• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.631-642
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• 1998

Fall-out particles were collected by the modified British deposit gauges at 35 sampling sites in Suwon area from January to November, 1996. Twenty chemical species (Al. Ba, Cd, Cr, K, Pb, Sb, Zn, Cu, Fe, Ni, V, F-, Cl-, NO3-, 5042-, Na+, NH4+, Mg2+, and Ca2+) were analyzed by AAS and If. The purposes of this study were to estimate qualitatively various emission sources of the fell-out particle by applying multivariate statistical techniques such as factor analysis, multiple regression analysis, and discriminant analysis. During the study, outlier sites were determined by a z-score method. Cl-, Na+, Mg2+, and SO42- were highly correlated due to their common marine related source. Wind speed was the most influential factor for the deposition fluxes of the particle itself and all the chemical species as well. When applying the factor analysis, 8 source patterns were qualitatively obtained, such as marine source, soil source, oil burning source, Cr related source, tire source, Cd related source, agriculture source, and F- related source. As a result of the multiple regression analysis, we could suggest that some chemical compounds may possibly exist in the form of CaSO4, NaN03, NaCl, MgC12, (NH4)2SO4, NaF, and CaCl2 in the fall-out particles. Finally, spatial and seasonal classification study performed by a discriminant analysis showed th.at SO42-, Ca2+, Cl-, and Fe were dominant in the group of spatial pattern; however, SO42-, Cl-, Al, and V were in the group of seasonal pattern.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.3
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• pp.395-406
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• 2015

This research carried out an analysis on input cost and leakage reduction effect by leakage reduction method, focusing on the project for establishing an optimal water pipe network management system in the Taebaek region, which has been executed annually since 2009. Based on the result, optimal cost-benefit analysis models for water distribution network rehabilitation project were developed using DEA(data envelopment analysis) and multiple regression analysis, which have been widely utilized for efficiency analysis in public and other projects. DEA and multiple regression analysis were carried out by applying 4 analytical methods involving different ratios and costs. The result showed that the models involving the analytical methods 2 and 4 were of low significance (which therefore were excluded), and only the models involving the analytical methods 1 and 3 were suitable. From the result it was judged that the leakage management method to be executed with the highest priority for the improvement of revenue water ratio was installation of pressure reduction valve, followed by replacement of water distribution pipe, replacement of water supply pipe, and then leakage detection and repair; and that the execution of leakage management methods in this order would be most economical. In addition, replacement of water meter was also shown to be necessary in case there were a large number of defective water meters.

• Korean Journal of Human Ecology
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• v.20 no.6
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• pp.1135-1151
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• 2011

This study examined green consumption behavior according to the lifestyles of college students. The data were collected from 314 college students in Yeungnam region by a self-administered questionnaire. Frequencies, Cronbach's alpha, factor analysis, cluster analysis, chi-square tests, one-way analysis of variance, Duncan's multiple range tests, Pearson's correlation analysis, and multiple regression analyses were conducted by SPSS Windows V.18.0. According to the result of factor analysis, lifestyles were categorized into six factors: thrift-saving type, enthusiastic activity type, brand ostentation type, freedom-seeking type, material oriented type, and practice-seeking type. Cluster analysis showed respondents belonged to one of four groups: thrift practice group, indifference group, freedom-seeking group, and material ostentation group. The levels of green purchase behavior, green usage behavior and green disposal behavior of the respondents was not high. The thrift practice group showed higher levels of green purchase behavior, green usage behavior, and green disposal behavior. Finally, according to multiple regression analyses, environmental consciousness, knowledge about green consumption, lifestyle groups were the significant factors affecting green consumption behaviors. These results imply that green consumption education for college students should be activated to induce green life.

• 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.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.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.129-141
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• 2019

In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures.

• 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.