• Journal of the Korean Chemical Society
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• v.56 no.2
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• pp.257-263
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• 2012

The selection of suitable delignification conditions and optimization of process variables is crucial to the successful operation of chemical pulping processes. Soda pulping of Carpolobia lutea was investigated, as an alternative raw material for pulp and paper production. The process was optimized under the influence of three operational variables, namely, temperature, time and concentration of cooking liquor. Equations derived using a second - order polynomial design predicted the pulp yield and lignin dissolution with errors less than 8% and 11% respectively. The maximum variations in the pulp yield using a second order factorial design was caused by changes in both time and alkali concentration. Optimum pulp yield of 43.87% was obtained at low values of the process variables. The selectivity of lignin dissolution was independent of the working conditions, allowing quantitative estimations to be established between the pulp yield and residual lignin content within the range studied.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.847-850
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• 2002

Stochastic process analysis is often based on Monte Carlo simulations. As a more rigorous alternative, a deterministic algorithm based on numerical integration is proposed in this paper. which calculates the probability distributions of dependent random variables using the results of simulation with grid points of independent random variables. For performance evaluation, the proposed algorithm is applied to an example problem which can be analytically solved. and the result is compared with that of Monte Carlo simulation. The proposed algorithm is suitable for general process simulation problems with a few independent random variables, and expected to be applicable to areas such as safety analysis and quality control.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.201-208
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• 2013

In this paper, we consider the mixture components-process variables model and propose a model selection strategy using MTS. This strategy is illustrated using an example that involves three mixture components and two process variables in a bread making experiment that was studied in several literatures.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.03b
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• pp.23-30
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• 1996

The purpose of this study was to investigate changes in thewall thickness of tube sinking and working forces by the upper bound method and ABAQUS code. The independent variables were : Workpiece material, original wall thickness of tube, die angle, friction, and diameter reduction. The results indicated that of these five variables were a factor in wall-thickness increase and working forces. Three variables, a inner tube wall angle and two angles of the velocity discontinuous surfaces, are optimized in this proposed velocity field by the upper bound method. In this method, we can estimate the working forces and final tube thicknesses whcih are similar to acturla forming process. Optimized process variables which are obtained by upper bound method are used in ABAQUS pre-model . In ABAQUS analysis, the stress and the strain contours which are considered to be heat generation occured by the friction during forming process are observed.

• Journal of Welding and Joining
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• v.15 no.6
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• pp.116-123
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• 1997

In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.334-344
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• 2003

A mixture experiment is a special type of response surface experiment in which factors are the ingredients or components of a mixture, and the response is a function of the proportions of each ingredient. Evolutionary operation is useful to improve on-line full-scale manufacturing process by systematically changing the levels of the process variables without jeopardizing the product. This paper presents an evolutionary operation procedure with mixture variables for large-scale mixture production process which can be beneficial to practitioners who should improve on-line mixture quality while maintaining the production amount of the mixture product.

• Journal of Korean Elementary Science Education
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• v.20 no.1
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• pp.1-7
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• 2001

The purpose of this study is to examine the learner's variables affecting on scientific thinking and scientific process skills. To study this purpose, through the procedure study, the learner's variables were divided into cognitive variable, ego variable, and affective variable, then the questionaire survey through the reconstruction of standardization instrument was made over 120 elementary school fifth grade student in Seoul, Anyang, and Pajoo. The results of this study were as follows: 1) The learner's variables affecting on scientific thinking were cognitive variable and for female students, also affect affective variable. The subordinated catagories of statistically significant degree of explanation were achievement motivation, cognitive level, and cognitive style and another statistically significant correlation were meta-cognition, self regulated learning, self efficacy, and muliple intelligence. 2) The learner's variables affecting on science process skills were cognitive variable and affective variable. And the subordinated catagories of statistically significant degree of explanation were achievement motivation, and cognitive level. And another statistically significant correlation were meta-cognition, self regulated loaming, self efficacy, multiple intelligence, and attribution.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.155-164
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• 2000

This paper considers the problem of determining the optimum proccss mean value of the quality characteristic of interest, and the screening limit for two correlated variables under single-stage screening. In the single-stage screening, inspection is performed on two correlated variables which are correlated with the quality characteristic of interest. Model is constructed which involves selling price, production, inspection, and penalty costs. Method for finding the optimum process mean and screening limit are presented when the quality characteristic of interest and the correlated variables are assumed to be jointly normally distributed. A numerical example is presented and numerical analysis is performed to compare the proposed screening based on two screening variables with screening based on one screening variable.

• Journal of Families and Better Life
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• v.20 no.1
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• pp.115-124
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• 2002

The purpose of this study is to examine the social competence of children with reference to day care center's structural, process variables and demographic variables. The subjects were 156 children who attend day care center, aged from 3 to 5 years and 9 teachers in Seoul or the province of KyungkiDo. Data were gathered via the structured Questionnaires distributed to the teachers to rate children's social competence and their own job satisfaction. And two observers rated teacher-child interaction in day care center The major findings are as follows The variables predicting children's social competence were child's sex, age, period of attendance in day care center, teacher's job satisfaction, and group size. Especially this study suggests that teachers who are highly satisfied with their job and small group size influence children's social competence positively.

• Honam Mathematical Journal
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• v.32 no.1
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• pp.91-99
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• 2010

In this paper we introduce the concept of asymptotically almost negatively associated random variables in a Hilbert space and obtain the strong law of large numbers for a strictly stationary asymptotically almost negatively associated sequence of H-valued random variables with zero means and finite second moments. As an application we prove a strong law of large numbers for a linear process generated by asymptotically almost negatively random variables in a Hilbert space with this result.