• 제목/요약/키워드: Distribution Data Process

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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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New Inference for a Multiclass Gaussian Process Classification Model using a Variational Bayesian EM Algorithm and Laplace Approximation

  • Cho, Wanhyun;Kim, Sangkyoon;Park, Soonyoung
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권4호
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    • pp.202-208
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    • 2015
  • In this study, we propose a new inference algorithm for a multiclass Gaussian process classification model using a variational EM framework and the Laplace approximation (LA) technique. This is performed in two steps, called expectation and maximization. First, in the expectation step (E-step), using Bayes' theorem and the LA technique, we derive the approximate posterior distribution of the latent function, indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. In the maximization step, we compute the maximum likelihood estimators for hyper-parameters of a covariance matrix necessary to define the prior distribution of the latent function by using the posterior distribution derived in the E-step. These steps iteratively repeat until a convergence condition is satisfied. Moreover, we conducted the experiments by using synthetic data and Iris data in order to verify the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm shows good performance on these datasets.

Precise Distribution Simulation of Scattered Submunitions Based on Flight Test Data

  • Yun, Sangyong;Hwang, Junsik;Suk, Jinyoung
    • International Journal of Aeronautical and Space Sciences
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    • 제18권1호
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    • pp.108-117
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    • 2017
  • This paper presents a distribution simulation model for dual purpose improved conventional munitions based on flight test data. A systematic procedure for designing a dispersion simulation model is proposed. A new accumulated broken line graph was suggested for designing the distribution shape. In the process of verification and simulation for the distribution simulation model, verification was performed by first comparing data with firing test results, and an application simulation was then conducted. The Monte Carlo method was used in the simulations, which reflected the relationship between ejection conditions and real distribution data. Before establishing the simulation algorithm, the dominant ejection parameter of the submunitions was examined. The relationships between ejection conditions and distribution results were investigated. Five key distribution parameters were analyzed with respect to the ejection conditions. They reflect the characteristics of clustered particle dynamics and aerodynamics.

Modelling on Multi-modal Circular Data using von Mises Mixture Distribution

  • Jang, Young-Mi;Yang, Dong-Yoon;Lee, Jin-Young;Na, Jong-Hwa
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.517-530
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    • 2007
  • We studied a modelling process for unimodal and multimodal circular data by using von Mises and its mixture distribution. In particular we suggested EM algorithm to find ML estimates of the mixture model. Simulation results showed the suggested methods are very accurate. Applications to two kinds of real data sets are also included.

Tests for the Change-Point in the Zero-Inflated Poisson Distribution

  • Kim, Kyung-Moo
    • Journal of the Korean Data and Information Science Society
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    • 제15권2호
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    • pp.387-394
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    • 2004
  • Zero-Inflated Poisson distribution is Poisson distribution with excess zeros. Recently defects of product hardley happen in the manufacturing process. In this case it is desirable to apply to the Zero-Inflated Poisson distribution rather than Poisson. Our target of this paper is to study the tests for changes of rate of defects after the unknown change-point. We are going to compare the powers of the two proposed tests with likelihood tests by the simulations.

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Approximation to GPH Distributions and Its Application

  • Baek, Jang-Hyun
    • Journal of the Korean Data and Information Science Society
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    • 제17권3호
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    • pp.687-705
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    • 2006
  • In this paper we consider GPH distribution that is defined as a distribution for sum of random number of random variables following exponential distribution. We establish approximation process of general distributions to GPH distributions and offer numerical results for various cases to show the accuracy of the approximation. We also propose analysis method of delay distribution of queueing systems using approximation to GPH distributions and offer numerical results for various queueing systems to show applicability of GPH approximation.

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베이지안 공액 사전분포를 이용한 키워드 데이터 분석 (Keyword Data Analysis Using Bayesian Conjugate Prior Distribution)

  • 전성해
    • 한국콘텐츠학회논문지
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    • 제20권6호
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    • pp.1-8
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    • 2020
  • 빅데이터 분석에서 텍스트 데이터의 활용이 증가하고 있다. 따라서 텍스트 데이터의 분석 기법에 관한 많은 연구가 이루어지고 있다. 본 논문에서는 텍스트 데이터로부터 추출된 키워드 데이터의 분석을 위하여 공액사전분포 기반의 베이지안 학습 방법이 연구된다. 베이지안 통계학은 기존의 데이터에 새로운 데이터가 추가될 때마다 모수를 갱신하는 데이터 학습을 제공하기 때문에 시간에 따라 대용량의 데이터가 생성 및 추가되는 빅데이터 환경에서 효율적인 방법을 제공한다. 제안 방법의 성능과 적용 가능성을 보이기 위하여 실제 특허 빅데이터를 전처리하여 구축된 정형화된 키워드 데이터를 분석하는 사례연구를 수행한다.

Non-Gaussian analysis methods for planing craft motion

  • Somayajula, Abhilash;Falzarano, Jeffrey M.
    • Ocean Systems Engineering
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    • 제4권4호
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    • pp.293-308
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    • 2014
  • Unlike the traditional displacement type vessels, the high speed planing crafts are supported by the lift forces which are highly non-linear. This non-linear phenomenon causes their motions in an irregular seaway to be non-Gaussian. In general, it may not be possible to express the probability distribution of such processes by an analytical formula. Also the process might not be stationary or ergodic in which case the statistical behavior of the motion to be constantly changing with time. Therefore the extreme values of such a process can no longer be calculated using the analytical formulae applicable to Gaussian processes. Since closed form analytical solutions do not exist, recourse is taken to fitting a distribution to the data and estimating the statistical properties of the process from this fitted probability distribution. The peaks over threshold analysis and fitting of the Generalized Pareto Distribution are explored in this paper as an alternative to Weibull, Generalized Gamma and Rayleigh distributions in predicting the short term extreme value of a random process.

미세변동공정관리를 위한 가속수명시험관리도 설계 (Design of ALT Control Chart for Small Process Variation)

  • 김종걸;엄상준
    • 대한안전경영과학회지
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    • 제14권3호
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    • pp.167-174
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    • 2012
  • In the manufacturing process the most widely used $\bar{X}$ chart has been applied to control the process mean. Also, Accelerated Life Test(ALT) is commonly used for efficient assurance of product life in development phases, which can be applied in production reliability acceptance test. When life data has lognormal distribution, through censored ALT design so that censored ALT data has asymptotic normal distribution, $ALT\bar{X}$ control chart integrating $\bar{X}$ chart and ALT procedure could be applied to control the mean of process in the manufacturing process. In the situation that process variation is controlled, $Z_p$ control chart is an effective method for the very small fraction nonconforming of quality characteristic. A simultaneous control scheme with $ALT\bar{X}$ control chart and $Z_p$ control chart is designed for the very small fraction nonconforming of product lifetime.

Investigating Factors Affecting Value Creation and Its Distribution on Company's Performance

  • Ahmad FIRMAN;Muhammad HIDAYAT
    • 유통과학연구
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    • 제21권9호
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    • pp.23-34
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    • 2023
  • Purpose: This study aims to determine the effect of business processes, quality of human resources and organizational culture and its distribution in creating value to achieve competitive advantage. Research Design, Data, and Methodology: Data collection in this study was carried out by distributing questionnaires to 90 employees of Delivery service companies in Makassar City. Partial Least Square (PLS) analysis was used as data analysis. Result: this study indicates that business processes do not directly affect competitive advantage, but business processes will have an effect if they go through the value creation process as an intervening variable, while the quality of human resources and work environment have a direct effect on competitive advantage and have a direct effect on Value creation. The quality of human resources and organizational culture also have an indirect effect on competitive advantage through the value creation process. This research also indicates that value creation has an effect on competitive advantage. Conclusion: Competitive advantage will be realized if organizational processes run well, company management that able to carry out good organizational processes and able to create a conducive organizational culture, will be able to distribute company resources to create value that leads to achieving competitive advantage for companies in the future.