• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.421-430
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• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.1-7
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• 2021

Since recently only an auto-correlated superposition coding (SC) scheme for non-orthogonal multiple access(NOMA) has been investigated, this paper proposes a cross-correlated SC scheme for NOMA. First, we derive the closed-form expression of the sum rate of the proposed cross-correlated SC scheme. Then, numerical analyses demonstrate that the sum rate of the proposed cross-correlated SC scheme is larger than that of the conventional auto-correlated SC scheme. We also show that for the stronger channel gain user, the signal-to-noise ratio (SNR) gain of the proposed cross-correlated SC scheme is about 15, compared with the conventional auto-correlated SC scheme. As a result, the proposed cross-correlated SC scheme could be a promising technology for 6G ultra-reliable low-latency communications (URLLC).

• Imaging Science in Dentistry
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• v.52 no.1
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• pp.43-51
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• 2022

Purpose: The aim of this study was to evaluate the reliability of the Vectra M3 (3D Imaging System; Canfield Scientific, Parsippany, NJ, USA) in detecting chin asymmetry, and to assess whether the automatic markerless tracking function is reliable compared to manually plotting landmarks. Materials and Methods: Twenty subjects (18 females and 2 males) with a mean age of 42.5±10.5 years were included. Three-dimensional image acquisition was carried out on all subjects with simulated chin deviation in 4 stages (1-4 mm). The images were analyzed by 2 independent observers through manually plotting landmarks and by Vectra software auto-tracking mode. Repeated-measures analysis of variance and the Tukey post-hoc test were performed to evaluate the differences in mean measurements between the 2 operators and the software for measuring chin deviation in 4 stages. The intraclass correlation coefficient (ICC) was calculated to estimate the intra- and inter-examiner reliability. Results: No significant difference was found between the accuracy of manually plotting landmarks between observers 1 and 2 and the auto-tracking mode (P=0.783 and P=0.999, respectively). The mean difference in detecting the degree of deviation according to the stage was <0.5 mm for all landmarks. Conclusion: The auto-tracking mode could be considered as reliable as manually plotted landmarks in detecting small chin deviations with the Vectra^® M3. The effect on the soft tissue when constructing a known dental movement yielded a small overestimation of the soft tissue movement compared to the dental movement (mean value<0.5 mm), which can be considered clinically non-significant.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.252-258
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• 2007

There has been a lot of research done in scheme guaranteeing user's mobility and effective resources management to satisfy the requested by users in the wireless/mobile networks. In this paper, we propose a predictive resource allocation scheme based on ARMA(Auto Regressive Moving Average) prediction model to meet QoS requirements(handoff dropping rate) for guaranteeing users' mobility. The proposed scheme predicts the demanded amount of resource in the future time by ARMA time series prediction model, and then reserves it. The ARMA model can be used to take into account the correlation of future handoff resource demands with present and past handoff demands for provision of targeted handoff dropping rate. Simulation results show that the proposed scheme outperforms the existing RCS(Reserved channel scheme) in terms of handoff connection dropping rate and resource utilization.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.5
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• pp.569-581
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• 2003

A method of synthetic time series generation was developed and applied to the simulation of homogeneous turbulence in a periodic 3 - D box and the hourly wind data simulation. The method can simulate almost exact sample auto and cross correlations of multiple time series and control non-Gaussian distribution. Using the turbulence simulation, influence of correlations, non-Gaussian distribution, and one-direction anisotropy on homogeneous structure were studied by investigating the spatial distribution of turbulence kinetic energy and enstrophy. An hourly wind data of Typhoon Robin was used to illustrate a capability of the method to simulate sample cross correlations of multiple time series. The simulated typhoon data shows a similar shape of fluctuations and almost exactly the same sample auto and cross correlations of the Robin.

• Journal of Auto-vehicle Safety Association
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• v.7 no.4
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• pp.16-19
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• 2015

FMVSS226 Ejection Mitigation Impact Test is usually performed by real vehicle. But it is necessary to perform the test using by Reinforced B.I.W. with considering vehicle developing timing and roof rail airbag (RRAB) supplier capacity. We sometimes need tendency (quick data) instead of slow accurate data to fix RRAB design as proper timing. Test with Reinforced B.I.W. is helpful saving time and cost. But it should be confirmed how much different between vehicle conditioned test result and Reinforced B.I.W. conditioned test result. There are some points to be improved even in the test with vehicle. Understanding of deviation of Reinforced B.I.W. conditioned test result from vehicle conditioned test result is needed to get benefits with using Reinforced B.I.W. conditioned in the test.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.4 s.247
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• pp.287-297
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• 2006

The Holographic Particle Velocimetry system can be a promising optical tool for the measurements of three dimensional particle velocities. One of inherent limitations of particle holography is the very long depth of field of particle images, which causes considerable difficulty in the determination of particle positions in the optical axis. In this study, we introduced three auto-focusing parameters corresponding to the size of particles, namely, Correlation Coefficient, Sharpness Index, and Depth Intensity to determine the focal plane of a particle along the optical axis. To investigate the suitability of the above parameters, the plane image of dot array screens containing different size of dots was recorded by diffused illumination holography and the positions of each dot in the optical axis were evaluated. In addition, the effect of particle position from the holographic film was examined by changing the distance of the screen from the holographic film. All measurement results verified that the evaluated positions using suggested auto-focusing parameters remain within acceptable range of errors. These research results may provide fundamental information for the development of the holographic velocimetry system based on the automatic image processing.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.89-98
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• 2020

Prediction of clock behaviors is necessary to generate very high stable system time which is essential for a satellite navigation system. For the purpose, we applied the Auto-Regressive Integrated Moving Average (ARIMA) model to the prediction of two hydrogen masers' behaviors with respect to the rapid Coordinated Universal Time (UTCr). Using the packaged programming language R, we made an analysis and prediction of time series data of [UTCr - clocks]. The maximum variation width of the residuals which were obtained by the difference between the predicted and measured values, was 6.2 ns for 106 days. This variation width was just one-sixth of [UTCr-UTC (KRIS)] published by the BIPM for the same period. Since the two hydrogen masers were found to be strongly correlated, we applied the Vector Auto-Regressive Moving Average (VARMA) model for more accurate prediction. The result showed that the prediction accuarcy was improved by two times for one hydrogen maser.

• Asia pacific journal of information systems
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• v.26 no.4
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• pp.526-541
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• 2016

This research aims to examine the predictive power of multiple online stock message boards, namely, NAVER Finance and PAXNET, which are the most popular stock message boards in South Korea, in stock market activities. If predictive power exists, we then compare the predictive power of multiple online stock message boards. To accomplish the research purpose, we constructed a panel data set with close price, volatility, Spell out acronyms at first mention.PER, and number of posts in 40 companies in three months, and conducted a panel vector auto-regression analysis. The analysis results showed that the number of posts could predict stock market activities. In NAVER Finance, previous number of posts positively influenced volatility on the day. In PAXNET, previous number of posts positively influenced close price, volatility, and PER on the day. Second, we confirmed a difference in the prediction power for stock market activities between multiple online stock message boards. This research is limited by the fact that it only considered 40 companies and three stock market activities. Nevertheless, we found correlation between online stock message board and stock market activities and provided practical implications. We suggest that investors need to focus on specific online message boards to find interesting stock market activities.