• Water for future
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• v.8 no.1
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• pp.80-88
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• 1975

In this paper the authors established the best fit distribution function by applying the concept of probabiaity to the annual minimum flow of nine areas along the Nakdong river basin which is one of the largest Korean rivers and calculated the probable minimum flow suitable to those distribution function. Lastly, the authors tried to establish the best method to estimate the probable minimun flow by comparing some frequency analysis methods. The results obtained are as follows (1) It was considered that the extremal distribution type III was the most suitable one in the distributional types as a result of the comparision with Exponential distribution, Log-Normal distribution, Extremal distribution type-III and so on. (2) It was found that the formula of extremal distribution type-II for the estimation of probable minimum flow gave the best result in deciding the probable minimum flow of the Nakdong river basin. Therfore, it is recommended that the probable minimum flow should be estimated by using the extremal distribution type-III method. (3) It could be understood that in the probable minimum flow the average non-excessive probability appeared to be $Po{\fallingdotseq}1-\frac{1}{2T}$ and gave the same values of the probable variable without any difference in the various methods of plotting technique.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.41-49
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• 2005

We have developed a random heterogeneous velocity model with bimodal distribution in methane hydrate-bearing Bones. The P-wave well-log data have a von Karman type autocorrelation function and non-Gaussian distribution. The velocity histogram has two peaks separated by several hundred metres per second. A random heterogeneous medium with bimodal distribution is generated by mapping of a medium with a Gaussian probability distribution, yielded by the normal spectral-based generation method. By using an ellipsoidal autocorrelation function, the random medium also incorporates anisotropy of autocorrelation lengths. A simulated P-wave velocity log reproduces well the features of the field data. This model is applied to two simulations of elastic wane propagation. Synthetic reflection sections with source signals in two different frequency bands imply that the velocity fluctuation of the random model with bimodal distribution causes the frequency dependence of the Bottom Simulating Reflector (BSR) by affecting wave field scattering. A synthetic cross-well section suggests that the strong attenuation observed in field data might be caused by the extrinsic attenuation in scattering. We conclude that random heterogeneity with bimodal distribution is a key issue in modelling hydrate-bearing Bones, and that it can explain the frequency dependence and scattering observed in seismic sections in such areas.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.501-512
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• 2014

Modified cut-off sampling is widely used for highly skewed data. A serious drawback of modified cut-off sampling is the difficulty of adjustment of non-response in take-all stratum. Therefore, solutions of the problems of non-response in take-all stratum have been studied in various ways such as substitute of samples, imputation or re-weight method. In this paper, a new cut-off point based on minimizing MSE being used in exponential and power functions is suggested and it can be reduced the number of take-all stratum. We also investigate another cut-off point determination method with underlying distributions such as truncated log-normal and truncated gamma distributions. Finally we suggest the optimal cut-off point which has a minimum of take-all stratum size among suggested methods. Simulation studies are performed and Labor Survey data and simulated data are used for the case study.

• Journal of The Korean Astronomical Society
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• v.53 no.2
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• pp.49-57
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• 2020

We present numerical simulations of decaying hydrodynamic turbulence initially driven by solenoidal (divergence-free) and compressive (curl-free) drivings. Most previous numerical studies for decaying turbulence assume an isothermal equation of state (EOS). Here we use a polytropic EOS, P ∝ ρ^γ, with polytropic exponent γ ranging from 0.7 to 5/3. We mainly aim at determining the effects of γ and driving schemes on the decay law of turbulence energy, E ∝ t^-α. We additionally study probability density function (PDF) of gas density and skewness of the distribution in polytropic turbulence driven by compressive driving. Our findings are as follows. First of all, we find that even if γ does not strongly change the decay law, the driving schemes weakly change the relation; in our all simulations, turbulence decays with α ≈ 1, but compressive driving yields smaller α than solenoidal driving at the same sonic Mach number. Second, we calculate compressive and solenoidal velocity components separately and compare their decay rates in turbulence initially driven by compressive driving. We find that the former decays much faster so that it ends up having a smaller fraction than the latter. Third, the density PDF of compressively driven turbulence with γ > 1 deviates from log-normal distribution: it has a power-law tail at low density as in the case of solenoidally driven turbulence. However, as it decays, the density PDF becomes approximately log-normal. We discuss why decay rates of compressive and solenoidal velocity components are different in compressively driven turbulence and astrophysical implication of our findings.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.3
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• pp.63-70
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• 2018

In this study, a simple probabilistic approach using equivalent coefficient of consolidation ($c_e$) was proposed to consider the spatial variability of coefficient of vertical consolidation ($c_v$), and the effect of the probability distribution of coefficient of consolidation on degree of consolidation in heterogeneous soil was investigated. The statistical characteristics of consolidation coefficient were estimated from 1,226 field data, and four probability distributions (Normal, Log-normal, Gamma, and Weibull) were applied to consider the effect of probability distribution. The random fields of coefficient of consolidation were generated based on Karhunen-Loeve expansion. Then, the equivalent coefficient of consolidation was calculated from the random field and used as the input value of consolidation analysis. As a result, the probabilistic analysis can be performed effectively by separating random field and numerical analysis, and probabilistic analysis was performed using a Latin hypercube Monte Carlo simulation. The results showed that the statistical properties of $c_e$ were changed by the probability distribution and spatial variability of $c_v$, and the probability distribution of $c_v$ has considerable effects on the probabilistic results. There was a large difference of failure probability depend on the probability distribution when the autocorrelation distance was small (i.e., highly heterogeneous soil). Therefore, the selection of a suitable probability distribution of $c_v$ is very important for reliable probabilistic analysis of consolidation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2396-2402
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• 2015

Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.311-316
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• 2016

Breast cancer is one of the most common causes of cancer mortality in Iran. Social determinants of health are among the key factors affecting the pathogenesis of diseases. This cross-sectional study aimed to determine the social determinants of breast cancer survival time with parametric and semi-parametric regression models. It was conducted on male and female patients diagnosed with breast cancer presenting to the Cancer Research Center of Shohada-E-Tajrish Hospital from 2006 to 2010. The Cox proportional hazard model and parametric models including the Weibull, log normal and log-logistic models were applied to determine the social determinants of survival time of breast cancer patients. The Akaike information criterion (AIC) was used to assess the best fit. Statistical analysis was performed with STATA (version 11) software. This study was performed on 797 breast cancer patients, aged 25-93 years with a mean age of 54.7 (${\pm}11.9$) years. In both semi-parametric and parametric models, the three-year survival was related to level of education and municipal district of residence (P<0.05). The AIC suggested that log normal distribution was the best fit for the three-year survival time of breast cancer patients. Social determinants of health such as level of education and municipal district of residence affect the survival of breast cancer cases. Future studies must focus on the effect of childhood social class on the survival times of cancers, which have hitherto only been paid limited attention.

• The Journal of Engineering Geology
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• v.17 no.3
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• pp.483-494
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• 2007

The properties of fracture system on road-cut slopes along the Busan-Ulsan express way under construction are investigated and analyzed. Fracture spacing distributions show log-normal form with extension fractures and negative exponential form with shear fractures. Straight line segments in log-log plots of cumulative fracture length indicate a power-law scaling with exponents of -1.13 in site 1, -1.01 in site 2 and -1.52 in site 3. It is likely that the stability and strength of rock mass are the lowest in site 1 as judged from the analyses of spacing, density and inter-section of fractures in three sites. In contrast, the highest efficiency of the fracture network for conducting fluid flow is seen in site 3 where the largest cluster occupies 73% through the window map. Based on the field survey data, this study modified weighting values of the RMR system using a multiple regression analysis method. The analysis result suggests a modified weighting values of the RMR parameters as follows; 18 for the intact strength of rock; 61 for RQD; 2 for spacing of discontinuities; 2 for the condition of discontinuities; and 17 for ground water.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.47 no.4
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• pp.177-186
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• 2015

Until Mandelbrot introduced the concept of fractal geometry and fractal dimension in early 1970s, it has been generally considered that the geometry of nature should be too complex and irregular to describe analytically or mathematically. Here fractal dimension indicates a non-integer number such as 0.5, 1.5, or 2.5 instead of only integers used in the traditional Euclidean geometry, i.e., 0 for point, 1 for line, 2 for area, and 3 for volume. Since his pioneering work on fractal geometry, the geometry of nature has been found fractal. Mandelbrot introduced the concept of fractal geometry. For example, fractal geometry has been found in mountains, coastlines, clouds, lightning, earthquakes, turbulence, trees and plants. Even human organs are found to be fractal. This suggests that the fractal geometry should be the law for Nature rather than the exception. Fractal geometry has a hierarchical structure consisting of the elements having the same shape, but the different sizes from the largest to the smallest. Thus, fractal geometry can be characterized by the similarity and hierarchical structure. A process requires driving energy to proceed. Otherwise, the process would stop. A hierarchical structure is considered ideal to generate such driving force. This explains why natural process or phenomena such as lightning, thunderstorm, earth quakes, and turbulence has fractal geometry. It would not be surprising to find that even the human organs such as the brain, the lung, and the circulatory system have fractal geometry. Until now, a normal frequency distribution (or Gaussian frequency distribution) has been commonly used to describe frequencies of an object. However, a log-normal frequency distribution has been most frequently found in natural phenomena and chemical processes such as corrosion and coagulation. It can be mathematically shown that if an object has a log-normal frequency distribution, it has fractal geometry. In other words, these two go hand in hand. Lastly, applying fractal principles is discussed, focusing on pulp and paper industry. The principles should be applicable to characterizing surface roughness, particle size distributions, and formation. They should be also applicable to wet-end chemistry for ideal mixing, felt and fabric design for papermaking process, dewatering, drying, creping, and post-converting such as laminating, embossing, and printing.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.835-849
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• 2016

Accurate drought outlook and drought monitoring have been preceded recently to mitigate drought damages that further deepen. This study improved the limitations of the previous MSWSI (Modified Surface Water Supply Index) used in Korea and carried out probabilistic drought forecasts based on ensemble technique with the improved MSWSI. This study investigated available hydrometeorological components in Geum river basin and supplemented appropriate components (dam water level, dam release discharge) in addition to the four components (streamflow, groundwater, precipitation, dam inflow) usedin the previous MSWSI to each sub-basin. Although normal distribution was fitted in the previous MSWSI, the most suitable probabilistic distributions to each meteorological component were estimated in this study, including Gumbel distribution for precipitation and streamflow data; 2-parameter log-normal distribution for dam inflow, water level, and release discharge data; 3-parameter log-normal distribution for groundwater. To verify the improved MSWSI results using historical precipitation and streamflow, simulated drought situations were used. Results revealed that the improved MSWSI results were closer to actual drought than previous MSWSI results. The probabilistic forecasts based on ensemble technique with improved MSWSI were performed and evaluated in 2006 and 2014. The accuracy of the improved MSWSI was better than the previous MSWSI. Moreover, the drought index of actual drought was included in ranges of drought forecasts using the improved MSWSI.