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Different estimation methods of reliability in stress-strength model under chen distribution

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Bayesian Analysis of five Exponentiated Distributions under different Priors and loss functions

The paper is concerned with posterior analysis of five exponentiated (Weibull, Exponential, Inverted Weibull, Pareto, Gumbel) distrebutions. The expressions for Bayes estimators of the shape parameters have been derived under four different prior distributions assuming four different loss functions. The posterior predictive distributions have been obtained, and the comparison between estimators made by using the mean squared errors through generated different sample sizes by using simulation technique. In general, the performance of estimators under Chi-square prior using squared error loss function is the best.

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Publication Date
Wed Nov 20 2024
Journal Name
Journal Of Engineering
Drag Reduction Using Passive Methods on KIA PRIDE Car Model

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Drag Reduction Using Passive Methods on KIA PRIDE Car Model

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the avera

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Clinical Dentistry
THE EFFECT OF A PROTECTIVE BARRIER ON THE SHEAR BOND STRENGTH OF DIFFERENT ORTHODONTIC BRACKETS

Background and objectives: This study aimed at testing the effect of plastic sleeve or barrier, used to cover the guide of the light cure unit to prevent cross-infection, on the shear bond strength and site of bond failure of stainless steel and ceramic orthodontic brackets. Materials and methods: Forty orthodontic brackets; twenty stainless steel and twenty ceramic brackets bonded to forty extracted human maxillary first premolars using light cure adhesive cured with and without the use of a protective plastic barrier on the guide. Comparing the effect of this barrier on the shear bond strength and adhesive remnant index was performed using an independent t-test and Chi-square test. Results: The protective barrier had decreased the shear b

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Scopus
Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Electrical Insulation Breakdown Strength and Thermal Conductivity of Different Blended Nanocomposites of New Epoxy Resins

This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values  are higher while thermal conductivity values of

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Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Electrical Insulation Breakdown Strength and Thermal Conductivity of Different Blended Nanocomposites of New Epoxy Resins

This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values  are higher while thermal conductivity values of

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some Estimation methods for the two models SPSEM and SPSAR for spatially dependent data

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Determination of Mono-crystalline Silicon Photovoltaic Module Parameters Using Three Different Methods

For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of

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Publication Date
Sat Feb 26 2022
Journal Name
Iraqi Journal Of Science
Preparation and Characterization of ZnO Nano-Sheets Prepared by Different Depositing Methods

    Hydrothermal technology has many advantages compared to other growth methods such as the availability of their simple equipment,catalyst-free growth,Environmental friendliness, less dangerous environmental, and low costs. Combine spinning method technology with Hydrothermal could improve the structural of ZnO NS by increasing the formation of ZnO NS due to influence of heat annealed treatments on the structure of ZnO NS.   ZnONano-Sheets (NS)were prepared to employ hydrothermal process utilizing zinc acetate, that  has the chemical composition (Zn (CH3CO2)2.2H2O),as a precursor. After preparing the material, it is deposited in two methods, the first being disti

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Scopus (3)
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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
A Note on the Hierarchical Model and Power Prior Distribution in Bayesian Quantile Regression

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

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