The purpose of this study was to analyze the differences of breast shapes by age, to classify breast types, and to investigate the characteristics of breast shapes by type and the distributions of types by age group, using comparative analysis for women in 20's and 40's. The subjects of anthropometry were 323 women in 20's and 40's. The anthropometric measurements were analyzed by mean, standard deviation, frequency, T-test, F-test, Duncan test, factor and cluster analysis. The results are as follws : 1) According to the increase of age, the items of height were decreased and the items of width, depth, circumference and length were increased, being obeser and breast points were dropped. So the volume and bottom area of 40's women's breast were larger than 20's women's and the breast point to breast point width of 40's women was being wider by the increase of the intereior of breast. 2) 6 factor were extracted from factor analysis by age group. There was no significant difference in consist of factor between age group. There was no significant difference in consist of facotr between age group, but were differences in the connection of factor extracted items and factor loading. Through factor analysis of all age froup, 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) The breast shapes were classified into 4 types by cluster analysis. The frequency of 20's women's breast types appeared in order of type1(53.0%), type3(32.0%), type2(11.0%), type4(4.0%), but that of breast types of 40's women appeared in order of type2(37.9%), type3(31.1%), type4(26.5%), type1(4.5%). Namely, there was few type4 in 20's women and few type1 in 40's women. 20's women's breast types were characterized as type1·3 and type2·3·4 in 40's women. So 40's women had more various breast types than 20's women's.
Purpose - This study identified internationalization factors forKorean SMEs and explored factor differences between AEO and non-AEO authorized companies. Research design, data, and methodology - The study was designed to assess internationalization factors for AEO authorization in Korea through a questionnaire survey and an empirical analysis. The questionnaires were conducted for AEO and Non-AEO authorized companies that were undergoing AEO authorization. The study was conducted through e-mail and AEO manager education classes. Ninety-five questionnaires were collected. We employed the exploratory factor analysis methodology to derive internationalization factors for KoreanSMEs, and explored the factor differences between AEO and Non-AEO authorized companies. Results - AEO authorized companies outperformed Non-AEO authorized companies in R&D and technology. This indicated that AEO authorized companies were recognized as reliable and safe companies by the Korea Customs Service and other Customs services in trade facilitation and customs clearance processes. Conclusions - This study has some implications for AEO authorization and internationalization processes, and involved the empirical analysis of SMEs and the exploratory factor analysis in the internationalization process.
The factor of safety is the most common measure of the safety margin for slopes. When the traditionally defined factor is used in kinematic approach of limit analysis, calculations can become elaborate, and iterative methods have to be used. To avoid this inconvenience, the safety factor was defined in terms of the work rates that are part of the work balance equation used in limit analysis. It was demonstrated for two simple slopes that the safety factors calculated according to the new definition fall close to those calculated using the traditional definition. Statistical analysis was carried out to find out whether, given normal distribution of the strength parameters, the distribution of the safety factor can be approximated with a well-defined probability density function. Knowing this function would make it convenient to calculate the probability of failure. The results indicated that the normal distribution could be used for low internal friction angle (up to about $16^{\circ}$) and the Johnson distribution could be used for larger angles ${\phi}$. The data limited to two simple slopes, however, does not allow assuming these distributions a priori for other slopes.
The purpose of this study is to investigate how VMD structural elements affect fashion brand attitude and intention of store revisiting. For the research, we surveyed 200 females in their 20's and 30's, who are target consumers of SPA brands from April 10th to 15th in 2009. With SPSS 12.0 program, the data was analysed by frequency analysis, reliability analysis, factor analysis and multiple regression analysis. The results are as follows: First, regarding to the results of factor analysis, VMD structural elements were divided into the space layout and information factor, display and aesthetic factor, and store atmosphere factor. Second, intention of store revisiting was statically affected by fashion brand attitude and VMD structural elements, especially space layout and information factor. Third, we found differences in the path effects of VMD structural elements - brand attitude - store revisiting according to the familiarity of SPA stores. The results revealed that VMD structural elements are important marketing strategic tools affecting consumer's preference and store behavior on fashion brands.
This study investigates the characteristics of metallic and ionic elements concentration, concentration according to transport path, and factor analysis in $PM_{10}$ at Guducsan in Busan in the springtime of 2015. $PM_{10}$ concentration in Guducsan and Gwaebeopdong were $59.5{\pm}9.04{\mu}g/m^3$ and $87.5{\pm}20.2{\mu}g/m^3$, respectively. Contribution rate of water-soluble ions and secondary ion in $PM_{10}$ concentration in Guducsan were 37.0% and 27.8% respectively. [$NO_3{^-}/SO{_4}^{2-}$] ratio and contribution rate of sea salt of $PM_{10}$ in Guducsan and Gwaebeopdong were 0.91 and 1.12, 7.0% and 5.3%, respectively. The results of the backward trajectory analysis indicates that $PM_{10}$ concentration, total inorganic water-soluble ions and total secondary ions were high when the air parcels moved from Sandong region in China than non-Sandong and northen China to Busan area. The results of the factor analysis at Guducsan indicates that factor 1 was anthropogenic source effects such as automobile emissions and industrial combustion processes, factor 2 was marine sources such as sea salts from sea, and factor 3 was soil component sources.
The purpose of this study is to examine the relationships between each type of attitudes toward money and the attributes of choosing family restaurants. A self-administrated questionnaire was completed by 387 students, and data were analysed by frequency, factor, reliability and canonical correlation. Seven factors were obtained from factor analysis of attitudes toward money; Factor 1 "power", Factor 2 "obsession", Factor 3 "retention", Factor 4 "achievement", Factor 5 "anxiety", Factor 6 "distrust", and Factor7 "evaluation". The attributes of family restaurant choice were extracted into six factors: Factor 1 "quality of food", Factor 2 "restaurant event", Factor 3 "interior environment", Factor 4 "value of food", Factor 5 "convenience for approach", and Factor 6 "employees' service". Canonical correlation analysis showed three significant functions. Canonical function 1 showed that the attitudes of considering the power of money, its retention and achievement were indicated to have significantly positive relationships with the quality of food in the attributes of choosing family restaurants. Canonical function 2 showed that significantly negative relationships between distrust and restaurant events and convenience for approach. Canonical function 3 also showed that significantly positive relationships between obsession and anxiety and the interior of restaurants and employees' service, and significantly negative relationships between evaluation and the interior of restaurants and employees' service.
Current seismic design provisions allow structures to deform into inelastic range during design level earthquakes since the chance to meet such event is quite rare. For this purpose, design base shear is defined in current seismic design provisions as the value of elastic seismic shear force divided by strength reduction factor, R (${\geq}1$). Strength reduction factor generally consists of four different factors, which can account for ductility capacity, overstrength, damping, and redundancy inherent in structures respectively. In this study, R factor is assumed to account for only the ductility rather than overstrength, damping, and redundancy. The R factor considering ductility is called "ductility factor" ($R_{\mu}$). This study proposes ductility factor with correction factor, C, which can account for dynamic P-${\Delta}$ effect. Correction factor, C is established as the functional form since it requires computational efforts and time for calculating this factor. From the statistical study using the results of nonlinear dynamic analysis for 40 earthquake ground motions (EQGM) it is shown that the dependence of C factor on structural period is weak, whereas C factor is strongly dependant on the change of ductility ratio and stability coefficient. To propose the functional form of C factor statistical study is carried out using 79,920 nonlinear dynamic analysis results for different combination of parameters and 40 EQGM.
Journal of the Korean Society of Clothing and Textiles
/
v.12
no.3
s.28
/
pp.309-318
/
1988
The purposes of this study were: 1) to develop specific AIO variables(clothing variables) based on clothing behavior studies, 2) to segment apparel market by clothing variables, 3) to discribe the profile of each segment with clothing variables, lifestyle variables and demographic variables, 4) to Suggest effective strategies on apparel market of women's clothing. The Likert Type clothing questionnaires measured 6 aspects of clothing (fashion, conformity-individuality, practicality, aesthetics, modesty and brand consciousness & status symbols) dealing with activities, interests and opinions. In addition, lifestyle variables were measured with general AIO statements. The questionnaires were administered to 563 young women (students, career women and homemakers) living in Seoul. The data were analysed by factor analysis, ctustering analysis, multiple discriminant analysis, one-way ANOVA ana Duncan's multiple range test. The results of the study were as follow: 1) 4 factors emerged from factor analysis of clothing variables. Factor 1: lower interest in modesty and higher interest in aesthics, Factor 2: brand consciousness and status symbols, Factor 3: conformity, Factor4 : fashion. 2) Lifestyle variables clustered into 3 factors. Factor 1: positive social activity, Factor 2: family-oriented type, Factor S: materialism. 3) By cluster analysis of the 4 factors of the clothing variables, the apparel market of women's clothing was categorised into 3 segments (innovative aesthetics seeker group, brand and status symbols conscious group, clothing unconscious group). 4) The above three segmented groups were also significantly discriminated by lifestyle and demosraphic variables. 5) On the basis of the findings, effective marketing strategies of women's clothing were suggested.
Postpartum depression is one of the most serious problems in maternal health because it affects not only the mother but also her family. Postpartum depression disturbs the maternal-infant interaction and attachment. However, most postpartum depression patients ignore this problem and do not seek treatment. Many clinicians and researchers realiza there is a need to develop a postpartum depression scale. Thus, this study has been designed to development of a postpartum depression scale. Data were collected through a survey over a period of three months. Subjects who participated in the study were 167 Korean mothers in their postpartum period. The author used a convenience sampling method. The analysis of the data was done with SPSS PC/sup +/ for descriptive statistics, item analysis and factor analysis. Initially 62 items were generated from the interview data of eight postpartum depression patients and from a literature review. This preliminary scale was analyzed for reliability and validity. The results of this analysis are as follows. 1. Initially 62 items were analyzed through the Index of Content Validity(CVI) and 48 items were selected. 2. Seven factors were extracted through the principal component analysis, and these contributed 61% of the variance in the total score. Finally 46 items in the scale loaded .41∼ .84 on one of seven factors. 3. Each factor was labeled. Factor 1 was labeled 'emotional phenomena-emotional upset' and included 13 items, factor 2 was labeled' cognitive phenomena-self concept disturbance' and included seven items, factor 3 was labeled 'relationship to baby-negative feeling' and included six items, factor 4 was labeled 'relationship to baby- overload' and included eight items, factor 5 was labeled 'negative maternal identity' and included five items, factor 6 was labeled 'biophysiological phenomena-disturbance of physical functioning' and included four items, and factor 7 was labeled' interpersonal relationship phenomena-blamed others' and included three items. 4. Cronbach Coefficient Alpha for internal consistency was .95 for the total 46 items. Finally, the author suggests that this scale could be adequately applied in assessing the postpartum depression of mothers during the postpartum period. The results of this study can contribute to designing an appropriate postpartum depression prevention strategy.
Journal of Korean Society for Geospatial Information Science
/
v.19
no.4
/
pp.139-144
/
2011
This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.
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