• Korean Chemical Engineering Research
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• v.44 no.6
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• pp.659-668
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• 2006

The optimization of supercritical water oxidation (SCWO) process for decomposing nitromethane was studied by means of a design of experiments. The optimum operating region for the SCWO process to minimize COD and T-N of treated water was obtained in a lab scale unit. The authors had compared the results from a SCWO pilot plant with those from a lab scale system to explore the problems of scale-up of SCWO process. The COD and T-N in treated waters were selected as key process output variables (KPOV) for optimization, and the reaction temperature (Temp) and the mole ratio of nitromethane to ammonium hydroxide (NAR) were selected as key process input variables (KPIV) through the preliminary tests. The central composite design as a statistical design of experiments was applied to the optimization, and the experimental results were analyzed by means of the response surface method. From the main effects analysis, it was declared that COD of treated water steeply decreased with increasing Temp but slightly decreased with an increase in NAR, and T-N decreased with increasing both Temp and NAR. At lower Temp as $420{\sim}430^{\circ}C$, the T-N steeply decreased with an increase in NAR, however its variation was negligible at higher Temp above $450^{\circ}C$. The regression equations for COD and T-N were obtained as quadratic models with coded Temp and NAR, and they were confirmed with coefficient of determination ($r^2$) and normality of standardized residuals. The optimum operating region was defined as Temp $450-460^{\circ}C$ and NAR 1.03-1.08 by the intersection area of COD < 2 mg/L and T-N < 40 mg/L with regression equations and considering corrosion prevention. To confirm the optimization results and investigate the scale-up problems of SCWO process, the nitromethane was decomposed in a pilot plant. The experimental results from a SCWO pilot plant were compared with regression equations of COD and T-N, respectively. The results of COD and T-N from a pilot plant could be predicted well with regression equations which were derived in a lab scale SCWO system, although the errors of pilot plant data were larger than lab ones. The predictabilities were confirmed by the parity plots and the normality analyses of standardized residuals.

• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.51-79
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• 1990

Research on technical efficiency, an important dimension of market performance, had received little attention until recently by most industrial organization empiricists, the reason being that traditional microeconomic theory simply assumed away any form of inefficiency in production. Recently, however, an increasing number of research efforts have been conducted to answer questions such as: To what extent do technical ineffciencies exist in the production activities of firms and plants? What are the factors accounting for the level of inefficiency found and those explaining the interindustry difference in technical inefficiency? Are there any significant international differences in the levels of technical efficiency and, if so, how can we reconcile these results with the observed pattern of international trade, etc? As the first in a series of studies on the technical efficiency of Korea's manufacturing industries, this paper attempts to answer some of these questions. Since the estimation of technical efficiency requires the use of plant-level data for each of the five-digit KSIC industries available from the Census of Manufactures, one may consture the findings of this paper as empirical evidence of technical efficiency in Korea's manufacturing industries at the most disaggregated level. We start by clarifying the relationship among the various concepts of efficiency-allocative effciency, factor-price efficiency, technical efficiency, Leibenstein's X-efficiency, and scale efficiency. It then becomes clear that unless certain ceteris paribus assumptions are satisfied, our estimates of technical inefficiency are in fact related to factor price inefficiency as well. The empirical model employed is, what is called, a stochastic frontier production function which divides the stochastic term into two different components-one with a symmetric distribution for pure white noise and the other for technical inefficiency with an asymmetric distribution. A translog production function is assumed for the functional relationship between inputs and output, and was estimated by the corrected ordinary least squares method. The second and third sample moments of the regression residuals are then used to yield estimates of four different types of measures for technical (in) efficiency. The entire range of manufacturing industries can be divided into two groups, depending on whether or not the distribution of estimated regression residuals allows a successful estimation of technical efficiency. The regression equation employing value added as the dependent variable gives a greater number of "successful" industries than the one using gross output. The correlation among estimates of the different measures of efficiency appears to be high, while the estimates of efficiency based on different regression equations seem almost uncorrelated. Thus, in the subsequent analysis of the determinants of interindustry variations in technical efficiency, the choice of the regression equation in the previous stage will affect the outcome significantly.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.427-443
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• 2007

The purpose of this study is to investigate spacio-temporal structures of traffic flows on the subway network in the Metropolitan Seoul, and the relationships between topological structures of traffic flows and land use patterns. In particular we analyze in the topological structures of traffic flows on the subway network in time dimension as well as in spatial dimension. For the purpose, this study utilizes data mining techniques to the one day T-card transaction data of the last four years, which has developed for exploring the characteristics of traffic flows from large scale trip-transaction databases. The topological structures of traffic flows on the subway network has changed considerably during the last four years. The volumes of traffic flows, the travel time and stops per trip have increased until 2006 and decreased again in 2007. The results are visualized by utilizing GIS and analyzed, and thus the spatial patterns of traffic flows are analyzed. The spatial distribution patterns of trip origins and destinations show substantial differences among time zones during a day. We analyze the relationships between traffic flows at subway stops and the geographical variables reflecting land use around them. We obtain 6 log-linear functions from stepwise multiple regression analysis. We test multicollinearity among the variables and autocollelation for the residuals.

• The korean journal of orthodontics
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• v.37 no.1 s.120
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• pp.16-28
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• 2007

Objective: Evaluation of individual growth is important in orthodontics. The aim of this study was to develop a convenient software that can evaluate current growth status and predict further growth. Methods: Stature data of 2 to 20 year-old Koreans (4893 boys and 4987 girls) were extracted from a nationwide data. Age-sex-specific continuous functions describing percentile growth curves were constructed using natural cubic spline function (NCSF). Then, final stature prediction algorithm was developed and its validity was tested using longitudinal series of stature measurements on randomly selected 200 samples. Various accuracy measurements and analyses of errors between observed and predicted stature using NCSF growth curves were performed. Results: NCSF growth curves were shown to be excellent models in describing reference percentile stature growth curie over age. The prediction accuracy compared favorably with previous prediction models, even more accurate. The current prediction models gave more accurate results in girls than boys. Although the prediction accuracy was high, the error pattern of the validation data showed that in most cases, there were a lot of residuals with the same sign, suggestive of autocorrelation among them. Conclusion: More sophisticated growth prediction algorithm is warranted to enhance a more appropriate goodness of model fit for individual growth.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• Journal of Korea Water Resources Association
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• v.53 no.1
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• pp.45-56
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• 2020

This study aims to quantify the uncertainty that can be induced by the objective function when calibrating SWAT parameters using SWAT-CUP. SWAT model was constructed to estimate runoff in Naesenong-cheon, which is the one of mid-watershed in Nakdong River basin, and then automatic calibration was performed using eight objective functions (R², bR², NS, MNS, KGE, PBIAS, RSR, and SSQR). The optimum parameter sets obtained from each objective function showed different ranges, and thus the corresponding hydrologic characteristics of simulated data were also derived differently. This is because each objective function is sensitive to specific hydrologic signatures and evaluates model performance in an unique way. In other words, one objective function might be sensitive to the residual of the extreme value, so that well produce the peak value, whereas ignores the average or low flow residuals. Therefore, the hydrological similarity between the simulated and measured values was evaluated in order to select the optimum objective function. The hydrologic signatures, which include not only the magnitude, but also the ratio of the inclining and declining time in hydrograph, were defined to consider the timing of the flow occurrence, the response of watershed, and the increasing and decreasing trend. The results of evaluation were quantified by scoring method, and hence the optimal objective functions for SWAT parameter calibration were determined as MNS (342.48) and SSQR (346.45) with the highest total scores.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.525-533
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• 2019

There are two feature collection methods in digital mapping using the UAV (Unmanned Aerial Vehicle) Photogrammetry: vectorization and stereo plotting. In vectorization, planar information is extracted from orthomosaics and elevation value obtained from a DSM (Digital Surface Model) or a DEM (Digital Elevation Model). However, the exact determination of the positional accuracy of 3D features such as ground facilities and buildings is very ambiguous, because the accuracy of vectorizing results has been mainly analyzed using only check points placed on the ground. Thus, this study aims to review the possibility of 3D spatial information acquisition and digital map production of vectorization by analyzing the corner point coordinates of different layers as well as check points. To this end, images were taken by a Phantom 4 (DJI) with 3.6 cm of GSD (Ground Sample Distance) at altitude of 90 m. The outcomes indicate that the horizontal RMSE (Root Mean Square Error) of vectorization method is 0.045 cm, which was calculated from residuals at check point compared with those of the field survey results. It is therefore possible to produce a digital topographic (plane) map of 1:1,000 scale using ortho images. On the other hand, the three-dimensional accuracy of vectorization was 0.068~0.162 m in horizontal and 0.090~1.840 m in vertical RMSE. It is thus difficult to obtain 3D spatial information and 1:1,000 digital map production by using vectorization due to a large error in elevation.

• Journal of Environmental Health Sciences
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• v.28 no.5
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• pp.42-52
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• 2002

Two full-scale distribution systems, one treating water by ozonation and another treating water by nanofiltration in parallel with lime softening, were monitored for bacterial growth. Both systems kept disinfectant residuals surf as chlorine and chloramine in their respective distribution systems. Bacterial growth was assessed by heterotrophic plate counts (HPC) on R2A agar. In the distribution systems fed by ozonated water, HPCs were correlated ($R^2$= 0.97) using an exponential model with the assimilable organic carbon (AOC) at each sampling site. Also, it was observed that ozonation caused a significant increase in the AOC concentration of the distribution system (over 100％ increase) as well as a significant increase in the bacterial counts of the distribution system (average increase over 100％). The HPCs from the distribution systems fed by nanofiltration in parallel with lime-softening water also displayed an exponential correlation ($R^2$ = 0.75) with an exponential model based on AOC. No significant correlation was found between bacteria growth on R2A agar and BDOC concentrations. Therefore, in agreement with previous work, bacterial growth in the distribution systems was found to correlate with AOC concentrations.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.5
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• pp.690-695
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• 2016

This study was performed to evaluate the effect of alkaline treatment on Styela clava tunic (SCT). Considerable damage to the surface of alkali-treated SCT was observed by scanning electron microscopy (SEM) in a concentration-dependent manner upon alkaline treatment. The amount of crystalline region in SCT gradually increased with increasing NaOH concentration, which was analyzed by X-ray diffraction and thermogravimetric analysis. The initial enzymatic reaction of Celluclast toward SCT was elevated by treatment with NaOH up to 1.0 N concentration due to disruption of the SCT surface by promoting binding of enzymes with SCT. However, in the late stage of the enzyme reaction, hydrolysis rate decreased with elevation of NaOH concentration, thereby increasing the amount of non-reacted residuals. This result was due to the increase in the crystalline regions in SCT.