Classifying Time-Bound Hierarchical Key Assignment Schemes

Vadi, Vikas Rao; Kumar, Naveen; Abidin, Shafiqul

doi:10.1007/978-981-15-4409-5_10

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…For this purpose many other words Used in real-Time Factory [19], or intelligent factory of the future [20]. Scientist's smart production technology, attitude [21] or using paradigm [18]. All terms within and ideas much for future technological development Promising opportunities.…”

Section: Smart Factorymentioning

confidence: 99%

A Review on Industry 4.0 Information Integration and Its Application

2022

JEMM

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Information integration with CPS and industrial advanced technologies, Industry 4.0 will improve the overall quality of industrial production. The "smart factory" is an integral part of the future focused on the implementation of intelligent manufacturing systems and the infrastructure of distributed processes and production facilities across the network. The literature review concludes by searching for some key words. Scopus and Google Scholar were searched to search for these keywords. Some of the sustainable smart manufacturing initiatives in the international arena are using the words "smart manufacturing" and "Industry 4.0". These words are considered interchangeable although there are slight differences in their definitions from each other. All three terms refer to the primary objective of implementing businesses in different countries, which are production ecosystems to integrate and adopt new information and operational technologies, as well as to create new revenue and cost and efficiency business models for profit and operation. Findings from this literature review indicate that current reference models and frameworks derived from these SM initiatives are highly relevant and readily available to MNEs

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Section: Smart Factorymentioning

confidence: 99%

A Review on Industry 4.0 Information Integration and Its Application

2022

JEMM

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An efficient flexible hierarchical access control scheme enabling real-life exceptions

Lal

Kumar

2022

Sādhanā

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Disease Detection System

Sawhney,

Tiwari,

Kirti

et al. 2024

Advances in Healthcare Information Systems and Administration

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A type of machine learning called supervised learning uses labelled training data to teach computers how to forecast the outcome. The labeled data denotes that some input data has been already marked with the correct output. This training data acts as a supervisor, guiding the machines to accurately forecast the output, akin to a teacher supervising a student. The objective of supervised learning is to provide a machine-learning model with correct input and output data. The method seeks a mapping function that connects the input variable (x) to the output variable (y). The spread of numerous diseases through common means such as air and touch has become a significant concern, particularly during the COVID-19 pandemic. The Disease Detection System employs supervised learning to address this challenge by detecting diseases with just a few clicks on the software. In the future, the input-based prediction system could be extended to an im-age-based prediction system.

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Classifying Time-Bound Hierarchical Key Assignment Schemes

Cited by 7 publications

References 16 publications

A Review on Industry 4.0 Information Integration and Its Application

A Review on Industry 4.0 Information Integration and Its Application

An efficient flexible hierarchical access control scheme enabling real-life exceptions

Disease Detection System

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