Traditional password-based authentication methods confront several issues such as security weaknesses, user inconvenience, and susceptibility to various attacks, e.g. phishing. These issues are solved with newly creat...
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Automatic monitoring and evaluation of cattle welfare status in smart pastures requires tracking and identification of the target cattle39;s ear area and morphology based on video images. Most of the traditional met...
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In this paper, the average bit-error-rate (BER) performance of a two-hop parallel-relayed underwater wireless optical communication (UWOC) systems with on-off keying (OOK) was analyzed in generalized gamma distributio...
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Network resource sharing needs more flexible and efficient for diversified services with the rapid evolution of 5G network and IoT technology, the current sharing cannot support highly decentralized resource collabora...
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As social beings, humans like to interact with each other, including other creatures of God, such as animals, and keep them as pets. Many pets, such as dogs, cats, birds, fish, rabbits, and so on, include unusual pets...
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Smart solutions in the healthcare domain have garnered considerable attention due to their potential to enhance standard treatment methods and improve overall health. However, privacy concerns often prevent the sharin...
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ISBN:
(纸本)9798350369458;9798350369441
Smart solutions in the healthcare domain have garnered considerable attention due to their potential to enhance standard treatment methods and improve overall health. However, privacy concerns often prevent the sharing of healthcare data, which can limit the scope for improvement. In this context, Federated Learning (FL) has emerged as a transformative paradigm in machine learning. It enables collaborative model training across decentralised devices while preserving data privacy and security. This approach has gained significant traction in recent years, particularly within the healthcare sector. It offers unprecedented opportunities to harness collective intelligence from diverse healthcare datasets without compromising sensitive patient information. This survey paper summarises numerous research works that focus on the application of FL to address various healthcare challenges. Moreover, a comparison of these works is conducted, summarising the different technologies employed in each case. Therefore, in light of the previous remarks, this paper provides an up-to-date overview of the state of the art in the application of FL in the healthcare industry.
The high proportion of distributed new energy access and large-scale power electronics applications make the new power system more complex, leading the power grid operation facing greater challenges. Therefore, there ...
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Based on the time series online prediction model, this paper proposes a WE-OSELM online prediction algorithm, which can control the product life and performance in real time in the field of engine, and effectively man...
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Due to the rapid development of Internet of Things (IoT) technology, there is a closer and more complex coupling relationship between energy network and information network in the integrated energy park than ever that...
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Quality and quantity plays a vital role in Jewellery stores, the main part for a store is maintaining the quality and quantity of the product. The solution for this is to use Blockchain. Blockchain was firstly used fo...
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