• Journal of Ginseng Research
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• v.44 no.3
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• pp.413-423
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• 2020

Background: Ginseng berries (GBs) show temporal metabolic variations among different maturation stages, determining their organoleptic and functional properties. Methods: We analyzed metabolic variations concomitant to five different maturation stages of GBs including immature green (IG), mature green (MG), partially red (PR), fully red (FR), and overmature red (OR) using mass spectrometry (MS)-based metabolomic profiling and multivariate analyses. Results: The partial least squares discriminant analysis score plot based on gas chromatography-MS datasets highlighted metabolic disparity between preharvest (IG and MG) and harvest/postharvest (PR, FR, and OR) GB extracts along PLS1 (34.9%) with MG distinctly segregated across PLS2 (18.2%). Forty-three significantly discriminant primary metabolites were identified encompassing five developmental stages (variable importance in projection > 1.0, p < 0.05). Among them, most amino acids, organic acids, 5-C sugars, ethanolamines, purines, and palmitic acid were detected in preharvest GB extracts, whereas 6-C sugars, phenolic acid, and oleamide levels were distinctly higher during later maturation stages. Similarly, the partial least squares discriminant analysis based on liquid chromatography-MS datasets displayed preharvest and harvest/postharvest stages clustered across PLS1 (11.1 %); however, MG and PR were separated from IG, FR, and OR along PLS2 (5.6 %). Overall, 24 secondary metabolites were observed significantly discriminant (variable importance in projection > 1.0, p < 0.05), with most displaying higher relative abundance during preharvest stages excluding ginsenosides Rg1 and Re. Furthermore, we observed strong positive correlations between total flavonoid and phenolic metabolite contents in GB extracts and antioxidant activity. Conclusion: Comprehending the dynamic metabolic variations associated with GB maturation stages rationalize their optimal harvest time per se the related agroeconomic traits.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.598-604
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• 2014

In this paper, we develop stepwise regression data envelopment model to select important variables. We formulate null hypothesis to understand the importance of each variable and use Kruskal-Wallis test for this purpose. If the Kruskal-Wallis test does reject the null hypothesis this will imply there is significant fluctuation in the efficiency score relative to base model. And therefore we have to further check the pair of variables that causes the fluctuation in order to determine its importance using Conover-Inman test. The proposed models helps understand the extent of misclassification decision making units as efficient/inefficient when variables are retained or discarded alongside provides useful managerial prescription to make improvement strategies.

• Applied Chemistry for Engineering
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• v.23 no.1
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• pp.35-41
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• 2012

This paper proposes a new methodology for the real-time on-line quality monitoring of biofuel processes through the integration of infrared spectroscopy and chemometrics. A method of Partial Least Squares (PLS) in Chemometrics is employed for quantitative analysis of key components in bioethanol products. After a number of preprocessing methods and variable importance in projection (VIP) are used, Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed method allows us to economically forecast the concentration of multiple impurities encountered with the production of bioethanol. The proposed system is also accurate enough ($R^2$ > 0.99) to replace the laboratory analysis.

• The Korean Journal of Health Service Management
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• v.3 no.1
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• pp.47-58
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• 2009

This study is to grasp selection factors and habits of information searching of customers of ophthalmic service and to verify the differences in them and to investigate how they affect in selecting medical institute by demographic sociological characters, selection factors by classification and habits of information searching, how many times they used and the type of medical treatment. The result of analysis of importance of selection factors of medical institute, it showed that doctors' career were evaluated high by classification and it showed in order of university hospital, hospital, clinic in facilities and equipment and in order of university hospital, clinic, hospital in distance transportation Analysis of importance of selection factors by sex distinction, it showed that doctors' career were high for both male and female and according to the result of analysis of selection factors by an age, doctors' career variable was measured high and it showed in order of facilities, equipment, distance and convenient transportation. The result of analysis by the form of medical treatment, doctors' career were measured high in all diseases. Facilities and equipment were measured high in case of a corrective operation of eyesight and distance transportation variable showed high in simple eye diseases. According to the result of analysis of habits of searching information by utility frequency, one's own experience in the past(direct visits) was the highest over all and it showed in order of introduction of other ophthalmic department in case of people who go to the institutes many times.

• Journal of Korean Academy of Nursing
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• v.54 no.2
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• pp.193-210
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• 2024

Purpose: The objective of this study was to develop a predictive model for the sexual experiences of adolescents using the random forest method and to identify the "variable importance." Methods: The study utilized data from the 2019 to 2021 Korea Youth Risk Behavior Web-based Survey, which included 86,595 man and 80,504 woman participants. The number of independent variables stood at 44. SPSS was used to conduct Rao-Scott χ² tests and complex sample t-tests. Modeling was performed using the random forest algorithm in Python. Performance evaluation of each model included assessments of precision, recall, F1-score, receiver operating characteristics curve, and area under the curve calculations derived from the confusion matrix. Results: The prevalence of sexual experiences initially decreased during the COVID-19 pandemic, but later increased. "Variable importance" for predicting sexual experiences, ranked in the top six, included week and weekday sedentary time and internet usage time, followed by ease of cigarette purchase, age at first alcohol consumption, smoking initiation, breakfast consumption, and difficulty purchasing alcohol. Conclusion: Education and support programs for promoting adolescent sexual health, based on the top-ranking important variables, should be integrated with health behavior intervention programs addressing internet usage, smoking, and alcohol consumption. We recommend active utilization of the random forest analysis method to develop high-performance predictive models for effective disease prevention, treatment, and nursing care.

• Geomechanics and Engineering
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• v.38 no.5
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• pp.517-528
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• 2024

For numerous tunnelling projects implemented in urban areas due to limited space, it is crucial to take into account the interaction between the foundation, ground, and tunnel. In predicting the deformation of piled foundations and the ground during twin tunnel excavation, it is essential to consider various factors. Therefore, this study derived a prediction model for pile group settlement using machine learning to analyze the importance of various factors that determine the settlement of piled foundations during twin tunnelling. Laboratory model tests and numerical analysis were utilized as input data for machine learning. The influence of each independent variable on the prediction model was analyzed. Machine learning techniques such as data preprocessing, feature engineering, and hyperparameter tuning were used to improve the performance of the prediction model. Machine learning models, employing Random Forest (RF), eXtreme Gradient Boosting (XGB), and Light Gradient Boosting Machine (LightGBM, LGB) algorithms, demonstrate enhanced performance after hyperparameter tuning, particularly with LGB achieving an R² of 0.9782 and RMSE value of 0.0314. The feature importance in the prediction models was analyzed and P_N was the highest at 65.04% for RF, 64.81% for XGB, and P_CTC (distance between the center of piles) was the highest at 31.32% for LGB. SHAP was utilized for analyzing the impact of each variable. P_N (the number of piles) consistently exerted the most influence on the prediction of pile group settlement across all models. The results from both laboratory model tests and numerical analysis revealed a reduction in ground displacement with varying pillar spacing in twin tunnels. However, upon further investigation through machine learning with additional variables, it was found that the number of piles has the most significant impact on ground displacement. Nevertheless, as this study is based on laboratory model testing, further research considering real field conditions is necessary. This study contributes to a better understanding of the complex interactions inherent in twin tunnelling projects and provides a reliable tool for predicting pile group settlement in such scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.47-53
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• 2018

Various types of robotic arms are being used for industrial purposes, particularly with the small production of multi-products, and the importance of the gripper, which can be used in industrial fields, is increasing. This study evaluated a variable stiffness mechanism gripper that can change the stiffness using the nonlinearity of a flexible material. A prototype of the gripper was fabricated and examined to confirm the change in stiffness. The previous gripper was unable to grip objects in some situations with three variable stiffness mechanism. In addition, these mechanisms were not balanced and rarely rotated when the object was gripped. Therefore, a new type of gripper was needed to solve this problem. Inspired by the movements of the human palm and Venus Flytrap, a new type of a variable stiffness soft robot hand was designed. The possibility of grasping could be increased by interlocking the palm folding mechanism by pulling the tendon attached to the variable stiffness mechanism. The soft robotic hand was used to grasp objects of various shapes and weights more stably than the previous variable stiffness mechanism gripper. This new variable stiffness soft robot hand can be used selectively depending on the application and environment to be used.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1365-1372
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• 2018

The purpose of this study is to analyze the importance of the determinants of housing sales agency's role in the sale of apartment housing. For this purpose, a hierarchical decision model was constructed to understand the role and importance of the sales agency. The analytical variable items structured by the research model were set up through literature review, precedent research, and expert brainstorming. The questionnaire consisted of two comparisons for AHP analysis and the importance of absolute importance for fuzzy analysis. Afterwards, the work of correcting the importance was carried out. As a result of the analysis, it was found that the contractor prioritized the sale conditions and the sales agency had priority over the planning for the sale. As a result of analysis, planning of customer pre-sale counseling data, planning of client subscription and contract maximization plan, planning method of advertisement public media method were found to be the most important factors. The results of measurement of absolute importance(fuzzy) & relative importance(,AHP) showed similar tendency. Therefore, it can be seen that the timing of the model house operation is an important period in which the subscription rate depends on the role of the sales agency and the marketing strategy.

• Journal of Educational Research in Mathematics
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• v.14 no.3
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• pp.305-325
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• 2004

This study is on the teaching-learning of parameter concept in secondary school mathematics. In our school mathematics curriculum, parameter concept is explicitly presented at high school mathematics textbook. But student have difficulty in understanding parameter concept because this concept is implicitly used in the textbook from 7-grade mathematics. Moreover, it is true that mathematics teacher give a little attention to student's understanding of parameter con- cept. In this study, we analyzed concept definition of parameter and the extension of parameter on the basis of preceding research, our mathematical curriculum, mathematical dictionaries. After that, we concluded that parameter is explicitly called in t where x= f(t), y= g(t) and parameter is implicitly treated in the learning of relation between quantities in our mathematical curriculum. We pointed to the importance of parameter concept in the successful learning of school algebra. Specially, when the level of algebra is in the learning of relation between quantities, parameter is the key concept for understanding and representing of families of equations or functions. In mathematics class, students have opportunity to reflect that what the role of each variable(parameter, dependent variable, independent variable etc.) is, and where the information which determines it comes from. It is for mathematical communications as well as learning school algebra. Therefore, mathematics teacher's didactical attention is more needed to student have a good concept image of parameter before they learn explicitly its concept definition.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.3
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• pp.19-28
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• 2001

The purpose of this paper is to examine factors affecting user´s satisfaction in development of natural recreation forest(NRF) in order to answer the research question: What is the magnitude of factors affecting user´s satisfaction in development of NRF. After reviewing the literature, mechanism of outdoor recreation, and development factors in NRF, we constructed the conceptual framework and have formulated the hypothesis of this research. we have obtained data through a questionnaire, which surveyed 625 visitors at 10 of the 72 natural recreation forests in Korea in 1999, We have analyzed the data using the mean difference test, Pearson´s correlation analysis, and multiple linear regression method. We found that 1) all the development factors except recreational resources affecting user´s satisfaction have turned out to be statistically significant at one percent level. The direction of relationship between independent variable and dependent variable is the same as that of dependent variable. 2) in bivariate analysis, the relationships between user´s satisfaction and all the development factors are fairly high and statistically significant. The higher the value of development factors, the higher the degree of user´s satisfaction. 3 in multivariate analysis, such variables as the suitability of activities level of services, atmosphere, and facility have been statistically significant at one percent level, and 4) Their relative contribution of the suitability of various recreational activities, level of atmosphere, and service on dependent variable have been turned out to have 8.167, 4.889, 3.333, and 1.611 times more importance than that of the suitabity of recreational resources, respectively. The research results suggest that a guideline for the creation of marketable NFR and development of use-programs and recreational atmosphere be recommended in the planning and development process of NRF, and excessive investment on facilities is not desirable. The approach and analysis method adopted by this research is highly useful for an evaluation criterion of NRF and development of devices for increasing user´s satisfaction in NRF. It is recommended that more empirical study on individual factors affecting user´s satisfaction be performed in the future.