This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Recently, there has been a major trend towards environmental issues and concern for the green product because traditional products cause serious environmental impacts such as reduced resources, global warming, energy consumption, emissions and other environmental damage. Under these developments, economic units are looking for cost-effective technologies that reduce the cost of a green product that has four main dimensions: reducing energy, reducing resource consumption, preventing pollution, and using renewable energy while not compromising quality and satisfying customers in order to enhance competitive advantage.

This research will address one of the most important cost-effective green technologies, Gr

Health insurance and its benefits are of great importance and impact on the employees who represent the human capital of each organization because they are related to the health reality. The study took into account the most important and the last of his writing of the concepts and literary reviews and enriched the theoretical part of the practical side has addressed the financial data and analysis for the period from 2013 to 2017 to know the impact and the relationship between the variables that They were reviewed on the theoretical side. The study came out with a number of results, on the basis of which practical conclusions were drawn and reflected what was observed on the basis of which the recommendations were formulated

يواجه العراق تحديات مائية خطيرة نتيجة التغيرات المناخية، مثل انخفاض معدلات هطول الأمطار، ارتفاع درجات الحرارة، وزيادة معدلات الجفاف والتصحر، فهذه التحديات تتطلب إستراتيجيات فعالة لإدارة الموارد المائية بشكل مستدام، وهو ما يمكن تحقيقه من خلال تبني التطورات التكنولوجية الحديثة في مجال الحوكمة البيئية ، و يركز هذا البحث على دور التحول الرقمي والتقنيات الذكية في تعزيز كفاءة إدارة المياه، إذ يمكن لتطبيقا

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The research aims to show the relationship between artificial intelligence in accounting education and its role in achieving sustainable development goals in the Kingdom of Bahrain. The research dealt with the role of artificial intelligence applications in accounting education at the University of Applied Sciences as a model for Bahraini universities to achieve sustainable development goals. The application of artificial intelligence in accounting education achieves seven of the seventeen sustainable development goals. It also concludes that there is an artificial intelligence infrastructure in the Kingdom of Bahrain, as it occupies a leading regional position in digital transformation, as Bahrain ranks first in the Arab world i