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Analysis of the Causal Relationship Long-and Short-term Between the Price of Crude Oil, the Global Price of Gold and the US. Dollar Exchange Rate
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This research aims to test the causal relationship long-and short-run between the price of gold the global crude oil price and the exchange rate of the dollar and how you can take advantage of the nature of this relationship, particularly in the Arab oil states that achieve huge surpluses, including Iraq and how to keep on the purchasing power of these surpluses or reduce the levels of risk.

The problem is that the Arab oil countries, adversely affected, as a result of that relationship, due to the fact that its role confined to the sale of crude oil only. They do not have control in the dollar, then they are not able to take advantage of its impact on the price of gold the fact that gold is effective protection against fluctuations in the U.S. dollar

Model was used Vectors Error Correction Model VECM) to test the causal relationship long-term and short-term between the price of gold the global crude oil price and the dollar exchange rate, using daily data for 86 observations for the period from  1 jan  2013 until 27 march 2013

The results showed that there is a long-term equilibrium relationship between both the global price of gold and the dollar exchange rate with the price of crude oil. The study also shows that the price of crude oil in the short term have  positive relationship with  the price of gold, and have negative relationship with the  exchange rate of dollar   according to the  results  of Wald Test.

When taken The outcome of those the inter relationship between oil and gold, producing Arab states find themselves forced to bear the losses resulting from the relationship between the dollar and oil gold.

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed Mar 01 2023
Journal Name
Iranian Journal Of Materials Science And Engineering
First-Principles Analysis of Cr-Doped SrTiO3 Perovskite as Optoelectronic Materials
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The influence of Cr3+ doping on the ground state properties of SrTiO3 perovskite was evaluated using GGA-PBE approximation. Computational modeling results infered an agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ introducing into SrTiO3 were investigated. Structural parameters assumed that Cr3+ doping alters the electronic structures of SrTiO3 by shifting the conduction band through lower energies for the Sr and Ti sites. Besides, results showed that the band gap was reduced by approximately 50% when presenting one Cr3+ atom into the SrTiO3 system and particularly positioned at Sr sites. Interestingly, substituting Ti site by Cr3+ led to eliminating the band ga

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Publication Date
Fri Mar 15 2024
Journal Name
Al-adab Journal
A Rhetorical Stylistic Analysis of English Political Headlines in Selected Newspapers
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This study explores the language used in reporting political headlines conducting a rhetorical stylistic analysis. It is based on showing the effect of the rhetorical stylistic relations in news reporting. The aim is to investigate the structure adopted in reporting political news. It argues that the rhetorical stylistic devices are necessary and applicable to non-literary texts, i.e. political headlines to evaluate language use in the representation of non-literary texts. The analysis was carried out on data selected from the British broadsheet The Guardian and the American New York Times newspaper headlines. The data were examined and subjected to a contrastive analysis incorporating rhetorical and stylistic tools to discern h

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Publication Date
Mon Aug 01 2022
Journal Name
Communications In Mathematical Biology And Neuroscience
Stability analysis of a competitive ecological system in a polluted environment
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The interplay of species in a polluted environment is one of the most critical aspects of the ecosystem. This paper explores the dynamics of the two-species Lokta–Volterra competition model. According to the type I functional response, one species is affected by environmental pollution. Whilst the other degrades the toxin according to the type II functional response. All equilibrium points of the system are located, with their local and global stability being assessed. A numerical simulation examination is carried out to confirm the theoretical results. These results illustrate that competition and pollution can significantly change the coexistence and extinction of each species.

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Publication Date
Sat Jan 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Fri Jan 20 2023
Journal Name
Iranian Journal Of Materials Science And Engineering
First-Principles Analysis of Cr-Doped SrTiO3 Perovskite as Optoelectronic Materials
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This contribution evaluates the influence of Cr doping on the ground state properties of SrTiO3 Perovskite using GGA-PBE approximation. Results of the simulated model infer agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ doping levels in SrTiO3 has been investigated. Structural parameters infer that Cr3+ doping alters the electronic structures of SrTiO3 by shifting the conduction band through lower energies for the Sr and Ti sites. Substituting Ti site by Cr3+ results the energy gap in being eliminated revealing a new electrical case of conducting material for the system. Furthermore, it has been noticed that Cr doping either at Sr or Ti positions could effectiv

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Publication Date
Mon Aug 17 2020
Journal Name
International Journal Of Applied Mechanics And Engineering
Analysis of Structural Concrete Bar Members Based on Secant Stiffness Methods
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Abstract<p>In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A compari</p> ... Show More
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Publication Date
Tue Oct 01 2024
Journal Name
Science Progress
Jaw vs abdominal Burkitt's lymphoma: An analysis of 25 Iraqi cases
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This study compared the clinicopathological, immunohistochemical characteristics and Epstein-Barr virus (EBV) detection of Burkitt's lymphoma (BL) in the abdomen and jaw of Iraqi patients. A cohort/retrospective study was carried out between August and September 2024 using 25 tissue blocks (14 gnathic and 11 abdominal BL) from the Oral and Maxillofacial Laboratory, University of Baghdad, College of Dentistry, and the National Centre for Educational Laboratories. The sections were stained with haematoxylin and eosin (H&E), while CD10, CD20, Bcl-2, BCl-6, C-Myc and Ki-67 markers were used for diagnosis. The DNA detection of the EBV was performed by polymerase chain reaction (PCR). The tumours showed 22 classical and 3 atypical histologi

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Publication Date
Wed Oct 12 2022
Journal Name
Axioms
Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
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Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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