• Korean Journal of Heritage: History & Science
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• v.57 no.2
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• pp.102-115
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• 2024

Painted Cultural heritage uses various materials such as paper, silk, wood, soil, and lime as a base layer to draw on using ink sticks and express lines or colors using various colorants. The importance of underdrawings is emphasized when it comes to replication and preservation, as they can reveal the original drawing. Investigations using infrared have been extensively conducted to detect underdrawings. However, there has been a paucity of research on the influence of underdrawing detection according to the base layer. In this study, the effect of the base layer materials on underdrawing detection in painted cultural heritage was confirmed using an infrared camera and hyperspectral camera (900 to 1700 nm). The study samples marked '檢' with ink below the color layer (cinnabar, orpiment, malachite, azurite, white lead, and red lead) by the base layer materials: Paper (Dakji, indigo/Dakji), silk (silk, silk/white lead), wood (celadonite/wood), soil (celadonite/soil), and lime. The difference in the effect on underdrawing detection was minimal for paper and silk, and no significant differences were found between Dakji and indigo/Dakji, or between silk and silk/white lead. However, we found that celadonite/wood, celadonite/soil, and lime have a significant impact on underdrawing detection. In particular, for wood and soil painted with celadonite, underdrawings were not detected for all six color layers. In the case of lime, it was found that all color layers except malachite had a more positive effect on underdrawing detection. The findings of this study will aid in selecting the appropriate method for underdrawing analysis in the restoration of painted cultural heritage.

• Korean Journal of Human Ecology
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• v.14 no.3
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• pp.467-473
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• 2005

The integrative Internet program was developed for the selection of optimal brassiere components according to the breast types of middle-aged women. In this program, a customer is classified into a certain group through three steps of a discriminant analysis. Three variables used in the analysis include breast volume, radii of curvature of under-breast curve, and a distance between inner breast points. Using individual data of three variables, the optimal brassiere components, i.e. brassiere cup size, curvature of front panel and wire, distance between cups, are suggested for each customer. Discrimination of breast types using only 2D measurements is also included for those who do not have easy access to a 3D measurement device.