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.
In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
... Show MoreIn this work, the effects of size, and temperature on the linear and nonlinear optical properties in InGaN/GaN inverse parabolic and triangular quantum wells (IPQW and ITQW) for different concentrations at the well center were theoretically investigated. The indium concentrations at the barriers were fixed to be always xmax = 0.2. The energy levels and their associated wave functions are computed within the effective mass approximation. The expressions of optical properties are obtained analytically by using the compact density-matrix approach. The linear, nonlinear, and total absorption coefficients depending on the In concentrations at the well center are investigated as a function of the incident photon energy for different
... Show MoreIn the present work, the pollutants of the municipal wastewater are reduced using Chlorella vulgaris microalgae. The pollutants that were treated are: Total organic carbon (TOC), Chemical oxygen demand (COD), Nitrate (NO3), and Phosphate (PO4). Firstly, the treatment was achieved at atmospheric conditions (Temperature = 25oC), pH 7 with time (1 – 48 h). To study the effect of other microorganisms on the reduction of pollutants, sterilized wastewater and unsterilized wastewater were used for two types of packing (cylindrical plastic and cubic polystyrene) as well as algae's broth (without packing), where the microalgae are grown on the packing then transported to the wastewater for treatment. Th
... Show MoreIt has become clear to see the role of the small and medium enterprises in the economy, and for the continuity of these projects it is necessary to supply finance from the banks, How ever the latter suffers risk of lending.
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... Show MoreExamining of 80 feces samples showed that 31 samples of the house and stray cats harbored either single or mixed infection with eight species of parasites and protozoa with a total infection rate 38.75 %.The results on parasite classes are: Toxocara cati (5%), Ancylostoma tubeforme (3.75%), Capillaria felis(3.75%), Isospora sp.(10%), Cryptosporidium parvum(3.75%), Cryptosporidium muris (6.25%), Toxoplasma gondi (3.75%), Giardia sp.(2.5%) infection from feces of cats that showed single, double and triple infections. Our findings revealed the risk for public health, thus preventive measures should be implemented.
Abstract:
Sought the search to find out what small businesses, the importance of funding, and the role of funders in supporting such projects, which have been addressed in the search through a sample of government banks (Rafidain and Rasheed) and private banks (the Middle East, the Gulf, North, Assyria) and a sample of Small projects borrowed from these banks, but in order to achieve that rely researchers on scientific methods discreet marked by the curriculum descriptive analytical method which is based on the compilation of facts and information then collated and analyzed to reach acceptable results, as well as data collection tool (checklist) was whereby examine questions of a sample of
... Show MoreBackground: Polycystic ovary syndrome is among the leading causes of fertility-related problems and menstrual irregularities in women of reproductive age. The granulosa cells of the developing pre-antral and antral follicles produce inhibin B, which triggers chemical responses in the ovaries. Inhibin B is most often observed in the follicular phase when levels peak early and then decline over time Objectives: This study was designed to investigate the role of serum inhibin B and the Luteinizing Hormone / Follicle Stimulating Hormone ratio in differentiation between the different phenotypes of polycystic ovary syndrome as well as to define the predominant PCOS phenotype. Methods: This cross-sectional research was conducted in the
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