• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.87-94
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• 2017

Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.645-652
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• 2016

The statistical modeling of input random variables is necessary in reliability analysis, reliability-based design optimization, and statistical validation and calibration of analysis models of mechanical systems. In statistical modeling methods, there are the Akaike Information Criterion (AIC), AIC correction (AICc), Bayesian Information Criterion, Maximum Likelihood Estimation (MLE), and Bayesian method. Those methods basically select the best fitted distribution among candidate models by calculating their likelihood function values from a given data set. The number of data or parameters in some methods are considered to identify the distribution types. On the other hand, the engineers in a real field have difficulties in selecting the statistical modeling method to obtain a statistical model of the experimental data because of a lack of knowledge of those methods. In this study, commonly used statistical modeling methods were compared using statistical simulation tests. Their advantages and disadvantages were then analyzed. In the simulation tests, various types of distribution were assumed as populations and the samples were generated randomly from them with different sample sizes. Real engineering data were used to verify each statistical modeling method.

• Journal of The Korean Association For Science Education
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• v.34 no.6
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• pp.583-592
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• 2014

The purpose of this study is to investigate the impact of argument-based modeling strategy using scientific writing on student's modeling ability. For this study, 66 students (three classes) from the 7th grade were selected and of these, 43 students (two classes) were assigned to two experimental groups while the other 23 students (one class) were assigned to comparative group. In the experimental groups, one group (22 students) was Argument-based multimodal Representation and Modeling (AbRM), and the other group (21 students) was Argument-based Modeling (AbM). Modeling ability consisted of identifying the problem, structuring of scientific concepts, adequacy of claim and evidence and index of multimodal representation. As for the modeling ability, AbRM group scored significantly higher than the other groups, AbM group was significantly higher than comparative group. The four sub-elements of modeling ability in the AbRM group was significantly higher than the other groups statistically and AbM group scored significantly higher than comparative group. From these results, the argument-based modeling strategy using scientific writing was effective on students' modeling ability. Students organized or expressed the model and evaluated or modified it through the process of argument-based modeling using scientific writing and the exchange of opinions with others by scientific language as argument and writing.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.161-164
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• 2010

식품의약품안전청은 산발적으로 흩어져 있던 임상시험 관련 정보를 통합하여 서비스하기 위한 방안으로 임상시험정보방을 개설하게 되었다. 임상시험승인현황 등 원시자료는 종이형태로 생산, 관리된다. 이를 통계자료로 활용하기 위해서 식품의약품안전청의 관련 시스템인 KiFDA 시스템에 입력을 하게 된다. 이 시스템에 입력된 데이터는 실시간으로 임상시험관련 웹서비스 시스템에 구축된다. 이때에 실시간 통계정보의 정확성이 무엇보다 중요하다. KiFDA 시스템의 데이터베이스의 실시기관명과 임상시험계획승인제도(IND) 승인리스트 원본의 실시기관명이 틀린 것도 있었다. 이는 동일한 실시기관도 화면에서는 서로 다른 실시기관으로 보일 수 있다는 것을 의미한다. 결국 통계자료가 부정확하게 표출되는 데는 이런 원인들이 있었던 것이다. 본 논문에서는 기존의 문제점을 개선하기위해 임상시험정보방의 효율적인 통계모델링을 설계하여 물리적 데이터베이스를 구축하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.245-248
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• 2004

본 연구는 레거시 시스템의 인터페이스 정보로부터 의미 있는 정보를 파악하여 새로운 시스템에 통합될 수 있도록 하기 위한 기존 레거시 시스템의 인터페이스에 기반한 객체 추출 기법(이하 TEILOR ; Techniques to extract Object based on Interface of Legacy System for Object Reusability)을 제안한다. 본 논문에서 제안하는 TEILOR는 인터페이스 사용사례 분석 단계, 인터페이스 객체 분할 단계, 객체구조 모델링 단계, 객체 모델 통합 단계 등 4단계로 구성되어 있다. 인터페이스 사용사례 분석 단계는 인터페이스 구조, 레거시 시스템과 사용자간의 상호작용 정보를 획득하는 단계이다. 인터페이스 객체분할 단계는 인터페이스 정보를 의미 있는 필드들로 구분하는 단계이며, 객체구조 모델링 단계는 인터페이스 객체들간의 구조적 관계와 협력 관계를 파악하여 모델링하는 단계이다. 마지막으로 객체 모델 통합 단계는 객체 단위의 단위 모델들을 통합하여 추상화된 정보를 포함한 상위 수준의 통합 모델을 유도하는 단계다. TEILOR에 의해 생성된 객체 통합 모델은 역공학 기술자들의 레거시 시스템 이해와 레거시 시스템의 정보를 새로운 시스템에 적용하는데 있어 효율성을 극대화할 수 있다.

• Journal of Gifted/Talented Education
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• v.22 no.3
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• pp.503-525
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• 2012

This study compared levels of mathematically talented students' statistical thinking with those of non-talented students in statistical modeling and sampling distribution understanding. t tests were conducted to test for statistically significant differences between mathematically gifted students and non-gifted students. In case of statistical modeling, for both of elementary and middle school graders, the t tests show that there is a statistically significant difference between mathematically gifted students and non-gifted students. Table of frequencies of each level, however, shows that levels of mathematically gifted students' thinking were not distributed at the high levels but were overlapped with those of non-gifted students. A similar tendency is also present in sampling distribution understanding. These results are thought-provoking results in statistics instruction for mathematically talented students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2603-2609
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• 2014

Reliability analysis of mechanical systems requires statistical modeling of input random variables such as distribution function types and statistical parameters that affect the performance of the mechanical systems. Some random variables are correlated, but considered as independent variables or wrong assumptions on input random variables have been used. In this paper, joint distributions were modeled using copulas and Bayesian method from limited number of data. To verify the proposed method, statistical simulation tests were carried out for various number of samples and correlation coefficients. As a result, the Bayesian method selected the most probable copula types among candidate copulas even though the candidate copula shapes are similar for low correlations or the number of data is limited. The most probable copulas also yielded similar reliabilities with the true reliability obtained from a true copula, so that it can be concluded that the Bayesian method provides accurate statistical modeling for the reliability analysis.

• Journal of the Korean School Mathematics Society
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• v.24 no.3
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• pp.283-308
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• 2021

This study aims to analyze statistical tasks in Korean and Singaporean textbooks with the mathematical modeling perspective and compare the learning contents and experiences of students from both countries. I analyzed mathematical modeling tasks in the textbooks based on five aspects: (1) the mathematical modeling process, (2) the data type, (3) the expression type, (4) the context, and (5) the mathematical activity. The results of this study show that Korean and Singaporean textbooks provide the highest percentage of the "working-with-mathematics" task, the highest percentage of the "matching task," and the highest percentage of the "picture" task. The real-world context and mathematical activities used in Korean and Singaporean textbooks differed in percentage. This study provides implications for the development of textbook tasks to support future mathematical modeling activities. This includes providing a balanced experience in mathematical modeling processes and presenting tasks in various forms of expression to raise students' cognitive level and expand the opportunity to experience meaningful mathematizing. In addition, it is necessary to present a contextually realistic task for students' interest in mathematical modeling activities or motivation for learning.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.883-888
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• 2014

Simulation is now using in various area as an effective decision analysis tool in complex environment of today. But, There is a focus to the simulation model development and execution better than result analysis. This article will emphasis to the importance of result analysis apart from model development in simulation, and will use R package for profit optimization simulation. R has a various function in statistic analysis and data manipulation, graphic display. So this research can show the value of R as a tool for simulation.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.1-4
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• 2000

상위 $20\%$의 우량고객이 기업수익의 $80\%$를 기여한다는 파레토 법칙을 인용하지 않더라도 고객이 원하는 상품과 서비스를 지속적으로 제공함으로써 고객과의 지속적인 관계를 통한 고객과의 지속적인 관계유지, 특히 우량고객의 확보, 유지는 기업의 수익증대에 깊은 관계가 있으며 결국 기업의 생존을 가늠하는 길이 될 것이다. 최근에는 금융권간 업무영역이 무너지면서 모든 금융기관들은 우수고객 확보를 위해 영업력을 집중시키고 있다. 특히 수익기여도가 높은 우수고객에 대해서는 차별적인 우대서비스를 명시적으로 규정하고 우량고객 확보를 위한 생존을 건 경쟁이 벌어지고 있다. 따라서 우량고객은 자료를 통한 객관적이고 합리적 기준에 의해 확보되어야 한다. 본 연구에서는 이에 대한 방법론으로서 데이터베이스 모델링을 제시하며, 그 효과를 측정하도록 하고, 고객 속성에 따른 고객세분화에 이용될 수 있음을 보여준다.