• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.665-676
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• 2013

The present study analyzed the KOCCA's Game Immersion data to explore the relationship between psychological traits and game immersion. Psychological traits were classified into four categories; emotional stability, self-esteem, willpower, and happiness. These were put into the multiple regression analysis as the dependent variables with age, sex (dummy), economic status of the homes, variety of leisure activities, friend and family relationship, and time to play games. Four types of immersion (psychological unstability, bad relationship, interrupted daily lives, and failure to control game time and desire) were put into the multiple regression analysis as the independent variables. The multiple regression analysis indicated that the dependent variables predicted the game immersion. Among the psychological traits emotional stability was the strongest factor (negative) that influences the game immersion. Next powerful indicator (negative) among the psychological traits was self-esteem. Based on the findings, measures to alleviate the problems of game immersion and ideas for further research were suggested.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.375-383
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• 2009

This study examined hydraulic characteristics on diagonal weirs with hydraulic experiment and presented a discharge coefficient equation utilizing multiple regression analysis for various design conditions. This study had a object in designing efficiently diagonal weirs utilizing this equation. Diagonal weirs maintained uniformly upstream water level than rectangular suppressed weirs. Also, as installation degrees of diagonal weirs increased, diagonal weirs increased maintenance effects of a upstream water level. Because of these characteristics, diagonal weirs were suitable to canal system. This study presented discharge coefficient equations for diagonal weirs utilizing simple regression analysis. But, these equations are some restrictions on degrees. Therefore, this study presented an equation to estimate directly discharge coefficients to various degrees utilizing multiple regression analysis. This equation was verified by making use of analyses of $R^2$, the sum of residuals, MAPE. Therefore, this equation is enable to make good use of a design in diagonal weirs.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.65-73
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• 2016

The objective of this study was to investigate factors influencing leadership life skills of self esteem and club activities by nursing students. Participants were 331 nursing students in 3 cities. The data were analyzed with the SPSS/Win 20.0 programs, using descriptive statistics, Pearson's correlation coefficients and multiple regression. Findings revealed that; 1) Pearson's correlation revealed a significant association among leadership life skills and self esteem; 2) hierarchical multiple regression analysis showed self esteem and major satisfaction significantly influenced leadership life skills in nursing students. The regression model explained 29.6% of leadership life skills. These findings can be utilized to development of strategies for increasing leadership life skills of nursing students.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.313-320
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• 2013

In this study of tourism destination brand equity and self-consistent interstellar significant attachment relationships and brand equity and behavioral intention was to determine the effect on the relationship. First, the tourism destination brand equity of the self-consistent sex tourists will have a significant impact is to test the hypothesis of a multiple regression analysis was conducted brand equity, loyalty, self image and gender matched only indicates the relationship was significant. Second, self Correspondence tourist destination tourists will have a significant effect on attachment. In order to verify the hypothesis that the multiple regression analysis was conducted for self-Correspondence attachment was significantly related shows. Third, the attachment of tourist destinations for travelers of action also will have a significant impact on. Hypotheses multiple regression analysis was conducted to attachment behavior also shows significant relationship was about.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.64-71
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• 2013

Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle: $10^{\circ}-25^{\circ}$), and 14 severe scoliosis patients (Cobb angle: $25^{\circ}-50^{\circ}$) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement ($R^2$ = 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately $3.2{\pm}1.8$. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.173-181
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• 2019

The purpose of this study was to identify the effects of gender role conflicts, professional nursing value on career preparation behaviors of male nursing university student. Data were collected from 127 male nursing university student in grade 2-4 by using structured questionnaires from July 1 to November 30, 2018. The collected data were analyzed by descriptive statistics, independent t-test, ANOVA, Pearson's correlation coefficients and stepwise multiple regression by using SPSS Win 24.0 program. Multiple regression analysis showed that the predictors of career preparation behaviors were professional nursing values(${\beta}=0.28$, p=.001), satisfaction with major (${\beta}=0.23$, p=.006), club(${\beta}=.19$, p=.020) and the regression equation explained 20.8% of career preparation behaviors. Based on the results of this study, it is necessary to provide career educational programs considering according to the academic year of male nursing students and to develop educational programs to improve the nursing professionalism of male nursing students.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.333-339
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• 2022

In this study, we study the effects of note-taking skills on students' academic performance, satisfaction, and concentration, and immersiveness when students are taking online classes. The Cornell note format was used for the note-taking skills. The survey result shows that note-taking skills in online class increase students' diligence, participation, and concentration. We find a strong positive correlation between the number of Cornell note submission and academic performance, and we show that the association between two is a statistically significant by using simple/multiple regression analysis. The multiple regression result shows that one unit increase in the Cornell note submission is associated with the increase in 0.253 midterm score on average. In addition, one unit increase in the Cornell note submission is associated with increase in 0.287 final exam score on average. Further, we conduct bootstrapping regression as a robustness test and show that the results are consistent with the simple/multiple regression results. These analyses show that Cornell note taking skills in online classes can be beneficial for students to improve the quality of their learning.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.891-897
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• 2021

There is a need for a technology that can quickly and accurately analyze soil carbon contents. Existing soil carbon analysis methods are cumbersome in terms of professional manpower requirements, time, and cost. It is against this background that the present study leverages the soil physical properties of color and water content levels to develop a model capable of predicting the carbon content of soil sample. To predict the total carbon content of soil, the RGB values, water content of the soil, and lux levels were analyzed and used as statistical data. However, when R, G, and B with high correlations were all included in a multiple regression analysis as independent variables, a high level of multicollinearity was noted and G was thus excluded from the model. The estimates showed that the estimation coefficients for all independent variables were statistically significant at a significance level of 1%. The elastic values of R and B for the soil carbon content, which are of major interest in this study, were -2.90 and 1.47, respectively, showing that a 1% increase in the R value was correlated with a 2.90% decrease in the carbon content, whereas a 1% increase in the B value tallied with a 1.47% increase in the carbon content. Coefficient of determination (R²), root mean square error (RMSE), and mean absolute percentage error (MAPE) methods were used for regression verification, and calibration samples showed higher accuracy than the validation samples in terms of R² and MAPE.

• Animal Bioscience
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• v.37 no.6
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• pp.1077-1084
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• 2024

Objective: The present work was conducted to evaluate suitable variables and develop prediction equations using chemical composition and physical characteristics for estimating standardized ileal digestibility (SID) of lysine (Lys) in full-fat soybeans (FFSB). Methods: The chemical composition and physical characteristics were determined including trypsin inhibitor activity (TIA), urease activity (UA), protein solubility in 0.2% potassium hydroxide (KOH), protein dispersibility index (PDI), lysine to crude protein ratio (Lys:CP), reactive Lys:CP ratio, neutral detergent fiber, neutral detergent insoluble nitrogen (NDIN), acid detergent insoluble nitrogen (ADIN), acid detergent fiber, L* (lightness), and a* (redness). Pearson's correlation (r) was computed, and the relationship between variables was determined by linear or quadratic regression. Stepwise multiple regression was performed to develop prediction equations for SID of Lys. Results: Negative correlations (p<0.01) between SID of Lys and protein quality indicators were observed for TIA (r = -0.80), PDI (r = -0.80), and UA (r = -0.76). The SID of Lys also showed a quadratic response (p<0.01) to UA, NDIN, TIA, L*, KOH, a* and Lys:CP. The best-fit model for predicting SID of Lys in FFSB included TIA, UA, NDIN, and ADIN, resulting in the highest coefficient of determination (R² = 0.94). Conclusion: Quadratic regression with one variable indicated the high accuracy for UA, NDIN, TIA, and PDI. The multiple linear regression including TIA, UA, NDIN, and ADIN is an alternative model used to predict SID of Lys in FFSB to improve the accuracy. Therefore, multiple indicators are warranted to assess either insufficient or excessive heat treatment accurately, which can be employed by the feed industry as measures for quality control purposes to predict SID of Lys in FFSB.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.73-87
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• 2016

The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.