• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.101-109
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• 2011

Generally, learning tools like robots are being mainly used as teaching aids to enhance creativity of a group of students who are superior in their studies and have an excellent potential in private education. This study uses a relatively cheap line tracer as a teaching aid and connects it with regular subjects so that elementary school higher graders showing academic achievement lower than average can get robot learning. This research developed a line tracer learning curriculum and teaching materials for total 12 sessions and taught students showing academic achievement below average and evaluated them after. According to the result of evaluating their achievement levels based on their results of learning in each session, most of the students with low academic achievement was evaluated to understand most of the contents in the curriculum fully. Through its empirical implementation, this paper has found the possibilities of robot education connected with the regular curriculum for elementary students exhibiting relatively lower academic achievement.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.4
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• pp.221-231
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• 2005

The present study is deeply concerned with the reliability design method(Level III) for caisson breakwaters using expected sliding distance, and the objectives of this study are to propose the employment of a doubly-truncated normal distribution and to present the validity for it. In this study, therefore, the explanations are made for consideration of effects of uncertain factors, and a clear basis that the doubly-truncated normal distribution should be employed in the computation process of expected sliding distance by Monte-Carlo simulation is presented with introduction of the employment method. Even though only caisson breakwaters are treated in this paper, the employment of doubly-truncated normal distribution can be applied to various coastal structures as well as other engineering fields, and therefore it is expected that the present study will be extended in various fields.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.271-276
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• 2014

Short message service(SMS) in a mobile communication environment is a very convenient method. However, it caused a serious side effect of generating spam messages for advertisement. Those who send spam messages distort or deform SMS sentences to avoid the messages being filtered by automatic filtering system. In order to increase the performance of spam filtering system, we need to recover the distorted sentences into normal sentences. This paper proposes a method of normalizing the various types of distorted sentence and extracting keywords through automatic word spacing and compound noun decomposition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.298-304
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• 2012

In this paper, we propose robust estimators for the frequency offset of orthogonal frequency division multiplexing in non-Gaussian noise environments. We first propose a maximum-likelihood (ML) estimator in non-Gaussian noise modeled as a complex isotropic Cauchy process, and then, we present a simpler suboptimal estimator based on the ML estimator. From numerical results, it is demonstrated that the proposed estimators not only outperform the conventional estimators, but also have a robustness in non-Gaussian noise environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.547-552
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• 2019

Recently, the massive growth in the scale of data has been observed as a major issue in the Big Data. Furthermore, the Big Data should be preprocessed for normalization to get a high performance of the Machine learning since the Big Data is also an input of Machine Learning. The performance varies by many factors such as the scope of the columns in a Big Data or the methods of normalization preprocessing. In this paper, the various types of normalization preprocessing methods and the scopes of the Big Data columns will be applied to the SVM(: Support Vector Machine) as a Machine Learning method to get the efficient environment for the normalization preprocessing. The Machine Learning experiment has been programmed in Python and the Jupyter Notebook.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.243-246
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• 2001

턱 논문에서는 복잡한 배경에서 다양한 조명과 얼굴의 크기 변화를 가지는 영상으로부터 눈을 검출하는 새로운 방법을 제안한다. 반사 대칭 조건과 타원 모델링을 이용하여 먼저 얼굴을 검출하고 그 영역 내에서 수리 형태학을 이용한 valley detection, binary opening을 수행함으로써 눈 후보 영역을 추출한다. 그리고 정확한 눈동자의 위치를 검출하기 위하여 눈동자 정합 마스크를 제안하였다 얼굴 검출 과정에서 타원의 단축 길이를 추정하여 추출된 얼굴 영상의 크기를 정규화 하였다. 정규화 된 얼굴 영상에서 눈 검출에 적합한 형태소(structuring element)를 결정하여 눈 검출 결과를 보다 견실하게 하였다.

• Digital Contents
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• no.12 s.127
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• pp.146-148
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• 2003

인터넷 입시 과외를 비롯 외국어학습, 대학 정규과정 등 각종 e-러닝(e-Learning) 학습 프로그램이 빠른 속도로 번지고 있다. 또한 기업 연수현장에도‘사이버 바람’이 거세게 불고 있다. 이런 배경에서 지난 10월 23일 정보통신부는 한국e-러닝학회, KDI국제정책대학원, 한국정보통신기자협회의 후원 아래‘한국 e-러닝 산업 활성화 전략 세미나’를 개최했다. 국내 e-러닝 비즈니스 관계자 182명이 참석한 이날 행사에는 e-러닝 산업현황 및 성공사례, 비즈니스 모델 등이 발표되고, 게임 및 모바일 관점에서의 서비스 동향도 소개돼 뜻깊은 자리가 됐다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.331-333
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• 2003

본 논문에서는 새로운 얼굴 인식 방법을 제안한다. 제안된 방법은 입력 영상에서 눈이라고 생각되는 영역을 형판 정합방법을 이용하여 먼저 추출하고. 양 눈의 위치 정보를 사용하여 얼굴 영역의 크기와 회전정도를 보정하여 정규화된 얼굴영상을 만들며, 결국 PCA 방법을 사용하여 인식하게 된다. 이렇게 함으로써 PCA가 안정된 영상이 입력되면 좋은 인식률을 보이지만 전반적인 조명의 변화에 잘 대응하지 못하고, 복잡한 배경인 경우 얼굴영역의 위치 변화에 민감하며, 많이 기울어진 영상에 취약하다는 단점을 형판 정합을 통한 전 처리 과정을 통해 보완할 수 있게 된다. 실험 결과 제안된 방법이 PCA의 인식 성능을 크게 향상시킬 수 있음을 알 수 있었다.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1067-1076
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• 2006

Although the proportional hazards model is the most common approach used for studying the relationship of event times and covariates, alternative models are needed for occasions when it does not fit data. In the two-sample case, proportional odds models are useful for fitting data whose hazard rates converge asymptotically. In this thesis, we propose a new estimator of the relative odds ratio of the proportional odds model when two independent random samples are observed under uncensorship. We prove the asymptotic normality and consistency of the estimator by using martingale-representation. The efficiency of the proposed is assessed through a simulation study.

• Review of KIISC
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• v.19 no.1
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• pp.40-58
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• 2009

증가하는 인터넷 해킹사고와 전자정부의 확산 등으로 정보보호에 대한 필요성이 증대하고 있으며, 산업체 또는 정부에서 정보보호를 담당하는 인력의 수요가 필요하다. 본고에서는 정보보호 인력 양성의 방법으로 정보보호 관련 정규과정에 의한 방법이 아닌 정보보호 자격 검정에 의한 방안을 다룬다. 국외의 공인정보시스템보안전문가(CISSP), 공인정보시스템 감사사(CISA) 및 국내의 정보보호전문가(SIS) 등 국내외 3개의 정보보호 자격에 대한 비교연구를 통하여 정보보호전문가 자격제도의 발전 방안을 제시하고자 한다.