The aim of this work is studying many concepts of a pure submodule related to sub-module L and introducing the two concepts, T_pure submodule related to submodule and the crossing property of T_pure related to submodule. Another characterizations and study some properties of this concept.
Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in pr
In this study, the investigation of flavorings used in 567 model of local food products and imported in our local markets through information contents cards media shoddy standard Iraqi has been found that foods that appeal to children of sugar confectionery and Crapt and other barely Atkhalo of flavorings used that lead tohealth risks
This study objective is to identify the visual pollution in Karrada district main streets as an example of main streets in Baghdad, the public opinion about each pollutants, solutions to reduce and eliminate the pollution were suggested as well. In order to accomplish this objective different methods were used, 16 pollutants were selected, pictures of each pollutants were taken and a questioner were distributed randomly for 270 people to evaluate the public opinion with statistical methods. Garbage, their disposal and storage areas took the first two places as the highest offensive pollutants. The people showed that they find long lines of vehicles, debris and generators appearance ranked third, fourth and fifth respectively .This resear
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
... Show MoreThis study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas
... Show MoreMaulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the method To address a problem and method To address a problem , In this research a comparisons are employed between the biased method and unbiased method with Bayesian using Gamma distribution method addition to Ordinary Least Square metho
... Show MoreAs 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 .
... Show MoreThe specimens of Camponotusxerxes Forel, 1904 were collected from different localities in Iraq; the purpose of morphological study of this species in details throughout the present study.
The description was based on major workers belonging to this species, also some notes of polymorphism in workers have been mentioned; the most important of morphological features are illustrated and figured.