Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

This study seeks to address the impact of marketing knowledge dimensions (product, price, promotion, distribution) on the organizational performance in relation to a number of variables which are (efficiency, effectiveness, market share, customer satisfaction), and seeks to reveal the role of marketing knowledge in organizational performance.

In order to achieve the objective of the study the researcher has adopted a hypothetical model that reflects the logical relationships between the variables of the study. In order to reveal the nature of these relationships, several hypotheses have been presented as tentative solutions and this study seeks to verify the validity of these hypotheses.

In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.

     The General Company for Iraqi Cement is regarded as one of the companies that contribute to support the Iraqi economy. It contributes to provide the material of cement which fulfils the consumer and investment need in the markets in competitive prices and not to resort to the importing of the cement from abroad. That would save a great share of the purchase parity of the poor sectors of society. The estimation  of production function will contribute to putting the company.

The application functions of  the standard production of  benefit critical to clarify the actual relationship between production & its components, & allow to clarify the i

With the aim of developing potential antimicrobials, a series of new 5-fluoroisatin derivatives incorporated with different secondary amines (piperidine, morpholine, pyrrolidine, dimethylamine, and diphenylamine) for monomer, and (piperazine) in case of dimer Mannich bases, separately in presence of formaldehyde to obtain Mannich bases of 5-fluoroisatin derivatives, which then each Mannich derivatives reacts with phenylhydrazine to form Schiff bases as final products. The resulting compounds were characterized by two spectroscopic analyses; (Fourier- transform infrared) FT-IR and proton nuclear magnetic resonance spectroscopy (¹H-NMR). In addition, the in vitro antibacterial and antifungal activities were tested against some human pathogen

In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

Here, a high sensitive method for biomarker identification according to nanostructure, using enzyme-linked immunosorbent assays (ELISAs), called Nano-ELISA, was presented. Different shapes of gold nanostructures (star and sphere; GNSs and GNPs) with a particle size of 40 nm for sphere particles were altered with a monoclonal antibody (Ab) as a detector Ab. To amplify the optical signal, gold nanostructures were employed as carriers of the signaling specific antibody against insulin growth factor binding protein- 3 (IGFBP-3). The substrate was catalytically oxidized by the Horseradish Peroxidase (HRP) conjugated gold nanostructure, and HRP also enhanced the optical signals, reflecting the amount of the targeting IGFBP-3. In comparison to t

             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo