The research aims to know the availability of supra-cognitive thinking skills in the questions and activities of the computer book for the fifth grade preparatory scientific and literary branches in Iraq for the academic year 2018/2019, as the researcher has prepared a list of supra-cognitive thinking skills included two areas and (6) key skills and (27) A sub - skill, where by the questions and activities of the aforementioned authors were analyzed. The researcher followed the descriptive analytical approach "method of content analysis", and adopted the explicit and implicit unit of analysis, as was verified the validity and stability of the analysis, and the results showed unevenness and imbalance in the distribution of supra-cognitive th

A series of batch demulsification runs were carried out to evaluate the final emulsified water content of emulsion samples after the exposure to microwave. An experimental study was conducted to evaluate the effects of a set of operating variables on the demulsification performance. Several microwave irradiation demulsification runs were carried out at different irradiation powers (700, 800, and 900 watt), using water-in-oil emulsion samples containing different water contents (20-80%, 30-70%, and 50-50%) and salt contents (10000, 20000, and 30000 ppm). It was found that the best separation efficiency was obtained at 900watt, 50% water content and 160 s of irradiation time. Experimental results showed that microwave radiation method can

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro

     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

The solution gas-oil ratio is an important measurement in reservoir engineering calculations. The correlations are used when experimental PVT data from particular field are missing. Additional advantages of the correlations are saving of cost and time.
This paper proposes a correlation to calculate the solution gas -oil ratio at pressures below bubble point pressure. It was obtained by multiple linear regression analysis of PVT data collected from many Iraqi fields.
In this study, the solution gas-oil ratio was taken as a function of bubble point pressure, stock tank oil gravity, reservoir pressure, reservoir temperature and relative gas density.
The construction of the new correlation is depending on thirty seven PVT reports th

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg