Unsupervised Dimensionality Reduction Modeling for Analyzing Aging Characteristics of Hanji

Yong Ju Lee; Ji Eun Cha; Na Young Kang; Soon Wan Kweon; Hyoung Jin Kim; Kwang-Ho Kang

doi:10.7584/JKTAPPI.2023.12.55.6.96

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2023 Vol.55, Issue 6 Preview Page Next Page

Research Article

Unsupervised Dimensionality Reduction Modeling for Analyzing Aging Characteristics of Hanji 비지도학습 기반 차원 축소 모델링을 통한 한지의 열화특성 분

30 December 2023. pp. 96-108

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Abstract

This study investigated the applicability of principal component analysis (PCA) and infrared (IR) spectroscopy in the context of paper aging. Furthermore, it explored the feasibility of employing a t-distributed stochastic neighbor embedding (t-SNE) model for visualizing the aging characteristics of Hanji, a traditional Korean paper, particularly in relation to accelerated aging categories. A total of 130 Hanji IR spectra were collected via attenuated total reflectance IR spectroscopy and categorized into four groups based on the origin, aging time, and aging method (dry and moist heat). The PCA and t-SNE analysis were conducted on the first derivative of the IR spectra. This process enabled the classification and visualization of aged Hanji. Additionally, PCA identified carboxyl and carbonyl groups as critical components influencing cellulose aging. Overall, unsupervised dimensionality reduction models, such as PCA and t-SNE, along with IR spectral data, can be used to characterize the chemical properties of aged papers.

Keywords

PCA

t-SNE

dimensionality reduction

chemometrics

Hanji

aging

aged paper

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Information

Publisher :Korea Technical Association of The Pulp and Paper Industry
Publisher(Ko) :한국펄프종이공학회
Journal Title :Journal of Korea TAPPI
Journal Title(Ko) :펄프종이기술
Volume : 55
No :6
Pages :96-108
Received Date : 2023-11-21
Revised Date : 2023-12-12
Accepted Date : 2023-12-15
DOI :https://doi.org/10.7584/JKTAPPI.2023.12.55.6.96

Journal of Korea TAPPI 펄프종이기술 ISSN:0253-3200(Print)

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