• Atmosphere
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• v.32 no.4
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• pp.395-409
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• 2022

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

• Speech Sciences
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• v.5 no.1
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• pp.7-21
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• 1999

This paper proposes an improved training procedure in speech recognition based on the continuous density of the Hidden Markov Model (CDHMM). Of the three parameters (initial state distribution probability, state transition probability, output probability density function (p.d.f.) of state) governing the CDHMM model, we focus on the third parameter and propose an efficient algorithm that determines the p.d.f. of each state. It is known that the resulting CDHMM model converges to a local maximum point of parameter estimation via the iterative Expectation Maximization procedure. Specifically, we propose two independent algorithms that can be embedded in the segmental K -means training procedure by replacing relevant key steps; the adaptation of the number of mixture Gaussian p.d.f. and the initialization using the CDHMM parameters previously estimated. The proposed adaptation algorithm searches for the optimal number of mixture Gaussian humps to ensure that the p.d.f. is consistently re-estimated, enabling the model to converge toward the global maximum point. By applying an appropriate threshold value, which measures the amount of collective changes of weighted variances, the optimized number of mixture Gaussian branch is determined. The initialization algorithm essentially exploits the CDHMM parameters previously estimated and uses them as the basis for the current initial segmentation subroutine. It captures the trend of previous training history whereas the uniform segmentation decimates it. The recognition performance of the proposed adaptation procedures along with the suggested initialization is verified to be always better than that of existing training procedure using fixed number of mixture Gaussian p.d.f.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.137-146
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• 2005

Neural network is one of the most notable technique. It usually provides more powerful forecasting models than the traditional time series techniques. Employing the Ensemble technique in forecasting model, one should provide a initial distribution. Usually the uniform distribution is assumed so that the initialization is noninformative. However, it would be expected a sequential informative initialization based on data rather than the uniform initialization gives further reduction in forecasting error. In this note, a modified Ensemble algorithm using sequential initial probability is developed. The sequential distribution is designed to have much weight on the recent data.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.57.4-57
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• 2002

$\textbullet$ Image segmentation is an essential technique of image analysis. In spite of the traditional issues in contour initialization and boundary concavities, active contour models(snakes) are popular and known as successful methods for segmentation. $\textbullet$ We could find in experiment that snake using Gaussian External Force is fast in time but low in accuracy and snake using Gradient Vector Flow by Chenyang Xu and Jerry L. Prince is high in accuracy but slow in time. $\textbullet$ In this paper, we presented a new active contour model, GGF snake, for segmentation of endoscopic image. Proposed GGF snake made up for the defects of the traditional snakes in contour initialization and boundary...

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.753-762
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• 2006

The Snakes and GVF used to find object edges dynamically have assigned their initial contour arbitrarily. If the initial contours are located in the neighboring regions of object edges, Snakes and GVF can be close to the true boundary. If not, these will likely to converge to the wrong result. Therefore, this paper proposes a new initialization of Snakes and GVF using convex hull approximation, which initializes the vertex of Snakes and GVF as a convex polygonal contour near object edges. In simulation result, we show that the proposed algorithm has a faster convergence to object edges than the existing methods. Our algorithm also has the advantage of extracting whole edges in real images.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.182-183
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• 2022

In this study, compared and analyzed various loss function minimization techniques to present a methodology for developing a natural intelligence-based prediction system. As a result of the analysis, He Initialization was the best with RMSE: 3.78, R2: 0.94, and the error rate was 6%. However, it is considered desirable to construct a prediction system by combining each technique for optimization.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.189-190
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• 2007

We propose an efficient internetworking model for fast handover between UMTS and WLAN networks. Mobility anchor (MA) is provided at the boundary between GGSN and PDG, under the 3GPP-proposed internetworking reference model. Such MA can enable authentication and session initialization before L2 handover of the mobile terminal, so that seamless and fast vertical handover could be possible.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1679-1683
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• 1997

In this paper a linear Kalman filter for calibration of gimballed inertial navigation system(GINS) is designed and its performace is analyzed through the simulation with a real navigation data. Simulation results show that the proposed Kalman filter gives a good performance to calibrate the sensor errors.

• Journal of the Korea Computer Graphics Society
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• v.6 no.1
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• pp.19-27
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• 2000

This paper proposes a non-self-intersecting multiresolution deformable model to extract and reconstruct three-dimensional boundaries of objects from volumetric data. Deformable models offer an attractive method for extracting and reconstructing the boundary surfaces. However, convensional deformable models have three limitations- sensitivity to model initialization, difficulties in dealing with severe object concavities, and model self-intersections. We address the initialization problem by multiresolution model representation, which progressively refines the deformable model based on multiresolution volumetric data in order to extract the boundaries of the objects in a coarse-to-fine fashion. The concavity problem is addressed by mesh size regularization, which matches its size to the unit voxel of the volumetric data. We solve the model self-intersection problem by including a non-self-intersecting force among the customary internal and external forces in the physics-based formulation. This paper presents results of applying our new deformable model to extracting a sphere surface with concavities from a computer-generated volume data and a brain cortical surface from a MR volume data.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.165-170
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• 2013

When we build up a 3D model from the given 2D images, linear algorithms are often used to reduce computational cost or for initialization of nonlinear algorithms. However, contemporary linear algorithms have apparently linear structures, but virtually they are implemented using SVD. The SVD is also implemented using numerical analysis algorithms that need initialization. Moreover, solutions using SVD are more difficult to analyze than closed-form solutions. To avoid from such inconvenient numerical analysis algorithms of the contemporary methods and for convenient analysis of solutions, this paper proposes a convenient linear method that produces a closed-form solution.