• Bulletin of the Korean Chemical Society
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• 제7권1호
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• pp.29-35
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• 1986

An empirical formula for semiconductive metal oxides is proposed relating nonstoichiometric value x to a temperature or an oxygen partial pressure such that experimental data can be represented more accurately by the formula than by the well-known Arrhenius-type equation. The proposed empirical formula is log x = A + $B{\cdot}1000/T\;+\;C{\cdot}$exp$(-D{\cdot}1000/T)$ for a temperature dependence and $log\;{\times}\;=a\;+b{\cdot}log\;Po_2\;+\;c{\cdot}$exp$(-d{\cdot}log\;Po_2)$ for an oxygen partial pressure dependence. The A, B, C, D and a, b, c, d are parameters which are evaluated by means of a best-fitting method to experimental data. Subsequently, this empirical formula has been applied to the n-type metal oxides of $Zn_{1+x}O,\; Cd_{1+x}O,\;and\;PrO_{1.8003-x}$, and the p-type metal oxides of $CoO_{1+x},\; FeO_{1+x},\;and\;Cu_2O_{1+x}$. It gives a very good agreement with the experimental data through the best-fitted parameters within 6% of relative error. It is also possible to explain approximately qualitative characters of the parameters A, B, C, D and a, b, c, d from theoretical bases.

• 한국습지학회지
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• 제2권1호
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• pp.49-58
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• 2000

The frequency analysis of annual maximum rainfall data and the derivation of probable rainfall intensity formula at Masan station are performed in this study. Based on the eight different rainfall duration data from 10 minutes to 24 hours, eight types of probability distribution (Gamma, Lognormal, Log-Pearson type III, GEV, Gumbel, Log-Gumbel, Weibull, and Wakeby distributions), three types of parameter estimation scheme (moment, maximum likelihood and probability weighted methods) and three types of goodness-of-fit test (${\chi}^2$, Kolmogorov-Smirnov and Cramer von Mises tests) were considered to find an appropriate probability distribution at Masan station. The Lognormal-2 distribution was selected and the probable rainfall intensity formula was derived by regression analysis. The derived formula can be used for estimating rainfall quantiles of the Masan vicinity areas with convenience and reliability in practice.

• 한국식품저장유통학회지
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• 제24권6호
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• pp.827-833
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• 2017

시판 살균제의 실제 적용 시 감균 효과를 조사하기 위해 양상추를 신선편의 가공하고, 세척 시 살균제로 이들을 적용한 후 저장 중 pH 및 일반세균, 효모, 곰팡이, 대장균, 대장균군의 변화를 조사하였다. 살균제 스크리닝 결과, 0.02%의 염소수 처리 시 3.1 log 감소를, 1% 농도에서 acetic acid는 2.4 log, ascorbic acid는 1.3, citric acid는 0.7 log의 감균 효과를 나타내었다. 시판 중인 살균제 대부분에서 2 log 의 감균 효과를 나타내어, 이들을 신선편의 양상추에 적용하고 $10^{\circ}C$에 저장하면서 양상추의 pH 변화 및 미생물의 변화를 조사하였다. 저장 초기 양상추의 pH는 살균제 용액의 pH에 따라 변화하고 있었는데, 용액의 pH가 가장 높은 칼슘제제(12.0)가 6.1, 가장 낮은 Formula 4(4%, pH 1.7)에서 가장 낮은 pH(4.7)로 나타났으며 저장일 경과에 따라 pH는 유의적으로 증가하고 있었다. 대장균군을 제외하고 0.02%의 염소수가 가장 높은 수준의 미생물 저해 효과를 나타내었다. 반면 Formula 4, Fresh produce wash 모두 3% 이상에서 미생물 저해 효과가 나타나고 있었다. 특히 Formula 4는 대장균 및 대장균군 저해 효과가 매우 좋았다. 모든 처리구에서 곰팡이는 검출되지 않았으며 효모의 경우 염소수와 Fresh produce wash 및 알코올 살균제 중 키토콜과 칼슘 제제 처리구가 효과적으로 저해하고 있었다. 시판 살균제에 따라 미생물 저해 효과는 다르게 나타나고 있었으나 염소수와 비교했을 때 초기 미생물 저해 효과는 존재하고 있기 때문에 부가적인 hurdle technology 및 공정관리를 통해 저장 중 항미생물 효과를 지속시킨다면 실제 적용이 가능할 것으로 판단된다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제27권3호
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• pp.180-193
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• 2023

Approximating the implied volatilities and estimating the model parameters are important topics in quantitative finance. This study proposes an approximation formula for short-maturity near-the-money implied volatilities in stochastic volatility models. A general second-order nonlinear PDE for implied volatility is derived in terms of time-to-maturity and log-moneyness from the Feyman-Kac formula. Using regularity conditions and the Taylor expansion, an approximation formula for implied volatility is obtained for short-maturity nearthe-money call options in two stochastic volatility models: Heston model and SABR model. In addition, we proposed a novel numerical method to estimate model parameters. This method reduces the number of model parameters that should be estimated. Generating sample data on log-moneyness, time-to-maturity, and implied volatility, we estimate the model parameters fitting the sample data in the above two models. Our method provides parameter estimates that are close to true values.

• Journal of Microbiology and Biotechnology
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• 제17권2호
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• pp.364-368
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• 2007

Enterobacter sakazakii may be related to outbreaks of meningitis, septicemia, and necrotizing enterocolitis, mainly in neonates. To reduce the risk of E. sakazakii in baby foods, thermal characteristics for Korean E. sakazakii isolates were determined at 52, 56, and $60^{\circ}C$ in saline solution, rehydrated powdered infant formula, and dried baby food. In saline solution, their D-values were 12-16, 3-5, and 0.9-1 min for each temperature. D-values increased to 16-20, 4-5, and 2-4 min in rehydrated infant formula and 14-17, 5-6, and 2-3 min in dried baby food. The overall calculated z-value was 6-8 for saline, 8-10 for powdered infant formula, and 9-11 for dried baby food. Thermal inactivation of E. sakazakii during rehydration of powdered infant formula was investigated by viable counts. Inactivation of cultured E. sakazakii in infant formula milk did not occur for 20 min at room temperature after rehydration with the water at $50^{\circ}C$ and their counts were reduced by about 1-2 log CFU/g at $60^{\circ}C$ and 4-6 log CFU/ml with the water at 65 and $70^{\circ}C$. However, the thermo stability of adapted E. sakazakii to the powdered infant formula increased more than two times. Considering that the levels of E. sakzakii observed in powdered infant formula have generally been 1 CFU/100 g of dry formula or less, contamination with E. sakazakii can be reduced or eliminated by rehydrating water with at least $10^{\circ}C$ higher temperature than the manufacturer-recommended $50^{\circ}C$.

• Journal of Communications and Networks
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• 제6권3호
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• pp.209-215
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• 2004

In this paper, a butterfly Log-MAP decoding algorithm for turbo code is proposed. Different from the conventional turbo decoder, we derived a generalized formula to calculate the log-likelihood ratio (LLR) and drew a modified butterfly states diagram in 8-states systematic turbo coded system. By comparing the complexity of conventional implementations, the proposed algorithm can efficiently reduce both the computations and work units without bit error ratio (BER) performance degradation.

• 한국수자원학회논문집
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• 제39권9호
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• pp.737-744
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• 2006

난류의 내부 영역의 유속은 단순한 공식으로 표현하기 매우 어려운 형태를 가지고 있다. 이 속도 분포를 기술하는 여러 가지 공식들이 제안된 바 있지만, 모든 공식들은 많은 항들을 가지거나 적분형 또는 음함수꼴을 가지고 있다. 이것은 이 식들이 적용하기 힘들거나, 매개 변수들을 추정하기 어렵다는 것을 의미한다. 이 연구에서는 매끄러운 바닥 위를 흐르는 난류 내부 영역의 유속 분포를 표현할 수 있는 간단한 형태의 새로운 공식을 제안하였다. 이 공식은 전통적인 대수 법칙에 감쇄 함수를 곱한 형태이다. 단 하나의 추가적인 매개 변수를 도입하여, 전체 내부 영역의 유속 분포를 적절하게 표현할 수 있었다. 이 공식은 벽법칙이 성립하는 바닥 근처의 유속과 대수 법칙이 성립되는 중복 영역의 유속 분포까지를 적절하게 나타낼 수 있다. 또한, 추가된 매개 변수인 감쇄 계수는 쉽게 추정할 수 있다. 이 변수는 Reynolds 수의 변화에 민감하지 않으며, 공식에 의하여 계산된 유속 분포도 또한 이 매개 변수의 변화에 대해서 민감하지 않다.

• Communications for Statistical Applications and Methods
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• 제22권4호
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• pp.389-399
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• 2015

It is important not to overcalculate sample sizes for clinical trials due to economic, ethical, and scientific reasons. Kang and Kim (2014) investigated the accuracy of a well-known sample size calculation formula based on the approximate power for continuous endpoints in equivalence trials, which has been widely used for Development of Biosimilar Products. They concluded that this formula is overly conservative and that sample size should be calculated based on an exact power. This paper extends these results to binary endpoints for three popular metrics: the risk difference, the log of the relative risk, and the log of the odds ratio. We conclude that the sample size formulae based on the approximate power for binary endpoints in equivalence trials are overly conservative. In many cases, sample sizes to achieve 80% power based on approximate powers have 90% exact power. We propose that sample size should be computed numerically based on the exact power.

• 자원환경지질
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• 제4권4호
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• pp.225-234
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• 1971

With the advance of civilization and steadily increasing population rivalry and competition for the use of the sewage, culverts, farm irrigation and control of various types of flood discharge have developed and will be come more and more keen in the future. The author has tried to calculated a formula that could adjust these conflicts and bring about proper solutions for many problems arising in connection with these conditions. The purpose of this study is to find out effective sewage, culvert, drainage, farm irrigation, flood discharge and other engineering needs in the Taegu area. If demands expand further a new formula will have to be calculated. For the above the author estimated methods of control for the probable expected rainfall using a formula based on data collected over a long period of time. The formula is determined on the basis of the maximum daily rainfall data from 1921 to 1971 in the Taegu area. 1. Iwai methods shows a highly significant correlation among the variations of Hazen, Thomas, Gumbel methods and logarithmic normal distribution. 2. This study obtained the following major formula: ${\log}(x-2.6)=0.241{\xi}+1.92049{\cdots}{\cdots}$(I.M) by using the relation $F(x)=\frac{1}{\sqrt{\pi}}{\int}_{-{\infty}}^{\xi}e^{-{\xi}^2}d{\xi}$. ${\xi}=a{\log}_{10}\(\frac{x+b}{x_0+b}\)$ ($-b<x<{\infty}$) ${\log}(x_0+b)=2.0448$ $\frac{1}{a}=\sqrt{\frac{2N}{N-1}}S_x=0.1954$. $b=\frac{1}{m}\sum\limits_{i=1}^{m}b_s=-2.6$ $S_x=\sqrt{\frac{1}{N}\sum\limits^N_{i=1}\{{\log}(x_i+b)\}^2-\{{\log}(x_0+b)\}^2}=0.169$ This formule may be advantageously applicable to the estimation of flood discharge, sewage, culverts and drainage in the Taegu area. Notation for general terms has been denoted by the following. Other notations for general terms was used as needed. $W_{(x)}$ : probability of occurranec, $W_{(x)}=\int_{x}^{\infty}f_{(n)}dx$ $S_{(x)}$ : probability of noneoccurrance. $S_{(x)}=\int_{-\infty}^{x}f_(x)dx=1-W_{(x)}$ T : Return period $T=\frac{1}{nW_{(x)}}$ or $T=\frac{1}{nS_{(x)}}$ $W_n$ : Hazen plot $W_n=\frac{2n-1}{2N}$ $F_n=1-W_x=1-\(\frac{2n-1}{2N}\)$ n : Number of observation (annual maximum series) P : Probability $P=\frac{N!}{{t!}(N-t)}F{_i}^{N-t}(1-F_i)^t$ $F_n$ : Thomas plot $F_n=\(1-\frac{n}{N+1}\)$ N : Total number of sample size $X_l$ : $X_s$ : maximum, minumum value of total number of sample size.

• 한국농공학회지
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• 제15권4호
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• pp.3160-3169
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• 1973

Rainfall, evaporation, and permeability of water are the most important factors in determining the demand of water. The Daegu area has only a meteorologi observatory and there is not sufficient data for adapting the advanced method for derivation of the estimated of evaporation in the Daegu area. However, by using available data, the writer devoted his great effort in deriving the most reasonable formula applicable to the Daegu area and it is adaptable for various purposes such as industry and estimation of groundwater etc. The data used in this study was the monthly amount of evaporation of the Daegu area for the past 13 years(1960 to 1970). A year can be divided into two groups by relative degrees of evaporation in this area: the first group (less evaporation) is January, February, March, October, November, and December, and the second (more evaporation) is April, May, June, July, August, and September. The amount of evaporation of the two groups were statistically treated by the theory of probability for derivation of estimated formula of evaporation. The formula derved is believed to fully consider. The characteristic hydrological environment of this area as the following shows: log(x＋3)=0.8963＋0.1125$\xi$..........(4, 5, 6, 7, 8, 9 month) log(x-0.7)=0.2051＋0.3023$\xi$..........(1, 2, 3, 10, 11, 12 month) This study obtained the above formula of probability of the monthly evaporation of this area by using the relation: $F_(x)=\frac{1}{{\surd}{\pi}}\int\limits_{-\infty}^{\xi}e^{-\xi2}d{\xi}\;{\xi}=alog_{\alpha}({\frac{x_0+b'}{x_0+b})\;(-b<x<{\infty})$ $$log(x_0＋b)=0.80961$ $$\frac{1}{a}=\sqrt{\frac{2N}{N-1}}\;Sx=0.1125$$ $$b=\frac{1}{m}\sum\limits_{i-I}^{m}b_s=3.14$$ $$S_x=\sqrt{\frac{1}{N}\sum\limits_{i-I}^{N}\{log(x_i+b)\}^2-\{log(x_i+b)\}^2}=0.0791$$ (4, 5, 6, 7, 8, 9 month) This formula may be advantageously applied to estimation of evaporation in the Daegu area. Notation for general terms has been denoted by following: $W_(x)$: probability of occurance. $$W_(x)=\int_x^{\infty}f(x)dx$$ P : probability $$P=\frac{N!}{t!(N-t)}{F_i^{N-{\pi}}(1-F_i)^l$$ $$F_{\eta}:\; Thomas\;plot\;F_{\eta}=(1-\frac{n}{N+1})$$ $X_l\;X_i$: maximun, minimum value of total number of sample size(other notation for general terms was used as needed)