Optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. Though currently optimization is an interdisciplinary subject cutting through the boundaries of mathematics, economics, engineering, natural sciences, and many other fields of human Endeavour it had its root in antiquity. In modern day language the problem mathematically is as follows - Among all closed curves of a given length find the one that closes maximum area. This is called the Isoperimetric problem. This problem is now mentioned in a regular fashion in any course in the Calculus of Variations. However, most problems of antiquity came from geometry and since there were no general methods to solve such problems, each one of them was solved by very different approaches.
In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.
Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st
... Show MoreIn this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less
... Show MoreCompetencies topic in general , and Administrative competencies in specific, are considered as important subject in the contemporary administrative literature in all countries as well as in public and privet Organizations. For this reason, we have need to study those competencies in many Iraqi Organizations.
Two Organizations wer chosen for this research one of them is the Institution of taxation, and the other is the General company of Electric the data and information related to the research have been collected by desined questioner which has been given to a sample of (50) persions divided eqully between the two maintioned organizations.
The results of the study had differences
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Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
... Show MoreIn this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da
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