This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

The synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.

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

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

Gravity and magnetic data were used to study the deep crustal structures in Karbala and surrounding areas in central Iraq. The space window method was used to separate the residual from regional anomalies of gravity and magnetic data, the spaces of window are equal to 48,36 and 24 km. The Total Horizontal Derivative (THD) techniques and local wavenumber of gravity and magnetic are used to identify the faults and their trends with the basement rocks.  The N45W, N45E, N-S and rarely E-W trends of faults are detected in the basement rock. It is believed that some of these faults extending from the basement to the uppermost layer of the sedimentary rocks.

On 2-9th April 2001 the Energetic and Relativistic Nuclei and Electron (ERNE) instrument on the Solar and Heliospheric Observatory (SOHO) observed three gradual solar energetic particle (SEP) events separated by 9 hour and 7days respectively, in association with three effective solar flares and coronal mass ejections (CMEs).
In this paper, a study of MESEP events was considered. As the definition of this phenomenon suggested there might be many sources for each MESEP event. This event has been examined in order to view the different sources that might relate to suspected accelerator of the SEPs. A careful analysis for the spectra and associated emission with such eruptions was made. Soft X-ray emission was observed by the Geostationar

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is still a severe threaft for human health currently, and the researches about it is a focus topic worldwide.

Aim of the study: In this study, we will collect some laboratory results of the patients with coronavirus disease (COVID-19) to assess the function of liver, heart, kidney and even pancreas. 

Subjects and Methods: Laboratory results of the patients with COVID-19 are collected. The biochemical indices are classified and used to assess the according function of liver, heart, kidney; meantime, and blood glucose is also observed and taken as an index to roughly evaluate pancreas.

Results: There were some in

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic worldwide. On a daily basis the number of deaths associated with COVID-19 is rapidly increasing. The main transmission route of SARS-CoV-2 is through the air (airborne transmission). This review details the airborne transmission of SARS-CoV-2, the aerodynamics, and different modes of transmission (e.g. droplets, droplet nuclei, and aerosol particles). SARS-CoV-2 can be transmitted by an infected person during activities such as expiration, coughing, sneezing, and talking. During such activities and some medical procedures, aerosols and droplets contaminated with SARS-CoV-2 particles are formed. Depending on their

A new results for fusion reactivity and slowing-down energy distribution functions for controlled thermonuclear fusion reactions of the hydrogen isotopes are achieved to reach promising results in calculating the factors that covered the design and construction of a given fusion system or reactor. They are strongly depending upon their operating fuels, the reaction rate, which in turn, reflects the physical behavior of all other parameters characterization of the system design

The importance of efficient vehicle detection (VD) is increased with the expansion of road networks and the number of vehicles in the Intelligent Transportation Systems (ITS). This paper proposes a system for detecting vehicles at different weather conditions such as sunny, rainy, cloudy and foggy days. The first step to the proposed system implementation is to determine whether the video’s weather condition is normal or abnormal. The Random Forest (RF) weather condition classification was performed in the video while the features were extracted for the first two frames by using the Gray Level Co-occurrence Matrix (GLCM). In this system, the background subtraction was applied by the mixture of Gaussian 2 (MOG 2) then applying a number