• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.121-145
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• 1992

This paper examines characteristics of time series data related to the construction investment(stationarity and time series components such as secular trend, cyclical fluctuation, seasonal variation, and random change) and surveys predictibility, fitness, and explicability of independent variables of various models to build a short-term construction investment forecasting model suitable for current economic circumstances. Unit root test, autocorrelation coefficient and spectral density function analysis show that related time series data do not have unit roots, fluctuate cyclically, and are largely explicated by lagged variables. Moreover it is very important for the short-term construction investment forecasting to grasp time lag relation between construction investment series and leading indicators such as building construction permits and value of construction orders received. In chapter 3, we explicate 7 forecasting models; Univariate time series model (ARIMA and multiplicative linear trend model), multivariate time series model using leading indicators (1st order autoregressive model, vector autoregressive model and error correction model) and multivariate time series model using National Accounts data (simple reduced form model disconnected from simultaneous macroeconomic model and VAR model). These models are examined by 4 statistical tools that are average absolute error, root mean square error, adjusted coefficient of determination, and Durbin-Watson statistic. This analysis proves two facts. First, multivariate models are more suitable than univariate models in the point that forecasting error of multivariate models tend to decrease in contrast to the case of latter. Second, VAR model is superior than any other multivariate models; average absolute prediction error and root mean square error of VAR model are quitely low and adjusted coefficient of determination is higher. This conclusion is reasonable when we consider current construction investment has sustained overheating growth more than secular trend.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.153-160
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• 2000

Crustal velocities around the Korea peninsula are estimated and investigated from eight IGS permanent stations in eastern Asia area. GPS data for the period of May 1995 to December 1991 were analyzed to estimate daily coordinates of each site relative to TAEJ site. The velocity vector of each site is estimated from linear regression analysis with time series of coordinates. As the result, horizontal velocity components for four stations(Tsukuba, Usuda,Taiwan and Shanghai) using thirty-two months data were estimated with the standard error less than 1 mm/year. Our GPS velocity of six sites on the interiors of the Eurasia plate are similar within 1 cm/year with small differences respectively. On the other hand, the velocities of Tsukuba and Usuda showed the great differences from the other six sites. This can be explained by the fact that these two sites are enforced by the surrounding four plates, such as the Pacific, Eurasia, North America and Philipine plate. This study showed that the distance between Korea and Japan is shortened with the rate of 3 cm per year.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• The Korean Journal of Zoology
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• v.38 no.3
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• pp.417-425
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• 1995

The present study was carried out to investigate the effect of microwave fixation in comparison with that of chemical fixation in preparing the microscopic samples. The microwave fixator was equipped with infrared-temperature sensor, and that was designed to compensate air temperature in the microwave fixator. In the microwave fixation, rat tongue was well preserved in terms of muscular fasciculus and pancreas stained by Feulgen reagents showed clear reaction products in the nucleus. Reaction products by PAS method in duodenal villi appeared specifically at the goblet cells. In electron microscopy, pancreatic cellular components such as secretory granules and collagen bundles were well preserved in both fixations. In aspect of histochemical reaction and electron microscopy, high quality was due to the protein content of microwave fixed specimen. The microwave fixation method saved total duration engaging microscopic preparation.

• Journal of Life Science
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• v.21 no.8
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• pp.1134-1141
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• 2011

Transmembrane protein 21 (TMP21) is a member of the p24 cargo protein family and has been shown to modulate ${\alpha}$-secretase-mediated A${\beta}$ production which was specifically observed in the brains of subjects with Alzheimer's disease (AD). In order to investigate whether TMP21 could affect nerve growth factor (NGF) receptor signaling pathway, the alteration of NGF receptors and their downstream proteins were detected in TMP21 over-expressed cells. CMV/hTMP21 vector used in this study was successfully expressed into TMP21 proteins in B35 cells after lipofectamin transfection. Expressed TMP21 proteins induced the down-regulation of ${\gamma}$-secretase complex components including Presenlin-1 (PS-1), PS-2, Nicastrin (NST), Pen-2 and APH-1. Also, the expression level of NGF receptor $p75^{NTR}$ and RhoA were significantly higher in CMV/hTMP21 transfectants than vehicle transfectants, while their levels returned to vehicle levels after NGF treatment. However, the phosphorylation of NGF receptor TrkA was dramtically decreased in NGF No-treated CMV/hTMP21 transfectants compared with vehicle transfectants, and increased in NGF treated CMV/hTMP21 transfectants. In TrkA downstream signaling pathway, the phosphorylation level of ERK was also decreased in CMV/hTMP21 transfectants, while the phosphorylation of Akt was increased in the same transfectants. Furthermore, NGF treatment induced the increase of phosphorylation level of Akt and ERK in CMV/hTMP21 transfectants. Therefore, these results suggested that over-expression of TMP21may simultaneously induce the up-regulation of $p75^{NTR}$/RhoA expression and the down-regulation of TrkA/ERK phosphorylation through the inhibition of ${\gamma}$-secretase activity.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.2
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• pp.106-115
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• 2011

The aim of this study is to assess the importance of ballast water discharge as a vector for the introduction of exotic species into Pusan and Daesan Ports, Korea. We also examined to understand the impacts of environmental factors on the survival success of introduced species by ship's ballast water in laboratory experiments. Seven ship's ballast water originated from the coastal water of China (Taicang, Ningbo and Jinshan), Japan (Tokuyama, Moji and Akita), and Singapore. According to PCA (principal components analysis) analysis, environmental factor in the each ballast and shipside waters were different by bioregion. Based on cluster analysis, the phytoplankton community structures were distinguished for ballast water origin. Most of the major taxonomic groups were diatoms and, the others were dinoflagellate, silcoflagellate and several fresh-waters species. In particular, species number and standing crops of phytoplankton in the ballast tanks decreased with the increasing age ofballast water(r = -0.35 for standing crop; r = -0.63 for species number). In the laboratory study, although phytoplankton in ballast water treatment did not survive even in optimal temperature, the in vivo fluorescence of phytoplankton viability increased under the nutrient typical of shipside water and F/2 medium at $15^{\circ}C$ and $20^{\circ}C$. The diatoms species such as Skeletonema costatum and Thalassiosira pseudonana in ballast water were successfully regrown. On the salinity gradient experiments for Shui Shan (2) vessel, several freshwater species, brackish and marine species were successfully adapted. Of these, S.costatum was able to tolerate a wide range of salinities (10 to 30 psu) and its species-specific viability was suitable for colonization.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.191-201
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• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.353-359
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• 2018

In this study, the performance between subjective refraction and open-field/closed view autorefraction was estimated. We measured the refractive error of early adults aged 18 to 20 years who did not have eye disease. The differences between measurements obtained by subjective refraction and open-field autorefraction for SE, J0, and J45 were $-0.13{\pm}0.53D$ (p=0.17), $+0.33{\pm}0.68D$ (p=0.01), and $+0.13{\pm}0.68D$ (p=0.26), respectively, with only J0 differing significantly. The differences between the measurements of subjective refraction and closed-view autorefraction for SE, J0, and J45 were $-0.30{\pm}0.42D$ (p=0.00), $+0.30{\pm}0.71D$ (p=0.02), and $-0.02{\pm}0.63D$ (p=0.88), respectively, with only SE and J0 differing significantly. The coefficient of accuracy for SE, J0, and J45 components of open-field and closed-view autorefraction were 1.04, 1.33, and 1.34 and 0.83, 1.40, and 1.24, respectively. It is possible to predict the refractive error, which is necessary when deciding on subjective refraction, by measuring the objective refraction of open-field/closed view autorefractors.