• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.77-78
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• 2002

A regression formula including the inlet film thickness as the parameter for the starvation factor in EHL condition is obtained by numerical analysis with Elord‘s cavitation algorithm. In addition, an apparatus for starved film thickness measurement by use of the white light interferometry is developed in order to verify the proposed regression formula. From observation results by this apparatus, the proposed regression formula can predict the reduction of central film thickness caused by starvation in a ball-plate contact with an uncertainty up to 10%

• Geomechanics and Engineering
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• v.17 no.1
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• pp.11-18
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• 2019

The formulas offered so far on the settlement of raft footings provide only a rough estimate of the actual settlement. One of the best ways to make an accurate estimation is to conduct 3-dimensional finite element analyses. However, the required procedure for these analyses is comparatively cumbersome and expensive and needs a bit more expertise. In order to address this issue, in this study, a raft footing settlement formula was developed based on ninety finite element model configurations. The formula was derived using multi-parameter exponential regression analyses. The settlement formula incorporates the dimensions and the elastic modulus of a rectangular raft, vertical uniform pressure and soil moduli and Poisson's ratios up to 5 layers. In addition to this, an equation was offered for the estimation of average deflection of the raft. The proposed formula was checked against 3 well-documented case studies. The formula that is derived from 3D finite element analyses is useful in optimising the raft properties.

• The Research Journal of the Costume Culture
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• v.7 no.2
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• pp.275-288
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• 1999

The purpose of this is providing a simple, relatively errorless body surface area calculation. Subjects were 10 married women and 10 singles women whose age was 20 to 29 years old. The Gypsum method has applied for the sampling of body surface. The Weight method has been used to measure body surface by means of transferring gypsum shape on uniform plane polypropylene films. In this study, compare analyzed errors between the traditional formulas for measuring body surface area and measuring data in this experiment. More than all, it has been to induce a regression equation for measuring body surface area, which is so simple to calculate with less errors, with variable factors as weight and height. The results of this experiment as follows : 1. In the traditional formulas, weight formula was shown high average error : Niya\`s height formula. which was modified K value as 0.62 in the height formula (S = KH) is shown lower average error than Lassabliere\`s Height formula. 2. In the weight-height formula (S=K √WH), it was shown high average error according to the increasing of K value. Kawanami\`s formula, which 5.378 as K value, was shown low average error both the singles and the married women. 3. Dubois weight-heingt formula (S=W/sup a/·H/sub b/·K) was shown low average error than the weight, height, weight-height (S=K√WH) formula. 4. The regression equations with variable factors as weight and height are 156.74W + 86.05H - 660.25 (Single women) and 136.02W + 90.57H - 6241.32 (Married women) the average error and absolute average error to the singles are 0.09%, 0.94% and resoectively -0.13%, 1.16% for the married women.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.374-383
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• 2020

At ship design stage, the maneuverability is generally estimated based on the empirical formula or the computational fluid dynamic (CFD), which is one of the numerical simulation methods. Using the hydrodynamic derivatives derived through these methods can quantitatively estimate the maneuverability of target vessels and evaluate indirect maneuverability. Nevertheless, research on estimating maneuverability is insufficient for ships not subject to IMO maneuverability standard, especially fishing vessels, and even at the design stage, the empirical formula developed for merchant ships is applied without modification. An estimation error may occur due to the empirical formula derived from the regression analysis results of a model test if the empirical formula developed for merchant ships with different hull shapes is applied to fishing vessels without any modification. In this study, the modified empirical formula that can more accurately estimate the fishing vessel's maneuverability was derived by including the hull shape parameter of target fishing trawlers in the regression analysis process that derives Kijima et al. (1990) formula. As a result, the modified empirical formula showed an average estimation error of 6%, and the result improved the average error of 49% of Kijima et al. (1990) formula developed for merchant ships.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.71-76
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• 2009

This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

• Journal of Oral Medicine and Pain
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• v.10 no.1
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• pp.73-89
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• 1985

This study comprised 157 extracted teeth, 73 of the teeth originated from mates and 84 from females, the age range was 12-79 years. The correlation coefficient of each Gustafson's criteria in relation to age was carried out. Age estimation were performed on 157 teeth according to the method by Gustafson and by use of multiple regression, as used by Johanson, after evaluating the six criteria of Gustafson by multiple regression computer analysis. Two prediction formulas and standard deviations were compared with each other. The results were as follows : 1. The author found that six Gustafson's criteria had strong correlation with age except root resorption, and correlation coefficients were r = 0.79 (Transparent dentin), r=0.72 (Secondary dentin), r 0.69 (Periodontal change), r=0.63(Attrition), r = 0.39 (Root resorption), respecti vely. 2. The age estimation formula by Gustafson's method was calculated as follows: Y 8.88 + 3.52X r =0.87, r2 = 0.76, SD = 8.18, F = 483.56, P < 0.01 The age estimation formula by multiple regression was calculated as follows: Y 8.57 + 6.37T + 6.37T + 4.63P + 2.70S + 2.40C + 3.08A + 1.34R r= 0.89, r2 = 0.78, SD = 7.82, F = 91.62, P < 0.01, Durbin-Watson Coefficient = 1.09 3. In comparison of two estimation formulas, the formula by multiple regression, the method of Johanson, was found to be slightly more reliable than Gustafson's method. Gustafson's method SD = 8.18, Multiple regression (Johanson's method) SD = 7.82 4. It was reaffirmed that Gustafson's six criteria could be a independent variable in multiple regression analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.3
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• pp.285-291
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• 2014

This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

• The Korean Journal of Food & Health Convergence
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• v.8 no.1
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• pp.21-30
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• 2022

This study proposed a multiple regression equation for predicting VO2max of elderly men and women using functional performance variables required to conduct daily activities. The subjects of this study were 58 elderly men (72.4±5.9 yrs) and 117 elderly women (73.4±4.5 yrs) aged 65-90 who belong to the senior welfare center. The maximal graded exercise test using a cycle ergometer and functional performance representing muscle strength, endurance, static and dynamic flexibility, mobility, and agility were measured. For statistical processing, multiple regression analysis was performed, and the statistical significance level was α = .05. As a result, the VO2max estimation formula for the elderly was 0.419 (standing up and sitting down a chair) + 0.199 (leg endurance against wall) + 5.383, and R2=0.406. In addition, the VO2max estimation formula for elderly women is - 0.737 (standing up from a supine position) - 0.144 (waking around two cones in a figure 8) - 0.135 (%body fat) + 0.042 (one leg balance with eyes open) + 29.395, R2=0.367 was calculated. The conclusion is that if the maximal graded exercise test is not available, it is considered that VO2max of the elderly can be predicted properly by using the estimation formula calculated based on the functional performance variable.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.163-174
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• 2010

As pointed out in the OECD BEMUSE Program, when a high computation time is taken to obtain the relevant output values of a complex physical model (or code), the number of statistical samples that must be evaluated through it is a critical factor for the sampling-based uncertainty analysis. Two alternative methods have been utilized to avoid the problem associated with the size of these statistical samples: one is based on Wilks' formula, which is based on simple random sampling, and the other is based on the conventional nonlinear regression approach. While both approaches provide a useful means for drawing conclusions on the resultant uncertainty with a limited number of code runs, there are also some unique corresponding limitations. For example, a conclusion based on the Wilks' formula can be highly affected by the sampled values themselves, while the conventional regression approach requires an a priori estimate on the functional forms of a regression model. The main objective of this paper is to assess the feasibility of the ACE-RSM approach as a complementary method to the Wilks' formula and the conventional regression-based uncertainty analysis. This feasibility was assessed through a practical application of the ACE-RSM approach to the LOFT L2-5 LBLOCA PCT uncertainty analysis, which was implemented as a part of the OECD BEMUSE Phase III program.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.87-94
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• 2014

According to the technical guideline of water pollutant load management, the rainfall captured ratio which can be estimated by the empirical formula is an important element to estimate reduction loads of non-point pollutants water quality control basin. In this study, the rainfall captured ratio is altered to stormwater captured ratio considering its meaning in the technical guideline of water pollutant load management, and the new empircal formula of stormwater captured ratio is suggested. In order to do this, we calculate stormwater captured ratio by using the hourly rainfall data of seven urban weather stations (Busan, Daegu, Daejeon, Gangreung, Seoul, Gwangju, and Jeju) for 43 years. The regression coefficients of the existed empirical formula cannot reflect the catchment properties at all, because they are fixed values regardless of regions. However the empirical formula of stormwater captured ratio has flexible regression coefficients by runoff coefficient(C), so it is allowed to consider the characteristics of runoff in catchment. It is expected that reduction loads of storage based water quality control basin can be more reasonably estimated than before.