The present research aims to test the effect of cognitive complexity as an independent variable in organizational agility as a responsive variable among the leaders working at the headquarters of the Iraqi Petroleum Products Distribution Company.

 To conclude a number of recommendations that contribute in the organizational agility in the company, and due to the importance of this research in public organizations and its notable role in community organizations. The research was carried out on a random sample of 101 individuals out of a total of 308, which represents the high leaders in the company (general managers, head of departments, and division officials). A questionnaire was used as information

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

Abstract:
One of the most prominent historical stage feature that is well- known
nowadays in the world is democracy issue. This issue gives man the right to
reflect his concept and notions . It,s the world of freedom , human right and
liberation of women. This leads to the principle of equality between women
and men which is put in the top of liberty and Improvement lists .
Improvement can be defined as a group of means and ways that is
used to direct human work to improve their level of life economically and
socially .
This study contains three sections, the first presents the social state of
women in pre-history period . And the second section presents the theory of
improvement as an important social ph

The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

Modern trends have appeared recently in educational thought that call for the achievement of the outcomes of the educational process. Some of these trends are the development of individual thinking skills, considering the individual differences, and learning basic skills. The five-year learning cycle is one of these models. It is called as five-year learning cycle because it passes through five stages. These five stages are: (operate - discover - clarify - expand – Evaluate), which make the learner as the main axis for activating thinking processes. This can be done by organizing study materials through research, investigation, and identifying concepts by himself, as in learning sports skills that depend on motor performance and teamwork,

     In this study, the first kind Bessel function was used to solve Kepler equation for an elliptical orbiting satellite. It is a classical method that gives a direct solution for calculation of the eccentric anomaly. It was solved for one period from (M=0-360)° with an eccentricity of (e=0-1) and the number of terms from (N=1-10). Also, the error in the representation of the first kind Bessel function was calculated. The results indicated that for eccentricity of (0.1-0.4) and (N = 1-10), the values of eccentric anomaly gave a good result as compared with the exact solution. Besides, the obtained eccentric anomaly values were unaffected by increasing the number of terms (N = 6-10) for eccentricities (0.8 and 0.9). The Bessel

Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

Abstract:

     This study aims to identify the level of patients’ satisfaction among a sample of hospitalized patients in the targeted hospital (Al-Kindy Teaching Hospital, and Al-Yarmook Teaching Hospital). Moreover, this study highlights the reality of services for patients, especially in the targeted governmental teaching hospitals. The Patient Satisfaction with Nursing Care (PSNCS) has been measured in these hospitals through the revised scale by Tang et al, (2013).This scale includes four major domains; Health Information (5 items), Influencing Support (4 items), Decision Control (4 items), Specialized Technical Competence (7 items). The method of surveying patients’ opinions about the degree

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an