• Journal of the Ergonomics Society of Korea
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• v.13 no.2
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• pp.25-31
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• 1994

This research examines classifying and characterizing breast form's classification on elderly women, 242 subjects from 55 to 75 years of age participated. 27 direct anthropometric measurement were applied to classify the breast typesl. We analyzed measurement data using factor analysis, cluster analysis, analysis of variance. The results of the study were as follows. 1) 55-64 aged group was taller and higher than 65-79 aged group. Typical breast form in 55-64 aged group was more obese than breast form in 65-79 aged group. 2) We extracted 5 factors(obesity of breast, height of breast, height of breast items, location & size of breast, width of upper chest & shouldet length, height of breast & lower length of nipples) from total items through factor analysis. 3) Through cluster analysis, we categorized 3 clusters. Namely, type 1; characterized the best slender type, type 2; characterized middle sized type, type 3: characterized obesity type. Type 2 is the typical type on elderly women.

• Journal of Korean Society of Forest Science
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• v.70 no.1
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• pp.28-37
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• 1985

In order to estimate breast-height form factors of Pinus thunbergii and Cryptomeria japonica, 8 models based on tree age, diameter at breast height and tree height were suggested and evaluated. It was the following equations that turned out to be most fit for estimating them; for Pinus thunbergii, $F=0.553-4.567\;1/A+71.409\;1/A^2$ ($R^2=0.928$), based on tree age, ($6.727^{**}$) ($14.100^{**}$) $F=0.356+1.774\;1/D-0.770\;1/D^2$ ($R^2=0.944$), based on diameter at breast height, ($15.102^{**}$) ($2.908^{**}$) $F=0.316+1.546\;1/H+0.397\;1/H^2$ ($R^2=0.941$), based on tree height, ($8.380^{**}$) ($3.896^{**}$) for Cryptomeria japonica, $F=0.400+2.348\;1/A+17.053\;1/A^2$ ($R^2=0.889$), based on tree age, ($3.501^{**}$) ($3.298^{**}$) $F=0.353+2.118\;1/D-1.462\;1/D^2$ ($R^2=0.923$), based on diameter at breast height, ($14.873^{**}$) ($3.545^{**}$) $F=0.403+0.427\;1/H+2.843\;1/H^2$ ($R^2=0.887$), based on tree height. ($3.254^{**}$) ($5.742^{**}$) The above estimated breast-height form factors proved to be overestimated for young trees and small diameter trees, and to be underestimated for old trees and large diameter trees, in comparison to generally accepted figure in Korea, that is, the form factor of 0.45.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.249-267
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• 1995

The purpose of this study is to analyze breast shape by age, to classify breast types and then to suggest brassiere size chart. The subject of anthropometric measurement were 232 women in 20's and 40's. The direct anthropmetric measurement were analyzed by mean, standard deviation, duncan test, T-test, ANOVA, factor & cluster analysis The results are as follows; 1) as a result of analysis for the measurements, according to the increase of age, the items of height were decreased and the items of width, depth, cir- cumference, length were increased, being obesity and breast points were dropped. So the volume and bottom area of 40's women's breast were lager than 20's women's. The width of breast points was bide by increasing of intereior. 2) as a result of factor analyxis, 5 factors were extracted as important factor of breast shapes(obesity of breast and location of breast point, breast height and volume, upper dimensions of breast/lower dimensions of breast, interior dimensions of breast/exterior dimensions of breast, volume of the lower part and drop of breast) 3) as a reslut of cluster analysis, the breast shape were classified into 4 types. namely, typel has the smallest volume, bottom area of breast and the slenderest breast, type2 was the second obesity type. type3 was middle sized type. type4 has much dropped, wide bottom area of breast and the biggest form. 4) To establish brassiere sizing system, the loss funtion was used to decide interval of under bust girth and cup size of size chart. 20 brassiere sizes were established and the size chart covers 92.2% of all subject.

• Journal of radiological science and technology
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• v.23 no.1
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• pp.49-54
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• 2000

It is important to identify modifiable risk factors for breast cancer, because the breast cancer is one of the major causs of mortality among women. Some reported that obesity is a risk factor for breast cancer, but the results are not constant. Many risk factors are related to the duration of estrogenic stimulation of the breast. In general, early menarche and late menopause are positive risk factors. Human breast cancer has different characteristics according to the status of menopause(premenopause and postmenopause). In premenopausal women, about 60% of circulating estrogen is from the ovaries in the form of estradiol, and the remaining 40% is estrogen formed primarily in the adipose(fat) tissue via aromatization of androstenedion from the adrenal glands. After menopause this adipose cell production of estrone is the main source of estrogens and the level of estrone is maintained approximately at premenopausal levels. This study was undertaken to determine the role of body size and body mass index by status of menopause in development of breast cancer using retrospective case/control study. From March 1991 to February 1997 at the Wonkwang University Hospital, the breast cancer cases(n=72) and controls(n=86) were selected. By statistical analysis method, regression analysis, paired T-test and multiple logistic regression were done to estimate the influenced factors same as height, weight, BMI, age at menarche and age at menopause. The following results were obtained : 1. In premenopausal women, age at menarche was showed comparatively high correlation coefficients and BMI was described prominently highly in postmenopause. 2. At the results of multiple regression analysis, age at monarch, BMI and weight were showed as significant variables. In this method, critical factor ($R^2$) was 0.054. 3. Paired samples T-test was undertaken to test mean difference between two groups of cases and controls. The result of test performance showed a significant difference. 4. In comparison with women whose weight less than 50 kg, the ORs for the upper 5th group was 1.82(95% confidence interval). The heaviest women had a higher risk(OR=1.14, 95% confidence interval $1.12{\sim}1.31$, p=0.005). Higher body mass index was significantly associated with increased risk of premenopausal breast cancer (OR=1.01, 95% confidence interval $1.08{\sim}l.18$, p=0.05).

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.2
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• pp.177-196
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• 1993

By cluster sampling measurements, passing months of pregnancy according to changes of pregnant women body forms. On the basis of the above mentioned data, sizes of pregnant women clothes were decided. The results are as follows. 1. By cluster sampling measurements, sixty-nine items of apparel were obtained during the three different periods of pregnancy. They included the mean and standard deviation of body form measurement and the minimum and maximum values (Chart 3-4). The results of these surveys made it possible to notice the changes of pregnant womens' physical characteristics, i. e., the increased physical proportions: frontal waist area, umbilicus width, abdominal girth, crotch length, the length of the nipple, and body weight and the decreased proportions: omphalos height, perineum dimension. There was little change in the rear parts of the body. 2. The analized results of principle factors for body form measurements by cluster measurements produced seven major factors for which the proper values were over 1.0. They were: form factor, pregnancy factor, posture factor, breast formation factor, rear body formation factor, and nipple to nipple breadth. 3. In deciding garment sizes of pregnant women, four different sizes were established; small, medium, large, and extra-large according to the third, fifth, eighth, and tenth month of pregnancy. The measurement value of each item was produced by estimate.

• Archives of design research
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• v.20 no.3 s.71
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• pp.107-118
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• 2007

The aim of this paper is to suggest a design guideline for a teaching assistant robot by finding out images that satisfy the role of the teaching assistant robot, and to search for a body features that show such images. Role images of teaching assistant robots were established from literature review and factor analysis. And eight elements of body features were extracted from human's elements of body feature. Robot external form samples varied according to the body feature was modeled three-dimensionally. Children, who are the main users of teaching assistant robots, valuated the 3D robot samples projected onto wall in real size. The valuation basis was role images of teaching assistant robots, adjectives about age and gender, preference, and appropriateness as teaching assistant robots. The result of valuation was analyzed by analysis of variance, and analysis of correlation. The result revealed the fact that four elements of body feature (the ratio of head length, height, the ratio of breast girth, and waist girth) were related to role images. Among these elements, height and waist girth was more important than the rest, particularly, waist girth had strong relation with all the role images. Also, in order to reveal tender and kind image, the ratio of head length was proved to have to be adjusted according to waist girth. On the basis of these result, a design guideline for a teaching assistant robot was suggested.

• Journal of the Korean Society of Costume
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• v.50 no.5
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• pp.117-130
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• 2000

The purpose of this thesis is to offer basic data for clothing design which is intended to apply appropriate shape and capacity to clothes. The following are the analyzed results of an investigation which was conducted to characterize the upper half of the female body of 193 women whose ages are 18 to 25, taking part in this investigation. According to the results of analyzing young women's bust, I came to find a large individual difference of the wide varying factor numbers at the items of the side feature, the body stance, and the dart quantity. For the analysis of the female's upper body, 11 factors are used. The are as follows: Factor 1. width of the bust Factor 2. height of the bust and length of the arm Factor 3. side thickness of the bust and the upside type Factor 4. length of the bust on the front Factor 5. length of the bust on the back Factor 6. salient ratio of the breast Factor 7. width of the neck. the armhole, and measurement of the droop Factor 8. length of the shoulder Factor 9. flat ratio of the bust Factor 10. inclination of the shoulder factor 11. form of the back The shape of young women's upper bodies can be divided into four groups. The character ization of each group are as follows : Group 1 . 28.5% of the women who take part in this investigation belong to Group 1 These women have the shortest body, with a longer length of the front than the back and more thickness on the front than the back. Group 2. 21.1% of the women who take part in this investigation belong to this group. They show a longer length of the back and more thickness of the back than the front. In addition, this group is bent forward. Group 3. This group is the mast common type, showing the shortest and thickest character. 37.8% of the women who take part in this investigation have this bust character Group 4. 12.4% of the women belong to Group 4. They possess the highest and fattest character, skewing smaller necks, armholes, and waists than the other groups. This group also shows the drooping shoulders.

• Journal of Korean Society of Forest Science
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• v.70 no.1
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• pp.7-16
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• 1985

To grasp canonical correlations, their related backgrounds in various growth factors of stem, the characteristics of stem by synthetical dispersion analysis, principal component analysis and canonical correlation analysis as optimum method were applied to Larix leptolepis. The results are as follows; 1) There were high or low correlation among all factors (height ($x_1$), clear height ($x_2$), form height ($x_3$), breast height diameter (D. B. H.: $x_4$), mid diameter ($x_5$), crown diameter ($x_6$) and stem volume ($x_7$)) except normal form factor ($x_8$). Especially stem volume showed high correlation with the D.B.H., height, mid diameter (cf. table 1). 3) (1) Canonical correlation coefficients and canonical variate between stem volume and composite variate of various height growth factors ($x_1$, $x_2$ and $x_3$) are ${\gamma}_{u1,v1}=0.82980^{**}$, $\{u_1=1.00000x_7\\v_1=1.08323x_1-0.04299x_2-0.07080x_3$. (2) Those of stem volume and composite variate of various diameter growth factors ($x_4$, $x_5$ and $x_6$) are ${\gamma}_{u1,v1}=0.98198^{**}$, $\{{u_1=1.00000x_7\\v_1=0.86433x_4+0.11996x_5+0.02917x_6$. (3) And canonical correlation between stem volume and composite variate of six factors including various heights and diameters are ${\gamma}_{u1,v1}=0.98700^{**}$, $\{^u_1=1.00000x_7\\v1=0.12948x_1+0.00291x_2+0.03076x_3+0.76707x_4+0.09107x_5+0.02576x_6$. All the cases showed the high canonical correlation. Height in the case of (1), D.B.H. in that of (2), and the D.B.H, and height in that of (3) respectively make an absolute contribution to the canonical correlation. Synthetical characteristics of each qualitative growth are largely affected by each factor. Especially in the case of (3) the influence by the D.B.H. is the most significant in the above six factors (cf. table 2). 3) Canonical correlation coefficient and canonical variate between composite variate of various height growth factors and that of the various diameter factors are ${\gamma}_{u1,v1}=0.78556^{**}$, $\{u_1=1.20569x_1-0.04444x_2-0.21696x_3\\v_1=1.09571x_4-0.14076x_5+0.05285x_6$. As shown in the above facts, only height and D.B.H. affected considerably to the canonical correlation. Thus, it was revealed that the synthetical characteristics of height growth was determined by height and those of the growth in thickness by D.B.H., respectively (cf. table 2). 4) Synthetical characteristics (1st-3rd principal component) derived from eight growth factors of stem, on the basis of 85% accumulated proportion aimed, are as follows; Ist principal component ($z_1$): $Z_1=0.40192x_1+0.23693x_2+0.37047x_3+0.41745x_4+0.41629x_5+0.33454x_60.42798x_7+0.04923x_8$, 2nd principal component ($z_2$): $z_2=-0.09306x_1-0.34707x_2+0.08372x_3-0.03239x_4+0.11152x_5+0.00012x_6+0.02407x_7+0.92185x_8$, 3rd principal component ($z_3$): $Z_3=0.19832x_1+0.68210x_2+0.35824x_3-0.22522x_4-0.20876x_5-0.42373x_6-0.15055x_7+0.26562x_8$. The first principal component ($z_1$) as a "size factor" showed the high information absorption power with 63.26% (proportion), and its principal component score is determined by stem volume, D.B.H., mid diameter and height, which have considerably high factor loading. The second principal component ($z_2$) is the "shape factor" which indicates cubic similarity of the stem and its score is formed under the absolute influence of normal form factor. The third principal component ($z_3$) is the "shape factor" which shows the degree of thickness and length of stem. These three principal components have the satisfactory information absorption power with 88.36% of the accumulated percentage. variance (cf. table 3). 5) Thus the principal component and canonical correlation analyses could be applied to the field of forest measurement, judgement of site qualities, management diagnoses for the forest management and the forest products industries, and the other fields which require the assessment of synthetical characteristics.

• Korean Journal of Plant Resources
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• v.33 no.1
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• pp.1-14
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• 2020

This study was conducted to analyze community structure and species composition of Pinus densiflora for. erecta Stand in Mt. Cheonchuk (653 m). Field survey was carried out from June to September in 2013. 74 plots (20×20 m) were set up, 5 herb layer plots (3×3 m) were constructed for each plot, and there, Diameter at Breast Heigh t(DBH), height, environmental factor, annual growth were measured. Vascular plants were surveyed as following; 66 family, 165 genus, 211 species, 2 sub species, 29 variety, 6 form 248 taxa. Results of cluster analysis for P. densiflora for. erecta forest, 3 communities were divided into; Quercus mongolica (P-1), Quercus variabilis (P-2) and Quercus aliena-Stephanandra incisa (P-3). There were significant environmental factors that organic layer, annual growth, CEC, total total nitrogen, organic matter and pH for each community. As a result of DCA, P-1 and P-2 were distributed large range of environmental factors but relatively limited in P-3. Distributions of herb layer were affected by sand, cation exchange capacity, silt and total nitrogen. Results of MRPP test for herb layer communities, it was significantly analyzed (A=0.003, P<0.008). Species diversity index was highly recorded in P-3 and influenced by cation exchange capacity, total nitrogen, annual growth in consequence of NMS analysis.