• 융합보안논문지
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• 제11권4호
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• pp.85-91
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• 2011

소프트웨어 시스템의 대규모 응용 프로그램으로 인해, 소프트웨어 신뢰성은 소프트웨어 개발에서 중요한 역할올 담당하고 있다. 본 연구에서는 소프트웨어 신뢰성장 모형 중에서 고장 시간 절단 모형인 로그 로지스틱 분포에 근거한 모형이 제안되었다 고정시간에 따른 강도함수, 평균값함수, 신뢰도를 추정하였고 모수 추정은 최우 추정 법을 사용하였다. 실중분석에서는 이 분야에서 기본 모형인 포아송 실행 시간 모형과 비교 분석하였다. 그 결과 로그-로지스틱 모형이 기존의 로그 포아송 실행 시간 모형보다 신뢰성 측면에서 더 효율적이기 때문에 이 분야에서 기존 모형의 대안으로 로그-로지스틱모형을 사용할 수 있음을 확인 할 수 있었다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.323-330
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• 2016

Purpose: Recently, propensity score matching method is used in a large number of research paper, nonetheless, there is no research using fitness test of before and after propensity score matching. Therefore, comparing fitness of before and after propensity score matching by logistic regression analysis using data from 'online survey of adolescent health' is the main significance of this research. Method: Data that has similar propensity in two groups is extracted by using propensity score matching then implement logistic regression analysis on before and after matching separately. Results: To test fitness of logistic regression analysis model, we use Model summary, -2Log Likelihood and Hosmer-Lomeshow methods. As a result, it is confirmed that the data after matching is more suitable for logistic regression analysis than data before matching. Conclusion: Therefore, better result which has appropriate fitness will be shown by using propensity score matching shows better result which has better fitness.

• Journal of Biosystems Engineering
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• 제29권5호
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• pp.441-450
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• 2004

This study was performed to estimate mid and long term demands of a tractor, a rice transplanter, a combine and a grain dryer by using logistic curve function and Markov chain model. Field survey was done to decide some parameters far logistic curve function and Markov chain model. Ceiling values of tractor and combine fer logistic curve function analysis were 209,280 and 85,607 respectively. Based on logistic curve function analysis, total number of tractors increased slightly during the period analysed. New demand for combine was found to be zero. Markov chain analysis was carried out with 2 scenarios. With the scenario 1(rice price $10\%$ down and current supporting policy by government), new demand for tractor was decreased gradually up to 700 unit in the year 2012. For combine, new demand was zero. Regardless of scenarios, the replacement demand was increased slightly after 2003. After then, the replacement demand is decreased after the certain time. Two analysis of logistic owe function and Markov chain model showed the similar trend in increase and decrease for total number of tractors and combines. However, the difference in numbers of tractors and combines between the results from 2 analysis got bigger as the time passed.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.707-712
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• 2015

Background: To evaluate use of magnetic resonance imaging (MRI) and a logistic model including risk factors for lymph node metastasis for improved diagnosis. Materials and Methods: The subjects were 176 patients with rectal cancer who underwent preoperative MRI. The longest lymph node diameter was measured and a cut-off value for positive lymph node metastasis was established based on a receiver operating characteristic (ROC) curve. A logistic model was constructed based on MRI findings and risk factors for lymph node metastasis extracted from logistic-regression analysis. The diagnostic capabilities of MRI alone and those of the logistic model were compared using the area under the curve (AUC) of the ROC curve. Results: The cut-off value was a diameter of 5.47 mm. Diagnosis using MRI had an accuracy of 65.9%, sensitivity 73.5%, specificity 61.3%, positive predictive value (PPV) 62.9%, and negative predictive value (NPV) 72.2% [AUC: 0.6739 (95%CI: 0.6016-0.7388)]. Age (<59) (p=0.0163), pT (T3+T4) (p=0.0001), and BMI (<23.5) (p=0.0003) were extracted as independent risk factors for lymph node metastasis. Diagnosis using MRI with the logistic model had an accuracy of 75.0%, sensitivity 72.3%, specificity 77.4%, PPV 74.1%, and NPV 75.8% [AUC: 0.7853 (95%CI: 0.7098-0.8454)], showing a significantly improved diagnostic capacity using the logistic model (p=0.0002). Conclusions: A logistic model including risk factors for lymph node metastasis can improve the accuracy of MRI diagnosis of rectal cancer.

• 품질경영학회지
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• 제26권3호
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• pp.130-140
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• 1998

Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.783-791
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• 2008

Estimation procedure of the finite population proportion and distribution function is considered. Based on a logistic regression model, an approximately model- optimal estimator is defined and conditions for the estimator to be design-consistent are given. Simulation study shows that the model-optimal design-consistent estimator defined under a logistic regression model performs well in estimating the finite population distribution function.

• Journal of the Korean Data and Information Science Society
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• 제14권1호
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• pp.119-129
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• 2003

We propose a new logistic regression model of normality curves for normal(diseased) and abnormal(nondiseased) classifications by neural networks in data mining. The fitted logistic regression lines are estimated, interpreted and plotted by the neural network technique. A few goodness-of-fit test statistics for normality are discussed and the performances by the fitted logistic regression lines are conducted.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.1-10
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• 2013

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. In the course of correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and was proposed release policies of the life distribution, half-logistic and log-logistic distributions model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameter estimation using maximum likelihood estimation of failure time data make out, and software optimal release time was estimated.

• 대한산업공학회지
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• 제28권3호
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• pp.240-246
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• 2002

In this paper, economic screening procedures with dichotomous performance variable T and continuous screening variable X are considered when the rejected items are reprocessed. Two models are considered; normal and logistic models. It is assumed that X given T is normally distributed in the normal model, and P(T=1|X=x) is given by a logistic function in the logistic model. Profit models are constructed which involve four price/cost components; selling price, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal screening procedures are presented and numerical examples are given.

• 한국식물병리학회지
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• 제14권4호
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• pp.331-338
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• 1998

To develop the model for prediction of potato late blight progress, the relationship between severity index of potato late blight transformed by the logit and Gompit transformation function and cumulative severity value (CSV) processing weather data during growing period in Taegwallyeong alpine area, 1975 to 1992 were examined. When logistic model and Gompertz model were compared by determining goodness of fit for progressive degree of late blight using CSV as independent variable, the coefficients of determination were higher as 0.742 in the logistic model than 0.680 in the Gompertz model. Parameters in logistic model were composed of progressive rate and initial value of logistic model. Initial value was calculated in -3.664. The progressive rate of potato late blight was 0.137 in cv. Superior, 0.136 in cv. Irish Cobbler, and 0.070 in cv. Jopung without fungicide sprays. According to in crease of the number of spray times the progressive rate was lowered, was 0.020 in cv. Superior under the conventional program of fungicide sprays, 10 times sprays during cropping season. Equation of progressive rate, b1=0.0088 ACSV-0.033 (R2=0.976), was written by examining the relationship between the parameters of progressive rate of late blight and the average CSV (ACSV) quantifing weather information. By estimating parameters of logistic function, model able to describe the late blight progress of potato, cv. Superior was formulated in Y=4/(1+39.0·exp((0.0088 ACSV-0.033)·CSV).