A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

This research aims at measuring the relationship between moral intelligence and academic adjustment for sixth year primary School Pupils.

The research is assigned to sixth year primary school pupils- Baghdad –the 2^nd   karkh of the both genders .The total sample includes (500) pupils .The researchers has built two scales one for Moral Intelligence and another for Academic Adjustment and applied them on the total sample of the research .The researchers treated data by appropriate statistical means .The research has reached the following results:

• The pupils of sixth year primary school characterized by Moral Intelligence.
• The

This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

Dielectric measurements were carried on pure and doping potassium sulfate with copper and iron ions samples at 1wt.% and 3wt.% for both of copper and iron. The dielectric constant (ε') decreases exponentially from 2.8 to 1.5 as frequency increase for both dopant which is attributed to the space charge and structural distortion. The dielectric loss (ε") for Cu dopant decrease gradually with frequency. The same behavior for 1%Fe dopant while its 3%Fe doping started from 0.27 then decrease exponential. Band gaps for all samples almost constant around 6 eV.

This research studies the possibility of producing Bone China with available local and geological substitutes and other manufactured ones since it’s traditionally produced by Bone ash, Cornish stone, and China clay, while the substitutes are Kaolin instead of China clay and Feldspar potash instead of Cornish stone. Because of the unavailability of Feldspar in Iraq, it was substituted with the manufactured alternative Feldspar. Bone ash was prepared from cow bones with heating treatments, grinding and sifting. The alternative Feldspar was prepared by chemical analysis of the natural Feldspar potash with local materials that include Dwaikhla Kaolin, Urdhuma Silica sand, Potassium Carbonate, and Sodium Carbonate. The mixture was burned at

The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen