• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.93-103
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• 2016

In the paper, we discuss dimension reduction of predictors ${\mathbf{X}}{\in}{{\mathbb{R}}^p}$ in a regression of $Y{\mid}{\mathbf{X}}$ with a notion of sufficiency that is called sufficient dimension reduction. In sufficient dimension reduction, the original predictors ${\mathbf{X}}$ are replaced by its lower-dimensional linear projection without loss of information on selected aspects of the conditional distribution. Depending on the aspects, the central subspace, the central mean subspace and the central $k^{th}$-moment subspace are defined and investigated as primary interests. Then the relationships among the three subspaces and the changes in the three subspaces for non-singular transformation of ${\mathbf{X}}$ are studied. We discuss the two conditions to guarantee the existence of the three subspaces that constrain the marginal distribution of ${\mathbf{X}}$ and the conditional distribution of $Y{\mid}{\mathbf{X}}$. A general approach to estimate them is also introduced along with an explanation for conditions commonly assumed in most sufficient dimension reduction methodologies.

• Progress in Medical Physics
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• v.4 no.1
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• pp.55-71
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• 1993

Measured and calculated the TMR and SMR factors from percent depth dose underpartial attenuators which cover the whole part of the radiation beam with variousfilter thickness from 0 to 50 mm. This study was performed for x-ray beams generated with a 6 MV linear acceleratorat source to surface distance of 100cm in a water phantom for Lipowitz metal. TMR(0,d,t) was derived from non-linear polynomial regression with field sizedifferencies and a given filter thickness. In this experiments, the TMR(0,10,50) of 50mm of filter thickness was showed13.6 % higher than that of open field and SMR(5,10,50) was 38.5% smaller than thatof open field in same depth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.143-150
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• 2006

Box-Cox model and T-factor method have been widely used to measure economic depreciations for industrial property. The Box-Cox model which combines economic efficiency with depreciation pattern is here extended to the reliability function. To do so a Rayleigh distribution which has been used to estimate the reliability of current assets was chosen as an efficiency curve of marginal productivity. Such an approach provides the possibility to classify the efficiency curves into four categories. It is also possible to analyze the types of depreciation curves. Therefore, the power family of a non-linear Box-Cox model could be set at certain constant values, then the model can be transformed into a linear model to estimate the economic depreciation rates by utilizing the reliability function. Estimating the resultant linear regression equation requires minimal number of observations, while at the same time facilitating the test of hypothesis on depreciation rates.

• The Journal of Engineering Geology
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• v.20 no.1
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• pp.35-45
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• 2010

The soil tests have been performed on the specimens obtained from about 1,150 sites including landslides and non-landslides areas in natural terrains for last 10 years. Based on the results of those tests, the average soil properties are estimated and the simple equations for estimating permeability are proposed according to geologic conditions. The average permeability in Granite and Mudstone sites is higher than other sites and the content of silt and clay in Mudstone and Gneiss sites is higher than other sites. The correlation analysis and the regression analysis were performed to estimate the coefficient of permeability according to geological conditions. As the result of the correlation analysis, the coefficient of permeability is selected as a dependent variable, and the silt and clay contents, the water contents and the dry unit weights are selected as independent variables. As the result of the regression analysis, the silt and clay contents and the void ratio were involved commonly in the linear regression equations according to geological conditions. To verify the proposed the linear regression equations, the measured result of the coefficient of permeability at other sites was compared with the result predicted with the proposed equations. As the result of comparison, there were a little bit different between them for some data. However the difference was relatively small. Therefore, the linear regression equations for estimating the coefficient of permeability according to geological conditions may be applied to Korean soils. However, these equations should be verified and corrected continuously to improve the accuracy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.325-342
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• 2020

The current study is focused on the evaluation of the ultimate strength of stiffened panels found in ship hull structures that are subjected to combined uniaxial thrust, in-plane and out-of-plane bending moments. This loading condition, which is in general ignored when performing buckling checks, applies to representative control geometries (stiffener with attached plating) as a consequence of the linearly varying normal stresses along the ship's depth induced by the hull-girder vertical bending moment. The problem is generalized by introducing a non-uniform thrust described by a displacement ratio and rotation angle and by introducing the slenderness ratios, within the practical range of interest. The formed design space is explored through methods sourcing from Design of Experiments and by applying non-linear finite element procedures. Surrogate empirical models have been constructed through regression analysis and Response Surface Methods. An additional empirical model is provided to the literature for predicting the ultimate strength under uniaxial thrust. The numerical experimentation has shown that is a significant influence on the ultimate strength of stiffened panels as the thrust non-uniformity increases.

• Physical Therapy Korea
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• v.22 no.4
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• pp.27-33
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• 2015

The purpose of this study was to find which spatiotemporal gait parameters gained from stroke patients could be predictive factors for the gait part of Tinetti Performance-Oriented Mobility Assessment (POMA-G). Two hundred forty-six stroke patients were recruited for this study. They participated in two assessments, the POMA-G and computerized spatiotemporal gait analysis. To analyze the relationship between the POMA-G and spatiotemporal parameters, we used Pearson's correlation coefficients. In addition, multiple linear regression analyses (stepwise method) were used to predict the spatiotemporal gait parameters that correlated most with the POMA-G. The results show that the gait velocity (r=.67, p<.01), cadence (r=.66, p<.01), step length of the affected side (r=.49, p<.01), step length of the non-affected side (r=.53, p<.01), swing percentage of the non-affected side (r=.47, p<.01), and single support percentage of the affected side (r=.53, p<.01) as well as the double support percentage of the non-affected side (r=-.42, p<.01) and the step-length asymmetry (r=-.64, p<.01) correlated with POMA-G. The gait velocity, step-length asymmetry, cadence, and single support percentage of the affected side explained 67%, 2%, 2%, and 1% of the variance in the POMA-G, respectively. In conclusion, gait velocity would be the most predictive factor for the POMA-G.

• Steel and Composite Structures
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• v.43 no.4
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• pp.501-509
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• 2022

Cracks are common defects in concrete structures. Thus far, crack inspection has been manually performed using the contact inspection method. This manpower-dependent method inevitably increases the cost and work hours. Various non-contact studies have been conducted to overcome such difficulties. However, previous studies have focused on developing a methodology for non-contact inspection or local quantitative detection of crack width or length on concrete surfaces. However, crack depth can affect the safety of concrete structures. In particular, although macrocrack depth is structurally fatal, it is difficult to find it with the existing method. Therefore, an experimental investigation based on non-contact infrared thermography and multivariate machine learning was performed in this study to estimate the hidden macrocrack depth. To consider practical applications for inspection, an experiment was conducted that considered the simulated piloting of an unmanned aerial vehicle equipped with infrared thermography equipment. The crack depths (10-60 mm) were comparatively evaluated using linear regression, gradient boosting, and random forest (AI regression methods).

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.374-386
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• 2024

To predict the apparent total tract digestibility (ATTD) of crude protein (CP) in dogs we developed an in vitro system using an in vitro digestion method and a statistical analysis. The experimental diets used chicken meat powder as the protein source, with CP levels of 20% (22.01%, analyzed CP value as dry-based), 30% (31.35%, analyzed CP value as dry-based), and 40% (41.34%, analyzed CP value as dry-based). To simulate in vivo digestive processes a static in vitro digestion was performed in two steps; stomach and small intestine. To analyze ATTD the total fecal samples were collected in eight neutered beagle dogs during the experimental period. CP digestibility was calculated by measuring CP levels in dog food, in vitro undigested fraction, and dog feces. In result, CP digestibility at both in vivo and in vitro was increased with increasing dietary CP levels. To estimate in vivo digestibility the co-relation of in vivo ATTD and in vitro digestibility was investigated statistically and a regression equation was developed to predict the CP ATTD (% = 2.5405 × in vitro CP digestibility (%) + + 151.8). The regression equation was evaluated its feasibility by using a commercial diet. The predicted CP digestibility which was calculated by the regression equation showed high index of similarity (100.16%) with that of in vivo in dogs. With that, it would be a feasible non-animal method to predict in vivo CP digestibility by using in vitro digestion method and the proposed linear regression equation in adult dogs.

• Journal of Soil and Groundwater Environment
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• v.14 no.5
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• pp.41-50
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• 2009

Water levels in groundwater monitoring wells of Jeju Island were analyzed using parametric and non-parametric trend analyses. Number of used monitoring wells in the analysis are 94 among totally 106 monitoring wells and the monitoring period is greater than single year, from 2001 to 2009. For the trend analysis, both parametric (linear regression) and nonparametric (Mann-Kendall trend test and Sen's trend test) methods were adopted. Results of the linear regression analysis on daily basis indicated that about 58.5% of the monitoring wells showed a decreasing trend, and analysis using monthly median indicated that about 79.8% showed a decreasing trend. The Mann-Kendall trend test and Sen's trend test with monthly median values in confidence levels of 95% and 99% showed the same analysis results. In confidence level of 95%, 32% were decreased, 3% were increased and the remains showed no trend. However, in confidence level of 99%, 16% were decreased, 2% were increased and the remains showed no trend. The largest decline rates of water levels were detected mainly at the coast of the northwestern and southwestern parts, which is expected to closely related to the increased pumping in the urban area and tourist resort.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8791-8799
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• 2015

In this paper, One-way car-sharing System represents the verification system consider events in revenue effects. Revenue which the time and distance represented the graph, compare one-way vehicle relocate car-sharing system which proven in existing international papers with one-way vehicle relocate car-sharing system consider the event currently in the Korea. Especially, The maximum profit according to the distance and time were assessed through multiple linear regression analysis, and there are probable maximum loss allow for the maximum loss. The company suggested using the event as a discount coupon to customers through various marketing strategies, and then focused on increasing customer demand. So, Correlation analysis to determine the maximum revenue of the actual travel distance and time were carried out through Non-linear Regression.