• Journal of Radiation Protection and Research
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• v.11 no.1
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• pp.22-28
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• 1986

Densities of a large number of mixed uranyl nitrate-thorium nitrate solutions were measured with pycnometer. By the least squares analysis of the experimental result, an empirical formula for determining water content of mixed uranyl nitrate-thorium nitrate solutions as functions of uranium concentration, thorium concentration and nitric acid normality is derived; $W=1.0-0.358\;C_u-0.4538\;C_{Th}-0.0307\;H^+$ where $W,\;C_u,\;C_{Th},\;and\;H^+$ stand for water content(g/cc), uranium concentration (g/cc), thorium concentration (g/cc), and nitric acid normality, respectively. Water contents of the mixed uranyl nitrate-thorium nitrate solutions are calculated by using the empirical formula, and compared with the values calculated by Bouly's equation in which an additional data, solution density, is required. The two results show good agreements within 2.7%.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1039-1047
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• 2014

An autoregressive model with normal errors is a natural model that attempts to fit time series data. More flexible models that include normal distribution as a special case are necessary because they can cover normality to non-normality models. The skewed exponential power distribution is a possible candidate for autoregressive models errors that may have tails lighter(platykurtic) or heavier(leptokurtic) than normal and skewness; in addition, the use of skewed exponential power distribution can reduce the influence of outliers and consequently increases the robustness of the analysis. We use SIR algorithm and grid method for an efficient Bayesian estimation.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.333-339
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• 2019

The purpose of this study is to clarify the effect of magnesium water on the cognitive function, concentration and performance of bowling players. The total number of subjects in this study was 42, and changes in blood magnesium concentration, cognitive ability, concentration and performance were identified during the four-week experiment period. Data distribution was analyzed using SPSS18.0 with Normality test and Repeated measure two way ANOVA. Studies show that the concentration of magnesium in the blood of bowling players has changed with the intake of magnesium drinks, and that the concentration of magnesium in the blood has a proportional relationship with the cognitive function, concentration and performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.154-154
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• 2022

The frequency of natural disasters, including floods and drought events, driven by climate change has increased in recent times. Investigating the climate regimes and the roles of climate variables are indispensable to forestall future climate change-related disasters. This study compares the variability of two popular and widely used climate indices i.e., the United Nations Environment Programme (UNEP) aridity index and the Modified De-Martonne (MDM) index to assess the trend of climate change in the Chungcheong provinces of South Korea. The trend of annual and monthly climate indices was conducted using a non-parametric Mann-Kendall test and Kolmogorov-Smirnov normality test with daily climate data of 48 years (1978-2020) from 10 synoptic stations. The findings indicate that UNEP and MDM indices had a wet climate regime for the annual trend, with the UNEP index indicating a relatively humid trend of 60% humid, 20% semi-arid, and 10% sub-humid for the 48-years study period. However, the MDM index showed a high frequency of a severe wet climatic condition followed by the semi-arid condition. The months of July and August had the highest occurring frequency of the wet climatic condition (90%) for both UNEP and MDM indices. Comparing the two provinces, Chungnam showed a relatively wetter climatic condition using the UNEP index, while the MDM index indicated no significant regional difference in climate regime between the two provinces. The Kolmogorov-Smirnov normality test showed that all the 10 stations are normally distributed for monthly climate conditions at a 5% significant level in the two provinces except five stations for UNEP index and four stations for MDM index in the month of January.

• Journal of Korean Medicine Rehabilitation
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• v.34 no.3
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• pp.89-96
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• 2024

Objectives This study is designed to evaluated the safety of peony root extract tablet in healthy male volunteers. Methods 12 healthy male volunteers were recruited, and this study was conducted by a single center. The safety was evaluated by collecting laboratory test and vital signs of volunteers. As the registration process, 12 subjects were assigned by serial number. To evaluate safety, vital signs were checked and blood samples were collected 4 times during the screening period, pre & post-administration (after 8 hours) and post-administration (after 7 days). The difference in variables was summarized by the mean±standard deviation. The normality test was carried out using the Shapiro-Wilk test and Kolmogorov-Smirnov test. When normality is fulfilled, a paired t-test is applied and the significance level was p<0.05. And the incidence of all adverse effects and serious adverse effects are shown in percentage. Results In the case of vital sign, body temperature (BT) (℃) was 0.06±0.05 ℃ (p=0.008), and there was a statistically significant difference in before and after administration. However, clinical symptoms were not occurred and BT (℃) of all subjects before and after administration showed values within the normal reference value. There was no significant difference from the control group in all other vital signs and laboratory test data. And no side-effects associated to clinical trial drugs were followed. Conclusions The peony root extract tablet was considered to be safe for healthy male volunteers.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.4.1-4.6
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• 2010

The most common type of microarray experiment has a simple design using microarray data obtained from two different groups or conditions. A typical method to identify differentially expressed genes (DEGs) between two conditions is the conventional Student's t-test. The t-test is based on the simple estimation of the population variance for a gene using the sample variance of its expression levels. Although empirical Bayes approach improves on the t-statistic by not giving a high rank to genes only because they have a small sample variance, the basic assumption for this is same as the ordinary t-test which is the equality of variances across experimental groups. The t-test and empirical Bayes approach suffer from low statistical power because of the assumption of normal and unimodal distributions for the microarray data analysis. We propose a method to address these problems that is robust to outliers or skewed data, while maintaining the advantages of the classical t-test or modified t-statistics. The resulting data transformation to fit the normality assumption increases the statistical power for identifying DEGs using these statistics.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.97-110
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• 2021

Fog can cause large-scale human and economic damages, including traffic systems and agriculture. So, Korea Meteorological Administration is operating about 290 visibility meters to improve the observation level of fog. However, it is still insufficient to detect very localized fog. In this study, high-resolution grid-type visibility data were retrieved from irregularly distributed visibility data across the country. To this end, three objective analysis techniques (Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Universal Kriging (UK)) were used. To find the best method and parameters, sensitivity test was performed for the effective radius, power parameter and variogram model that affect the level of objective analysis. Also, the effect of data distribution characteristics (level of normality) on the performance level of objective analysis was evaluated. IDW showed a relatively high level of objective analysis in terms of bias, RMSE and correlation, and the performance is inversely proportional to the effective radius and power parameter. However, the two Krigings showed relatively low level of objective analysis, in particular, greatly weakened the variability of the variables, although the level of output was different depending on the variogram model used. As the level of objective analysis is greatly influenced by the distribution characteristics of data, power, and models used, care should be taken when selecting objective analysis techniques and parameters.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.143-152
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• 1997

In this paper, we obtain maximum likelihood estimators for $P(X_{1}\;<\;X_{2})$ in the Marshall and Olkin's bivariate exponential model with bivariate censored data. The asymptotic normality of the estimator is derived. Also we propose approximate testing for $P(X_{1}\;<\;X_{2})$ based on the M.L.E. We compare the test powers under vsrious conditions through Monte Carlo simulation.

• Phonetics and Speech Sciences
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• v.10 no.4
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• pp.31-37
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• 2018

Pitch trajectories reflect a continuous variation of vocal fold movements over time. This study examined the pitch trajectories of English vowels produced by 139 American English speakers, statistically analyzing their trajectories using the Generalized Additive Mixed Models (GAMMs). First, Praat was used to read the sound data of Hillenbrand et al. (1995). A pitch analysis script was then prepared, and six pitch values at the corresponding time points within each vowel segment were collected and checked. The results showed that the group of men produced the lowest pitch trajectories, followed by the groups of women, boys, then girls. The density line showed a bimodal distribution. The pitch values at the six corresponding time points formed a single dip, which changed gradually across the vowel segment from 204 to 193 to 196 Hz. The normality tests performed on the pitch data rejected the null hypothesis. Nonparametric tests were therefore conducted to discover the significant differences in the values among the four groups. The GAMMs, which analyzed all the pitch data, produced significant results among the pitch values at the six corresponding time points but not between the two groups of boys and girls. The GAMMs also revealed that the two groups were significantly different only at the first and second time points. Accordingly, the methodology of this study and its findings may be applicable to future studies comparing curvilinear data sets elicited by experimental conditions.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.393-399
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• 2009

This paper introduces an automated tool named Advanced Stochastic Schedule Simulation System (AS4). The system automatically integrates CPM schedule data exported from Primavera Project Planner (P3) and historical activity duration data obtained from a project data warehouse, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, computes the optimum number of simulation runs, simulates the schedule network for the optimum number of simulation runs, and estimates the best fit PDF of project completion times (PCTs). AS4 improves the reliability of simulation-based scheduling by effectively dealing with the uncertainties of the activities' durations, increases the usability of the schedule data obtained from commercial CPM software, and effectively handles the variability of the PCTs by finding the best fit PDF of PCTs. It is designed as an easy-to-use computer tool programmed in MATLAB. AS4 encourages the use of simulation-based scheduling because it is simple to use, it simplifies the tedious and burdensome process involved in finding the PDFs of the many activities' durations and in assigning the PDFs to the many activities of a new network under modeling, and it does away with the normality assumptions used by most simulation-based scheduling systems in modeling PCTs.