• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.17-32
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• 2022

This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.859-866
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• 2001

The problem of wavelet density estimation is studied when the sample observations are contaminated with random noise. In this paper a linear wavelet estimator based on Meyer-type wavelets is shown to be L$_1$ strongly consistent for f(x) with bounded support when Fourier transform of random noise has polynomial descent or exponential descent.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.243-248
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• 1995

The problem of optimal design for a nonparametric regression with binary data is considered. The aim of the statistical analysis is the estimation of a quantal response surface in two dimensions. Bias, variance and IMSE of kernel estimates are derived. The optimal design density with respect to asymptotic IMSE is constructed.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.99-111
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• 1995

It is shown that the adaptive kernel methods can potentially produce superior density estimates to the fixed one. In using the adaptive estimates, problems pertain to the initial choice of the estimate can be solved by iteration. Also, simultaneous recommended for variety of distributions. Some data-based method for the choice of the parameters are suggested based on simulation study.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.113-113
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• 2017

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.679-691
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• 2003

The band-width of disk drive servo system is rapidly increasing for the robustness to external disturbance as the track density is increasing. The increase of the band-width may cause mechanical resonance of an actuator. In disk drive servo system, a notch filter is usually used to suppress the mechanical resonance of the actuator. However, the resonance frequency differs from drive to drive because of manufacturing tolerance and varies with temperature even within a single drive. The variation of resonance frequency degrades the suppression performance of the notch filter. In this paper, we present an adaptive digital notch filter that identifies the resonance frequency of the disk drive servo actutaor precisely and adjusts automatically its center frequency. For this, we design an adaptive FIR digital filter for the estimation of the resonance frequency. The estimation filter identifies the resonance frequency adaptively using the output signal generated from the servo system, which is excited with an excitation signal including all the expected resonance frequency components. We prove mathematically the convergence of the resonance frequency estimation filter. Furthermore, in order to demonstrate the practical use of our work, we present some experimental results using a commercially available disk drive.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2369-2379
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• 2013

The Soil-Water Characteristics Curve (SWCC) is affected by the initial density of soil under unsaturated condition. Also, the characteristic of hydraulic conductivity is changed by the initial density of soil. To study the effect of initial density of unsaturated soil, SWCC and the Hydraulic Conductivity Function (HCF) of Jumoonjin sand with various relative densities, 40%, 60% and 75% were measured in both drying and wetting processes. As the results of SWCC estimated by van Genuchten (1980) model, the parameter related to Air Entry Value(AEV), ${\alpha}$ in the wetting process is larger than that in drying process, but the parameters related to the SWCC slope, n and the residual water content, m are larger than those in wetting process. The AEV is increased or Water Entry Value (WEV) is decreased with increasing the relative density of sand. The AEV is larger than the WEV at the same relative density of sand. As the results of HCF estimated by van Genuchten (1980) model which is one of the parameter estimation methods, the unsaturated hydraulic conductivity maintained at a saturated one in the low level of matric suctions and then suddenly decreased just before the AEV or the WEV. The saturated hydraulic conductivity in drying process is larger than that in wetting process. The saturated hydraulic conductivity is decreased with increasing the relative density of sand in both drying and wetting processes. Also, the hysteresis in unsaturated HCFs between drying and wetting process was occurred like the hysteresis in SWCCs. According to the test results, the AEV on SWCC is decreased and the saturated hydraulic conductivity is increased with increasing the initial density. It means that SWCC and HCF are affected by the initial density in the unsaturated soil.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.4
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• pp.344-350
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• 2011

Higher integrated density in 3D ICs also brings the difficulties of routing, which can cause the routing failure or re-design from beginning. Hence, precise congestion estimation at the early physical design stage such as floorplan is beneficial to reduce the total design time cost. In this paper, an effective estimation method of routing congestion is proposed for 3D ICs at floorplan stage. This method uses synthesized virtual signal nets, power/ground network and clock network to achieve the estimation. During the synthesis, the TSV location is also under consideration. The experiments indicate that our proposed method had small difference with the estimation result got at the post-placement stage. Furthermore, the comparison of congestion maps obtained with our method and global router demonstrates that our estimation method is able to predict the congestion hot spots accurately.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.721-733
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• 2011

We consider the state price densities that are implicit in financial asset prices. In the pricing of an option, the state price density is proportional to the second derivative of the option pricing function and this relationship together with no arbitrage principle imposes restrictions on the pricing function such as monotonicity and convexity. Since the state price density is a proper density function and most of the shape constraints are caused by this, we propose to estimate the state price density directly by specifying candidate densities in a flexible nonparametric way and applying methods of regularization under extra constraints. The problem is easy to solve and the resulting state price density estimates satisfy all the restrictions required by economic theory.

• Korean Chemical Engineering Research
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• v.46 no.6
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• pp.1043-1051
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• 2008

In polyolefin processes melt index (MI) is the most important controlled variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the $1^{st}$-order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. Using the model predictive control method based on the present dynamic MI estimation model, MI values are estimated and compared with those of MI setpoints. From the numerical simulation of the proposed control system, it was found that significant reduction of transition time and the amount of off-spec during grade changes were achieved.