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New FMVSS301 법규 조건에 의한 승용차의 후방충돌 해석 사례
황인수(Insoo Hwang),임종현(Jonghyun Yim),김동석(Dongseok Kim) 한국자동차공학회 2004 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
NHTSA upgraded the rear impact test in the FMVSS(Federal Motor Vehicle Safety Standard) on fuel system integrity. This new rule replaces a full rear impact test procedure at 48 ㎞/h with an offset rear impact test procedure specifying that only a portion of the width of the rear of the test vehicle be impacted at 80 ㎞/h. In this paper, we performed the rear crash simulation according to the new rule and evaluated the results of simulation and test. The result showed higher deformation value than that of old FMVSS301. All simulation results existed within the in-house guideline, and test result was satisfied with body deformation requirements.
인터넷 검색과 형태소분석을 이용한 표절검사시스템의 개발에 관한 연구
황인수(Insoo Hwang) 한국데이타베이스학회 2009 Journal of information technology applications & m Vol.16 No.1
As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.
연관분석을 이용한 효과적인 표절검사 및 문서분류에 관한 연구
황인수 ( In Soo Hwang ) 한국정보시스템학회 2014 情報시스템硏究 Vol.23 No.3
Plagiarism occurs when the content is copied without permission or citation, and the problem of plagiarism has rapidly increased because of the digital era of resources available on the World Wide Web. An important task in plagiarism detection is measuring and determining similar text portions between a given pair of documents. One of the main difficulties of this task is that not all similar text fragments are examples of plagiarism, since thematic coincidences also tend to produce portions of similar text. In order to handle this problem, this paper proposed association analysis in data mining to detect plagiarism. This method is able to detect common actions performed by plagiarists such as word deletion, insertion and transposition, allowing to obtain plausible portions of plagiarized text. Experimental results employing an unsupervised document classification strategy showed that the proposed method outperformed traditionally used approaches.