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A Comparison Between Recursive Least-Squares (RLS) and Extended Recursive Least-Squares (E-RLS) for Tracking Multiple Fast Time Variation Rayleigh Fading Channel
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In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the statistical methods used to Forecast the size of the Iraqi GDP for the two sectors (public and private) for the period (2025-2016)
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Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

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Publication Date
Wed Feb 03 2016
Journal Name
Iraqi Journal Of Physics
Study the variation of synodic month for the moon through 2000-2100
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In this research study the synodic month for the moon and theirrelationship with the mean anomaly for the moon orbit and date A.Dand for long periods of time (100 years), we was design a computerprogram that calculates the period of synodic months, and thecoordinates of the moon at the moment of the new moon with highaccuracy. During the 100 year, there are 1236 period of synodicmonths.We found that the when New Moon occurs near perigee (meananomaly = 0°), the length of the synodic month at a minimum.Similarly, when New Moon occurs near apogee (mean anomaly =180°), the length of the synodic month reaches a maximum. Theshortest synodic month on 2053 /1/ 16 and lasted (29.27436) days.The longest synodic month began on 2008 /11/ 27 a

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study the variation of synodic month for the moon through 2000-2100
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In this research study the synodic month for the moon and their
relationship with the mean anomaly for the moon orbit and date A.D
and for long periods of time (100 years), we was design a computer
program that calculates the period of synodic months, and the
coordinates of the moon at the moment of the new moon with high
accuracy. During the 100 year, there are 1236 period of synodic
months.
We found that the when New Moon occurs near perigee (mean
anomaly = 0°), the length of the synodic month at a minimum.
Similarly, when New Moon occurs near apogee (mean anomaly =
180°), the length of the synodic month reaches a maximum. The
shortest synodic month on 2053 /1/ 16 and lasted (29.27436) days.
The lo

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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
Dilemmas in teaching human rights and democracy between the current reality and the difficulties in seeking to spread a culture of human rights
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In the age of information and communication revolution, education as one of life aspects has influenced with that revolution by integrating technology in education, which have become as an important learning tools of the whole educational process . Technology, when used appropriately, can help make science classroom a site of active learning and critical thinking, furthering student inquiry and connections with different materials. It is necessary to develop human rights education programs and materials for discretionary and extracurricular activities as it provide them with the skills and tools so that they are empowered to take action to realize their rights. Human rights education is a critical means of instilling the knowledge، skil

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
On Generalized Φ- Recurrent of Kenmotsu Type Manifolds
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          The present paper studies the generalized Φ-  recurrent of Kenmotsu type manifolds. This is done to determine the components of the covariant derivative of the Riemannian curvature tensor. Moreover, the conditions which make Kenmotsu type manifolds to be locally symmetric or generalized Φ- recurrent have been established. It is also concluded that the locally symmetric of Kenmotsu type manifolds are generalized recurrent under suitable condition and vice versa. Furthermore, the study establishes the relationship between the Einstein manifolds and locally symmetric of Kenmotsu type manifolds.

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Comparison the Formation of Spark Corona Discharge between Tap and distilled Waters at Liquid Electrode System
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In this paper, we studied the spark corona discharge in tap and distillited waters. The results show the shape of cone that generated on the tip of capillary tube is different with conductivity of liquids. The blue glow appears at the end of capillary tube and the drop extends into a cone. In addition, the conducitivity is affected on the relationship between the appearance of the blue glow discharge with the applied voltage. The size of the cone decreases with an increase in applied voltage. The cone diameter at the base of capillary tube oscillates with period approximately 1 Sec. this oscillates in the cone diameters is due to the change distance between the liquid electrode and the surface of liquid. The intensity of spark corona dis

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Publication Date
Tue Jan 28 2014
Journal Name
Journal Of Energy And Power Engineering
Comparison between Two Vertical Enclosures Filled With Porous Media under the Effect of Radiation and Magnetohydrodynamics
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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