In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

In dental and medical applications, poly-methyl methacrylate (PMMA) has been widely accepted due to the excellent biocompatibility and easy fabrication. Yet, some of the physical and mechanical characteristics of this compound are considered inferior. Seven groups of PMMA nano-composite samples were reported to be fabricated at laboratory temperature . These samples could be used in manufacturing the complete or partial maxillary denture base. The aim of this research is to prepare nano-composite materials which consist of PMMA as a matrix material and two different types of powder (prepared nanoparticles of SnO₂ and natural egg shell powder (ESP)) as strengthening materials. The selected additives were used in many cases as p

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

This study includes a palynological and organic geochemical evaluation of Nahr Umr, Zubair, and Yamama Formations in the Subba field, Southern Iraq, represented by three wells (Su-14, Su-9 and Su-8). The determination of quantity organic matter showed that the rocks of Nahr Umr Formation had a total organic carbon of 4.76%, indicating very good production of hydrocarbons where type (II) kerogen was dominant, but the rocks were thermally immature. Zubair Formation had a total organic carbon of 1.91% to 2.26%, indicating good to very good production of hydrocarbons where kerogen of types (I) and (II/III) were dominant, with low thermal maturity. Yamama Formation showed a total organic carbon of 1.68%, revealing good production of hydrocarb

Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.

    Three bacterial species were isolated from three polluted soils with gasoline which leaks from electricity generators that used in different regions in Baghdad; the regions choices to collect the polluted soils were (Al-Shaab, Al- Jadryia and Al-Saydiya).     The bacterial species were identified according to international biochemical   methods. It was found that these species were Escherichia coli, Enterobacter    aerogenes and serratia marcesens.      It was found that the optimum temperature and pH were 37C°and 9 these were to cultivate E.coli and S.marcesens, while for   E.aerogenes   were 25 C° and   9. &

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

The  purpose  of  the  paper  is  to  tind  the  degree  of  the approximation of a functions  f be bounded , measurable and defined

in  interval   [a,h]by  Bernstein  polynomial  in  LP    space  1 $ p < oo by

using Ditzian-Totik modulus  of smootlmess  and  k 1n  average modvlus of smoothness.

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe