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 (ro) 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 system was implemented. Analytical analysis was used to define the wave front and aberrations of the circular aperture telescope. Zernike polynomials were used to describe the residual error and figure out how much the compensation changed the measured turbulence values. The results of the computer simulation involving atmospheric turbulence reveal that elevating the ro values (4, 8, 12, 16, 20, 24, 28, 32) cm resulted in a 3.4% rise in S. However, when the adaptive optics system operated with a constant ro (20 cm), augmenting the Zernike aberration modes led to a remarkable 44% increase in S, signifying a substantial enhancement in the compensation procedure.
This work reports the study of heat treatment effect on the structural, morphological, optical and electrical properties of poly [3-hexylthiophene] and its blend with [6,6]-phenyl C61 butyric acid methyl ester ( P3HT:PC61BM). X-ray diffraction (XRD) measurements show that the crystallinity of the films increased with annealing. The evaluation of surface roughness and morphology was investigated using atomic force microscope (AFM), and field emission scanning microscope(FESEM). The optical properties were emphasized a strong optical absorption of P3HT compared with the blend. Hall effect measurement was used to study the electrical properties which revealed there is an increase in the electrical conductivity and Hall mobility of th
... Show MoreCurrent design codes and specifications allow for part of the bonded flexure tension reinforcement to be distributed over an effective flange width when the T-beams' flanges are in tension. This study presents an experimental and numerical investigation on the reinforced concrete flanged section's flexural behavior when reinforcement in the tension flange is laterally distributed. To achieve the goals of the study, numerical analysis using the finite element method was conducted on discretized flanged beam models validated via experimentally tested T-beam specimen. Parametric study was performed to investigate the effect of different parameters on the T-beams flexural behavior. The study revealed that a significant reduction in the
... Show MoreA novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)
Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine
... Show MoreIn this work, the performance of the receiver in a quantum cryptography system based on BB84 protocol is scaled by calculating the Quantum Bit Error Rate (QBER) of the receiver. To apply this performance test, an optical setup was arranged and a circuit was designed and implemented to calculate the QBER. This electronic circuit is used to calculate the number of counts per second generated by the avalanche photodiodes set in the receiver. The calculated counts per second are used to calculate the QBER for the receiver that gives an indication for the performance of the receiver. Minimum QBER, 6%, was obtained with avalanche photodiode excess voltage equals to 2V and laser diode power of 3.16 nW at avalanche photodiode temperature of -10
... Show MoreThis paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
... Show MoreDocument source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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