• 대한교통학회지
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• 제34권4호
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• pp.330-340
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• 2016

본 연구는 대중교통전용지구 도입 목적 달성 여부를 판단하기 위한 것으로, 이를 위해 현재 운영중인 3개 도시의 대중교통전용지구에 대한 운영상황을 비교 검토하고, 2015년 가장 최근에 도입된 부산광역시를 대상으로 방문객의 만족과 불만족을 판별하는 요소들을 도출하는 판별모형식을 제안하였다. 국내 도입된 3개 도시를 비교 검토한 결과 도시별로 운영방식이 다르며, 서울의 경우는 교통수요관리, 부산의 경우는 보행환경, 대구의 경우는 대중교통 이용 접근성이 타도시 보다 높은 수준이라는 결론을 도출하였다. 또한, 부산의 대중교통전용지구 도입 목적 달성 여부를 판단할 수 있는 판별모형식을 통해 상권 활성화 여부가 만족 여부를 판단하는 가장 유용한 변수이고, 버스 이용편의 증대 여부, 교통위험성 증가 여부, 보행자 수 증가 여부, 상가방문자 증가 여부의 순으로 판별력이 높은 변수라는 결과를 도출하였다. 이러한 결과는 각종 event 행사와 상가 주민과 협의체를 구성하는 등의 상권 활성화 방안을 마련하고, 일반차량의 통행제한 시간 확대, 도시철도와 연계하는 방안 마련 등 교통여건 개선이 필요함을 시사한다.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.931-940
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• 2011

분류분석은 학습표본으로부터 분류규칙을 도출한 후 새로운 표본에 적용하여 특정 범주로 분류하는 방법이다. 데이터의 복잡성에 따라 다양한 분류분석 방법이 개발되어 왔지만, 데이터 차원이 높고 변수간 상관성이 높은 경우 정확하게 분류하는 것은 쉽지 않다. 본 연구에서는 데이터차원이 상대적으로 높고 변수간 상관성이 높을 때 강건한 분류방법을 제안하고자 한다. 부분최소자승법은 연속형데이터에 사용되는 기법으로서 고차원이면서 독립변수간 상관성이 높을 때 예측력이 높은 통계기법으로 알려져 있는 다변량 분석기법이다. 벌점 부분최소자승법을 이용한 분류방법을 실제데이터와 시뮬레이션을 적용하여 성능을 비교하고자 한다.

• Environmental Engineering Research
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• 제18권1호
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• pp.37-43
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• 2013

Water distribution pipes installed underground have potential risks of pipe failure and burst. After years of use, pipe walls tend to be corroded due to aggressive soil environments where they are located. The present study aims to assess the degree of external corrosion of a distribution pipe network. In situ data obtained through test pit excavation and direct sampling are carefully collated and assessed. A statistical approach is useful to predict severity of pipe corrosion at present and in future. First, criteria functions defined by discriminant function analysis are formulated to judge whether the pipes are seriously corroded. Data utilized in the analyses are those related to soil property, i.e., soil resistivity, pH, water content, and chloride ion. Secondly, corrosion factors that significantly affect pipe wall pitting (vertical) and spread (horizontal) on the pipe surface are identified with a view to quantifying a degree of the pipe corrosion. Finally, a most reliable model represented in the form of a multiple regression equation is developed for this purpose. From these analyses, it can be concluded that our proposed model is effective to predict the severity and rate of pipe corrosion utilizing selected factors that reflect the fuzzy soil environment.

• 성인간호학회지
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• 제19권3호
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• pp.389-400
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• 2007

Purposes: This study was designed to explore the stage distribution of subjects according to stage of change for calcium intake and for exercise, and to identify factors that could discriminate among subjects in various stages. Methods: The sample consisted of 142 subjects who had taken bone mineral densitometry tests. The instruments used in this study were the Stage Placement Instrument for Calcium Intake and Exercise, the Osteoporosis Health Belief Scale and the Osteoporosis Knowledge Test, and the Osteoporosis Self Efficacy Scale. Data were analyzed using chi square, ANOVA, and discriminant analysis by using the SPSS 12.0 program. Results: For calcium stages, economic level, calcium knowledge, positive social norms for calcium intake, & educational level showed high standardized canonical discriminant function coefficients. For exercise stages, exercise efficacy, susceptibility, exercise benefit, educational level, positive social norm to exercise, educational level, and exercise barrier showed high standardized canonical discriminant function coefficients. Conclusion: This study implies that bone mass promoting program incorporating a stages of change model can be applied as useful nursing intervention.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

• Bulletin of the Korean Chemical Society
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• 제31권4호
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• pp.825-828
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• 2010

To classify Glycyrrhiza species, samples of different species were analyzed by $^1H$ NMR-based metabolomics technique. Partial least squares discriminant analysis (PLS-DA) was used as the multivariate statistical analysis of the 1H NMR data sets. There was a clear separation between various Glycyrrhiza species in the PLS-DA derived score plots. The PLS-DA model was validated, and the key metabolites contributing to the separation in the score plots of various Glycyrrhiza species were lactic acid, alanine, arginine, proline, malic acid, asparagine, choline, glycine, glucose, sucrose, 4-hydroxy-phenylacetic acid, and formic acid. The compounds present at relatively high levels were glucose, and 4-hydroxyphenylacetic acid in G. glabra; lactic acid, alanine, and proline in G. inflata; and arginine, malic acid, and sucrose in G. uralensis. This is the first study to perform the global metabolomic profiling and differentiation of Glycyrrhiza species using $^1H$ NMR and multivariate statistical analysis.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.487-492
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• 2008

Facial expression recognition is an intensive research area for designing Human Computer Interfaces. In this work, we present a new facial expression recognition system utilizing Enhanced Independent Component Analysis (EICA) for feature extraction and discrete Hidden Markov Model (HMM) for recognition. Our proposed approach for the first time deals with sequential images of emotion-specific facial data analyzed with EICA and recognized with HMM. Performance of our proposed system has been compared to the conventional approaches where Principal and Independent Component Analysis are utilized for feature extraction. Our preliminary results show that our proposed algorithm produces improved recognition rates in comparison to previous works.

• 한국의류학회지
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• 제28권11호
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• pp.1482-1494
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• 2004

This study identified convergent validity and discriminant validity of measurement variables by factor analysis using Spss program and tested covariance measurement model including latent variables such as the website attributes (interactivity, search and visual information of website), shopping values(utilitarian and hedonic value) and attitude toward website by AMOS program. The data were collected from a sample of 271 internet shopper of university students(male: 82, female: 189). They visited the website for apparel shopping and, after searching a casual clothing which they wanted to buy, requested to answer the questionnaire. The results were as follows: Variables that reduce validity were deleted in the several steps of factor analysis and initial measurement model testing. Final measurement model was constructed by valid variables was accepted. This measurement model will be input for testing causal research model that can explain how attributes of the website influences on consumer attitude toward the website.

• 한국조경학회지
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• 제24권4호
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• pp.96-111
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• 1997

This study was carried out to identify users' choice behavior of theme parks. overland. Lotte World, Seoul Land, Dreamland and Children's Grand Park were selected as study areas. Both multinomial logic model(MNL), nested logic model(NMNL) and joint logit model wet$.$e test using a choice-based sample collected on study areas. Hausman-McFadden test showed that the MNL is not appropriate because the IIA assumption is violated. To avoid the problematic IIA assumption, the NMNL was tested. It splits similar alternatives into groups and nests separate decisions into hierarchical order to avoid the IIA assumption. Cluster analysis and discriminant analysis were conducted to find applicable nest structures. The inclusive value coefficient was 0.7788. It meant that sufficient condition of this model is met and users' choice behavior can be better understood by NMNL than MNL. The $\rho$2 value and accuracy of prediction of this model were 0.402 and 46.33% , respectively. Several comments were suggested to make the NMNL to be more reliable for future research on users' choice behavior of theme park.

• 기술혁신학회지
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• 제19권3호
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• pp.511-544
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• 2016

표준은 호환성 증진, 품질확보 및 안정성 증진, 정보제공 등의 긍정적인 기능과 함께 기술혁신을 유발하는 것으로 알려져 있다. 표준의 순기능이 어떤 특정 기업 집단의 기술혁신 활동이나 사업화에 영향을 주는지 밝히는 것은 표준관련 정책을 수요 집단에 맞춰 적절하게 기획하고 집행하는 것을 가능하게 한다. 따라서 본 연구는 표준 정책 수립과 집행에서 증거기반 정책이라는 측면에서 기여하고자 중소기업 중에서 연구개발 동기가 표준 대응인 기업과 기술사업화를 위해서 표준제도 도입이 필요한 기업을 프로파일링하여, 이런 특정 기업을 판별할 수 있는 예측모형을 개발하고자 한다. 이를 위해, 본 연구는 의사결정나무 분석을 통해 표준 대응을 위해 연구개발을 하는 중소기업과 기술사업화를 위해 표준 규격이나 기술인증 정책을 필요로 하는 중소기업의 특징을 데이터마이닝을 통해 프로파일링 했다. 또한 판별분석을 활용하여 프로파일링된 두 가지 조건의 기업군을 몇 가지 변수로 판별할 수 있는 예측모형을 제시하였으며 판별식의 활용 가능성도 통계적으로 확인했다. 연구결과에 따르면 표준 및 규제 대응을 위해 연구개발을 수행하는 기업은 R&D기획 소요기간, 표준산업분류, 종업원 수, 기술의 신규성 등의 변수에서 차이가 있는 것으로 나타났다. 기술사업화를 위한 표준정책지원 수요기업의 프로파일링 결과에 따르면 표준산업분류, 주거래처, 연구개발 소요기간, 시험검사 능력 등의 변수에서 차이가 있었다. 본 연구에서 프로파일링 결과와 판별분석을 통해 제시한 모형은 향후 표준관련 정책을 기획하거나 집행할 때 표준지원을 필요로 하는 기업에 대한 객관적인 정보를 제공하여 표준관련 사업 성공률을 제고하는데 기여할 것으로 기대된다.