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The role of audit committees in reducing the risk of external Auditors Engagement Regarding Accepting Assignment: An Applied research in a sample of Iraqi private banks And Audit Bureaus
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The research aims to identify the most important concerns that led to the increase of  interest in the topic of corporate governance and specifically highlighting  the role of the audit committees of the Administration  Board in reducing the risk of the auditor and the rationalization of professional judgments، in particular about accepting  the assignment and setting the fees of the audit process by extrapolating  global experience in this area ، and a field study is conducted for a sample of private Iraqi banks to evaluate the role of audit committees constituted currently per with bank law no. (94) of 2004 and to be acknowledged with actual performance of these committees and their role in recommending the nomination of external auditor to be employed، setting the fees for him and being provided with necessary facilities to perform his audit missions by coordinating with internal audit and working as communication channel with administration board، and to follow up how the administration responds to observations mentioned in his report to be tackled and avoided. Then suggested disciplines are concluded to estimate the risk of auditors’ engagement regarding accepting assignment and setting fees. These disciplines are addressed to the Council of Accounting and Auditing profession in Republic of Iraq to assist auditors in dealing with engagement risk and rationalize their professional judgments concerned with that judgment. To accomplish the goals of the research، the following items are studied thoroughly in the field study:

  Studying and assessing current and actual performance of audit committees in private Iraqi banks as a sample of research by studying released financial annual reports of these companies for the period 2009-2012 ، as well as some officials in directorate general of banking and credit control in  the CBI.

Design a questionnaire to solicit the views of a number of auditors in the offices and audit firms approved، and distributed (50) questionnaire

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Thu Sep 23 2021
Journal Name
Egyptian Journal Of Chemistry
Some 3,4,5-Trisubstituted-1,2,4-triazole Synthesis, Antimicrobial Activity, and Molecular Docking Studies
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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Content Based Image Retrieval Based on Feature Fusion and Support Vector Machine
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Sun Sep 01 2013
Journal Name
2013 Ieee International Conference On Circuits And Systems (iccas)
Improved undetected error probability model for JTEC and JTEC-SQED coding schemes
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The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

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Publication Date
Sat Oct 31 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
RELATIONSHIP BETWEEN PIGMENTS PRODUCTION AND BIOFILM FORMATION FROM LOCAL PSEUDOMONAS AERUGINOSA ISOLATES
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The current study was designed to explore the association between the pigments production and biofilm construction in local Pseudomonas aeruginosa isolates. Out of 143 patients suffering from burns, urinary tract infections (UTI), respiratory tract infections and cystic fibrosis obtained from previous study by Mahmood (2015), twenty two isolates  (15.38%) were identified  from (11) hospitals in Iraq, splitted  into three provinces, Baghdad, Al-Anbar and Karbala for the duration of June 2017 to April 2018.  Characterization was carried out by using microscopical, morphological and biochemical methods which showed that all these isolates belong to P. aeruginosa.  Screening of   biofilm production isolates was carried out by usi

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Wed Dec 08 2021
Journal Name
Scientific Reports
Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions
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Abstract<p>Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are app</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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