• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.

• Journal of the Korean Society of Food Culture
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• v.17 no.2
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• pp.120-130
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• 2002

The purpose of this study is to investigate whether a group of predictor variables which constitute four determinants of dining satisfaction do exert a significant influence on messures of dining satisfaction in family restaurant. Canonical correlation analysis is used to achieve the purpose of this study. This technique enables the researcher to test for the effects of a set of predictor variables upon a multidimensional measure of dining satisfaction in family restaurant. Results suggest that multiple determinants are important in determining dining satisfaction in family restaurant. No one determinant can fully explain its complexities. The four determinants also appear to vary in terms of importance. Individual variables within four determinants also appear to vary in terms of importance. Finally, the results of the study provide some insight into the types of marketing strategies that can be successfully used by operators who manage family restaurants.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.18-27
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• 2022

Construction accidents are difficult to prevent because several different types of activities occur simultaneously. The current method of accident analysis only indicates the number of occurrences for one or two variables and accidents have not reduced as a result of safety measures that focus solely on individual variables. Even if accident data is analyzed to establish appropriate safety measures, it is difficult to derive significant results due to a large number of data variables, elements, and qualitative records. In this study, in order to simplify the analysis and approach this complex problem logically, data preprocessing techniques, such as latent class cluster analysis (LCCA) and predictor importance were used to discover the most influential variables. Finally, the correlation was analyzed using an alluvial flow diagram consisting of seven variables and fourteen elements based on accident data. The alluvial diagram analysis using reduced variables and elements enabled the identification of accident trends into four categories. The findings of this study demonstrate that complex and diverse construction accident data can yield relevant analysis results, assisting in the prevention of accidents.

• The Korean Journal of Food & Health Convergence
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• v.8 no.2
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• pp.15-27
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• 2022

This study aims to analyze the relative importance of bone age and chronological age in physique according to gender and to identify the relative importance of bone age, chronological age, and physique in physical fitness and motor coordination according to gender in order to alleviate the imbalance between physique and physical fitness in children. A total of 666 children(346 males, 320 females) between the ages of 11-14 were enrolled as subjects, and the skeletal maturation The skeletal maturation were measured by taking hand-wrist. Physical fitness were measured through a total of 4 components: muscular strength. The results of this study. First, physique variables for both males and females aged 11-14 were found to be more significant predictors of bone age than chronological age. Second, for physical fitness in males, in the order of %fat, body water, waist-hip ratio, weight, fat-free mass, and chronological age were more significant predictor variables; and in females, in the order of %fat, fat-free mass, height, chronological age, weight, bone age, fat mass, and body water were more significant predictor variables. For bone age and chronological age in physical fitness, bone age in males and chronological age in females found to be the more representative variables respectively.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.177-190
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• 2021

Random forests is a popular method that improves the instability and accuracy of decision trees by ensembles. In contrast to increasing the accuracy, the ease of interpretation is sacrificed; hence, to compensate for this, variable importance is provided. The variable importance indicates which variable plays a role more importantly in constructing the random forests. However, when a predictor is correlated with other predictors, the variable importance of the existing importance algorithm may be distorted. The downward bias of correlated predictors may reduce the importance of truly important predictors. We propose a new algorithm remedying the downward bias of correlated predictors. The performance of the proposed algorithm is demonstrated by the simulated data and illustrated by the real data.

• Korean Journal of Child Studies
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• v.20 no.3
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• pp.199-216
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• 1999

The 121 five-year-old Korean subjects of this study were divided in 3 groups based on their experience in learning a foreign language (English). A battery of tests was administered to measure spoken and written language ability and the 3 metalinguistic domains of phonological, semantic, and syntactic awareness. Spoken language ability was positively correlated with semantic and syntactic awareness. The relative importance of each metalinguistic domain varied with level of written language development. Phonological awareness was the only predictor of decoding. Syntactic awareness and phonological awareness were significant variables in sentence comprehension. Metalinguistic ability was a better predictor of written language development than spoken language ability. Foreign language learning experience had an effect on syntactic awareness: low experience was superior to no experience, but high experience was not superior to low experience.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.185-193
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• 2009

Machine learning methods such as support vector machines and random forests yield nonparametric prediction functions of the form y = $f(x_1,{\ldots},x_p)$. As a sequel to the previous article (Huh and Lee, 2008) for visualizing nonparametric functions, I propose more sensible graphs for visualizing y = $f(x_1,{\ldots},x_p)$ herein which has two clear advantages over the previous simple graphs. New graphs will show a small number of prototype curves of $f(x_1,{\ldots},x_{j-1},x_j,x_{j+1}{\ldots},x_p)$, revealing statistically plausible portion over the interval of $x_j$ which changes with ($x_1,{\ldots},x_{j-1},x_{j+1},{\ldots},x_p$). To complement the visual display, matching importance measures for each of p predictor variables are produced. The proposed graphs and importance measures are validated in simulated settings and demonstrated for an environmental study.

• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.3
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• pp.387-395
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• 2016

Purpose: The purpose of this study was to identify factors associated with performance of nursing care for postoperative delirium of elderly patients among recovery room nurses. Methods: The research was a cross-sectional, descriptive design using questionnaires. The participants were 99 nurses from five urban recovery rooms. Data were analyzed using descriptive statistics, t-test, ANOVA and multiple regression with SPSS WIN 21.0. Results: The performance level of delirium nursing care was low because its mean score was 3.80 out of 5. Performance of nursing care was significantly positively correlated with the importance of nursing care and self-efficacy. Stepwise multiple regression analysis for performance of nursing care revealed that the most powerful predictor was the importance of nursing care. The importance of nursing care and self-efficacy explained 32.3% of the variance. Conclusion: The results indicate a need to enhance the performance of nursing care for postoperative delirium of elderly patients among recovery room nurses. The findings also suggest that consideration be given to strategies for improving the importance of nursing care and self-efficacy in developing programs to enhance the performance level of nursing care for elderly patients with postoperative delirium.

• English Language & Literature Teaching
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• v.7 no.2
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• pp.77-102
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• 2002

Factors affecting foreign language learning task are diverse in nature due to the different social and cultural backgrounds so that learners have to somehow use strategies and expressions to adjust diverse factors to their learning environments. The main purpose of this paper is to show how important NNS vs. NNs interaction through CCDL can be in their enhancement of English proficiency by giving examples from their chatting conversation(written conversation) data collected for over two semesters. Chatting as a means of synchronous communication interaction between students from two different cultural backgrounds can act as a predictor of foreign language achievement. Chatting and Telemeet activities have their own advantages in enhancing communicative competence when learning English. By engaging in these synchronous communication activities learners of English from different cultural backgrounds can acquire unique strategies and expressions from which they learn from each other. In short, this study advocates the importance of strategies and patterns foreign language learners can acquire from interaction among culturally different peer groups.

• The Research Journal of the Costume Culture
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• v.6 no.2
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• pp.92-108
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• 1998

The purpose of this study was designed a) to examine the relative importance for college students' clothing disposal causes and their factor structure: b) to test the effects of gender, clothing satisfaction and family income on clothing disposal determinants; and c) to assess the relationship between clothing purchase determinants and overall clothing satisfaction and clothing disposal determinants. Data (n=660) were collected from college students in Cheju Do. The survey questionnaire composed of a revised Clothing Disposal Determinants Scale, Clothing Purchase Determinants Scale and background variables. First, the most important reasons for clothing disposal were to unfit with body change, get washed our and raise nap on clothe, wornout with long-term use, do not ware for new purchasing clothe, uneasy on wear. Second, factor analysis of the revised Clothing Disposal Determinants Scale revealed five factors; unfitness, fashion change, quality dissatisfaction, product efficiency decrement, and maintenance/inconvenience. Third, female students perceived significantly higher in fashion change and unfitness than male students. Forth, unfitness and product efficiency decrement were significantly discriminated between between clothing satisfaction groups, unfitness and fashion change variables were significantly discriminated between family income groups. fifth, impulsive purchase factor was the best predictor of composite clothing disposal measure, followed by individuality, clothing satisfaction, practicality. The best predictors of each disposal factors were individuality oriented purchasing criterion in unfitness factor. Fashion in fashion change, impulsive purchase in quality dissatisfaction and product efficiency decrement factors, and practicality in maintenance/inconvenience factor. As a whole, the most consistent predictor of clothing disposal determinants was impulsive purchase factor.