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Modeling The Power Grid Network Of Iraq
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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.

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Publication Date
Sat Sep 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
استخدام برمجة (DeNovo) لتطوير شبكة المياه في استراتيجيات القرار المتعدد
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The object of this study is to establish a global model to use of DeNovo programming the strategies of multi-Decision making process in the city of Baghdad.

Thus, we have chosen an important and an effective subject in the life of the citizen due to the importance of this subject in the Iraqi citizen of luck of water and for many reasons.

In this thesis, we have tackled the establishment of a global model to be able to reach solution or an alternative model a money the available alternative.

        The alternative proposed here utilizes the application of the (DeNovo) programming approach suggested by (1982) in solving t

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of governmental consumer spending on the development of the current account balance in Iraq for the period (1990-2014) using ARDL model
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To avoid the negative effects due to inflexibility of the domestic production inresponse to the increase in government consumption expenditure leads to more  imports to meet the increase in domestic demand resulting from the increase in government consumption expenditure. Since the Iraqi economy economy yield unilateral depends on oil revenues to finance spending, and the fact government consumer spending is a progressive high flexibility the increase in overall revenues, while being a regressive flexibility is very low in the event of reduced public revenues, and therefore lead to a deficit in the current account position. And that caused the deficit for imbalance are the disruption of the

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Thu Dec 15 2022
Journal Name
Al Kut Journal Of Economics And Administrative Sciences
The relationship of demographic diversity to institutional effectiveness An analytical study of a sample of workers in public organizations in Iraq
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Diversity has become one of the required phenomena to be available within public organizations, in light of the changes taking place in the global and international environment and in various fields. Therefore, it was imperative to study the impact of this phenomenon in various institutions, especially public ones, in most developing countries, including Iraq. The current research aims to analyze the relationship between The demographic diversity and institutional effectiveness of a sample of workers in public institutions included (500) respondents. The questionnaires were distributed to them randomly. Diversity is considered an independent variable and institutional effectiveness a dependent variable. The researcher used interview tools a

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Modeling and Simulation of the Boilers at Al-Mussaib Thermal Station
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Publication Date
Sat Mar 10 2018
Journal Name
Opción
The Effect of Cognitive Modeling Strategy in chemistry achievement for students
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The aim of the current research is to verify the effect of the cognitive modeling strategy on the achievement of the chemistry course for the students of the first intermediate grade. To achieve the objective of the research, the null hypothesis was formulated via cognitive modeling strategy. The results showed that the experimental group's students performed better than the students in the control group. In the light of the results, the researchers concluded: The impact of the cognitive modeling strategy in the achievement of students of first intermediate grade in chemistry.

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
The The Application of Virtual Reality to (Mechatronics Engineering) by Creating an Articulated Robotic Work Cell Using EON Reality V9.22.24.24477
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Virtual reality, VR, offers many benefits to technical education, including the delivery of information through multiple active channels, the addressing of different learning styles, and experiential-based learning. This paper presents work performed by the authors to apply VR to engineering education, in three broad project areas: virtual robotic learning, virtual mechatronics laboratory, and a virtual manufacturing platform. The first area provides guided exploration of domains otherwise inaccessible, such as the robotic cell components, robotic kinematics and work envelope.  The second promotes mechatronics learning and guidance for new mechatronics engineers when dealing with robots in a safe and interactive manner. And the thir

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Publication Date
Fri Sep 01 2017
Journal Name
2017 9th Computer Science And Electronic Engineering (ceec)
Modelling the power cost and trade-off of live migration the virtual machines in cloud-radio access networks
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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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