• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.378-384
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• 2015

Indoor localization is becoming one of the most important technologies for smart mobile applications with different requirements from conventional outdoor location estimation algorithms. Fingerprinting location estimation techniques based on neural networks have gained increasing attention from academia due to their good generalization properties. In this paper, we propose a novel location estimation algorithm based on an ensemble of multiple neural networks. The neural network ensemble has drawn much attention in various areas where one neural network fails to resolve and classify the given data due to its' inaccuracy, incompleteness, and ambiguity. To the best of our knowledge, this work is the first to enhance the location estimation accuracy in indoor wireless environments based on a neural network ensemble using fingerprinting training data. To evaluate the effectiveness of our proposed location estimation method, we conduct the numerical experiments using the TGn channel model that was developed by the 802.11n task group for evaluating high capacity WLAN technologies in indoor environments with multiple transmit and multiple receive antennas. The numerical results show that the proposed method based on the NNE technique outperforms the conventional methods and achieves very accurate estimation results even in environments with a low number of APs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.768-772
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• 2009

This paper proposes a method for measurement three-dimensional trajectories of bubbles generated around a swimmer's arms from stereo high-speed camera videos. This method is based on two techniques: two-dimensional trajectory estimation in single-camera images and trajectory pair matching in stereo-camera images. The two-dimensional trajectory is estimated by block matching using similarity of bubble shape and probability of bubble displacement. The trajectory matching is achieved by a consistensy test using epipolar constraint in multiple frames. The experimental results in two-dimensional trajectory estimation showed the estimation accuracy of 47% solely by the general optical flow estimation, whereas 71% taking the bubble displacement into consideration. This concludes bubble displacement is an efficient aspect in this estimation. In three-dimensional trajectory estimation, bubbles were visually captured moving along the flow generated by an arm; which means an efficient material for swimmers to swim faster.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.39-74
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• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.35-38
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• 2000

The method of Content-based Triangular Mesh Image representation in moving pictures makes better performance in prediction error ratio and visual efficiency than that of classical block matching. Specially if background and objects can be separated from image, the objects are designed by Irregular mesh. In this case this irregular mesh design has an advantage of increasing video coding efficiency. This paper presents the techniques of mesh generation, motion estimation using these mesh, uses image warping transform such as Affine transform for image reconstruction, and evaluates the content based mesh design through computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1303-1307
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• 2018

A improving sensorless compensator for the IPMSM(Interior Permanent Magnet Synchronous Motor) drive system is proposed. Generally, the motor drive system is required the robust parameter variation and disturbance. The speed estimation methods of the conventional IRP(Instantaneous Reactive Power) compensator is improved by the speed estimation techniques of the current model observer with the proposed instantaneous reactive power compensator. Performance evaluations of the novel speed error compensator and sensorless control system are carried out by the experiments.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.581-589
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• 1998

An algorithm is proposed for the $L_1$-estimation with linear equality and inequality constraints in linear regression model. The algorithm employs a linear scaling transformation to obtain the optimal solution of linear programming type problem. And a special scheme is used to maintain the feasibility of the updated solution at each iteration. The convergence of the proposed algorithm is proved. In addition, the updating and orthogonal decomposition techniques are employed to improve the computational efficiency and numerical stability.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.643-646
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• 1994

A method of trajectory error estimation of a hypersonic vehicle, by a covariance analysis technique is presented and discussed. The method itself is a wellkown technique, however, the thema has been rarely treated. As the importance is increasing, it is explained here and some of our newly deviced techniques are also presented.

• 한국데이터정보과학회:학술대회논문집
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• 2002.06a
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• pp.75-84
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• 2002

This paper compares long-run returns of privatization initial public offerings to those of domestic stock markets of respective countries using a sample of 196 privatization initial public offerings from 39 countries. The evidence indicates that the privatization initial public offerings (IPOs) significantly outperform their domestic stock markets. There are substantial differences in the long-run performance of privatization IPOs depending on the return estimation techniques, however. Evidence indicates that the inference based either on conventional t or on skewness-adjusted t statistics may yield misspecified test statistics. The quality of estimation tends to be improved by simply eliminating the outliers from the sample, especially for the buy-and-hold abnormal return technique.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1807-1810
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• 2002

This paper presents a technique for avoid- ing indefiniteness in Maximum Likelihood (ML) criteria for Direction-of-Arrival (DOA) finding using a sensor ar- ray with arbitrary configuration. The ML criterion has singular points in the solution space where the criterion becomes indefinite. Solutions fly iterative techniques for ML bearing estimation may oscillate because of numerical instability which occurs due to the indefiniteness, when bearings more than one approach to the identical value. The oscillation makes the condition for terminating iterations complex. This paper proposes a technique for avoiding the indefiniteness in ML criteria.