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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
Wed Sep 01 2021
Journal Name
International Scientific Congress Of Pure, Applied And Technological Sciences (minar Congress)
Evaluation Of Electromagnetic Pollution Of Cellular Mobile Network
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Wireless communications are characterized by their fastest growth in history, as they used ever-evolving and renewed technologies, which have allowed them to spread widely. Every day, communication technology introduces a new invention with features that differ from its predecessor. Bell Laboratories first suggested mobile wireless communication services to the general population in the late 1940s. Still, it wasn't easy at that time to use on a large scale due to its high costs. This paper aims to describe the state of cellular mobile networks; by comparing the sources of electromagnetic pollution caused by these networks, measure the level of power density in some residential areas, and compare them with international standards adopted in

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Sun Mar 28 2021
Journal Name
Journal Of The College Of Education For Women
Social Protection and its Impact on the Cohesion of Vulnerable Groups: A Field Study of a Sample Social Protection Network Beneficiaries: دينا داود محمد المولى
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Social protection meets different aspects of the needs of vulnerable groups, such as the economic, health, education, and family relations and ties in the Iraqi society. This is because vulnerable groups have suffered from social and economic influences that have negative implications on the social reality as a whole. Poverty is a case in point, which paved the way to frequent setbacks that have led to social structure instability. Accordingly, the present study aims to examine the role and effect of the Net of Social Protection Program in equally distributing social protection to curb or mitigate any negative consequnces that might happen to the poor segments and vulnerable people, who are succeptible to shocks, such as: the orphans, un

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Recurrent Neural Networks and its Applications in Time Series Data
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Publication Date
Mon Jan 01 2024
Journal Name
Aims Mathematics
Solving quaternion nonsymmetric algebraic Riccati equations through zeroing neural networks
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<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
In vitro isolation and expansion of neural stem cells NSCs
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   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Fri Apr 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An adaptive neural control methodology design for dynamics mobile robot
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Publication Date
Sun Nov 16 2025
Journal Name
Lecture Notes In Networks And Systems
The Extent to Which Public Relations Departments in Government Institutions Use Artificial Intelligence Applications in Their Communication Activities: A Field Study
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Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

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