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High-accuracy models for iris recognition with merging features
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Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual information (MI), along with analysis of variance (ANOVA) for feature selection. Two iris classification systems were developed: one using LDA as an input for the OneR machine learning algorithm and another innovative hybrid model based on a One Dimensional Convolutional Neural Network (HM-1DCNN). The MMU database was employed, achieving a performance measure of 94.387% accuracy for the OneR model. Additionally, the HM-1DCNN model achieved 99.9% accuracy by integrating LDA with MI and ANOVA. Comparisons with previous studies show that the HM-1DCNN model performs exceptionally well, with at least 1.69% higher accuracy and lower processing time.

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Publication Date
Tue Apr 06 2021
Journal Name
Journal Of Polymers And The Environment
Novel Sorbent of Sand Coated with Humic Acid-Iron Oxide Nanoparticles for Elimination of Copper and Cadmium Ions from Contaminated Water
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Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Economics And Finance Studies
INTEGRATION BETWEEN COBIT AND COSO FOR INTERNAL CONTROL AND ITS REFLECTION ON AUDITING RISK WITH CORPORATE GOVERNANCE AS THE MEDIATING VARIABLE
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an education program for Caregivers Knowledge Related to Management of Children with Growth Hormone Deficiency in Outpatient Endocrine Clinics
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Objectives: The study aims to assess and evaluate the caregivers  knowledge  about management of the children with growth hormone deficiency and to find out the relationship between caregivers kowledge and caregivers age, gender, number of individual in house hold, Date of treatment started ,Caregivers level education and economic status Methodology: Quazi expermental study design was carried out at (Child's Central Teaching Hospital, Medical City of Al Imamian Al Khadhmain Teaching Hospital, and National Centre for Treatment and Research of Diabetes,Specialized Center for Endocrine Diseases and Diabetes, and Department of Medical City Children Welfare Teaching Hospital started  from 

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Integration between hydrochemical and physical data with geographic information systems (GIS) for selecting the best locations groundwater wells in Baghdad city
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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Thu May 01 2025
Journal Name
Journal Of Industrial And Engineering Chemistry
An innovative combination of anodic oxidation using Cu/SnO2–Sb2O5 rotating cylinder anode with TiO2 photocatalytic process for treating hospital wastewater
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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

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Publication Date
Sun Nov 01 2015
Journal Name
Karbala International Journal Of Modern Science
Batch and flow injection spectrophotometric methods for the determination of barbituric acid in aqueous samples via oxidative coupling with 4-aminoantipyrine
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A batch and flow injection (FI) spectrophotometric methods are described for the determination of barbituric acid in aqueous and urine samples. The method is based on the oxidative coupling reaction of barbituric acid with 4-aminoantipyrine and potassium iodate to form purple water soluble stable product at λ 510 nm. Good linearity for both methods was obtained ranging from 2 to 60 μg mL−1, 5–100 μg mL−1 for batch and FI techniques, respectively. The limit of detection (signal/noise = 3) of 0.45 μg mL−1 for batch method and 0.48 μg mL−1 for FI analysis was obtained. The proposed methods were applied successfully for the determination of barbituric acid in tap water, river water, and urine samples with good recoveries of 99.92

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis of new Conjugates of some NSAIDs with Sulfonamide as Possible Mutual Prodrugs using Tyrosine Spacer for Colon Targeted Drug Delivery
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The purpose of this research work is to synthesize conjugates of some NSAIDs with sulfamethoxazole as possible mutual prodrugs to overcome the local gastric irritation of NSAID with free carboxyl group by formation of ester linkage that supposed to remain intact in stomach and may hydrolyze in intestine chemically or enzymatically; in addition to that attempting to target the synthesized derivative to the colon by formation of azo group that undergo reduction only by colonic bacterial azo reductaze enzyme to liberate the parent compound to act locally (treatment of  inflammation and infections in colon).

Key words: Mutual prodrug, Ester linkage, Azo bond, Colon targeting

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Publication Date
Mon May 01 2017
Journal Name
Ieee International Electrical Machines & Drives Conference Ieee (iemdc2017), Miami, Usa
The effect of power converter on the design of a Linear Alternator for use with a Joule Cycle-Free Piston Engine
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