• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.87-93
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• 1999

This study is focus on exploring the relationship between the index of shape and the factor of perception. This study site is a Sorak National Park which sciences of road-landscape. Slides, which were used in the study, were taken in the Sorak National Park along the roads. For this purpose, the study used the questionnairy about the Road-landscape which was presented by a slide projection, also used th index of Shape. This research used analysis method of multi-regression between the preference and perceptional factors, and between the preference and index of shape. 1) The regression result of $R^2$ is 00827 between the preference and perceptional factors, therefore we can positively consider that the preference is related to the perception. The preference is affected highly by the intimacy which is the one of perceptional factors. 2) The regression result of $R^2$ is 0.692 between the preference and the index of shape. The preference has a relation with the index of shape, and it is affected highly by the index of sky. 3) Therefore, this study identifies the relationship between the preference and the perceptional factors, and the index of shape makes this relationship possible.

• International Journal of Human Ecology
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• v.7 no.1
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• pp.37-52
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• 2006

This study was designed to analyze the three-dimensional shapes of Hanbok Chima made with various fabrics and to clarify the relationship between fabric properties as well as the objective and subjective evaluations of the 3D shape. For 3D shape data, a dress form (9A2 (N; nude)) was scanned with eight Chima garments made with the same number of fabrics. The scanner used was a non-contact three-dimensional human body measuring system belonging to Bunka Women's University in Japan. Data concerning the objective evaluation of the 3D shape was obtained from the measurements of the vertical and horizontal sections: those for subjective evaluation were through the sensory test after exposure to photographs from a front and side view. Four fabric factors were extracted from fabric physical properties: softness, extension, thickness of threads, and weight of fabric. Such factors as expansion (volume), sag of rear train, shape of nodes were influential in explaining the 3D shape of Hanbok Chima. From the analysis of the 3D shape, it can be deduced that with the constituent fabric stiffer, lighter, and less stretchable, the more expanded the 3D shape appeared to be. Multiple regression results showed that vertical shape factors have a greater effect on the evaluation of the 3D shape. It also implies that dependent variables of this study such as the subjective evaluation and 3D shape can be derived from regression equations on independent variables as fabric property factors or 3D shape factors. These results can enable the manufacturers to predict the 3D shape of the garment as well as the human subjective assessment to improve the efficacy of production. The investigation method proposed in this study can also be applicable to other garment items.

• Current Optics and Photonics
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• v.4 no.5
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• pp.411-420
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• 2020

Non-contact three-dimensional (3D) measuring technology is used to identify defects in miniature products, such as optics, polymers, and semiconductors. Hence, this technology has garnered significant attention in computer vision research. In this paper, we focus on shape from focus (SFF), which is an optical passive method for 3D shape recovery. In existing SFF techniques using interpolation, all datasets of the focus volume are approximated using one model. However, these methods cannot demonstrate how a predefined model fits all image points of an object. Moreover, it is not reasonable to explain various shapes of datasets using one model. Furthermore, if noise is present in the dataset, an error will be generated. Therefore, we propose an algorithm based on polynomial regression analysis to address these disadvantages. Our experimental results indicate that the proposed method is more accurate than existing methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1016-1021
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• 2013

While using the hydrogen mixture gas torch, the glass edge sealing and the shape of the edge sealing parts is affected by many parameters such as flow rate of gas, traveling speed of torch, distance between glass and torch. As the glass edge sealing shape have effects on the insulation and airtightness and strength of the glass panel; the sealing shapes are predicted according to the process parameters. The paper highlight the nonlinear regression equations of the cross-sectional shape of the sealing shape according to the parameters, that is experimentally predicted later compared and verified the equation with the experimental result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.306-310
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.306-311
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• Fashion & Textile Research Journal
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• v.17 no.2
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• pp.265-277
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• 2015

The aim of this study was to successfully reflect human body changes on the transformation of the virtual body within 3D virtual fitting spaces. For this purpose, existing problems of shape transformation of the virtual body were analyzed and regression equations which provides useful basic data for transformation of the virtual body that can be applied usefully to the 3D virtual fitting system was developed. Necessary data for the analyses were body measurement and 3D scan data of women with average physical form between the ages of 40 through 49. The reason that we used human body changes of the female subjects in their forties was based on the recognition that fundamental female body changes start to occur from age of forty. Body shapes were largely divided into 3 groups according to obesity which was found to be the biggest factor of shape change. Seven factors were extracted based on factor analysis of 47 body measurement categories and regression equations were created to extract specific measurements for each BMI group based on these seven factors. The major contribution of this paper can be summarized as follows. First, the regression equations to extract specific measurements based on the 7 representative variables remediated existing problem of virtual bodies as it increased the number of body shape transformation areas. Second, the regression equations helped to overcome the problem of current failing to reflecting changes in body cross-section shape based on simple girth measurements based on analysis of cross-section distances.

• Transactions of Materials Processing
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• v.21 no.8
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• pp.479-484
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• 2012

The objective of this study is to compensate the elastic recovery in the flexible forming process using the predictive models. The target shape was limited to two-dimensional shape having only one curvature radius in the longitudinal-direction. In order to predict the shape error the regression and neural network models were established based on the finite element (FE) simulations. A series of simulations were conducted considering input variables such as the elastic pad thickness, the thickness of plate, and the objective curvature radius. Then, at sampling points in the longitudinal-direction, the shape errors between formed and objective shapes could be calculated from the FE simulations as an output variable. These shape errors were expressed to a representative error value by the root mean square error (RMSE). To obtain the correct objective shape the die shape was adjusted by the closed-loop using the neural network model since the neural network model shows a higher capability of estimating the shape error than the regression model. Finally the experimental result shows that the formed shape almost agreed with the objective shape.

• Korean Journal of Mathematics
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• v.22 no.2
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• pp.289-305
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• 2014

In this paper we propose a new approach to the variable selection problem for a primary resolution and wavelet basis functions in wavelet regression. Most wavelet shrinkage methods focus on thresholding the wavelet coefficients, given a primary resolution which is usually determined by the sample size. However, both a primary resolution and the basis functions are affected by the shape of an unknown function rather than the sample size. Unlike existing methods, our method does not depend on the sample size and also takes into account the shape of the unknown function.

• Journal of the Korean Home Economics Association
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• v.42 no.8
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• pp.133-145
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• 2004

The purpose of this study was to identify the effect of children's perception of body shape and body image on their negative emotions. The subjects were 345 3rd and 6th graders. Questionnaires were used to investigate the children's perception of their body shape and body image, and negative emotions. Data analyzed by SPSS-WIN program included mean, standard deviation, ANOVA, Scheffe's test and regression. Results were as follows. (1) The 6th graders perceived their body image more negatively than the 3rd graders did. (2) The children who perceived themselves more obesely had more negative body image and more negative emotions than those who did not. (3) There were interaction effects among the children's grade, sex and body shape perception on their body image perception. (4) The regression analysis demonstrated that children's perception of appearance was more influential on the negative emotions than their body shape perception.