• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.338-357
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• 2012

This study investigated any possible financial attributes of the CDS spreads of a firm belonging to financial industries headquartered in the Republic of Korea. There were few studies on this issue, especially for the firms located in emerging capital markets. Coupled with the models such as a multiple regression and a principal component analysis(PCA), this research has identified that only two explanatory variables such as SLOPE and INTER3 (i.e. interaction effect between the BETA and the SLOPE) consistently showed their statistically significant influence on the CDS spreads through the 'selected' model without and with applying a stepwise regression procedure for the robustness. Given the rapid developments of sophisticated financial derivatives, this study may suggest a valuable insight to foreign and domestic investors to identify the possible determinants of CDS spreads at the firm- and/or the industry-level.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.86-94
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• 2019

This study investigated the differences of perceived parenting attitude and academic stress on smartphone addiction according to the classification of addiction-risk group among middle school students. A descriptive research design was used. The subjects were 358 middle school students from five middle school in Daegu. Data were analyzed by descriptive statistics, ${\chi}^2$ test, t-test, and stepwise multiple regression using SPSS 18.0. Smartphone addiction-risk group was 97(27.0%) and general group was 261(72.9%). Smartphone addiction-risk group was more negatively perceived parenting attitude and higher academic stress than the general group. The most influential factors on addiction-risk group was using time in a day(${\beta}=.29.4$, p=.003) and general group was academic stress(${\beta}=.298$, p=.000). It is important to develop an intervention program to prevention the smartphone addiction according to the classification of addiction-risk group.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.379-388
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• 2018

The Purpose of this study was to identify the factors affecting patient safety management activity targeted nursing student and to provide basic data for patient safety in nursing education and to develop education program improving students' patient safety management activity. The participants of this study were 358 nursing students in a region and collected data by self-reported questionnaire. Data were analyzed by descriptive statistics, t-test, ANOVA, correlation analysis, stepwise multiple regression analysis. As a resutls, Significant positive correlations were found between patient safety competency, performance confidence, coping and patient safety management activity for nursing students. Patient safety competency, performance confidence were significant factors related to patient safety management activity but coping was not found to directly affect patient safety management activity. Thus, we propose to develop a education intervention program that considers patient safety competency, performance confidence in order to improve patient safety management activity of nursing students.

• Applied Biological Chemistry
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• v.48 no.2
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• pp.183-188
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• 2005

This study was conducted to develop a method for the quantitative determination of soil clay content by spectophotometry. The optimum wavelength obtained with reference clay minerals for spectrophotometry was 500 nm. For the proposed spectrophotometry, 0.5 g of soil sample was put in the 250 ml Erlenmeyer flask and 100 ml dispersing agent was added. After shaking the flask at 130 rpm with a mechanical shaker overnight, the flask was removed from the shaker and was shaken up-and-down for 30 seconds. With a micro-pipet, 4 ml of the suspension was transferred into the previously-inserted cell and the absorbance was measured instantly. Results by the spectrophotometry for clay content analysis were compared with those by the conventional sedimentation technique (the pipet method). The proposed equation was $y\;=\;38.03x_1-0.17x_2-1.17$, where y, $x_1$, and $x_2$ were clay content (%) by the pipet method, water content corrected clay content (%) by spectrophotometry, and organic matter content ($g{\cdot}kg^{-1}$), respectively. The regression coefficient for the equation was $r\;=\;0.984^{**}$, indicating highly significant correlation between the results of the two methods.

• Exercise Science
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• v.21 no.2
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• pp.231-242
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• 2012

The purpose of this study was to develop the prediction model of VO₂max using submaximal metabolic responses from the Bruce protocol, HR responses at several stages and 1,200 m running record, and to compare and analyse the validity of these prediction models. The subjects were consisted of 255 male(133 male for 1,200 m running). They were participated maximal exercise testing with Bruce protocol, and the metabolic responses were measured in the end of the first(3 minute), second stage(6 minute), and 1,200 m running record. Measurement items were VO₂(㎖/kg/min), VCO₂(㎖/kg/min), VE(L/min), HR(bpm) of 3 and 6 minute, time to HR 150 bpm and 170 bpm, HR difference between Bruce protocol 6 and 3 minute, 1,200 m running record. Analyzing with all variables using enter method, the multiple R of total variable model was 0.642(p<.01), SEE was 4.38 ㎖/kg/min, CV was 10.8 %, but multicolinearity was appeared. The multiple R of 3 minutes model 1 and model 2 were 0.341 and 0.461, SEE was 6.05 and 5.72 ㎖/kg/min, CV was 14.9 and 14.1%, and multicolinearity did not appeared. The multiple R of 6 minutes model 1 and model 2 were 0.350 and 0.456, SEE was 6.03 and 5.74 ㎖/kg/min, CV was 14.9 and 14.2%, and multicolinearity did not appeared. The R of HR 170 and HR 170 model were 0.151 and 0.154, SEE were 6.36~6.37 ㎖/kg/min, CV were 15.7%. The R of 1,200 m running model was 0.444, SEE was 4.82 ㎖/kg/min, CV were 11.9%. In conclusion, with considering usefulness and convenience through the validity of these prediction models, the prediction model of VO₂max recommended 6 and 3 minute model, and the validity of HR model and 1,200 m running model were moderately low.

• Land and Housing Review
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• v.13 no.1
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• pp.55-65
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• 2022

This paper investigates the distinct characteristics of freehold and leasehold households living in the seven largest cities and the other areas. We employ the two-stage logit regression analysis to identify the marginal effects of wealth and income after controlling for the other one. We document the following results. First, households with more net wealth are more likely to reside in their own houses, regardless of living areas. Second, the pure income effect after controlling for wealth and other variables lowers the tendency of freeholders to live in the seven largest cities while increasing the tendency to live in the other areas. Furthermore, the income effects reduce the tendency to live in the former regions. Our results suggest that the pure income effects enhance preferences for a better living environment (e.g., larger spaces, better school districts, etc.), whereas the wealth effect increases the likelihood of freeholds.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.351-360
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• 2021

The aim of the study was to assess the prevalence of young adults obesity, morbid obesity and severe obesity and to identify associated factors. Data for 50,095 participants aged 20-39 from Community Health Survey 2019. Chi-square test and multiple logistic regression were used for the analysis. Prevalence for young adults obesity, morbid obesity and severe obesity were 23.60%, 5.86% and 1.31%. Aged of 20's, male, low income, low educational level and marital status were found to be associated with all stages of obesity. Current smoking, high risk drinking, physical activity, health promotion practices, subjective health, EQ-5D, stress, depressive symptoms and comorbidities increased the prevalence of obesity in young adults. Health check-up, subjective health, EQ-5D, stress, depressive symptoms and comorbidities increased the prevalence of severe obesity in young adults. Based on the results, it is necessary to develop and provide focused intervention consisting of characteristics of young adults and stages of obesity.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.461-470
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• 2024

This study aimed to predict total phosphorus (T-P) to address early eutrophication caused by nutrient influx from various human activities. Traditional T-P monitoring systems are labor-intensive and time-consuming, leading to a global trend of using direct reading sensors. Therefore, this study utilized water quality parameters obtained from direct reading sensors in a two-stage T-P prediction process. The importance of turbidity (Tur) in T-P prediction was examined, and an analysis was conducted to determine if T-P prediction is possible using only direct reading sensor parameters by adding automatic water quality analyzer parameters. The study found that T-P concentrations were higher in the mid-lower reaches of the Nakdong River basin compared to the upper reaches. Pearson correlation analysis identified water quality parameters highly correlated with T-P at each site, which were then used in multiple linear regression analysis to predict T-P. The analysis was conducted with and without the inclusion of Tur, and the performance of models incorporating automatic water quality analyzer parameters was compared with those using only direct reading sensor parameters. The results confirmed the significance of Tur in T-P prediction, suggesting that it can be used as a foundational element in the development of measures to prevent eutrophication.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.59-70
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• 2020

This study was proceeded to empirically identify the start-up support policy as an element that affects the performance of the early start-ups and measure the effectiveness of the current start-up support policy, in order to suggest the direction future policies according to the study. To accomplish this the influence of the start-up support policy on the early start-ups was analyzed, and the differences according to the industry and growth stage of the start-ups, as the characteristics of the start-ups, were identified. The research subjects collected real data of 297 start-ups of the past three years that were selected for the Initial Start-Up Package project, and performed multiple regression analysis on the influence between variables, and hierarchical regression analysis on moderating effects. The summary of the study is as follows. First, as a result of identifying the influential relationship between the start-up support policy and the performance of the start-up, sales had made a significant impact on the start-up fund, start-up mentoring, and start-up infrastructure(space), while start-up education failed to show a significant effect on the increase in sales. In terms of employment, start-up mentoring was the only field that showed a significant influential relationship. Second, as a result of identifying the moderating effect of the start-up's industry and growth stage, the industry did not have a statistically significant influence, but the interactive effect was seen in start-up education. To be more specific in terms of the sales relationship of each industry, knowledge services turned out to be helpful in improving sales, while manufacturing turned out to be effective in improving sales regardless of being supported with start-up mentoring and start-up infrastructure (space). The sales relationship regarding the start-up growth stage was identified to be statistically significant. The preliminary stage was not statistically significant, while providing start-up mentoring and start-up funding were effective for start-up stage and growing stage, respectively. On the other hand, employment did not perform a significant influence on the start-up growth stage. This study analyzes the effectiveness the start-up support policy for early start-ups, identifies the need in differentiated support policies according to the characteristics of the start-ups, and suggests implications for the direction in which future policies should be made towards.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.