• Journal of Information Technology Application
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• v.3 no.3
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• pp.91-106
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• 2001

We propose a software-reliability growth model incoporating the amount of uniform and Weibull testing efforts during the software testing phase in this paper. The time-dependent behavior of testing effort is described by uniform and Weibull curves. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, the model is formulated by a nonhomogeneous Poisson process. Using this model the method the data analysis for software reliability measurement is developed. The optimum release time is determined by considering how the initial reliability R($\chi$ 0) would be. The conditions are ($R\chi$ 0)＞$R_{o}$ , $P_{o}$ ＞R($\chi$ 0)＞ $R_{o}$ $^{d}$ and R($\chi$ 0)＜$R_{o}$ $^{d}$ for uniform testing efforts. deal case is $P_{o}$ ＞($R\chi$ 0)＞ $R_{o}$ $^{d}$ Likewise, it is ($R\chi$ 0)$\geq$$R_{o}$ , $R_{o}$ ＞($R\chi$ 0)＞R(eqation omitted) and ($R\chi$ 0)＜R(eqation omitted)for Weibull testing efforts. Ideal case is $R_{o}$ ＞ R($\chi$ 0)＞ R(eqation omitted).

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1418-1426
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• 2009

There has been a lot of interest in an effective method for background subtraction in an effort to separate foreground objects from a predefined background image. Promising results on background subtraction using statistical methods have recently been reported are robust enough to operate in dynamic environments, but generally require very large computational resources and still have difficulty in obtaining clear segmentation of objects. We use a simple running-average method to model a gradually changing background, instead of using a complicated statistical technique. We employ a single global threshold vector, optimized by a genetic algorithm, instead of pixel-by-pixel thresholds. A new fitness function is defined and trained to evaluate segmentation result. The system has been implemented on a PC with a webcam, and experimental results on real images show that the new method outperforms an existing method based on a mixture of Gaussian.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.3-9
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• 1999

This paper presents the study on the rejection capability based on anti-phone modeling for vocabulary independent speech recognition system. The rejection system detects and rejects out-of-vocabulary words which were not included in candidate words which are defined while the speech recognizer is made. The rejection system can be classified into two categories by their implementation methods, keyword spotting method and utterance verification method. The keyword spotting method uses an extra filler model as a candidate word as well as keyword models. The utterance verification method uses the anti-models for each phoneme for the calculation of confidence score after it has constructed the anti-models for all phonemes. We implemented an utterance verification algorithm which can be used for vocabulary independent speech recognizer. We also compared three kinds of means for the calculation of confidence score, and found out that the geometric mean had shown the best result. For the normalization of confidence score, usually Sigmoid function is used. On using it, we compared the effect of the weight constant for Sigmoid function and determined the optimal value. And we compared the effects of the size of cohort set, the results showed that the larger set gave the better results. And finally we found out optimal confidence score threshold value. In case of using the threshold value, the overall recognition rate including rejection errors was about 76%. This results are going to be adapted for stock information system based on speech recognizer which is currently provided as an experimental service by Korea Telecom.

• Journal of the Korean Society of Groundwater Environment
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• v.2 no.2
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• pp.49-57
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• 1995

Areas of Chungyang in Chungcheongnamdo, Cheju island and Georgia in U.S.A. were selected to calculate their groundwater ages and dispersion parameters using tritium. Piston flow model, Completely mixing model and Dispersion binomial model which calculate men residence times, and Dispersion normal model and Dispersion model(C$\_$FF) which calculate mean residence times and dispersion parameters simultaneously were applied. Since the input data, tritium concentrations of rainwaters, lack in part, tritium input function was prepared using the correlation of tritium concentrations of rainwaters of Pohang, Korea and Ottawa, Canada. Similar results of PFM and DBM reflect the intrinsical similarity of two models, assumption of low dispersion. The ages of sites of showing relatively higher tritium concentrations than other sites in the sam, region were not calculated by CMM. Since the calculations of DNM and DM(C$\_$FF/) provide the combination of wide ranges of parameters and groundwater ages, the ranges of dispersion parameters were narrowed down under the assumption that ages calculated by PFM and DBM are correct. Since large variation of tritium concentrations of outflows in a same region may reflect the different characteristics of each groundwater flow regime, using only one specific model on a whole region is not recommended.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.7
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• pp.118-126
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• 2003

In this study, a battery charge and discharge regulator of modular type is designed as paralleled bi-directional converter that is possible to provide the power without failure not only in the steady state but also in the transient period by the step load variation or the unexpected faults among the converter modules. Each converter module is designed to get stability, performance, reliability, and maintainability and the average current mode method used for controller has the advantages such as noise immunity, fast response, and the real average current signal acquisition. The equivalent model and small signal model for the paralleled battery chargerIdischarger are presented, and also the transfer functions are analyzed for the CCM(Continuous Charge Mode), CDM(Continuous Discharge Mode) and DDM(Discontinuous Discharge Mode). The experiments of the paralleled bi-directional converter are carried out in the step load variation, and in faults of one converter module respectively. And the performance of paralleled bi-directional converter is verified via the experimental results.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.123-123
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• 2012

일강수량은 수공구조물 설계 및 수자원계획을 수립하기 위한 입력 자료로 이용된다. 일반적으로 수자원계획은 장기적인 목적을 가지고 수행되어지며, 장기간의 일강수량 자료를 필요로 한다. 하지만 장기간의 일강수량 자료의 획득의 어려움으로 단기간의 일강수량자료를 이용하여 모의한 장기간 강수자료를 이용하게 된다. 이처럼 수자원계획의 수립에 있어서 일강수량 모의기법의 성능은 수자원계획의 신뢰성 및 결과에 큰 영향을 준다. 일강수량 모의기법은 국내외적으로 매우 활발하게 이루어지고 있으며, 수자원계획 및 수공구조물 설계 외에도 매우 다양한 목적으로 활용되어 지고 있다. 일강수량을 모의기법 중 강수계열의 단기간의 기억(memory)을 활용한 Markov Chain 모형이 가장 일반적이지만, 기존 Markov Chain 모형을 통한 일강수량 모의는 극치강수량을 재현하기 어렵다는 문제점이 있다. 또한, 일강수량 모의 기법의 목적인 수자원계획 및 수공구조물 설계 등의 입력자료로 활용되어지기 위해서는 모의 결과가 유역내 지점별 공간 상관성을 재현함으로써 모형의 우수성과 자료결과의 신뢰성을 확보할 수 있어야 하겠다. 이러한 점에서 본 연구에서는 내삽에서 우수한 재현능력을 갖는 핵 밀도함수와 극치강수량 재현에 유리한 GPD분포의 특징을 함께 고려할 수 있는 불연속 Kernel-Pareto Distribution 기반에 공간상관성 재현 알고리즘을 결합한 일강수량모의기법을 개발하였다. 한강유역의 18개 강수지점에 대해서 기존 Gamma분포를 사용한 Markov Chain 모형과 본 연구에서 제안한 방법을 적용하여 모형을 평가해 보고자 한다. Gamma 분포기반 Markov Chain 모형의 경우 일강수량 모의 시 1차모멘트인 평균과 2-3차 모멘트 모두 효과적으로 재현하지 못하는 문제점이 나타났다. 그러나 본 연구에서 적용한 다지점 불연속 Kernel-Pareto 분포 모형은 강수계열의 평균적인 특성뿐만 아니라 표준편차 및 왜곡도의 경우에도 관측치의 통계특성을 매우 효과적으로 재현하며, 100년빈도 강수량 모의결과 기존 모의모형의 문제점을 보완할 수 있는 개선된 결과를 보여주었다. 본 연구에서 제시한 방법론은 유역내의 공간상관성을 재현하며, 평균 및 중간값 등 낮은 차수의 모멘트 등 일강수량 분포특성을 더욱 효과적으로 모의할 수 장점을 확인하였다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.78-82
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• 2022

Phenology determines the timing of crop development, and the timing of phenological events is strongly influenced by the temperature during the growing season. In process-based model, leaf area is simulated dynamically by coupling of morphology and phenology module. Therefore, the prediction of leaf appearance rate and final leaf number affects the performance of whole crop model. The dataset for the model equation was collected from SPA R chambers with five different temperature treatments. Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf appearance rate as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0℃ and 35.3℃, respectively. For evaluation of the model, the accumulated number of onion leaves observed in a temperature gradient chamber was compared with model estimates. The model estimate is the result of accumulating the daily increase in the number of onion leaves obtained by inputting the daily mean temperature during the growing season into the temperature model. In this study, the coefficient of determination (R²) and RMSE value of the model were 0.95 and 0.89, respectively.

• Nuclear Engineering and Technology
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• v.23 no.4
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• pp.444-455
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• 1991

An accurate and fast running NEDAR model for calculating radial power profile throughout fuel life in both solid and annular pellets for existing and advanced CANDU-PHWR-fuel was developed in this work. This model contains resultant flux depression equations and neutron depression data tables which have been developed for CANDU-PHWR fuel of pellet with the diameter 8.0 to 19.5 mm and enrichment 0.71-6.0 wt % U-235, over a bumup range of 0 to 840 MWh /kgU (35000 MWD/T). In order to obtain the neutron flux distribution in the fuel pellet, the CE-HAMMER physics code was run for a neutron flux spectrum appropriate to a CANDU-PHWR to give predictions of radial power profile for several ranges of fuel design parameters. The results, which were calculated by the CE-HAMMER physics code, were fitted to an equation which is solved in terms of Bessel and exponential functions in order to obtain the parameters, $textsc{k}$, $\beta$ and λ in the resultant equation. The present NEDAR model produce a radial profile which, when normalized to unity at the pellet surface, is slightly higher than the profile of the original ELESIM data table. The predictions of the fission gas release by KAFEPA-NEDAR are in slightly better agreement with the experiments than those of ELESIM. The NEDAR model described in this study has been shown to provide an effective, reliable, and accurate method for determining radial power profiles in CANDU-PHWR fuel rods without incurring a significant increase in computing time.

• Journal of Korean Society of Forest Science
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• v.90 no.5
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• pp.650-662
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• 2001

The growth and yield models for five different kinds of natural forest types were systemically developed in the natural Broadleaved-Korean pine Forests in Northeast China. The data were collected from 359 temporary plots and 58 permanent plots with area ranged from 0.06 ha to 1.0 ha, ranging in stand age from 43 to 364 years. The Site Class Index (SCI) was introduced to evaluate site quality and the Crown Competition Factor (CCF) was selected as a measure of stand density for the mixed natural forest. The Chapman-Richards function was adopted to develop SCI equation and height-diameter curve. The Schumacher growth function was selected as base model to develop the DBH, basal area, and stand volume growth models by using re-parameterized method. In modeling mean DBH and basal area growth, it was found that the asymptotic parameter A of Schumacher function was exponentially related to site quality (SCI) and stand density (CCF). The rate parameter k was related to stand density and it was independent of SCI. Several validation measures for predicted stand variables were evaluated in the growth and yield models using independent data sets. The results indicated that relative mean errors (RME) in predicted stand attributes were less than ${\pm}5%$ and the estimated precision values of the stand variables were all greater than 95%.

• Korean Journal of Soil Science and Fertilizer
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• v.23 no.2
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• pp.87-93
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• 1990

A statistical model to predict soil temperature from the ambient meteorological factors including mean, maximum and minimum air temperatures, precipitation, wind speed and snow depth combined with Fourier time series expansion was developed with the data measured at the Suwon Meteorolical Service from 1979 to 1988. The stepwise elimination technique was used for statistical analysis. For the yearly oscillation model for soil temperature with 8 terms of Fourier expansion, the mean square error was decreased with soil depth showing 2.30 for the surface temperature, and 1.34-0.42 for 5 to 500-cm soil temperatures. The $r^2$ ranged from 0.913 to 0.988. The number of lag days of air temperature by remainder analysis was 0 day for the soil surface temperature, -1 day for 5 to 30-cm soil temperature, and -2 days for 50-cm soil temperature. The number of lag days for precipitaion, snow depth and wind speed was -1 day for the 0 to 10-cm soil temperatures, and -2 to -3 days for the 30 to 50-cm soil teperatures. For the statistical soil temperature prediction model combined with the yearly oscillation terms and meteorological factors as remainder terms considering the lag days obtained above, the mean square error was 1.64 for the soil surfac temperature, and ranged 1.34-0.42 for 5 to 500cm soil temperatures. The model test with 1978 data independent to model development resulted in good agreement with $r^2$ ranged 0.976 to 0.996. The magnitudes of coeffcicients implied that the soil depth where daily meteorological variables night affect soil temperature was 30 to 50 cm. In the models, solar radiation was not included as a independent variable ; however, in a seperated analysis on relationship between the difference(${\Delta}Tmxs$) of the maximum soil temperature and the maximum air temperature and solar radiation(Rs ; $J\;m^{-2}$) under a corn canopy showed linear relationship as $${\Delta}Tmxs=0.902+1.924{\times}10^{-3}$$ Rs for leaf area index lower than 2 $${\Delta}Tmxs=0.274+8.881{\times}10^{-4}$$ Rs for leaf area index higher than 2.