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Medical Image Enhancement to Extract Brain Tumors from CT and MRI images
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     Always MRI and CT Medical images are noisy so that preprocessing is necessary for enhance these images to assist clinicians and make accurate diagnosis. Firstly, in the proposed method uses two denoising filters (Median and Slantlet) are applied to images in parallel and the best enhanced image gained from both filters is voted by use PSNR and MSE as image quality measurements. Next, extraction of brain tumor from cleaned images is done by segmentation method based on k-mean.  The result shows that the proposed method is giving an optimal solution due to denoising method which is based on multiple filter types to obtain best clear images and that is leads to make the extraction of tumor more precision best.

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Mon Jul 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Applying Shrinkage Estimation Technique of P(Y<Max X1, X2,…, Xk) in Case of Generalized Exponential Distribution
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     This paper concerned with estimation reliability (­ for K components parallel system of the stress-strength model with non-identical components which is subjected to a common stress, when the stress and strength follow the Generalized Exponential Distribution (GED) with unknown shape parameter α and the known scale parameter θ (θ=1) to be common. Different shrinkage estimation methods will be considered to estimate ­ depending on maximum likelihood estimator and prior estimates based on simulation using mean squared error (MSE) criteria. The study approved that the shrinkage estimation using shrinkage weight function was the best.

 

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Utilizing a Magnetic Abrasive Finishing Technique (MAF) Via Adaptive Nero Fuzzy(ANFIS)
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 Abstract

An experimental study was conducted for measuring the quality of surface finishing roughness using magnetic abrasive finishing technique (MAF) on brass plate which is very difficult to be polish by a conventional machining process where the cost is high and much more susceptible to surface damage as compared to other materials. Four operation parameters were studied, the gap between the work piece and the electromagnetic inductor, the current that generate the flux, the rotational Spindale speed and amount of abrasive powder size considering constant linear feed movement between machine head and workpiece. Adaptive Neuro fuzzy inference system  (ANFIS) was implemented for evaluation of a serie

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Charge density distributions for odd-A of 2s-1d shell nuclei
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An analytical expression for the charge density distributions is derived based on the use of occupation numbers of the states and the single particle wave functions of the harmonic oscillator potential with size parameters chosen to reproduce the observed root mean square charge radii for all considered nuclei. The derived expression, which is applicable throughout the whole region of shell nuclei, has been employed in the calculations concerning the charge density distributions for odd- of shell nuclei, such as and nuclei. It is found that introducing an additional parameters, namely and which reflect the difference of the occupation numbers of the states from the prediction of the simple shell model leads to obtain a remarkabl

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
On y-closed Dual Rickart Modules
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In this paper, we develop the work of Ghawi on close dual Rickart modules and discuss y-closed dual Rickart modules with some properties. Then, we prove that, if are y-closed simple -modues and if -y-closed is a dual Rickart module, then either Hom ( ) =0 or . Also, we study the direct sum of y-closed dual Rickart modules.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Reliability Estimation for the Exponential-Pareto Hybrid System
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     The reliability of hybrid systems is important in modern technology, specifically in engineering and industrial fields; it is an indicator of the machine's efficiency and ability to operate without interruption for an extended period of time. It also allows for the evaluation of machines and equipment for planning and future development. This study looked at reliability of hybrid (parallel series) systems with asymmetric components using exponential and Pareto distributions. Several simulation experiments were performed to estimate the reliability function of these systems using the Maximum Likelihood method  and the Standard Bayes method  with a quadratic loss (QL) function and two priors: non-informative (Jeffery) and inform

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On A Bitopological (1,2)*- Proper Functions
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   In this paper, we introduce a new type of functions in bitopological spaces, namely, (1,2)*-proper functions. Also, we study the basic properties and characterizations of these functions . One of the most important of equivalent definitions to the (1,2)*-proper functions is given by using (1,2)*-cluster points of filters . Moreover we define and study (1,2)*-perfect functions and (1,2)*-compact functions in bitopological spaces and we study the relation between (1,2)*-proper functions and each of (1,2)*-closed functions , (1,2)*-perfect functions and (1,2)*-compact functions and we give an example when the converse may not be true .
 

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Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Bayes' Estimators for the Exponential Reliability Function Under Different Prior Functions
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 In this study, we derived the estimation for Reliability of the Exponential distribution based on the Bayesian approach. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .We  derived  posterior distribution the parameter of the Exponential distribution under four types priors distributions for the scale parameter of the Exponential distribution is: Inverse Chi-square distribution, Inverted Gamma distribution, improper distribution, Non-informative distribution. And the estimators for Reliability is obtained using the two proposed loss function in this study which is based on the natural logarithm for Reliability function .We used simulation technique, to compare the

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Publication Date
Thu Apr 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate Complete the Survival Function for Real Data of Lung Cancer Patients
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 In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best

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Publication Date
Tue Jun 04 2024
Journal Name
Int. J. Operational Research
Pascal’s triangle graded mean defuzzification approach for solving fuzzy assignment models by using pentagonal fuzzy numbers
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The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal’s triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely deve

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