Current study obtained (75) isolate of Pseudomonas aeruginosa collected from different cases included : 28 isolates from otitis media, 23 isolates from burn infections, 10 isolates from wound infections, 8 isolates from urinary tract infections and 6 isolates from blood, during the period between 1/9/2014 to 1/11/2014

       The result revealed that the tox A gene was present in 54 isolates (72%) of Pseudomonas aeruginosa. The gel electrophoresis showed that the molecular weight of tox A gene was 352 bp. The result shows 17 isolates (60.71%) from otitis media has tox A gene, 1

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

The tagged research (realism in the Paintings of Iraqi Kurdistan artists, “a study of expression methods”) dealt with realism in an objective way, as well as the complexity of its concepts through its formations and formations. On realism and its historical dimension in concept and meaning, as for the second chapter, the research was focused on the methods of expression in painting, while the third chapter was concerned with the procedural applications of realistic methods of expression in the drawings of Iraqi Kurdistan, and according to these axes and to achieve the goal of the research, a number of Among the results are:
1- Realism documented the life of the Kurdish society in line with the developments of the era, as the sty

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi