• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.435-452
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• 2016

Land Surface Temperature (LST) has been operationally retrieved from the Communication, Ocean, and Meteorological Satellite (COMS) data by the spilt-window method (CSW_v2.0) developed by Cho et al. (2015). Although the CSW_v2.0 retrieved the LST with a reasonable quality compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, it showed a relatively poor performance for the strong inversion and lapse rate conditions. To solve this problem, the LST retrieval algorithm (CSW_v2.0) was updated using the simulation results of radiative transfer model (MODTRAN 4.0) by considering the diurnal variations of air temperature. In general, the upgraded version, CSW_v3.0 showed a similar correlation coefficient between the prescribed LSTs and retrieved LSTs (0.99), the relatively smaller bias (from -0.03 K to-0.012 K) and the Root Mean Square Error (RMSE) (from 1.39 K to 1.138 K). Particularly, CSW_v3.0 improved the systematic problems of CSW_v2.0 that were encountered when temperature differences between LST and air temperature are very large and/or small (inversion layers and superadiabatic lapse rates), and when the brightness temperature differences and surface emissivity differences were large. The bias and RMSE of CSW_v2.0 were reduced by 10-30% in CSW_v3.0. The indirect validation results using the MODIS LST data showed that CSW_3.0 improved the retrieval accuracy of LST in terms of bias (from -0.629 K to -0.049 K) and RMSE (from 2.537 K to 2.502 K) compared to the CSW_v2.0.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.981-993
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• 2015

The analysis of hydrologic time series data is crucial for the effective management of water resources. Therefore, it has been widely used for the long-term forecasting of hydrologic variables. In tradition, time series analysis has been used to predict a time series without considering exogenous variables. However, many studies using decomposition have been widely carried out with the assumption that one data series could be mixed with several frequent factors. In this study, the empirical mode decomposition method was performed for decomposing a hydrologic time series data into several components, and each component was applied to the time series models, autoregressive moving average (ARMA). After constructing the time series models, the forecasting values are added to compare the results with traditional time series model. Finally, the forecasted estimates from ARMA model with empirical mode decomposition method showed better performance than sole traditional ARMA model indicated from comparing the root mean square errors of the two methods.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.755-765
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• 2013

This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.257-264
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• 2020

Vectorization is currently the main method in feature collection (extraction) during digital mapping using UAV-Photogrammetry. However, this method is time consuming and prone to gross elevation errors when extracted from a DSM (Digital Surface Model), because three-dimensional feature coordinates are vectorized separately: plane information from an orthophoto and height from a DSM. Consequently, the demand for stereo plotting method capable of acquiring three- dimensional spatial information simultaneously is increasing. However, this method requires an expensive equipment, a Digital Photogrammetry Workstation (DPW), and the technology itself is still incomplete. In this paper, we evaluated the accuracy of low-cost stereo plotting system, Menci's StereoCAD, by analyzing its three-dimensional spatial information acquisition. Images were taken with a FC 6310 camera mounted on a Phantom4 pro at a 90 m altitude with a Ground Sample Distance (GSD) of 3 cm. The accuracy analysis was performed by comparing differences in coordinates between the results from the ground survey and the stereo plotting at check points, and also at the corner points by layers. The results showed that the Root Mean Square Error (RMSE) at check points was 0.048 m for horizontal and 0.078 m for vertical coordinates, respectively, and for different layers, it ranged from 0.104 m to 0.127 m for horizontal and 0.086 m to 0.092 m for vertical coordinates, respectively. In conclusion, the results showed 1: 1,000 digital topographic map can be generated using a stereo plotting system with UAV images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.105-112
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• 2018

To determine the position of receiver, the GPS (Global Positioning System) uses position information of satellites and pseudo ranges based on signals. These are reflected by surrounding structures and multipath errors occur. This paper proposes a method for multipath error reduction using digital images to enhance the accuracy. The goal of the study is to calculate the shielding environment of receiver using image processing and apply it to GPS positioning. The proposed method, firstly, performs a preprocessing to reduce the effect of noise on images. Next, it uses hough transform to detect the outline of building roofs and determines mask angles and permissible azimuth range. Then, it classifies the satellites according to the condition using the image processing results. Finally, base on point positioning, it computes the receiver position by applying a weight model that assigns different weights to the classified satellites. We confirmed that the RMSE (Root Mean Square Error) was reduced by 2.29m in the horizontal direction and by 15.62m in the vertical direction. This paper showed the potential for the hybrid of GPS positioning and image processing technology.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.377-377
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• 2012

Microprocessor technology now relies on copper for most of its electrical interconnections. Because of the high diffusivity of copper, Atomic layer deposition (ALD) $TaN_x$ is used as a diffusion barrier to prevent copper diffusion into the Si or $SiO_2$. Another problem with copper is that it has weak adhesion to most materials. Strong adhesion to copper is an essential characteristic for the new barrier layer because copper films prepared by electroplating peel off easily in the damascene process. Thus adhesion-enhancing layer of cobalt is placed between the $TaN_x$ and the copper. Because, cobalt has strong adhesion to the copper layer and possible seedless electro-plating of copper. Until now, metal film has generally been deposited by physical vapor deposition. However, one draw-back of this method is poor step coverage in applications of ultralarge-scale integration metallization technology. Metal organic chemical vapor deposition (MOCVD) is a good approach to address this problem. In addition, the MOCVD method has several advantages, such as conformal coverage, uniform deposition over large substrate areas and less substrate damage. For this reasons, cobalt films have been studied using MOCVD and various metal-organic precursors. In this study, we used $C_{12}H_{10}O_6(Co)_2$ (dicobalt hexacarbonyl tert-butylacetylene, CCTBA) as a cobalt precursor because of its high vapor pressure and volatility, a liquid state and its excellent thermal stability under normal conditions. Furthermore, the cobalt film was also deposited at various $H_2/NH_3$ gas ratio(1, 1:1,2,6,8) producing pure cobalt thin films with excellent conformality. Compared to MOCVD cobalt using $H_2$ gas as a reactant, the cobalt thin film deposited by MOCVD using $H_2$ with $NH_3$ showed a low roughness, a low resistivity, and a low carbon impurity. It was found that Co/$TaN_x$ film can achieve a low resistivity of $90{\mu}{\Omega}-cm$, a low root-mean-square roughness of 0.97 nm at a growth temperature of $150^{\circ}C$ and a low carbon impurity of 4~6% carbon concentration.

• Analytical Science and Technology
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• v.6 no.2
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• pp.167-180
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• 1993

The effects of coating variables on the formation of aluminide coating layer with good oxidation resistance on the strongest hot-forged superalloy in the world, KM 1557 developed at KIST by pack cementation process were studied. Pack aluminizing were performed by high-activity process with pure aluminium powders and by low-activity process with codep powders. For high-activity process, Al deposition rate, growth rate of coating layer, and cross-sectional microstructures were influenced by the species and additive amounts of activators and the additive amounts of pure aluminium powders. For low-activity process, Al deposition rate, growth rate of coating layer, and the cross-sectional microstructures were not influenced by the species but additive amounts of activators. Surface structures of coating layer were influenced by the species of activators. Regardless of aluminium activity, Al deposition rate was proportional to the square root of time and parabolic rate constants were different with the species of activators. The activation energy for deposition of aluminium was different with the species of activators for high-activity process. Regardless of the species of activators, the activation energy for deposition of aluminium was 12~14 Kcal/mole for low-activity process.

• Journal of Korean Physical Therapy Science
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• v.12 no.3
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• pp.47-58
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• 2005

The purpose of this study is to estimate how much the motility of affected and unaffected lower limb respectively would have effects on their ambulation through comparing the difference between their affected and unaffected lower limb and studying the correlation between such difference and their ambulation. In addition, the study also intends to find out remedial measures suitable for improving their ambulation with relevant physical treatment. To do this, a quantitative electromyogram(QEMG) test was done to both quadriceps and hamstring of affected and unaffected lower limb so as to yield IP values. Based on such IP values, RMS(root mean square) values as the total sum of IP values were found with QEMG analysis system (made by Medelec Co.) and then the ambulation depending on the difference in muscular strength were analyzed by ink-foot print method as well as the corresponding statistics were processed by T-test through SPSS. The effect of differences in muscular strength of quadriceps in affected and unaffected limb of hemiplegic patients on their ambulation was also different in each element of ambulation. However, there was not any statistically significant difference (p>.05). The differences in muscular strength of hamstring in unaffected limbs of hemiplegic patients only affect stride length. It was statistically significant. The effect of difference in muscular strength of the hamstring in affected limb of hemiplegic patients on their ambulation was very different between strong and weak group in terms of walking velocity, step per minute, stride and step length, showing statistically significant difference(p<.05). Although there was a difference in the step length of the affected limb, it was not statistically significant(p>.05). For the unaffected hamstring, there were significant differences of stride length between in unaffected limb and in affected limb. For the affected hamstring, there were also significant differences in walking velocity, step per minute, stride and step length. Besides, it was found that the difference of the muscular strength between strong and weak group was at the highest. Thus, the effect of difference in muscular strength on ambulatory factors such as walking velocity, step per minute, stride and step length did not show any statistical significance but differences in affected and unaffected quadriceps. However, it was found that both the difference of stride in unaffected hamstring and the difference of all ambulatory factors except from step length with affected limb had effects on ambulation depending upon muscular strength.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• School Mathematics
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• v.10 no.3
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• pp.357-374
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• 2008

The complex number system is supposed to introduce first chapter in the first grade of high school. When number system is expanded to complex numbers, the main aim is to understand preservation of algebraic structure with regard to the flow of curriculum and textbook. This research reviewed overall alternative articulation and treatment of textbooks from a logical viewpoint. Two research questions are developed below. First, in the structure of the current curriculum, when we consider student's 'level', how are the alternative articulation and treatment of textbooks in complex unit on a logical point of view? Second, What are more logical alternative articulation and treatment? What alternative articulation and treatment are suitable for a running goal? and what are the improvement which is definitive?