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Titlebook: Real-Time Intelligence for Heterogeneous Networks; Applications, Challe Fadi Al-Turjman Book 2021 The Editor(s) (if applicable) and The Aut

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發(fā)表于 2025-3-23 11:50:31 | 只看該作者
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發(fā)表于 2025-3-23 14:42:48 | 只看該作者
Akbar Abbasi,Fatemeh Mirekhtiary,Hesham?M.H. Zakalyepidemiology or statistics.Provides students and other healtThis textbook was born from a disparate collection of written materials that were created to teach Epidemiology and Biostatistics to second year medical students at the University of Washington. These materials included handouts, practice p
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發(fā)表于 2025-3-23 20:11:58 | 只看該作者
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發(fā)表于 2025-3-24 01:18:24 | 只看該作者
Correction to: Nuclear Radiation Monitoring in the Heterogeneous Internet of Things Era,
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發(fā)表于 2025-3-24 04:26:59 | 只看該作者
Machine Learning Applications for Heterogeneous Networks,rms a heterogeneous network (HetNet). Initial studies indicate that HetNets will be an integral part of 6G. This chapter presents an overview of HetNets, discusses research challenges, and outlines how a machine learning (ML) approach can address some of the challenges.
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發(fā)表于 2025-3-24 08:14:05 | 只看該作者
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發(fā)表于 2025-3-24 12:51:07 | 只看該作者
Cooperative Mobile Traffic Offloading in Mobile Edge Computing for 5G HetNet IoT Applications,ad. The existing infrastructure converges IoT and cloud computing to provide a multi-level processing technology. This technological development modernizes the information age to extend the technical support which builds smart cities to analyze digital technologies. In a smart city, the digital proc
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發(fā)表于 2025-3-24 18:50:53 | 只看該作者
Convergence of Blockchain in IoT Applications for Heterogeneous Networks, its potential benefits. Further, it discusses the use cases for the application of blockchain in IoT and examines the consensus mechanism and data stored in the blockchain of different IoT applications. It also provides an insight into the challenges and open issues for the large-scale implementati
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發(fā)表于 2025-3-24 20:25:56 | 只看該作者
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發(fā)表于 2025-3-25 02:54:46 | 只看該作者
Classification of Solid Wastes Using CNN Method in IoT Het-Net Era,ing them by human hands. With artificial intelligence applied machines, the classification of garbage is faster and hygienic. These methods are particularly beneficial in terms of being hygienic and time-saving. In this paper, there are 6 classes of recyclable materials, including 3198 waste garbage
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