• Journal of the East Asian Society of Dietary Life
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• v.18 no.2
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• pp.253-263
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• 2008

This study examined the menu management and utilization of cooking equipment at school foodservice operations in the Chonbuk area. Self-administered questionnaires were collected from a total of 193 school dietitians. Statistical data analysis was completed using the SPSS v. 11.5 program. The results are summarized as follows. Among the 193 schools, 58.5% were elementary schools and 41.5% were middle and high schools. Approximately 97% of the schools prepared meals in the conventional manner. Among the school, 68.4% had a menu cycle of 1${\sim}$2 weeks. The frequency of using convenience foods was significantly different between the elementary schools and middle and high schools(p<0.001). Approximately 45% of the dietitians responded that the most important details for menu planning were menu variety and consumer preference. However, 66.8% of the dietitians responded that a key problem for menu planning was limited and worn-out kitchen equipment. Although the cost of purchasing cooking equipment is high, most dietitians responded they have high needs for equipment in order to meet of the quantity demands of food production. In terms of utilized cooking equipment, most schools had mixers, vegetable cutters, choppers, dish washers, etc. Yet the amenities most often lacking were meat slicers, composting machines, ovens, and griddles. In utilizing the cooking equipment, there was no significant difference between the dietitians in the elementary(3.67) schools and those in the middle and high school foodservice systems(3.70); however, the utilization level was poor. Therefore, governmental regulatory agencies should review and finance support for purchasing cooking equipment. Finally, purchasing analysis was conducted regarding the dietitians' opinions on menu recipes and useful equipment.

• Journal of Distribution Science
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• v.11 no.10
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• pp.55-62
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• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.

• Journal of dental hygiene science
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• v.13 no.3
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• pp.347-353
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• 2013

This study was conducted to provide dental hygiene students with an opportunity which let them learn and have responsibility on bioethical perception by carrying out a survey for bioethical perception by personality types targeting 519 dental hygiene students. The study results were as follows: 1. Generally, in personality types, gender affects friendliness. Also, significant difference was shown in conscientiousness by age and practical experience. From finance point of view, significant difference was shown in neuroticism, extroversion, conscientiousness and openness, however, they did not satisfy test for equality of variances. 2. Generally, in bioethical perception, gender affects embryos right to life significantly (p <0.001) and considerable difference was appeared in intrauterine insemination by age. Significant differences were shown in embryos right to life by grade and whether students have practical experiences or not was the key factor which lead considerable difference in abortion. 3. In correlation of variances for personality types and bioethical perception, only friendliness and embryos right to life had weak correlation of 0.119. 4. In personality types affecting bioethical perception, friendlier personality had strong influence on embryos right to life. From this study, it can be concluded that bioethical perception could be affected by five personality types although they are not conclusive indicators which provide all the information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Journal of Nutrition and Health
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• v.50 no.4
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• pp.391-401
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• 2017

Purpose: The purpose of this study was to estimate the dietary flavonoid intakes of Korean adults according to socioeconomic status. Methods: Using data from the 2007~2012 Korea National Health and Nutrition Examination Survey, a total of 31,112 subjects aged over 19 years were included in this study. We estimated individuals' daily intakes of total flavonoids and seven flavonoid subclasses, including flavonols, flavones, flavanones, flavan-3-ols, anthocyanins, proanthocyanidin, and isoflavones,by linking food consumption data with the flavonoids database for commonly consumed Korean foods. We compared intakes of flavonoids according to the levels of household income and education. Results: Average dietary flavonoid intakes of the study subjects were 321.8 mg/d in men and 308.3 mg/d in women. Daily flavonoid intakes were positively associated with household income level (p < 0.0001) and education level (p < 0.0001). The subjects in the highest household income and highest education level group (OR 0.37, 95% CI 0.30~0.45, p < 0.0001 in men, OR 0.50, 95% CI 0.41~0.60, p < 0.0001 in women) had a lower likelihood of having low total flavonoid intake (less than 25 percentile) compared to the lowest household income and lowest education level group. The food group that contributed to total flavonoid intake with the biggest difference between the lowest and highest groups for both household income level and education level was beverages. Conclusion: This study shows that socioeconomic status was positively associated with flavonoid intake in a representative Korean population. Further research is needed to analyze the association of flavonoid intake with health outcomes according to socioeconomic status such as household income and education level.

• Child Health Nursing Research
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• v.2 no.2
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• pp.45-57
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• 1996

A serious disease in a family influences the entire family member given the fact that the members closely interact with each other. Especially in terms of pediatric nursing, study on family gains importance as the need to care of families whose children with developmental disabilities and chronic disease This study was done based on The Resiliency Model of Family Adjustment and Adaptation(McCubbin, 1991) is intended to examine the stress of parents whose children suffer from cleft lip or /and cleft palate. It also helps them to cope with the stress and analyze the relationship between the stress and coping This study used Family Inventory of Life Events and Changes (FILE) and Coping Health Inventory for Parents(CHIP) for measuring family stress and coping. The two instruments are revised to fit the social and cultural environment of Korean culture. Data collection was done from April 18, 1996 to May 18, 1996 at 8 University medical centers located in Seoul. Those who answered questionnaires were 84 parents whose children have cleft lip or /and cleft palate. SPSS PC+ was used to analyze the data collotted. Programs used for data analysis were t-test, ANOVA, Pearson correlation coefficient. The study is summarized as follows .1. The average score of family stress is 10.46(percentage of the full score 24.90) and 'finance and business strains'(3.25), and 'intrafamily strains'(2.65) ranked the highest. The average score of family's coping is 1.93, which is close to the answer of' moderately helpful' and they are measured to put their utmost efforts to' intergration and cooperation of family and optimistic definition on the situation'. 2. There is no significant statistical correlation between the family stress and coping. 3. Mothers show more stress than fathers in the parts of 'illness and family care strains' and 'losses'(t〓-2.34, t〓-2.32, p<.05). 4. Fathers show more willingness to cope with the stress than mothers do in the parts of' seeking social support','self-esteem','emotional comfort' 5. Mothers are more stress than fathers in the parts of family stress and its coping with it by usual traits(t〓-2.78, p<.05). Parents with religion are measured to cope more willingly than those who are not 6. Income of a family shows positive correlationship with family coping (r〓.28, p<.05). The study shows that gender difference is significant variable in studying on family stress and coping. Mothers get more stress than fathers, which has much to do with the fact that they are in charge of raising children and keeping houseworks. Accordingly, managing family crisis and its survival can be induced by giving support for the mothers, studying fathers including the rest of the family members and giving nursing care and arbitration ; religious background is also considered to be one of the important factors in family stress , judging from the relationship between family income and family's coping, caring given to suffering children is needed on societal levels. The above considerations bring up the need to have a longitudinal study of children with congenital anomaly including cleft lip or /and cleft palate and their families about family stress and coping. Resiliency programs on family system and their effectiveness and the relationship between the enlarged families with social and cultural values reflecting Korean tradition are also needed to be studied.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.43 no.4
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• pp.247-255
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• 2017

Objectives: The aim of this study was to compare the quality of life (QoL) of parents/caregivers of children with cleft lip and/or palate before and after surgical repair of an orofacial cleft. Materials and Methods: Families of subjects who required either primary or secondary orofacial cleft repair who satisfied the inclusion criteria were recruited. A preoperative and postoperative health-related QoL questionnaire, the 'Impact on Family Scale' (IOFS), was applied in order to detect the subjectively perceived QoL in the affected family before and after surgical intervention. The mean pre- and postoperative total scores were compared using paired t-test. Pre- and postoperative mean scores were also compared across the 5 domains of the IOFS. Results: The proportion of families whose QoL was affected before surgery was 95.7%. The domains with the greatest impact preoperatively were the financial domain and social domains. Families having children with bilateral cleft lip showed QoL effects mostly in the social domain and 'impact on sibling' domain. Postoperatively, the mean total QoL score was significantly lower than the mean preoperative QoL score, indicating significant improvement in QoL (P<0.001). The mean postoperative QoL score was also significantly lower than the mean preoperative QoL score in all domains. Only 3.2% of the families reported affectation of their QoL after surgery. The domains of mastery (61.3%) with a mean of $7.4{\pm}1.8$ and finance (45.1%) with a mean score of $7.2{\pm}1.6$ were those showing the greatest postoperative impact. The proportion of families whose QoL was affected by orofacial cleft was markedly different after treatment (95.7% preoperative and 3.2% postoperative). Conclusion: Caring for children with orofacial clefts significantly reduces the QoL of parents/caregivers in all domains. However, surgical intervention significantly improves the QoL of the parents/caregivers of these children.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• 한국사회정책
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• v.20 no.3
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• pp.77-115
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• 2013

The purpose of this study is to present empirical evidence for discussion of financing social welfare via estimating optimal tax burden in the main member countries of the OECD by using Hausman-Taylor method considering endogeneity of explanatory variables. Also, the author produced an international tax comparison index reflecting theoretical hypotheses on revenue-expenditure nexus within a model to compare real tax burden by countries and to examine feasibility of tax increase in Korea. As a result of the analysis, the higher the level of tax burden was, the higher the level of welfare expenditure was, indicating the connection between high burden and high welfare from the aspect of scale. The results also indicated that the subject countries recently entered into the state of low tax burden. Meanwhile, Korea had maintained low burden until the late 1990s but the tax burden soared up since the financial crisis related to the IMF. However, due to the impact of foreign economy and the tax reduction policy, it reentered into the low-burden state after 2009. On the other hand, the degree of social welfare expenditure's reducing tax burden has been gradually enhanced since the crisis. In this context, the current optimal tax burden ratio of Korea as of 2010 may be 25.8%~26.5% of GDP based on input of welfare expenditure variables, a percent that Korea was investigated to be a 'high tax burden-low ITC' country whose tax increase of 0.7~1.4%p may be feasible and that the success of tax system reform for tax increase might be higher probability when compare to others. However, measures of increasing social security contributions and consumption tax were analyzed to be improper from the aspect of managing finance when compared to increase in other tax items, considering the relatively higher ITC. Tax increase is not necessarily required though there may be room for tax increase; the optimal tax burden ratio can be understood as the level that may be achieved on average when compared to other nations, not as the "proper" level. Thus, discussion of tax increase should be accompanied with comprehensive understanding of models of economic developmental difference from nations and institutional & historical attributes included in specific tax mix.