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Deep Learning and Machine Learning via a Genetic Algorithm to Classify Breast Cancer DNA Data
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       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

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Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function
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In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.

Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Weibull Distribution under Generalized Weighted Loss Function
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In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Effect of Anti Diuretic Hormon (ADH) in Kidney Function on Post Hemodialysis End Stage Renal Failure Disease (ESRD) Iraqi Patients
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Chronic renal disease (CRD) is a patho-physiologic process with multiple etiologies, resulting in the inexorable attrition of Nephron number and function and frequently leading to end-stage renal disease (ESRD). In turn, ESRD represents a clinical state or condition in which there has been an irreversible loss of endogenous renal function, of a degree sufficient to render the patient permanently dependent upon renal replacement therapy (dialysis of transplantation) in order to avoid life threatening uremia. The current study was applied on 80 patients, the age range within 25-70 years, selected sample of patients who attend Iraqi center of kidney dialysis, Baghdad Teaching Hospital and Al-Yarmok Teaching Hospital . All t

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Spot Size on the Fractal Optical Modulation
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The present paper analyzes the signal emitting from the Reticle during changing the spot size of laser falling on the disk and shows the optimum frequency and the amount of energy window in different patterns of modulator (Reticle).  All results are obtained by establishing   a special program named “Disk optical modulator version 3" using the language visual basic 6 ahich contains many parameters. All models of optical modulator consist of twenty sectors, ten sectors are opaque and other ten sectors are transmitted for the laser. The number of sectors depends on several factors as chopping frequency, power transparent and modulation transfer function.   It has been demonstrated by simulations, the optimal

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Fuzzy Based Clustering for Grayscale Image Steganalysis
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Fuzzy Based Clustering for Grayscale Image Steganalysis

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Publication Date
Sun Apr 26 2020
Journal Name
Iraqi Journal Of Science
Fixed Point Theorem for Set Valued Mapping with Rational Condition
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In this paper, we generalized the principle of Banach contractive to the relative formula and then used this formula to prove that the set valued mapping has a fixed point in a complete partial metric space. We also showed that the set-valued mapping can have a fixed point in a complete partial metric space without satisfying the contraction condition. Additionally, we justified an example for our proof.

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study of the Anti-Diuretic Hormone (ADH) on End Stage Renal Failure Disease (ESRD) Pre-Hemodialysis in Iraqi Patients
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     Chronic renal disease (CRD) is a pathophysiologic process with multiple etiologies, resulting in the inexorable attrition of Nephron number and function and frequently leading to end-stage renal disease (ESRD). In turn, ESRD represents a clinical state or condition in which there has been an irreversible loss of endogenous renal function, of a degree sufficient to render the patient permanently dependent upon renal replacement therapy (dialysis of transplantation) in order to avoid life threatening uremia, reflecting a dysfunction of all organ systems as a result of untreated or under treated acute or chronic renal failure. The current study was involved 80 patients, the age range within 25-70 ye

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function
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This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
The Local Bifurcation of an Eco-Epidemiological Model in the Presence of Stage- Structured with Refuge
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In this paper, we establish the conditions of the occurrence of the local bifurcations, such as saddle node, transcritical and pitchfork, of all equilibrium points of an eco-epidemiological model consisting of a prey-predator model with SI (susceptible-infected) epidemic diseases in prey population only and a refuge-stage structure in the predators. It is observed that there is a transcritical bifurcation near the axial and free predator equilibrium points, near disease-free equilibrium point is a saddle-node bifurcation and near positive (coexistence) equilibrium point is a saddle-node bifurcation, a transcritical bifurcation and a pitchfork bifurcation. Further investigations for Hopf bifurcation near coexistence equilibrium point are

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