Economic analysis plays a pivotal role in managerial decision-making processes. This analysis is predicated on deeply understanding economic forces and market factors influencing corporate strategies and decisions. This paper delves into the role of economic data analysis in managing small and medium-sized enterprises (SMEs) to make strategic decisions and enhance performance. The study underscores the significance of this approach and its impact on corporate outcomes. The research analyzes annual reports from three companies: Al-Mahfaza for Mobile and Internet Financial Payment and Settlement Services Company Limited, Al-Arab for Electronic Payment Company, and Iraq Electronic Gateway for Financial Services Company. The paper concl

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load at different operating frequencies. The effect of relative density, depth of embedment, foundation area as well as the imposed harmonic load was investigated. It was found that the amplitude of displacement of the foundation increases with increasing the amplitude of dynamic force and operating frequency meanwhile it decreases with increasing the relative density of sand, degree of saturation, depth of embedment and contact area of footing. The maximum displacement was noticed at 33.34 to 41.67 Hz. The maximum displacement amplitude respons

Background. Bone healing is a complex and dynamic process that represents a well-orchestrated series of biological events of cellular recruitment, proliferation, and differentiation. The use of medicinal plants in bone healing has attracted increasing interest because of their lower side effects. Punica granatum seed oil (PSO) contains high levels of phenolic compounds, promotes osteoblast function, and plays an important role in bone remodeling. A gelatin sponge (Spongostan) is a hemostatic agent that is extensively applied as scaffolds in engineering and as drug carriers in the medical field. This study aimed to evaluate the effectiveness of PSO for bone healing enhancement. Twenty adult male New Zealand rabbits, weighing an avera

In this study a polymeric composite material was prepared by hand
lay-up technique from epoxy resin as a matrix and magnesium oxide
(MgO) as a reinforcement with different weight fraction (5,10,15,
and 20)% to resin. Then the prepared samples were immersed under
normal condition in H₂So₄(1 M) solution, for periods ranging up to
10 weeks. The result revealed that the diffusion coefficient
decreasing as the concentration of MgO increase. Also we studied
Hardness for the prepared samples before and after immersion. The
result revealed that the hardness values increase as the concentration
of MgO increase, while the hardness for the samples after immersion
in H₂SO₄ dec

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load at different operating frequencies. The effect of relative density, depth of embedment, foundation area as well as the imposed harmonic load was investigated. It was found that the amplitude of displacement of the foundation increases with increasing the amplitude of dynamic force and operating frequency meanwhile it decreases with increasing the relative density of sand, degree of saturation, depth of embedment and contact area of footing. The maximum displacement was noticed at 33.34 to 41.67 Hz. The maximum displaceme

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims