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A new algorithm of modified binary particle swarm optimization based on the Gustafson-Kessel for credit risk assessment
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Publication Date
Sun Jul 30 2023
Journal Name
American Journal Of Environmental Economics
Impact of Brand Capital on the Stock Price Crash Risk, an Empirical Study
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The factors influencing the financial market are rapidly becoming more complex. The impact of non-financial factors on the performance of a company’s common stock can increase in ways that were not previously expected. This study investigated how brand capital affects the risk of stock prices in Iraqi private banks listed on the Iraq Stock Exchange failing by identifying the likelihood of a crash caused by a negative deviation in the distribution of returns on ordinary shares. As a result, the current study’s concept is to review an analytical knowledge framework of the nature of that relationship, its changes, and its impact on the pricing of ordinary shares of the banks of the researched sector for the years 2009 to 2017, as w

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The role credit guarantee companies to bank guarantee in the financing of small and medium enterprises
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       It has become clear to see the role of the small and medium enterprises in the economy, and for the continuity of these projects it is necessary to supply finance from the banks, How ever the latter suffers risk of lending.                                                                          

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Publication Date
Wed Dec 23 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review
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Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Fri Dec 01 2023
Journal Name
Nano Biomedicine And Engineering
The Impact of Modified Metallic Nanoparticles on Thermomechanical Properties of PMMA Soft Liner
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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The efficiency of the tax examiner and its impact on reducing the risk of tax evasion
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The research dealt with the effect of the tax examiner's efficiency in detecting tax evasion, as the research problem dealt with tax evasion, especially in Iraq, for many reasons and factors, including those related to tax administration represented in administrative corruption and the complexity of procedures in the tax accounting process and failure to achieve justice in the tax treatment, including the taxpayer himself, as he tries to evade for reasons Related to the level of tax awareness, loss of confidence in the tax administration, and reasons related to the state's inability to manage the services file well and its ability to achieve the set goals, This reflected negatively on the emergence of some of the consequences of

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Publication Date
Mon Feb 20 2023
Journal Name
Baghdad Science Journal
Modeling and Analyzing the Influence of Fear on the Harvested Modified Leslie-Gower Model
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A modified Leslie-Gower predator-prey model with a Beddington-DeAngelis functional response is proposed and studied. The purpose is to examine the effects of fear and quadratic fixed effort harvesting on the system's dynamic behavior. The model's qualitative properties, such as local equilibria stability, permanence, and global stability, are examined. The analysis of local bifurcation has been studied. It is discovered that the system experiences a saddle-node bifurcation at the survival equilibrium point whereas a transcritical bifurcation occurs at the boundary equilibrium point. Additionally established are the prerequisites for Hopf bifurcation existence. Finally, using MATLAB, a numerical investigation is conducted to verify t

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Modeling and Analyzing the Influence of Fear on the Harvested Modified Leslie-Gower Model
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A modified Leslie-Gower predator-prey model with a Beddington-DeAngelis functional response is proposed and studied. The purpose is to examine the effects of fear and quadratic fixed effort harvesting on the system's dynamic behavior. The model's qualitative properties, such as local equilibria stability, permanence, and global stability, are examined. The analysis of local bifurcation has been studied. It is discovered that the system experiences a saddle-node bifurcation at the survival equilibrium point whereas a transcritical bifurcation occurs at the boundary equilibrium point. Additionally established are the prerequisites for Hopf bifurcation existence. Finally, using MATLAB, a numerical investigation is conducted to verify the va

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Publication Date
Thu Jul 01 2021
Journal Name
Solar Energy
A new approach for employing multiple PCMs in the passive thermal management of photovoltaic modules
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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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