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Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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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
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Thu Oct 01 2009
Journal Name
Iraqi Postgraduate Medical J
Scarring and none scarring facial Acne vulgaris and the frequency of associated skin diseases
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S Khalifa E, AH Khalil I, N Adil A, AB Razan A…, 2009

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Postgraduate Medical Journal
Scarring and None Scarring Facial Acne Vulgaris and the Frequency of Associated Skin Diseases
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BSTRACT: BACKGROUND: Acne vulgaris(AV)is chronic inflammatory disease of pilosebaceous unit of young people. Patients with acne with or with out scarring might differ in regard to their immunological background from those free from acne. OBJECTIVES: To evaluate the problem of facial AV especially patients with scarring and to determine the frequency of associated skin diseases and to be compared with acne free control. METHODS: A cross sectional randomized controlled epidemiological study was conducted from Oct.2005-Oct. 2006.Three hundred students from Basra University; 132 (44%) males and 168 (56%) females were enrolled, their ages ranged from 18-25 (20.9±1.8) years. They were divided into: Group A those free from acne (98 individuals),G

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Neural Tube Defects in Iraq
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1.
Embryonic Origin of Neural Tube Defects.
Insaf Jasim Mahmoud
2.
Etiology of Neural Tube Defectss.
Ali Abdul Razzak Obed
3.
Epidemiology of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi
4.
Surgical Management of Neural Tube Defects.
Laith Thamer Al-Ameri
5.
Prevention of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi

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Publication Date
Tue Jul 31 2018
Journal Name
The Open Electrical &amp; Electronic Engineering Journal
Minimum Delay Congestion Control in Differentiated Service Communication Networks
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This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

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Publication Date
Fri Jun 30 2006
Journal Name
Al-kindy College Medical Journal
The Use of Spiral Computerized Tomography in the Diagnosis of Middle –Third Facial Fractures as Compared to Plain Radiography
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Background: Trauma is one of the most common
clinical problems that confront the maxillofacial
surgeon and radiologist alike. Middle third facial
fractures are diagnosed primarily on the bases of
clinical examination and plain radiographs than can
result in much preoperative speculation.
Objective: To assess the advantages of spiral
computerized tomography over conventional
radiography in the pre-surgical evaluation of middle
third facial fractures.
Methods: Thirty patients with thirty-eight facial
fractures were studied, all patients were examined
clinically, by plain radiography and then by spiral CT.
Results: Of the 38 middle-third fractures, 16
(42.1%) were zygomatic fractures, 8 (21.1%) were

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