• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.69-82
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• 2021

This study targeted 4,572 middle-aged women to examine the relationship between nutritional status and dietary inflammatory index according to blood glucose level using data from the Korean National Health and Nutrition Examination Survey (KNHANES). Data were analyzed using complex survey chi-square, General Linear Model and logisitc regression in SPSS Win 25.0 program. Women with high blood glucose (normal blood sugar→diabetes) had high rates of obesity and blood TG/HDL-cholesterol ratio. On the other hand, the Mean Adequacy Ratio (10 nutrients) and the intake of anti-inflammatory foods: beans, seeds, mushrooms, and fruits, were lower in the diabetic category. When we analysed the association between blood glucose and the Dietary Inflammatory Index, the risk of pre-diabetes and diabetes was significantly higher in the most pro-inflammatory diet category (Q5) compared to the most anti-inflammatory diet category (Q1). These findings suggest that nutritional education emphasizing the intake of various foods should be effectively conducted effectively in order to improve blood glucose among middle-aged women.

• Journal of Nutrition and Health
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• v.52 no.4
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• pp.354-368
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• 2019

Purpose: This study evaluated the glycemic response of diets using estimated glycemic load (eGL), which had been developed for mixed meals for Korean adults, and examined its associations with cardiometabolic risk factors among Korean adults. Methods: A total of 4,655 men and 6,760 women aged 19 years and above were included from the 2013 ~ 2016 Korea National Health and Nutrition Examination Survey. eGL was calculated by each meal (breakfast, lunch, dinner, and snack) and then summed to give daily total eGL. A multiple logistic regression analysis was used to examine the association. Results: Mean daily total eGL was 112.6 in men and 99.3 in women. Daily total eGL was positively associated with carbohydrate and fiber intakes, but negatively associated with protein and fat intakes in both men and women (p < 0.05 for all). Daily total eGL showed an inverse association with HDL-cholesterol level in both men and women (p = 0.0036 for men and p = 0.0008 for women). Men in the highest quintile of daily total eGL showed a 66% increased risk of hypercholesterolemia (OR, 1.66; 95% CI, 1.10 ~ 2.50; p for trend = 0.0447) compared with those in the lowest quintile. Conclusion: These findings suggest that eGL based on carbohydrate, protein, fat and fiber intakes can reflect glycemic response and therefore can be used as an index for dietary planning, nutrition education and in the food industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.82-92
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• 2019

The purpose of this study was to analyze the relationship and degree of agreement between the six types of Geometry Psychological Assessment (GEOPIA) and four functions of the Myers-Briggs Type Indicator (MBTI) personality test, and to investigate the appropriate level of vocational aptitude commonly recommended by each tool. A total of 377 adult men and women from Korea, aged between 19 and 70 years, were tested using GEOPIA and the MBTI. Cronbach's alpha was calculated to verify the validity and reliability of the measuring tools, and the mean and standard deviation of each variable were calculated. Also, a cross-sectional analysis was conducted to examine the relationship between GEOPIA and the MBTI. The results showed that Round/Triangle (RT) types, Round/Box (RB) types, Triangle/Box (TB) types and Box/Curve (BC) types among the GEOPIA personality types are highly related to MBTI's Sensing/Thinking (ST) types. GEOPIA RC types were related to Intuition/Feeling (NF) and Sensing/Feeling (SF) types, and TC types were highly related to Intuition/Thinking (NT) types. Based on the common characteristics of the two tests, the findings suggest appropriate levels of vocational aptitude. Through this research, it was confirmed that GEOPIA (a Korean psychology and personality test) can be used in counseling, coaching, and education, and above all, is a reliable tool for vocational psychological assessment to search for career aptitude.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.675-687
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• 2019

In recent years, the needs for double deck-tunnels have increased in large cities due to the increase in traffic volume and high land compensation costs. In Korea, a network type tunnel which is smaller than general road tunnels and crosses another tunnel underground is planned. In the shield tunnel joints between the existing shield tunnel and the box-type enlargement section, a partial steel-concrete joint is proposed where the bending moment is large instead of the existing full-section steel joint. In order to analysis the enlargement section of the shield tunnel diverged section to reflect the three-dimensional effect, the two-dimensional analysis model is considered to consider the column effect and the stiffness effect of the longitudinal member. A two-dimensional analysis method is proposed to reflect the stiffness of the longitudinal member and the column effect of the longitudinal point by considering the rigidity of the longitudinal member as the elastic spring point of the connecting part in the lateral model. As a result of the analysis of the model using the longitudinal member, it was considered that the structural safety of the partial steel-concrete joint can be secured by reducing the bending moment of the joint and the box member by introducing the longitudinal member having the stiffness equal to or greater than a certain value.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.142-156
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• 2011

This study aims to suggest improvements in night landscape lighting of Bomun Lake, a representative waterfront landscape in Gyeongju which is the city designated as UNESCO World Heritage in December 2000. This study divided the area into three types of sections-that is, road section, walking section, and landscape section- based on the present condition of land use and users of the Bomun Lake area. In addition, this study classified the lightingtypes by section into nine lighting types-that is, road, crossroad, parking lot, pedestrian passage, trail, sculpture, tree, waterfront deck-by comparing them to the park lighting types suggested by the KS A illuminance standards, and examined the problems of the current Bomun Lake lighting base on the standards. By using this as basic data, this study established relevant plans and collected research material. This study suggested directions of each of the three sections and improvements in illuminance, color temperature, creating methods of each of the nine lighting types to the night Lighting planning of the Bomun Lake area reflecting the landscape characteristics of Gyeongju, a historical, cultural city.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.620-628
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• 2021

This study was conducted to investigate public's perception of the effects of particulate matter (PM) in oral health and to provide specific motivation to prevent oral disease by PM. A total of 134 adults were selected as final analysis subjects from some people all over the country. The data collected is analyzed using SPSS 21.0 for windows. Frequency analysis was used to identify general characteristics and hygiene habit. For identifying perception of effects of PM on oral health, crossover analysis was used. The largest number of people recognized that the level of PM had deteriorated, compared to five years ago. That perception was highest among those in 30 years of age and service professions. Those who check the concentration of PM are more concerned with oral health care when the PM is occurred in high concentration. People who perceive PM as a threat to the oral health are more concerned about oral health care when the PM is occurred in high concentration. It is concerned those who are aware of the relationship between PM and oral health specifically manage the oral health to protect the oral cavity from PM.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.105-115
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• 2021

The purpose of this study is to present the effect of differences in individual coping and organizational homogeneity culture on information security compliance from an exploratory perspective. The study divided groups into individual coping (task-oriented, emotion-oriented) and organizational homogeneity culture (homogeneity, heterogeneity), confirms the difference in information security for each group through cross-design and presents a multiple mediation model between information security factors. As a result of the study, in the coping dimension, the average of the security compliance factors was higher in the emotion-oriented than the task-oriented, and in the homogeneity culture dimension, the average of the security compliance factors was higher in the homogeneity than the heterogeneity. Additionally, social influence and involvement had a multiple mediation effect on the relationship between information security awareness and compliance intention. The implications of this study were to confirm the difference in the effect of individual decision-making styles on security compliance according to the organizational culture differences. The results suggest the necessity of applying a customized information security compliance model for each organization and individual characteristics.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.