• 제목/요약/키워드: Quantitative Data

검색결과 5,138건 처리시간 0.043초

Randomized Response Model with Discrete Quantitative Attribute by Three-Stage Cluster Sampling

  • Lee, Gi-Sung;Hong, Ki-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.1067-1082
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    • 2003
  • In this paper, we propose a randomized response model with discrete quantitative attribute by three-stage cluster sampling for obtaining discrete quantitative data by using the Liu & Chow model(1976), when the population was made up of sensitive discrete quantitative clusters. We obtain the minimum variance by calculating the optimum number of fsu, ssu, tsu under the some given constant cost. And we obtain the minimum cost under the some given accuracy.

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Data Governance 정량평가 모델 개발방법의 제안 (A Quantitative Assessment Model for Data Governance)

  • 장경애;김우제
    • 한국경영과학회지
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    • 제42권1호
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    • pp.53-63
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    • 2017
  • Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

Quantitative Analysis for Plasma Etch Modeling Using Optical Emission Spectroscopy: Prediction of Plasma Etch Responses

  • Jeong, Young-Seon;Hwang, Sangheum;Ko, Young-Don
    • Industrial Engineering and Management Systems
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    • 제14권4호
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    • pp.392-400
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    • 2015
  • Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

Quantitative Reliability Assessment for Safety Critical System Software

  • Chung, Dae-Won
    • Journal of Electrical Engineering and Technology
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    • 제2권3호
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    • pp.386-390
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    • 2007
  • At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

사용자 의도 기반 정량적 빅데이터 시각화 가이드라인 툴 (A Guiding System of Visualization for Quantitative Bigdata Based on User Intention)

  • 변정윤;박용범
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제5권6호
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    • pp.261-266
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    • 2016
  • 기존의 다양한 데이터 시각화 툴에서 제공하는 차트 추천 방식은 사용자의 의도를 고려하지 않은 상태로 차트를 추천한다. 일부 시각화 툴에서는 세분화된 정량적 데이터 분류 체계를 따르지 않기 때문에 명확한 데이터 시각화가 이루어지지 않고 있다. 본 논문에서는 입력된 정량적 데이터를 정확하게 분류하고, 사용자 의도를 반영하여 효율적으로 차트를 추천하는 가이드라인을 제안한다. 가이드라인은 데이터를 분석하는 분석 가이드라인과, 입력된 데이터 타입과 사용자의 의도를 반영하여 차트를 추천하는 추천 가이드라인으로 구성되어 있다. 이러한 가이드라인을 통해 차트 선택 과정에서 사용자의 의도에 부합하지 않는 차트를 배제하였고, 사용자가 차트를 선택하는데 소요되는 시간이 감소하였음을 확인하였다.

Comparative Study of Quantitative Data Binning Methods in Association Rule

  • Choi, Jae-Ho;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • 제19권3호
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    • pp.903-911
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    • 2008
  • Association rule mining searches for interesting relationships among items in a given large database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. Many data is most quantitative data. There is a need for partitioning techniques to quantitative data. The partitioning process is referred to as binning. We introduce several binning methods ; parameter mean binning, equi-width binning, equi-depth binning, clustering-based binning. So we apply these binning methods to several distribution types of quantitative data and present the best binning method for association rule discovery.

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Quantitative Linguistic Analysis on Literary Works

  • Choi, Kyung-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.1057-1064
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    • 2007
  • From the view of natural language process, quantitative linguistic analysis is a linguistic study relying on statistical methods, and is a mathematical linguistics in an attempt to discover various linguistic characters by interpreting linguistic facts quantitatively through statistical methods. In this study, I would like to introduce a quantitative linguistic analysis method utilizing a computer and statistical methods on literary works. I also try to introduce a use of SynKDP, a synthesized Korean data process, and show the relations between distribution of linguistic unit elements which are used by the hero in a novel #Sassinamjunggi# and theme analysis on literary works.

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Quantitative Application of TM Data in Shallow Geological Structure Reconstruction

  • Yang, Liu;Liqun, Zou;Mingxin, Liu
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1313-1315
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    • 2003
  • This paper is dedicated to studying the quantitative analysis method with remote-sensing data in shallow geological structure reconstruction by the example of TM data in western China. A new method of computing attitude of geological contacts from remote-sensing data is developed and assessed. We generate several geological profiles with remotely derived measurements to constrain the shallow geological structure reconstruction in three dimensions.

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마케팅 리서치에서 다중측정방법에 관한 실증적 연구 (A Case Study of Fashion Marketing Research using Multiple Methods)

  • 박혜정;김혜정;이영주;임숙자
    • 복식문화연구
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    • 제10권6호
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    • pp.601-616
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    • 2002
  • Qualitative research is a method widely used in marketing research. However, the method has seldom been used in fashion marketing research in Korea. The purpose of this study was to prove that using both qualitative and quantitative research methods in main stage is much useful than using qualitative research method only in exploratory stage. Qualitative data were gathered by conducting Focus Group Interview(FGI) with 48 college students. Quantitative data were gathered by surveying college students, and 487 questionnaires were used in the statistical analysis. The data were analyzed using content analysis, mean, standard deviation, and t-test. As a result, FGI, one of the tools used in qualitative research methods, was proved to be useful in revealing consumers´deep emotional needs as well as purchase motives. FGI also revealed information which quantitative research method tools such as survey could have missed. Therefore, it is best to use multiple methods-simultaneous use of quantitative and qualitative methods-to understand fast changing consumers´needs and purchase motives.

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사회과학을 위한 양적 텍스트 마이닝: 이주, 이민 키워드 논문 및 언론기사 분석 (Quantitative Text Mining for Social Science: Analysis of Immigrant in the Articles)

  • 이수정;최두영
    • 한국콘텐츠학회논문지
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    • 제20권5호
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    • pp.118-127
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    • 2020
  • 본 연구는 최근 사회과학에서 실시되고 있는 양적 텍스트 분석의 흐름과 분석을 실시함에 있어 주의해야 할 사례를 포함하여 기술 하였다. 특히, 2017년부터 2019년까지 3년간 학술지와 언론에서 사용된 "이주", "이민" 키워드를 기반으로 사례연구를 실시하였다. 이를 위해 최근 사회과학분야에서 주목 받는 자연어 처리 기술(NLP)를 이용한 양적 텍스트 분석 (Quantitate text analysis)을 사용하였다. 양적 텍스트 분석은 문서를 구조적 데이터로 변환하여, 가설의 발견 및 검증을 실시하는 데이터 과학의 영역으로, 데이터의 모델링 및 가시화 등이 가능하고, 특히 비구조화 된 데이터를 구조화할 수 있다는 점에서 사회과학 분야에 많이 도입하였다. 따라서 본 연구는 양적 텍스트 분석을 통해 "이주", "이민"을 키워드로 한 연구 및 언론 기사에 대한 통계 분석을 실시하고 도출된 결론에 대한 해석을 실시하였다.