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The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)

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Cover of 'The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)'

Table of Contents

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    Book Overview
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    Chapter 1 Apply Trust Computing and Privacy Preserving Smart Contracts to Manage, Share, and Analyze Multi-site Clinical Trial Data
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    Chapter 2 Design Principles for Interoperability of Private Blockchains
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    Chapter 3 Blockchain for Proposal Management
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    Chapter 4 One-Shot Federated Learning-based Model-Free Reinforcement Learning
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    Chapter 5 A New Approach for Selecting Features in Cancer Classification Using Grey Wolf Optimizer
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    Chapter 6 A Smart Video Surveillance System for Helping Law Enforcement Agencies in Detecting Knife Related Crimes
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    Chapter 7 Biologically Inspired Variational Auto-Encoders for Adversarial Robustness
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    Chapter 8 Detecting Illicit Ethereum Accounts Based on Their Transaction History and Properties and Using Machine Learning
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    Chapter 9 Identifying Incentives for Extortion in Proof of Stake Consensus Protocols
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    Chapter 10 Three-Valued Model Checking Smart Contract Systems with Trust Under Uncertainty
Attention for Chapter 5: A New Approach for Selecting Features in Cancer Classification Using Grey Wolf Optimizer
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Chapter title
A New Approach for Selecting Features in Cancer Classification Using Grey Wolf Optimizer
Chapter number 5
Book title
The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-16035-6_5
Book ISBNs
978-3-03-116034-9, 978-3-03-116035-6
Authors

AlMazrua, Halah, AlShamlan, Hala

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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