Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visualized and analyzed according to the theory of Complex Networks by representing the stations as nodes and the transmission lines as edges. This analysis is done by applying network metrics to the proposed national IPG network. Finally, this work provides a professional visualization of the generated network based on the demographic distribution and the accurate coordinates of the power stations. Thus, this proposed network is useful for the Iraqi Ministry of Electricity. Besides, it can be adopted by officials and specialists to understand, visualize and evaluate the performance of the current IPG network since it is still under development and modernization.
The research aims to test the relationship and impact of High Involvement Management as an independent variable in negotiation strategies as a response variable, at the headquarters of the Iraqi Ministry of Industry and Minerals in Baghdad Governorate, and then trying to come up with a set of recommendations that contribute to strengthening the negotiations carried out by the ministry’s leaders and based on the importance of the topic of research in public organizations and the importance of the surveyed organizations to the society. The descriptive-analytical approach was adopted in the completion of this research, and the research included a sample of (180) leaders of the Iraqi Ministry of Industry and Minerals, and data was
... Show MoreStatic Synchronous Series Compensator (SSSC) is a well known device for effectively regulating the active power flow in a power system. In this paper, the SSSC linearized power flow equations are incorporated into Newton-Raphson algorithm in a MATLAB written program to investigate the control of active poweer flow and the transient stability of a five bus and a thirty bus IEEE test systems, during abnormal conduction (three phase fault near buses). A comparison of the results obtained for the base case without SSSC and with it to investigate the effectiveness of the device on both of the active power flow and the transient stability.
This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.
A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga
... Show MoreIn this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m3
... Show More(January 25, 2011) represented a real opportunity to bring about fundamental changes in Egyptian foreign policy and to start a new phase that would cut off all the negative and problematic aspects of Egyptian politics in the period before the revolution. Through the employment of Egypt's huge balance and the role of historical is a civilization rooted in the roots of thousands of years and Islamic reference represented over more than a thousand years the Islamic medium of religion in the start of vision and tools to achieve the Egyptian national interest, and safeguarding Egyptian national security in its comprehensive sense. The research attempts to answer a central question: Is there a role for Egyptian soft power in the Islamic world
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database