Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart

Conventional DL-EPRT was extrapolated into accounting for inherent inconsistencies amongst grain boundary (GB) dimensions whilst correlating two distinct methods of ir/ia normalization, namely the approximate Cihal method (CM) and the relatively involved image processing (IP). Inasmuch as facilitati...

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Main Author: Abdulla F. Alshater
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Nuclear Materials and Energy
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352179124001558
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author Abdulla F. Alshater
author_facet Abdulla F. Alshater
author_sort Abdulla F. Alshater
collection DOAJ
description Conventional DL-EPRT was extrapolated into accounting for inherent inconsistencies amongst grain boundary (GB) dimensions whilst correlating two distinct methods of ir/ia normalization, namely the approximate Cihal method (CM) and the relatively involved image processing (IP). Inasmuch as facilitating the forecast of IP- from CM-based normalizations, the full spectrum of plausible predictive models was subjected to cross validations that revealed those emanating from GB length-based endeavors to be quadratic with R2 and mean error (E) of 0.9215 and 0.5769, respectively. Meanwhile, GB area normalizations succumbed to a linear polynomial yielding R2 and E values of 0.8795 and 0.3664, respectively.
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spelling doaj-art-afb42dba4efd4bc1a6af1f9edb455b2a2025-08-20T01:57:04ZengElsevierNuclear Materials and Energy2352-17912024-12-014110173210.1016/j.nme.2024.101732Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpartAbdulla F. Alshater0College of Engineering, University of Bahrain, PO.Box 32038, Isa Town Campus, Kingdom of BahrainConventional DL-EPRT was extrapolated into accounting for inherent inconsistencies amongst grain boundary (GB) dimensions whilst correlating two distinct methods of ir/ia normalization, namely the approximate Cihal method (CM) and the relatively involved image processing (IP). Inasmuch as facilitating the forecast of IP- from CM-based normalizations, the full spectrum of plausible predictive models was subjected to cross validations that revealed those emanating from GB length-based endeavors to be quadratic with R2 and mean error (E) of 0.9215 and 0.5769, respectively. Meanwhile, GB area normalizations succumbed to a linear polynomial yielding R2 and E values of 0.8795 and 0.3664, respectively.http://www.sciencedirect.com/science/article/pii/S2352179124001558Degree of sensitizationDouble loop electrochemical potentiokinetic reactivationNormalizationCihal methodImage processing
spellingShingle Abdulla F. Alshater
Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
Nuclear Materials and Energy
Degree of sensitization
Double loop electrochemical potentiokinetic reactivation
Normalization
Cihal method
Image processing
title Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
title_full Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
title_fullStr Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
title_full_unstemmed Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
title_short Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart
title_sort predicting image processing normalized dl eprt performance from rudimentary cihal method based counterpart
topic Degree of sensitization
Double loop electrochemical potentiokinetic reactivation
Normalization
Cihal method
Image processing
url http://www.sciencedirect.com/science/article/pii/S2352179124001558
work_keys_str_mv AT abdullafalshater predictingimageprocessingnormalizeddleprtperformancefromrudimentarycihalmethodbasedcounterpart