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

     In the current Airlines Air Traffic Management (ATM), the Air Traffic Control Operators (ATCO), with the Air Traffic Control systems (ATC), operate air traffic paths with a small number of fixed routes. Problems of fixed routes appear such that even when they reduce the chance for conflict, they also produce flight paths plans that do not reduce flight time or fuel usage. In nowadays Airlines are heavily overloaded and anxious to minimize the aircrafts fuel usage costs, increase airplanes, and optimize the paths or the flight routes in order to find the most optimal suitable flight paths. This paper presents a new path planning method that deal with such problem effectively, the idea was to produce flights routes

The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.

In this paper, some Bayesian estimators for the unknown scale parameter  of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of   estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggeste

Objective(s): To assess the eating habits of adolescent females with iron deficient anemia.

Methodology: This study employed a quantitative research, descriptive evaluation design.The study was carried out on adolescent girls attending Kirkuk secondary school, period from 11 April to 27 December 2022. A non- probability (Purposive) sample has been applied to obtain the study goals. The study sample was (62) student who participate in the study.

Results: Pre-test results from the study revealed that 54.8% of students had moderate IDA. While the students' iron levels returned to normal in the posttest (53.2%). The majority of students (59.7%) had poor eatin