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bsj-6959
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
Sun Jan 08 2017
Journal Name
International Journal Of Information Technology And Computer Science
Adaptive Modeling of Urban Dynamics during Armada Event using CDRs
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi Geological Journal
Reservoir modeling for mishrif formation in Nasiriyah oilfield
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Publication Date
Sat Jun 01 2019
Journal Name
Synthetic Metals
Modeling tunnel currents in organic permeable-base transistors
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Modeling and Simulating NOMA Performance for Next Generations
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Non-orthogonal Multiple Access (NOMA) is a multiple-access technique allowing multiusers to share the same communication resources, increasing spectral efficiency and throughput. NOMA has been shown to provide significant performance gains over orthogonal multiple access (OMA) regarding spectral efficiency and throughput. In this paper, two scenarios of NOMA are analyzed and simulated, involving two users and multiple users (four users) to evaluate NOMA's performance. The simulated results indicate that the achievable sum rate for the two users’ scenarios is 16.7 (bps/Hz), while for the multi-users scenario is 20.69 (bps/Hz) at transmitted power of 25 dBm. The BER for two users’ scenarios is 0.004202 and 0.001564 for

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
A Impact of High Voltage Direct Current Link on Transmission Line in Kurdistan Power System
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Kurdistan power system is expanded along years ago. The electrical power is transmitted through long transmission lines. The main problem of transmission lines is active and reactive power losses. It is important to solve this issue, unless, the most of electrical energy will lost over transmission system. In this study, High Voltage Direct Current links/bipolar connection were connected in a power system to reduce the power losses. The 132kV, 50 Hz, 36 buses Kurdistan power system is used as a study case. The load flow analysis was implemented by using ETAP.16 program in which Newton-Raphson method for three cases. The results show that the losses are reduced after inserted HVDC links.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Apr 01 2015
Journal Name
Al–bahith Al–a'alami
Methods of US propaganda in Iraq- A Study of Coalition Provisional Authority and US Army Data after 2003
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with an organized propaganda campaign. This military campaign was helped to formulate its speech by many institutions, research centers, and knowledge and intelligence circles in order to mobilize public opinion gain supporters and face the opponents by different means depending on a variety of styles to achieve its required effects. 
          After the US occupation of Iraq, US media fighters sought to influence the Iraqi public opinion and making them convinced them of the important presence of US military forces in Iraq which necessitated finding its justification through the use of persuasive techniques in its intensive propaganda campaigns. 
  This research discusses the most important

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Detection of Leishmania tropica Using Nested-PCR and Some of Their Virulence Factors in Thi-Qar Province, Iraq
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Cutaneous leishmaniasis is one of endemic diseases in Iraq. It is considered as widely health problem and is an uncontrolled disease. The aim of the study is to identify of Leishmania species that cause skin lesions among patients in Thi-Qar Province, South of Iraq, also to detect some virulence factors of L. tropica. This study includes three local locations, Al-Hussein Teaching, Suq Al-Shyokh General and Al-Shatrah General Hospitals in Province for the period from the beginning of December 2018 to the end of September 2019. The samples were collected from 80 patients suffering from cutaneous leishmaniasis, both genders, different ages, various residence places and single and multiple lesions. Nested-PCR technique was

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