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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
Sun Nov 17 2019
Journal Name
Journal Of Interdisciplinary Mathematics
Fuzzy preinvexity via ranking value functions with applications to fuzzy optimization problems
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Publication Date
Fri Jan 07 2022
Journal Name
Materials
Impact Behavior of Composite Reinforced Concrete Beams with Pultruded I-GFRP Beam
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The present study experimentally and numerically investigated the impact behavior of composite reinforced concrete (RC) beams with the pultruded I-GFRP and I-steel beams. Eight specimens of two groups were cast in different configurations. The first group consisted of four specimens and was tested under static load to provide reference results for the second group. The four specimens in the second group were tested first under impact loading and then static loading to determine the residual static strengths of the impacted specimens. The test variables considered the type of encased I-section (steel and GFRP), presence of shear connectors, and drop height during impact tests. A mass of 42.5 kg was dropped on the top surface at the m

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Publication Date
Sun Jan 01 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
The dynamics of a delayed ecological model with predator refuge and cannibalism
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This study has contributed to understanding a delayed prey-predator system involving cannibalism. The system is assumed to use the Holling type II functional response to describe the consuming process and incorporates the predator’s refuge against the cannibalism process. The characteristics of the solution are discussed. All potential equilibrium points have been identified. All equilibrium points’ local stability analyses for all time delay values are investigated. The system exhibits a Hopf bifurcation at the coexistence equilibrium, which is further demonstrated. The center manifold and normal form theorems for functional differential equations are then used to establish the direction of Hopf bifurcation and the stability of the per

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Publication Date
Thu Feb 26 2026
Journal Name
Buildings
Performance Analysis of Cement Mortar Modified with Nano-Silica and Nano-Alumina
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The limitations of conventional cement mortar as a widely used construction material include low tensile capacity, high permeability, and susceptibility to chemical degradation. The increasing demand for durable and sustainable construction materials has led to increased attention in modifying cementitious materials through nanotechnology. This study investigates the influence of nano-silica (NS) and nano-alumina (NA) on the physical, strength-related, and durability characteristics of cement mortar to determine the optimum nanomaterial type and dosage for performance enhancement. Six mortar mixes, in addition to a reference mix, were designed and prepared by adding 1%, 1.5%, and 2% of the cement weight with NS and NA separately, an

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Publication Date
Sat Mar 21 2026
Journal Name
Iraqi Journal Of Hematology
Assessment of the immunomodulatory cytokines interleukin-35, interleukin-10, and transforming growth factor-β in patients with idiopathic immune thrombocytopenia purpura on treatment with romiplostim: A cross-sectional analysis
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BACKGROUND: Idiopathic immune thrombocytopenia purpura is an autoimmune bleeding disorder that accounts for approximately one-third of clinical hemorrhagic diseases. Pathophysiologically, it involves a complicated imbalance in the immune system. OBJECTIVES: This study focuses on evaluating the levels of the immunomodulatory cytokines interleukin (IL)-35, interleukin-10, and transforming growth factor-β (TGF)-β in patients with refractory idiopathic immune thrombocytopenia undergoing treatment with romiplostim. MATERIALS AND METHODS: A cross-sectional study encompassed 78 individuals with idiopathic immune thrombocytopenia and conducted measurements of different immunomodulatory cytokines in response to different responses of idiopath

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Publication Date
Mon Jan 01 2018
Journal Name
Research Journal Of Pharmacy And Technology
Impact of Human Cytomegalovirus Infection associated with the expressed protein of mutated <i>BRCA1</i> gene in breast tissues from a group of Iraqi Female Patients with Breast Carcinoma
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Sun Jul 29 2018
Journal Name
Science International
THE EFFECT OF QUR'ANIC VERSES STRATEGY ON ACHIEVING SCIENCE AND SYSTEMIC INTELLIGENCE FOR SECOND GRADE STUDENTS.
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The objective of the research is to uncover the effect of the strategy of Quranic verses in the collection of science and systemic intelligence for second-grade students. The research sample consisted of (48) students of second grade students in the middle of Al Rasheed Boys School of the second Karkh Directorate, Distribution in the two divisions, Division of (b) and experimental group that studied strategy of Quranic verses, and the Division (a) control group which studied the regular way, and results indicated a statistically significant differences for the experimental group students studied using the strategy Verses in systemic intelligence collection.

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Difficulties toward third level students in the department of Arabic language for both Education for Women College and Ibn Rushd/University of Baghdad for the studying of Arabic language curriculum: Difficulties toward third level students in the department of Arabic language for both Education for Women College and Ibn Rushd/University of Baghdad for the studying of Arabic language curriculum
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Abstract
The curriculum is amodern science which reflects the social philosophy and
what it needs . It searches for amothod that limits the knowledge that the
indiridual gets in the society and the sorts of the culture that suits the enrironment
in which they live. It also clears for them their history and their great in heritance.
It has a great in flunce in their mental growth ,and it teacher the students new
roles in the thin king ,and training then on what they have learned . According to
there points the problem concentrats on the mostimpotant difficulties which facer
thestudents in studing Arabic langnage text-books
In spite of the great care that the text taker but it is full of subjects and studies
w

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