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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
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Structural and Morphological Characterization of MEH-PPV Nanocomposite Doped with FeCl3
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Poly [2-methoxy-5-(2-ethylhexyloxy)-1, 4-phenylenevinyl] (MEH-PPV) thin films were created in this study using both spin coating and drop casting processes. MEH-PPV thin films generated by Ferric Chloride (FeCl3) doping (0.03, 0.06, 0.09, and 0.12 wt%) were studied for some physical features using Fourier-Transform Infrared Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FE-SEM), and Energy Dispersive X-ray Spectroscopy (EDX). An FTIR test showed that there was no chemical reaction that occurred between Ferric Chloride (FeCl3) and MEH-PPV, but rather a physical one, that is, an organic material composite occurred. As for FE-SEM, the pure sample MEH-PPV formed uniformly, but when FeCl3 was added by weight, we have differ

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Effectiveness of Deep Brain Stimulation in Iraqi Patients with Parkinson Disease
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Fri Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Aspirin Derivatives Exploration: A Review on Comparison Study with Parent Drug
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In recent decades, drug modification is no longer unusual in the pharmaceutical world as living things are evolving in response to environmental changes. A non-steroidal anti-inflammatory drug (NSAID) such as aspirin is a common over-the-counter drug that can be purchased without medical prescription. Aspirin can inhibit the synthesis of prostaglandin by blocking the cyclooxygenase (COX) which contributes to its properties such as anti-inflammatory, antipyretic, antiplatelet and etc. It is also being considered as a chemopreventive agent due to its antithrombotic actions through the COX’s inhibition. However, the prolonged use of aspirin can cause heartburn, ulceration, and gastro-toxicity in children and adults. This review article hi

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Publication Date
Wed Jan 25 2023
Journal Name
International Journal Of Biomaterials
Surface Characterization of Stainless Steel 316L Coated with Various Nanoparticle Types
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Background. Material tribology has widely expanded in scope and depth and is extended from the mechanical field to the biomedical field. The present study aimed to characterize the nanocoating of highly pure (99.9%) niobium (Nb), tantalum (Ta), and vanadium (V) deposited on 316L stainless steel (SS) substrates which considered the most widely used alloys in the manufacturing of SS orthodontic components. To date, the coating of SS orthodontic archwires with Nb, Ta, and V using a plasma sputtering method has never been reported. Nanodeposition was performed using a DC plasma sputtering system with three different sputtering times (1, 2, and 3 hours). Results. Structural and elemental analyses were conducted on the deposited coating

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Publication Date
Mon Mar 02 2026
Journal Name
Ultrastructural Study Of The Placenta In Women Complication With Diabetes Mellitus
Ultrastructural Study of the Placenta in Women Complication with Diabetes Mellitus
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Diabetes mellitus is a multifaceted, chronic disease that happens either when the pancreas does not produce enough insulin or when the human body cannot competently use the insulin it produces. The study was aimed to determine and show the ultrastructural changes of cells in the placenta of women suffering from diabetes mellitus disease. In this study, a total of 102 placentas were investigated by transmission electron microscopy, which includes 34 placentas with gestational diabetes, 34 placentas with pregestational diabetes, and 34 placentas with normal pregnancy as a control group. Placental vascular-syncytial membrane, trophoblastic basement membrane, villous stroma, and fetal vessel were investigated for their thickening basement membr

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Publication Date
Sat Feb 01 2025
Journal Name
Plant Disease
Plant-Parasitic Nematode Genera Associated with Date Palm in Central Iraq
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A survey of plant-parasitic nematode genera associated with roots of mature date palm trees was conducted in central Iraq to study their occurrence, population density, and geographical distribution. This study in Baghdad, Babil, Diyala, Karbela, Najaf, and Wasit governorates was conducted from 2019 to 2023, during the months from October to April. A total of 150 soil and root samples were gathered from 46 fields, and plant-parasitic nematodes were extracted and morphologically identified to genus level. Eleven genera of plant-parasitic nematodes were detected in the declining order of frequency: Tylenchorhynchus spp. (20%) in Baghdad, Babil, Diyala, Karbala, and Najaf; Meloidogyne spp. (17.3%) in Baghdad, Babil, Diyala, Najaf, and

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Publication Date
Thu Nov 01 2018
Journal Name
Indian Journal Of Public Health Research & Development
Histopathological changes of placenta in pregnant women complicated with pregestational diabetes
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Publication Date
Mon Jan 01 2018
Journal Name
Indian Journal Of Public Health Research & Development
Histopathological alternations of placenta in pregnancy women complicated with gestational diabetes
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

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