The outbreak of COVID-19 disrupts the life of many people in the *** response to this global pandemic,various institutions across the globe had soon issued their prevention *** in the US had also implemented social di...
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The outbreak of COVID-19 disrupts the life of many people in the *** response to this global pandemic,various institutions across the globe had soon issued their prevention *** in the US had also implemented social distancing ***,those policies,which were designed to slow the spread of COVID-19,and its compliance,have varied across the states,which led to spatial and temporal heterogeneity in COVID-19 *** paper aims to propose a spatio-temporal model for quantifying compliance with the US COVID-19 mitigation policies at a regional *** achieve this goal,a specific partial differential equation(PDE)is developed and validated with shortterm *** proposed model describes the combined effects of transboundary spread among state clusters in the US and human mobilities on the transmission of *** model can help inform policymakers as they decide how to react to future outbreaks.
Batch Normalization (BN) is a well-known technique used in training deep neural networks. The main idea behind batch normalization is to normalize the features of the layers (i.e., transforming them to have a mean equ...
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Many high impact applications suffer from missing information. For example, disease-dedicated social networks provide additional resources to glimpse into patients’ daily life related to disease management. However, ...
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This paper presents a novel two-stage approach to enhance the quality and privacy of X-ray medical images. The first stage leverages generative adversarial networks (GANs) for effective denoising, eliminating noise an...
This paper presents a novel two-stage approach to enhance the quality and privacy of X-ray medical images. The first stage leverages generative adversarial networks (GANs) for effective denoising, eliminating noise and artifacts from X-ray images while improving the visibility of critical anatomical structures. Subsequently, number-theoretic transform (NTT) polynomial multiplication is integrated with Kyber to accelerate the encryption and decryption of the denoised X-ray images. This encryption safeguards the privacy of sensitive patient data and provides resilience against potential quantum computing attacks, ensuring long-term data security. Implementing Kyber-based encryption and decryption on a graphics processing unit (GPU) architecture significantly reduces latency, enabling real-time and secure access to critical healthcare information.
The deep operator network (DeepONet) architecture is a promising approach for learning functional operators, that can represent dynamical systems described by ordinary or partial differential equations. However, it ha...
Many hospitals in developing regions like East Malaysia are increasingly adopting health information systems (HIS) to enhance operational efficiency. The systems development life-cycle (SDLC) has been the traditional ...
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Recent advances in machine learning research have produced powerful neural graph embedding methods, which learn useful, low-dimensional vector representations of network data. These neural methods for graph embedding ...
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Maximum likelihood estimation (MLE) is often used in econometric and other statistical models despite its computational considerations and because of its strong theoretical appeal. The non-linear optimization discipli...
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Recently, the D3WA system was proposed as a paradigm shift in how complex goal-oriented dialogue agents can be specified by taking a declarative view of design. However, it turns out actual users of the system have a ...
Unstructured point clouds with varying sizes are increasingly acquired in a variety of environments through laser triangulation or Light Detection and Ranging (LiDAR). Predicting a scalar response based on unstructure...
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