• 패션비즈니스
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• 제11권3호
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• pp.69-78
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• 2007

This study explored the perceptions of Korean college women concerning their clothing deprivation and clothing decision factors. A convenience sample was used consisting of 101 female college students aged from 18 to 36 years, with a mean age of 20.78 (SD = 4.24). Descriptive statistics were used to develop a profile of the participants. To test the research objectives, multivariate analysis of variance (MANOVA), using Wilk's lambda criterion was conducted for the study. The results indicated that a college woman's year significantly influences her perceived clothing deprivation, at p =0.003 (Wilk's lambda). There was a significant positive correlation (r = 0.24, p= 0.02) between college year and perceived clothing deprivation for special occasion clothes. The two clothing decision factors clothes that fit me well and clothes that look best on me were found to be the top two factors determining clothing decisions for the study participants.

• 응용통계연구
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• 제12권1호
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• pp.97-107
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• 1999

프로파일 분석은 반복측정 자료를 분석하는데 있어서 널리 사용되는 다변량 분석모형이다. 프로파일 분석에서는 처리 그룹간의 비교와 반응 프로파일의 평행성 검정을 위해서 4가지 검정통계량이 널리 사용되고 있다. 이들 검정통계량은 Wilks의 통계량($\Lambda$), Pillai's Trace 통계량(V), Hotelling-Lawley Trace 통계량(U), Roy's Maximum Root 통계량($\Theta$ )이다. 그 동안 이들 통계량들을 비교하기 위한 여러 연구가 있었지만 주로 일반적인 다변량 분산분석 모형에 근거한 비교였다. 본 논문에서는 자료가 반복측정 자료이고 우리의 관심이 프로파일 분석에 있을 때에 이 4가지 통계량의 비교에 초점을 맞추었다.

• 응용통계연구
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• 제15권1호
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• pp.9-20
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• 2002

본 논문은 방학기간 중 실시되는 몰입형 영어교육이 학생들의 영어능력을 향상시키는데 효과적인지 검증해본다. 학생들의 영어능력 차이는 여러 가지 요인에 기인한다. 또한 학생들의 영어능력 또는 능력향상에 유의한 영향을 미치는 객관적인 요인들을 찾아 보는 것이 본 논문의 두 번째 목적이다. 분석 방법으로는 일반화 선형모형 (GLM)을 주로 사용한다.

• 한국지구과학회지
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• 제40권6호
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• pp.606-612
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• 2019

채소작물과 과수작물의 생육에 악영향을 미치는 서리발생을 미리 예측하기 위해 모형을 구축하고 채소 주산지에 적용해 보았다. 서리 발생 전날에 관측되는 다양한 기상인자들(최저기온, 18시 기온, 21시 기온, 24시 기온, 평균풍속, 18시 풍속, 21시 풍속, 구름량, 5일간 강수량, 3일간 강수량, 상대습도, 이슬점온도, 초상최저기온, 지면온도)을 수집하고, 그 중에서 서리발생에 유의한 영향이 있다고 판단되는 변수들을 통계적 방법(T-test, Random Forest, Multicollinearity test, Akaike Informaiton Criteria, 그리고 Wilk's lambda values)을 통해 선택하였다. 여러 통계적 방법을 통해 선택된 유의한 기상 인자는 24시 기온, 구름량, 이슬점온도, 21시 풍속 이였으며, 이 기상인자를 기계학습법의 한 종류인 랜덤 포레스트에 적용하여 서리 발생 예측 모형을 구축하였다. 이렇게 구축 된 서리 발생예측 모형의 정확도는 70.6%로 나타났으며, 이 모형을 가을배추와 가을무의 주산지인 홍성과 서산에 적용하였을 때 65.2%와 78.6%로 나타났다.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.305-315
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• 2021

This article aims to explore the contribution of social media value to a company's financial performance in a digital environment economy since the awareness of companies and investors in the use of social media opens up new mechanisms for disseminating information. Quantitative method is used in this study with Multivariate Analysis of Variance as the analysis tool. The data used is secondary data gathered from Indonesia Stock Exchange (IDX) using 308 companies as samples. In the multivariate test, four kinds of multivariate significance tests were carried out, namely Pillai Trace, Wilk Lambda, Hotelling's Trace, and Roy's Largest Root. It was found that social media value has a small contribution in the difference of the level of profitability and the value of the company in Indonesia, but it doesn't have a contribution to the difference of the level of liquidity. The contribution was an implication of online Word of Mouth (WOM) motives which are interrelated with signal theory and as additional information for investors in relation to single-person decision theory. This study provides an insight into the importance of social media management considering that the world of digital economy will continue to develop, so companies in Indonesia need to take advantage of these opportunities.

• 대한간호학회지
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• 제45권3호
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• pp.347-356
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• 2015

Purpose: In this study, the effectiveness of a motivational interviewing smoking cessation YOU-TURN program for adolescents was examined. The program was based on the self-determination theory. Methods: The study was carried out with a nonequivalent control group pretest-posttest design. Participants in the present study were 136 high school students living in D city. The students were assigned to the experimental group (n=52) who participated in the motivational interviewing smoking cessation YOU-TURN program based on self-determination theory, or to the control group (n=84) who participated in a general smoking cessation program. Data were collected from September 1, 2013 through April 30, 2014. Collected data were analyzed using SPSS PC+ 21.0 with Chi-square test, Fisher's exact test, t-test, Mann-Whitney U test, Repeated Measures ANOVA, and MANOVA-Wilk's Lambda. Results: The experimental group had a significant increase in basic psychological needs, and duration of quitting-smoking in comparison with the control group. The experimental group had a significant decrease in cigarettes smoked per day and cotinine in urine in comparison with the control group. Conclusion: The motivational interviewing YOU-TURN program, when delivered to adolescents who smoked, was effective in discouraging smoking, and can be utilized as an effective nursing intervention for adolescents who smoke.

• 한국공작기계학회논문집
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• 제18권2호
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• pp.170-177
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• 2009

The objective of this study is to evaluate an acoustic emission (AE) source characterization and fracture behavior of the SM45C steel by using back-propagation neural network (BPN). In previous research Ref. [8] about k-nearest neighbor classifier (k-NNC) continuity, we used K-means clustering method as an unsupervised learning method for obtaining multi-variate AE main data sets, such as AE counts, energy, amplitude, risetime, duration and counts to peak. Similarly, we applied k-NNC and BPN as a supervised learning method for obtaining multi-variate AE working data sets. According to the error of convergence for determinant criterion Wilk's ${\lambda}$, heuristic criteria D&B(Rij) and Tou values are discussed. As a result, in k-NNC before fracture signal is detected or when fracture signal is detected, showed that produce some empty classes in BPN. And we confirmed that could save trouble in AE signal processing if suitable error of convergence or acceptable encoding error give to BPN.

• 대한안전경영과학회지
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• 제11권1호
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• pp.27-33
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• 2009

A study of fracture to material is getting interest in nuclear and aerospace industry as a viewpoint of safety. Acoustic emission (AE) is a non-destructive testing and new technology to evaluate safety on structures. In previous research continuously, all tensile tests on the pre-defected coupons were performed using the universal testing machine, which machine crosshead was move at a constant speed of 5mm/min. This study is to evaluate an AE source characterization of SM45C steel by using k-nearest neighbor classifier, k-NNC. For this, we used K-means clustering as an unsupervised learning method for obtained multi -variate AE main data sets, and we applied k-NNC as a supervised learning pattern recognition algorithm for obtained multi-variate AE working data sets. As a result, the criteria of Wilk's $\lambda$, D&B(Rij) & Tou are discussed.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1565-1571
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• 2016

이 논문에서는 중국소비자들을 대상으로 휴대폰의 원산국 효과에 따라 라이프스타일에서 어떤 차이점이 있는지 실증 분석해 보고자 한다. 분석 데이터는 Kim 등 (2006, 2007)에 의해 선행연구 된 바 있다. 그룹 멤버십은 휴대폰의 원산국 효과에 대한 응답을 바탕으로 응답자를 4개 그룹으로 분류하였다. 즉, 4개 그룹은 한국산 휴대폰을 선호하는 그룹 K, 일본산 휴대폰을 선호하는 그룹 J, 미국산 휴대폰을 선호하는 그룹 U, 그리고 중국산 휴대폰을 선호하는 그룹 C이다. 이러한 그룹 멤버십을 바탕으로 일원배치 분산분석과 단계적 판별분석을 이용하여 89개 라이프스타일 변수와 2개 개인정보로 이루어진 학습표본 (training sample)을 4개 그룹으로 분류하였다. 그 결과 한국산 휴대폰을 선호하는 그룹 K는 중국산 휴대폰을 선호하는 그룹 C에 비해 개방적이고, 진보적이고, 적극적이고, 그리고 개성이 강한 것으로 보였다.