• 천문학회보
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• 제45권1호
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• pp.51.2-51.2
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• 2020

Luminous blue variables (LBVs) are massive evolved stars that show unpredictable photometric and spectral variation. It is generally assumed that they undergo one or more of large eruptions. We have obtained high dispersion NIR spectra of several LBVs with Immersion GRating INfrared Spectrometer (IGRINS). One notable feature in their IGRINS spectra is the existence of broad lines (~ a few hundred km/s) with unusual boxy profile. They are fluorescent lines of Fe II by Lyman α photons in the stellar wind. However, modeling of these lines with radiative transfer code CMFGEN predicts much weaker line strength. We propose that incorporating broadening of Lyman α line by scattering processes in dense wind can enhance the Fe II fluorescent lines. We further discuss how these Fe II fluorescent lines can be used to characterize massive LBV wind.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.287-292
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we confirmed advantages/disadvantages of four algorithms and identified application methods of few algorithms.

• 한국경영과학회지
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• 제6권2호
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• pp.35-49
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• 1981

This paper is concerned with developing a Multi-period Behavioral Model for the portfolio selection problem. The unique feature of the model is that it treats a number of factors and decision variables considered germane in decision making on an interrelated basis. The formulated problem has the structure of a Chance Constrained programming Model. Then empoloying arguments of Central Limit Theorem and normality assumption the stochastic model is reduced to that of a Non-Linear Programming Model. Finally, a number of interesting properties for the reduced model are established.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.117-120
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• 1996

The objective of this study is to suggest modified Covariance Structure Analysis that combine with existing Multivariate Statistical Method which is used Casual Analysis Method in Management Information. For this purpose, we'll consider special feature and limitation about Correlation Analysis, Regression Analysis, Path Analysis and connect Covariance Structure Analysis with Statistical Factor Analysis so that theoretical casual model compare with variables structure in collecting data. A example is also presented to show the practical applicability of this approach.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.271-276
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• 2003

In this study, we compared backpropagation neural network(BPNN) with probabilistic neural network(PNN) as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to two algorithm. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we comfirmed advantages/disadvantages of two algorithms and identified application methods of two algorithms.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.280-285
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself. Through this process, we comfirmed advantages/disadvantages of four algorithms and identified application methods of four algorithms.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.143-155
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• 2009

Best subset selection procedure based on mutual information (MI) between a set of explanatory variables and a dependent class variable is suggested. Derivation of multivariate MI is based on normal mixtures. Several types of normal mixtures are proposed. Also a best subset selection algorithm is proposed. Four real data sets are employed to demonstrate the efficiency of the proposals.

• Journal of the Korean Data and Information Science Society
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• 제23권5호
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• pp.961-970
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• 2012

국방연구개발에 참여하는 업체 중에 특정기술을 일정기간에 개발할 수 있는 역량을 구비한 업체를 선정하기 위해서는 사업목적에 적합한 평가지표를 개발하는 것이 매우 중요하다. 본 연구는 선행연구와 국방 연구개발의 특성, 현재 사용하고 있는 항목을 종합하여 새로운 지표를 개발하고 전문가 인터뷰를 통해 객관화 하였다. 선정항목의 타당성 검증과 계층구조 모형설계를 위해 주축요인분석을 실시하였으며 27개 변수 중 타당성이 없는 10개를 제외하고 17개 변수를 최종 선정하였다. 17개 변수는 계층분석법 (analytic hierarchy process)을 통해 평가지표 항목의 가중치를 부여하였으며, 상위계층에서는 업체능력이 개발계획보다 중요하게 나타났고, 하위계층에서는 고객과의 의사소통 및 협력방안과 현 사업 유사기술 특허 및 논문의 우수성, 소요기술 확보현황 등이 높은 순위로 나타났다. 반면 기술유출 방지대책, 협력업체 전문성 및 관리의 적절성, 소프트웨어 개발방안 등은 낮은 순위로 나타났다.

• 한국한의학연구원논문집
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• 제17권3호
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• pp.97-104
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• 2011

Objectives : In this paper, we proposed a method for selecting reliable variables from various vocal features such as frequency derivative features, frequency band ratios, intensities of 5 vowels and an intensity of a sentence, since some features are sensitive to the variation of a subject's utterance. Methods : To obtain the reliable voice variables, the coefficient of variation (CV) was used as the index to evaluate the level of reliability. Since the distributions of a few features are not Gaussian, but are instead skewed to the right or left, we transformed the features by taking the log or square root. Moreover, the definition of the variables that are suitable to represent the vocal property was explained and analyzed. Results : At first, we recorded the vowels and the sentence five times both in the morning and afternoon of the same day, totally ten recordings from each of six subjects (three males and three females). We then analyzed the CVs of each subject's voice to obtain the stable features with a sufficient repeatability. The features having less than 20% CVs for all six subjects were selected. As a result, 92 stable variables from the 222 features were extracted, which included all the transformed variables. Conclusions : Voice can be widely used to classify the four constitution types and to recognize one's health condition from extracting meaningful features as physical quantity in traditional Korean medicine or Western medicine. Therefore, stable voice variables can be useful in the u-Healthcare system of personalized medicine and for improving diagnostic accuracy.

• 한국정보통신학회논문지
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• 제16권1호
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• pp.33-40
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• 2012

본 논문은 생물 조기 경보 시스템을 구현하기 위한 방법을 제안한다. 이 시스템은 모니터링 데몬을 이용해 간헐적으로 데이터 사건을 생성하고, 이 데이터 집합으로부터 특징 매개변수들을 추출한다. 특징 매개변수는 6개의 변수(x/y 축 좌표, 거리, 절대 거리, 각도, 프랙털 차원)를 가지고 유도된다. 특히 프랙털 이론을 사용해 제안 알고리즘은 입력된 특징들이 독성 환경에 있는지 아닌지의 유기물 특성을 정의한다. 추출된 특징 데이터를 학습하기 위한 적절한 알고리즘을 위해 기계학습 분야에서 널리 쓰이는 확장된 학습 알고리즘(UChoo)을 사용한다. 그리고 본 알고리즘은 특징 집합들이 모니터링 데몬에 의해 주기적으로 추가된다는 BEWS의 특징을 극복하기 위해 확장된 데이터 표현 방법을 이용하는 학습 방법을 포함한다. 이 알고리즘에서 결정트리 분류기는 확장된 데이터 표현에서 가중치 매개변수를 사용하는 부류 분포 정보를 정의 한다. 실험 결과들은 제안된 BEWS가 환경적인 독성을 탐지하는데 이용 될 수 있음을 보인다.