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Modeling and Optimization the Influence of CO2-MAG Welding Parameters on the Weld Joint Shape Factors
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This paper represents an experimentalattempt to predict the influence of CO2-MAG welding variables on the shape factors of the weld joint geometry. Theinput variables were welding arc voltage, wire feeding speed and gas flow rate to investigate their effects on the shape factorsof the weld joint geometry in terms of weld joint dimensions (bead width, reinforcement height, and penetration). Design of experiment with response surface methodology technique was employed to buildmathematical models for shape factors in terms of the input welding variables. Thepredicted models were found quadratic type and statistically checked by ANOVA analysis for adequacy purpose. Also, numerical and graphical optimizations were carried out to determine the optimum values for all responses and input variables. The optimum values of the voltage, wire feeding speed, gas flow rate, WPSF, and WRFF are (20 Volt), (153 cm/min), (10 L/min), (5.222), and (3.970), respectively. And, a good agreement was found between the experimental and predicted results. The weld joint efficiency was found (73%) at the optimum conditions.

 

 

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Properties of Kumaraswamy binary Distribution and compare methods of estimating parameters
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The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Visual Modeling Language for Agent Treasury Pharmaceutical
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The researches to discover useful ways to represent the agents and agent-based
systems are continuous. Unified Modeling Language (UML) is a visual modeling language
used for software and non software modeling systems. The aim of this paper is: using UML
class diagram to design treasury pharmaceuticals agent and explain its internal action. The
diagram explains the movement of the agent among other nodes to achieve user's requests
(external) after it takes them. The paper shows that it is easy to model the practical systems by
using agent UML when they are used in a complex environment.

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Publication Date
Wed Nov 02 2022
Journal Name
Annals Of Forest Research
EXTRACTION AND OPTIMIZATION LIGNINOLYTIC ENZYMES LACCASE, LIGNIN PEROXIDASE AND MANGANESE PEROXIDASE FROM TERMITE
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Publication Date
Sun Oct 15 2017
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Optimization of IPv6 Protocol Independent Multicast-Sparse Mode Multicast Routing Protocol based on Greedy Rendezvous Point Selection Algorithm
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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Ecological Engineering
Enhancing the Removal of Methyl Orange Dye by Electrocoagulation System with Nickel Foam Electrode – Optimization with Surface Response Methodology
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Azo dyes like methyl orange (MO) are very toxic components due to their recalcitrant properties which makes their removal from wastewater of textile industries a significant issue. The present study aimed to study their removal by utilizing aluminum and Ni foam (NiF) as anodes besides Fe foam electrodes as cathodes in an electrocoagulation (EC) system. Primary experiments were conducted using two Al anodes, two NiF anodes, or Al-NiF anodes to predict their advantages and drawbacks. It was concluded that the Al-NiF anodes were very effective in removing MO dye without long time of treatment or Ni leaching at in the case of adopting the Al-Al or NiF-NiF anodes, respectively. The structure and surface morphology of the NiF electrode were inves

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Publication Date
Thu Sep 01 2022
Journal Name
Fuel
Experimental evaluation of Carbon Dioxide-Assisted Gravity Drainage process (CO2-AGD) to improve oil recovery in reservoirs with strong water drive
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Improvement of Fading Channel Modeling Performance for Wireless Channel
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Fading channel modeling is generally defined as the variation of the attenuation of a signal with various variables. Time, geographical position, and radio frequency which is included. Fading is often modeled as a random process. Thus, a fading channel is a communication channel that experiences fading. In this paper, the proposed system presents a new design and simulate a wireless channel using Rayleigh channels. Rayleigh channels using two approaches (flat and frequency-selective fading channels) in order to calculate some path space loss efforts and analysis the performance of different wireless fading channel modeling. The results show that the bite error rate (BER) performance is dramatically improved in the value of signal to

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