• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.1-12
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• 2004

In this paper, we consider choosing the appropriate covariance structure for analyzing repeated measures data with three repeat factors from a study of blood pressure data, which is collected from the local residents of Yangpyeong, Gyeonggi-do (2001) and fitted linear mixed models to find the significant covariates on outcome variable(Blood Pressure)

• Korean small business review
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• v.41 no.3
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• pp.49-75
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• 2019

Market instability offers opportunities as well as the need for careful innovation strategies and learning for a company's survival. Companies that find new opportunities decide to carry out innovation and decide on the size of their investments by considering their position in the market they are aiming for and the intensity of competition. This study was conducted to check whether obstacles to innovation face by SMEs in the manufacturing sector vary depending on the stage of corporate growth and to identify the impact of the government support system on the decision-making process on the performance of innovation. According to the analysis, there were differences in obstacles to innovation depending on the stage of corporate growth. It was found that more innovative SMEs are, more obstacles they face, and to overcome such obstacles, they try to access government support systems more. In addition, the use of a government support system eliminated obstacles to innovation, and the positive and significant effects of investing in innovation were identified. This study is meaningful in that it explicitly approached these hypotheses by applying a multistage model to the process of innovation carried out by SMEs in the manufacturing sector.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Korean Library and Information Science Society
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• v.40 no.1
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• pp.433-449
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• 2009

The purpose of this study is to find out the factors which have interrupted Library Assisted Instruction in various schools' libraries and to analyze the factors by the tools and to propose the solutions to the obstacles for the desired Library Assisted Instruction. For doing this, some experimental processes had been made: firstly, to make the analysis model based on HPT for the improvement of the real LAI, secondly, to apply the model to LAI, to draw out the problems and to analyze them, and to propose the solutions. As the results of this study, the 5 solutions are presented; 1) LAIs should have the obvious and concrete teaching&learning objectives. 2) The supporting systems for LAI like the web community ought to be prepared. 3) External motivation systems, that is, teachers and teacher-librarians' performance assessment with LAI participation rate per year, should be developed. 4) The various, practical LAI programs should be developed. 5) The obscure refusal of teachers & teacher-librarians to LAI should be disappeared and the directors of schools should be confident of the LAI's educational, positive effects.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.331-339
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• 2020

The purpose of this study was to develop and validate future teacher competencies diagnosis tools required for pre-service teachers. In this study, the hypothesis model was established by hierarchizing basic competency and job competency in three dimensions such as knowledge, practice, and personality as teachers' competencies required in future society. Based on this hypothesis model, 54 preliminary questions were developed, and competencies diagnosis test was conducted for 237 pre-service teachers in J area, Korea. The results of this study are as follows: First, as a result of this study, a total of 53 questions were extracted, including 18 questions with 6 factors in the knowledge dimension, 17 questions with 6 factors in the practice dimension, and 18 questions with 6 factors in the personality dimension. Second, the goodness-of-fit of future teacher competencies diagnosis model required was verified, and convergence and discriminant validity were verified. The results of this study were discussed. Finally, the implications and suggestions for further research were presented.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.177-187
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• 2023

This study aims to validate a tool evaluating MOOCs for higher education from the perspective of education service. Based on the results of related researches, a potential model for evaluating MOOCs (4 factors and 8 sub-factors) was made. An evaluation tool consisting of 18 survey items was delivered to 138 college students. After data cleaning, 136 surveys were used for exploratory factor analysis (principal component analysis. varimax rotation) and reliability analysis that confirmed the fitness of the potential model. Four exploratory constructs and seven sub-factors were extracted: Factor I was labeled as 'Systemic Learning Experience,' Factor II, 'Value Experience,' Factor III, 'Co-creation of Value Experience,' and Factor IV, 'High Order Learning Experience.' Reliability estimates using Cronbach's alpha indicated that the evaluation tool had good internal consistency. In conclusion, the evaluation tool for MOOCs in higher education was proven to be valid and reliable.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.133-143
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• 2014

The paper uses a panel gravity model to analyse the determinants of export via Gwangyang port for the period from 2000-2012. The gravity model includes export via Gwangyang port, GDP and population of trading partners, the distances between Korea and its partners, and Korea-ASEAN FTA dummy. Hausman test shows up which one is exactly appropriate between random effect estimation and fixed effect estimation to use panel dataset. It depends on whether or not existence or nonexistence of the correlation between unobserved omitted factors and variables. Fixed effect estimation is suitable for this paper by the rejection of null hypothesis. An Empirical analysis of this paper shows GDP influences positive effects and distance influences negative effects to Gwangyang port trading partners. In addition, the results strongly supported the effects of Korea-ASEAN FTA on the growth of Gwangyang port export.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.195-220
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• 2020

The purpose of this study was to validate the Korean version of the post-traumatic growth inventory-expanded(K-PTGI-X), which has been widely used to assess posttraumatic growth. The PTGI-X is a measure of the addition of the items to measure the existential growth as the need for modification to the factors of the 'increase of spiritual interest' in the existing PTGI is suggested. We examined the factor structure, reliability, and validity of a Korean version of the PTGI-X among 625 Korean adults who have experienced trauma events. First, EFA confirmed the appropriate PTGI-X factor structure and found that the 4-factor structure was the most appropriate. Next, as a result of CFA, it was found that the model to which correlation between items was added to the 4-factor model was good. Next, testing internal consistency, CR, and AVE of the K-PTGI-X showed that PTGI-X's items are reliable. Also, we tested the concurrent validity and discriminative validity. All of the K-PTGI-X scales significantly correlated with measures of deliberate rumination and core-belief except for the intrusive rumination. Finally, to add an understanding of K-PTGI-X, t-test according to demographic variables was conducted. Recommendations for future research and implications were discussed.