• Journal of Information Display
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• v.5 no.3
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• pp.35-40
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• 2004

In this study, we collected data used to formulate the relationship between quantitative metrological parameters in CRT display and the perceived focus quality. Human perception of the focusing quality was evaluated in terms of user feedback scores regarding the character legibility from four highly trained inspectors. Thirteen CRT monitors from five different manufacturers were compared relatively with respect to the norm monitor. The profile of electron beam such as spot size and the shape of distribution made by electron beam, contrast, convergence of RGB beams, and luminance characteristics were measured using a precision measurement system. Linear regression analysis and artificial neural network models were used to formulate the relationship between human perception and the quantitative measurements. The accuracy of the formulated linear regression model ($R^2$=0.515) was not satisfactory but the nonlinear neural network model ($R^2$=0.716) was fairly convincing and robust even the utilized data included subjective differences.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.16-17
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• 2019

In order to measure the amount of carbon dioxide emitted from the construction sites, many literature which have been conducted have proposed methodologies for calculating coefficients based on actual data collections for estimating the emission formula. The existing data collected under controlled conditions not on site measurement were too limited to apply in actual sites. The purpose of this study is to conduct analysis based on the data measured in fields and to present predictive models using artificial neural network and nonlinear regression analysis for appropriate predictions and practical applications.

• Steel and Composite Structures
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• v.48 no.6
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• pp.625-639
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• 2023

In this paper, a Taguchi-based finite element method (FEM) has been proposed and implemented to assess optimal design parameters for minimum static deflection in laminated composite plate. An orthodox mathematical model (based on higher-order shear deformation plate theory and Green-Lagrange geometrical nonlinearity) has been used to compute the nonlinear central deflection values of laminated composite plates according to Taguchi design of experiment via a self-developed MATLAB computer code. The lay-up scheme, aspect ratio, thickness ratio and the support conditions of the laminated composite plate structure were designated as the governable design parameters. Analysis of variance (ANOVA) is used to investigate the effect of diverse control factors on the nonlinear static responses. Moreover, regression model is developed for predicting the desired responses. The ANOVA revealed that the lay-up scheme alongside the support condition plays vital role in minimizing the central deflection values of laminated composite plate under uniformly distributed load. The conformity test results of Taguchi analysis are also in good agreement with the numerical experimentation results.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.83-97
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• 2013

This study was carried out to suggest an experimental base in selecting the drought resistance of plants. Adopting the natural drought method, this paper studies the drought resistance of 12 kinds of ground cover plants. focusing on analyzing the changes of relative water content on leaf, relative electric conductivity and chlorophyll content in 12 kinds of plants, and and the relation between soil water content under drought stress. The drought resistance of the plants were subject to laboratory and rooftop drought resistance treatments. The Logistic model of nonlinear regression analysis was used to evaluate the lethal time that were predicted with the range of 10.4~30.1d on roof top, and 19.5~39.0d on hothouse. The result shows that with the increase of stress time, relative water content and chlorophyll content on leaf were in a downward trend; the relative electric conductivity was upward tendency. Among 12 species of ground cover plants, exclude Pulsatilla koreana, Ainsliaea acerifolia were selected for rooftop plants because they showed resist drought strongly and took adaptive ability.

• Computers and Concrete
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• v.26 no.6
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• pp.587-593
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• 2020

In this study, bond behavior of ordinary concrete and rebars with different diameters and development length was investigated by using Hinged Beam Test (HBT) and Eccentric Pull-Out Test (EPT) comparatively. For this purpose, three different rebar size and development length depending on rebar diameter were chosen as variables. Three specimens were produced for each series of specimens and totally 54 specimens were tested. At the end of the tests it was observed that obtained results for both tests were quite similar. On the other hand, increased bar size, especially for the specimen with 14 mm bar size and 14 development length (lb), caused shear failure of test specimens. This situation infers that when bigger bar size and lb are used in such test, dimensions of test specimens should be chosen bigger and stirrups should be used for producing of test specimens to obtain more adequate result by preventing shear failure. Also, a nonlinear regression analysis was employed between HBT and EPT results. There was a high correlation between the EPT values, lb, rebar diameters and estimated theoretical HBT. In addition, at the end of the study an equation was suggested to estimate bond strength for HBT by using EPT results.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.39-46
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• 2001

This research conducted to investigate the variation of the moisture content, crack ratio, and hardness of the whole and cracked brown rice after conditioning at the initial moisture content of 13, 14, and 15% with time lapse. The conditioning was conducted by increasing the moisture content of the sample to 0.4 and 0.8%. For basic information and conditioning characteristics for the development of a conditioning machine for the brown rice, predicted models of above three properties were developed using a nonlinear regression analysis of SAS with Gauss-Newton, Gradient, and DUD methods. Results of this research could be summarized as follows. 1. No moisture variation occurred after 0.5 hour conditioning. 2. The increasement of the crack ratio was 7.6 and 17.5% with the sample increased the moisture content of 0.4 and 0.8%, respectively, after 8 hours conditioning. 3. The hardness of the conditioned whole grain of the brown rice decreased 0.82 and 1,000kg$\_$f/ with the sample increased moisture content 0.4 and 0.8%, respectively, after 8 hours conditioning with respect to the non-conditioned sample. 4. The hardness of the conditioned cracked grain of the brown rice decreased 0.54 and 0.81kg$\_$f/ with the sample increased moisture content 0.4 and 0.8%, respectively, after 8 hours conditioning with respect to the non-conditioned sample. The hardness of the broken grain was about 0.81∼1.88kg$\_$f/ lower than whole grain. 5. The moisture content variation, increasing rate of the crack ratio, and hardness of the cracked and whole grain was predicted as a negative exponential function. 6. Each predicted model with the nonlinear regression analysis, which was very accurate and had a very small amount of sum of square of error between experimental value and predicted value, which could be used for predicting the physical variation after conditioning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.83-91
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• 1994

An efficient method was developed to determine the ultimate strength for the segment subjected to cross-sectional distortion. Cumulative data based on the finite element analysis were used to perform the multi-regression analysis. A moment-thrust-curvature relationship of short segment was obtained with mathematical forms in the nonlinear range. The extensive parametric study was performed to generate the ultimate strength for the various segments. The result was compared with the experimental result which was not included in the database. The proposed method gives an essential tool for the nonlinear analysis of beam-column.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.193-217
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• 2001

Despite of the rich literature in discriminant analysis, this complicated subject remains much to be explored. In this article, we study the theoretical foundation that supports Fisher's linear discriminant analysis (LDA) by setting up the classification problem under the dimension reduction framework as in Li(1991) for introducing sliced inverse regression(SIR). Through the connection between SIR and LDA, our theory helps identify sources of strength and weakness in using CRIMCOORDS(Gnanadesikan 1977) as a graphical tool for displaying group separation patterns. This connection also leads to several ways of generalizing LDA for better exploration and exploitation of nonlinear data patterns.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.581-586
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• 2001

An increasingly important facet of software development is the ability to estimated the associated coast and effort of development early in the development life cycle. In spite of the most generally sued procedures for estimation of the software development effort and cost were linear regression analysis. As a result of the software complexity and various development environments, the software effort and cost estimates that are grossly inaccurate. The application of nonlinear methods hold the greatest promise for achieving this objects. Therefore this paper presents an RBF (radial basis function) network model that is able to represent the nonlinear relation for software development effort, The research describes appropriate RBF network modeling in the context of a case study for 24 software development projects. Also, this paper compared the RBF network model with a regression analysis model. The RBF network model is the most accuracy of all.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.