• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.829-846
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• 2017

Purpose: This paper compares the effectiveness of typical selective assembly criteria and suggests the most promising one. Based on the result of a computer simulation, the key issues of selective assembly are examined and the best criterion is recommended from the effectiveness perspective. Methods: Using JAVA program, production of ten thousand units for each pair of components are simulated for selective assembly of the two types. And the number of mismatching and the fraction nonconforming for each criterion are determined. Results: The best match criterion appeared to be most promising from the perspectives of both mismatching and nonconforming problems. Its effectiveness appears to be also good even when the precision of one component is different from that of the other. Conclusion: For designing an optimal method for selective assembly, the best match criterion is recommendable as the base criterion.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

• Education of Primary School Mathematics
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• v.8 no.2 s.16
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• pp.97-113
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• 2004

The purpose of this study is to develop instructional methods for the formalized algorithm through informal knowledge in teaching division of fractions. The following results have been drawn from this study: First, before students learn formal knowledge about division of fractions, they knowledge or strategies to solve problems such as direct modeling strategies, languages to reason mathematically, and using operational expressions. Second, students could solve problems using informal knowledge which is based on partitioning. But they could not solve problems as the numbers involved in problems became complex. In the beginning, they could not reinvent invert-and-multiply rule only by concrete models. However, with the researcher's guidance, they can understand the meaning of a reciprocal number by using concrete models. Moreover, they had an ability to apply the pattern of solving problems when dividend is 1 into division problems of fractions when dividend is fraction. Third, instructional activities were developed by using the results of the teaching experiment performed in the second research step. They consist of student's worksheets and teachers' guides. In conclusion, formalizing students' informal knowledge can make students understand formal knowledge meaningfully and it has a potential that promote mathematical thinking. The teaching-learning activities developed in this study can be an example to help teachers formalize students' informal knowledge.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Proceedings of the Korean Society for Environmental Edudation Conference
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• 2004.08a
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• pp.48-55
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• 2004

In Korea almost all subjects in school teach environmental education. In such situation it is difficult that the environmental subject as a regular stand-alone subject for environmental education establishes its own individuality. In many cases it and the other subjects teach identical contents with the nearly same methods. Such redundancy could make students lose their interest in the topics that were already taught by other subject. And the environmental subject and the other subjects might compete with one another rather than cooperate. To avoid such negative effects we need to partition their roles. For example, the other subjects focus on teaching their own knowledge and skills related to environmental problems. And the environmental subject focuses on encouraging students to possess environmental attitude and to participate in environmental activities. Above all, the environmental subject needs to teach the social nature of environmental problems and the social process through which we make a decision on the problems. It should let students experience highly integrated process of environmental decision. In order to establish the individuality of the environmental subject I discussed its goals and contents. I hope that the related persons in all the subjects start to deeply discuss the partitioning of roles, with open mind, in order to effectively achieve the goal of environmental education in school.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.194-202
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• 2000

In this paper, an efficient fuzzy rule generation scheme for Adaptive Network-based Fuzzy Inference System(ANFIS) using the conditional fuzzy-means(CFCM) and fuzzy equalization(FE) methods is proposed. Usually, the number of fuzzy rules exponentially increases by applying the gird partitioning of the input space, in conventional ANFIS approaches. Therefore, CFCM method is adopted to render the clusters which represent the given input and output fuzzy and FE method is used to automatically construct the fuzzy membership functions. From this, one can systematically obtain a small size of fuzzy rules which shows satisfying performance for the given problems. Finally, we applied the proposed method to the truck backer-upper control and Box-Jenkins modeling problems and obtained a better performance than previous works.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.377-382
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• 2006

Advantageous features of flash memory are stimulating its exploitation in mobile and ubiquitous related devices. The hardware characteristics of flash memory however place restrictions upon this current trend. In this paper, a cleaning policy for flash memory is proposed in order to decrease the necessary penally for recycling of memory minimizing the degradation of performance at the same time. The proposed cleaning algorithm is based on partitioning of candidate memory regions, to be reclaimed as free, into a number of groups. In addition, in order to improve the balanced utilization of the entire flash memory space in terms of 'wearing-out', a free segment selection algorithm is discussed. The impact of the proposed algorithms is evaluated through a number of experiments. Moreover, the composition of the optimal configuration featuring the proposed methods is tested through experiments.

• Environmental Analysis Health and Toxicology
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• v.26
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• pp.4.1-4.6
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• 2011

Objectives: This study was carried out to determine whether or not pine needles can be used as passive samplers of atmospheric polycyclic aromatic hydrocarbons (PAHs) using the correlation between accumulated PAH concentrations in air (Ca, ng/$m^3$) and those deposited on pine needles (Cp, ng/g dry). Methods: PAHs in ambient air was collected using low volume PUF sampler and pine needles was gathered at same place for 7 months. Results: A good correlation ($R^2$=0.8582, p<0.05) was found between Ca and Cp for PAHs with a higher gaseous state in air (AcPy, Acp, Flu, Phen, Ant, Flt, Pyr, BaA and Chry), but there was a poorer correlation ($R^2$=0.1491, p=0.5123) for the PAHs with a lower gaseous state (BbF, BkF, BaP, DahA, BghiP and Ind123). A positive correlation ($R^2$=0.8542) was revealed between the logarithm of the octanol-air partitioning coefficient ($logK_{oa}$) and Cp/Ca for the PAHs with a higher gaseous state in air, but there was a negative correlation ($R^2$=0.8131) for the PAHs with a lower gaseous state. The Ca-Cp model could not be used to estimate PAHs concentrations in air using deposited PAHs concentrations on pine needles, but the logKoa-Cp/Ca model could be used. Conclusions: It was found that pine needles can be used as passive samplers of atmospheric PAHs.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2453-2460
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• 1997

Among the method of developing software there are many object-oriented analysis(OOA) techniques, and the new ones are being introduced continuously. The present OOA techniques, however, have difficulty in the identification and the verification of the objects and tend to ignore high-level control aspects of the problem due to the initial partitioning of them on the basis of the data. As a result, it brings inaccurate understanding and faults in the software which is required by users. Therefore the purpose of this paper is to design the TOVERC to verify completeness and consistency through cross-reference between the state transition diagram and the methods of object model in order to reflect the requirements of users in the analysis of software considering this problem.

• Genomics & Informatics
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• v.19 no.3
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• pp.34.1-34.6
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• 2021

Digital PCR (dPCR) is the third-generation PCR that enables real-time absolute quantification without reference materials. Recently, global diagnosis companies have developed new dPCR equipment. In line with the development, the Lab On An Array (LOAA) dPCR analyzer (Optolane) was launched last year. The LOAA dPCR is a semiconductor chip-based separation PCR type equipment. The LOAA dPCR includes Micro Electro Mechanical System that can be injected by partitioning the target gene into 56 to 20,000 wells. The amount of target gene per wells is digitized to 0 or 1 as the number of well gradually increases to 20,000 wells because its principle follows Poisson distribution, which allows the LOAA dPCR to perform precise absolute quantification. LOAA determined region of interest first prior to dPCR operation. To exclude invalid wells for the quantification, the LOAA dPCR has applied various filtering methods using brightness, slope, baseline, and noise filters. As the coronavirus disease 2019 has now spread around the world, needs for diagnostic equipment of point of care testing (POCT) are increasing. The LOAA dPCR is expected to be suitable for POCT diagnosis due to its compact size and high accuracy. Here, we describe the quantitative principle of the LOAA dPCR and suggest that it can be applied to various fields.