Digital mode of communication is widely used for exchanging various kinds of data through internet. The data that is being transmitted may be used in sensitive applications. Thus, those data have to be secured from va...
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Retina is a vital component of the eye;it plays a crucial role in visual perception. Any damage to the retina can lead to vision impairment and severe ocular diseases. Early detection and accurate diagnosis of retinal...
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The integration of blockchain technology into the grocery purchasing process offers a transformative approach to enhancing transparency, security, and efficiency. This paper presents a comprehensive framework for a bl...
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This study investigates the potential use of blockchain technology and smart contracts to construct a decentralised land registry system. It looks at the problems with traditional land registry systems and provides a ...
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This work investigates using Convolutional Neural Networks (CNN) and VGGNet architecture, for realtime emotion detection. Raw data from the FER-2013 dataset is transformed from CSV format into organized image director...
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DCD (Developmental Coordination Disorder) has become a global problem, and several studies have shown that early detection and intervention are important for the prevention and treatment of DCD in children. To address...
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Assessing sleep stages is crucial for identifying and managing sleep disorders such as REM sleep disorders and narcolepsy. Automating this process not only expedites detection but also enhances diagnostic accuracy. Th...
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A Bike rental expectation conjectures the interest for bikes rentals in reliance of climate conditions like the temperature and calendric data. In bike rental frameworks, it is vital that the managers have to realize ...
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Thyroid disease is estimated to be the most common illness in the twenty-first century. The thyroid hormones are produced by a butterfly-shaped gland in the throat. The crucial function these hormones play in bodily m...
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To predict the lithium-ion(Li-ion)battery degradation trajectory in the early phase,arranging the maintenance of battery energy storage systems is of great ***,under different operation conditions,Li-ion batteries pre...
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To predict the lithium-ion(Li-ion)battery degradation trajectory in the early phase,arranging the maintenance of battery energy storage systems is of great ***,under different operation conditions,Li-ion batteries present distinct degradation patterns,and it is challenging to capture negligible capacity fade in early *** the data-driven method showing promising performance,insufficient data is still a big issue since the ageing experiments on the batteries are too slow and *** this study,we proposed twin autoencoders integrated into a two-stage method to predict the early cycles'degradation *** two-stage method can properly predict the degradation from course to *** twin autoencoders serve as a feature extractor and a synthetic data generator,***,a learning procedure based on the long-short term memory(LSTM)network is designed to hybridize the learning process between the real and synthetic *** performance of the proposed method is verified on three datasets,and the experimental results show that the proposed method can achieve accurate predictions compared to its competitors.
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