• Journal of the Korean Institute of Telematics and Electronics
• /
• v.20 no.4
• /
• pp.47-54
• /
• 1983

The performance of an intra-frame DCT/DPCM hybrid coding is investigated with the criteria of normalized mean square error and subjective test for various system parameters. It includes the prediction coefficient in transform domain, normalization factor and bit-map in block quantizer, and adaptive coding. It is shown that the generalized covariance model of image is a convenient tool for bit-map and adaptive coding, and for a fast low bit-rate coding.

• Journal of Ocean Engineering and Technology
• /
• v.19 no.5 s.66
• /
• pp.71-77
• /
• 2005

This paper presents an integrated underwater navigational algorithm for unmanned underwater vehicles, using additional two-range transducers. This paper proposes a measurement model, using two range measurements, to improve the performance of an IMU-DVL (inertial measurement unit - Doppler velocity log) navigation system for long-time operation of underwater vehicles, excluding DVL measurement. Extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation when the external measurements are available. Simulation was conducted with the 6-d.o.f nonlinear numerical model of an AUV in lawn-mowing survey mode, at current flaw, where the velocity information is unavailable. Simulations illustrate the effectiveness of the integrated navigation system, assisted by the additional range measurements without DVL sensing.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.287-297
• /
• 2018

To improve the performance of sensorless induction motor (IM) drives, a novel speed estimation method based on the real-time adaptive extended Kalman filter (RAEKF) is proposed in this paper. In this algorithm, the fuzzy factor is introduced to tune the measurement covariance matrix online by the degree of mismatch between the actual innovation and the theoretical. Simultaneously, the fuzzy factor can be continuously self-tuned tuned by the fuzzy logic reasoning system based on Takagi-Sugeno (T-S) model. Therefore, the proposed method improves the model adaptability to the actual systems and the environmental variations, and reduces the speed estimation error. Furthermore, a simple exponential function based on the fuzzy theory is used to reduce the computational burden, and the real-time performance of the system is improved. The correctness and the effectiveness of the proposed method are verified by the simulation and experimental results.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.1
• /
• pp.108-114
• /
• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• Wind and Structures
• /
• v.19 no.4
• /
• pp.371-387
• /
• 2014

Probability plotting positions are popular and used as the basis for distribution fitting and for inspecting the quality of the fit because of its simplicity. The plotting positions that lead to excellent approximation to the mean of the order statistics should be used if the objective of the fitting is to estimate quantiles. Since the mean depends on the sample size and is not amenable for simple to use closed form solution, many plotting positions have been presented in the literature, including a new plotting position that is derived based on the weighted least-squares method. In this study, the accuracy of using the new plotting position to fit the Gumbel distribution for estimating quantiles is assessed. Also, plotting positions derived by fitting the mean of the order statistics for all ranks is proposed, and an approximation to the covariance of the order statistics for the Gumbel (and Weibull) variate is given. Relative bias and root-mean-square-error of the estimated quantiles by using the proposed plotting position are shown. The use of the proposed plotting position to estimate the quantiles of annual maximum wind speed is illustrated.

• Quantitative Bio-Science
• /
• v.37 no.2
• /
• pp.133-141
• /
• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• Journal of Astronomy and Space Sciences
• /
• v.35 no.4
• /
• pp.295-308
• /
• 2018

In this study, orbit determination (OD) simulation for the Korea Pathfinder Lunar Orbiter (KPLO) was accomplished for investigation of the observational arc-length effect using a sequential estimation algorithm. A lunar polar orbit located at 100 km altitude and $90^{\circ}$ inclination was mainly considered for the KPLO mission operation phase. For measurement simulation and OD for KPLO, the Analytical Graphics Inc. Systems Tool Kit 11 and Orbit Determination Tool Kit 6 software were utilized. Three deep-space ground stations, including two deep space network (DSN) antennas and the Korea Deep Space Antenna, were configured for the OD simulation. To investigate the arc-length effect on OD, 60-hr, 48-hr, 24-hr, and 12-hr tracking data were prepared. Position uncertainty by error covariance and orbit overlap precision were used for OD performance evaluation. Additionally, orbit prediction (OP) accuracy was also assessed by the position difference between the estimated and true orbits. Finally, we concluded that the 48-hr-based OD strategy is suitable for effective flight dynamics operation of KPLO. This work suggests a useful guideline for the OD strategy of KPLO mission planning and operation during the nominal lunar orbits phase.

• Animal Bioscience
• /
• v.34 no.7
• /
• pp.1100-1104
• /
• 2021

Objective: The objective of present study was to estimate heritability of non-return rate (NRR) and success of first insemination (SFI) by using the Bayesian approach with Gibbs sampling. Methods: Heifer Traits were denoted as NRR-h and SFI-h, and cow traits as NRR-c and SFI-c. The variance covariance components were estimated using threshold model under Bayesian procedures THRGIBBS1F90. Results: The SFI was more relevant to evaluating success of insemination because a high percentage of animals that demonstrated no return did not successfully conceive in NRR. Estimated heritability of NRR and SFI in heifers were 0.032 and 0.039 and the corresponding estimates for cows were 0.020 and 0.027. The model showed low values of Geweke (p-value ranging between 0.012 and 0.018) and a low Monte Carlo chain error, indicating that the amount of a posteriori for the heritability estimate was valid for binary traits. Genetic correlation between the same traits among heifers and cows by using the two-trait threshold model were low, 0.485 and 0.591 for NRR and SFI, respectively. High genetic correlations were observed between NRR-h and SFI-h (0.922) and between NRR-c and SFI-c (0.954). Conclusion: SFI showed slightly higher heritability than NRR but the two traits are genetically correlated. Based on this result, both two could be used for early indicator for evaluate the capacity of cows to conceive.

• Journal of Information Processing Systems
• /
• v.16 no.6
• /
• pp.1343-1358
• /
• 2020

In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.29 no.2
• /
• pp.148-160
• /
• 2023

Purpose: The purpose of this study was to construct and test a structural model of nursing students' performing communication skills. Methods: The data collection was conducted from October 13 to October 20, 2020. The participants were 286 students from nursing colleges located in three cities. The data analysis method was a covariance structure analysis with using IBM SPSS statistics version 23.0 and AMOS 21.0 statistical programs. Results: The hypothetical model showed a proper fit with the data: root mean square error of approximation=.08, standardized root mean square residual=.06, adjusted goodness of fit=.85, normed fit index=.91, and comparative fit index=.94. The model fit indices were normed to fit index=2.96. Statistically significant explanatory variables for the performing communication skills of nursing students were peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. The variables accounted for 66.1% of the performing communication skills of nursing students. Conclusion: Based on the above results, it appears necessary to develop strategies for improving the performing communication skills of nursing students, and having positive effects on health outcomes of the subjects by considering the variables of peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. Such strategies could potentially have positive effects on the health outcomes of the patients.