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Evaluating biometrics by using a hybrid MCDM model
Biometrics has been developing for decades in diverse industries, such as consumer electronics, internet of things, financial industry, etc. The purpose of this research is to build a decision-making model to evaluate and improve the performances of biometrics for administrators to design and make s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531444/ https://www.ncbi.nlm.nih.gov/pubmed/34675251 http://dx.doi.org/10.1038/s41598-021-00180-2 |
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author | Tsuei, Hung-Jia Shen, Guiping Tzeng, Gwo-Hshiung |
author_facet | Tsuei, Hung-Jia Shen, Guiping Tzeng, Gwo-Hshiung |
author_sort | Tsuei, Hung-Jia |
collection | PubMed |
description | Biometrics has been developing for decades in diverse industries, such as consumer electronics, internet of things, financial industry, etc. The purpose of this research is to build a decision-making model to evaluate and improve the performances of biometrics for administrators to design and make suitable biometric systems. This paper adopts a hybrid multiple criteria decision making (MCDM) model, comprising decision-making trial and evaluation laboratory (DEMATEL), and DEMATEL-based analytic network process (called DANP) to probe into the interrelationship and influential weights among criteria of biometrics. According to DEMATEL technique, the empirical results indicate that criteria of biometrics have self-effect relationships. The dimension of biometrics that administrators of biometrics should enhance first when improving the performances is usability. The criterion of universality with the highest influencing value to systematically affect all other evaluation factors is what administrators of biometrics should comprehensively consider. In the top three criteria for evaluation by DANP, biometric systems with the most influential weight is the criterion that can be improved to have higher recognition rates for increasing the performances of biometrics, followed by biometric conditions and permanence. |
format | Online Article Text |
id | pubmed-8531444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85314442021-10-25 Evaluating biometrics by using a hybrid MCDM model Tsuei, Hung-Jia Shen, Guiping Tzeng, Gwo-Hshiung Sci Rep Article Biometrics has been developing for decades in diverse industries, such as consumer electronics, internet of things, financial industry, etc. The purpose of this research is to build a decision-making model to evaluate and improve the performances of biometrics for administrators to design and make suitable biometric systems. This paper adopts a hybrid multiple criteria decision making (MCDM) model, comprising decision-making trial and evaluation laboratory (DEMATEL), and DEMATEL-based analytic network process (called DANP) to probe into the interrelationship and influential weights among criteria of biometrics. According to DEMATEL technique, the empirical results indicate that criteria of biometrics have self-effect relationships. The dimension of biometrics that administrators of biometrics should enhance first when improving the performances is usability. The criterion of universality with the highest influencing value to systematically affect all other evaluation factors is what administrators of biometrics should comprehensively consider. In the top three criteria for evaluation by DANP, biometric systems with the most influential weight is the criterion that can be improved to have higher recognition rates for increasing the performances of biometrics, followed by biometric conditions and permanence. Nature Publishing Group UK 2021-10-21 /pmc/articles/PMC8531444/ /pubmed/34675251 http://dx.doi.org/10.1038/s41598-021-00180-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tsuei, Hung-Jia Shen, Guiping Tzeng, Gwo-Hshiung Evaluating biometrics by using a hybrid MCDM model |
title | Evaluating biometrics by using a hybrid MCDM model |
title_full | Evaluating biometrics by using a hybrid MCDM model |
title_fullStr | Evaluating biometrics by using a hybrid MCDM model |
title_full_unstemmed | Evaluating biometrics by using a hybrid MCDM model |
title_short | Evaluating biometrics by using a hybrid MCDM model |
title_sort | evaluating biometrics by using a hybrid mcdm model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531444/ https://www.ncbi.nlm.nih.gov/pubmed/34675251 http://dx.doi.org/10.1038/s41598-021-00180-2 |
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