• Knowledge Management Research
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• v.11 no.5
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• pp.59-78
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• 2010

In this paper, we arrange the concept of 'Green' in SCM after literature study of Green SCM and investigate causal relationships between influencing factors, practice level and environmental performance focused on Korean firms empirically and conduct path analysis for hypothesis test using partial least squares regression with bootstrap. Firstly, we divide influencing factors of Green SCM into environmental and organizational factors through the previous studies of innovation diffusion theory and environmental management theory, and then we selected 'uncertainty', 'competitiveness' as the environmental factors and 'top management support', 'perceived benefit', 'training' as the organizational factors. Secondly, we classify practice level of Green SCM into 'internal environmental management', 'green purchasing', 'eco-design'. Finally, we selected 'financial performance', 'environmental performance' as the organizational performance. We conducted a survey on the middle manager of manufacturing companies implementing SCM and an empirical analysis. The results of analysis show that there exist causal relationships between influencing factors, practice level, and environmental performance of Green SCM. We expect that the result of this study will suggest useful information to managers who are responsible for SCM to design and execute Green SCM in strategic perspectives.

• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.279-285
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• 2009

Prediction of glucose concentration in the interstitial fluid (ISF) based on mid-infrared absorption spectroscopy was examined at the glucose fundamental absorption band of 1000 - 1500/cm (10 - 6.67 um) using multi-component analysis. Simulated ISF samples were prepared by including four major ISF components. Sodium lactate had absorption spectra that interfere with those of glucose. The rest NaCl, KCl and $CaCl_2$ did not have any signatures. A preliminary experiment based on Design of Experiment, an optimization method, proved that sodium lactate influenced the prediction accuracy of glucose. For the main experiment, 54 samples were prepared whose glucose and sodium lactate concentration varied independently. A partial least squares regression (PLSR) analysis was used to build calibration models. The prediction accuracy was dependent on spectrum preprocessing methods, and Mean Centering produced the best results. Depending on calibration sample sets whose sodium lactate had different concentration levels, the standard error prediction (SEP) of glucose ranged $17.19{\sim}21.02\;mg/dl$.

• The Journal of Information Systems
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• v.21 no.1
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• pp.173-203
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• 2012

In this paper, we arrange the concept of 'Green' in SCM after literature study of Green SCM and investigate causal relationships between influencing factors, practice level and environmental performance focused on Korean firms empirically and conduct path analysis for hypothesis test using partial least squares regression with bootstrap. Firstly, we divide influencing factors of Green SCM into environmental and organizational factors through the previous studies of innovation diffusion theory and environmental management theory, and then we selected 'uncertainty', 'competitiveness' as the environmental factors and 'top management support', 'perceived benefit', 'training' as the organizational factors. Secondly, we classify practice level of Green SCM into 'internal environmental management', 'green purchasing', 'eco-design'. Finally, we selected 'financial performance', 'environmental performance' as the organizational performance. We conducted a survey on the middle manager of manufacturing companies implementing SCM and an empirical analysis. The results of analysis show that there exist causal relationships between influencing factors, practice level, and environmental performance of Green SCM. We expect that the result of this study will suggest useful information to managers who are responsible for SCM to design and execute Green SCM in strategic perspectives.

• Journal of the Korean Wood Science and Technology
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• v.43 no.3
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• pp.311-319
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• 2015

Near infrared (NIR) reflectance spectroscopy was employed to develop moisture content prediction model of pitch pine (Pinus rigida), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), yellow poplar (Liriodendron tulipifera) wood below fiber saturation point. NIR reflectance spectra of specimens ranging from 1000 nm to 2400 nm were acquired after humidifying specimens to reach several equilibrium moisture contents. To determine the optimal moisture contents prediction model, 5 mathematical preprocessing methods (moving average (smoothing point: 3), baseline, standard normal variate (SNV), mean normalization, Savitzky-Golay $2^{nd}$ derivatives (polynomial order: 3, smoothing point: 11)) were applied to reflectance spectra of each specimen as 8 combinations. After finishing mathematical preprocessings, partial least squares (PLS) regression analysis was performed to each modified spectra. Consequently, the mathematical preprocessing methods deriving optimal moisture content prediction were 1) moving average/SNV for pitch pine and red pine, 2) moving average/SNV/Savitzky-golay $2^{nd}$ derivatives for Korean pine and yellow poplar. Every model contained three principal components.

• Journal of the Korean Wood Science and Technology
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• v.43 no.3
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• pp.304-310
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• 2015

The moisture content of sawdust must be measured accurately and controlled appropriately during storage and transportation because biological degradation could be caused by improper moisture. In this study, to measure the moisture contents of Larix kaempferi sawdust, the near-infrared reflectance spectra (Wavelength 1000-2400 nm) of sawdust were used as detection parameter. After acquiring the NIR reflection spectrum of specimens which were humidified at each relative humidity condition ($25^{\circ}C$, RH 30~99%), moisture content prediction model was developed using mathematical preprocessings (e.g. smoothing, standard normal variate) and partial least squares (PLS) analysis with the acquired spectrum data. High reliability of the MC regression model with NIR spectroscopy was verified by cross validation test ($R^2$ = 0.94, RMSEP = 1.544). The results of this study show that NIR spectroscopy could be used as a convenient and accurate method for the nondestructive determination of moisture content of sawdust, which could lead to optimize wood utilization.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1075-1083
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• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.

• Korean Journal of Organic Agriculture
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• v.13 no.3
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• pp.281-289
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• 2005

In order to find out an alternative way of analysis of food waste compost, the Near Infrared Reflectance Spectroscopy(NIRS) was used for the compost assessment because the technics has been known as non-detructive, cost-effective and rapid method. One hundred thirty six compost samples were collected from Incheon food waste compost factory at Namdong Indurial Complex. The samples were analyzed for nitrogen, organic matter (OM), ash, P, and K using Kjedahl, ignition method, and acid extraction with spectrophotometer, respectively. The samples were scanned using FOSS NIRSystem of Model 6500 scanning mono-chromator with wavelength from $400\~2,400nm$ at 2nm interval. Modified partial Least Squares(MPLS) was applied to develop the most reliable calibration model between NIR spectra and sample components such as nitrogen, ash, OM, P, and K. The regression was validated using validation set(n=30). Multiple correlation coefficient($R^2$) and standard error of prediction(SEP) for nitrogen, ash, organic matter, OM/N ratio, P and K were 0.87, 0.06, 0.72, 1.07, 0.68, 1.05, 0.89, 0.31, 0.77, 0.06, and 0.64, 0.07, respectively. The results of this experiment indicates that NIRS is reliable analytical method to assess some components of feed waste compost, also suggests that feasibility of NIRS can be Justified in case of various sample collection around the year.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.497-502
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• 2001

Influence of other blond components on measuring glucose concentration was analyzed B)food phantom containing five major components was made. The prediction model was developed based on the measurement of absorption spectra including the first overtone glucose band, i.e.. 1500 ∼ 1850 nm. The concentrations were Predicted using the Partial least squares regression. Factor analysis based on Design of Experiment was Performed to study the influence of other components in predicting glucose concentration. Triglyceride does not influence. Albumin and globulin haute minor effects. However, hemoglobin showed substantial response and the compensation of hemoglobin concentration appears to be required for the model of glucose measurement.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.4
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• pp.497-502
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• 2012

This study investigates the prediction of soil OM on Korean soils using the Visible-Near Infrared (Vis-NIR) spectroscopy. The ASD Field Spec Pro was used to acquire the reflectance of soil samples to visible to near-infrared radiation (350 to 2500 nm). A total of 503 soil samples from 61 Korean soil series were scanned using the instrument and OM was measured using the Walkley and Black method. For data analysis, the spectra were resampled from 500-2450 nm with 4 nm spacing and converted to the $1^{st}$ derivative of absorbance (log (1/R)). Partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil OM. Regression rules model estimates the target value by building conditional rules, and each rule contains a linear expression predicting OM from selected absorbance values. The regression rules model was shown to give a better prediction compared to PLSR. Although the prediction for Andisols had a larger error, soil order was not found to be useful in stratifying the prediction model. The stratification used by Cubist was mainly based on absorbance at wavelengths of 850 and 2320 nm, which corresponds to the organic absorption bands. These results showed that there could be more information on soil properties useful to classify or group OM data from Korean soils. In conclusion, this study shows it is possible to develop good prediction model of OM from Korean soils and provide data to reexamine the existing prediction models for more accurate prediction.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.3
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• pp.92-106
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• 2017

This paper examines the validity of issuing municipal bonds for land compensation of long-term unexecuted urban parks and greenbelts. Then it suggests that municipal bonds should be issued for compensation priority areas with high rising prices. By conducting correlation analysis and PLS(Partial Least Squares) regression for 32 long-term unexecuted urban parks and greenbelts, the factors were identified that affected 'rising prices of IAPLP(Individually Announced Public Land Price) after seven years'. According to the analysis results, Variable Importance in the Projection in PLS regression was higher in 'IAPLP of base year(1.919)' and 'Accumulated rising Rates of average IAPLP in the borough(1.176).' The implications of this study are as follows. In Seoul, the accumulated rising rates of average IAPLP over the past 12 years is higher than the accumulated interest rates for seven years of urban planning facility bonds, which means that IAPLP have risen more than the interest payments due to the issuance of municipal bonds. In addition, since the actual compensation is three times that of IAPLP, it is judged that the land price is actually much higher than the interest payments. This shows that issuing municipal bonds and preferentially compensating for areas like high rising land prices can increase the economic efficiency of the budget execution. Also, for economic efficiency of budget execution, it is necessary to propose an 'area with high IAPLP' or 'a part in the borough with high rising rate of average IAPLP,' which is expected to have a high rising land price as criteria for compensation priority areas. In the future, when issuing municipal bonds to compensate long-term unexecuted urban parks and greenbelts, variousresearch on financing for municipal bonds repayment should be conducted.