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      KCI등재 SCIE SCOPUS

      Dyeing Behavior of Enzyme and Chitosan-Modified Polyester and Estimation of Colorimetry Parameters Using Random Forests

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      https://www.riss.kr/link?id=A108969924

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      Dyeing of the crystalline structure necessitates a process with a disperse dye either at high temperatures or with a carrier dueto its compact and non-ionic structure of polyester. In this study, in order to eliminate these limitations and develop mor...

      Dyeing of the crystalline structure necessitates a process with a disperse dye either at high temperatures or with a carrier dueto its compact and non-ionic structure of polyester. In this study, in order to eliminate these limitations and develop moreenvironmentally friendly dyeing processes, the dyeability of polyester under different conditions with reactive, direct, andacid dyes after surface modifications with enzyme and chitosan was investigated. In addition to the corresponding physicalexperiments, CIELAB and color strength values were also estimated using random forests. The results of the physical experimentsshowed that the surface modifications conducted with enzyme and chitosan significantly increased the color depthsobtained in dyeing for reactive, direct, and acid dyes, especially at pH 4.5. This was explained by the potentially protonatedamine groups in acidic medium of chitosan could have attracted large amounts of anionic dye molecules with physical forces.
      The highest color depths were obtained from acid dyeing. Washing fastness of the pre-treated and dyed fabrics (except theacid-dyed fabrics) decreased with the shift of the bath pH values to the acidic region. In the next phase of the study, weimplemented random forests to estimate CIELAB and color strength values. We considered different random forest designsand trained each design ten times to observe the performance of the corresponding topology. The results of the computationalexperiments showed that the estimation performance of the random forests is quite satisfactory (with R-values greater than99%) and random forests could be used to estimate CIELAB and color strength values successfully.

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