• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.188-205
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• 2024

The food truck business, which involves selling various types of food from mobile vehicles, has gained significant popularity in urban centers and at events. These food trucks have rapidly expanded due to their relatively low initial investment and high flexibility, attracting customers with unique menus and personalized services. However, as competition increases, the need to manage service quality to boost customer satisfaction and encourage repeat visits has become more critical. Despite this growing importance, there has been limited empirical research on the topic. This study aims to analyze customer experiences with food truck services to gain strategic insights for improving service quality. By applying structural topic modeling to customer review data, the study identified 50 key topics. The process included a comprehensive evaluation of model diagnostics and interpretability to determine the optimal number of topics, ultimately selecting the most relevant ones related to service experiences. The impact of these identified topics on overall customer satisfaction was empirically tested using regression analysis. The results showed that aspects such as "Food Taste," "Friendly Staff," and "Positive Emotion" had a positive influence on customer satisfaction, whereas "Delayed Service," "Negative Emotion," and "Beverage Service" had a negative impact. Based on this analysis, the study proposes concrete methods for food truck operators to systematically analyze customer feedback and use it to drive service improvements and innovation. This research highlights the importance of data-driven decision-making in small business environments like food trucks and contributes to expanding the application of topic modeling in the service industry.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.9
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• pp.955-960
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• 2008

We investigated and estimated at the characteristics of decomposition and mineralization of benomyl using a design of experiment(DOE) based on the general factorial design in an E-beam process, and also the main factors(variables) with benomyl concentration(X$_1$) and E-beam irradiation(X$_2$) which consisted of 5 levels in each factor was set up to estimate the prediction model and the optimization conditions. At frist, the benomyl in all treatment combinations except 17 and 18 trials was almost degraded and the difference in the decomposition of benomyl in the 3 blocks was not significant(p > 0.05, one-way ANOVA). However, the % of benomyl mineralization was 46%(block 1), 36.7%(block 2) and 22%(block 3) and showed the significant difference of the % that between each block(p < 0.05). The linear regression equations of benomyl mineralization in each block were also estimated as followed; block 1(Y$_1$ = 0.024X$_1$ + 34.1(R$^2$ = 0.929)), block 2(Y$_2$ = 0.026X$_2$ + 23.1(R$^2$ = 0.976)) and block 3(Y$_3$ = 0.034X$_3$ + 6.2(R$^2$ = 0.98)). The normality of benomyl mineralization obtained from Anderson-Darling test in all treatment conditions was satisfied(p > 0.05). The results of prediction model and optimization point using the canonical analysis in order to obtain the optimal operation conditions were Y = 39.96 - 9.36X$_1$ + 0.03X$_2$ - 10.67X$_1{^2}$ - 0.001X$_2{^2}$ + 0.011X$_1$X$_2$(R$^2$ = 96.3%, Adjusted R$^2$ = 94.8%) and 57.3% at 0.55 mg/L and 950 Gy, respectively. A Microtox test using V. fischeri showed that the toxicity, expressed as the inhibition(%), was reduced almost completely after an E-beam irradiation, whereas the inhibition(%) for 0.5 mg/L, 1 mg/L and 1.5 mg/L was 10.25%, 20.14% and 26.2% in the initial reactions in the absence of an E-beam illumination.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.661-670
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• 2020

The water supply system has a wider installation range and various components of it than other infrastructure, making it difficult to secure stability against earthquakes. Therefore, it is necessary to develop methods for evaluating the seismic performance of water supply systems. Ground Motion Prediction Equation (GMPE) is used to evaluate the seismic performance (e.g, failure probability) for water supply facilities such as pump, water tank, and pipes. GMPE is calculated considering the independent variables such as the magnitude of the earthquake and the ground motion such as PGV (Peak Ground Velocity) and PGA (Peak Ground Acceleration). Since the large magnitude earthquake data has not accumulated much to date in Korea, this study tried to select a suitable GMPE for the domestic earthquake simulation by using the earthquake data measured in Korea. To this end, GMPE formula is calculated based on the existing domestic earthquake and presented the results. In the future, it is expected that the evaluation will be more appropriate if the determined GMPE is used when evaluating the seismic performance of domestic waterworks. Appropriate GMPE can be directly used to evaluate hydraulic seismic performance of water supply networks. In other words, it is possible to quantify the damage rate of a pipeline during an earthquake through linkage with the pipe failure probability model, and it is possible to derive more reasonable results when estimating the water outage or low-pressure area due to pipe damages. Finally, the quantifying result of the seismic performance can be used as a design criteria for preparing an optimal restoration plan and proactive seismic design of pipe networks to minimize the damage in the event of an earthquake.

• Korean Journal of Culture and Social Issue
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• v.28 no.2
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• pp.187-217
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• 2022

The aim of this study is to examine the psychometric properties of the Korean version of the Post-traumatic Stress Disorder Checklist for DSM-5(PCL-5). For this purpose, online surveys were conducted for two times with a one year interval using the data from 1,077 Korean adults at time 1, and 563 Korean adults at time 2. First, from the result of the confirmatory factor analysis, comparing the model fit of the 1, 4, 6, and 7-factor model, the 4, 6, and 7-factor model showed a acceptable fit, and the best fit was seen in the order of the 7, 6, 4-factor model. Second, the internal consistency, omega coefficient, construct validity, average variance extracted, and test-retest reliability results were all satisfactory.. Third, a correlation analysis with the K-PC-PTSD-5 and the sub-factors of BSI-18 was conducted to check the validity of the Korean Version of PCL-5. As a result, a positive correlation was seen with both K-PC-PTSD-5 and BSI-18. Fourth, a hierarchical multiple regression was performed to examine whether the Korean Version of PCL-5 predicts future PTSD, depression, anxiety, and somatization. As a result, the Korean Version of PCL-5 measured at time 1 significantly predicted PTSD, depression, anxiety, and somatization symptoms at time 2. Fifth, by analyzing the ROC curve, the discriminant power of PCL-5 for screening PTSD symptom groups was confirmed, and the best cut-off score was suggested. As a result of the longitudinal validation of Korean version of PCL-5, it was found that this scale is a reliable and valid measure for Korean adults. By looking into the predictive validity of the scale, it was found that the Korean version of PCL-5 can predict not only PTSD symptoms but also PTSD-related symptoms such as depression, anxiety, and somatization. Also, this study differs from previous validation studies measuring PTSD symptoms in that it suggested a cut-off score to help differentiate PTSD symptom groups.