• Korean Journal of Community Nutrition
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• v.2 no.3
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• pp.294-304
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• 1997

The purpose of this study was to explore the relationship between dietary behavior and the nutrient intake status in the youth of rural areas, based on their personal characters such as their sex, age, family type, number of family members, mother's age, occupation, and school career. This study was made by use of a self-administrated questionnaire with a 24-hour recall for 5days as an instrument with 439 randomly selected students. Statistical methods applied to analyze the data were frequency, percent, Willcoxon Rank-sum test, Kruskal-wallis test, x2-test by contingence table, and Spearman's correlation coefficient in non parametric statistical cases. Some of the interesting results are as follows : 1) The correlation between sex and breakfast is highly significant. That is, over 80% of male students had breakfast every day, whereas only about 60% of female students had breakfast every day. Bad table manners and some other problems are insignificant with respect to the personal characters in the relations between the personal characters and eating behaviors. However, the regularity of every meal, the frequency of having meals with other family members, and the frequency of meals eaten out and snacks show significant differences. 2) The mother's occupation does not have any influence on the nutrient intake of their students when the relationship between personal characters and nutrient intake was analysed. On the other hand sex, the mother's school career, the numbers of family members, the type of family, and the income of the family showed significant differences nutrient intakes. 3) The regularity and the frequency of having meals, meals eaten out with their family members, and the table manners during meals showed significant differences in the intake of nutrient elements such as calorie, protein, fat, fiber, calcium, iron, phosphorus, vitamin B1, vitamin B2, niacin and vitamin C. However some consideration during meals and problems in eating habit are insignificant with regard to nutrient intake.

• Journal of the East Asian Society of Dietary Life
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• v.7 no.2
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• pp.199-210
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• 1997

The purpose of this study was to investigate the mutual relationship between food preference and nutrient intake status of high school students, based on the their personal characters which are sex, age, family type, number of family, mother's age, occupation, and school career. 439 students were selected with random stratified cluster sampling method. The study used a self-administrated questionnaire and 24-hour recall method for 5 days as instrument tools. Statistical methods applied to analyze the data were frequency, percent, Willcoxon Rank-sum test, Kruskal-Wallis test, ${x^2}-test$ by contingence table, and Spearman's correlation coefficient in non parametric statistical methods. Some of interesting results are as follows : 1. The correlation between sex and the set of characters of mother's age, school career and income is highly significant. However there is no any significant difference on the kinds of job and the types of family. 2. The relation between the preference of main dishes and the nutrient intake show a significant difference except to the noodles. This marks that preference of main dishes shows a direct proportion with the nutrient intakes except for the fat, vitamin A, vitamin C. 3. The preference of animal food marks a direct proportion with the nutrients such as energy, protein, fat, fiber, phosphorus, iron, vitamin $B_{1}$, vitamin $B_{2}$, and niacin 4. The preference of vegetable food gives some influence on the nutrient intake but the preference of soup is insignificant, the preference of Kimchi is in reverse proportion, and the preference of vegetable marks a direct proportion with the nutrient intake. 5. The preference of snacks marks a direct proportion with all kinds of nutrients intake except for the vitamin A, and vitamin C.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1081-1090
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• 2010

Most nations including Korean government make a great endeavor to realize low-carbon and green-growth world. We also work hard to expand bicycle facilities and bicycle road in order to increase bicycle transportation rate. Nowadays number of cyclists is increasing but fortunately, bicycle accidents also increase rapidly. Most data of bicycle accidents published by National Police Agency annually are represented as frequencies in two dimensional contingency tables. In this work, risk rates and characteristics of bicycle accidents are analyzed by using concepts of the probability and conditional probability. Especially with numbers of estimated cyclists and registered cars, risk rates of various kinds of bicycle accidents are obtained. Under the assumption of the conditional independence, probability of bicycle accident occurred at realistic situations could be estimated. Furthermore we discuss to reduce bicycle accidents with these results obtained in this work.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.