• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.433-441
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• 2007

Creativity has very important significance to children. Although active researches and educations on other studies (for instance, mathematics, science, logics, music, etc) are being done, evaluation or development on children's creativity in design is very inadequate. Therefore, this study is a basic research to develop evaluation to judge design creativity of children as an incipient stage of educational method development to develop children's creativity in design. Evaluation categories (originality - novelty/fun, practicality-function/possibility) that can evaluate design creativity of children were drawn out based on documentary records, and as the results or performing experimental research to figure out correlativity between creativity of idea and design creativity targeting children in second grade of elementary school, subordinate provinces of idea's creativity related to design creativity were fluency and elaboration. However, it does not mean that fluency and delicacy are the only subordinate provinces of idea's creativity related to design creativity, but they are more influential compared to other provinces (creativity, abstractness of title, and resistance to premature closure) This study is to prepare basic framework of educational method to improve design creativity education of children, and has its meaning to complement what are lacked in design creativity through the educational method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.489-495
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• 2014

A micro-genetic algorithm (MGA) is one of the improved forms of a genetic algorithm. It is used to reduce the number of iterations and the computing resources required by using small populations. The efficiency of MGAs has been proved through many problems, especially problems with 3-5 design variables. This study proposes an optimization algorithm based on the sequential design of experiments (SDOE) and an MGA. In a previous study, the authors used the SDOE technique to reduce trial-and-error in the conventional approximate optimization method by using the statistical design of experiments (DOE) and response surface method (RSM) systematically. The proposed algorithm has been applied to various mathematical examples and a structural problem.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1397-1405
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• 2013

The optimal rib pattern design of B-pillar trim considering occupant head protection can be determined by two methods. One is the conventional approximate optimization method that uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained through the iterative process by trial-and-error. The quality of results strongly depends on the factors and levels assigned by a designer. The other is a methodology derived from previous work by the authors, called the sequential design of experiments (SDOE), to reduce the trial-and-error procedure and to find an appropriate condition for using artificial neural network (ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.2
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• pp.229-260
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• 2014

The purpose of this study was to investigate the appropriateness of the open competitive examination subjects to selecting the personnel with work profession targeted the public official librarian engaging the libraries directly operated by education office and city hall of Seoul. Also, this study suggested the ways for selecting excellent personnel within work profession. First, the public official librarian recognized that there was no practicality regarding the subjects of the open recruitment that recruit for the personnel with work profession. Second, 78.5% of the public official librarian responded the new subjects including science of public administration, social studies, science, and mathematics needed to be revised to a written examination. Third, the public official librarian thought the subjects such as library management theory, organization of information, and collection management was more appropriate for the improvement of the profession.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.11-22
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• 2012

This paper proposes for practical engineers a lightweight modeling and simulation environment for continuous system models specified in ordinary differential equations, which are time-domain specification of such systems. We propose a block-oriented specification formalism that has two levels: one for atomic behavior and the other the structure of models. Also we provide with a simulation framework, called BlockSim++, which make models specified in the block-oriented formalism be easily translated in object-oriented program that runs with the proposed simulation framework. The proposed formalism and framework has advantage of reuse such that it can be easily integrated into application programs and heterogeneous simulators. We illustrates the usefulness of the proposed framework by a simple hybrid modeling simulation example.

• Journal of Gifted/Talented Education
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• v.25 no.1
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• pp.119-138
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• 2015

This study analyzed the academic achievements on above-level testing of mathematics, physics, chemistry, and English in newly entering students of science specialized high schools. It can be expected that newly students of science high specialized schools have reached ceiling level in the middle school mathematics and science academic scores. Above-level testing(or off-level testing) is a test tool used to evaluate student's ability which are above-grade level. In this study, above-level testing tools were used to develop the same type examination paper of the 2013 Korean College Scholastic Ability Test(CSAT) in mathematics, physics, chemistry, and English. The conclusions of this study were as follow: First, the academic achievement level of science specialized high school freshmen were higher the average level of general high school senior because that over 50% of them are within the 5 grade of CSAT in mathematics, physics, and chemistry. In English, 19.3% science specialized high school freshmen have reached within the 5 grade of CSAT. Second, as a result of examining characteristics of academic achievement with respect to units of subjects, in mathematics, it was showed that the academic achievement of 'continuity and limit of a function' unit was higher, 'statistics' unit was lower. In physics, the academic achievement of 'Electricity and Magnetism' unit was higher, 'Waves and particles' unit was lower. In chemistry, the academic achievement of 'compounds in life' unit was higher, 'Air' unit was lower. In English, the academic achievement of 'practical sentence' of reading area was higher, 'Sentence' of writing area was lower. In conclusion, above-level testing provided a good strategy for identifying and determining appropriate programming interventions for gifted students who are two or more grade levels above their age-mates in achievements, aptitude, or ability.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.845-852
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• 2018

Mayer-Schönberger and Cukier(2013) explain why big data is important for our life, while showing many cases in which analysis of big data has great significance for our life and raising intriguing issues on the analysis of big data. The two authors claim that correlation is in many ways practically far more efficient and versatile in the analysis of big data than causality. Moreover, they claim that causality could be abandoned since analysis and prediction founded on correlation must prevail. I critically examine the two authors' accounts of causality and correlation. First, I criticize that corelation is sufficient for our analysis of data and our prediction founded on the analysis. I point out their misunderstanding of the distinction between correlation and causality. I show that spurious correlation misleads our decision while analyzing Simpson paradox. Second, I criticize not only that causality is more inefficient in the analysis of big data than correlation, but also that there is no mathematical theory for causality. I introduce the mathematical theories of causality founded on structural equation theory, and show that causality has great significance for the analysis of big data.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.735-761
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• 2004

As a possible alternative to Traditional Discounted Cash Flow Method, "Option Pricing Model" has drawn academic attentions for the last a few decades. However, it has failed to replace traditional DCF method practically due to its mathematical complexity. This paper introduces an option pricing valuation model specifically adjusted for the natural resource development projects. We add market information and industry-specific features into the model so that the model remains objective as well as realistic after the adjustment. The following two features of natural resource development projects take central parts in model construction; product price is a unique source of cash flow's uncertainty, and the projects have cost structure from capital-intense industry, in which initial capital cost takes most part of total cost during the projects. To improve the adaptability of Option Pricing Model specifically to the natural resource development projects, we use Two-Factor Model and Long-term Asset Model for the analysis. Although the model introduced in this paper is still simple and reflects limited reality, we expect an improvement in applicability of option pricing method for the evaluation of natural resource development projects can be made through the process taken in this paper.

• Journal of Radiation Protection and Research
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• v.33 no.1
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• pp.27-34
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• 2008

A Korean urban contamination model METRO-K (${\underline{M}}odel$ for ${\underline{E}}stimates$ the ${\underline{T}}ransient$ Behavior of ${\underline{R}}adi{\underline{O}}active$ Materials in the ${\underline{K}}orean$ Urban Environment, which is capable of calculating the exposure doses resulting from radioactive contamination in an urban environment, is taking part in a model testing program EMRAS (${\underline{E}}nvironmental$ ${\underline{M}}odelling$ for ${\underline{RA}}diation$ ${\underline{S}}afety$) oragnized by the IAEA (${\underline{I}}nternational$ ${\underline{A}}tomic$ ${\underline{E}}nergy$ ${\underline{A}}gency$). For radioactive contamination scenarios of Pripyat districts and a hypothetical RDD (${\underline{R}}adiological$ ${\underline{D}}ispersal$ ${\underline{D}}evice$), the predicted results using METRO-K were submitted to the EMRAS's Urban Contamination Working Group. In this paper, the predicted results for the contamination scenarios of a Pripyat district were shown in case of both without remediation measures and with ones. Comparing with the predictied results of the models that have taken part in EMRAS program, a feasibility for decision-making support of METRO-K was investigated. As a predicted result of METRO-K, to take immediately remediation measures following a radioactive contamination, if possible, might be one of the best ways to reduce exposure dose. It was found that the discrepancies of predicted results among the models are resulted from 1) modeling approaches and applied parameter values, 2) exposure pathways which are considered in models, 3) assumptions of assessor such as contamination surfaces which might affect to an exposure receptor and their sizes, 4) parameter values which are related with remediation measures applied through literature survey. It was indentified that a Korean urban contamination model METRO-K is a useful tool for dicision-making support through the participation of EMRAS program.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.23-36
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• 2018

Discrete Event System Specification (DEVS) has been used for decades as it provides sound semantics for hierarchical modular specification of discrete event systems. Instead of the mathematical specification, the DEVS diagram, based on the structured DEVS formalism, has provided more intuitive and convenient representation of complex DEVS models. This paper proposes a clean room process for implementation and verification of a DEVS diagram model specification into a simulation software source code. Specifically, it underlies a sequence of transformation steps from conformance and integrity checking of a given diagram model, translation into a corresponding tabular model, and finally conversion to a simulation source code, with each step being inversely verifiable for traceability. A simple example helps developers to understand the proposed process with associated transformation methods; a case study shows that the proposed process is effective for and adaptable to practical simulation software development.