A journey of WEB and Blockchain towards the Industry 4.0: An Overview

Khan, Abdul Ghaffar; Zahid, Amjad Hussain; Hussain, Muzammil; Farooq, Muhammad; Riaz, Usama; Alam, Talha Mahboob

doi:10.1109/icic48496.2019.8966700

Cited by 60 publications

(16 citation statements)

References 6 publications

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“…Advantages of private blockchain can be stated as lower transaction cost, faster transaction speed and scalability. Major disadvantages are need for trust and centralized network structure (Khan et al, 2019). Consortium blockchains are almost a hybrid of public and private blockchains.…”

Section: Overview Of Blockchain Systemsmentioning

confidence: 99%

Corporate governance: Theory and practice

Kumar¹

2022

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Section: Overview Of Blockchain Systemsmentioning

confidence: 99%

Corporate governance: Theory and practice

Kumar¹

2022

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“…Consortium or federated blockchain networks show similarities in permissions to private blockchain networks. Consortium blockchain is a specific blockchain that has authorized nodes to protect distributed data [13,14].…”

Section: Blockchain and Usesmentioning

confidence: 99%

A Study of Blockchain in Iot Architecture

Şimşek

2021

International Journal of Engineering and Innovative Research

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Industry 4.0 includes that components such as artificial intelligence, big data, autonomous systems, human-robot interaction, and the internet of things. Because of these components; some benefits are aimed, such as minimizing human impact, reducing costs, and increasing business volume. It is seen that the most fundamental problem of Internet of Things (IoT) technology, which is one of the basic concepts of Industry 4.0, is security. In recent years, blockchain architectures have been trying to find a solution to this problem. This study focuses on blockchain architectures used in the IoT ecosystem.

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“…Several approaches for predicting and detecting COVID19 were explored. Most ML-based tactics have been used to forecast the presence, trends, or expansion of COVID19, whereas most Deep Learning approaches have been used to detect COVID19, showing that this problem has a diverse set of solutions and methodologies [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. The suggested approach is innovative because, in previous analogous techniques, just a few algorithms are employed and results are compared, or the dataset utilized is confined to one nation or fewer, or the dataset is made up of a smaller number of observations [43][44][45][46][47][48].…”

Section: Related Workmentioning

confidence: 99%

FLOSSC: A Computer-Aided Tool for Detecting Corona Virus Infections through Chest X-Ray Images

Ahmad

Javed

Aftab

et al. 2021

2021 International Conference on Innovative Computing (ICIC)

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Artificial intelligence has radically altered the world, and it continues to progress at an alarming rate as time passes. AI applications include healthcare and medical solutions, illness diagnostics, agriculture, constructing security infrastructures, autonomous cars, intelligent systems, industrial production, robotics, and much more. COVID19 is a deadly virus that first appeared in China in 2019 and soon spread over the world. By 2020, the globe had witnessed a tremendous epidemic, with countless lives lost as a result of this dreadful virus, which has now become a severe health danger. Furthermore, in 2021, several nations will be infected with new Covid19 forms that are more deadly and spread quicker. The research describes the proposed methodology for diagnosing covid-19 and pneumonia from human chest X-ray images using transfer learning with Resnet-18 and VGG-16 neural networks. The focal loss function was also used to homogenize the imbalanced dataset, which included X-ray images of normal, pneumonia, and Covid-19 patients. The purpose is to assess the performance and accuracy of fine-tuned neural networks after including Binary Cross-Entropy (BCE) and Focal Loss (FL) functions. However, when we used our Resnet-18 and VGG-16 neural networks with BCE and FL functions, the VGG-16 with FL function outperformed all other models, with training and validation accuracy of 98.37 percent and 97.37 percent, correspondingly.

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A journey of WEB and Blockchain towards the Industry 4.0: An Overview

Cited by 60 publications

References 6 publications

Corporate governance: Theory and practice

Corporate governance: Theory and practice

A Study of Blockchain in Iot Architecture

FLOSSC: A Computer-Aided Tool for Detecting Corona Virus Infections through Chest X-Ray Images

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