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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 (Digital Signal Processing (DSP)) compensation stages to minimize the impairments. The behaviour of the proposed system was investigated under four conditions: without compensation, with only optical compensator, with only DSP compensator and finally with both compensators. An evidence improvement was noticed in the case of hybrid compensation, where the transmission distance was multiplied from (720 km) to more than (3000 km) at 40 Gb/s.</span>

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Self-adaptive Differential Evolution based Optimized MIMO Beamforming 5G Networks
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     The industrial factory is one of the challenging environments for future wireless communication systems, where the goal is to produce products with low cost in short time. This high level of network performance is achieved by distributing massive MIMO that provides indoor networks with joint beamforming that enhances 5G network capacity and user experience as well. Judging from the importance of this topic, this study introduces a new optimization problem concerning the investigation of multi-beam antenna (MBA) coverage possibilities in 5G network for indoor environments, named Base-station Beams Distribution Problem (BBDP). This problem has an extensive number of parameters and constrains including user’s location, required d

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Publication Date
Tue Sep 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Density and Approximation by Using Feed Forward Artificial Neural Networks
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I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

 

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Success rate of Percutaneous Coronary Intervention of Chronic Total Occlusion in Ibn Al-Baitar Hospital for cardiac surgery and Al-Nassyeria cardiac center
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Back ground: Chronic total occlusion (CTO) of coronary arteries remains one of the most challenging lesion subsets in interventional cardiology even with the development of medical devices and operator expertise. Successful revascularization results in improved in angina status ,increased exercise capacity and reduces the need for lat CABG surgery .
Objectives: This study sought to determine the overall procedural success rate of percutaneous coronary intervention (PCI) for CTOs and to examine the relation between variables such as; patients’ characteristics, risk factors, lesion characteristics and procedural success rate.
Methods: In this study ,clinical and coronary angiography data of (80) patients with CTO who underwent PCI

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The impact of the RMB exchange rate on the value of Chinese exports For the period (1978-2017) using the Angel-Granger model
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In this research, we sought to identify the nature of the relationship between the exchange rate of the Chinese yuan and the value of Chinese exports, through the formulation of a standard model based on the model of common integration, and based on the data of the study and using the test "Angel-Granger" It reflects the relationship between the two research variables, through which the relationship between the RMB exchange rate and the value of Chinese exports was estimated during the period 1978-2017.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Potential Benefits of Ethanol extract of Anredera cordifolia for Antiobesity of High Fat diet-Induced Obesity in White Male Rat Wistar
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Obesity-related deaths continue to rise, and thus losing weight in overweight and obese patients is critical to prevent complications. Anredera cordifolia (Ten,) Steenis, species of succulent plant of the genus Basellaceae, is widely used in herbal medicine to decrease body weight. This study evaluated the potential benefits of Anredera cordifolia ethanol extract to reduce body weight in high-fat diet-induced obesity rat model. This was an experimental with post-test only control group design study involving 36 obese rats. They were divided into two groups: three control groups (K1, K2, K3) and three treatment groups (P1, P2, P3). All the groups were induced with high-fat diet, except K1 control group that received a standard di

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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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