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Using the Sherrod model in predicting financial failure in Iraqi private banks: an applied study in the Iraqi commercial and Iraqi Islamic banks
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Abstract:

              The phenomenon of financial failure is one of the phenomena that requires special attention and in-depth study due to its significant impact on various parties, whether they are internal or external and those who benefit from financial performance reports. With the increase in cases of bankruptcy and default facing companies and banks, interest has increased in understanding the reasons that led to this financial failure. This growing interest should be a reason to develop models and analytical methods that help in the early detection of this increasing phenomenon in recent year   . The research examines the use of Sherrod's model in predicting financial failure in Iraqi private banks. The researchers relied on this mathematical model to analyze financial data and estimate the probability of financial failure occurring in these banks. Financial data was collected for a sample of private banks in Iraq over several years, and these data were used to apply the Sherrod model. As for the sample, a sample was chosen from the research consisting of two banks (the Commercial Bank of Iraq and the Iraqi Islamic Bank) for the research and a time series that extended for five years (2017 – 2021) , The results showed that the Sherrod model has a good ability to predict financial failure in Iraqi private banks. The researchers used a variety of financial and accounting variables in the model, which contributed to improving the accuracy of predicting financial failure.    This study represents an important contribution to understanding how mathematical models such as Sherrod's model can be used to estimate the risk of financial failure in banks. These tools help guide strategies and make sound financial decisions. This research is considered an important step towards improving the sustainability and performance of private banks in Iraq and enhancing confidence in the financial system.

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Publication Date
Mon May 15 2017
Journal Name
Journal Of Theoretical And Applied Information Technology
Anomaly detection in text data that represented as a graph using dbscan algorithm
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

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Publication Date
Sat Jan 26 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Secure Mobile Sink Node location in Wireless Sensor Network using Dynamic Routing Protocol
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The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

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Publication Date
Wed Mar 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
ESTIMATION OF MASS TRANSFER COEFFICIENTS IN A PACKED DISTILLATION COLUMN USING BATCH MODE
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This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.

KOV = 3.3 * 10-10

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Publication Date
Wed Jan 26 2022
Journal Name
Iraqi Journal Of Science
Potentiometric Determination of Mebeverine Hydrochloride Using Imprinted Molecular Polymer in PVC Matrix Membrane‏
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Publication Date
Mon Mar 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Simulation of Two Phase Flow Mixing Co – Current in T Junction Using Comsol
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The analysis, behavior of two-phase flow incompressible fluid in T-juction is done by using "A Computational Fluid Dynamic (CFD) model" that application division of different in industries. The level set method was based in “Finite Element method”. In our search the behavior of two phase flow (oil and water) was studed. The two-phase flow is taken to simulate by using comsol software 4.3. The multivariable was studying such as velocity distribution, share rate, pressure and the fraction of volume at various times.  The velocity was employed at the inlet (0.2633, 0.1316, 0.0547 and 0.0283 m/s) for water and (0.1316 m/s) for oil, over and above the pressure set at outlet as a boundary condition. It was observed through the program

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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Publication Date
Sun Mar 29 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Photocatalytic Degradation of Reactive Yellow Dye in Wastewater using H2O2/TiO2/UV Technique
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In the present study, advanced oxidation treatment, the TiO2 /UV/H2O2  process was applied to decolorisation of the reactive yellow dyes in aqueous solution. The UV radiation was carried out with a 6 W low-pressure mercury lamp. The rate of color removal was studied by measuring the absorbency at a characteristic wavelength. The effects of H2O2 dosage, dye initial concentration and pH on decolorisation kinetics in the batch photoreactor were investigated. The highest decolorisation rates were observed (98.8) at pH range between 3 and 7. The optimal levels of H2O2 needed for the process were examined. It appears that high levels of H2O2 could reduce decolori

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Crossref (19)
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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Advanced Oxidation of Antibiotics Polluted Water Using Titanium Dioxide in Solar Photocatalysis Reactor
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The aim of this study was to investigate antibiotic amoxicillin removal from syn­thetic pharmaceutical wastewater. Titanium dioxide (TiO2) was used in photocatalysis treatment method under natural solar irradiation in a tubular reactor. The photocatalytic removal efficiency was evaluated by the reduction in amoxicillin concentration. The effects of antibiotics concentration, TiO2 dose, irradiation time and the effect of pH were studied. The optimum conditions were found to be irradiation time 5 hr, catalyst dosage 0.6 g/L, flow rate 1 L/min and pH 5. The photocatalytic treatment was able to destruct the amoxicillin in 5 hr and induced an amoxicillin reduction of about 10% with 141.8 kJ/L accumulate

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Crossref (13)
Crossref
Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Translating the Genre of Quran: the Challenge of translating the inimitable: Translating the Genre of Quran: the Challenge of translating the inimitable
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Abstract
The main question raised in this paper is: Is it possible to translate the ‘genre’
of Quran? And if this ‘genre’ is Quran specific, a ‘genre’ of its own, i.e. a unique one,
how can the Quranic text be translated from Arabic into English or any other
language? This question has been raising a lot of controversy among translation
theorists, linguists, philosophers and scholars of Islam and specialists in the sciences
of Arabic language let alone Quran exegetes. Scholars of the Arabic language and
scholars of Islam have argued that because of the genre of Quran is the genre of (ijaz),
translatability can never be possible. Equivalence, thus, cannot be achieved especially
if we know that so far

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Publication Date
Mon Apr 25 2022
Journal Name
Knowledge And Information Systems
Unsupervised model for aspect categorization and implicit aspect extraction
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People’s ability to quickly convey their thoughts, or opinions, on various services or items has improved as Web 2.0 has evolved. This is to look at the public perceptions expressed in the reviews. Aspect-based sentiment analysis (ABSA) deemed to receive a set of texts (e.g., product reviews or online reviews) and identify the opinion-target (aspect) within each review. Contemporary aspect-based sentiment analysis systems, like the aspect categorization, rely predominantly on lexicon-based, or manually labelled seeds that is being incorporated into the topic models. And using either handcrafted rules or pre-labelled clues for performing implicit aspect detection. These constraints are restricted to a particular domain or language which is

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