• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.25-34
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• 2012

In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.981-998
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• 2012

In this paper, several count data model of travel cost recreation demand with Poisson and negative binominal specification are applied to estimate the value of access to the estuary area of Yeongsan river from visitor survey data. The results show that the negative binomial model that accounts for truncation and overdispersion provides the better goodness-of-fit, and therefore the value per visit(i.e. consumer surplus) is 89,350 won for resident of Jeolla province and 432,526 won for that of other provinces. If don't correct overdispersion by relying on Poisson estimates, the consumer surplus will be underestimated. Whereas the consumer surplus will be overestimated unless correct truncation by using estimates of untruncated models. As a result, the truncated negative binomial model should be applied to estimate the travel demand and the consumer surplus per visit by using survey data from single site visitors.

• Convergence Security Journal
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• v.12 no.1
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• pp.9-16
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• 2012

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

• International Journal of Contents
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• v.2 no.2
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• pp.17-24
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• 2006

The work presented in this paper is divided into two parts. The first part presents finite urn problems which generate truncated negative binomial random variables. Some combinatorial identities that arose from the negative binomial sampling and truncated negative binomial sampling are established. These identities are constructed and serve important roles when we deal with these distributions and their characteristics. Other important results including cumulants and moments of the distributions are given in somewhat simple forms. Second, the distributions of the maximum of two chi-square variables and the distributions of the maximum correlated F-variables are then derived within the negative binomial sampling scheme. Although multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information and deeper insight regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of these distributions. We supplement our findings with exact simple computational methods where no interpolations are involved.

• Advances in nano research
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• v.14 no.4
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• pp.375-389
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• 2023

In this study, free vibration analysis of functionally graded (FG) porous truncated conical shell panels reinforced by graphene platelets (GPLs) has been investigated for the first time. Additionally, the effect of three different types of porosity distribution and five different types of GPLs patterns on dynamic response of the shell are also studied. Halpin-Tsai micromechanical model and Voigt's rule are used to determine Young modulus, shear modulus and Poisson's ratio with mass densities of the shell, respectively. The main novelties of present study are: applying 3D elasticity theory and the finite element method in conjunction with Rayleigh-Ritz method to give more accurate results unlike other simplified shell theories, and also presenting a general 3D solution in cylindrical coordinate system that can be used for analyses of different structures such as circular, annular and annular sector plates, cylindrical shells and panels, and conical shells and panels. A convergence study is performed to justify the correctness of the obtained solution and numerical results. The impact of porosity and GPLs patterns, the volume of voids, the weight fraction of graphene nanofillers, semi vertex and span angles of the cone, and various boundary conditions on natural frequencies of the functionally graded panel have been comprehensively studied and discussed. The results show that the most important parameter on dynamic response of FG porous truncated conical panel is the weight fraction of nanofiller and adding 1% weight fraction of nanofiller could increase 57% approximately the amounts of natural frequencies of the shell. Moreover, the porosity distribution has great effect on the value of natural frequency of structure rather than the porosity coefficient.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• Management & Information Systems Review
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• v.33 no.2
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• pp.301-315
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• 2014

The purpose of this study is to estimate the economic value of the Kumjung Mountain, using a Individual Travel Cost Model(ITCM). This paper compares Poisson and negative binomial count data models to measure the tourism demands. Interviewers were instructed to interview only individuals. So the sample was taken in 700. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 60,669 Korean won and the total economic value was estimated to be 252,383 Korean won.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.50-62
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• 2014

The number of traffic accidents has been decreased since 2000; however, the downward trend of crash occurrence has been slower after 2006. A few decades ago, physical improvement projects such as alignment improvement and the installation of safety facilities were usually implemented to decrease the occurrence of traffic accidents, but the effects of physical improvement on safety have been gradually decreased. The main objective of this study is to identify how the drivers' characteristics affect and/or are related to traffic accidents. Most of previous works have focused on revealing the difference of the nature of the drivers between the drivers who have no experience and the drivers with experience of traffic accidents. This study tries to analyze the habitual accidents proneness through a survey of drivers' personalities for drivers who were involved in traffic accidents at least once. As a result, nine personality factors were found to be statistically significant: Neuroticism(N), Lie(L), Psychoticism* Neuroticism(PN), Psychoticism*Lie(PL), Extraversion*Lie(EL), Neuroticism*Lie(NL), Impulsiveness(IMP), Venturesomeness(VEN), Empathy(EMP). Among these factors, single character factors were found to increase accidents, whereas complex factors were found to decrease the occurrence of accidents.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.687-695
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• 2009

The Bayesian multiple change-point estimation has been applied to the daily means of ozone and PM10 data in Seoul for the period 1999. We focus on the detection of multiple change-points in the ozone and PM10 bivariate vectors by evaluating the posterior probabilities and Bayesian information criterion(BIC) using the stochastic approximation Monte Carlo(SAMC) algorithm. The result gives 5 change-points of mean vectors of ozone and PM10, which are related with the seasonal characteristics.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.439-454
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• 2013

This study presents a Bayesian multiple change-point detection approach to segment and classify the observations that no longer come from an initial population after a certain time. Inferences are based on the multiple change-points in a sequence of random variables where the probability distribution changes. Bayesian multiple change-point estimation is classifies each observation into a segment. We use a truncated Poisson distribution for the number of change-points and conjugate prior for the exponential family distributions. The Bayesian method can lead the unsupervised classification of discrete, continuous variables and multivariate vectors based on latent class models; therefore, the solution for change-points corresponds to the stochastic partitions of observed data. We demonstrate segmentation with real data.