Abstract

were determine the problem of current research to answer the  question on the consciousness of the Ministry of Agriculture to adopt Staffing  strategy and identify the shortcomings  as the independent variable, represented by the three dimensions (recruitment , selection, placement) and its impact on high performance, as  dependent   variable is described  in  four dimensions (leadership, strategy, structure and processes, culture), in this research were  Used  analytical descriptive  style . This research aims to identify the correlation and impact  of Staffing strategy at high-performance in Ministry of Agriculture , To clarify the relationship between

The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.

Background: Hemorrhoids are one of the most
common surgical conditions .Conventional
haemorrhoidectomy was the traditional operation for
the treatment of hemorrhoids. Other modalities of
treatment had been used as an alternative operations
including CO2 laser haemorrhoidectomy.
Objectives: To determine the outcome of treatment
of hemorrhoids by using CO2 laser
haemorrhoidectomy and its advantages over
conventional surgery
Methods: This is a retrospective comparative
interventional study of 1024 case of third degree
haemorhoids selected out of 1300 case of
hemorrhoids of different degrees, admitted to
ALKINDY, ALYERMOUK teaching hospitals and
ABD ALMAGEED private hospital, from May 1998
to J

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability