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Prediction of spot welding parameters using fuzzy logic controlling

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Publication Date
Fri Aug 01 2008
Journal Name
2008 International Symposium On Information Technology
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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using the Size Strain Plot Method to Specity Lattice Parameters

X-ray diffractometers deliver the best quality diffraction data while being easy to use and adaptable to various applications. When X-ray photons strike electrons in materials, the incident photons scatter in a direction different from the incident beam; if the scattered beams do not change in wavelength, this is known as elastic scattering, which causes amplitude and intensity diffraction, leading to constructive interference. When the incident beam gives some of its energy to the electrons, the scattered beam's wavelength differs from the incident beam's wavelength, causing inelastic scattering, which leads to destructive interference and zero-intensity diffraction. In this study, The modified size-strain plot method was used to examin

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the general exponential distribution parameters using the simulation method

The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation technique .. It was obse

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Publication Date
Sat Jan 14 2023
Journal Name
Cogent Engineering
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Publication Date
Mon May 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Chained fuzzy modules

        Let R be a commutative ring with unity. In this paper we introduce the notion of chained fuzzy modules as a generalization of chained modules. We investigate several characterizations and properties of this concept

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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Semimaximal Submodules

     Let R be a commutative ring with unity and an R-submodule N is called semimaximal if and only if

 the sufficient conditions of F-submodules to be semimaximal .Also the concepts of (simple , semisimple) F- submodules and quotient F- modules are  introduced and given some  properties .

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Distributive Modules

  Let R be a commutative ring with unity. In this paper we introduce and study fuzzy distributive modules and fuzzy arithmetical rings as generalizations of (ordinary) distributive modules and arithmetical ring. We give some basic properties about these concepts.  

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Publication Date
Sun Aug 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Semimaximal ideals

    Let R be a commutative ring with identity. A proper ideal I of R is called semimaximal if I is a finite intersection of maximal ideals of R. In this paper we fuzzify this concept to fuzzy ideals of R, where a fuzzy ideal A of R is called semimaximal if A is a finite intersection of fuzzy maximal ideals. Various basic properties are given. Moreover some examples are given to illustrate this concept.

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Publication Date
Thu May 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Semiprime Fuzzy Modules

  In this paper we introduce the notion of semiprime fuzzy module as a generalization of semiprime module. We investigate several characterizations and properties of this concept.

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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