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Using Different Methods to Estimate the Parameters of Probability Death Density Function with Application
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In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Effect of the Clenbuterol drug in some physiological parameters in male rabbits(Oryctolagus cuniculs)
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This study was designed to investigate the effect of the Clenbuterol drug in some physiological parameters of Liver, Kidney function and lipidprofie concentration. Fourty adult male rabbits were used in this study. The animals were randomly divided into four groups,the first group was given distilled water (control) ,while the other third groups were given (2,4,6 µg/kg) of Clenbuterol drug for 30 days. Blood samples were collected after 14 and 30 days of the treatment for biochemical study. Drug caused non significant increase(P<0.05)in the AST and ALT enzymeactivity in second and third groups during treatment period ,while we note a significant increase(P<0.05) in both AST,ALT enzyme level in fourth group compared with control group , as

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Publication Date
Sun Sep 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Residence Time Parameters on Thermal Cracking Extract Phase Lubricating Oil
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This work studies with produce of light fuel fractions of gasoline, kerosene and gas oil from treatment of residual matter that will be obtained from the solvent extraction process as by product from refined lubricate to improve oil viscosity index in any petroleum refinery. The percentage of this byproduct is approximately 10% according to all feed (crude oil) in the petroleum refinery process. The objective of this research is to study the effect of the residence time parameter on the thermal cracking process of the byproduct feed at a constant temperature, (400 °C). The first step of this treatment is the thermal cracking of this byproduct material by a constructed batch reactor occupied with control device at a selective range of re

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Parameters Affecting the Strength and Behavior of RC Dapped-End Beams: A Numerical Study
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The finite element method has been used in this paper to investigate the behavior of precast reinforced concrete dapped-ends beams (DEBs) numerically. A parametric investigation was performed on an experimental specimen tested by a previous researcher to show the effect of numerous parameters on the strength and behavior of RC dapped-end beams. Reinforcement details and steel arrangement, the influence of concrete compressive strength, the effect of inclined load, and the effect of support settlement on the strength of dapped-ends beams are examples of such parameters. The results revealed that the dapped-end reinforcement arrangement greatly affects the behavior of dapped end beam. The failure load decreases by 25% when

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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Hydrogen Energy
Improvement of bioenergy generation using innovative application of food waste materials for coating carbon nanotubes-loaded bioanode in 3D-microbial fuel cells
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Publication Date
Wed Feb 15 2023
Journal Name
Environmental Technology
Bio-synthesis of TiO<sub>2</sub> using grape leaves extract and its application for photocatalytic degradation of ibuprofen from aqueous solution
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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Correlation of Paschen parameters in magnetized argon plasma
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A number of glow discharge experiments has been carried out in a relatively large-volume metallic vacuum chamber containing argon at low pressure and immersed in an inhomogeneous magnetic field generated by a solenoidal coil capable of delivering 2100G. Two Paschen curves demonstrating the dependence of the discharge voltage on sparking parameter Pd and magnetic field strength B were deduced. A graphical correlation showing the behaviour of the voltage difference from the two curves on the ratio B/Pd was constructed. Investigations showed a reduction in the nominal impedance of the discharge device of nearly 20% when B reaches a value of 525G. Plasma confinement regions were found around the internal surface of the chamber at the entranc

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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