Abstract

 This study is aim to :

• Put a standard to evaluate the altruistic behavior in kindergarten children.
• Know level of the altruistic behavior in the kindergarten children according to their mother "s points of view.
• Know the level of the altruistic behavior in the kindergarten children according to their teacher "s points of view.
• The differences in the level of altruistic behavior in kindergarten children between their mothers & teachers points of view.

      The sample consists of (120) children of kindergarten children in Baghdad. The researcher has built a to

In this research study failed Annunciation No. 10 for the fourth phase of the pressure of carbon dioxide of the company for Southern Fertilizers and repeated the failures more than once for the same gospel was a detailed study of the gospel included a series tests for properties Mechanical and Structural addition to the tests microscopic and scanning electron microscope shows m This study parameters and a failure Elal well as the existence of an old internal cracks in the metal of the Annunciation

this paper presents a novel method for solving nonlinear optimal conrol problems of regular type via its equivalent two points boundary value problems using the non-classical

Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy. Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when appropriate, was

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe