• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.11-18
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• 2010

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 vibration signal of the shaving process using beta probability distribution in order to extract the effective features for TCM. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating the parameters of beta probability distribution based on method of moments. The performance of features obtained from the proposed method was evaluated and discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.95-106
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• 1983

The probability of failure is used to analyze the reliability of three dimensional slope failure, instead of conventional factor of safety. The strength parameters are assumed to be normal variated and beta variated. These are interval estimated under the specified confidence level and maximum likelihood estimation. The pseudonormal and beta random variables are generated using the uniform probability transformation method according to central limit theorem and rejection method. By means of a Monte-Carlo Simulation, the probability of failure is defined as; $$P_f$$=M/N N: Total number of trials M: Total number of failures some of the conclusions derived from the case study include; 1. If the strength parameters are assumed to be normal variated, the relationship between safety factor and the probability of failure is fairly consistent, regardless of the procedures of analysis and dimensions of assumed rupture surfaces. 2. However if the strength parameters are beta variated, general relationship between $F_s$ and $P_f$ is hardly found.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.75-83
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• 1984

The probability of failure is used to analyze the reliability of three dimensional slope failure, instead of conventional factor of safety. The strength parameters are assumed to be normal variated and beta variated. These are interval estimated under the specified confidence level and maximum likelihood estimation. The pseudonormal and beta random variables are generated using the uniform probability transformation method according to central limit theorem and rejection method. By means of a Monte-Carlo Simulation, the probability of failure is defined as; $P_f=M/N$ N: Total number of trials M: Total number of failures Some of the conclusions derived. from the case study include; 1. Three dimensional factors of safety are generally much higher than 2-D factors of safety. However situations appear to exist where the 3-D factor of safety can be lower than the 2-D factor of safety. 2. The $F_3/F_2$ ratio appears to be quite sensitive to c and ${\phi}$ and to the shape of the 3-D shear surface and the slope but not to be to the unit weight of soil. 3. From the two models (normal, beta) considered for the distribution of the factor of safety, the beta distribution generally provides lager than normal distribution. 4. Results obtained using the beta and normal models are presented in a nomgraph relating slope height and slop angle to probability of failure.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.157-164
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• 1994

본 연구에서는 확률화응답기법을 이용하여 모집단내의 민감집단의 비율을 추정함에 있어 조사의 효율성을 높이기 위한 층화표본의 최적할당방법을 제안한다. 확률화응답기법은 Warner(1965)에 의하여 제안된 방법으로 민감한 사안에 대한 조사시 무응답이나 거짓응답으로 인한 비표본오차를 줄일수 있는 기법으로 간접질문에 의한 조사방법이다. 여기에서 최적할당이란 베이즈위험을 최소로 하는 할당법을 의미하며, 이 과정에서 민감집단의 모비율에 대한 사전분포로는 베타분포를 취하였다.

• 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.

• 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.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2841-2852
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• 2018

This study examines regression modeling method using zero-inflated distribution in relation to estimation of exposure distribution required in advertisement media planning. Exposure distribution is the percentage of audiences that are exposed each time the ad is repeated. Such an exposure distribution plays a very important role in providing basic information necessary for calculating various indicators for quantitatively measuring the advertising effect. Especially, due to the decrease of advertising price and the spread of various media, the frequency of the advertisement or the broadcasting of specific advertisements has been greatly increased compared to the past. As a result, the frequency of exposure is relatively decreasing. In this situation, the number of individuals who are not exposed to the media, that is, are not exposed to advertising structurally is increasing. This research proposes advertising exposure distribution models using a zero-inflated regression model, and conducts a comparative study using actual cases.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.3
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• pp.183-189
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• 2013

In this paper, uncertainties and failure criteria of structure are mathematically expressed by random variables and a limit state equation. A limit state equation is approximated by Fleishman's 3rd order polynomials and the theoretical moments of an approximated limit state equation are calculated. Fleishman introduced a 3rd order polynomial in terms of only standard normal distiribution random variables. But, in this paper, Fleishman's polynomial is extended to various random variables including beta, gamma, uniform distributions. Cumulants and a normalized limit state equation are used to calculate a theoretical moments of a limit state equation. A cumulative distribution function of a normalized limit state equation is approximated by a Pearson system.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.14-14
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• 2020

일반적으로 수문빈도해석은 치수계획 수립에 이용되는 설계강수량, 계획홍수량 등을 산정하기 위해 연최대치계열 또는 연초과치계열 자료를 이용한 극치빈도해석을 수행하고, 확률분포의 우측꼬리(right tail) 부분을 이용하여 확장된 재현기간에 해당하는 확률수문량을 추정한다. 하지만 가뭄 관련 분석에서는 확률분포의 좌측꼬리(left tail) 부분은 이용해 확장된 재현기간별 확률수문량을 추정해야할 경우가 발생한다. 또한 물관리 실무에서 장 단기 운영계획 수립을 위해 이용하는 갈수빈도 유입량 산정 등에서도 평년보다 작은 수문량에 대한 빈도해석이 필요한 경우가 있다. 국가 가뭄정보분석센터에서는 기존에 K-water연구원에서 개발한 빈도해석 프로그램인 K-FAT의 분석모듈을 이용해 극소치계열 또는 갈수빈도 유입량 분석에 특화된 가뭄빈도해석 프로그램을 개발하였다. 본 프로그램은 GEV, Gumbel, Weibull 등 14개의 확률분포형을 포함하며, 모멘트법, 최우도법 및 L-모멘트법을 사용하여 매개변수를 추정한다. 적합도 검정의 경우 χ², K-S, CVM, PPCC 및 수정 Anderson-Darling test를 이용하여 다각적인 검정을 할 수 있도록 하였다. 분석을 위한 입력 자료의 경우 사용자가 전처리를 통해 준비한 연최소치계열 등 연도별 시계열자료를 이용할 수 있으며, 일단위 및 월단위의 강수량 또는 댐 유입량 자료를 이용해 사용자가 원하는 기간의 누적강수량, 평균 유입량으로 변환할 수 있는 자료변환 기능을 추가하여 실무 활용성을 높였다. 또한 최적 확률분포 선정을 위해 참고할 수 있도록 AIC(Akaike information criteria)와 BIC(Bayesian information criteria) 분석이 포함되어 있으며, Bootstrap 기법 등을 이용한 불확실성 산정을 통해 추정 값의 신뢰구간을 표시하도록 하였다. 개발된 프로그램은 베타버전 시험배포를 거쳐 가뭄정보포털을 통해 배포할 예정이다.