• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.301-309
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• 2006

The main purpose of this study is to derive a regression equation that predicts the individual differences in activity energy expenditure (AEE) using accelerometer during different types of activity. Two subject groups were recruited separately in time: One is a homogeneous group of 94 healthy young adults with age ranged from $20\sim35$ yrs. The other subject group has a broad spectrum of physical characteristics in terms of age and fat ratio. 226 adolescents and adults of age ranged from $12\sim57$ yrs and fat ratio from $4.1\sim39.7%$ were in the second group. The wireless 3-axis accelerometers were developed and carefully fixed at the waist belt level. Simultaneously the total calorie expenditure was measured by gas analyzer. Each subject performed walking and running at speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.5, and 8.5 km/hr. A generalized sensor-independent regression equation for AEE was derived. The regression equation was developed fur walking and running. The regression coefficients were predicted as functions of physical factors-age, gender, height, and weight with multivariable regression analysis. The generalized calorie estimation equation predicts AEE with correlation coefficient of 0.96 and the average accuracy of the accumulated calorie was $89.6{\pm}7.9%$.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.679-688
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• 2008

In multivariate regression analysis there exist many influence measures on the regression estimates. However it seems to be few of influence diagnostics on test statistics in hypothesis testing. Case-deletion approach is fundamental for investigating influence of observations on estimates or statistics. Tang and Fung (1997) derived single case-deletion of the Wilks' ratio, Lawley-Hotelling trace, Pillai's trace for testing a general linear hypothesis of the regression coefficients in multivariate regression. In this paper we derived more extended form of those measures to deal with joint influence among observations. A numerical example is given to illustrate the effect of joint influence on the test statistics.

• Journal of Families and Better Life
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• v.10 no.1 s.19
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• pp.131-138
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• 1992

Regression analysis has become a standard statistical tool in the behavioral science. Because of its widespread popularity. regression has been often misused. Such is the case when the dependent variable is a qualitative measure rather than a continuous, interval measure. Regression estimates with a qualitative dependent variable does not meet the assumptions underlying regression. It can lead to serious errors in the standard statistical inference. Logit model is recommended as alternatives to the regression model for qualitative dependent variables. Researchers can employ this model to measure the relationship between independent variables and qualitative dependent variables without assuming that logit model was derived from probabilistic choice theory. Coefficients in logit model are typically estimated by the method of Maximum Likelihood Estimation in contrast to ordinary regression model which estimated by the method of Least Squares Estimation. Goodness of fit in logit model is based on the likelihood ratio statistics and the t-statistics is used for testing the null hypothesis.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.737-742
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• 2002

The chief factors for the penetration and diffusion of chloride ions in concrete are water-cement ratio(w/c), aging, thickness of cover concrete, chloride ions concentration of given environment, wet and dry conditions and etc. In this study, effect of w/c and aging on the characteristics of chloride ions diffusion in concrete were researched when environmental factors for the penetration and diffusion of chloride ions were constant. For this purpose, the voltages passing through the diffusion cell were measured by using accelerated test method using potential difference, and then diffusion coefficients of chloride ions by using Andrade's method were estimated for 44%, 49.5% and 55% of w/c, respectively. As a result, correlation among diffusion coefficients of chloride ions, w/c and aging were concluded through multiple regression model.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.2
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• pp.160-165
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• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• Archives of Pharmacal Research
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• v.11 no.2
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• pp.99-113
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• 1988

Quantitation of ethenzamide, isopropylantipyrine and caffeine takes about 41 hrs by conventional GC method. Quantitation of allylisoprorylacetylurea takes about 40 hrs by conventional UV method. But quantitation of them takes about 6 hrs by DRIFT developing method. Each standard and sample sieved, powdered and acquired DRIFT spectrum. Out of them peak of each component was selected and ratio of each peak to standard peak was acquired, and then linear stepwise multiple regression was performed with these data and concentration. Reflectance value, Kubelka-Munk equation and Inverse-Kubelka-Munk equation were modified by us. Inverse-Kubelka-Munk equation completed the deficit of Kubelka-Munk equation. Correlation coefficients acquired by conventioanl GC and UV against DRIFT were more than 0.95.

• Journal of Oral Medicine and Pain
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• v.6 no.1
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• pp.91-100
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• 1981

The author collected 146 men's stone models and 175 women;s stone models over the age of twenties, and studied area ratio of attrition of molars. Area ratio of attrition = (area of attrition / area of occlusal surface)*100(%) All data were analyzed by means of statistical method, and following results were obtained. 1. There was correlation between age and area ratio of attrition, that is, area ratio of attrition was increased with aging process. 2. Regression equtions and coefficients of correlation showed a significant meaning. 3. Generally, upper teeth showed higher tendency of area ratio of attrition, being compared with lowers. 4. Being compared with male and female, there was no uniform difference.

• Journal of Environmental Health Sciences
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• v.32 no.3
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• pp.199-206
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• 2006

Various heavy metals have been known for causing ischemic stroke. In order to describe the causative relationship between the blood levels of various heavy metals and stroke patients, 116 patients with stroke and 111 patients without stroke were selected from one Oriental medical hospital in Wonju, Korea. Total of 9 kinds of metals such as As, Cd, Co, Cu, Hg, Mn, Ni, Pb, and Zn were analyzed in blood from patients with and without stroke. There were no significant differences in the means of metal concentrations between the stroke and nonstroke patients except for the mean of Co concentration. In the case of Co, the means for stroke and non-stroke patients were 0.44 ug/l and 0.40 ug/l showing a significant difference at the level of p-value=0.05. The odds ratios for each metal ranged from 0.96 to 2.86. Most odds ratios were not significant but the odds ratio for Co, $2.86{\pm}1.49$ was significant, indicating that Co increases the risk of stroke by 2.86 times. In order to identify the specific risk level of stroke increased by a multiple interaction of metals, regression coefficients and odds ratio for a pair or multiple pair of metals were reanalyzed. However, all of regression coefficients and odds ratios were not significant. In conclusion, Co showed the significant level in blood from patients with stroke. In addition, the odds ratio of stroke was significantly different from other metals. Thus, it is considered that Co among various metals analyzed in this study is the important metal for increasing the risk of stroke.

• Journal of Ocean Engineering and Technology
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• v.30 no.1
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• pp.25-31
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• 2016

In this study, hydrodynamic coefficients were obtained from a Rotating Arm (RA) test, which is one of the captive model tests used to provide accurate coefficients in the control motion equation of an underwater vehicle. The RA test was carried out at the RA facility of ADD (Agency for Defense Development), and the forces and moments acting on the underwater vehicle were measured using a six-axis waterproof gage. A multiple regression analysis was used in the analysis of the measured data. The experimental results were also verified by comparison with the theoretical values of the previous linear coefficients. In addition, the stability indices in the horizontal plane were calculated using the linear and nonlinear coefficients, and the dynamic stability of the underwater vehicle was estimated to have a good dynamic performance with a depth ratio of 6.0.

• Journal of the Korean Society of Safety
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• v.30 no.2
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• pp.70-76
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• 2015

This study deals with the traffic accident of circular intersections. The purpose of the study is to develop the accident models by traffic violation type. In pursuing the above, this study gives particular attention to analyzing various factors that influence traffic accident and developing such the optimal models as Poisson and Negative binomial regression models. The main results are the followings. First, 4 negative binomial models which were statistically significant were developed. This was because the over-dispersion coefficients had a value greater than 1.96. Second, the common variables in these models were not adopted. The specific variables by model were analyzed to be traffic volume, conflicting ratio, number of circulatory lane, width of circulatory lane, number of traffic island by access road, number of reduction facility, feature of central island and crosswalk.