The purpose of this study was to develop and validate Korean version of Deaf Acculturation Scales(DAS). Pilot items were made a faithful translation of the Acculturation Scales of Maxwell-McCaw and Zea (2011) and were modified for Korean Deaf people. The Scale involves two dimensions, in order to measure the acculturation of Deaf people; Deaf acculturation and hearing acculturation. Using factor analysis, we developed a Korean version of DAS consisted of twenty-five items for Deaf acculturation dimension and twenty-five items for hearing acculturation dimension. These analysis supported the four factors of Deaf acculturation dimension and the five factors of hearing acculturation dimension. Reliability, assessed by Cronbach's ${\alpha}$, was .93 for Deaf acculturation and .93 for hearing acculturation, respectively, which confirm the Koran version of DAS. Construct validity was demonstrated through correlation with Deaf acculturation-related variables: age, age of Deafness, Degree of hearing loss, American Sign Language ability, and lip-reading ability. Criterion validity was supported by correlation with Collective Self-Esteem Scale. Limitation and implication of this study and direction for future research were discussed.
Journal of Korean Society for Atmospheric Environment
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v.13
no.1
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pp.51-63
/
1997
Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.
Journal of Fisheries and Marine Sciences Education
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v.19
no.2
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pp.278-287
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2007
Since traffic congestion ratio at any given port fluctuates on the number of arriving and departing vessels, the total tonnage of freight volume being handled, and the number of berth in operation and other factors, there exists a need to numerically analyze the waterway traffic volume. However, there are no effective regulations in regards to the waterway traffic analysis prior to expansion of a port facility. The current analysis requires the traffic analysis in relation only to the width of the waterway, which clearly falls short of achieving a comprehensive evaluation study that could be used in consideration of port expansion.This study provides five scenarios to execute a comprehensive evaluation study and base for the sensitivity study by analyzing the scenarios. As a result of the sensitivity analysis, the A, B, and C scenarios varies the average arrival ratio of the berth shows 1.1, 1.19, and 1.28 times of delays respectively. Also, The D and E scenarios take place malfunctions of pier shows 1.21 and 1.53 times of delays respectively. Therefore, various strategies of harbor development and method of harbor management are needed for the flexible correspondence to the environmental changes such as the excessive increasing of the freight volume and often taking place of malfunctioning.
The Journal of Korean Academic Society of Nursing Education
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v.26
no.3
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pp.322-331
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2020
Purpose: The purpose of this study was to investigate the validity and reliability of the Korean Version of the Grit (Grit-K) scale for nursing students in Korea. Methods: The participants in the study were 277 nursing students. Their grit was verified by using self-reports and the results of a questionnaire. Grit was translated into Korean and its content validity was verified by five experts. The validity of the instrument was verified through item analysis, exploratory factor analysis, and confirmatory factor analysis. Reliability verification was analyzed by using internal consistency reliability. Results: Two factors were identified through exploratory factor analysis and six items of the original instrument were found to be valid. In the confirmatory factor analysis, the validity of the instrument was verified as the model. The internal consistency reliability was also acceptable and Grit was found to be an applicable instrument. Conclusion: This study shows that the Korean Version of the Grit Questionnaire is a valid and reliable instrument to assess nursing students in Korea.
Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.
The Journal of Economics, Marketing and Management
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v.11
no.5
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pp.45-55
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2023
Purpose: As one of the continuous studies on the offline distribution industry, the purpose of this study is to find ways for offline stores to respond to the growth of online shopping by identifying research trends on department stores. Research design, data and methodology: To this end, this study conducted word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and dynamic topic modeling using Python 3.7 on a total of 551 English abstracts searched with the keyword 'department store' in scienceON as of October 10, 2022. Results: The results of word frequency analysis and co-occurrence frequency analysis revealed that research related to department stores frequently focuses on factors such as customers, consumers, products, satisfaction, services, and quality. BERTopic and LDA analyses identified five topics, including 'store image,' with 'shopping information' showing relatively high interest, while 'sales systems' were observed to have relatively lower interest. Conclusions: Based on the results of this study, it was concluded that research related to department stores has so far been conducted in a limited scope, and it is insufficient to provide clues for department stores to secure competitiveness against online platforms. Therefore, it is suggested that additional research be conducted on topics such as the true role of department stores in the retail industry, consumer reinterpretation, customer value and lifetime value, department stores as future retail spaces, ethical management, and transparent ESG management.
International Journal of Advanced Culture Technology
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v.12
no.3
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pp.434-440
/
2024
SIZE KOREA updates body measurement data every five years, providing essential information for the fashion industry. This anthropometric data is widely used to diagnose consumer body shapes and develop optimal clothing sizes. Artificial intelligence, particularly machine learning, excels in predicting such body shape classifications. This study seeks to enhance the suitability of clothing design by applying the new analytical methodology of machine learning techniques to better capture and classify the unique body shapes of Korean women. In this study, machine learning techniques such as K-means clustering, Silhouette analysis, and Decision Tree analysis were used to classify the lower body shapes of Korean women in their twenties and identify standard body shapes useful for slacks design. The results showed that the lower body of the age group could be classified into three categories: 'small stature' (the majority), 'tall with an average lower body volume,' and 'medium height with a fuller lower body' (the smallest share). The three-cluster approach is validated through Silhouette analysis, which minimizes misclassification. Decision Tree analysis then further defines the criteria for these clusters, highlighting waist height and hip depth as the most significant factors, achieving a classification accuracy of 90.6%. While this study is not directly related to Robotic Process Automation, its detailed analysis of body shapes for slacks patterns can aid RPA in clothing production. Future research should continue integrating machine learning in human body and fashion design studies.
Kim, Jin A;Yang, Tae-Jin;Kim, Jung Sun;Park, Jee Young;Kwon, Soo-Jin;Lim, Myung-Ho;Jin, Mina;Lee, Sang Choon;Lee, Soo In;Choi, Beom-Soon;Um, Sang-Hee;Kim, Ho-Il;Chun, Changhoo;Park, Beom-Seok
Molecules and Cells
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v.23
no.2
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pp.145-153
/
2007
Elucidation of the roles of circadian associated factors requires a better understanding of the molecular mechanisms of circadian rhythms, control of flowering time through photoperiodic pathways, and photosensory signal transduction. In Arabidopsis, the APRR1 quintet, APRRs 1, 3, 5, 7, and 9, are known as central oscillator genes. Other plants may share the molecular mechanism underlying the circadian rhythm. To identify and characterize these circadian response genes in Brassica crops whose genome was triplicated after divergence from Arabidopsis, we identified B. rapa BAC clones containing these genes by BLAST analysis of B. rapa BAC end sequences against the five corresponding Arabidopsis regions. Subsequent fingerprinting, Southern hybridization, and PCR allowed identification of five BAC clones, one for each of the five circadian-related genes. By draft shotgun sequencing of the BAC clones, we identified the complete gene sequences and cloned the five expressed B. rapa circadian-associated gene members, BrPRRs 1, 3, 5, 7, and 9. Phylogenetic analysis revealed that each BrPRR was orthologous to the corresponding APRR at the sequence level. Northern hybridization revealed that the five genes were transcribed at distinct points in the 24 hour period, and Southern hybridization revealed that they are present in 2, 1, 2, 2, and 1 copies, respectively in the B. rapa genome, which was triplicated and then diploidized during the last 15 million years.
Purpose - This paper aims to provide a step-by-step approach to factor analytic procedures, such as principal component analysis (PCA) and exploratory factor analysis (EFA), and to offer a guideline for factor analysis. Authors have argued that the results of PCA and EFA are substantially similar. Additionally, they assert that PCA is a more appropriate technique for factor analysis because PCA produces easily interpreted results that are likely to be the basis of better decisions. For these reasons, many researchers have used PCA as a technique instead of EFA. However, these techniques are clearly different. PCA should be used for data reduction. On the other hand, EFA has been tailored to identify any underlying factor structure, a set of measured variables that cause the manifest variables to covary. Thus, it is needed for a guideline and for procedures to use in factor analysis. To date, however, these two techniques have been indiscriminately misused. Research design, data, and methodology - This research conducted a literature review. For this, we summarized the meaningful and consistent arguments and drew up guidelines and suggested procedures for rigorous EFA. Results - PCA can be used instead of common factor analysis when all measured variables have high communality. However, common factor analysis is recommended for EFA. First, researchers should evaluate the sample size and check for sampling adequacy before conducting factor analysis. If these conditions are not satisfied, then the next steps cannot be followed. Sample size must be at least 100 with communality above 0.5 and a minimum subject to item ratio of at least 5:1, with a minimum of five items in EFA. Next, Bartlett's sphericity test and the Kaiser-Mayer-Olkin (KMO) measure should be assessed for sampling adequacy. The chi-square value for Bartlett's test should be significant. In addition, a KMO of more than 0.8 is recommended. The next step is to conduct a factor analysis. The analysis is composed of three stages. The first stage determines a rotation technique. Generally, ML or PAF will suggest to researchers the best results. Selection of one of the two techniques heavily hinges on data normality. ML requires normally distributed data; on the other hand, PAF does not. The second step is associated with determining the number of factors to retain in the EFA. The best way to determine the number of factors to retain is to apply three methods including eigenvalues greater than 1.0, the scree plot test, and the variance extracted. The last step is to select one of two rotation methods: orthogonal or oblique. If the research suggests some variables that are correlated to each other, then the oblique method should be selected for factor rotation because the method assumes all factors are correlated in the research. If not, the orthogonal method is possible for factor rotation. Conclusions - Recommendations are offered for the best factor analytic practice for empirical research.
This study analyzed the dietary lifestyle among housewives and found out the effect of dietary lifestyle on consumption pattern of soybean paste. Data were collected from 312 housewives living in Gyeongnam region through a self-administered questionnaire. According to the result of the factor analysis, dietary lifestyle were categorized into five factors: health-seeking type, convenience-seeking type, safety-seeking type, popularity-seeking type, and taste-seeking type. About thirty-five percent of the respondents knew the way how to prepare soybean paste while nineteen percent did not. There were significant differences in awareness regarding how to prepare soybean paste according to healthy-seeking lifestyle, convenience-seeking lifestyle, safety-seeking lifestyle, and popularity-seeking lifestyle. Thirty-seven percent of the respondents obtained soybean paste from family or relatives, whereas twenty-six percent made it at home. The result of the multinomial logistic regression analysis showed that the factors affecting the ways of obtaining soybean paste were age, monthly household income, employment status, coresidence with parent(s), husband's parent(s), or older relative(s), dwelling types, healthy-seeking lifestyle, convenience-seeking lifestyle and safety-seeking lifestyle.
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