• 제목/요약/키워드: Data Management Method

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Life table method을 이용한 자동차 생산기간의 생존분석 (Life table method of survival analysis using the automobile production period)

  • 김성제;조재립
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2009년도 춘계학술대회
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    • pp.531-539
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    • 2009
  • The environment of automobile industry in the world is rapidly changing. It is changing of high oil price, technology, environment and construction of competition by newly rising an economic district. Automobile company is focusing on three issue because they want to reinforce competition of automobile industry in the world. That is innovation of production profit management through quality management and Lean. Chance of success is separated in R&D, providing distribution, manufacture, distribution, selling in automobile industry. Emphasis on development process, distribution process, manufacture process, circulation and selling process for strengthening the competitiveness and guarantee. In this thesis, we try to analysis the data set period of automobile production by using survival analysis. While using mean comparison of general statistics commit mistakes, survival analysis can used for including censored data in order to heighten analysis efficiency.

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한국인 안면부 인체 데이터를 이용한 마스크 계면 프로토타입 설계 (Half-Mask Interface Prototype Design using Korean Face Anthropometric Data)

  • 송영웅;양원호
    • 대한안전경영과학회지
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    • 제12권4호
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    • pp.87-92
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    • 2010
  • The mask-face interface design should consider the face shape to improve the half mask respirator's fit ratio. This study tried to design the mask-face interface using recent Korean face data. By using the data of 1536 men's 3D face scanning (Size Korea data), head clay mock-up was made and mask-face interface line was extracted from this head mock-up. Using this interface line, the half-mask prototype was made. According to the quantitative fitting test, the proposed mask was found to be well fitted (average fit-ratio > 100). The proposed method had two advantages. 1) The method could use massive head-related anthropometric data like Size Korea data. 2) The qualitative fit test (observation) could be conducted very quickly by fitting the prototype to the head mock-up. However, this method also had several limitations. 1) The head clay mock-up could be different according to the mock-up maker. 2) The average values of the head-related anthropometric data were used to make the head mock-up. Small and large size head mock-ups should be made and tested.

시설물 유지관리를 위한 BIM 데이터 입력기준 개발방안 : 건축 기계설비를 중심으로 (Development Method of BIM Data Modeling Guide for Facility Management : Focusing on Building Mechanical System)

  • 원지선;조근하;주기범
    • 설비공학논문집
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    • 제25권4호
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    • pp.216-224
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    • 2013
  • Facility data is created throughout the design and construction phase. But the most facility managers bear significant costs that arise from the lack of interoperability with facility lifecycle. This paper is concerned with the way to collect facility data using BIM technology. The aim of this paper is to suggest BIM data modeling guide for the facility management using the information that need to be delivered from design and construction phase to operation and management phase. The BIM data modeling guide focus on the properties of mechanical equipment. It is to be hoped that this study will contribute to collect facility data from as-built BIM data and to build facility management system database without difficulty.

지식관리(KM)를 위한 건설공사 실적자료관리 개선방안 연구 (A Study on the Improvement of Historical Data For Knowledge Management in Construction Project)

  • 이태식;송재영
    • 한국건설관리학회:학술대회논문집
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    • 한국건설관리학회 2001년도 학술대회지
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    • pp.468-471
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    • 2001
  • 건설공사를 수행하는데 있어 초기 프로젝트 계획에 대한 중요성이 널리 인식되어 지고 있다. 프로젝트와 관련된 방대한 양의 실적자료들이 초기 계획단계에서부터 활용될 수 있다면, 프로젝트의 전체 범위와 비용견적을 비교적 정확하게 예측할 수 있는 중요한 원천이 될 것이다. 그러나, 공사 실적자료들의 축적, 분석, 활용의 정도가 미비하여 상당한 양의 유용한 정보들이 쉽게 사장되거나 적용되지 못한 채 보유되고 있다. 이런 문제점을 개선하기 위해서는 건설사업 참여자들이 획득한 수많은 양의 실적자료들을 유용한 지식으로 획득, 저장, 공유, 활용할 수 있는 체계적, 종합적인 실적자료관리시스템을 개발하여 관리할 필요성이 있다. 본 연구에서는 이러한 기술적 흐름과 병행하여, 현재 건설공사의 실적자료들을 효과적으로 관리하여 유사프로젝트에 유용하게 이용하고자 한다

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모바일 그리드에서 데이터마이닝을 이용한 효율적인 사용자 패턴 연구 (Study of the effective use pattern using Data Mining in a mobile grid)

  • 김휴찬;김미정
    • 디지털산업정보학회논문지
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    • 제9권2호
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    • pp.23-32
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    • 2013
  • The purpose of this study is to make effective mobile grid considered general environment, which can be summarized as irregular mobility, service exploration, data sharing, variety of machines, limit to the battery duration, etc. The data was extracted from the Dartmouth College. We analysed mobile use pattern of a specific group and applied pattern using hybrid method. As a result, we could adjust infra usage effectively and appropriately and cost cutting and increase satisfaction of user. In this study, by applying weighting method based on access time interval, we analysed use pattern added time variation with association rule during users in mobile grid environment. We proposed more stable way to manage patterns in a mobile grid environment that is being used as a hybrid form to process the data value received from the server in real time. Further studies are needed to get appropriate use pattern by group using use patterns of various groups.

특별고압 수전설비 관리에 데이터 마이닝 기법을 적용한 파급고장 발생가능고객 예측시스템 구현 연구 (A Study on Constructing the Prediction System Using Data Mining Techniques to Find Medium-Voltage Customers Causing Distribution Line Faults)

  • 배성환;김자희;임한승
    • 전기학회논문지
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    • 제58권12호
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    • pp.2453-2461
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    • 2009
  • Faults caused by medium-voltage customers have been increased and enlarged their portion in total distribution faults even though we have done many efforts. In the previous paper, we suggested the fault prediction model and fault prevention method for these distribution line faults. However we can't directly apply this prediction model in the field. Because we don't have an useful program to predict those customers causing distribution line faults. This paper presents the construction method of data warehouse in ERP system and the program to find customers who cause distribution line faults in medium-voltage customer's electric facility management applying data mining techniques. We expect that this data warehouse and prediction program can effectively reduce faults resulted from medium-voltage customer facility.

다변량 모형을 이용한 보증데이터 분석 방법 연구 (A Study on Analysis Method of Warranty Data Using Multivariate Model)

  • 김종걸;성기우
    • 대한안전경영과학회지
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    • 제17권2호
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    • pp.241-247
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    • 2015
  • The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

도로관리 종합정보 시스템을 위한 도로망 데이타베이스 구축방안 (The Method of Creating the Road Network Database for an Integrated Road Management System)

  • 김충평;이강원;김경희
    • Spatial Information Research
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    • 제3권1호
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    • pp.55-63
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    • 1995
  • 데이타베이스 설계는 데이타베이스의 기본틀과 조직을 논리적으로 구성해주는 것으로 사용자의 요구와 응용분야, 다양한 데이타간의 관계성, 데이타와 적용분야간의 관계성 등을 고려하여 설정된다. 도로망데이타는 각 구간들의 현황을 파악하고 시의 다른 데이타들과 연결하는데 필요한 다수의 데이타 요소를 가지므로 기하학적 위상구조를 가지는 구조화된 도로 데이타베이스가 만들어져야 한다. 본 고에서는 도로관리 종합관리를 위한 도로망 데이타베이스 구축방안을 제시하고자 한다.

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Feature Selection Methodology in Quality Data Mining

  • Soo, Nam-Ho;Halim, Yulius
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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    • pp.698-701
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    • 2004
  • In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

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Predicting the popularity of TV-show through text mining of tweets: A Drama Case in South Korea

  • 김도연;김유신;최상현
    • 인터넷정보학회논문지
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    • 제17권5호
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    • pp.131-139
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    • 2016
  • This paper presents a workflow validation method for data-intensive graphical workflow models using real-time workflow tracing mode on data-intensive workflow designer. In order to model and validate workflows, we try to divide as modes have editable mode and tracing mode on data-intensive workflow designer. We could design data-intensive workflow using drag and drop in editable-mode, otherwise we could not design but view and trace workflow model in tracing mode. We would like to focus on tracing-mode for workflow validation, and describe how to use workflow tracing on data-intensive workflow model designer. Especially, it is support data centered operation about control logics and exchange variables on workflow runtime for workflow tracing.