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Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Financial Variables and Their Effects on The Development of Bank Credit and Productive Sectors in Iraq Using a Path Analysis Model
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This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

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Publication Date
Thu Mar 13 2025
Journal Name
Journal Of Lifestyle And Sdgs Review
Enhancing Sustainability Reporting in Green Universities Through Social Media: A Case Study of Baghdad University on Advancing SDG
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Objectives: This study aims to evaluate the role of social media in promoting awareness of green university initiatives and assess the effectiveness of sustainability reports in engaging students at Baghdad University. In alignment with Sustainable Development Goal 12 (Responsible Consumption and Production),It seeks to provide recommendations for enhancing digital platforms for sustainability communication.   Theoretical Framework: The study is grounded in the Green University Model, Social Media Engagement Theory, and the Sustainability Reporting Framework, which emphasize integrating sustainable practices in education, using digital platforms for community engagement, and leveraging sustainability reports for transparency and

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Emotional Intelligence in kindergarten and its relationship with some variables
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This study aims at finding out the sentimental smartness of the kindergarten children
and its relationship with some variables.
1- The level of the sentimental smartness of the kindergarten children.
2- Investigating the Zero hypothesis in that there are no significant statistical differences in
the sentimental smartness between the kindergarten children according to the sex variables
(males and females).
Some statistical tools have been used in order to arrive at the results that verify the
hypotheses of this study. The researcher uses (1) the distinctive power between two
distinctive groups; (2) the relationship between the item and the total degree (Pearson
correlation factor); and (3) Elfakronbach formula t

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Entrepreneurial performance in accordance with the competitive intelligence and strategic
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 The research aims to study the entrepreneurial performance of the banks, according to the intelligence of competitive and strategic as the entrepreneurial performance is the one who does not stand the benefits of excellence in accomplished when just achieving the bank's objectives planned, but exceed it down to creativity in accomplishing these goals in a manner leads to making a entrepreneurial bank in the markets and the focus the eyes of competitors and the banks and other Following his example.

Was chosen the subject of research and strategic intelligence and competitive because of its impact on the strategic success of the banking sector, the fact is the entrepreneurial in the Iraqi banking mar

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Publication Date
Tue Dec 22 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Tax Audit and Its Impact on Tax Returns Quality
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     The study aims at showing the role of tax audit in Impact the quality of tax statements. Tax audit is one of the most important means used by tax management to identify taxable revenues in a just, fair manner. The quality of statements relies on the extent to which the information provided by taxpayers is true and accurate. Tax audit works is compatible with the strategy of increasing tax adherence and detecting non-adherence cases and penalizing those who commit such violations. The study reached a number of results and conclusions. One of the most important results is that tax audit helps improve the information content of the taxpayers tax statements. This leads to recalculating taxable incomes and re-fixing t

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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