• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.47-75
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• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1189-1197
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• 2013

Data mining is the process of analyzing a huge database from different perspectives and summarizing it into useful information. One of the well-studied problems in data mining is association rule generation. Association rule mining finds the relationship among several items in massive volume database using the interestingness measures such as support, confidence, lift, etc. Typical applications for this technique include retail market basket analysis, item recommendation systems, cross-selling, customer relationship management, etc. But these interestingness measures cannot be used to establish a causality relationship between antecedent and consequent item sets. This paper propose causal association thresholds to compensate for this problem, and then check the three conditions of interestingness measures. The comparative studies with basic and causal association thresholds are shown by numerical example. The results show that causal association thresholds are better than basic association thresholds.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.587-594
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• 2016

Autonomous A.I. vehicles are seemingly soon ready for our life. One of the critical problems with autonomous vehicles is how one could assign responsibility for accidents to them. We can envisage that autonomous vehicles may confront an ethical dilemma. Then a question arises of how we are able to assign legal responsibility to autonomous vehicles. In this paper, I first introduce what the ethical dilemma of autonomous vehicles is about. Second, I show how we could be able to assign legal responsibility for autonomous vehicles. Legal probability is the received criteria for causal responsibility most of the legal theorists consider. But it remains vague. I articulate the concept of legal probability in terms of the probabilitstic theory of individual level causality while considering how one can assign causal responsibility for autonomous vehicles. My theory of causal responsibility may help one to assign legal responsibility not just for autonomous vehicles but also for people.

• Korean Journal of Logic
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• v.12 no.2
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• pp.89-114
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• 2009

We have many causal beliefs, and they play an important role in our decision making. Unlike evidential decision theory, causal decision theory claims that an account of rational choice must use causal beliefs to identify the considerations that make a choice rational. I claim that evidential decision theory is refuted by the original Newcomb's problem but not by the medical Newcomb problem. The latter is taken to be the best example to point out the weakness of evidential decision theory. However, by the explicit statement about causal relations, I argue that the medical Newcomb problem loses its strength in refuting evidential decision theory. With this argument, this paper clarifies the difference between evidential decision theory and causal decision theory.

• Nuclear industry
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• v.36 no.4
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• pp.61-69
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• 2016

• Journal of Korea Port Economic Association
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• v.23 no.4
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• pp.159-175
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• 2007

The purpose of this study is to examine the causal relationship between trading volume of freight and industrial growth in Korea ports, and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply Granger causality based on an error correction model, Hsiao(1981) method and variance decomposition. The results indicate that the extent of causality between trading volume of freight and industrial growth is strong in order of Incheon port, Busan port, Gwang Yang port, Ulsan port. We can infer policy suggestions as follows; The port policy of government must be focused on re-adjusting investment among Korea ports and raising competitive power of Korea ports

• The Korean Society of Law and Medicine
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• v.17 no.2
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• pp.57-81
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• 2016

It can determine the outcome of the lawsuit whether or not there is a causality between the medical malpractice of a physician and the patient's injury when the patient is filing a lawsuit against the physician in order to pursue civil liability for a medical accident. In medical malpractice lawsuits, it is not easy to judge causality between different civil cases because of the special nature of medical care. Also, information such as medical records is concentrated on doctors and the medical knowledge of the patient is relatively insufficient compared with the doctor. Therefore, it is recognized through medical malpractice lawsuits that the burden of proof of the causality burdened by the plaintiff patient is relaxed. In this paper, I examine the legal theory on how to recognize causality in medical civil liability and then concern the attitude of the case in Korea, which is divided into the types of the causality - such as the case of general medical practice, explanation duty, no causality with medical malpractice.

• Radioisotope journal
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• v.15 no.3
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• pp.78-92
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• 2000

낮은 선량의 방사선피폭으로 인한 건강 위해의 여부에 대하여 과학적 현황을 고찰하였다. 선량과 영향 사이에 문턱 없는 선형비례 모델(LN-T모델)에 대해 역학적, 수학적, 방사선생물학적 측면의 긍정적 논리와 호메시스, 적응반응, 통계적 관점의 비판적 논거를 대비하여 평가하였다. 방사선 피폭이력자에게 발현한 확률적 영향 특히 백혈병을 포함한 암에 대해 그 질환의 방사선 인과성 판단에 대한 애로와 접근 방향을 논의하였다. 객관적인 평가 지표의 하나로 기인확률(PC)을 적용하되 근로자에 대한 제도적 배려 등 고려할 사항을 논의하였다.

• 월간산업보건
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• s.288
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• pp.45-49
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• 2012

• Journal of Korea Ship Safrty Technology Authority
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• v.15
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• pp.31-44
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• 2004

어선전복사고의 원인을 분석하여 이러한 사고가 선체복원성, 예비부력, 방수구 및 잘못된 선체운용술과 어떠한 인과관계가 있는지를 판단하고 이에 대한 개선점을 도출코자 하였다.<중략>