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Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Finding the best estimation of generalized for failure rates by using Simulation
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The statistical distributions study aimed to obtain on best descriptions  of variable sets phenomena, which each of them got one behavior of that distributions .  The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result  this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods  like greatest ability, minimum squares method and Mixing method (suggested method).        

The research

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Spectrophotometric Method for the Estimation of Ceftriaxone in Pure Form and Pharmaceuticals
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Ceftriaxone sodium were one of the widely antibacterial drugs used. Azo dye derivatization of diazonium salt that formed via the reaction between ceftriaxone with hydrochloric acid and sodium nitrite was developed for the on-research drug analysis then coupling with each one 2,5-dimethylphenol (2,5-DMP) and 4-tertbutylphenol (4-TBP) respectively in the alkaline media. The developed diazonium coupling methods include an optimization study. The results show a limit of detection and limit of quantification 0.482, 0.284 µg/mL, and 1.607, 0.945 µg/mL using 2,5-DMP and 4-TBP reagents respectively. Moreover, the recovery % obtained was 100.89%, and 103.37% at linear concentration range 3.0 – 50, and 10 – 30 µg/mL, with mo

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Thu Apr 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Exponential Distribution under Different Loss Functions
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In this paper, two parameters for the Exponential distribution were estimated using the
Bayesian estimation method under three different loss functions: the Squared error loss function,
the Precautionary loss function, and the Entropy loss function. The Exponential distribution prior
and Gamma distribution have been assumed as the priors of the scale γ and location δ parameters
respectively. In Bayesian estimation, Maximum likelihood estimators have been used as the initial
estimators, and the Tierney-Kadane approximation has been used effectively. Based on the MonteCarlo
simulation method, those estimators were compared depending on the mean squared errors (MSEs).The results showed that the Bayesian esti

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Reliability Estimation for the Exponential Distribution Based on Monte Carlo Simulation
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        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of a Dot -ELIZA for the Diagnosis of Human Hydatid Disease
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Fourty  -tow   Libyan     patients  with  hydatidosis,  which  were

referred to by the physician for the detection of hydatid cyst by X - rays, Ultrasound and CT-Scan.  The  infection rate  in  females and males was(69% )and (31% )respectively .The highest rate 69% was in the liver, followed by the lung( 23.8%), the brain (4.8%) and kidney

(2.4%).

A total of  42 serum  samples were gathered from Libyan patients infected with hydatidosis, 33 serum samples from patients cases with other parasitic diseases than hydatidosis and 30 serum samples from healthy normal controls and were tested by Dot-ELIZA utilizing antigen B from sheep hy

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Medical Image Classification for Coronavirus Disease (COVID-19) Using Convolutional Neural Networks
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     The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

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Scopus (15)
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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
PFDINN: Comparison between Three Back-propagation Algorithms for Pear Fruit Disease Identification
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     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

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