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Enhanced Oil Recovery using Smart Water Injection
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Smart water flooding (low salinity water flooding) was mainly invested in a sandstone reservoir. The main reasons for using low salinity water flooding are; to improve oil recovery and to give a support for the reservoir pressure.

In this study, two core plugs of sandstone were used with different permeability from south of Iraq to explain the effect of water injection with different ions concentration on the oil recovery. Water types that have been used are formation water, seawater, modified low salinity water, and deionized water.

The effects of water salinity, the flow rate of water injected, and the permeability of core plugs have been studied in order to summarize the best conditions of low salinity water flooding. The result of this experimental work shows that the water without any free ions (deionized water) and modified low salinity water have improved better oil recovery than the formation water and seawater as a secondary oil process. The increase in oil recovery factor related to the wettability alteration during low salinity water flooding which causes a decrease in the interfacial tension between the crude oil in porous media and the surface of reservoir rocks. As well as the dissolution of minerals such as calcite Ca+2 was observed in this work, which causes an increase in the pH value. All these factors led to change the wettability of rock to be more water-wet, so the oil recovery can be increased.

 

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Publication Date
Sat Jan 01 2011
Journal Name
Baghdad Science Journal
Effect of cultar, potassium and salinity of irrigation water on some characteristics of vegetative growth of two cultivars of apricot (Prunus armeniaca L.)‏
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Publication Date
Tue Jan 01 2013
Journal Name
Innovative Systems Design And Engineering
Water And Alcohol Extraction Of Thyme Plant (Thymus Vulgaris) And Activity Study Against Bacteria, Tumors And Used As Anti-Oxidant In Margarine Manufacture
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Isolation had been done for active substances from Thyme plant (Thymus Vulgaris) such as volatile oils, Saponins and Tannins. The percentage in form was (21.1%),(59.2%),( 9.7%) respectively. Also a study of anti-bacterial activity of extracts from Thyme using two types of pathogenic bacteria Escherichia Coli and aurous Staphylococcus showed the ability of inhibition for all different extracts by vary inhibition diameters for different active substances, concentrations and bacteria. One type of cancer cellular line used to study the effect of Thyme extracts on the growth of cells in the laboratory and thus know the specifications of extracts as anti-tumor, (L20B) cell line have been used which is mice Transformed cell Line. The possibility o

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Publication Date
Tue Apr 30 2019
Journal Name
Journal Of Planner And Development
The environmental impacts of reviving Hor Alsnav By the water of the river of out fall drain in the province of Dhi Qar
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The aim of this study is to explain methods to be followed for the recovery Alsnav Hor, who represents the northwest portion of the Hammar Marsh in the province of Dhi Qar, after the drought in which that happened in 2008. The study included description of the region before the drought, the description of its natural and human environments, the economic events and activities, then the study included drought throughout the region, the environmental impacts caused by drought, its impact on social reality, economic and healthy for its environment, and then reached to the problems of social and economic in the region, depending on the Field studies and documented in the specialized government departments, information analysis for the

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Publication Date
Wed Nov 30 2016
Journal Name
International Business Management
ESTIMATE OF THE MULTIPLIER EFFECT OF THE MONETARY AND FISCAL POLICY ON NON-OIL GROSS DOMESTIC PRODUCT IN THE IRAQI ECONOMY FOR THE PERIOD OF 1990-2014
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The monetary policy is a vital method used in implementing monetary stability through: the management of income and adjustment of the price (monetary targets) in order to promote stability and growth of real output (non-cash goals); the tool of interest rate and direct investment guides or movement towards the desired destination; and supervisory instruments of monetary policy in both quantitative and qualitative. The latter is very important as a standard compass to investigate the purposes of the movement monetary policy in the economy. The public and businesses were given monetary policy signals by those tools. In fiscal policy, there are specific techniques to follow to do the spending and collection of revenue. This is done in order to

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Publication Date
Wed Feb 04 2026
Journal Name
Proceedings Of The 2026 2nd International Conference On Computing And Emerging Sciences
Development of Design fuzzy logic hierarchy structure by Using Decision Tree Algorithm
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Sustainable development has recently gained significant attention in the field of water Quality (WQ), which is critical for a healthy lifestyle. Our work suggests an intelligent hybrid model for assessing water quality using a water portability dataset, which was used to evaluate the water quality. The dataset contains physical and chemical features such as pH, Organic Carbon, sulfate, etc. Based on the combination of a Decision Tree Algorithm (DTA) and fuzzy logic Approaches, the findings revealed that sulfate was the most important factor in the model, with an accuracy of 1.00, followed by pH with an accuracy of 0.9667, and solids and chloramines with an accuracy of 0.95. The other parameters achieved a similar accuracy of 0.9167, showing

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Shadow Removal Using Segmentation Method
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Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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