• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1306-1313
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• 1999

In this paper, we propose the signal strength path loss model (modified Hata path loss Model) and the signal strength distribution model (log-normal distribution) for the cell design of the land mobile communication system. We applied the measured experimental data at Soosungdon and Sanjuckdong in Daeku, to this model and calculate the fraction of total area above threshold.

• Convergence Security Journal
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• v.11 no.4
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• pp.85-91
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• 2011

Due to the large-scale application software syslmls, software reliability, software development has animportantrole. In this paper, software truncated software reliability growth model was proposed based on log-logistic distribution. According to fixed time, the intensity function, the mean value function, the reliability was estimated and the parameter estimation used to maximum likelihood. In the empirical analysis, Poisson execution time model of the existiog model in this area and the log-logistic model were compared Because log-logistic model is more efficient in tems of reliability, in this area, the log-logistic model as an alternative 1D the existiog model also were able to confim that you can use.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.775-781
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• 2008

It is developed that a family of the semicircular Laplace distributions for modeling semicircular data by simple projection method. Mathematically it is simple to simulate observations from a semicircular Laplace distribution. We extend it to the l-axial Laplace distribution by a simple transformation for modeling any arc of arbitrary length. Similarly we develop the l-axial log-Laplace distribution based on the log-Laplace distribution. A bivariate version of l-axial Laplace distribution is also developed.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.704-705
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• 2006

Discrete element analysis is used to map various log-normal particle size distributions into measures of the in-sphere pore size distribution. Combinations evaluated range from monosized spheres to include bimodal mixtures and various log-normal distributions. The latter proves most useful in providing a mapping of one distribution into the other (knowing the particle size distribution we want to predict the pore size distribution). Such metrics show predictions where the presence of large pores is anticipated that need to be avoided to ensure high sintered properties.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.655-666
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• 2008

Small sample likelihood based inference for the shape parameter of the inverse Gaussian distribution is the purpose of this paper. When shape parameter is of interest, the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic are derived. Hsieh (1990) gave a statistical inference for the shape parameter based on an exact method. Throughout simulation, we will compare the statistical properties of the proposed statistics to the statistic given by Hsieh (1990) in term of confidence interval and power of test. We also discuss a real data example.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.443-446
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• 2003

This study was conducted to draw design rainfall for the regional design rainfall derived by the optimal distribution and method of frequency analysis. The design rainfalls were calculated by the regional and at-site analysis for Log-Pearson type III and GEV distributions and were compared with Relative efficiency(RE) which is ratio of Relative root-mean-square error(RRMSE) by the regional and at-site analysis for Log-Pearson type III and GEV distributions. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis for GEV distribution and design rainfall maps were drawn by GIS techniques.

• Journal of the Korean Wood Science and Technology
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• v.21 no.4
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• pp.55-59
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• 1993

한국의 중서부 지역에서 주로 벌채한 잣나무 간벌 제재목을 경기도 광주 소재 제재소에서 무작위로 추출하여 구입하였다. 본 연구는 휨강도 시험을 표준 시험 방법에 의하여 실시하였다. 각 무결점 시편으로부터 측정한 영 계수와 휨 강도에 대하여 이론적 통계 분포인 정상 분포, Log-normal 분포, Weibull 분포를 계산하여 비교하였다. Weibull 분포가 휨영계수 및 휨강도 모두에 적합하였으며, Log-normal 분포는 영계수 분포에 대한 이용에 적합하였다. 휨강도 분포에서는 Normal 분포가 Log-normal 분포보다 적합하다.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1829-1831
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• 2012

Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

• The Journal of Engineering Geology
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• v.25 no.2
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• pp.281-290
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• 2015

Log density data were collected and compared with the core density data throughout the southern Korean Peninsula. The comparison reveals that the log densities obtained from gamma-gamma log are much lower than the core densities obtained from laboratory density measurement of core samples. The anomalously low log densities can be attributed to the small-source density log data. Correlation analysis reveals differences between densities derived from the two methods, indicating that a data quality problem arises when using small-source log data. The problem is probably due to the fact that small-source data have not been obtained under ideal conditions for maintaining the appropriate relationship between gamma response and formation density. The frequency distribution characteristics of formation density in the southern Korean Peninsula could be determined using the core and the standard-source log data which are well-correlated.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.219-226
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• 2014

In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The shape parameter using the Erlang and Log-logistic model that is widely used in the field of reliability problems presented. The software failure model was used finite failure non-homogeneous Poisson process model, the parameters estimation using maximum likelihood estimation was conducted. In comparison result of software cost model based on the Erlang distribution and the log-logistic distribution software cost model, because Erlang model is to predict the optimal release time can be software, but the log-logistic model to predict to optimal release time can not be, Erlang distribution than the log-logistic distribution appears to be effective. In this research, software developers to identify software development cost some extent be able to help is considered.