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Chemical sensor based on a solid-core photonic crystal fiber interferometer
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Photonic crystal fiber interferometers are used in many sensing applications. In this work, an in-reflection photonic crystal fiber (PCF) based on Mach-Zehnder (micro-holes collapsing) (MZ) interferometer, which exhibits high sensitivity to different volatile organic compounds (VOCs), without the needing of any permeable material. The interferometer is robust, compact, and consists of a stub photonic crystal fiber of large-mode area, photonic crystal fiber spliced to standard single mode fiber (SMF) (corning-28), this splicing occurs with optimized splice loss 0.19 dB In the splice regions the voids of the holey fiber are completely collapsed, which allows the excitation and recombination of core and cladding modes. The device reflection spectrum exhibits a sinusoidal interference pattern which shifts differently when the voids of the PCF are infiltrated with VOC molecules. The volume of voids responsible for the shift is less than 5microliters whereas the detectable levels are in the nanomole range. Laser diode with a wavelength 1550nm has been used as a pump light source. Two types of chemical liquids used (N-Hexane, and Propanol). The detection limits of our device associated with the maximum shifts of the wavelength is 4.4 nm for N-Hexane vapor when the length of the head sensor 20mm. In this work, the maximum sensitivity obtained of volatile organic compounds is 15420 nm/mol at the vapor of N-Hexane.

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Mon Jan 01 2024
Journal Name
Infocommunications Journal
On the Performance of Metamaterial based Printed Circuit Antenna for Blood Glucose Level Sensing Applications: A Case Study
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Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Wed Nov 14 2018
Journal Name
Fiber And Integrated Optics
Design Investigation of 2 × 2 Mach–Zehnder Optical Switch Based on a Metal–Polymer–Silicon Hybrid Plasmonic Waveguide
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In this paper, a miniaturized 2 × 2 electro-optic plasmonic Mach– Zehnder switch (MZS) based on metal–polymer–silicon hybrid waveguide is presented. Adiabatic tapers are designed to couple the light between the plasmonic phase shifter, implemented in each of the MZS arms, and the 3-dB input/output directional couplers. For 6 µm-long hybrid plasmonic waveguide supported by JRD1 polymer (r33= 390 pm/V), a π-phase shift voltage of 2 V is obtained. The switch is designed for 1550 nm operation wavelength using COMSOL software and characterizes by 2.3 dB insertion loss, 9.9 fJ/bit power consumption, and 640 GHz operation bandwidth

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Publication Date
Fri Oct 02 2020
Journal Name
International Journal Of Pharmaceutical Research
A turbidimetric method for the quantitative determination of cyproheptadine hydrochloride in tablets using an optoelectronic detector based on the LEDs array
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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Developing a Predictive Model and Multi-Objective Optimization of a Photovoltaic/Thermal System Based on Energy and Exergy Analysis Using Response Surface Methodology
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Effect of the Aquatic Plant Hydrella vorticellata as a Fertilizer on Seed Germination and some Chemical and Cytogenetics Parameters in the cell of Hordeum vulgare and Vicia faba
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The present study is concerned with studying the effect of aquatic plant Hydrella vorticellata with the concentration of 10 and 20 gm/2 K gm soil on percentage and growth rate of germinating seeds of Hordeum vulgare and Vicia faba. More overs, the quantitative amount of NPK in both tested plants and Hydrella vorticellata, are estimated as an organic fertilizer. It has also been find the total number of root cells, the number of dividing cells, and stages of mitosis. The study reveales, that there are no significant differences between the concentration of hydrella used in germination percentage, growth rate, wet and dry weight. While there are differences in the plants containing NPK. The number of cells dividing stages and number of divid

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Publication Date
Mon Jan 01 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
A Sensitive Electrochemical Sensor for Rapid Determination of Mebeverine Hydrochloride and Metronidazole Benzoate Selective Molecular Imprinted Polymer in the PVC Membrane
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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Evaluation Study of Glass Fiber Reinforced Polyester and Kevlar Reinforced Polyester by Taguchi Method
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     In the present investigation two different types of fiber reinforced polymer composites were prepared by hand lay-up method using three different parameters (curing temperature, pressing load and fiber volume fraction). These composites were prepared from the polyester resin as the matrix material reinforced with glass fibers as first group of samples and mat Kevlar fibers as the second group, both with different volume fractions (4%, 8%, and 12%) of fibers. They were then tested by tensile strength and impact strength. The main objective in this study is to use Taguchi method for predicting the better parameters that give the better tensile and impact strength to the composites, and then preparing composites at

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