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, focusi

In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

Cooperation spectrum sensing in cognitive radio networks has an analogy to a distributed decision in wireless sensor networks, where each sensor make local decision and those decision result are reported to a fusion center to give the final decision according to some fusion rules. In this paper the performance of cooperative spectrum sensing examines using new optimization strategy to find optimal weight and threshold curves that enables each secondary user senses the spectrum environment independently according to a floating threshold with respect to his local environment. Our proposed approach depends on proving the convexity of the famous optimization problem in cooperative spectrum sensing that stated maximizing the probability of detec

Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp