• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.265-276
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• 2008

The observed data of enough period need for design of hydrological works. But, most hydrological data aren't enough. Therefore in this paper, hourly precipitation generated by nonhomogeneous Markov chain model using variable Kernel density function. First, the Kernel estimator is used to estimate the transition probabilities. Second, wet hours are decided by transition probabilities and random numbers. Third, the amount of precipitation of each hours is calculated by the Kernel density function that estimated from observed data. At the results, observed precipitation data and generated precipitation data have similar statistic. Also, rainfall mass curve is derived by calculated transition probabilities for generation of hourly precipitation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.173-181
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• 2019

To estimate probabilistic distribution function from experimental data, kernel density estimation(KDE) is mostly used in cases when data is insufficient. The estimated distribution using KDE depends on bandwidth selectors that smoothen or overfit a kernel estimator to experimental data. In this study, various bandwidth selectors such as the Silverman's rule of thumb, rule using adaptive estimates, and oversmoothing rule, were compared for accuracy and conservativeness. For this, statistical simulations were carried out using assumed true models including unimodal and multimodal distributions, and, accuracies and conservativeness of estimating distribution functions were compared according to various data. In addition, it was verified how the estimated distributions using KDE with different bandwidth selectors affect reliability analysis results through simple reliability examples.

• The Journal of the Acoustical Society of Korea
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• v.35 no.3
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• pp.234-242
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• 2016

In this paper, an on-line noise coherence estimation algorithm for binaural speech enhancement system is proposed. A number of noise Power Spectral Density (PSD) estimation algorithms based on the noise coherence between two microphones have been proposed to improve the speech enhancement performance. In the conventional algorithms, the noise coherence was characterized using a real-valued analytic model. However, unlike the analytic model, the noise coherence between the two microphones is time-varying in real environments. Thus, in this paper, the noise coherence is updated in accordance with the variation of the acoustic environment to track the realistic noise coherence. The noise coherence can be updated only during the absence of speech, and the simulation results demonstrate the superiority of the proposed algorithm over the conventional algorithms based on the analytic model.

• Journal of Korean Society of Forest Science
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• v.97 no.2
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• pp.171-180
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• 2008

The characterization of tree species and forest stand conditions is useful in the planning of activities aimed to conserve biodiversity. The main objective of this study was to describe tree species diversity, species composition and stand structure of tropical deciduous forests distributed in three regions in Myanmar. Forest inventory was conducted in the Oktwin teak bearing forest, the Letpanpin community forest and Alaungdaw Kathapa National Park. According to the Jackknife estimator of species richness, 85 species (${\pm}18.16$), 70 species (${\pm}5.88$) and 186 species (${\pm}17.10$) belonging to 31 families were found in the Oktwin teak bearing forest, 33 families in Letpanpin community forest and 53 families in Alaungdaw Kathapa national park, respectively. Shannon's diversity indices were significantly different among the forests (p<0.05). It ranged from 3.36 to 4.36. Mean tree density (n/ha) of the Oktwin teak bearing forest, Letpanpin community forest and Alaungdaw Kathapa National Park were 488 (${\pm}18.6$), 535 (${\pm}15.6$) and 412 (${\pm}14.1$), while basal areas per hectare were $46.96m^2({\pm}3.23),\;49.01m^2({\pm}5.08)\;and\;60.03m^2({\pm}3.88)$, respectively. At the family level, Verbenaceae, Myrtaceae and Combretaceae occupied the highest importance value index, while at the species level it was Tectona grandis, Lagerstoremia speciosa and Xylia xylocarpa.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.705-712
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• 2009

Histogram is the oldest and most widely used density estimator for presentation and exploration of observed univariate data. The structure of a histogram really depends on the number of bins and the width of the bins, so that slight changes on bins can produce totally different shape of a histogram. In order to solve this problem the fuzzy histogram was introduced and the result was good enough (Loquin and Strauss, 2008). In particular, when estimating loss distribution related with operational risk a histogram has been widely used. In this article, instead of an ordinary histogram we try to use a fuzzy histogram for estimating loss distribution and show that a fuzzy histogram provide more stable results.

• Korean Journal of Mathematics
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• v.21 no.4
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• pp.429-437
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• 2013

Let $X_1$, $X_2$, ${\cdots}$, $X_n$ be independent and identically distributed random variables having common exponential density with unknown mean ${\mu}$. In the sequential confidence interval estimation for the exponential hazard rate ${\theta}=1/{\mu}$, when the loss function is strictly convex, the following stopping rule is proposed with the half length d of prescribed confidence interval $I_n$ for the parameter ${\theta}$; ${\tau}$ = smallest integer n such that $n{\geq}z^2_{{\alpha}/2}\hat{\theta}^2/d^2+2$, where $\hat{\theta}=(n-1)\bar{X}{_n}^{-1}/n$ is the minimum risk estimator for ${\theta}$ and $z_{{\alpha}/2}$ is defined by $P({\mid}Z{\mid}{\leq}{\alpha}/2)=1-{\alpha}({\alpha}{\in}(0,1))$ Z ~ N(0, 1). For the confidence intervals $I_n$ which is required to satisfy $P({\theta}{\in}I_n){\geq}1-{\alpha}$. These estimated intervals $I_{\tau}$ have the asymptotic consistency of the sequential procedure; $$\lim_{d{\rightarrow}0}P({\theta}{\in}I_{\tau})=1-{\alpha}$$, where ${\alpha}{\in}(0,1)$ is given.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.445-461
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• 2019

It is possible that data are not always fitted with sufficient precision by the existing distributions; therefore this article presents a methodology that enables the use of families of asymmetric distributions as alternative probabilistic models for survival analysis, with censorship on the right, different from those usually studied (the Exponential, Gamma, Weibull, and Lognormal distributions). We use a more flexible parametric model in terms of density behavior, assuming that data can be fit by a distribution of stable distribution families considered unconventional in the analyses of survival data that are appropriate when extreme values occur, with small probabilities that should not be ignored. In the methodology, the determination of the analytical expression of the risk function h(t) of the $L{\acute{e}}vy$ distribution is included, as it is not usually reported in the literature. A simulation was conducted to evaluate the performance of the candidate distribution when modeling survival times, including the estimation of parameters via the maximum likelihood method, survival function ${\hat{S}}$(t) and Kaplan-Meier estimator. The obtained estimates did not exhibit significant changes for different sample sizes and censorship fractions in the sample. To illustrate the usefulness of the proposed methodology, an application with real data, regarding the survival times of patients with colon cancer, was considered.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1011-1020
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• 2018

This study aims to develop a drought monitoring scheme based on groundwater which can be exploit for water supply under drought stress. In this context, groundwater level can be used as a proxy for better understanding the temporal evolution of drought state. First, kernel density estimator is presented in the monthly groundwater level over the entire national groundwater stations. The estimated cumulative distribution function is then utilized to map the monthly groundwater level into the standardized groundwater level index (SGI). The SGI for each station was eventually converted into the index for major cities through the Thiessen polygon approach. We provide a drought classification for a given SGI to better characterize the degree of drought condition. Ultimately, we conclude that the proposed monitoring framework enables a more reliable estimation of the drought stress, especially for a limited water supply area.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.332-345
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• 2013

In this paper, recently, it is described to the piezoelectric transformer technology develops, because it was have to favorable characteristics such as electromagnetic-noise free, compact size, higher efficiency, and superior power density, flux linkage, noiseless, etc. its resonance frequency was used to output waveform of a sine wave. A rotor speed identification method of induction motor based on the theory of flux model reference adaptive system(FMRAS). The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the model are introduced to perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM techniuqe and DC-DC converter. High speed calculation and processing for vector control is carried out by digital signal one chip microprocessor. Validity of the proposed control method is verified through simulation and experimental results.