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Supervisory oversight role for the central bank to raise awareness of the banking supervisory: Applied Research in the Central Bank of Iraq and a sample of the Iraqi private banks
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Representing banking supervision An important function performed by the Iraqi Central Bank, in order to achieve stability in the financial and banking system, and safeguard the rights of depositors, investors and other targets, and to realize the Iraqi Central Bank banking supervision actors on banks, there must be an awareness of regulatory bank's existing control and subject them, as well as the role of banking oversight interested in spreading this awareness.
So sought search to find out the role played by the Iraqi Central Bank in raising awareness of the regulatory banking between the parties to the regulatory process, through the presentation and analysis of the legal framework for banking supervision and awareness supervisory banking, as well as analysis of the views of a sample of the various communities, which represent the parties the regulatory process, and by measuring banking supervisory awareness of these parties.
Search it built on the basic premise (that the banking supervisory awareness by the Central Bank of Iraq's existing oversight and subject them and interested in them) leads to: -
1- improve performance for those in charge of banking supervision and subject to them.

2- To maintain public money and private equity.

3- Quality audit work for those in charge of banking supervision.

This has been proven this hypothesis and to reach a set of conclusions, including: the importance of the role played by the Central Bank of Iraq in the banking supervisory awareness among the parties to the regulatory process, As well as the lack of a modern guide regulating the actions of banking supervision of the staff of the Central Bank of Iraq.

As output Find a set of recommendations including: focus by the Iraqi Central Bank on the rehabilitation and development of the skills of banking supervision of his employees, and attention to the human element in order to keep pace with the global development through training courses in the field of banking supervision, so as to increase awareness of the regulatory banking have, and that reflected on the exercise of effective banking supervision on banks

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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Publication Date
Thu Jun 30 2011
Journal Name
Kufa Journal For Veterinary Medical Sciences
Bacterial isolation from burn wound infections and studying their antimicrobial susceptibility
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The present study was carried out to determine the bacterial isolates and study their antimicrobial susceptibility in case of burned wound infections. 70 burn wound swabs were taken from patients, who presented invasive burn wound infection from both sex and average age of 3-58 years, admitted to teaching medical Al- Kendi hospital from October 2007 to June 2008. Pseudomonas aeruginosa was found to be the most common isolate (48.9%) followed by Staphylococcus aureus (24.4%), Citrobacter braakii (13.3%), Enterobacter spp. (11.1%), Coagulase-negative Staphylococci (11.1%), Proteus vulgaris (6.66%), Corynebacterium spp. (6.66%), Micrococcus (6.66%), Proteus mirabilis (4.44%), Enterococcus faecalis (4.44%), E.coli (4.44%), Klebsiella spp. (2.22

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DYE REMOVAL FROM TEXTILE WASTEWATER BY COAGULATION USING ALUM AND PAC
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Removal of solar brown and direct black dyes by coagulation with two aluminum based
coagulants was conducted. The main objective is to examine the efficiency of these
coagulants in the treatment of dye polluted water discharged from Al-Kadhymia Textile
Company (Baghdad-Iraq). The performance of these coagulants was investigated through
jar test by comparing dye percent removal at different wastewater pH, coagulant dose,
and initial dye concentration. Results show that alum works better than PAC under acidic
media (5-6) and PAC works better under basic media (7-8) in the removal of both solar
brown and direct black dyes. Higher doses of PAC were required to achieve the
maximum removal efficiency under optimum pH co

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Digital Speech Files Encryption based on Hénon and Gingerbread Chaotic Maps
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Speech encryption approaches are used to prevent eavesdropping, tracking, and other security concerns in speech communication. In this paper, a new cryptography algorithm is proposed to encrypt digital speech files. Initially, the digital speech files are rearranged as a cubic model with six sides to scatter speech data. Furthermore, each side is encrypted by random keys that are created by using two chaotic maps (Hénon and Gingerbread chaotic maps). Encryption for each side of the cube is achieved, using the based map vector that is generated randomly by using a simple random function. Map vector that consists of six bits, each bit refers to one of the specific chaotic maps that generate a random key to encrypt each face of the cube. R

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

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Scopus (9)
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Crossref (6)
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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Publication Date
Fri Sep 15 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.</p> ... Show More
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Publication Date
Wed Dec 12 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
Preparation and characterization DLC thin films using atmospheric pressure plasma Jet
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Diamond-like carbon, amorphous hydrogenated films forms of carbon, were pretreated from cyclohexane (C6H12) liquid using plasma jet which operates with alternating voltage 7.5kv and frequency 28kHz. The plasma Separates molecules of cyclohexane and Transform it into carbon nanoparticles. The effect of argon flow rate (0.5, 1 and 1.5 L/min) on the optical and chemical bonding properties of the films were investigated. These films were characterized by UV-Visible spectrophotometer, X-ray diffractometer (XRD) Raman spectroscopy and scanning electron microscopy (SEM). The main absorption appears around 296, 299 and 309nm at the three flow rate of argon gas. The value of the optical energy gap is 3.37, 3.55 and 3.68 eV at a different flow rate o

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Crude Oil Price Forecasts Using Support Vector Regression and Technical Indicators
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Oil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measur

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