• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.44-53
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• 2009

In this paper, Recursive Least Squares (RLS) and Fourier Transform Regression (FTR) methods for estimating stability and control derivatives of small unmanned helicopter are evaluated together with MMLE technique. Flight data simulated by using a commercial small-scale helicopter model are exploited to estimate the parameters with accuracies for hover and cruise modes. The performances of the system identification methods are also compared by analyzing the responses of the reconstructed systems using estimated derivatives.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.888-890
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• 2003

The objective of this investigation is to establish a simple yet effective block adjustment procedure for the orthorectification of multi-orbit satellite images. The major works of the proposed scheme are: (1) adjustment of satellite‘s orbit accurately, (2) calculation of the error vectors for each tie point using digital terrain model and ray tracing technique, (3) refining the orbit using the Least Squares Filtering technique and (4) generation of the orthophotos. In the process of least squares filtering, we use the residual vectors on ground control points and tie points to collocate the orbit. In orthorectification, we use the indirect method to generate the orthoimage. Test areas cover northern Taiwan. Test images are from SPOT 5 satellite. Experimental results indicate that proposed method improves the relative accuracy significantly.

• Wind and Structures
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• v.27 no.3
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• pp.199-211
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• 2018

This paper deals with wind fragility and risk analysis of high rise buildings subjected to stochastic wind load. Conventionally, such problems are dealt in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, to make the procedure computationally efficient, application of metamodelling technique in fragility analysis is explored in the present study. Since, accuracy by the conventional Least Squares Method (LSM) based metamodelling is often challenged, an efficient Moving Least Squares Method based adaptive metamodelling technique is proposed for wind fragility analysis. In doing so, artificial time history of wind load is generated by three wind field models: i.e., a simple one based on alongwind component of wind speed; a more detailed one considering coherence and wind directionality effect, and a third one considering nonstationary effect of mean wind. The results show that the proposed approach is more accurate than the conventional LSM based metamodelling approach when compared to full simulation approach as reference. At the same time, the proposed approach drastically reduces computational time in comparison to the full simulation approach. The results by the three wind field models are compared. The importance of non-linear structural analysis in fragility evaluation has been also demonstrated.

• Journal of KSNVE
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• v.8 no.4
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• pp.690-699
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• 1998

This paper discusses the techniques, procedures and the results of the ground vibration test(GVT) performed on the development aircraft and the simple procedure of FE model updating technique from the GVT results. The GVT was carried out using random excitation technique with MIMO(Multi-Input-Multi-Output) data acquistion method, and taking full advantage of poly-reference global parameter estimation technique to identify the vibration modes. In dynamic FE modeling, the aircraft was represented by beam elements and all dynamic analysis was performed using MSC/NASTRAN for this model. In updating procedure, the stiffness of the beam model was adjusted iteratively so as to get the natural frequencies and mode shapes close to the GVT results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.219-224
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• 2020

Binary classification has been broadly investigated in machine learning. In addition, binary classification can be easily extended to multi class problems. To successfully utilize machine learning methods for classification tasks, preprocessing and feature extraction steps are essential. These are important steps to improve their classification performances. In this paper, we propose a new learning method based on weighted least squares. In the weighted least squares, designing weights has a significant role. Due to this necessity, we also propose a new technique to obtain weights that can achieve feature transformation. Based on this weighting technique, we also propose a method to combine the learning and feature extraction processes together to perform both processes simultaneously in one step. The proposed method shows the promising performance on five UCI machine learning data sets.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.920-928
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted least squares filtering with iCAM06 model. To show more perceptual high dynamic range images in conventional display, we decompose high dynamic range image into base layers and detail layers. The base layers are obtained by using weighted least squares filter. Then, we adopt chromatic adaption function and non-linear compression function to deal with base layers. Only the base layers reduce contrast, and preserving detail. The image quality assessment shows that our tone mapped image is more similar to original high dynamic range image. Moreover, the subjective result shows our algorithm produces more reliable and pleasing image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.621-628
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• 2018

More than four visible GPS (Global Positioning System) satellites are required to obtain absolute positioning. However, it is not easy to satisfy this condition when a rover is in such unfavorable condition as an urban area. As a consequence, clock-aided positioning has been used as an alternative method especially when the number of visible satellites is three providing that receive clock error information is available. In this study, LSC (Least-Squares Collocation) method is proposed to interpolate clock errors for clock-aided positioning after analyzing the characteristics of receiver clock errors. Numerical tests are performed by using GPS data collected at one of Korean CORS (Continuously Operating Reference Station) and a nearby GPS station. The receiver clock errors are obtained through the DGPS (Differential GPS) positioning technique and segmentation procedures are applied for efficient interpolation. Then, LSC is applied to predicted clock error at epoch which clock information is not available. The numerical test results are analyzed by examining the differences between the original and interpolated clock errors. The mean and standard deviation of the residuals are 0.24m and 0.49m, respectively. Therefore, it can be concluded that sufficient accuracy can be obtained by using the proposed method in this study.

• Archives of Pharmacal Research
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• v.28 no.5
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• pp.598-603
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• 2005

The purpose of this study was to determine the influence of weight with gentamicin assay error on the Bayesian and nonlinear least squares regression analysis in 12 Korean appen dicitis patients. Gentamicin was administered intravenously over 0.5 h every 8 h. Three specimens were collected at 48 h after the first dose from all patients at the following times, just before regularly scheduled infusion, at 0.5 h and 2 h after the end of 0.5 h infusion. Serum gentamicin levels were analyzed by fluorescence polarization immunoassay technique with TDxFLx. The standard deviation (SD) of the assay over its working range had been determined at the serum gentamicin concentrations of 0, 2, 4, 8, 12, and 16 ${\mu}g$/mL in quadruplicate. The polynominal equation of gentamicin assay error was found to be SD (${\mu}g$/mL) = 0.0246-(0.0495C)+ (0.00203C$^2$). There were differences in the influence of weight with gentamicin assay error on pharmacokinetic parameters of gentamicin using the nonlinear least squares regression analysis but there were no differences on the Bayesian analysis. This polynominal equation can be used to improve the precision of fitting of pharmacokinetic models to optimize the process of model simulation both for population and for individualized pharmacokinetic models. The result would be improved dosage regimens and better, safer care of patients receiving gentamicin.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.229-234
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• 2022

The study aims to investigate whether Musharakah management has an impact on Chinese and Malaysian business partnerships. To estimate the relationship between Musharakah and the Sino-Malaysian partnership, this study uses a panel econometric technique namely pooled ordinary least squares. Ordinary Least Squares regression (OLS) is a common technique for estimating coefficients of linear regression equations which describe the relationship between one or more independent quantitative variables and a dependent variable. Data was retrieved from the annual reports (from 2009 to 2019) of non-financial firms listed on the stock exchange of China and Malaysia. Four partnership measures (i.e., Musharakah, Mudarabah, Tawuruq, and Kafalah) were used to estimate the impact of Musharakah on the Sino-Malaysian partnership. Empirical results reveal that Musharakah and Mudarabah are positively related to Kafalah but the relationship is statistically insignificant. Alternatively, Musharakah is positively and significantly related to Mudarabah. Musharakah and Mudarabah have a positive but insignificant relationship. The findings of this study suggest that management of partnership has a positive impact on firm partnership. Furthermore, it supports the hypothesis that improving partnership enhances Musharakah, which has a positive impact on the firm's partnership.