This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

Abstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr

While the impact of the fourth Industrial Revolution on the economy keeps accelerating, the signs of the fifth industrial revolution, whose key is innovation and creativity started to evolve. However, the challenge of achieving sustainable development and its goals remains faced by the global organizations; In this situation, Islamic banks are exposed to many challenges among which is the challenge of keeping themselves abreast of the latest developments in the modern technology which in turn is a tool for continuity and competition. On the flip side, to avoid the negative impact that these changes can have such as an increased gap between financial innovations and the requirements of sustainable development. Islamic banks in the

When it comes to boosting the economy, development, and allocation of financial resources from accessible savings to be employed in all economic sectors (industrial, agricultural, and service), commercial banks in developing and Arab countries are seen as one of the tools. Foreign and domestic investment play critical roles in the economies of both established and developing nations by providing much-needed capital, allowing for the more efficient use of available natural and human resources, and allowing for the more rapid adoption of cutting-edge technologies. Investment success depends on the presence of institutions and capacities of a developed financial and banking type. The significance of this study can be seen in how it exa

The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera

Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o

Recently, Social Sustainability has gained significant value as it was considered by the late studies as a principal dimension along with the environmental and economic sustainability. And because of, on the other hand, the significant social role of the school for forming the student’s personality, this research is an appeal for rehabilitating and promoting Iraqi Schools according the issue of social sustainability.As there is no evaluation for the Iraqi Schools, the research is dedicated to this problem, aiming to carry out the stated evaluation and define the design treatments needed for the rehabilitation process. To achieve this goal, a theoretical background for the concept of social sustainability, its criteria, the school and i

Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be