• Journal of Digital Convergence
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• v.12 no.6
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• pp.69-77
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• 2014

System Dynamics(SD) is one of the complexity theories that has attracted attention as a computer-aided simulation methodology to analyze a dynamic problem and to develop a policy(strategy) in social science. Though there are properly unproven cases in research models which were developed in various fields by SD methodology during the last five decades, they are utilized as models to represent SD sub-theories. For this reason, this study targeted the population dynamics model which was frequently utilized to explain SD fundamentals and it proved errors of reasoning a structure of the existing causal and dominant feedback loop. Consequently, we presented a strategy to strengthen the coherence between CLD(causal loop diagram) and SFD(stocks-and-flows diagram) for improving validity of the existing model. The findings of this study contribute to the advancement of the existing SD and to the reinforcement of validation for policy research models of SD.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.39-48
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• 2014

Good and bad luck is an important factor that frequently affects human information processing. However, in spite of its significance, few studies have been done to examine how good and bad luck influences information processing and reasoning. The current research was performed to explore the effect of good and bad luck on reasoning and, for this, two experiments were conducted. In experiment 1, participants were primed with good or bad luck and were asked to make an inference for a given murder case and include as many as clues for it, while in experiment 2, participants were asked to exclude as many as clues for the same murder case. Results show that, in experiment 1, participants who were primed with good luck included more clues than those who were primed with bad luck. However, in Experiment 2, it was found that participants who were primed with bad luck excluded more clues than those who were primed with good luck. Findings from this study indicate that priming good luck enhances holistic thinking which leads to including more and excluding less clues whereas priming bad luck increases analytic thinking which leads to including less and excluding more clues. Implications of this study for inference and decision making, consumer behavior, and addict psychology are discussed.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.191-193
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• 2016

인적오류 예방은 해양사고 예방에 가장 중요한 이슈로 현재 인식되고 있다. 현재 이러한 인적오류를 예방하기 위한 다양한 과학적인 기법들이 등장하고 있으나, 실제 인적오류를 예방할 수 있는 기법은 아직 개발되어 있지 못한 실정이다. 그 이유는 인적오류의 발생 원인과 특징이 사람을 대상으로 하기 때문에 실로 방대하고 원인식별이 어려우며, 원인과 결과 사이의 인과관계 구축에는 한계가 있기 때문이다. 기존 개발된 다양한 기법들은 이론적으로는 완벽할 수 있으나, 실제 방대한 원인과 결과 사이에 형성된 연계체인을 모두 흡수하기가 곤란하기 때문이다. 현재 IMO의 공식안전성평가(FSA) 기법이 해상분야에 널리 적용되고 있으나 구체적으로 어떠한 기법을 적용하여 인적오류를 적용할 수 있는지에 대해서는 아직도 애매모호한 실정이다. FTA, ETA, FEMA, SWIFT 등 다양한 분석기법의 등장과 AI, Fuzzy, MMC, Kalman 등 기초과학분야의 기본적인 이론과 기술을 적용할 수 있으나 인간의 인적오류 식별과 분석 및 평가와 예측에는 한계가 있는 것이 현재의 실정이다. 한편 최근에는 기존에 많은 문제점을 내포하고 있는 것으로 고려되었던 베이지안 네트워크(Bayesian Network, BN)가 다시 분석과 예측 분야에 등장하고 있는데, BN의 장점을 수용하고 단점을 해결할 수 있는 방법들이 연구되고 있기 때문이다. BN의 장점은 전방추론과 후방추론을 적용하여 사고의 원인과 결과를 분석한 후, 이에 대한 해결 방안을 식별할 수 있기 때문이다. BN의 단점은 이진(binary) 구조의 데이터만을 수용할 수 있기 때문에 상관 변수들이 방대한 경우 계산시간이 방대해지고 이를 모두 수용할 수 있는 방법이 없기 때문이다. 따라서 BN 구조를 어떻게 설계하는냐가 최근의 이수로 등장하고 있다. 본 연구에서는 이러한 제 문제점을 고찰하고 인적오류 모델 개발에 최적인 방법 또는 기술을 모색하는데 있다.

• Journal of Practical Engineering Education
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• v.6 no.1
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• pp.1-7
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• 2014

The variable control in the inductive inference for the confirmation and verification when the experimental data are collected is studied by applying the principle of probability inference. The control in engineering experiments is to protect any effect by of intervening variable except primary independent variable on the dependent variable. By the special condition the possibility for developing a phenomenon will be maximized; otherwise, by the extraneous condition the possibility for developing a phenomenon will be minimized. By doing so, the control may provide insurance for the causal relationship between the certain prior event (independent variable) and the post-event (the dependent variable). Some experiments by using both elliptical trainer and tread mill under the variable control are performed in order to find the relations between the energy expenditure, the respiratory exchange ratio (RER), and the heart rate (HR) against the exercise speed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.23-26
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• 1996

인과관계적 추론 방법(causal reasoning)은 시스템 고장을 시스템 구조나 행동의 원인 상과관계를 사용하여 분류하는 것으로서 관측된 행도오가 기대행동의 차이를 조사하여 인식하게 된다. 본 연구에서는 징후(symptom)를 분석 및 분류할 때에 시스템의 기능적인 계층구조를 이용한다. 전문가시스템의 구축은 KAPPA-PC를 사용하였다. KAPPA-PC는 규칙 및 논리에 근거한 방법과 객체지향적 지식 표현 기법을 사용한다. 대다수의 사람들이 일상적으로 사용하는 PC(Personal Computer)는, 특히 하드웨어에서 고장이 일어났을 때 수리자의 노우하우(know-how)로 고쳐지는 경우가 대부분이다. 본 논문에서는 자주 일어날수 있는 PC의 하드웨어적 고장에 일반사용자들이 쉽게 접근해서 그 원인과 진단을 내릴 수 있도록 했으며 작은 고장 원인이 전체 시스템구조내에서 어떤 상관관계를 가지는지를 고찰하였다.

• Journal of Oral Medicine and Pain
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• v.30 no.1
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• pp.35-44
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• 2005

Purpose: The aim of this preliminary study was to evaluate the effect of Problem-Based Learning (PBL) curriculum on development of comprehension of basic medical knowledge and quality of semi-structured problem solving including scientific reasoning skill. This scientific reasoning contained five components including: size of simple, design of research cause-effect, construction of risk factor, analysis statistic of data, interpretation of result. Materials and Methods: Seoul National University Dental students (100) participated in this experience during two weeks, 2004. Forty eight multiple-choice questions (MCQ) concerned "Infection Control and Prevention" were asked before and after two sections of Lecture-Based Learning (LBL) and PBL (pretest-posttest control group design). A semi-structured problem in epidemiological research was asked to these students after two sections (posttest-only control group design). Data (mean and SD) were analysed using the t Test for two independent samples (p<.05), comparing PBL versus LBL. Results: Our analyse of scores show no difference between LBL and PBL in the development of comprehension of "Infection Control and Prevention". The quality problem solving (epidemiological research) was significantly different between the two groups (p=.029); specially, two components' scores of reflection on scientific reasoning cause-effect (p=.000) and interpretation of result (p=.001) were significantly better for PBL than for LBL. Conclusion: Theses results indicate that comparing LBL and PBL, PBL curriculum have not been disadvantaged in comprehension of basic knowledge, and have contributed to develop the scientific reasoning in problem solving.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.369-376
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• 2001

도심지에서 자주 발생되는 교통체증의 문제를 효과적으로 해결하기 위해서는 교통 상황을 신속하고 정확하게 진단하며, 이를 바탕으로 최대한의 효율을 얻을 수 있도록 교통 신호체계를 수립하는 것이 중요하다. 본 논문에서는 '병렬기반 미시적 교통류 시뮬레이션 시스템'을 활용하여 교통상황을 정확하게 모델링한 결과정보를 추출하고, 이를 바탕으로 교통상황을 종합적으로 진단할 수 있는 '교통류 시뮬레이션 평가 및 진단 시스템'을 제시한다. 교통상황에 대한 시뮬레이션 결과정보를 쉽게 분석할 수 있는 교통류 시뮬레이션 평가 및 진단 시스템을 개발하기 위하여, 교통상황의 해석에 필요한 제반 문제와 원인들의 인과관계를 파악하여 규칙화하고, 이를 바탕으로 규칙 기반추론 기법을 적용할 수 있도록 전문가시스템을 도입하였다. 또한 효율적인 진단을 위하여 시뮬레이션 결과정보로부터 구한 정량적인 각종 평가 지표를 정성적인 측면에서 재평가하여 사유할 수 있도록 fuzzy 기술을 도입하였다. 아울러 교통류 시뮬레이션 평가 및 진단 시스템의 결과는 최적의 신호체계를 수립하는데 활용될 수 있도록 하였다. 서울광역시 과천 주변의 8 개 교차로를 포함하는 교통망에 대한 교통정보를 바탕으로 실험해 봄으로써 사용자가 복잡한 교통망에 대해 보다 효과적으로 교통흐름을 분석하여 정체원인을 실시간으로 판단할 수 있는 가능성을 보여준다.

• Journal of Preventive Medicine and Public Health
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• v.40 no.6
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• pp.495-504
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• 2007

Objectives : This study attempts to show how studies using non-experimental data can strengthen causal inferences by applying propensity score and instrumental variable methods based on the counterfactual framework. For illustrative purposes, we examine the effect of having private health insurance on the probability of experiencing at least one hospital admission in the previous year. Methods : Using data from the 4th wave of the Korea Labor and Income Panel Study, we compared the results obtained using propensity score and instrumental variable methods with those from conventional logistic and linear regression models, respectively. Results : While conventional multiple regression analyses fail to identify the effect, the results estimated using propensity score and instrumental variable methods suggest that having private health insurance has positive and statistically significant effects on hospital admission. Conclusions : This study demonstrates that propensity score and instrumental variable methods provide potentially useful alternatives to conventional regression approaches in making causal inferences using non-experimental data.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.161-177
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• 2023

Scientific explanation is composed of various representations such as texts, diagrams, and graphs, and each representation contributes to expanding scientific meaning by connecting similar but slightly different meanings as a 'mode'. Based on this perspective of social semiotics, we aimed to identify the characteristics of meaning formation demonstrated in students' science writing (verbal mode) and science drawing (visual mode) and to discuss the pedagogical use of multimodal representations. To that end, 18 science drawings and 18 scientific writings constructed by science-gifted elementary students on air pressure were collected. The characteristics of the drawn and written explanations were then analyzed from the affordance perspective in social semiotics. In science drawing, students showed a tendency to use the affordance of the visual mode to infer concrete changes from the particle view, such as the movement of air particles, the number of air particles, and the collision of particles. In science writing, students used the affordance of the verbal mode mainly to infer the causal relationship between the concept of air pressure and other related factors at an abstract level. Based on those results, we discuss the educational implications and provide concrete examples of how to use the unique affordances of each form to complement one another.