• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.347-354
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• 2009

Physical properties of rocks are strongly dependant on details of pore micro-structures, which can be used for quantifying relations between physical properties of rocks through pore-scale simulation techniques. Recently, high-resolution scan techniques, such as X-ray microtomography and high performance computers make it possible to calculate permeability from pore micro-structures of rocks. We try to extend this simulation methodology to velocity and electrical conductivity. However, the smoothing effect during tomographic inversion creates artifacts in pore micro-structures and causes inaccurate property estimation. To mitigate this artifact, we tried to use sharpening filter and neural network classification techniques. Both methods gave noticeable improvement in pore structure imaging and accurate estimation of permeability and electrical conductivity, which implies that our method effectively removes the smoothing effect in pore structures. However, the calculated velocities showed only incremental improvement. By comparison between thin section images and tomogram, we found that our resolution is not high enough, and it is mainly responsible for the inaccuracy in velocity despite the successful removal of the smoothing effect. In conclusion, our methods can be very useful for pore-scale modeling, since it can create accurate pore structure without the smoothing effect. For accurate velocity estimation, the resolution of pore structure should be at least three times higher than that for permeability simulation.

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.371-382
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• 2004

To improve the precision of relative positioning for GPS single frequency(L1) receiver, we accomplished the GPS data processing using the weighted smoothing techniques. The weighted phase smoothing technique is used to minimize the measurement error of pseudorange and position domain smoothing technique is adopted to make the complement of cycle-slip affection. we also considered some component errors like as ionospheric error, which are related with baseline length, and processed for several baselines (5, 10, 30, 40, and 150 km) to check the coverage area of this algorithm. This paper shows that weighted phase smoothing technique give more stable results after using this technique and the position domain smoothing technique can reduce the errors which are sensitive to the observational environment. Based on the results, we could find out that this algorithm is available for post-time and real-time applications and these techniques can be substitution methods which is able to get the high accuracy and precision without resolving the Integer ambiguity.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.800-809
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• 2014

The gridded environmental data is usually provided by the numerical simulation coupled with a data assimilation technique and various inter- or extrapolation algorithms, both of which are based on the observation spanning from simple equipments to satellites. But it is difficult to represent the natural phenomenon such as sea mount, internal-wave, warm eddy in modeling or observation because of increase in the complexity of model. This paper introduces the algorithm artificially representing the natural phenomenon and the techniques applying it to the gridded volume data and smoothing for natural effects. Moreover, the inserted results are analyzed by use of graphical tool. The results can be used for the battle simulation or acoustic model.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.87-95
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• 2010

In this paper, we address issues associated with mixed-lingual text-to-speech based on context-dependent HMMs, where there are multiple sets of HMMs corresponding to each individual language. In particular, we propose smoothing techniques of synthesis parameters at the boundaries between different languages to obtain more natural quality of speech. In other words, mel-frequency cepstral coefficients (MFCCs) at the language boundaries are smoothed by applying several linear and nonlinear approximation techniques. It is shown from an informal listening test that synthesized speech smoothed by a modified version of linear least square approximation (MLLSA) and a quadratic interpolation (QI) method is preferred than that without using any smoothing technique.

• Transactions of Materials Processing
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• v.12 no.4
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• pp.340-347
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• 2003

In the rigid-plastic finite element simulation of hot forging processes using hexahedral mesh, remeshing of a flash is important for design and control of the process to obtain desirable defect-free products. The mesh compression method is a remeshing technique which enables the construction of an effective hexahedral mesh in the flash. However, because the mesh is distorted during the compression procedure of the mesh compression method, when it is used in resuming the analysis, it causes discretization error and decreases the conversance rate. Therefore, mesh smoothing is necessary to improve the mesh quality. In this study, several geometric mesh smoothing techniques and optimization techniques are introduced and modified to improve mesh quality. Then, the most adaptive technique is recommended for the mesh compression method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.331-334
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• 2003

In the finite element simulation of hot forging processes using hexahedron, remeshing of a flash is very difficult. The mesh compression method is a remeshing technique to construct an effective hexahedral mesh. However, because mesh is distorted during the compression procedure or the mesh compression method, mesh smoothing is necessary to improve the mesh Qualify. in this study, several geometric mesh smoothing techniques and a matrix norm optimization technique are applied and compared which is more adaptive to the mesh compression method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.529-535
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• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.273-278
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• 1988

This paper represents the computer application techniques of initial and modification machining for dies with 3-dimensional scluptured surfaces. All procedures from die design to die machining and measurement are covered. The component of modelling is data management and modification (extrapolation and smoothing), surface modelling, and nc program preparation. Also this paper introduces the utility for successful and efficient operation of system such as map generation, data communication, tool path verification, contour map generation, graphic processing of extrapolation and smoothing results, and CAD/CAM system interface. Examples are given to illustrate the modelling.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.811-816
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• 2000

The purpose of this paper is to study of data-driven smoothing goodness of it test, when the hypothesis is complete. The smoothing goodness of fit test statistic by nonparametric function estimation techniques is proposed in this paper. The results of simulation studies for he powers of show that the proposed test statistic compared well to other.