The problem of constant and change values is one of the important problems that the philosophy thought had faced as the religious and social studies had taken it as it considers as one of the most dangerous which touch the basic . the research deals with the effect of change value of new Iraqi situation to be as an attempt , as participation or an excitement that can be occupied a space through the area of questions on the fix and change of moral values shed light on the economical ,social and political events that the Iraqi society passes through them .it is part of interests that becomes importance to everyone through the light of moral change Which is arbitrary to the life of the individual .It is not possible to rebuild the society o

The present work deals with five species of parasitic Hymenoptera belonging to Pteromalidae, Eupelmidae and Eurytornidae which have been reared from brachid beetles. A new species, Eurytoma irakensis is described and the species, Bruchocida orientalis Crawford is recorded for the first time from Iraq.

In this paper, A.C conductivity of micro and nano grain size- TiO2 filled epoxy composites is measured. The dielectric material used is epoxy resin, while micro and nano-sized titanium dioxide (TiO2) of grain size (1.5μm, and 50nm) was used as filler at low filler concentrations by weight (3%, and 5%). Additionally the effect of annealing temperature range (293-373)º K and at a frequency range of 102-106 Hz on the A.C conductivity of the various specimens was studied.
The result of real permittivity for micro and nanocomposite show that the real permittivity increases with decreasing frequency at range of 102-106Hz. The micron-filled material has a higher real relative permittivity than the nano-filled this is true at all the temper

The Dielectric properties of EP/TiO2 and MgO nanocomposite at
a frequency range of (102-106 Hz) were studied. The composite were
prepared with the state volume ratio (0, 0.05, 0.1) for EP/TiO2 and
MgO respectively. The impedance, dielectric constant and dielectric
loss were found decrease with frequency increase.

Gas lift is one of the oldest methods used to produce hydrocarbon fluids from wells experiencing declining production. It works by aerating the mixture inside production tubing and forcing it to the surface. One of the reasons for declining production in oil wells is an increase in water cut or a drop in reservoir pressure, which requires one of the artificial lift methods to restore production. (A) oil field suffers from an increase in water cut, which has affected well productivity. The wells under study have a water cut of up to 66%, resulting in very low production rates. In this research, Pipesim software was used to build a physical and fluid model, then design an optimal gas lift system that achieves the highest possible prod

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class