• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.643-650
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• 2021

The purpose of this study was to evaluate the impact of lecture content on the overall academic satisfaction in non-contact online classes. The study was conducted using an online survey of 107 university students attending metropolitan, local and foreign universities for a week from August 25th, 2020 to September 2nd, 2020. The analysis methods used included descriptive statistics and chi-square distribution, Fisher's exact test, linear by linear association, and logistic regression. The result of the study showed a significant decrease in Junior by 0.025 times compared to Senior (p<.05). Furthermore, a significant decrease in the impact of recorded lectures by 0.036 times compared to a hybrid of face-to-face and online lectures (p<.05). Compared to the response 'No', the number of student's responses of 'Yes' increased significantly by 31.358 times (p<.05). Additionally, a significant increase was seen in teaching methods by 19.709 times, and academic satisfaction by 7.989 times(p<.05). In conclusion, the results imply that the quality of lecture content is also important to improve the student's satisfaction with school life, but overall management is required in the areas of appropriate teaching methods, appropriate tuition, and evaluation methods.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.47-55
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• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Spatial Information Research
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• v.20 no.3
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• pp.39-50
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• 2012

The objective of this study is the quantitative analysis of climate change effects by performing several statistical analyses with hydrometeorological data sets for past 30 years in Geum river watershed. Temperature, precipitation, relative humidity data sets were collected from eight observation stations for 37 years(1973~2009) in Geum river watershed. River level data was collected from Gongju and Gyuam gauge stations for 36 years(1973~2008) considering rating curve credibility problems and future long-term runoff modeling. Annual and seasonal year-to-year variation of hydrometeorological components were analyzed by calculating the average, standard deviation, skewness, and coefficient of variation. The results show precipitation has the strongest variability. Run test, Turning point test, and Anderson Exact test were performed to check if there is randomness in the data sets. Temperature and precipitation data have randomness and relative humidity and river level data have regularity. Groundwater level data has both aspects(randomness and regularity). Linear regression and Mann-Kendal test were performed for trend test. Temperature is increasing yearly and seasonally and precipitation is increasing in summer. Relative humidity is obviously decreasing. The results of this study can be used for the evaluation of the effects of climate change on water resources and the establishment of future water resources management technique development plan.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.119-127
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• 2009

It has been known that bus route and company related characteristics have influences on punctuality, but fewer research have been conducted. Independent variables used in this study were selected using correlation analysis, and OLS(Ordinary Least Square) and HLM(Hierarchical Linear Model) were employed to identify factors affecting bus punctuality(headway deviation). The results showed that ICC(intraclass Correlation Coefficient) is 0.10, indicating that hierarchical linear models are more adequate for these data because there is effective variation in the subjects between companies. Punctuality was found to be negatively associated with the number of vehicles, the number of persons per vehicle, and total travel time. On the other hand, average headway and company size have a positive relationship with punctuality. Therefore, the number of vehicles per route, average headway, and the number of vehicles managed by a company should be considered for more accurately evaluating the management of piunctuality.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.225-232
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• 2021

The purpose of this study is to identify the psychological characteristics of the elderly and to investigate the variables that affect the life satisfaction of the elderly. To achieve this purpose, psychological characteristics such as self-esteem, alienation, loss, and depression were selected. A survey was conducted on the elderly living in Gwangju Metropolitan City. A total of 218 copies were collected and 203 copies were analyzed, excluding poor responses. To draw the results of the research, quantitative analysis was conducted through questionnaires, and SPSSWIN 21.0 statistical program was used as an analysis tool. The analysis methods were frequency and ratio analysis, technical statistical analysis, bivariate correlation analysis, and linear regression analysis. The results of the analysis are as follows: First, the relationship between the psychological characteristics of the elderly showed significant correlations among the self-esteem, alienation, loss, depression, and life satisfaction of the elderly. Second, for the elderly, alienation and depression had a negative effect on life satisfaction, and self-esteem had a positive effect on life satisfaction. However, loss did not have a significant effect on life satisfaction. In conclusion, it suggests that it is necessary to develop and operate policies and programs to improve self-esteem and reduce alienation and depression in order to improve the quality of life of the elderly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.65-77
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• 2008

The effects of climatic changes owing to urbanization, geographical and topographical conditions on annual and monthly FAO Penman-Monteith (FAO P-M) reference evapotranspiration, and energy and aerodynamic terms of FAO P-M reference evapotranspiration were studied. In this study, 21 climatological stations were selected. The statistical methods applied for trend analysis are Spearman rank test, Sen's test, linear regression analysis and analysis of actual variation ratio. Furthermore, the cluster analysis was applied to cluster 21 study stations by considering the geographical and topographical characteristics of study area. The study results indicate that urbanization affects the trend and amount of FAO P-M reference evapotranspiration, energy term and aerodynamic term; however, the result of Sen's test indicates that urbanization does not significantly affect the magnitude of trend (Sen's slope). The energy term increased at study stations located in coastal area; however, decreased at study stations located in inland area. The topographical slope of study area did not significantly influence on the trend of energy term. The aerodynamic term increased in both coastal area and inland area, indicating much significantly increasing trend in inland area, and it was also affected by the topographical slope of the study area.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.52-68
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• 2014

In this study, we investigated the seasonal variation of SST(Sea Surface Temperature) and thermal effluents estimated by using Landsat-7 ETM+ around the Kori Nuclear Power Plant for 10 years(2000~2010). Also, we analyzed the direction and range of thermal effluents dispersion by the tidal current and tide. The results are as follows, First, we figured out the algorithm to estimate SST through the linear regression analysis of Landsat DN(Digital Number) and NOAA SST. And then, the SST was verified by compared with the in situ measurement and NOAA SST. The determination coefficient is 0.97 and root mean square error is $1.05{\sim}1.24^{\circ}C$. Second, the SST distribution of Landsat-7 estimated by linear regression equation showed $12{\sim}13^{\circ}C$ in winter, $13{\sim}19^{\circ}C$ in spring, and $24{\sim}29^{\circ}C$ and $16{\sim}24^{\circ}C$ in summer and fall. The difference of between SST and thermal effluents temperature is $6{\sim}8^{\circ}C$ except for the summer season. The difference of SST is up to $2^{\circ}C$ in August. There is hardly any dispersion of thermal effluents in August. When it comes to the spread range of thermal effluents, the rise range of more than $1^{\circ}C$ in the sea surface temperature showed up to 7.56km from east to west and 8.43km from north to south. The maximum spread area was $11.65km^2$. It is expected that the findings of this study will be used as the foundational data for marine environment monitoring on the area around the nuclear power plant.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.4
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• pp.325-329
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• 2015

Purpose: The aim of this study was to compare the film thicknesses of several resin cements as a function of time after mixing and to examine the effect of working time on the film thicknesses. Materials and methods: The film thickness (${\mu}m$) of 4 resin cements (n=10), 1 composite resin (Panavia F 2.0), 3 self-adhesive resin (Clearfil SA luting, Zirconite, RelyX U200) cements was measured at 20-second intervals after mixing of the cements up to 200 seconds under a load of 50 N. Linear regression was fitted to verify the effect of working time on the film thickness of each cement. Data were compared to the working time recommended by manufacturers using Wilcoxon test ($\alpha$=.05). Results: All of the materials showed a positive linear correlation between the film thickness and working time. There was no statistically significant difference between the working time based on our results and the values recommended by the manufacturers even though there was a discrepancy between those two values. Conclusion: The film thickness of resin cements could increase with the increase of working time. Working time to meet the ISO standard of $50-{\mu}m$ maximum film thickness could be different from the manufacturer's recommended value.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.353-366
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• 2018

The purpose of this study was assessment the quality of water by using the statistical analysis technique of the Water flow and water quality from January 2012 to December 2016 at the unit basin for total pollutant load management system (TPLMS) in the Imjin River. Water flow and water quality were monitored at an average of 8 day intervals, 11 parameters were used for correlation analysis, principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). The Hierarchical CA was classified into three according to the change of space, such as natural rivers, urban rivers, point with large influence of point pollution source, it was found that the type of contamination source the similarity of water quality affected the classification of cluster. Using one-way analysis of variance (ANOVA) and post-hoc Analysis, there were statistically significant differences between mean values among the clusters. Correlation analysis showed the correlation coefficient between $COD_{Mn}$ and TOC was 0.951 (p<0.01) and the correlation was statistically significantly higher. According to the result PCA and FA, 3 principal components can explaining 72% of the total variations in water quality characteristics and main factor was EC, $BOD_5$, $COD_{Mn}$, TN, TP and TOC indirect indicators of organic matter and nutrients were influenced. This study presented the regression equation obtained by applying the factor scores to the multiple linear regression analysis and concluded that the management Indirect indicators of organic matter and nutrients is important for water quality management in the Imjin River basin.