• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.7-17
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• 2014

This technical paper deals with development of on-board orbit generation algorithm for GEO Satellite. This paper presents the research analysis results performed in order to improve the accuracy of the existing algorithm used for generating real-time orbit information for GEO satellite. The error impact on orbit accuracy due to the orbit error sources were analyzed with the algorithm suggested by this research. As a result of the analyses, it is found that the initial orbit should be determined with an accuracy of less than 50 m and the reference position angle error for the ground station and the satellite should be maintained within ${\pm}0.0025deg$ in order to meet the orbit accuracy specification. The development of on-board flight software based on the new algorithm was accomplished and the performance verification is ongoing by using a software based performance verification tool.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.2
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• pp.37-45
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• 2007

A lot of conventional algorithms has tried to cancel the Residual Frame Synchronization Error (RFSE), which causes the performance degradation of channel estimation when using interpolation in lattice-type pilot-aided Time Division Duplex (TDD) OFDM systems. Among them, a pre- and post-compensation method has been attractive to eliminate the effects of RFSE, providing good performance but requiring high computational complexity. In this paper we propose a new method which lowers computational costs by adjusting the starting point of TDD OFDM systems' FFT window in order to compensate for the RFSE. For the performance verification, we apply the proposed method to IEEE 802.16e standard and also estimate additionally required computational power of it compared to the pre- and post-compensation method. Simulation and implementation results show that the proposed algorithm has performance similar to the conventional method and is very efficient with low power implementation, requiring only 4.9 % of the power which the conventional method needs additionally.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4
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• pp.71-79
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• 1992

In general, the accelerogram of earthquake ground motion or the accelerogram obtained from dynamic tests contain various errors. In these errors of the accelerograms, there are instrumental errors(magnitude and phase distortion) due to the response characteristics of accelerometer and the digitizing error concentrated in low and high frequency components and random errors. Then, these errors may be detrimental to the results of data processing and dynamic analysis. An efficient method which can correct the errors of the accelerogram is proposed in this study. The correction of errors can be accomplished through four steps as followes ; 1) using an interpolation method a data form appropriate to the error correction is prepared, 2) low and high frequency errors of the accelerogram are removed by band-pass filter between prescribed frequency limits, 3) instrumental errors are corrected using dynamic equilibrium equation of the accelerometer, 4) velocity and displacement are obtained by integrating corrected accelerogram. Presently, infinite impulse response(IIR) filter and finite impulse response (FIR) filter are generally used as band-pass filter. In the proposed error correction procedure, the deficiencies of FIR filter and IIR filter are reduced and, using the properties of the differentiation and the integration of Fourier transform, the accuracy of instrument correction and integration is improved.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.316-323
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• 2001

Gamut mapping is a technique that acts on cross-media color reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends on the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device- independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using three-dimensional interpolation.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.8-16
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• 2023

In Japan, high-speed ground transportation service using linear motors at speeds of 500 km/h is scheduled to begin in 2027. To accommodate 5G services in trains, a subcarrier spacing frequency of 30 kHz will be used instead of the typical 15 kHz subcarrier spacing to mitigate Doppler effects in such high-speed transport. Furthermore, to increase the cell size of the 5G mobile system, multiple base station antennas will transmit identical downlink (DL) signals to form an expanded cell size along the train rails. In this situation, the forward and backward antenna signals are Doppler-shifted in opposite directions, respectively, so the receiver in the train may suffer from estimating the exact Channel Transfer Function (CTF) for demodulation. In a previously published paper, we proposed a channel estimator based on Delay and Doppler Profiler (DDP) in a 5G SISO (Single Input Single Output) environment and successfully implemented it in a signal processing simulation system. In this paper, we extend it to 2×2 MIMO (Multiple Input Multiple Output) with spatial multiplexing environment and confirm that the delay and DDP based channel estimator is also effective in 2×2 MIMO environment. Its simulation performance is compared with that of a conventional time-domain linear interpolation estimator. The simulation results show that in a 2×2 MIMO environment, the conventional channel estimator can barely achieve QPSK modulation at speeds below 100 km/h and has poor CNR performance versus SISO. The performance degradation of CNR against DDP SISO is only 6dB to 7dB. And even under severe channel conditions such as 500km/h and 8-path inverse Doppler shift environment, the error rate can be reduced by combining the error with LDPC to reduce the error rate and improve the performance in 2×2 MIMO. QPSK modulation scheme in 2×2 MIMO can be used under severe channel conditions such as 500 km/h and 8-path inverse Doppler shift environment.

• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.614-630
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• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Spatial Information Research
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• v.7 no.1
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• pp.1-12
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• 1999

The DTM(Digital Terrain Model) in GIS(Geographical Information System) shows the elevation from interpolation using data points surveyed. In panoramic flat landform, pixel size, resolution of source data may not be the problem in using DTM However, in mountainous landform like Korea, appropriate resolution accuracy of source data are important factors to represent the topography concerned. In this study, the difference in contour interval of source data, the resolution after interpolation, and different data structures were compared to figure out the accuracy of slope calculation using DTM from the topographic maps of Togyusan National Park Two types of GIS softwares, Idrisi(grid) ver. 2.0 using the altitude matrices and ArcView(TIN) ver. 3.0a using TIN were used for this purpose. After the analysis the conclusions are as follows: 1) The coarser resolution, the more smoothing effect inrepresenting the topography. 2) The coarser resolution the more difference between the grid-based Idrisi and the TIN-based ArcView. 3) Based on the comparison analysis of error for 30 points from clustering, there is not much difference among 10, 20, 30 m resolution in TIM-based Airview ranging from 4.9 to 6.2n However, the coarser resolution the more error for elevation and slope in the grid-based Idrisi. ranging from 6.3 to 10.9m. 4) Both Idrisi and ArcView could net consider breaklines of lanform like hilltops, valley bottoms.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.33-47
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• 1995

The representation of point-observed environmental variables in Geographic Information Systems(GIS) has often been inadequate to meet the need of regional-scale ecological and environmental applications. To create a map of continuous surface that would represent more reliable spatial variations for these applications, I present three spatial estimation methods. Using a secondary variable of the proximity to coast line together with rainfall acidity data collected at the 63 acid rain monitoring stations in Korea, average rainfall acidity map was cteated using co-kriging. For comparison, two other commonly used interpolation methods (inverse distance weighting and kriging) were also applied to rainfall acidity data without reference to the secondary variable. These estimation methods were evaluated by both visual assessments of the output maps and the quantitative comparison of error measures that were obtained from cross validation. The co-kriging method produced a rainfall acidity map that showed noticeable improvement in repoducing the inherent spatial pattern as well as provided lower statistical error as compared to the methods using only the primary variable.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.125-140
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• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.