• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.4
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• pp.69-79
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• 2019

This study aims to seek knitting methods that can enhance the neck design of seamless knitwear and to find out how to improve the designs by comparing and analyzing the characteristics of the knitting methods used for v-neck pullovers. The investigator analyzed the characteristics of the knitting methods and assessed the wearing sensation by using six different pieces of clothing for the experiment. The results were analyzed based on a variance analysis (ANOVA). Among the items showing significant results, the Duncan-test was used for more intensive research. As a result, while using the basic pattern of knitting methods, Experiment Clothes A ended up binding on the back neckline, and not making the hem of back. Also, the neck was the widest. In the case of the special neck, Experimental Clothes B (1:1), which had the least number of the knitting course in relation to the knitting ratio, the bottom part of the back body had the most wrinkles. According to the result of wearing sensation, the front part, the side part, and the back part showed similar results (p<0.000) in all items. Specifically, the appearance of the Experiment Clothes A (normal) in both the front and rear aspects were evaluated as the best. In the case of the special neck, the Experimental Clothes F was ranked the highest, whereas the Experimental Clothes B (1:1) was ranked the lowest. Based on the results of the study, it seems possible to provide concrete and technical data for the planning of unique and productive designs. With regard to seamless knitwear neck designs, a comparative analysis of the knitting method of v-neck pullovers will be of practical use in the development and manufacturing of the product.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.649-657
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• 2009

The paper presents the measurement split split-plot models for saving the time and cost. The split split-plot designs developed are efficiently used to estimating the gauge R&R(Reproducibility & Repeatability) when the completely randomized design of all factors(such as high pressure and temperature) is expensive and time consuming. The models studied include three split split-plots considering the type of experimental units.

• Journal of Microbiology and Biotechnology
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• v.19 no.4
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• pp.378-386
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• 2009

A sequential optimization strategy, based on statistical experimental designs, is employed to enhance the production of alkaline protease by a Bacillus pseudofirmus local isolate. To screen the bioprocess parameters significantly influencing the alkaline protease activity, a 2-level Plackett-Burman design was applied. Among 15 variables tested, the pH, peptone, and incubation time were selected based on their high positive significant effect on the protease activity. A near-optimum medium formulation was then obtained that increased the protease yield by more than 5-fold. Thereafter, the response surface methodology(RSM) was adopted to acquire the best process conditions among the selected variables, where a 3-level Box-Behnken design was utilized to create a polynomial quadratic model correlating the relationship between the three variables and the protease activity. The optimal combination of the major medium constituents for alkaline protease production, evaluated using the nonlinear optimization algorithm of EXCEL-Solver, was as follows: pH of 9.5, 2% peptone, and incubation time of 60 h. The predicted optimum alkaline protease activity was 3,213 U/ml/min, which was 6.4 times the activity with the basal medium.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.83-102
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• 1994

Some optimal designs and data analysis methods based on a Gaussian spatial linear model for computer simulation experiments are considered. For designs of computer experiments, Latin-hypercube designs and some optimal designs are combined. A two-stage computational (2-points exchange and Newton-type) algorithm for finding the optimal Latin-hypercube design is presented. The spatial prediction model which was discussed by Sacks, Welch, Mitchell and Wynn(1989) for computer experiments, is used for analysis of the simulated data. Moreover, a method of contructing sequential (optimal) Latin-hypercube designs is considered. An application of this approach to the quality improvement and optimization of the integrated circuit design via the main-effects plot and the sequential experimental strategy is presented.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.267-280
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• 2007

Various single-valued design optimality criteria such as D-, G-, and V-optimality are used often in constructing optimal experimental designs for mixture experiments in a constrained region R where lower and upper bound constraints are imposed on the ingredients proportions. Even though they are optimal in the strict sense of particular optimality criterion used, it is known that their performance is unsatisfactory with respect to the prediction capability over a constrained region. (Vining et at., 1993; Khuri et at., 1999) We assume the quadratic polynomial model as the mixture response surface model and are interested in finding efficient designs in the constrained design space for a mixture. In this paper, we make an expanded list of candidate design points by adding interior points to the extreme vertices, edge midpoints, constrained face centroids and the overall centroid. Then, we want to propose a robust design with respect to D-optimality, G-optimality, V-optimality and distance-based U-optimality. Comparing scaled prediction variance quantile plots (SPVQP) of robust designs with that of recommended designs in Khuri et al. (1999) and Vining et al. (1993) in the well-known examples of a four-component fertilizer experiment as well as McLean and Anderson's Railroad Flare Experiment, robust designs turned out to be superior to those recommended designs.

• The Research Journal of the Costume Culture
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• v.20 no.6
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• pp.912-922
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• 2012

With a long crotch length and much ease in the hip area, baggy pants are visually expressed in a variety of designs when compared with regular pants. The purpose of this study is to define the image differences of various baggy pants designs according to hip circumference and crotch length ease. To that end, this study deduced the visual image variable of experimental baggy pants and analyzed visual images according to changes in hip circumference and crotch length. Nine baggy pants with different levels of hip circumference and crotch length ease were produced as experimental pants. The image of each pair of experimental baggy pants was evaluated based on pictures taken of the pants worn by a woman in her 20s with a standard body figure. The image assessment team was composed of 105 clothing majors. The research results are as follows. Four visual image factors of experimental baggy pants were extracted: whole body compensation, lower body compensation, hip compensation, and waist compensation. Among the 4 factors, the whole body compensation factor was shown as the most representative factor. The body compensation image was higher with less hip circumference ease in the experimental baggy pants, and more hip circumference ease created the optical illusion of a larger body figure, presenting a significant difference between waist circumference and hip circumference. The lower body compensation factor, hip compensation factor, and waist compensation factor all showed a significant influence on changes in hip circumference ease. This result shows that changes in hip circumference ease exerted more influence on the body compensation image than did changes in crotch length ease. The results of this study provide basic data for predicting visual images according to differences in the level of ease in baggy pants, helping people select clothing suitable to their preferences and body shapes.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.52-59
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• 1998

This paper represents identification and control designs using neural networks for a class of nonlinear dynamic systems. A proposed neuro-controller is a combination of a linear controller and a neural network, and is trained by indirect neuro-control scheme. The proposed neuro-controller is implemented and tested on an IBM PC-based bar system, and is applicable to many dc-motor-driven precisiion servo mechanisms. The ideas, algorithm, and experimental results are described. Experimental resutls are shown to be superior to those of conventional control.

• Honam Mathematical Journal
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• v.4 no.1
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• pp.147-154
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• 1982

Estimation methods of missing points for an experimental design are described. Formulae are provided for the estimation of missing points using matrix notation. The correct analysis of variance table is given. Estimation methods of a single missing point and two missing points in $2^{n}$ factorial designs are described.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.49-54
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• 2006

When using response surface designs, the experimental trials should be carried out in blocks in case of heterogeneity of conditions. When we use nearly orthogonal blocking, we need evaluate the degree of orthogonal blocking. Graphical methods for evaluating the degree of orthogonal blocking are suggested.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.669-675
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• 2006

When using response surface designs, the experimental trials should be carried out in blocks in case of heterogeneity of conditions. When we use nearly orthogonal blocking, we need evaluate the degree of orthogonal blocking. Graphical methods for evaluating the degree of orthogonal blocking are suggested.