• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.1-8
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• 1999

The estimation technique of surface water temperature by satellite remote sensing has been applied to ocean and large lakes using AVHRR. However, the spatial resolution AVHBR is not abquate for coastal region and small lakes. Landsat 5 TM has 120 m spatial resolution, which suits better. We carried out analysis of surface water temperature in Lake Sihwa and near coastal area using Landsat 5 TM. To relate digital number to the brightness temperature, we applied Empirical, NASA, RESTEC, Quadratic methods. Comparing calculated and observed value, we obtained as follows; NASA method, $R^2=0.9343$, RMSE(Root Mean Square Error)=3.5876$^{\circ}C$; RESTEC method, $R^2=0.8937$, RMSE=3.76$^{\circ}C$; Quadratic method, $R^2=0.8967$, RMSE=2.949$^{\circ}C$. Because Landsat TM has only one band for extracting surface temperature, it was difficult to correct for the atmospheric errors. For improving the accuracy of surface temperature detection using Landsat TM, there is a need for a method to decrease the effect of atmospheric contents.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.315-324
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• 2022

The experimental data obtained in a wave flume were analyzed using machine learning techniques to establish a model that predicts the input wave height of the wavemaker based on the waves that have experienced wave shoaling and to verify the performance of the established model. For this purpose, artificial neural network (NN), the most representative machine learning technique, and Gaussian process regression (GPR), one of the non-parametric regression analysis methods, were applied respectively. Then, the predictive performance of the two models was compared. The analysis was performed independently for the case of using all the data at once and for the case by classifying the data with a criterion related to the occurrence of wave breaking. When the data were not classified, the error between the input wave height at the wavemaker and the measured value was relatively large for both the NN and GPR models. On the other hand, if the data were divided into non-breaking and breaking conditions, the accuracy of predicting the input wave height was greatly improved. Among the two models, the overall performance of the GPR model was better than that of the NN model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.113-128
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• 2024

Items of road tunnel PISD (Precise Inspection for Safety and Diagnosis) were reviewed and analyzed using newly enhanced MMS (Mobile Mapping System) technology. Possible items with MMS can be visual inspection, survey and non-destructive test, structural analysis, and maintenance plan. The resolution of 3D point cloud decreased when the vehicle speed of MMS is too fast while the calibration error increased when it is too slow. The speed measurement of 50 km/h is determined to be effective in this study. Although image resolution by MMS has a limit to evaluating the width of crack with high precision, it can be used as data to identify the status of facilities in the tunnel and determine whether they meet disaster prevention management code of tunnel. 3D point cloud with MMS can be applicable for matching of cross-section and also possible for the variation of longitudinal survey, which can intuitively check vehicle clearance throughout the road tunnel. Compared with the measurement of current PISD, number of test and location of survey is randomly sampled, the continuous measurement with MMS for environment condition can be effective and meaningful for precise estimation in various analysis.

• Journal of Korean Society of Forest Science
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• v.46 no.1
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• pp.29-43
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• 1980

The sampling methods selected for this area was (1) Simple random sampling (2) Systematic sampling and (3) Sub-sampling. For the calculation of the number of sampling plot, 10 % coefficient of variation was adapted. As a result, 57 plots each for simple random sampling and systematic sampling was calculated. In the sub-sampling method, however, total of 40 plots, which were consisted of 5 Blocks, secondary 4 major units and tertiary 2 minor units, were examined. The reuslts obtained are summarized as follows : 1. The rate of expected error was 9.24% for simple random sampling, 8.36% for systematic sampling and 7.54% for sub-sampling, respectively. Therefore, the sub-sampling was proved to be the most accurate method among the test. 2. The volume calculated by each sampling method was compared to the volume of all stand. The rate of expected error was also lowest in the sub-sampling (0.39%), followed by systematic sampling (4.18%) and simple random sampling (7.92%). 3. Comparing the various reuslts and analysis of these results, the sub-sampling was regarded as the most rapid and economical method because this method had not only the least number of plots but also the least expected error among the tested sampling methods Therefore the sub-sampling is proved to be an ideal sampling method for forest survey.

• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.3 s.10
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• pp.151-163
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• 2003

In this study, the algorithm of groundwater flow process was established for koreanized groundwater program development dealing with the geographic and geologic conditions of the aquifer have dynamic behaviour in groundwater flow system. All the input data settings of the 3-DFM model which is developed in this study are organized in Korean, and the model contains help function for each input data. Thus, it is designed to get detailed information about each input parameter when the mouse pointer is placed on the corresponding input parameter. This model also is designed to easily specify the geologic boundary condition for each stratum or initial head data in the work sheet. In addition, this model is designed to display boxes for input parameter writing for each analysis condition so that the setting for each parameter is not so complicated as existing MODFLOW is when steady and unsteady flow analysis are performed as well as the analysis for the characteristics of each stratum. Descriptions for input data are displayed on the right side of the window while the analysis results are displayed on the left side as well as the TXT file for this results is available to see. The model developed in this study is a numerical model using finite differential method, and the applicability of the model was examined by comparing and analyzing observed and simulated groundwater heads computed by the application of real recharge amount and the estimation of parameters. The 3-DFM model is applied in this study to Sehwa-ri, and Songdang-ri area, Jeju, Korea for analysis of groundwater flow system according to pumping, and obtained the results that the observed and computed groundwater head were almost in accordance with each other showing the range of 0.03 - 0.07 error percent. It is analyzed that the groundwater flow distributed evenly from Nopen-orum and Munseogi-orum to Wolang-bong, Yongnuni-orum, and Songja-bong through the computation of equipotentials and velocity vector using the analysis result of simulation which was performed before the pumping started in the study area. These analysis results show the accordance with MODFLOW's.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.169-206
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• 2009

This study stems from a question, "How should we understand the pattern of the Korean economy after the 1990s?" Among various analytic methods applicable, this study chooses a Structural Vector Autoregression (SVAR) with long-run restrictions, identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts. To that end, SVAR is applied to four economic models; Blanchard and Quah (1989)'s 2-variable model, its 3-variable extensions, and the two other New Keynesian type linear models modified from Stock and Watson (2002). Especially, the latter two models are devised to reflect the recent transitions in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting). When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea's economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea's high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of each sector on overall economic status. Despite the fact that a diverse mixture of models and impacts has been used for analysis, always two common findings are observed in the result. Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea's potential growth rate. The contents of this paper are constructed as follows: The second section observes the recent trend of the economic development of Korea and related Korean articles, which might help in clearly defining the scope and analytic methodology of this study. The third section provides an analysis model to be used in this study, which is Structural VAR as mentioned above. Variables used, estimation equations, and identification conditions of impacts are explained. The fourth section reports estimation results derived by the previously introduced model, and the fifth section concludes.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.287-294
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• 2021

In order to expand facility agriculture and reduce greenhouse construction costs in reclaimed land, a greenhouse foundation method that satisfies economic feasibility and structural safety at the same time is required. As an alternative, the allowable bearing capacity and settlement were reviewed when the DCM(Deep cement mixing) method was applied among the soft ground reinforcement methods. To examine the applicability of the greenhouse foundation, the allowable bearing capacity and settlement were calculated by applying the theory of Terzaghi, Meyerhof, Hansen, and Schmertmann. In case of the diameter of 800mm and the width and length of the foundation of 4m, the allowable bearing capacity was 179kN/m² and the settlement was 7.25mm, which satisfies the required bearing capacity and settlement standards. The calculation results were verified through FEM(Finite element method) analysis using the Mohr-Coulomb material model. The allowable bearing capacity was 169kN/m² and the settlement was 2.52mm. The bearing capacity showed an error of 5.6% compared to calculated value, and the settlement showed and error of 65.4%. Through theoretical calculations and FEM analysis, it was confirmed that the allowable bearing capacity and settlement satisfies the design criteria as a greenhouse foundation when the width and length of the foundation were 4m. Based on the verified design values, it is expected to be able to present the foundation design criteria for greenhouses through empirical tests such as bearing capacity tests and long-term settlement monitoring.