The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the purposes of assessment and estimating and fitting, this along with the use of the classical method. It was to identify the best estimation method through the use of a of comparison criteria: Root of Mean Square Error: RMSE, and the Mean Absolute Percentage Error: MAPE. Sample sizes were selected as (n = 18, 30, 50, 81) which represents the size of data generation n = 18 five-year age groups for the phenomenon being studied and the sample size n = 81 age group represents a unilateral, and replicated the experiment (500) times. The results showed the simulation that the Maximum Likelihood method is the best in the case of small and medium-sized samples where it was applied to the data for five-year age groups suffering from disturbances and confusion of Iraq Household socio-Economic survey: IHSES II2012 while entropy method outperformed in the case of large samples where it was applied to age groups monounsaturated resulting from the use of mathematical method lead to results based on the staging equation data (Formula for Interpolation) placed Sprague (Sprague) and these transactions or what is called Sprague transactions (Sprague multipliers) are used to derive the preparation of deaths and the preparation of the population by unilateral age within the age groups a five-year given the use of the death toll and the preparation of the population in this age group and its environs from a five-year categories by using Excel program where the use of age groups monounsaturated data for accuracy not detect any age is in danger of annihilation.
The survival of dried spores of A.flavus, Penicillia Spp., and Cladosporia Spp.inoculated into multivitamins and folic acid tablets were examined at different compression pressures.Survival of fungal spores decreased with increasing compression pressure. The level of survival at particular pressures was shown to depend on the size of the contaminating fungal spores.The lethal effect of tabletting was attributed to shearing forces upon the contaminating spores generated by interparticulate movement. This hypothesis was supported by the dependence of survival upon spore size.
Key words: Fungal spores, microbial contamination.
In this study, we derived the estimation for Reliability of the Exponential distribution based on the Bayesian approach. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .We derived posterior distribution the parameter of the Exponential distribution under four types priors distributions for the scale parameter of the Exponential distribution is: Inverse Chi-square distribution, Inverted Gamma distribution, improper distribution, Non-informative distribution. And the estimators for Reliability is obtained using the two proposed loss function in this study which is based on the natural logarithm for Reliability function .We used simulation technique, to compare the
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In this paper, the single scatter model for gamma backscatter densitometer has been used to investigate the materials of Halley’s nucleus. Monte Carlo simulation tool is used for the evaluation and calibration of gamma backscatter densitometer; and also used to calculate the bulk density. A set of parameters effecting detected count rate of γ – ray backscattering, mainly the source energy, the source – detector separation (sonde length), density and composition, were calculated.
Results obtained with the present method are compared with experimental data and the computed data may be considered entirely satisfactory.
The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.
Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreIn this work we study gamma modules which are implying full stability or implying by full stability. A gamma module is fully stable if for each gamma submodule of and each homomorphism of into . Many properties and characterizations of these classes of gamma modules are considered. We extend some results from the module to the gamma module theories.
(1)
Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)
This research is concerned with designing and simulating an auto control system for a car provided with obstacle avoidance sensors. This car is able to pass through predefined path an around the detected obstacles, and then come back to the intended path. The IR sensor detects the existence of the obstacle through an assumed range of detection, while the visual sensor (camera) feeds back an image including the path that contains an obstacle, which can be useful for determining the obstacle's length, speed, and direction. According to such information, the controller creates transient away point along the longitudinal axis of the obstacle which is the same as the transverse axis of the simulator path at an assumed distance from the
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