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

Coaxial (wire-cylinder) electrodes arrangements are widely used for electrostatic deposition of dust particles in flue gases, when a high voltage is applied to electrodes immersed in air and provide a strongly non-uniform electric field. The efficiency of electrostatic filters mainly depends on the value of the applied voltage and the distribution of the electric field. In this work, a two-dimensional computer simulation was constructed to study the effect of different applied voltages (20, 22, 25, 26, 28, 30 kV) on the inner electrode and their effect on the efficiency of the electrostatic precipitator. Finite Element Method (FEM) and COMSOL Multiphysics software were used to simulate the cross section of a wire cylinder. The results sh

Software-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

The development of the perforated fin had proposed in many studies to enhance the heat transfer from electronic pieces. This paper presents a novel derivative method to find the temperature distribution of the new design (inclined perforated) of the pin fin. Perforated with rectangular section and different angles of inclination was considered. Signum Function is used for modeling the variable heat transfer area. Set of parameters to handle the conduction and convection area were calculated. Degenerate Hypergeometric Equation (DHE) was used for modeling the Complex energy differential equation and then solved by Kummer’s series. In the validation process, Ansys 16.0-Steady State Thermal was used. Two geometric models were consider

This research aims to improve the radiation shielding properties of polymer-based materials by mixing PVC with locally available building materials. Specifically, two key parameters of fast neutron attenuation (removal cross-section and half-value layer) were studied for composite materials comprising PVC reinforced with common building materials (cement, sand, gypsum and marble) in different proportions (10%, 30% and 50% by weight). To assess their effectiveness as protection against fast neutrons, the macroscopic neutron cross-section was calculated for each composite. Results show that neutron cross-section values are significantly affected by the reinforcement ratios, and that the composite material PVC + 50% gypsum is an effect

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Abstract

      This research aims to identify the role of Psychological Capital (PsyCap) in the Spirituality at the Workplace (SAW) for a sample of the teaching staff of the four Colleges of the University of Kufa reached (200) out of (470) teaching, and to achieve the objective of this research and through access to research and studies of foreign adopted researchers standards scales of research variables, since it relied on the model (Luthans, Youssef, et al., 2007) to represent the components of Psychological Capital (self-efficacy, and hope, and optimism, and resilience), and given the attention organizations in the human element because of it

In this article, the solvability of some proposal types of the multi-fractional integro-partial differential system has been discussed in details by using the concept of abstract Cauchy problem and certain semigroup operators and some necessary and sufficient conditions. 

The parameters of resistance spot welding (RSW) performed on low strength commercial aluminum sheets are investigated experimentally, the performance requirements and weldability issues were driven the choice of a specific aluminum alloy that was AA1050. RSW aluminum alloys has a major problem of inconsistent quality from weld to weld comparing with welding steel
alloys sheet, due to the higher thermal conductivity, higher thermal expansion, narrow plastic temperature range, and lower electrical resistivity. Much effort has been devoted to the study of describing the relation between the parameters of the process (welding current, welding time, and electrode force) and weld strength. Shear-tensile strength tests were performed to ind