• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7A
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• pp.778-784
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• 2007

Predictive channel reservation techniques have widely been studied in mobile cellular networks in order to meet the desired quality-of-service requirements. Those efforts are mostly concentrated on predicting the target cell that a mobile will move to and reserving the channel before the actual handoff, and subsequently reducing handoff-dropping probability and improving bandwidth utilization. In this paper, we propose adaptive reporting schemes that a mobile reports its mobility status information such as position, speed, and direction in an appropriate moment based on the user's mobility pattern characteristics and, hence the network can make a more-accurate prediction on the user's mobility. We show from the simulations that the proposed scheme is capable of keeping target cell prediction more accurate and required number of reporting through the wireless up-link channel lower.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.241-247
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• 2016

The tracking filter plays a key role in the accurate estimation and prediction of maneuvering a vessel's position and velocity when attempting to enhance safety by avoiding collision. Therefore, in order to achieve accurate estimation and prediction, many oceangoing vessels are equipped with the Automatic Radar Plotting Aid (ARPA) system. However, the accuracy of prediction depends on the tracking filter's ability to reduce noise and maintain a stable transient response. The purpose of this paper is to derive the optimal values of the gain parameters used in tracking a High Dynamic Warship. The algorithm employs a ${\alpha}-{\beta}-{\gamma}$ filter to provide accurate estimates and updates of the state variables, that is, positions, velocity and acceleration of the high dynamic warship based on previously observed values. In this study, the filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from set values of the damping parameter, ${\xi}$. Optimization of the damping parameter, ${\xi}$, is achieved experimentally by plotting the residual error against different values of the damping parameter to determine the least value of the damping parameter that results in the optimum smoothing coefficients leading to a reduction in the noise corruption effect. Further investigation of the performance of the filter indicates that optimal smoothing coefficients depend on the initial and average velocity of the target.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.407-419
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• 2008

In this study, the transition Reynolds number of compressible axi-symmetric sharp cone boundary layer is predicted by using a linear stability theory and the -method. The compressible linear stability equation for sharp cone boundary layer was derived from the governing equations on the body-intrinsic axi-symmetric coordinate system. The numerical analysis code for the stability equation was developed based on a second-order accurate finite-difference method. Stability characteristics and amplification rate of two-dimensional second mode disturbance for the sharp cone boundary layer were calculated from the analysis code and the numerical code was validated by comparing the results with experimental data. Transition prediction was performed by application of the -method with N=10. From comparison with wind tunnel experiments and flight tests data, capability of the transition prediction of this study is confirmed for the sharp cone boundary layers which have an edge Mach number between 4 and 8. In addition, effect of wall cooling on the stability of disturbance in the boundary layer and transition position is investigated.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.204-209
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• 2003

In an urban area telecommunication using wireless system, the accurate prediction and analysis of wave propagation characteristics are very important to determine the service area, optimized selection of base station, and cell design, etc. In the stage of these analyses, we have to present the propagation prediction model which is varied with the type of antenna, directional angle, and configuration of the ground in our urban area. In addition we need to perform an analysis of the conventional model which is similar to ours and dig out the parameters to evaluate the wave environment before the cell design for the selected area. In this paper, we propose a wave propagation prediction model concerning the topography and obstacles in our urban area. We extract the parameters and apply them to the proposed wave environment for the simulation analyzing the propagation characteristics. Throughout these analyzing procedure, we extracted the essential parameters such as the position of the base station, the height of topography, and adequate type and height of the antenna with our preferable correctness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.4006-4011
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• 2013

Reverse parking guidance system help driver's safe reverse parking with display of the expected reverse path of the car on portable navigation device or rear-view camera display. In this paper, we suggest a reverse path prediction method of vehicle which reflect the differences in steering angle according to various types of vehicles and calibrate easily the distance error according to the property and the installation position of rear-view camera and we developed reverse parking guidance system with the our reverse path prediction method. This system can be applied to various types of vehicles, a variety of characteristics and installation of rear-view camera and navigation support systems, or portable devices are compatible and easily detachable, can be configured easily.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.23-34
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• 2004

In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

• Atmosphere
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• v.23 no.4
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• pp.453-470
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• 2013

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.332-339
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• 2008

This study was carried out to develop the score table for prediction of landslide hazard in Gyeongsangbuk-Do province. It was studied to 172 places landslided in 23 cities and counties of Gyeongsangbuk-Do province. An analyze of the score table for landslide hazard was carried out through the multiple statistics of quantification method (I) by the computer. Factors effected to landslide occurrence quantity were shown in order of slope position, slope length, bedrock, aspect, forest age, slope form and slope. As results of the development of score table for prediction of landslide hazard in Gyeongsangbuk-Do province, total score range was divided that 107 under is stable area (IV class), 107~176 is area with little susceptibility to landslide (III class), 177~246 is area with moderate susceptibility to landslide (II class), above 247 area with severe susceptibility to landslide (I class).

• Atmosphere
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• v.28 no.4
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• pp.357-367
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• 2018

In this study, the temperature bias of aircraft observation was estimated through comparison with sonde observation prior to developing the temperature bias correction method at the Korea Institute of Atmospheric Prediction Systems (KIAPS). First, we tried to compare aircraft temperature with collocated sonde observations at 0000 UTC on June 22, 2012. However, it was difficult to estimate the temperature bias due to the lack of samples and the uncertainty of the sonde position at high altitudes. Second, we attempted a background innovation comparison for sonde and aircraft using KIAPS Package for Observation Processing (KPOP). The one month averaged background innovation shows the aircraft temperature have a warm bias against sonde for all levels. In particular, there is a globally distinct warm bias about 0.4 K between 200 hPa and 300 hPa corresponding to flight level. Spatially, most of the areas showed the warm bias except for below 300 hPa in some part of China at 0000 and 1200 UTC and below 850 hPa in Australia at 0000 UTC. In general, the temperature bias was larger at 1200 UTC than 0000 UTC. Based on the estimated temperature bias, we have applied the static bias correction method to the aircraft temperature observation. As a result, the warm bias of the aircraft temperature has decreased at most levels, but a slight cold bias has occurred in some areas.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.3
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• pp.72-81
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• 2022

Positions of five drifting buoys deployed on August 2020 near southwestern area of Jeju Island and numerically predicted velocities were used to develop five Artificial Intelligence-based models (AI models) for the prediction of particle tracks. Five AI models consisted of three machine learning models (Extra Trees, LightGBM, and Support Vector Machine) and two deep learning models (DNN and RBFN). To evaluate the prediction accuracy for six models, the predicted positions from five AI models and one numerical model were compared with the observed positions from five drifting buoys. Three skills (MAE, RMSE, and NCLS) for the five buoys and their averaged values were calculated. DNN model showed the best prediction accuracy in MAE, RMSE, and NCLS.