Background/objectives: To study the motion equation under all perturbations effect for Low Earth Orbit (LEO) satellite. Predicting a satellite’s orbit is an important part of mission exploration. Methodology: Using 4th order Runge–Kutta’s method this equation was integrated numerically. In this study, the accurate perturbed value of orbital elements was calculated by using sub-steps number m during one revolution, also different step numbers nnn during 400 revolutions. The predication algorithm was applied and orbital elements changing were analyzed. The satellite in LEO influences by drag more than other perturbations regardless nnn through semi-major axis and eccentricity reducing. Findings and novelty/improvement: The results demo

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

The nanostructured Manganese dioxide/Carbon fiber (CF) composite electrode was prepared galvanostatically using a facile method of anodic electrodeposition by varying the reaction time and MnSO4 concentration of the electrochemical solution. The effects of these parameters on the structures and properties of the prepared electrode were evaluated. For determining the crystal characteristics, morphologies, and topographies of the deposited MnO2 films onto the surfaces of carbon fibers, the X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and atomic force microscopy (AFM) techniques were used, respectively. It found that the carbon fibers were coated with γ-MnO2 with a density that increased with increasing the de

One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a

This work deals with preparation of Sulfated Zirconia catalyst (SZ) for isomerization of n-hexane model and refinery light naphtha, as well as enhanced the role of promoters to get the target with the mild condition, stability, and to prevent formation of coke precursors on strong acidic sites of the catalyst. The prepared SZ catalysts were characterization by fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer –Emmett-Teller (BET) surface area analysis, Thermogravimetric Analysis (TGA), Scanning Electron Microscope (SEM) and atomic force microscopy (AFM) Analyzer. The results illustrate that the maximum conversion and selectivity for n-hexane isomerization with Ni-WSZ and operating temperature of 150 °C

Kirchhoff Time migration was applied in Pre and Post-Stack for 2D seismic survey for line AJ-99N, that is located in Ajeel oilfield in Salah Al-Din Governorate, Central Iraq. The process follows several accurate steps to reach the final time migration stage. The results of applied time migration give an accurate image for the Ajeel anticline reservoir and to improve the signal to noise ratio. Pre-Stack shows a clearer image for the structure in the study area, and the time-frequency analysis insure the result.

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

     In this paper, the maximum likelihood estimator and the Bayes estimator of the reliability function for negative exponential distribution has been derived, then a Monte –Carlo simulation technique was employed to compare the performance of such estimators. The integral mean square error (IMSE) was used as a criterion for this comparison. The simulation results displayed that the Bayes estimator performed better than the maximum likelihood estimator for different samples sizes.