• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.889-904
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• 2021

This study is a follow-up study of Kang and Kim (2020). In this study, we derive the sample influence functions of the t-statistic which were not directly derived in previous researches. Throughout these results, we both mathematically examine the relationship between the empirical influence function and the sample influence function, and consider a method to approximate the sample influence function by the empirical influence function. Also, the validity of the relationship between an approximated sample influence function and the empirical influence function is verified by a simulation of a random sample of size 300 from normal distribution. As a result of the simulation, the relationship between the sample influence function which is derived from the t-statistic and the empirical influence function, and the method of approximating the sample influence function through the empirical influence function were verified. This research has significance in proposing both a method which reduces errors in approximation of the empirical influence function and an effective and practical method that evolves from previous research which approximates the sample influence function directly through the empirical influence function by constant revision.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.51-58
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• 2022

In this paper, we propose a decision tree-based machine learning model that leads to food exchange table renewal by classifying food groups through machine learning for existing food and food data found by web crawling. The food exchange table is the standard for food exchange intake when composing a diet such as diet and diet, as well as patients who need nutritional management. The food exchange table, which is the standard for the composition of the diet, takes a lot of manpower and time in the process of revision through the National Health and Nutrition Survey, making it difficult to quickly reflect food changes according to new foods or trends. Since the proposed technique classifies newly added foods based on the existing food group, it is possible to organize a rapid food exchange table reflecting the trend of food. As a result of classifying food into the proposed model in the study, the accuracy of the food group in the food exchange table was 97.45%, so this food classification model is expected to be highly utilized for the composition of a diet that suits your taste in hospitals and nursing homes.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.607-616
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• 2016

The purpose of this study was to confirm how the students have responded to their class according to STEB (science teaching efficacy belief) of secondary science teacher in astronomy classes. Middle school teachers in charge of 'The Solar System' and 'The Exosphere and Space Development' in the 2009 Revision Science Curriculum content system is selected as an object of study through random sampling method. Twenty-nine teachers were taken STEB questionnaire and asked to make it out. Twenty-seven completed a questionnaire of them is selected for this study. In addition, the top and bottom 5% selected through frequency analysis with the total score from the questionnaire were regarded as high and low STEB teachers. For data collection, this study was used methods such as semi-structured interviews, recording, participant observation. The results were as follows: First, science teachers of high STEB had a high accessibility about excellent professional knowledge and content of the curriculum relating to astronomical field. Second, high STEB teachers were prepared by the appropriate teaching strategies adequate to student-centered learning, whereas the low STEB teachers totally have had teacher-centered learning. Third, high STEB teachers had been provided as the idea that you can take advantage of a variety of instruments, as well as scientific knowledge through the Astronomical Society. Therefore, confidence in astronomical class and teaching strategies through content of the curriculum were very important variables to predict the STEB as well as astronomy-related class activities such as astronomical observations.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.527-540
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• 2020

While analyzing data, researching outliers, which are out of the main tendency, is as important as researching data that follow the general tendency. In this study we discuss the influence function for outlier discrimination. We derive sample influence functions of sample mean, sample variance, and sample standard deviation, which were not directly derived in previous research. The results enable us to mathematically examine the relationship between the empirical influence function and sample influence function. We can also consider a method to approximate the sample influence function by the empirical influence function. Also, the validity of the relationship between the approximated sample influence function and the empirical influence function is also verified by the simulation of random sampled data in normal distribution. As the result of a simulation, both the relationship between the two influence functions, sample and empirical, and the method of approximating the sample influence function through the emperical influence function were verified. This research has significance in proposing a method that reduces errors in the approximation of the empirical influence function and in proposing an effective and practical method that proceeds from previous research that approximates the sample influence function directly through empirical influence function by constant revision.