• Journal of Korean Home Economics Education Association
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• v.13 no.3
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• pp.103-118
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• 2001

The purpose of this study was to analyze the casual relationship of the background variables. 4-value orientations. 5 money spending styles and the money management behavior of high school girls. The subjects were 498 high school girls. We used Cronbach\` $\alpha$. Pearson correlation coefficients multiple regression and path analysis as statistical analysis. The results were summarized as follows Resulting from path analysis, the money spending styles were the most influential variable on money management behavior and value orientations were more influential variable on the money spending styles rather than the money management behavior. The money management behavior of high school girls had the directive linear relationships with the variables such as goal-oriented value and 4 money spending styles-security conspicuous. non-monetary and unconcerned.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.9-18
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• 2020

This study seeks to analyze the effect of Non-Performing Loans and Capital Adequacy Ratio on Return on Assets on ten conventional banks listed on the Indonesia Stock Exchange (BEI-IDX). This study uses secondary panel data for 2015-2019 in the form of CAR and NPL values from ten conventional banks listed on the BEI-IDX during the 2020 observation period. The research approach is quantitative descriptive with data analysis methods, namely, linear regression. The testing phase of this study includes: transform value, F-test, T-test and hypothesis test with significancy level sig < 0.05. The results of this study reveal that Non-Performing Loans had a significant negative effect (t = -2,637) (0.011 <0.0) on Return on Assets, while Capital Adequacy Ratio has no significant effect on ROA (0.760 > 0.05). R2 value is 0.128 or 12.8%. It has a significant effect on variables, calling efforts by banks, governments, and authorities monetary of related institutions to maintain the stability of finance. The reduction of Non-Performing Loan impacts on assets and capital adequacy ratio, besides, the normal NPL will control the stability of finance. If a balance is created either in the form of values or amounts of the variables, the reduction in Non-Performing Loans will be controlled.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.128-135
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• 2007

In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed. Therefore, effects have been made to build an air/water temperature relationship at three study regions using the data collected by the Ministry of the Maritime Affairs and Fisheries (MOMAF). The air/water relationship varies with time-scale and weekly time-scale was chosen for the study. The data were fitted to the S-shaped non-linear relationship, and the parameters for the S-curve were derived using a single-criteria multi-parameter optimization scheme. Separate regression curves were fitted to consider seasonal hysteresis at the Masan site. The study results support the S-shaped non-linear relationship is the best fit for the air/water relationship at the Korean coastal zone. This study will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.307-313
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• 2022

Although telecommuting of SMEs has been activated due to the COVID-19 phenomenon, the security model for this is insufficient. Accordingly, the study was divided into threats centered on smartphones and threats centered on smartphone users. As a result of the study, one-third of SMEs are working from home. At this company with 100 employees, more than 50% of them work from home.and In the metal, machinery and chemical industries with factories, 20% of them work from home. As a result of analyzing the correlation between telecommuting according to the presence or absence of a factory, the correlation coefficient (r=-.385) has a clear linear relationship. And, as a result of the regression analysis, the R-squared value was 0.148, so companies with factories are highly related to telecommuting. In other words, we found that SMEs with factories do not want to work from home. In addition, as a result of analyzing the level of security threats, there were great concerns about theft, hacking, and phone taking during remote work. As limitations of the study, there were difficulties in selecting SMEs from the population in a non-face-to-face work environment, and there were limitations in the questionnaire items for deriving a non-face-to-face work environment.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.1
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• pp.28-34
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• 2015

Pulse wave velocity (PWV) is used to non-invasively estimate the severity of arteriosclerosis by measuring arterial stiffness. Increased arterial stiffness measured by PWV stands for progressive arteriosclerosis and is caused by atherosclerotic risk factors. This study is focused on how brachial-ankle pulse wave velocity (baPWV) is related to the leading risk factors for arteriosclerosis or atherosclerosis. Subjects were 114, 69 males and 45 females who are in 60's and had baPWV test for acute stroke. The results are as follows: the group with increased arterial stiffness showed significant increase in HbA1c, total cholesterol, BSBP (brachial artery systolic blood pressure), BDBP (brachial artery diastolic blood pressure), CSBP (central artery systolic blood pressure), CDBP (central artery diastolic blood pressure), augmentation index (AIx) and diabetes mellitus. Correlation analysis between baPWV and atherosclerotic risk factor showed significant relationship in age, HbA1c, LDL cholesterol, BSBP, BDBP, CSBP, CDBP and augmentation index. baPWV was independently related to age and BSBP in multiple linear regression analysis. The group with increased arterial stiffness was independently related to BDBP in multiple logistic regression analysis. This study might be meaningful in evaluating the relationship between arterial stiffness and atherosclerotic risk factor in a new way, and be helped to make various studies for cardiovascular disease.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.21-29
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• 2018

In many companies handling flammable liquids, explosion-proof electrical equipment have been installed according to the Korean Industrial Standards (KS C IEC 60079-10-1). In these standards, hazardous area for explosive gas atmospheres has to be classified by the evaluation of the evaporation rate of flammable liquid leakage. The evaporation rate is an important factor to determine the zones classification and hazardous area distance. However, there is no systematic method or rule for the estimation of evaporation rate in these standards and the first principle equations of a evaporation rate are very difficult. Thus, it is really hard for industrial workplaces to employ these equations. Thus, this problem can trigger inaccurate results for evaluating evaporation range. In this study, empirical models for estimating an evaporation rate of flammable liquid have been developed to tackle this problem. Throughout the sensitivity analysis of the first principle equations, it can be found that main factors for the evaporation rate are wind speed and temperature and empirical models have to be nonlinear. Polynomial regression is employed to build empirical models. Methanol, benzene, para-xylene and toluene are selected as case studies to verify the accuracy of empirical models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.157-165
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• 2016

Among high-tech products, the mobile phone has experienced a rapid rate of innovation and a shortening of its product life cycle. The shortened product life cycle poses major challenges to those involved in the creation of forecasting methods fundamental to strategic management and planning systems. This study examined whether the best model applies to the entire diffusion life span of a mobile phone. Mobile phone sales data from a specific mobile service provider in Korea from March of 2013 to August of 2014 were analyzed to compare the performance of two S-shaped diffusion models and two non-linear regression models, the Gompertz, logistic, Michaelis-Menten, and logarithmic models. The experimental results indicated that the logistic model outperforms the other three models over the fitted region of the diffusion. For forecasting, the logistic model outperformed the Gompertz model for the period prior to diffusion saturation, whereas the Gompertz model was superior after saturation approaches. This analysis may help those estimate the potential mobile phone market size and perform inventory and order management of mobile phones.

• Imaging Science in Dentistry
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• v.49 no.1
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• pp.19-26
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• 2019

Purpose: It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods: Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results: The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion: The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.4
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• pp.1-10
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• 2023

As a result of climate change, non-point source pollution (NPS) from farmland with the steep slope during the rainy season is expected to have a significant impact on the water system. This study aimed to evaluate the effect of furrow mulching using alfalfa and PAM (Polyacrylamide) materials for each rainfall event, while considering the load characteristics of NPS. The study was conducted in Wanju-gun, Jeollabuk-do, in 2022, with a testbed that had a slope of 13%, sandy loam soil, and maize crops. The testbed was composed of four plots: bare soil (Bare), No mulching (Cont.), Vegetation mulching (VM), and PAM mulching (PM). Runoff was collected from each rainfall event using a 1/40 sampler and the NPS load was calculated by measuring the concentrations of SS, T-N, T-P, and TOC. During farming season, the reduction efficiency of NPS load was 37.1~59.5% for VM and 38.2~75.7% for PM. The analysis found that VM had a linear regression correlation (R²=0.28~0.86, P-value=0.01~0.1) with elapsed time of application, while PM had a quadratic regression correlation (R²=0.35~0.80, P-value=0.1). These results suggest that the selection of furrow mulch materials and the appropriate application method play a crucial role in reducing non-point pollution in farmland. Therefore, further studies on the time-series reduction effect based on the application method are recommended to develop more effective preemptive reduction technologies.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1071-1078
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• 2014

Recently, information providing service using Big Data is being expanded. Big Data processing technology is actively being academic research to an important issue in the IT industry. In this paper, we analyze a skilled pattern of welder through Big Data analysis or extraction of welding based on R programming. We are going to reduce cost on welding work including weld quality, weld operation time by providing analyzed results non-skilled welder. Welding has a problem that should be invested long time to be a skilled welder. For solving these issues, we apply connection rules algorithms and regression method to much pattern variable for welding pattern analysis of skilled welder. We analyze a pattern of skilled welder according to variable of analyzed rules by analyzing top N rules. In this paper, we confirmed the pattern structure of power consumption rate and wire consumption length through experimental results of analyzed welding pattern analysis.