Laser shock peening (LSP) is deemed as a deep-rooted technology for stimulating compressive residual stresses below the surface of metallic elements. As a result, fatigue lifespan is improved, and the substance properties become further resistant to wear and corrosion. The LSP provides more unfailing surface treatment and a potential decrease in microstructural damage. Laser shock peening is a well-organized method measured up to the mechanical shoot peening. This kind of surface handling can be fulfilled via an intense laser pulse focused on a substantial surface in extremely shorter intervals. In this work, Hydrofluoric Acid (HF) and pure water as a coating layer were utilized as a new technique to improve the properti

The first section of this research discussed  the manner of the research from many sides like the problem it faces, importance of it , its targets ,boundaries, the way to collect and get information's and its assumption.

When the second chapter discussed the press – manufacturing and the development ,importance and types of newspapers, also its merits and weaknesses.

The third chapter talked about the scientific side and how to choose an assumption for the research . as it talked also about the apparent honest and stability tests that help in analyzing the research until getting results and so the right assumption for  the research will be chosen.

And finally, the fourth chapter put highlight on the be

Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

      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

Propranolol is a nonselective-adrenergic blocker used in the treatment of hypertension, cardiac arrhythmias, and angina pectoris. A significant problem in propranolol therapy is that it undergoes extensive presystemic metabolism after oral administration leading to reduced bioavailability. In this study, two new propranolol derivatives have been designed, synthesized and characterized. These compounds were formed by acylation of propranolol followed by nucleophilic substitution reaction of acylated propranolol, these derivatives were analyzed for IR, CHN, melting points, and evaluated for their lipophilic properties compared with propranolol. The lower partition coefficient of these two derivatives revealed that the prodrug approach may be