Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

      In this research, a variable stiffness actuator is proposed to enhance the damping of the mechanical vibrating system. The frequency response analysis of the vibrating system is dependant in order to analyze and synthesis this semi-active damping, where the suggested process is using active filter to estimate the present frequency of the vibration system, and this will limit the value of the stiffness of the vibrated system. Two active filter s are needed, low-pass-filter (LPF) to choose the higher stiffness of the actuator at small frequencies as well as more damping and high-pass-filter (HPF) to choose the lower stiffness of the actuator at high frequencies as well as more damping, and so

Through this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model

In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

 A simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators

Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and

Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

To maintain a sustained competitive position in the contemporary environment of  knowledge  economy,  organizations  as an open social systems must have an ability to learn and know  how to adapt to rapid changes  in a proper fashion so that organizational objectives will be achieved efficiently and effectively.  A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t