The formula of Ijarah and Ijarah ending with ownership is one of the investment formulas in Islamic banks, so this research has shed light on it in order to benefit from the experiences of the research sample banks, This research aims to find a reliable way for Iraqi Islamic banks, namely (leasing and leasing ending with ownership) in order to invest their money without usurious interests, The problem of the research emerges through the lack of awareness of the Iraqi Islamic banks to work with different Islamic financing formulas and their inability to invest their money through the adoption of their administrations for different formulas, including the leasing, and this is reflected in the decrease and fluctuation of its profits, Therefore, the growth and importance of rental returns and rent-to-own ownership were measured and analyzed, as well as a study of the role and reflection of these returns on the profits of those Islamic banks for the period from (2012-2021) in addition to financial analysis through the use of profitability indicators, in addition to the comparison between Emirates Islamic Bank And Emirates NBD Bank, and the hypothesis that the research came up with is that Islamic banks achieve high returns through the use of the lease and lease-to-own-ownership formula, which are positively reflected on the profits of a bank.
Purpose: The aim of this study is to examine knowing the real role and impact of manufacturing flexibility on competitiveness through operations management practices, which is to determine the role and impact of manufacturing flexibility on competitiveness directly in the General Company for the Battery Industry. On the other hand, identifying the indirect role of flexible manufacturing systems in enhancing competitiveness. Theoretical framework: The main purpose of the theoretical framework is to identify all the dimensions and variables included in the current study, and thus form a deep scientific view of the study and its variables. Design/methodology/approach: field coexistence, personal interviews, and classification of
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The Plerion nebula is characterized by its pulsar that fills the center of the supernova remnant with radio and X-ray frequencies. In our galaxy there are nine naked plerionic systems known, of which the Crab Nebula is the best-known example. It has been studied this instance in order to investigate how the pulsar energy affect on the distribution and evolution of the remnant as well as study the pulsar kick velocity and its influence on the remnant. From the obtained results it's found that, the pulsar of the Crab Nebula injects about (2−3)𝑥 1047 erg of energy to the remnant, although this energy is small compared to the supernova explosion energy which is about 1051 erg but still plays a significant role in the distribution and the m
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The study population growth of the most important demographic phenomena upon which planners to meet changes in the size of the population increase is through knowledge of the requirements of population growth can be planned for the future. On this basis, Tuz District was chosen for the study of population growth, which set her period (1977-2012), and compared with the growth of the population of the province and the extent of the variation in population growth, according to the administrative units, has touched search numerical and proportional distribution of the population according to the administrative aspects of the judiciary, as well as environmental distribution.
The elimination of the study population growth dramatically
... Show MoreABSTRACT Planetary Nebulae (PN) distances represent the fundamental parameter for the determination the physical properties of the central star of PN. In this paper the distances scale to Planetary Nebulae in the Galactic bulge were calculated re- lated to previous distances scales. The proposed distance scale was done by recalibrated the previous distance scale technique CKS/D82. This scale limited for nearby PN (D ≤ 3.5 kpc), so the surface fluxes less than other distance scales. With these criteria the results showed that the proposed distance scale is more accurate than other scales related to the observations for adopted sample of PN distances, also the limit of ionized radius (Rio) for all both optically thick and optically thin in
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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The potential application of granules of brick waste (GBW) as a low-cost sorbent for removal of Ni+2ions from aqueous solutions has been studied. The properties of GBW were determined through several tests such as X-Ray diffraction (XRD), Energy dispersive X-ray (EDX), Scanning electron microscopy (SEM), and BET surface area. In batch tests, the influence of several operating parameters including contact time, initial concentration, agitation speed, and the dose of GBW was investigated. The best values of these parameters that provided maximum removal efficiency of nickel (39.4%) were 1.5 hr, 50 mg/L, 250 rpm, and 1.8 g/100mL, respectively. The adsorption data obtained by batch experiments subjected to the Three i
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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