• Journal of Distribution Research
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• v.16 no.4
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• pp.1-27
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• 2011

Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

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.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.9
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• pp.1265-1273
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• 2012

The purpose of this study was to investigate the BMI, intake of snacks, and perceptions and use of food and nutrition labels by middle school students (144 boys and 189 girls) in Chuncheon area. The average height and weight of boys were $171.0{\pm}6.4$ cm and $61.0{\pm}11.4$ kg, respectively, whereas those of girls were $160.0{\pm}4.8$ cm and $50.8{\pm}6.6$ kg, respectively. Average body mass index (BMI) of boys and girls were $20.8{\pm}3.3$ and $19.8{\pm}2.4$, respectively (p<0.01). Dietary intake attitude score of girls ($34.39{\pm}5.66$) was higher than that of boys ($33.92{\pm}5.40$) (p<0.05). Subjects bought and ate snacks 1 to 3 times per week (40.2%) by themselves, and most consumed snacks were cookies (23.1%), instant noodles (16.2%), ice cream (13.2%), and candy and chocolates (13.2%). The most important factor in purchasing of snacks was 'taste' ($4.49{\pm}0.67$). When subjects bought processed foods, the rates of reading food labels was 86.6%. The most important factor of the food labels was 'expiration date' (42.9%). The degree of reading food labels on processed foods by girls ($22.70{\pm}5.72$) was higher than that of boys ($20.96{\pm}5.35$) (p<0.01). Of the 13.2% of subjects that did not read food labels, the reason why was that they were not interested (50.0%). Of the 78.4% of subjects that read nutrition labels, the most important component of the nutrition labels was 'calories' (75.9%). The main reason for reading nutrition labels was 'to control weight' (45.6%). In general, use of food labels correlated positively with dietary intake attitude score (p<0.05) and use of nutrition labels (p<0.01). Using multiple regression analysis, we found that 'usefulness of dietary life' was the most significant variable that affects the importance of food and nutrition labels. Therefore, development of an educational program on food and nutrition labels for adolescents will be effective in improving dietary life.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Sleep Medicine and Psychophysiology
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• v.9 no.1
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• pp.34-40
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• 2002

Objectives: The gold standard for diagnosing obstructive sleep apnea syndrome (OSAS) is nocturnal polysomnography (NPSG). This is rather expensive and somewhat inconvenient, however, and consequently simpler and cheaper alternatives to NPSG have been proposed. Oximetry is appealing because of its widespread availability and ease of application. In this study, we have evaluated whether oximetry alone can be used to diagnose or screen OSAS. The diagnostic performance of an analysis algorithm using arterial oxygen saturation ($SaO_2$) base on 'dip index', mean of $SaO_2$, and CT90 (the percentage of time spent at $SaO_2$<90%) was compared with that of NPSG. Methods: Fifty-six patients referred for NPSG to the Division of Sleep Studies at Seoul National University Hospital, were randomly selected. For each patient, NPSG with oximetry was carried out. We obtained three variables from the oximetry data such as the dip index most linearly correlated with respiratory disturbance index (RDI) from NPSG, mean $SaO_2$, and CT90 with diagnosis from NPSG. In each case, sensitivity, specificity and positive and negative predictive values of oximetry data were calculated. Results: Thirty-nine patients out of fifty-six patients were diagnosed as OSAS with NPSG. Mean RDI was 17.5, mean $SaO_2$ was 94.9%, and mean CT90 was 5.1%. The dip index [4%-4sec] was most linearly correlated with RDI (r=0.861). With dip index [4%-4sec]${\geq}2$ as diagnostic criteria, we obtained sensitivity of 0.95, specificity of 0.71, positive predictive value of 0.88, and negative predictive value of 0.86. Using mean $SaO_2{\leq}97%$, we obtained sensitivity of 0.95, specificity of 0.41, positive predictive value of 0.79, and negative predictive value of 0.78. Using $CT90{\geq}5%$, we obtained sensitivity of 0.28, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of 0.38. Conclusions: The dip index [4%-4sec] and mean $SaO_2{\leq}97%$ obtained from nocturnal oximetry data are helpful in diagnosis of OSAS. CT90${\leq}$5% can be also used in excluding OSAS.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.504-512
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• 1994

Background: It is well known that severe hypoxemia is often associated with liver cirrhosis without preexisting cardiac or pulmonary diseases. Pulmonary vascular impairments, more specifically, intrapulmonary shunting have been considered as a major mechanism. Intrapulmonary shunting arises from pulmonary vascular dilatation at the precapillary level or direct arteriovenous communication and has relationship with the characteristic skin findings of spider angioma. However, these results are mainly from Western countries where alcoholic and primary biliary cirrhosis are dominant cuases of cirrhosis. It is uncertain that the same is true in viral hepatitiss associated liver cirrhosis, which is dominant causes of liver cirrhosis in Korea. We investigated the incidences of hypoxemia and orthodeoxia in Korean cirrhotic patients dominantly composed of postnecrotic cirrhosis and the significance of intrapulmonary shunting as the suggested mechanism of hypoxemia, Method: We performed the arterial blood gas analysis separately both at the supine and errect position in 48 stable cirrhotic patients without the evidences of severe complications such as ascites, variceal bleeding, and hepatic coma. According to the results of arterial blood gas analysis, all patients were divided into hypoxemic and normoxemic group. In each group, pulmonary function test and Tc-99m-MAA whole body scan were performed. The shunting fraction was calculated based on the fact that the sum of cerebral and bilateral renal blood flow is 32% of the systemic blood flow. Results: The hypoxemia of $PaO_2$ less than 80 mmHg was observed in 9 patients(18.8%) and Orthodeoxia more than 10 mmHg was observed in 8 patients(16.7%). But there was no patient with significant hypoxemia of $PaO_2$ less than 60 mmHg. $PaO_2$ was significantly decreased in the patients with spider angioma than the pathients without spider angioma and showed no correlation with the serologic type and severities of liver function test findings. Any parameters of pulmonary function test did not demonstrate the difference between normoxemic and hypoxemic group. But hypoxemic group showed significantly increased shunt fraction of $11.4{\pm}4.1%$ than normoxemic group of $4.1{\pm}2.0%$ (p<0.05). Conclusions: Hypoxemia is not infrequently observed complication in liver cirrhosis and intrapulmonary shunting is suggested to p1ay a major ro1e in the development of hypxemia. But there was no great likelihood of clinically significant hypoxemia in our domestic cirrhotic patients predominantly composed of postnecrotic type.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.285-301
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• 2020

Looking at the problem of aging in the nation from a demographic perspective, it is not a problem of the overall population, but of the structure of the population. It is the baby boomer and post-baby boomers, the largest population in the country. Baby boomers were born between 1955 and 1963, and currently have a population of 7001,333, which is 13.6 percent (as of 2015). The Post-Baby Boomer generation was born between 1964 and 1974, with a total population of 9,567,171, accounting for 18.8 percent of the total population. In particular, baby boomers and post-baby boomers (32.4% of the total population) have begun to retire or will retire soon. The average life expectancy continues to increase due to the development of medical technology, and the falling birth rate of newborns and the declining population of the production population are darkening the domestic economy. In a policy proposal aimed at easing the nation's falling economic growth rate, women's participation rate is as high as Sweden and men's efforts to increase it as high as Japan's, while the elderly rate is desirable to maintain Korea's high level. This is because the expansion of the elderly generation's participation in economic activities could ease a sharp drop in economic growth and reduce the burden of supporting the elderly population. The study, based on this social problem awareness and problem solving plan, looks at the relationship between career orientation and satisfaction in start-up education based on the diverse career base of active seniors, and also suggests the importance of customized start-up education on the diversity of active seniors by clarifying the relationship between them, and suggests the desirable direction of senior start-up policy design, funding, and start-up education. Based on the theoretical background, the concept of five factors was defined: active senior, career-oriented, satisfaction level of start-up education, willingness to start a business, and the concept definition of an active senior, which is particularly key to the baby boomers in their 50s and 60s, is generally regarded as a source of consumption or welfare benefits, but in this study, the concept of active start-up is reflected in the domestic start-up market by young people in their 40s, 50s and 60s. As a result of a hypothesis test. Hypothesis 1 and Hypothesis 5: Career orientation has been verified to affect the willingness to start a business and the behavior of preparation for a start-up. Hypothesis 3: The willingness to start a business has been verified as having an effect between startup preparation actions. Hypothesis 4: The satisfaction level of start-up education has been verified to affect start-up preparation behavior. However, hypothesis 2: The satisfaction level of education for start-ups does not affect the willingness to start a business. Such results can be inferred that satisfaction in start-up education does not have a direct effect on the will to start a business and increases the will to start a business through the influence of personal career orientation.

• The Korean Journal of Food And Nutrition
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• v.11 no.3
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• pp.323-328
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• 1998

This study was to investigate regularity of breakfast and food habits of commuting local college students. The regularly breakfast eating rate was found to be 32.9% in man and 26.5% in woman. The mean score of food habits was pretty low, 36.7 out of minimum possible score 12 and maximum 60. The mean score of nutrition attitude was 58.1 out of minimum possible score 18 and maximum 90. This survey showed that skipping breakfast or irregularity of breakfast led to overeating, high fat diet, lot of alcohol and imbalanced diet. It was known that breakfast was the most important among three meals. But having balanced breakfast daily was very difficult according to loss of appetite and busy schedule early in the morning. I suggested carbohydrate food, protein food, and vitamin & mineral food items desirable for nutritionally balanced, easily digestible, tasteful, quick and easily cooking breakfast menu. It was recommended to choose on item out of each of three food categories considering calory(1/3 of daily recommended calory intake for breakfast).

• Clinical and Experimental Reproductive Medicine
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• v.34 no.3
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• pp.189-196
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• 2007

Objectives: The purpose of this study is to investigate the clinical significance of age and basal serum FSH in predicting the outcomes of in vitro fertilization (IVF) in patients with poor-ovarian response. Methods: From January 2000 to December 2004, 85 second IVF cycles of 85 poor-ovarian response patients under the age of 42 with a back-ground of the first IVF cycles at our infertility center and 5 or less oocytes were retrieved and their basal serum FSH levels of 15$\sim$25 mIU/ml were enrolled in this study. Exclusion criteria were patients with a male factor for the etiology of infertility and undergoing genetic diagnosis of embryo such as PGD. Flare-up protocol was used for ovarian stimulation in all cases. Results: When we stratified the study groups by patient's age, the younger age group (age<35, n=35) showed significantly higher implantation rate (19.0% versus 4.0%, p<0.05) and higher ongoing pregnancy rate (100% versus 14.3%, p<0.05) than the older age group (age$\geq$35, n=50). And then, when we stratified the study populations by basal serum FSH level, the lower FSH group (basal serum FSH<20 mIU/ml, n=58) showed significantly higher number of retrieved oocytes (4.6$\pm$0.7 versus 2.2$\pm$0.5, p<0.05) and lower cancellation rate (19.0% versus 55.6%, p<0.05) than higher FSH group (basal serum FSH$\geq$20 mIU/ml, n=27). Conclusions: In conclusion, it was suggested that the patient's age could predict the IVF outcomes in respect to its potency of pregnancy and ongoing pregnancy. Serum basal FSH levels could predict more accurately the ovarian response of cycle, but not clinical outcomes.