As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

In this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.

In this study, the four tests employed for non-linear dependence which is Engle (1982), McLeod &Li (1983), Tsay (1986), and Hinich & Patterson (1995). To test the null hypothesis that the time series is a serially independent and identical distribution process .The linear structure is removed from the data which is represent the sales of State Company for Electrical Industries, through a pre-whitening model, AR (p) model .From The results for tests to the data is not so clear.

Abstract. Shatt Al-Arab River was the most important tide river in Iraq, it suffered from neglect and lack of maintenance in the past decades. The river embankment is constantly exposed to erosion processes due to several factors, one of the most important of these factors is the movement of water currents due to the tidal energy coming from the Arabian Gulf. In this study, one dimension unsteady-state model was implemented to study river flood capacity simulation by using HEC-RAS (5.0.7) software in Shatt Al Arab River and its tributaries. The data included flow rate, water level records were collected daily from 2018 to 2020 at different stations along the mentioned river and its feeders, additionally, the considered flood discharge data

Hydatid cyst disease is one of the most common diseases in many places in the world. The infection occurs when human and livestock drinking or eating contaminated water and food with eggs of Echinococcus granulosus worm. Surgery is the best solution to eradicate cysts and rapid healing, but it may be accompanied by some risks such as rupture of the cyst and leakage its contents of protoscolices, which leads to the return of infection and spread in the body. Several methods have been used to reduce the risks of surgery, including withdrawal of hydatid fluid and its contents and injection scolicidal substances like ethanol and others. Researchers have recently tested the efficiency of nanoparticles such as selenium, silver, and gold nanoparti

Backgr ound: The transfer of the tibialis posterior tendon to the anterior aspect of the ankle not only replaces the function of the paralyzed muscles, but also removes the deforming force on the medial aspect of the foot. Objecti ves: In this study, we evaluated patients who underwent tibialis posterior tendon transfer for the treatment of foot drop, and comparison through interosseous membrane route versus anterior to lower tibia route of tibialis posterior tendon transfer, with evaluation of the results according to carayon criteria Methods: Nine patients with foot drop secondary to different causes treated with tibialis posterior tendon transfer from January 2011 to January 2012 were followed up for a mean of 12 months in Al Kindy Teach

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and