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 organizational culture is considered as an important topic. In this research, this topic was studied in modern paints Industries Company to assess its role in job performance and to show if there is this relationship between them or no. it is, also, attempted to measure this strength of this relationship if any. The 40 cases research sample was chosen. This sample included the chief executive, his assistants, key managers, and their assistants. The questioner consists of two sets of questions : the first set ( concerning the organizational culture) covers six variables (Physical structures , Symbols
... Show MoreEven though in recent decades a bulk of studies have been accomplished on the use of communicative language teaching (CLT) in English as a foreign language (EFL) environments, fairly a limited numbers of studies precisely dealt with investigating the attitudes of language teachers, students and supervisors concerning the principals of CLT in the context of Iraq. Henceforth, this study was designed to delve into the attitudes of teachers, learners and supervisors about the implementation. To this end, the study was accomplished using a mixed method design. The present study was carried out in two phases: designing and using a questionnaire plus interviewing the teachers, students and supervisors (51 language learners, 41 teachers and
... Show MoreStudy of the Mechanical and Electrical Properties of Modified Unsaturated Polyester Blends
Background: Despite the importance of vaccines in preventing COVID-19, the willingness to receive COVID-19 vaccines is lower among RA patients than in the general population. Objective: To determine the extent of COVID-19 knowledge among RA patients and their attitudes and perceptions of COVID-19 vaccines. Methods: A qualitative study with a phenomenology approach was performed through face-to-face, individual-based, semi-structured interviews in the Baghdad Teaching Hospital, Baghdad, Iraq, rheumatology unit. A convenient sample of RA patients using disease-modifying anti-rheumatic drugs was included until the point of saturation. A thematic content analysis approach was used to analyze the obtained data. Results: Twenty-five RA pa
... Show MoreFundamentalist detective
On matters of consensus
Of Khala book complete the teacher benefits of Muslim
Judge Ayaz
(May God have mercy on him)
The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
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