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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
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Thu Jun 01 2023
Journal Name
Heliyon
Heterogeneously catalyzed transesterification reaction using waste snail shell for biodiesel production
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Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

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Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
قياس وتحليل تفاعل عمل المضاعف والمعجل في الاقتصاد العراقي باستخدام نموذج المستخدم – المنتج الديناميكي
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The individual average income is considered one of the most used criteria for the distinguishing between the developed and the developing countries, for this reason the efforts of economic development has been construed on increasing the average national income, the investment expenditures is considered one of the basic foundations for economic development operation which lead to the expanding the prodection power of the economy, and increasing the level of national income in an averages greaten than the primary expenditures due to the work and interaction between the multiplier and the accelerator. But the ability of the economic sectors in the generation of national income as a result of the primary expenditures is different fr

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Publication Date
Wed Sep 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
دراسة المتغيرات المؤثرة على زيادة أعداد الحيوانات المنوية النشطة باستخدام نموذج توبت (Tobit Model
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The no parity problem causes determining is the most interesting case by doctors and researchers in this filed, because it helps them to pre-discovering of it, from this point the important of this paper is came, which tries to determine the priority causes and its fluency, thus it helps doctors and researchers to determine the problem and it’s fluency of increase or decrease the active sperm which fluencies of peregrinating. We use the censored regression (Tobit) model to analyze the data that contains 150 observations may by useful to whom it concern.         

 

 

 

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Utilizing a Magnetic Abrasive Finishing Technique (MAF) Via Adaptive Nero Fuzzy(ANFIS)
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 Abstract

An experimental study was conducted for measuring the quality of surface finishing roughness using magnetic abrasive finishing technique (MAF) on brass plate which is very difficult to be polish by a conventional machining process where the cost is high and much more susceptible to surface damage as compared to other materials. Four operation parameters were studied, the gap between the work piece and the electromagnetic inductor, the current that generate the flux, the rotational Spindale speed and amount of abrasive powder size considering constant linear feed movement between machine head and workpiece. Adaptive Neuro fuzzy inference system  (ANFIS) was implemented for evaluation of a serie

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Thu Jan 02 2020
Journal Name
مجلة العلوم الاقتصادية والإدارية
تقييم الاداء المصرفي على وفق نموذج CAMELS دراسة تطبيقية لمصرف المنصور للاستثمار للفترة من 2014-2018
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The banking sector has a significant impact on the economic growth of the country, and the importance of this sector must assess its financial performance from time to time, to measure the situation related to money for each bank and how to put the supervision of the efficiency of the full. The research aims at evaluating the financial performance according to the elements of the CAMELS model, which including capital adequacy, asset quality, management efficiency, profitability, liquidity and market risk sensitivity. The research included the study of Al-Mansour Investment Bank during the period from 2014 to 2018. The base capital ratio was used to total assets to measure capital adequacy The proportion of investments to total assets to mea

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Fri Feb 14 2014
Journal Name
Desalination And Water Treatment
Copper biosorption using local Iraqi natural agents
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Industrial effluents loaded with heavy metals are a cause of hazards to the humans and other forms of life. Conventional approaches, such as electroplating, ion exchange, and membrane processes, are used for removal of copper, cadmium, and lead and are often cost prohibitive with low efficiency at low metal ion concentration. Biosorption can be considered as an option which has been proven as more efficient and economical for removing the mentioned metal ions. Biosorbents used are fungi, yeasts, oil palm shells, coir pith carbon, peanut husks, and olive pulp. Recently, low cost and natural products have also been researched as biosorbent. This paper presents an attempt of the potential use of Iraqi date pits and Al-Khriet (i.e. substances l

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Publication Date
Fri Nov 01 2019
Journal Name
2019 1st International Informatics And Software Engineering Conference (ubmyk)
Radial Basis Function (RBF) Based on Multistage Autoencoders for Intrusion Detection system (IDS)
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

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