• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.247-256
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• 2012

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

• Advances in nano research
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• v.15 no.5
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• pp.401-410
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• 2023

Vibration investigation of fluid-filled three layered cylindrical shells is studied here. A cylindrical shell is immersed in a fluid which is a non-viscous one. Shell motion equations are framed first order shell theory due to Love. These equations are partial differential equations which are usually solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the wave propagation approach procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. Hankel's functions of second kind designate the fluid influence. Mathematically the integral form of the Lagrange energy functional is converted into a set of three partial differential equations. It is also exhibited that the effect of frequencies is investigated by varying the different layers with constituent material. The coupled frequencies changes with these layers according to the material formation of fluid-filled FG-CSs. Throughout the computation, it is observed that the frequency behavior for the boundary conditions follow as; clamped-clamped (C-C), simply supported-simply supported (SS-SS) frequency curves are higher than that of clamped-simply (C-S) curves. Expressions for modal displacement functions, the three unknown functions are supposed in such way that the axial, circumferential and time variables are separated by the product method. Computer software MATLAB codes are used to solve the frequency equation for extracting vibrations of fluid-filled.

• Journal of the Korean earth science society
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• v.34 no.6
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• pp.524-535
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• 2013

Catastrophe risk models require the damage functions of each vulnerable item in inventory to estimate volcanic ash losses. The damage functions are used to represent the relation between damage factors and damage and also widely used in engineering and natural hazard studies to calculate the vulnerability. In most cases, damage functions are constructed as fragility or vulnerability curves, and researchers are confused by the similarities between them particularly when they perform interdisciplinary research. Thus, we aim to explain the similarities and differences between fragility and vulnerability curves and their relationship by providing case studies to construct them. In addition, we suggest a simple method to construct the damage functions between damage ratio and volcanic ash thickness using limited damage data. This study comes from the fact that damage functions are generally constructed using damage data. However, there is no available volcanic ash damage data in Korea, and not even enough volcanic disaster data to construct damage functions in the world, compared to other hazards. Using the method suggested in the study and the limited damage data from Japan and New Zealand, we construct Weibull-type functions or linear functions dependent of available data to calculate volcanic ash loss estimation, which we think need to be corrected to make it more suitable for inventory characteristics and environmental conditions in Korea.

• Nutrition Research and Practice
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• v.10 no.2
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• pp.198-205
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• 2016

BACKGROUND/OBJECTIVES: A healthy diet has been reported to be associated with physical development, cognition and academic performance, and personality during adolescence. This study was performed to investigate the relationships among milk consumption and academic performance, learning motivation and strategies, and personality among Korean adolescents. SUBJECTS/METHODS: The study was divided into two parts. The first part was a survey on the relationship between milk consumption and academic performance, in which intakes of milk and milk products and academic scores were examined in percentiles among 630 middle and high school students residing in small and medium-sized cities in 2009. The second part was a survey on the relationships between milk consumption and learning motivation and strategy as well as personality, in which milk consumption habits were collected and Learning Motivation and Strategy Test (L-MOST) for adolescents and Total Personality Inventory for Adolescents (TPI-A) were conducted in 262 high school students in 2011. RESULTS: In the 2009 survey, milk and milk product intakes of subjects were divided into a low intake group (LM: ${\leq}60.2g/day$), medium intake group (MM: 60.3-150.9 g/day), and high intake group (HM: ${\geq}151.0g/day$). Academic performance of each group was expressed as a percentile, and performance in Korean, social science, and mathematics was significantly higher in the HM group (P < 0.05). In the 2011 survey, the group with a higher frequency of everyday milk consumption showed significantly higher "learning strategy total," "testing technique," and "resources management technique" scores (P < 0.05) in all subjects. However, when subjects were divided by gender, milk intake frequency, learning strategy total, class participation technique, and testing technique showed significantly positive correlations (P < 0.05) in boys, whereas no correlation was observed in girls. Correlations between milk intake frequency and each item of the personality test were only detected in boys, and milk intake frequency showed positive correlations with "total agreeability", "organization", "responsibility", "conscientiousness", and "intellectual curiosity" (P < 0.05). CONCLUSION: Intakes of milk and milk products were correlated with academic performance (Korean, social science, and mathematics) in Korean adolescents. In male high school students, particularly, higher milk intake frequency was positively correlated with learning motivation and strategy as well as some items of the personality inventory.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.189-201
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• 2022

In this study, we propose factor augmentation to improve forecasting power of cryptocurrency return. We consider financial and economic variables as well as psychological aspect for possible factors. To be more specific, financial and economic factors are obtained by applying principal factor analysis. Psychological factor is summarized by news sentiment analysis. We also visualize such factors through impulse response analysis. In the modeling perspective, we consider ARIMAX as the classical model, and random forest and deep learning to accommodate nonlinear features. As a result, we show that factor augmentation reduces prediction error and the GRU performed the best amongst all models considered.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.971-987
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• 2015

This paper aims at analyzing SW club acitivities on the science core high school using information disclosure. Targeting 103 schools across the nation science core high schools, the factors influencing the SW Club was analyzed. And science core high school education plans, business plans and management reports were analyzed in SW club activities. It was the most influencing on the SW club in Creative-Experiential activities organization of computer courses. So computer curriculum reform is urgently needed. SW extra subject activities and funding was having a positive effect. Tuition reimbursement rates was having a negative effect. But academic achievement did not significantly affect. Therefore as many students as possible should be able to assist the SW extra subject activities. And it is required Programs and budget support that reflect the characteristics of local and school. Also, as science core high schools have STEAM education, science, mathematics and technology home economics teachers etc were leading the SW club activities by fusing the their curriculum and SW education. As these activities are consistent with the purpose of SW education, research should be more active autonomic consisting of various teachers.

• The Korean Journal of Food And Nutrition
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• v.33 no.6
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• pp.599-613
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• 2020

The purpose of this study was to evaluate the quality characteristics of white pan bread added with wheat sprout powder without treatment (WP) and wheat sprout powder with only enzyme treatment (WPE), only lactic acid bacteria treatment (WPL) and enzyme and lactic acid bacteria treatment (WPE&L). The three different powder concentration levels of 1%, 3%, and 5% were added to flour to produce the white pan bread. The bread volume and specific volume of the WPE&L group were the highest among all the addition groups. The bread weight, a-value, and b-value of the WP group was highest among all the addition groups, but the bread baking loss and the L-value of the WP group was the lowest among all the addition groups. The texture measurements indicated that the hardness, gumminess, and chewiness values of the bread were the highest in the WP group. The sensory evaluation test showed that bread in the WPE&L group with 3% wheat sprout powder was the best among all the samples studied. Based on our findings, we suggest that the enzyme and lactic acid bacteria pretreated wheat sprout powder is an effective ingredient for improving the overall quality of white pan bread.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.25-36
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• 2010

The generally known important functions of forests include air purification and the health benefits that humans can receive when relaxing and enjoying recreation in the forests. In recent years, people have appreciated the value of the natural environment but it is not easy to answer the question how much monetary value a natural environment has. Because environmental property is public property, which is not traded on the market, market prices cannot be established, so it is not easy to assess the currency value. Methods for estimating environmental property value have been studied by economists. The representative method for measuring environmental property value is a contingent valuation method, or CVM. Various methods have been researched and attempted along with the development and fusion of mathematics, statistics, and economics. Representative methods of CVM are single-bound and double-bound logit and probit methods. This study has been carried out to compare four estimates. Estimates are as follows: the lowest estimate is derived from a single-bound logit WTPmedian while the highest estimate is from double-bound probit WTPmean. While there are some preceding studies on price estimation and methods of measurement through CVM, they offer only partial comparisons. This study suggests four analytic methods and prices through 1,123 questionnaires. The results can be used for the subsequent comparison of estimate prices and the methods of measurement

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.935-946
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• 2016

In this paper, we analyzed wage determinants of the vocational high school graduates utilizing both individual-level and work region-level variables. We formulate the models in the way wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and work region-level (level-2) variables. To incorporate dependency between individual wages into the model, we utilize hierarchical linear model (HLM). The major results are as follows. First, it is shown that the HLM model is better than the OLS regression models which do not take level-1 and level-2 variables simultaneously into account. Second, random effects on sex, maester dummy and engineering dummy variables are statistically significant. Third, the fixed effects on business hours and mean wage of regular job for level-2 variables are statistically significant effect individual-level wages. Finally, parental education level, parental income, number of licenses and high school grade are statistically significant for higher individual-level wages.