• Journal of the Korean Institute of Navigation
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• v.10 no.2
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• pp.83-96
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• 1986

In the restricted sea way such as fair way in harbor, narrow channel etc, the safe ship-handling is a very important problem, which is greatly related with turning ability of ships. It is of great importance that ship-handlers can grasp the position of pivoting point varying with time increase at any moment for relevant steering activities. Mean while, in advanced ship-building countries they study and investigated pivoting point related with turning characteristics, hut their main interest lies in ship design, not in safe ship controlling and maneuvering. In this regards it is the purpose of this paper to provide ship-handlers better under standing of pivoting point location together with turning characteristics and then to help them in safe ship-handling by presenting fact that pivoting points vary according to configuration of ships. The author calculated the variation of pivoting point as per time increase for various type of vessels, based on the hydrodynamic derivatives obtained at test of Davidson Laboratory of Stevens Institutes of Technology , New Jersey, U.S.A. The results were classified and investigated according to the magnitude of block coefficient , length-beam ratio, length-draft ratio, rudder area ratio ete, and undermentioned results were obtained. (1) The trajectory of pivoting point due to variation of rudder angle are all the same at any time, though the magenitude of turning circle are changed variously. (2) The moving of pivoting point is affected by the magnitude of block coefficient, length-beam ratio, length-draft ratio, however the effect by rudder area ratio might be disregarded. (3) In controlling and maneuvering of vessels in harbor, ship-handlers might regard that the pivoting point would be placed on 0.2~0.3L forward from center of gravity at initial stage. (4) The pivoting point of VLCC or container feeder vessels which have block coefficient more than 0.8 and length-beam ratio less than 6.5 are located on or over bow in the steady turning. (5) When a vessel intends to avoid some floating obstruction such as buoy forward around her eourse, the ship-handler might consider that the pivoting point would be close by bow in ballast condition and cloase by center of gravity in full-loaded condition.

• Investigative Magnetic Resonance Imaging
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• v.22 no.2
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• pp.79-85
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• 2018

Purpose: To determine the impact of pseudoglandular formation on apparent diffusion coefficient (ADC) values of hepatocellular carcinoma (HCC) in diffusion-weighted imaging (DWI), and to validate the results using histopathological grades. Materials and Methods: We assessed 182 HCCs surgically resected from 169 consecutive patients. Each type of tumor pseudoglandular formation was categorized into "non-," "mixed-," or "pure-," based on official histopathology reports. The ADC for each tumor was independently measured, using the largest region of interest on the ADC map. Data were assessed using the analysis of variance test, with Bonferroni correction for post hoc analysis to stratify the relationship of ADCs with pseudoglandular formation, followed by subgroup analysis according to the histopathological tumor grades. Results: The mean ADC was significantly higher in pure pseudoglandular lesions (n = 5, $1.29{\pm}0.08{\times}10^{-3}mm^2/s$) than in non-pseudoglandular lesions (n = 132, $1.08{\pm}0.17{\times}10^{-3}mm^2/s$; P = 0.003) or mixed-pseudoglandular lesions (n = 45, $1.16{\pm}0.24{\times}10^{-3}mm^2/s$; P = 0.034). The ADC values and pseudoglandular formation were significantly correlated in moderately differentiated HCCs (n = 103; r = 0.307, P = 0.007), while well- (n = 19) and poorly-differentiated HCCs (n = 60) did not show significant correlation (r = 0.105 and 0.068, respectively; P = 0.600 and 0.685, respectively). Conclusion: The degree of pseudoglandular formation could be one of the determinants of ADC in DWI of HCCs-especially moderately differentiated HCCs-while its influence does not appear to be significant in well- or poorly differentiated HCCs.

• The Research Journal of the Costume Culture
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• v.4 no.2
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• pp.277-302
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• 1996

The purpose of this study is to suggest fundamental information about wearing method and production of brassiere, which is suitable for physiological hygiene and efficient action for elderly women. The subject is 418 elderly women aged 50∼69 years old. Data is processed by a computer(SAS) and is analyzed by using frequency, percentage, x²-test. The main results of this study are as follows. 1. Elderly women'weight and breast size are higher thant their younger counterparts'in their 20's, but the older and poorer women with more children have smaller weight and breast. Most of the elderly women feel that their breasts are drooped or falling apart. I fact, those elderly women who gave birth to more children have more drooped and wider breasts. The major type of elderly women'breast is the 'drooped breast' featured more by those elderly women who have more children. 2. Most of the elderly women began to wear the brassiere for the first time in their 20's the older women with more children began to wear the brassiere earlier, while those less educated and poorer began to protect their breasts with brassiere later. Many elderly women wear the brassiere to be protected from dirt, noise or look more neat, but day tend to wear the brassiere not all day around but at certain times, older, less educated and proper women with more children tend to use the brassiere for etiquette and less often. This group of elderly women feel tedious, stage or uncomfortable for the brassiere. 3. Most of the elderly women know about their brassiere size. Such variables as age, education and income are correlated positively with the interest in and consciousness of the brassiere size. All in all, the statistical distribution of elderly women's brassiere size is very wide, while most of them use 90A, 85A and 95A sizes. On the other hand, the most popular size of the under bust circumference is 85∼90cm, while their primary cup size is A.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of Korean Home Economics Education Association
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• v.16 no.3
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• pp.43-61
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• 2004

This study is purposed to examine the interests of students and usefulness of TechnologyㆍHome Economics, which is a requirement for both male and female high school students. The targeted subject of this study were 533 high school sophomores and seniors in Kyungsangnamdo region and in consideration of regional differences, three high schools were selected in urban Jinju and three other schools were selected in countryside of Hapchun. The collected data was processed by SAS program, a social, scientific and statistical processing program. and analyzed the date using the statistical methods of frequency, percentage and average along with t-test and one-way ANOVA. The results and conclusions of this study are summarized as follow: 1. The interests of students' Technology. Home Economics. the respondents gave 3.10 points of the perfect 5.0. The influential variables to the interests of high school students to TechnologyㆍHome Economics were sex, type of school, location of inhabitation. grades, favor to textbook, and self-esteem. 2. The practical usefulness of students' TechnologyㆍHome Economics, the respondents gave 3.17 points of the perfect 5.0. The influential variables to the usefulness of TechnologyㆍHome Economics were sex, type of school, location of inhabitation, age of father, occupation of mother, domestic financial status, grades, favor to textbook and self-esteem.

• Korean Journal of Biological Psychiatry
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• v.22 no.4
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• pp.223-232
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• 2015

Objectives In this study, the authors evaluated the correlation between levels of serum lipid, homocysteine, and folate with volumes of hippocampus, amygdala, corpus callosum, and in patients with amnestic mild cognitive impairment (aMCI) or Alzheimer's disease (AD) type. Methods The study recruited patients who visited the dementia clinic of Haeundae Paik Hospital in Korea between March 2010 and June 2014. Among those, patients who had taken the neurocognitive test, brain magnetic resonance imaing, tests for serum lipid, homocysteine, folate, and apolipoprotein E (APOE) genotyping and diagnosed with aMCI or AD were included for analysis. Bilateral hippocampus, entorhinal cortex, amygdala and corpus callosum were selected for region of interest (ROI). The cross-sectional relationships between serum lipid, homocysteine, folate and ROI were assessed by partial correlation analysis and multiple linear regression analysis. Results In patients with aMCI, old age (> 80) and APOE ${\varepsilon}4$ carrier were associated with AD [odds ration (OR) : 12.80 ; 95% confidence interval (CI) : 2.25-72.98 and OR : 4.48 ; 95% CI : 1.58-12.67, respectively]. In patients with aMCI or AD, volumes and thickness of ROI were inversely correlated with levels of serum lipid and homocysteine. In multiple linear regression analyses, higher total cholesterol level was related to lower left, right hippocampus volume and left amygdala volume ; higher low-density lipoprotein cholesterol was related to lower right entorhinal cortex thickness ; higher homocysteine level was related to lower corpus callosum volume. Conclusions Higher serum lipid and homocysteine levels are associated with decreased volume of hippocampus, amygdala, corpus callosum and entorhinal cortex thickness in patients with aMCI or AD. These findings suggest that serum lipid and homocysteine levels are associated with AD as a modifiable risk factor.

• Journal of The Korean Association For Science Education
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• v.36 no.3
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• pp.499-507
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• 2016

A flipped learning class was held in an attempt to overcome the limits of lecture-type classes in pre-service science teacher training and to provide a student-oriented education suitable for digital native generation. The principles of teaching-learning in flipped learning were applied to the general ADDIE model to design the class; learning materials were developed accordingly. The developed flipped learning materials and class design were verified for their validity using an expert panel's Delphi method and validity test, in which the validity was verified with 0.75 CVR. The developed flipped learning materials were applied to the theory of science education and the instructional effectiveness was analyzed. The results suggest that the students' motivation to study, interest, and confidence in learning increased; however, their satisfaction in class decreased by 30% as compared to the lecture-type class and their self-confidence in the improvement of their academic achievement was not sufficient. In order for a flipped learning class to be successful, the class should be small in size, which would ensure appropriate teacher-student communication and individualized learning; also, the students' burden of learning should be reduced and accessibility to video materials for pre-class learning should be reinforced.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.867-874
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• 2021

The IoT (Internet of Things) technology is rapidly becoming an important consideration in many engineering fields in the current 4th industrial era. In recent years, the concepts of digital shipbuilding and smart factories have been adopted as trends in shipyards. However, there is active interest in research on implementing autonomous driving in autonomous vehicles and airplanes, which is currently available in commercial form in a limited capacity. The present study is regarding the path-tracking performance of a boat to accomplish an autonomous driving mission using a flight controller (FC) and real-time kinematic (RTK) global positioning system (GPS) based on an open-source Ardupilot; an actual sea test is also performed using this system on a calm lake. The boat's mission is to evaluate the maneuverability of the self-driving process to a specific point and returning to the home position. For a given speed, the difference between the preset mission trajectory and actual operational trajectory was analyzed, and a series of studies were conducted on the applicability of the system to ships. In addition, the movements and maneuverability of the OmniX-type hull with four propellers were investigated, and the driving path-tracking performance was observed to increase by a maximum of 48%.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.51-89
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• 2007

INTRODUCTION Due to the high broadband internet penetration rate and its group-oriented culture, various types of online communities operate in Korea. This study use 'Uses and Gratification Approach, and argue that members' usage-needs satisfaction with brand community is an important factor for promoting community commitment. Based on previous studies identifying the effect of brand image on consumers' responses to various marketing stimuli, this study hypothesizes that brand image can be a moderate variable affecting the relationship between usage-needs satisfaction with brand community and members' commitment to brand community. This study analyzes the influence of usage-needs satisfaction on brand community commitment and how apparel brand image affects the relationships between usage-needs satisfactions and community commitments. The hypotheses of this study are proposed as follows. H1-3: The usage-needs satisfaction of apparel brand community (interest, transaction, relationship needs) influences emotional (H1), continuous (H2), and normative (H3) commitments to apparel brand communities. H4-6: Apparel brand image has a moderating effect on the relationship between usage-needs satisfaction and emotional (H4), continuous (H5), and normative (H6) commitments to apparel brand communities. METHODS Brand communities founded by non-company affiliates were excluded and emphasis was placed instead on communities created by apparel brand companies. Among casual apparel brands registered in 6 Korean portal sites in August 2003, a total of 9 casual apparel brand online communities were chosen, depending on the level of community activity and apparel brand image. Data from 317 community members were analyzed by exploratory factor analysis, moderated regression analysis, ANOVA, and scheffe test. Among 317 respondents answered an online html-type questionnaire, 80.5% were between 16 to 25 years old. There were a total of 150 respondents from apparel brand communities(n=3) recording higher-than-average brand image scores (Mean > 3.75) and a total of 162 respondents from apparel brand communities(n=6) recording lower-than-average brand image scores(Mean < 3.75). In this study, brand community commitment was measured by a 5-point Likert scale: emotional, continuous and normative commitment. The degree of usage-needs satisfaction (interest, transaction, relationship needs) was measured on a 5-point Likert scale. The level of brand image was measured by a 5-point Likert scale: strength, favorability, and uniqueness of brand associations. RESULTS In the results of exploratory factor analysis, the three usage-needs satisfactions with brand community were classified as interest, transaction, and relationship needs. Brand community commitment was also divided into the multi-dimensional factors: emotional, continuous, and normative commitments. The regression analysis (using a stepwise method) was used to test the influence of 3 independent variables (interest-needs satisfaction, transaction-needs, and relationship-needs satisfactions) on the 3 dependent variables (emotional, continuous and normative commitments). The three types of usage-needs satisfactions are positively associated with the three types of commitments to apparel brand communities. Therefore, hypothesis 1, 2, and 3 were significantly supported. Moderating effects of apparel brand image on the relationship between usage-needs satisfaction and brand community commitments were tested by moderated regression analysis. The statistics result showed that the influence of transaction-needs on emotional commitment was significantly moderated by apparel brand image. In addition, apparel brand image had moderating effects on the relationship between relationship-needs satisfaction and emotional, continuous and normative commitments to apparel brand communities. However, there were not significant moderate effects of apparel brand image on the relationships between interest-needs satisfaction and 3 types of commitments (emotional, continuous and normative commitments) to apparel brand communities. In addition, the influences of transaction-needs satisfaction on 2 types of commitments (continuous and normative commitments) were not significantly moderated by apparel brand image. Therefore, hypothesis 4, 5 and 6 were partially supported. To explain the moderating effects of apparel brand image, four cross-tabulated groups were made by averages of usage-needs satisfaction (interest-needs satisfaction avg. M=3.09, transaction-needs satisfaction avg. M=3.46, relationship-needs satisfaction M=1.62) and the average apparel brand image (M=3.75). The average scores of commitments in each classified group are presented in Tables and Figures. There were significant differences among four groups. As can be seen from the results of scheffe test on the tables, emotional commitment in community group with high brand image was higher than one in community group with low brand image when transaction-needs satisfaction was high. However, when transaction-needs satisfaction was low, there was not any difference between the community group with high brand image and community group with low brand image regarding emotional commitment to apparel brand communities. It means that emotional commitment didn't increase significantly without high satisfaction of transaction-needs, despite the high apparel brand image. In addition, when apparel brand image was low, increase in transaction-needs did not lead to the increase in emotional commitment. Therefore, the significant relationship between transaction-needs satisfaction and emotional commitment was found in only brand communities with high apparel brand image, and the moderating effect of apparel brand image on this relationship between two variables was found in the communities with high satisfaction of transaction-needs only. Statistics results showed that the level of emotional commitment is related to the satisfaction level of transaction-needs, while overall response is related to the level of apparel brand image. We also found that the role of apparel brand image as a moderating factor was limited by the level of transaction-needs satisfaction. In addition, relationship-needs satisfaction brought significant increase in emotional commitment in both community groups (high and low levels of brand image), and the effect of apparel brand image on emotional commitment was significant in both community groups (high and low levels of relationship-needs satisfaction). Especially, the effect of brand image was greater when the level of relationship-needs satisfaction was high. in contrast, increase in emotional commitment responding to increase in relationship-needs satisfaction was greater when apparel brand image is high. The significant influences of relationship-needs satisfaction on community commitments (continuous and normative commitments) were found regardless of apparel brand image(in both community groups with low and high brand image). However, the effects of apparel brand image on continuous and normative commitments were found in only community group with high satisfaction level of relationship-needs. In the case of communities with low satisfaction levels of relationship needs, apparel brand image marginally increases continuous and normative commitments. Therefore, we could not find the moderating effect of apparel brand image on the relationship between relationship-needs satisfaction and continuous and normative commitments in community groups with low satisfaction levels of relationship needs, CONCLUSIONS AND IMPLICATIONS From the results of this study, we draw several conclusions; First, the increases in usage-needs satisfactions through apparel brand communities result in the increases in commitments to apparel brand communities, wheres the degrees of such relationship depends on the level of apparel brand image. That is, apparel brand image is a moderating factor strengthening the relationship between usage-needs satisfaction and commitment to apparel brand communities. In addition, the effect of apparel brand image differs, depending on the level and types of community usage-needs satisfactions. Therefore, marketers of apparel brand companies must determine the appropriate usage-needs, depending on the type of commitment they wish to increase and the level of their apparel brand image, to promote member's commitments to apparel brand communities. Especially, relationship-needs satisfaction was very important factor for increasing emotional, continuous and normative commitments to communities. However the level of relationship-needs satisfaction was lower than interest-needs and transaction-needs. satisfaction. According to previous study on apparel brand communities, relationship-need satisfaction was strongly related to member's intention of participation in their communities. Therefore, marketers need to develope various strategies in order to increase the relationship- needs as well as interest and transaction needs. In addition, despite continuous commitment was higher than emotional and normative commitments, all types of commitments to apparel brand communities had scores lower than 3.0 that was mid point in 5-point scale. A Korean study reported that the level of members' commitment to apparel brand community influenced customers' identification with a brand and brand purchasing behavior. Therefore, marketers should try to increase members' usage-needs satisfaction and apparel brand image as the necessary conditions for bringing about community commitments. Second, marketers should understand that they should keep in mind that increasing the level of community usage needs (transaction and relationship) is most effective in raising commitment when the level of apparel brand image is high, and that increasing usage needs (transaction needs) satisfaction in communities with low brand image might not be as effective as anticipated. Therefore, apparel companies with desirable brand image such as luxury designer goods firms need to create formal online brand communities (as opposed to informal communities with rudimentary online contents) to satisfy transaction and relationship needs systematically. It will create brand equity through consumers' increased emotional, continuous and normative commitments. Even though apparel brand is very famous, emotional commitment to apparel brand communities cannot be easily increased without transaction-needs satisfaction. Therefore famous fashion brand companies should focus on developing various marketing strategies to increase transaction-needs satisfaction.