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Prediction of Process Parameters That Affecting on Surface Roughness in Multi-Point Forming Process Using ANOVA Algorithm
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Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed that affect the surface integrity for brass (Cu Zn 65-35) with 0.71 mm thickness.

This paper focuses on the development of prediction models for estimation of the product quality. Using Analysis of Variance (ANOVA), surface roughness has been modeled. In the development of this predictive model, blank holder, rubber thickness and forming speed have been considered as model parameters. The mean surface roughness (Ra) is used as response parameter to predict the surface roughness of multipoint forming parts. The data required has been generated, compared and evaluated to the proposed models obtained from experiments.

Taguchi algorithm was used to predict the forming parameters (blank holder, rubber thickness and forming speed) on product roughness in forming process of Brass (Cu Zn 65-35) based on orthogonal array of L9 and finally ANOVA was used to find the optimum parameters that have effect on the product quality.

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Publication Date
Mon Oct 12 2020
Journal Name
Molecules
Phase Change Process in a Zigzag Plate Latent Heat Storage System during Melting and Solidification
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Applying a well-performing heat exchanger is an efficient way to fortify the relatively low thermal response of phase-change materials (PCMs), which have broad application prospects in the fields of thermal management and energy storage. In this study, an improved PCM melting and solidification in corrugated (zigzag) plate heat exchanger are numerically examined compared with smooth (flat) plate heat exchanger in both horizontal and vertical positions. The effects of the channel width (0.5 W, W, and 2 W) and the airflow temperature (318 K, 323 K, and 328 K) are exclusively studied and reported. The results reveal the much better performance of the horizontal corrugated configuration compared with the smooth channel during both melti

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Publication Date
Sun May 28 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
On-Line Navigational Problem of a Mobile Robot Using Genetic Algorithm
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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation
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In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
An Efficient Method for Heat Recovery Process and燭emperature燨ptimization
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Publication Date
Tue Jul 01 2025
Journal Name
South African Journal Of Chemical Engineering
Electrocoagulation process for cobalt removal from industrial wastewater: Optimization and kinetic study
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun Apr 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Information Hiding using LSB Technique based on Developed PSO Algorithm
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<p>Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most effi

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Publication Date
Thu Dec 01 2011
Journal Name
Aes-atema International Conference Series - Advances And Trends In Engineering Materials And Their Applications
Effect of new tool geometry on weld strength of AA2024 aluminum alloy plates welded by friction stir spot welding process
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A new tool geometry was used to achieve friction stir spot welding (FSSW) in which the shoulder was designed separately from the rotating pin, and in order to examine weldment strength through the modified tool, a lap joints of AA2024 aluminum alloy plate 1 mm thick were welded successfully by using 6 mm pin diameter and varying process parameters (rotational speeds, tool nose geometry, and depth of tool penetration in the lower welded plate). Experimental tests indicate that the maximum average tensile shear load was 3100 N at the best selected condition. Microstructure examination and micro hardness test along the spot zones were investigated as well as measuring pin penetration load. Visual inspection of the welded spot surface shows a g

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