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

Recently, new generalizations have been presented for the hyponormal operators, which are (N, k)-hyponormal operators and (h, M)-hyponormal operators. Some properties of these concepts have also been proved, one of these properties is that the product of two (N, k)-hyponormal operator is also (N, k)- hyponormal operator and the product of two (h, M)-hyponormal operators is (h, M)-hyponormal operator. In our research, we will reprove these properties by using the (l,m)-commuting operator equations, in addition to that we will solve the (l, m)-commuting operator equations for (N, k)-hyponormal operators and (h, M)-hyponormal operators.

This research represents a reflection seismic study (structural and stratigraphic) for a (852) km2 area located in the south of Iraq within the administrative border of the province of Al-Muthanna and Qadisiyah province ,by using 2-D seismic data from Oil Exploration company three main seismic reflectors are picked, these are (Zubair and Yamama) Formations which they deposited during the Cretaceous age , and (Gotnia) Formation which deposited during Jurassic age .Structural maps of Formations are prepared to obtain the location and direction of the sedimentary basin and shoreline ,time, velocity and depth maps are drawn depending on the structural interpretation of the picked reflectors and show several structural feature as nose structu

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

The thermal maturity ,  burial history and petroleum generation history of  four oil wells selected  from four oil fields in Southern Iraq, they are: Nasiriyah(Ns-1 well) , Gharraf (GA-5well) ,Abu Ammood (Ab-1well) and Riffai (Ri-1well) have been studied using 1D basin and petroleum systems modeling. Results showed  different period of subsidence, which ranges from high to moderate subsidence, occurred at upper Jurassic to Mid-Cretaceous and slow subsidence in Miocene  . The porosity in the studied area represents the highest value in Dammam , Tayarat ,Um-Eradhuma and Khasib Formations. For most of the studied wells, the Paleocene to Miocene has to be regarded as times when the maximum temperature prevailed assoc

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

This paper deals with the problem of the mechanics of the operation of cinematography in the development of museum exhibition halls. In the first chapter, the researcher dealt with the problem and presented it to reach the goals and purpose of the research, which was represented in using and developing the methods and mechanisms of the presentation to keep pace with what is happening in the world of technology and access to the presented model to new formula and vision declares aesthetical and cognitive measure, thus the search constitutes an importance in absorbing Scenography dimensions in the theater and moved to the idea of the museum and the development of the display models and using them in drawing and representation of perception

In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

    Current study was carried out to determine the adsorption ability of the Multiwall carbon nanotubes (MWCNTs) by adsorption Malachite Green dye from an aqueous solution. Crystal structure of the materials was measured using powder X-rays diffraction (PXRD), UV–Vis diffuse reflectance and specific surface area (BET). Many parameters that affecting the adsorption process such as contact time, pH, adsorbent dosage, initial dye concentration and temperature were studied. The outcome showed that an increasing occurred in the adsorbent dosage and the rate of dye removal, and the best efficiency for Malachite Green dye removal was amounted 99. 11 %. The results were obtained at optimal reaction conditions were pH = 5.5, cata