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ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Information And Communication Convergence Engineering
Survey on Physical Layer Security in Downlink Networks
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In this paper, we discuss physical layer security techniques in downlink networks, including eavesdroppers. The main objective of using physical layer security is delivering a perfectly secure message from a transmitter to an intended receiver in the presence of passive or active eavesdroppers who are trying to wiretap the information or disturb the network stability. In downlink networks, based on the random feature of channels to terminals, opportunistic user scheduling can be exploited as an additional tool for enhancing physical layer security. We introduce user scheduling strategies and discuss the corresponding performances according to different levels of channel state information (CSI) at the base station (BS). We show that the avai

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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Publication Date
Sun Jun 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Study the Effects of Anadrol Overdose on Liver Function in Male Rats
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Anadrol (oxymetholone) is an active androgenic anabolic steroid that has been clinically studied in numerous diseases since the 1960s. It is used in the treatment of anemia and the replacement of male sex steroids. Unfortunately, in attempts to improve physical performance, Anadrol could be misused by athletes, that can lead to poisoning contributes to hepatotoxicity.

The aim of this study was to investigate the impact of anadrol on the liver function in rat model, via assessment of liver enzymes and histopathological study.

A forty male rats, weights about (200-300 gm), aged 8-12 weeks, after acclimatization, the rats were ‎randomly divided into four groups (10 rats in each group) as follow: control group (in w

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Publication Date
Wed Dec 31 2025
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Comparison between the Effects of Hypertension on Diabetic Mellitus with Endothelin Function
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both strongly associated with vascular and metabolic complications. Endothelin-1 is a potent vasoconstrictor that plays a key role in vascular tone regulation and endothelial function. Objective: To evaluate serum Endothelin-1 levels, lipid profile parameters (total cholesterol, LDL-C, VLDL-C, HDL-C, triglycerides), and HbA1c in patients with type 2 diabetes and essential hypertension compared with healthy controls, in order to assess their association with vascular injury and metabolic risk. Methods: A case-control study was conducted in the Department of Biochemistry, College of Medicine, University of Baghdad. Between November 2024 and February 2025, a sample of patients were recruited from Baghdad Teaching Hospital and Ibn Al-Bi

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Bayesian Inference for Reliability Function of Gompertz Distribution
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Abstract<p>In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based o</p> ... Show More
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Publication Date
Sun Dec 01 2013
Journal Name
Al- Mustansiriyah Journal Science
Convex Approximation by q- Meyer-König-Zeller Durrmeyer Operators
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Approximation fixed point theorems via generalized like contraction mappings
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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Thu Aug 25 2016
Journal Name
International Journal Of Mathematics Trends And Technology
Pretest Single Stage Shrinkage Estimator for the Shape Parameter of the Power Function Distribution
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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Pais estimator for the reliability function of the Pareto model of Type I failure
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In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).

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