Objectives: The research aims to demonstrate the integration between Quantum Computing (QC) and Predictive Analysis (PA) and their role in reducing costs while achieving Sustainable Development Goals (SDGs). The study addresses the inefficiencies in calculating and measuring product costs under traditional systems and examines how QC and PA can enhance cost reduction and product quality to better meet customer needs. Additionally, the research seeks to strengthen the theoretical framework with practical applications, illustrating how this integration improves a company’s competitive position while promoting social, environmental, and economic sustainability. Methods: The study employs a descriptive analytical approach, focusing on the practical application of QC and PA in cost management. It relies on financial and cost data from a selected company to analyze the impact of integrating QC and PA on cost reduction and sustainable development. The methodology aims to provide empirical evidence supporting the effectiveness of this integration in optimizing resource and energy use. Results: The research findings confirm that integrating QC and PA significantly contributes to cost reduction, which in turn plays a crucial role in achieving SDGs. The study highlights how this integration enhances efficiency in resource and energy utilization, identifies weaknesses in traditional cost systems, and supports the transition toward sustainable manufacturing. By improving production processes and minimizing waste, the application of QC and PA fosters innovation in sustainable product development. Conclusion: The study underscores the importance of integrating QC and PA in modern cost management strategies to achieve sustainability objectives. Encouraging innovative local manufacturing through enhanced efficiency and resource optimization supports the transition toward sustainable production. The findings suggest that companies adopting QC and PA can improve their competitive edge, reduce costs, and contribute to environmental and economic sustainability, ultimately aligning with global sustainable development goals.
As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,
... Show MoreThe ability of single and mixed bacterial culture to utilize Dora-refineries petroleum wastes was compared. Pseudomonas aeruginosa and Serratia ficaria mixed culture consumed the wastes better than the single bacterial cultures. The highest log. number of viable cells in mixed culture was 6.842 , while in single bacterial cultures it was 6.683 and 5.631, respectively. after 3 days in API medium containing the refinery wastes. The effect of some environmental conditions on the degradation of petroleum wastes was studied included aeration , NaCl concentration , pH and temperature. The growth of bacteria in the agitated culture was higher than stagnant culture the log. of cell no. was 6.021 in the first culture. The h
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreNewly prepared derivatives of Heterocyclic of dicarboxylic acid include 1, 2, 4-Triazoledicarboxylic acid. Thiocarbohydrazine (TCH) reacts with aliphatic and aromatic dicarboxylic acids, and when these resulting compounds interact with compounds containing a group of carbonyl they result in Schiff base, which are very important in the industrial and medical fields and the acids used (oxalic acid, succinic, terephthalic) to prepare the triazole, then the reaction with Para-chlorobenzendihaide. and some physical properties were measured for these products. The biological activity of the prepared compounds has been studied, and it has been shown that they have different effects on the bacteria, compounds prepared with Fourier Transform Infrare
... Show MoreBackground: Pumpkin seeds are a valuable source of high-quality protein and can be utilized as functional food ingredients due to their properties, such as solubility, foam formation, and stability. This study aims to produce protein isolate and its enzymatic hydrolysates from local pumpkin seeds to study their properties. Methodology: Preparing defatted pumpkin seeds for protein extraction, followed by the enzymes’ hydrolysis using Trypsin and Pepsin enzymes separately and together in two methods. The determination of amino acids and the degree of hydrolysis was conducted; moreover, protein properties were studied, including solubility, emulsifying activity, stability index, foaming capacity, and stability. Results: A protein sample was
... Show MoreBacterial strains were isolated from oil-contaminated soil, in 2018, these isolates were identified, and with the aim of finding out the ability of these isolates to degrede the oil compounds, the color change of medium which added to it isolates was read by the method of Pacto Bushnell Hans. Then the change in the petroleum compounds was read by gas chromatography, for the most effective isolates.
The nine isolated bacterial showed different degrees of color change, and the isolates (Pseudomonas, Bacillus, Micrococcus) outperformed the color change amount (78, 78, 77) %, respectively, compared to the control, and the three isolates together showed the best color change of 90.7. % Compared to the control, and the
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