In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

The research aims to identify the tax policy strategy adopted in Iraq after the change of the tax system in 2003 and beyond, and then make a comparison of the two strategies on corporate data whether they are charged with progressive tax rates and after the change of the system as the tax rates became fixed, and then indicate the changes In the tax proceeds, and knowing the dimensions of the approved tax policy, is it a tax reform strategy or a strategy to attract investments.

The research started from the problem of exposure of the Iraqi tax system to several changes in the tax strategy from 2003 until now, as this led to a reflection on the technical organization of taxes, in terms of the tax exemption.And these many amendments

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

The main idea of this paper is to define other types of a fuzzy local function and study the advantages and differences between them in addition to discussing some definitions of finding new fuzzy topologies. Also in this research, a new type of fuzzy closure has been defined, where the relation between the new type and different types of fuzzy local function has been studied

Abstract. This work presents a detailed design of a three-jointed tendon-driven robot finger with a cam/pulleys transmission and joint Variable Stiffness Actuator (VSA). The finger motion configuration is obtained by deriving the cam/pulleys transmission profile as a mathematical solution that is then implemented to achieve contact force isotropy on the phalanges. A VSA is proposed, in which three VSAs are designed to act as a muscle in joint space to provide firm grasping. As a mechatronic approach, a suitable type and number of force sensors and actuators are designed to sense the touch, actuate the finger, and tune the VSAs. The torque of the VSAs is controlled utilizing a designed Multi Input Multi Output (MIMO) fuzzy controll

In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi