• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.465-474
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• 2009

Convective/stratiform radar echo classification schemes by Steiner et al. (1995) and Biggerstaff and Listemaa (2000) are examined on a monsoonal front during the summer monsoon-Changma period, which is organized as a cloud cluster with mesoscale convective complex. Target radar is S-band with wavelength of 10cm, spatial resolution of 1km, elevation angle interval of 0.5-1.0 degree, and minimum elevation angle of 0.19 degree at Jindo over the Korean Peninsula. For verification of rainfall amount retrieved from the echo classification, ground-based rain gauge observations (Automatic Weather Stations) are examined, converting the radar echo grid data to the station values using the inverse distance weighted method. Improvement from the echo classification is evaluated based on the correlation coefficient and the scattered diagram. Additionally, an optimal use method was designed to produce combined rainfalls from the radar echo and Tropical Rainfall Measuring Mission Precipitation Radar (TRMM/PR) data. Optimal values for the radar rain and TRMM/PR rain are inversely weighted according to the error variance statistics for each single station. It is noted how the rainfall distribution during the summer monsoon frontal system is improved from the classification of convective/stratiform echo and the use of the optimal use technique.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.161-167
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• 2021

This paper proposes a new personalized HRTF estimation method which is based on a deep neural network (DNN) model and improved elevation reproduction using a notch filter. In the previous study, a DNN model was proposed that estimates the magnitude of HRTF by using anthropometric measurements [1]. However, since this method uses zero-phase without estimating the phase, it causes the internalization (i.e., the inside-the-head localization) of sound when listening the spatial sound. We devise a method to estimate both the magnitude and phase of HRTF based on the DNN model. Personalized HRIR was estimated using the anthropometric measurements including detailed data of the head, torso, shoulders and ears as inputs for the DNN model. After that, the estimated HRIR was filtered with an appropriate notch filter to improve elevation reproduction. In order to evaluate the performance, both of the objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated HRTF are measured. For subjective evaluation, the MUSHRA test and preference test are conducted. As a result, the proposed method can make listeners experience more immersive audio than the previous methods.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.23 no.1
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• pp.18-24
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• 1987

For the purpose of getting the accuracy of NNSS fix, the continuous observation was performed to search the factors affecting the accuracy of NNSS fix, and then to examine their effects. The observation was made at Lat. $35^{\circ}'||'&'||'<\TEX>05'04"N, Long. '||'&'||'129^{\circ}'||'&'||'<\TEX> 02'13"E from 28th January to 20th July in 1985. Accuracy of the position fixed in accordance with the observation time, each satellite, elevation angle doppler count, passed direction of each satellite and the antenna height were analyzed. The results obtaines are summerized as follows: 1. The deflaetion error is reduced to 0.21 miles when the geodetic system of the calculating the position converted from WGS-72 to Bessel. 2. When the elevation angle of the mountain is high, or the range of the elevation angle of satellite is 20-70 degrees, the position fixed comes nearest the true position. 3. The position fixed is more accurate on the condition that doppler count is more than 21, and at night than in daytime. 4. The accuracy of the position fixed is more seriously affected when the input data of the antenna height has considerable errors. But there occures almost little difference in the accuracy of position according to each satellite.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1313-1321
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• 2000

In recent years LEO(Low Earth Orbit) satellite communication systems have gained a lot of interest as high speed multimedia services by satellite are about to be provided. It is mandatory to use very efficient ECC(Error Correcting Code) to support high speed multimedia services over LEO satellite channel. Turbo codes developed by Berrou et al. in 1993 have been actively researched since it can achieve a performance close to the Shannon limit. In this paper, a LEO satellite channel model is adopted and the fading characteristics of LEO satellite channel are analyzed for the change of elevation angle in various propagation environments. The performance of turbo code is analyzed and compared to that of conventional convolutional code using the satellite channel model. In the simulation results using the Globalstar orbit constellations, performance of turbo codes shows 1.0~2.0dB coding gain compared to that of convolutional codes over all elevation angle and propagation environment ranges we have investigated. The performance difference resulting from the change of elevation angle in various propagation environments and the performance of different ECC are analyzed in detail, so that the results can be applied to choose an appropriate ECC scheme for various system environment.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.299-303
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• 2018

Generally, when predicting the accuracy of the anti-air artillery system, the error is classified as fixed bias, variable bias, and random error. Then the standard deviation on the target is expressed as the square root of the squared sum of each error value which comes from the random error and variable bias and in the case of fixed bias, the mean value is shifted as the sum of errors from the fixed bias. At this time, the variables indicating the displacement of the direction of azimuth and elevation direction with regard to the change of the unit value of each error are weighted. These errors are then used to predict the system's delivery accuracy through a normally distributed integral. This paper presents a method of predicting system accuracy by considering the correlation of errors. This approach shows that it helps to predict the delivery accuracy of the system, precisely.

• Journal of Korean Society on Water Environment
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• v.34 no.3
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• pp.328-338
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• 2018

The objective of this study was to evaluate the applicability of a HSPF (Hydrological Simulation Program-Fortran) model for runoff estimation in the Namgang dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input for the HSPF model, which was calibrated and validated using observed runoff data from 2004 to 2015 for three stations (Sancheong, Shinan, Changchon) in the study watershed. Parameters for runoff calibration were selected based on the user's manual and references, and parameter calibration was done by trial and error. The $R^2$ (determination coefficient), RMSE (root-mean-square error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (relative mean absolute error) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within a ${\pm}5%$ error in Sancheong and Shinan, whereas there was a14% error in Changchon. The model performance criteria for calibration and validation showed that $R^2$ ranged from 0.80 to 0.92, RMSE was 2.33 to 2.39 mm/day, NSE was 0.71 to 0.85, and RMAE was 0.37 to 0.57 mm/day for daily runoff. Visual inspection showed that the simulated daily flow, monthly flow, and flow exceedance graph agreed well with observations for the Sancheong and Shinan stations, whereas the simulated flow was higher than observed at the Changchon station.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.69-77
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• 2019

The objective of this study was to calibrate and validate the HSPF (Hydrological Simulation Program-Fortran) model for estimating the runoff of the Hapcheon dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input data for the HSPF model. Observed runoff data from 2000 to 2016 in study watershed were used for calibration and validation. Hydrologic parameters for runoff calibration were selected based on the user's manual and references, and trial and error method was used for parameter calibration. The $R^2$, RMSE (root-mean-square error), RMAE (relative mean absolute error), and NSE (Nash-Sutcliffe efficiency coefficient) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within ${\pm}4%$ error. The model performance criteria for calibration and validation showed that $R^2$ was in the rang of 0.78 to 0.83, RMSE was 2.55 to 2.76 mm/day, RMAE was 0.46 to 0.48 mm/day, and NSE was 0.81 to 0.82 for daily runoff. The amount of inflow to Hapcheon Dam was calculated from the calibrated HSPF model and the result was compared with observed inflow, which was -0.9% error. As a result of analyzing the relation between inflow and storage capacity, it was found that as the inflow increases, the storage increases, and when the inflow decreases, the storage also decreases. As a result of correlation between inflow and storage, $R^2$ of the measured inflow and storage was 0.67, and the simulated inflow and storage was 0.61.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.9-13
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• 2022

In this paper, the tracking error of monopulse radar caused by cross-eye jamming using terrain bounce is analyzed. Cross-eye jamming is a method of generating an error in a radar tracking system by simultaneously transmitting two signals with different phases and amplitudes. When the monopulse radar receives the cross-eye jamming signal generated by the terrain bounce, a tracking error occurs in the elevation direction. In the presence of multipath, this signal is a combination of the direct target return and a return seemingly emanating from the target image beneath the terrain surface. Terrain bounce jamming has the advantage of using a single jammer, but the space affecting the jamming is limited by the terrain reflection angle and the degree of scattering of the terrain. This study can be usefully used to protect ships from low-altitude missiles or aircraft in the sea.

• Journal of Ecology and Environment
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• v.41 no.4
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.9-19
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• 2016

The objective of this study was to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for runoff estimation in the Nam river dam watershed. Input data for the SWAT model were established using spatial data (land use, soil, digital elevation map) and weather data. The SWAT model was calibrated and validated using observed runoff data from 2003 to 2014 for three stations (Sancheong, Shinan, Changchon) within the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Parameters for runoff calibration were selected based on user's manual and references and trial and error method was applied for parameter calibration. Calibration results showed that annual mean runoff were within ${\pm}5%$ error compared to observed. $R^2$ were ranged 0.64 ~ 0.75, RMSE were 2.51 ~ 4.97 mm/day, NSE were 0.48 ~ 0.65, and RMAE were 0.34 ~ 0.63 mm/day for daily runoff, respectively. The runoff comparison for three stations showed that annual runoff was higher in Changchon especially summer and winter seasons. The flow exceedance graph showed that Sancheong and Shinan stations were similar while Changchon was higher in entire fraction.