• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.501-512
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• 2005

This research supposed when a fictitious KSIV-I space launch vehicle launches from NARO space center. This compared and analyzed the results from real-time trajectory estimation using the Extended Kalman Filter and the Unscented Kalman Filter. A virtual trajectory and observation data are generated for the fictitious KSLV-I and three measurement radars. The performances of both Otters are compared for several simulations with small initial errors, large initial errors, 20Hz and 10Hz data rate. The results show that the Unscented Kalman Filter yields faster convergence and more accurate than the Extended Kalman Filter for the cases with larger initial error and slower data rate conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.271-277
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• 2017

As a result of rapid industrialization, air pollutants are seriously threatening the health of the people, the forecast is becoming more and more important. In forecasting air quality, it is very important to create a reliable initial field because the initial field input to the air quality forecasting model affects the accuracy of the forecast. There are several methods for enhancing the initial field input. One of the necessary techniques is data assimilation. The number of operations and the time required for such data assimilation is exponentially increased as the forecasting area is widened and the number of observation sites increases. Therefore, as the forecast size increases, it is difficult to apply the existing sequential processing method to a field requiring fast processing speed. In this paper, we propose a method that can process Cresman's method, which is one of the data assimilation techniques, in real time using CUDA. As a result, the proposed parallel processing method using CUDA improved at least 35 times faster than the conventional sequential method and other parallel processing methods.

• Atmosphere
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• v.25 no.4
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• pp.623-637
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• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• Journal of the Korean Society of Combustion
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• v.8 no.2
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• pp.41-49
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• 2003

Ultrasonic field of 28kHz with sound pressure level 162dB has been employed to agglomerate the fine soot particle produces in a diffusion flame in a chamber. The agglomeration process has been investigated with digital camcorder and analysed in terms of the decrease of number density with exposure time. From the observation of agglomeration process, the initial agglomeration has been carried out during the short time, and it has been dominated by the orthokinetic collision. Thereafter, a slower agglomeration mechanism, driven by acoustic streaming in the chamber takes over and agglomeraters grew to diameters of several millimeters were levitated at the pressure node of the acoustic wave. And, the circular disk shape of large agglomeraters with the rotational and translational motion is observed.

• Journal of Periodontal and Implant Science
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• v.38 no.3
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• pp.529-534
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• 2008

Purpose: The objective of this study was to compare initial implant stability measured by RFA between different implant systems during the initial healing period. Material and Methods: Fifty-four patients (36 males/18 females) who had been treated at the Department of Periodontology, Chonbuk National University Dental Hospital during the period between January and November in 2007 were included in the study. The mean age of the subjects was 49 years old (18 to 77). A total of 104 implants (Type A: 3i $Osseotite^{(R)}$, Type B: $Replace^{(R)}$ select, Type C: ITI implant) were placed following the manufacturer's standard surgical protocols. Implant stability quotient (ISQ) readings were obtained for each implant at the time of surgery, 2-, and 4-month postoperatively. Result: No implant was failed during the observation period. At the baseline, the difference between mean ISQ values of 3 implant systems was statistically significant (p<0.05). However, at 2-, and 4-month following implant surgery, no significant difference was observed between ISQ values of the implant systems. In the same implant, the ISQ values of Type B and C implants increased (p<0.05), but those of Type A implants decreased during the 2-month healing period. The mean ISQ values of Type B and C implants showed a increasing tendency, while those of Type A implants were stable for the 4-month follow-up period. Conclusion: Within limits of this study, it can be concluded that implant design and surface topography of implant might influence the ISQ value and changing pattern during the initial healing period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.375-387
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• 2012

This paper proposes a new real-time object tracking algorithm using particle filters with color and texture features in moving CCD camera images. If the user selects an initial object, this region is declared as a target particle and an initial state is modeled. Then, N particles are generated based on random distribution and CS-LBP (Centre Symmetric Local Binary Patterns) for texture model and weighted color distribution is modeled from each particle. For observation likelihoods estimation, Bhattacharyya distance between particles and their feature models are calculated and this observation likelihoods are used for weights of individual particles. After weights estimation, a new particle which has the maximum weight is selected and new particles are re-sampled using the maximum particle. For performance comparison, we tested a few combinations of features and particle filters. The proposed algorithm showed best object tracking performance when we used color and texture model simultaneously for likelihood estimation.

• Journal of Astronomy and Space Sciences
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• v.21 no.3
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• pp.221-232
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• 2004

Gauss method for the initial orbit determination was tested using angle-only data obtained by orbit propagation using TLB and SGP4/SDP4 orbit propagation model.. As the analysis of this simulation, a feasible time span between observation time of satellite resulting the minimum error to the true orbit was found. Initial orbit determination is performed using observational data of GPS 26 and Koreasat 2 from 0.6m telescope of KAO(Korea Astronomy Observatory) and precise orbit determination is also performed using simulated data. The result of precise orbit determination shows that the accuracy of resulting orbit is related to the accuracy of the observations and the number of data.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2161-2166
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• 2009

It is important for 0-6 hour nowcasting to provide for a high-quality initial condition in a meso-scale atmospheric model by a data assimilation of several observation data. The polarimetric radar data is expected to be assimilated into the forecast model, because the radar has a possibility of measurements of the types, the shapes, and the size distributions of hydrometeors. In this paper, an impact on rainfall prediction of the data assimilation of hydrometeor types (i.e. raindrop, graupel, snowflake, etc.) is evaluated. The observed information of hydrometeor types is estimated using the fuzzy logic algorism. As an implementation, the cloud-resolving nonhydrostatic atmospheric model, CReSS, which has detail microphysical processes, is employed as a forecast model. The local ensemble transform Kalman filter, LETKF, is used as a data assimilation method, which uses an ensemble of short-term forecasts to estimate the flowdependent background error covariance required in data assimilation. A heavy rainfall event occurred in Okinawa in 2008 is chosen as an application. As a result, the rainfall prediction accuracy in the assimilation case of both hydrometeor types and the Doppler velocity and the radar echo is improved by a comparison of the no assimilation case. The effects on rainfall prediction of the assimilation of hydrometeor types appear in longer prediction lead time compared with the effects of the assimilation of radar echo only.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1078-1082
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• 1997

The distance in load parameter space to the closest voltage collapse point provides the worst case power margin and the left eigenvector identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper presents the results of the comparative performance study of the algorithms, which are applicable to a large scale power system, for computing the closest saddle node bifurcation (CSNB) point. Dobson's iterative method converges with robustness. However the slow process of updating the load increasing direction makes the algorithm less efficient. The direct method converges very quickly. But it diverges if the initial guess is not very close to CSNB. Zeng's method of estimating the approximate critical point in the pre-determined direction is attractive in the sense that it uses only using load flow equations. However, the method is found to be less efficient than Dobson's iterative method. It may be concluded from the above observation that the direct method with the initial values obtained by carrying out the iterative method twice is most efficient at this time and more efficient algorithms are needed for on-line application.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.20-27
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• 2011

A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.