In this research, we discussed and analyzed the relationship between oil prices and the U.S. dollar exchange rate in Iraq. The study adopted the descriptive analysis and econometrics analysis. The descriptive analysis refers to the rise (fall) in crude oil price lead to appreciate (depreciate) in the Iraqi dinar exchange rate, though the channel of the international reserves. The econometrics analysis is based on monthly data covered the period (December/2002 – December/2011), the unit root test, co-integration test, vector error correction model, and Granger causality test have been adopted in this research to check the existence and direction of this relationship. The results refer to the lon

The purpose of the search definition on factors superior this whoever  impact on the improvement the exploitation  decision this  detect on stock exchange markets  assumption , and using  questioners to data accumulate  and the Iraq market of financial papers  battleground to search annoy chose the eyeball extension (47) peoples from peoples employees on the market , and using the bought statistic program (SPSS) on input and analysis search  data , and machinate the search outputs to their group of factors internal and external which impact on exploitation  decision on financial papers markets , and the search commend on necessary rise  the incumbency direction  in the stock exchange

KE Sharquie, AA Noaimi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2012 - Cited by 36

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

The present study investigated the impact of fuel kind on the emitted emissions at the idling period. Three types of available fuels in Iraq were tested. The tests conducted on ordinary gasoline with an octane number of 82, premium gasoline with an octane number of 92, and M20 (consist of 20% methanol and 80% regular gasoline). The 2 liters Mercedes-Benz engine was used in the experiments.

The results showed that engine operation at idle speed emits high levels of CO, CO₂, HC, NOx and noise. The produced emission levels depend highly on fuel type. The premium gasoline (ON=92) represents the lower emissions level except for noise at all idling speed. Adding methanol to ordinary gasoline (ON=82) showed high levels of emi

   The modified Hummers method was applied to prepare graphene oxide (GO) from the graphite powder. Tin oxide nanoparticles with different loading (10-20 wt.%) supported on reduced graphene oxide were synthesized to evaluate the oxidative desulfurization efficiency. The catalyst was synthesized by the incipient wetness impregnation (IWI) technique. Different analysis methods like FT-IR, XRD, FESEM, AFM, and Brunauer-Emmett-Teller (BET) were utilized to characterize graphene oxide and catalysts. The XRD analysis showed that the average crystal size of graphene oxide was 6.05 nm. In addition, the FESEM results showed high metal oxide dispersions on the rGO. The EDX analysis shows the weight ratio of Sn is close to its theoretical weight.

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For