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Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certainly visible. This criterion was used on the dataset for ANN learning to compare its efficiency with the actual moon visibility events.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Wed Mar 01 2023
Journal Name
Al-khwarizmi Engineering Journal
A Methodology for Evaluating and Scheduling Preventive Maintenance for a Thermo-Electric Unit Using Artificial Intelligence
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Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Clinical And Experimental Dentistry
Bond strength of a new Kevlar fiber-reinforced composite post with semi-interpenetrating polymer network (IPN) matrix
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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamic Channel Assignment Using Neural Networks
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This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Link Failure Recovery for a Large-Scale Video Surveillance System using a Software-Defined Network
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The software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem.  The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

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Publication Date
Wed May 17 2023
Journal Name
College Of Islamic Sciences
Lessons learned from the personality of Salah al-Din al-Ayyubi and his policy
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The personality of the hero Salah al-Din al-Ayyubi (may God have mercy on him) came from the womb of jihad after difficult travails that the Arab Islamic nation experienced through the jihad of its loyal and honest sons who vowed themselves to God in defense of his religion and law, so between 490 AH - 540 AH outstanding jihadi leaders emerged who took upon themselves the responsibility of jihad and mobilizing the nation's energies To fight its enemies - the Franks, the Crusaders - in the Levant, and those leaders succeeded in achieving impressive victories over the Frankish military effort and regained some cities that were usurped by the Franks. Balak bin Bahram, Suqman, and Jakarmish, but these leaders could not maintain a state of un

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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