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Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

 

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Transient Stability Enhancement and Critical Clearing Time Improvement for Kurdistan Region Network using Fact Configuration
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The Electrical power system has become vast and more complex, so it is subjected to sudden changes in load levels. Stability is an important concept which determines the stable operation of the power system. Transient stability analysis has become one of the significant studies in the power system to ensure the system stability to withstand a considerable disturbance. The effect of temporary occurrence can lead to malfunction of electronic control equipment. The application of flexible AC transmission systems (FACTS) devices in the transmission system have introduced several changes in the power system. These changes have a significant impact on the power system protection, due to differences inline impedance, line curre

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Applying Water Quality Index Technique to Estimate the Euphrates River Suitability for different uses in Samawa and Nasiriya, Southern Iraq
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     Water salinity assessment is fundamental to the management of water resources. The objective of this research is to calculate the water quality index of the Euphrates River by using mathematical methods. As well as to evaluate the water for various uses by estimating the inorganic pollution in the river water in two sites: Samawa and Nasiriya sites. Based on physiochemical characteristics such as pH, TDS, EC,  and concentrations of the major ions of calcium (Ca2+), sodium (Na+), magnesium (Mg2+), potassium (K+), sulphate (SO42-)  and Chloride (Cl-), bicarbonate ions (HCO3-), and minor elements of nitrate (NO32-

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
A Review on Face Detection Based on Convolution Neural Network Techniques
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     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Radioactivity Levels in Water Samples of Tigris River in Baghdad City, Iraq
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   The natural radioactivity levels in water samples along the Tigris river (one of the major rivers of the world) within Baghdad city were investigated to determine and evaluate the radioactivity risks in the water of the river. The specific activity of the radionuclides (238U, 232Th, 40K, and 137Cs) for thirty different water samples from Tigris river within Baghdad city were measured using gamma-ray spectrometer, employing a NaI(Tl) scintillation detector. The results showed that the average value of the specific activity for 238U, 232Th, 40K, and 137Cs were (24.20, 16.70, 329.22, and 19.40) Bq/l, respectively. The calculated average annual effec

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Publication Date
Sun Dec 05 2021
Journal Name
Iraqi Journal Of Science
Climatic Analysis and Climatic Water Balance Determination for Al- Yusufiyah Area, Southern Baghdad, Iraq
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The Climatic parameters for the years (1985-2015) were collected from Baghdad
meteorological station and then were applied to evaluate the climatic conditions for
the Al-Yusufyiah area south Baghdad. The total annual rainfall is (119.65 mm),
while the total annual evaporation is (3201.7 mm), relative humidity is (43.62%),
sunshine (8.76 h/day), temperature (23.28 C◦) and wind speed (3.06 m/sec). Climate
of the study area is described as an arid according to classification of (Kettaneh and
Gangopadhyaya, 1974), (Mather, 1973), and (Al-Kubaisi, 2004). Mean monthly
water surplus for the period (1985-2015) was recorded in the study area about (4.7
mm) in November, (11.67 mm) in December, (20.56 mm) in January and (6

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Publication Date
Thu May 04 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design Feed Forward Neural Network to Determine Doses of the Decongestant for Cold Pills
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The aim of this paper is to design feed forward neural network to determine the effects of
cold pills and cascades from simulation the problem to system of first order initial value
problem. This problem is typical of the many models of the passage of medication throughout
the body. Designer model is an important part of the process by which dosage levels are set.
A critical factor is the need to keep the levels of medication high enough to be effective, but
not so high that they are dangerous.

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