase of processing time when compared to existing encoder-based 3D GAN inversion methods. Additionally, we enforce a novel geometric loss constraint on the encoder to predict view-invariant latent codes, thus effectively mitigating the trade-off between geometric and texture quality in 3D GAN inversion. Extensive experimental results demonstrate that our extended encoder-based method has achieved best trade-off performance in terms of novel view synthesis quality and its execution time. Our method has gained comparable synthesis quality with exponentially decreased processing time when compared to iterative optimisation methods, while improved synthesis performance of encoder-based methods significantly. IEEE
The detection of foreign object debris (FOD) in real-time is crucial for airport safety and security. In this paper, we propose a holistic FOD detection framework that utilizes both present and past data. A baseline m...
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The scope of visible light communication (VLC) in the navigation industry is expanding day by day. This is due to the potential of achieving high navigation accuracy in indoor and outdoor environments. It outperforms ...
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Despite recent progress made in the theory and practice of Artificial Intelligence (AI), there is still a lack of tools and algorithms for the design and implementation of Neural Networks (NN) capable of explaining ho...
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Offloading some of the traffic management decision-making functionalities to intelligent data-planes (IDPs) can significantly enhance the accuracy and adaptation speed of network services. An IDP executes, at line-spe...
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