• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.513-521
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• 2020

In this paper, we have developed a Fama - French five factor model (FF5 model) from Fama & French (2015) by using concept of time-varying coefficient. For a data set, we have used monthly data form Kenneth R. French home page, it include Japan portfolios (classified by using size and book-to-market) and 5 factors from July 1990 to April 2020. The first analysis, we used Augmented Dickey-Fuller test (ADF test) for the stationary test, from the result, all Japan portfolios and 5 factors are stationary. Next analysis, we estimated a coefficient of Fama - French five factor model by using a generalized additive model with a thin-plate spline to create the time-varying coefficient Fama - French five factor model (TV-FF5 model). The benefit of this study is TV-FF5 model which can capture a different effect at different times of 5 factors but the traditional FF5 model can't do it. From the result, we can show a time-varying coefficient in all factors and in all portfolios, for time-varying coefficients of Rm-Rf, SMB, and HML are significant for all Japan portfolios, time-varying coefficients of RMW are positively significant for SM, and SH portfolio and time-varying coefficients of CMA are significant for SM, SH, and BM portfolio.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.2
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• pp.187-192
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• 2009

A snap ring is a kind of metal spring with open ends which can be installed into a groove to prevent lateral movement. In this study a nonlinear finite element analysis model is developed to simulate the fastening process of a snap ring connecting the constant velocity joint and the transmission. Insert load, disengage load and breakage are three important issues. They are analyzed using the developed model. The load histories of simulations are similar to those of tests and the differences of maximum load are around 10%. Bending of the entire ring and unfolding of the end section are major contributors of the fastening load. The load variations caused by the angular position of spline tooth are about 50%. Breakage is highly sensitive to the position of a snap ring.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.121-124
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• 2009

A moving mesh system is one of the critical parts in a computational fluid dynamics analysis. In this study, the RBF(Radial Basis Function) which shows better performance than hybrid meshes was developed to obtain the deformed grid. The RBF method can handle large mesh deformations caused by translations, rotations and deformations, both for 2D and 3D meshes. Another advantage of the method is that it can handle both structured and unstructured grids with ease. The method uses a volume spline technique to compute the deformation of block vertices and block edges, and deformed shape.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.43-50
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• 2019

Purpose The principle of nuclear medicine test is divided into two main categories: competition(radioimmunoassay, RIA) and noncompetitive reaction(Immunoradiometric assay, IRMA). It is known that the curve fitting method, which is commonly used in inspection field, uses Spline interpolation in RIA method and Linear interpolation method in IRMA method. Among them, the insulin test using the IRMA test showed a significant difference, especially at low concentrations, despite the same algorithm of linear interpolation between fully automated radio immunoassay analyzers. In this study, we aim to obtain results from applying two different of algorithm using fully automated radio immunoassay analyzers including Gamma pro, Gamma 10, Cobra, and SR300. Materials and Methods A total of 30 test samples were selected for the test of TSH, ferritin, C-peptide, and insulin serum levels. Test was performed by IRMA method. We compared the difference in the results of applying the linear interpolation method and the spline interpolation method to Gamma Pro, Gamma 10, Cobra, and SR300 equipment. Results Two-way ANOVA was used for statistical analysis. The significance level was applied as P <0.05. The results of TSH, ferritin, C-peptide, and insulin tests were compared between the fully automated radio immunoassay analyzers. There was a significant difference between ferritin, C-peptide, and insulin serum levels(P<0.001). TSH didn't show any significant different between the devices(P=0.29). In the difference between linear and spline interpolation, there was no significant difference between insulin test(P=0.08), TSH test(P=0.81), and Ferritin test(P=0.06). However, C-peptide test showed a significant difference(P=0.03). Especially, the insulin test showed significant difference in lower ranges. As a result of comparing and analyzing the difference between the two interpolation methods, the devices in the low concentration group showed significant difference(P<0.001). Conclusion In case of new equipment in the laboratory it is necessary to recognize that there is a difference in the curve fitting method for each automated radio immunoassay analyzers in the low concentration area when the principle of inspection is IRMA method.

• Journal of Ocean Engineering and Technology
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• v.11 no.2
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• pp.145-153
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• 1997

This paper constructs a data base to create the Hull lines prior to piece manufacture and nesting steps with a personal computer using the data of created as the advanced software, TRIBON. The lines are plotted smoohtly, which are called the spline. The S/W is excellentlt estimated on the ptrcision among shipping exclusive S/W, which are currentlyused So, the S/W is mainly used as as shipping CAD program. High-cost H/W and high-performance S/W(TRIBON etc.) sre used with the bases of technique and capital power in the big shipbuilding yard; but small but small and medium-sized shipbuilding yard and related companycan't purchase dueto the high-cost product. To bring upthe small and medium sized shipbuilding yard lacking little competitive power, the data base S/W is joined with the CADRA of graphic S/W and is developed to create the Hull lines to be needed on as automatic cutting process usiing the personal computer.

• Computers and Concrete
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• v.25 no.1
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• pp.1-14
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• 2020

This study presents applications of the multivariate adaptive regression splines (MARS) method for predicting the ultimate loading carrying capacity (N_u) of rectangular concrete-filled steel tubular (CFST) columns subjected to eccentric loading. A database containing 141 experimental data was collected from available literature to develop the MARS model with a total of seven variables that covered various geometrical and material properties including the width of rectangular steel tube (B), the depth of rectangular steel tube (H), the wall thickness of steel tube (t), the length of column (L), cylinder compressive strength of concrete (f'_c), yield strength of steel (f_y), and the load eccentricity (e). The proposed model is a combination of the MARS algorithm and the grid search cross-validation technique (abbreviated here as GS-MARS) in order to determine MARS' parameters. A new explicit formulation was derived from MARS for the mentioned input variables. The GS-MARS estimation accuracy was compared with four available mathematical methods presented in the current design codes, including AISC, ACI-318, AS, and Eurocode 4. The results in terms of criteria indices indicated that the MARS model was much better than the available formulae.

• Geomechanics and Engineering
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• v.10 no.3
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• pp.269-284
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• 2016

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.15-21
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• 1994

In the previous researches on mesh curve fairing method, a set of discrete data points in a mesh can be selected as variables. End tangent vectors can not be variables. This restriction makes some problems in preparing the end tangent vectors at the bow or stern parts, because their slopes are not infinites or zeros. In this paper end tangent vectors are included as variables and the more smooth results are obtained. Also two methods of constructing ship hull surface from mesh curves are examined. It is shown that the skinning method is better than non-uniform B-spline fitting method in representing the area near boundary. The generation of a ship surface is given as an example.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.38 no.2
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• pp.110-118
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• 2002

The element free Galerkin method has been suggested by Belyschko, etc. it is applied for linear elastic analysis of solid problems and its convergence characteristics and stability are shown according to the weight function, influence domain and scattered points. The various numerical examples are performed to check the efficiency of 1D EFG and 2D EFG program by changing factors. As a result it have the best results when it used the cubic spline weight function and the scaling parameter d$_{max}$=2. These programs were developed by mixed language programming method using Visual Basic and the C language. so it is fast and efficient. and visually shown the result.t.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5125-5135
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• 2015

Background: Total fat intake may be associated with increased risk of breast cancer, and fish oil has been suggested as a protection factor to breast cancer. But the effect of vegetable oils is inconclusive. We aimed to investigate the association with high vegetable oils consumption and breast cancer risk, and evaluated their dose-response relationship. Design: We systematically searched the MEDLINE, EMBASE, Cochrane databases, and CNKI updated to December 2014, and identified all observational studies providing quantitative estimates between breast cancer risk and different vegetable oils consumption. Fixed or random effect models were used to estimate summary odds ratios for the highest vs. lowest intake, and dose-response relationship was assessed by restricted cubic spline model and generalized least-squares trend (GLST) model. Results: Five prospective cohort studies and 11 retrospective case-control studies, involving 11,161 breast cancer events from more than 150,000 females, met the inclusion criteria. Compared with the lowest vegetable oils consumption, higher intake didn't increased the risk of breast cancer with pooled OR of 0.88 (95% CIs:0.77-1.01), and the result from dose-response analyses didn't show a significant positive or negative trend on the breast cancer risk for each 10g vegetable oil/day increment (OR=0.98, 95% CIs: 0.95-1.01). In the subgroup analyses, the oils might impact on females with different strata of BMI. Higher olive oil intake showed a protective effect against breast cancer with OR of 0.74 (95% CIs: 0.60-0.92), which was not significant among the three cohort studies. Conclusions: This meta-analyses suggested that higher intake of vegetable oils is not associated with the higher risk of breast cancer. Olive oil might be a protective factor for the cancer occurrence among case-control studies and from the whole. Recall bias and imbalance in study location and vegetable oils subtypes shouldn't be ignored. More prospective cohort studies are required to confirm the interaction of the impact of vegetable oils on different population and various cancer characteristic, and further investigate the relationship between different subtype oils and breast cancer.