• Title/Summary/Keyword: 베타분포

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An Analysis on the Data Distribution of Construction Equipment Operations - A Case on Muck Hauling System - (건설 장비 운영 데이터 분포 특성에 관한 연구 - 버력 처리 시스템을 중심으로 -)

  • Seo, Hyeong Beom;Jung, Won Ji;Kim, Kyoungmin;Kim, Kyong Ju
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.661-670
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    • 2006
  • The utilization of simulation has been limited in planning construction process because it is difficult to collect data and build a model using simulation method. This study collects construction operation data and analyzes the characteristics of its distribution. Through the statistical analysis on the empirical data, this study identifies Beta distribution functions is one of the most proper in duplicating the characteristics of construction equipment operation data into a computer simulation. The information obtained in this study can support preparing input data for another simulation.

A BPN model for Web-based Business Process Modeling (웹기반 비즈니스 프로세스 명세를 위한 BPN 모형)

  • 최상수;이강수
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05d
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    • pp.971-976
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    • 2002
  • 최근 대부분의 정보시스템은 웹기반 정보시스템으로 이주하고 있으며 이의 개발과 유지보수시에 '웹 위기' 현상이 발생하고 있다. 이를 해결하기 위한 웹엔지니어링 기술 중 웹기반 비즈니스 프로세스 명세 기술이 필요하다. 따라서 본 논문에서는 웹기반 비즈니스 프로세스 명세를 위한 BPN(Business Process Net) 모형을 제시한다. BPN 모형은 베타분포형 확률 패트리넷이며 수행가능형 Activity Diagram이라 할 수 있다. BPN을 모형화할 때 Use Case 분석을 이용하며, 비즈니스 프로세스의 수행 시간 및 비용적 불확실성은 베타분포를 이용하고 있다. BPN 모형은 XML 기반 비즈니스 프로세스 명세언어를 위한 공통 명세모형으로 이용될 수 있다.

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Measuring Process Capability with Beta Distributions (베타분포의 공정능력 평가)

  • 김진수;김홍준
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.50
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    • pp.281-291
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    • 1999
  • This paper is a brief review of the different procedures that are available for fitting theoretical distributions to data. The use of each technique is illustrated by reference to a distribution system which including the Pearson, Johnson and Burr functions. These functions can be used to calculate percent out of specification. The main objectives of this study are to propose a new methods for estimating a measure of process capability for Beta distributed variable data by using the percentage nonconforming. The comprehensive information for the process can be used to evaluate more accurately process capability.

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A Study on Probability of Failure of Shallow Foundations (얕은 기초의 파괴확률에 관한 연구)

  • Lee, Song;Lim, Byung-Jo;Paik, Young-Shik;Kim, Young-Soo
    • Geotechnical Engineering
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    • v.1 no.1
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    • pp.47-58
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    • 1985
  • A new approach is develped to analyze the reliability of the shallow foundation. The measure of the safety of the structhure is expressed In terms of the probability of failure, instead of the conventional factor of safety. Many uncertainties involved in the deterministic stability anaitsis can be reasouably treated by using the probabilistic approach. Both the soil properties and loads are assumed to be random variables. Accordingly, the capacity and demand are considered to be normal, log-normal, and beta variated. Use is made of Error Propagation Method to investigate the probability of failure. And the relationship is investigated between the probability of failure and the central factor of safety. The results are computer programed and several case studies are performed using developed program.

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Tool condition monitoring using parameters of beta distribution in gear shaving process (기어 세이빙 공정에서 베타 확률 분포를 이용한 공구 상태 검출)

  • Choi, Deok-Ki;Kim, Seong-Jun;Oh, Young-Tak
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1069-1074
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    • 2008
  • Tool condition monitoring (TCM) is crucial for improvement of productivity in manufacturing process. However, TCM techniques have not been applied to monitor tool failure in an industrial gear shaving application. Therefore, this work studied a statistical TCM method for monitoring gear shaving tool condition. The method modeled the shaving process using beta probability distribution in order to extract the effective features. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating parameters of beta probability distribution based on method of moments. The usefulness of features obtained from the proposed method was evaluated and discussed.

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Design of Bayesian Zero-Failure Reliability Demonstration Test and Its Application (베이지안 신뢰성입증시험 설계와 활용)

  • Kwon, Young Il
    • Journal of Applied Reliability
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    • v.13 no.1
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    • pp.1-10
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    • 2013
  • A Bayesian zero-failure reliability demonstration test method for products with exponential lifetime distribution is presented. Beta prior distribution for reliability of a product is used to design the Bayesian test plan and selecting a prior distribution using a prior test information is discussed. A test procedure with zero-failure acceptance criterion is developed that guarantees specified reliability of a product with given confidence level. An example is provided to illustrate the use of the developed Bayesian reliability demonstration test method.

Approximation Method for Failure Rates in a General Event Tree (사건 가지상의 사고율 추정을 위한 근사적인 방법)

  • Yang, Hee Joong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.52
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    • pp.181-189
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    • 1999
  • 사건 가지 상의 파라메터 추정을 위한 베이지안 접근방식이 제시된다. 먼저 일반적인 사건 가지를 따라 발생하는 사고를 예측하기 위한 모형에 대해 설명한다. 이 경우 이론적으로 베이지안 기법을 적용하는 방법에 대해 논하고 실제로 문제를 풀 경우에 발생하는 다차원 수치적분 문제를 다룬다. 감마 분포와 베타분포가 이용될 경우 위 문제를 쉽게 해결할 수 있는 근사적 방법에 대해 연구한다. 또한 사건가지상의 여러 경로가 같은 수준의 사고로 분류 될 수 있는 경우에 대해서도 위와 같은 방법에 관한 연구를 한다. 결과적으로 한 사고율이 여러 개의 파라메터의 함수로 표현되어 다차원의 수치적분이 요구되는 경우 이를 쉽게 해결 할 수 있는 근사적인 방법이 제시되어 베이지안 기법의 적용이 용이해 질 수 있다.

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Relationship between Molecular Structure of Rice Amylopectin and Texture of Cooked Rice (쌀의 아밀로펙틴 분자구조와 밥의 텍스쳐)

  • Kang, Kil-Jin;Kim, Kwan;Kim, Sung-Kon
    • Korean Journal of Food Science and Technology
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    • v.27 no.1
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    • pp.105-111
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    • 1995
  • The relationship betwwen the molecular structure of amylopectin and the texture of cooked rice was investigated using Korean rice [3 varieties of Japonica type and 3 varieties of Tongil type(Japonica-Indica breeding type)]. The molecular structure of rice amylopectin was polymodal and distributed A chain of $\overline{DP}$ 12.4, short B chain of $\overline{DP}$ 20.6, B chain of $\overline{DP}$ 26.3, long B chain of $\overline{DP}$ 45 and super long chain of above $\overline{DP}$ 55. The super long chain of amylopectin was composed of long linear chain with poorly branched chain. Also, the super long chain of amylopectin showed positive correlated with average chain length, inherent viscosity and ${\beta}-amyloysis$ limit$({\%})$, but negative correlated with ${\lambda}max$ of iodine reaction of amylopectin. The structural properties of amylopectin in Japonica type were different from those of amylopectin in Tongil type. In relationship between molecular structure of amylopectin and texture of cooked rice, the average chain length, inherent viscosity, ${\beta}-amyloysis$ limit and super long chain of amylopectin was showed a positive correlation with hardness, but a negative correlation with adhesiveness of cooked rice. The long chain of rice amylopectin is the less, the eating quality of cooled rice was the better. These results suggest that the molecular structure of rice amylopectin could be responsible for the texture of cooked rice.

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

  • Jun, Sunghae
    • The Journal of the Korea Contents Association
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    • v.20 no.6
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    • pp.1-8
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    • 2020
  • The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

Bayesian Algorithms for Evaluation and Prediction of Software Reliability (소프트웨어 신뢰도의 평가와 예측을 위한 베이지안 알고리즘)

  • Park, Man-Gon;Ray
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.1
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    • pp.14-22
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    • 1994
  • This paper proposes two Bayes estimators and their evaluation algorithms of the software reliability at the end testing stage in the Smith's Bayesian software reliability growth model under the data prior distribution BE(a, b), which is more general than uniform distribution, as a class of prior information. We consider both a squared-error loss function and the Harris loss function in the Bayesian estimation procedures. We also compare the MSE performances of the Bayes estimators and their algorithms of software reliability using computer simulations. And we conclude that the Bayes estimator of software reliability under the Harris loss function is more efficient than other estimators in terms of the MSE performances as a is larger and b is smaller, and that the Bayes estimators using the beta prior distribution as a conjugate prior is better than the Bayes estimators under the uniform prior distribution as a noninformative prior when a>b.

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