• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.371-381
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• 2017

The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

• Atmosphere
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• v.31 no.5
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• pp.473-488
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• 2021

A new physical/statistical diagnostic downscale model has been developed for use to improve near-surface air temperature forecasts. The model includes a series of physical and statistical correction methods that account for un-resolved topographic and land-use effects as well as statistical bias errors in a low-resolution atmospheric model. Operational temperature forecasts of the Local Data Assimilation and Prediction System (LDAPS) were downscaled at 100 m resolution for three months, which were used to validate the model's physical and statistical correction methods and to compare its performance with the forecasts of the Korea Meteorological Administration Post-processing (KMAP) system. The validation results showed positive impacts of the un-resolved topographic and urban effects (topographic height correction, valley cold air pool effect, mountain internal boundary layer formation effect, urban land-use effect) in complex terrain areas. In addition, the statistical bias correction of the LDAPS model were efficient in reducing forecast errors of the near-surface temperatures. The new high-resolution downscale model showed better agreement against Korean 584 meteorological monitoring stations than the KMAP, supporting the importance of the new physical and statistical correction methods. The new physical/statistical diagnostic downscale model can be a useful tool in improving near-surface temperature forecasts and diagnostics over complex terrain areas.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.446-451
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• 2017

The statistical context-sensitive spelling correction technique in this thesis is based upon Shannon's noisy channel model. The interpolation method is used for the improvement of the correction method proposed in the paper, and the general interpolation method is to fill the middle value of the probability by (N-1)-gram and (N-2)-gram. This method is based upon the same statistical corpus. In the proposed method, interpolation is performed using the frequency information between the statistical corpus and the correction document. The advantages of using frequency of correction documents are twofold. First, the probability of the coined word existing only in the correction document can be obtained. Second, even if there are two correction candidates with ambiguous probability values, the ambiguity is solved by correcting them by referring to the correction document. The method proposed in this thesis showed better precision and recall than the existing correction model.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.457-457
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• 2022

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.295-304
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• 2005

This paper concentrates on the prediction of typhoon tracks using the dynamic linear model (DLM) for the statistical correction of the numerical model guidance used in the JMA. The DLM with proposed forecast strategy is applied to reduce their systematic errors using the latest observation. All parameters of the DLM are updated dynamically and backward forecasting is performed to remove the effect of initial values.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.141-142
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• 2002

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.167-173
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• 2012

PURPOSES : This study is to develop speed correction factor for more realistic Level-of-Service(LOS) at multilane highway. METHODS : In this study, we compared speed difference the degree of speed reductions in actual multilane road conditions with speed reduction considering speed correction factor presented in highway capacity manual using statistical techniques. And also we presents new speed correction factor analyzing collected data at national highway No.1 (Goyang~Wolrung). RESULTS : The result of analyzing and comparing new suggested speed correction factor with speed correction factor in Korea Highway Capacity Manual (KHCM) shows RMSE (Root Mean Square Error) in new speed correction factor (RMSE 1.5) is much lower than existing speed correction factor (RMSE 13.4). New suggested speed correction can be used for analyzing Level-of-Service at multilane highway. And also we suggests improvements for analysis procedure in analyzing Level-of-Service at multilane highway CONCLUSIONS : As a result of comparing differences, we draw the causes that effect the differences in speed and suggest new speed correction factor that consider traffic volumes. It can be more rational because it uses speed correction factor which can consider more realistic traffic conditions, etc.

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.345-366
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• 2005

This paper considers the cointegrating vector estimator in the error correction model with stationary covariates, which combines the stationary vector autoregressive model and the nonstationary error correction model. The cointegrating vector estimator is shown to follow the locally asymptotically mixed normal distribution. The variance of the estimator depends on the co­variate effect of stationary regressors, and the asymptotic efficiency improves as the magnitude of the covariate effect increases. An economic application of the money demand equation is provided.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.101-101
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• 2023

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.418-421
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• 2005

In this study, we analyzed surface temperature of lakes in the Han River system, using Landsat-5 and -7 time-series images. Surface temperature was extracted using NASA equation and compared with in situ 10m-depth temperature in Lake Soyang and surface temperature on five other dam lakes downstream. The 24 images out of 29 showed standard deviation of temperature difference less than $2^{\circ}C$, to which a novel statistical atmospheric correction could be applied. The correlation coefficients were 0.950 at Lake Soyang and 0.979-0.997 at the other lakes after atmospheric correction.