This study aims to impact statement played by banking governance according to the decisions of the Basel Committee in achieving the strategic objectives of the banks, But order to achieve the this goal has been the adoption of two hypotheses in addition to the two main hypotheses as sub answered preliminary The study seeks to verify their health and two (no correlation relationship and impact between Banking  governance and achieve strategic objectives), has been tested hypotheses. Study has reached

Suspicion in the truth that the satisfaction of the student in the criticism of the speech of the poet and the writer to I bin Al-Atheer

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

The research was performed in order to investigate the prevalence of Eimeria spp in buffalo. Coccidiosis, is a common livestock disease include water buffaloes and nothing is known about the most pathogenic species of Eimeria. Since the highest prevalence of oocyst shedding and incidence of disease occurs in buffalo calves less than one year of age. The omnipresent occurrence and negative effects of the infection on health and buffalo growth output are taken into account. Therefore, both farmers and veterinarians should pay greater attention to infections with Eimeria spp. And there is little analysis of data reported in Iraq and the world regarding Eimeria infection in river buffalo spp.