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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
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Priority Based Transmission Rate Control with Neural Network Controller in WMSNs
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Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia appli

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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
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Spectrophotometric Determination of Olanzapine via Coupling with Diazotized p-Nitroaniline
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A new spectrophotometric method has been developed for the assay of olanzapine (OLN.) in pure and dosage forms. The method is based on the diazocoupling of (OLN.) with diazotized p-nitroaniline in alkaline medium to form a stable brown colored water-soluble azo dye with a maximum absorption at 405 nm.  The variables that affect the completion of reaction have been carefully optimized. Beer’s law is obeyed over the concentration range of (0.5-45.0 μg.mL-1) with a molar absorptivity of 1.5777×104 L.mol-1.cm-1.  The limit of detection was  0.3148  Î¼g.mL-1 and  Sandell’s  sensitivity value was 0.0198 μg.cm-2. The propose

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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
Tue Apr 01 2025
Journal Name
Medical Journal Of Babylon
Response to Treatment in a sample of Iraqi Patients with Prolactinoma
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Abstract<sec> <title>Background:

Hyperprolactinemia is a common endocrine abnormality caused by physiological factors like pregnancy and lactation, drug-induced factors like antipsychotics, pituitary adenomas that secrete prolactin, or stalk compression or section that reduces dopamine inhibition. Dopamine agonists cure most prolactinomas.

Objectives:

To assess response to treatment in micro versus macroprolactinoma.

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Plasma levels and diagnostic utility of MMP-2 and TIMP-2 in the diagnosis of Iraqi women with breast tumor: A comparative study with Ca 15-3
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Plasma levels and diagnostic utility of MMP-2 and TIMP-2 in the diagnosis of Iraqi women with breast tumor: A comparative study with Ca 15-3
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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Global Pharma Technology
Calculation of Stabilization Energy of Tetrahedrane with its Nitrogen Substituted Derivatives by DFT Method and Driving an Empirical Relation Connect it with Charge Functions of the Molecule
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In this work the strain energy of tetrahedrane and its nitrogen substituted molecules were calculated by isodesmic reaction method according to DFT quantum chemical fashion, the used basis set was 6-31G/B3-LYP, in addition all structures were optimized by RM1 semi-empirical method. From the obtained data we estimate an empirical equation connect between strain energy of the molecule with charge functions represented by dipole moment of the molecule plus accumulated charge density involved within the tetrahedron frame plus the number of nitrogen atoms. The results indicate the charge spreading factors by polarization and processes are the most important factors in decreasing the strain energy.

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Publication Date
Wed Jun 29 2022
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF OZONE ENRICHMENT AND SPRAYING WITH ORGANIC NUTRIENT ON NUTRIENT AND WATER USE EFFICIENCY AND FERTILIZER PRODUCTIVITY OF BROCCOLI PLANT CULTIVATED HYDROPONICALLY WITH MODIFIED NFT TECHNOLOGY.
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This study was carried out at University of Baghdad - College of Agricultural Engineering Sciences - research station B during the fall season of 2019-2020, in order to evaluate the effect of Ozone enrichment and the foliar application of organic nutrient  on nutrient and water use efficiency and fertilizer productivity of broccoli plant using the modified NFT film technology. A factorial experiment (2*5) was carried out within Nested Design with three replicates. The ozone treatment was distributed into the main plots which consisted of oxygen (O2) and ozone (O3). The foliar application of organic nutrients were distributed randomly within each replicate including five treatments, which were the control treatment (T0), Coconut wat

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