• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.566-573
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• 2019

In order to obtain high-quality images by motion compensation in the airborne synthetic aperture radar (SAR), accurate motion sensing in image acquisition section is necessary. Especially, reducing relative position error and discontinuity in motion sensing is important. To overcome the problem, we propose a pre-parametric error modeling (P-PEM) algorithm which is a real-time motion sensing algorithm for the airborne SAR in this paper. P-PEM is an extended version of parametric error modeling (PEM) method which is a motion sensing algorithm to mitigate the errors in the previous work. PEM estimates polynomial coefficients of INS error which can be assumed as a polynomial in the short term. Otherwise, P-PEM estimates polynomial coefficients in advance and uses at image acquisition section. Simulation results show that the P-PEM reduces relative position error and discontinuity effectively in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4418-4437
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• 2017

In this paper a three-phase secure compressive sensing (CS) and received signal strength (RSS) based target localization approach is proposed to mitigate the effect of malicious node attack. RSS measurements are first arranged into a group of subsets where the same measurement can be included in multiple subsets. Intermediate target position estimates are then produced using individual subsets of RSS measurements and the CS technique. From the intermediate position estimates, the residual error vector and residual error square vector are formed. The least median of residual error square is utilized to define a verifier parameter. The selected residual error vector is utilized along with a threshold to determine whether a node or measurement is under attack. The final target positions are estimated by using only the attack-free measurements and the CS technique. Further, theoretical analysis is performed for parameter selection and computational complexity evaluation. Extensive simulation studies are carried out to demonstrate the advantage of the proposed CS-based secure localization approach over the existing algorithms.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.34-42
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• 2001

In this paper, we study on a modified mesh generation method based on the pollution error estimate. This method is designed for the control of the pollution error in any patch of elements of interest. It is a well-known fact that the pollution error estimates are much more than the local one. Reliable a posteriori error estimation is possible by controlling the pollution error in the patch through proper design of the mesh outside the patch. This design is possible by equally distributing the pollution error indicators over the mesh outside the patch. The conventional feedback pollution-adaptive mesh generation algorithm needs many iterations. Therefore, the solution time is significant. But we use the remeshing scheme in the proposed method. We will also show that the pollution error reduces less than the local error.

• Journal of the Korean Society for Railway
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• v.2 no.3
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• pp.46-53
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• 1999

In this paper, made was a study on a mesh generation method based on the pollution error. This method is designed for the control of the pollution error in any patch of elements of interest. It is a well-known fact that the pollution error estimates are much more than the local one. When the pollution error is significant, nothing can be said about the reliability of any estimator based on local computations in the patch. Reliable a posteriori error estimation is possible by controlling the pollution error in the patch through proper design of the mesh outside the patch. This design is possible by equally distributing the pollution error indicators over the mesh outside the patch. The mesh generated from the conventional feedback pollution-adaptive mesh generation algorithm needs many iterations. Therefore, the solution time is significant. But the remeshing scheme in the proposed method was used here. It was shown that the pollution-adaptive mesh improves the E.I., simply denoted as Effectivity Index, on the patch of interest, and the pollution error reduces less than the local error.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.7-17
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• 2018

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the Korea Stock Exchange. The data is restricted to the period for which monthly data are available from January 1986 to October 2016 (370 observations) retrieved from the Economic Statistics System database sponsored by the Bank of Korea. The study employs unit root test, cointegration test, vector error correction estimates, impulse response test, and structural break test. The results of the Johansen cointegration test indicate at least three cointegrating equations exist at the 0.05 level in the model, confirming that there is a long-run equilibrium relationship between stock prices and macroeconomic variables in Korea. The results of vector error correction model (VECM) estimates indicate that money supply and short-term interest rate are not related to stock prices in the short-run. However, exchange rate is positively related to stock prices while the industrial production index and inflation are negatively related to stock prices in the short-run. Furthermore, the VECM estimates indicate that the external shock, such as regional and global financial crisis shocks, neither affects changes in the endogenous variables nor causes instability in the cointegrating vector. This study finds that the endogenous variables are determined by their own dynamics in the model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2562-2570
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• 2014

One of the important hints for inferring the function of unknown proteins is the knowledge about protein subcellular localization. Recently, there are considerable researches on the prediction of subcellular localization of proteins which simultaneously exist at multiple subcellular localization. In this paper, label power-set classification is improved for the accurate prediction of multiple subcellular localization. The predicted multi-labels from the label power-set classifier are combined with their prediction probability to give the final result. To find the accurate probability estimates of multi-classes, this paper employs pair-wise comparison and error-correcting output codes frameworks. Prediction experiments on protein subcellular localization show significant performance improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4408-4428
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• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.310-312
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• 2009

The heterodyne laser interferometer has been widely used in precise measurement field. However, the accuracy is limited by the nonlinearity error caused from incomplete laser sources and nonideal optical components. In this paper, we propose the Dual-EKF which estimates states and weights simultaneously to improve the resolution of heterodyne laser interferometer. As a proof, we demonstrate the effectiveness of our proposed method through experimental results.

• Journal of the Korean Statistical Society
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• v.8 no.1
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• pp.23-36
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• 1979

In the multiple linear regression model a class of weighted least absolute error estimaters, which minimize the sum of weighted absolute residuals, is proposed. It is shown that the weighted least absolute error estimators with Wilcoxon scores are equivalent to the Koul's Wilcoxon type estimator. Therefore, the asymptotic efficiency of the proposed estimator with Wilcoxon scores relative to the least squares estimator is the same as the Pitman efficiency of the Wilcoxon test relative to the Student's t-test. To find the estimates the iterative weighted least squares method suggested by Schlossmacher is applicable.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.33-55
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• 2005

The temporal discretisation of a moderate semilinear parabolic problem in an abstract setting by the two-step backward differentiation formula with variable step sizes is analysed. Stability as well as optimal smooth data error estimates are derived if the ratios of adjacent step sizes are bounded from above by 1.91.