• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.7-18
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• 2001

This study represents a first attempt in Korea to develop the simultaneous freight supply-demand model which considers the relationship between freight supply and demand. As the existing study was limited in one area, or the supply and the demand was separated and assumed not to affect each other, this study take it into consideration the fact that the demand affects supply and simultaneously vice versa. This approach allows us to diagnose a policy carried on and helps us to make a resonable alternative for the effectiveness of freight transportation system. To find a relationship between them, we use a method of econometrics. a structural equation theory and two stage least-squares(2SLS) estimation technique, to get rid of bias which involves two successive applications of OLS. Based on the domestic freight data, this study consider as explanatory variables a number of population(P), industry(IN), the amount of production of the mining and manufacturing industries(MMI), the rate of the effectiveness of freight capacity(LE) and the distance of an empty carriage operation(VC). This study describes well the simultaneous process of freight supply-demand system in that the increase of VC from the decrease of VC raises the cargo capacity and cargo capacity also augments VC. By the way. it is analyzed that the increment of VC due to the increase of the cargo capacity is larger than the reduction of VC owing to the increase of the quantify of goods. Therefore an alternative policy is needed in a short and long run point of view. That is to say, to promote the effectiveness of the freight transportation system, a short term supply control and a long run logistic infrastructure are urgent based on the restoration of market economy by successive deregulation. So we are able to conclude that gradual deregulation is more desirable to build effective freight market.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.35-50
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• 2020

This study aimed to investigate the changes of emotional perception biases according to the level of social phobia and the relationship with visuospatial attention allocation ability. This study used the Korean self-report assessment test (Korean version of social avoidance and distress, K-SAD) to measure the level of social phobia. Moreover, the emotional perception and useful field of view (UFOV) tasks were employed for measuring emotional perception biases and visuospatial attention allocation ability, respectively. A total of 118 participants participated in this experiment, and only 107 (males: 94, females: 13) data were analyzed due to the exclusion of response errors and other statistical problems. The average age of the participants used in the analysis was 21 years (SD: 3.64), and those participants were divided into three groups according to the K-SAD scores. Consequently, all experimental groups showed negative emotional perception biases in the emotional perception task, but the magnitudes of the biases of each group were not significantly different. Furthermore, the positive emotional perception biases were higher at higher levels of social phobia, which could be related to the tendency of interpreting positive stimuli negatively. In the UFOV task, the higher the level of social phobia, the lower the visuospatial attention allocation ability. These results suggest that the deterioration of visuospatial attention allocation ability potentially contributes to the increase of positive emotional perception biases by being difficult to perceive external stimuli. Thus, this paper discusses the potential contribution of visuospatial attention allocation ability to the increased perceptual biases of positive emotions as the level of social phobia increases.

• Korean Journal of Materials Research
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• v.17 no.12
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• pp.642-647
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• 2007

We investigated dry etching of acrylic (PMMA) in $O_2/N_2$ plasmas using a multi-layers electrode reactive ion etching (RIE) system. The multi-layers electrode RIE system had an electrode (or a chuck) consisted of 4 individual layers in a series. The diameter of the electrodes was 150 mm. The etch process parameters we studied were both applied RIE chuck power on the electrodes and % $O_2$ composition in the $N_2/O_2$ plasma mixtures. In details, the RIE chuck power was changed from 75 to 200 W.% $O_2$ in the plasmas was varied from 0 to 100% at the fixed total gas flow rates of 20 sccm. The etch results of acrylic in the multilayers electrode RIE system were characterized in terms of negatively induced dc bias on the electrode, etch rates and RMS surface roughness. Etch rate of acrylic was increased more than twice from about $0.2{\mu}m/min$ to over $0.4{\mu}m/min$ when RIE chuck power was changed from 75 to 200 W. 1 sigma uniformity of etch rate variation of acrylic on the 4 layers electrode was slightly increased from 2.3 to 3.2% when RIE chuck power was changed from 75 to 200 W at the fixed etch condition of 16 sccm $O_2/4\;sccm\;N_2$ gas flow and 100 mTorr chamber pressure. Surface morphology was also investigated using both a surface profilometry and scanning electron microscopy (SEM). The RMS roughness of etched acrylic surface was strongly affected by % $O_2$ composition in the $O_2/N_2$ plasmas. However, RIE chuck power changes hardly affected the roughness results in the range of 75-200 W. During etching experiment, Optical Emission Spectroscopy (OES) data was taken and we found both $N_2$ peak (354.27 nm) and $O_2$ peak (777.54 nm). The preliminarily overall results showed that the multi-layers electrode concept could be successfully utilized for high volume reactive ion etching of acrylic in the future.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.11
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• pp.1445-1454
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• 2010

Two separate animal trials were conducted to evaluate the coincidence of dry matter intake (DMI) and average daily gain (ADG) predicted by the Cornell Net Carbohydrate and Protein System (CNCPS) and observed actually in crossbred growing bulls kept in a traditionally confined feeding system in China. In Trial 1, 45 growing Simmental${\times}$Mongolia crossbred F1 bulls were assigned to three treatments (T1-3) with 15 animals in each treatment. Trial 2 was conducted with 60 Limousin${\times}$Fuzhou crossbred F2 bulls allocated to 4 treatments (t1-4). All of the animals were confined in individual stalls. DMI and ADG for each bull were measured as a mean of each treatment. All of the data about animals, environment, management and feeds required by the CNCPS model were collected, and model predictions were generated for animals on each treatment. Subsequently, model-predicted DMI and ADG were compared with the actually recorded results. In the three treatments in Trial 1, 93.3, 80.0 and 73.3% of points fell within the range from -0.4 to 0.4 kg/d for DMI mean bias; similarly, in the four treatments in Trial 2, about 86.7, 73.3, 73.3 and 80.0% of points fell within the same range. These results indicate that the CNCPS model can accurately predict DMI of crossbred bulls in the traditionally confined feeding system in China. There were no significant differences between predicted and observed ADG for T1 (p = 0.06) and T2 (p = 0.09) in Trial 1, and for t1 (p = 0.07), t2 (p = 0.14) and t4 (p = 0.83) in Trial 2. However, significant differences between predicted and observed ADG values were observed for T3 in Trial 1 (p<0.01) and for t3 in Trial 2 (p = 0.04). By regression analysis, a statistically different value of intercept from zero for the regression equation of DMI (p<0.01) or an identical value of ADG (p = 0.06) were obtained, whereas the slopes were significantly different (p<0.01) from unity for both DMI and ADG. Additionally, small root mean square error (RMSE) values were obtained for the unbiased estimator of the two variances (DMI and ADG). Thus, the present results indicated that the CNCPS model can give acceptable estimates of DMI and ADG of crossbred growing bulls kept in a traditionally confined feeding system in China.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.4
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• pp.247-254
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• 2003

This study was conducted to develop site index equations by main species grown in Gyunggi and Chungcheong provinces using environmental factors obtained from a digital forest site map. For this, 28 environmental factors were regressed on site index by species. Four to five environmental factors by species were selected as independent variables in the best site index equations (coefficients of determination greater than 0.91). For these site index equations, three evaluation statistics, mean difference, standard deviation of difference, and standard error of difference, were applied to the data set. Site index equations by species relationships developed in this study effectively estimate forest productivity in the study area. However, the site index equation of Larix leptolepis showed a larger than expected bias between the estimated and the measured site index. The reason is not clear in this situation, but might be because of the small sample set. It will be necessary, therefore, to conduct more studies to determine the exact reason. It is also expected that the site index equations with a few environmental factors as independent variables could provide valuable information about species well suited to given site conditions. Site index equations for other species should be developed to establish a rational policy about the selection of best species for site conditions.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.599-605
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• 2019

Rice yield (kg 10a^-1) in South Korea was estimated by meteorological variables that are influential factors in crop growth. This study investigated the possibility of anticipating the rice yield variability using a simple but an efficient statistical method, a multiple linear regression analysis, on the basis of the annual variation of meteorological variables. Due to heterogeneous environmental conditions by region, the yearly rice yield was assessed and validated for each province in South Korea. The monthly mean meteorological data for the period 1986-2018 (33 years) from 61 weather stations provided by Korean Meteorological Administration was used as the independent variable in the regression analysis. An 11-fold (leave-three-out) cross-validation was performed to check the accuracy of this method estimating rice yield at each province. This result demonstrated that temporal variation of rice yield by province in South Korea can be properly estimated using such concise procedure in terms of correlation coefficient (0.7, not significant). Furthermore, the estimated rice yield well captured spatial features of observation with mean bias of 0.7 kg 10a^-1 (0.15%). This method may offer useful information on rice yield by province in advance as long as accurate agro-meteorological forecasts are timely obtained from climate models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.273-282
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• 2020

This study analyzed the physiological effects of silkworms and silkworm pupae on the reduction of serum lipid levels. Research data specific to silkworms and their pupae published over the last 10 years were collected and analyzed. A large effect size of 0.852 was observed in the overall results and the range of 95% confidence intervals was 0.662 to 0.999. The Q value was 23.264, the Higgin's I² value was 92.217, indicating that each study was heterogeneous. There was no publication bias, as the corrected observed number of statistically significant effect sizes and the expected number of statistically significant effect sizes were both 0.654. The silkworm study showed a large effect size with respect to blood sugar and blood lipid reduction at 0.801 and 0.948, respectively, and LDL-cholesterol reduction at 1.371, showing a very large effect size. Aspartate transaminase / glutamic oxaloacetic transaminase (AST/GOT) was 0.768, alanine transaminase /glutamate-pyruvate transaminase (ALT/GPT) was 0.788, which was a medium effect size. The experiment period had a very large effect size of 1.170 for five to eight weeks and 1.020 for an intake of 1 to 50 mg/kg. The silkworm pupae had a large effect size of 0.991 and 0.951, respectively on blood lipids and total cholesterol reduction. The experimental period showed a very large effect size at 1.103 for more than nine weeks, and the intake showed a large effect size at 0.855 for 5001 mg/kg.

• Atmosphere
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• v.28 no.1
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• pp.37-51
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• 2018

In this study, we investigate the performance of Global Seasonal Forecasting System version 5 (GloSea5) in Korea Meteorological Administration on the relationship between El $Ni{\tilde{n}}o$ and East Asian climate for the period of 1991~2010. It is found that the GloSea5 has a great prediction skill of El $Ni{\tilde{n}}o$ whose anomaly correlation coefficients of $Ni{\tilde{n}}o$ indices are over 0.96 during winter. The eastern Pacific (EP) El $Ni{\tilde{n}}o$ and the central Pacific (CP) El $Ni{\tilde{n}}o$ are considered and we analyze for EP El $Ni{\tilde{n}}o$, which is well simulated in GloSea5. The analysis period is divided into the developing phase of El $Ni{\tilde{n}}o$ summer (JJA(0)), mature phase of El $Ni{\tilde{n}}o$ winter (D(0)JF(1)), and decaying phase of El $Ni{\tilde{n}}o$ summer (JJA(1)). The GloSea5 simulates the relationship between precipitation and temperature in East Asia and the prediction skill for the East Asian precipitation and temperature varies depending on the El $Ni{\tilde{n}}o$ phase. While the precipitation and temperature are simulated well over the equatorial western Pacific region, there are biases in mid-latitude region during the JJA(0) and JJA(1). Because the low level pressure, wind, and vertical stream function are simulated weakly toward mid-latitude region, though they are similar with observation in low-latitude region. During the D(0)JF(1), the precipitation and temperature patterns analogize with observation in most regions, but there is temperature bias in inland over East Asia. The reason is that the GloSea5 poorly predicts the weakening of Siberian high, even though the shift of Aleutian low is predicted. Overall, the predictability of precipitation and temperature related to El $Ni{\tilde{n}}o$ in the GloSea5 is considered to be better in D(0)JF(1) than JJA(0) and JJA(1) and better in ocean than in inland region.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.252-263
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• 2008

This study was conducted to derive the optimal regionalization of the precipitation data which can be classified on the basis of climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analyses. K-means clustering mettled is used to identify homogeneous regions all over the regions. Five homogeneous regions for the precipitation were classified by the K-means clustering. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the generalized extreme value (GEV) distribution among applied distributions. The regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.