• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.2
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• pp.67-75
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• 2012

Carbon-dioxide capture and storage (CCS) process is consisted by capturing carbon-dioxide from large point source such as power plant and steel works, transporting and sequestrating captured $CO_2$ in a stable geological structure. During CCS process, it is inevitable of introducing impurities from combustion, capture and purification process into $CO_2$ stream. Impurities such as $SO_2$, $H_2O$, CO, $N_2$, Ar, $O_2$, $H_2$, can influence on process efficiency, capital expenditure, operation expense of CCS process. In this study, experimental apparatus is built to simulate the behavior of $CO_2$ transport under various impurity composition and process pressure condition. With this apparatus, $N_2$ impurity effect on $CO_2$ mixture transportation was experimentally evaluated. The result showed that as $N_2$ ratio increased pressure drop per mass flow and specific volume of $CO_2-N_2$ mixture also increased. In 120 and 100 bar condition the mixture was in single phase supercritical condition, and as $N_2$ ratio increased gradient of specific volume change and pressure drop per mass flow did not change largely compared to low pressure condition. In 70 bar condition the mixture phase changed from single phase liquid to single phase vapor through liquid-vapor two phase region, and it showed that the gradient of specific volume change and pressure drop per mass flow varied in each phase.

• Korea journal of population studies
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• v.4 no.1
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• pp.105-130
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• 1981

This study was conducted to compare the characteristics of high performane areas for family planning with that of low performance areas and to find factors which strongly affected contraceptive practice behavior. For the study, eight areas were selected from 274 rural family planning canvassing areas of Korean Population Policy and Program Evaluation Study, which was an action study operated in all areas of Cheju Island from July 1, 1976 until December 31,1979. As a first step of the action study, Cheju Island was devided up 318 family planning canvasser areas Each area was consisted of 200 households in rural district and 300 households in urhan one Duriog the period of project, each canvassing area had been managed by a female family planning canvasser, selected by director of health center considering several individual conditions needed for family planning activities Basic activities of canvassers were to counsell all the eligihie couples in own charged area about family planning methods and also to distribute contraceptives such as condoms and oral pills. In case couples desire to accept sterilization including vasectomy and tubal-ligation, the canvassers played a linking role connecting potential client with family planning field workers. Canvassng areas shows significant differentce in performance for family planning, nevertheless they are supposed to have almost the same conditions regarding family planning distribution channel. Because the purpose of the Cheju project was to eliminate all the problems that existed in governmental distribution system, that is to remove geographic, economic, cognitive and administrative barriers Accumulated performances of family planning methods accepted by residents in each area were calculated by eligible women aged 14-49. And then canvassing areas were ranked according to performance score. Consequently, 4 areas in extremely high and low family planning performance areas were selected respectively. Major results were obtained by comparing characteristics of high performance area with that of low performance areas, which are as follows: 1. The mean number of living children was about the same both in high and low performance areas for family planning. But respondents' mean age (38.5) in high performance areas was higher than that (37.0) in low performance areas 2. Respondents' perception in the expectant educational level of others' children in high performance areas was higher than that in low performance areas, although respondents educational level, monthly expenditure and ratio of children in high school and above was not different. 3. Ratio of ownerships of TV and newspaper in high performance areas was highen than that in low performance areas 4. The duration of canvasser' charge in high performance areas was longer than that of low performance areas, showing the fact that canvassers didn't move cut in high performance areas 5. In high performance areas, canvassers' houses were relatively located in the center part of the village. And so villagers resided in near distances from the anvasser's house 6. 4H clubs' activities in high performance areas were more active than those in low performance areas Therefore it was assumed that cohesiveness of community in high performance areas were stronger than that in low areas. 7. Canvassers' family planning practice rate was higher than that in low performance areas, and also canvassers' human relationship was more sociable than that of canvassers in low performance areas. 8. Fourteen variables which showed relatively high significance level in $X^2$ and F test were selected as independent variables for stepwise regression analysis. According to the results of regression analysis. five of 14 variables-distributors education level ($R^2$=.4439), duration of distributor's charge ($R^2$=.6166), 4H club activities ($R^2$=.6697), canvasser's contraceptive practice ($R^2$=.7377) and location of distributions house ($R^2$=.8010) explained 80.1 percent of total variance.

• Journal of Nutrition and Health
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• v.51 no.1
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• pp.60-72
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• 2018

Purpose: The purpose of this study was to determine differences in eating-out, dietary life styles, and healthy dietary competencies among middle-aged consumers according to obesity status and gender for implications of consumer education. Methods: Data were drawn from the 2016 Food Consumption Behavior Survey, and 3,022 subjects (mail 1,388; female 1,634) who were middle-aged adults were investigated. Analysis of variance with $Scheff\acute{e}$ test, t-test, $x^2$-test, and factor analysis were performed using SPSS v.24. Results: Males showed less interest in diet than females. For both males and females, higher BMI degrees were associated with higher levels of interest in diet. For frequency, monthly average consumption expenditure, one-time cost for eating out, and drinking frequency, males showed higher levels than females. Especially for the male group, higher obesity status was associated with higher levels of eating out and drinking. Dietary lifestyles of males and females turned out to be very similar. For the male group, normal weight group was more likely to show 'health and high quality pursuit dietary life-style' than the other groups. For females, the normal weight group were more likely to show 'health and high quality pursuit dietary life-style' and 'safety pursuit dietary life-style' than the other groups. The level of 'healthy dietary competence' for females was found to be higher than that for males. For the female group, there were significant differences according to obesity status, and practice was more important than knowledge in determining a healthy dietary life. Conclusion: For dietary life-related education for obese middle-aged consumers, it is important to emphasize less eating-out and drinking and less overeating while eating-out based on the results that eating-out, drinking, and overeating in the obesity group were significantly higher than in the normal group. It is important to focus on the value of dietary life and diverse foods, based on the results that the obesity group was less likely to be have healthy dietary lifestyles and consume less diverse foods than the normal group.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Distribution Research
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• v.15 no.3
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• pp.71-110
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• 2010

1. Introduction Today Internet is recognized as an important way for the transaction of products and services. According to the data surveyed by the National Statistical Office, the on-line transaction in 2007 for a year, 15.7656 trillion, shows a 17.1%(2.3060 trillion won) increase over last year, of these, the amount of B2C has been increased 12.0%(10.2258 trillion won). Like this, because the entry barrier of on-line market of Korea is low, many retailers could easily enter into the market. So the bigger its scale is, but on the other hand, the tougher its competition is. Particularly due to the Internet and innovation of IT, the existing market has been changed into the perfect competitive market(Srinivasan, Rolph & Kishore, 2002). In the early years of on-line business, they think that the main reason for success is a moderate price, they are awakened to its importance of on-line service quality with tough competition. If it's not sure whether customers can be provided with what they want, they can use the Web sites, perhaps they can trust their products that had been already bought or not, they have a doubt its viability(Parasuraman, Zeithaml & Malhotra, 2005). Customers can directly reserve and issue their air tickets irrespective of place and time at the Web sites of travel agencies or airlines, but its empirical studies about these Web sites for reserving and issuing air tickets are insufficient. Therefore this study goes on for following specific objects. First object is to measure service quality and service recovery of Web sites for reserving and issuing air tickets. Second is to look into whether above on-line service quality and on-line service recovery have an impact on overall service quality. Third is to seek for the relation with overall service quality and customer satisfaction, then this customer satisfaction and loyalty intention. 2. Theoretical Background 2.1 On-line Service Quality Barnes & Vidgen(2000; 2001a; 2001b; 2002) had invented the tool to measure Web sites' quality four times(called WebQual). The WebQual 1.0, Step one invented a measuring item for information quality based on QFD, and this had been verified by students of UK business school. The Web Qual 2.0, Step two invented for interaction quality, and had been judged by customers of on-line bookshop. The WebQual 3.0, Step three invented by consolidating the WebQual 1.0 for information quality and the WebQual2.0 for interactionquality. It includes 3-quality-dimension, information quality, interaction quality, site design, and had been assessed and confirmed by auction sites(e-bay, Amazon, QXL). Furtheron, through the former empirical studies, the authors changed sites quality into usability by judging that usability is a concept how customers interact with or perceive Web sites and It is used widely for accessing Web sites. By this process, WebQual 4.0 was invented, and is consist of 3-quality-dimension; information quality, interaction quality, usability, 22 items. However, because WebQual 4.0 is focusing on technical part, it's usable at the Website's design part, on the other hand, it's not usable at the Web site's pleasant experience part. Parasuraman, Zeithaml & Malhorta(2002; 2005) had invented the measure for measuring on-line service quality in 2002 and 2005. The study in 2002 divided on-line service quality into 5 dimensions. But these were not well-organized, so there needed to be studied again totally. So Parasuraman, Zeithaml & Malhorta(2005) re-worked out the study about on-line service quality measure base on 2002's study and invented E-S-QUAL. After they invented preliminary measure for on-line service quality, they made up a question for customers who had purchased at amazon.com and walmart.com and reassessed this measure. And they perfected an invention of E-S-QUAL consists of 4 dimensions, 22 items of efficiency, system availability, fulfillment, privacy. Efficiency measures assess to sites and usability and others, system availability measures accurate technical function of sites and others, fulfillment measures promptness of delivering products and sufficient goods and others and privacy measures the degree of protection of data about their customers and so on. 2.2 Service Recovery Service industries tend to minimize the losses by coping with service failure promptly. This responses of service providers to service failure mean service recovery(Kelly & Davis, 1994). Bitner(1990) went on his study from customers' view about service providers' behavior for customers to recognize their satisfaction/dissatisfaction at service point. According to them, to manage service failure successfully, exact recognition of service problem, an apology, sufficient description about service failure and some tangible compensation are important. Parasuraman, Zeithaml & Malhorta(2005) approached the service recovery from how to measure, rather than how to manage, and moved to on-line market not to off-line, then invented E-RecS-QUAL which is a measuring tool about on-line service recovery. 2.3 Customer Satisfaction The definition of customer satisfaction can be divided into two points of view. First, they approached customer satisfaction from outcome of comsumer. Howard & Sheth(1969) defined satisfaction as 'a cognitive condition feeling being rewarded properly or improperly for their sacrifice.' and Westbrook & Reilly(1983) also defined customer satisfaction/dissatisfaction as 'a psychological reaction to the behavior pattern of shopping and purchasing, the display condition of retail store, outcome of purchased goods and service as well as whole market.' Second, they approached customer satisfaction from process. Engel & Blackwell(1982) defined satisfaction as 'an assessment of a consistency in chosen alternative proposal and their belief they had with them.' Tse & Wilton(1988) defined customer satisfaction as 'a customers' reaction to discordance between advance expectation and ex post facto outcome.' That is, this point of view that customer satisfaction is process is the important factor that comparing and assessing process what they expect and outcome of consumer. Unlike outcome-oriented approach, process-oriented approach has many advantages. As process-oriented approach deals with customers' whole expenditure experience, it checks up main process by measuring one by one each factor which is essential role at each step. And this approach enables us to check perceptual/psychological process formed customer satisfaction. Because of these advantages, now many studies are adopting this process-oriented approach(Yi, 1995). 2.4 Loyalty Intention Loyalty has been studied by dividing into behavioral approaches, attitudinal approaches and complex approaches(Dekimpe et al., 1997). In the early years of study, they defined loyalty focusing on behavioral concept, behavioral approaches regard customer loyalty as "a tendency to purchase periodically within a certain period of time at specific retail store." But the loyalty of behavioral approaches focuses on only outcome of customer behavior, so there are someone to point the limits that customers' decision-making situation or process were neglected(Enis & Paul, 1970; Raj, 1982; Lee, 2002). So the attitudinal approaches were suggested. The attitudinal approaches consider loyalty contains all the cognitive, emotional, voluntary factors(Oliver, 1997), define the customer loyalty as "friendly behaviors for specific retail stores." However these attitudinal approaches can explain that how the customer loyalty form and change, but cannot say positively whether it is moved to real purchasing in the future or not. This is a kind of shortcoming(Oh, 1995). 3. Research Design 3.1 Research Model Based on the objects of this study, the research model derived is