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

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear

Myrtle plant was washed, dried, and powdered after harvesting to produce a fine powder used in water treatment. An alcoholic extract was created from the myrtle plant using ethanol, which was then analyzed using GC-Mass, Fourier Transform Infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using alcoholic extract. FT-IR, UV-Vis, SEM, EDX, and TEM were used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with myrtle extract and powder were employed to clean polluted water containing pesticides and antibiotic. First, 2 g of zinc nanoparticles was mixed with 20 ml of polluted water and the result was (Tetra 44%, Levo 32%),

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition S

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.