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Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while the other eight deep beams were with openings in shear spans and with carbon fiber–reinforced polymer sheet strengthening around opening zones. The opening size was adopted to be 200 × 200 mm dimensions in eight deep beams, while it was considered to be 230 × 230 mm dimensions in the other eight specimens. In eight specimens the opening was located at the center of the shear span, while in the other eight beams the opening was attached to the interior edge of the shear span. Carbon fiber–reinforced polymer sheets were installed around openings to compensate for the cutout area of concrete. Results gained from the experimental test showed that the creation of openings in shear spans affect the load-carrying capacity, where the reduction of the failure load for specimens with the opening but without strengthening may attain 66% compared to deep beams without openings. On the other hand, the strengthening by carbon fiber–reinforced polymer sheets for beams with openings increased the failure load by 20%–47% compared with the identical deep beam without strengthening. A significant contribution of carbon fiber–reinforced polymer sheets in restricting the deformability of deep beams was observed.

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Publication Date
Tue Dec 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Hybrid compensation of polarization-multiplexed QPSK optical format for high bit rate networks
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<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Design and Implementation for optical fiber communication system using frequency shift coding
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In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a

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Publication Date
Mon Jun 01 2015
Journal Name
International Photonics And Optoelectronics
Canonical Logic Units using Bidirectional Four-Wave Mixing in Highly Nonlinear Fiber
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All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Laser
PDF Tunable Optical filters Using Etched Polarization Maintaining Fiber Hybrid Sagnac Interferometer
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: In modern optical communication system, noise rejection multiple access interference (MAI) must be rejected in dense access network (DAN). This paper will study the dual optical band pass and notch filters. They will be extracted with tunable FWHM using 10cm (PMF) with different cladding diameters formed with etching 125μm PMF after immersing it with 40% of hydrofluoric acid (HF). This fiber acts as assessing fiber to perform Sagnac interferometer with splicing regions that placed 12cm (SMF) for performing hybrid Sagnac interferometer that consists of Mach-Zehnder instead of Sagnac loop which is illuminated by using laser source with centroid wavelength of 1546.7nm and FWHM of 286 pm or 9 ns in the time domain. . Firs

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Publication Date
Mon Oct 21 2019
Journal Name
Civil Engineering Journal
Non-Smooth Behavior of Reinforced Concrete Beam Using Extended Finite Element Method
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Flexure members such as reinforced concrete (RC) simply supported beams subjected to two-point loading were analyzed numerically. The Extended Finite Element Method (XFEM) was employed for the treatment the non-smooth h behaviour such as discontinuities and singularities. This method is a powerful technique used for the analysis of the fracture process and crack propagation in concrete. Concrete is a heterogeneous material that consists of coarse aggregate, cement mortar and air voids distributed in the cement paste. Numerical modeling of concrete comprises a two-scale model, using mesoscale and macroscale numerical models. The effectiveness and validity of the Meso-Scale Approach (MSA) in modeling of the reinforced concrete beams w

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Publication Date
Fri Nov 30 2018
Journal Name
Civil Engineering Journal
Determining the Causes of Punching Shear in Reinforced Slabs Using Fishbone Diagram
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Risk identification and assessment can be analysed using many risk management tools. Fishbone diagram is one of these techniques which can be employed, for the identification of the causes behind the construction failure, which   has become a phenomenon that often gets repeated in several projects. If these failures are not understood and handled scientifically, it may lead to disputes between the project parties. Additionally, the construction failure also leads to an increase in the project budget, which in turn causes a delay in the completion of the projects. Punching shear in reinforcement slab may be one of the reasons for construction failures. However, there are many doubts about other causes that lead to this failure as w

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Punching Shear Behavior of Reinforced Concrete Slabs under Fire using Finite Elements
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The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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