Journal of Textile Engineering
Online ISSN : 1880-1986
Print ISSN : 1346-8235
ISSN-L : 1346-8235
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Volume 60, Issue 6
Displaying 1-2 of 2 articles from this issue
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Original Papers
  • Relation between Hand of Bath Towel and Physical Properties
    Toyonori NISHIMATSU, Hiroyuki KANAI, Megumi FUJIWARA, Kyouhei TAKAHAS ...
    2014 Volume 60 Issue 6 Pages 91-98
    Published: December 15, 2014
    Released on J-STAGE: March 03, 2015
    DOIhttps://doi.org/10.4188/jte.60.91
    JOURNAL FREE ACCESS
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    The hand is one of the important qualities of bath towels. It is interesting to study what physical properties of bath towels correlate to their hand. In this paper, the relationship between the sensory values for the good feel and physical properties of twelve bath towels was studied by means of the principle regression analysis and the correlation analysis. The results are as follows.
    (1) As a result of principal component analysis, it was found that two principal component “good in touch” and “sturdy and drying property” were chosen to represent the hand of bath towel.
    (2) The compression feeling was affected by compression properties((To-TM), compression ratio, compression energy, and recovery energy). And the softness feeling was affected by the friction property(MMD), and the warmth by the thermal property(q-max).
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  • Wrinkle Grading of Cotton Slacks Using Wrinkle Tester
    Hajime TSUJI, Hiroyuki KANAI , Takamoto TAZAWA, Kiyohiro SHIBATA
    2014 Volume 60 Issue 6 Pages 99-102
    Published: December 15, 2014
    Released on J-STAGE: March 03, 2015
    DOIhttps://doi.org/10.4188/jte.60.99
    JOURNAL FREE ACCESS
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    In business settings, casual wear has become more common under the influence of COOL BIZ. There have been few reported studies on mitigation technology and methods for quantifying wrinkles in easy-to-wrinkle fabrics. Therefore, in this study, we investigated a method of predicting a wrinkle grade of cotton slacks. Image processing and texture analysis were performed on images of wrinkles, and the features of wrinkles were extracted. The method for predicting wrinkle grade from the features appearing in wrinkle images was derived on the basis of multiple regression analysis. As the result, the difference variance (DVAR) of wrinkle image was adopted as an explanatory variable.
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