• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.40-49
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• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Analytical Science and Technology
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• v.16 no.2
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• pp.95-101
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• 2003

In this study, water content in the mixture of methanol and ethanol was nondestructively measured by near infrared (NIR) spectroscopy. Two types of NIR instruments, portable NIR system with a photo-diode array and scanning type NIR spectrometer were used and the calibration results were compared. Partial least squares regression (PLSR) was applied for the calibration and validation for the quantitative analysis. The calibration results from both instruments showed good correlation with actual values. The calibration with the use of PLS model predicted water concentration with a standard error of prediction (SEP) of 0.10% and 0.12% for photo diode array and scanning type, respectively. During 6 days, routine analyses for 3%, 5% and 7% water in ethanol solution with 2% methanol were performed to validate the robustness of the developed calibration model. The routine analyses showed good results with coefficient of variation (CV) of within 3% for both types of NIR spectrometers. This study showed that the rapid determination of water in the mixture of methanol and ethanol was successfully performed by NIR spectroscopy and the performance of the portable NIR system with a photo diode array detector was comparable to that of the scanning type NIR spectrometer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.448-458
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• 2017

This study reviews the literature related to the omni-channel and derived structural relationship between experiential perception of omni-channel brand and consumer-brand relational quality. A total of 250 questionnaires were distributed to university students, workers, and consumers in Busan, Korea, who had experience using SSG.com. 210 questionnaires were used for final validation of research model. The hypotheses set in this study was validated through SPSS18.0 and LISREL8.3 based on the research model. The results showed that all hypotheses were accepted, except for 2 hypotheses(Hypothesis 2-3, Hypothesis 2-4). Findings of this study suggest the following:First, the consumer's experience with the omni-channel brand was found to be an important factor influencing consumers' cognitive and emotional responses formed by the transfer effect of experiential factors through senses. Second, the relationship between consumers and the omni-channel brand was found to be an important factor in building attachment and psychological bond through experience and trust for the omni-channel brand. Thus, the results of this study provide the basis for overall understanding of the strategic experiential module (SEMs) for the omni-channel, which recently emerged as a new trend of distribution channel, as well as for managing the spatial environment. Finally, we present the theoretical and practical implications related to consumers' experience and relational perception.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.15 no.4
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• pp.321-332
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• 2017

In order to build a general model of a high-throughput uranium electrorefining process according to the electrode configuration, numerical analysis was conducted using the COMSOL Multiphysics V5.3 electrodeposition module with Ordinary Differential Equation (ODE) interfaces. The generated model was validated by comparing a current density-potential curve according to the distance between the anode and cathode and the electrode array, using a lab-scale (1kg U/day) multi-electrode electrorefiner made by the Korea Atomic Energy Research Institute (KAERI). The operating temperature was $500^{\circ}C$ and LiCl-KCl eutectic with 3.5wt% $UCl_3$ was used for molten salt. The efficiency of the uranium electrorefining apparatus was improved by lowering the cell potential as the distance between the electrodes decreased and the anode/cathode area ratio increased. This approach will be useful for constructing database for safety design of high throughput spent nuclear fuel electrorefiners.

• Journal of Distribution Science
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• v.9 no.2
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• pp.61-72
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• 2011

The object of this research is to examine the factors leading to intercompany win-win by finding the antecedents and consequences that affect a supplier's fairness perception. We assume that the antecedent factors of a supplier's fairness perception are vertical coordination, cooperation support, information sharing, and legalistic plea. We assume that the consequential factors of a supplier's fairness perception are supply chain dependence and supply chain flexibility. The object industry is an electronic parts manufacturing company. We tested our model by using the SPSS 17.0 and the LISREL 8.5. For measurement validation, we verified by using a confirmatory factor analysis and a reliability analysis. For hypothesis analysis, we did a path analysis with the LISREL 8.5. By checking the modification index and expecting parameter changes, we modified the model. First, the buyer's vertical coordination had a positive effect on the supplier's distributive fairness perception and procedural fairness perception. Second, the buyer's cooperation support had no effect on the supplier's distributive fairness perception and procedural fairness perception: we suppose that the buyer's requests were burdensome, although they cooperated with the supplier. Third, the buyer's information sharing had a positive effect on distributive fairness perception but had no direct effect on procedural fairness perception. Fourth, the buyer's legalistic plea had a negative effect on the supplier's distributive fairness perception. and a negative effect on the supplier's procedural fairness perception at a 0.1 significance level. Fifth, although procedural fairness perception had no direct effect on supply chain dependence, fairness perception had an effect on supply chain dependence and supply chain flexibility both directly and indirectly.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.3
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• pp.286-292
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• 2005

This study is to investigate the industrial boiler which can be significantly affected by the restriction of NOx. Note that the application of SNCR method to industrial boiler is usually blown as not feasible due to the insufficient residence time for proper mixing. The purpose of this study is to investigate the applicability of the SNCR system application to the industrial boiler, which produces 40 tons of steam per hour using heavy oil. For the industrial boiler with 3-D rectangular coordinate, the general coding are made fur various turbulence modeling such as turbulent flow, turbulent fuel combustion, thermal NO formation and destruction together with the NO reaction with reducing agents. Further, the incorporation of drop trajectory model is successfully made in 3-D rectangular coordinate with Lagrangian frame and the main swirl burner effect on the characteristics of flame is considered. As expected a short flame was created and thereby NOx is removed more efficiently by increasing the proper region of temperature for NO reduction reaction. The validation of program was made successfully by the comparison of experimental data. Based on the reliable calculation results, the SNCR method in a industrial boiler shows the possibility as one of viable NO reduction method by the use of well designed mixing air of reducing agent.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.7-13
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• 2013

A scaled version of a roller rig is developed to demonstrate the dynamic characteristics of a railway vehicle for academic purposes. This rig is designed based on Jaschinski's similarity law. It is scaled to 1/10 of actual size and allows 9-DOF motion to examine the up and down vibration of a train set. The test rig consists of three sub-hardware components: (i) a driving roller mechanism with a three-phase AC motor and an inverter, (ii) a bogie structure with first and second suspensions, and (iii) the vehicle body. The motor of the rig is capable of 3,600rpm, allowing the test to simulate a vehicle up to a maximum speed of 400Km/hr. Because bearings and joints are properly connected to the sub-structures, various motion analyses, such as a lateral, pitching, and yawing motion, are allowed. The slip motion between the rail and the wheel set is also monitored by several sensors mounted in the rig. After the construction of the hardware, an experiment is conducted to obtain the natural frequencies of the dynamic behavior of the specimen. First, the test rig is run and data are collected from six sets of accelerometers. Then, a numerical analysis of the model based on the ADAMS program is derived. Finally, the measurement data of the first three fundamental frequencies are compared to the analytical result and the validation of the test rig is conducted. The results show that the developed roller rig provides good accuracy in simulating the dynamic behavior of the vehicle motion. Although the roller rig designed in this paper is intended for academia, it can easily be implemented as part of a dynamic experiment of a bogie and a vehicle body for a high-speed train as part of the research efforts in this area.

• Journal of Korea Water Resources Association
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• v.53 no.5
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• pp.347-356
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• 2020

The main objective of the study is to propose the most efficient SWAT model calibration method using SWAT-CUP with less computing time and high performance. In order to achieve the goal, Case1-3 (250, 500, and 1,000 simulation runs) and Case4 (1,000 simulation runs in the first iteration and then 500 simulation runs for the following iterations) were defined to compare the results. When evaluating the values of the objective function, Case2 and Case3 reached the same value after the fourth iteration, and Case1 reached the closed value of Case2-3 after the eighth iteration. However, the final estimates of the parameters had different ranges in Cases1-3, and only the results of Case3 and Case4 converged similarly. Thus, it can be considered that the parameter calibration results are highly affected by the initial number of simulation runs. On the other hand, SWAT simulation results did not show the significant difference after the first iteration, unlike the parameter ranges. From the analysis results, we can conclude that the most suitable and effective method was to repeat one or two times of iterations with a sufficient number of simulation runs, as in Case4.

• Journal of dental hygiene science
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• v.9 no.1
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• pp.53-59
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• 2009

Infection control is now recognized as an important quality indicator in dental health service setting. The purpose of this study was to develop and validate Dental Hygienist's Infection Control Practice Scale for quality management of dental health service in Korea. The data of 254 dental hygienists was subjected to exploratory factor analysis using SPSS 16.0 and confirmatory factor analysis using AMOS 16.0. The total items of preliminary scale were 21 items and 5 subscale. Principal component analysis was completed with Varimax rotation. The results show a change in factor structure from 5 factor solution to 4 factor solution. The confirmatory factor analysis confirmed the four subscales(Immunization and periodic tests, Clinical procedure, Handwashing, Personal protection) which have a total of 12 items. After the item deleted because factor loading was low, measured model was tested. The results of the measurement model indicated fit indices: $x^2$= 79.593(df = 38, 0 = 0.000), RMR = 0.045, GFI = 0.940, CFI = 0.904, AGFI = 0.896, NFI = 0.837, TLI = 0.861, RMSEA = 0.67. The squared correlation between four constructs were less than the average variance extracted(AVE) of four constructs. Multiple regression analysis was completed. Dependent variable was the perceived infection control practice by dental hygienist. Independent variables were four summated subscales(R = 0.552, $R^2$= 0.304, Adjusted $R^2$= 0.431, F = 25.813, p = 0.000). Unstandardized coefficients of three independent variables were statistically significant.