Early Results of Heart Transplantaion: A Review of 20 Patients (심장이식술 20례의 조기성적)
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- Journal of Chest Surgery
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- v.30 no.2
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- pp.164-171
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- 1997
Heart transplantation is now accepted as a definitive therapeutic modality in patients with terminal hear failure. The first successful heart transplantation in humans was done in 1967 and the first case in Korea was performed in november, 1992. Since the first case in 1992, more than 50 cases have been performed in Korea. A total of 20 patients underwent orthotopic heart transplantation since November, 1992 in Asan Medicla Center. The purpose of this study is to evaluate the early results and the follow-up course of 20 cases of heart transplantation done in Asan Medical Center. The average age of 20 patients was 39.9
This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.
We used the health screening data of some rural and urban residents to examine the cross-sectional association between leukocyte count and hypertension. The 206 male and 203 female rural residents were selected by multi-stage cluster sampling method in Kyungsan-Kun area of Kyungbuk province in 1985 and 600 urban residents were selected by the same sampling method as the rural residents in Daegu city of the same province in 1986 compatible with age-sex distribution of Daegu city of 1985 census, but of whom 384 actually responded. The rest of 600 were replaced by age and sex with those who were members of the medical insurance plan visiting the health management department of the university hospital to get the biannual preventive medical checkups. Excluded in the analysis were those having hypertensive history, diseases and extreme outlying values of the screening tests, leaving 373 rural and 571 urban residents. Leukocyte count was measured with ELT-8 Laser shadow method and the unit
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.
To measure variations in some of the important agronomic characteristics of rice varieties under shifting of seedling dates, this study has been carried out at the Paddy Crop Division of Crop Experiment Station(then Agricultural Experiment Station) in Suwon for the period of three years 1958 to 1960. The varieties used in this study were Kwansan, Suwon #82, Mojo, Paltal and Chokwang, which have the different agronomic characteristics such as earliness and plant type. Seeds of each variety were sown at 14 different dates in 10-day interval starting on March 2. The seedlings were grown on seed bed for 30, 40, 50, 60, 70 and 80 days, respectively. The results of this study are as follows: A. Heading dates. 1. As the seeding date was delayed, the heading dates was almost proportionally delayed. The degree of delay was higher in early varieties and lower in late varieties and the longer the seedling stage, the more delayed the heading date. 2. Number of days to heading was proportionally lessened as seeding was delayed in all the varieties but the magnitude varied depending upon variety. In other words, the required period for heading in case of late planting was much shortened in late variety compared with early one. Within a variety, the number of days to heading was less shortened as the seedling stage was prolonged. Early variety reached earlier than late variety to the marginal date for the maximum shortening of days to heading and the longer the seeding stage, the limitted date came earlier. There was a certain limit in seeding date for shortening of days to heading as seeding was delayed, and days to heading were rather prolonged due to cold weather when seeded later than that date. 3. In linear regression equation, Y=a+bx obtained from the seeding dates and the number of days to heading, the coefficient b(shortening rate of days to heading) was closely correlated with the average number of days to heading. That is, the period from seeding to heading was more shortened in late variety than early one as seeding was delayed. 4. To the extent that the seedling stage is not so long and there is a linear relationship between delay of seeding and shortening of days to heading, it might be possible to predict heading date of a rice variety to be sown any date by using the linear regression obtained from variation of heading dates under the various seeding dates of the same variety. 5. It was found out that there was a close correlation between the numbers of days to heading in ordinary culture and the other ones. When a rice variety was planted during the period from the late part of March to the middle of June and the seedling ages were within 30 to 50 days, it could be possible to estimate heading date of the variety under late or early culture with the related data of ordinary culture. B. Maturing date. 6. Within (he marginal date for maturation of rice variety, maturing date was proportionally delayed as heading was delayed. Of course, the degree of delay depended upon varieties and seedling ages. The average air temperature (Y) during the ripening period of rice variety was getting lower as the heading date. (X) was delayed. Though there was a difference among varieties, in general, a linear regression equation(y=25.53-0.182X) could be obtained as far as heading date were within August 1 to September 13. 7. Depending upon earliness of a rice variety, the average air temperature during the ripening period were greatly different. Early variety underwent under 28