This paper presents on the design of L-Band Multiwavelength laser for Hybrid Time Division Multiplexing/ Wavelength Division Multiplexing (TDM/WDM) Passive Optical Network (PON) application. In this design, an L-band Mulltiwavelength Laser is designed as the downstream signals for TDM/WDM PON. The downstream signals ranging from 1569.865 nm to 1581.973 nm with 100GHz spacing. The multiwavelength laser is designed using OptiSystem software and it is integrated into a TDM/WDM PON that is also designed using OptiSystem simulation software. By adapting multiwavelength fiber laser into a TDM/WDM network, a simple and low-cost downstream signal is proposed. From the simulation design, it is found that the proposed design is suitable to be used in TDM/WDM PON for up to 64 Optical Network Units (ONUs).
Solubility problem of many of effective pharmaceutical molecules are still one of the major obstacle in theformulation of such molecules. Candesartan cilexetil (CC) is angiotensin II receptor antagonist with very low water solubility and this result in low and variable bioavailability. Self- emulsifying drug delivery system (SEDDS) showed promising result in overcoming solubility problem of many drug molecules. CC was prepared as SEDDS by using novel combination of two surfactants (tween 80 and cremophore EL) and tetraglycol as cosurfactant, in addition to the use of triacetin as oil. Different tests were performed in order to confirm the stability of the final product which includes thermodynamic study, determination of self-emulsificat
... Show MoreThe aim of this paper is to introduce the concepts of asymptotically p-contractive and asymptotically severe accretive mappings. Also, we give an iterative methods (two step-three step) for finite family of asymptotically p-contractive and asymptotically severe accretive mappings to solve types of equations.
Study of the development of an activated carbon nanotube catalyst for alkaline fuel cell technology. Through the prepared carbon nanotubes catalyst by an electrochemical deposition technique. Different analytical approaches such as X-ray diffraction (XRD) to determine the structural properties and Scanning Electron Microscope (SEM), were used to characterize, Mesh stainless steel catalyst substrate had an envelope structure and a large surface area. Voltages were also obtained at 1.83 V and current at 3.2 A of alkaline fuel cell. In addition, study the characterization of the electrochemical parameters.
In this paper, a methodology is presented for determining the stress and strain in structural concrete sections, also, for estimating the ultimate combination of axial forces and bending moments that produce failure. The structural concrete member may have a cross-section with an arbitrary configuration, the concrete region may consist of a set of subregions having different characteristics (i.e., different grades of concretes, or initially identical, but working with different stress-strain diagrams due to the effect of indirect reinforcement or the effect of confinement, etc.). This methodology is considering the tensile strain softening and tension stiffening of concrete in additio
Naproxen is non-steroidal anti-inflammatory drug, which has antipyretic and anti-inflammatory effect. It is extensively bound to plasma albumin, and exhibits gastric toxicity, so it may be more efficient to deliver the drug in its sustained release dosage form and adequate blood level is achieved. Three liquid formulations with in situ gelling properties have been assessed for their potential for the oral sustained delivery of naproxen . The formulations were dilute solutions of: (a) pectin; (b) gellan gum and; (c) sodium alginate, all containing complexed calcium ion that form gels when these ions are released in the acidic environment of the stomach . The viscosity of the sols and drug release were measured, and was found to be depende
... Show MoreSoftware-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
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