• The Plant Pathology Journal
• /
• v.26 no.1
• /
• pp.17-24
• /
• 2010

A logistic model for describing combined effects of both temperature and wetness period on appressorium formation was developed using laboratory data on percent appressorium formation of Colletotrichum acutatum. In addition, the possible use of the logistic model for forecasting infection risks was also evaluated as compared with a first-order linear model. A simplified equilibrium model for enzymatic reactions was applied to obtain a temperature function for asymptote parameter (A) of logistic model. For the position (B) and the rate (k) parameters, a reciprocal model was used to calculate the respective temperature functions. The nonlinear logistic model described successfully the response of appressorium formation to the combined effects of temperature and wetness period. Especially the temperature function for asymptote parameter A reflected the response of upper limit of appressorium formation to temperature, which showed the typical temperature response of enzymatic reactions in the cells. By having both temperature and wetness period as independent variables, the nonlinear logistic model can be used to determine the length of wetness periods required for certain levels of appressorium formation under different temperature conditions. The infection model derived from the nonlinear logistic model can be used to calculate infection risks using hourly temperature and wetness period data monitored by automated weather stations in the fields. Compared with the nonlinear infection model, the linear infection model always predicted a shorter wetness period for appressorium formation, and resulted in significantly under- and over-estimation of response at low and high temperatures, respectively.

• Journal of the Korean Statistical Society
• /
• v.13 no.1
• /
• pp.48-56
• /
• 1984

This paper considers one-sample and two-sample test for the logistic function by means of Kolmororov-Smirnov type statistics. The standard tables used for the Kolmogorov-Smirnov test are valid only when the function is completely specified; but they are not valid if the parameters of function are estimated from the sample. This note presents modified tables for the Kolmogorov-Sminov type staistic. These tables can be used to test the hypothesis that a sample comes from a logistic function when shape parameter $(\alpha)$ and location parameter $(\beta)$ must be estimated from the sample by the method of maximum likelihood. Monte Carlo method is employed to calculate the criticla values of the test. The tables of the critical values are provided.

• Journal of Information Technology Applications and Management
• /
• v.12 no.2
• /
• pp.1-13
• /
• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.1
• /
• pp.119-129
• /
• 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.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.17 no.32
• /
• pp.163-175
• /
• 1994

This paper is to establish rational logistic system practical study between korea and Japan. In this paper the five logistic function of korea business are classified and investigated and analyzed. And two, i.e., strategic and tactic, aspects of logistic system between two nations are compared with each other through practical study Finally this Paper Proposes a integrated logistic system exploiting the strength of both nations.

• Convergence Security Journal
• /
• v.11 no.4
• /
• pp.85-91
• /
• 2011

Due to the large-scale application software syslmls, software reliability, software development has animportantrole. In this paper, software truncated software reliability growth model was proposed based on log-logistic distribution. According to fixed time, the intensity function, the mean value function, the reliability was estimated and the parameter estimation used to maximum likelihood. In the empirical analysis, Poisson execution time model of the existiog model in this area and the log-logistic model were compared Because log-logistic model is more efficient in tems of reliability, in this area, the log-logistic model as an alternative 1D the existiog model also were able to confim that you can use.

• Communications for Statistical Applications and Methods
• /
• v.27 no.1
• /
• pp.47-64
• /
• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• Journal of Korean Institute of Industrial Engineers
• /
• v.29 no.3
• /
• pp.239-246
• /
• 2003

Individual items are produced continuously from an industrial process. Each item is checked to determine whether it satisfies a lower screening limit for the quality characteristic which is the weight of an expensive ingredient. If it does, it is sold at a regular price; if it does not, it is reprocessed or sold at a reduced price. The process mean may be adjusted to a higher value in order to reduce the proportion of the nonconforming items. Using a higher process mean, however, may result in a higher production cost. In this paper, the optimal process mean and lower screening limit are determined in situations where the probability that an item functions well is given by a logistic function of the quality characteristic. Profit models are constructed which involve four price/cost components; selling prices, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal process mean and lower screening limit are presented and numerical examples are given.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1565-1571
• /
• 2017

The standard logistic map is an iterative function, which forms a discrete-time dynamic system. The chaotic logistic map is a kind of ergodic map defined over the unit interval. In this paper we study the limiting behaviors on the several processes induced by the chaotic logistic map. We derive the law of large numbers for the process induced by the chaotic logistic map. We also derive the uniform law of large numbers for this process. When deriving the uniform law of large numbers, we study the role of bracketing of the indexed class of functions associated with the process. Then we apply the idea of DeHardt (1971) associated with the bracketing method to the process induced by the logistic map. We finally illustrate an application to Monte Carlo integration.

• Journal of the Korean Society of Systems Engineering
• /
• v.1 no.2
• /
• pp.34-42
• /
• 2005

Logistic Support Analysis(LSA) and Logistic Supportability Review must be carried out as soon as possible in development stage in order to minimize operation/maintenance cost that head the list of weapon cost and improve logistic supportability of the weapon system. And the result must be used for hardware designs to set up to be able to input to the system design and logistic support elements. Therefore Logistic Support Elements must be planed/developed/supplied with the main combat system concurrently and performance and logistic supportability of the comabat system had better be improved mutually. This report describes maintenance concept changes of weapon systems, fault diagnosis function and test equipment state on the domestic MBT(main battle tank). And then it presents application and intensification of itself fault diagnosis system for a domestic future MBT considering connection with IETM(Interactive Electronic Technical Manual) and TE(Test Equipment).