Electroluminescence (EL) efficiency of perovskite light-emitting diodes (PeLEDs) based on a few square millimeters has improved significantly in recent years. Nevertheless, the EL efficiency of PeLEDs would be plunged...
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One major cause of Alzheimer’s disease(AD) is evidently due to the aggregation and deposition of amyloidβ peptides(Aβ) in the brain tissue of the patient. Preventing misfolding and self-aggregation of Aβ protein c...
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One major cause of Alzheimer’s disease(AD) is evidently due to the aggregation and deposition of amyloidβ peptides(Aβ) in the brain tissue of the patient. Preventing misfolding and self-aggregation of Aβ protein can reduce the formation of highly toxic polymer, which is important for the treatment of AD. Among them, the α-helix consisting of42 residues(Aβ42) is the main component of senile plaques in AD. In this paper, 500 ns accelerated molecular dynamics are performed at different temperatures(300 K, 350 K, 400 K, 450 K) to study of the effect of temperature-induced conformation changes of Aβ42 protein during the unfolding process respectively.
Combining the mutual information theory and the sequential hypothesis testing(SHT)method,a selfadapting radio frequency(RF)stealth signal design method is proposed. The channel information is gained through the radar ...
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Combining the mutual information theory and the sequential hypothesis testing(SHT)method,a selfadapting radio frequency(RF)stealth signal design method is proposed. The channel information is gained through the radar echo and feeds back to the radar system,and then the radar system adaptively designs the transmission waveform. So the close-loop system is formed. The correlations between these transmission waveforms are decreased because of the adaptive change of these transmission waveforms,and the number of illuminations is reduced for adopting the SHT,which lowers the transmission power of the radar system. The radar system using the new method possesses the RF stealth performance. Aiming at the application of radar automatic target recognition(RATR),experimental simulations show the effectiveness and feasibility of the proposed method.
Single channel blind source separation (SCBSS) refers to separate multiple sources from a mixed signal collected by a single sensor. The existing methods for SCBSS mainly focus on separating two sources and have weak ...
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Training deep convolutional neural networks (CNNs) for airway segmentation is challenging due to the sparse supervisory signals caused by severe class imbalance between long, thin airways and background. In view of th...
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There are more than 70 million people worldwide who suffer from stuttering problems. This will affect the confidence of public speaking in people who suffer from this issue. To solve this problem many people take ther...
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There are more than 70 million people worldwide who suffer from stuttering problems. This will affect the confidence of public speaking in people who suffer from this issue. To solve this problem many people take therapy sessions but the therapy sessions are a temporary solution, as soon as they leave therapy sessions this problem might arise again. This work aims to use state of the art machine learning algorithms that have improved over the past few years to solve this problem. We have used the dataset from UCLASS archives which provide the data for stuttered speech *** format with time-aligned transcriptions. We have tried different algorithms and optimized our model by hyper parameter tuning to maximize the model's accuracy. The algorithm is tested on random speech data with low to heavy stuttering from the same dataset, and it is observed that there is significant reduction in the Word Error Rate(WER) for most of the test cases.
The pixel variation signal extracted from the nasal region of RGB-Thermal images can be used to achieve breathing rate (BR) measurement. However, this method fails when the nasal region is not detected in complicated ...
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For those who love painting but unfortunately have visual impairments, holding a paintbrush to create a work is really a difficult task. For the purpose of solving this problem, a painting navigation system for visual...
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The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope(FAST) Survey(CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signal...
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The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope(FAST) Survey(CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts are not likely to thoroughly examine these signals, and various machine sorting methods are used to aid the classification of the FAST candidates. In this study, we propose a new ensemble classification system for pulsar candidates. This system denotes the further development of the pulsar image-based classification system(PICS), which was used in the Arecibo Telescope pulsar survey, and has been retrained and customized for the FAST drift-scan survey. In this study, we designed a residual network model comprising 15 layers to replace the convolutional neural networks(CNNs) in PICS. The results of this study demonstrate that the new model can sort >96% of real pulsars to belong the top 1% of all candidates and classify >1.6 million candidates per day using a dual-GPU and 24-core computer. This increased speed and efficiency can help to facilitate real-time or quasi-real-time processing of the pulsar-search data stream obtained from CRAFTS. In addition, we have published the labeled FAST data used in this study online, which can aid in the development of new deep learning techniques for performing pulsar searches.
With the advancement of IoT and artificial intelligence technologies, and the need for rapid application growth in fields such as security entrance control and financial business trade, facial information processing h...
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