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wavelength division multiplexing passive optical network modelling using optical system simulator
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical fiber links when the signal passes through all the components such as optical fiber, splitters, multiplexers then find a good quality of signal in all receivers. The system performance is presented through various parameters such as BER analyzer and the Eye Diagram.

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Publication Date
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Analysing Iraqi Railways Network by Applying Specific Criteria Using the GIS Techniques
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The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq’s provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS®10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this st

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Increasing confidence in full field modelling and water flood planning for a giant reservoir under primary depletion through Material Balance modelling
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Abstract<p>One of the principle inputs to project economics and all business decisions is a realistic production forecast and a practical and achievable development plan (i.e. waterflood). Particularly this becomes challenging in supergiant oil fields with medium to low lateral connectivity. The main objectives of the Production Forecast and feasibility study for water injection are:</p><p>1- Provide an overview of the total expected production profile, expected wells potential/spare capacity, water breakthrough timing and water cut development over time</p><p>2- Highlight the requirements to maintain performance, suggest the optimum developmen</p> ... Show More
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Study The Effect of Annealing on Structural and Optical Properties of Indium Selenide (InSe) Thin Films Prepared by Vacuum Thermal Evaporation Technique
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Abstract<p>In this work, InSe thin films were deposited on glass substrates by thermal evaporation technique with a deposit rate of (2.5∓0.2) nm/sec. The thickness of the films was around (300∓10) nm, and the thin films were annealed at (100, 200 and 300)°C. The structural, morphology, and optical properties of Indium selenide thin films were studied using X-ray diffraction, Scanning Electron Microscope and UV–Visible spectrometry respectively. X-ray diffraction analyses showed that the as deposited thin films have amorphous structures. At annealing temperature of 100°C and 200°C, the films show enhanced crystalline nature, but at 300°C the film shows a polycrystalline structure with Rhombohedral phas</p> ... Show More
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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Thu Mar 30 2006
Journal Name
College Of Islamic Sciences
The Islamic call for the unity of human society and the rejection of division
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الحمد الله أولا واخرا وبعد .. إن الواقع الذي عايشه الناس في ظل دولة المسلمين منذ إقامة دولة الإسلام بعد بعثة الرسول الكريم (صلى الله عليه وسلم ) في المدينة ولأكثر من أربعة عشر قرنا نرى إنه عاش في كنف هذه الدولة الكبيرة من بلاد الصين شرقا وإلى وسط أوربا وجنوب فرنسا غربا العشرات من الملل و الأديان والأجناس وممن لا يدينون بالإسلام وهم كما تحفظ لهم دولة الإسلام منهم وعيشهم الرغيد فهم يمارسون شعائرهم وطقوسهم الديني

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
The Phenomenon of Division and Modification of The Individual Houses in Baghdad after 2003
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The Research deals with the negative phenomena which appeared in the urban scenes of the  Iraqi cities after 2003, particularly trespassing the architectural design of the urban Individual houses.  Many academic researchers , critics, and cultural circles, drawn attention to the impact of  political and cultural variable change on such phenomena  without detailed  analysis . The research problem  is set according to central questions : If the phenomena is the trespass , what
are the sides which are being trespassed  in the division of the individual house? , If the diagnosis of the phenomena denotes perceived repetition of the cases , So what's size of this transposes on the architectural design of t

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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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
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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