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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; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied.

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
A study of the characterization of CdS/PMMA nanocomposite thin film
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Nanocomposites of polymer material based on CdS as filler
material and poly methyl methacrylate (PMMA) as host matrix have
been fabricated by chemical spray pyrolysis method on glass
substrate. CdS particles synthesized by co-precipitation route using
cadimium chloride and thioacetamide as starting materials and
ammonium hydroxide as precipitating agent. The structure is
examined by X-ray diffraction (XRD), the resultant film has
amorphous structure. The optical energy gap is found to be (4.5,
4.06) eV before and after CdS addition, respectively. Electrical
activation energy for CdS/PMMA has two regions with values of
0.079 and 0.433 eV.

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Study of the Furocoumarin Derivative of Ruta Chalepensis L. (Rutaceae)
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  The content of Furocoumarin derivatives (Psoralens) of Ruta Chalepensis L. (Whole plant) was studied by simple extraction with petroleum ether (b.p. 60-80Co). The results indicated that the plant contains a total of about (0.015%).

       Investigation of these compounds by thin layer chromatography (TLC) revealed the presence of at least four compounds of which methoxsalen (8-methoxypsoralen) was isolated.     It was identified and authenticated with a standard by spectral method, IR, NMR, Mass spectra and HPLC.This plant could be considered as a good source for supplying this compound, which is widely used in dermatological preparations.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
representations of body language in the contemporary Iraqi theatrical show "Imagine That as a model": عمار عبد سلمان محمد
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There is no doubt that each of the arts has a material from which the aesthetic achievement is built, so the researcher found that the art of theater, especially the show, whose artistic achievement is based on the body of the actor who emits the formal language (body language), is the focus of interest and active presence, because the body possesses its spiritual qualities that made him and the ability to The formation of things by (his body language), so the researcher studied this theatrical phenomenon and divided it into four chapters. In the first chapter, the research problem included the following question: (Is there a phenomenon of body language in the contemporary theatrical show "Imagine that" as a model) so It is of cognitive

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Publication Date
Thu Aug 17 2023
Journal Name
Migration Letters
Employing the Teleological-Causal Presumption between Al-Khwarizmi and Ibn Yaish’s Explanations of Al-Mufasal (even) as a Model
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It is a moral presumption that includes the object for its sake, and it is called the object for it or the object for its sake, which is the present tense after (lam, ki, fa, willn, and then), and it is not an excuse for the occurrence of the matter (1), and it requires a connection between the two sides of (a cause with a cause) united by a reason for a specific purpose (2). The object has a reason or an excuse, because it is an explanation of what came before it, of the cause. The reason for the occurrence of the action, being the motive for causing the action and the bearer of it (3), indicates that the infinitive is restricted to a special reason. So if I said: (I came to you with the hope of honoring you), then I attributed the coming

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Restructuring of the public industrial sector companies Wayshift to private shareholding companies and mixed (Iraqi experience as a model)
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That the main feature of  the economics many countries in general is a tendency towards defining the role of the public sector in economic activity and the tendency towards encourage the private sector to investment in public projects especially in countries those tendency towards market economy actually.

That increased economic development proven failure in achieving more economic growth both individually in many countries especially developing countries socialist, by researchers this led one way or another to direction of corrective reforms in their economic was one of them in Transformation of public companies into Shareholding companies contributes to the public sector in resources and expertise

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice &amp; Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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