In order to increase the amount of solar radiation reaching a solar panel, and hence increase its performance, a tracking system might be used. A prototype of an efficient and portable solar tracking system, for home applications was constructed. The Arduino Uno Microcontroller is utilized to drive the proposed tacking system. The results of area under curve show that at certain circumstances, the open-loop tracking system is more efficient as compared with fixed one, while  the closed-loop tracker is slightly efficient than open-loop tracker.

In this study, the performance of the adaptive optics (AO) system was analyzed through a numerical computer simulation implemented in MATLAB. Making a phase screen involved turning computer-generated random numbers into two-dimensional arrays of phase values on a sample point grid with matching statistics. Von Karman turbulence was created depending on the power spectral density. Several simulated point spread functions (PSFs) and modulation transfer functions (MTFs) for different values of the Fried coherent diameter (r_o) were used to show how rough the atmosphere was. To evaluate the effectiveness of the optical system (telescope), the Strehl ratio (S) was computed. The compensation procedure for an AO syst

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process

A theoretical and experimental investigation was carried out to study the behavior of a two-phase closed thermosyphon loop (TPCTL) during steady-state operation using different working fluids. Three working fluids were investigated, i.e., distilled water, methanol, and ethanol. The TPCTL was constructed from an evaporator, condenser, and two pipelines (riser and downcomer). The driving force is the difference in pressure between the evaporator and condenser sections and the fluid returns to the heating section by gravity. In this study, the significant parameters used in the experiments were filling ratios (FR%) of 50%, 75%, and 100% and heat-input range at the evaporator section of 215-860.2 W. When the loop reached to

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

This research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values ​​of 1000  for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected   as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning

The communication networks (mobile phone networks, social media platforms) produce digital traces from their usages. This type of information help to understand and analyze the human mobility in very accurate way. By these analyzes over cities, it can give powerful data on daily citizen activities, urban planners have in that way, relevant indications for decision making on design and development. As well as, the Call detail Records (CDRs) provides valuable spatiotemporal data at the level of citywide or even nationwide. The CDRs could be analyzed to extract the life patterns and individuals mobility in an observed urban area and during ephemeral events. Whereas, their analysis gives conceptual views about human density and mobility pattern

A soliton is a solitary wave whose amplitude, shape, and velocity are conserved after a collision with another soliton. Solitons, in general, manifest themselves in a large variety of wave/particle systems in nature: practically in any system that possesses both dispersion (in time or space) and nonlinearity. Solitons have been identified in optics, plasmas, fluids, condensed matter, particle physics, and astrophysics. Yet over the past decade, the forefront of soliton research has shifted to neuroscience. The Soliton model in optical fiber is a recently developed model that attempts to explain how signals are propagated within optical fiber without dispersion. In this research, it proposes that the signals travel along the Single Mode O

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl