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Adaptive inter frame compression using image segmented technique
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The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.

           Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit, the research modifies a method for video image data compression based on the two-component code; in this coding technique, the video image is partitioned into regions of slowly varying intensity. The contours separating the regions are coded by DCT, while the rest image regions are coded by Block-Truncation Coding. this hybrid coding technique called segmented image coding (SIC). Also in this paper A modify of the four step search for motion Estimation technique was produce. for searching scheme has been introduced which is contributed in decreasing  the motion estimation  searching time of the successive inter frames.

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Publication Date
Tue Sep 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Microwave Assisted Demulsification of Iraqi Crude Oil Emulsions Using Tri-octyl Methyl Ammonium Chloride (TOMAC) Ionic Liquid
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In the present work, the efficiency of Tri-octyl Methyl Ammonium Chloride (TOMAC) ionic liquid was investigated as new and green demulsifier for three types of Iraqi crude oil emulsions (Nafut Khana (NK), Kirkuk and Basrah). The separation efficiency was studied at room temperature and by using microwave heating technique. Several batch experiments were done to specify the suitable conditions for the emulsification and demulsification which were specified as 45 minutes and 3000 rpm for crude oil emulsification while the ionic liquid doses were (500,300,150,50) ppm and the conditions of microwave heating were 1000 watt and 50 second as irradiation time. The results were very encouraging especially for NK and Kirkuk crude oil emulsions whe

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Publication Date
Mon May 01 2017
Journal Name
Nano Hybrids And Composites
White Light Generation from Electroluminescence Devices Using TPD:PMMA/QDs/Alq<sub>3</sub>
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Quantum dots of CdSe, CdS and ZnS QDs were prepared by chemical reaction and used to fabricate organic quantum dot hybrid junction device. QD-LEDs were fabricated using layers of ITO/TPD: PMMA/CdSe/Alq3, ITO/TPD: PMMA/CdS/Alq3 and ITO/TPD: PMMA/ZnS/Alq3 devices which prepared by phase segregation method. The hybrid white light emitting devices consists, of three-layers deposited successively on the ITO glass substrate; the first layer was of N, N’-bis (3-methylphenyl)-N, N’-bis (phenyl) benzidine (TPD) polymer mixed with polymethyl methacrylate (PMMA) polymers. The second layer was QDs while the third layer was tris (8-hydroxyquinoline) aluminium (Alq3

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Enhancing Assurance Services Using Non-Renewable Resources Standard (NR0401) “Constructive Materials: Applied Research for Kufa Cement Factory
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The importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab

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Publication Date
Tue Nov 08 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
The effect of background vacuum pressure on the length of gas discharge plasma by using Aluminum electrodes
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Length of plasma generated by dc gas discharge under different vacuum pressures was studied experimentally. The cylindrical discharge tube of length 2m was evacuated under vacuum pressure range (0.1-0.5) mbar at constant external working dc voltage 1500V. It was found that the plasma length (L) increased exponentially with increasing of background vacuum air pressure. Empirical equation has been obtained between plasma length and gas pressure by using Logistic model of curve fitting. As vacuum pressure increases the plasma length increases due to collisions, ionizations, and diffusions of electrons and ions.

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
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Thu May 16 2019
Journal Name
Al-khwarizmi Engineering Journal
Study of Transverse and Longitudinal Crack Propagation in Human Bone Using the Finite Element Method with MATLAB
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A finite element is a study that is capable of predicting crack initiation and simulating crack propagation of human bone. The material model is implemented in MATLAB finite element package, which allows extension to any geometry and any load configuration. The fracture mechanics parameters for transverse and longitudinal crack propagation in human bone are analyzed. A fracture toughness as well as stress and strain contour are generated and thoroughly evaluated. Discussion is given on how this knowledge needs to be extended to allow prediction of whole bone fracture from external loading to aid the design of protective systems.

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Mechanisms of Plant-Correlation Phytoremediation of Al-Daura Iraqi Refinery Wastewater Using Wetland Plant from Tigris River
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In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant

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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
Consideration of Worker Safety in the Design Process: A Statistical-Based Approach Using Analysis of Variance (ANOVA)
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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