Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Twilight is that light appear on the horizon before sunrise and after sunset, Astronomically it is known that sunrise and sunset are effected by high above sea level, but the effect of high above sea level on the time of astronomical twilight still not decided and controversy among astronomers, in This research we studies the effect of high above sea level on the time of astronomical twilight, through adding the equation correct high above sea level to equation computation of twilight and then calculate of changing in the time of twilight for different highest (0-10000) meters above sea level , and the ratio of increase for time with high between (15.45-20.5) minutes. It was found that there was an increase in the time of the twilight along

The tracking of satellites motion and their path around the earth is important things in the mechanical of satellites motion. Significant parameters for the determination of time entrance and existence of the satellite could be obtained from the shadow of the earth. In the present work the tracking and time determination for entry and exit from earth shadow have been studied. In the present work we built a software for tracking the motion of satellites in orbit around the earth and determine the change of both distance and speed as a function of time. The perturbations effect on the satellite has been neglected from the earth atmosphere drag and the earth gravity and other effects. The equation for calculating the shadow is solved using num