• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.434-448
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• 2011

In this study, an empirical analysis was carried out to determine the effect of tourism motivation for traditional indigenous foods experience tourism on expectation, community attachment and tourism satisfaction in festival event. The result is as follows. First, the effect of tourism motivation for foods experience tourism on expectation of tourism products in experience event showed that exchangeable, educational, aesthetic, derivative and adventurous attributes have a positive effect on expectation of tourism products. Second, the effect of tourism motivation for foods experience tourism on community attachment in experience event showed that exchangeable, educational, aesthetic and derivative attributes have a positive effect on community attachment. Finally, expectation of tourism products and community attachment had a statistically significant effect on community attachment and tourism satisfaction, and tourism satisfaction, respectively. That suggests that the development of various food tourism resources as the tourist value, which can get tourism resources of traditional foods through festival events, could not only introduce tourists to unique food culture, but add the pleasure of delicious food and tourism. Consequently, the preservation, inheritance and development of regional indigenous foods could increased local patriotism, and develop the related industry, maximizing economic effects.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.531-542
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• 2008

The unit root test is the major tool for determining whether we use differencing or detrending to eliminate the trend from time series data. Dickey-Fuller test (Dickey and Fuller, 1979) has the low power of test when the sample size is small or the true coefficient of AR(1) process is almost unit root and the Bayesian unit root test has complicated testing procedure. We propose a new unit root testing procedure, which mixed Bayesian approach with the traditional testing procedure. Using simulation studies, our approach showed locally higher powers than Dickey-Fuller test when the sample size is small or the time series has almost unit root and simpler procedure than Bayesian unit root test procedure. Proposed testing procedure can be applied to the time series data that are not observed as process with unit root.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.323-331
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• 2012

Cell division in biological education is an important and unintelligible unit. Most of students have no interest in learning the content, and don't concentrate on it because cell division unit contains relatively difficult content. In this vein, during considering the effective learning methods, the researcher found role-play as the method for student's positive access to important and unintelligent learning content. Effect of role-play on their learning achievement of science was analysed through the Chapter of cell division on 3rd grade of middle school students. For this study three levels of middle school students were selected from the school located in Seoul. And divided this students into experiment group and control group by 2 classes respectively. Before putting into practice this instruction, there took into account the before and after of students' learning achievement and their learning attitude by using same questionnaire. On the other hand, the researcher put into practice co-variate analysis by using SPSS statistical package as the measurement method.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.139-154
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• 2016

The purpose of this study is to identify the causality between satisfaction /stress with school life and drinking-related behaviors of students majoring in the Dept. of Culinary Arts. The majors taught in college will connect to the job in the future directly. Therefore, in this regard, the results of this study have great importance for Dept. Culinary Arts student training. Results indicated that a positive perception of drinking partially influenced the levels at < ${\beta}=-.219$, p<0.01> a partial impact on school life satisfaction and stress. Negative perceptions also appeared to influence < ${\beta}=.445$, p<0.01> and < ${\beta}=.213$, p<0.01> levels of satisfaction and stress. Therefore, drinking behavior appears to affect the college life experience stress. Schools will have to incorporate this as part of the curriculum to correct the drinking behavior of students.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.323-330
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• 2008

Since complex diseases are caused by interactions of multiple genes, traditional statistical methods are limited in its power to predict the onset of a complex disease. Recently new approaches using machine learning techniques are introduced. Neural nets are a suitable model to find patterns in complex data. When large amount of data are fed into a neural net, however, it takes a long time for learning and finding patterns. In this study we suggest a new model that combines the set association, which is a statistical technique to find important SNPs associated with complex diseases, and neural network. We experiment with SNP data related to asthma to test the effectiveness of our model. Our model shows higher prediction accuracy and shorter execution time than neural net only. We expect our model can be used effectively to predict the onset of other complex diseases.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.125-133
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• 2014

This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which demonstrated high efficiency, can certainly provide great help in decision making in the field of hotel management and in deciding on the bankruptcy or financial solidity of each branch of serviced residence hotel.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.7
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• pp.537-546
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• 2020

The reliability used as a performance indicator during the development of space launch vehicle should be validated by the launch success probability, and the launch data need to be fed back for reliability management. In this paper, the launch data of space launch vehicles around the world were investigated and statistically analyzed for the success probabilities according to the launch vehicle models and maturity. The Bayesian estimation of launch success probability was reviewed and analyzed by comparing the estimated success probabilities using several prior distributions and the statistical success probability. We presented the method of generating prior distribution function and considerations for Bayesian estimation.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.211-224
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• 2016

The purpose of this study were to devise prerequisite learning reminding model to elementary mathematics classes and actually apply it to fifth graders in experimental lessons, thus investigating their effects on mathematics academic achievement and self-efficacy. the study conducted a pre and post test to measure academic achievement and self-efficacy on the experiment and control group. the finding were as follows. First, the study found significant differences in mathematics academic achievement between the experiment and control group. mathematics lessons based on the prerequisite learning reminding model resulted in no significant differences among the upper and lower level groups. Secondly, the study analyzed the effects of prerequisite learning reminding model on the self-efficacy and found significant differences in self-efficacy between the experiment and control group. While there were no differences in self-confidence and preference for task difficulty among the subarea of self-efficacy, it had positive differences effect on self-regulation efficacy.

• Journal of the Korean Chemical Society
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• v.56 no.4
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• pp.500-508
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• 2012

The purpose of this study was to investigate the impact of multimodal representation-based lesson on embeddedness of multimodal representation in high school students' writing. The participants in this study were two groups of second-year science-track students (74 students) at an academic high school in a metropolitan city. One group (41 students) was assigned to the experimental group, the other group (33 students) was assigned to the comparative group. Data analysis showed that the students of the experimental group were better at utilizing and embedding multimodal representations. Thus, the conclusion was drawn that multimodal representation-based lesson had an effect on high school students' embeddedness of multimodal representation.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.65-71
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• 2012

Recently the high-resolution satellite images are helpfully using the land cover, status data for the natural resources or environment management. The effective satellite analysis process for these satellite images that require high investment can be increase the effectiveness has become increasingly important. In this Study, the statistical value of the training data is calculated and analyzed during the preprocessing. Also, that is explained about the maximum likelihood classification of traditional classification method, artificial neural network (ANN) classification method and Support Vector Machines(SVM) classification method and then the IKONOS high-resolution satellite imagery was produced the land cover map using each classification method. Each result data had to analyze the accuracy through the error matrix. The results of this study prove that SVM classification method can be good alternative of the total accuracy of about 86% than other classification method.