• Korean Journal of Human Ecology
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• v.23 no.3
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• pp.501-514
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• 2014

In this study, visual images were analyzed with the representative seven kinds of selected skirts, by the differences of shape and length which are affecting to the images of skirts. In addition, the purpose of the study is to present the basic data for the skirt design and patterns those are appropriate to the preferred images of 20-30s. The results of this study are as follows. First, analyzed by the visual evaluation about the composing factors are as follows. Factor 1 is a Cute image factor, factor 2 is a charming image factor, factor 3 is a transversal factor, Factor 4 is active image factor, Factor 5 was classified as a longitudinal factors. Second, analyzed by the visual evaluation according to the shape and length of the skirt, 20-30s women's most preferred form of the skirt is pleated skirt which was highly evaluated looks good, beautiful, favorite, attractive factors. Non-prefered skirts are gored skirt which was highly evaluated not corny, not pretty, heavy, unattractive factors and gored skirt which was negatively evaluated with classic and dislike factors. In the length of skirt, the knee length short skirt is attractive, active and positively evaluated by the 20-30s women than long skirt. Therefore, the results of this study, there are almost no differences according to the age groups of 20-30s women. They are more affected from the length of the skirt rather than the shape.

• The Research Journal of the Costume Culture
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• v.12 no.6 s.53
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• pp.933-944
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• 2004

This study was aimed to provide the fundamental and various measurement data of the head and face for male children. Two hundred forty one male children, aged nine to twelve years, participated for this study. The 31 regions on the head and face of the subjects were directly measured by the expert experimenters. Through factor analysis, the six factors were extracted upon factor scores and those factors comprised $67.47\%$ for the total variances. The first factor was described the general height elements for the mouth and the environs of the mouth. The second factor was described the general height around the nose, forehead and eyes. The third factor was described the height of the ear environs. The forth factor contained the length around the sinciput to the occiput, the head thick and the head circumstance. The fifth factor was described the general width of the outer head and the corner of the eyes. The last factor contained the depth of the mouth and nose. Four clusters as their head and face shape were categorized using six factor scores by cluster analysis. Type 1 was characterized by the shortest head and face width, surface length and girth, and the shorter length of head, but the highest position of chin, philtrum, upper lip. Type 2 was characterized by the shortest head and face length and thickness, and the lowest position of the forehead, eye, nose, mouth, ear environs, but that had wider width of head and face. Type 3 was characterized by the longest and the widest head and face type, and the highest position of the mouth. Type 4 was characterized by longer length of head and face, and the widest head girth and largest head thickness, and the highest position of the forehead, eye, nose environs. And this type had the widest width of nose and mouth, and the longest head surface length.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.4
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• pp.631-646
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• 1996

The purpose of this study was to investigate the difference of visual evaluation about silhouette image. The specific objective were; 1) to construct of silhouette image evaluation instrument using semantic differential scale for the purpose of measuring the width and length; 2) to identify the factor structure of the silhouette; 3) to test the difference of visual perception to the silhouette as the variation of width; 4) to test the difference of visual perception to the silhouette as the variation of length; 5) to test interaction effect between width and length. The major finding were; For the visual evaluation of silhouette as shoulder width variatiorl, there were significant difference in hardness and softness factor. For the hard and soft image, we should express by variation of the shoulder width. For the visual evaluation of silhouette as skirt width variation, there were significant difference in attention factor. For the attensive image, we should express by variation of the skirt width. For the visual evaluation of silhouette as skirt length variation, there were significant difference in activity factor. For the active image, we should express by variation of the skirt length.

• Journal of Fashion Business
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• v.13 no.5
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• pp.81-92
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• 2009

The purpose of this study is to evaluate the differences of visual effects by variations in the number of pleats and the length of the pleats skirt. The stimuli are 18 samples: 6 variations of the number of pleats and 3 variations of the length of skirt. The data has been obtained from 54 fashion design majors. The data has been analyzed by Factor Analysis, Anova, Scheffe's Test and the MCA method. The results of the study are as follows: The visual effects by the number of pleats and the length of skirt are composed of 3 factors : vertical of lower body, curves of lower body and shape abdomen. In these factors, vertical factor is estimated by the most important factor. The visual effect is positive when the number of pleats is added and the length of skirt is getting shorter. The short length of skirt and more pleats make legs and calves looked long and slim. The interaction effects between the number of pleats and the length of skirt do not appear. In the vertical of low body factor, the length of skirt is more effective than the number of pleats, and in the curve of low body factor, the number of pleats has more effects than the length of the skirt. In the shape of abdomen, the number of pleats and length of skirt have similar influences.

• Journal of the Korean Society of Costume
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• v.51 no.6
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• pp.167-176
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• 2001

This study analyzes characterization and classification of body types of Mongolian women aged 18∼39 ages. The anthropometric measurements of the research subjects come up to a total of 23 items and are summarized as follows : 1. As the results of comparative analysis of the body measurements by age group, 16 items show a significant difference except shoulder height, thigh girth, neck base girth, back length shoulder length, sleeve length and weight. Both age group are considered to be of average weight but 25 to 39 age group were slightly greater than that of the 18 to 24 age group. 2. As the results of factor analysis, 4 factors such as the first factor on the obesity of body, the second factor on the vertical size of body, the third factor on the back length, the forth factor on the shoulder width and neck base girth were extracted. 3. As the results of classification based on the duster analysis, the body types were classified into 3 types in each age group. In each age group the most frequent body type is average stature and slightly thin type.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.55-65
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• 2019

Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models' backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.137-146
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• 2020

The manual measurements of 182 unmarried women subjects in their 20s was classified 4-breast types. For the breast type classification, 4 factors were identified, such as overall breast factor, upper breast internal shape factor, breast volume factor, and lower breast external shape factor. The breast shapes were 'breast with well-grown upper part', 'flat breast', 'breast with well-grown lower part', and 'protruded breast'. The breast types can be differentiated in 10 items of actual anthropometric dimension the length between frontal neck point and nipple point, length between lateral neck point and nipple point, length between the breast inner points, nipple to nipple breadth, diameter below the breast, inner depth of breast, outer length of breast, length below the breast, length between breast outer point and upper breast point, and contour line length below the breast.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.2
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• pp.203-214
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• 1998

The purpose of this study is to classify the upper body of women into several kinds of somatotypes, using the method of Surgical Tape and making their shells. The subjects are 53 females 30 to 39 years-old. Fifty-three anthropometric data are measured per shell of bodysurface; six somatotype factors are obtained through principal component analysis and orthogonal rotation by the method of Varimax, Somatotype of women's upper body is achieved by cluster analysis, using the standardized factor score as an independent variable and the FASTCLUS of SAS by Kmeans. The results are as follows: 1. The number of the factors which explain the somatotype is six and those factors comprise 76.12 percent of total variance. Factor 1: related to the size of shape in the front of upper body Factor S: related to the size of shape in the back of upper body Factor 3: related to the type of the upper chest over the chest circumference line Factor 4: related to the length of·the upper body Factor 5: related to the part of the neck Factor 6: related to the type of the lower chest under the chest circumference line 2. Cluster analysis results in classification of upper body into five clusters. Cluster L: the length is the largest and the circumference is small. The part of waist is the largest and widest among surface areas. Cluster 2: Slender body line from chest to waist is characteristic. The length is longer. The part of upper and lower chest is larger among surface areas. Cluster S: the circumference is the smallest and armhole is small. The length and surface area are small. Cluster 4: the circumference and armhole is the largest. The length is the smallest. Cluster 5: the circumference is average and the length is a little long. The body line(silhouette) from chest to waist is curved slightly.

• Journal of the Korea Fashion and Costume Design Association
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• v.10 no.2
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• pp.79-89
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• 2008

The purpose of this study is to evaluate the differences among visual images under variations in shoulder length and puff volume of the puff sleeve blouse. The stimuli are 21 samples: three variations of shoulder length and seven variations of puff volume. The data has been obtained from 40 fashion design majors, where they had been analyzed through frequency, factor analysis, ANOVA, Scheffe's test and MCA method. The results of the study are as the following: As a result, through factor analysis of the visual images according to the variation of shoulder point and puff volume, the following four factors had been identified. Factor 1 is the brightness from evaluation terms such as childish-precocious, cute-mature, bright-genteel, soft-hard, enlarged-reduced, particular-ordinary, interesting- uninteresting, etc. Factor 2 is the attractiveness from evaluation terms such as refine-rustic, stylish-dull, attractive-unattractive, modern-classic, urban-rural, cool-gloomy, spacious-tight. etc. Factor 3 is the comfortness from evaluation terms such as comfort-discomfort, intense-indistinct, etc. Factor 4 is the elegance from evaluation terms such as elegance-shallowness, womanish-manly, etc. These four factors were 66.7% of the total variables. Of the total variables, the first factor had been evaluated as brightness in 26.2%, attractive in 21.0%, comfortness in 11.1%, and elegance in 8.4%. From this study, the more puff volume and shorter shoulder length, the puff volume wrapped the shoulder naturally, thus making the shoulder look narrow, and giving a cute and bright image. However, by having less puff volume and excessively short shoulder length, the puff volume did not naturally wrap the shoulder, which gave an unnatural and unattractive feel.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.126-134
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• 1997

In this study, We made visual inspection system using Vision Board. It is consist of an illuminator (a fluorescent lamp), image input device (CCD (Charge-Coupled Device) camera), image processing system(Vision Board(FARAMVB-02)), image output device (video monitor, printer), and a measuring instrument(TELMN1000). Length measurement by visual inspection system make use of 100mm guage block(instead of calculating distance between a camera and a object). It measured horizontal and vertical length factor from 400mm to 650mm by increasing 50mm. In this place, measured horizontal and vertical length factor made use of length measure- ment of a injection. A measuring instrument used to ompare a measured length of a injection visual inspection system with it. In conclusion, length measurement of a injection compared a measuring instrument with visual inspecion system using length factor of 100mm gauge block. We find that maximum error of length is 0.55mm when it compar with the measuring value of two devices(FARAMVB-02, TELMN1000). Program of visual inspection system is made up Borland C++3.1.