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Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20 people with six images for each person and a measure of the time differences between the methods is given.

 

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
In vitro isolation and expansion of neural stem cells NSCs
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   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Investigation of Size-dependent Nonlinearity of Ag Nano-Fluids using Self-defocusing Technique
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In this work, the effect of different particle size on the nonlinear optical properties of silver nanoparticles in de-ionized water was studied. The experimental observation of the far field diffraction patterns by CCD camera in two and three dimensions. The maximum change of nonlinear refractive index and the relative phase shift were calculated. The self-defocusing technique was used with a continuous-wave radiation from DPSS Blue laser .The wavelength is 473 nm with an output power of 270 mW. All the Ag colloids samples containing the sizes 15, 30, 50, and 70 nm of silver nanoparticles used in the study were chemically prepared. It was found that the nonlinear refractive index is a particle size dependent and of the order of 10-7 cm2/

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Publication Date
Thu Jan 23 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Impact of self-assessment on income and sales tax collections from the point of view of income tax auditors in Jordan
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This study aimed to show the extent of compliance with the income taxpayer  to provide tax returns and increase the speed of collection of these taxes in addition to increasing confidence in  Income Tax department and reduce the number of cases transferred to the courts and promote taxpayer awareness in charge of the importance of system self-assessment, and study sought to investigate the effect of the existence of records documents, technical audit, and computational audit and documentary audit on income tax collections in Jordan, from the point of view of Jordanian income tax auditors ,results shows there's a strong  relation between these variables and Income Tax collections.

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Mon Jul 06 2026
Journal Name
Iraqi Journal For Computer Science And Mathematics
Enhanced Intrusion Detection Using Recurrent Neural Networks with Amino Acid Codon Features
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Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFECT OF ANIMAL FEED SUPPLEMENTATION WITH DIFFERENT CONCENTRATIONS OF FENUGREEK SEEDS (Trigonellafoenumgraecum) ON ANIMAL PRODUCTION AND MICROBIAL CHICKEN MEAT.: EFFECT OF ANIMAL FEED SUPPLEMENTATION WITH DIFFERENT CONCENTRATIONS OF FENUGREEK SEEDS (Trigonellafoenumgraecum) ON ANIMAL PRODUCTION AND MICROBIAL CHICKEN MEAT.
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This study was conducted in the poultry field of Al-Mustansiriya University/ Baghdad, to show the effect of adding different levels 0, 1, 5 and 10% of the fenugreek seeds in the rations containing many contaminated microbes on the productive performance of broilers. 150-day-old rose meat was used with a 41 average weight (gm), were randomly allocated to 4 treatments with 3 replicates, and for each treatment 15 chicks per repetition: 0, 1, 5, and 10% (T0-T3), respectively. The results of this study showed that fenugreek seeds contain good amounts of protein, fat, ash and carbohydrates, which are 24.92, 8.82, 3.08 and 54.28 respectively. Fenugreek seeds also have high levels of tannins, coumarins and flavones, followed by saponins,

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
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Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessment of Serum Levels of Advanced Oxidation Protein Products in Type 2 Diabetic Patients with and without Retinopathy Taking Different Antidiabetic Treatments
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The goal of this study was to investigate the protein peroxidation role by measuring serum levels of advanced oxidation protein products (AOPP) in type 2 diabetic patients with or without retinopathy and comparing them to controls to see if circulating AOPP levels can be used as a detection biomarker for DR. And see which of the two widely used antidiabetic treatment groups had the most impact on this oxidative stress marker. The groups were divided into two subgroups: 1) 70 type 2 diabetic patients (36 male, 34 female), 35 with diabetic retinopathy (DR) and 35 with no evidence of DR, and 2) non-diabetic controls (11 male, 9 female) were chosen from Ibn AL-Haitham Hospital for Ophthalmology and a Specialized Center for Endocrinology and Dia

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Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
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The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

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