Research topic: (The Epistemological Foundations for Comparison of Religions by al-Amiri)

The research sought to study the topic with: a descriptive methodology by investigating the components of al-Amiri's approach to the interfaith comparison. And analytical, by showing the applied perception of an objective model in the comparison of religions to answer two questions: What are the cognitive foundations of al-Amiri? And what is his approach to establishing an objective comparison between religions?

The research started by introducing Abu al-Hassan al-Amiri, and then presented four topics: An introduction to al-Amiri's efforts in the interfaith comparison, his knowledge foundations, an applied model

A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus

In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.

Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

      In this study, different methods were used for estimating location parameter  and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment  estimation (ME),and approximation  estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile  as estimation for distribution f

Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries.  In this research, for the segmentation of anatomical structures in medical images three approaches were implemented and compared like (original snake model, distance potential force model and Gradient Vector Flow (GVF) snake model). We used Computed Tomography image (CT) for our experiments.  Our experiments show that original snake model has two problems; first is the limited capture range and the second is the poor convergence. Distance potential force model solved only the first problem of original snake and failed with second problem. Gradient Vector Flow (GVF snake) provides a go

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

The chemical composition of wastes of pressed grapes and found that the main components of wastes of pressed grapes, represented by the percentage of moisture was 6.47%, and the proportions are 3.71%. Either carbohydrates amounted to 85.77 %, either in fat models using petroleum ether Petroleum ether) was the increase of 0.27%. estimated the percentage of ash in the sampls was 3.78%, either fiber reached 69.47 %,, in addition to the test extracts towards the growth of seven types of bacteria, which included Bacillus subtilis, Bacillus cereus, Bacillus stearothermophilus, Escherishia coli, Staphylococcus aureus, Salmonella typhimurium and Pseudomonas fluorescens and yeast Candida albicans and Kluyveromyces marxianus, ( diffusion method ).