• 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 of Clothing and Textiles
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• v.26 no.8
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• pp.1165-1176
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• 2002

This study intended to provide more refined information on color preferences by systematizing the concept of the color preference(general color preference, apparel color preference) and revealing different trends in the color preference and the actual possession of apparels. We collected data from 303 females in the ages between 20 and 40 in Seoul and analyzed by paired t-test. The results were as follows: 1. The analysis on general color preference, apparel color preference, and apparel possession color revealed that the cold colors such as blue and violet marked higher, and the warm colors such as yellow and orange marked lower in general color preference. For apparel color preference, neutral and brown were among the highest and the rest of the colors were in the same trend as general color preference. Apparel possession color showed defined accordance with apparel color preference. In terms of tones, pale tone marked the highest in general color preference and was followed by vivid, dull, and dark tones in decreasing order. For apparel color preference, pastel, dul1, and dark tones were among the highest. 2. Comparison between general color preference and apparel color preference in terms of hue showed that, except for orange, every hue showed disagreement in general color preference and apparel color preference. Neutral and brown hues marked higher in apparel color preference than in general color preference where as a]1 the other hues marked higher in general color preference. Comparison between apparel color preference and apparel possession color in terms of hue revealed that in most hues, apparel possession color was lower than apparel color preference. In terms of tones, vivid and pale tones marked higher in general color preference than in apparel color preference while dull and dark tones marked higher in apparel color preference than in general color preference.

• Computers and Concrete
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• v.32 no.1
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• pp.99-117
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• 2023

The crack under the influence of the higher intensities of the stresses grows and the structure gets collapsed with the time when the crack length reaches to critical value. Therefore, the fracture behavior of a structure in terms of stress intensity factors (SIF) becomes important to determine the remaining fracture strength and capacity of material and structure for avoiding catastrophic failure, increasing safety and further improvement in the design. The robustness of the method has been demonstrated by comparing the numerical results with analytical and experimental results of some problems. XFEM is used to model cracks and holes in structures and predict their strength and reliability under service conditions. Further, XFEM is extended with a stochastic method for predicting the sensitivity in terms of output COVs and fracture strength in terms of mean values of stress intensity factors (SIFs) of a structure with discontinuities (cracks and holes) under tensile loading condition with input individual and combined randomness in different system parameters. In stochastic technique, the second order perturbation technique (SOPT) has been used for the predicting the fracture behavior of the structures. The stochastic/perturbation technique is also known as Taylor series expansion method and it provides the reliable results if the input randomness is less than twenty percentage. From the present numerical analysis it is observed that, the crack tip near to the hole is under the influence of the stress concentration and the variational effect of the input random parameters on the crack tip in terms of the SIFs are lesser so the COVs are the less sensitive. The COVs of mixed mode SIFs are the most sensitive for the crack angles (α=45° to 90°) for all the values of c₁ and d₁. The plate with the shorter distance between hole and crack is the most sensitive with all the crack angles but the crack tip which is much nearer to the hole has the highest sensitivity.

• The Journal of Korean Society for School & Community Health Education
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• v.24 no.4
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• pp.51-60
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• 2023

Objectives: This study attempted to examine the factors that affect the national health checkup rate of the elderly, analyze the impact of these factors, and discuss countermeasures to problems that may arise based on this. Methods: This study used the '8th National Health and Nutrition Examination Survey (2019-2021)', a nationwide survey, as the main data. The subjects of the study are seniors aged 65 years or older, the dependent variable is whether or not they underwent a national health checkup, and the independent variables are gender, marital status, residence, education level, income level, economic activity, type of medical coverage, private insurance subscription, subjective health, High blood pressure, diabetes, depression, stress, and weight change were selected. The statistical analysis package for data analysis is SPSS ver. 27.0 was used, and a p value of less than 0.05 was considered significant. Results: Of the 2,806 seniors aged 65 years or older, 2,074 (73.9%) took the national health screening over the past two years. In terms of marital status, married was 1.451 times higher than single (p<0.001), and in terms of residence, myeon was 1.240 times higher than dong (p<0.01). In terms of education level, college graduates were 2.053 times higher than elementary school graduates (p<0.001), and in terms of economic activity, the employed were 1.325 times higher than the unemployed (p<0.01). Private insurance was 1.883 times higher than non-subscription (p<0.001), weight change was 1.234 times higher for change than no change (p<0.05), and current smoking rate was 2.003 times higher for non-smokers than for former smokers. It was high (p<0.001). Conclusion: In conclusion, if differentiated promotion and health education are strengthened for the elderly who cannot participate in the national health screening, the participation rate of the elderly in the national health screening is expected to increase.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.38-42
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• 2007

Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of functional information from a large corpus of gene expression data is still a time-consuming task. In this paper, we propose an efficient method for identifying functional categories of differentially expressed genes from a micro-array experiment by using Gene Ontology (GO). Our method is as follows: (1) The expression data set is first filtered to include only genes with mean expression values that differ by at least 3-fold between the two groups. (2) The genes are then ranked based on the t-statistics. The 100 most highly ranked genes are selected as informative genes. (3) The t-value of each informative gene is imposed as a score on the associated GO terms. High-scoring GO terms are then listed with their associated genes and represent the functional category information of the micro-array experiment. A system called HMDA (Hallym Micro-array Data analysis) is implemented on publicly available micro-array data sets and validated. Our results were also compared with the original analysis.

• Korean Journal of Human Ecology
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• v.21 no.2
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• pp.389-405
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• 2012

The purposes of this study were to investigate students' perception on importance and performance of service quality of university foodservice, and to examine Importance-Performance Analysis(IPA) of foodservice quality for male and female students. A total of 500 university students in Daejeon were surveyed and 432 responses were returned. Excluding responses with significant missing data, 412 responses were used for data analysis. In terms of importance of service quality attributes, 'sanitation(4.74)' category received the highest score, followed by 'food(4.36)', 'service(4.22)', 'convenience(4.01)', 'menu(3.90)' and 'atmosphere(3.73)'. In terms of performance, the highest service quality attribute was associated with 'convenience(3.30)', followed by 'service(3.06)', 'sanitation(2.95)', 'food(2.88)', 'atmosphere(2.79)' and 'menu(2.68)'. As the results of IPA, 'staff's kindness', 'overall quality of service', 'taste of the food', 'freshness of the food', 'overall quality of the food', and 'cleanliness of the facility' fell into the Quadrant IV(Focus here) for female students. On the other hand, male students' IPA grid illustrated that 'taste of the food', 'freshness of the food', 'nutrition of the food', 'sanitation of the food', and 'sanitation of the utensils' fell into Quadrant IV(Focus here).

• Spatial Information Research
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• v.11 no.3
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• pp.301-325
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• 2003

Urban residential area, one of the main subjects of urban and architectural studies, can be analyzed accurately and rapidly with CIS. (Geographic Information System) And the applications of GIS in urban studies are too macro to be explained in architectural terms and the ones in architectural studies are not so much active rather be used as a secondary means. So the studies in urban-architectural scale are very useful in many ways. This study explores urban-architectural possibilities of analytic capabilities of GIS through the analysis of spatial characteristics of residential area in terms of land price according to parcel attributes. It is found, firstly, that the parcel attributes have relations with land price and its distribution patterns. Secondly, it is verified that the visualization capability of GIS can be a very useful method of analysis through user-interface effects in urban-architectural scaled analysis.

• The Journal of Information Systems
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• v.21 no.3
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• pp.137-161
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• 2012

The increasing interest in big data analysis using various data mining techniques indicates that many commercial data mining tools now need to be equipped with fundamental text analysis modules. The most essential prerequisite for accurate analysis of text documents is an understanding of the exact semantics of each term in a document. The main difficulties in understanding the exact semantics of terms are mainly attributable to homonym and synonym problems, which is a traditional problem in the natural language processing field. Some major text mining tools provide a thesaurus to solve these problems, but a thesaurus cannot be used to resolve complex synonym problems. Furthermore, the use of a thesaurus is irrelevant to the issue of homonym problems and hence cannot solve them. In this paper, we propose a semantic text mining methodology that uses ontologies to improve the quality of text mining results by resolving the semantic ambiguity caused by homonym and synonym problems. We evaluate the practical applicability of the proposed methodology by performing a classification analysis to predict customer churn using real transactional data and Q&A articles from the "S" online shopping mall in Korea. The experiments revealed that the prediction model produced by our proposed semantic text mining method outperformed the model produced by traditional text mining in terms of prediction accuracy such as the response, captured response, and lift.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.77-81
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• 2009

The radar cross section (RCS) of a warship is one of the most important design features in terms of her survivability in hostile environments. Ocean waves continuously changes the attitude of an objective warship to hostile radar and distorts the RCS as a result. This paper presents a dynamic RCS analysis technique and procedure that considers temporal ship motion. First, data sets are prepared for ship motions in 6 degrees of freedom, which are numerically simulated for an objective warship via frequency to time domain conversion with response amplitude operators and specified ocean wave spectra. Second, a series of RCS analysis models are transformed geometrically by referring to ship motion data sets. Finally, temporal RCS analyses are carried out with the RCS simulation code, SYSCOS. As an example, RCS analysis results are given for a virtual warship, which show that ship motions temporally change RCS values and cause RCS reduction compared with static value in terms of mean values.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.