• 패션비즈니스
• /
• 제6권5호
• /
• pp.136-150
• /
• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• 대한기계학회논문집B
• /
• 제31권6호
• /
• pp.522-530
• /
• 2007

The practical studies on the method of particle contamination control for yield enhancement in the cleanroom were carried out. The method of the contamination control was proposed, which are composed of data collection, data analysis, improvement action, verification, and implement control. The partition check method and the composition analysis for data collection and data analysis were respectively used in the main board and the cellular phone module production lines. And these methods were evaluated by the variation of yield loss between before and after improvement action. In case that the partition check method was applied, the critical process step was selected and yield loss reduction through improvement actions was observed. While in case that the composition analysis was applied, the critical sources were selected and yield loss reduction through improvement actions was also investigated. From these results, it is concluded that the partition check and the composition analysis are effective solutions for particle contamination control in the cleanroom production lines.

• 한국멀티미디어학회논문지
• /
• 제17권6호
• /
• pp.671-680
• /
• 2014

Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.

• 한국공간정보시스템학회 논문지
• /
• 제9권2호
• /
• pp.81-91
• /
• 2007

본 논문에서는 공간 데이터 웨어하우스에서 시공간 분석지원을 위한 공간 데이터의 비중복 적재 기법을 제안한다. SDW는 이기종의 다양한 서비스를 지원하는 SDBMS로부터 공간 데이터를 추출한다. 제안 기법에서는 SOW에 소스로 참여하는 SDBMS에서 변경된 부분만을 추출하고, 이를 공간연산을 통해 중복된 데이터를 제거한 후 통합된 형태로 적재함으로써 빠른 공간 데이터 분석을 지원할 수 있으며, 저장 공간의 낭비를 줄일 수 있다. 이는 공간 마이닝등의 시간에 따른 분석 및 예측 분야에 효율적인 형태로 공간 데이터를 적재한다.

• Journal of the Korean Data and Information Science Society
• /
• 제24권3호
• /
• pp.533-541
• /
• 2013

이 연구에서는 라소를 이용한 간편한 주성분분석을 제안한다. 이 방법은 다음의 두 단계로 구성되어 있다. 먼저 주성분분석에 의해 주성분을 구한다. 다음으로 각 주성분을 반응변수로 하고 원자료를 설명변수로 하는 라소 회귀모형에 의한 회귀계수 추정량을 구한다. 이 회귀계수 추정량에 기반한 새로운 주성분을 사용한다. 이 방법은 라소 회귀분석의 성질에 의해 회귀계수 추정량이 보다 쉽게 0이 될 수 있기 때문에 해석이 쉬운 장점이 있다. 왜냐하면 주성분을 반응변수로 하고 원자료를 설명변수로 하는 회귀모형의 회귀계수가 고유벡터가 되기 때문이다. 라소 회귀모형을 위한 R 패키지를 이용하여 모의생성된 자료와 실제 자료에 이 방법을 적용하여 유용성을 보였다.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 2010년도 춘계 학술대회 제22권1호
• /
• pp.485-486
• /
• 2010

이 연구에서는 초고층 건축물의 시공단계부터 사용단계까지 안전성을 검토하고, 사용성을 평가하기 위해 새로운 해석기법을 개발하였으며, 개발된 해석기법은 초고층 건축물의 점진적인 시공단계와 콘크리트 재료의 비탄성 변형을 고려할 수 있으며, 골조효과를 반영함으로써 구조물의 거동을 보다 명확하게 파악하기 위해 3차원 해석기법이 도입되었다. 또한 개발된 해석기법을 바탕으로 해석 목적에 따라 실무에 적용이 가능한 실용적인 모델링 기법과 해석방법을 제안되었다. 개발된 해석기법의 검증을 위해, 현재 건설중인 초고층 건축물에서 측정한 계측자료와 개발된 해석기법으로 얻은 해석결과를 비교 검토하였으며, 해석결과가 계측자료를 잘 모사한다는 사실이 확인 되었다. 그러나, 추후 연구를 통해 보다 성공적인 검증작업을 수행하기 위해서는 추가적인 계측자료가 확보 되어야 하며, 이와 동시에 정확하고 합리적인 계측기법이 마련되어야 한다.

• 한국안전학회지
• /
• 제28권1호
• /
• pp.158-163
• /
• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• 한국실내디자인학회논문집
• /
• 제31호
• /
• pp.56-63
• /
• 2002

This study intends to prepare a system that can be used, by applying digital technique, in analyzing complexity of architectural forms that have been visualized by the correlation based on the distribution chart made in accordance with profile lines. The profile lines are derived from the edge analysis of the architectural forms, simplified based on the visual theory. For the purpose, this study was conducted in the following ways: First, problems of the existing models for the elevation analysis were examined along with formal analysis based on visual recognition to consider the profile lines derived from the forms. Secondly, in elevation analysis, profile lines were derived by digital method to measure them qualitatively. To verify the objectivity of the measured data value, a survey was conducted based on the adjective cataloging method, and the correlation of the survey result and analyzed data was analyzed to verify the validity of the derived data. Thirdly, supplementation for the problems deducted from experiments and the possibility to use it in designing were suggested. Digital method has many advantages over the conventional analyzing system in deriving precise data value by excluding subjectivity. It also allows various analytical methods in analyzing numerous data repeatedly. Diversified models and methods of analysis considering numerous factors arising in the process of designing remain assignments to research in future.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2007년도 춘계학술대회B
• /
• pp.2338-2343
• /
• 2007

The practical studies on the method of particle contamination control for yield enhancement in the cleanroom were carried out. The method of the contamination control was proposed, which are composed of data collection, data analysis, improvement action, verification, and implement control. The partition check method for data collection and data analysis was used in the cellular phone module production lines. And this method was evaluated by the variation of yield loss between before and after improvement action. In case that the partition check method was applied, the critical process step was selected and yield loss reduction through improvement actions was observed. From these results, it is concluded that the partition check method is effective solution for particle contamination control in the cleanroom production lines.

• Communications for Statistical Applications and Methods
• /
• 제28권2호
• /
• pp.135-150
• /
• 2021

We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.