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Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determining the optimal processing variables of Electrical Discharge Machining.

The material removal rate (MRR) and tool wear (Tw) were investigated using the process variables of pulse on time (Ton), pulse off time (Toff), and current intensity (Ip). The established empirical models were used to perform Genetic Algorithm (GA) to maximize (MRR) and minimize (Tw). The optimization results were utilized to establish machining conditions, validate empirical models, and obtain optimization outcomes. The optimal result that appears in this work was the pulse on (176.261 μs), pulse off (39.42 μs), and current intensity (23.62 Amp.) to maximize the MRR to (0.78391 g/min) and reduce tool wear to (0.0451 g/min).

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Aeronautical Materials
Motor Response Speed And Its Relationship To The Performance Accuracy Of A Skills Of Passing From The Top And Smash Serve In Volleyball
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The game of volleyball requires the formation of new motor responses, which in turn requires special physical characteristics in the performance of that skill, and the correct and accurate performance during the performance of the skills of passing from the top and smash serve in volleyball cannot be developed or improved without a good level of accuracy and what is required to perform the movements in terms of responses to the defense and attack movements. Therefore, the researchers decided to identify the type of relationship between the motor response speed with the performance accuracy of the skills of passing from the top and the smash serve in volleyball. The research aims to: 1. Identifying the motor response speed of fourth-stage s

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Enhanced Performance of Consensus Wireless Sensor Controlled System via Particle Swarm Optimization Algorithm
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     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
About Semi-parametric Methodology for Fuzzy Quantile Regression Model Estimation: A Review
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In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
In Vitro Comparative Assessment of Composite Nanoleakage Using Various Dentine Surface Treatments
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Background: The treatment of dental tissues proceeding to adhesive procedures is a crucial step in the bonding protocol and decides the clinical success ofrestorations. This study was conducted in vitro, with the aim of evaluating thenanoleakage on the interface between the adhesive system and the dentine treated by five surface modalities using scanning electron microscopy and energydispersiveX-ray spectrometry. Materials and methods: Twenty five extracted premolars teeth were selected in the study. Standardized class V cavities were prepared on the buccal and lingual surfaces then the teeth divided into five main groups of (5 teeth in each group n=10) according to the type of dentine surface treatment that was used: Group (A): dentine was

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Baghdad College Of Dentistry
In Vitro Comparative Assessment of Composite Nanoleakage Using Various Dentine Surface Treatments
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Background: The treatment of dental tissues proceeding to adhesive procedures is a crucial step in the bonding protocol and decides the clinical success ofrestorations. This study was conducted in vitro, with the aim of evaluating thenanoleakage on the interface between the adhesive system and the dentine treated by five surface modalities using scanning electron microscopy and energydispersiveX-ray spectrometry. Materials and methods: Twenty five extracted premolars teeth were selected in the study. Standardized class V cavities were prepared on the buccal and lingual surfaces then the teeth divided into five main groups of (5 teeth in each group n=10) according to the type of dentine surface treatment that was used: Group (A): dentine was

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Publication Date
Sat Jul 13 2019
Journal Name
Journal Of Northern Europe Academy For Studies & Research Denmark
The relationship between motor response speed and performance of the volleyball smash skill for students at the University of Baghdad - College of Physical Education and Sports Sciences
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NEACADEMY's JOURNALS

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Investigation of the optimum cutting conditions during turning aluminum alloy using Taguchi method
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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