• Human Ecology Research
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• v.58 no.1
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• pp.105-120
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• 2020

This study helps infant teachers practice a constructivism-based teacher education program that supports infant mathematical inquiry activities and examines improvements in mathematical teaching knowledge, mathematical teaching initiatives, mathematical interaction, constructivism belief and mathematical teaching efficacy. Twenty two experiment group infant teachers and twenty two comparison group infant teachers were chosen at two workforce educare centers. The experiment group infant teachers participated in 18 sessions of a constructivism teacher training program for 8 weeks, but the comparison group infant teachers did not take part in the program. Pretest and post-tests were implemented for the mathematical teaching knowledge, mathematical teaching initiatives, mathematical interactions, constructivism belief and mathematical teaching efficacy in the experiment group. Independent sample t-test and ANCOVA were tested using Windows SPSS statistics 21.0. The homogeneity test for the experiment and comparison group revealed significant differences. ANCOVA was carried out after the pretest score was controlled as a co-variance. Significant differences were indicated in mathematical teaching knowledge, mathematical teaching initiative, mathematical interaction, constructivism belief and mathematical teaching efficacy. The results indicated that a constructivism-based teacher education program to support infant mathematical inquiry activities influenced improvements in mathematical teaching knowledge, mathematical teaching initiative, mathematical interaction, constructivism belief and mathematical teaching efficacy. This study proved the effects of the program based on constructivism theory content for the knowledge, skills and attitude about infant teaching of mathematical initiatives and practiced a program of exploration, investigation, application and assessment for infant teachers. The results can help infant teachers teach mathematical exploration activities and help activate infant mathematical exploration activities.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.469-477
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• 2020

The main objective of this paper is to examine the applicability of Linan and Chen's entrepreneurial intention model (EIM) in predicting the entrepreneurial intention. EIM is an adaptation of the Theory of Planned Behavior that focuses on entrepreneurial intention and hypothesizing slightly different patterns of relationship with regards to subjective norms. The model also includes human capital and demographic factors. Snowball sampling method was used to collect data using the entrepreneurial intention questionnaire (EIQ) through several social media platforms. The survey indicates that the overall entrepreneurial intention of Saudi students is high (mean = 5.41). Eight out of the seventeen hypothesized relationships were found to be significant. Among the demographic variables, gender-personal attitude was significant whereas self employment experience and years of business education were found to be significantly related with perceived behavioral control. The statistical analysis using partial least square structural equation modelling validated the model. All the three antecedents of entrepreneurial intention were significantly related with entrepreneurial intention. The results of this study will help policy makers to get deep understanding into the phenomenon of entrepreneurship among Saudi university students and thereby develop a conducive environment. This study also validates the entrepreneurial intention model in a different cultural context.

• 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.

• 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.

• 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.

• 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.

• 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 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.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.