This research aims to study and analyze the reality of monetary policy and financial sustainability in Iraq through either a descriptive or analytical approach by trying to link and coordinate between monetary policy and fiscal policy to enhance economic sustainability. The research is based on the hypothesis that the monetary policy of Iraq contributes to achieving financial stability, which improves economic sustainability by providing aid and assistance to the state to reduce the budget deficit and exacerbate indebtedness. The author used the monetary policy indicators, the re-deduction of Treasury transfers by the central bank and the money supply, and financial sustainability indicators, including the public debt indicators and the

The demand for expatriate labor to Iraq increased after 2003 as a result of the openness that Iraq experienced, but this expatriate labor, which was requested at an increasing rate, has had economic, social, and political effects on the Iraqi economy in general, and the Iraqi labor market in particular. This is due to the high rates of unemployment, as most of these expatriate workers cause competition to local labor, and thus cause repercussions on the Iraqi economy as a whole, except for those expatriate workers coming with companies working in the oil sector. Iraq's GDP

Abstract. In this research, the uranium concentration in (16) water samples collected from some agricultural areas surrounded with AlTuwitha nuclear site in Baghdad-Iraq was measured by using a CR-39 detector. The concentration of uranium in this study was from (0.6 ± 0.33mg/l) to (2.51 ± 0.49 mg/l), and the weighted average for the concentrations (1.262 ± 0.402 mg/l). The results showed it is a concentration of uranium level in water samples studied is higher than the allowed limit recommended by WHO and ICRP.

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Background: Information concerning the maximum bite force in human population is important to clinical orthodontics. Additionally, the influence of bite force on the vertical stability of any treatment result is important. The new position of the dentition should be compatible with the dynamics of the muscular and occlusal forces in all planes. This study was conducted to 1) to measure and compare maximum bite force, body height and weight among normal occlusion and malocclusion groups (cl I,cl II,cl III) in both gender 2) to evaluate the correlation between bite force and craniofacial morphology, body height and weight. Materials and Methods: The sample consists of 100 Iraqi adult subjects aged 18-25 years. It was classified in to four gr

Abstract

This study aims to identify the degree to which the first cycle teachers use different feedback patterns in the e-learning system in addition to the differences in the degree of use according to specialization, teaching experience, and in-service training in the field of classroom assessment, as well as the interaction between them. The study sample consisted of (350) female teachers of the first cycle in government schools in Muscat Governorate for the academic year 2020/2021. The study used a questionnaire that contained four different patterns of feedback, which are reinforcement, informative, corrective, and interpretive feedback. The psychometric properties of the que

Abstract

This study aims to identify the level of emotional intelligence among principals of basic education schools in Al-Dakhiliya Governorate. The descriptive approach was used. A questionnaire of two parts was utilized; its second part included (27) items divided into five dimensions related to emotional intelligence. The study sample consisted of (337) teachers representing 52% of the study sample were randomly selected. The study result showed that level of the emotional intelligence is high and the motivation dimension is the highest. There were no statistical differences at the level (α≤ 0.05) due to the impact of (the social type, the educational qualification, and the years of experience) in all the

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.