• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1213-1214
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• 2012

Global variables can be read or modified by any part of the program, making it difficult to remember or reason about every possible use. Sometime it has tight couplings between some of other variables, and couplings between variables and functions. The main focus of this paper is to use call graph and the control flow analysis to design a model from where we generate the test cases for testing global variables.

• Journal of Families and Better Life
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• v.8 no.1
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• pp.31-47
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• 1990

The purpose of this study were to investigate: 1) The level of information-processing competencies of children consumers. 2) The differences of information-processing competencises of children consumers according to the cognitive development stage, the variables related to social learning and the socio-ecomonic variables. 3) The independent influences of variables related to information-processing competencies of children consumers. 4) The independent influences of variables related to information-processing competencies of children consumers according to the cognitive development stage. For these purposes, a survey was conducted using questionaires. The questionaires consisted of mother's and child's were distributed to children of second and 6th grade and their mothers of 5 elementary schools in Seoul 634 cases were selected for data analysis. Then, these data were analyzed with statistical methods such as Frequency Distribution, Percentile, Mean, One-way Anova, Scheff -Test, T-Test, Pearson's Correlation and Multiple Regression Analysis. From these finding, the follawing suggestions are made. First, to improve information processing competencies of children consumers, children consumers should be offered the consumer information that is suitable to child's cognitive development stage. Second, the consumer education and learning practical discriminatory competencies on TV ads. should be conducted for children consumers and his mothers. Third, children consumers should have the opportunities to practice as a consumer. The last, children consumers in low-income should be offered the specially educational program.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.345-359
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• 2024

A regression model represents the relationship between explanatory and response variables. In real life, explanatory variables often affect a response variable with a certain time lag, rather than immediately. For example, the marriage rate affects the birth rate with a time lag of 1 to 2 years. Although deep learning models have been successfully used to model various relationships, most of them do not consider the time lags between explanatory and response variables. Therefore, in this paper, we propose an extension of deep learning models, which automatically finds the time lags between explanatory and response variables. The proposed method finds out which of the past values of the explanatory variables minimize the error of the model, and uses the found values to determine the time lag between each explanatory variable and response variables. After determining the time lags between explanatory and response variables, the proposed method trains the deep learning model again by reflecting these time lags. Through various experiments applying the proposed method to a few deep learning models, we confirm that the proposed method can find a more accurate model whose error is reduced by more than 60% compared to the original model.

• Proceedings of the Korean Society of Laser Processing Conference
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• 2002.11a
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• pp.51-54
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• 2002

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.671-676
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• 2000

This study was to determine the technical feasibility of using wastepaper fibers, obtained through dry processing of wastepaper, as reinforcement in thin cement produces. Dry-processed waste papers have high levels of noncellulosic impurities, and the recycling process also breads and damages the fibers. To produce wastepaper fiber-cement composites, first the influential variables in the slurry-dewatering method of processing the composites were identified in an experimental study based on factorial design. Among the proportioning and processing variables investigated, fiber mass fraction and level of substitution of virgin fibers with recycled ones were found to have statistically significant effects on mechanical and physical properties of composites. Subsequently, response surface analysis techniques were used to devise an experimental program that helped determine the optimum combinations of the selected influential variables based on mechanical and physical properties, and cost.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.826-827
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• 2006

Copper infiltration is demonstrated as a viable solution to achieve higher mechanical properties by filling the interconnected porosities of a ferrous structure with copper infiltrant. This paper will present the results of a design of experiments study based on the selected processing variables in the copper infiltration process. The variables are the following: Infiltrating temperatures, infiltrating time at pre-heat zone and hot zone, the green density of iron part, the migration of copper into the iron part at different processing conditions. The results show the flexibility of the infiltration process to attain certain mechanical properties by changing the processing conditions.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.224-233
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• 1999

The quality of injection molded parts is affected by the variables such as materials, design variables of part and mold, molding machine, and processing conditions. It is difficult to consider all the variables at the same time to predict the quality. In this paper neural network was applied to analyze the relationship between processing conditions and volumetric shrinkage of part. Engineering plastic gear was used for the study, and the learning data was extracted by the simulation software like Moldflow. Results of neural network was good agreement with simulation results. Nonlinear regression model was formulated using the test data of 3,125 obtained from neural network, Optimal processing conditions were calculated to minimize the volumetric shrinkage of molded part by the application of RQP(Recursive Quadratic Programming) algorithm.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• Transactions of Materials Processing
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• v.21 no.2
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• pp.107-112
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• 2012

Gas-assisted injection molding(GAIM) produces parts with hollow internal sections. The technique offers benefits to powder injection molding(PIM), with lower material usage and reduced time for de-binding processes. In this study, the effects of processing parameters on gas penetration length of gas-assisted powder injection molding(GAPIM) were investigated for SUS316L stainless steel powder feedstock. Experiments were planned based on the Taguchi method, involving processing variables such as melt temperature, shot size, gas pressure, and gas delay time. The most significant parameters affecting gas penetration length were gas delay time and shot size, while the effects of melt temperature and gas pressure was relatively insignificant.

• Transactions of Materials Processing
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• v.18 no.3
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• pp.256-261
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• 2009

Polyurethane has been one of the most important materials for automobile elastic parts such as bumper, head rest, instrument panel and so on since it covers very wide range of mechanical characteristics with low production costs. The processing variables such as formulation of ingredients and mold temperature, mixing speed, etc. can affect the quality of produced polyurethane foams so that process conditions should be determined appropriately. In this study, foaming behaviors of semi-rigid polyurethane were investigated by conducting cup foam tests with two major processing variables such as environmental temperature and blowing agent content. In addition, it was verified that processing conditions of real practice can be determined effectively by considering foaming characteristics obtained by the cup foam tests.