• Journal of Life Science
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• v.18 no.11
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• pp.1532-1537
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• 2008

The purpose of this study was to investigate the effect of different arthroplasty designs on knee kinematic and lower limb muscular activation for up-stair and down-stair movement. 3-D video analysis of whole body and joint kinematics and EMG analysis of quadriceps and hamstrings were conducted. One-way ANOVAs were used for statistical analyses (p=0.05). The single-radius group exhibited more arthroplasty limb quadriceps EMG and hamstring coactivation EMG than the multi-radius group. Single-radius demonstrated more abduction angular displacement and reached peak abduction earlier than the multi-radius arthroplasty limb. The single- radius the percent body fat showed similar values in the Elderly, Single and Multi-radius group among the periods, however Control group was Lowered among the periods. Single-radius group limb also increased the quadriceps muscle activation level to produce more knee extension moment to compensate for the short quadriceps moment arm. Resting metabolic rate was significantly increased in control group in the period of LI. Energy expenditure was extremely increased in all groups except control group among the periods. We can say this is the exercise effects.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1201-1212
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• 2016

Value at Risk (VaR) for market risk management is a favorite method used by financial companies; however, there are some problems that cannot be explained for the amount of loss when a specific investment fails. Conditional Tail Expectation (CTE) is an alternative risk measure defined as the conditional expectation exceeded VaR. Multivariate loss rates are transformed into a univariate distribution in real financial markets in order to obtain CTE for some portfolio as well as to estimate CTE. We propose multivariate CTEs using multivariate quantile vectors. A relationship among multivariate CTEs is also derived by extending univariate CTEs. Multivariate CTEs are obtained from bivariate and trivariate normal distributions; in addition, relationships among multivariate CTEs are also explored. We then discuss the extensibility to high dimension as well as illustrate some examples. Multivariate CTEs (using variance-covariance matrix and multivariate quantile vector) are found to have smaller values than CTEs transformed to univariate. Therefore, it can be concluded that the proposed multivariate CTEs provides smaller estimates that represent less risk than others and that a drastic investment using this CTE is also possible when a diversified investment strategy includes many companies in a portfolio.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2805-2812
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• 2018

The methylation score, expressed as a percentage of the methylation status data derived from the iterative sequencing process, has a value between 0 and 1. It is contrary to the assumption of normal distribution that simply applying the t-test to examine the difference in population-specific methylation scores in these data. In addition, since the result may vary depending on the number of repetitions of sequencing in the process of methylation score generation, a method that can analyze such errors is also necessary. In this paper, we introduce the symbolic data analysis and the interval K-S test method which convert observation data into interval data including uncertainty rather than one numerical data. In addition, it is possible to analyze the characteristics of methylation score by using Beta distribution without using normal distribution in the process of converting into interval data. For the data analysis, the nature of the proposed method was examined using sequencing data of actual patients and normal persons. While the t-test is only possible for the location test, it is found that the interval type K-S statistic can be used to test not only the location parameter but also the heterogeneity of the distribution function.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.745-758
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• 2009

Cluster analysis is the automated search for groups of related observations in a data set. To group the observations into clusters many techniques has been proposed, and a variety measures aimed at validating the results of a cluster analysis have been suggested. In this paper, we compare complete linkage, Ward's method, K-means and model-based clustering and compute validity measures such as connectivity, Dunn Index and silhouette with simulated data from multivariate distributions. We also select a clustering algorithm and determine the number of clusters of Korean consumers based on Korean consumers' palatability scores for Hanwoo bull in BBQ cooking method.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.291-303
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• 2006

Data mining is the work to extract information from existing data file. So, the one of best important thing in data mining process is the quality of data to be used. In this thesis, we propose the data fusion technique using decision rule for data enrichment that one phase to improve data quality in KDD process. Simulations were performed to compare the proposed data fusion technique with the existing techniques. As a result, our data fusion technique using decision rule is characterized with low MSE or misclassification rate in fusion variables.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.665-679
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• 2017

When measuring productive efficiency, often it is necessary to have knowledge of the production frontier function that shows the maximum possible output of production units as a function of inputs. Canonical parametric forms of the frontier function were initially considered under the framework of stochastic frontier model; however, several additional nonparametric methods have been developed over the last decade. Efforts have been recently made to impose shape constraints such as monotonicity and concavity on the non-parametric estimation of the frontier function; however, most existing methods along that direction suffer from unnecessary non-smooth points of the frontier function. In this paper, we propose methods to estimate the smooth frontier function with monotonicity for stochastic frontier models and investigate the effect of imposing a monotonicity constraint into the estimation of the frontier function and the finite dimensional parameters of the model. Simulation studies suggest that imposing the constraint provide better performance to estimate the frontier function, especially when the sample size is small or moderate. However, no apparent gain was observed concerning the estimation of the parameters of the error distribution regardless of sample size.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.427-439
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• 2017

Quade (1967) proposed RANK ANCOVA, which is a nonparametric method to test differences between treatments when there are covariates. Hwang and Kim (2012) also proposed a joint placement test on covariate-adjusted residuals. In this paper, we proposed a new nonparametric method to control the effect of covariate on a response variable that uses linear statistics on covariate adjusted-residuals. The score function used in the linear statistics was proposed by Jeon and Kim (2016). Monte Carlo simulation is also conducted to compare the empirical powers of the proposed method with previous methods.

• Journal of the Korean Institute of Gas
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• v.11 no.3
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• pp.13-18
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• 2007

The multivariate statistical analysis, using the multiple linear regression(MLR), have been applied to analyze and predict the flash points of binary systems. Prediction for the flash points of flammable substances is important for the examination of the fire and explosion hazards in the chemical process design. In this paper, the flash points are predicted by MLR based on the physical properties of pure substances and the experimental flash points data. The results of regression and prediction by MLR are compared with the values calculated by Raoult's law and Van Laar equation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.4
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• pp.592-601
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• 2015

Rubus coreanus is known as Korean black raspberry, native to Korea, Japan, and China. Preliminary studies evaluating their potential for cancer treatment in mammalian test systems are ongoing. In recent years, interest has been renewed due to their high levels of anthocyanins. Anthocyanins in black raspberry are important due to their potential health benefits as dietary antioxidant, anti-inflammatory compound, and as a chemopreventive agent. In the present study, Saccharomyces cerevisiae BA29 was isolated from black raspberry fruit and fruit juice as a biogenic amine non-producing strain for manufacturing of black raspberry wine, after which we investigated its characteristics: biogenic amine-producing ability, cell growth ability, alcohol-fermentation ability, and resistance to alcohol, glucose, and sulfur dioxide. Based on preliminary experiments, we optimized culture medium compositions for improving dried cell weight of S. cerevisiae BA29 by response surface methodology (RSM) as a statistical method. Design for RSM used a central composite design, and molasses with the industrial applicability was used as a carbon source. Through statistical analysis, we obtained optimum values as follows: molasses 200 g/L, peptone 30 g/L, and yeast extract 40 g/L. For the model verification, we confirmed about 3-fold improvement of dried cell weight from 6.39 to 20.9167 g/L compared to basal yeast peptone dextrose medium. Finally, we manufactured black raspberry wine using S. cerevisiae BA29 and produced alcohol of 20.33%. In conclusion, S. cerevisiae isolated from black raspberry fruit and juices has a great potential in the fermentation of black raspberry wine.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.3
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• pp.281-286
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• 2010

Purpose: This research provided basic data for refraction by comparing the corrected diopter of trial lens and phoropter. Methods: We compared the corrected diopter of trial lens and phoropter, and analyzed statistical significance and relations of the spherical lens corrected diopter and cylindrical lens corrected diopter according to the types (trial lens and phoropter) of subjective refractive instruments. Also we analyzed statistical significance and relations between cylindrical lens corrected diopter at the astigmatism and the types (trial lens and phoropter) of subjective refractory instruments. Results: When we measured the corrected diopter of simple myopia, the mean value for corrected diopter was S-2.74D using the trial lens and S-2.65D using the phoropter. So the corrected diopter was 0.09D smaller when measured by phoropter. The degree of astigmatism was measured C-0.81D using the trial lens and C-0.77D using the phoropter which showed that the measured value was 0.04D smaller using the phoropter. On correlation analysis between the refractive instruments (trial lens and phoropter) and the corrected diopter, there was significant (p<0.01) strong correlation between refractory machine and corrected spherical diopter (r=0.996) and the correlation between refractory machine and corrected cylindrical diopter was r=0.986 and was also significant (p<0.01). Conclusions: The use of phoropter than trial lens was more desirable when performing refraction on high myopia (simple refractive error, high astigmatism), and when using trial lens, you should consider the vertex distance and the gap between overlapped lenses before prescription.