The current research aims to :
•know the level of the chaotic behavior of the sample as a whole .
•Know the differences with statistical significance in disorderly behavior between the
disadvantaged and non-disadvantaged peers .
To achieve these objectives, the selected sample of Talbhalmrahlh medium and specifically
students of the second grade average, were chosen randomly stratified's (360) students
included sex (male, female) and (deprived of the Father and the non-deprived) for the
academic year (2013-2014) to the province Baghdad on both sides (Rusafa-Karkh (
As applied to them measurements of disorderly behavior, which is prepared by the researcher,
having achieved _khasaúsma of psychometric (valid and reliable .)
When analyzing the data were used statistical methods, both when extracting multiple
psychometric properties, crashes or achieve the objectives of the research, including (Pearson
correlation coefficient, and the equation Alvakronbach and samples t-test for one sample and
samples t-test for two independent samples .
The researcher found the following results :
•When members of the research sample behavior messy low .
•The existence of statistically significant differences in disorderly behavior among
adolescents deprived of their parents and their peers who live with their parents, and for thebenefit of disadvantaged parents, that is deprived of parents is more chaotic behavior of
children deprived of others .
In light of the findings of the researcher made a number of recommendations and suggestions .
Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
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