Colloidal crystals (opals) made of close-packed polymethylmethacrylate (PMMA) were fabricated and grown by Template-Directed methods to obtain porous materials with well-ordered periodicity and interconnected pore systems to manufacture photonic crystals. Opals were made from aqueous suspensions of monodisperse PMMA spheres with diameters between 280 and 415 nm. SEM confirmed the PMMA spheres crystallized uniformly in a face-centered cubic (FCC) array. Optical properties of synthesized pores PMMA were characterized by UV–Visible spectroscopy. It shows that the colloidal crystals possess pseudo photonic band gaps in the visible region. A combination of Bragg’s law of diffraction and Snell’s law of refraction were used to calculate the sphere diameter. Finally, colloidal crystals were subjected to Z-scan experiment under pulsed Q-switched Nd:YAG laser illumination to characterize it for third order nonlinear optical properties. Z-scan results show the change in transmittance of a beam, and the nonlinear refractive index is n2 = 9.82787 x 10-12 (cm2/GW), while the nonlinear absorption coefficient β= 0.04673908 (cm/GW). These results were attributed to enhance the self-focusing arising from Kerr effect and the two-photon absorption.
In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the BE
... Show MoreThe convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreA mathematical model constructed to study the combined effects of the concentration and the thermodiffusion on the nanoparticles of a Jeffrey fluid with a magnetic field effect the process of containing waves in a three-dimensional rectangular porous medium canal. Using the HPM to solve the nonlinear and coupled partial differential equations. Numerical results were obtained for temperature distribution, nanoparticles concentration, velocity, pressure rise, pressure gradient, friction force and stream function. Through the graphs, it was found that the velocity of fluid rises with the increase of a mean rate of volume flow and a magnetic parameter, while the velocity goes down with the increasing a Darcy number and lateral walls. Also, t
... Show MoreThe present study analyzes the effect of couple stress fluid (CSF) with the activity of connected inclined magnetic field (IMF) of a non-uniform channel (NUC) through a porous medium (PM), taking into account the sliding speed effect on channel walls and the effect of nonlinear particle size, applying long wavelength and low Reynolds count estimates. The mathematical expressions of axial velocity, stream function, mechanical effect and increase in pressure have been analytically determined. The effect of the physical parameter is included in the present model in the computational results. The results of this algorithm have been presented in chart form by applying the mathematical program.
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
Financial funding of a construction firm plays an important role in all aspects of the process development. It has been noted that financial crises have a direct impact on the construction industry. The Iraqi government, whether locally or globally, has faced a severe shortage of financing which has resulted in incomplete projects. Due to the financial crisis that Iraq went through which led to the suspension of many residential complex projects and the difficulty of the use of public financing methods, we researched the private financing (public-private partnership) methods instead of public financing methods in residential complex projects implementation. This study verified the financial problems and the factors that relate to th
... Show MoreChange detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac