• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.237-243
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• 2002

This paper studies the channel estimation schemes of Time Division Duplex (TDD) Code Division Multiple Access (CDMA) system with a parallel interference canceller (PIC) in multi-path fading channels. furthermore, the effective interpolation method which maintains the flexibility of UTRA TDD mode is proposed. By Monte Carlo simulations, it is verified that the proposed interpolation method can be used in order to obtain the proper performance of a multi-stage PIC and in order to reduce the required Eb/No for a given bit error rate (BER).

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.872-878
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• 2018

Steam tables including superheated, saturated and compressed region were simultaneously modeled using the neural networks. Pressure and temperature were used as two inputs for superheated and compressed region. On the other hand Pressure and dryness fraction were two inputs for saturated region. The outputs were specific volume, specific enthalpy and specific entropy. The neural network model were compared with the linear interpolation model in terms of the percentage relative errors. The criterion of judgement was selected with the percentage relative error of 1%. In conclusion the neural networks showed better results than the interpolation method for all data of superheated and compressed region and specific volume of saturated region, but similar for specific enthalpy and entropy of saturated region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1691-1697
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• 1997

This paper presents a new motion compensated error coding method suitable for region based image coding system. Compared with block based conding, the region based coding improves subjective quality as it estimates and compensates 2D (or 3D) translantional, rotational, and scaling motion for each regions. although the region based coding has this advantage, its merit is reduced as bock-DCT (2D-DCT) is used to encode motion-compensated error. To overcome this problem, a new region adaptive motion compensated error coding technique which improver subjective and objective quality in the region boundary is proposed in this paper. In the proposed method, regions with large error are estimated using contour of the regions and contrast between the regions. The regions estiated as those with large error are coded by arbitrarily shaped image segment coding method. The mask information of the coded regions is not transmitted because it is estimated as the same algorithm in the encoder and the decoder. The proposed region adaptive motion conpensated error coding method improves about 0.5dB when it is compared with conventional block based method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.205-208
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• 2008

In numerical analysis numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But most of the thermodynamic properties of the steam table are determined by experiment. Therefore they are supposed to have measurement errors. In order to make noised thermodynamic properties corresponding to errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. the neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure. It was proved that the neural networks give smaller percentage error compared with quadratic spline interpolation. From this fact it was confirmed that the neural networks trace the original values of thermodynamic properties better than the quadratic interpolation method.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1865-1873
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• 2017

The feature-based visual SLAM requires 3D positions for the extracted feature points to perform 3D-2D motion estimation. LiDAR can provide reliable and accurate 3D position information with low computational burden, while stereo camera has the problem of the impossibility of stereo matching in simple texture image region, the inaccuracy in depth value due to error contained in intrinsic and extrinsic camera parameter, and the limited number of depth value restricted by permissible stereo disparity. However, the sparsity of LiDAR data may increase the inaccuracy of motion estimation and can even lead to the result of motion estimation failure. Therefore, in this paper, we propose three interpolation methods which can be applied to interpolate sparse LiDAR data. Simulation results obtained by applying these three methods to a visual odometry algorithm demonstrates that the selective bilinear interpolation shows better performance in the view point of computation speed and accuracy.

• Environmental Engineering Research
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• v.21 no.3
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• pp.226-232
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• 2016

Rainfall is one of crucial factors that impact on our environment. Rainfall data is important in water resources management, flood forecasting, and designing hydraulic structures. However, it is not available in some rural watersheds without rain gauges. Thus, effective ways of interpolating the available records are needed. Despite many widely used spatial interpolation methods, few studies have investigated rainfall center characteristics. Based on the theory that the spatial distribution of convective rainfall event has a definite center with maximum rainfall, we present a mathematical interpolation method to estimate convective rainfall distribution and indicate the rainfall center location and the center rainfall volume. We apply the method to estimate three convective rainfall events in Santa Catalina Island where reliable hydrological data is available. A cross-validation technique is used to evaluate the method. The result shows that the method will suffer from high relative error in two situations: 1) when estimating the minimum rainfall and 2) when estimating an external site. For all other situations, the method's performance is reasonable and acceptable. Since the method is based on a continuous function, it can provide distributed rainfall data for distributed hydrological model sand indicate statistical characteristics of given areas via mathematical calculation.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.316-320
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• 2010

HRV(Heart rate variability) analysis parameter is widely used as an index to evaluate the autonomic nervous system and cardiac function. For reliable HRV analysis, we need to acquire the accurate ECG signals. Most of commercially available portable ECG devices have low sampling rate because of low power consumption and small size issues, which make it difficult to measure RR-interval accurately. This study is to improve the accuracy of RR-interval by developing R-wave interpolation technique, based on the morphological characteristics of the QRS complex. When the developed method was applied to ECG obtained at 200 Hz and the results were compared with 1000 Hz reference device, the error range decreased by 1.33 times in sitting and by 2.38 times in cycling exercise. Therefore, the proposed interpolation technique is thought to be useful to improve the accuracy of R-R interval in the portable ECG device with low sampling rate.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.72-74
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• 2022

Several types of data are collected from buoy due to the development of hardware technology.. However, the collected data are difficult to use due to errors including missing values and outliers depending on mechanical faults and meteorological environment. Therefore, in this study, linear interpolation is performed by adding the missing time data to enable machine learning to the insufficient meteorological data. After the linear interpolation, XGBoost and KNN-regressor, are used to forecast error data and suggested model is evaluated by using real-world data of a buoy.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.117-126
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• 1994

This paper describes an application step of a $R^{-{\theta}}$ method which measures circular movements in machining centers. The detection of composite errors of circular movements and a high precision cutting method in machining centers were investigated by the analysis of data measured by $R^{\theta }$method which can detect the rotating angle and is applicable to variable measuring radius. When the error by squareness error and unbalance of position-loop-gain were mixed, the detection method of each error was proposed. Although the errors by squarenss error and backlash compensation were mixed, the errors by squareness error be detected. If the errors by unbalance of position-loop-gain and backlash compensation were mixed, the errors by unbalance of position-loop-gain could not detected. A high precision cutting mehod, which uses the NC program compensated by using feed-back data from error measured by the $R^{\theta }$method, was proposed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.1
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• pp.14-26
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• 2011

Surface currents were observed by high-frequency (HF) radars off the Keum River estuary from December 2008 to February 2009. The dataset of observed surface currents had data gaps due to the interference of electromagnetic waves and the deteriorating weather conditions. To fill the data gaps an optimal interpolation procedure was developed. The characteristics of spatial correlation in the surface currents off the Keum River estuary were investigated and the spatial data gaps were filled using the optimal interpolation. Then, the temporal and spatial distribution of the interpolated surface currents and the patterns of interpolation error were examined. The correlation coefficients between the surface currents in the coastal region were higher than 0.7 because tidal currents dominate the surface circulation. The sample data covariance matrix (C), spatially averaged covariance matrix with localization ($C^G_{sm}$) and covariance matrix fitted by an exponential function ($C_{ft}$) were used to interpolate the original dataset. The optimal interpolation filled the data gaps and suppressed the spurious data with spikes in the time series of surface current speed so that the variance of the interpolated time series was smaller than that of the original data. When the spatial data coverage was larger (smaller) than 70% of the region, the interpolation error produced by $C^G_{sm}$ ($C_{ft}$) was smaller compared with that by C.