• 제목/요약/키워드: statistical analysis.

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반도체 제조공정의 Critical Dimension 변동에 대한 통계적 분석 (Statistical Analysis on Critical Dimension Variation for a Semiconductor Fabrication Process)

  • 박성민;이정인;김병윤;오영선
    • 산업공학
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    • 제16권3호
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    • pp.344-351
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    • 2003
  • Critical dimension is one of the most important characteristics of up-to-date integrated circuit devices. Hence, critical dimension control in a semiconductor wafer fabrication process is inevitable in order to achieve optimum device yield as well as electrically specified functions. Currently, in complex semiconductor wafer fabrication processes, statistical methodologies such as Shewhart-type control charts become crucial tools for practitioners. Meanwhile, given a critical dimension sampling plan, the analysis of variance technique can be more effective to investigating critical dimension variation, especially for on-chip and on-wafer variation. In this paper, relating to a typical sampling plan, linear statistical models are presented for the analysis of critical dimension variation. A case study is illustrated regarding a semiconductor wafer fabrication process.

주사전자 현미경의 통계적 인자 해석 (Statistical Factor Analysis of Scanning Electron Microscope)

  • 권상희;김병환
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.335-337
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    • 2009
  • A scanning electron microscope(SEM) is a system that visualizes complex surface features. The resolution of SEM is affected by each of equipment components. In this study, we examined the effects of the four factors including the beam current, magnification, voltage and working distance. A statistical analysis was conducted to investigate the main and interaction effects. For a systematic characterization, a $2^4$ full factorial experiment was conducted. The $R^2$ of constructed statistical model was 88.9%. The main effect revealed that the current and working distance are dominant factors. Of the interactions, those between the current and voltage yielded the highest interaction. 3D plots generated from the model were used to explore various parameter effects.

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시간$\cdot$공간적 변화에 따른 장수지수 결정 요인의 특성 (Characteristics of Longevity Factor with Time and Spatial Changes)

  • 김한중;정남수;김대식;윤성수;이정재
    • 한국농공학회지
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    • 제45권3호
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    • pp.116-126
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    • 2003
  • In this study, we research about the relationships of human longevity and environments, inducted the significant factors of longevity from the statistical analysis, and represented spatial distribution of longevity using geographic information system. The factors confining human longevity can be categorized by geography/geology, climate/weather, economy, and social welfare. After analyzing statistical data, dependent variable which means the longevity index is defined by the ratio of population more than 85 years old among population more than 65 years old. The results of analysis show that longevity are related with waterworks ratio, temperature, local tax ratio, and latitude. In this study we discussed about the spatial characteristics which are represented by variance of the longevity index and described a spatial relationship between the longevity index and significant factors which are chosen by statistical analysis. In the further study, in order to sustain the longevity of a region, it is necessary for the effective rural planning to propagate a longevity of rural areas.

정밀유도무기 품질관리를 위한 공정관리 수행모델에 관한 연구 (A Study on Process Control Modeling for Precision Guided Munitions Quality Control)

  • 김시옥;이창우;차성희
    • 품질경영학회지
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    • 제41권3호
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    • pp.487-494
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    • 2013
  • Purpose: In this study, we propose the precision guided munitions verification methodology using the statistical analysis method has been proposed. and it can be applied to the precision guided munitions quality assurance work. Methods: This modeling is based on Failure Mode and Effects Analysis, Statistical Process Control, Defense Quality Managerment System, Production Readiness Review, Manufacturing Readiness Assesment and so on. Results: The Process Control Modeling that has the following procedures ; searching the critical to quality, statistical analysis by process, verify process. Moreover, the effectiveness of the methodology is verified by applying to the precision guided munitions. Conclusion: To achieve a analysis methods of statistical process control and verify process for precision guided munitions.

R을 이용한 구조방정식모델링: 매개효과분석/조절효과분석 및 다중집단분석 (Structural Equation Modeling Using R: Mediation/Moderation Effect Analysis and Multiple-Group Analysis)

  • 곽기영
    • 지식경영연구
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    • 제20권2호
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    • pp.1-24
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    • 2019
  • This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

Application of Statistical Models for Default Probability of Loans in Mortgage Companies

  • Jung, Jin-Whan
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.605-616
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    • 2000
  • Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

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TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data

  • Lim, Jae Hyun;Lee, Soo Youn;Kim, Ju Han
    • Genomics & Informatics
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    • 제15권1호
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    • pp.51-53
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    • 2017
  • High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

Big Data Smoothing and Outlier Removal for Patent Big Data Analysis

  • Choi, JunHyeog;Jun, Sunghae
    • 한국컴퓨터정보학회논문지
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    • 제21권8호
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    • pp.77-84
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    • 2016
  • In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

A Diagnostic Method in Principal Factor Analysis

  • Kang-Mo Jung
    • Communications for Statistical Applications and Methods
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    • 제6권1호
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    • pp.33-42
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    • 1999
  • A method of detecting influential observations in principal factor analysis is suggested. it is based on a perturbation of the empirical distribution function and an adoption of the local influence method. An illustrative example is given.

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