The ring modulator described in part I of this paper is designed here for two operating wavelengths 1550nm and 1310nm. For each wavelength, three structures are designed corresponding to three values of polymer slot widths (40, 50 and 60nm). The performance of these modulators are simulated using COMSOL software (version 4.3b) and the results are discussed and compared with theoretical predictions. The performance of intensity modulation/direct detection short range and long rang optical communication systems incorporating the designed modulators is simulated for 40 and 100Gb/s data rates using Optisystem software (version 12). The results reveal that an average energy per bit as low as 0.05fJ can be obtained when the 1550nm modulator is designed with a phase shifter length equals twice the coupling length.
A new furfural Schiff base derivative ligand (L-FSB) named N-(4- Bromo-2-methylphenyl)-1-(furan-2-yl)methanimine, was synthesized from the condensation reaction of furfural (fur) with 4-Bromo-2- methylaniline (bma) in 1:1molar ratio. A new series of VO(II), Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Cd(II) metal complexes are synthesized according to the metal content analysis in an 2:1 ligand:metal ratio. The stereochemistry of the ligand complexes have been deduced by Fourier Transform-Infra Red (FT-IR), Atomic Adsorption (A.A), Ultra violate-Visible Spectra (UV-Vis Spectra), (Mass Spectra, Proton,13Carbon-Nuclear Magnetic Resonance) (1H-NMR,13CNMR) for ligand), magnetic susceptibility at 25oC and conductivity measurements. Fr
... Show Moreالوصف New complexes of Cu (ll), Ni (II)„Co (II), and Zn (ll) with 2-amino-5-p-Flouro Phenyl 1, 3, 4-Thiadiazole have been synthesized. The products were isolated, studied and characterized by physical measurements, ie,(FT-IR)„UV-Vis and the melting points were determined. The new Schiff base (L) has been used to prepare some complexes. The prepared complexes were identified and their structural geometry were suggested
This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
... Show MoreGlobal technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid “Al2O3-Cu/water” nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simu
... Show MoreThe aim of this work is the synthesis of new grafted PVA polymer with a derivative of Erythro-ascorbic acid (pentulosono-ɣ -lactone-2, 3-enedianisoate). All synthesized compounds were characterized by thin layer chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR, 13CNMR and mass spectra. They were also evaluated for antimicrobial properties by dilute method against four pathogenic bacteria (Escherichia coli ,Klebsiella pneumonae, Staphylococcus aureus, Staphylococcus Albus) and two fungal (Aspergillus Niger, Yeast). All polymer metal complexes showed good activities against the various microbial isolates. The polymer metal complexes showed higher activity than the free polymer. The order of increa
... Show MoreThis work is focused on studying the effect of liquid layer level (height above a target material) on zinc oxide nanoparticles (ZnO and ZnO2) production using liquid-phase pulsed laser ablation (LP-PLA) technique. A plate of Zn metal inside different heights of an aqueous environment of cetyl trimethyl ammonium bromide (CTAB) with molarity (10-3 M) was irradiated with femtosecond pulses. The effect of liquid layer height on the optical properties and structure of ZnO was studied and characterized through UV-visible absorption test at three peaks at 213 nm, 216 nm and 218 nm for three liquid heights 4, 6 and 8 mm respectively. The obtained results of UV–visible spectra test show a blue shift accomp
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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