• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.591-598
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• 2019

The purpose of this study is to identify the perceptions of SW education among elementary, middle and high school students, parents, and teachers, and to identify the variables that influence the perception of SW education. For this study, a total of 50 elementary schools, 14 middle schools, and 8 high schools were selected from the stratified sampling method, and an online survey was conducted for students, parents, and teachers. According to the results, the questionnaires of 2,231 students, 615 parents, and 173 teachers were analyzed. According to the results of the study, students, parents, and teachers who had experienced SW leading schools had a high awareness of SW education, and school-level students showed higher recognition in the order of elementary, middle, and high school. As a result of analyzing the difference of perception according to the characteristics of the study subjects, the students were more aware of the fact that male students, students who participated in SW-related club activities, students who participated in SW-related competitions, higher class times of the desired. In the case of parents, the parents of male students, parents who taught SW-related educational activities outside the school, and the parents with high hopes had high awareness. In the case of teachers, the higher the educational experience of SW, the higher the students' perception of the desired time of 2 hours. As a result of analyzing the influence of the characteristics of the subjects on the perception through the multiple regression analysis, the students 'and parents' awareness and the degree of hemming on the SW-related education were found to have a positive effect. In addition, teacher awareness and SW education career were found to have a positive effect.

• Journal of Korean Home Economics Education Association
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• v.31 no.1
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• pp.1-19
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• 2019

The purposes of this study were to concretely reveal the effect of the parents' child-rearing attitude perceived by adolescents and the school life adaptation on the problem behavior, and to verify the moderating effect of the ego-resilience on the relationship between the parents' child-rearing attitude and the school life adaptation and the adolescent problem behavior. This study analyzed a total of 2,107 students in the first year of high school, which was the 4th year data(2013) of Korea Children Youth Panel Survey(KCYPS) 2010. The reliability, descriptive statistics, t-test, and hierarchical regression analysis were conducted using SPSS WIN 22.0. The results were as follows. First, the effect of the parents' child-rearing attitude(supervision, affection, reasonable explanation, excessive interference, excessive expectation, and inconsistency), school life adaptation(relationship with teacher, relationship with friend, school regulation, and learning activity), and ego-resilience on the adolescent problem behavior was analyzed. As a result, the relationship with friend(-) had the highest influence on the adolescent problem behavior, followed by learning activity(-), inconsistency(+), ego-resilience(-), excessive interference(+), and supervision(-). However, the remaining sub-variables did not have any significant influence on the adolescent problem behavior. Second, the moderating effect of the ego-resilience on the relationship among the parents' child-rearing attitude, adaptation to school life, and adolescent problem behavior. The ego-resilience was found to moderate the effects of parents' positive child-rearing attitude, interpersonal relationships, and school adaptation on the adolescent problem behavior. However, the moderating effect was not significant for the effect of negative child-rearing attitude on the adolescent problem behavior. Therefore, various ego-resilience enhancement programs need to be developed and researched as a part of the safety education through the home economics class.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of Korean Society of Forest Science
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• v.33 no.1
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• pp.33-58
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• 1977

A bark comprises about 10 to 20 percents of a typical log by volume, and is generally considered as an unwanted residue rather than a potentially valuable resourses. As the world has been confronted with decreasing forest resources, natural resources pressure dictate that a bark should be a raw material instead of a waste. The utilization of the largely wasted bark of genus Pinus, Quercus, and Populus grown in Korea can be enhanced by learning its physical and mechanical properties. However, the study of tree bark grown in Korea have never been undertaken. In the present paper, an investigative study is carried out on the bark of three genus, eleven species representing not only the major bark trees but major species currently grown in Korea. For each species 20 trees were selected, at Suweon and Kwang-neung areas, on the same basis of the diameter class at the proper harvesting age. One $200cm^2$ segment of bark was obtained from each tree at brest height. Physical properties of bark studied are: bark density, moisture content of green bark (inner-, outer-, and total-bark), fiber saturation point, hysteresis loop, shrinkage, water absorption, specific heat, heat of wetting, thermal conductivity, thermal diffusivity, heat of combustion, and differential thermal analysis. The mechanical properties are studied on bending and compression strength (radial, longitudinal, and tangential). The results may be summarized as follows: 1. The oven-dry specific gravities differ between wood and bark, further more even for a given bark sample, the difference is obersved between inner and outer bark. 2. The oven-dry specific gravity of bark is higher than that of wood. This fact is attributed to the anatomical structure whose characters are manifested by higher content of sieve fiber and sclereids. 3. Except Pinus koraiensis, the oven-dry specific gravity of inner bark is higher than that of outer bark, which results from higher shrinkage of inner bark. 4. The moisture content of bark increases with direct proportion to the composition ratio of sieve components and decreases with higher percent of sclerenchyma and periderm tissues. 5. The possibility of determining fiber saturation point is suggested by the measuring the heat of wetting. With the proposed method, the fiber saturation point of Pinus densiflora lies between 26 and 28%, that of Quercus accutissima ranges from 24 to 28%. These results need be further examined by other methods. 6. Contrary to the behavior of wood, the bark shrinkage is the highest in radial direction and the lowest in longitudinal direction. Quercus serrata and Q. variabilis do not fall in this category. 7. Bark shows the same specific heat as wood, but the heat of wetting of bark is higher than that of wood. In heat conductivity, bark is lower than wood. From the measures of oven-dry specific gravity (${\rho}d$) and moisture fraction specific gravity (${\rho}m$) is devised the following regression equation upon which heat conductivity can be calculated. The calculated heat conductivity of bark is between $0.8{\times}10^{-4}$ and $1.6{\times}10^{-4}cal/cm-sec-deg$. $$K=4.631+11.408{\rho}d+7.628{\rho}m$$ 8. The bark heat diffusivity varies from $8.03{\times}10^{-4}$ to $4.46{\times}10^{-4}cm^2/sec$. From differential thermal analysis, wood shows a higher thermogram than bark under ignition point, but the tendency is reversed above ignition point. 9. The modulus of rupture for static bending strength of bark is proportional to the density of bark which in turn gives the following regression equation. M=243.78X-12.02 The compressive strength of bark is the highest in radial direction, contrary to the behavior of wood, and the compressive strength of longitudinal direction follows the tangential one in decreasing order.

• Journal of Korean Society of Forest Science
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• v.84 no.4
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• pp.465-478
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• 1995

The objective of this study was to investigate the impacts of large-scale timber harvesting on the environment of a mature hardwood forest. To achieve the objective, the effects of harvesting on forest environmental factors were analyzed quantitatively using the field data measured in the study sites of Seoul National University Research Forests [(Mt.) Paekunsan] for two years(1993-1994) following timber harvesting. The field data include information on vegetation, soil mesofauna, physicochemical characteristics of soil, surface water runoff, water quality in the stream, and hillslope erosion. For comparison, field data for each environmental factor were collected in forest areas disturbed by logging and undisturbed, separately. The results of this study were as follows : The diversity of vegetational species increased in the harvested sites. However, the similarity index value of species between harvested and non-harvested sites was close to each other. Soil bulk density and soil hardness were increased after timber harvesting, respectively. The level of organic matter, total-N, avail $P_2O_5$, CEC($K^+$, $Na^+$, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$) in the harvested area were found decreased. While the population of Colembola spp., and Acari spp. among soil mesofauna in harvested sites increased by two to seven times compared to those of non-harvested sites during the first year, the rates of increment decreased in the second year. However, those members of soil mesofauna in harvested sites were still higher than those of non-harvested sites in the second year. The results of statistical analysis using the stepwise regression method indicated that the diversity of soil mesofauna were significantly affected by soil moisture, soil bulk density, $Mg^{{+}{+}}$, CEC, and soil temperature at soil depth of 5(0~10)cm in the order of importance. The amount of surface water runoff on harvested sites was larger than that of non-harvested sites by 28% in the first year and 24.5% in the second year after timber harvesting. The level of BOD, COD, and pH in the stream water on the harvested sites reached at the level of the domestic use for drinking in the first and second year after timber harvesting. Such heavy metals as Cd, Pb, Cu, and organic P were not found. Moreover, the level of eight factors of domestic use for drinking water designated by the Ministry of Health and Welfare of Korea were within the level of the first class in the quality of drinking water standard. The study also showed that the amount of hillslope erosion in harvested sites was 4.77 ton/ha/yr in the first year after timber harvesting. In the second year, the amount decreased rapidly to 1.0 ton/ha/yr. The impact of logging on hillslope erosion in the harvested sites was larger than that in non-harvested sites by seven times in the first year and two times in the second year. The above results indicate that the large-scale timber harvesting cause significant changes in the environmental factors. However, the results are based on only two-year field observation. We should take more field observation and analyses to increase understandings on the impacts of timber harvesting on environmental changes. With the understandings, we might be able to improve the technology of timber harvesting operations to reduce the environmental impacts of large-scale timber harvesting.