CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.  Many trials have been done to ma

CO₂ Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.

Ceftriaxone sodium were one of the widely antibacterial drugs used. Azo dye derivatization of diazonium salt that formed via the reaction between ceftriaxone with hydrochloric acid and sodium nitrite was developed for the on-research drug analysis then coupling with each one 2,5-dimethylphenol (2,5-DMP) and 4-tertbutylphenol (4-TBP) respectively in the alkaline media. The developed diazonium coupling methods include an optimization study. The results show a limit of detection and limit of quantification 0.482, 0.284 µg/mL, and 1.607, 0.945 µg/mL using 2,5-DMP and 4-TBP reagents respectively. Moreover, the recovery % obtained was 100.89%, and 103.37% at linear concentration range 3.0 – 50, and 10 – 30 µg/mL, with mo

Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

This study includes six species related to the genus Echinops L. (composite) grown in Iraq which are listed below: E.armatus Boiss. & Hausskn., E. bicolor Nabelek, E. cephalotes DC., E.haussknechtii Boiss., E. moulensis Rech., E. nitens Bornm., the geographical distribution and ecological preferences' were documented.
It has been also observed that this genus was distributed near waterfalls, vallies, road side, dry limestone, clay soil and hard rocky soil in Different heights. The most separated species was E.armatus and the least separated one was E.haussknechtii, the species was listed in diagram and distributed on a map.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

An    Experimental     comparison     between     the     current-voltage

characteristic and    the  efficiency    conversion from  solar  to  electric energy   were studied  for square  and circular  single crystal  silicon  solar

cell of equal area (35.28  cm2)  . The results show  that the solar shape is

an  important factor  in  calculating the  current-voltage characteristics and  efficiency of  the  solar  cell.  It was  shown   that  the  performance effici

Biological image edge detection preserving the important structural properties in an image. Detecting accurate edges are very important for analyzing the basic properties associated with a biological image. Gradient operator plays very important role in edge detection. In this paper the images had been using are color biological images taken from microbiology laboratory at the biological department college of science Al-MustansiriyhUniversity and the effect of gradient operation have applied on around 10 different biological color images but view only two. In our proposed approach comparative of various gradient of biological image include (gradient of image, gradient of image using first order derivative edge detection (Soble,Prewitt,Ro

Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m