• Journal of Nutrition and Health
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• v.40 no.6
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• pp.566-575
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• 2007

The purpose of this research was to understand how individuals reflect on the frequency and quantity of foods that they consume. Participants selected 5 males and 15 females aged 30 years or older were first interviewed on the frequency of their food consumption. Then based on this data, they were given a cognitive interview using the method of verbal proving. The individual cognitive interviews were recorded with consent while being conducted after complete approval by the Seoul National University Institution Review Board. The recorded material was evaluated using a thematic analysis after transcribing them into text. By analyzing stages of reflection, the major barriers to make the device difficult are revealed: 1) More difficulty in remembering events over the course of a full year due to diversification in the types of food that people consume 2) difficulty calculating the average for seasonal foods 3) difficulty estimating the amount of consumption from the photos presented 4) difficulty estimating amount of consumption from the quantity presented 5) difficulty processing foods that people think are healthy and foods are unhealthy simultaneously 6) difficulty having to consider foods where target food goes in as an ingredient; 7) difficulties arising from having to increase frequency when the amount consumed is higher than the quantity that is presented 8) difficulty having to combine the frequency and quantity of each food item when numerous foods are clustered into one category. These findings show that the less participants were involved in cooking, the more diverse their eating habits were, and the more they tried to adhere to rules of filling out the questionnaire, the more it was difficult for them to come up with an answer to the question being asked. It therefore seems necessary to construct a Food Frequency questionnaire that is attentive to these problems that arise from the recall stages.

• Human Ecology Research
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• v.54 no.2
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• pp.207-225
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• 2016

This study investigated a conceptual framework of fashion consumers' purchase decision-making styles related to behavioral typology of personality. In response to critiques on fragmented and varied use of personality measurements, this study selectively tested and verified an alternative typological model of Enneagram value systems and self-construal levels that could explain the fashion consumers' typological propensities in purchase decision-making. One hundred-item measurement scale for the fashion consumers' purchase decision-making styles was developed based on the extensive literature. Three groups of fashion major students, a total of 107 participants, who respectively participated in 2-hour-long Enneagrams seminars from spring 2013 to fall 2014, were asked to re-sentence the question items to clearly reflect their Enneagram personality to make purchase decisions. Participants described their propensities in their own words about the most comfortable state during the 5-step processes of the purchase decision making process. The revised scale was distributed to 423 participants in January 2016, and the results verified the group differences in various styles in the process of purchase decision-making corresponding to the typological variables discussed in Enneagram. The correlation between Enneagram core values embodied by fashion consumers during the stages of purchase decision-making in extensive levels of self-construal were verified in the context of their fashion decision making. This study found the possibility of the typological approach toward Enneagram types of personality to be applicable to explain and predict peculiar facets of fashion consumers' purchase decision-making styles.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.361-375
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• 2008

We propose proper methods to impute the item nonresponse in 4-8-4 rotation sample survey. We consider nonignorable nonresponse mechanism that can happen when survey deals with sensitive question (e.g. income, labor force). We utilize modeling imputation method based on Bayesian approach to avoid a boundary solution problem. We also estimate a interview time bias using imputed data and calculate cell expectation and marginal probability on fixed time after removing estimated bias. We compare the mean squared errors and bias between maximum likelihood method and Bayesian methods using simulation studies.

• Journal of Physiology & Pathology in Korean Medicine
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• v.28 no.6
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• pp.585-592
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• 2014

This study is to develop a standard tool for pattern identifications in Korean Medicine for Lung Cancer. The advisor committee for this study was organized by 12 Korean Medicine professors from the Korean Association of Traditional Oncology. The item and structure of instrument were based on review of published literature. We took the consultation twice from the advisor committee and additional advices by e-mail correspondences. We divided the symptoms and signs of lung cancer into 6 pattern identifications. - lung spleen both deficiency (肺脾兩虛), lung kidney both deficiency (肺腎兩虛), dampness phlegm obstructing the lung (濕痰蘊肺), qi stagnation blood stasis (氣滯血瘀), yin deficiency toxin heat (陰虛毒熱), and heat toxin accumulation (熱毒蘊結). We obtained the mean weights which reflected the standard deviations from each symptoms of the 6 pattern identifications which were scored on a 5-point scale by 12 experts. We designed the Korean medicine pattern identification tool for lung cancer. It was composed of 57 questions in the question-and-answer format. Though there are some limits that this study is not proved about validity and reliability, the instrument is meaningful and expected to be applied to the subsequent research.

• Journal of Sasang Constitutional Medicine
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• v.15 no.1
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• pp.27-38
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• 2003

Purpose: This study has focused on evaluating the effectiveness and accuracy of the questionnaire which considered as a basic data to indentify constitution Methods: By analysing the tendency of the respondents who has defined constitution by clinical diagnosis and comparing of their answers, the result of their constitution analysis by our questionnaire were re-examed. The answer of each question to each constitution were tested how it is relevent to a scale of a constitution. So I analysed each item response rates on QSCCII of those who had been tested and diagnosed as Taeyangin, Soyangin, Taeumin, Soeumin respectively. Results: 1. From the 537 results of QSCCII of those who were examined by professors, I made a selected Taeyang scale which is consists of 18 items, a selected Soyang scale which is consists of 40 items, a selected Taeum scale which is consists of 41 items and a selected Soeum scale which is consists of 32 items. 2. I have found that there is limitation to find out constitution by the questionnaire we used, one I hope that suitable questionnaire will be developed for the research in the future

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.31-45
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• 2016

In this study, the case of error became the object of learning, and the investigator applied these cases to an actual class and established three study problems in order to achieve the purpose of this study. The results of analysis of students' errors in figure based on before achievement test are shown as follows: First, the most errors occurred in the figure was the ones from deficient mastery of prerequisite concepts and definitions. Specially, the errors from deficient mastery of prerequisite concepts and definitions have the majority. it is very high ratio even if it considers an influence of an evaluation question item. so, I think it is necessary to teach concept related figure above all. Second, as the results of application 'finding errors' to a class, there is a meaningful difference in the mathematical achievement and reasoning ability within significance level 5%. This means 'finding errors' is one of the teaching method that it develops the mathematical achievement and reasoning ability.

• Journal of the Korean Operations Research and Management Science Society
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• v.1 no.1
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Journal of Korean Home Economics Education Association
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• v.29 no.2
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• pp.53-66
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• 2017

The aim of this research is to analyze the items of the Secondary School Teacher's Placement Test(SSTPT) which was submitted for 8 years from 2009 to 2016 according to' detailed criteria of SSTPT'. The results of this study are summarized as follows. First, according to the analysis of items which were covered for the last 8 years, it was found that there was little difference between the evaluation area, the evaluation content elements, and the questionnaires since the questions presented in the 12 items of 12 evaluation areas and 42 of 43 evaluation contents. Second, each of the items in the 8-year questionnaire are as follows. Home economics and education 93 times (32.7%), dietary life 43 times (15.2%), family life 41 times (14.4%), clothing 41 times (14.4%), housing life 34 times (12.0%), consumer life 31 times (11.3%). This shows that there is not a large difference between the basic curriculum subjects of the content education and the ratio of question items. Third, the content elements of evaluation categorized by frequency of questionnaires for 8 years are as follows. Home economics and education mainly covers 'the methodology of teaching and learning,' Family life, 'human development,' Consumer life, 'the understanding of household economics and financial management' and 'consumer decision making,' Dietary life, 'cooking principle and practice' and 'management of dietary life,' Clothing life, 'clothing and household goods production,' Housing life, 'the understanding if residential living.' Based on these results, all the areas set in the evaluation area and content should be treated equally, and qualitative item analysis is necessary from a microscopic point of view.

• Korean Journal of Environment and Ecology
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• v.33 no.3
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• pp.292-302
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• 2019

This study conducted a hierarchy analysis based on a questionnaire survey of experts in park management, ecosystem survey, and ecological environment planning to establish evaluation items and a weighing value of each item to develop ecological connectivity in Baekdudaegan mountain range neighboring the Taebaeksan National Park using the AHP approach. We selected four high-level evaluation indexes and 13 low-level evaluation indexes through literature review and interview with the people in the field and calculated weights for each question through the consistency analysis. The analysis showed that increasing the ecological value was the most important item with the index of 0.474 among the high-level evaluation items, followed by the mitigation of human-nature conflict at 0.247, participation by local residents at 0.165, and the economic perspective at 0.114. Among the low-level evaluation indexes, the movement route of wildlife was the highest at 0.116, followed by the connectivity of landscape ecological patch at 0.112, and functional habitat at 0.099. The comparison of the evaluation items in each working group and the weight factors showed that the movement route of wildlife was the most important at 0.116 in ecosystem survey, the functional habitat was the most important at 0.110 in park management, and the regional preservation and distribution of resources was the most important at 0.123 in ecological environment planning. The results of this study is useful to identify evaluation items for developing ecological network with a diverse source of the actual environmental data in the Taebaeksan National Park.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.