• 대기
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• 제24권4호
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• pp.503-514
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• 2014

Evaluation of predictability of numerical models for tropical cyclone track was performed using along-and cross-track component. The along-and cross-track bias were useful indicators that show the numerical models predictability associated with cause of errors. Since forecast errors, standard deviation and consistency index of along-track component were greater than those of cross-track component, there was some rooms for improvement in alongtrack component. There was an overall slow bias. The most accurate model was JGSM for 24-hour forecast and ECMWF for 48~96-hour forecast in direct position error, along-track error and cross-track error. ECMWF and GFS had a high variability for 24-hour forecast. The results of predictability by track type showed that most significant errors of tropical cyclone track forecast were caused by the failure to estimate the recurvature phenomenon.

• 한국생산제조학회지
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• 제9권1호
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• pp.60-67
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• 2000

An improved disturbance rejection control scheme is presented for minimizing the position error due to the repeatable runout disturbances in high density disk drive systems The proposed control algorithm is capable of attenuating repeatable disturbances which is one of the major detractors to hard disk drive quality and performance. This is achieved by a sys-tematic combination of an optimal feedback component and a feedforward preview component. The feedback component is designed where the emphasis is placed on robustness. The feedforward component is on the basis of a preview control comprised of a measured disturbance signals which leads to better disturbance rejection capabilites. The designed con-troller is applied as a plug-in module to a high density hard disk drive with a pre-existing conventional servo controller. Simulations have been carried out to demonstrate the effectiveness of this control scheme in the reduction of the periodic disturbances.

• 산업공학
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• 제22권3호
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• pp.214-222
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• 2009

In the early design stage, system reliability must be estimated from life testing data at the component level. Previously, a point estimate of system reliability was obtained from the unbiased estimate of the component reliability after assuming that the number of failed components for a given time followed a binomial distribution. For deriving the confidence interval of system reliability, either the lognormal distribution or the normal approximation of the binomial distribution was assumed for the estimator of system reliability. In this paper, a new estimator is used for the component level reliability, which is biased but has a smaller mean square error than the previous one. We propose to use the beta distribution rather than the lognormal or approximated normal distribution for developing the confidence interval of the system reliability. A numerical example based on Monte Carlo simulation illustrates advantages of the proposed approach over the previous approach.

• Journal of Positioning, Navigation, and Timing
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• 제12권3호
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• pp.215-228
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• 2023

The State Space Representation (SSR) method provides individual corrections for each Global Navigation Satellite System (GNSS) error components. This method can lead to less bandwidth for transmission and allows selective use of each correction. Precise Point Positioning (PPP) - Real-Time Kinematic (RTK) is one of the carrier-based precise positioning techniques using SSR correction. This technique enables high-precision positioning with a fast convergence time by providing atmospheric correction as well as satellite orbit and clock correction. Currently, the positioning service that supports PPP-RTK technology is the Quazi-Zenith Satellite System Centimeter Level Augmentation System (QZSS CLAS) in Japan. A system that provides correction for each GNSS error component, such as QZSS CLAS, requires monitoring of each error component to provide reliable correction and integrity information to the user. In this study, we conducted an analysis of the performance of residual error bounding for each error component. To assess this performance, we utilized the correction and quality indicators provided by QZSS CLAS. Performance analyses included the range domain, dispersive part, non-dispersive part, and satellite orbit/clock part. The residual root mean square (RMS) of CLAS correction for the range domain approximated 0.0369 m, and the residual RMS for both dispersive and non-dispersive components is around 0.0363 m. It has also been confirmed that the residual errors are properly bounded by the integrity parameters. However, the satellite orbit and clock part have a larger residual of about 0.6508 m, and it was confirmed that this residual was not bounded by the integrity parameters. Users who rely solely on satellite orbit and clock correction, particularly maritime users, thus should exercise caution when utilizing QZSS CLAS.

• 대한기계학회논문집A
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• 제21권11호
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• pp.1871-1884
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• 1997

This paper describes the design process of a 3-component load cell with a multiple parallel plate structure which may be used to measure transverse forces and twisting moment simultaneously. Also we have derived equations to predict the bending strains on the surface of the beams in the multiple parallel plate structure under transverse force or twisting moment. It reveals that the bending strains calculated from the derived equations are in good agreement with the results from finite element analysis and experiment. Also we have evaluated the rated output and interference error of each component, which can be efficiently used to design a 3-component load cell with a multiple parallel plate structure.

• 한국정밀공학회지
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• 제18권2호
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• pp.214-221
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• 2001

This paper describes the design of 3-component force/moment sensor with the force and moment ratio of wide range. It can measure the x-direction force Fx, y-direction force Fy and z-direction moment Mz simultaneously. In order to accurately measure forces and moment using 3-component force/moment sensor, it should get suitable force and moment ratio(the ratio of force Fx=200 N and moment Mz=20 Nm is ten to one), and small interference error. In this paper, in order to design the 3-component force/moment sensor with the force and moment ratio of wide range, the procedures are performed as follow : 1) the derivation of the equations to predict the bending strains on the surfaces of the plate-beams under the force or the moments, 2) the determination of the size of the sensing elements of the force/moment sensor by using the derived equations, 3) the Finite Element Method(FEM) analysis and the characteristic test for confirming the strains from the theory analysis, 4) the selection of the attachment locations of the strain gages of each sensor, 5) the analysis of the rated strain and the interference error at the attachment location of strain gages. It reveals that the rated strains calculated from the derived equations make a good agreement with the results from the Finite Element Method analysis and the characteristic test.

• 대한원격탐사학회지
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• 제33권4호
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• Journal of Pharmaceutical Investigation
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• 제37권6호
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• pp.377-395
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• 2007

Near infrared(NIR) spectral data have been used for the noninvasive analysis of various biological samples. Nonetheless, absorption bands of NIR region are overlapped extensively. It is very difficult to select the proper wavelengths of spectral data, which give the best PCR(principal component regression) models for the analysis of constituents of biological samples. The NIR data were used after polynomial smoothing and differentiation of 1st order, using Savitzky-Golay filters. To find the best PCR models, all-possible combinations of available principal components from the given NIR spectral data were derived by in-house programs written in MATLAB codes. All of the extensively generated PCR models were compared in terms of SEC(standard error of calibration), $R^2$, SEP(standard error of prediction) and SECP(standard error of calibration and prediction) to find the best combination of principal components of the initial PCR models. The initial PCR models were found by SEC or Malinowski's indicator function and a priori selection of spectral points were examined in terms of correlation coefficients between NIR data at each wavelength and corresponding concentrations. For the test of the developed program, aqueous solutions of BSA(bovine serum albumin) and glucose were prepared and analyzed. As a result, the best PCR models were found using a priori selection of spectral points and the final model selection by SEP or SECP.

• 말소리와 음성과학
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• 제10권3호
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• pp.19-29
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• 2018

We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.