This work deals with the effect of adding aluminum nanoparticles on the mechanical properties, micro-hardness and porosity of memory-shape alloys (Cu-Al-Ni). These alloys have wide applications in various industrial fields such as (high damping compounds and self-lubricating applications). The samples are manufactured using the powder metallurgy method, which involved pressing in only one direction and sintered in a furnace surrounded by an inert gas. Four percentages (0%, 5%, 10%, and 15%) of aluminum nanoparticles were fabricated, which depended on the weight of aluminum powder (13%) in the sample under study. To find out which phase is responsible for the reliability of the formation of this type of alloy and its porosity, X-ray diffraction (XRD) and scanning electron microscopy (SEM) tests are used. The Vickers micro-hardness and porosity properties of these alloys were studied using a Vickers micro-hardness and porosity tester according to ASTM b328-1996. The results showed that increasing the concentration of aluminum nanoparticles in the alloy led to an increase in hardness with a decrease in the porosity, and the sample (15%) gave the best hardness (190.8 HV). The sample (0%) gave the highest porosity (19.573) %.
The research aims to verifying the tax exemptions granted in accordance with the Iraqi tax legislations, showing their suitability for basic tax rules, and identifying their role to reduce the tax evasion phenomenon and the negative effects resulting therefrom, which arerepresented by a decrease in the proceeds of tax revenue and therefore leadings to a reduction of public revenues of the state. Also, the research tries to identify the ways to reduce cases of tax evasion due to their reflection positively on the public budgetof the state. The data of the research was collected through two models of questionnaires distributed to a sample of taxpayers from some professions and a sample of the tax administration staff. The research has reac
... Show MoreBackground: Bimaxillary protrusion is considered as one of the most important causes to seek the orthodontic treatment to get better esthetics. This study aimed to test the effect of orthodontic treatment in improvement the facial esthetics. Materials and Methods: Ten Iraqi Arab females having bimaxillary protrusion based on Class I malocclusions treated with fixed orthodontic appliance and extraction of the maxillary and mandibular 1st permanent premolars. Pre and post-treatment facial profile photographs were taken for each patients and the effect of treatment was tested in comparison with the pre-treatment photographs by using seven angular measurements. Results: After treatment, the upper and lower lip projections were decreased signifi
... Show MoreThis work involves three parts , first part is manufacturing different types of laminated below knee prosthetic socket materials with different classical laminated materials used in Baghdad center for prosthetic and orthotic (4perlon layers+2carbon fiber layer+4 perlon layers) , two suggested laminated materials(3perlon layers+2carbon fiber layer+3 perlon layers) and (3perlon layers+1carbon fiber layer+3 perlon layers) ) in order to choose perfect laminated socket . The second part tests (Impact test) the laminated materials specimens used in socket manufacturing in order to get the impact properties for each socket materials groups using an experimental rig designed especially for this purpose. The interface pressure between
... Show MoreBackground: Since the periodontal disease Index of Ramfjord (Ramfjord index) can potentially shorten the examination time by almost half, many studies evaluated Ramfjord teeth in predicting full-mouth periodontal status of an adult population. The aim of this study was to evaluate the benefit of Ramfjord teeth in predicting the full-mouth clinical attachment level of an adult population in patients attending the college of dentistry- Baghdad University. Materials and methods: The study participants were 100 patients with age range from 30-60 years old which represent group zero. The patients were divided into three main groups according to the age of the patients. Group I and group II each of them composed of 30 patients while group III co
... Show MoreThe reality of teaching the Arabic language rules is not satisfactory, as the pedagogical methods used do not help students develop their mental skills, especially critical thinking skills. They are often traditional in terms of teaching students, who are passive, passive, often passive, active, and often active, their listening task, and the teacher's task of narrating facts and judgments. It is a blind simulation student, a dependency on others, and a weak spirit of creativity, innovation, and opinion. The opinions of educators and teachers almost agree on the reasons for students' weakness in learning the rules of Arabic, and that the reason lies in the way of teaching. The difficulty or the ease of the rules of Arabic does not lie in th
... Show MoreGarlic is rich in nutritional and medicinal value as it has been found that the water extract of garlic plant contains 31% carbohydrates and rich in elements calcium, phosphorus, magnesium, potassium, sodium, iron, zinc, manganese, vitamin C, thiamine, riboflavin, niacin and pyridoxine. The aim of this study was to investigate the effect of garlic extract (
In accounting studies, more than one method is used to measure income and balance sheets elements. One of these methods is called the fair value, which use to determine the assets and liabilities ad it includes the benefits or self-satisfaction ability. This paper aims to focus on the importance of fair value as a basis of accounting measurement and its effects to achieve the relevant characteristics by using the equation is used by (Kythreotis) in his research, And Also , Editing this equation depending on the financial data and information of Iraqi Banks as a case.
The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
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